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Updated: Aug 12, 2025

Describing a Transcription Factor Dependent Regulation of the MicroRNA Transcriptome
Published on: June 15, 2016
Decoding transcriptional regulation via a human gene expression predictor
Yuzhou Wang1, Yu Zhang2, Ning Yu3
1The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui 230027, China; MOE Key Laboratory for Cellular Dynamics, School of Life Sciences, Division of Life Sciences and Medicine, University of Science and Technology of China, Innovation Academy for Seed Design, Chinese Academy of Sciences, Hefei, Anhui 230027, China.
Abstract:
Transcription factors (TFs) regulate cellular activities by controlling gene expression, but a predictive model describing how TFs quantitatively modulate human transcriptomes is lacking. We construct a universal human gene expression predictor named EXPLICIT-Human and utilize it to decode transcriptional regulation. Using the expression of 1613 TFs, the predictor reconstitutes highly accurate transcriptomes for samples derived from a wide range of tissues and conditions. The broad applicability of the predictor indicates that it recapitulates the quantitative relationships between TFs and target genes ubiquitous across tissues. Significant interacting TF-target gene pairs are extracted from the predictor and enable downstream inference of TF regulators for diverse pathways involved in development, immunity, metabolism, and stress response. A detailed analysis of the hematopoiesis process reveals an atlas of key TFs regulating the development of different hematopoietic cell lineages, and a portion of these TFs are conserved between humans and mice. The results demonstrate that our method is capable of delineating the TFs responsible for fate determination. Compared to other existing tools, EXPLICIT-Human shows a better performance in recovering the correct TF regulators.
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