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bioRxiv · 10.1101/2020.04.07.029470

Decoding transcriptional regulation via a human gene expression predictor

Wang, Y.·Zhang, Y.·Gong, J.·Bao, J.·Ma, S.
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Abstract

Transcription factors (TF) regulate cellular activities via controlling gene expression, but a predictive model describing how TFs quantitatively modulate human transcriptomes was lacking. We constructed a universal human gene expression predictor and utilized it to decode transcriptional regulation. Using 1613 TFs expression, the predictor reconstituted highly accurate transcriptomes for samples derived from a wide range of tissues and conditions. The predictors broad applicability indicated it had recapitulated the quantitative relationships between TFs and target genes ubiquitous across tissues. Significant interacting TF-target gene pairs were then extracted from the predictor and enabled downstream inference of TF regulators for diverse pathways involved in development, immunity, metabolism, and stress response. Thus, we present a novel approach to study human transcriptional regulation following the "understanding by modeling" principle.

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Wang, Y., Zhang, Y., Gong, J., Bao, J., Ma, S.. 2020-04-08. Decoding transcriptional regulation via a human gene expression predictor. https://doi.org/10.1101/2020.04.07.029470

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