Linkage Disequilibrium Estimation in Low Coverage High-Throughput Sequencing Data. Issue 2 (26th March 2018)

• Record Type: Journal Article
• Authors: Bilton, Timothy P; McEwan, John C; Clarke, Shannon M; Brauning, Rudiger; van Stijn, Tracey C; Rowe, Suzanne J; Dodds, Ken G
• Is Part Of: Genetics. Volume 209:Issue 2(2018)
• Page Start: 389
• Page End: 400
• Publication Date: 2018-03-26
• Subjects: genotyping-by-sequencing -- linkage disequilibrium -- maximum likelihood -- allelic dropout -- low coverage; Genetics -- Periodicals; 576.5
• DOI: 10.1534/genetics.118.300831
• Languages: English
• ISSNs: 0016-6731

Abstract

Abstract: High-throughput sequencing methods provide a cost-effective approach for genotyping and are commonly used in population genetics studies. A drawback of these methods, however, is that sequencing and genotyping errors can arise... High-throughput sequencing methods that multiplex a large number of individuals have provided a cost-effective approach for discovering genome-wide genetic variation in large populations. These sequencing methods are increasingly being utilized in population genetic studies across a diverse range of species. Two side-effects of these methods, however, are (1) sequencing errors and (2) heterozygous genotypes called as homozygous due to only one allele at a particular locus being sequenced, which occurs when the sequencing depth is insufficient. Both of these errors have a profound effect on the estimation of linkage disequilibrium (LD) and, if not taken into account, lead to inaccurate estimates. We developed a new likelihood method, GUS-LD, to estimate pairwise linkage disequilibrium using low coverage sequencing data that accounts for undercalled heterozygous genotypes and sequencing errors. Our findings show that accurate estimates were obtained using GUS-LD, whereas underestimation of LD results if no adjustment is made for the errors.