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在弗吉尼亚体重品系的深度近交系中进行低覆盖度测序,为生长的多基因遗传结构提供了深入了解:通过增加功效和提高基因组覆盖度揭示了新的基因座。

Low-coverage sequencing in a deep intercross of the Virginia body weight lines provides insight to the polygenic genetic architecture of growth: novel loci revealed by increased power and improved genome-coverage.

机构信息

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.

出版信息

Poult Sci. 2023 May;102(5):102203. doi: 10.1016/j.psj.2022.102203. Epub 2022 Oct 1.

Abstract

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.

摘要

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。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2f8b/10024170/c4da3396c4aa/gr1.jpg

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