Experimental intercrosses between outbred founder populations are powerful resources for mapping loci that contribute to complex traits i.e. quantitative trait loci (QTL). Here, we present an approach and its accompanying software for high-resolution reconstruction of founder mosaic genotypes in the intercross offspring from such populations using whole-genome high-coverage sequence data on founder individuals (~ 30×) and very low-coverage sequence data on intercross individuals (< 0.5×). Sets of founder-line informative markers were selected for each full-sib family and used to infer the founder mosaic genotypes of the intercross individuals. The application of this approach and the quality of the estimated genome-wide genotypes are illustrated in a large F2 pedigree between two divergently selected lines of chickens. We describe how we obtained whole-genome genotype data for hundreds of individuals in a cost- and time-efficient manner by using a Tn5-based library preparation protocol and an imputation algorithm that was optimized for this application. In total, 7.6 million markers segregated in this pedigree and, within each full-sib family, between 10.0 and 13.7% of these were fully informative, i.e. fixed for alternative alleles in the founders from the divergent lines, and were used for reconstruction of the offspring mosaic genotypes. The genotypes that were estimated based on the low-coverage sequence data were highly consistent (> 95% agreement) with those obtained using individual single nucleotide polymorphism (SNP) genotyping. The estimated resolution of the inferred recombination breakpoints was relatively high, with 50% of them being defined on regions shorter than 10 kb. A method and software for inferring founder mosaic genotypes in intercross offspring from low-coverage whole-genome sequencing in pedigrees from heterozygous founders are described. They provide high-quality, high-resolution genotypes in a time- and cost-efficient manner. The software is freely available at https://github.com/CarlborgGenomics/Stripes .

中文翻译：

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远交创始人的杂交谱系中低覆盖率全基因组测序的基因分型：一种经济高效的方法

远交建立者群体之间的实验杂交是用于绘制有助于复杂性状（即数量性状基因座（QTL））的基因座的强大资源。在这里，我们介绍了一种方法及其随附软件，可使用创始人的全基因组高覆盖率序列数据（〜30倍）和极低覆盖率的序列数据，高分辨率重组此类群体的杂交后代中的奠基者镶嵌基因型。在交叉个体上（<0.5×）。为每个同胞家族选择建立者行信息标记集，并用于推断交叉个体的建立者镶嵌基因型。该方法的应用和估计的全基因组全基因型的质量在两只不同选择的鸡系之间的大F2谱系中得到了说明。我们描述了如何通过使用基于Tn5的文库制备方案和针对该应用进行了优化的插补算法，以经济高效的方式获得数百个个体的全基因组基因型数据。在该谱系中以及每个全同胞家族中，总共分离出760万个标记，这些标记中的10.0至13.7％具有充分的信息，即固定了创始人中不同等位基因的替代等位基因，并用于重建后代镶嵌基因型。基于低覆盖率序列数据估算的基因型与使用单个单核苷酸多态性（SNP）基因型获得的基因型高度一致（> 95％一致）。推断的重组断点的估计分辨率相对较高，其中50％的区域定义在短于10 kb的区域。描述了一种方法和软件，该方法和软件可从杂合创始人的家系中的低覆盖率全基因组测序中推断出杂交后代中的创始人马赛克基因型。它们以节省时间和成本的方式提供了高质量，高分辨率的基因型。该软件可从https://github.com/CarlborgGenomics/Stripes免费获得。