Unknown

Dataset Information

0

Evolution of binding preferences among whole-genome duplicated transcription factors.


ABSTRACT: Throughout evolution, new transcription factors (TFs) emerge by gene duplication, promoting growth and rewiring of transcriptional networks. How TF duplicates diverge was studied in a few cases only. To provide a genome-scale view, we considered the set of budding yeast TFs classified as whole-genome duplication (WGD)-retained paralogs (~35% of all specific TFs). Using high-resolution profiling, we find that ~60% of paralogs evolved differential binding preferences. We show that this divergence results primarily from variations outside the DNA-binding domains (DBDs), while DBD preferences remain largely conserved. Analysis of non-WGD orthologs revealed uneven splitting of ancestral preferences between duplicates, and the preferential acquiring of new targets by the least conserved paralog (biased neo/sub-functionalization). Interactions between paralogs were rare, and, when present, occurred through weak competition for DNA-binding or dependency between dimer-forming paralogs. We discuss the implications of our findings for the evolutionary design of transcriptional networks.

SUBMITTER: Gera T 

PROVIDER: S-EPMC9000951 | biostudies-literature | 2022 Apr

REPOSITORIES: biostudies-literature

altmetric image

Publications

Evolution of binding preferences among whole-genome duplicated transcription factors.

Gera Tamar T   Jonas Felix F   More Roye R   Barkai Naama N  

eLife 20220411


Throughout evolution, new transcription factors (TFs) emerge by gene duplication, promoting growth and rewiring of transcriptional networks. How TF duplicates diverge was studied in a few cases only. To provide a genome-scale view, we considered the set of budding yeast TFs classified as whole-genome duplication (WGD)-retained paralogs (~35% of all specific TFs). Using high-resolution profiling, we find that ~60% of paralogs evolved differential binding preferences. We show that this divergence  ...[more]

Similar Datasets

| S-EPMC8788222 | biostudies-literature
| S-EPMC5548724 | biostudies-literature
| S-EPMC6233140 | biostudies-literature
| S-EPMC4288167 | biostudies-literature
2023-04-30 | GSE227616 | GEO
| S-EPMC3725104 | biostudies-literature
| S-EPMC11514967 | biostudies-literature
| S-EPMC314286 | biostudies-literature
| S-EPMC11734700 | biostudies-literature
2018-11-05 | GSE118416 | GEO