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CATS Small RNA-seq Kit x24

Catalog Number

Format

Price

C05010040

24 rxns

DISCONTINUED

Diagenodeの「CATS small RNA-seq Kit」は、革新的なCATS法（Capture and Amplification by Tailing and Switching）を採用することで、ライゲーションが不要でかつ低インプットRNA量から次世代シークエンシングのDNAライブラリーを作製することができるキットです。

多様なスモールRNAを回収可能
10pgの超少量インプットRNAで優れた再現性
難しいサンプルでの優れたパフォーマンス

続きを読む

CATSは、RNAの3’末端をキャプチャーするためのポリヌクレオチドテーリングおよび、cDNA合成時に5’末端をキャプチャーするためのMMLV-RTによるテンプレートスイッチ能力を利用した技術です。この方法なら、10ピコグラムの低インプットRNA量からわずか数時間でIllumina用シークエンシングライブラリーを作製することができます。

ライブラリーは、ストランド特異的な情報を保持しています。「CATS RNA-seq Kit」は、増幅を最小限に抑えることでより多くの有効な鋳型をキャプチャーし、また、バイアスを最小限に抑えることで高い複雑性を得ることができるので、他のライゲーションベースの手法と比べより高いライブラリー作製効率を示します。

Unique sncRNAs detected in circulating plasma RNA

sncRNA transcripts detected using the CATS small RNA-seq Kit vs the Competitor’s Kit. The input was 1 ng circulating small RNA in plasma samples. In total, 908 transcripts were found in the CATS small RNA-seq libraries. TPM≥1

PCR cycles: CATS 14x vs Competitor 21x. Final library yield: CATS 27 ng vs Competitor 1.2 ng.

More miRNA transcripts detected from challenging samples

Transcripts detected in miRNA samples of CATS small RNA-seq Kit vs the Competitor’s Kit.

Input: 1 ng circulating small RNA in plasma samples. PCR cycles: CATS 14x vs Competitor 21x. Final library yield: CATS 27 ng vs Competitor 1.2 ng.

Ultra low inputs, excellent reproducibility

Correlation between 2 different operators using CATS small RNA-seq Kit on two different inputs (100 pg vs 1 ng) for ncRNA detected at TPM ≥2.
R² = 0.86

Consistency across template switching techniques

Comparison of the number of detected small non-coding RNAs CATS small RNA-seq Kit vs SMARTer
Input: 100 pg isolated small RNA. TPM ≥2. Transcripts taken into consideration: miRNA, piRNA, scRNA, scaRNA, snoRNA, snRNA and vaultRNA. 1,217 transcripts found in both libraries at this expression level.

High number of reads mapped

Representation of detected transcripts different biotypes with CATS small RNA-seq Kitvs NEBNext UltraI kit. TPM≥2.
100 ng total RNA, 1 ng small RNA used as input.

Excellent performance on challenging samples

Heatmap clustering of the top 50 differentially expressed miRNAs after library preparation:

CATS Small RNA-seq Kit on 1 ng exosomal RNA (Exosome sample 1, 2)
CATS RNA-seq Kit on 1 ng total RNA from parent (HEK293T) cells (Cell sample 1, 2).

Prior library preparation, exosomes were isolated with Diagenode exosome capture solutions Exosomes

CATS saves time

特徴
FAQs
資料
D-Plex Small RNA-seq Kit for Illumina MANUAL
Note: The D-Plex Small RNA-seq Kit manual describes the protocol for both UDI and SI li... Download
D-Plex Small RNA DNBSEQ™ Kit for MGI MANUAL
Download

出版物

How to properly cite this product in your work

Diagenode strongly recommends using this: CATS Small RNA-seq Kit x24 (Diagenode Cat# C05010040). Click here to copy to clipboard.

Using our products in your publication? Let us know!

Functional microRNA targetome undergoes degeneration-induced shift in the retina
Chu-Tan JA et al.
Background: MicroRNA (miRNA) play a significant role in the pathogenesis of complex neurodegenerative diseases including age-related macular degeneration (AMD), acting as post-transcriptional gene suppressors through their association with argonaute 2 (AGO2) - a key member of the RNA Induced Silencing Complex...

Repeat RNAs associate with replication forks and post-replicative DNA.
Gylling HM, Gonzalez-Aguilera C, Smith MA, Kaczorowski DC, Groth A, Lund AH
Non-coding RNA has a proven ability to direct and regulate chromatin modifications by acting as scaffolds between DNA and histone-modifying complexes. However, it is unknown if ncRNA plays any role in DNA replication and epigenome maintenance, including histone eviction and re-instalment of histone-modifications aft...

Multisite Evaluation of Next-Generation Methods for Small RNA Quantification.
Herbert ZT, Thimmapuram J, Xie S, Kershner JP, Kolling FW, Ringelberg CS, LeClerc A, Alekseyev YO, Fan J, Podnar JW, Stevenson HS, Sommerville G, Gupta S, Berkeley M, Koeman J, Perera A, Scott AR, Grenier JK, Malik J, Ashton JM, Pivarski KL, Wang X, Kuffe
Small RNAs (smRNAs) are important regulators of many biologic processes and are now most frequently characterized using Illumina sequencing. However, although standard RNA sequencing library preparation has become routine in most sequencing facilities, smRNA sequencing library preparation has historically been chall...

Circulating miRNA analysis for cancer diagnostics and therapy.
Valihrach L, Androvic P, Kubista M
Successful treatment of cancer depends on early diagnosis and effective monitoring of patients' response to therapy. Traditional tools based on tumor biopsies lack the sensitivity and specificity to capture cancer development in its early phases and are not applicable for continuous monitoring. To overcome these bar...

The sncRNA Zoo: a repository for circulating small noncoding RNAs in animals.
Fehlmann T, Backes C, Pirritano M, Laufer T, Galata V, Kern F, Kahraman M, Gasparoni G, Ludwig N, Lenhof HP, Gregersen HA, Francke R, Meese E, Simon M, Keller A
The repertoire of small noncoding RNAs (sncRNAs), particularly miRNAs, in animals is considered to be evolutionarily conserved. Studies on sncRNAs are often largely based on homology-based information, relying on genomic sequence similarity and excluding actual expression data. To obtain information on sncRNA expres...

MicroRNAs and Transplantation.
Khan Z, Suthanthiran M, Muthukumar T
miRNAs, ∼20 to 22 nucleotide single-stranded RNA species that play a pivotal role in the regulation of protein-coding genes, are emerging as robust biomarkers for assessing allograft status. Herein, the authors briefly review the biogenesis and function of the miRNAs and provide an overview of the tools to quant...

NGS analysis of total small non coding RNAs from low input RNA from dried blood sampling
Marcello Pirritano, Tobias Fehlmann, Thomas Laufer, Nicole Ludwig, Gilles Gasparoni, Yongping Li, Eckart Meese, Andreas Keller, and Martin Simon
Circulating miRNAs are favored for biomarker candidates as they can reflect tissue specific miRNA dysregulation in disease contexts. Moreover, they have additional advantages that they can be monitored in a minimal invasive manner. Blood-borne miRNAs are therefore currently characterized to identify, describe and va...

関連商品
- C05030001
  
  D-Plex Small RNA-seq Library Prep Kit x24
- C05030051
  
  D-Plex Small RNA DNBSEQ™ Kit

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			'description' => '<p style="text-align: justify;">Diagenodeの「CATS small RNA-seq Kit」は、革新的なCATS法（Capture and Amplification by Tailing and Switching）を採用することで、ライゲーションが不要でかつ低インプットRNA量から次世代シークエンシングのDNAライブラリーを作製することができるキットです。</p>
<ul>
<li>多様なスモールRNAを回収可能</li>
<li>10pgの超少量インプットRNAで優れた再現性</li>
<li>難しいサンプルでの優れたパフォーマンス</li>
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<p style="text-align: justify;">CATSは、RNAの3&rsquo;末端をキャプチャーするためのポリヌクレオチドテーリングおよび、cDNA合成時に5&rsquo;末端をキャプチャーするためのMMLV-RTによるテンプレートスイッチ 能力を利用した技術です。この方法なら、10ピコグラムの低インプットRNA量からわずか数時間でIllumina用シークエンシングライブラリーを作製することができます。</p>
<p style="text-align: justify;">ライブラリーは、ストランド特異的な情報を保持しています。「CATS RNA-seq Kit」は、増幅を最小限に抑えることでより多くの有効な鋳型をキャプチャーし、また、バイアスを最小限に抑えることで高い複雑性を得ることができるので、他のライゲーションベースの手法と比べより高いライブラリー作製効率を示します。</p>
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<h3>Unique sncRNAs detected in circulating plasma RNA</h3>
<div class="large-7 small-12 medium-7 columns"><img src="https://www.diagenode.com/img/product/kits/cats/cats-908-competitor-3.png" /></div>
<div class="large-5 small-12 medium-5 columns">
<p>sncRNA transcripts detected using the <strong>CATS small RNA-seq Kit</strong> vs the Competitor&rsquo;s Kit. The input was <strong>1 ng circulating small RNA</strong> in plasma samples. In total, 908 transcripts were found in the CATS small RNA-seq libraries. TPM&ge;1</p>
<p><strong>PCR cycles: CATS 14x</strong> vs Competitor 21x. <strong>Final library yield: CATS 27 ng</strong> vs Competitor 1.2 ng.</p>
</div>
</div>
<div>
<h3>More miRNA transcripts detected from challenging samples</h3>
<div class="large-7 small-12 medium-7 columns"><img src="https://www.diagenode.com/img/product/kits/cats/cats-mirnas-present-in-1-copy-in-1ng-circulating-rna.png" /></div>
<div class="large-5 small-12 medium-5 columns">
<p>Transcripts detected in miRNA samples of <strong>CATS small RNA-seq Kit</strong> vs the Competitor&rsquo;s Kit.</p>
<p>Input: <strong>1 ng circulating small RNA</strong> in plasma samples. <strong>PCR cycles: CATS 14x</strong> vs Competitor 21x. <strong>Final library yield: CATS 27 ng</strong> vs Competitor 1.2 ng.</p>
</div>
</div>
<div>
<h3>Ultra low inputs, excellent reproducibility</h3>
<div class="large-7 small-12 medium-7 columns"><img src="https://www.diagenode.com/img/product/kits/cats/CATS White Paper_CATS-fig3.png" /></div>
<div class="large-5 small-12 medium-5 columns">
<p>Correlation between 2 different operators using <strong>CATS small RNA-seq Kit</strong> on two different inputs (100 pg vs 1 ng) for ncRNA detected at TPM &ge;2. <br />R<sup>2</sup> = 0.86</p>
</div>
</div>
<div>
<h3>Consistency across template switching techniques</h3>
<div class="large-7 small-12 medium-7 columns"><img src="https://www.diagenode.com/img/product/kits/cats/CATS-White-Paper_graph-fig12.png" /></div>
<div class="large-5 small-12 medium-5 columns">
<p>Comparison of the number of detected small non-coding RNAs <strong>CATS small RNA-seq Kit</strong> vs SMARTer <br />Input: <strong>100 pg isolated small RNA</strong>. TPM &ge;2. Transcripts taken into consideration: miRNA, piRNA, scRNA, scaRNA, snoRNA, snRNA and vaultRNA. 1,217 transcripts found in both libraries at this expression level.</p>
</div>
</div>
<div>
<h3>High number of reads mapped</h3>
<div class="large-7 small-12 medium-7 columns"><img src="https://www.diagenode.com/img/product/kits/cats/CATS-White-Paper_graph-fig6.jpg" /></div>
<div class="large-5 small-12 medium-5 columns">
<p>Representation of detected transcripts different biotypes with <strong>CATS small RNA-seq Kit</strong>vs NEBNext UltraI kit. TPM&ge;2. <br /> <strong>100 ng total RNA, 1 ng small RNA</strong> used as input.</p>
</div>
</div>
<div>
<h3>Excellent performance on challenging samples</h3>
<div class="large-7 small-12 medium-7 columns"><img src="https://www.diagenode.com/img/product/kits/cats/Exosomes-page_heatt-1.jpg" /></div>
<div class="large-5 small-12 medium-5 columns">
<p>Heatmap clustering of the top 50 differentially expressed miRNAs after library preparation:</p>
<ul>
<li><strong>CATS Small RNA-seq Kit</strong> on 1 ng exosomal RNA (Exosome sample 1, 2)</li>
<li><strong>CATS RNA-seq Kit</strong> on 1 ng total RNA from parent (HEK293T) cells (Cell sample 1, 2).</li>
</ul>
<p>Prior library preparation, exosomes were isolated with Diagenode exosome capture solutions <a href="../categories/exosomes">Exosomes</a></p>
</div>
</div>
<div>
<h3>CATS saves time</h3>
<img src="https://www.diagenode.com/img/categories/library-prep/cats-save-time.png" /></div>
</div>
</div>
</div>
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<ul>
<li>多様なスモールRNAを回収可能</li>
<li>10pgの超少量インプットRNAで優れた再現性</li>
<li>難しいサンプルでの優れたパフォーマンス</li>
</ul>
<ul class="accordion" data-accordion="">
<li class="accordion-navigation"><a href="#more" style="color: #13b29c; background-color: transparent; display: inline; padding: 0;">続きを読む</a>
<div id="more" class="content">
<p style="text-align: justify;">CATSは、RNAの3&rsquo;末端をキャプチャーするためのポリヌクレオチドテーリングおよび、cDNA合成時に5&rsquo;末端をキャプチャーするためのMMLV-RTによるテンプレートスイッチ 能力を利用した技術です。この方法なら、10ピコグラムの低インプットRNA量からわずか数時間でIllumina用シークエンシングライブラリーを作製することができます。</p>
<p style="text-align: justify;">ライブラリーは、ストランド特異的な情報を保持しています。「CATS RNA-seq Kit」は、増幅を最小限に抑えることでより多くの有効な鋳型をキャプチャーし、また、バイアスを最小限に抑えることで高い複雑性を得ることができるので、他のライゲーションベースの手法と比べより高いライブラリー作製効率を示します。</p>
</div>
</li>
</ul>
<div class="carrousel" style="background-position: center;">
<div class="container">
<div class="row" style="background: rgba(255,255,255,0.1); height: 241px;">
<div class="large-12 columns slick">
<div>
<h3>Unique sncRNAs detected in circulating plasma RNA</h3>
<div class="large-7 small-12 medium-7 columns"><img src="https://www.diagenode.com/img/product/kits/cats/cats-908-competitor-3.png" /></div>
<div class="large-5 small-12 medium-5 columns">
<p>sncRNA transcripts detected using the <strong>CATS small RNA-seq Kit</strong> vs the Competitor&rsquo;s Kit. The input was <strong>1 ng circulating small RNA</strong> in plasma samples. In total, 908 transcripts were found in the CATS small RNA-seq libraries. TPM&ge;1</p>
<p><strong>PCR cycles: CATS 14x</strong> vs Competitor 21x. <strong>Final library yield: CATS 27 ng</strong> vs Competitor 1.2 ng.</p>
</div>
</div>
<div>
<h3>More miRNA transcripts detected from challenging samples</h3>
<div class="large-7 small-12 medium-7 columns"><img src="https://www.diagenode.com/img/product/kits/cats/cats-mirnas-present-in-1-copy-in-1ng-circulating-rna.png" /></div>
<div class="large-5 small-12 medium-5 columns">
<p>Transcripts detected in miRNA samples of <strong>CATS small RNA-seq Kit</strong> vs the Competitor&rsquo;s Kit.</p>
<p>Input: <strong>1 ng circulating small RNA</strong> in plasma samples. <strong>PCR cycles: CATS 14x</strong> vs Competitor 21x. <strong>Final library yield: CATS 27 ng</strong> vs Competitor 1.2 ng.</p>
</div>
</div>
<div>
<h3>Ultra low inputs, excellent reproducibility</h3>
<div class="large-7 small-12 medium-7 columns"><img src="https://www.diagenode.com/img/product/kits/cats/CATS White Paper_CATS-fig3.png" /></div>
<div class="large-5 small-12 medium-5 columns">
<p>Correlation between 2 different operators using <strong>CATS small RNA-seq Kit</strong> on two different inputs (100 pg vs 1 ng) for ncRNA detected at TPM &ge;2. <br />R<sup>2</sup> = 0.86</p>
</div>
</div>
<div>
<h3>Consistency across template switching techniques</h3>
<div class="large-7 small-12 medium-7 columns"><img src="https://www.diagenode.com/img/product/kits/cats/CATS-White-Paper_graph-fig12.png" /></div>
<div class="large-5 small-12 medium-5 columns">
<p>Comparison of the number of detected small non-coding RNAs <strong>CATS small RNA-seq Kit</strong> vs SMARTer <br />Input: <strong>100 pg isolated small RNA</strong>. TPM &ge;2. Transcripts taken into consideration: miRNA, piRNA, scRNA, scaRNA, snoRNA, snRNA and vaultRNA. 1,217 transcripts found in both libraries at this expression level.</p>
</div>
</div>
<div>
<h3>High number of reads mapped</h3>
<div class="large-7 small-12 medium-7 columns"><img src="https://www.diagenode.com/img/product/kits/cats/CATS-White-Paper_graph-fig6.jpg" /></div>
<div class="large-5 small-12 medium-5 columns">
<p>Representation of detected transcripts different biotypes with <strong>CATS small RNA-seq Kit</strong>vs NEBNext UltraI kit. TPM&ge;2. <br /> <strong>100 ng total RNA, 1 ng small RNA</strong> used as input.</p>
</div>
</div>
<div>
<h3>Excellent performance on challenging samples</h3>
<div class="large-7 small-12 medium-7 columns"><img src="https://www.diagenode.com/img/product/kits/cats/Exosomes-page_heatt-1.jpg" /></div>
<div class="large-5 small-12 medium-5 columns">
<p>Heatmap clustering of the top 50 differentially expressed miRNAs after library preparation:</p>
<ul>
<li><strong>CATS Small RNA-seq Kit</strong> on 1 ng exosomal RNA (Exosome sample 1, 2)</li>
<li><strong>CATS RNA-seq Kit</strong> on 1 ng total RNA from parent (HEK293T) cells (Cell sample 1, 2).</li>
</ul>
<p>Prior library preparation, exosomes were isolated with Diagenode exosome capture solutions <a href="../categories/exosomes">Exosomes</a></p>
</div>
</div>
<div>
<h3>CATS saves time</h3>
<img src="https://www.diagenode.com/img/categories/library-prep/cats-save-time.png" /></div>
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			'name' => 'CATS Small RNA-seq Kit x24',
			'description' => '<p style="text-align: left;"><strong>An updated version of this kit using D-Plex technology&nbsp;is available for superior performance.</strong></p>
<h4><span>Discover our <strong>NEW<a href="https://www.diagenode.com/en/p/D-Plex-Small-RNA-seq-Library-Prep-x24"> D-Plex Small RNA-seq Kit&nbsp;for Illumina</a></strong>&nbsp;and <strong><a href="https://www.diagenode.com/en/p/d-plex-small-RNA-dnbseq-kit-x24">D-Plex Small DNBSEQ Kit for MGI</a></strong>.</span></h4>',
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			'name' => 'D-Plex Small RNA-seq Kit for Illumina',
			'description' => '<div class="small-12 medium-12 large-12 columns" style="border: 3px solid #B02736; padding: 10px; margin: 10px;">
<h2>Product Features</h2>
<ul style="list-style-type: disc;">
<li>Ultra-low input capability, down to 10 pg for small RNAs and 100 pg for total RNA samples</li>
<li>High library complexity providing novel and diverse transcript detection</li>
<li>Versatile integartion into numerpus transcriptomic analysis workflow: ribosome profiling, CLIP-seq, RIP-seq and other</li>
<li>Improved quantification accuracy through the use of UMIs</li>
<li>Easy to use with minimal hands-on time: one day, one tube protocol</li>
</ul>
</div>
<p></p>
<p></p>
<center><em><a class="chip diahome button" href="https://www.diagenode.com/files/products/kits/MA-D-Plex.pdf" target="_blank" title="D-Plex Small RNA library preparation user manual"><strong>Download the manual</strong></a></em></center>
<p>D-Plex Small RNA-seq Library Prep Kit is a tool designed for the study of the <strong>small non-coding transcriptome</strong>. The kit is using the<a href="https://www.diagenode.com/en/pages/dplex" target="_blank"> D-Plex technology</a> to generate&nbsp;small RNA libraries for Illumina sequencing directly from total RNAs or enriched small RNAs.</p>
<p>The D-Plex technology utilizes&nbsp;two innovative&nbsp;<strong>ligation-free mechanisms</strong> - <strong>poly(A) tailing</strong> and <strong>template switching</strong>&nbsp;- to produce sequencing libraries&nbsp;from ultra-low input amounts, down to 10 pg for small RNAs and 100 pg for total RNAs.&nbsp;Combined with <strong>unique molecular identifiers</strong> (UMI), this complete solution ensures a <strong>realistic</strong> and <strong>accurate representation of diverse small RNA species</strong> (such as microRNAs, piRNAs, tRNAs, and siRNAs) with minimized quantitative bias.</p>
<p>D-Plex Small RNA-seq Kit offers a time saving protocol that can be completed within <strong>5 hours</strong> and requires minimal hands-on time.&nbsp;<span>The library preparation takes place in a&nbsp;</span><strong>single tube</strong><span>, increasing the efficiency tremendously.&nbsp;</span></p>
<p>D-Plex Small RNA-seq Kit includes all buffers and enzymes necessary for the library preparation. Specific D-Plex Indexes were designed and validated to fit the D-Plex technology and are available separately:</p>
<p><strong>For D-Plex UDI library construction:</strong></p>
<ul style="list-style-type: disc;">
<li><a href="https://www.diagenode.com/en/p/D-Plex-24-Unique-Dual-Indexes-Set-A" title="D-Plex UDI Module - Set A" target="_blank"><span>C05030021</span>&nbsp;- D-Plex Unique Dual Indexes for Illumina - Set A</a></li>
<li><a href="https://www.diagenode.com/en/p/D-Plex-24-Unique-Dual-Indexes-Set-B" title="D-Plex UDI Module - Set B" target="_blank"><span>C05030022</span>&nbsp;- D-Plex Unique Dual Indexes for Illumina - Set B</a></li>
<li><a href="https://www.diagenode.com/en/p/D-Plex-24-Unique-Dual-Indexes-Set-C">C05030023 - D-Plex&nbsp;Unique Dual&nbsp;Indexes for Illumina - Set C</a></li>
<li><a href="https://www.diagenode.com/en/p/D-Plex-24-Unique-Dual-Indexes-Set-D">C05030024 - D-Plex&nbsp;Unique Dual&nbsp;Indexes for Illumina - Set D</a></li>
</ul>
<p><span>The use of UDI is highly recommended&nbsp;to mitigate errors introduced by read misassignment, including index&nbsp;hopping frequently observed with patterned flow cells such as Illumina&rsquo;s&nbsp;NovaSeq system.</span></p>
<p><strong>For D-Plex SI library construction:</strong></p>
<ul style="list-style-type: disc;">
<li><a href="https://www.diagenode.com/en/p/D-Plex-24-Single-Indexes-Set-A" title="D-Plex SI Module - Set A" target="_blank">C05030010 - D-Plex Single Indexes for Illumina - Set A</a></li>
<li><a href="https://www.diagenode.com/en/p/D-Plex-24-Single-Indexes-Set-B" title="D-Plex SI Module - Set B" target="_blank">C05030011 - D-Plex Single Indexes for Illumina - Set B</a></li>
</ul>
<p><strong>D-Plex is also available for MGI sequencing, check <a href="https://www.diagenode.com/en/p/d-plex-small-RNA-dnbseq-kit-x24" target="_blank">here</a>!</strong></p>
<p></p>
<p></p>
<p></p>
<center><strong>The D-Plex smRNA-seq is a versatile tool for a plethora of transciptomic analysis</strong></center>
<p></p>
<center><img src="https://www.diagenode.com/img/product/kits/dplex/versatile-circle.png" /></center>
<p></p>
<p>With low-input capability, accuracy and ability to incorporate different transcript classes independent of chemical moieties, the strong D-Plex library-preparation method can be included in various analysis workflows (i.e., ribosome profiling, genome-wide mapping of protein: RNA binding sites).</p>
<p></p>
<p></p>',
			'label1' => 'Characteristics and library prep. workflow ',
			'info1' => '<div class="row">
<div class="small-12 columns">
<p><strong>High library diversity for ultra-low inputs</strong></p>
<center><img src="https://www.diagenode.com/img/product/kits/dplex/dplex-diversity-fig1.png" /></center></div>
<div class="small-12 columns"><center><img src="https://www.diagenode.com/img/product/kits/dplex/dplex-fig2-captures.png" /></center></div>
</div>
<p></p>
<div class="row">
<div class="small-12 columns">
<p>D-Plex smRNA-seq captures the smRNA complexity of the sample in a sensitive manner. A large number of features is detected for each biotype at a CPM &ge;5, as shown above for different species.</p>
</div>
</div>
<p></p>
<p><strong>Accurate representation of the smRNA content of a sample</strong></p>
<div class="row">
<div class="small-6 columns"><center><img src="https://www.diagenode.com/img/product/kits/dplex/dplex-fig-ratplasma.png" /></center></div>
<div class="small-6 columns"><center><img src="https://www.diagenode.com/img/product/kits/dplex/dplex-fig-miRNAdistribution.png" /></center></div>
</div>
<div class="row">
<div class="small-6 columns">
<p><strong>Accurate identification of PCR duplicates in low-input samples using unique molecular identifiers (UMIs).</strong><br />The UMI read deduplication that is embedded in the D-Plex construct is used to avoid over-estimation of transcripts by identifying clones generated during the PCR amplification of the library. Despite limiting starting RNA input, the UMI correction removed technical copies of transcripts, maintaining the initial sample abundance.</p>
</div>
<div class="small-6 columns">
<p>D-Plex (template switching) technology enables recovery of the initial miRNA distribution of the miRXplore Universal Reference (Miltenyi Biotech Inc., Cat. No. 130-093-521). In contrast, ligation-based kits display a strong distortion of the miRNA equimolar distribution initially present in the pool, indicating sample incorporation bias.</p>
</div>
</div>
<p></p>
<p></p>
<div class="row">
<div class="small-6 columns"><center><img src="https://www.diagenode.com/img/product/kits/dplex/dplex-fig-foldchange.jpg" /></center></div>
<div class="small-6 columns"><strong>D-Plex smRNA-seq in association with the MGcount analysis correlates strongly (R&sup2; &gt; 0.8) with the RT-qPCR analysis, which is considered the gold-standard for accuracy. </strong><br />The figures shows a fold-change accuracy of a panel of 20 different small-RNA (figure taken from MGcount publication - Hita et al., BMC bioinformatics, 23-39(2022).</div>
</div>
<p></p>
<p></p>
<p><strong>Maximize information from the regulatory transcriptome using D-Plex small RNA-seq kit and MGcount*</strong></p>
<div class="row">
<div class="small-6 columns"><center><img src="https://www.diagenode.com/img/product/kits/dplex/dplex-fig-multialignments.png" /></center></div>
<div class="small-6 columns">By analyzing D-Plex dataset with MGcount, more reads are kept during the analysis, which ultimately preserves biological complexity linked to ncRNA expression without decreasing the accuracy of detection. <br /><span style="line-height: 1em;"><small>*Hita, A., Brocart, G., Fernandez, A. et al. MGcount: a total RNA-seq quantification tool to address multi-mapping and multi-overlapping alignments ambiguity in non-coding transcripts. BMC Bioinformatics 23, 39 (2022). <a href="https://doi.org/10.1186/s12859-021-04544-3">https://doi.org/10.1186/s12859-021-04544-3</a></small></span></div>
</div>
<p></p>
<p></p>
<div class="row">
<div class="small-12 columns">
<p>The D-Plex technology uses two innovative ligation-free mechanisms, <strong>poly(A) tailing and template switching</strong>, to produce sequencing libraries from ultra-low input amounts.</p>
</div>
</div>
<div class="row" style="background-color: #f5f5f5;">
<div class="small-12 columns"><br />
<p><strong>WORKFLOW</strong></p>
<center><img src="https://www.diagenode.com/img/product/kits/dplex/FL-Image-Workflow.jpg" width="50%" /></center></div>
<div class="small-12 columns">
<p style="text-align: justify; padding: 15px;"><br />RNA molecules are polyadenylated at the 3&rsquo;-end and primed with an oligo(dT) primer containing part of the ILMN 3&rsquo;-adapter sequence. The addition of a template-switching oligonucleotide during cDNA synthesis enables fusion of part of the ILMN 5&rsquo;-adapter during reverse transcription. After PCR, the library comprises double stranded DNA constructs that are ready for sequencing.</p>
</div>
</div>
<p><br /><br /></p>
<p></p>
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			'info2' => '<p>A specific bioinformatics pipeline has been developed to process the special sequences present in the D-Plex construct, namely the UMI, the A-tail, and the template switch motif. All guidelines and free softwares are shared in the user manual. Subject to the compatibility of D-Plex constructs, other specific pipelines can be used.</p>
<p><img src="https://www.diagenode.com/img/product/kits/dplex/bioinfoPipe.png" alt="small RNA sequencing bioinformatics pipeline" caption="false" width="925" height="196" /></p>
<p>Need help for your bioinformatics analysis of miRNA?</p>
<p></p>
<div class="small-12 medium-3 large-3 columns"><center><a href="https://ccb-compute.cs.uni-saarland.de/mirmaster" target="_blank"><img src="https://www.diagenode.com/img/product/kits/dplex/miRMaster_logo.png" /></a></center>
<p>&nbsp;</p>
<p>&nbsp;</p>
</div>
<div class="small-12 medium-9 large-9 columns">
<p>Diagenode has collaborated with <strong>Andreas Keller</strong> and <strong>Tobias Fehlmann</strong> to develop a new bioinformatics pipeline for&nbsp;<span>the <strong>prediction of novel miRNAs</strong>.</span><br /><a href="https://ccb-compute.cs.uni-saarland.de/mirmaster" target="_blank"></a></p>
<ul>
<li style="text-align: justify;"><a href="https://ccb-compute.cs.uni-saarland.de/mirmaster2">miRMaster 2</a></li>
<li style="text-align: justify;"><a href="https://ccb-compute.cs.uni-saarland.de/mirmaster" target="_blank">miRMaster</a></li>
</ul>
</div>
<p>&nbsp;</p>
<p>&nbsp;</p>',
			'label3' => 'Data analysis - Counting using MGcount',
			'info3' => '<p>The counting or expression level calculation is the last step of the processing to generate an expression level matrix. We recommend using MGcount*, a counting tool developed at Diagenode with a suitable annotations file that include the small RNA transcripts that are object of study. MGcount, built on top of featureCounts, employs a flexible quantification approach to deal with datasets containing multiple RNA biotypes such as D-plex libraries. Non-coding RNAs varying in length, biogenesis, and function, may overlap in a genomic region, and are sometimes present in the genome with a high copy number. Consequently, reads may align equally well to more than one position in the reference genome or/and align to a position where more than one annotated transcript is located. MGcount employs two strategies to quantify these reads. Firstly, it assigns reads in rounds prioritizing small-RNAs over long-RNAs ensuring the unbiased read attribution to intergenic and intragenic small RNAs while preventing host-genes transcription over-estimation. Secondly, MGcount collapses loci where reads consistently multi-map into communities of loci with a graph-based approach. The resultant communities are groups of biologically related loci with nearly identical sequence. Subsequently, quantification of reads is performed at the loci-community level, reducing multi-alignments ambiguity at individual locus. Ultimately, this strategy maximizes the transcriptome information analysed and improves the interrogation of non-coding RNAs. MGcount software repository provides annotation files for A. thaliana, H. sapiens, M. musculus and C. elegans. The required input files for MGcount are a .txt file listing the paths to the alignment input files (.bam format) and the annotations file (.gtf format). The output directory path has to be provided as an input as well.</p>
<p><strong>Example command:</strong></p>
<p style="background-color: #f0f0f0;">MGcount -T 2 --gtf Homo_sapiens.GRCh38.gtf --outdir outputs --bam_infiles input_bamfilenames.txt</p>
<p>MGcount provides the choice to enable/disable the quantification of all RNA biotypes included in the annotation file in the form of "communities" as optional parameters for small-RNA (--ml_flag_small) and long-RNA (--ml_flag_long). Both are enabled by default. The main output of MGcount is the count_matrix.csv file containing an expression matrix that can be imported to R or any other software for downstream analyses.<br />A full user guide for MGCount is available here: <a href="https://filedn.com/lTnUWxFTA93JTyX3Hvbdn2h/mgcount/UserGuide.html">https://filedn.com/lTnUWxFTA93JTyX3Hvbdn2h/mgcount/UserGuide.html</a>.</p>
<p>Other standard counting tools such as featureCounts or HTSeq-counts can also be used alternatively. Given the high complexity of D-Plex libraries, we recommend having a clear understanding of the scientific question and the goal of the project before proceeding to the choice of the counting method as this will strongly impact downstream analyses. Diagenode provides bioinformatics support as a service (please, contact us if you need help with data analysis).</p>
<p>Notice that D-Plex produces forward-stranded data. Stranded libraries have the benefit that reads map to the genome strand where they were originated from. Therefore, when estimating transcript expression, reads aligned to the forward strand should be assigned only to transcript features in the forward strand whereas reads aligned to the reverse strand should be assigned only to transcript features in the reverse strand. For this, make sure you select &ldquo;stranded mode&rdquo; in any tool of choice. Stranded mode is selected by default in MGcount.</p>
<p><em><small>*Hita, A., Brocart, G., Fernandez, A. et al. MGcount: a total RNA-seq quantification tool to address multi-mapping and multi-overlapping alignments ambiguity in non-coding transcripts. BMC Bioinformatics 23, 39 (2022). <a href="https://doi.org/10.1186/s12859-021-04544-3">https://doi.org/10.1186/s12859-021-04544-3</a></small></em></p>',
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			'meta_title' => 'D-Plex Small RNA-seq Library Prep Kit | Diagenode ',
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			'meta_description' => 'Small RNA-seq library preparation for Illumina sequencing - Unique D-Plex technology - Optimized for ultra-low input (100 pg total RNA) - UMI reduce PCR biases - UDI detect index hopping - Compatibility with plasma samples - User-friendly and fast protocol',
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<p></p>
<center><a class="chip diahome button" href="https://www.diagenode.com/files/products/kits/D-Plex-Small-RNA-DNBSEQ.pdf" target="_blank" title="D-Plex Small RNA DNBSEQ user manual"><strong>Download the manual</strong></a></center>
<p></p>
<p>D-Plex Small RNA DNBSEQ&trade; Kit is a tool designed for the study of the small non-coding transcriptome. The kit is using the <a href="https://www.diagenode.com/en/pages/dplex" target="_blank">D-Plex technology</a> to generate double-stranded DNA libraries ready to be used for the DNA single-strand circularization step required for DNBSEQ sequencing on MGI sequencers.</p>
<p>The D-Plex technology&nbsp;utilizes the innovative capture and amplification by&nbsp;tailing and switching, a&nbsp;ligation-free&nbsp;method for RNA library preparation from ultra-low input amounts, down to 10 pg for small RNAs and 100 pg for total RNAs.&nbsp;This innovative solution enables diverse and novel transcripts detection, even from challenging clinical samples such as liquid biopsies.</p>
<p><span>D-Plex Small&nbsp;RNA&nbsp;<span>DNBSEQ&trade;</span> Kit offers a time saving protocol that can be completed within 5 hours and requires minimal hands-on time.&nbsp;</span><span>The library preparation takes place in a&nbsp;</span><span>single tube</span><span>, increasing the efficiency tremendously.&nbsp;This ensures high technical&nbsp;reliability and reproducibility<span>.</span></span></p>
<p>D-Plex Small RNA DNBSEQ&trade; Kit includes all buffers and enzymes necessary for the library preparation. Specific D-Plex DNBSEQ Barcodes were designed and validated to fit the D-Plex technology and are available separately:</p>
<ul>
<li><a href="https://www.diagenode.com/en/p/d-plex-24-dnbseq-barcodes-set-a">C05030060 - D-Plex DNBSEQ Barcodes for MGI - Set A</a></li>
<li><a href="https://www.diagenode.com/en/p/d-plex-24-dnbseq-barcodes-set-b">C05030061 - D-Plex DNBSEQ Barcodes for MGI - Set B</a></li>
</ul>
<p><b><strong>D-Plex is also available for Illumina sequencing, check<span>&nbsp;</span><a href="https://www.diagenode.com/en/p/D-Plex-Small-RNA-seq-Library-Prep-x24" target="_blank">here</a>!</strong></b></p>
<div class="row">
<div class="carrousel" style="background-position: center;">
<div class="container">
<div class="row" style="background: rgba(255,255,255,0.1);">
<div class="large-12 columns slick">
<div>
<h3>Diverse and novel transcript detection</h3>
<div class="large-10 small-12 medium-10 large-centered medium-centered small-centered columns"><img style="height: 400px; display: block; margin-left: auto; margin-right: auto;" src="https://www.diagenode.com/img/product/kits/dplex/dplex-transcript.png" alt="small RNA library preparation for Illumina" /></div>
<div class="large-8 small-12 medium-6 large-centered medium-centered small-centered columns"><center>
<p style="text-align: justify;">The D-Plex Small RNA DNBSEQ protocol generates complex RNA libraries deciphering the wide diversity of small non-coding RNA spectrum (including miRNAs, snoRNAs, snRNAs)&nbsp; in human plasma samples.</p>
</center></div>
</div>
<div>
<h3>Ultra-low input performance</h3>
<div class="large-10 small-12 medium-10 large-centered medium-centered small-centered columns"><img style="height: 400px; display: block; margin-left: auto; margin-right: auto;" src="https://www.diagenode.com/img/product/kits/dplex/dplex-ultralow-input.png" alt="Ultra-low input performance" /></div>
<div class="large-8 small-12 medium-6 large-centered medium-centered small-centered columns"><center>
<p style="text-align: justify;">Sequencing data from circulating RNA samples of two input amounts (25 pg and 2.5 ng) were highly correlated (<i>R = 0.99</i>) when compared using Pearson correlation coefficient.</p>
</center></div>
</div>
<div>
<h3>High mapping efficiency</h3>
<div class="large-10 small-12 medium-10 large-centered medium-centered small-centered columns"><img style="height: 400px; display: block; margin-left: auto; margin-right: auto;" src="https://www.diagenode.com/img/product/kits/dplex/dplex-mapping.png" alt="High mapping efficiency" /></div>
<div class="large-8 small-12 medium-6 large-centered medium-centered small-centered columns"><center>
<p style="text-align: justify;"><b></b>The D-Plex Small RNA DNBSEQ kit is compatible with clinical-relevant samples, such as human plasma, and ultra low range of circulating RNA input (down to 10 pg) and exhibits good read mapping of sequencing reads (up to 70% mapping rate).</p>
</center></div>
</div>
<div>
<h3>High quality DNBSEQ sequencing solution</h3>
<div class="large-10 small-12 medium-10 large-centered medium-centered small-centered columns"><img style="height: 400px;" src="https://www.diagenode.com/img/product/kits/dplex/dplex-dnbseq.png" alt="High quality DNBSEQ sequencing solution" /></div>
<div class="large-8 small-12 medium-6 large-centered medium-centered small-centered columns"><center>
<p><b></b>The D-Plex Small RNA DNBSEQ kit combines our best-in-class RNA library preparation &ndash; D-Plex technology &ndash; with MGI&rsquo;s high-quality, cost-effective, DNA nanoballs &ndash; DNBSEQ &ndash; sequencing solution, creating a unified platform to support high quality small RNA sequencing.</p>
</center></div>
</div>
</div>
</div>
</div>
</div>
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<li><strong>Latest innovation in RNA-seq</strong>:&nbsp;unique D-Plex technology&nbsp;offering ligation-free&nbsp;protocol for library preparation</li>
<li><strong>Ultra-low input capability</strong>: down to 10 pg for small RNAs and 100 pg for total RNAs</li>
<li><strong>High library complexity</strong>:<strong> </strong>obtain a complete view of&nbsp;your small RNA transcriptome</li>
<li><strong>Optimal performance on clinical samples</strong>: validated&nbsp;with circulating RNAs from liquid biopsies</li>
<li><strong>Easy to use with minimal hands-on time</strong>: one day, one tube protocol</li>
<li><strong>Highest sequencing quality</strong>: specifically formatted for MGI DNBSEQ&trade; sequencers</li>
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<li><a href="https://www.diagenode.com/en/p/d-plex-24-dnbseq-barcodes-set-a">C05030060 - D-Plex 24 DNBSEQ Barcodes for MGI - Set A</a></li>
<li><a href="https://www.diagenode.com/en/p/d-plex-24-dnbseq-barcodes-set-b">C05030061 - D-Plex 24 DNBSEQ Barcodes for MGI - Set B</a></li>
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<div class="small-12 medium-12 large-12 columns">
<p><span style="font-weight: 400;">Most of the major next-generation sequencing platforms require ligation of specific adaptor oligos to </span><a href="../applications/dna-rna-shearing"><span style="font-weight: 400;">fragmented DNA or RNA</span></a><span style="font-weight: 400;"> prior to sequencing</span></p>
<p><span style="font-weight: 400;">After input DNA has been fragmented, it is end-repaired and blunt-ended</span><span style="font-weight: 400;">. The next step is a A-tailing in which dAMP is added to the 3&acute; end of the blunt phosphorylated DNA fragments to prevent concatemerization and to allow the ligation of adaptors with complementary dT overhangs. In addition, barcoded adapters can be incorporated to facilitate multiplexing prior to or during amplification.</span></p>
<center><img src="https://www.diagenode.com/img/categories/library-prep/flux.png" /></center>
<p><span style="font-weight: 400;">Diagenode offers a comprehensive product portfolio for library preparation:<br /></span></p>
<strong><a href="https://www.diagenode.com/en/categories/Library-preparation-for-RNA-seq">D-Plex&nbsp;RNA-seq Library Preparation Kits</a></strong><br />
<p><span style="font-weight: 400;">Diagenode&rsquo;s new RNA-sequencing solutions utilize the innovative c</span><span style="font-weight: 400;">apture and a</span><span style="font-weight: 400;">mplification by t</span><span style="font-weight: 400;">ailing and s</span><span style="font-weight: 400;">witching&rdquo;</span><span style="font-weight: 400;">, a ligation-free method to produce DNA libraries for next generation sequencing from low input amounts of RNA. </span><span style="font-weight: 400;"></span><a href="../categories/Library-preparation-for-RNA-seq">Learn more</a></p>
<strong><a href="../categories/library-preparation-for-ChIP-seq">ChIP-seq and DNA sequencing library preparation solutions</a></strong><br />
<p><span style="font-weight: 400;">Our kits have been optimized for DNA library preparation used for next generation sequencing for a wide range of inputs. Using a simple three-step protocols, our</span><a href="http://www.diagenode.com/p/microplex-library-preparation-kit-v2-x12-12-indices-12-rxns"><span style="font-weight: 400;"> </span></a><span style="font-weight: 400;">kits are an optimal choice for library preparation from DNA inputs down to 50 pg.&nbsp;</span><a href="../categories/library-preparation-for-ChIP-seq">Learn more</a></p>
<a href="../p/bioruptor-pico-sonication-device"><span style="font-weight: 400;"></span><strong>Bioruptor Pico - short fragments</strong></a><a href="../categories/library-preparation-for-ChIP-seq-and-DNA-sequencing"><span style="font-weight: 400;"></span></a><br />
<p><span style="font-weight: 400;"></span><span style="font-weight: 400;">Our well-cited Bioruptor Pico is the shearing device of choice for chromatin and DNA fragmentation. Obtain uniform and tight fragment distributions &nbsp;between 150bp -2kb. </span><a href="../p/bioruptor-pico-sonication-device">Learn more</a></p>
<strong><a href="../p/megaruptor2-1-unit"><span href="../p/bioruptor-pico-sonication-device">Megaruptor</span>&reg; - long fragments</a></strong><a href="../p/bioruptor-pico-sonication-device"><span style="font-weight: 400;"></span></a><a href="../categories/library-preparation-for-ChIP-seq-and-DNA-sequencing"><span style="font-weight: 400;"></span></a><br />
<p><span style="font-weight: 400;"></span><span style="font-weight: 400;">The Megaruptor is designed to shear DNA from 3kb-75kb for long-read sequencing.&nbsp; <a href="../p/megaruptor2-1-unit">Learn more</a></span></p>
<span href="../p/bioruptor-pico-sonication-device"></span><span style="font-weight: 400;"></span></div>
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			'description' => '<p style="text-align: left;"><em><strong>Note:</strong><span>&nbsp;</span>The D-Plex Small RNA-seq Kit manual describes the protocol for&nbsp;both UDI and SI library constructions.</em></p>',
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			'id' => '4216',
			'name' => 'Functional microRNA targetome undergoes degeneration-induced shift in the retina',
			'authors' => 'Chu-Tan JA et al.',
			'description' => '<div class="abstract-content selected" id="enc-abstract">
<p><strong class="sub-title">Background:<span>&nbsp;</span></strong>MicroRNA (miRNA) play a significant role in the pathogenesis of complex neurodegenerative diseases including age-related macular degeneration (AMD), acting as post-transcriptional gene suppressors through their association with argonaute 2 (AGO2) - a key member of the RNA Induced Silencing Complex (RISC). Identifying the retinal miRNA/mRNA interactions in health and disease will provide important insight into the key pathways miRNA regulate in disease pathogenesis and may lead to potential therapeutic targets to mediate retinal degeneration.</p>
<p><strong class="sub-title">Methods:<span>&nbsp;</span></strong>To identify the active miRnome targetome interactions in the healthy and degenerating retina, AGO2 HITS-CLIP was performed using a rodent model of photoreceptor degeneration. Analysis of publicly available single-cell RNA sequencing (scRNAseq) data was performed to identify the cellular location of AGO2 and key members of the microRNA targetome in the retina. AGO2 findings were verified by in situ hybridization (RNA) and immunohistochemistry (protein).</p>
<p><strong class="sub-title">Results:<span>&nbsp;</span></strong>Analysis revealed a similar miRnome between healthy and damaged retinas, however, a shift in the active targetome was observed with an enrichment of miRNA involvement in inflammatory pathways. This shift was further demonstrated by a change in the seed binding regions of miR-124-3p, the most abundant retinal AGO2-bound miRNA, and has known roles in regulating retinal inflammation. Additionally, photoreceptor cluster miR-183/96/182 were all among the most highly abundant miRNA bound to AGO2. Following damage, AGO2 expression was localized to the inner retinal layers and more in the OLM than in healthy retinas, indicating a locational miRNA response to retinal damage.</p>
<p><strong class="sub-title">Conclusions:<span>&nbsp;</span></strong>This study provides important insight into the alteration of miRNA regulatory activity that occurs as a response to retinal degeneration and explores the miRNA-mRNA targetome as a consequence of retinal degenerations. Further characterisation of these miRNA/mRNA interactions in the context of the degenerating retina may provide an important insight into the active role these miRNA may play in diseases such as AMD.</p>
</div>
<p><strong class="sub-title">Keywords:<span>&nbsp;</span></strong>Argonaute; HITS-CLIP; Inflammation; Retina; Retinal degeneration; Transcriptome; mRNA; microRNA.</p>',
			'date' => '2021-08-31',
			'pmid' => 'https://pubmed.ncbi.nlm.nih.gov/34465369/',
			'doi' => '10.1186/s13024-021-00478-9',
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			'id' => '3949',
			'name' => 'Repeat RNAs associate with replication forks and post-replicative DNA.',
			'authors' => 'Gylling HM, Gonzalez-Aguilera C, Smith MA, Kaczorowski DC, Groth A, Lund AH',
			'description' => '<p>Non-coding RNA has a proven ability to direct and regulate chromatin modifications by acting as scaffolds between DNA and histone-modifying complexes. However, it is unknown if ncRNA plays any role in DNA replication and epigenome maintenance, including histone eviction and re-instalment of histone-modifications after genome duplication. Isolation of nascent chromatin has identified a large number of RNA-binding proteins in addition to unknown components of the replication and epigenetic maintenance machinery. Here, we isolated and characterized long and short RNAs associated with nascent chromatin at active replication forks and track RNA composition during chromatin maturation across the cell cycle. Shortly after fork passage, GA-rich-, Alpha- and TElomeric Repeat-containing RNAs (TERRA) are associated with replicated DNA. These repeat containing RNAs arise from loci undergoing replication, suggesting an interaction in cis. Post-replication during chromatin maturation, and even after mitosis in G1, the repeats remain enriched on DNA. This suggests that specific types of repeat RNAs are transcribed shortly after DNA replication and stably associate with their loci of origin throughout cell cycle. The presented method and data enables studies of RNA interactions with replication forks and post-replicative chromatin and provides insights into how repeat RNAs and their engagement with chromatin are regulated with respect to DNA replication and across the cell cycle.</p>',
			'date' => '2020-05-11',
			'pmid' => 'http://www.pubmed.gov/32393525',
			'doi' => '10.1261/rna.074757.120',
			'modified' => '2020-08-17 10:03:46',
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			'id' => '3862',
			'name' => 'Multisite Evaluation of Next-Generation Methods for Small RNA Quantification.',
			'authors' => 'Herbert ZT, Thimmapuram J, Xie S, Kershner JP, Kolling FW, Ringelberg CS, LeClerc A, Alekseyev YO, Fan J, Podnar JW, Stevenson HS, Sommerville G, Gupta S, Berkeley M, Koeman J, Perera A, Scott AR, Grenier JK, Malik J, Ashton JM, Pivarski KL, Wang X, Kuffe',
			'description' => '<p>Small RNAs (smRNAs) are important regulators of many biologic processes and are now most frequently characterized using Illumina sequencing. However, although standard RNA sequencing library preparation has become routine in most sequencing facilities, smRNA sequencing library preparation has historically been challenging because of high input requirements, laborious protocols involving gel purifications, inability to automate, and a lack of benchmarking standards. Additionally, studies have suggested that many of these methods are nonlinear and do not accurately reflect the amounts of smRNAs . Recently, a number of new kits have become available that permit lower input amounts and less laborious, gel-free protocol options. Several of these new kits claim to reduce RNA ligase-dependent sequence bias through novel adapter modifications and to lessen adapter-dimer contamination in the resulting libraries. With the increasing number of smRNA kits available, understanding the relative strengths of each method is crucial for appropriate experimental design. In this study, we systematically compared 9 commercially available smRNA library preparation kits as well as NanoString probe hybridization across multiple study sites. Although several of the new methodologies do reduce the amount of artificially over- and underrepresented microRNAs (miRNAs), we observed that none of the methods was able to remove all of the bias in the library preparation. Identical samples prepared with different methods show highly varied levels of different miRNAs. Even so, many methods excelled in ease of use, lower input requirement, fraction of usable reads, and reproducibility across sites. These differences may help users select the most appropriate methods for their specific question of interest.</p>',
			'date' => '2020-01-10',
			'pmid' => 'http://www.pubmed.gov/31966025',
			'doi' => '10.7171/jbt.20-3102-001',
			'modified' => '2020-03-20 17:53:30',
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			'description' => '<p>Successful treatment of cancer depends on early diagnosis and effective monitoring of patients' response to therapy. Traditional tools based on tumor biopsies lack the sensitivity and specificity to capture cancer development in its early phases and are not applicable for continuous monitoring. To overcome these barriers, liquid biopsies have been introduced as a minimally invasive and cost-efficient means of diagnosis with high level of specificity and sensitivity. Traditionally, liquid biopsy markers include circulating tumor cells and circulating tumor DNA. During the last decade, a new promising group of biomarkers has appeared and its utilization for cancer diagnosis and monitoring is intensively studied - the microRNAs (miRNAs). In this review, we provide a comprehensive overview of circulating miRNA analysis. We highlight the importance of sampling and quality control, discuss the technical aspects of miRNA extraction and quantification, summarize recommendations for downstream analysis and conclude with future perspectives. Taken together, we present the current state of knowledge in the field of miRNA analysis in liquid biopsies and the expected development and standardization.</p>',
			'date' => '2019-10-18',
			'pmid' => 'http://www.pubmed.gov/31635843',
			'doi' => '10.1016/j.mam.2019.10.002',
			'modified' => '2019-12-05 11:07:26',
			'created' => '2019-12-02 15:25:44',
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		),
		(int) 4 => array(
			'id' => '3697',
			'name' => 'The sncRNA Zoo: a repository for circulating small noncoding RNAs in animals.',
			'authors' => 'Fehlmann T, Backes C, Pirritano M, Laufer T, Galata V, Kern F, Kahraman M, Gasparoni G, Ludwig N, Lenhof HP, Gregersen HA, Francke R, Meese E, Simon M, Keller A',
			'description' => '<p>The repertoire of small noncoding RNAs (sncRNAs), particularly miRNAs, in animals is considered to be evolutionarily conserved. Studies on sncRNAs are often largely based on homology-based information, relying on genomic sequence similarity and excluding actual expression data. To obtain information on sncRNA expression (including miRNAs, snoRNAs, YRNAs and tRNAs), we performed low-input-volume next-generation sequencing of 500&nbsp;pg of RNA from 21 animals at two German zoological gardens. Notably, none of the species under investigation were previously annotated in any miRNA reference database. Sequencing was performed on blood cells as they are amongst the most accessible, stable and abundant sources of the different sncRNA classes. We evaluated and compared the composition and nature of sncRNAs across the different species by computational approaches. While the distribution of sncRNAs in the different RNA classes varied significantly, general evolutionary patterns were maintained. In particular, miRNA sequences and expression were found to be even more conserved than previously assumed. To make the results available for other researchers, all data, including expression profiles at the species and family levels, and different tools for viewing, filtering and searching the data are freely available in the online resource ASRA (Animal sncRNA Atlas) at https://www.ccb.uni-saarland.de/asra/.</p>',
			'date' => '2019-05-21',
			'pmid' => 'http://www.pubmed.gov/30937442',
			'doi' => '10.1093/nar/gkz227',
			'modified' => '2019-06-28 13:44:35',
			'created' => '2019-06-21 14:55:31',
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			'id' => '3609',
			'name' => 'MicroRNAs and Transplantation.',
			'authors' => 'Khan Z, Suthanthiran M, Muthukumar T',
			'description' => '<p>miRNAs, &sim;20 to 22 nucleotide single-stranded RNA species that play a pivotal role in the regulation of protein-coding genes, are emerging as robust biomarkers for assessing allograft status. Herein, the authors briefly review the biogenesis and function of the miRNAs and provide an overview of the tools to quantify miRNAs in tissues and body fluids. They then review their studies of discovery and validation of alterations in miRNA expression within kidney allografts with or without acute rejection, as well as with or without fibrosis, and summarize published data on miRNA expression patterns in kidney transplant recipients.</p>',
			'date' => '2019-03-01',
			'pmid' => 'http://www.pubmed.gov/30709501',
			'doi' => '10.1016/j.cll.2018.10.003',
			'modified' => '2019-04-17 14:48:18',
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			'authors' => 'Marcello Pirritano, Tobias Fehlmann, Thomas Laufer, Nicole Ludwig, Gilles Gasparoni, Yongping Li, Eckart Meese, Andreas Keller, and Martin Simon',
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<ul>
<li>多様なスモールRNAを回収可能</li>
<li>10pgの超少量インプットRNAで優れた再現性</li>
<li>難しいサンプルでの優れたパフォーマンス</li>
</ul>
<ul class="accordion" data-accordion="">
<li class="accordion-navigation"><a href="#more" style="color: #13b29c; background-color: transparent; display: inline; padding: 0;">続きを読む</a>
<div id="more" class="content">
<p style="text-align: justify;">CATSは、RNAの3&rsquo;末端をキャプチャーするためのポリヌクレオチドテーリングおよび、cDNA合成時に5&rsquo;末端をキャプチャーするためのMMLV-RTによるテンプレートスイッチ 能力を利用した技術です。この方法なら、10ピコグラムの低インプットRNA量からわずか数時間でIllumina用シークエンシングライブラリーを作製することができます。</p>
<p style="text-align: justify;">ライブラリーは、ストランド特異的な情報を保持しています。「CATS RNA-seq Kit」は、増幅を最小限に抑えることでより多くの有効な鋳型をキャプチャーし、また、バイアスを最小限に抑えることで高い複雑性を得ることができるので、他のライゲーションベースの手法と比べより高いライブラリー作製効率を示します。</p>
</div>
</li>
</ul>
<div class="carrousel" style="background-position: center;">
<div class="container">
<div class="row" style="background: rgba(255,255,255,0.1); height: 241px;">
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<div>
<h3>Unique sncRNAs detected in circulating plasma RNA</h3>
<div class="large-7 small-12 medium-7 columns"><img src="https://www.diagenode.com/img/product/kits/cats/cats-908-competitor-3.png" /></div>
<div class="large-5 small-12 medium-5 columns">
<p>sncRNA transcripts detected using the <strong>CATS small RNA-seq Kit</strong> vs the Competitor&rsquo;s Kit. The input was <strong>1 ng circulating small RNA</strong> in plasma samples. In total, 908 transcripts were found in the CATS small RNA-seq libraries. TPM&ge;1</p>
<p><strong>PCR cycles: CATS 14x</strong> vs Competitor 21x. <strong>Final library yield: CATS 27 ng</strong> vs Competitor 1.2 ng.</p>
</div>
</div>
<div>
<h3>More miRNA transcripts detected from challenging samples</h3>
<div class="large-7 small-12 medium-7 columns"><img src="https://www.diagenode.com/img/product/kits/cats/cats-mirnas-present-in-1-copy-in-1ng-circulating-rna.png" /></div>
<div class="large-5 small-12 medium-5 columns">
<p>Transcripts detected in miRNA samples of <strong>CATS small RNA-seq Kit</strong> vs the Competitor&rsquo;s Kit.</p>
<p>Input: <strong>1 ng circulating small RNA</strong> in plasma samples. <strong>PCR cycles: CATS 14x</strong> vs Competitor 21x. <strong>Final library yield: CATS 27 ng</strong> vs Competitor 1.2 ng.</p>
</div>
</div>
<div>
<h3>Ultra low inputs, excellent reproducibility</h3>
<div class="large-7 small-12 medium-7 columns"><img src="https://www.diagenode.com/img/product/kits/cats/CATS White Paper_CATS-fig3.png" /></div>
<div class="large-5 small-12 medium-5 columns">
<p>Correlation between 2 different operators using <strong>CATS small RNA-seq Kit</strong> on two different inputs (100 pg vs 1 ng) for ncRNA detected at TPM &ge;2. <br />R<sup>2</sup> = 0.86</p>
</div>
</div>
<div>
<h3>Consistency across template switching techniques</h3>
<div class="large-7 small-12 medium-7 columns"><img src="https://www.diagenode.com/img/product/kits/cats/CATS-White-Paper_graph-fig12.png" /></div>
<div class="large-5 small-12 medium-5 columns">
<p>Comparison of the number of detected small non-coding RNAs <strong>CATS small RNA-seq Kit</strong> vs SMARTer <br />Input: <strong>100 pg isolated small RNA</strong>. TPM &ge;2. Transcripts taken into consideration: miRNA, piRNA, scRNA, scaRNA, snoRNA, snRNA and vaultRNA. 1,217 transcripts found in both libraries at this expression level.</p>
</div>
</div>
<div>
<h3>High number of reads mapped</h3>
<div class="large-7 small-12 medium-7 columns"><img src="https://www.diagenode.com/img/product/kits/cats/CATS-White-Paper_graph-fig6.jpg" /></div>
<div class="large-5 small-12 medium-5 columns">
<p>Representation of detected transcripts different biotypes with <strong>CATS small RNA-seq Kit</strong>vs NEBNext UltraI kit. TPM&ge;2. <br /> <strong>100 ng total RNA, 1 ng small RNA</strong> used as input.</p>
</div>
</div>
<div>
<h3>Excellent performance on challenging samples</h3>
<div class="large-7 small-12 medium-7 columns"><img src="https://www.diagenode.com/img/product/kits/cats/Exosomes-page_heatt-1.jpg" /></div>
<div class="large-5 small-12 medium-5 columns">
<p>Heatmap clustering of the top 50 differentially expressed miRNAs after library preparation:</p>
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<li><strong>CATS Small RNA-seq Kit</strong> on 1 ng exosomal RNA (Exosome sample 1, 2)</li>
<li><strong>CATS RNA-seq Kit</strong> on 1 ng total RNA from parent (HEK293T) cells (Cell sample 1, 2).</li>
</ul>
<p>Prior library preparation, exosomes were isolated with Diagenode exosome capture solutions <a href="../categories/exosomes">Exosomes</a></p>
</div>
</div>
<div>
<h3>CATS saves time</h3>
<img src="https://www.diagenode.com/img/categories/library-prep/cats-save-time.png" /></div>
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<ul>
<li>多様なスモールRNAを回収可能</li>
<li>10pgの超少量インプットRNAで優れた再現性</li>
<li>難しいサンプルでの優れたパフォーマンス</li>
</ul>
<ul class="accordion" data-accordion="">
<li class="accordion-navigation"><a href="#more" style="color: #13b29c; background-color: transparent; display: inline; padding: 0;">続きを読む</a>
<div id="more" class="content">
<p style="text-align: justify;">CATSは、RNAの3&rsquo;末端をキャプチャーするためのポリヌクレオチドテーリングおよび、cDNA合成時に5&rsquo;末端をキャプチャーするためのMMLV-RTによるテンプレートスイッチ 能力を利用した技術です。この方法なら、10ピコグラムの低インプットRNA量からわずか数時間でIllumina用シークエンシングライブラリーを作製することができます。</p>
<p style="text-align: justify;">ライブラリーは、ストランド特異的な情報を保持しています。「CATS RNA-seq Kit」は、増幅を最小限に抑えることでより多くの有効な鋳型をキャプチャーし、また、バイアスを最小限に抑えることで高い複雑性を得ることができるので、他のライゲーションベースの手法と比べより高いライブラリー作製効率を示します。</p>
</div>
</li>
</ul>
<div class="carrousel" style="background-position: center;">
<div class="container">
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<div class="large-12 columns slick">
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<h3>Unique sncRNAs detected in circulating plasma RNA</h3>
<div class="large-7 small-12 medium-7 columns"><img src="https://www.diagenode.com/img/product/kits/cats/cats-908-competitor-3.png" /></div>
<div class="large-5 small-12 medium-5 columns">
<p>sncRNA transcripts detected using the <strong>CATS small RNA-seq Kit</strong> vs the Competitor&rsquo;s Kit. The input was <strong>1 ng circulating small RNA</strong> in plasma samples. In total, 908 transcripts were found in the CATS small RNA-seq libraries. TPM&ge;1</p>
<p><strong>PCR cycles: CATS 14x</strong> vs Competitor 21x. <strong>Final library yield: CATS 27 ng</strong> vs Competitor 1.2 ng.</p>
</div>
</div>
<div>
<h3>More miRNA transcripts detected from challenging samples</h3>
<div class="large-7 small-12 medium-7 columns"><img src="https://www.diagenode.com/img/product/kits/cats/cats-mirnas-present-in-1-copy-in-1ng-circulating-rna.png" /></div>
<div class="large-5 small-12 medium-5 columns">
<p>Transcripts detected in miRNA samples of <strong>CATS small RNA-seq Kit</strong> vs the Competitor&rsquo;s Kit.</p>
<p>Input: <strong>1 ng circulating small RNA</strong> in plasma samples. <strong>PCR cycles: CATS 14x</strong> vs Competitor 21x. <strong>Final library yield: CATS 27 ng</strong> vs Competitor 1.2 ng.</p>
</div>
</div>
<div>
<h3>Ultra low inputs, excellent reproducibility</h3>
<div class="large-7 small-12 medium-7 columns"><img src="https://www.diagenode.com/img/product/kits/cats/CATS White Paper_CATS-fig3.png" /></div>
<div class="large-5 small-12 medium-5 columns">
<p>Correlation between 2 different operators using <strong>CATS small RNA-seq Kit</strong> on two different inputs (100 pg vs 1 ng) for ncRNA detected at TPM &ge;2. <br />R<sup>2</sup> = 0.86</p>
</div>
</div>
<div>
<h3>Consistency across template switching techniques</h3>
<div class="large-7 small-12 medium-7 columns"><img src="https://www.diagenode.com/img/product/kits/cats/CATS-White-Paper_graph-fig12.png" /></div>
<div class="large-5 small-12 medium-5 columns">
<p>Comparison of the number of detected small non-coding RNAs <strong>CATS small RNA-seq Kit</strong> vs SMARTer <br />Input: <strong>100 pg isolated small RNA</strong>. TPM &ge;2. Transcripts taken into consideration: miRNA, piRNA, scRNA, scaRNA, snoRNA, snRNA and vaultRNA. 1,217 transcripts found in both libraries at this expression level.</p>
</div>
</div>
<div>
<h3>High number of reads mapped</h3>
<div class="large-7 small-12 medium-7 columns"><img src="https://www.diagenode.com/img/product/kits/cats/CATS-White-Paper_graph-fig6.jpg" /></div>
<div class="large-5 small-12 medium-5 columns">
<p>Representation of detected transcripts different biotypes with <strong>CATS small RNA-seq Kit</strong>vs NEBNext UltraI kit. TPM&ge;2. <br /> <strong>100 ng total RNA, 1 ng small RNA</strong> used as input.</p>
</div>
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<div>
<h3>Excellent performance on challenging samples</h3>
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<div class="large-5 small-12 medium-5 columns">
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<ul>
<li><strong>CATS Small RNA-seq Kit</strong> on 1 ng exosomal RNA (Exosome sample 1, 2)</li>
<li><strong>CATS RNA-seq Kit</strong> on 1 ng total RNA from parent (HEK293T) cells (Cell sample 1, 2).</li>
</ul>
<p>Prior library preparation, exosomes were isolated with Diagenode exosome capture solutions <a href="../categories/exosomes">Exosomes</a></p>
</div>
</div>
<div>
<h3>CATS saves time</h3>
<img src="https://www.diagenode.com/img/categories/library-prep/cats-save-time.png" /></div>
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<h4><span>Discover our <strong>NEW<a href="https://www.diagenode.com/en/p/D-Plex-Small-RNA-seq-Library-Prep-x24"> D-Plex Small RNA-seq Kit&nbsp;for Illumina</a></strong>&nbsp;and <strong><a href="https://www.diagenode.com/en/p/d-plex-small-RNA-dnbseq-kit-x24">D-Plex Small DNBSEQ Kit for MGI</a></strong>.</span></h4>',
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<p></p>
<p></p>
<center><em><a class="chip diahome button" href="https://www.diagenode.com/files/products/kits/MA-D-Plex.pdf" target="_blank" title="D-Plex Small RNA library preparation user manual"><strong>Download the manual</strong></a></em></center>
<p>D-Plex Small RNA-seq Library Prep Kit is a tool designed for the study of the <strong>small non-coding transcriptome</strong>. The kit is using the<a href="https://www.diagenode.com/en/pages/dplex" target="_blank"> D-Plex technology</a> to generate&nbsp;small RNA libraries for Illumina sequencing directly from total RNAs or enriched small RNAs.</p>
<p>The D-Plex technology utilizes&nbsp;two innovative&nbsp;<strong>ligation-free mechanisms</strong> - <strong>poly(A) tailing</strong> and <strong>template switching</strong>&nbsp;- to produce sequencing libraries&nbsp;from ultra-low input amounts, down to 10 pg for small RNAs and 100 pg for total RNAs.&nbsp;Combined with <strong>unique molecular identifiers</strong> (UMI), this complete solution ensures a <strong>realistic</strong> and <strong>accurate representation of diverse small RNA species</strong> (such as microRNAs, piRNAs, tRNAs, and siRNAs) with minimized quantitative bias.</p>
<p>D-Plex Small RNA-seq Kit offers a time saving protocol that can be completed within <strong>5 hours</strong> and requires minimal hands-on time.&nbsp;<span>The library preparation takes place in a&nbsp;</span><strong>single tube</strong><span>, increasing the efficiency tremendously.&nbsp;</span></p>
<p>D-Plex Small RNA-seq Kit includes all buffers and enzymes necessary for the library preparation. Specific D-Plex Indexes were designed and validated to fit the D-Plex technology and are available separately:</p>
<p><strong>For D-Plex UDI library construction:</strong></p>
<ul style="list-style-type: disc;">
<li><a href="https://www.diagenode.com/en/p/D-Plex-24-Unique-Dual-Indexes-Set-A" title="D-Plex UDI Module - Set A" target="_blank"><span>C05030021</span>&nbsp;- D-Plex Unique Dual Indexes for Illumina - Set A</a></li>
<li><a href="https://www.diagenode.com/en/p/D-Plex-24-Unique-Dual-Indexes-Set-B" title="D-Plex UDI Module - Set B" target="_blank"><span>C05030022</span>&nbsp;- D-Plex Unique Dual Indexes for Illumina - Set B</a></li>
<li><a href="https://www.diagenode.com/en/p/D-Plex-24-Unique-Dual-Indexes-Set-C">C05030023 - D-Plex&nbsp;Unique Dual&nbsp;Indexes for Illumina - Set C</a></li>
<li><a href="https://www.diagenode.com/en/p/D-Plex-24-Unique-Dual-Indexes-Set-D">C05030024 - D-Plex&nbsp;Unique Dual&nbsp;Indexes for Illumina - Set D</a></li>
</ul>
<p><span>The use of UDI is highly recommended&nbsp;to mitigate errors introduced by read misassignment, including index&nbsp;hopping frequently observed with patterned flow cells such as Illumina&rsquo;s&nbsp;NovaSeq system.</span></p>
<p><strong>For D-Plex SI library construction:</strong></p>
<ul style="list-style-type: disc;">
<li><a href="https://www.diagenode.com/en/p/D-Plex-24-Single-Indexes-Set-A" title="D-Plex SI Module - Set A" target="_blank">C05030010 - D-Plex Single Indexes for Illumina - Set A</a></li>
<li><a href="https://www.diagenode.com/en/p/D-Plex-24-Single-Indexes-Set-B" title="D-Plex SI Module - Set B" target="_blank">C05030011 - D-Plex Single Indexes for Illumina - Set B</a></li>
</ul>
<p><strong>D-Plex is also available for MGI sequencing, check <a href="https://www.diagenode.com/en/p/d-plex-small-RNA-dnbseq-kit-x24" target="_blank">here</a>!</strong></p>
<p></p>
<p></p>
<p></p>
<center><strong>The D-Plex smRNA-seq is a versatile tool for a plethora of transciptomic analysis</strong></center>
<p></p>
<center><img src="https://www.diagenode.com/img/product/kits/dplex/versatile-circle.png" /></center>
<p></p>
<p>With low-input capability, accuracy and ability to incorporate different transcript classes independent of chemical moieties, the strong D-Plex library-preparation method can be included in various analysis workflows (i.e., ribosome profiling, genome-wide mapping of protein: RNA binding sites).</p>
<p></p>
<p></p>',
			'label1' => 'Characteristics and library prep. workflow ',
			'info1' => '<div class="row">
<div class="small-12 columns">
<p><strong>High library diversity for ultra-low inputs</strong></p>
<center><img src="https://www.diagenode.com/img/product/kits/dplex/dplex-diversity-fig1.png" /></center></div>
<div class="small-12 columns"><center><img src="https://www.diagenode.com/img/product/kits/dplex/dplex-fig2-captures.png" /></center></div>
</div>
<p></p>
<div class="row">
<div class="small-12 columns">
<p>D-Plex smRNA-seq captures the smRNA complexity of the sample in a sensitive manner. A large number of features is detected for each biotype at a CPM &ge;5, as shown above for different species.</p>
</div>
</div>
<p></p>
<p><strong>Accurate representation of the smRNA content of a sample</strong></p>
<div class="row">
<div class="small-6 columns"><center><img src="https://www.diagenode.com/img/product/kits/dplex/dplex-fig-ratplasma.png" /></center></div>
<div class="small-6 columns"><center><img src="https://www.diagenode.com/img/product/kits/dplex/dplex-fig-miRNAdistribution.png" /></center></div>
</div>
<div class="row">
<div class="small-6 columns">
<p><strong>Accurate identification of PCR duplicates in low-input samples using unique molecular identifiers (UMIs).</strong><br />The UMI read deduplication that is embedded in the D-Plex construct is used to avoid over-estimation of transcripts by identifying clones generated during the PCR amplification of the library. Despite limiting starting RNA input, the UMI correction removed technical copies of transcripts, maintaining the initial sample abundance.</p>
</div>
<div class="small-6 columns">
<p>D-Plex (template switching) technology enables recovery of the initial miRNA distribution of the miRXplore Universal Reference (Miltenyi Biotech Inc., Cat. No. 130-093-521). In contrast, ligation-based kits display a strong distortion of the miRNA equimolar distribution initially present in the pool, indicating sample incorporation bias.</p>
</div>
</div>
<p></p>
<p></p>
<div class="row">
<div class="small-6 columns"><center><img src="https://www.diagenode.com/img/product/kits/dplex/dplex-fig-foldchange.jpg" /></center></div>
<div class="small-6 columns"><strong>D-Plex smRNA-seq in association with the MGcount analysis correlates strongly (R&sup2; &gt; 0.8) with the RT-qPCR analysis, which is considered the gold-standard for accuracy. </strong><br />The figures shows a fold-change accuracy of a panel of 20 different small-RNA (figure taken from MGcount publication - Hita et al., BMC bioinformatics, 23-39(2022).</div>
</div>
<p></p>
<p></p>
<p><strong>Maximize information from the regulatory transcriptome using D-Plex small RNA-seq kit and MGcount*</strong></p>
<div class="row">
<div class="small-6 columns"><center><img src="https://www.diagenode.com/img/product/kits/dplex/dplex-fig-multialignments.png" /></center></div>
<div class="small-6 columns">By analyzing D-Plex dataset with MGcount, more reads are kept during the analysis, which ultimately preserves biological complexity linked to ncRNA expression without decreasing the accuracy of detection. <br /><span style="line-height: 1em;"><small>*Hita, A., Brocart, G., Fernandez, A. et al. MGcount: a total RNA-seq quantification tool to address multi-mapping and multi-overlapping alignments ambiguity in non-coding transcripts. BMC Bioinformatics 23, 39 (2022). <a href="https://doi.org/10.1186/s12859-021-04544-3">https://doi.org/10.1186/s12859-021-04544-3</a></small></span></div>
</div>
<p></p>
<p></p>
<div class="row">
<div class="small-12 columns">
<p>The D-Plex technology uses two innovative ligation-free mechanisms, <strong>poly(A) tailing and template switching</strong>, to produce sequencing libraries from ultra-low input amounts.</p>
</div>
</div>
<div class="row" style="background-color: #f5f5f5;">
<div class="small-12 columns"><br />
<p><strong>WORKFLOW</strong></p>
<center><img src="https://www.diagenode.com/img/product/kits/dplex/FL-Image-Workflow.jpg" width="50%" /></center></div>
<div class="small-12 columns">
<p style="text-align: justify; padding: 15px;"><br />RNA molecules are polyadenylated at the 3&rsquo;-end and primed with an oligo(dT) primer containing part of the ILMN 3&rsquo;-adapter sequence. The addition of a template-switching oligonucleotide during cDNA synthesis enables fusion of part of the ILMN 5&rsquo;-adapter during reverse transcription. After PCR, the library comprises double stranded DNA constructs that are ready for sequencing.</p>
</div>
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<p><br /><br /></p>
<p></p>
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			'label2' => 'Data analysis',
			'info2' => '<p>A specific bioinformatics pipeline has been developed to process the special sequences present in the D-Plex construct, namely the UMI, the A-tail, and the template switch motif. All guidelines and free softwares are shared in the user manual. Subject to the compatibility of D-Plex constructs, other specific pipelines can be used.</p>
<p><img src="https://www.diagenode.com/img/product/kits/dplex/bioinfoPipe.png" alt="small RNA sequencing bioinformatics pipeline" caption="false" width="925" height="196" /></p>
<p>Need help for your bioinformatics analysis of miRNA?</p>
<p></p>
<div class="small-12 medium-3 large-3 columns"><center><a href="https://ccb-compute.cs.uni-saarland.de/mirmaster" target="_blank"><img src="https://www.diagenode.com/img/product/kits/dplex/miRMaster_logo.png" /></a></center>
<p>&nbsp;</p>
<p>&nbsp;</p>
</div>
<div class="small-12 medium-9 large-9 columns">
<p>Diagenode has collaborated with <strong>Andreas Keller</strong> and <strong>Tobias Fehlmann</strong> to develop a new bioinformatics pipeline for&nbsp;<span>the <strong>prediction of novel miRNAs</strong>.</span><br /><a href="https://ccb-compute.cs.uni-saarland.de/mirmaster" target="_blank"></a></p>
<ul>
<li style="text-align: justify;"><a href="https://ccb-compute.cs.uni-saarland.de/mirmaster2">miRMaster 2</a></li>
<li style="text-align: justify;"><a href="https://ccb-compute.cs.uni-saarland.de/mirmaster" target="_blank">miRMaster</a></li>
</ul>
</div>
<p>&nbsp;</p>
<p>&nbsp;</p>',
			'label3' => 'Data analysis - Counting using MGcount',
			'info3' => '<p>The counting or expression level calculation is the last step of the processing to generate an expression level matrix. We recommend using MGcount*, a counting tool developed at Diagenode with a suitable annotations file that include the small RNA transcripts that are object of study. MGcount, built on top of featureCounts, employs a flexible quantification approach to deal with datasets containing multiple RNA biotypes such as D-plex libraries. Non-coding RNAs varying in length, biogenesis, and function, may overlap in a genomic region, and are sometimes present in the genome with a high copy number. Consequently, reads may align equally well to more than one position in the reference genome or/and align to a position where more than one annotated transcript is located. MGcount employs two strategies to quantify these reads. Firstly, it assigns reads in rounds prioritizing small-RNAs over long-RNAs ensuring the unbiased read attribution to intergenic and intragenic small RNAs while preventing host-genes transcription over-estimation. Secondly, MGcount collapses loci where reads consistently multi-map into communities of loci with a graph-based approach. The resultant communities are groups of biologically related loci with nearly identical sequence. Subsequently, quantification of reads is performed at the loci-community level, reducing multi-alignments ambiguity at individual locus. Ultimately, this strategy maximizes the transcriptome information analysed and improves the interrogation of non-coding RNAs. MGcount software repository provides annotation files for A. thaliana, H. sapiens, M. musculus and C. elegans. The required input files for MGcount are a .txt file listing the paths to the alignment input files (.bam format) and the annotations file (.gtf format). The output directory path has to be provided as an input as well.</p>
<p><strong>Example command:</strong></p>
<p style="background-color: #f0f0f0;">MGcount -T 2 --gtf Homo_sapiens.GRCh38.gtf --outdir outputs --bam_infiles input_bamfilenames.txt</p>
<p>MGcount provides the choice to enable/disable the quantification of all RNA biotypes included in the annotation file in the form of "communities" as optional parameters for small-RNA (--ml_flag_small) and long-RNA (--ml_flag_long). Both are enabled by default. The main output of MGcount is the count_matrix.csv file containing an expression matrix that can be imported to R or any other software for downstream analyses.<br />A full user guide for MGCount is available here: <a href="https://filedn.com/lTnUWxFTA93JTyX3Hvbdn2h/mgcount/UserGuide.html">https://filedn.com/lTnUWxFTA93JTyX3Hvbdn2h/mgcount/UserGuide.html</a>.</p>
<p>Other standard counting tools such as featureCounts or HTSeq-counts can also be used alternatively. Given the high complexity of D-Plex libraries, we recommend having a clear understanding of the scientific question and the goal of the project before proceeding to the choice of the counting method as this will strongly impact downstream analyses. Diagenode provides bioinformatics support as a service (please, contact us if you need help with data analysis).</p>
<p>Notice that D-Plex produces forward-stranded data. Stranded libraries have the benefit that reads map to the genome strand where they were originated from. Therefore, when estimating transcript expression, reads aligned to the forward strand should be assigned only to transcript features in the forward strand whereas reads aligned to the reverse strand should be assigned only to transcript features in the reverse strand. For this, make sure you select &ldquo;stranded mode&rdquo; in any tool of choice. Stranded mode is selected by default in MGcount.</p>
<p><em><small>*Hita, A., Brocart, G., Fernandez, A. et al. MGcount: a total RNA-seq quantification tool to address multi-mapping and multi-overlapping alignments ambiguity in non-coding transcripts. BMC Bioinformatics 23, 39 (2022). <a href="https://doi.org/10.1186/s12859-021-04544-3">https://doi.org/10.1186/s12859-021-04544-3</a></small></em></p>',
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			'price_USD' => '1475',
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			'price_JPY' => '231060',
			'price_CNY' => '10195',
			'price_AUD' => '3688',
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			'slug' => 'D-Plex-Small-RNA-seq-Library-Prep-x24',
			'meta_title' => 'D-Plex Small RNA-seq Library Prep Kit | Diagenode ',
			'meta_keywords' => 'RNA kit, RNA-seq kit, small RNA kit, small RNA-seq kit, low input RNA-seq, UMI RNA-seq, RNA-seq library preparation, D-Plex, higher RNA diversity',
			'meta_description' => 'Small RNA-seq library preparation for Illumina sequencing - Unique D-Plex technology - Optimized for ultra-low input (100 pg total RNA) - UMI reduce PCR biases - UDI detect index hopping - Compatibility with plasma samples - User-friendly and fast protocol',
			'modified' => '2024-04-12 11:41:21',
			'created' => '2019-09-04 12:04:31',
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			'id' => '3170',
			'antibody_id' => null,
			'name' => 'D-Plex Small RNA DNBSEQ™ Kit for MGI Sequencing',
			'description' => '<center><img src="https://www.diagenode.com/img/banners/banner-dplex-mgi.png" width="550" /></center>
<p></p>
<center><a class="chip diahome button" href="https://www.diagenode.com/files/products/kits/D-Plex-Small-RNA-DNBSEQ.pdf" target="_blank" title="D-Plex Small RNA DNBSEQ user manual"><strong>Download the manual</strong></a></center>
<p></p>
<p>D-Plex Small RNA DNBSEQ&trade; Kit is a tool designed for the study of the small non-coding transcriptome. The kit is using the <a href="https://www.diagenode.com/en/pages/dplex" target="_blank">D-Plex technology</a> to generate double-stranded DNA libraries ready to be used for the DNA single-strand circularization step required for DNBSEQ sequencing on MGI sequencers.</p>
<p>The D-Plex technology&nbsp;utilizes the innovative capture and amplification by&nbsp;tailing and switching, a&nbsp;ligation-free&nbsp;method for RNA library preparation from ultra-low input amounts, down to 10 pg for small RNAs and 100 pg for total RNAs.&nbsp;This innovative solution enables diverse and novel transcripts detection, even from challenging clinical samples such as liquid biopsies.</p>
<p><span>D-Plex Small&nbsp;RNA&nbsp;<span>DNBSEQ&trade;</span> Kit offers a time saving protocol that can be completed within 5 hours and requires minimal hands-on time.&nbsp;</span><span>The library preparation takes place in a&nbsp;</span><span>single tube</span><span>, increasing the efficiency tremendously.&nbsp;This ensures high technical&nbsp;reliability and reproducibility<span>.</span></span></p>
<p>D-Plex Small RNA DNBSEQ&trade; Kit includes all buffers and enzymes necessary for the library preparation. Specific D-Plex DNBSEQ Barcodes were designed and validated to fit the D-Plex technology and are available separately:</p>
<ul>
<li><a href="https://www.diagenode.com/en/p/d-plex-24-dnbseq-barcodes-set-a">C05030060 - D-Plex DNBSEQ Barcodes for MGI - Set A</a></li>
<li><a href="https://www.diagenode.com/en/p/d-plex-24-dnbseq-barcodes-set-b">C05030061 - D-Plex DNBSEQ Barcodes for MGI - Set B</a></li>
</ul>
<p><b><strong>D-Plex is also available for Illumina sequencing, check<span>&nbsp;</span><a href="https://www.diagenode.com/en/p/D-Plex-Small-RNA-seq-Library-Prep-x24" target="_blank">here</a>!</strong></b></p>
<div class="row">
<div class="carrousel" style="background-position: center;">
<div class="container">
<div class="row" style="background: rgba(255,255,255,0.1);">
<div class="large-12 columns slick">
<div>
<h3>Diverse and novel transcript detection</h3>
<div class="large-10 small-12 medium-10 large-centered medium-centered small-centered columns"><img style="height: 400px; display: block; margin-left: auto; margin-right: auto;" src="https://www.diagenode.com/img/product/kits/dplex/dplex-transcript.png" alt="small RNA library preparation for Illumina" /></div>
<div class="large-8 small-12 medium-6 large-centered medium-centered small-centered columns"><center>
<p style="text-align: justify;">The D-Plex Small RNA DNBSEQ protocol generates complex RNA libraries deciphering the wide diversity of small non-coding RNA spectrum (including miRNAs, snoRNAs, snRNAs)&nbsp; in human plasma samples.</p>
</center></div>
</div>
<div>
<h3>Ultra-low input performance</h3>
<div class="large-10 small-12 medium-10 large-centered medium-centered small-centered columns"><img style="height: 400px; display: block; margin-left: auto; margin-right: auto;" src="https://www.diagenode.com/img/product/kits/dplex/dplex-ultralow-input.png" alt="Ultra-low input performance" /></div>
<div class="large-8 small-12 medium-6 large-centered medium-centered small-centered columns"><center>
<p style="text-align: justify;">Sequencing data from circulating RNA samples of two input amounts (25 pg and 2.5 ng) were highly correlated (<i>R = 0.99</i>) when compared using Pearson correlation coefficient.</p>
</center></div>
</div>
<div>
<h3>High mapping efficiency</h3>
<div class="large-10 small-12 medium-10 large-centered medium-centered small-centered columns"><img style="height: 400px; display: block; margin-left: auto; margin-right: auto;" src="https://www.diagenode.com/img/product/kits/dplex/dplex-mapping.png" alt="High mapping efficiency" /></div>
<div class="large-8 small-12 medium-6 large-centered medium-centered small-centered columns"><center>
<p style="text-align: justify;"><b></b>The D-Plex Small RNA DNBSEQ kit is compatible with clinical-relevant samples, such as human plasma, and ultra low range of circulating RNA input (down to 10 pg) and exhibits good read mapping of sequencing reads (up to 70% mapping rate).</p>
</center></div>
</div>
<div>
<h3>High quality DNBSEQ sequencing solution</h3>
<div class="large-10 small-12 medium-10 large-centered medium-centered small-centered columns"><img style="height: 400px;" src="https://www.diagenode.com/img/product/kits/dplex/dplex-dnbseq.png" alt="High quality DNBSEQ sequencing solution" /></div>
<div class="large-8 small-12 medium-6 large-centered medium-centered small-centered columns"><center>
<p><b></b>The D-Plex Small RNA DNBSEQ kit combines our best-in-class RNA library preparation &ndash; D-Plex technology &ndash; with MGI&rsquo;s high-quality, cost-effective, DNA nanoballs &ndash; DNBSEQ &ndash; sequencing solution, creating a unified platform to support high quality small RNA sequencing.</p>
</center></div>
</div>
</div>
</div>
</div>
</div>
</div>
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<li><strong>Latest innovation in RNA-seq</strong>:&nbsp;unique D-Plex technology&nbsp;offering ligation-free&nbsp;protocol for library preparation</li>
<li><strong>Ultra-low input capability</strong>: down to 10 pg for small RNAs and 100 pg for total RNAs</li>
<li><strong>High library complexity</strong>:<strong> </strong>obtain a complete view of&nbsp;your small RNA transcriptome</li>
<li><strong>Optimal performance on clinical samples</strong>: validated&nbsp;with circulating RNAs from liquid biopsies</li>
<li><strong>Easy to use with minimal hands-on time</strong>: one day, one tube protocol</li>
<li><strong>Highest sequencing quality</strong>: specifically formatted for MGI DNBSEQ&trade; sequencers</li>
</ul>
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			'label2' => 'DNBSEQ Barcodes',
			'info2' => '<p>D-Plex DNBSEQ Barcodes are not included in the kit. Two sets are available separately:</p>
<ul style="list-style-type: disc;">
<li><a href="https://www.diagenode.com/en/p/d-plex-24-dnbseq-barcodes-set-a">C05030060 - D-Plex 24 DNBSEQ Barcodes for MGI - Set A</a></li>
<li><a href="https://www.diagenode.com/en/p/d-plex-24-dnbseq-barcodes-set-b">C05030061 - D-Plex 24 DNBSEQ Barcodes for MGI - Set B</a></li>
</ul>
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			'price_JPY' => '231060',
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			'slug' => 'd-plex-small-RNA-dnbseq-kit-x24',
			'meta_title' => 'D-Plex Small RNA-seq Library Prep Kit for MGI Sequencing | Diagenode	',
			'meta_keywords' => 'Small RNA-seq Library Prep Kit for MGI Sequencing',
			'meta_description' => 'Small RNA-seq library preparation with D-Plex technology - Suitable for MGI sequencing platforms - Optimized for ultra-low input (100 pg total RNA) - Compatibility with plasma samples - User-friendly and fast protocol',
			'modified' => '2021-05-26 11:03:01',
			'created' => '2020-12-18 14:25:42',
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<p><span style="font-weight: 400;">Most of the major next-generation sequencing platforms require ligation of specific adaptor oligos to </span><a href="../applications/dna-rna-shearing"><span style="font-weight: 400;">fragmented DNA or RNA</span></a><span style="font-weight: 400;"> prior to sequencing</span></p>
<p><span style="font-weight: 400;">After input DNA has been fragmented, it is end-repaired and blunt-ended</span><span style="font-weight: 400;">. The next step is a A-tailing in which dAMP is added to the 3&acute; end of the blunt phosphorylated DNA fragments to prevent concatemerization and to allow the ligation of adaptors with complementary dT overhangs. In addition, barcoded adapters can be incorporated to facilitate multiplexing prior to or during amplification.</span></p>
<center><img src="https://www.diagenode.com/img/categories/library-prep/flux.png" /></center>
<p><span style="font-weight: 400;">Diagenode offers a comprehensive product portfolio for library preparation:<br /></span></p>
<strong><a href="https://www.diagenode.com/en/categories/Library-preparation-for-RNA-seq">D-Plex&nbsp;RNA-seq Library Preparation Kits</a></strong><br />
<p><span style="font-weight: 400;">Diagenode&rsquo;s new RNA-sequencing solutions utilize the innovative c</span><span style="font-weight: 400;">apture and a</span><span style="font-weight: 400;">mplification by t</span><span style="font-weight: 400;">ailing and s</span><span style="font-weight: 400;">witching&rdquo;</span><span style="font-weight: 400;">, a ligation-free method to produce DNA libraries for next generation sequencing from low input amounts of RNA. </span><span style="font-weight: 400;"></span><a href="../categories/Library-preparation-for-RNA-seq">Learn more</a></p>
<strong><a href="../categories/library-preparation-for-ChIP-seq">ChIP-seq and DNA sequencing library preparation solutions</a></strong><br />
<p><span style="font-weight: 400;">Our kits have been optimized for DNA library preparation used for next generation sequencing for a wide range of inputs. Using a simple three-step protocols, our</span><a href="http://www.diagenode.com/p/microplex-library-preparation-kit-v2-x12-12-indices-12-rxns"><span style="font-weight: 400;"> </span></a><span style="font-weight: 400;">kits are an optimal choice for library preparation from DNA inputs down to 50 pg.&nbsp;</span><a href="../categories/library-preparation-for-ChIP-seq">Learn more</a></p>
<a href="../p/bioruptor-pico-sonication-device"><span style="font-weight: 400;"></span><strong>Bioruptor Pico - short fragments</strong></a><a href="../categories/library-preparation-for-ChIP-seq-and-DNA-sequencing"><span style="font-weight: 400;"></span></a><br />
<p><span style="font-weight: 400;"></span><span style="font-weight: 400;">Our well-cited Bioruptor Pico is the shearing device of choice for chromatin and DNA fragmentation. Obtain uniform and tight fragment distributions &nbsp;between 150bp -2kb. </span><a href="../p/bioruptor-pico-sonication-device">Learn more</a></p>
<strong><a href="../p/megaruptor2-1-unit"><span href="../p/bioruptor-pico-sonication-device">Megaruptor</span>&reg; - long fragments</a></strong><a href="../p/bioruptor-pico-sonication-device"><span style="font-weight: 400;"></span></a><a href="../categories/library-preparation-for-ChIP-seq-and-DNA-sequencing"><span style="font-weight: 400;"></span></a><br />
<p><span style="font-weight: 400;"></span><span style="font-weight: 400;">The Megaruptor is designed to shear DNA from 3kb-75kb for long-read sequencing.&nbsp; <a href="../p/megaruptor2-1-unit">Learn more</a></span></p>
<span href="../p/bioruptor-pico-sonication-device"></span><span style="font-weight: 400;"></span></div>
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			'name' => 'Functional microRNA targetome undergoes degeneration-induced shift in the retina',
			'authors' => 'Chu-Tan JA et al.',
			'description' => '<div class="abstract-content selected" id="enc-abstract">
<p><strong class="sub-title">Background:<span>&nbsp;</span></strong>MicroRNA (miRNA) play a significant role in the pathogenesis of complex neurodegenerative diseases including age-related macular degeneration (AMD), acting as post-transcriptional gene suppressors through their association with argonaute 2 (AGO2) - a key member of the RNA Induced Silencing Complex (RISC). Identifying the retinal miRNA/mRNA interactions in health and disease will provide important insight into the key pathways miRNA regulate in disease pathogenesis and may lead to potential therapeutic targets to mediate retinal degeneration.</p>
<p><strong class="sub-title">Methods:<span>&nbsp;</span></strong>To identify the active miRnome targetome interactions in the healthy and degenerating retina, AGO2 HITS-CLIP was performed using a rodent model of photoreceptor degeneration. Analysis of publicly available single-cell RNA sequencing (scRNAseq) data was performed to identify the cellular location of AGO2 and key members of the microRNA targetome in the retina. AGO2 findings were verified by in situ hybridization (RNA) and immunohistochemistry (protein).</p>
<p><strong class="sub-title">Results:<span>&nbsp;</span></strong>Analysis revealed a similar miRnome between healthy and damaged retinas, however, a shift in the active targetome was observed with an enrichment of miRNA involvement in inflammatory pathways. This shift was further demonstrated by a change in the seed binding regions of miR-124-3p, the most abundant retinal AGO2-bound miRNA, and has known roles in regulating retinal inflammation. Additionally, photoreceptor cluster miR-183/96/182 were all among the most highly abundant miRNA bound to AGO2. Following damage, AGO2 expression was localized to the inner retinal layers and more in the OLM than in healthy retinas, indicating a locational miRNA response to retinal damage.</p>
<p><strong class="sub-title">Conclusions:<span>&nbsp;</span></strong>This study provides important insight into the alteration of miRNA regulatory activity that occurs as a response to retinal degeneration and explores the miRNA-mRNA targetome as a consequence of retinal degenerations. Further characterisation of these miRNA/mRNA interactions in the context of the degenerating retina may provide an important insight into the active role these miRNA may play in diseases such as AMD.</p>
</div>
<p><strong class="sub-title">Keywords:<span>&nbsp;</span></strong>Argonaute; HITS-CLIP; Inflammation; Retina; Retinal degeneration; Transcriptome; mRNA; microRNA.</p>',
			'date' => '2021-08-31',
			'pmid' => 'https://pubmed.ncbi.nlm.nih.gov/34465369/',
			'doi' => '10.1186/s13024-021-00478-9',
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			'authors' => 'Gylling HM, Gonzalez-Aguilera C, Smith MA, Kaczorowski DC, Groth A, Lund AH',
			'description' => '<p>Non-coding RNA has a proven ability to direct and regulate chromatin modifications by acting as scaffolds between DNA and histone-modifying complexes. However, it is unknown if ncRNA plays any role in DNA replication and epigenome maintenance, including histone eviction and re-instalment of histone-modifications after genome duplication. Isolation of nascent chromatin has identified a large number of RNA-binding proteins in addition to unknown components of the replication and epigenetic maintenance machinery. Here, we isolated and characterized long and short RNAs associated with nascent chromatin at active replication forks and track RNA composition during chromatin maturation across the cell cycle. Shortly after fork passage, GA-rich-, Alpha- and TElomeric Repeat-containing RNAs (TERRA) are associated with replicated DNA. These repeat containing RNAs arise from loci undergoing replication, suggesting an interaction in cis. Post-replication during chromatin maturation, and even after mitosis in G1, the repeats remain enriched on DNA. This suggests that specific types of repeat RNAs are transcribed shortly after DNA replication and stably associate with their loci of origin throughout cell cycle. The presented method and data enables studies of RNA interactions with replication forks and post-replicative chromatin and provides insights into how repeat RNAs and their engagement with chromatin are regulated with respect to DNA replication and across the cell cycle.</p>',
			'date' => '2020-05-11',
			'pmid' => 'http://www.pubmed.gov/32393525',
			'doi' => '10.1261/rna.074757.120',
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			'description' => '<p>Small RNAs (smRNAs) are important regulators of many biologic processes and are now most frequently characterized using Illumina sequencing. However, although standard RNA sequencing library preparation has become routine in most sequencing facilities, smRNA sequencing library preparation has historically been challenging because of high input requirements, laborious protocols involving gel purifications, inability to automate, and a lack of benchmarking standards. Additionally, studies have suggested that many of these methods are nonlinear and do not accurately reflect the amounts of smRNAs . Recently, a number of new kits have become available that permit lower input amounts and less laborious, gel-free protocol options. Several of these new kits claim to reduce RNA ligase-dependent sequence bias through novel adapter modifications and to lessen adapter-dimer contamination in the resulting libraries. With the increasing number of smRNA kits available, understanding the relative strengths of each method is crucial for appropriate experimental design. In this study, we systematically compared 9 commercially available smRNA library preparation kits as well as NanoString probe hybridization across multiple study sites. Although several of the new methodologies do reduce the amount of artificially over- and underrepresented microRNAs (miRNAs), we observed that none of the methods was able to remove all of the bias in the library preparation. Identical samples prepared with different methods show highly varied levels of different miRNAs. Even so, many methods excelled in ease of use, lower input requirement, fraction of usable reads, and reproducibility across sites. These differences may help users select the most appropriate methods for their specific question of interest.</p>',
			'date' => '2020-01-10',
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			'doi' => '10.7171/jbt.20-3102-001',
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			'description' => '<p>Successful treatment of cancer depends on early diagnosis and effective monitoring of patients' response to therapy. Traditional tools based on tumor biopsies lack the sensitivity and specificity to capture cancer development in its early phases and are not applicable for continuous monitoring. To overcome these barriers, liquid biopsies have been introduced as a minimally invasive and cost-efficient means of diagnosis with high level of specificity and sensitivity. Traditionally, liquid biopsy markers include circulating tumor cells and circulating tumor DNA. During the last decade, a new promising group of biomarkers has appeared and its utilization for cancer diagnosis and monitoring is intensively studied - the microRNAs (miRNAs). In this review, we provide a comprehensive overview of circulating miRNA analysis. We highlight the importance of sampling and quality control, discuss the technical aspects of miRNA extraction and quantification, summarize recommendations for downstream analysis and conclude with future perspectives. Taken together, we present the current state of knowledge in the field of miRNA analysis in liquid biopsies and the expected development and standardization.</p>',
			'date' => '2019-10-18',
			'pmid' => 'http://www.pubmed.gov/31635843',
			'doi' => '10.1016/j.mam.2019.10.002',
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			'authors' => 'Fehlmann T, Backes C, Pirritano M, Laufer T, Galata V, Kern F, Kahraman M, Gasparoni G, Ludwig N, Lenhof HP, Gregersen HA, Francke R, Meese E, Simon M, Keller A',
			'description' => '<p>The repertoire of small noncoding RNAs (sncRNAs), particularly miRNAs, in animals is considered to be evolutionarily conserved. Studies on sncRNAs are often largely based on homology-based information, relying on genomic sequence similarity and excluding actual expression data. To obtain information on sncRNA expression (including miRNAs, snoRNAs, YRNAs and tRNAs), we performed low-input-volume next-generation sequencing of 500&nbsp;pg of RNA from 21 animals at two German zoological gardens. Notably, none of the species under investigation were previously annotated in any miRNA reference database. Sequencing was performed on blood cells as they are amongst the most accessible, stable and abundant sources of the different sncRNA classes. We evaluated and compared the composition and nature of sncRNAs across the different species by computational approaches. While the distribution of sncRNAs in the different RNA classes varied significantly, general evolutionary patterns were maintained. In particular, miRNA sequences and expression were found to be even more conserved than previously assumed. To make the results available for other researchers, all data, including expression profiles at the species and family levels, and different tools for viewing, filtering and searching the data are freely available in the online resource ASRA (Animal sncRNA Atlas) at https://www.ccb.uni-saarland.de/asra/.</p>',
			'date' => '2019-05-21',
			'pmid' => 'http://www.pubmed.gov/30937442',
			'doi' => '10.1093/nar/gkz227',
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			'description' => '<p>miRNAs, &sim;20 to 22 nucleotide single-stranded RNA species that play a pivotal role in the regulation of protein-coding genes, are emerging as robust biomarkers for assessing allograft status. Herein, the authors briefly review the biogenesis and function of the miRNAs and provide an overview of the tools to quantify miRNAs in tissues and body fluids. They then review their studies of discovery and validation of alterations in miRNA expression within kidney allografts with or without acute rejection, as well as with or without fibrosis, and summarize published data on miRNA expression patterns in kidney transplant recipients.</p>',
			'date' => '2019-03-01',
			'pmid' => 'http://www.pubmed.gov/30709501',
			'doi' => '10.1016/j.cll.2018.10.003',
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			'authors' => 'Marcello Pirritano, Tobias Fehlmann, Thomas Laufer, Nicole Ludwig, Gilles Gasparoni, Yongping Li, Eckart Meese, Andreas Keller, and Martin Simon',
			'description' => '<p><span>Circulating miRNAs are favored for biomarker candidates as they can reflect tissue specific miRNA dysregulation in disease contexts. Moreover, they have additional advantages that they can be monitored in a minimal invasive manner. Blood-borne miRNAs are therefore currently characterized to identify, describe and validate their potential suitability for a biomarker, however, sampling and as well miRNA detection methods limit these studies in terms of sensitivity but also practicability in clinical, at-home or low-resource sampling of high quality circulating RNA samples. We describe here a novel and innovative method of circulating RNA microsampling from minimal volume dried blood spots with direct enrichment for small RNA fractions in combination with ligation free library preparation. We evaluated crucial parameters for efficient library preparation from low RNA inputs of 50pg for efficient dissection not only of miRNAs but also isomiRs, piRNAs, and lincRNAs. We compared these data to classical microarrays and characterize the technical reproducibility and its sensitivity. We demonstrate and evaluate a method for easy low resource sampling and NGS analysis of circulating RNAs providing a powerful tool for massive cohort and remote patient monitoring.</span></p>',
			'date' => '2018-09-10',
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<p><span>Discover our<strong><a href="https://www.diagenode.com/en/p/D-Plex-Small-RNA-seq-Library-Prep-x24"><span>&nbsp;</span>D-Plex Small RNA-seq kit&nbsp;for Illumina</a></strong>&nbsp;and<span>&nbsp;</span><strong><a href="https://www.diagenode.com/en/p/d-plex-small-RNA-dnbseq-kit-x24">D-Plex Small DNBSEQ kit for MGI</a></strong><span>&nbsp;</span>sequencing.</span></p>',
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        <p><strong><input name="data[Cart][quantity]" placeholder="1" value="1" min="1" style="width:60px;display:inline" type="number" id="CartQuantity" required="required"/></strong>D-Plex Small RNA DNBSEQ™ Kit for MGI Sequencing個カートに追加。</p>

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            <h6 style="height:60px">D-Plex Small RNA DNBSEQ™ Kit </h6>
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<p></p>
<center><a class="chip diahome button" href="https://www.diagenode.com/files/products/kits/D-Plex-Small-RNA-DNBSEQ.pdf" target="_blank" title="D-Plex Small RNA DNBSEQ user manual"><strong>Download the manual</strong></a></center>
<p></p>
<p>D-Plex Small RNA DNBSEQ&trade; Kit is a tool designed for the study of the small non-coding transcriptome. The kit is using the <a href="https://www.diagenode.com/en/pages/dplex" target="_blank">D-Plex technology</a> to generate double-stranded DNA libraries ready to be used for the DNA single-strand circularization step required for DNBSEQ sequencing on MGI sequencers.</p>
<p>The D-Plex technology&nbsp;utilizes the innovative capture and amplification by&nbsp;tailing and switching, a&nbsp;ligation-free&nbsp;method for RNA library preparation from ultra-low input amounts, down to 10 pg for small RNAs and 100 pg for total RNAs.&nbsp;This innovative solution enables diverse and novel transcripts detection, even from challenging clinical samples such as liquid biopsies.</p>
<p><span>D-Plex Small&nbsp;RNA&nbsp;<span>DNBSEQ&trade;</span> Kit offers a time saving protocol that can be completed within 5 hours and requires minimal hands-on time.&nbsp;</span><span>The library preparation takes place in a&nbsp;</span><span>single tube</span><span>, increasing the efficiency tremendously.&nbsp;This ensures high technical&nbsp;reliability and reproducibility<span>.</span></span></p>
<p>D-Plex Small RNA DNBSEQ&trade; Kit includes all buffers and enzymes necessary for the library preparation. Specific D-Plex DNBSEQ Barcodes were designed and validated to fit the D-Plex technology and are available separately:</p>
<ul>
<li><a href="https://www.diagenode.com/en/p/d-plex-24-dnbseq-barcodes-set-a">C05030060 - D-Plex DNBSEQ Barcodes for MGI - Set A</a></li>
<li><a href="https://www.diagenode.com/en/p/d-plex-24-dnbseq-barcodes-set-b">C05030061 - D-Plex DNBSEQ Barcodes for MGI - Set B</a></li>
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<p><b><strong>D-Plex is also available for Illumina sequencing, check<span>&nbsp;</span><a href="https://www.diagenode.com/en/p/D-Plex-Small-RNA-seq-Library-Prep-x24" target="_blank">here</a>!</strong></b></p>
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<h3>Diverse and novel transcript detection</h3>
<div class="large-10 small-12 medium-10 large-centered medium-centered small-centered columns"><img style="height: 400px; display: block; margin-left: auto; margin-right: auto;" src="https://www.diagenode.com/img/product/kits/dplex/dplex-transcript.png" alt="small RNA library preparation for Illumina" /></div>
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<p style="text-align: justify;">The D-Plex Small RNA DNBSEQ protocol generates complex RNA libraries deciphering the wide diversity of small non-coding RNA spectrum (including miRNAs, snoRNAs, snRNAs)&nbsp; in human plasma samples.</p>
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<h3>Ultra-low input performance</h3>
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<div class="large-8 small-12 medium-6 large-centered medium-centered small-centered columns"><center>
<p style="text-align: justify;">Sequencing data from circulating RNA samples of two input amounts (25 pg and 2.5 ng) were highly correlated (<i>R = 0.99</i>) when compared using Pearson correlation coefficient.</p>
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<div>
<h3>High mapping efficiency</h3>
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<div class="large-8 small-12 medium-6 large-centered medium-centered small-centered columns"><center>
<p style="text-align: justify;"><b></b>The D-Plex Small RNA DNBSEQ kit is compatible with clinical-relevant samples, such as human plasma, and ultra low range of circulating RNA input (down to 10 pg) and exhibits good read mapping of sequencing reads (up to 70% mapping rate).</p>
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<div>
<h3>High quality DNBSEQ sequencing solution</h3>
<div class="large-10 small-12 medium-10 large-centered medium-centered small-centered columns"><img style="height: 400px;" src="https://www.diagenode.com/img/product/kits/dplex/dplex-dnbseq.png" alt="High quality DNBSEQ sequencing solution" /></div>
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<p><b></b>The D-Plex Small RNA DNBSEQ kit combines our best-in-class RNA library preparation &ndash; D-Plex technology &ndash; with MGI&rsquo;s high-quality, cost-effective, DNA nanoballs &ndash; DNBSEQ &ndash; sequencing solution, creating a unified platform to support high quality small RNA sequencing.</p>
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<li><strong>Ultra-low input capability</strong>: down to 10 pg for small RNAs and 100 pg for total RNAs</li>
<li><strong>High library complexity</strong>:<strong> </strong>obtain a complete view of&nbsp;your small RNA transcriptome</li>
<li><strong>Optimal performance on clinical samples</strong>: validated&nbsp;with circulating RNAs from liquid biopsies</li>
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	'description' => '<p><span>Circulating miRNAs are favored for biomarker candidates as they can reflect tissue specific miRNA dysregulation in disease contexts. Moreover, they have additional advantages that they can be monitored in a minimal invasive manner. Blood-borne miRNAs are therefore currently characterized to identify, describe and validate their potential suitability for a biomarker, however, sampling and as well miRNA detection methods limit these studies in terms of sensitivity but also practicability in clinical, at-home or low-resource sampling of high quality circulating RNA samples. We describe here a novel and innovative method of circulating RNA microsampling from minimal volume dried blood spots with direct enrichment for small RNA fractions in combination with ligation free library preparation. We evaluated crucial parameters for efficient library preparation from low RNA inputs of 50pg for efficient dissection not only of miRNAs but also isomiRs, piRNAs, and lincRNAs. We compared these data to classical microarrays and characterize the technical reproducibility and its sensitivity. We demonstrate and evaluate a method for easy low resource sampling and NGS analysis of circulating RNAs providing a powerful tool for massive cohort and remote patient monitoring.</span></p>',
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	'meta_description' => 'Capture and Amplification by Tailing and Switching Small RNA-seq Kit is a ligation-free assay providng increased efficiency and minimum bias, with low inputs down to 100 picograms. User-friendly with reduced hands-on time and fewer steps',
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			'name' => 'CATS Small RNA-seq Kit x24',
			'description' => '<p style="text-align: justify;">Diagenodeの「CATS small RNA-seq Kit」は、革新的なCATS法（Capture and Amplification by Tailing and Switching）を採用することで、ライゲーションが不要でかつ低インプットRNA量から次世代シークエンシングのDNAライブラリーを作製することができるキットです。</p>
<ul>
<li>多様なスモールRNAを回収可能</li>
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<ul class="accordion" data-accordion="">
<li class="accordion-navigation"><a href="#more" style="color: #13b29c; background-color: transparent; display: inline; padding: 0;">続きを読む</a>
<div id="more" class="content">
<p style="text-align: justify;">CATSは、RNAの3&rsquo;末端をキャプチャーするためのポリヌクレオチドテーリングおよび、cDNA合成時に5&rsquo;末端をキャプチャーするためのMMLV-RTによるテンプレートスイッチ 能力を利用した技術です。この方法なら、10ピコグラムの低インプットRNA量からわずか数時間でIllumina用シークエンシングライブラリーを作製することができます。</p>
<p style="text-align: justify;">ライブラリーは、ストランド特異的な情報を保持しています。「CATS RNA-seq Kit」は、増幅を最小限に抑えることでより多くの有効な鋳型をキャプチャーし、また、バイアスを最小限に抑えることで高い複雑性を得ることができるので、他のライゲーションベースの手法と比べより高いライブラリー作製効率を示します。</p>
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<h3>Unique sncRNAs detected in circulating plasma RNA</h3>
<div class="large-7 small-12 medium-7 columns"><img src="https://www.diagenode.com/img/product/kits/cats/cats-908-competitor-3.png" /></div>
<div class="large-5 small-12 medium-5 columns">
<p>sncRNA transcripts detected using the <strong>CATS small RNA-seq Kit</strong> vs the Competitor&rsquo;s Kit. The input was <strong>1 ng circulating small RNA</strong> in plasma samples. In total, 908 transcripts were found in the CATS small RNA-seq libraries. TPM&ge;1</p>
<p><strong>PCR cycles: CATS 14x</strong> vs Competitor 21x. <strong>Final library yield: CATS 27 ng</strong> vs Competitor 1.2 ng.</p>
</div>
</div>
<div>
<h3>More miRNA transcripts detected from challenging samples</h3>
<div class="large-7 small-12 medium-7 columns"><img src="https://www.diagenode.com/img/product/kits/cats/cats-mirnas-present-in-1-copy-in-1ng-circulating-rna.png" /></div>
<div class="large-5 small-12 medium-5 columns">
<p>Transcripts detected in miRNA samples of <strong>CATS small RNA-seq Kit</strong> vs the Competitor&rsquo;s Kit.</p>
<p>Input: <strong>1 ng circulating small RNA</strong> in plasma samples. <strong>PCR cycles: CATS 14x</strong> vs Competitor 21x. <strong>Final library yield: CATS 27 ng</strong> vs Competitor 1.2 ng.</p>
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<div>
<h3>Ultra low inputs, excellent reproducibility</h3>
<div class="large-7 small-12 medium-7 columns"><img src="https://www.diagenode.com/img/product/kits/cats/CATS White Paper_CATS-fig3.png" /></div>
<div class="large-5 small-12 medium-5 columns">
<p>Correlation between 2 different operators using <strong>CATS small RNA-seq Kit</strong> on two different inputs (100 pg vs 1 ng) for ncRNA detected at TPM &ge;2. <br />R<sup>2</sup> = 0.86</p>
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<div>
<h3>Consistency across template switching techniques</h3>
<div class="large-7 small-12 medium-7 columns"><img src="https://www.diagenode.com/img/product/kits/cats/CATS-White-Paper_graph-fig12.png" /></div>
<div class="large-5 small-12 medium-5 columns">
<p>Comparison of the number of detected small non-coding RNAs <strong>CATS small RNA-seq Kit</strong> vs SMARTer <br />Input: <strong>100 pg isolated small RNA</strong>. TPM &ge;2. Transcripts taken into consideration: miRNA, piRNA, scRNA, scaRNA, snoRNA, snRNA and vaultRNA. 1,217 transcripts found in both libraries at this expression level.</p>
</div>
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<div>
<h3>High number of reads mapped</h3>
<div class="large-7 small-12 medium-7 columns"><img src="https://www.diagenode.com/img/product/kits/cats/CATS-White-Paper_graph-fig6.jpg" /></div>
<div class="large-5 small-12 medium-5 columns">
<p>Representation of detected transcripts different biotypes with <strong>CATS small RNA-seq Kit</strong>vs NEBNext UltraI kit. TPM&ge;2. <br /> <strong>100 ng total RNA, 1 ng small RNA</strong> used as input.</p>
</div>
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<div>
<h3>Excellent performance on challenging samples</h3>
<div class="large-7 small-12 medium-7 columns"><img src="https://www.diagenode.com/img/product/kits/cats/Exosomes-page_heatt-1.jpg" /></div>
<div class="large-5 small-12 medium-5 columns">
<p>Heatmap clustering of the top 50 differentially expressed miRNAs after library preparation:</p>
<ul>
<li><strong>CATS Small RNA-seq Kit</strong> on 1 ng exosomal RNA (Exosome sample 1, 2)</li>
<li><strong>CATS RNA-seq Kit</strong> on 1 ng total RNA from parent (HEK293T) cells (Cell sample 1, 2).</li>
</ul>
<p>Prior library preparation, exosomes were isolated with Diagenode exosome capture solutions <a href="../categories/exosomes">Exosomes</a></p>
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</div>
<div>
<h3>CATS saves time</h3>
<img src="https://www.diagenode.com/img/categories/library-prep/cats-save-time.png" /></div>
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$meta_title = 'CATS Small RNA-seq Kit x24 | Diagenode'
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		'description' => '<p style="text-align: justify;">Diagenodeの「CATS small RNA-seq Kit」は、革新的なCATS法（Capture and Amplification by Tailing and Switching）を採用することで、ライゲーションが不要でかつ低インプットRNA量から次世代シークエンシングのDNAライブラリーを作製することができるキットです。</p>
<ul>
<li>多様なスモールRNAを回収可能</li>
<li>10pgの超少量インプットRNAで優れた再現性</li>
<li>難しいサンプルでの優れたパフォーマンス</li>
</ul>
<ul class="accordion" data-accordion="">
<li class="accordion-navigation"><a href="#more" style="color: #13b29c; background-color: transparent; display: inline; padding: 0;">続きを読む</a>
<div id="more" class="content">
<p style="text-align: justify;">CATSは、RNAの3&rsquo;末端をキャプチャーするためのポリヌクレオチドテーリングおよび、cDNA合成時に5&rsquo;末端をキャプチャーするためのMMLV-RTによるテンプレートスイッチ 能力を利用した技術です。この方法なら、10ピコグラムの低インプットRNA量からわずか数時間でIllumina用シークエンシングライブラリーを作製することができます。</p>
<p style="text-align: justify;">ライブラリーは、ストランド特異的な情報を保持しています。「CATS RNA-seq Kit」は、増幅を最小限に抑えることでより多くの有効な鋳型をキャプチャーし、また、バイアスを最小限に抑えることで高い複雑性を得ることができるので、他のライゲーションベースの手法と比べより高いライブラリー作製効率を示します。</p>
</div>
</li>
</ul>
<div class="carrousel" style="background-position: center;">
<div class="container">
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<div>
<h3>Unique sncRNAs detected in circulating plasma RNA</h3>
<div class="large-7 small-12 medium-7 columns"><img src="https://www.diagenode.com/img/product/kits/cats/cats-908-competitor-3.png" /></div>
<div class="large-5 small-12 medium-5 columns">
<p>sncRNA transcripts detected using the <strong>CATS small RNA-seq Kit</strong> vs the Competitor&rsquo;s Kit. The input was <strong>1 ng circulating small RNA</strong> in plasma samples. In total, 908 transcripts were found in the CATS small RNA-seq libraries. TPM&ge;1</p>
<p><strong>PCR cycles: CATS 14x</strong> vs Competitor 21x. <strong>Final library yield: CATS 27 ng</strong> vs Competitor 1.2 ng.</p>
</div>
</div>
<div>
<h3>More miRNA transcripts detected from challenging samples</h3>
<div class="large-7 small-12 medium-7 columns"><img src="https://www.diagenode.com/img/product/kits/cats/cats-mirnas-present-in-1-copy-in-1ng-circulating-rna.png" /></div>
<div class="large-5 small-12 medium-5 columns">
<p>Transcripts detected in miRNA samples of <strong>CATS small RNA-seq Kit</strong> vs the Competitor&rsquo;s Kit.</p>
<p>Input: <strong>1 ng circulating small RNA</strong> in plasma samples. <strong>PCR cycles: CATS 14x</strong> vs Competitor 21x. <strong>Final library yield: CATS 27 ng</strong> vs Competitor 1.2 ng.</p>
</div>
</div>
<div>
<h3>Ultra low inputs, excellent reproducibility</h3>
<div class="large-7 small-12 medium-7 columns"><img src="https://www.diagenode.com/img/product/kits/cats/CATS White Paper_CATS-fig3.png" /></div>
<div class="large-5 small-12 medium-5 columns">
<p>Correlation between 2 different operators using <strong>CATS small RNA-seq Kit</strong> on two different inputs (100 pg vs 1 ng) for ncRNA detected at TPM &ge;2. <br />R<sup>2</sup> = 0.86</p>
</div>
</div>
<div>
<h3>Consistency across template switching techniques</h3>
<div class="large-7 small-12 medium-7 columns"><img src="https://www.diagenode.com/img/product/kits/cats/CATS-White-Paper_graph-fig12.png" /></div>
<div class="large-5 small-12 medium-5 columns">
<p>Comparison of the number of detected small non-coding RNAs <strong>CATS small RNA-seq Kit</strong> vs SMARTer <br />Input: <strong>100 pg isolated small RNA</strong>. TPM &ge;2. Transcripts taken into consideration: miRNA, piRNA, scRNA, scaRNA, snoRNA, snRNA and vaultRNA. 1,217 transcripts found in both libraries at this expression level.</p>
</div>
</div>
<div>
<h3>High number of reads mapped</h3>
<div class="large-7 small-12 medium-7 columns"><img src="https://www.diagenode.com/img/product/kits/cats/CATS-White-Paper_graph-fig6.jpg" /></div>
<div class="large-5 small-12 medium-5 columns">
<p>Representation of detected transcripts different biotypes with <strong>CATS small RNA-seq Kit</strong>vs NEBNext UltraI kit. TPM&ge;2. <br /> <strong>100 ng total RNA, 1 ng small RNA</strong> used as input.</p>
</div>
</div>
<div>
<h3>Excellent performance on challenging samples</h3>
<div class="large-7 small-12 medium-7 columns"><img src="https://www.diagenode.com/img/product/kits/cats/Exosomes-page_heatt-1.jpg" /></div>
<div class="large-5 small-12 medium-5 columns">
<p>Heatmap clustering of the top 50 differentially expressed miRNAs after library preparation:</p>
<ul>
<li><strong>CATS Small RNA-seq Kit</strong> on 1 ng exosomal RNA (Exosome sample 1, 2)</li>
<li><strong>CATS RNA-seq Kit</strong> on 1 ng total RNA from parent (HEK293T) cells (Cell sample 1, 2).</li>
</ul>
<p>Prior library preparation, exosomes were isolated with Diagenode exosome capture solutions <a href="../categories/exosomes">Exosomes</a></p>
</div>
</div>
<div>
<h3>CATS saves time</h3>
<img src="https://www.diagenode.com/img/categories/library-prep/cats-save-time.png" /></div>
</div>
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			'description' => '<p style="text-align: left;"><strong>An updated version of this kit using D-Plex technology&nbsp;is available for superior performance.</strong></p>
<h4><span>Discover our <strong>NEW<a href="https://www.diagenode.com/en/p/D-Plex-Small-RNA-seq-Library-Prep-x24"> D-Plex Small RNA-seq Kit&nbsp;for Illumina</a></strong>&nbsp;and <strong><a href="https://www.diagenode.com/en/p/d-plex-small-RNA-dnbseq-kit-x24">D-Plex Small DNBSEQ Kit for MGI</a></strong>.</span></h4>',
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			'description' => '<div class="small-12 medium-12 large-12 columns" style="border: 3px solid #B02736; padding: 10px; margin: 10px;">
<h2>Product Features</h2>
<ul style="list-style-type: disc;">
<li>Ultra-low input capability, down to 10 pg for small RNAs and 100 pg for total RNA samples</li>
<li>High library complexity providing novel and diverse transcript detection</li>
<li>Versatile integartion into numerpus transcriptomic analysis workflow: ribosome profiling, CLIP-seq, RIP-seq and other</li>
<li>Improved quantification accuracy through the use of UMIs</li>
<li>Easy to use with minimal hands-on time: one day, one tube protocol</li>
</ul>
</div>
<p></p>
<p></p>
<center><em><a class="chip diahome button" href="https://www.diagenode.com/files/products/kits/MA-D-Plex.pdf" target="_blank" title="D-Plex Small RNA library preparation user manual"><strong>Download the manual</strong></a></em></center>
<p>D-Plex Small RNA-seq Library Prep Kit is a tool designed for the study of the <strong>small non-coding transcriptome</strong>. The kit is using the<a href="https://www.diagenode.com/en/pages/dplex" target="_blank"> D-Plex technology</a> to generate&nbsp;small RNA libraries for Illumina sequencing directly from total RNAs or enriched small RNAs.</p>
<p>The D-Plex technology utilizes&nbsp;two innovative&nbsp;<strong>ligation-free mechanisms</strong> - <strong>poly(A) tailing</strong> and <strong>template switching</strong>&nbsp;- to produce sequencing libraries&nbsp;from ultra-low input amounts, down to 10 pg for small RNAs and 100 pg for total RNAs.&nbsp;Combined with <strong>unique molecular identifiers</strong> (UMI), this complete solution ensures a <strong>realistic</strong> and <strong>accurate representation of diverse small RNA species</strong> (such as microRNAs, piRNAs, tRNAs, and siRNAs) with minimized quantitative bias.</p>
<p>D-Plex Small RNA-seq Kit offers a time saving protocol that can be completed within <strong>5 hours</strong> and requires minimal hands-on time.&nbsp;<span>The library preparation takes place in a&nbsp;</span><strong>single tube</strong><span>, increasing the efficiency tremendously.&nbsp;</span></p>
<p>D-Plex Small RNA-seq Kit includes all buffers and enzymes necessary for the library preparation. Specific D-Plex Indexes were designed and validated to fit the D-Plex technology and are available separately:</p>
<p><strong>For D-Plex UDI library construction:</strong></p>
<ul style="list-style-type: disc;">
<li><a href="https://www.diagenode.com/en/p/D-Plex-24-Unique-Dual-Indexes-Set-A" title="D-Plex UDI Module - Set A" target="_blank"><span>C05030021</span>&nbsp;- D-Plex Unique Dual Indexes for Illumina - Set A</a></li>
<li><a href="https://www.diagenode.com/en/p/D-Plex-24-Unique-Dual-Indexes-Set-B" title="D-Plex UDI Module - Set B" target="_blank"><span>C05030022</span>&nbsp;- D-Plex Unique Dual Indexes for Illumina - Set B</a></li>
<li><a href="https://www.diagenode.com/en/p/D-Plex-24-Unique-Dual-Indexes-Set-C">C05030023 - D-Plex&nbsp;Unique Dual&nbsp;Indexes for Illumina - Set C</a></li>
<li><a href="https://www.diagenode.com/en/p/D-Plex-24-Unique-Dual-Indexes-Set-D">C05030024 - D-Plex&nbsp;Unique Dual&nbsp;Indexes for Illumina - Set D</a></li>
</ul>
<p><span>The use of UDI is highly recommended&nbsp;to mitigate errors introduced by read misassignment, including index&nbsp;hopping frequently observed with patterned flow cells such as Illumina&rsquo;s&nbsp;NovaSeq system.</span></p>
<p><strong>For D-Plex SI library construction:</strong></p>
<ul style="list-style-type: disc;">
<li><a href="https://www.diagenode.com/en/p/D-Plex-24-Single-Indexes-Set-A" title="D-Plex SI Module - Set A" target="_blank">C05030010 - D-Plex Single Indexes for Illumina - Set A</a></li>
<li><a href="https://www.diagenode.com/en/p/D-Plex-24-Single-Indexes-Set-B" title="D-Plex SI Module - Set B" target="_blank">C05030011 - D-Plex Single Indexes for Illumina - Set B</a></li>
</ul>
<p><strong>D-Plex is also available for MGI sequencing, check <a href="https://www.diagenode.com/en/p/d-plex-small-RNA-dnbseq-kit-x24" target="_blank">here</a>!</strong></p>
<p></p>
<p></p>
<p></p>
<center><strong>The D-Plex smRNA-seq is a versatile tool for a plethora of transciptomic analysis</strong></center>
<p></p>
<center><img src="https://www.diagenode.com/img/product/kits/dplex/versatile-circle.png" /></center>
<p></p>
<p>With low-input capability, accuracy and ability to incorporate different transcript classes independent of chemical moieties, the strong D-Plex library-preparation method can be included in various analysis workflows (i.e., ribosome profiling, genome-wide mapping of protein: RNA binding sites).</p>
<p></p>
<p></p>',
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<div class="small-12 columns">
<p><strong>High library diversity for ultra-low inputs</strong></p>
<center><img src="https://www.diagenode.com/img/product/kits/dplex/dplex-diversity-fig1.png" /></center></div>
<div class="small-12 columns"><center><img src="https://www.diagenode.com/img/product/kits/dplex/dplex-fig2-captures.png" /></center></div>
</div>
<p></p>
<div class="row">
<div class="small-12 columns">
<p>D-Plex smRNA-seq captures the smRNA complexity of the sample in a sensitive manner. A large number of features is detected for each biotype at a CPM &ge;5, as shown above for different species.</p>
</div>
</div>
<p></p>
<p><strong>Accurate representation of the smRNA content of a sample</strong></p>
<div class="row">
<div class="small-6 columns"><center><img src="https://www.diagenode.com/img/product/kits/dplex/dplex-fig-ratplasma.png" /></center></div>
<div class="small-6 columns"><center><img src="https://www.diagenode.com/img/product/kits/dplex/dplex-fig-miRNAdistribution.png" /></center></div>
</div>
<div class="row">
<div class="small-6 columns">
<p><strong>Accurate identification of PCR duplicates in low-input samples using unique molecular identifiers (UMIs).</strong><br />The UMI read deduplication that is embedded in the D-Plex construct is used to avoid over-estimation of transcripts by identifying clones generated during the PCR amplification of the library. Despite limiting starting RNA input, the UMI correction removed technical copies of transcripts, maintaining the initial sample abundance.</p>
</div>
<div class="small-6 columns">
<p>D-Plex (template switching) technology enables recovery of the initial miRNA distribution of the miRXplore Universal Reference (Miltenyi Biotech Inc., Cat. No. 130-093-521). In contrast, ligation-based kits display a strong distortion of the miRNA equimolar distribution initially present in the pool, indicating sample incorporation bias.</p>
</div>
</div>
<p></p>
<p></p>
<div class="row">
<div class="small-6 columns"><center><img src="https://www.diagenode.com/img/product/kits/dplex/dplex-fig-foldchange.jpg" /></center></div>
<div class="small-6 columns"><strong>D-Plex smRNA-seq in association with the MGcount analysis correlates strongly (R&sup2; &gt; 0.8) with the RT-qPCR analysis, which is considered the gold-standard for accuracy. </strong><br />The figures shows a fold-change accuracy of a panel of 20 different small-RNA (figure taken from MGcount publication - Hita et al., BMC bioinformatics, 23-39(2022).</div>
</div>
<p></p>
<p></p>
<p><strong>Maximize information from the regulatory transcriptome using D-Plex small RNA-seq kit and MGcount*</strong></p>
<div class="row">
<div class="small-6 columns"><center><img src="https://www.diagenode.com/img/product/kits/dplex/dplex-fig-multialignments.png" /></center></div>
<div class="small-6 columns">By analyzing D-Plex dataset with MGcount, more reads are kept during the analysis, which ultimately preserves biological complexity linked to ncRNA expression without decreasing the accuracy of detection. <br /><span style="line-height: 1em;"><small>*Hita, A., Brocart, G., Fernandez, A. et al. MGcount: a total RNA-seq quantification tool to address multi-mapping and multi-overlapping alignments ambiguity in non-coding transcripts. BMC Bioinformatics 23, 39 (2022). <a href="https://doi.org/10.1186/s12859-021-04544-3">https://doi.org/10.1186/s12859-021-04544-3</a></small></span></div>
</div>
<p></p>
<p></p>
<div class="row">
<div class="small-12 columns">
<p>The D-Plex technology uses two innovative ligation-free mechanisms, <strong>poly(A) tailing and template switching</strong>, to produce sequencing libraries from ultra-low input amounts.</p>
</div>
</div>
<div class="row" style="background-color: #f5f5f5;">
<div class="small-12 columns"><br />
<p><strong>WORKFLOW</strong></p>
<center><img src="https://www.diagenode.com/img/product/kits/dplex/FL-Image-Workflow.jpg" width="50%" /></center></div>
<div class="small-12 columns">
<p style="text-align: justify; padding: 15px;"><br />RNA molecules are polyadenylated at the 3&rsquo;-end and primed with an oligo(dT) primer containing part of the ILMN 3&rsquo;-adapter sequence. The addition of a template-switching oligonucleotide during cDNA synthesis enables fusion of part of the ILMN 5&rsquo;-adapter during reverse transcription. After PCR, the library comprises double stranded DNA constructs that are ready for sequencing.</p>
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<p><br /><br /></p>
<p></p>
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			'info2' => '<p>A specific bioinformatics pipeline has been developed to process the special sequences present in the D-Plex construct, namely the UMI, the A-tail, and the template switch motif. All guidelines and free softwares are shared in the user manual. Subject to the compatibility of D-Plex constructs, other specific pipelines can be used.</p>
<p><img src="https://www.diagenode.com/img/product/kits/dplex/bioinfoPipe.png" alt="small RNA sequencing bioinformatics pipeline" caption="false" width="925" height="196" /></p>
<p>Need help for your bioinformatics analysis of miRNA?</p>
<p></p>
<div class="small-12 medium-3 large-3 columns"><center><a href="https://ccb-compute.cs.uni-saarland.de/mirmaster" target="_blank"><img src="https://www.diagenode.com/img/product/kits/dplex/miRMaster_logo.png" /></a></center>
<p>&nbsp;</p>
<p>&nbsp;</p>
</div>
<div class="small-12 medium-9 large-9 columns">
<p>Diagenode has collaborated with <strong>Andreas Keller</strong> and <strong>Tobias Fehlmann</strong> to develop a new bioinformatics pipeline for&nbsp;<span>the <strong>prediction of novel miRNAs</strong>.</span><br /><a href="https://ccb-compute.cs.uni-saarland.de/mirmaster" target="_blank"></a></p>
<ul>
<li style="text-align: justify;"><a href="https://ccb-compute.cs.uni-saarland.de/mirmaster2">miRMaster 2</a></li>
<li style="text-align: justify;"><a href="https://ccb-compute.cs.uni-saarland.de/mirmaster" target="_blank">miRMaster</a></li>
</ul>
</div>
<p>&nbsp;</p>
<p>&nbsp;</p>',
			'label3' => 'Data analysis - Counting using MGcount',
			'info3' => '<p>The counting or expression level calculation is the last step of the processing to generate an expression level matrix. We recommend using MGcount*, a counting tool developed at Diagenode with a suitable annotations file that include the small RNA transcripts that are object of study. MGcount, built on top of featureCounts, employs a flexible quantification approach to deal with datasets containing multiple RNA biotypes such as D-plex libraries. Non-coding RNAs varying in length, biogenesis, and function, may overlap in a genomic region, and are sometimes present in the genome with a high copy number. Consequently, reads may align equally well to more than one position in the reference genome or/and align to a position where more than one annotated transcript is located. MGcount employs two strategies to quantify these reads. Firstly, it assigns reads in rounds prioritizing small-RNAs over long-RNAs ensuring the unbiased read attribution to intergenic and intragenic small RNAs while preventing host-genes transcription over-estimation. Secondly, MGcount collapses loci where reads consistently multi-map into communities of loci with a graph-based approach. The resultant communities are groups of biologically related loci with nearly identical sequence. Subsequently, quantification of reads is performed at the loci-community level, reducing multi-alignments ambiguity at individual locus. Ultimately, this strategy maximizes the transcriptome information analysed and improves the interrogation of non-coding RNAs. MGcount software repository provides annotation files for A. thaliana, H. sapiens, M. musculus and C. elegans. The required input files for MGcount are a .txt file listing the paths to the alignment input files (.bam format) and the annotations file (.gtf format). The output directory path has to be provided as an input as well.</p>
<p><strong>Example command:</strong></p>
<p style="background-color: #f0f0f0;">MGcount -T 2 --gtf Homo_sapiens.GRCh38.gtf --outdir outputs --bam_infiles input_bamfilenames.txt</p>
<p>MGcount provides the choice to enable/disable the quantification of all RNA biotypes included in the annotation file in the form of "communities" as optional parameters for small-RNA (--ml_flag_small) and long-RNA (--ml_flag_long). Both are enabled by default. The main output of MGcount is the count_matrix.csv file containing an expression matrix that can be imported to R or any other software for downstream analyses.<br />A full user guide for MGCount is available here: <a href="https://filedn.com/lTnUWxFTA93JTyX3Hvbdn2h/mgcount/UserGuide.html">https://filedn.com/lTnUWxFTA93JTyX3Hvbdn2h/mgcount/UserGuide.html</a>.</p>
<p>Other standard counting tools such as featureCounts or HTSeq-counts can also be used alternatively. Given the high complexity of D-Plex libraries, we recommend having a clear understanding of the scientific question and the goal of the project before proceeding to the choice of the counting method as this will strongly impact downstream analyses. Diagenode provides bioinformatics support as a service (please, contact us if you need help with data analysis).</p>
<p>Notice that D-Plex produces forward-stranded data. Stranded libraries have the benefit that reads map to the genome strand where they were originated from. Therefore, when estimating transcript expression, reads aligned to the forward strand should be assigned only to transcript features in the forward strand whereas reads aligned to the reverse strand should be assigned only to transcript features in the reverse strand. For this, make sure you select &ldquo;stranded mode&rdquo; in any tool of choice. Stranded mode is selected by default in MGcount.</p>
<p><em><small>*Hita, A., Brocart, G., Fernandez, A. et al. MGcount: a total RNA-seq quantification tool to address multi-mapping and multi-overlapping alignments ambiguity in non-coding transcripts. BMC Bioinformatics 23, 39 (2022). <a href="https://doi.org/10.1186/s12859-021-04544-3">https://doi.org/10.1186/s12859-021-04544-3</a></small></em></p>',
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			'slug' => 'D-Plex-Small-RNA-seq-Library-Prep-x24',
			'meta_title' => 'D-Plex Small RNA-seq Library Prep Kit | Diagenode ',
			'meta_keywords' => 'RNA kit, RNA-seq kit, small RNA kit, small RNA-seq kit, low input RNA-seq, UMI RNA-seq, RNA-seq library preparation, D-Plex, higher RNA diversity',
			'meta_description' => 'Small RNA-seq library preparation for Illumina sequencing - Unique D-Plex technology - Optimized for ultra-low input (100 pg total RNA) - UMI reduce PCR biases - UDI detect index hopping - Compatibility with plasma samples - User-friendly and fast protocol',
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<p></p>
<center><a class="chip diahome button" href="https://www.diagenode.com/files/products/kits/D-Plex-Small-RNA-DNBSEQ.pdf" target="_blank" title="D-Plex Small RNA DNBSEQ user manual"><strong>Download the manual</strong></a></center>
<p></p>
<p>D-Plex Small RNA DNBSEQ&trade; Kit is a tool designed for the study of the small non-coding transcriptome. The kit is using the <a href="https://www.diagenode.com/en/pages/dplex" target="_blank">D-Plex technology</a> to generate double-stranded DNA libraries ready to be used for the DNA single-strand circularization step required for DNBSEQ sequencing on MGI sequencers.</p>
<p>The D-Plex technology&nbsp;utilizes the innovative capture and amplification by&nbsp;tailing and switching, a&nbsp;ligation-free&nbsp;method for RNA library preparation from ultra-low input amounts, down to 10 pg for small RNAs and 100 pg for total RNAs.&nbsp;This innovative solution enables diverse and novel transcripts detection, even from challenging clinical samples such as liquid biopsies.</p>
<p><span>D-Plex Small&nbsp;RNA&nbsp;<span>DNBSEQ&trade;</span> Kit offers a time saving protocol that can be completed within 5 hours and requires minimal hands-on time.&nbsp;</span><span>The library preparation takes place in a&nbsp;</span><span>single tube</span><span>, increasing the efficiency tremendously.&nbsp;This ensures high technical&nbsp;reliability and reproducibility<span>.</span></span></p>
<p>D-Plex Small RNA DNBSEQ&trade; Kit includes all buffers and enzymes necessary for the library preparation. Specific D-Plex DNBSEQ Barcodes were designed and validated to fit the D-Plex technology and are available separately:</p>
<ul>
<li><a href="https://www.diagenode.com/en/p/d-plex-24-dnbseq-barcodes-set-a">C05030060 - D-Plex DNBSEQ Barcodes for MGI - Set A</a></li>
<li><a href="https://www.diagenode.com/en/p/d-plex-24-dnbseq-barcodes-set-b">C05030061 - D-Plex DNBSEQ Barcodes for MGI - Set B</a></li>
</ul>
<p><b><strong>D-Plex is also available for Illumina sequencing, check<span>&nbsp;</span><a href="https://www.diagenode.com/en/p/D-Plex-Small-RNA-seq-Library-Prep-x24" target="_blank">here</a>!</strong></b></p>
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<div class="container">
<div class="row" style="background: rgba(255,255,255,0.1);">
<div class="large-12 columns slick">
<div>
<h3>Diverse and novel transcript detection</h3>
<div class="large-10 small-12 medium-10 large-centered medium-centered small-centered columns"><img style="height: 400px; display: block; margin-left: auto; margin-right: auto;" src="https://www.diagenode.com/img/product/kits/dplex/dplex-transcript.png" alt="small RNA library preparation for Illumina" /></div>
<div class="large-8 small-12 medium-6 large-centered medium-centered small-centered columns"><center>
<p style="text-align: justify;">The D-Plex Small RNA DNBSEQ protocol generates complex RNA libraries deciphering the wide diversity of small non-coding RNA spectrum (including miRNAs, snoRNAs, snRNAs)&nbsp; in human plasma samples.</p>
</center></div>
</div>
<div>
<h3>Ultra-low input performance</h3>
<div class="large-10 small-12 medium-10 large-centered medium-centered small-centered columns"><img style="height: 400px; display: block; margin-left: auto; margin-right: auto;" src="https://www.diagenode.com/img/product/kits/dplex/dplex-ultralow-input.png" alt="Ultra-low input performance" /></div>
<div class="large-8 small-12 medium-6 large-centered medium-centered small-centered columns"><center>
<p style="text-align: justify;">Sequencing data from circulating RNA samples of two input amounts (25 pg and 2.5 ng) were highly correlated (<i>R = 0.99</i>) when compared using Pearson correlation coefficient.</p>
</center></div>
</div>
<div>
<h3>High mapping efficiency</h3>
<div class="large-10 small-12 medium-10 large-centered medium-centered small-centered columns"><img style="height: 400px; display: block; margin-left: auto; margin-right: auto;" src="https://www.diagenode.com/img/product/kits/dplex/dplex-mapping.png" alt="High mapping efficiency" /></div>
<div class="large-8 small-12 medium-6 large-centered medium-centered small-centered columns"><center>
<p style="text-align: justify;"><b></b>The D-Plex Small RNA DNBSEQ kit is compatible with clinical-relevant samples, such as human plasma, and ultra low range of circulating RNA input (down to 10 pg) and exhibits good read mapping of sequencing reads (up to 70% mapping rate).</p>
</center></div>
</div>
<div>
<h3>High quality DNBSEQ sequencing solution</h3>
<div class="large-10 small-12 medium-10 large-centered medium-centered small-centered columns"><img style="height: 400px;" src="https://www.diagenode.com/img/product/kits/dplex/dplex-dnbseq.png" alt="High quality DNBSEQ sequencing solution" /></div>
<div class="large-8 small-12 medium-6 large-centered medium-centered small-centered columns"><center>
<p><b></b>The D-Plex Small RNA DNBSEQ kit combines our best-in-class RNA library preparation &ndash; D-Plex technology &ndash; with MGI&rsquo;s high-quality, cost-effective, DNA nanoballs &ndash; DNBSEQ &ndash; sequencing solution, creating a unified platform to support high quality small RNA sequencing.</p>
</center></div>
</div>
</div>
</div>
</div>
</div>
</div>
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<li><strong>Latest innovation in RNA-seq</strong>:&nbsp;unique D-Plex technology&nbsp;offering ligation-free&nbsp;protocol for library preparation</li>
<li><strong>Ultra-low input capability</strong>: down to 10 pg for small RNAs and 100 pg for total RNAs</li>
<li><strong>High library complexity</strong>:<strong> </strong>obtain a complete view of&nbsp;your small RNA transcriptome</li>
<li><strong>Optimal performance on clinical samples</strong>: validated&nbsp;with circulating RNAs from liquid biopsies</li>
<li><strong>Easy to use with minimal hands-on time</strong>: one day, one tube protocol</li>
<li><strong>Highest sequencing quality</strong>: specifically formatted for MGI DNBSEQ&trade; sequencers</li>
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			'info2' => '<p>D-Plex DNBSEQ Barcodes are not included in the kit. Two sets are available separately:</p>
<ul style="list-style-type: disc;">
<li><a href="https://www.diagenode.com/en/p/d-plex-24-dnbseq-barcodes-set-a">C05030060 - D-Plex 24 DNBSEQ Barcodes for MGI - Set A</a></li>
<li><a href="https://www.diagenode.com/en/p/d-plex-24-dnbseq-barcodes-set-b">C05030061 - D-Plex 24 DNBSEQ Barcodes for MGI - Set B</a></li>
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<div class="small-12 medium-12 large-12 columns">
<p><span style="font-weight: 400;">Most of the major next-generation sequencing platforms require ligation of specific adaptor oligos to </span><a href="../applications/dna-rna-shearing"><span style="font-weight: 400;">fragmented DNA or RNA</span></a><span style="font-weight: 400;"> prior to sequencing</span></p>
<p><span style="font-weight: 400;">After input DNA has been fragmented, it is end-repaired and blunt-ended</span><span style="font-weight: 400;">. The next step is a A-tailing in which dAMP is added to the 3&acute; end of the blunt phosphorylated DNA fragments to prevent concatemerization and to allow the ligation of adaptors with complementary dT overhangs. In addition, barcoded adapters can be incorporated to facilitate multiplexing prior to or during amplification.</span></p>
<center><img src="https://www.diagenode.com/img/categories/library-prep/flux.png" /></center>
<p><span style="font-weight: 400;">Diagenode offers a comprehensive product portfolio for library preparation:<br /></span></p>
<strong><a href="https://www.diagenode.com/en/categories/Library-preparation-for-RNA-seq">D-Plex&nbsp;RNA-seq Library Preparation Kits</a></strong><br />
<p><span style="font-weight: 400;">Diagenode&rsquo;s new RNA-sequencing solutions utilize the innovative c</span><span style="font-weight: 400;">apture and a</span><span style="font-weight: 400;">mplification by t</span><span style="font-weight: 400;">ailing and s</span><span style="font-weight: 400;">witching&rdquo;</span><span style="font-weight: 400;">, a ligation-free method to produce DNA libraries for next generation sequencing from low input amounts of RNA. </span><span style="font-weight: 400;"></span><a href="../categories/Library-preparation-for-RNA-seq">Learn more</a></p>
<strong><a href="../categories/library-preparation-for-ChIP-seq">ChIP-seq and DNA sequencing library preparation solutions</a></strong><br />
<p><span style="font-weight: 400;">Our kits have been optimized for DNA library preparation used for next generation sequencing for a wide range of inputs. Using a simple three-step protocols, our</span><a href="http://www.diagenode.com/p/microplex-library-preparation-kit-v2-x12-12-indices-12-rxns"><span style="font-weight: 400;"> </span></a><span style="font-weight: 400;">kits are an optimal choice for library preparation from DNA inputs down to 50 pg.&nbsp;</span><a href="../categories/library-preparation-for-ChIP-seq">Learn more</a></p>
<a href="../p/bioruptor-pico-sonication-device"><span style="font-weight: 400;"></span><strong>Bioruptor Pico - short fragments</strong></a><a href="../categories/library-preparation-for-ChIP-seq-and-DNA-sequencing"><span style="font-weight: 400;"></span></a><br />
<p><span style="font-weight: 400;"></span><span style="font-weight: 400;">Our well-cited Bioruptor Pico is the shearing device of choice for chromatin and DNA fragmentation. Obtain uniform and tight fragment distributions &nbsp;between 150bp -2kb. </span><a href="../p/bioruptor-pico-sonication-device">Learn more</a></p>
<strong><a href="../p/megaruptor2-1-unit"><span href="../p/bioruptor-pico-sonication-device">Megaruptor</span>&reg; - long fragments</a></strong><a href="../p/bioruptor-pico-sonication-device"><span style="font-weight: 400;"></span></a><a href="../categories/library-preparation-for-ChIP-seq-and-DNA-sequencing"><span style="font-weight: 400;"></span></a><br />
<p><span style="font-weight: 400;"></span><span style="font-weight: 400;">The Megaruptor is designed to shear DNA from 3kb-75kb for long-read sequencing.&nbsp; <a href="../p/megaruptor2-1-unit">Learn more</a></span></p>
<span href="../p/bioruptor-pico-sonication-device"></span><span style="font-weight: 400;"></span></div>
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			'description' => '<div class="abstract-content selected" id="enc-abstract">
<p><strong class="sub-title">Background:<span>&nbsp;</span></strong>MicroRNA (miRNA) play a significant role in the pathogenesis of complex neurodegenerative diseases including age-related macular degeneration (AMD), acting as post-transcriptional gene suppressors through their association with argonaute 2 (AGO2) - a key member of the RNA Induced Silencing Complex (RISC). Identifying the retinal miRNA/mRNA interactions in health and disease will provide important insight into the key pathways miRNA regulate in disease pathogenesis and may lead to potential therapeutic targets to mediate retinal degeneration.</p>
<p><strong class="sub-title">Methods:<span>&nbsp;</span></strong>To identify the active miRnome targetome interactions in the healthy and degenerating retina, AGO2 HITS-CLIP was performed using a rodent model of photoreceptor degeneration. Analysis of publicly available single-cell RNA sequencing (scRNAseq) data was performed to identify the cellular location of AGO2 and key members of the microRNA targetome in the retina. AGO2 findings were verified by in situ hybridization (RNA) and immunohistochemistry (protein).</p>
<p><strong class="sub-title">Results:<span>&nbsp;</span></strong>Analysis revealed a similar miRnome between healthy and damaged retinas, however, a shift in the active targetome was observed with an enrichment of miRNA involvement in inflammatory pathways. This shift was further demonstrated by a change in the seed binding regions of miR-124-3p, the most abundant retinal AGO2-bound miRNA, and has known roles in regulating retinal inflammation. Additionally, photoreceptor cluster miR-183/96/182 were all among the most highly abundant miRNA bound to AGO2. Following damage, AGO2 expression was localized to the inner retinal layers and more in the OLM than in healthy retinas, indicating a locational miRNA response to retinal damage.</p>
<p><strong class="sub-title">Conclusions:<span>&nbsp;</span></strong>This study provides important insight into the alteration of miRNA regulatory activity that occurs as a response to retinal degeneration and explores the miRNA-mRNA targetome as a consequence of retinal degenerations. Further characterisation of these miRNA/mRNA interactions in the context of the degenerating retina may provide an important insight into the active role these miRNA may play in diseases such as AMD.</p>
</div>
<p><strong class="sub-title">Keywords:<span>&nbsp;</span></strong>Argonaute; HITS-CLIP; Inflammation; Retina; Retinal degeneration; Transcriptome; mRNA; microRNA.</p>',
			'date' => '2021-08-31',
			'pmid' => 'https://pubmed.ncbi.nlm.nih.gov/34465369/',
			'doi' => '10.1186/s13024-021-00478-9',
			'modified' => '2022-03-28 11:05:53',
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			'name' => 'Repeat RNAs associate with replication forks and post-replicative DNA.',
			'authors' => 'Gylling HM, Gonzalez-Aguilera C, Smith MA, Kaczorowski DC, Groth A, Lund AH',
			'description' => '<p>Non-coding RNA has a proven ability to direct and regulate chromatin modifications by acting as scaffolds between DNA and histone-modifying complexes. However, it is unknown if ncRNA plays any role in DNA replication and epigenome maintenance, including histone eviction and re-instalment of histone-modifications after genome duplication. Isolation of nascent chromatin has identified a large number of RNA-binding proteins in addition to unknown components of the replication and epigenetic maintenance machinery. Here, we isolated and characterized long and short RNAs associated with nascent chromatin at active replication forks and track RNA composition during chromatin maturation across the cell cycle. Shortly after fork passage, GA-rich-, Alpha- and TElomeric Repeat-containing RNAs (TERRA) are associated with replicated DNA. These repeat containing RNAs arise from loci undergoing replication, suggesting an interaction in cis. Post-replication during chromatin maturation, and even after mitosis in G1, the repeats remain enriched on DNA. This suggests that specific types of repeat RNAs are transcribed shortly after DNA replication and stably associate with their loci of origin throughout cell cycle. The presented method and data enables studies of RNA interactions with replication forks and post-replicative chromatin and provides insights into how repeat RNAs and their engagement with chromatin are regulated with respect to DNA replication and across the cell cycle.</p>',
			'date' => '2020-05-11',
			'pmid' => 'http://www.pubmed.gov/32393525',
			'doi' => '10.1261/rna.074757.120',
			'modified' => '2020-08-17 10:03:46',
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			'name' => 'Multisite Evaluation of Next-Generation Methods for Small RNA Quantification.',
			'authors' => 'Herbert ZT, Thimmapuram J, Xie S, Kershner JP, Kolling FW, Ringelberg CS, LeClerc A, Alekseyev YO, Fan J, Podnar JW, Stevenson HS, Sommerville G, Gupta S, Berkeley M, Koeman J, Perera A, Scott AR, Grenier JK, Malik J, Ashton JM, Pivarski KL, Wang X, Kuffe',
			'description' => '<p>Small RNAs (smRNAs) are important regulators of many biologic processes and are now most frequently characterized using Illumina sequencing. However, although standard RNA sequencing library preparation has become routine in most sequencing facilities, smRNA sequencing library preparation has historically been challenging because of high input requirements, laborious protocols involving gel purifications, inability to automate, and a lack of benchmarking standards. Additionally, studies have suggested that many of these methods are nonlinear and do not accurately reflect the amounts of smRNAs . Recently, a number of new kits have become available that permit lower input amounts and less laborious, gel-free protocol options. Several of these new kits claim to reduce RNA ligase-dependent sequence bias through novel adapter modifications and to lessen adapter-dimer contamination in the resulting libraries. With the increasing number of smRNA kits available, understanding the relative strengths of each method is crucial for appropriate experimental design. In this study, we systematically compared 9 commercially available smRNA library preparation kits as well as NanoString probe hybridization across multiple study sites. Although several of the new methodologies do reduce the amount of artificially over- and underrepresented microRNAs (miRNAs), we observed that none of the methods was able to remove all of the bias in the library preparation. Identical samples prepared with different methods show highly varied levels of different miRNAs. Even so, many methods excelled in ease of use, lower input requirement, fraction of usable reads, and reproducibility across sites. These differences may help users select the most appropriate methods for their specific question of interest.</p>',
			'date' => '2020-01-10',
			'pmid' => 'http://www.pubmed.gov/31966025',
			'doi' => '10.7171/jbt.20-3102-001',
			'modified' => '2020-03-20 17:53:30',
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			'name' => 'Circulating miRNA analysis for cancer diagnostics and therapy.',
			'authors' => 'Valihrach L, Androvic P, Kubista M',
			'description' => '<p>Successful treatment of cancer depends on early diagnosis and effective monitoring of patients' response to therapy. Traditional tools based on tumor biopsies lack the sensitivity and specificity to capture cancer development in its early phases and are not applicable for continuous monitoring. To overcome these barriers, liquid biopsies have been introduced as a minimally invasive and cost-efficient means of diagnosis with high level of specificity and sensitivity. Traditionally, liquid biopsy markers include circulating tumor cells and circulating tumor DNA. During the last decade, a new promising group of biomarkers has appeared and its utilization for cancer diagnosis and monitoring is intensively studied - the microRNAs (miRNAs). In this review, we provide a comprehensive overview of circulating miRNA analysis. We highlight the importance of sampling and quality control, discuss the technical aspects of miRNA extraction and quantification, summarize recommendations for downstream analysis and conclude with future perspectives. Taken together, we present the current state of knowledge in the field of miRNA analysis in liquid biopsies and the expected development and standardization.</p>',
			'date' => '2019-10-18',
			'pmid' => 'http://www.pubmed.gov/31635843',
			'doi' => '10.1016/j.mam.2019.10.002',
			'modified' => '2019-12-05 11:07:26',
			'created' => '2019-12-02 15:25:44',
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		(int) 4 => array(
			'id' => '3697',
			'name' => 'The sncRNA Zoo: a repository for circulating small noncoding RNAs in animals.',
			'authors' => 'Fehlmann T, Backes C, Pirritano M, Laufer T, Galata V, Kern F, Kahraman M, Gasparoni G, Ludwig N, Lenhof HP, Gregersen HA, Francke R, Meese E, Simon M, Keller A',
			'description' => '<p>The repertoire of small noncoding RNAs (sncRNAs), particularly miRNAs, in animals is considered to be evolutionarily conserved. Studies on sncRNAs are often largely based on homology-based information, relying on genomic sequence similarity and excluding actual expression data. To obtain information on sncRNA expression (including miRNAs, snoRNAs, YRNAs and tRNAs), we performed low-input-volume next-generation sequencing of 500&nbsp;pg of RNA from 21 animals at two German zoological gardens. Notably, none of the species under investigation were previously annotated in any miRNA reference database. Sequencing was performed on blood cells as they are amongst the most accessible, stable and abundant sources of the different sncRNA classes. We evaluated and compared the composition and nature of sncRNAs across the different species by computational approaches. While the distribution of sncRNAs in the different RNA classes varied significantly, general evolutionary patterns were maintained. In particular, miRNA sequences and expression were found to be even more conserved than previously assumed. To make the results available for other researchers, all data, including expression profiles at the species and family levels, and different tools for viewing, filtering and searching the data are freely available in the online resource ASRA (Animal sncRNA Atlas) at https://www.ccb.uni-saarland.de/asra/.</p>',
			'date' => '2019-05-21',
			'pmid' => 'http://www.pubmed.gov/30937442',
			'doi' => '10.1093/nar/gkz227',
			'modified' => '2019-06-28 13:44:35',
			'created' => '2019-06-21 14:55:31',
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		(int) 5 => array(
			'id' => '3609',
			'name' => 'MicroRNAs and Transplantation.',
			'authors' => 'Khan Z, Suthanthiran M, Muthukumar T',
			'description' => '<p>miRNAs, &sim;20 to 22 nucleotide single-stranded RNA species that play a pivotal role in the regulation of protein-coding genes, are emerging as robust biomarkers for assessing allograft status. Herein, the authors briefly review the biogenesis and function of the miRNAs and provide an overview of the tools to quantify miRNAs in tissues and body fluids. They then review their studies of discovery and validation of alterations in miRNA expression within kidney allografts with or without acute rejection, as well as with or without fibrosis, and summarize published data on miRNA expression patterns in kidney transplant recipients.</p>',
			'date' => '2019-03-01',
			'pmid' => 'http://www.pubmed.gov/30709501',
			'doi' => '10.1016/j.cll.2018.10.003',
			'modified' => '2019-04-17 14:48:18',
			'created' => '2019-04-16 12:25:30',
			'ProductsPublication' => array(
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		),
		(int) 6 => array(
			'id' => '3387',
			'name' => 'NGS analysis of total small non coding RNAs from low input RNA from dried blood sampling',
			'authors' => 'Marcello Pirritano, Tobias Fehlmann, Thomas Laufer, Nicole Ludwig, Gilles Gasparoni, Yongping Li, Eckart Meese, Andreas Keller, and Martin Simon',
			'description' => '<p><span>Circulating miRNAs are favored for biomarker candidates as they can reflect tissue specific miRNA dysregulation in disease contexts. Moreover, they have additional advantages that they can be monitored in a minimal invasive manner. Blood-borne miRNAs are therefore currently characterized to identify, describe and validate their potential suitability for a biomarker, however, sampling and as well miRNA detection methods limit these studies in terms of sensitivity but also practicability in clinical, at-home or low-resource sampling of high quality circulating RNA samples. We describe here a novel and innovative method of circulating RNA microsampling from minimal volume dried blood spots with direct enrichment for small RNA fractions in combination with ligation free library preparation. We evaluated crucial parameters for efficient library preparation from low RNA inputs of 50pg for efficient dissection not only of miRNAs but also isomiRs, piRNAs, and lincRNAs. We compared these data to classical microarrays and characterize the technical reproducibility and its sensitivity. We demonstrate and evaluate a method for easy low resource sampling and NGS analysis of circulating RNAs providing a powerful tool for massive cohort and remote patient monitoring.</span></p>',
			'date' => '2018-09-10',
			'pmid' => 'https://www.ncbi.nlm.nih.gov/pubmed/?term=NGS+analysis+of+total+small+non+coding+RNAs+from+low+input+RNA+from+dried+blood+sampling',
			'doi' => '',
			'modified' => '2018-12-31 11:32:28',
			'created' => '2018-09-20 11:18:35',
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	'name' => 'CATS Small RNA-seq Kit x96',
	'description' => '<p><strong>An updated version of this kit using D-Plex technology&nbsp;is available for superior performance.</strong></p>
<p><span>Discover our<strong><a href="https://www.diagenode.com/en/p/D-Plex-Small-RNA-seq-Library-Prep-x24"><span>&nbsp;</span>D-Plex Small RNA-seq kit&nbsp;for Illumina</a></strong>&nbsp;and<span>&nbsp;</span><strong><a href="https://www.diagenode.com/en/p/d-plex-small-RNA-dnbseq-kit-x24">D-Plex Small DNBSEQ kit for MGI</a></strong><span>&nbsp;</span>sequencing.</span></p>',
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<p></p>
<center><a class="chip diahome button" href="https://www.diagenode.com/files/products/kits/D-Plex-Small-RNA-DNBSEQ.pdf" target="_blank" title="D-Plex Small RNA DNBSEQ user manual"><strong>Download the manual</strong></a></center>
<p></p>
<p>D-Plex Small RNA DNBSEQ&trade; Kit is a tool designed for the study of the small non-coding transcriptome. The kit is using the <a href="https://www.diagenode.com/en/pages/dplex" target="_blank">D-Plex technology</a> to generate double-stranded DNA libraries ready to be used for the DNA single-strand circularization step required for DNBSEQ sequencing on MGI sequencers.</p>
<p>The D-Plex technology&nbsp;utilizes the innovative capture and amplification by&nbsp;tailing and switching, a&nbsp;ligation-free&nbsp;method for RNA library preparation from ultra-low input amounts, down to 10 pg for small RNAs and 100 pg for total RNAs.&nbsp;This innovative solution enables diverse and novel transcripts detection, even from challenging clinical samples such as liquid biopsies.</p>
<p><span>D-Plex Small&nbsp;RNA&nbsp;<span>DNBSEQ&trade;</span> Kit offers a time saving protocol that can be completed within 5 hours and requires minimal hands-on time.&nbsp;</span><span>The library preparation takes place in a&nbsp;</span><span>single tube</span><span>, increasing the efficiency tremendously.&nbsp;This ensures high technical&nbsp;reliability and reproducibility<span>.</span></span></p>
<p>D-Plex Small RNA DNBSEQ&trade; Kit includes all buffers and enzymes necessary for the library preparation. Specific D-Plex DNBSEQ Barcodes were designed and validated to fit the D-Plex technology and are available separately:</p>
<ul>
<li><a href="https://www.diagenode.com/en/p/d-plex-24-dnbseq-barcodes-set-a">C05030060 - D-Plex DNBSEQ Barcodes for MGI - Set A</a></li>
<li><a href="https://www.diagenode.com/en/p/d-plex-24-dnbseq-barcodes-set-b">C05030061 - D-Plex DNBSEQ Barcodes for MGI - Set B</a></li>
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<p><b><strong>D-Plex is also available for Illumina sequencing, check<span>&nbsp;</span><a href="https://www.diagenode.com/en/p/D-Plex-Small-RNA-seq-Library-Prep-x24" target="_blank">here</a>!</strong></b></p>
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<h3>Diverse and novel transcript detection</h3>
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<p style="text-align: justify;">The D-Plex Small RNA DNBSEQ protocol generates complex RNA libraries deciphering the wide diversity of small non-coding RNA spectrum (including miRNAs, snoRNAs, snRNAs)&nbsp; in human plasma samples.</p>
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<div>
<h3>Ultra-low input performance</h3>
<div class="large-10 small-12 medium-10 large-centered medium-centered small-centered columns"><img style="height: 400px; display: block; margin-left: auto; margin-right: auto;" src="https://www.diagenode.com/img/product/kits/dplex/dplex-ultralow-input.png" alt="Ultra-low input performance" /></div>
<div class="large-8 small-12 medium-6 large-centered medium-centered small-centered columns"><center>
<p style="text-align: justify;">Sequencing data from circulating RNA samples of two input amounts (25 pg and 2.5 ng) were highly correlated (<i>R = 0.99</i>) when compared using Pearson correlation coefficient.</p>
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</div>
<div>
<h3>High mapping efficiency</h3>
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<div class="large-8 small-12 medium-6 large-centered medium-centered small-centered columns"><center>
<p style="text-align: justify;"><b></b>The D-Plex Small RNA DNBSEQ kit is compatible with clinical-relevant samples, such as human plasma, and ultra low range of circulating RNA input (down to 10 pg) and exhibits good read mapping of sequencing reads (up to 70% mapping rate).</p>
</center></div>
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<h3>High quality DNBSEQ sequencing solution</h3>
<div class="large-10 small-12 medium-10 large-centered medium-centered small-centered columns"><img style="height: 400px;" src="https://www.diagenode.com/img/product/kits/dplex/dplex-dnbseq.png" alt="High quality DNBSEQ sequencing solution" /></div>
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<p><b></b>The D-Plex Small RNA DNBSEQ kit combines our best-in-class RNA library preparation &ndash; D-Plex technology &ndash; with MGI&rsquo;s high-quality, cost-effective, DNA nanoballs &ndash; DNBSEQ &ndash; sequencing solution, creating a unified platform to support high quality small RNA sequencing.</p>
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<h3>Unique sncRNAs detected in circulating plasma RNA</h3>
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<p>sncRNA transcripts detected using the <strong>CATS small RNA-seq Kit</strong> vs the Competitor&rsquo;s Kit. The input was <strong>1 ng circulating small RNA</strong> in plasma samples. In total, 908 transcripts were found in the CATS small RNA-seq libraries. TPM&ge;1</p>
<p><strong>PCR cycles: CATS 14x</strong> vs Competitor 21x. <strong>Final library yield: CATS 27 ng</strong> vs Competitor 1.2 ng.</p>
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<h3>More miRNA transcripts detected from challenging samples</h3>
<div class="large-7 small-12 medium-7 columns"><img src="https://www.diagenode.com/img/product/kits/cats/cats-mirnas-present-in-1-copy-in-1ng-circulating-rna.png" /></div>
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<p>Transcripts detected in miRNA samples of <strong>CATS small RNA-seq Kit</strong> vs the Competitor&rsquo;s Kit.</p>
<p>Input: <strong>1 ng circulating small RNA</strong> in plasma samples. <strong>PCR cycles: CATS 14x</strong> vs Competitor 21x. <strong>Final library yield: CATS 27 ng</strong> vs Competitor 1.2 ng.</p>
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<p>Correlation between 2 different operators using <strong>CATS small RNA-seq Kit</strong> on two different inputs (100 pg vs 1 ng) for ncRNA detected at TPM &ge;2. <br />R<sup>2</sup> = 0.86</p>
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<p>Comparison of the number of detected small non-coding RNAs <strong>CATS small RNA-seq Kit</strong> vs SMARTer <br />Input: <strong>100 pg isolated small RNA</strong>. TPM &ge;2. Transcripts taken into consideration: miRNA, piRNA, scRNA, scaRNA, snoRNA, snRNA and vaultRNA. 1,217 transcripts found in both libraries at this expression level.</p>
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<p>Representation of detected transcripts different biotypes with <strong>CATS small RNA-seq Kit</strong>vs NEBNext UltraI kit. TPM&ge;2. <br /> <strong>100 ng total RNA, 1 ng small RNA</strong> used as input.</p>
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<li><strong>CATS RNA-seq Kit</strong> on 1 ng total RNA from parent (HEK293T) cells (Cell sample 1, 2).</li>
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<p>Prior library preparation, exosomes were isolated with Diagenode exosome capture solutions <a href="../categories/exosomes">Exosomes</a></p>
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<h3>CATS saves time</h3>
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<li class="accordion-navigation"><a href="#more" style="color: #13b29c; background-color: transparent; display: inline; padding: 0;">続きを読む</a>
<div id="more" class="content">
<p style="text-align: justify;">CATSは、RNAの3&rsquo;末端をキャプチャーするためのポリヌクレオチドテーリングおよび、cDNA合成時に5&rsquo;末端をキャプチャーするためのMMLV-RTによるテンプレートスイッチ 能力を利用した技術です。この方法なら、10ピコグラムの低インプットRNA量からわずか数時間でIllumina用シークエンシングライブラリーを作製することができます。</p>
<p style="text-align: justify;">ライブラリーは、ストランド特異的な情報を保持しています。「CATS RNA-seq Kit」は、増幅を最小限に抑えることでより多くの有効な鋳型をキャプチャーし、また、バイアスを最小限に抑えることで高い複雑性を得ることができるので、他のライゲーションベースの手法と比べより高いライブラリー作製効率を示します。</p>
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<div class="container">
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<h3>Unique sncRNAs detected in circulating plasma RNA</h3>
<div class="large-7 small-12 medium-7 columns"><img src="https://www.diagenode.com/img/product/kits/cats/cats-908-competitor-3.png" /></div>
<div class="large-5 small-12 medium-5 columns">
<p>sncRNA transcripts detected using the <strong>CATS small RNA-seq Kit</strong> vs the Competitor&rsquo;s Kit. The input was <strong>1 ng circulating small RNA</strong> in plasma samples. In total, 908 transcripts were found in the CATS small RNA-seq libraries. TPM&ge;1</p>
<p><strong>PCR cycles: CATS 14x</strong> vs Competitor 21x. <strong>Final library yield: CATS 27 ng</strong> vs Competitor 1.2 ng.</p>
</div>
</div>
<div>
<h3>More miRNA transcripts detected from challenging samples</h3>
<div class="large-7 small-12 medium-7 columns"><img src="https://www.diagenode.com/img/product/kits/cats/cats-mirnas-present-in-1-copy-in-1ng-circulating-rna.png" /></div>
<div class="large-5 small-12 medium-5 columns">
<p>Transcripts detected in miRNA samples of <strong>CATS small RNA-seq Kit</strong> vs the Competitor&rsquo;s Kit.</p>
<p>Input: <strong>1 ng circulating small RNA</strong> in plasma samples. <strong>PCR cycles: CATS 14x</strong> vs Competitor 21x. <strong>Final library yield: CATS 27 ng</strong> vs Competitor 1.2 ng.</p>
</div>
</div>
<div>
<h3>Ultra low inputs, excellent reproducibility</h3>
<div class="large-7 small-12 medium-7 columns"><img src="https://www.diagenode.com/img/product/kits/cats/CATS White Paper_CATS-fig3.png" /></div>
<div class="large-5 small-12 medium-5 columns">
<p>Correlation between 2 different operators using <strong>CATS small RNA-seq Kit</strong> on two different inputs (100 pg vs 1 ng) for ncRNA detected at TPM &ge;2. <br />R<sup>2</sup> = 0.86</p>
</div>
</div>
<div>
<h3>Consistency across template switching techniques</h3>
<div class="large-7 small-12 medium-7 columns"><img src="https://www.diagenode.com/img/product/kits/cats/CATS-White-Paper_graph-fig12.png" /></div>
<div class="large-5 small-12 medium-5 columns">
<p>Comparison of the number of detected small non-coding RNAs <strong>CATS small RNA-seq Kit</strong> vs SMARTer <br />Input: <strong>100 pg isolated small RNA</strong>. TPM &ge;2. Transcripts taken into consideration: miRNA, piRNA, scRNA, scaRNA, snoRNA, snRNA and vaultRNA. 1,217 transcripts found in both libraries at this expression level.</p>
</div>
</div>
<div>
<h3>High number of reads mapped</h3>
<div class="large-7 small-12 medium-7 columns"><img src="https://www.diagenode.com/img/product/kits/cats/CATS-White-Paper_graph-fig6.jpg" /></div>
<div class="large-5 small-12 medium-5 columns">
<p>Representation of detected transcripts different biotypes with <strong>CATS small RNA-seq Kit</strong>vs NEBNext UltraI kit. TPM&ge;2. <br /> <strong>100 ng total RNA, 1 ng small RNA</strong> used as input.</p>
</div>
</div>
<div>
<h3>Excellent performance on challenging samples</h3>
<div class="large-7 small-12 medium-7 columns"><img src="https://www.diagenode.com/img/product/kits/cats/Exosomes-page_heatt-1.jpg" /></div>
<div class="large-5 small-12 medium-5 columns">
<p>Heatmap clustering of the top 50 differentially expressed miRNAs after library preparation:</p>
<ul>
<li><strong>CATS Small RNA-seq Kit</strong> on 1 ng exosomal RNA (Exosome sample 1, 2)</li>
<li><strong>CATS RNA-seq Kit</strong> on 1 ng total RNA from parent (HEK293T) cells (Cell sample 1, 2).</li>
</ul>
<p>Prior library preparation, exosomes were isolated with Diagenode exosome capture solutions <a href="../categories/exosomes">Exosomes</a></p>
</div>
</div>
<div>
<h3>CATS saves time</h3>
<img src="https://www.diagenode.com/img/categories/library-prep/cats-save-time.png" /></div>
</div>
</div>
</div>
</div>
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			'name' => 'CATS Small RNA-seq Kit x24',
			'description' => '<p style="text-align: left;"><strong>An updated version of this kit using D-Plex technology&nbsp;is available for superior performance.</strong></p>
<h4><span>Discover our <strong>NEW<a href="https://www.diagenode.com/en/p/D-Plex-Small-RNA-seq-Library-Prep-x24"> D-Plex Small RNA-seq Kit&nbsp;for Illumina</a></strong>&nbsp;and <strong><a href="https://www.diagenode.com/en/p/d-plex-small-RNA-dnbseq-kit-x24">D-Plex Small DNBSEQ Kit for MGI</a></strong>.</span></h4>',
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			'name' => 'D-Plex Small RNA-seq Kit for Illumina',
			'description' => '<div class="small-12 medium-12 large-12 columns" style="border: 3px solid #B02736; padding: 10px; margin: 10px;">
<h2>Product Features</h2>
<ul style="list-style-type: disc;">
<li>Ultra-low input capability, down to 10 pg for small RNAs and 100 pg for total RNA samples</li>
<li>High library complexity providing novel and diverse transcript detection</li>
<li>Versatile integartion into numerpus transcriptomic analysis workflow: ribosome profiling, CLIP-seq, RIP-seq and other</li>
<li>Improved quantification accuracy through the use of UMIs</li>
<li>Easy to use with minimal hands-on time: one day, one tube protocol</li>
</ul>
</div>
<p></p>
<p></p>
<center><em><a class="chip diahome button" href="https://www.diagenode.com/files/products/kits/MA-D-Plex.pdf" target="_blank" title="D-Plex Small RNA library preparation user manual"><strong>Download the manual</strong></a></em></center>
<p>D-Plex Small RNA-seq Library Prep Kit is a tool designed for the study of the <strong>small non-coding transcriptome</strong>. The kit is using the<a href="https://www.diagenode.com/en/pages/dplex" target="_blank"> D-Plex technology</a> to generate&nbsp;small RNA libraries for Illumina sequencing directly from total RNAs or enriched small RNAs.</p>
<p>The D-Plex technology utilizes&nbsp;two innovative&nbsp;<strong>ligation-free mechanisms</strong> - <strong>poly(A) tailing</strong> and <strong>template switching</strong>&nbsp;- to produce sequencing libraries&nbsp;from ultra-low input amounts, down to 10 pg for small RNAs and 100 pg for total RNAs.&nbsp;Combined with <strong>unique molecular identifiers</strong> (UMI), this complete solution ensures a <strong>realistic</strong> and <strong>accurate representation of diverse small RNA species</strong> (such as microRNAs, piRNAs, tRNAs, and siRNAs) with minimized quantitative bias.</p>
<p>D-Plex Small RNA-seq Kit offers a time saving protocol that can be completed within <strong>5 hours</strong> and requires minimal hands-on time.&nbsp;<span>The library preparation takes place in a&nbsp;</span><strong>single tube</strong><span>, increasing the efficiency tremendously.&nbsp;</span></p>
<p>D-Plex Small RNA-seq Kit includes all buffers and enzymes necessary for the library preparation. Specific D-Plex Indexes were designed and validated to fit the D-Plex technology and are available separately:</p>
<p><strong>For D-Plex UDI library construction:</strong></p>
<ul style="list-style-type: disc;">
<li><a href="https://www.diagenode.com/en/p/D-Plex-24-Unique-Dual-Indexes-Set-A" title="D-Plex UDI Module - Set A" target="_blank"><span>C05030021</span>&nbsp;- D-Plex Unique Dual Indexes for Illumina - Set A</a></li>
<li><a href="https://www.diagenode.com/en/p/D-Plex-24-Unique-Dual-Indexes-Set-B" title="D-Plex UDI Module - Set B" target="_blank"><span>C05030022</span>&nbsp;- D-Plex Unique Dual Indexes for Illumina - Set B</a></li>
<li><a href="https://www.diagenode.com/en/p/D-Plex-24-Unique-Dual-Indexes-Set-C">C05030023 - D-Plex&nbsp;Unique Dual&nbsp;Indexes for Illumina - Set C</a></li>
<li><a href="https://www.diagenode.com/en/p/D-Plex-24-Unique-Dual-Indexes-Set-D">C05030024 - D-Plex&nbsp;Unique Dual&nbsp;Indexes for Illumina - Set D</a></li>
</ul>
<p><span>The use of UDI is highly recommended&nbsp;to mitigate errors introduced by read misassignment, including index&nbsp;hopping frequently observed with patterned flow cells such as Illumina&rsquo;s&nbsp;NovaSeq system.</span></p>
<p><strong>For D-Plex SI library construction:</strong></p>
<ul style="list-style-type: disc;">
<li><a href="https://www.diagenode.com/en/p/D-Plex-24-Single-Indexes-Set-A" title="D-Plex SI Module - Set A" target="_blank">C05030010 - D-Plex Single Indexes for Illumina - Set A</a></li>
<li><a href="https://www.diagenode.com/en/p/D-Plex-24-Single-Indexes-Set-B" title="D-Plex SI Module - Set B" target="_blank">C05030011 - D-Plex Single Indexes for Illumina - Set B</a></li>
</ul>
<p><strong>D-Plex is also available for MGI sequencing, check <a href="https://www.diagenode.com/en/p/d-plex-small-RNA-dnbseq-kit-x24" target="_blank">here</a>!</strong></p>
<p></p>
<p></p>
<p></p>
<center><strong>The D-Plex smRNA-seq is a versatile tool for a plethora of transciptomic analysis</strong></center>
<p></p>
<center><img src="https://www.diagenode.com/img/product/kits/dplex/versatile-circle.png" /></center>
<p></p>
<p>With low-input capability, accuracy and ability to incorporate different transcript classes independent of chemical moieties, the strong D-Plex library-preparation method can be included in various analysis workflows (i.e., ribosome profiling, genome-wide mapping of protein: RNA binding sites).</p>
<p></p>
<p></p>',
			'label1' => 'Characteristics and library prep. workflow ',
			'info1' => '<div class="row">
<div class="small-12 columns">
<p><strong>High library diversity for ultra-low inputs</strong></p>
<center><img src="https://www.diagenode.com/img/product/kits/dplex/dplex-diversity-fig1.png" /></center></div>
<div class="small-12 columns"><center><img src="https://www.diagenode.com/img/product/kits/dplex/dplex-fig2-captures.png" /></center></div>
</div>
<p></p>
<div class="row">
<div class="small-12 columns">
<p>D-Plex smRNA-seq captures the smRNA complexity of the sample in a sensitive manner. A large number of features is detected for each biotype at a CPM &ge;5, as shown above for different species.</p>
</div>
</div>
<p></p>
<p><strong>Accurate representation of the smRNA content of a sample</strong></p>
<div class="row">
<div class="small-6 columns"><center><img src="https://www.diagenode.com/img/product/kits/dplex/dplex-fig-ratplasma.png" /></center></div>
<div class="small-6 columns"><center><img src="https://www.diagenode.com/img/product/kits/dplex/dplex-fig-miRNAdistribution.png" /></center></div>
</div>
<div class="row">
<div class="small-6 columns">
<p><strong>Accurate identification of PCR duplicates in low-input samples using unique molecular identifiers (UMIs).</strong><br />The UMI read deduplication that is embedded in the D-Plex construct is used to avoid over-estimation of transcripts by identifying clones generated during the PCR amplification of the library. Despite limiting starting RNA input, the UMI correction removed technical copies of transcripts, maintaining the initial sample abundance.</p>
</div>
<div class="small-6 columns">
<p>D-Plex (template switching) technology enables recovery of the initial miRNA distribution of the miRXplore Universal Reference (Miltenyi Biotech Inc., Cat. No. 130-093-521). In contrast, ligation-based kits display a strong distortion of the miRNA equimolar distribution initially present in the pool, indicating sample incorporation bias.</p>
</div>
</div>
<p></p>
<p></p>
<div class="row">
<div class="small-6 columns"><center><img src="https://www.diagenode.com/img/product/kits/dplex/dplex-fig-foldchange.jpg" /></center></div>
<div class="small-6 columns"><strong>D-Plex smRNA-seq in association with the MGcount analysis correlates strongly (R&sup2; &gt; 0.8) with the RT-qPCR analysis, which is considered the gold-standard for accuracy. </strong><br />The figures shows a fold-change accuracy of a panel of 20 different small-RNA (figure taken from MGcount publication - Hita et al., BMC bioinformatics, 23-39(2022).</div>
</div>
<p></p>
<p></p>
<p><strong>Maximize information from the regulatory transcriptome using D-Plex small RNA-seq kit and MGcount*</strong></p>
<div class="row">
<div class="small-6 columns"><center><img src="https://www.diagenode.com/img/product/kits/dplex/dplex-fig-multialignments.png" /></center></div>
<div class="small-6 columns">By analyzing D-Plex dataset with MGcount, more reads are kept during the analysis, which ultimately preserves biological complexity linked to ncRNA expression without decreasing the accuracy of detection. <br /><span style="line-height: 1em;"><small>*Hita, A., Brocart, G., Fernandez, A. et al. MGcount: a total RNA-seq quantification tool to address multi-mapping and multi-overlapping alignments ambiguity in non-coding transcripts. BMC Bioinformatics 23, 39 (2022). <a href="https://doi.org/10.1186/s12859-021-04544-3">https://doi.org/10.1186/s12859-021-04544-3</a></small></span></div>
</div>
<p></p>
<p></p>
<div class="row">
<div class="small-12 columns">
<p>The D-Plex technology uses two innovative ligation-free mechanisms, <strong>poly(A) tailing and template switching</strong>, to produce sequencing libraries from ultra-low input amounts.</p>
</div>
</div>
<div class="row" style="background-color: #f5f5f5;">
<div class="small-12 columns"><br />
<p><strong>WORKFLOW</strong></p>
<center><img src="https://www.diagenode.com/img/product/kits/dplex/FL-Image-Workflow.jpg" width="50%" /></center></div>
<div class="small-12 columns">
<p style="text-align: justify; padding: 15px;"><br />RNA molecules are polyadenylated at the 3&rsquo;-end and primed with an oligo(dT) primer containing part of the ILMN 3&rsquo;-adapter sequence. The addition of a template-switching oligonucleotide during cDNA synthesis enables fusion of part of the ILMN 5&rsquo;-adapter during reverse transcription. After PCR, the library comprises double stranded DNA constructs that are ready for sequencing.</p>
</div>
</div>
<p><br /><br /></p>
<p></p>
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			'label2' => 'Data analysis',
			'info2' => '<p>A specific bioinformatics pipeline has been developed to process the special sequences present in the D-Plex construct, namely the UMI, the A-tail, and the template switch motif. All guidelines and free softwares are shared in the user manual. Subject to the compatibility of D-Plex constructs, other specific pipelines can be used.</p>
<p><img src="https://www.diagenode.com/img/product/kits/dplex/bioinfoPipe.png" alt="small RNA sequencing bioinformatics pipeline" caption="false" width="925" height="196" /></p>
<p>Need help for your bioinformatics analysis of miRNA?</p>
<p></p>
<div class="small-12 medium-3 large-3 columns"><center><a href="https://ccb-compute.cs.uni-saarland.de/mirmaster" target="_blank"><img src="https://www.diagenode.com/img/product/kits/dplex/miRMaster_logo.png" /></a></center>
<p>&nbsp;</p>
<p>&nbsp;</p>
</div>
<div class="small-12 medium-9 large-9 columns">
<p>Diagenode has collaborated with <strong>Andreas Keller</strong> and <strong>Tobias Fehlmann</strong> to develop a new bioinformatics pipeline for&nbsp;<span>the <strong>prediction of novel miRNAs</strong>.</span><br /><a href="https://ccb-compute.cs.uni-saarland.de/mirmaster" target="_blank"></a></p>
<ul>
<li style="text-align: justify;"><a href="https://ccb-compute.cs.uni-saarland.de/mirmaster2">miRMaster 2</a></li>
<li style="text-align: justify;"><a href="https://ccb-compute.cs.uni-saarland.de/mirmaster" target="_blank">miRMaster</a></li>
</ul>
</div>
<p>&nbsp;</p>
<p>&nbsp;</p>',
			'label3' => 'Data analysis - Counting using MGcount',
			'info3' => '<p>The counting or expression level calculation is the last step of the processing to generate an expression level matrix. We recommend using MGcount*, a counting tool developed at Diagenode with a suitable annotations file that include the small RNA transcripts that are object of study. MGcount, built on top of featureCounts, employs a flexible quantification approach to deal with datasets containing multiple RNA biotypes such as D-plex libraries. Non-coding RNAs varying in length, biogenesis, and function, may overlap in a genomic region, and are sometimes present in the genome with a high copy number. Consequently, reads may align equally well to more than one position in the reference genome or/and align to a position where more than one annotated transcript is located. MGcount employs two strategies to quantify these reads. Firstly, it assigns reads in rounds prioritizing small-RNAs over long-RNAs ensuring the unbiased read attribution to intergenic and intragenic small RNAs while preventing host-genes transcription over-estimation. Secondly, MGcount collapses loci where reads consistently multi-map into communities of loci with a graph-based approach. The resultant communities are groups of biologically related loci with nearly identical sequence. Subsequently, quantification of reads is performed at the loci-community level, reducing multi-alignments ambiguity at individual locus. Ultimately, this strategy maximizes the transcriptome information analysed and improves the interrogation of non-coding RNAs. MGcount software repository provides annotation files for A. thaliana, H. sapiens, M. musculus and C. elegans. The required input files for MGcount are a .txt file listing the paths to the alignment input files (.bam format) and the annotations file (.gtf format). The output directory path has to be provided as an input as well.</p>
<p><strong>Example command:</strong></p>
<p style="background-color: #f0f0f0;">MGcount -T 2 --gtf Homo_sapiens.GRCh38.gtf --outdir outputs --bam_infiles input_bamfilenames.txt</p>
<p>MGcount provides the choice to enable/disable the quantification of all RNA biotypes included in the annotation file in the form of "communities" as optional parameters for small-RNA (--ml_flag_small) and long-RNA (--ml_flag_long). Both are enabled by default. The main output of MGcount is the count_matrix.csv file containing an expression matrix that can be imported to R or any other software for downstream analyses.<br />A full user guide for MGCount is available here: <a href="https://filedn.com/lTnUWxFTA93JTyX3Hvbdn2h/mgcount/UserGuide.html">https://filedn.com/lTnUWxFTA93JTyX3Hvbdn2h/mgcount/UserGuide.html</a>.</p>
<p>Other standard counting tools such as featureCounts or HTSeq-counts can also be used alternatively. Given the high complexity of D-Plex libraries, we recommend having a clear understanding of the scientific question and the goal of the project before proceeding to the choice of the counting method as this will strongly impact downstream analyses. Diagenode provides bioinformatics support as a service (please, contact us if you need help with data analysis).</p>
<p>Notice that D-Plex produces forward-stranded data. Stranded libraries have the benefit that reads map to the genome strand where they were originated from. Therefore, when estimating transcript expression, reads aligned to the forward strand should be assigned only to transcript features in the forward strand whereas reads aligned to the reverse strand should be assigned only to transcript features in the reverse strand. For this, make sure you select &ldquo;stranded mode&rdquo; in any tool of choice. Stranded mode is selected by default in MGcount.</p>
<p><em><small>*Hita, A., Brocart, G., Fernandez, A. et al. MGcount: a total RNA-seq quantification tool to address multi-mapping and multi-overlapping alignments ambiguity in non-coding transcripts. BMC Bioinformatics 23, 39 (2022). <a href="https://doi.org/10.1186/s12859-021-04544-3">https://doi.org/10.1186/s12859-021-04544-3</a></small></em></p>',
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			'meta_title' => 'D-Plex Small RNA-seq Library Prep Kit | Diagenode ',
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			'meta_description' => 'Small RNA-seq library preparation for Illumina sequencing - Unique D-Plex technology - Optimized for ultra-low input (100 pg total RNA) - UMI reduce PCR biases - UDI detect index hopping - Compatibility with plasma samples - User-friendly and fast protocol',
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			'name' => 'D-Plex Small RNA DNBSEQ™ Kit for MGI Sequencing',
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<p></p>
<center><a class="chip diahome button" href="https://www.diagenode.com/files/products/kits/D-Plex-Small-RNA-DNBSEQ.pdf" target="_blank" title="D-Plex Small RNA DNBSEQ user manual"><strong>Download the manual</strong></a></center>
<p></p>
<p>D-Plex Small RNA DNBSEQ&trade; Kit is a tool designed for the study of the small non-coding transcriptome. The kit is using the <a href="https://www.diagenode.com/en/pages/dplex" target="_blank">D-Plex technology</a> to generate double-stranded DNA libraries ready to be used for the DNA single-strand circularization step required for DNBSEQ sequencing on MGI sequencers.</p>
<p>The D-Plex technology&nbsp;utilizes the innovative capture and amplification by&nbsp;tailing and switching, a&nbsp;ligation-free&nbsp;method for RNA library preparation from ultra-low input amounts, down to 10 pg for small RNAs and 100 pg for total RNAs.&nbsp;This innovative solution enables diverse and novel transcripts detection, even from challenging clinical samples such as liquid biopsies.</p>
<p><span>D-Plex Small&nbsp;RNA&nbsp;<span>DNBSEQ&trade;</span> Kit offers a time saving protocol that can be completed within 5 hours and requires minimal hands-on time.&nbsp;</span><span>The library preparation takes place in a&nbsp;</span><span>single tube</span><span>, increasing the efficiency tremendously.&nbsp;This ensures high technical&nbsp;reliability and reproducibility<span>.</span></span></p>
<p>D-Plex Small RNA DNBSEQ&trade; Kit includes all buffers and enzymes necessary for the library preparation. Specific D-Plex DNBSEQ Barcodes were designed and validated to fit the D-Plex technology and are available separately:</p>
<ul>
<li><a href="https://www.diagenode.com/en/p/d-plex-24-dnbseq-barcodes-set-a">C05030060 - D-Plex DNBSEQ Barcodes for MGI - Set A</a></li>
<li><a href="https://www.diagenode.com/en/p/d-plex-24-dnbseq-barcodes-set-b">C05030061 - D-Plex DNBSEQ Barcodes for MGI - Set B</a></li>
</ul>
<p><b><strong>D-Plex is also available for Illumina sequencing, check<span>&nbsp;</span><a href="https://www.diagenode.com/en/p/D-Plex-Small-RNA-seq-Library-Prep-x24" target="_blank">here</a>!</strong></b></p>
<div class="row">
<div class="carrousel" style="background-position: center;">
<div class="container">
<div class="row" style="background: rgba(255,255,255,0.1);">
<div class="large-12 columns slick">
<div>
<h3>Diverse and novel transcript detection</h3>
<div class="large-10 small-12 medium-10 large-centered medium-centered small-centered columns"><img style="height: 400px; display: block; margin-left: auto; margin-right: auto;" src="https://www.diagenode.com/img/product/kits/dplex/dplex-transcript.png" alt="small RNA library preparation for Illumina" /></div>
<div class="large-8 small-12 medium-6 large-centered medium-centered small-centered columns"><center>
<p style="text-align: justify;">The D-Plex Small RNA DNBSEQ protocol generates complex RNA libraries deciphering the wide diversity of small non-coding RNA spectrum (including miRNAs, snoRNAs, snRNAs)&nbsp; in human plasma samples.</p>
</center></div>
</div>
<div>
<h3>Ultra-low input performance</h3>
<div class="large-10 small-12 medium-10 large-centered medium-centered small-centered columns"><img style="height: 400px; display: block; margin-left: auto; margin-right: auto;" src="https://www.diagenode.com/img/product/kits/dplex/dplex-ultralow-input.png" alt="Ultra-low input performance" /></div>
<div class="large-8 small-12 medium-6 large-centered medium-centered small-centered columns"><center>
<p style="text-align: justify;">Sequencing data from circulating RNA samples of two input amounts (25 pg and 2.5 ng) were highly correlated (<i>R = 0.99</i>) when compared using Pearson correlation coefficient.</p>
</center></div>
</div>
<div>
<h3>High mapping efficiency</h3>
<div class="large-10 small-12 medium-10 large-centered medium-centered small-centered columns"><img style="height: 400px; display: block; margin-left: auto; margin-right: auto;" src="https://www.diagenode.com/img/product/kits/dplex/dplex-mapping.png" alt="High mapping efficiency" /></div>
<div class="large-8 small-12 medium-6 large-centered medium-centered small-centered columns"><center>
<p style="text-align: justify;"><b></b>The D-Plex Small RNA DNBSEQ kit is compatible with clinical-relevant samples, such as human plasma, and ultra low range of circulating RNA input (down to 10 pg) and exhibits good read mapping of sequencing reads (up to 70% mapping rate).</p>
</center></div>
</div>
<div>
<h3>High quality DNBSEQ sequencing solution</h3>
<div class="large-10 small-12 medium-10 large-centered medium-centered small-centered columns"><img style="height: 400px;" src="https://www.diagenode.com/img/product/kits/dplex/dplex-dnbseq.png" alt="High quality DNBSEQ sequencing solution" /></div>
<div class="large-8 small-12 medium-6 large-centered medium-centered small-centered columns"><center>
<p><b></b>The D-Plex Small RNA DNBSEQ kit combines our best-in-class RNA library preparation &ndash; D-Plex technology &ndash; with MGI&rsquo;s high-quality, cost-effective, DNA nanoballs &ndash; DNBSEQ &ndash; sequencing solution, creating a unified platform to support high quality small RNA sequencing.</p>
</center></div>
</div>
</div>
</div>
</div>
</div>
</div>
<script src="chrome-extension://hhojmcideegachlhfgfdhailpfhgknjm/web_accessible_resources/index.js"></script>',
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<li><strong>Latest innovation in RNA-seq</strong>:&nbsp;unique D-Plex technology&nbsp;offering ligation-free&nbsp;protocol for library preparation</li>
<li><strong>Ultra-low input capability</strong>: down to 10 pg for small RNAs and 100 pg for total RNAs</li>
<li><strong>High library complexity</strong>:<strong> </strong>obtain a complete view of&nbsp;your small RNA transcriptome</li>
<li><strong>Optimal performance on clinical samples</strong>: validated&nbsp;with circulating RNAs from liquid biopsies</li>
<li><strong>Easy to use with minimal hands-on time</strong>: one day, one tube protocol</li>
<li><strong>Highest sequencing quality</strong>: specifically formatted for MGI DNBSEQ&trade; sequencers</li>
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			'label2' => 'DNBSEQ Barcodes',
			'info2' => '<p>D-Plex DNBSEQ Barcodes are not included in the kit. Two sets are available separately:</p>
<ul style="list-style-type: disc;">
<li><a href="https://www.diagenode.com/en/p/d-plex-24-dnbseq-barcodes-set-a">C05030060 - D-Plex 24 DNBSEQ Barcodes for MGI - Set A</a></li>
<li><a href="https://www.diagenode.com/en/p/d-plex-24-dnbseq-barcodes-set-b">C05030061 - D-Plex 24 DNBSEQ Barcodes for MGI - Set B</a></li>
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			'meta_description' => 'Small RNA-seq library preparation with D-Plex technology - Suitable for MGI sequencing platforms - Optimized for ultra-low input (100 pg total RNA) - Compatibility with plasma samples - User-friendly and fast protocol',
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			'description' => '<div class="row">
<div class="small-12 medium-12 large-12 columns">
<p><span style="font-weight: 400;">Most of the major next-generation sequencing platforms require ligation of specific adaptor oligos to </span><a href="../applications/dna-rna-shearing"><span style="font-weight: 400;">fragmented DNA or RNA</span></a><span style="font-weight: 400;"> prior to sequencing</span></p>
<p><span style="font-weight: 400;">After input DNA has been fragmented, it is end-repaired and blunt-ended</span><span style="font-weight: 400;">. The next step is a A-tailing in which dAMP is added to the 3&acute; end of the blunt phosphorylated DNA fragments to prevent concatemerization and to allow the ligation of adaptors with complementary dT overhangs. In addition, barcoded adapters can be incorporated to facilitate multiplexing prior to or during amplification.</span></p>
<center><img src="https://www.diagenode.com/img/categories/library-prep/flux.png" /></center>
<p><span style="font-weight: 400;">Diagenode offers a comprehensive product portfolio for library preparation:<br /></span></p>
<strong><a href="https://www.diagenode.com/en/categories/Library-preparation-for-RNA-seq">D-Plex&nbsp;RNA-seq Library Preparation Kits</a></strong><br />
<p><span style="font-weight: 400;">Diagenode&rsquo;s new RNA-sequencing solutions utilize the innovative c</span><span style="font-weight: 400;">apture and a</span><span style="font-weight: 400;">mplification by t</span><span style="font-weight: 400;">ailing and s</span><span style="font-weight: 400;">witching&rdquo;</span><span style="font-weight: 400;">, a ligation-free method to produce DNA libraries for next generation sequencing from low input amounts of RNA. </span><span style="font-weight: 400;"></span><a href="../categories/Library-preparation-for-RNA-seq">Learn more</a></p>
<strong><a href="../categories/library-preparation-for-ChIP-seq">ChIP-seq and DNA sequencing library preparation solutions</a></strong><br />
<p><span style="font-weight: 400;">Our kits have been optimized for DNA library preparation used for next generation sequencing for a wide range of inputs. Using a simple three-step protocols, our</span><a href="http://www.diagenode.com/p/microplex-library-preparation-kit-v2-x12-12-indices-12-rxns"><span style="font-weight: 400;"> </span></a><span style="font-weight: 400;">kits are an optimal choice for library preparation from DNA inputs down to 50 pg.&nbsp;</span><a href="../categories/library-preparation-for-ChIP-seq">Learn more</a></p>
<a href="../p/bioruptor-pico-sonication-device"><span style="font-weight: 400;"></span><strong>Bioruptor Pico - short fragments</strong></a><a href="../categories/library-preparation-for-ChIP-seq-and-DNA-sequencing"><span style="font-weight: 400;"></span></a><br />
<p><span style="font-weight: 400;"></span><span style="font-weight: 400;">Our well-cited Bioruptor Pico is the shearing device of choice for chromatin and DNA fragmentation. Obtain uniform and tight fragment distributions &nbsp;between 150bp -2kb. </span><a href="../p/bioruptor-pico-sonication-device">Learn more</a></p>
<strong><a href="../p/megaruptor2-1-unit"><span href="../p/bioruptor-pico-sonication-device">Megaruptor</span>&reg; - long fragments</a></strong><a href="../p/bioruptor-pico-sonication-device"><span style="font-weight: 400;"></span></a><a href="../categories/library-preparation-for-ChIP-seq-and-DNA-sequencing"><span style="font-weight: 400;"></span></a><br />
<p><span style="font-weight: 400;"></span><span style="font-weight: 400;">The Megaruptor is designed to shear DNA from 3kb-75kb for long-read sequencing.&nbsp; <a href="../p/megaruptor2-1-unit">Learn more</a></span></p>
<span href="../p/bioruptor-pico-sonication-device"></span><span style="font-weight: 400;"></span></div>
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			'description' => '<p style="text-align: left;"><em><strong>Note:</strong><span>&nbsp;</span>The D-Plex Small RNA-seq Kit manual describes the protocol for&nbsp;both UDI and SI library constructions.</em></p>',
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			'name' => 'Functional microRNA targetome undergoes degeneration-induced shift in the retina',
			'authors' => 'Chu-Tan JA et al.',
			'description' => '<div class="abstract-content selected" id="enc-abstract">
<p><strong class="sub-title">Background:<span>&nbsp;</span></strong>MicroRNA (miRNA) play a significant role in the pathogenesis of complex neurodegenerative diseases including age-related macular degeneration (AMD), acting as post-transcriptional gene suppressors through their association with argonaute 2 (AGO2) - a key member of the RNA Induced Silencing Complex (RISC). Identifying the retinal miRNA/mRNA interactions in health and disease will provide important insight into the key pathways miRNA regulate in disease pathogenesis and may lead to potential therapeutic targets to mediate retinal degeneration.</p>
<p><strong class="sub-title">Methods:<span>&nbsp;</span></strong>To identify the active miRnome targetome interactions in the healthy and degenerating retina, AGO2 HITS-CLIP was performed using a rodent model of photoreceptor degeneration. Analysis of publicly available single-cell RNA sequencing (scRNAseq) data was performed to identify the cellular location of AGO2 and key members of the microRNA targetome in the retina. AGO2 findings were verified by in situ hybridization (RNA) and immunohistochemistry (protein).</p>
<p><strong class="sub-title">Results:<span>&nbsp;</span></strong>Analysis revealed a similar miRnome between healthy and damaged retinas, however, a shift in the active targetome was observed with an enrichment of miRNA involvement in inflammatory pathways. This shift was further demonstrated by a change in the seed binding regions of miR-124-3p, the most abundant retinal AGO2-bound miRNA, and has known roles in regulating retinal inflammation. Additionally, photoreceptor cluster miR-183/96/182 were all among the most highly abundant miRNA bound to AGO2. Following damage, AGO2 expression was localized to the inner retinal layers and more in the OLM than in healthy retinas, indicating a locational miRNA response to retinal damage.</p>
<p><strong class="sub-title">Conclusions:<span>&nbsp;</span></strong>This study provides important insight into the alteration of miRNA regulatory activity that occurs as a response to retinal degeneration and explores the miRNA-mRNA targetome as a consequence of retinal degenerations. Further characterisation of these miRNA/mRNA interactions in the context of the degenerating retina may provide an important insight into the active role these miRNA may play in diseases such as AMD.</p>
</div>
<p><strong class="sub-title">Keywords:<span>&nbsp;</span></strong>Argonaute; HITS-CLIP; Inflammation; Retina; Retinal degeneration; Transcriptome; mRNA; microRNA.</p>',
			'date' => '2021-08-31',
			'pmid' => 'https://pubmed.ncbi.nlm.nih.gov/34465369/',
			'doi' => '10.1186/s13024-021-00478-9',
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			'name' => 'Repeat RNAs associate with replication forks and post-replicative DNA.',
			'authors' => 'Gylling HM, Gonzalez-Aguilera C, Smith MA, Kaczorowski DC, Groth A, Lund AH',
			'description' => '<p>Non-coding RNA has a proven ability to direct and regulate chromatin modifications by acting as scaffolds between DNA and histone-modifying complexes. However, it is unknown if ncRNA plays any role in DNA replication and epigenome maintenance, including histone eviction and re-instalment of histone-modifications after genome duplication. Isolation of nascent chromatin has identified a large number of RNA-binding proteins in addition to unknown components of the replication and epigenetic maintenance machinery. Here, we isolated and characterized long and short RNAs associated with nascent chromatin at active replication forks and track RNA composition during chromatin maturation across the cell cycle. Shortly after fork passage, GA-rich-, Alpha- and TElomeric Repeat-containing RNAs (TERRA) are associated with replicated DNA. These repeat containing RNAs arise from loci undergoing replication, suggesting an interaction in cis. Post-replication during chromatin maturation, and even after mitosis in G1, the repeats remain enriched on DNA. This suggests that specific types of repeat RNAs are transcribed shortly after DNA replication and stably associate with their loci of origin throughout cell cycle. The presented method and data enables studies of RNA interactions with replication forks and post-replicative chromatin and provides insights into how repeat RNAs and their engagement with chromatin are regulated with respect to DNA replication and across the cell cycle.</p>',
			'date' => '2020-05-11',
			'pmid' => 'http://www.pubmed.gov/32393525',
			'doi' => '10.1261/rna.074757.120',
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			'name' => 'Multisite Evaluation of Next-Generation Methods for Small RNA Quantification.',
			'authors' => 'Herbert ZT, Thimmapuram J, Xie S, Kershner JP, Kolling FW, Ringelberg CS, LeClerc A, Alekseyev YO, Fan J, Podnar JW, Stevenson HS, Sommerville G, Gupta S, Berkeley M, Koeman J, Perera A, Scott AR, Grenier JK, Malik J, Ashton JM, Pivarski KL, Wang X, Kuffe',
			'description' => '<p>Small RNAs (smRNAs) are important regulators of many biologic processes and are now most frequently characterized using Illumina sequencing. However, although standard RNA sequencing library preparation has become routine in most sequencing facilities, smRNA sequencing library preparation has historically been challenging because of high input requirements, laborious protocols involving gel purifications, inability to automate, and a lack of benchmarking standards. Additionally, studies have suggested that many of these methods are nonlinear and do not accurately reflect the amounts of smRNAs . Recently, a number of new kits have become available that permit lower input amounts and less laborious, gel-free protocol options. Several of these new kits claim to reduce RNA ligase-dependent sequence bias through novel adapter modifications and to lessen adapter-dimer contamination in the resulting libraries. With the increasing number of smRNA kits available, understanding the relative strengths of each method is crucial for appropriate experimental design. In this study, we systematically compared 9 commercially available smRNA library preparation kits as well as NanoString probe hybridization across multiple study sites. Although several of the new methodologies do reduce the amount of artificially over- and underrepresented microRNAs (miRNAs), we observed that none of the methods was able to remove all of the bias in the library preparation. Identical samples prepared with different methods show highly varied levels of different miRNAs. Even so, many methods excelled in ease of use, lower input requirement, fraction of usable reads, and reproducibility across sites. These differences may help users select the most appropriate methods for their specific question of interest.</p>',
			'date' => '2020-01-10',
			'pmid' => 'http://www.pubmed.gov/31966025',
			'doi' => '10.7171/jbt.20-3102-001',
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			'name' => 'Circulating miRNA analysis for cancer diagnostics and therapy.',
			'authors' => 'Valihrach L, Androvic P, Kubista M',
			'description' => '<p>Successful treatment of cancer depends on early diagnosis and effective monitoring of patients' response to therapy. Traditional tools based on tumor biopsies lack the sensitivity and specificity to capture cancer development in its early phases and are not applicable for continuous monitoring. To overcome these barriers, liquid biopsies have been introduced as a minimally invasive and cost-efficient means of diagnosis with high level of specificity and sensitivity. Traditionally, liquid biopsy markers include circulating tumor cells and circulating tumor DNA. During the last decade, a new promising group of biomarkers has appeared and its utilization for cancer diagnosis and monitoring is intensively studied - the microRNAs (miRNAs). In this review, we provide a comprehensive overview of circulating miRNA analysis. We highlight the importance of sampling and quality control, discuss the technical aspects of miRNA extraction and quantification, summarize recommendations for downstream analysis and conclude with future perspectives. Taken together, we present the current state of knowledge in the field of miRNA analysis in liquid biopsies and the expected development and standardization.</p>',
			'date' => '2019-10-18',
			'pmid' => 'http://www.pubmed.gov/31635843',
			'doi' => '10.1016/j.mam.2019.10.002',
			'modified' => '2019-12-05 11:07:26',
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			'id' => '3697',
			'name' => 'The sncRNA Zoo: a repository for circulating small noncoding RNAs in animals.',
			'authors' => 'Fehlmann T, Backes C, Pirritano M, Laufer T, Galata V, Kern F, Kahraman M, Gasparoni G, Ludwig N, Lenhof HP, Gregersen HA, Francke R, Meese E, Simon M, Keller A',
			'description' => '<p>The repertoire of small noncoding RNAs (sncRNAs), particularly miRNAs, in animals is considered to be evolutionarily conserved. Studies on sncRNAs are often largely based on homology-based information, relying on genomic sequence similarity and excluding actual expression data. To obtain information on sncRNA expression (including miRNAs, snoRNAs, YRNAs and tRNAs), we performed low-input-volume next-generation sequencing of 500&nbsp;pg of RNA from 21 animals at two German zoological gardens. Notably, none of the species under investigation were previously annotated in any miRNA reference database. Sequencing was performed on blood cells as they are amongst the most accessible, stable and abundant sources of the different sncRNA classes. We evaluated and compared the composition and nature of sncRNAs across the different species by computational approaches. While the distribution of sncRNAs in the different RNA classes varied significantly, general evolutionary patterns were maintained. In particular, miRNA sequences and expression were found to be even more conserved than previously assumed. To make the results available for other researchers, all data, including expression profiles at the species and family levels, and different tools for viewing, filtering and searching the data are freely available in the online resource ASRA (Animal sncRNA Atlas) at https://www.ccb.uni-saarland.de/asra/.</p>',
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			'date' => '2019-03-01',
			'pmid' => 'http://www.pubmed.gov/30709501',
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			'description' => '<p><span>Circulating miRNAs are favored for biomarker candidates as they can reflect tissue specific miRNA dysregulation in disease contexts. Moreover, they have additional advantages that they can be monitored in a minimal invasive manner. Blood-borne miRNAs are therefore currently characterized to identify, describe and validate their potential suitability for a biomarker, however, sampling and as well miRNA detection methods limit these studies in terms of sensitivity but also practicability in clinical, at-home or low-resource sampling of high quality circulating RNA samples. We describe here a novel and innovative method of circulating RNA microsampling from minimal volume dried blood spots with direct enrichment for small RNA fractions in combination with ligation free library preparation. We evaluated crucial parameters for efficient library preparation from low RNA inputs of 50pg for efficient dissection not only of miRNAs but also isomiRs, piRNAs, and lincRNAs. We compared these data to classical microarrays and characterize the technical reproducibility and its sensitivity. We demonstrate and evaluate a method for easy low resource sampling and NGS analysis of circulating RNAs providing a powerful tool for massive cohort and remote patient monitoring.</span></p>',
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<center><a class="chip diahome button" href="https://www.diagenode.com/files/products/kits/D-Plex-Small-RNA-DNBSEQ.pdf" target="_blank" title="D-Plex Small RNA DNBSEQ user manual"><strong>Download the manual</strong></a></center>
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<p>D-Plex Small RNA DNBSEQ&trade; Kit is a tool designed for the study of the small non-coding transcriptome. The kit is using the <a href="https://www.diagenode.com/en/pages/dplex" target="_blank">D-Plex technology</a> to generate double-stranded DNA libraries ready to be used for the DNA single-strand circularization step required for DNBSEQ sequencing on MGI sequencers.</p>
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<p>D-Plex Small RNA DNBSEQ&trade; Kit includes all buffers and enzymes necessary for the library preparation. Specific D-Plex DNBSEQ Barcodes were designed and validated to fit the D-Plex technology and are available separately:</p>
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<li><a href="https://www.diagenode.com/en/p/d-plex-24-dnbseq-barcodes-set-a">C05030060 - D-Plex DNBSEQ Barcodes for MGI - Set A</a></li>
<li><a href="https://www.diagenode.com/en/p/d-plex-24-dnbseq-barcodes-set-b">C05030061 - D-Plex DNBSEQ Barcodes for MGI - Set B</a></li>
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<p><b><strong>D-Plex is also available for Illumina sequencing, check<span>&nbsp;</span><a href="https://www.diagenode.com/en/p/D-Plex-Small-RNA-seq-Library-Prep-x24" target="_blank">here</a>!</strong></b></p>
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<p style="text-align: justify;">The D-Plex Small RNA DNBSEQ protocol generates complex RNA libraries deciphering the wide diversity of small non-coding RNA spectrum (including miRNAs, snoRNAs, snRNAs)&nbsp; in human plasma samples.</p>
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<p style="text-align: justify;"><b></b>The D-Plex Small RNA DNBSEQ kit is compatible with clinical-relevant samples, such as human plasma, and ultra low range of circulating RNA input (down to 10 pg) and exhibits good read mapping of sequencing reads (up to 70% mapping rate).</p>
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<p><b></b>The D-Plex Small RNA DNBSEQ kit combines our best-in-class RNA library preparation &ndash; D-Plex technology &ndash; with MGI&rsquo;s high-quality, cost-effective, DNA nanoballs &ndash; DNBSEQ &ndash; sequencing solution, creating a unified platform to support high quality small RNA sequencing.</p>
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	'modified' => '2018-12-31 11:32:28',
	'created' => '2018-09-20 11:18:35',
	'ProductsPublication' => array(
		'id' => '2823',
		'product_id' => '2845',
		'publication_id' => '3387'
	)
)
$externalLink = ' <a href="https://www.ncbi.nlm.nih.gov/pubmed/?term=NGS+analysis+of+total+small+non+coding+RNAs+from+low+input+RNA+from+dried+blood+sampling" target="_blank"><i class="fa fa-external-link"></i></a>'
include - APP/View/Products/view.ctp, line 755
View::_evaluate() - CORE/Cake/View/View.php, line 971
View::_render() - CORE/Cake/View/View.php, line 933
View::render() - CORE/Cake/View/View.php, line 473
Controller::render() - CORE/Cake/Controller/Controller.php, line 963
ProductsController::slug() - APP/Controller/ProductsController.php, line 1052
ReflectionMethod::invokeArgs() - [internal], line ??
Controller::invokeAction() - CORE/Cake/Controller/Controller.php, line 491
Dispatcher::_invoke() - CORE/Cake/Routing/Dispatcher.php, line 193
Dispatcher::dispatch() - CORE/Cake/Routing/Dispatcher.php, line 167
[main] - APP/webroot/index.php, line 118

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