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调控网络结构对复杂性状遗传力和进化的重要性。

The Importance of Regulatory Network Structure for Complex Trait Heritability and Evolution.

作者信息

Stone Katherine, Platig John, Quackenbush John, Fagny Maud

机构信息

Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA.

Department of Data Science and Center for Cancer Computational Biology, Dana-Farber Cancer Institute, Boston, Massachusetts, USA.

出版信息

bioRxiv. 2024 Sep 9:2024.02.27.582063. doi: 10.1101/2024.02.27.582063.

Abstract

Complex traits are determined by many loci-mostly regulatory elements-that, through combinatorial interactions, can affect multiple traits. Such high levels of epistasis and pleiotropy have been proposed in the omnigenic model and may explain why such a large part of complex trait heritability is usually missed by genome-wide association studies while raising questions about the possibility for such traits to evolve in response to environmental constraints. To explore the molecular bases of complex traits and understand how they can adapt, we systematically analyzed the distribution of SNP heritability for ten traits across 29 tissue-specific Expression Quantitative Trait Locus (eQTL) networks. We find that heritability is clustered in a small number of tissue-specific, functionally relevant SNP-gene modules and that the greatest heritability occurs in local "hubs" that are both the cornerstone of the network's modules and tissue-specific regulatory elements. The network structure could thus both amplify the genotype-phenotype connection and buffer the deleterious effect of the genetic variations on other traits. We confirm that this structure has allowed complex traits to evolve in response to environmental constraints, with the local "hubs" being the preferential targets of past and ongoing directional selection. Together, these results provide a conceptual framework for understanding complex trait architecture and evolution.

摘要

复杂性状由许多基因座(大多是调控元件)决定,这些基因座通过组合相互作用,可影响多个性状。全基因模型中提出了如此高水平的上位性和多效性,这或许可以解释为什么全基因组关联研究通常会遗漏大部分复杂性状的遗传力,同时也引发了关于此类性状能否响应环境限制而进化的疑问。为了探究复杂性状的分子基础并理解它们如何适应环境,我们系统地分析了29个组织特异性表达数量性状基因座(eQTL)网络中十个性状的单核苷酸多态性(SNP)遗传力分布。我们发现,遗传力聚集在少数组织特异性、功能相关的SNP-基因模块中,且最大遗传力出现在局部“枢纽”中,这些“枢纽”既是网络模块的基石,也是组织特异性调控元件。因此,网络结构既能放大基因型与表型的联系,又能缓冲遗传变异对其他性状的有害影响。我们证实,这种结构使得复杂性状能够响应环境限制而进化,局部“枢纽”是过去和正在进行的定向选择的优先目标。总之,这些结果为理解复杂性状结构和进化提供了一个概念框架。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c2c5/11422970/9fdd4d2be888/nihpp-2024.02.27.582063v2-f0001.jpg

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