Gene expression variability in mammalian embryonic stem cells using single cell RNA-seq data

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• 作者：Anna Mantsoki ^{Anna.Mantsoki@roslin.ed.ac.uk" class="auth_mail" title="E-mail the corresponding author} ; Guillaume Devailly ^{Guillaume.Devailly@roslin.ed.ac.uk" class="auth_mail" title="E-mail the corresponding author} ; Anagha Joshi ; ^{Anagha.joshi@roslin.ed.ac.uk" class="auth_mail" title="E-mail the corresponding author}
• 关键词：Single cell RNA-seq ; Embryonic stem cells ; Transcription control ; Gene expression variance ; Coefficient of variance ; Background
• 刊名：Computational Biology and Chemistry
• 出版年：2016
• 出版时间：August 2016
• 年：2016
• 卷：63
• 期：Complete
• 页码：52-61
• 全文大小：2688 K

文摘

Gene expression heterogeneity contributes to development as well as disease progression. Due to technological limitations, most studies to date have focused on differences in mean expression across experimental conditions, rather than differences in gene expression variance. The advent of single cell RNA sequencing has now made it feasible to study gene expression heterogeneity and to characterise genes based on their coefficient of variation.

Methods

We collected single cell gene expression profiles for 32 human and 39 mouse embryonic stem cells and studied correlation between diverse characteristics such as network connectivity and coefficient of variation (CV) across single cells. We further systematically characterised properties unique to High CV genes.

Results

Highly expressed genes tended to have a low CV and were enriched for cell cycle genes. In contrast, High CV genes were co-expressed with other High CV genes, were enriched for bivalent (H3K4me3 and H3K27me3) marked promoters and showed enrichment for response to DNA damage and DNA repair.

Conclusions

Taken together, this analysis demonstrates the divergent characteristics of genes based on their CV. High CV genes tend to form co-expression clusters and they explain bivalency at least in part.