Decoding transcriptional regulation via a human gene expression predictor.

Area of Science:

• Genomics
• Systems Biology
• Transcriptional Regulation

Background:

• Transcription factors (TFs) are crucial regulators of cellular activities by controlling gene expression.
• A quantitative predictive model for TF-mediated human transcriptome modulation is currently lacking.

Purpose of the Study:

• To develop a universal human gene expression predictor, EXPLICIT-Human, to decode transcriptional regulation.
• To identify significant TF-target gene interactions and infer TF regulators for various biological pathways.

Main Methods:

• Construction of EXPLICIT-Human, a predictive model utilizing the expression of 1613 TFs.
• Reconstitution of human transcriptomes across diverse tissues and conditions using the predictor.
• Extraction of significant TF-target gene pairs and downstream inference of TF regulators.

Main Results:

• EXPLICIT-Human accurately reconstitutes human transcriptomes, demonstrating broad applicability across tissues and conditions.
• The model recapitulates quantitative TF-target gene relationships.
• Identification of key TFs regulating development, immunity, metabolism, and stress response, including an atlas for hematopoiesis.
• EXPLICIT-Human outperforms existing tools in recovering correct TF regulators.

Conclusions:

• EXPLICIT-Human provides a powerful tool for decoding transcriptional regulation and understanding TF-mediated gene expression.
• The method successfully delineates TFs responsible for cell fate determination, with conserved examples found between humans and mice.