High rates of phasing errors in highly polymorphic species with low levels of linkage disequilibrium. (21st March 2016)

• Record Type: Journal Article
• Authors: Bukowicki, Marek; Franssen, Susanne U.; Schlötterer, Christian
• Is Part Of: Molecular ecology resources. Volume 16:Number 4(2016:Jul.)
• Page Start: 874
• Page End: 882
• Publication Date: 2016-03-21
• Subjects: computational phasing -- Drosophila melanogaster -- haplotype analysis -- single nucleotide polymorphism -- switch errors; Molecular ecology -- Periodicals; 572.8
• DOI: 10.1111/1755-0998.12516
• Languages: English
• ISSNs: 1755-098X

Abstract

Abstract: Short read sequencing of diploid individuals does not permit the direct inference of the sequence on each of the two homologous chromosomes. Although various phasing software packages exist, they were primarily tailored for and tested on human data, which differ from other species in factors that influence phasing, such as SNP density, amounts of linkage disequilibrium (LD) and sample sizes. Despite becoming increasingly popular for other species, the reliability of phasing in non‐human data has not been evaluated to a sufficient extent. We scrutinized the phasing accuracy for Drosophila melanogaster, a species with high polymorphism levels and reduced LD relative to humans. We phased two D. melanogaster populations and compared the results to the known haplotypes. The performance increased with size of the reference panel and was highest when the reference panel and phased individuals were from the same population. Full genomic SNP data and inclusion of sequence read information also improved phasing. Despite humans and Drosophila having similar switch error rates between polymorphic sites, the distances between switch errors were much shorter in Drosophila with only fragments <300–1500 bp being correctly phased with ≥95% confidence. This suggests that the higher SNP density cannot compensate for the higher recombination rate in D. melanogaster . Furthermore, we show that populations that have gone through demographic events such as bottlenecks can be phased with higher accuracy. Our results highlight that statistically phased data are particularly error prone in species with large population sizes or populations lacking suitable reference panels.