Chu Thinh Tuan, Jensen Just
Center for Quantitative Genetics and Genomics, Aarhus University, Aarhus, Denmark.
Faculty of Animal Science, Vietnam National University of Agriculture, Hanoi, Vietnam.
Front Genet. 2025 Feb 10;16:1513615. doi: 10.3389/fgene.2025.1513615. eCollection 2025.
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.
随机模拟软件ADAM是为动植物育种优化以及遗传评估中使用的统计模型验证而开发的。与其他常见模拟程序一样,ADAM假定数量性状基因座(QTL)处于双等位基因状态。虽然标记基因座的双等位基因状态是由于单核苷酸多态性(SNP)芯片基因分型技术的普遍选择,但对于连锁QTL,该假设可能不成立。在ADAM-Multi版本中,我们采用了一种新颖的模拟模型,该模型能够模拟不同倍性水平物种的加性、显性和上位性基因型效应,为QTL变异的多等位基因提供了更现实的假设。当假定为双等位基因QTL时,我们提出的模型与常见模拟程序以及遗传教科书中的模型假设相同。随着ADAM-Multi中更新模拟模型的描述,本文展示了两项小规模研究,它们调查了模拟中多等位基因与双等位基因假设的影响以及在马铃薯单群体育种计划中使用不同预测模型的情况。我们发现,尽管存在多等位基因QTL,但使用密集双等位基因标记的基因组模型能够有效地预测结构良好群体中个体的育种值。此外,小规模研究表明,在选择的预测模型中纳入非加性遗传效应并不会提高育种计划的遗传增益率。