Pervasive Variation of Transcription Factor Orthologs Contributes to Regulatory Network Evolution
Pervasive Variation of Transcription Factor Orthologs Contributes to Regulatory Network Evolution
Differences in transcriptional regulatory networks underlie much of the phenotypic variation observed across organisms. Changes to cis-regulatory elements are widely believed to be the predominant means by which regulatory networks evolve, yet examples of regulatory network divergence due to transcription factor (TF) variation have also been observed. To systematically ascertain the extent to which TFs contribute to regulatory divergence, we analyzed the evolution of the largest class of metazoan TFs, Cys2-His2 zinc finger (C2H2-ZF) TFs, across 12 Drosophila species spanning ~45 million years of evolution. Remarkably, we uncovered that a significant fraction of all C2H2-ZF 1-to-1 orthologs in flies exhibit variations that can affect their DNA-binding specificities. In addition to loss and recruitment of C2H2-ZF domains, we found diverging DNA-contacting residues in ~47% of domains shared between D. melanogaster and the other fly species. These diverging DNA-contacting residues, found in ~66% of the D. melanogaster C2H2-ZF genes in our analysis and corresponding to ~24% of all annotated D. melanogaster TFs, show evidence of functional constraint: they tend to be conserved across phylogenetic clades and evolve slower than other diverging residues. These same variations were rarely found as polymorphisms within a population of D. melanogaster flies, indicating their rapid fixation. The predicted specificities of these dynamic domains gradually change across phylogenetic distances, suggesting stepwise evolutionary trajectories for TF divergence. Further, whereas proteins with conserved C2H2-ZF domains are enriched in developmental functions, those with varying domains exhibit no functional enrichments. Our work suggests that a subset of highly dynamic and largely unstudied TFs are a likely source of regulatory variation in Drosophila and other metazoans.
29 pages, 5 figures, 5 supplemental figures, 3 supplemental tables
- Department of Computer Science Princeton University United States
- Institute of Health Czech Republic
- University of Chicago United States
- Princeton University United States
- University of Chicago United States
Genomics (q-bio.GN), Populations and Evolution (q-bio.PE), Zinc Fingers, QH426-470, Regulatory Sequences, Nucleic Acid, DNA-Binding Proteins, Evolution, Molecular, Species Specificity, FOS: Biological sciences, Genetics, Animals, Quantitative Biology - Genomics, Drosophila, Gene Regulatory Networks, Quantitative Biology - Populations and Evolution, Phylogeny, Research Article, Transcription Factors
Genomics (q-bio.GN), Populations and Evolution (q-bio.PE), Zinc Fingers, QH426-470, Regulatory Sequences, Nucleic Acid, DNA-Binding Proteins, Evolution, Molecular, Species Specificity, FOS: Biological sciences, Genetics, Animals, Quantitative Biology - Genomics, Drosophila, Gene Regulatory Networks, Quantitative Biology - Populations and Evolution, Phylogeny, Research Article, Transcription Factors
138 Research products, page 1 of 14
- 2017IsRelatedTo
- 2017IsRelatedTo
- 2017IsRelatedTo
- 2017IsRelatedTo
- 2017IsRelatedTo
- 2017IsRelatedTo
- 2017IsRelatedTo
- 2017IsRelatedTo
- 2017IsRelatedTo
- 2017IsRelatedTo
chevron_left - 1
- 2
- 3
- 4
- 5
chevron_right
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).19 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Average impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%
