ArticleMolecular biology and evolution2018
The Genotype-Phenotype Relationships in the Light of Natural Selection.
Article in Molecular biology and evolution, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Population-scale chemical response revealed by a barcoded yeast collection.Nature communications · 2026Article
- Exploring the omnigenic architecture of selected complex traits.American journal of human genetics · 2025Article
- Discovery of positive and purifying selection in metagenomic time series of hypermutator microbial populations.PLoS genetics · 2022Article
- Phenotypic variation ofPeerJ · 2022Article
- iTARGEX analysis of yeast deletome reveals novel regulators of transcriptional buffering in S phase and protein turnover.Nucleic acids research · 2021Article
- A High-Resolution Map of Human Enhancer RNA Loci Characterizes Super-enhancer Activities in Cancer.Cancer cell · 2020Article
- The Origin of Additive Genetic Variance Driven by Positive Selection.Molecular biology and evolution · 2020Article
- Decoupling gene functions from knockout effects by evolutionary analyses.National science review · 2020Article
- Article
- Fast-Evolving Human-Specific Neural Enhancers Are Associated with Aging-Related Diseases.Cell systems · 2018Article
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Authors and funding
3 authors.
Funding
Abstract
Although any genotype-phenotype relationships are a result of evolution, little is known about how natural selection and neutral drift, two distinct driving forces of evolution, operate to shape the relationships. By analyzing ∼500 yeast quantitative traits, we reveal a basic "supervisor-worker" gene architecture underlying a trait. Supervisors are often identified by "perturbational" approaches (such as gene deletion), whereas workers, which usually show small and statistically insignificant deletion effects, are tracked primarily by "observational" approaches that examine the correlation between gene activity and trait value across a number of conditions. Accordingly, supervisors provide most of the genetic understandings of the trait whereas workers provide rich mechanistic understandings. Further analyses suggest that most observed supervisor-worker interactions may evolve largely neutrally, resulting in pervasive between-worker epistasis that suppresses the tractability of workers. In contrast, a fraction of supervisors are recruited/maintained by natural selection to build worker co-expression, boosting the tractability of workers. Thus, by revealing a supervisor-worker gene architecture underlying complex traits, the opposite roles of natural selection versus neutral drift in shaping the gene architecture, and the complementary strengths of the perturbational and observational research strategies in characterizing the gene architecture, this study may lay a new conceptual foundation for understanding the molecular basis of complex traits.
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