Gienapp Phillip, Calus Mario P L, Laine Veronika N, Visser Marcel E
Department of Animal Ecology Netherlands Institute of Ecology (NIOO-KNAW) Wageningen The Netherlands.
Animal Breeding and Genomics Wageningen University & Research Wageningen The Netherlands.
Evol Lett. 2019 Mar 5;3(2):142-151. doi: 10.1002/evl3.103. eCollection 2019 Apr.
Artificial selection experiments are a powerful tool in evolutionary biology. Selecting individuals based on multimarker genotypes (genomic selection) has several advantages over phenotype-based selection but has, so far, seen very limited use outside animal and plant breeding. Genomic selection depends on the markers tagging the causal loci that underlie the selected trait. Because the number of necessary markers depends, among other factors, on effective population size, genomic selection may be in practice not feasible in wild populations as most wild populations have much higher effective population sizes than domesticated populations. However, the current possibilities of cost-effective high-throughput genotyping could overcome this limitation and thereby make it possible to apply genomic selection also in wild populations. Using a unique dataset of about 2000 wild great tits (), a small passerine bird, genotyped on a 650 k SNP chip we calculated genomic breeding values for egg-laying date using the so-called GBLUP approach. In this approach, the pedigree-based relatedness matrix of an "animal model," a special form of the mixed model, is replaced by a marker-based relatedness matrix. Using the marker-based relatedness matrix, the model seemed better able to disentangle genetic and permanent environmental effects. We calculated the accuracy of genomic breeding values by correlating them to the phenotypes of individuals whose phenotypes were excluded from the analysis when estimating the genomic breeding values. The obtained accuracy was about 0.20, with very little effect of the used genomic relatedness estimator but a strong effect of the number of SNPs. The obtained accuracy is lower than typically seen in domesticated species but considerable for a trait with low heritability (∼0.2) as avian breeding time. Our results show that genomic selection is possible also in wild populations with potentially many applications, which we discuss here.
人工选择实验是进化生物学中的一种强大工具。基于多标记基因型选择个体(基因组选择)相对于基于表型的选择具有若干优势,但迄今为止,在动物和植物育种之外的应用非常有限。基因组选择依赖于标记因果位点的标记,这些位点是所选性状的基础。由于所需标记的数量除其他因素外还取决于有效种群大小,在野生种群中基因组选择在实践中可能不可行,因为大多数野生种群的有效种群大小比驯化种群高得多。然而,当前具有成本效益的高通量基因分型可能性可以克服这一限制,从而也有可能在野生种群中应用基因组选择。我们使用一个独特的数据集,该数据集包含约2000只野生大山雀(一种小型雀形目鸟类),这些大山雀在一个650k单核苷酸多态性(SNP)芯片上进行了基因分型,我们使用所谓的GBLUP方法计算了产卵日期的基因组育种值(GBV)。在这种方法中,“动物模型”(混合模型的一种特殊形式)基于系谱的亲缘关系矩阵被基于标记的亲缘关系矩阵所取代。使用基于标记的亲缘关系矩阵,该模型似乎更能区分遗传效应和永久环境效应。我们通过将基因组育种值与在估计基因组育种值时其表型被排除在分析之外的个体的表型进行关联来计算基因组育种值的准确性。获得的准确性约为0.20,所用基因组亲缘关系估计器的影响很小,但单核苷酸多态性数量的影响很大。获得的准确性低于驯化物种中通常看到的准确性,但对于像鸟类繁殖时间这样具有低遗传力(约0.2)的性状来说是相当可观的。我们的结果表明,基因组选择在野生种群中也是可能的,并且有许多潜在应用,我们将在此进行讨论。