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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...

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Detalles Bibliográficos
Autores principales: Gao, Weiwu, Ku, Wai Lim, Pan, Lixia, Perrie, Jonathan, Zhao, Tingting, Hu, Gangqing, Wu, Yuzhang, Zhu, Jun, Ni, Bing, Zhao, Keji
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2021
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
Descripción
Sumario: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.