Inferring upstream regulatory genes of FOXP3 in human regulatory T cells from time-series transcriptomic data

Area of Science:

• Genomics
• Immunology
• Computational Biology

Background:

• Discovering upstream regulatory genes for a gene of interest is a significant challenge in molecular biology.
• The regulatory mechanisms controlling the master regulator FOXP3 in human regulatory T cells (Tregs) remain largely unknown.

Purpose of the Study:

• To develop and apply a scalable computational method for unbiased prediction of candidate regulatory genes across the whole genome.
• To identify novel upstream regulators of FOXP3 in human primary Tregs.

Main Methods:

• Genome-wide computational prediction of candidate regulatory genes.
• Case study focusing on the transcription factor FOXP3 in human primary Tregs.
• Experimental validation of top-ranked candidate genes through knockdown and mRNA expression analysis.

Main Results:

• The computational method identified five top-ranked candidate upstream regulatory genes.
• Proof-of-concept experiments demonstrated that knockdown of three out of five candidates significantly affected FOXP3 mRNA expression.
• The study provides insights into the regulatory network of FOXP3 in Tregs.

Conclusions:

• The developed computational approach offers a scalable and accurate method for predicting upstream regulatory genes.
• This study successfully identified novel regulators of FOXP3, advancing our understanding of Treg biology.
• The findings highlight the potential of computational genomics for uncovering gene regulatory mechanisms.