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Evolution of transcription factor binding through sequence variations and turnover of binding sites

ABSTRACT: Variations in noncoding regulatory sequences play a central role in evolution but interpreting such variations remains difficult even in the context of defined attributes such as transcription factor (TF) binding sites. Here, we systematically link variations in cis-regulatory sequences to TF binding by profiling the allele-specific binding of 27 TFs expressed in a yeast hybrid, which contains two related genomes within the same nucleus. TFs localize preferentially to sites containing their known binding motifs, but occupy only a small fraction of the potential motif-coding genomic sites. Differential binding of TFs to the two orthologues is well explained by sequence variations that alter the consensus core motif, while changes in chromatin accessibility were of little apparent effect. Motif variations that abolish binding when present in one allele show only moderately reduced binding when common to both alleles, suggesting evolutionary compensation. At the promoter level, we report cases of turnover, where binding in the two orthologues localized to different promoter regions, yet most interspecies differences resulted from higher number of binding sites in one of the alleles. Our results suggest that cis variations affecting TF binding occur primarily through the gain and loss of cis-regulatory motifs at accessible regions.

ORGANISM(S): Saccharomyces cerevisiae x Saccharomyces paradoxus

PROVIDER: GSE196451 | GEO | 2022/04/29

REPOSITORIES: GEO

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Project description:Contemporary high throughput technologies permit the rapid identification of transcription factor (TF) target genes on a genome-wide scale, yet the functional significance of TFs requires knowledge of target gene expression patterns, cooperating TFs and cis-regulatory element (CRE) structures. Here we investigated the myogenic regulatory network downstream of the Drosophila zinc finger TF Lame duck (Lmd) by combining both previously published and newly performed genomic data sets, including chromatin immunoprecipitation sequencing (ChIP-seq), genome-wide mRNA profiling, cell-specific expression patterns of putative transcriptional targets, analysis of histone mark signatures, studies of TF co-occupancy by additional mesodermal regulators, TF binding site determination using protein binding microarrays (PBMs), and machine learning of candidate CRE motif compositions. Our findings suggest that Lmd orchestrates an extensive myogenic regulatory network, a conclusion supported by the identification of Lmd-dependent genes, histone signatures of Lmd-bound genomic regions, and the relationship of these features to cell-specific gene expression patterns. The heterogeneous co-occupancy of Lmd-bound regions with additional mesodermal regulators revealed that different transcriptional inputs are used to mediate similar myogenic gene expression patterns. Machine learning further demonstrated diverse combinatorial motif patterns within tissue-specific Lmd-bound regions. PBM analysis established the complete spectrum of Lmd DNA binding specificities, and site-directed mutagenesis of Lmd and additional, newly discovered motifs in known enhancers demonstrated the critical role of these TF binding sites in supporting full enhancer activity. Collectively, these findings provide new insights into the transcriptional codes regulating muscle gene expression, and offer a generalizable approach for similar studies in other systems. Examination of Lmd occupancy to genomic DNA from sorted mesodermal cells

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Evolution of transcription factor binding through sequence variations and turnover of binding sites

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