Data associated with publication: O'Brien et al. "The genetic architecture of polygenic adaptation under a network-derived trait"

This paper investigates the evolutionary outcomes of populations adapting towards a phenotypic optimum when the phenotype is a polygenic trait described by either an additive quantitative genetics model or a simple gene regulatory network, the negative autoregulation (NAR) motif. Under the network model, the trait is constructed by solving an ordinary differential equation, which is modified by mutations at loci along the genome. Two treatments of the NAR are constructed, with different coefficients in the equation being modified by mutations. Simulations were carried out in a custom version of SLiM 4.1 available at https://github.com/nobrien97/SLiM/releases/tag/PolygenicNAR2024. This dataset contains csv files measuring trait responses (detailing how the mean population trait value changed during adaptation), mutation information (allelic effect sizes, origin times, and frequencies), linkage disequilibrium, epistasis strength, and genetic variance.

本研究探究了当表型为多基因性状时，种群向表型最适值适应性演化的结局。该多基因性状可通过两种方式描述：其一为加性数量遗传学模型，其二为由负自调控（negative autoregulation, NAR）基序构成的简单基因调控网络。在基因调控网络模型下，该性状通过求解常微分方程（ordinary differential equation）构建，而基因组上各位点的突变会修饰该方程。针对该负自调控基序，本研究设置了两种处理方案，两种方案的方程中存在不同系数，且这些系数会受到突变的修饰。模拟实验基于定制版SLiM 4.1完成，该版本可从https://github.com/nobrien97/SLiM/releases/tag/PolygenicNAR2024获取。本数据集包含CSV格式文件，涵盖性状响应数据（详细记录了种群平均性状值在适应性演化过程中的变化情况）、突变信息（包括等位基因效应大小、起源时间与频率）、连锁不平衡、上位性强度以及遗传方差。