Table 1_ADAM-multi: software to simulate complex breeding programs for animals and plants with different ploidy levels and generalized genotypic effect models to account for multiple alleles.docx

Stochastic simulation software, ADAM, has been developed for the purpose of breeding optimization in animals and plants, and for validation of statistical models used in genetic evaluations. Just like other common simulation programs, ADAM assumed the bi-allelic state of quantitative trait locus (QTL). While the bi-allelic state of marker loci is due to the common choice of genotyping technology of single nucleotide polymorphism (SNP) chip, the assumption may not hold for the linked QTL. In the version of ADAM-Multi, we employ a novel simulation model capable of simulating additive, dominance, and epistatic genotypic effects for species with different levels of ploidy, providing with a more realistic assumption of multiple allelism for QTL variants. When assuming bi-allelic QTL, our proposed model becomes identical to the model assumption in common simulation programs, and in genetic textbooks. Along with the description of the updated simulation model in ADAM-Multi, this paper shows two small-scale studies that investigate the effects of multi-allelic versus bi-allelic assumptions in simulation and the use of different prediction models in a single-population breeding program for potatoes. We found that genomic models using dense bi-allelic markers could effectively predicted breeding values of individuals in a well-structure population despite the presence of multi-allelic QTL. Additionally, the small-scale study indicated that including non-additive genetic effects in the prediction model for selection did not lead to an improvement in the rate of genetic gains of the breeding program.

本研究开发了一款用于动植物育种优化以及遗传评估所用统计模型验证的随机模拟软件ADAM。与其他主流模拟程序一致，ADAM初始假设数量性状位点（quantitative trait locus, QTL）为双等位基因状态。由于单核苷酸多态性（single nucleotide polymorphism, SNP）芯片作为当前常用的基因分型技术，通常仅能检测双等位基因标记位点，该假设对于连锁的数量性状位点而言未必符合实际情况。在ADAM-Multi版本中，我们引入了一款新型模拟模型，可针对不同倍性水平的物种模拟加性、显性与上位性基因型效应，为数量性状位点变异提供更贴近真实场景的多等位基因假设。当假设数量性状位点为双等位基因时，本研究提出的模型与常见模拟程序及遗传学教材中的模型假设完全一致。本文在详细阐述ADAM-Multi更新后的模拟模型的同时，还呈现了两项小型研究：其一探究模拟场景下多等位基因与双等位基因假设的影响差异，其二针对马铃薯单群体育种项目，分析不同预测模型的应用效果。研究结果显示，即便存在多等位基因数量性状位点，采用高密度双等位基因标记的基因组模型仍可在结构良好的群体中有效预测个体的育种值。此外，该项小型研究还表明，在用于选择的预测模型中纳入非加性遗传效应，并未提升该育种项目的遗传增益速率。