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<p> The iDeal ChIP-seq kit for Histones<strong> </strong>is perfect for <strong>cells</strong> (<strong>100,000 cells</strong> to <strong>1,000,000 cells</strong> per IP) and has been validated for <strong>tissues</strong> (<strong>1.5 mg</strong> to <strong>5 mg</strong> of tissue per IP).</p>
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'description' => '<p>Don’t risk wasting your precious sequencing samples. Diagenode’s validated <strong>iDeal ChIP-seq kit for Histones</strong> has everything you need for a successful start-to-finish <strong>ChIP of histones prior to Next-Generation Sequencing</strong>. The complete kit contains all buffers and reagents for cell lysis, chromatin shearing, immunoprecipitation and DNA purification. In addition, unlike competing solutions, the kit contains positive and negative control antibodies (H3K4me3 and IgG, respectively) as well as positive and negative control PCR primers pairs (GAPDH TSS and Myoglobin exon 2, respectively) for your convenience and a guarantee of optimal results. The kit has been validated on multiple histone marks.</p>
<p> The iDeal ChIP-seq kit for Histones<strong> </strong>is perfect for <strong>cells</strong> (<strong>100,000 cells</strong> to <strong>1,000,000 cells</strong> per IP) and has been validated for <strong>tissues</strong> (<strong>1.5 mg</strong> to <strong>5 mg</strong> of tissue per IP).</p>
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<li>Highly <strong>optimized</strong> protocol for ChIP-seq from cells and tissues</li>
<li><strong>Validated</strong> for ChIP-seq with multiple histones marks</li>
<li>Most <strong>complete</strong> kit available (covers all steps, including the control antibodies and primers)</li>
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<li>Magnetic beads make ChIP easy, fast and more <strong>reproducible</strong></li>
<li>Combination with Diagenode ChIP-seq antibodies provides high yields with excellent <strong>specificity</strong> and <strong>sensitivity</strong></li>
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<p>Note: to obtain optimal results, this kit should be used in combination with the DiaMag1.5 - magnetic rack.</p>
<h3>ChIP-seq on cells</h3>
<p><img src="https://www.diagenode.com/img/product/kits/iDeal-kit-C01010053-figure-1.jpg" alt="Figure 1A" style="display: block; margin-left: auto; margin-right: auto;" /></p>
<p><strong>Figure 1A. The high consistency of the iDeal ChIP-seq kit on the Ion Torrent™ PGM™ (Life Technologies) and GAIIx (Illumina<sup>®</sup>)</strong><br /> ChIP was performed on sheared chromatin from 1 million HelaS3 cells using the iDeal ChIP-seq kit and 1 µg of H3K4me3 positive control antibody. Two different biological samples have been analyzed using two different sequencers - GAIIx (Illumina<sup>®</sup>) and PGM™ (Ion Torrent™). The expected ChIP-seq profile for H3K4me3 on the GAPDH promoter region has been obtained.<br /> Image A shows a several hundred bp along chr12 with high similarity of read distribution despite the radically different sequencers. Image B is a close capture focusing on the GAPDH that shows that even the peak structure is similar.</p>
<p class="text-center"><strong>Perfect match between ChIP-seq data obtained with the iDeal ChIP-seq workflow and reference dataset</strong></p>
<p><img src="https://www.diagenode.com/img/product/kits/perfect-match-between-chipseq-data.png" alt="Figure 1B" style="display: block; margin-left: auto; margin-right: auto;" /></p>
<p><strong>Figure 1B.</strong> The ChIP-seq dataset from this experiment has been compared with a reference dataset from the Broad Institute. We observed a perfect match between the top 40% of Diagenode peaks and the reference dataset. Based on the NIH Encode project criterion, ChIP-seq results are considered reproducible between an original and reproduced dataset if the top 40% of peaks have at least an 80% overlap ratio with the compared dataset.</p>
<p><img src="https://www.diagenode.com/img/product/kits/iDeal-kit-C01010053-figure-2.jpg" alt="Figure 2" style="display: block; margin-left: auto; margin-right: auto;" /></p>
<p><strong>Figure 2. Efficient and easy chromatin shearing using the Bioruptor<sup>®</sup> and Shearing buffer iS1 from the iDeal ChIP-seq kit</strong><br /> Chromatin from 1 million of Hela cells was sheared using the Bioruptor<sup>®</sup> combined with the Bioruptor<sup>®</sup> Water cooler (Cat No. BioAcc-cool) during 3 rounds of 10 cycles of 30 seconds “ON” / 30 seconds “OFF” at HIGH power setting (position H). Diagenode 1.5 ml TPX tubes (Cat No. M-50001) were used for chromatin shearing. Samples were gently vortexed before and after performing each sonication round (rounds of 10 cycles), followed by a short centrifugation at 4°C to recover the sample volume at the bottom of the tube. The sheared chromatin was then decross-linked as described in the kit manual and analyzed by agarose gel electrophoresis.</p>
<p><img src="https://www.diagenode.com/img/product/kits/iDeal-kit-C01010053-figure-3.jpg" alt="Figure 3" style="display: block; margin-left: auto; margin-right: auto;" width="264" height="320" /></p>
<p><strong>Figure 3. Validation of ChIP by qPCR: reliable results using Diagenode’s ChIP-seq grade H3K4me3 antibody, isotype control and sets of validated primers</strong><br /> Specific enrichment on positive loci (GAPDH, EIF4A2, c-fos promoter regions) comparing to no enrichment on negative loci (TSH2B promoter region and Myoglobin exon 2) was detected by qPCR. Samples were prepared using the Diagenode iDeal ChIP-seq kit. Diagenode ChIP-seq grade antibody against H3K4me3 and the corresponding isotype control IgG were used for immunoprecipitation. qPCR amplification was performed with sets of validated primers.</p>
<h3>ChIP-seq on tissue</h3>
<p><img src="https://www.diagenode.com/img/product/kits/ideal-figure-h3k4me3.jpg" alt="Figure 4A" style="display: block; margin-left: auto; margin-right: auto;" /></p>
<p><strong>Figure 4A.</strong> Chromatin Immunoprecipitation has been performed using chromatin from mouse liver tissue, the iDeal ChIP-seq kit for Histones and the Diagenode ChIP-seq-grade H3K4me3 (Cat. No. C15410003) antibody. The IP'd DNA was subsequently analysed on an Illumina® HiSeq. Library preparation, cluster generation and sequencing were performed according to the manufacturer's instructions. This figure shows the peak distribution in a region surrounding the GAPDH positive control gene.</p>
<p><img src="https://www.diagenode.com/img/product/kits/match-of-the-top40-peaks-2.png" alt="Figure 4B" caption="false" style="display: block; margin-left: auto; margin-right: auto;" width="700" height="280" /></p>
<p><strong>Figure 4B.</strong> The ChIP-seq dataset from this experiment has been compared with a reference dataset from the Broad Institute. We observed a perfect match between the top 40% of Diagenode peaks and the reference dataset. Based on the NIH Encode project criterion, ChIP-seq results are considered reproducible between an original and reproduced dataset if the top 40% of peaks have at least an 80% overlap ratio with the compared dataset.</p>',
'label2' => 'Species, cell lines, tissues tested',
'info2' => '<p>The iDeal ChIP-seq Kit for Histones is compatible with a broad variety of cell lines, tissues and species - some examples are shown below. Other species / cell lines / tissues can be used with this kit.</p>
<p><u>Cell lines:</u></p>
<p>Human: A549, A673, CD8+ T, Blood vascular endothelial cells, Lymphatic endothelial cells, fibroblasts, K562, MDA-MB231</p>
<p>Pig: Alveolar macrophages</p>
<p>Mouse: C2C12, primary HSPC, synovial fibroblasts, HeLa-S3, FACS sorted cells from embryonic kidneys, macrophages, mesodermal cells, myoblasts, NPC, salivary glands, spermatids, spermatocytes, skeletal muscle stem cells, stem cells, Th2</p>
<p>Hamster: CHO</p>
<p>Other cell lines / species: compatible, not tested</p>
<p><u>Tissues</u></p>
<p>Bee – brain</p>
<p>Daphnia – whole animal</p>
<p>Horse – brain, heart, lamina, liver, lung, skeletal muscles, ovary</p>
<p>Human – Erwing sarcoma tumor samples</p>
<p>Other tissues: compatible, not tested</p>
<p>Did you use the iDeal ChIP-seq for Histones Kit on other cell line / tissue / species? <a href="mailto:agnieszka.zelisko@diagenode.com?subject=Species, cell lines, tissues tested with the iDeal ChIP-seq Kit for TF&body=Dear Customer,%0D%0A%0D%0APlease, leave below your feedback about the iDeal ChIP-seq for Transcription Factors (cell / tissue type, species, other information...).%0D%0A%0D%0AThank you for sharing with us your experience !%0D%0A%0D%0ABest regards,%0D%0A%0D%0AAgnieszka Zelisko-Schmidt, PhD">Let us know!</a></p>',
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<p>Don’t risk wasting your precious sequencing samples. Diagenode’s validated <strong>iDeal ChIP-seq kit for Histones</strong> has everything you need for a successful start-to-finish <strong>ChIP of histones prior to Next-Generation Sequencing</strong>. The complete kit contains all buffers and reagents for cell lysis, chromatin shearing, immunoprecipitation and DNA purification. In addition, unlike competing solutions, the kit contains positive and negative control antibodies (H3K4me3 and IgG, respectively) as well as positive and negative control PCR primers pairs (GAPDH TSS and Myoglobin exon 2, respectively) for your convenience and a guarantee of optimal results. The kit has been validated on multiple histone marks.</p>
<p> The iDeal ChIP-seq kit for Histones<strong> </strong>is perfect for <strong>cells</strong> (<strong>100,000 cells</strong> to <strong>1,000,000 cells</strong> per IP) and has been validated for <strong>tissues</strong> (<strong>1.5 mg</strong> to <strong>5 mg</strong> of tissue per IP).</p>
<p> The iDeal ChIP-seq kit is the only kit on the market validated for the major sequencing systems. Our expertise in ChIP-seq tools allows reproducible and efficient results every time.</p>
<p></p>
<p> <strong></strong></p>
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<li>Highly <strong>optimized</strong> protocol for ChIP-seq from cells and tissues</li>
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<li>Most <strong>complete</strong> kit available (covers all steps, including the control antibodies and primers)</li>
<li>Optimized chromatin preparation in combination with the Bioruptor ensuring the best <strong>epitope integrity</strong></li>
<li>Magnetic beads make ChIP easy, fast and more <strong>reproducible</strong></li>
<li>Combination with Diagenode ChIP-seq antibodies provides high yields with excellent <strong>specificity</strong> and <strong>sensitivity</strong></li>
<li>Purified DNA suitable for any downstream application</li>
<li>Easy-to-follow protocol</li>
</ul>
<p>Note: to obtain optimal results, this kit should be used in combination with the DiaMag1.5 - magnetic rack.</p>
<h3>ChIP-seq on cells</h3>
<p><img src="https://www.diagenode.com/img/product/kits/iDeal-kit-C01010053-figure-1.jpg" alt="Figure 1A" style="display: block; margin-left: auto; margin-right: auto;" /></p>
<p><strong>Figure 1A. The high consistency of the iDeal ChIP-seq kit on the Ion Torrent™ PGM™ (Life Technologies) and GAIIx (Illumina<sup>®</sup>)</strong><br /> ChIP was performed on sheared chromatin from 1 million HelaS3 cells using the iDeal ChIP-seq kit and 1 µg of H3K4me3 positive control antibody. Two different biological samples have been analyzed using two different sequencers - GAIIx (Illumina<sup>®</sup>) and PGM™ (Ion Torrent™). The expected ChIP-seq profile for H3K4me3 on the GAPDH promoter region has been obtained.<br /> Image A shows a several hundred bp along chr12 with high similarity of read distribution despite the radically different sequencers. Image B is a close capture focusing on the GAPDH that shows that even the peak structure is similar.</p>
<p class="text-center"><strong>Perfect match between ChIP-seq data obtained with the iDeal ChIP-seq workflow and reference dataset</strong></p>
<p><img src="https://www.diagenode.com/img/product/kits/perfect-match-between-chipseq-data.png" alt="Figure 1B" style="display: block; margin-left: auto; margin-right: auto;" /></p>
<p><strong>Figure 1B.</strong> The ChIP-seq dataset from this experiment has been compared with a reference dataset from the Broad Institute. We observed a perfect match between the top 40% of Diagenode peaks and the reference dataset. Based on the NIH Encode project criterion, ChIP-seq results are considered reproducible between an original and reproduced dataset if the top 40% of peaks have at least an 80% overlap ratio with the compared dataset.</p>
<p><img src="https://www.diagenode.com/img/product/kits/iDeal-kit-C01010053-figure-2.jpg" alt="Figure 2" style="display: block; margin-left: auto; margin-right: auto;" /></p>
<p><strong>Figure 2. Efficient and easy chromatin shearing using the Bioruptor<sup>®</sup> and Shearing buffer iS1 from the iDeal ChIP-seq kit</strong><br /> Chromatin from 1 million of Hela cells was sheared using the Bioruptor<sup>®</sup> combined with the Bioruptor<sup>®</sup> Water cooler (Cat No. BioAcc-cool) during 3 rounds of 10 cycles of 30 seconds “ON” / 30 seconds “OFF” at HIGH power setting (position H). Diagenode 1.5 ml TPX tubes (Cat No. M-50001) were used for chromatin shearing. Samples were gently vortexed before and after performing each sonication round (rounds of 10 cycles), followed by a short centrifugation at 4°C to recover the sample volume at the bottom of the tube. The sheared chromatin was then decross-linked as described in the kit manual and analyzed by agarose gel electrophoresis.</p>
<p><img src="https://www.diagenode.com/img/product/kits/iDeal-kit-C01010053-figure-3.jpg" alt="Figure 3" style="display: block; margin-left: auto; margin-right: auto;" width="264" height="320" /></p>
<p><strong>Figure 3. Validation of ChIP by qPCR: reliable results using Diagenode’s ChIP-seq grade H3K4me3 antibody, isotype control and sets of validated primers</strong><br /> Specific enrichment on positive loci (GAPDH, EIF4A2, c-fos promoter regions) comparing to no enrichment on negative loci (TSH2B promoter region and Myoglobin exon 2) was detected by qPCR. Samples were prepared using the Diagenode iDeal ChIP-seq kit. Diagenode ChIP-seq grade antibody against H3K4me3 and the corresponding isotype control IgG were used for immunoprecipitation. qPCR amplification was performed with sets of validated primers.</p>
<h3>ChIP-seq on tissue</h3>
<p><img src="https://www.diagenode.com/img/product/kits/ideal-figure-h3k4me3.jpg" alt="Figure 4A" style="display: block; margin-left: auto; margin-right: auto;" /></p>
<p><strong>Figure 4A.</strong> Chromatin Immunoprecipitation has been performed using chromatin from mouse liver tissue, the iDeal ChIP-seq kit for Histones and the Diagenode ChIP-seq-grade H3K4me3 (Cat. No. C15410003) antibody. The IP'd DNA was subsequently analysed on an Illumina® HiSeq. Library preparation, cluster generation and sequencing were performed according to the manufacturer's instructions. This figure shows the peak distribution in a region surrounding the GAPDH positive control gene.</p>
<p><img src="https://www.diagenode.com/img/product/kits/match-of-the-top40-peaks-2.png" alt="Figure 4B" caption="false" style="display: block; margin-left: auto; margin-right: auto;" width="700" height="280" /></p>
<p><strong>Figure 4B.</strong> The ChIP-seq dataset from this experiment has been compared with a reference dataset from the Broad Institute. We observed a perfect match between the top 40% of Diagenode peaks and the reference dataset. Based on the NIH Encode project criterion, ChIP-seq results are considered reproducible between an original and reproduced dataset if the top 40% of peaks have at least an 80% overlap ratio with the compared dataset.</p>',
'label2' => 'Species, cell lines, tissues tested',
'info2' => '<p>The iDeal ChIP-seq Kit for Histones is compatible with a broad variety of cell lines, tissues and species - some examples are shown below. Other species / cell lines / tissues can be used with this kit.</p>
<p><u>Cell lines:</u></p>
<p>Human: A549, A673, CD8+ T, Blood vascular endothelial cells, Lymphatic endothelial cells, fibroblasts, K562, MDA-MB231</p>
<p>Pig: Alveolar macrophages</p>
<p>Mouse: C2C12, primary HSPC, synovial fibroblasts, HeLa-S3, FACS sorted cells from embryonic kidneys, macrophages, mesodermal cells, myoblasts, NPC, salivary glands, spermatids, spermatocytes, skeletal muscle stem cells, stem cells, Th2</p>
<p>Hamster: CHO</p>
<p>Other cell lines / species: compatible, not tested</p>
<p><u>Tissues</u></p>
<p>Bee – brain</p>
<p>Daphnia – whole animal</p>
<p>Horse – brain, heart, lamina, liver, lung, skeletal muscles, ovary</p>
<p>Human – Erwing sarcoma tumor samples</p>
<p>Other tissues: compatible, not tested</p>
<p>Did you use the iDeal ChIP-seq for Histones Kit on other cell line / tissue / species? <a href="mailto:agnieszka.zelisko@diagenode.com?subject=Species, cell lines, tissues tested with the iDeal ChIP-seq Kit for TF&body=Dear Customer,%0D%0A%0D%0APlease, leave below your feedback about the iDeal ChIP-seq for Transcription Factors (cell / tissue type, species, other information...).%0D%0A%0D%0AThank you for sharing with us your experience !%0D%0A%0D%0ABest regards,%0D%0A%0D%0AAgnieszka Zelisko-Schmidt, PhD">Let us know!</a></p>',
'label3' => ' Additional solutions compatible with iDeal ChIP-seq Kit for Histones',
'info3' => '<p><a href="../p/chromatin-shearing-optimization-kit-low-sds-100-million-cells">Chromatin EasyShear Kit - Ultra Low SDS </a>optimizes chromatin shearing, a critical step for ChIP.</p>
<p> The <a href="https://www.diagenode.com/en/categories/library-preparation-for-ChIP-seq">MicroPlex Library Preparation Kit </a>provides easy and optimal library preparation of ChIPed samples.</p>
<p><a href="../categories/chip-seq-grade-antibodies">ChIP-seq grade anti-histone antibodies</a> provide high yields with excellent specificity and sensitivity.</p>
<p> Plus, for our IP-Star Automation users for automated ChIP, check out our <a href="../p/auto-ideal-chip-seq-kit-for-histones-x24-24-rxns">automated</a> version of this kit.</p>',
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'name' => 'iDeal ChIP-seq kit for Transcription Factors',
'description' => '<p><a href="https://www.diagenode.com/files/products/kits/ideal-chipseq-transcription-factors-x10-manual.pdf"><img src="https://www.diagenode.com/img/buttons/bt-manual.png" /></a></p>
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<p><span style="font-weight: 400;">Diagenode’s <strong>iDeal ChIP-seq Kit for Transcription Factors</strong> is a highly validated solution for robust transcription factor and other non-histone proteins ChIP-seq results and contains everything you need for start-to-finish </span><b>ChIP </b><span style="font-weight: 400;">prior to </span><b>Next-Generation Sequencing</b><span style="font-weight: 400;">. This complete solution contains all buffers and reagents for cell lysis, chromatin shearing, immunoprecipitation, and DNA purification. In addition, unlike competing solutions, the kit contains positive and negative control antibodies (CTCF and IgG, respectively) as well as positive and negative control PCR primers pairs (H19 and Myoglobin exon 2, respectively) for your convenience and a guarantee of optimal results. <br /></span></p>
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<p><span style="font-weight: 400;">The </span><b> iDeal ChIP-seq kit for Transcription Factors </b><span style="font-weight: 400;">is compatible for cells or tissues:</span></p>
<table style="width: 419px; margin-left: auto; margin-right: auto;">
<tbody>
<tr>
<td style="width: 144px;"></td>
<td style="width: 267px; text-align: center;"><span style="font-weight: 400;">Amount per IP</span></td>
</tr>
<tr>
<td style="width: 144px;">Cells</td>
<td style="width: 267px; text-align: center;"><strong>4,000,000</strong></td>
</tr>
<tr>
<td style="width: 144px;">Tissues</td>
<td style="width: 267px; text-align: center;"><strong>30 mg</strong></td>
</tr>
</tbody>
</table>
<p><span style="font-weight: 400;">The iDeal ChIP-seq kit is the only kit on the market validated for major sequencing systems. Our expertise in ChIP-seq tools allows reproducible and efficient results every time. </span></p>
<p></p>
<p></p>',
'label1' => 'Characteristics',
'info1' => '<ul>
<li><span style="font-weight: 400;"><strong>Highly optimized protocol</strong> for ChIP-seq from cells and tissues</span></li>
<li><span style="font-weight: 400;"><strong>Validated</strong> for <strong>ChIP-seq</strong> with multiple transcription factors and non-histone targets<br /></span></li>
<li><span style="font-weight: 400;"><strong>Most complete kit</strong> available (covers all steps, including the control antibodies and primers)<br /></span></li>
<li><span style="font-weight: 400;"><strong>Magnetic beads</strong> make ChIP <strong>easy</strong>, <strong>fast</strong> and more <strong>reproducible</strong></span></li>
<li><span style="font-weight: 400;">Combination with Diagenode ChIP-seq antibodies provides <strong>high yields</strong> with excellent <strong>specificity</strong> and <strong>sensitivity</strong><br /></span></li>
<li><span style="font-weight: 400;">Purified DNA suitable for any downstream application</span></li>
<li><span style="font-weight: 400;">Easy-to-follow protocol</span></li>
</ul>
<p><span style="font-weight: 400;"></span></p>
<p> </p>
<h3>ChIP-seq on cells</h3>
<p><img src="https://www.diagenode.com/img/product/kits/ideal-ctcf-diagenode.jpg" alt="CTCF Diagenode" style="display: block; margin-left: auto; margin-right: auto;" /></p>
<p><strong>Figure 1.</strong> (A) Chromatin Immunoprecipitation has been performed using chromatin from HeLa cells, the iDeal ChIP-seq kit for Transcription Factors and the Diagenode ChIP-seq-grade CTCF antibody. The IP'd DNA was subsequently analysed on an Illumina<sup>®</sup> HiSeq. Library preparation, cluster generation and sequencing were performed according to the manufacturer's instructions. This figure shows the peak distribution in a region surrounding the GAPDH positive control gene.</p>
<p><img src="https://www.diagenode.com/img/product/kits/ideal-figure-b-total-diagendoe-peaks.png" alt="CTCF Diagenode" style="display: block; margin-left: auto; margin-right: auto;" /></p>
<p><strong>Figure 1B.</strong> The ChIP-seq dataset from this experiment has been compared with a reference dataset from the Broad Institute. We observed a perfect match between the top 40% of Diagenode peaks and the reference dataset. Based on the NIH Encode project criterion, ChIP-seq results are considered reproducible between an original and reproduced dataset if the top 40% of peaks have at least an 80% overlap ratio with the compared dataset.</p>
<p> </p>
<p><img src="https://www.diagenode.com/img/product/kits/ideal-TF-chip-seq-A.png" alt="ChIP-seq figure A" style="display: block; margin-left: auto; margin-right: auto;" /></p>
<p><img src="https://www.diagenode.com/img/product/kits/ideal-TF-chip-seq-B.png" alt="ChIP-seq figure B" style="display: block; margin-left: auto; margin-right: auto;" /></p>
<p><img src="https://www.diagenode.com/img/product/kits/ideal-TF-chip-seq-C.png" alt="ChIP-seq figure C" style="display: block; margin-left: auto; margin-right: auto;" /></p>
<p><strong>Figure 2.</strong> Chromatin Immunoprecipitation has been performed using chromatin from HeLa cells, the iDeal ChIP-seq kit for Transcription Factors and the Diagenode ChIP-seq-grade HDAC1 (A), LSD1 (B) and p53 antibody (C). The IP'd DNA was subsequently analysed on an Illumina<sup>®</sup> Genome Analyzer. Library preparation, cluster generation and sequencing were performed according to the manufacturer's instructions. This figure shows the peak distribution in regions of chromosome 3 (A), chromosome 12 (B) and chromosome 6 (C) respectively.</p>
<p> </p>
<h3>ChIP-seq on tissue</h3>
<p><img src="https://www.diagenode.com/img/product/kits/ideal-figure-3a.jpg" alt="ChIP-seq figure A" style="display: block; margin-left: auto; margin-right: auto;" /></p>
<p><strong>Figure 3A.</strong> Chromatin Immunoprecipitation has been performed using chromatin from mouse liver tissue, the iDeal ChIP-seq kit for Transcription Factors and the Diagenode ChIP-seq-grade CTCF antibody. The IP'd DNA was subsequently analysed on an Illumina® HiSeq. Library preparation, cluster generation and sequencing were performed according to the manufacturer's instructions. This figure shows the peak distribution in a region surrounding the Vwf positive control gene.</p>
<p><img src="https://www.diagenode.com/img/product/kits/match-of-the-top40-peaks.png" alt="Match of the Top40 peaks" style="display: block; margin-left: auto; margin-right: auto;" /></p>
<p><strong>Figure 3B.</strong> The ChIP-seq dataset from this experiment has been compared with a reference dataset from the Broad Institute. We observed a perfect match between the top 40% of Diagenode peaks and the reference dataset. Based on the NIH Encode project criterion, ChIP-seq results are considered reproducible between an original and reproduced dataset if the top 40% of peaks have at least an 80% overlap ratio with the compared dataset.</p>',
'label2' => 'Species, cell lines, tissues tested',
'info2' => '<p>The iDeal ChIP-seq Kit for Transcription Factors is compatible with a broad variety of cell lines, tissues and species - some examples are shown below. Other species / cell lines / tissues can be used with this kit.</p>
<p><span style="text-decoration: underline;">Cell lines:</span></p>
<p>Human: A549, A673, BT-549, CD4 T, HCC1806, HeLa, HepG2, HFF, HK-GFP-MR, ILC, K562, KYSE-180, LapC4, M14, MCF7, MDA-MB-231, MDA-MB-436, RDES, SKNO1, VCaP, U2-OS, ZR-75-1 </p>
<p>Mouse: ESC, NPCs, BZ, GT1-7, acinar cells, HSPCs, Th2 cells, keratinocytes</p>
<p>Cattle: pbMEC, <span>MAC-T</span></p>
<p><span>Other cell lines / species: compatible, not tested</span></p>
<p><span style="text-decoration: underline;">Tissues:</span></p>
<p>Mouse: kidney, heart, brain, iris, liver, limbs from E10.5 embryos</p>
<p><span>Horse: l</span>iver, brain, heart, lung, skeletal muscle, lamina, ovary</p>
<p>Other tissues: compatible, not tested</p>
<p><span style="text-decoration: underline;">ChIP on yeast</span></p>
<p>The iDeal ChIP-seq kit for TF is compatible with yeast samples. Check out our <strong><a href="https://www.diagenode.com/files/products/kits/Application_Note-ChIP_on_Yeast.pdf">Application Note</a></strong> presenting an optimized detailed protocol for ChIP on yeast.</p>
<p></p>
<p>Did you use the iDeal ChIP-seq for Transcription Factors Kit on other cell line / tissue / species? <a href="mailto:agnieszka.zelisko@diagenode.com?subject=Species, cell lines, tissues tested with the iDeal ChIP-seq Kit for TF&body=Dear Customer,%0D%0A%0D%0APlease, leave below your feedback about the iDeal ChIP-seq for Transcription Factors (cell / tissue type, species, other information...).%0D%0A%0D%0AThank you for sharing with us your experience !%0D%0A%0D%0ABest regards,%0D%0A%0D%0AAgnieszka Zelisko-Schmidt, PhD">Let us know!</a></p>',
'label3' => 'Additional solutions compatible with iDeal ChIP-seq kit for Transcription Factors',
'info3' => '<p><span style="font-weight: 400;">The</span> <a href="https://www.diagenode.com/en/p/chromatin-shearing-optimization-kit-low-sds-for-tfs-25-rxns"><span style="font-weight: 400;">Chromatin EasyShear Kit – Low SDS </span></a><span style="font-weight: 400;">is the kit compatible with the iDeal ChIP-seq kit for TF, recommended for the optimization of chromatin shearing, a critical step for ChIP.</span></p>
<p><a href="https://www.diagenode.com/en/p/chip-cross-link-gold-600-ul"><span style="font-weight: 400;">ChIP Cross-link Gold</span></a> <span style="font-weight: 400;">should be used in combination with formaldehyde when working with higher order and/or dynamic interactions, for efficient protein-protein fixation.</span></p>
<p><span style="font-weight: 400;">For library preparation of immunoprecipitated samples we recommend to use the </span><b> </b><a href="https://www.diagenode.com/en/categories/library-preparation-for-ChIP-seq"><span style="font-weight: 400;">MicroPlex Library Preparation Kit</span></a><span style="font-weight: 400;"> - validated for library preparation from picogram inputs.</span></p>
<p><a href="https://www.diagenode.com/en/categories/chip-seq-grade-antibodies"><span style="font-weight: 400;">ChIP-seq grade antibodies</span></a><span style="font-weight: 400;"> provide high yields with excellent specificity and sensitivity.</span></p>
<p><span style="font-weight: 400;">Check the list of available </span><a href="https://www.diagenode.com/en/categories/primer-pairs"><span style="font-weight: 400;">Primer pairs</span></a><span style="font-weight: 400;"> designed for high specificity to specific genomic regions.</span></p>
<p><span style="font-weight: 400;">Plus, for our <a href="https://www.diagenode.com/en/categories/ip-star">IP-Star Automation</a> users for automated ChIP, check out our <a href="https://www.diagenode.com/en/p/auto-ideal-chip-seq-kit-for-transcription-factors-x24-24-rxns">automated version</a> of this kit.</span></p>',
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'name' => 'H3K4me3 polyclonal antibody ',
'description' => '<p><span>Polyclonal antibody raised in rabbit against the region of histone H3 containing the trimethylated lysine 4 (H3K4me3), using a KLH-conjugated synthetic peptide.</span></p>
<script src="chrome-extension://hhojmcideegachlhfgfdhailpfhgknjm/web_accessible_resources/index.js"></script>',
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<div class="small-6 columns"><center><img src="https://www.diagenode.com/img/product/antibodies/C15410003-fig1-ChIP.jpg" /></center></div>
<div class="small-6 columns">
<p><small><strong>Figure 1. ChIP results obtained with the Diagenode antibody directed against H3K4me3</strong><br />ChIP assays were performed using human K562 cells, the Diagenode antibody against H3K4me3 (cat. No. C15410003) and optimized PCR primer pairs for qPCR. ChIP was performed with the iDeal ChIP-seq kit (cat. No. C01010051), using sheared chromatin from 500,000 cells. A titration consisting of 0.5, 1, 2 and 5 µg of antibody per ChIP experiment was analyzed. IgG (1 µg/IP) was used as a negative IP control. Quantitative PCR was performed with primers specific for the promoter of the active genes GAPDH and EIF4A2, used as positive controls, and for the inactive MYOD1 gene and the Sat2 satellite repeat, used as negative controls. Figure 1 shows the recovery, expressed as a % of input (the relative amount of immunoprecipitated DNA compared to input DNA after qPCR analysis). </small></p>
</div>
</div>
<div class="row">
<div class="small-12 columns"><center>A.<img src="https://www.diagenode.com/img/product/antibodies/C15410003-fig2a-ChIP-seq.jpg" width="800" /></center><center>B.<img src="https://www.diagenode.com/img/product/antibodies/C15410003-fig2b-ChIP-seq.jpg" width="800" /></center><center>C.<img src="https://www.diagenode.com/img/product/antibodies/C15410003-fig2c-ChIP-seq.jpg" width="800" /></center><center>D.<img src="https://www.diagenode.com/img/product/antibodies/C15410003-fig2d-ChIP-seq.jpg" width="800" /></center></div>
</div>
<div class="row">
<div class="small-12 columns">
<p><small><strong>Figure 2. ChIP-seq results obtained with the Diagenode antibody directed against H3K4me3</strong><br />ChIP was performed on sheared chromatin from 1 million HeLaS3 cells using 1 µg of the Diagenode antibody against H3K4me3 (cat. No. C15410003) as described above. The IP'd DNA was subsequently analysed on an Illumina Genome Analyzer. Library preparation, cluster generation and sequencing were performed according to the manufacturer's instructions. The 36 bp tags were aligned to the human genome using the ELAND algorithm. Figure 2 shows the peak distribution along the complete sequence and a 600 kb region of the X-chromosome (figure 2A and B) and in two regions surrounding the GAPDH and EIF4A2 positive control genes, respectively (figure 2C and D). These results clearly show an enrichment of the H3K4 trimethylation at the promoters of active genes.</small></p>
</div>
</div>
<div class="row">
<div class="small-12 columns"><center>A.<img src="https://www.diagenode.com/img/product/antibodies/C15410003-cuttag-a.png" width="800" /></center></div>
<div class="small-12 columns"><center>B.<img src="https://www.diagenode.com/img/product/antibodies/C15410003-cuttag-b.png" width="800" /></center></div>
</div>
<div class="row">
<div class="small-12 columns">
<p><small><strong>Figure 3. Cut&Tag results obtained with the Diagenode antibody directed against H3K4me3</strong><br />CUT&TAG (Kaya-Okur, H.S., Nat Commun 10, 1930, 2019) was performed on 50,000 K562 cells using 0.5 µg of the Diagenode antibody against H3K4me3 (cat. No. C15410003) and the Diagenode pA-Tn5 transposase (C01070001). The libraries were subsequently analysed on an Illumina NextSeq 500 sequencer (2x75 paired-end reads) according to the manufacturer's instructions. The tags were aligned to the human genome (hg19) using the BWA algorithm. Figure 3 shows the peak distribution in 2 genomic regions surrounding the FOS gene on chromosome 14 and the ACTB gene on chromosome 7 (figure 3A and B, respectively).</small></p>
</div>
</div>
<div class="row">
<div class="small-6 columns"><center><img src="https://www.diagenode.com/img/product/antibodies/C15410003-fig3-ELISA.jpg" width="350" /></center><center></center><center></center><center></center><center></center></div>
<div class="small-6 columns">
<p><small><strong>Figure 4. Determination of the antibody titer</strong><br />To determine the titer of the antibody, an ELISA was performed using a serial dilution of the Diagenode antibody against H3K4me3 (cat. No. C15410003). The antigen used was a peptide containing the histone modification of interest. By plotting the absorbance against the antibody dilution (Figure 4), the titer of the antibody was estimated to be 1:11,000.</small></p>
</div>
</div>
<div class="row">
<div class="small-6 columns"><img src="https://www.diagenode.com/img/product/antibodies/C15410003-fig4-DB.jpg" /></div>
<div class="small-6 columns">
<p><small><strong>Figure 5. Cross reactivity tests using the Diagenode antibody directed against H3K4me3</strong><br />To test the cross reactivity of the Diagenode antibody against H3K4me3 (cat. No. C15410003), a Dot Blot analysis was performed with peptides containing other histone modifications and the unmodified H3K4. One hundred to 0.2 pmol of the respective peptides were spotted on a membrane. The antibody was used at a dilution of 1:2,000. Figure 5A shows a high specificity of the antibody for the modification of interest.</small></p>
</div>
</div>
<div class="row">
<div class="small-4 columns"><img src="https://www.diagenode.com/img/product/antibodies/C15410003-fig5-WB.jpg" /></div>
<div class="small-8 columns">
<p><small><strong>Figure 6. Western blot analysis using the Diagenode antibody directed against H3K4me3</strong><br />Western blot was performed on whole cell extracts (40 µg, lane 1) from HeLa cells, and on 1 µg of recombinant histone H3 (lane 2) using the Diagenode antibody against H3K4me3 (cat. No. C15410003). The antibody was diluted 1:1,000 in TBS-Tween containing 5% skimmed milk. The position of the protein of interest is indicated on the right; the marker (in kDa) is shown on the left.</small></p>
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<div class="row">
<div class="small-12 columns">
<p><small><strong>Figure 7. Immunofluorescence using the Diagenode antibody directed against H3K4me3</strong><br />HeLa cells were stained with the Diagenode antibody against H3K4me3 (cat. No. C15410003) and with DAPI. Cells were fixed with 4% formaldehyde for 20’ and blocked with PBS/TX-100 containing 5% normal goat serum. The cells were immunofluorescently labelled with the H3K4me3 antibody (left) diluted 1:200 in blocking solution followed by an anti-rabbit antibody conjugated to Alexa568 or with DAPI (middle), which specifically labels DNA. The right picture shows a merge of both stainings.</small></p>
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'name' => 'H3K9me3 Antibody',
'description' => '<p><span>Polyclonal antibody raised in rabbit against the region of histone<strong> H3 containing the trimethylated lysine 9</strong> (<strong>H3K9me3</strong>), using a KLH-conjugated synthetic peptide.</span></p>',
'label1' => 'Validation Data',
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<div class="small-6 columns"><center><img src="https://www.diagenode.com/img/product/antibodies/C15410193-ChIP-Fig1.png" /></center></div>
<div class="small-6 columns">
<p><small><strong>Figure 1. ChIP results obtained with the Diagenode antibody directed against H3K9me3</strong><br />ChIP assays were performed using human HeLa cells, the Diagenode antibody against H3K9me3 (cat. No. C15410193) and optimized PCR primer sets for qPCR. ChIP was performed on sheared chromatin from 1 million HeLaS3 cells using the “iDeal ChIP-seq” kit (cat. No. C01010051). A titration of the antibody consisting of 0.5, 1, 2, and 5 µg per ChIP experiment was analysed. IgG (1 µg/IP) was used as negative IP control. QPCR was performed with primers for the heterochromatin marker Sat2 and for the ZNF510 gene, used as positive controls, and for the promoters of the active EIF4A2 and GAPDH genes, used as negative controls. Figure 1 shows the recovery, expressed as a % of input (the relative amount of immunoprecipitated DNA compared to input DNA after qPCR analysis).</small></p>
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<div class="row">
<div class="small-12 columns"><center>A.<img src="https://www.diagenode.com/img/product/antibodies/C15410193-ChIP-Fig2a.png" width="700" /></center><center>B.<img src="https://www.diagenode.com/img/product/antibodies/C15410193-ChIP-Fig2b.png" width="700" /></center><center>C.<img src="https://www.diagenode.com/img/product/antibodies/C15410193-ChIP-Fig2c.png" width="700" /></center><center>D.<img src="https://www.diagenode.com/img/product/antibodies/C15410193-ChIP-Fig2d.png" width="700" /></center></div>
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<div class="row">
<div class="small-12 columns">
<p><small><strong>Figure 2. ChIP-seq results obtained with the Diagenode antibody directed against H3K9me3</strong><br />ChIP was performed with 0.5 µg of the Diagenode antibody against H3K9me3 (cat. No. C15410193) on sheared chromatin from 1,000,000 HeLa cells using the “iDeal ChIP-seq” kit as described above. The IP'd DNA was subsequently analysed on an Illumina HiSeq 2000. Library preparation, cluster generation and sequencing were performed according to the manufacturer's instructions. The 50 bp tags were aligned to the human genome using the BWA algorithm. Figure 2A shows the signal distribution along the long arm of chromosome 19 and a zoomin to an enriched region containing several ZNF repeat genes. The arrows indicate two satellite repeat regions which exhibit a stronger signal. Figures 2B, 2C and 2D show the enrichment along the ZNF510 positive control target and at the H19 and KCNQ1 imprinted genes.</small></p>
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<div class="row">
<div class="small-12 columns"><center>A.<img src="https://www.diagenode.com/img/product/antibodies/C15410193-CT-Fig3a.png" width="700" /></center><center>B.<img src="https://www.diagenode.com/img/product/antibodies/C15410193-CT-Fig3b.png" width="700" /></center></div>
</div>
<div class="row">
<div class="small-12 columns">
<p><small><strong>Figure 3. Cut&Tag results obtained with the Diagenode antibody directed against H3K9me3</strong><br />CUT&TAG (Kaya-Okur, H.S., Nat Commun 10, 1930, 2019) was performed on 50,000 K562 cells using 1 µg of the Diagenode antibody against H3K9me3 (cat. No. C15410193) and the Diagenode pA-Tn5 transposase (C01070001). The libraries were subsequently analysed on an Illumina NextSeq 500 sequencer (2x75 paired-end reads) according to the manufacturer's instructions. The tags were aligned to the human genome (hg19) using the BWA algorithm. Figure 3 shows the peak distribution in a genomic regions on chromosome 1 containing several ZNF repeat genes and in a genomic region surrounding the KCNQ1 imprinting control gene on chromosome 11 (figure 3A and B, respectively).</small></p>
</div>
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<div class="row">
<div class="small-6 columns"><center><img src="https://www.diagenode.com/img/product/antibodies/C15410193-Elisa-Fig4.png" /></center></div>
<div class="small-6 columns">
<p><small><strong>Figure 4. Determination of the antibody titer</strong><br />To determine the titer of the antibody, an ELISA was performed using a serial dilution of the antibody directed against human H3K9me3 (cat. No. C15410193) in antigen coated wells. The antigen used was a peptide containing the histone modification of interest. By plotting the absorbance against the antibody dilution (Figure 4), the titer of the antibody was estimated to be 1:87,000.</small></p>
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<div class="row">
<div class="small-4 columns"><center><img src="https://www.diagenode.com/img/product/antibodies/C15410193-DB-Fig5.png" /></center></div>
<div class="small-8 columns">
<p><small><strong>Figure 5. Cross reactivity tests using the Diagenode antibody directed against H3K9me3</strong><br />A Dot Blot analysis was performed to test the cross reactivity of the Diagenode antibody against H3K9me3 (cat. No. C15410193) with peptides containing other modifications and unmodified sequences of histone H3 and H4. One hundred to 0.2 pmol of the peptide containing the respective histone modification were spotted on a membrane. The antibody was used at a dilution of 1:20,000. Figure 5 shows a high specificity of the antibody for the modification of interest.</small></p>
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<div class="row">
<div class="small-4 columns"><center><img src="https://www.diagenode.com/img/product/antibodies/C15410193-WB-Fig6.png" /></center></div>
<div class="small-8 columns">
<p><small><strong>Figure 6. Western blot analysis using the Diagenode antibody directed against H3K9me3</strong><br />Western blot was performed on whole cell (25 µg, lane 1) and histone extracts (15 µg, lane 2) from HeLa cells, and on 1 µg of recombinant histone H2A, H2B, H3 and H4 (lane 3, 4, 5 and 6, respectively) using the Diagenode antibody against H3K9me3 (cat. No. C15410193). The antibody was diluted 1:1,000 in TBS-Tween containing 5% skimmed milk. The position of the protein of interest is indicated on the right; the marker (in kDa) is shown on the left.</small></p>
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<div class="row">
<div class="small-12 columns"><center><img src="https://www.diagenode.com/img/product/antibodies/C15410193-IF-Fig7.png" /></center></div>
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<div class="row">
<div class="small-12 columns">
<p><small><strong>Figure 7. Immunofluorescence using the Diagenode antibody directed against H3K9me3</strong><br />HeLa cells were stained with the Diagenode antibody against H3K9me3 (cat. No. C15410193) and with DAPI. Cells were fixed with 4% formaldehyde for 10’ and blocked with PBS/TX-100 containing 5% normal goat serum and 1% BSA. The cells were immunofluorescently labelled with the H3K9me3 antibody (middle) diluted 1:500 in blocking solution followed by an anti-rabbit antibody conjugated to Alexa488. The left panel shows staining of the nuclei with DAPI. A merge of both stainings is shown on the right.</small></p>
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'name' => 'H3K27me3 Antibody',
'description' => '<p>Polyclonal antibody raised in rabbit against the region of histone <strong>H3 containing the trimethylated lysine 27</strong> (<strong>H3K27me3</strong>), using a KLH-conjugated synthetic peptide.</p>',
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<div class="small-6 columns">
<p>A. <img src="https://www.diagenode.com/img/product/antibodies/C15410195-ChIP-Fig1.png" alt="H3K27me3 Antibody ChIP Grade" /></p>
<p>B. <img src="https://www.diagenode.com/img/product/antibodies/C15410195-ChIP-Fig2.png" alt="H3K27me3 Antibody for ChIP" /></p>
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<div class="small-6 columns">
<p><small><strong>Figure 1. ChIP results obtained with the Diagenode antibody directed against H3K27me3</strong><br />ChIP assays were performed using human HeLa cells, the Diagenode antibody against H3K27me3 (Cat. No. C15410195) and optimized PCR primer pairs for qPCR. ChIP was performed with the “iDeal ChIP-seq” kit (Cat. No. C01010051), using sheared chromatin from 1 million cells. The chromatin was spiked with a panel of in vitro assembled nucleosomes, each containing a specific lysine methylation. A titration consisting of 0.5, 1, 2 and 5 µg of antibody per ChIP experiment was analyzed. IgG (1 µg/IP) was used as a negative IP control.</small></p>
<p><small><strong>Figure 1A.</strong> Quantitative PCR was performed with primers specific for the promoter of the active GAPDH and EIF4A2 genes, used as negative controls, and for the inactive TSH2B and MYT1 genes, used as positive controls. The graph shows the recovery, expressed as a % of input (the relative amount of immunoprecipitated DNA compared to input DNA after qPCR analysis).</small></p>
<p><small><strong>Figure 1B.</strong> Recovery of the nucleosomes carrying the H3K27me1, H3K27me2, H3K27me3, H3K4me3, H3K9me3 and H3K36me3 modifications and the unmodified H3K27 as determined by qPCR. The figure clearly shows the antibody is very specific in ChIP for the H3K27me3 modification.</small></p>
</div>
</div>
<div class="row">
<div class="small-12 columns">
<p>A. <img src="https://www.diagenode.com/img/product/antibodies/C15410195-ChIP-Fig2a.png" alt="H3K27me3 Antibody ChIP-seq Grade" /></p>
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<div class="extra-spaced"></div>
<div class="extra-spaced"></div>
<div class="extra-spaced"></div>
<div class="extra-spaced"></div>
<div class="extra-spaced"></div>
<div class="extra-spaced"></div>
<div class="row">
<div class="small-12 columns">
<p>B. <img src="https://www.diagenode.com/img/product/antibodies/C15410195-ChIP-Fig2b.png" alt="H3K27me3 Antibody for ChIP-seq" /></p>
<p>C. <img src="https://www.diagenode.com/img/product/antibodies/C15410195-ChIP-Fig2c.png" alt="H3K27me3 Antibody for ChIP-seq assay" /></p>
<p>D. <img src="https://www.diagenode.com/img/product/antibodies/C15410195-ChIP-Fig2d.png" alt="H3K27me3 Antibody validated in ChIP-seq" /></p>
</div>
</div>
<div class="row">
<div class="small-12 columns">
<p><small><strong>Figure 2. ChIP-seq results obtained with the Diagenode antibody directed against H3K27me3</strong><br />ChIP was performed on sheared chromatin from 1 million HeLa cells using 1 µg of the Diagenode antibody against H3K27me3 (Cat. No. C15410195) as described above. The IP'd DNA was subsequently analysed on an Illumina HiSeq. Library preparation, cluster generation and sequencing were performed according to the manufacturer's instructions. The 50 bp tags were aligned to the human genome using the BWA algorithm. Figure 2 shows the enrichment in genomic regions of chromosome 6 and 20, surrounding the TSH2B and MYT1 positive control genes (fig 2A and 2B, respectively), and in two genomic regions of chromosome 1 and X (figure 2C and D).</small></p>
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<div class="extra-spaced"></div>
<div class="extra-spaced"></div>
<div class="extra-spaced"></div>
<div class="extra-spaced"></div>
<div class="row">
<div class="small-12 columns">
<p>A. <img src="https://www.diagenode.com/img/product/antibodies/C15410195-CUTTAG-Fig3A.png" /></p>
<p>B. <img src="https://www.diagenode.com/img/product/antibodies/C15410195-CUTTAG-Fig3B.png" /></p>
</div>
</div>
<div class="row">
<div class="small-12 columns">
<p><small><strong>Figure 3. Cut&Tag results obtained with the Diagenode antibody directed against H3K27me3</strong><br />CUT&TAG (Kaya-Okur, H.S., Nat Commun 10, 1930, 2019) was performed on 50,000 K562 cells using 1 µg of the Diagenode antibody against H3K27me3 (cat. No. C15410195) and the Diagenode pA-Tn5 transposase (C01070001). The libraries were subsequently analysed on an Illumina NextSeq 500 sequencer (2x75 paired-end reads) according to the manufacturer's instructions. The tags were aligned to the human genome (hg19) using the BWA algorithm. Figure 3 shows the peak distribution in 2 genomic regions on chromosome and 13 and 20 (figure 3A and B, respectively).</small></p>
</div>
</div>
<div class="extra-spaced"></div>
<div class="extra-spaced"></div>
<div class="row">
<div class="small-6 columns">
<p><img src="https://www.diagenode.com/img/product/antibodies/C15410195-ELISA-Fig4.png" alt="H3K27me3 Antibody ELISA Validation " /></p>
</div>
<div class="small-6 columns">
<p><small><strong>Figure 4. Determination of the antibody titer</strong><br />To determine the titer of the antibody, an ELISA was performed using a serial dilution of the Diagenode antibody directed against H3K27me3 (Cat. No. C15410195). The antigen used was a peptide containing the histone modification of interest. By plotting the absorbance against the antibody dilution (Figure 4), the titer of the antibody was estimated to be 1:3,000.</small></p>
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</div>
<div class="extra-spaced"></div>
<div class="extra-spaced"></div>
<div class="extra-spaced"></div>
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<div class="row">
<div class="small-6 columns">
<p><img src="https://www.diagenode.com/img/product/antibodies/C15410195-DB-Fig5a.png" alt="H3K27me3 Antibody Dot Blot Validation " /></p>
</div>
<div class="small-6 columns">
<p><small><strong>Figure 5. Cross reactivity tests using the Diagenode antibody directed against H3K27me3</strong><br />A Dot Blot analysis was performed to test the cross reactivity of the Diagenode antibody against H3K27me3 (Cat. No. C15410195) with peptides containing other modifications of histone H3 and H4 and the unmodified H3K27 sequence. One hundred to 0.2 pmol of the peptide containing the respective histone modification were spotted on a membrane. The antibody was used at a dilution of 1:5,000. Figure 5 shows a high specificity of the antibody for the modification of interest. Please note that the antibody also recognizes the modification if S28 is phosphorylated.</small></p>
</div>
</div>
<div class="row">
<div class="small-6 columns">
<p><img src="https://www.diagenode.com/img/product/antibodies/C15410195-WB-Fig6.png" alt="H3K27me3 Antibody validated in Western Blot" /></p>
</div>
<div class="small-6 columns">
<p><small><strong>Figure 6. Western blot analysis using the Diagenode antibody directed against H3K27me3</strong><br />Western blot was performed on whole cell (25 µg, lane 1) and histone extracts (15 µg, lane 2) from HeLa cells, and on 1 µg of recombinant histone H2A, H2B, H3 and H4 (lane 3, 4, 5 and 6, respectively) using the Diagenode antibody against H3K27me3 (cat. No. C15410195) diluted 1:500 in TBS-Tween containing 5% skimmed milk. The position of the protein of interest is indicated on the right; the marker (in kDa) is shown on the left.</small></p>
</div>
</div>
<div class="row">
<div class="small-12 columns">
<p><img src="https://www.diagenode.com/img/product/antibodies/C15410195-IF-Fig7.png" alt="H3K27me3 Antibody validated for Immunofluorescence" /></p>
</div>
</div>
<div class="row">
<div class="small-12 columns">
<p><small><strong>Figure 7. Immunofluorescence using the Diagenode antibody directed against H3K27me3</strong><br />Human HeLa cells were stained with the Diagenode antibody against H3K27me3 (Cat. No. C15410195) and with DAPI. Cells were fixed with 4% formaldehyde for 10’ and blocked with PBS/TX-100 containing 5% normal goat serum and 1% BSA. The cells were immunofluorescently labelled with the H3K27me3 antibody (left) diluted 1:200 in blocking solution followed by an anti-rabbit antibody conjugated to Alexa488. The middle panel shows staining of the nuclei with DAPI. A merge of the two stainings is shown on the right.</small></p>
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'name' => 'H3K27ac Antibody',
'description' => '<p><span>Polyclonal antibody raised in rabbit against the region of histone <strong>H3 containing the acetylated lysine 27</strong> (<strong>H3K27ac</strong>), using a KLH-conjugated synthetic peptide.</span></p>',
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<div class="small-6 columns">A.<img src="https://www.diagenode.com/img/product/antibodies/C15410196-ChIP-Fig1a.png" width="356" /><br /> B.<img src="https://www.diagenode.com/img/product/antibodies/C15410196-ChIP-Fig1b.png" width="356" /></div>
<div class="small-6 columns">
<p><strong>Figure 1. ChIP results obtained with the Diagenode antibody directed against H3K27ac</strong></p>
<p>Figure 1A ChIP assays were performed using human HeLa cells, the Diagenode antibody against H3K27ac (Cat. No. C15410196) and optimized PCR primer pairs for qPCR. ChIP was performed with the “Auto Histone ChIP-seq” kit on the IP-Star automated system, using sheared chromatin from 1,000,000 cells. A titration consisting of 1, 2, 5 and 10 µg of antibody per ChIP experiment was analyzed. IgG (2 µg/IP) was used as a negative IP control. Quantitative PCR was performed with primers for the promoters of the active EIF4A2 and ACTB genes, used as positive controls, and for the inactive TSH2B and MYT1 genes, used as negative controls.</p>
<p>Figure 1B ChIP assays were performed using human K562 cells, the Diagenode antibody against H3K27ac (Cat. No. C15410196)and optimized PCR primer pairs for qPCR. ChIP was performed with the “iDeal ChIP-seq” kit (Cat. No. C01010051), using sheared chromatin from 100,000 cells. A titration consisting of 0.2, 0.5, 1 and 2 µg of antibody per ChIP experiment was analyzed. IgG (1 µg/IP) was used as a negative IP control. Quantitative PCR was performed with primers for the promoters of the active GAPDH and EIF4A2 genes, used as positive controls, and for the coding regions of the inactive MB and MYT1 genes, used as negative controls. Figure 1 shows the recovery, expressed as a % of input (the relative amount of immunoprecipitated DNA compared to input DNA after qPCR analysis)</p>
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<div class="small-12 columns"><center>
<p>A.<img src="https://www.diagenode.com/img/product/antibodies/C15410196-ChIP-Fig2a.png" /></p>
</center><center>
<p>B.<img src="https://www.diagenode.com/img/product/antibodies/C15410196-ChIP-Fig2b.png" /></p>
</center><center>
<p>C.<img src="https://www.diagenode.com/img/product/antibodies/C15410196-ChIP-Fig2c.png" /></p>
</center></div>
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<div class="row">
<div class="small-12 columns">
<p><strong>Figure 2. ChIP-seq results obtained with the Diagenode antibody directed against H3K27ac</strong></p>
<p>ChIP was performed on sheared chromatin from 100,000 K562 cells using 1 µg of the Diagenode antibody against H3K27ac (Cat. No. C15410196<span class="label-primary"></span>) as described above. The IP’d DNA was subsequently analysed on an Illumina Genome Analyzer. Library preparation, cluster generation and sequencing were performed according to the manufacturer’s instructions. The 36 bp tags were aligned to the human genome using the ELAND algorithm. Figure 2A shows the peak distribution along the complete human X-chromosome. Figure 2 B and C show the peak distribution in two regions surrounding the EIF4A2 and GAPDH positive control genes, respectively. The position of the PCR amplicon, used for validating the ChIP assay is indicated with an arrow.</p>
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<div class="row">
<div class="small-12 columns"><center><img src="https://www.diagenode.com/img/product/antibodies/C15410196-fig3.jpg" /></center></div>
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<div class="row">
<div class="small-12 columns">
<p><strong>Figure 3. Cut&Tag results obtained with the Diagenode antibody directed against H3K27ac</strong></p>
<p>CUT&TAG (Kaya-Okur, H.S., Nat Commun 10, 1930, 2019) was performed on 50,000 K562 cells using 1 µg of the Diagenode antibody against H3K27ac (cat. No. C15410196) and the Diagenode pA-Tn5 transposase (C01070001). The libraries were subsequently analysed on an Illumina NextSeq 500 sequencer (2x75 paired-end reads) according to the manufacturer's instructions. The tags were aligned to the human genome (hg19) using the BWA algorithm. Figure 3 shows the peak distribution in 2 genomic regions surrounding the EIF2S3 gene on the X-chromosome and the CCT5 gene on chromosome 5 (figure 3A and B, respectively).</p>
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<div class="row">
<div class="small-6 columns"><img src="https://www.diagenode.com/img/product/antibodies/C15410196-ELISA-Fig3.png" /></div>
<div class="small-6 columns">
<p><strong>Figure 4. Determination of the antibody titer</strong></p>
<p>To determine the titer of the antibody, an ELISA was performed using a serial dilution of the Diagenode antibody against H3K27ac (Cat. No. C15410196<span class="label-primary"></span>). The antigen used was a peptide containing the histone modification of interest. By plotting the absorbance against the antibody dilution (Figure 4), the titer of the antibody was estimated to be 1:8,300.</p>
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<div class="row">
<div class="small-4 columns"><center><img src="https://www.diagenode.com/img/product/antibodies/C15410196-DB-Fig4.png" /></center></div>
<div class="small-8 columns">
<p><strong>Figure 5. Cross reactivity tests using the Diagenode antibody directed against H3K27ac</strong><br />To test the cross reactivity of the Diagenode antibody against H3K27ac (Cat. No. C15410196<span class="label-primary"></span>), a Dot Blot analysis was performed with peptides containing other histone modifications and the unmodified H3K27. One hundred to 0.2 pmol of the respective peptides were spotted on a membrane. The antibody was used at a dilution of 1:20,000. Figure 5 shows a high specificity of the antibody for the modification of interest.</p>
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<div class="row">
<div class="small-4 columns"><center><img src="https://www.diagenode.com/img/product/antibodies/C15410196-WB-Fig5.png" /></center></div>
<div class="small-8 columns">
<p><strong>Figure 6. Western blot analysis using the Diagenode antibody directed against H3K27ac</strong><br />Western blot was performed on whole cell (25 µg, lane 1) and histone extracts (15 µg, lane 2) from HeLa cells, and on 1 µg of recombinant histone H2A, H2B, H3 and H4 (lane 3, 4, 5 and 6, respectively) using the Diagenode antibody against H3K27ac (Cat. No. C1541196). The antibody was diluted 1:1,000 in TBS-Tween containing 5% skimmed milk. The marker (in kDa) is shown on the left.</p>
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</div>
<div class="row">
<div class="small-4 columns"><img src="https://www.diagenode.com/img/product/antibodies/C15410196-IF-Fig6.png" /></div>
<div class="small-8 columns">
<p><strong>Figure 7. Immunofluorescence using the Diagenode antibody directed against H3K27ac</strong></p>
<p>HeLa cells were stained with the Diagenode antibody against H3K27ac (Cat. No. C15410196<span class="label-primary"></span>) and with DAPI. Cells were fixed with 4% formaldehyde for 10’ and blocked with PBS/ TX-100 containing 5% normal goat serum and 1% BSA. The cells were immunofluorescently labeled with the H3K27ac antibody (top) diluted 1:500 in blocking solution followed by an anti-rabbit antibody conjugated to Alexa488. The middle panel shows staining of the nuclei with DAPI. A merge of the two stainings is shown at the bottom.</p>
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<h5 class="large-12 columns"><strong></strong></h5>
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<li class="large-12 columns"><strong>Chromatin preparation: </strong>Crosslink chromatin-bound proteins (histones or transcription factors) to DNA followed by cell lysis.</li>
<li class="large-12 columns"><strong>Chromatin shearing:</strong> Fragment chromatin by sonication to desired fragment size (100-500 bp)</li>
<li class="large-12 columns"><strong>Chromatin IP</strong>: Capture protein-DNA complexes with <strong><a href="../categories/chip-seq-grade-antibodies">specific ChIP-seq grade antibodies</a></strong> against the histone or transcription factor of interest</li>
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<li class="large-12 columns"><strong>NGS Library Preparation</strong>: Ligate adapters and amplify IP'd material</li>
<li class="large-12 columns"><strong>Bioinformatic analysis</strong>: Perform r<span style="font-weight: 400;">ead filtering and trimming</span>, r<span style="font-weight: 400;">ead specific alignment, enrichment specific peak calling, QC metrics, multi-sample cross-comparison etc. </span></li>
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<h3 class="text-center" style="color: #b21329;">Need guidance?</h3>
<p class="text-justify">Choose our full ChIP kits or simply choose what you need from antibodies, buffers, beads, chromatin shearing and purification reagents. With the ChIP Kit Customizer, you have complete flexibility on which components you want from our validated ChIP kits.</p>
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<div class="small-6 medium-6 large-6 columns"><a href="../pages/which-kit-to-choose"><img alt="" src="https://www.diagenode.com/img/banners/banner-decide.png" /></a></div>
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<p><strong>ChIP</strong>, <b>C</b>hromatin <b>I</b>mmunoprecipitation, is a method used to determine the location of DNA binding sites on the genome for a particular protein of interest. This powerful method offers insight into the regulation of gene expression. This technique is now used in a variety of life science disciplines including cellular differentiation, tumor suppressor gene silencing, and the effect of histone modifications on gene expression.</p>
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<li><strong>Complete kits</strong> – including the reagents for all steps of the protocol</li>
<li><strong>Optimized robust protocols</strong></li>
<li>Magnetic beads for <strong>more reproducible results</strong></li>
<li><strong>Optimized DNA purification</strong> for maximum DNA recovery after immunoprecipitation</li>
<li><strong>Perfect match</strong> of sequencing results with reference dataset</li>
<li><strong>Many species tested</strong> (human, mouse, rat, horse, chicken, cow, pig, plants and more)</li>
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<p><em>Check out other products for: <a href="https://www.diagenode.com/en/categories/chromatin-function">Chromatin studies - </a> <a href="https://www.diagenode.com/en/categories/library-preparation-for-ChIP-seq">Library preparation after </a><a href="https://www.diagenode.com/en/categories/library-preparation-for-ChIP-seq">ChIP</a> - <a href="https://www.diagenode.com/en/categories/antibodies">Antibodies</a></em></p>
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<div class="center" style="text-align: center;"><a href="../pages/chip-kit-customizer-1"><img src="https://www.diagenode.com/img/banners/banner-customizer.png" alt="" /></a></div>
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<p><span> </span></p>',
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'description' => '<p>How histone modifications affect animal development remains difficult to ascertain. Despite the prevalence of histone 3 lysine 4 monomethylation (H3K4me1) on enhancers, hypomethylation appears to have minor effects on phenotype and viability. Here, we genetically reduce H3K4me1 deposition in Drosophila melanogaster and find that hypomethylation reduces transcription factor enrichment in nuclear microenvironments, disrupts gene expression, and reduces phenotypic robustness. Using a developmental phenomics approach, we find changes in morphology, metabolism, behavior, and offspring production. However, many phenotypic changes are only detected when hypomethylated flies develop outside of standard laboratory environments or with specific genetic backgrounds. Therefore, quantitative phenomics measurements can unravel how pleiotropic modulators of gene expression affect developmental robustness under conditions resembling the natural environments of a species.</p>',
'date' => '2022-12-01',
'pmid' => 'https://www.ncbi.nlm.nih.gov/pubmed/36516782',
'doi' => '10.1016/j.celrep.2022.111832',
'modified' => '2023-03-13 10:50:28',
'created' => '2023-02-28 12:19:11',
'ProductsPublication' => array(
[maximum depth reached]
)
),
(int) 5 => array(
'id' => '4490',
'name' => 'Repression and 3D-restructuring resolves regulatory conflicts inevolutionarily rearranged genomes.',
'authors' => 'Ringel A. et al.',
'description' => '<p>Regulatory landscapes drive complex developmental gene expression, but it remains unclear how their integrity is maintained when incorporating novel genes and functions during evolution. Here, we investigated how a placental mammal-specific gene, Zfp42, emerged in an ancient vertebrate topologically associated domain (TAD) without adopting or disrupting the conserved expression of its gene, Fat1. In ESCs, physical TAD partitioning separates Zfp42 and Fat1 with distinct local enhancers that drive their independent expression. This separation is driven by chromatin activity and not CTCF/cohesin. In contrast, in embryonic limbs, inactive Zfp42 shares Fat1's intact TAD without responding to active Fat1 enhancers. However, neither Fat1 enhancer-incompatibility nor nuclear envelope-attachment account for Zfp42's unresponsiveness. Rather, Zfp42's promoter is rendered inert to enhancers by context-dependent DNA methylation. Thus, diverse mechanisms enabled the integration of independent Zfp42 regulation in the Fat1 locus. Critically, such regulatory complexity appears common in evolution as, genome wide, most TADs contain multiple independently expressed genes.</p>',
'date' => '2022-09-01',
'pmid' => 'https://www.ncbi.nlm.nih.gov/pubmed/36179666',
'doi' => '10.1016/j.cell.2022.09.006',
'modified' => '2022-11-18 12:39:16',
'created' => '2022-11-15 09:26:20',
'ProductsPublication' => array(
[maximum depth reached]
)
),
(int) 6 => array(
'id' => '4220',
'name' => 'Effects of GSK-J4 on JMJD3 Histone Demethylase in Mouse Prostate Cancer Xenografts',
'authors' => 'Sanchez A. et al.',
'description' => '<p><strong class="sub-title">Background/aim:<span> </span></strong>Histone methylation status is required to control gene expression. H3K27me3 is an epigenetic tri-methylation modification to histone H3 controlled by the demethylase JMJD3. JMJD3 is dysregulated in a wide range of cancers and has been shown to control the expression of a specific growth-modulatory gene signature, making it an interesting candidate to better understand prostate tumor progression in vivo. This study aimed to identify the impact of JMJD3 inhibition by its inhibitor, GSK4, on prostate tumor growth in vivo.</p>
<p><strong class="sub-title">Materials and methods:<span> </span></strong>Prostate cancer cell lines were implanted into Balb/c nude male mice. The effects of the selective JMJD3 inhibitor GSK-J4 on tumor growth were analyzed by bioluminescence assays and H3K27me3-regulated changes in gene expression were analyzed by ChIP-qPCR and RT-qPCR.</p>
<p><strong class="sub-title">Results:<span> </span></strong>JMJD3 inhibition contributed to an increase in tumor growth in androgen-independent (AR-) xenografts and a decrease in androgen-dependent (AR+). GSK-J4 treatment modulated H3K27me3 enrichment on the gene panel in DU-145-luc xenografts while it had little effect on PC3-luc and no effect on LNCaP-luc. Effects of JMJD3 inhibition affected the panel gene expression.</p>
<p><strong class="sub-title">Conclusion:<span> </span></strong>JMJD3 has a differential effect in prostate tumor progression according to AR status. Our results suggest that JMJD3 is able to play a role independently of its demethylase function in androgen-independent prostate cancer. The effects of GSK-J4 on AR+ prostate xenografts led to a decrease in tumor growth.</p>',
'date' => '2022-05-01',
'pmid' => 'https://pubmed.ncbi.nlm.nih.gov/35430567/',
'doi' => '10.21873/cgp.20324',
'modified' => '2022-04-21 11:54:21',
'created' => '2022-04-21 11:54:21',
'ProductsPublication' => array(
[maximum depth reached]
)
),
(int) 7 => array(
'id' => '4554',
'name' => 'Immune disease variants modulate gene expression in regulatory CD4T cells.',
'authors' => 'Bossini-Castillo L. et al.',
'description' => '<p>Identifying cellular functions dysregulated by disease-associated variants could implicate novel pathways for drug targeting or modulation in cell therapies. However, follow-up studies can be challenging if disease-relevant cell types are difficult to sample. Variants associated with immune diseases point toward the role of CD4 regulatory T cells (Treg cells). We mapped genetic regulation (quantitative trait loci [QTL]) of gene expression and chromatin activity in Treg cells, and we identified 133 colocalizing loci with immune disease variants. Colocalizations of immune disease genome-wide association study (GWAS) variants with expression QTLs (eQTLs) controlling the expression of and , involved in Treg cell activation and interleukin-2 (IL-2) signaling, support the contribution of Treg cells to the pathobiology of immune diseases. Finally, we identified seven known drug targets suitable for drug repurposing and suggested 63 targets with drug tractability evidence among the GWAS signals that colocalized with Treg cell QTLs. Our study is the first in-depth characterization of immune disease variant effects on Treg cell gene expression modulation and dysregulation of Treg cell function.</p>',
'date' => '2022-04-01',
'pmid' => 'https://doi.org/10.1016%2Fj.xgen.2022.100117',
'doi' => '10.1016/j.xgen.2022.100117',
'modified' => '2022-11-24 09:28:15',
'created' => '2022-11-24 08:49:52',
'ProductsPublication' => array(
[maximum depth reached]
)
),
(int) 8 => array(
'id' => '4857',
'name' => 'Broad domains of histone marks in the highly compact macronucleargenome.',
'authors' => 'Drews F. et al.',
'description' => '<p>The unicellular ciliate contains a large vegetative macronucleus with several unusual characteristics, including an extremely high coding density and high polyploidy. As macronculear chromatin is devoid of heterochromatin, our study characterizes the functional epigenomic organization necessary for gene regulation and proper Pol II activity. Histone marks (H3K4me3, H3K9ac, H3K27me3) reveal no narrow peaks but broad domains along gene bodies, whereas intergenic regions are devoid of nucleosomes. Our data implicate H3K4me3 levels inside ORFs to be the main factor associated with gene expression, and H3K27me3 appears in association with H3K4me3 in plastic genes. Silent and lowly expressed genes show low nucleosome occupancy, suggesting that gene inactivation does not involve increased nucleosome occupancy and chromatin condensation. Because of a high occupancy of Pol II along highly expressed ORFs, transcriptional elongation appears to be quite different from that of other species. This is supported by missing heptameric repeats in the C-terminal domain of Pol II and a divergent elongation system. Our data imply that unoccupied DNA is the default state, whereas gene activation requires nucleosome recruitment together with broad domains of H3K4me3. In summary, gene activation and silencing in run counter to the current understanding of chromatin biology.</p>',
'date' => '2022-04-01',
'pmid' => 'https://www.ncbi.nlm.nih.gov/pubmed/35264449',
'doi' => '10.1101/gr.276126.121',
'modified' => '2023-08-01 14:45:37',
'created' => '2023-08-01 15:59:38',
'ProductsPublication' => array(
[maximum depth reached]
)
),
(int) 9 => array(
'id' => '4217',
'name' => 'CREBBP/EP300 acetyltransferase inhibition disrupts FOXA1-bound enhancers to inhibit the proliferation of ER+ breast cancer cells.',
'authors' => 'Bommi-Reddy A. et al.',
'description' => '<p><span>Therapeutic targeting of the estrogen receptor (ER) is a clinically validated approach for estrogen receptor positive breast cancer (ER+ BC), but sustained response is limited by acquired resistance. Targeting the transcriptional coactivators required for estrogen receptor activity represents an alternative approach that is not subject to the same limitations as targeting estrogen receptor itself. In this report we demonstrate that the acetyltransferase activity of coactivator paralogs CREBBP/EP300 represents a promising therapeutic target in ER+ BC. Using the potent and selective inhibitor CPI-1612, we show that CREBBP/EP300 acetyltransferase inhibition potently suppresses in vitro and in vivo growth of breast cancer cell line models and acts in a manner orthogonal to directly targeting ER. CREBBP/EP300 acetyltransferase inhibition suppresses ER-dependent transcription by targeting lineage-specific enhancers defined by the pioneer transcription factor FOXA1. These results validate CREBBP/EP300 acetyltransferase activity as a viable target for clinical development in ER+ breast cancer.</span></p>',
'date' => '2022-03-30',
'pmid' => 'https://pubmed.ncbi.nlm.nih.gov/35353838/',
'doi' => '10.1371/journal.pone.0262378',
'modified' => '2022-04-12 10:56:54',
'created' => '2022-04-12 10:56:54',
'ProductsPublication' => array(
[maximum depth reached]
)
),
(int) 10 => array(
'id' => '4379',
'name' => 'Screening of ETO2-GLIS2-induced Super Enhancers identifiestargetable cooperative dependencies in acute megakaryoblastic leukemia.',
'authors' => 'Benbarche S. et al.',
'description' => '<p>Super Enhancers (SEs) are clusters of regulatory elements associated with cell identity and disease. However, whether these elements are induced by oncogenes and can regulate gene modules cooperating for cancer cell transformation or maintenance remains elusive. To address this question, we conducted a genome-wide CRISPRi-based screening of SEs in ETO2-GLIS2 acute megakaryoblastic leukemia. This approach revealed SEs essential for leukemic cell growth and survival that are induced by ETO2-GLIS2 expression. In particular, we identified a de novo SE specific of this leukemia subtype and regulating expression of tyrosine kinase-associated receptors and . Combined expression of these two receptors was required for leukemic cell growth, and CRISPRi-mediated inhibition of this SE or treatment with tyrosine kinase inhibitors impaired progression of leukemia in vivo in patient-derived xenografts experiments. Our results show that fusion oncogenes, such as ETO2-GLIS2, can induce activation of SEs regulating essential gene modules synergizing for leukemia progression.</p>',
'date' => '2022-02-01',
'pmid' => 'https://www.ncbi.nlm.nih.gov/pubmed/35138899',
'doi' => '10.1126/sciadv.abg9455',
'modified' => '2022-08-04 16:20:06',
'created' => '2022-08-04 14:55:36',
'ProductsPublication' => array(
[maximum depth reached]
)
),
(int) 11 => array(
'id' => '4214',
'name' => 'Comprehensive characterization of the epigenetic landscape in Multiple Myeloma',
'authors' => 'Elina Alaterre et al.',
'description' => '<p>Background: Human multiple myeloma (MM) cell lines (HMCLs) have been widely used to understand the<br />molecular processes that drive MM biology. Epigenetic modifications are involved in MM development,<br />progression, and drug resistance. A comprehensive characterization of the epigenetic landscape of MM would<br />advance our understanding of MM pathophysiology and may attempt to identify new therapeutic targets.<br />Methods: We performed chromatin immunoprecipitation sequencing to analyze histone mark changes<br />(H3K4me1, H3K4me3, H3K9me3, H3K27ac, H3K27me3 and H3K36me3) on 16 HMCLs.<br />Results: Differential analysis of histone modification profiles highlighted links between histone modifications<br />and cytogenetic abnormalities or recurrent mutations. Using histone modifications associated to enhancer<br />regions, we identified super-enhancers (SE) associated with genes involved in MM biology. We also identified<br />promoters of genes enriched in H3K9me3 and H3K27me3 repressive marks associated to potential tumor<br />suppressor functions. The prognostic value of genes associated with repressive domains and SE was used to<br />build two distinct scores identifying high-risk MM patients in two independent cohorts (CoMMpass cohort; n =<br />674 and Montpellier cohort; n = 69). Finally, we explored H3K4me3 marks comparing drug-resistant and<br />-sensitive HMCLs to identify regions involved in drug resistance. From these data, we developed epigenetic<br />biomarkers based on the H3K4me3 modification predicting MM cell response to lenalidomide and histone<br />deacetylase inhibitors (HDACi).<br />Conclusions: The epigenetic landscape of MM cells represents a unique resource for future biological studies.<br />Furthermore, risk-scores based on SE and repressive regions together with epigenetic biomarkers of drug<br />response could represent new tools for precision medicine in MM.</p>',
'date' => '2022-01-16',
'pmid' => 'https://www.thno.org/v12p1715',
'doi' => '10.7150/thno.54453',
'modified' => '2022-01-27 13:17:28',
'created' => '2022-01-27 13:14:17',
'ProductsPublication' => array(
[maximum depth reached]
)
),
(int) 12 => array(
'id' => '4225',
'name' => 'Comprehensive characterization of the epigenetic landscape in Multiple
Myeloma',
'authors' => 'Alaterre, Elina and Ovejero, Sara and Herviou, Laurie and de
Boussac, Hugues and Papadopoulos, Giorgio and Kulis, Marta and
Boireau, Stéphanie and Robert, Nicolas and Requirand, Guilhem
and Bruyer, Angélique and Cartron, Guillaume and Vincent,
Laure and M',
'description' => 'Background: Human multiple myeloma (MM) cell lines (HMCLs) have
been widely used to understand the molecular processes that drive MM
biology. Epigenetic modifications are involved in MM development,
progression, and drug resistance. A comprehensive characterization of the
epigenetic landscape of MM would advance our understanding of MM
pathophysiology and may attempt to identify new therapeutic
targets.
Methods: We performed chromatin immunoprecipitation
sequencing to analyze histone mark changes (H3K4me1, H3K4me3,
H3K9me3, H3K27ac, H3K27me3 and H3K36me3) on 16
HMCLs.
Results: Differential analysis of histone modification
profiles highlighted links between histone modifications and cytogenetic
abnormalities or recurrent mutations. Using histone modifications
associated to enhancer regions, we identified super-enhancers (SE)
associated with genes involved in MM biology. We also identified
promoters of genes enriched in H3K9me3 and H3K27me3 repressive
marks associated to potential tumor suppressor functions. The prognostic
value of genes associated with repressive domains and SE was used to
build two distinct scores identifying high-risk MM patients in two
independent cohorts (CoMMpass cohort; n = 674 and Montpellier cohort;
n = 69). Finally, we explored H3K4me3 marks comparing drug-resistant
and -sensitive HMCLs to identify regions involved in drug resistance.
From these data, we developed epigenetic biomarkers based on the
H3K4me3 modification predicting MM cell response to lenalidomide and
histone deacetylase inhibitors (HDACi).
Conclusions: The epigenetic
landscape of MM cells represents a unique resource for future biological
studies. Furthermore, risk-scores based on SE and repressive regions
together with epigenetic biomarkers of drug response could represent new
tools for precision medicine in MM.',
'date' => '2022-01-01',
'pmid' => 'https://www.thno.org/v12p1715.htm',
'doi' => '10.7150/thno.54453',
'modified' => '2022-05-19 10:41:50',
'created' => '2022-05-19 10:41:50',
'ProductsPublication' => array(
[maximum depth reached]
)
),
(int) 13 => array(
'id' => '4244',
'name' => 'Developmental and Injury-induced Changes in DNA Methylation inRegenerative versus Non-regenerative Regions of the VertebrateCentral Nervous System',
'authors' => 'Reverdatto S. et al.',
'description' => '<p>Background Because some of its CNS neurons (e.g., retinal ganglion cells after optic nerve crush (ONC)) regenerate axons throughout life, whereas others (e.g., hindbrain neurons after spinal cord injury (SCI)) lose this capacity as tadpoles metamorphose into frogs, the South African claw-toed frog, Xenopus laevis, offers unique opportunities for exploring differences between regenerative and non-regenerative responses to CNS injury within the same organism. An earlier, three-way RNA-seq study (frog ONC eye, tadpole SCI hindbrain, frog SCI hindbrain) identified genes that regulate chromatin accessibility among those that were differentially expressed in regenerative vs non-regenerative CNS [11]. The current study used whole genome bisulfite sequencing (WGBS) of DNA collected from these same animals at the peak period of axon regeneration to study the extent to which DNA methylation could potentially underlie differences in chromatin accessibility between regenerative and non-regenerative CNS. Results Consistent with the hypothesis that DNA of regenerative CNS is more accessible than that of non-regenerative CNS, DNA from both the regenerative tadpole hindbrain and frog eye was less methylated than that of the non-regenerative frog hindbrain. Also, consistent with observations of CNS injury in mammals, DNA methylation in non-regenerative frog hindbrain decreased after SCI. However, contrary to expectations that the level of DNA methylation would decrease even further with axotomy in regenerative CNS, DNA methylation in these regions instead increased with injury. Injury-induced differences in CpG methylation in regenerative CNS became especially enriched in gene promoter regions, whereas non-CpG methylation differences were more evenly distributed across promoter regions, intergenic, and intragenic regions. In non-regenerative CNS, tissue-related (i.e., regenerative vs. non-regenerative CNS) and injury-induced decreases in promoter region CpG methylation were significantly correlated with increased RNA expression, but the injury-induced, increased CpG methylation seen in regenerative CNS across promoter regions was not, suggesting it was associated with increased rather than decreased chromatin accessibility. This hypothesis received support from observations that in regenerative CNS, many genes exhibiting increased, injury-induced, promoter-associated CpG-methylation also exhibited increased RNA expression and association with histone markers for active promoters and enhancers. DNA immunoprecipitation for 5hmC in optic nerve regeneration found that the promoter-associated increases seen in CpG methylation were distinct from those exhibiting changes in 5hmC. Conclusions Although seemingly paradoxical, the increased injury-associated DNA methylation seen in regenerative CNS has many parallels in stem cells and cancer. Thus, these axotomy-induced changes in DNA methylation in regenerative CNS provide evidence for a novel epigenetic state favoring successful over unsuccessful CNS axon regeneration. The datasets described in this study should help lay the foundations for future studies of the molecular and cellular mechanisms involved. The insights gained should, in turn, help point the way to novel therapeutic approaches for treating CNS injury in mammals. Supplementary Information The online version contains supplementary material available at 10.1186/s12864-021-08247-0.</p>',
'date' => '2022-01-01',
'pmid' => 'https://www.ncbi.nlm.nih.gov/pubmed/34979916',
'doi' => '10.1186/s12864-021-08247-0',
'modified' => '2022-05-20 09:20:25',
'created' => '2022-05-19 10:41:50',
'ProductsPublication' => array(
[maximum depth reached]
)
),
(int) 14 => array(
'id' => '4409',
'name' => 'Effects of GSK-J4 on JMJD3 Histone Demethylase in MouseProstate Cancer Xenografts.',
'authors' => 'Sanchez A. et al.',
'description' => '<p>BACKGROUND/AIM: Histone methylation status is required to control gene expression. H3K27me3 is an epigenetic tri-methylation modification to histone H3 controlled by the demethylase JMJD3. JMJD3 is dysregulated in a wide range of cancers and has been shown to control the expression of a specific growth-modulatory gene signature, making it an interesting candidate to better understand prostate tumor progression in vivo. This study aimed to identify the impact of JMJD3 inhibition by its inhibitor, GSK4, on prostate tumor growth in vivo. MATERIALS AND METHODS: Prostate cancer cell lines were implanted into Balb/c nude male mice. The effects of the selective JMJD3 inhibitor GSK-J4 on tumor growth were analyzed by bioluminescence assays and H3K27me3-regulated changes in gene expression were analyzed by ChIP-qPCR and RT-qPCR. RESULTS: JMJD3 inhibition contributed to an increase in tumor growth in androgen-independent (AR-) xenografts and a decrease in androgen-dependent (AR+). GSK-J4 treatment modulated H3K27me3 enrichment on the gene panel in DU-145-luc xenografts while it had little effect on PC3-luc and no effect on LNCaP-luc. Effects of JMJD3 inhibition affected the panel gene expression. CONCLUSION: JMJD3 has a differential effect in prostate tumor progression according to AR status. Our results suggest that JMJD3 is able to play a role independently of its demethylase function in androgen-independent prostate cancer. The effects of GSK-J4 on AR+ prostate xenografts led to a decrease in tumor growth.</p>',
'date' => '2022-01-01',
'pmid' => 'https://www.ncbi.nlm.nih.gov/pubmed/35430567',
'doi' => '10.21873/cgp.20324',
'modified' => '2022-08-11 15:11:58',
'created' => '2022-08-11 12:14:50',
'ProductsPublication' => array(
[maximum depth reached]
)
),
(int) 15 => array(
'id' => '4512',
'name' => 'Sp1-Induced SETDB1 Overexpression Transcriptionally InhibitsHPGD in a β-Catenin-Dependent Manner and Promotes theProliferation and Metastasis of Gastric Cancer',
'authors' => 'Fan Y. et al.',
'description' => '<p>Gastric cancer (GC) has high morbidity and mortality, the cure rate of surgical treatment and drug chemotherapy is not ideal. Therefore, development of new treatment strategies is necessary. We aimed to identify the mechanism underlying Sp1 regulation of GC progression.</p>',
'date' => '2022-01-01',
'pmid' => 'https://doi.org/10.5230%2Fjgc.2022.22.e26',
'doi' => '10.5230/jgc.2022.22.e26',
'modified' => '2022-11-24 08:39:02',
'created' => '2022-11-15 09:26:20',
'ProductsPublication' => array(
[maximum depth reached]
)
),
(int) 16 => array(
'id' => '4329',
'name' => 'Epigenetic remodelling of enhancers in response to estrogen deprivationand re-stimulation.',
'authors' => 'Sklias Athena et al.',
'description' => '<p>Estrogen hormones are implicated in a majority of breast cancers and estrogen receptor alpha (ER), the main nuclear factor mediating estrogen signaling, orchestrates a complex molecular circuitry that is not yet fully elucidated. Here, we investigated genome-wide DNA methylation, histone acetylation and transcription after estradiol (E2) deprivation and re-stimulation to better characterize the ability of ER to coordinate gene regulation. We found that E2 deprivation mostly resulted in DNA hypermethylation and histone deacetylation in enhancers. Transcriptome analysis revealed that E2 deprivation leads to a global down-regulation in gene expression, and more specifically of TET2 demethylase that may be involved in the DNA hypermethylation following short-term E2 deprivation. Further enrichment analysis of transcription factor (TF) binding and motif occurrence highlights the importance of ER connection mainly with two partner TF families, AP-1 and FOX. These interactions take place in the proximity of E2 deprivation-mediated differentially methylated and histone acetylated enhancers. Finally, while most deprivation-dependent epigenetic changes were reversed following E2 re-stimulation, DNA hypermethylation and H3K27 deacetylation at certain enhancers were partially retained. Overall, these results show that inactivation of ER mediates rapid and mostly reversible epigenetic changes at enhancers, and bring new insight into early events, which may ultimately lead to endocrine resistance.</p>',
'date' => '2021-09-01',
'pmid' => 'https://doi.org/10.1093%2Fnar%2Fgkab697',
'doi' => '10.1093/nar/gkab697',
'modified' => '2022-06-22 09:25:09',
'created' => '2022-05-19 10:41:50',
'ProductsPublication' => array(
[maximum depth reached]
)
),
(int) 17 => array(
'id' => '4273',
'name' => 'An integrated multi-omics analysis identifies prognostic molecularsubtypes of non-muscle-invasive bladder cancer',
'authors' => 'Lindskrog Sia Viborg et al.',
'description' => '<p>The molecular landscape in non-muscle-invasive bladder cancer (NMIBC) is characterized by large biological heterogeneity with variable clinical outcomes. Here, we perform an integrative multi-omics analysis of patients diagnosed with NMIBC (n = 834). Transcriptomic analysis identifies four classes (1, 2a, 2b and 3) reflecting tumor biology and disease aggressiveness. Both transcriptome-based subtyping and the level of chromosomal instability provide independent prognostic value beyond established prognostic clinicopathological parameters. High chromosomal instability, p53-pathway disruption and APOBEC-related mutations are significantly associated with transcriptomic class 2a and poor outcome. RNA-derived immune cell infiltration is associated with chromosomally unstable tumors and enriched in class 2b. Spatial proteomics analysis confirms the higher infiltration of class 2b tumors and demonstrates an association between higher immune cell infiltration and lower recurrence rates. Finally, the independent prognostic value of the transcriptomic classes is documented in 1228 validation samples using a single sample classification tool. The classifier provides a framework for biomarker discovery and for optimizing treatment and surveillance in next-generation clinical trials.</p>',
'date' => '2021-04-01',
'pmid' => 'https://www.ncbi.nlm.nih.gov/pubmed/33863885',
'doi' => '10.1038/s41467-021-22465-w',
'modified' => '2022-05-23 09:49:43',
'created' => '2022-05-19 10:41:50',
'ProductsPublication' => array(
[maximum depth reached]
)
),
(int) 18 => array(
'id' => '4196',
'name' => 'Functional annotations of three domestic animal genomes provide vitalresources for comparative and agricultural research.',
'authors' => 'Kern C. et al.',
'description' => '<p>Gene regulatory elements are central drivers of phenotypic variation and thus of critical importance towards understanding the genetics of complex traits. The Functional Annotation of Animal Genomes consortium was formed to collaboratively annotate the functional elements in animal genomes, starting with domesticated animals. Here we present an expansive collection of datasets from eight diverse tissues in three important agricultural species: chicken (Gallus gallus), pig (Sus scrofa), and cattle (Bos taurus). Comparative analysis of these datasets and those from the human and mouse Encyclopedia of DNA Elements projects reveal that a core set of regulatory elements are functionally conserved independent of divergence between species, and that tissue-specific transcription factor occupancy at regulatory elements and their predicted target genes are also conserved. These datasets represent a unique opportunity for the emerging field of comparative epigenomics, as well as the agricultural research community, including species that are globally important food resources.</p>',
'date' => '2021-03-01',
'pmid' => 'https://doi.org/10.1038%2Fs41467-021-22100-8',
'doi' => '10.1038/s41467-021-22100-8',
'modified' => '2022-01-06 14:30:41',
'created' => '2021-12-06 15:53:19',
'ProductsPublication' => array(
[maximum depth reached]
)
),
(int) 19 => array(
'id' => '4164',
'name' => 'Chromatin dysregulation associated with NSD1 mutation in head and necksquamous cell carcinoma.',
'authors' => 'Farhangdoost, Nargess et al. ',
'description' => '<p>Chromatin dysregulation has emerged as an important mechanism of oncogenesis. To develop targeted treatments, it is important to understand the transcriptomic consequences of mutations in chromatin modifier genes. Recently, mutations in the histone methyltransferase gene nuclear receptor binding SET domain protein 1 (NSD1) have been identified in a subset of common and deadly head and neck squamous cell carcinomas (HNSCCs). Here, we use genome-wide approaches and genome editing to dissect the downstream effects of loss of NSD1 in HNSCC. We demonstrate that NSD1 mutations are responsible for loss of intergenic H3K36me2 domains, followed by loss of DNA methylation and gain of H3K27me3 in the affected genomic regions. In addition, those regions are enriched in cis-regulatory elements, and subsequent loss of H3K27ac correlates with reduced expression of their target genes. Our analysis identifies genes and pathways affected by the loss of NSD1 and paves the way to further understanding the interplay among chromatin modifications in cancer.</p>',
'date' => '2021-02-01',
'pmid' => 'https://www.ncbi.nlm.nih.gov/pubmed/33626351',
'doi' => '10.1016/j.celrep.2021.108769',
'modified' => '2021-12-21 15:35:45',
'created' => '2021-12-06 15:53:19',
'ProductsPublication' => array(
[maximum depth reached]
)
),
(int) 20 => array(
'id' => '4185',
'name' => 'A distinct metabolic response characterizes sensitivity to EZH2inhibition in multiple myeloma.',
'authors' => 'Nylund P. et al.',
'description' => '<p>Multiple myeloma (MM) is a heterogeneous haematological disease that remains clinically challenging. Increased activity of the epigenetic silencer EZH2 is a common feature in patients with poor prognosis. Previous findings have demonstrated that metabolic profiles can be sensitive markers for response to treatment in cancer. While EZH2 inhibition (EZH2i) has proven efficient in inducing cell death in a number of human MM cell lines, we hereby identified a subset of cell lines that despite a global loss of H3K27me3, remains viable after EZH2i. By coupling liquid chromatography-mass spectrometry with gene and miRNA expression profiling, we found that sensitivity to EZH2i correlated with distinct metabolic signatures resulting from a dysregulation of genes involved in methionine cycling. Specifically, EZH2i resulted in a miRNA-mediated downregulation of methionine cycling-associated genes in responsive cells. This induced metabolite accumulation and DNA damage, leading to G2 arrest and apoptosis. Altogether, we unveiled that sensitivity to EZH2i in human MM cell lines is associated with a specific metabolic and gene expression profile post-treatment.</p>',
'date' => '2021-02-01',
'pmid' => 'https://www.ncbi.nlm.nih.gov/pubmed/33579905',
'doi' => '10.1038/s41419-021-03447-8',
'modified' => '2022-01-05 14:59:39',
'created' => '2021-12-06 15:53:19',
'ProductsPublication' => array(
[maximum depth reached]
)
),
(int) 21 => array(
'id' => '4187',
'name' => 'A brain cyst load-associated antigen is a Toxoplasma gondii biomarker forserodetection of persistent parasites and chronic infection.',
'authors' => 'Dard C. et al.',
'description' => '<p>BACKGROUND: Biomarker discovery remains a major challenge for predictive medicine, in particular, in the context of chronic diseases. This is true for the widespread protozoan Toxoplasma gondii which establishes long-lasting parasitism in metazoans, humans included. This microbe successively unfolds distinct genetic programs that direct the transition from high to low replicative potential inside host cells. As a slow-replicating cell, the T. gondii bradyzoite developmental stage persists enclosed in a cyst compartment within tissues including the nervous system, being held by a sustained immune equilibrium which accounts for the prolonged clinically silent phase of parasitism. Serological surveys indicate that nearly one third of the human population has been exposed to T. gondii and possibly host bradyzoites. Because any disruption of the immune balance drives the reverse transition from bradyzoite to fast replicating tachyzoite and uncontrolled growth of the latter, these people are at risk for life-threatening disease. While serological tests for discriminating recent from past infection are available, there is yet no immunogenic biomarker used in the serological test to allow ascertaining the presence of persistent bradyzoites. RESULTS: Capitalizing on genetically engineered parasites induced to produce mature bradyzoites in vitro, we have identified the BCLA/MAG2 protein being restricted to the bradyzoite and the cyst envelope. Using laboratory mice as relevant T. gondii host models, we demonstrated that BCLA/MAG2 drives the generation of antibodies that recognize bradyzoite and the enveloping cyst structure. We have designed an ELISA assay based on a bacterially produced BCLA recombinant polypeptide, which was validated using a large collection of sera from mice of different genetic backgrounds and infected with bcla+ or bcla-null cystogenic and non-cystogenic T. gondii strains. To refine the design of the ELISA assay, we applied high-resolution BCLA epitope mapping and identified a specific combination of peptides and accordingly set up a selective and sensitive ELISA assay which allowed the detection of anti-BCLA/MAG2 antibodies in the sera of human patients with various forms of toxoplasmosis. CONCLUSIONS: We brought proof of principle that anti-BCLA/MAG2 antibodies serve as specific and sensitive serological markers in the perspective of a combinatorial strategy for detection of persistent T. gondii parasitism.</p>',
'date' => '2021-02-01',
'pmid' => 'https://www.ncbi.nlm.nih.gov/pubmed/33557824',
'doi' => '10.1186/s12915-021-00959-9',
'modified' => '2022-01-05 15:04:11',
'created' => '2021-12-06 15:53:19',
'ProductsPublication' => array(
[maximum depth reached]
)
),
(int) 22 => array(
'id' => '4056',
'name' => 'Multi-omic comparison of Alzheimer's variants in human ESC-derivedmicroglia reveals convergence at APOE.',
'authors' => 'Liu, Tongfei and Zhu, Bing and Liu, Yan and Zhang, Xiaoming and Yin, Junand Li, Xiaoguang and Jiang, LuLin and Hodges, Andrew P and Rosenthal, SaraBrin and Zhou, Lisa and Yancey, Joel and McQuade, Amanda and Blurton-Jones,Mathew and Tanzi, Rudolph E an',
'description' => '<p>Variations in many genes linked to sporadic Alzheimer's disease (AD) show abundant expression in microglia, but relationships among these genes remain largely elusive. Here, we establish isogenic human ESC-derived microglia-like cell lines (hMGLs) harboring AD variants in CD33, INPP5D, SORL1, and TREM2 loci and curate a comprehensive atlas comprising ATAC-seq, ChIP-seq, RNA-seq, and proteomics datasets. AD-like expression signatures are observed in AD mutant SORL1 and TREM2 hMGLs, while integrative multi-omic analysis of combined epigenetic and expression datasets indicates up-regulation of APOE as a convergent pathogenic node. We also observe cross-regulatory relationships between SORL1 and TREM2, in which SORL1R744X hMGLs induce TREM2 expression to enhance APOE expression. AD-associated SORL1 and TREM2 mutations also impaired hMGL Aβ uptake in an APOE-dependent manner in vitro and attenuated Aβ uptake/clearance in mouse AD brain xenotransplants. Using this modeling and analysis platform for human microglia, we provide new insight into epistatic interactions in AD genes and demonstrate convergence of microglial AD genes at the APOE locus.</p>',
'date' => '2020-12-01',
'pmid' => 'https://www.ncbi.nlm.nih.gov/pubmed/32941599',
'doi' => '10.1084/jem.20200474',
'modified' => '2021-02-19 17:18:23',
'created' => '2021-02-18 10:21:53',
'ProductsPublication' => array(
[maximum depth reached]
)
),
(int) 23 => array(
'id' => '4331',
'name' => 'Kaposi’s Sarcoma-Associated Herpesvirus Processivity Factor,ORF59, Binds to Canonical and Linker Histones, and ItsCarboxy Terminus Is Dispensable for Viral DNA Synthesis',
'authors' => 'Gutierrez IV et al.',
'description' => '<p>Kaposi’s sarcoma-associated herpesvirus (KSHV) is an oncogenic virus and the causative agent of potentially fatal malignancies. Lytic replication of KSHV is an essential part of the viral life cycle, allowing for virus dissemination within the infected host and shedding to infect naive hosts.</p>',
'date' => '2020-12-01',
'pmid' => 'https://www.ncbi.nlm.nih.gov/pubmed/33361421',
'doi' => '10.1128/JVI.02169-20',
'modified' => '2022-08-03 17:10:55',
'created' => '2022-05-19 10:41:50',
'ProductsPublication' => array(
[maximum depth reached]
)
),
(int) 24 => array(
'id' => '4040',
'name' => 'Genomic profiling of T-cell activation suggests increased sensitivity ofmemory T cells to CD28 costimulation.',
'authors' => 'Glinos, Dafni A and Soskic, Blagoje and Williams, Cayman and Kennedy, Alanand Jostins, Luke and Sansom, David M and Trynka, Gosia',
'description' => '<p>T-cell activation is a critical driver of immune responses. The CD28 costimulation is an essential regulator of CD4 T-cell responses, however, its relative importance in naive and memory T cells is not fully understood. Using different model systems, we observe that human memory T cells are more sensitive to CD28 costimulation than naive T cells. To deconvolute how the T-cell receptor (TCR) and CD28 orchestrate activation of human T cells, we stimulate cells using varying intensities of TCR and CD28 and profiled gene expression. We show that genes involved in cell cycle progression and division are CD28-driven in memory cells, but under TCR control in naive cells. We further demonstrate that T-helper differentiation and cytokine expression are controlled by CD28. Using chromatin accessibility profiling, we observe that AP1 transcriptional regulation is enriched when both TCR and CD28 are engaged, whereas open chromatin near CD28-sensitive genes is enriched for NF-kB motifs. Lastly, we show that CD28-sensitive genes are enriched in GWAS regions associated with immune diseases, implicating a role for CD28 in disease development. Our study provides important insights into the differential role of costimulation in naive and memory T-cell responses and disease susceptibility.</p>',
'date' => '2020-11-01',
'pmid' => 'https://www.ncbi.nlm.nih.gov/pubmed/33223527',
'doi' => '10.1038/s41435-020-00118-0',
'modified' => '2021-02-19 12:08:04',
'created' => '2021-02-18 10:21:53',
'ProductsPublication' => array(
[maximum depth reached]
)
),
(int) 25 => array(
'id' => '4083',
'name' => 'H3K27M in Gliomas Causes a One-Step Decrease in H3K27 Methylation andReduced Spreading within the Constraints of H3K36 Methylation.',
'authors' => 'Harutyunyan, Ashot S and Chen, Haifen and Lu, Tianyuan and Horth, Cynthiaand Nikbakht, Hamid and Krug, Brian and Russo, Caterina and Bareke, Ericand Marchione, Dylan M and Coradin, Mariel and Garcia, Benjamin A andJabado, Nada and Majewski, Jacek',
'description' => '<p>The discovery of H3K27M mutations in pediatric gliomas marked a new chapter in cancer epigenomics. Numerous studies have investigated the effect of this mutation on H3K27 trimethylation, but only recently have we started to realize its additional effects on the epigenome. Here, we use isogenic glioma H3K27M cell lines to investigate H3K27 methylation and its interaction with H3K36 and H3K9 modifications. We describe a "step down" effect of H3K27M on the distribution of H3K27 methylation: me3 is reduced to me2, me2 is reduced to me1, whereas H3K36me2/3 delineates the boundaries for the spread of H3K27me marks. We also observe a replacement of H3K27me2/3 silencing by H3K9me3. Using a computational simulation, we explain our observations by reduced effectiveness of PRC2 and constraints imposed on the deposition of H3K27me by antagonistic H3K36 modifications. Our work further elucidates the effects of H3K27M in gliomas as well as the general principles of deposition in H3K27 methylation.</p>',
'date' => '2020-11-01',
'pmid' => 'https://www.ncbi.nlm.nih.gov/pubmed/33207202',
'doi' => '10.1016/j.celrep.2020.108390',
'modified' => '2021-03-15 17:05:20',
'created' => '2021-02-18 10:21:53',
'ProductsPublication' => array(
[maximum depth reached]
)
),
(int) 26 => array(
'id' => '4086',
'name' => 'Macrophage Immune Memory Controls Endometriosis in Mice and Humans.',
'authors' => 'Jeljeli, Mohamed and Riccio, Luiza G C and Chouzenoux, Sandrine and Moresi,Fabiana and Toullec, Laurie and Doridot, Ludivine and Nicco, Carole andBourdon, Mathilde and Marcellin, Louis and Santulli, Pietro and Abrão,Mauricio S and Chapron, Charles and ',
'description' => '<p>Endometriosis is a frequent, chronic, inflammatory gynecological disease characterized by the presence of ectopic endometrial tissue causing pain and infertility. Macrophages have a central role in lesion establishment and maintenance by driving chronic inflammation and tissue remodeling. Macrophages can be reprogrammed to acquire memory-like characteristics after antigenic challenge to reinforce or inhibit a subsequent immune response, a phenomenon termed "trained immunity." Here, whereas bacille Calmette-Guérin (BCG) training enhances the lesion growth in a mice model of endometriosis, tolerization with repeated low doses of lipopolysaccharide (LPS) or adoptive transfer of LPS-tolerized macrophages elicits a suppressor effect. LPS-tolerized human macrophages mitigate the fibro-inflammatory phenotype of endometriotic cells in an interleukin-10 (IL-10)-dependent manner. A history of severe Gram-negative infection is associated with reduced infertility duration and alleviated symptoms, in contrast to patients with Gram-positive infection history. Thus, the manipulation of innate immune memory may be effective in dampening hyper-inflammatory conditions, opening the way to promising therapeutic approaches.</p>',
'date' => '2020-11-01',
'pmid' => 'https://www.ncbi.nlm.nih.gov/pubmed/33147452',
'doi' => '10.1016/j.celrep.2020.108325',
'modified' => '2021-03-15 17:14:08',
'created' => '2021-02-18 10:21:53',
'ProductsPublication' => array(
[maximum depth reached]
)
),
(int) 27 => array(
'id' => '4197',
'name' => 'Derivation of Intermediate Pluripotent Stem Cells Amenable to PrimordialGerm Cell Specification.',
'authors' => 'Yu L. et al.',
'description' => '<p>Dynamic pluripotent stem cell (PSC) states are in vitro adaptations of pluripotency continuum in vivo. Previous studies have generated a number of PSCs with distinct properties. To date, however, no known PSCs have demonstrated dual competency for chimera formation and direct responsiveness to primordial germ cell (PGC) specification, a unique functional feature of formative pluripotency. Here, by modulating fibroblast growth factor (FGF), transforming growth factor β (TGF-β), and WNT pathways, we derived PSCs from mice, horses, and humans (designated as XPSCs) that are permissive for direct PGC-like cell induction in vitro and are capable of contributing to intra- or inter-species chimeras in vivo. XPSCs represent a pluripotency state between naive and primed pluripotency and harbor molecular, cellular, and phenotypic features characteristic of formative pluripotency. XPSCs open new avenues for studying mammalian pluripotency and dissecting the molecular mechanisms governing PGC specification. Our method may be broadly applicable for the derivation of analogous stem cells from other mammalian species.</p>',
'date' => '2020-11-01',
'pmid' => 'https://www.ncbi.nlm.nih.gov/pubmed/33271070',
'doi' => '10.1016/j.stem.2020.11.003',
'modified' => '2022-01-06 14:35:44',
'created' => '2021-12-06 15:53:19',
'ProductsPublication' => array(
[maximum depth reached]
)
),
(int) 28 => array(
'id' => '4087',
'name' => 'Radiation-induced H3K9 methylation on E-cadherin promoter mediated byROS/Snail axis : Role of G9a signaling during lung epithelial-mesenchymaltransition.',
'authors' => 'Nagaraja, SunilGowda Sunnaghatta and Subramanian, Umadevi and Nagarajan,Devipriya',
'description' => '<p>Lung cancer patients who have undergone radiotherapy developed severe complications such as pneumonitis and fibrosis. Upon irradiation, epithelial cells acquire mesenchymal phenotype via a process called epithelial to mesenchymal transition (EMT), which plays a vital role in organ fibrosis. Several mechanisms have been studied on EMT, however, the correlation between radiation-induced EMT and epigenetic changes are not well known. In the present study, we investigated the role of histone methyltransferase G9a on radiation-induced EMT signaling. There was an increase in total global histone methylation level in irradiated epithelial cells. Western blot analysis on irradiated cells showed an increased expression of H3K9me2/3. The pre-treatment of G9a inhibitor enhanced E-cadherin expression and decreased the mesenchymal markers like N-cadherin, vimentin in the radiated group. Surprisingly, radiation-induced ROS generation and pERK1/2 levels were also inhibited by G9a inhibitor BIX01294, which is showing its antioxidant potential. The ChIP-qPCR analysis on the E-cadherin promoter suggested that G9a and Snail might have formed complex to enrich suppressive marker H3K9me2/3. On the whole, our present study suggested that 1] ROS could modify H3K9 methylation via G9a and promote radiation-induced lung EMT in Beas2B and A549 cells 2] E-cadherin promoter enrichment with heterochromatin mark H3K9me2 expression upon irradiation could be modified by regulating G9a methyltransferase.</p>',
'date' => '2020-10-01',
'pmid' => 'https://www.ncbi.nlm.nih.gov/pubmed/33148527',
'doi' => '10.1016/j.tiv.2020.105037',
'modified' => '2021-03-15 17:16:05',
'created' => '2021-02-18 10:21:53',
'ProductsPublication' => array(
[maximum depth reached]
)
),
(int) 29 => array(
'id' => '4092',
'name' => 'Formation of the CenH3-Deficient Holocentromere in Lepidoptera AvoidsActive Chromatin.',
'authors' => 'Senaratne, Aruni P and Muller, Héloïse and Fryer, Kelsey A and Kawamoto,Munetaka and Katsuma, Susumu and Drinnenberg, Ines A',
'description' => '<p>Despite the essentiality for faithful chromosome segregation, centromere architectures are diverse among eukaryotes and embody two main configurations: mono- and holocentromeres, referring, respectively, to localized or unrestricted distribution of centromeric activity. Of the two, some holocentromeres offer the curious condition of having arisen independently in multiple insects, most of which have lost the otherwise essential centromere-specifying factor CenH3 (first described as CENP-A in humans). The loss of CenH3 raises intuitive questions about how holocentromeres are organized and regulated in CenH3-lacking insects. Here, we report the first chromatin-level description of CenH3-deficient holocentromeres by leveraging recently identified centromere components and genomics approaches to map and characterize the holocentromeres of the silk moth Bombyx mori, a representative lepidopteran insect lacking CenH3. This uncovered a robust correlation between the distribution of centromere sites and regions of low chromatin activity along B. mori chromosomes. Transcriptional perturbation experiments recapitulated the exclusion of B. mori centromeres from active chromatin. Based on reciprocal centromere occupancy patterns observed along differentially expressed orthologous genes of Lepidoptera, we further found that holocentromere formation in a manner that is recessive to chromatin dynamics is evolutionarily conserved. Our results help us discuss the plasticity of centromeres in the context of a role for the chromosome-wide chromatin landscape in conferring centromere identity rather than the presence of CenH3. Given the co-occurrence of CenH3 loss and holocentricity in insects, we further propose that the evolutionary establishment of holocentromeres in insects was facilitated through the loss of a CenH3-specified centromere.</p>',
'date' => '2020-10-01',
'pmid' => 'https://www.ncbi.nlm.nih.gov/pubmed/33125865',
'doi' => '10.1016/j.cub.2020.09.078',
'modified' => '2021-03-17 17:13:50',
'created' => '2021-02-18 10:21:53',
'ProductsPublication' => array(
[maximum depth reached]
)
),
(int) 30 => array(
'id' => '4091',
'name' => 'Epigenetic regulation of the lineage specificity of primary human dermallymphatic and blood vascular endothelial cells.',
'authors' => 'Tacconi, Carlotta and He, Yuliang and Ducoli, Luca and Detmar, Michael',
'description' => '<p>Lymphatic and blood vascular endothelial cells (ECs) share several molecular and developmental features. However, these two cell types possess distinct phenotypic signatures, reflecting their different biological functions. Despite significant advances in elucidating how the specification of lymphatic and blood vascular ECs is regulated at the transcriptional level during development, the key molecular mechanisms governing their lineage identity under physiological or pathological conditions remain poorly understood. To explore the epigenomic signatures in the maintenance of EC lineage specificity, we compared the transcriptomic landscapes, histone composition (H3K4me3 and H3K27me3) and DNA methylomes of cultured matched human primary dermal lymphatic and blood vascular ECs. Our findings reveal that blood vascular lineage genes manifest a more 'repressed' histone composition in lymphatic ECs, whereas DNA methylation at promoters is less linked to the differential transcriptomes of lymphatic versus blood vascular ECs. Meta-analyses identified two transcriptional regulators, BCL6 and MEF2C, which potentially govern endothelial lineage specificity. Notably, the blood vascular endothelial lineage markers CD34, ESAM and FLT1 and the lymphatic endothelial lineage markers PROX1, PDPN and FLT4 exhibited highly differential epigenetic profiles and responded in distinct manners to epigenetic drug treatments. The perturbation of histone and DNA methylation selectively promoted the expression of blood vascular endothelial markers in lymphatic endothelial cells, but not vice versa. Overall, our study reveals that the fine regulation of lymphatic and blood vascular endothelial transcriptomes is maintained via several epigenetic mechanisms, which are crucial to the maintenance of endothelial cell identity.</p>',
'date' => '2020-09-01',
'pmid' => 'https://www.ncbi.nlm.nih.gov/pubmed/32918672',
'doi' => '10.1007/s10456-020-09743-9',
'modified' => '2021-03-17 17:09:36',
'created' => '2021-02-18 10:21:53',
'ProductsPublication' => array(
[maximum depth reached]
)
),
(int) 31 => array(
'id' => '4027',
'name' => 'N-Methyladenosine co-transcriptionally directs the demethylation of histoneH3K9me2.',
'authors' => 'Li, Y and Xia, L and Tan, K and Ye, X and Zuo, Z and Li, M and Xiao, R andWang, Z and Liu, X and Deng, M and Cui, J and Yang, M and Luo, Q and Liu, Sand Cao, X and Zhu, H and Liu, T and Hu, J and Shi, J and Xiao, S',
'description' => '<p>A dynamic epigenome is critical for appropriate gene expression in development and health. Central to this is the intricate process of transcription, which integrates cellular signaling with chromatin changes, transcriptional machinery and modifications to messenger RNA, such as N-methyladenosine (mA), which is co-transcriptionally incorporated. The integration of these aspects of the dynamic epigenome, however, is not well understood mechanistically. Here we show that the repressive histone mark H3K9me2 is specifically removed by the induction of mA-modified transcripts. We demonstrate that the methyltransferase METTL3/METTL14 regulates H3K9me2 modification. We observe a genome-wide correlation between mA and occupancy by the H3K9me2 demethylase KDM3B, and we find that the mA reader YTHDC1 physically interacts with and recruits KDM3B to mA-associated chromatin regions, promoting H3K9me2 demethylation and gene expression. This study establishes a direct link between mA and dynamic chromatin modification and provides mechanistic insight into the co-transcriptional interplay between RNA modifications and histone modifications.</p>',
'date' => '2020-08-10',
'pmid' => 'http://www.pubmed.gov/32778823',
'doi' => '10.1038/s41588-020-0677-3',
'modified' => '2020-12-16 17:54:08',
'created' => '2020-10-12 14:54:59',
'ProductsPublication' => array(
[maximum depth reached]
)
),
(int) 32 => array(
'id' => '3928',
'name' => 'Combined deletion of Bap1, Nf2, and Cdkn2ab causes rapid onset of malignant mesothelioma in mice.',
'authors' => 'Badhai J, Pandey GK, Song JY, Krijgsman O, Bhaskaran R, Chandrasekaran G, Kwon MC, Bombardelli L, Monkhorst K, Grasso C, Zevenhoven J, van der Vliet J, Cozijnsen M, Krimpenfort P, Peeper D, van Lohuizen M, Berns A',
'description' => '<p>We have generated mouse models of malignant mesothelioma (MM) based upon disruption of the Bap1, Nf2, and Cdkn2ab tumor suppressor loci in various combinations as also frequently observed in human MM. Inactivation of all three loci in the mesothelial lining of the thoracic cavity leads to a highly aggressive MM that recapitulates the histological features and gene expression profile observed in human patients. The tumors also show a similar inflammatory phenotype. Bap1 deletion alone does not cause MM but dramatically accelerates MM development when combined with Nf2 and Cdkn2ab (hereafter BNC) disruption. The accelerated tumor development is accompanied by increased Polycomb repression and EZH2-mediated redistribution of H3K27me3 toward promoter sites with concomitant activation of PI3K and MAPK pathways. Treatment of BNC tumor-bearing mice with cisplatin and pemetrexed, the current frontline treatment, prolongs survival. This makes the autochthonous mouse model described here very well suited to explore the pathogenesis of MM and validate new treatment regimens for MM, including immunotherapy.</p>',
'date' => '2020-06-01',
'pmid' => 'http://www.pubmed.gov/32271879',
'doi' => '10.1084/jem.20191257',
'modified' => '2020-08-17 10:47:22',
'created' => '2020-08-10 12:12:25',
'ProductsPublication' => array(
[maximum depth reached]
)
),
(int) 33 => array(
'id' => '3957',
'name' => 'Restoration of KMT2C/MLL3 in human colorectal cancer cells reinforces genome-wide H3K4me1 profiles and influences cell growth and gene expression.',
'authors' => 'Larsson C, Cordeddu L, Siggens L, Pandzic T, Kundu S, He L, Ali MA, Pristovšek N, Hartman K, Ekwall K, Sjöblom T',
'description' => '<p>BACKGROUND: The histone 3 lysine 4 (H3K4) monomethylase KMT2C is mutated across several cancer types; however, the effects of mutations on epigenome organization, gene expression, and cell growth are not clear. A frequently recurring mutation in colorectal cancer (CRC) with microsatellite instability is a single nucleotide deletion within the exon 38 poly-A(9) repeat (c.8390delA) which results in frameshift preceding the functional carboxy-terminal SET domain. To study effects of KMT2C expression in CRC cells, we restored one allele to wild type KMT2C in the two CRC cell lines RKO and HCT116, which both are homozygous c.8390delA mutant. RESULTS: Gene editing resulted in increased KMT2C expression, increased H3K4me1 levels, altered gene expression profiles, and subtle negative effects on cell growth, where higher dependence and stronger effects of KMT2C expression were observed in RKO compared to HCT116 cells. Surprisingly, we found that the two RKO and HCT116 CRC cell lines have distinct baseline H3K4me1 epigenomic profiles. In RKO cells, a flatter genome-wide H3K4me1 profile was associated with more increased H3K4me1 deposition at enhancers, reduced cell growth, and more differential gene expression relative to HCT116 cells when KMT2C was restored. Profiling of H3K4me1 did not indicate a highly specific regulation of gene expression as KMT2C-induced H3K4me1 deposition was found globally and not at a specific enhancer sub-set in the engineered cells. Although we observed variation in differentially regulated gene sets between cell lines and individual clones, differentially expressed genes in both cell lines included genes linked to known cancer signaling pathways, estrogen response, hypoxia response, and aspects of immune system regulation. CONCLUSIONS: Here, KMT2C restoration reduced CRC cell growth and reinforced genome-wide H3K4me1 deposition at enhancers; however, the effects varied depending upon the H3K4me1 status of KMT2C deficient cells. Results indicate that KMT2C inactivation may promote colorectal cancer development through transcriptional dysregulation in several pathways with known cancer relevance.</p>',
'date' => '2020-05-29',
'pmid' => 'http://www.pubmed.gov/32471474',
'doi' => '10.1186/s13148-020-00863-z',
'modified' => '2020-08-17 09:10:54',
'created' => '2020-08-10 12:12:25',
'ProductsPublication' => array(
[maximum depth reached]
)
),
(int) 34 => array(
'id' => '3922',
'name' => 'Multi-omic analysis of gametogenesis reveals a novel signature at the promoters and distal enhancers of active genes.',
'authors' => 'Crespo M, Damont A, Blanco M, Lastrucci E, Kennani SE, Ialy-Radio C, Khattabi LE, Terrier S, Louwagie M, Kieffer-Jaquinod S, Hesse AM, Bruley C, Chantalat S, Govin J, Fenaille F, Battail C, Cocquet J, Pflieger D',
'description' => '<p>Epigenetic regulation of gene expression is tightly controlled by the dynamic modification of histones by chemical groups, the diversity of which has largely expanded over the past decade with the discovery of lysine acylations, catalyzed from acyl-coenzymes A. We investigated the dynamics of lysine acetylation and crotonylation on histones H3 and H4 during mouse spermatogenesis. Lysine crotonylation appeared to be of significant abundance compared to acetylation, particularly on Lys27 of histone H3 (H3K27cr) that accumulates in sperm in a cleaved form of H3. We identified the genomic localization of H3K27cr and studied its effects on transcription compared to the classical active mark H3K27ac at promoters and distal enhancers. The presence of both marks was strongly associated with highest gene expression. Assessment of their co-localization with transcription regulators (SLY, SOX30) and chromatin-binding proteins (BRD4, BRDT, BORIS and CTCF) indicated systematic highest binding when both active marks were present and different selective binding when present alone at chromatin. H3K27cr and H3K27ac finally mark the building of some sperm super-enhancers. This integrated analysis of omics data provides an unprecedented level of understanding of gene expression regulation by H3K27cr in comparison to H3K27ac, and reveals both synergistic and specific actions of each histone modification.</p>',
'date' => '2020-03-17',
'pmid' => 'http://www.pubmed.gov/32182340',
'doi' => '10.1093/nar/gkaa163',
'modified' => '2020-08-17 10:56:19',
'created' => '2020-08-10 12:12:25',
'ProductsPublication' => array(
[maximum depth reached]
)
),
(int) 35 => array(
'id' => '3884',
'name' => 'A MORC-driven transcriptional switch controls Toxoplasma developmental trajectories and sexual commitment.',
'authors' => 'Farhat DC, Swale C, Dard C, Cannella D, Ortet P, Barakat M, Sindikubwabo F, Belmudes L, De Bock PJ, Couté Y, Bougdour A, Hakimi MA',
'description' => '<p>Toxoplasma gondii has a complex life cycle that is typified by asexual development that takes place in vertebrates, and sexual reproduction, which occurs exclusively in felids and is therefore less studied. The developmental transitions rely on changes in the patterns of gene expression, and recent studies have assigned roles for chromatin shapers, including histone modifications, in establishing specific epigenetic programs for each given stage. Here, we identified the T. gondii microrchidia (MORC) protein as an upstream transcriptional repressor of sexual commitment. MORC, in a complex with Apetala 2 (AP2) transcription factors, was shown to recruit the histone deacetylase HDAC3, thereby impeding the accessibility of chromatin at the genes that are exclusively expressed during sexual stages. We found that MORC-depleted cells underwent marked transcriptional changes, resulting in the expression of a specific repertoire of genes, and revealing a shift from asexual proliferation to sexual differentiation. MORC acts as a master regulator that directs the hierarchical expression of secondary AP2 transcription factors, and these transcription factors potentially contribute to the unidirectionality of the life cycle. Thus, MORC plays a cardinal role in the T. gondii life cycle, and its conditional depletion offers a method to study the sexual development of the parasite in vitro, and is proposed as an alternative to the requirement of T. gondii infections in cats.</p>',
'date' => '2020-02-24',
'pmid' => 'http://www.pubmed.gov/32094587',
'doi' => '10.1038/s41564-020-0674-4',
'modified' => '2020-03-20 17:27:25',
'created' => '2020-03-13 13:45:54',
'ProductsPublication' => array(
[maximum depth reached]
)
),
(int) 36 => array(
'id' => '3882',
'name' => 'MYCN amplification and ATRX mutations are incompatible in neuroblastoma.',
'authors' => 'Zeineldin M, Federico S, Chen X, Fan Y, Xu B, Stewart E, Zhou X, Jeon J, Griffiths L, Nguyen R, Norrie J, Easton J, Mulder H, Yergeau D, Liu Y, Wu J, Van Ryn C, Naranjo A, Hogarty MD, Kamiński MM, Valentine M, Pruett-Miller SM, Pappo A, Zhang J, Clay MR, ',
'description' => '<p>Aggressive cancers often have activating mutations in growth-controlling oncogenes and inactivating mutations in tumor-suppressor genes. In neuroblastoma, amplification of the MYCN oncogene and inactivation of the ATRX tumor-suppressor gene correlate with high-risk disease and poor prognosis. Here we show that ATRX mutations and MYCN amplification are mutually exclusive across all ages and stages in neuroblastoma. Using human cell lines and mouse models, we found that elevated MYCN expression and ATRX mutations are incompatible. Elevated MYCN levels promote metabolic reprogramming, mitochondrial dysfunction, reactive-oxygen species generation, and DNA-replicative stress. The combination of replicative stress caused by defects in the ATRX-histone chaperone complex, and that induced by MYCN-mediated metabolic reprogramming, leads to synthetic lethality. Therefore, ATRX and MYCN represent an unusual example, where inactivation of a tumor-suppressor gene and activation of an oncogene are incompatible. This synthetic lethality may eventually be exploited to improve outcomes for patients with high-risk neuroblastoma.</p>',
'date' => '2020-02-14',
'pmid' => 'http://www.pubmed.gov/32060267',
'doi' => '10.1038/s41467-020-14682-6',
'modified' => '2020-03-20 17:30:52',
'created' => '2020-03-13 13:45:54',
'ProductsPublication' => array(
[maximum depth reached]
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),
(int) 37 => array(
'id' => '3848',
'name' => 'A comprehensive epigenomic analysis of phenotypically distinguishable, genetically identical female and male Daphnia pulex.',
'authors' => 'Kvist J, Athanàsio CG, Pfrender ME, Brown JB, Colbourne JK, Mirbahai L',
'description' => '<p>BACKGROUND: Daphnia species reproduce by cyclic parthenogenesis involving both sexual and asexual reproduction. The sex of the offspring is environmentally determined and mediated via endocrine signalling by the mother. Interestingly, male and female Daphnia can be genetically identical, yet display large differences in behaviour, morphology, lifespan and metabolic activity. Our goal was to integrate multiple omics datasets, including gene expression, splicing, histone modification and DNA methylation data generated from genetically identical female and male Daphnia pulex under controlled laboratory settings with the aim of achieving a better understanding of the underlying epigenetic factors that may contribute to the phenotypic differences observed between the two genders. RESULTS: In this study we demonstrate that gene expression level is positively correlated with increased DNA methylation, and histone H3 trimethylation at lysine 4 (H3K4me3) at predicted promoter regions. Conversely, elevated histone H3 trimethylation at lysine 27 (H3K27me3), distributed across the entire transcript length, is negatively correlated with gene expression level. Interestingly, male Daphnia are dominated with epigenetic modifications that globally promote elevated gene expression, while female Daphnia are dominated with epigenetic modifications that reduce gene expression globally. For examples, CpG methylation (positively correlated with gene expression level) is significantly higher in almost all differentially methylated sites in male compared to female Daphnia. Furthermore, H3K4me3 modifications are higher in male compared to female Daphnia in more than 3/4 of the differentially regulated promoters. On the other hand, H3K27me3 is higher in female compared to male Daphnia in more than 5/6 of differentially modified sites. However, both sexes demonstrate roughly equal number of genes that are up-regulated in one gender compared to the other sex. Since, gene expression analyses typically assume that most genes are expressed at equal level among samples and different conditions, and thus cannot detect global changes affecting most genes. CONCLUSIONS: The epigenetic differences between male and female in Daphnia pulex are vast and dominated by changes that promote elevated gene expression in male Daphnia. Furthermore, the differences observed in both gene expression changes and epigenetic modifications between the genders relate to pathways that are physiologically relevant to the observed phenotypic differences.</p>',
'date' => '2020-01-06',
'pmid' => 'http://www.pubmed.gov/31906859',
'doi' => '10.1186/s12864-019-6415-5',
'modified' => '2020-02-20 11:34:47',
'created' => '2020-02-13 10:02:44',
'ProductsPublication' => array(
[maximum depth reached]
)
),
(int) 38 => array(
'id' => '4068',
'name' => 'TIP60/P400/H4K12ac Plays a Role as a Heterochromatin Back-up Skeleton inBreast Cancer.',
'authors' => 'Idrissou, Mouhamed and Boisnier, Tiphanie and Sanchez, Anna and Khoufaf,Fatma Zohra Houfaf and Penault-Llorca, Frederique and Bignon, Yves-Jean andBernard-Gallon, Dominique',
'description' => '<p>BACKGROUND/AIM: In breast cancer, initiation of carcinogenesis leads to epigenetic dysregulation, which can lead for example to the loss of the heterochromatin skeleton SUV39H1/H3K9me3/HP1 or the supposed secondary skeleton TIP60/P400/H4K12ac/BRD (2/4), which allows the maintenance of chromatin integrity and plasticity. This study investigated the relationship between TIP60, P400 and H4K12ac and their implications in breast tumors. MATERIALS AND METHODS: Seventy-seven patients diagnosed with breast cancer were included in this study. Chromatin immunoprecipitation (ChIP) assay was used to identify chromatin modifications. Western blot and reverse transcription and quantitative real-time PCR were used to determine protein and gene expression, respectively. RESULTS: We verified the variation in H4K12ac enrichment and the co-localization of H4K12ac and TIP60 on the euchromatin and heterochromatin genes, respectively, by ChIP-qPCR and ChIP-reChIP, which showed an enrichment of H4K12ac on specific genes in tumors compared to the adjacent healthy tissue and a co-localization of H4K12ac with TIP60 in different breast tumor types. Furthermore, RNA and protein expression of TIP60 and P400 was investigated and overexpression of TIP60 and P400 mRNA was associated with tumor aggressiveness. CONCLUSION: There is a potential interaction between H4K12ac and TIP60 in heterochromatin or euchromatin in breast tumors.</p>',
'date' => '2020-01-01',
'pmid' => 'https://www.ncbi.nlm.nih.gov/pubmed/33099470',
'doi' => '10.21873/cgp.20223',
'modified' => '2021-02-19 17:52:18',
'created' => '2021-02-18 10:21:53',
'ProductsPublication' => array(
[maximum depth reached]
)
),
(int) 39 => array(
'id' => '4096',
'name' => 'Changes in H3K27ac at Gene Regulatory Regions in Porcine AlveolarMacrophages Following LPS or PolyIC Exposure.',
'authors' => 'Herrera-Uribe, Juber and Liu, Haibo and Byrne, Kristen A and Bond, Zahra Fand Loving, Crystal L and Tuggle, Christopher K',
'description' => '<p>Changes in chromatin structure, especially in histone modifications (HMs), linked with chromatin accessibility for transcription machinery, are considered to play significant roles in transcriptional regulation. Alveolar macrophages (AM) are important immune cells for protection against pulmonary pathogens, and must readily respond to bacteria and viruses that enter the airways. Mechanism(s) controlling AM innate response to different pathogen-associa 
