Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden.
Department of Animal and Poultry Sciences, Virginia Polytechnic Institute and State University, Blacksburg VA, USA.
Poult Sci. 2023 May;102(5):102203. doi: 10.1016/j.psj.2022.102203. Epub 2022 Oct 1.
Genetic dissection of highly polygenic traits is a challenge, in part due to the power necessary to confidently identify loci with minor effects. Experimental crosses are valuable resources for mapping such traits. Traditionally, genome-wide analyses of experimental crosses have targeted major loci using data from a single generation (often the F) with individuals from later generations being generated for replication and fine-mapping. Here, we aim to confidently identify minor-effect loci contributing to the highly polygenic basis of the long-term, bi-directional selection responses for 56-d body weight in the Virginia body weight chicken lines. To achieve this, a strategy was developed to make use of data from all generations (F-F) of the advanced intercross line, developed by crossing the low and high selected lines after 40 generations of selection. A cost-efficient low-coverage sequencing based approach was used to obtain high-confidence genotypes in 1Mb bins across 99.3% of the chicken genome for >3,300 intercross individuals. In total, 12 genome-wide significant, and 30 additional suggestive QTL reaching a 10% FDR threshold, were mapped for 56-d body weight. Only 2 of these QTL reached genome-wide significance in earlier analyses of the F generation. The minor-effect QTL mapped here were generally due to an overall increase in power by integrating data across generations, with contributions from increased genome-coverage and improved marker information content. The 12 significant QTL explain >37% of the difference between the parental lines, three times more than 2 previously reported significant QTL. The 42 significant and suggestive QTL together explain >80%. Making integrated use of all available samples from multiple generations in experimental crosses are economically feasible using the low-cost, sequencing-based genotyping strategies outlined here. Our empirical results illustrate the value of this strategy for mapping novel minor-effect loci contributing to complex traits to provide a more confident, comprehensive view of the individual loci that form the genetic basis of the highly polygenic, long-term selection responses for 56-d body weight in the Virginia body weight chicken lines.
高度多基因性状的遗传剖析是一个挑战,部分原因是需要有足够的效力来自信地识别具有较小效应的基因座。实验性杂交是用于绘制此类性状的宝贵资源。传统上,使用来自单个世代(通常是 F 世代)的个体的全基因组分析针对主要基因座进行了实验性杂交,而来自后代的个体则用于复制和精细映射。在这里,我们旨在自信地识别对弗吉尼亚体重鸡系的 56 天体重的长期、双向选择反应的高度多基因基础做出贡献的小效应基因座。为了实现这一目标,制定了一项策略,以利用高级互交系(由经过 40 代选择的低选择系和高选择系杂交后产生的)的所有世代(F-F)的数据。使用基于低成本、低覆盖率测序的方法,在 99.3%的鸡基因组中获得了 1Mb 区间的高置信度基因型,用于>3300 个互交个体。总共为 56 天体重映射了 12 个全基因组显著的和 30 个额外的提示性 QTL,达到了 10% FDR 阈值。这些 QTL 中只有 2 个在对 F 世代的早期分析中达到了全基因组显著水平。这里映射的小效应 QTL通常是由于通过跨世代整合数据而增加了效力,这得益于基因组覆盖度的增加和标记信息含量的提高。这 12 个显著 QTL 解释了亲本系之间差异的>37%,是之前报道的 2 个显著 QTL 的三倍多。42 个显著和提示性 QTL 一起解释了>80%。使用这里概述的低成本、基于测序的基因分型策略,经济上可行地整合利用实验性杂交中多个世代的所有可用样本。我们的实证结果说明了这种策略用于绘制新的小效应基因座的价值,这些基因座有助于复杂性状,为弗吉尼亚体重鸡系的 56 天体重的高度多基因、长期选择反应提供了更有信心、更全面的个体基因座视图。