scATAC-seq generates more accurate and complete regulatory maps than bulk ATAC-seq
Abstract Bulk ATAC-seq assays have been used to map and profile the chromatin accessibility of regulatory elements such as enhancers, promoters, and insulators. This has provided great insight into the regulation of gene expression in many cell types in a variety of organisms. To date, ATAC-seq has...
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Nature Portfolio
2025-01-01
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| author | E. Ravza Gur Jim R. Hughes |
| author_facet | E. Ravza Gur Jim R. Hughes |
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| description | Abstract Bulk ATAC-seq assays have been used to map and profile the chromatin accessibility of regulatory elements such as enhancers, promoters, and insulators. This has provided great insight into the regulation of gene expression in many cell types in a variety of organisms. To date, ATAC-seq has most often been used to provide an average evaluation of chromatin accessibility in populations of cells. The development of a single cell approach (scATAC-seq) assay enables researchers to evaluate chromatin accessibility in individual cells and identify sub-groups in mixed populations of cells. To investigate the full potential of single-cell epigenomic data, we have comprehensively compared the information derived from bulk ATAC-seq and scATAC-seq in populations of cells. We found that the chromatin architecture signal is the same using bulk ATAC-seq and scATAC-seq to analyse aliquots of the same cell population. However, scATAC-seq provides substantially higher data quality compared to bulk ATAC-seq improving the sensitivity to detect relatively weak, but functionally important ATAC-seq signals. Furthermore, we found that scATAC-seq identified differences in what was previously assumed to be a homogenous population of cells. Finally, we determined the number of cells required to generate aggregated open chromatin profiles from single cells and to identify biologically meaningful clusters after pseudo-bulking of data. This study illustrates the added value of using scATAC-seq rather than bulk ATAC-seq in evaluating both homogeneous and heterogeneous populations of cells. This paper provides a comprehensive guide on the benefits of using scATAC-seq data to study gene regulation. |
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| publishDate | 2025-01-01 |
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| spelling | doaj-art-c86627e51ab34491836bd2512ea9c26f2025-02-02T12:20:10ZengNature PortfolioScientific Reports2045-23222025-01-0115111410.1038/s41598-025-87351-7scATAC-seq generates more accurate and complete regulatory maps than bulk ATAC-seqE. Ravza Gur0Jim R. Hughes1MRC WIMM Centre for Computational Biology, MRC Weatherall Institute of Molecular Medicine, Radcliffe Department of Medicine, University of OxfordMRC WIMM Centre for Computational Biology, MRC Weatherall Institute of Molecular Medicine, Radcliffe Department of Medicine, University of OxfordAbstract Bulk ATAC-seq assays have been used to map and profile the chromatin accessibility of regulatory elements such as enhancers, promoters, and insulators. This has provided great insight into the regulation of gene expression in many cell types in a variety of organisms. To date, ATAC-seq has most often been used to provide an average evaluation of chromatin accessibility in populations of cells. The development of a single cell approach (scATAC-seq) assay enables researchers to evaluate chromatin accessibility in individual cells and identify sub-groups in mixed populations of cells. To investigate the full potential of single-cell epigenomic data, we have comprehensively compared the information derived from bulk ATAC-seq and scATAC-seq in populations of cells. We found that the chromatin architecture signal is the same using bulk ATAC-seq and scATAC-seq to analyse aliquots of the same cell population. However, scATAC-seq provides substantially higher data quality compared to bulk ATAC-seq improving the sensitivity to detect relatively weak, but functionally important ATAC-seq signals. Furthermore, we found that scATAC-seq identified differences in what was previously assumed to be a homogenous population of cells. Finally, we determined the number of cells required to generate aggregated open chromatin profiles from single cells and to identify biologically meaningful clusters after pseudo-bulking of data. This study illustrates the added value of using scATAC-seq rather than bulk ATAC-seq in evaluating both homogeneous and heterogeneous populations of cells. This paper provides a comprehensive guide on the benefits of using scATAC-seq data to study gene regulation.https://doi.org/10.1038/s41598-025-87351-7Bulk ATAC-seqscATAC-seqGene regulationRegulatory elementsChromatin accessibilityClustering |
| spellingShingle | E. Ravza Gur Jim R. Hughes scATAC-seq generates more accurate and complete regulatory maps than bulk ATAC-seq Scientific Reports Bulk ATAC-seq scATAC-seq Gene regulation Regulatory elements Chromatin accessibility Clustering |
| title | scATAC-seq generates more accurate and complete regulatory maps than bulk ATAC-seq |
| title_full | scATAC-seq generates more accurate and complete regulatory maps than bulk ATAC-seq |
| title_fullStr | scATAC-seq generates more accurate and complete regulatory maps than bulk ATAC-seq |
| title_full_unstemmed | scATAC-seq generates more accurate and complete regulatory maps than bulk ATAC-seq |
| title_short | scATAC-seq generates more accurate and complete regulatory maps than bulk ATAC-seq |
| title_sort | scatac seq generates more accurate and complete regulatory maps than bulk atac seq |
| topic | Bulk ATAC-seq scATAC-seq Gene regulation Regulatory elements Chromatin accessibility Clustering |
| url | https://doi.org/10.1038/s41598-025-87351-7 |
| work_keys_str_mv | AT eravzagur scatacseqgeneratesmoreaccurateandcompleteregulatorymapsthanbulkatacseq AT jimrhughes scatacseqgeneratesmoreaccurateandcompleteregulatorymapsthanbulkatacseq |