Department of Animal and Plant Science, University of Sheffield, Western Bank, Sheffield, S10 2TN, UK.
Mol Ecol. 2013 Aug;22(15):3963-80. doi: 10.1111/mec.12375. Epub 2013 Jul 13.
The underlying basis of genetic variation in quantitative traits, in terms of the number of causal variants and the size of their effects, is largely unknown in natural populations. The expectation is that complex quantitative trait variation is attributable to many, possibly interacting, causal variants, whose effects may depend upon the sex, age and the environment in which they are expressed. A recently developed methodology in animal breeding derives a value of relatedness among individuals from high-density genomic marker data, to estimate additive genetic variance within livestock populations. Here, we adapt and test the effectiveness of these methods to partition genetic variation for complex traits across genomic regions within ecological study populations where individuals have varying degrees of relatedness. We then apply this approach for the first time to a natural population and demonstrate that genetic variation in wing length in the great tit (Parus major) reflects contributions from multiple genomic regions. We show that a polygenic additive mode of gene action best describes the patterns observed, and we find no evidence of dosage compensation for the sex chromosome. Our results suggest that most of the genomic regions that influence wing length have the same effects in both sexes. We found a limited amount of genetic variance in males that is attributed to regions that have no effects in females, which could facilitate the sexual dimorphism observed for this trait. Although this exploratory work focuses on one complex trait, the methodology is generally applicable to any trait for any laboratory or wild population, paving the way for investigating sex-, age- and environment-specific genetic effects and thus the underlying genetic architecture of phenotype in biological study systems.
在自然种群中，数量性状遗传变异的基础，就因果变异的数量和其效应的大小而言，在很大程度上是未知的。人们期望复杂的数量性状变异归因于许多可能相互作用的因果变异，其效应可能取决于表达它们的性别、年龄和环境。动物育种中最近开发的一种方法从高密度基因组标记数据中得出个体之间的亲缘关系值，以估计家畜群体中的加性遗传方差。在这里，我们适应并测试了这些方法在具有不同亲缘关系个体的生态研究种群中跨基因组区域划分复杂性状遗传变异的有效性。然后，我们首次将这种方法应用于自然种群，并证明大山雀（Parus major）的翅膀长度的遗传变异反映了多个基因组区域的贡献。我们表明，多基因加性基因作用模式最能描述观察到的模式，并且我们没有发现性染色体剂量补偿的证据。我们的结果表明，影响翅膀长度的大多数基因组区域在两性中都具有相同的效应。我们发现雄性中存在有限的遗传方差，这归因于在雌性中没有影响的区域，这可能促进了该性状的性二态性。尽管这项探索性工作集中在一个复杂的性状上，但该方法通常适用于任何实验室或野生种群的任何性状，为研究性别、年龄和环境特异性遗传效应以及生物研究系统中表型的潜在遗传结构铺平了道路。
