An omnigenic interactome model to chart the genetic architecture of individual plants
Changjian Fa, Guijia Wang, Wenqi Pan, Yu Wang, Jincan Che, Ang Dong, Dengcheng Yang, Rongling Wu, Shing-Tung Yau, Lidan Sun
TL;DR
This paper introduces a new model to understand how genes interact to shape complex traits in plants, focusing on individual-level genetic effects.
Contribution
A novel statistical mechanics model combining functional mapping and evolutionary game theory to analyze gene interactions in individual plants.
Findings
The model can estimate gene interactions and their effects on individual phenotypes, beyond population-level averages.
Reconstructed idopNetworks in mei trees reveal distinct genetic architectures for fast- and slow-growing individuals.
Computer simulations confirm the model's statistical power to disentangle complex genetic interactions.
Abstract
Complex traits are controlled by many unknown genes, making it difficult to elucidate a global picture of the genotype–phenotype map. Here, we develop a statistical mechanics model to contextualize all possible genes into informative, dynamic, omnidirectional, and personalized idopNetworks. This model, derived from the combination of functional mapping and evolutionary game theory, can visualize and trace how genes act and interact with each other to shape the genetic architecture of complex traits. The model can estimate changes in the genotypic value of one gene due to the influence of other genes, specifically on individual subjects, surpassing traditional quantitative genetic studies that can only capture the marginal effect of a gene at the population level. We reconstruct growth idopNetworks from a genome-wide mapping data in a woody plant, mei, identifying unique genetic…
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Taxonomy
TopicsGenetic Mapping and Diversity in Plants and Animals · Greenhouse Technology and Climate Control · Morphological variations and asymmetry