Active Motif,
Tools to analyze nuclear function,
Your CartYour Cart 0 items


ゲノムワイドなオープンクロマチン領域解析 (<100,000 cells)

What our customers are saying about us ...

"I am studying the epigenetic regulation of heart failure. I have had a very good experience with Active Motif Epigenetic services and I will continue research with Active Motif in the future. I received good support from both the Sales Department and the Tech Support Team to help me to go through all the aspects of the service."
Ning Feng, MD, PhD
University of Pittsburgh
View complete list of testimonials >


ATAC-Seq は、トランスポゼースを利用して、シーケンス用のプライマーをオープンクロマチン領域に挿入することで、オープンクロマチン領域を決定する方法です。この方法により、網羅的にゲノム上のオープンクロマチン領域、活性化領域を解析することが可能です。
ATAC-Seq image


  1. 遺伝子調節、薬剤による細胞応答、疾患によるゲノムの構造変化がわかる
  2. 細胞運命決定や細胞応答における転写因子の同定が可能
  3. 組織サンプルや初代培養などの解析(膵ベータ細胞など)
  4. 患者由来のサンプルなど、量が少ない時の解析
  5. オープンクロマチン構造の差による患者、サンプル間の階層化


ATAC-Seq の受託解析内容;

  1. 細胞の調製
  2. トランスポゼースの反応
  3. ライブラリー調性
  4. Illumina シーケンサーによる解析
  5. バイオインフォマティクス解析


Active Motif’の専属スタッフは、組織サンプルのATAC-seqを定期的に行っている唯一のチームです。Active Motifでは、以下のサンプルからの解析も行っています。

  1. ヒト、動物組織(異種移植片やヒト生検サンプルを含む)
  2. 初代培養細胞(T細胞やB細胞も含む)
  3. FACS で分離した細胞
  4. レアな細胞集団

詳しくは、次のフォームでお問い合わせください Epigenetic Services Information Request. また受託サービスの概要は以下のガイドにもご紹介しています。 Epigenetic Services Brochure.

Name Cat No. 価格 (税抜)  
ATAC-Seq 25079 Request Quote
ATAC-Seq Data 1
Figure 1: Active Motif’s ATAC-Seq assay reliably detects regions of open chromatin.

DNAse-Seq, which has long been the gold standard for generating genome-wide profiles of open chromatin, is shown above in blue. The utility of DNAse-Seq has been limited since it requires tens of millions of cells and is technically challenging. Active Motif’s ATAC-Seq (shown above in green), uses only 50,000 cells and provides data that is comparable to DNAse-Seq.

ATAC-Seq Data 2
Figure 2: Active Motif’s ATAC-Seq assay distinguishes sample groups by identifying chromatin regions that are differentially open.

The example above shows ATAC-Seq data from 4 different samples, each performed in triplicate. Differentially open regions are highlighted in yellow.

ATAC-Seq Data 3
Figure 3: Gene Ontology using differential regions from ATAC-Seq

Open regions that lie near genes can be used to create gene lists for gene ontology analysis. In the example above, some of the top ontologies are related to B cell biology, revealing pathways that are relevant to this cell system.

ATAC-Seq Data 4
Figure 4: Identifying important transcription factor binding sites using ATAC-Seq

The underlying DNA sequence of differentially open chromatin regions can be analyzed to identify the most enriched transcription factor binding sites. In this cell system the two most enriched binding motifs are also relevant to B cell biology. Fra1 is quickly upregulated upon B cell activation and PU.1 is a key regulator of B cell fate specification.

ATAC-Seq Data 5
Figure 5: Distribution of Histone Modifications Relative to ATAC-Seq Peaks at Annotated Promoters

Comparison of ATAC-Seq data to different histone modification ChIP-Seq data sets reveals that ATAC-Seq peaks at promoters are most enriched for H3K4me3 and H3K9Ac.

ATAC-Seq Data 6
Figure 6: Distribution of Histone Modifications Relative to ATAC-Seq Peaks Outside of Annotated Promoters

ATAC-Seq peaks outside promoters are enriched for all active marks including the enhancer marks H3K27Ac and H3K4me1.

ATAC-Seq Data 7
Figure 7: Active Motif’s ATAC-Seq data generated from tissues

The images above show ATAC-Seq data generated using frozen mouse liver and lung tissue. The open chromatin profiles are similar to DNAse-Seq profiles generated by the ENCODE consortium.

ATAC-Seq Data 8
Figure 8: Active Motif’s ATAC-Seq data shows high reproducibility

The experiment above was performed using a cell line that was left untreated or treated under three different conditions and each condition was performed in triplicate. The correlation coefficients are presented in the heat map. Replicates have coefficients of at least 0.96. The heat map shows that the samples cluster into four distinct groups as expected.