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Updated: Jun 8, 2026

Following the Dynamics of Structural Variants in Experimentally Evolved Populations
Published on: February 3, 2023
Genomic patterns of pleiotropy and the evolution of complexity
Zhi Wang1, Ben-Yang Liao, Jianzhi Zhang
1Department of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, MI 48109, USA.
Most genes affect only a few traits, challenging previous models of pleiotropy. This study reveals that higher pleiotropy, or genes affecting many traits, actually enhances adaptation and complexity in organisms.
Area of Science:
- Genetics
- Evolutionary Biology
- Systems Biology
Background:
- Pleiotropy, where one gene influences multiple traits, is fundamental to biology but lacks empirical validation in theoretical models.
- Previous models of pleiotropy have not been extensively tested against real-world genomic data.
Purpose of the Study:
- To empirically investigate the genomic patterns of pleiotropy across different species.
- To analyze the relationship between gene pleiotropy, phenotypic effects, and organismal adaptation.
- To re-evaluate theoretical models of pleiotropy in light of genome-wide data.
Main Methods:
- Analysis of phenotypic data from large mutant collections in yeast, nematodes, and mice.
- Quantification of the fraction of traits affected by gene deletions.
- Statistical analysis of the distribution and scaling properties of gene pleiotropy and phenotypic effects.
Main Results:
- Most genes exhibit low pleiotropy, affecting only a small fraction of traits, and gene-trait relationships are highly modular.
- Genes with higher pleiotropy show larger per-trait phenotypic effects, contrary to expectations.
- A scaling property of pleiotropy counteracts the 'cost of complexity,' favoring intermediate organismal complexity for higher adaptation rates.
Conclusions:
- Genome-wide data necessitate significant revisions to existing theoretical models of pleiotropy.
- Observed patterns suggest pleiotropy has actively promoted, not hindered, the evolution of biological complexity.
- The modular nature and specific scaling of pleiotropy are key to understanding evolutionary trajectories.
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