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Single-Cell ATAC-seq 受託サービス

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個々の細胞からゲノム全体のクロマチンアクセシビリティを査定することで、発生生物学、腫瘍学、神経学などの多くの分野で独自の洞察が得られます。 Bio-RadのSureCell ATAC-seqは、単一細胞の解像度でエピゲノムの高速、堅牢で高感度の解析をご提供します。 この方法は、Bio-Radの液滴ベースのマイクロ流体と、個々の核のクロマチンにアダプターとバーコードをもたらす高活性Tn5トランスポザーゼの両方の組み合わせによって強化されています。 この最高クラスのソリューションは、環境のコンテキストにおける個々のセルの動作を更に理解するために役立ちます。



  • 高いキャプチャー効率
  • 核ゲノム、ATACピーク、および転写開始部位(TSS)に位置する多数のユニークなフラグメント
  • パワフルでカスタマイズされたデータ解析オプション

  • Intro to Diagenode’s and Bio-Rad’s scATAC-seq
    1. Single cell sequencing provides you more in-depth insight of gene expression and gene regulation at individual cell resolution
      scATAC-seq Service
    2. ATAC-Seq identifies subpopulations

      Chromatin accessibility is more cell type specific than mRNA expression in primary blood cells

      ATAC Sequencing for Chromatin Profiling

      RNA-seq: profile gene expression patterns
      ATAC-seq: profile regulators of cell identity

    3. Chromatin accessibility more adept than mRNA expression levels at classifying cell types.

      Chromatin accessibility is more cell type specific than mRNA expression in primary blood cells

      Single-cell chromatin profiling assay that is based on ATAC-seq technology
  • The technology and data of our scATAC-seq

    Workflow of our scATAC-seq solution

    scATAC-seq solution workflow

    Input: ~7,500 tagmented nuclei per well

    Output: 5,000 nuclei analyzed

    Bio-Rad’s Droplet Digital Technology

      • 1.

        Bead-based scATAC-Seq Processing

        1. Typically, cell data points are represented twice, “fractionated” which can cause inaccuracy
        2. Bio-Rad’s Droplet Digital Technology merges bead barcodes to create a droplet barcode to resolve this issue
        3. Unique “ATAC fingerpint” can be resolved using BAP: Bead-based scATAC-Seq Processing

      • 2.

        Bead-based scATAC-Seq Processing

        ATAC fingerprint

        Since Tn5 cuts randomly, every cell has a unique set of cut fragments: an ATAC fingerprint!

        If % unique fragments shared is high enough (compared to background), beads are inferred to have originated from the same droplet

        ATAC-seq Analysis

      • 3.

        SureCell ATAC-seq

        This bioinformatic process, BAP, works very well because there is a large difference in the similarity score between barcodes originating in the same droplet versus barcodes originating in different droplets. This is demonstrated by the very sharp knee on the plot.

        Y-axis = “similarity score” or the Jaccard index
        X-axis = bead pairs in rank order

    • 4.

      Workflow ATAC-seq

      First PCR product fully adaptered

      In the workflow, droplet reaction yields sequencing ready library. During droplet PCR, the tagmented nuclei are ligated with adaptors with beads barcode, sample index and P5 and P7, generating sufficient library that can be ready to sequence.

      Assay for Transposase-Accessible Chromatin using sequencing

    Performance data from a species mixing experiment of human and mouse cell lines.

    Excellent cell utilization and enrichment

    Mixed mouse 3T3 and human K562 cells

    • Cell Utilization up to 95%
    • TSS Enrichment score: >40*
    • > 40% Fraction of reads in peaks**
    • > 20,000 Unique Genomics Fragments/cell at a read depth of 50k reads/cell
    *40x more reads at TSS than at sites 2kb away from the TSS. ** . FRIP should be as high as possible because reads outside peaks are not useful for analyzing chromatin accessibility.

    Assay for Transposase-Accessible Chromatin with high-throughput sequencing

    Highly complex libraries results in more biological meaningful data at less sequencing depth

    Data generated from Bio-Rad’s ATAC-Seq kit
    Encyclopedia of DNA Elements (ENCODE)
    • NIH’s resource of human epigenomics data to catalyze basic biology and disease oriented research.
    • ENCODE contains consensus regions of open chromatin in PBMCs

    Data generated from Bio-Rad’s ATAC-Seq kit shows more consensus peaks across sequencing depth compared to competitor

    Better classification of cell types with Bio-Rad’s ATAC-Seq than competing technology

    PBMCs: Cell mis-classification
    Bio-Rad’s ATAC-Seq than competing technology

    PBMC datasets from Bio-Rad’s and competitor’s ATAC-Seq were correlated with the bulk ATAC-Seq references and assigned a cell type to each barcode

    Mis-classification rate of both datasets calculated by progressively down sampling the libraries by measuring number of cell types changed from non-downsampled cell types.

    Data obtained from competing technology has ~2X greater rate of misclassifying cells.

  • Our service advantages, workflow, and requirements

    Diagenode service advantages:

    Design your project with a leader in epigenomics profiling services.

    End to end service from nuclei isolation optimization to bioinformatic analyses, including 3 reports.

    Bio-Rad’s powerful technology:

    • Up to 95% cell capture for your precious samples
    • Allows analysis of 400-10,000 single cells, i.e. more than 30,000 cells/kit
    • Higher number of unique reads per cell
    • Obtain highly complex library dataset from both cultured and primary tissue samples
    • More biologically meaningful data at less sequencing compared to competitor
    • Better classification of cell types, true resolution of cell clusters

    Wide offering for bioinformatic analyses: Standard analyses, advanced analyses, integrative analyses, data mining.

    ATAC-seq bioinformatic analyses
  •  資料
    Full Diagenode products brochure BROCHURE
    Need to know more about our products? Download the brochure.
    Epigenomics Profiling Services FLYER
    Chromatin analysis DNA methylation services RNA-seq analysis
  •  出版物

    How to properly cite this product in your work

    Diagenode strongly recommends using this: Single-Cell ATAC-seq 受託サービス (Diagenode Cat# G02110000). Click here to copy to clipboard.

    Using our products in your publication? Let us know!

    Droplet-based combinatorial indexing for massive-scale single-cell chromatin accessibility
    Caleb A. Lareau, Fabiana M. Duarte, Jennifer G. Chew, Vinay K. Kartha, Zach D. Burkett, Andrew S. Kohlway, Dmitry Pokholok, Martin J. Aryee, Frank J. Steemers, Ronald Lebofsky, and Jason D. Buenrostro
    Recent technical advancements have facilitated the mapping of epigenomes at single-cell resolution; however, the throughput and quality of these methods have limited their widespread adoption. Here we describe a high-quality (105 nuclear fragments per cell) droplet-microfluidics-based method for single-cell pro...

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