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scPCOR-seq enables co-profiling of chromatin occupancy and RNAs in single cells

Cell-to-cell variation in gene expression is a widespread phenomenon, which may play important roles in cellular differentiation, function, and disease development(1–9). Chromatin is implicated in contributing to the cellular heterogeneity in gene expression(10–16). Fully understanding the mechanism...

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Detalles Bibliográficos
Autores principales: Pan, Lixia, Ku, Wai Lim, Tang, Qingsong, Cao, Yaqiang, Zhao, Keji
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9270334/
https://www.ncbi.nlm.nih.gov/pubmed/35804086
http://dx.doi.org/10.1038/s42003-022-03584-6
Descripción
Sumario:Cell-to-cell variation in gene expression is a widespread phenomenon, which may play important roles in cellular differentiation, function, and disease development(1–9). Chromatin is implicated in contributing to the cellular heterogeneity in gene expression(10–16). Fully understanding the mechanisms of cellular heterogeneity requires simultaneous measurement of RNA and occupancy of histone modifications and transcription factors on chromatin due to their critical roles in transcriptional regulation(17,18). We generally term the occupancy of histone modifications and transcription factors as Chromatin occupancy. Here, we report a technique, termed scPCOR-seq (single-cell Profiling of Chromatin Occupancy and RNAs Sequencing), for simultaneously profiling genome-wide chromatin protein binding or histone modification marks and RNA expression in the same cell. We demonstrated that scPCOR-seq can profile either H3K4me3 or RNAPII and RNAs in a mixture of human H1, GM12878 and 293 T cells at a single-cell resolution and either H3K4me3, RNAPII, or RNA profile can correctly separate the cells. Application of scPCOR-seq to the in vitro differentiation of the erythrocyte precursor CD36 cells from human CD34 stem or progenitor cells revealed that H3K4me3 and RNA exhibit distinct properties in clustering cells during differentiation. Overall, our work provides a promising approach to understand the relationships among different omics layers.