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GWAS on Imputed Whole-Genome Resequencing From Genotyping-by-Sequencing Data for Farrowing Interval of Different Parities in Pigs

机译:GWAS关于通过基因分型数据对猪不同胎次产卵间隔进行估算的全基因组重测序

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摘要

The whole-genome sequencing (WGS) data can potentially discover all genetic variants. Studies have shown the power of WGS for genome-wide association study (GWAS) lies in the ability to identify quantitative trait loci and nucleotides (QTNs). However, the resequencing of thousands of target individuals is expensive. Genotype imputation is a powerful approach for WGS and to identify causal mutations. This study aimed to evaluate the imputation accuracy from genotyping-by-sequencing (GBS) to WGS in two pig breeds using a resequencing reference population and to detect single-nucleotide polymorphisms (SNPs) and candidate genes for farrowing interval (FI) of different parities using the data before and after imputation for GWAS. Six hundred target pigs, 300 Landrace and 300 Large White pigs, were genotyped by GBS, and 60 reference pigs, 20 Landrace and 40 Large White pigs, were sequenced by whole-genome resequencing. Imputation for pigs was conducted using Beagle software. The average imputation accuracy (allelic R 2) from GBS to WGS was 0.42 for Landrace pigs and 0.45 for Large White pigs. For Landrace pigs (Large White pigs), 4,514,934 (5,533,290) SNPs had an accuracy >0.3, resulting an average accuracy of 0.73 (0.72), and 2,093,778 (2,468,645) SNPs had an accuracy >0.8, resulting an average accuracy of 0.94 (0.93). Association studies with data before and after imputation were performed for FI of different parities in two populations. Before imputation, 18 and 128 significant SNPs were detected for FI in Landrace and Large White pigs, respectively. After imputation, 125 and 27 significant SNPs were identified for dataset with an accuracy >0.3 and 0.8 in Large White pigs, and 113 and 18 SNPs were found among imputed sequence variants. Among these significant SNPs, six top SNPs were detected in both GBS data and imputed WGS data, namely, SSC2: 136127645, SSC5: 103426443, SSC6: 27811226, SSC10: 3609429, SSC14: 15199253, and SSC15: 150297519. Overall, many candidate genes could be involved in FI of different parities in pigs. Although imputation from GBS to WGS data resulted in a low imputation accuracy, association analyses with imputed WGS data were optimized to detect QTNs for complex trait. The obtained results provide new insight into genotype imputation, genetic architecture, and candidate genes for FI of different parities in Landrace and Large White pigs.
机译:全基因组测序(WGS)数据可以潜在地发现所有遗传变异。研究表明,WGS对于全基因组关联研究(GWAS)的作用在于能够识别数量性状基因座和核苷酸(QTN)。然而,成千上万的目标个体的重测序是昂贵的。基因型归因是WGS和确定因果突变的有力方法。这项研究旨在评估使用重测序参考群体的两个猪种从基因分型(GBS)到WGS的插补准确性,并检测单胎多态性(SNP)和候选基因的不同产仔间隔(FI)在GWAS估算之前和之后使用数据。通过GBS对600头目标猪,300头长白猪和300头大白猪进行基因分型,并通过全基因组重测序对60头参考猪,20头长白猪和40头大白猪进行测序。使用Beagle软件对猪进行插补。长白猪从GBS到WGS的平均估算准确度(等位基因R 2 )为0.42,大型白猪为0.45。对于长白猪(大白猪),4,514,934(5,533,290)个SNP的准确度> 0.3,平均准确度为0.73(0.72),而2,093,778(2,468,645)个SNP的准确度> 0.8,因此平均准确度为0.94(0.93) )。对两个人群中不同胎次的FI进行了归因前后数据的关联研究。在进行插补之前,在长白猪和大型白猪中分别检测到18和128个重要的SNP。估算后,在大型白猪中鉴定出125和27个有效SNP,准确度分别> 0.3和0.8,在估算序列变异中发现113和18个SNP。在这些重要的SNP中,在GBS数据和估算的WGS数据中均检测到六个最高的SNP,即SSC2:136127645,SSC5:103426443,SSC6:27811226,SSC10:3609429,SSC14:15199253和SSC15:150297519。这些基因可能参与了猪不同胎次的FI。尽管从GBS到WGS数据的插补导致较低的插补准确性,但已优化了与插补WGS数据的关联分析以检测QTN的复杂性状。获得的结果为长白猪和大型白猪的不同胎次的基因型归因,遗传结构和FI候选基因提供了新的见识。

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