Recruiting Transcription Factor Heterotypic Cooperativity to Design Computational Approach for Chromosome Wide Prediction of Human Limb Specific Enhancers

Abstract

Cells of a multicellular organism are genetically homogeneous but structurally and functionally heterogeneous owing to the differential expression of genes. Many of these differences in gene expression arise during development and are regulated spatio temporally by several gene regulatory elements, mainly cis-regulatory elements. Due to their substantial influence on transcription regulation, enhancers by far make up the most important category of cis-regulatory elements. Considering their significance in gene expression, considerable efforts are being made to identify these cis‐regulatory elements. However, due to lack of proper language, mode of action and the degeneracy of binding sites, they are hard to locate. Recruitment of sequence‐specific transcription factors is an essential hallmark of enhancers. Evidence demonstrates that transcription factors bind to the enhancers in a combinatorial manner, competing and collaborating to regulate common target genes. The enhancer's combinatorial binding of transcription factors permits it to express spatiotemporally while also leaving some significant indicators for its identification. Keeping the transcription factors cooperativity as rationale, a computational pipeline to predict enhancers was devised. Constraining the research scope to limb specific enhancers, transcription factor binding site mapping algorithm (TFBSMA) was utilized for the mapping of transcription factor binding sites on genome sequence, which were then clustered into putative limb specific enhancers. The devised pipeline effectively predicted 70 putative limb specific enhancers in non-coding, non-repetitive segments of human chromosome 17. The predicted enhancers were then validated by means of experimentally verified data of acetylation marks, methylation marks, DNase hypersensitive marks, and limb specific disease variants to establish their significance and reliability. Conservation analysis was also performed for these predicted enhancers which revealed that most of these enhancers are conserved till mammals, while a small number goes down to amphibians and fishes. Thus, cost and time proficiency, literature evidence and validation make this strategy of prediction a comparable substitute of already available computational and experimental approaches used to identify cis-regulatory modules