Shared regulation and functional relevance of local gene co-expression revealed by single cell analysis

Most human genes are co-expressed with a nearby gene. Previous studies have revealed this local gene co-expression to be widespread across chromosomes and across dozens of tissues. Yet, so far these studies used bulk RNA-seq, averaging gene expression measurements across millions of cells, thus bein...

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Veröffentlicht in:Communications biology Jg. 5; H. 1; S. 876 - 11
Hauptverfasser: M. Ribeiro, Diogo, Ziyani, Chaymae, Delaneau, Olivier
Format: Journal Article
Sprache:Englisch
Veröffentlicht: London Nature Publishing Group UK 26.08.2022
Nature Publishing Group
Nature Portfolio
Schlagworte:
38/39
45/91
631/114/2401
631/208/191/2018
631/208/199
631/208/200
Biology
Biomedical and Life Sciences
Chromosomes
Comorbidity
Gene expression
Gene regulation
Life Sciences
Lymphoblastoid cell lines
Pluripotency
Proteomics
Regulatory sequences
Ribonucleic acid
RNA
Stem cells
ISSN:2399-3642, 2399-3642
Online-Zugang:Volltext
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Zusammenfassung:Most human genes are co-expressed with a nearby gene. Previous studies have revealed this local gene co-expression to be widespread across chromosomes and across dozens of tissues. Yet, so far these studies used bulk RNA-seq, averaging gene expression measurements across millions of cells, thus being unclear if this co-expression stems from transcription events in single cells. Here, we leverage single cell datasets in >85 individuals to identify gene co-expression across cells, unbiased by cell-type heterogeneity and benefiting from the co-occurrence of transcription events in single cells. We discover >3800 co-expressed gene pairs in two human cell types, induced pluripotent stem cells (iPSCs) and lymphoblastoid cell lines (LCLs) and (i) compare single cell to bulk RNA-seq in identifying local gene co-expression, (ii) show that many co-expressed genes – but not the majority – are composed of functionally related genes and (iii) using proteomics data, provide evidence that their co-expression is maintained up to the protein level. Finally, using single cell RNA-sequencing (scRNA-seq) and single cell ATAC-sequencing (scATAC-seq) data for the same single cells, we identify gene-enhancer associations and reveal that >95% of co-expressed gene pairs share regulatory elements. These results elucidate the potential reasons for co-expression in single cell gene regulatory networks and warrant a deeper study of shared regulatory elements, in view of explaining disease comorbidity due to affecting several genes. Our in-depth view of local gene co-expression and regulatory element co-activity advances our understanding of the shared regulatory architecture between genes. Using single-cell data from cell lines, the co-expression of genes and co-activity of regulatory elements is analyzed, providing insight into shared architecture and regulation between genes.
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ISSN:2399-3642
2399-3642
DOI:10.1038/s42003-022-03831-w