Transcription factor expression is the main determinant of variability in gene co-activity

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Many genes are co-expressed and form genomic domains of coordinated gene activity. However, the regulatory determinants of domain co-activity remain unclear. Here, we leverage human individual variation in gene expression to characterize the co-regulatory processes underlying domain co-activity and systematically quantify their effect sizes. We employ transcriptional decomposition to extract from RNA expression data an expression component related to co-activity revealed by genomic positioning. This strategy reveals close to 1,500 co-activity domains, covering most expressed genes, of which the large majority are invariable across individuals. Focusing specifically on domains with high variability in co-activity reveals that contained genes have a higher sharing of eQTLs, a higher variability in enhancer interactions, and an enrichment of binding by variably expressed transcription factors, compared to genes within non-variable domains. Through careful quantification of the relative contributions of regulatory processes underlying co-activity, we find transcription factor expression levels to be the main determinant of gene co-activity. Our results indicate that distal trans effects contribute more than local genetic variation to individual variation in co-activity domains.
OriginalsprogEngelsk
Artikelnummere11392
TidsskriftMolecular Systems Biology
Vol/bind19
Udgave nummer7
Antal sider17
ISSN1744-4292
DOI
StatusUdgivet - 2023

Bibliografisk note

Funding Information:
We would like to thank all members of the Andersson lab at the University of Copenhagen for their rewarding comments and discussions during the project. This work was supported by funding from the Danish Council for Independent Research [grant 6108-00038], the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation program [grant 638173], and the Novo Nordisk Foundation [grant NNF20OC0059796].

Funding Information:
We would like to thank all members of the Andersson lab at the University of Copenhagen for their rewarding comments and discussions during the project. This work was supported by funding from the Danish Council for Independent Research [grant 6108‐00038], the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation program [grant 638173], and the Novo Nordisk Foundation [grant NNF20OC0059796].

Publisher Copyright:
© 2023 The Authors. Published under the terms of the CC BY 4.0 license.

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