Imputed WGS data of 626 birds

Genotype imputation was performed with two-step approach from 55 to 600 K, and then imputed to WGS. Before Genotype imputation, pre-phasing was executed in Beagle 4.1 with default parameter (Browning and Browning, 2016). Firstly, using 450 birds with 600 K chip data as a reference panel, these 194 birds were imputed from 55 K to 600 K chip data using Beagle 4.0 with pedigree. And then merge 600 K chip data of these 194 birds and 450 birds using VCFtools. Secondly, all of 644 birds with 600 K chip data were imputed to WGS data using a combined reference panel Beagle 4.1 with default parameter. The combined reference panels included 24 key individuals from the yellow-feather dwarf broiler population and 311 birds with WGS data from diverse chicken breeds. More detail information could be found in our previous study (Ye et al., 2019). After performed genotype imputation, quality control of the imputed WGS data was conducted using PLINK (Purcell et al., 2007) with the criteria of SNP call rate &gt; 95%, individual call rate &gt; 97%, MAF &gt; 0.5%, and Hardy-Weinberg equilibrium P-value &gt; 1.0e-6. In addition, individuals would be excluded who existed Mendelian errors. Finally, the remaining 626 individuals and 11,173,020 SNPs were used for further analysis.<br>

本研究采用两步法完成基因型填充：先将基因型从55K升级至600K芯片数据，随后进一步填充至全基因组测序（Whole Genome Sequencing, WGS）数据。在开展基因型填充前，先使用Beagle 4.1并采用默认参数完成预分型（Browning与Browning, 2016）。第一步，以450只携带600K芯片数据的个体作为参考面板，结合系谱信息，使用Beagle 4.0将194只个体的基因型从55K芯片数据填充至600K芯片数据；随后通过VCFtools合并这194只与450只个体的600K芯片基因型数据。第二步，以组合参考面板为基础，使用Beagle 4.1并采用默认参数，将全部644只携带600K芯片数据的个体的基因型填充至WGS数据；该组合参考面板包含24只黄羽矮肉鸡核心群体个体，以及来自多个鸡品种的311只拥有WGS数据的个体。详细研究细节可参见我们此前的发表工作（Ye等, 2019）。完成基因型填充后，使用PLINK（Purcell等, 2007）对填充得到的WGS数据开展质量控制，质控标准为：单核苷酸多态性（Single Nucleotide Polymorphism, SNP）检出率＞95%、个体检出率＞97%、最小等位基因频率（Minor Allele Frequency, MAF）＞0.5%，且哈迪-温伯格平衡（Hardy-Weinberg equilibrium）P值＞1.0×10^-6；此外，存在孟德尔错误的个体将被剔除。最终剩余626只个体与11,173,020个SNP位点用于后续分析。