Developing and applying of a parentage identification approach based on high density genetic markers

Abstract

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 distribution 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.