Efficient Inference of Haplotypes From Genotypes on a Large Animal Pedigree

Abstract

Abstract We present a simple algorithm for reconstruction of haplotypes from a sample of multilocus genotypes. The algorithm is aimed specifically for analysis of very large pedigrees for small chromosomal segments, where recombination frequency within the chromosomal segment can be assumed to be zero. The algorithm was tested both on simulated pedigrees of 155 individuals in a family structure of three generations and on real data of 1149 animals from the Israeli Holstein dairy cattle population, including 406 bulls with genotypes, but no females with genotypes. The rate of haplotype resolution for the simulated data was >91% with a standard deviation of 2%. With 20% missing data, the rate of haplotype resolution was 67.5% with a standard deviation of 1.3%. In both cases all recovered haplotypes were correct. In the real data, allele origin was resolved for 22% of the heterozygous genotypes, even though 70% of the genotypes were missing. Haplotypes were resolved for 36% of the males. Computing time was insignificant for both data sets. Despite the intricacy of large-scale real pedigree genotypes, the proposed algorithm provides a practical rule-based solution for resolving haplotypes for small chromosomal segments in commercial animal populations.