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A thousand empirical adaptive landscapes and their navigability
- Source :
- Nature Ecology and Evolution
- Publication Year :
- 2016
-
Abstract
- The adaptive landscape is an iconic metaphor that pervades evolutionary biology. It was mostly applied in theoretical models until recent years, when empirical data began to allow partial landscape reconstructions. Here, we exhaustively analyse 1,137 complete landscapes from 129 eukaryotic species, each describing the binding affinity of a transcription factor to all possible short DNA sequences. We find that the navigability of these landscapes through single mutations is intermediate to that of additive and shuffled null models, suggesting that binding affinity-and thereby gene expression-is readily fine-tuned via mutations in transcription factor binding sites. The landscapes have few peaks that vary in their accessibility and in the number of sequences they contain. Binding sites in the mouse genome are enriched in sequences found in the peaks of especially navigable landscapes and the genetic diversity of binding sites in yeast increases with the number of sequences in a peak. Our findings suggest that landscape navigability may have contributed to the enormous success of transcriptional regulation as a source of evolutionary adaptations and innovations.
- Subjects :
- 0301 basic medicine
Genetic diversity
Ecology
Fitness landscape
Systems biology
15. Life on land
Biology
Genome
DNA binding site
03 medical and health sciences
10127 Institute of Evolutionary Biology and Environmental Studies
030104 developmental biology
0302 clinical medicine
1105 Ecology, Evolution, Behavior and Systematics
Evolutionary biology
Navigability
570 Life sciences
biology
590 Animals (Zoology)
Gene
Transcription factor
2303 Ecology
030217 neurology & neurosurgery
Ecology, Evolution, Behavior and Systematics
Subjects
Details
- ISSN :
- 2397334X
- Volume :
- 1
- Issue :
- 2
- Database :
- OpenAIRE
- Journal :
- Nature ecologyevolution
- Accession number :
- edsair.doi.dedup.....30e34054befd3cecf57b6b8f17ff3c0c