系谱是人类遗传及动植物育种研究与实践的重要信息来源之一。系谱记录错误是育种生产中普遍存在的一种记录错误,影响基因定位、遗传值及表型值预测等相关研究结果的可靠性。现有的方法软件可以利用遗传标记信息对疑似亲子进行亲子鉴定,但这些软件方法操作复杂,限制标记数量,如Cervus。针对当前高密度SNP标记在人类及动植物研究中广泛应用的现状,文章提出了一种基于全基因组高密度SNP数据的亲子鉴定新方法,命名为EasyPC。对EasyPC及Cervus的运行效率进行了对比,并用中国荷斯坦牛(n=2180)和杜洛克猪(n=191)的全基因组SNP芯片数据对EasyPC进行了验证。结果表明：EasyPC运行效率高于Cervus,牛和猪群体系谱错误率分别为20%和6%,与相关研究报道相符。通过使用全基因组SNP标记对群体孟德尔错误率的经验分布进行分析,该方法不仅可以简单、快速、准确地判别系谱的正确性,而且还可以对错误系谱进行校正。EasyPC为解决全基因组研究中基因型及系谱数据前处理过程中的系谱校正问题提供了一种新的途径。
Pedigree is an important information source in the studies on human genetics and animal/plant breeding. Pedigree error is a common data error in breeding practice. It can affect the reliability of results from researches such as gene mapping, genetic or phenotypic value prediction. By using genetic markers, several approaches can identify the suspected pedigrees, but most of them are complex and the allowed number of genetic markers is limited, such as Cervus. Since the wide use of high density single nucleotide polymorphisms (SNPs) in human genetic and animal/plant breeding, a new parentage identification approach (named EasyPC, Easy Pedigree Checking) based on whole genome genetic data was proposed in this study. EasyPC was compared with Cervus on efficiency, and validated with a Chinese Holstein cattle (n=2180) and a Duroc swine (n=191) population. Results showed that EasyPC was much less time demanding than Cervus, and pedigree error rates were 20% for cattle and 6% for swine. Result from the cattle population is in accordance with previous study. By analyzing the empirical distribation of Mendelian error rate calculated in a population using all available SNPs, EasyPC not only can identify the correctness of a pedigree in a simple, fast, and accurate manner, but also can correct the wrong pedigree. EasyPC provides a promising alternative solution to traditional pedigree correction approaches and eases the data analysis of whole genome related studies.
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