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Epigenetic Services

ATAC-Seq

Genome-wide profiles of open chromatin regions from < 100,000 cells

ATAC-Seq is based on transposase-mediated insertion of sequencing primers into open chromatin regions. This assay provides genome-wide profiles of open and accessible regions of chromatin that are indicative of active regulatory regions.

ATAC-Seq image

Why study Open Chromatin?

  1. Gain mechanistic insight into gene regulation, cellular response to treatment or disease
  2. Identify which transcription factors are driving cell fate, disease, or response
  3. Primary tissues or cells such as pancreatic Beta cells
  4. Limited patient samples
  5. Stratify patients or sample groups based on open chromatin signatures

ATAC-Seq can be a good alternative to ChIP-Seq if it is unknown whether epigenetics plays a role in the response of your cell system, if it is unclear which histone modification is the most important to study using ChIP-Seq or when cell numbers are limited.

The ATAC-Seq assay includes;

  1. Cell preparation
  2. Transposase reaction
  3. Library amplification
  4. Sequencing on an Illumina platform
  5. Bioinformatic analysis

Sample Types

Active Motif’s services team is the only group routinely generating ATAC-Seq data from tissues. Active Motif will accept the following sample types for this service:

  1. Human and animal tissues (including xenografts and human biopsies)
  2. Primary cells (including T and B cells)
  3. FACS sorted cells
  4. Most rare cell populations

To learn more, send us an Epigenetic Services Information Request. You can also download Active Motif’s Epigenetic Services Profile.

 
Name Cat No. Price  
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.