Data associated with publication: 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. d_fx.csv - Effect sizes of samplde mutations during simulations (corrected s value)slim_qg_randomisedStarts.csv - Adaptive outcomes of simulations with randomised starting molecular component conditionsslim_qg_adjTau.csv - Adaptive outcomes for per-molecular component balanced simulationsslim_mutvar_adjtau.csv - Mutational variance for simulations with per-molecular component balanced Vmslim_mutvar.csv - Mutational variance for original SLiM simulations

本文探究了当表型为多基因性状时，种群适应表型最优值的演化结局。该多基因性状可通过加性数量遗传学模型，或是简单基因调控网络——负自调控（negative autoregulation，NAR）基序——进行描述。在基因调控网络模型框架下，该性状通过求解常微分方程构建，而基因组上各位点的突变会对该方程进行修饰。本研究针对NAR基序设计了两种处理方案，方程中的不同系数可通过突变进行修饰。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。
本数据集包含以下CSV格式文件：
d_fx.csv：模拟过程中采样突变的效应量（校正后的s值）
slim_qg_randomisedStarts.csv：以随机化分子组分初始条件开展的模拟实验的适应结局
slim_qg_adjTau.csv：针对各分子组分进行平衡处理的模拟实验的适应结局
slim_mutvar_adjtau.csv：各分子组分平衡Vm条件下模拟实验的突变方差
slim_mutvar.csv：原始SLiM模拟实验的突变方差
其中各文件所记录的核心内容包括：性状响应数据（详述种群平均性状值在适应过程中的变化规律）、突变信息（等位基因效应量、起源时间与频率）、连锁不平衡、上位性强度以及遗传方差。