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Multiplex indexing approach for the detection of DNase I hypersensitive sites in single cells
Single cell chromatin accessibility assays reveal epigenomic variability at cis-regulatory elements among individual cells. We previously developed a single-cell DNase-seq assay (scDNase-seq) to profile accessible chromatin in a limited number of single cells. Here, we report a novel indexing strate...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8191781/ https://www.ncbi.nlm.nih.gov/pubmed/33693880 http://dx.doi.org/10.1093/nar/gkab102 |
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author | Gao, Weiwu Ku, Wai Lim Pan, Lixia Perrie, Jonathan Zhao, Tingting Hu, Gangqing Wu, Yuzhang Zhu, Jun Ni, Bing Zhao, Keji |
author_facet | Gao, Weiwu Ku, Wai Lim Pan, Lixia Perrie, Jonathan Zhao, Tingting Hu, Gangqing Wu, Yuzhang Zhu, Jun Ni, Bing Zhao, Keji |
author_sort | Gao, Weiwu |
collection | PubMed |
description | Single cell chromatin accessibility assays reveal epigenomic variability at cis-regulatory elements among individual cells. We previously developed a single-cell DNase-seq assay (scDNase-seq) to profile accessible chromatin in a limited number of single cells. Here, we report a novel indexing strategy to resolve single-cell DNase hypersensitivity profiles based on bulk cell analysis. This new technique, termed indexing single-cell DNase sequencing (iscDNase-seq), employs the activities of terminal DNA transferase (TdT) and T4 DNA ligase to add unique cell barcodes to DNase-digested chromatin ends. By a three-layer indexing strategy, it allows profiling genome-wide DHSs for >15 000 single-cells in a single experiment. Application of iscDNase-seq to human white blood cells accurately revealed specific cell types and inferred regulatory transcription factors (TF) specific to each cell type. We found that iscDNase-seq detected DHSs with specific properties related to gene expression and conservation missed by scATAC-seq for the same cell type. Also, we found that the cell-to-cell variation in accessibility computed using iscDNase-seq data is significantly correlated with the cell-to-cell variation in gene expression. Importantly, this correlation is significantly higher than that between scATAC-seq and scRNA-seq, suggesting that iscDNase-seq data can better predict the cellular heterogeneity in gene expression compared to scATAC-seq. Thus, iscDNase-seq is an attractive alternative method for single-cell epigenomics studies. |
format | Online Article Text |
id | pubmed-8191781 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-81917812021-06-11 Multiplex indexing approach for the detection of DNase I hypersensitive sites in single cells Gao, Weiwu Ku, Wai Lim Pan, Lixia Perrie, Jonathan Zhao, Tingting Hu, Gangqing Wu, Yuzhang Zhu, Jun Ni, Bing Zhao, Keji Nucleic Acids Res Methods Online Single cell chromatin accessibility assays reveal epigenomic variability at cis-regulatory elements among individual cells. We previously developed a single-cell DNase-seq assay (scDNase-seq) to profile accessible chromatin in a limited number of single cells. Here, we report a novel indexing strategy to resolve single-cell DNase hypersensitivity profiles based on bulk cell analysis. This new technique, termed indexing single-cell DNase sequencing (iscDNase-seq), employs the activities of terminal DNA transferase (TdT) and T4 DNA ligase to add unique cell barcodes to DNase-digested chromatin ends. By a three-layer indexing strategy, it allows profiling genome-wide DHSs for >15 000 single-cells in a single experiment. Application of iscDNase-seq to human white blood cells accurately revealed specific cell types and inferred regulatory transcription factors (TF) specific to each cell type. We found that iscDNase-seq detected DHSs with specific properties related to gene expression and conservation missed by scATAC-seq for the same cell type. Also, we found that the cell-to-cell variation in accessibility computed using iscDNase-seq data is significantly correlated with the cell-to-cell variation in gene expression. Importantly, this correlation is significantly higher than that between scATAC-seq and scRNA-seq, suggesting that iscDNase-seq data can better predict the cellular heterogeneity in gene expression compared to scATAC-seq. Thus, iscDNase-seq is an attractive alternative method for single-cell epigenomics studies. Oxford University Press 2021-03-08 /pmc/articles/PMC8191781/ /pubmed/33693880 http://dx.doi.org/10.1093/nar/gkab102 Text en © The Author(s) 2021. Published by Oxford University Press on behalf of Nucleic Acids Research. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) ), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Methods Online Gao, Weiwu Ku, Wai Lim Pan, Lixia Perrie, Jonathan Zhao, Tingting Hu, Gangqing Wu, Yuzhang Zhu, Jun Ni, Bing Zhao, Keji Multiplex indexing approach for the detection of DNase I hypersensitive sites in single cells |
title | Multiplex indexing approach for the detection of DNase I hypersensitive sites in single cells |
title_full | Multiplex indexing approach for the detection of DNase I hypersensitive sites in single cells |
title_fullStr | Multiplex indexing approach for the detection of DNase I hypersensitive sites in single cells |
title_full_unstemmed | Multiplex indexing approach for the detection of DNase I hypersensitive sites in single cells |
title_short | Multiplex indexing approach for the detection of DNase I hypersensitive sites in single cells |
title_sort | multiplex indexing approach for the detection of dnase i hypersensitive sites in single cells |
topic | Methods Online |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8191781/ https://www.ncbi.nlm.nih.gov/pubmed/33693880 http://dx.doi.org/10.1093/nar/gkab102 |
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