ATAC-seq (Assay for Transposase-Accessible Chromatin Sequencing) is a modern epigenomic method for identifying open chromatin regions across the genome. It uses hyperactive Tn5 transposase, which simultaneously cuts DNA and adds sequencing adapters to accessible chromatin regions. This enables mapping of regulatory genomic elements such as promoters, enhancers and transcription-factor binding sites.
ATAC-seq workflow
01Isolation of cells or cell nuclei: The analysis begins with preparation of high-quality biological material. Depending on the sample type, whole cells or isolated cell nuclei may be used.
02Chromatin tagmentationThe key stage is tagmentation. Hyperactive Tn5 transposase recognises open chromatin regions where DNA is not tightly bound to nucleosomes. This selectively enriches the library for fragments from regulatory genomic regions. The enzyme simultaneously:
- cuts DNA,
- introduces sequencing adapters,
- prepares the material for further amplification.
03Library preparation: The resulting DNA fragments are amplified by PCR. This increases the amount of material required for sequencing and adds indexes for analysing multiple samples in one sequencing run.
04Library quality control: Before sequencing, the quality of the prepared libraries is assessed, including their concentration and DNA fragment-size distribution. A characteristic indicator of a correctly prepared ATAC-seq library is the presence of fragments corresponding to nucleosome-free regions (NFR), as well as DNA fragments associated with one or more nucleosomes. The fragment-size distribution may show a characteristic periodicity reflecting the organisation of nucleosomes in chromatin.
05Sequencing: The prepared libraries are sequenced on the Illumina platform, most often in paired-end mode (PE150). Sequencing both ends of the DNA fragments enables accurate mapping of reads to the reference genome and determination of fragment length, which is important for identifying open chromatin regions and analysing nucleosome organisation.
06Bioinformatics analysis: The data obtained undergo quality control, filtering and mapping to the reference genome. Open chromatin regions are then identified (peak calling) and subjected to genomic annotation and transcription-factor binding-motif analysis. In projects involving different experimental groups, differential chromatin accessibility analysis is also performed, making it possible to identify regulatory regions potentially involved in the biological processes studied.
Applications of ATAC-seq
ATAC-seq provides information about the regulatory landscape of the genome and is used in many areas of biological and biomedical research.
01Identification of open chromatin regions - the primary application is detection of active regulatory regions that may control gene expression.
02Transcription-factor binding-site analysis - ATAC-seq data identify potential binding sites through footprinting analysis.
03Enhancer and promoter mapping - ATAC-seq detects novel regulatory genomic elements and determines their activity in different cell types.
04Cancer studies - the technique is widely used to identify epigenetic changes associated with malignant transformation, disease progression and response to treatment.
05Developmental and stem-cell studies - ATAC-seq tracks dynamic changes in chromatin accessibility during cell differentiation and organismal development.
06Immunological studies - the method analyses lymphocyte activation, immune responses and gene-regulation mechanisms involved in immune-system function.
Technical specifications of ATAC-seq
- Sequencing mode: 2x150 bp
- Sequencers: Illumina platform, NovaSeq 6000 and NovaSeq X sequencers.
- Recommended amount of data per sample:
- 50M reads per sample - at least 3 biological replicates and an available high-quality reference genome
- Other configurations are also available depending on the client's needs.
- Recommended Sample Requirements - DNA/RNA:
- Sample type:
- Cells / nuclei: >5x105
- Tissue: >100 mg
- Blood: >2 mL
- Sample type:
ATAC-seq bioinformatics analysis
ATAC-seq data analysis includes a series of stages that identify open chromatin regions, determine their biological functions and compare changes in chromatin accessibility between study groups.
- Single-sample analysis (Intra-sample Analysis)
- Data quality control (QC) - Raw-read quality, duplication level, adapter content and mapping efficiency to the reference genome are analysed.
- Read mapping to the reference genome - Reads are aligned to the reference genome to determine their locations and assess the distribution of the ATAC-seq signal across the genome.
- Identification of open chromatin regions - the primary application is detection of active regulatory regions that may control gene expression. - Read enrichment is used to identify peaks corresponding to accessible chromatin regions such as promoters, enhancers and other regulatory elements.
- Peak annotation - Detected peaks are assigned to functional genomic elements such as promoters, exons, introns, intergenic regions and enhancers.
- Sequence-motif analysis and transcription-factor prediction - DNA motif-enrichment analysis identifies potential transcription factors responsible for regulating gene expression in the cells under study.
- Functional analysis of genes associated with differential peaks: Genes located near open chromatin regions undergo functional analysis including:
- Gene Ontology (GO) analysis,
- KEGG pathway enrichment analysis,
- functional enrichment analysis.
BIOINFORMATICS ANALYSIS SCOPE4 analyses
Inter-group comparative analysisFor studies involving different experimental conditions or biological groups, differential analysis is performed.
- Sample-correlation analysis - Biological and technical consistency between samples is assessed through correlation analysis and statistical sample clustering.
Identification of differentially accessible chromatin regionsGroup comparison detects regions with significantly increased or decreased chromatin accessibility (Differentially Accessible Regions, DARs).
Motif analysis in differential peaksRegulatory-motif analysis is performed for regions showing significant accessibility changes to identify potential transcription factors responsible for the observed differences.
Functional analysis of genes associated with differential peaksGenes associated with differentially accessible chromatin regions undergo GO, KEGG and functional enrichment analyses to identify biological processes and molecular pathways associated with the phenomenon studied.
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ChIP-seqSingle-cell ATAC-seqEPIGENOMICS & 3D GENOMEWhole Genome Bisulfite Sequencing (WGBS)Hi-C sequencingComparison: Illumina vs AVITIKEYWORDS
ATAC-seqchromatin accessibilityopen chromatingenome regulation
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