A thousand empirical adaptive landscapes and their navigability

Area of Science:

• Evolutionary biology
• Genomics
• Molecular biology

Background:

• The adaptive landscape is a key metaphor in evolutionary biology, primarily used in theoretical models.
• Recent advances in empirical data allow for partial reconstruction of these landscapes.
• Understanding transcription factor binding affinity is crucial for gene regulation.

Purpose of the Study:

• To analyze complete adaptive landscapes of transcription factor binding affinity across eukaryotic species.
• To investigate the navigability of these landscapes and their implications for evolutionary adaptation.
• To explore the relationship between landscape features and genomic binding site distribution.

Main Methods:

• Exhaustive analysis of 1,137 complete adaptive landscapes from 129 eukaryotic species.
• Quantification of binding affinity for transcription factors to all possible short DNA sequences.
• Comparison of landscape navigability with additive and shuffled null models.
• Analysis of binding site enrichment in mouse and yeast genomes.

Main Results:

• Landscape navigability is intermediate between additive and shuffled models, indicating easy fine-tuning of binding affinity via mutations.
• Adaptive landscapes feature a few peaks with varying accessibility and sequence representation.
• Mouse genome binding sites are enriched in sequences from navigable landscape peaks.
• Yeast binding site genetic diversity correlates with peak size.

Conclusions:

• The fine-tunability of transcription factor binding affinity through mutations is a significant factor in evolutionary adaptation.
• Landscape navigability likely contributed to the success of transcriptional regulation in driving evolutionary innovations.
• The structure of adaptive landscapes provides insights into the evolution of gene regulation.