The presence and impact of reference bias on population genomic studies of prehistoric human populations.

Haploid high quality reference genomes are an important resource in genomic research projects. A consequence is that DNA fragments carrying the reference allele will be more likely to map successfully, or receive higher quality scores. This reference bias can have effects on downstream population ge...

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Main Authors: Torsten Günther, Carl Nettelblad
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2019-07-01
Series:PLoS Genetics
Online Access:https://doi.org/10.1371/journal.pgen.1008302
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author Torsten Günther
Carl Nettelblad
author_facet Torsten Günther
Carl Nettelblad
author_sort Torsten Günther
collection DOAJ
description Haploid high quality reference genomes are an important resource in genomic research projects. A consequence is that DNA fragments carrying the reference allele will be more likely to map successfully, or receive higher quality scores. This reference bias can have effects on downstream population genomic analysis when heterozygous sites are falsely considered homozygous for the reference allele. In palaeogenomic studies of human populations, mapping against the human reference genome is used to identify endogenous human sequences. Ancient DNA studies usually operate with low sequencing coverages and fragmentation of DNA molecules causes a large proportion of the sequenced fragments to be shorter than 50 bp-reducing the amount of accepted mismatches, and increasing the probability of multiple matching sites in the genome. These ancient DNA specific properties are potentially exacerbating the impact of reference bias on downstream analyses, especially since most studies of ancient human populations use pseudo-haploid data, i.e. they randomly sample only one sequencing read per site. We show that reference bias is pervasive in published ancient DNA sequence data of prehistoric humans with some differences between individual genomic regions. We illustrate that the strength of reference bias is negatively correlated with fragment length. Most genomic regions we investigated show little to no mapping bias but even a small proportion of sites with bias can impact analyses of those particular loci or slightly skew genome-wide estimates. Therefore, reference bias has the potential to cause minor but significant differences in the results of downstream analyses such as population allele sharing, heterozygosity estimates and estimates of archaic ancestry. These spurious results highlight how important it is to be aware of these technical artifacts and that we need strategies to mitigate the effect. Therefore, we suggest some post-mapping filtering strategies to resolve reference bias which help to reduce its impact substantially.
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spelling doaj.art-87f29c13a5164a43bedf206ee0a543b52022-12-21T20:06:50ZengPublic Library of Science (PLoS)PLoS Genetics1553-73901553-74042019-07-01157e100830210.1371/journal.pgen.1008302The presence and impact of reference bias on population genomic studies of prehistoric human populations.Torsten GüntherCarl NettelbladHaploid high quality reference genomes are an important resource in genomic research projects. A consequence is that DNA fragments carrying the reference allele will be more likely to map successfully, or receive higher quality scores. This reference bias can have effects on downstream population genomic analysis when heterozygous sites are falsely considered homozygous for the reference allele. In palaeogenomic studies of human populations, mapping against the human reference genome is used to identify endogenous human sequences. Ancient DNA studies usually operate with low sequencing coverages and fragmentation of DNA molecules causes a large proportion of the sequenced fragments to be shorter than 50 bp-reducing the amount of accepted mismatches, and increasing the probability of multiple matching sites in the genome. These ancient DNA specific properties are potentially exacerbating the impact of reference bias on downstream analyses, especially since most studies of ancient human populations use pseudo-haploid data, i.e. they randomly sample only one sequencing read per site. We show that reference bias is pervasive in published ancient DNA sequence data of prehistoric humans with some differences between individual genomic regions. We illustrate that the strength of reference bias is negatively correlated with fragment length. Most genomic regions we investigated show little to no mapping bias but even a small proportion of sites with bias can impact analyses of those particular loci or slightly skew genome-wide estimates. Therefore, reference bias has the potential to cause minor but significant differences in the results of downstream analyses such as population allele sharing, heterozygosity estimates and estimates of archaic ancestry. These spurious results highlight how important it is to be aware of these technical artifacts and that we need strategies to mitigate the effect. Therefore, we suggest some post-mapping filtering strategies to resolve reference bias which help to reduce its impact substantially.https://doi.org/10.1371/journal.pgen.1008302
spellingShingle Torsten Günther
Carl Nettelblad
The presence and impact of reference bias on population genomic studies of prehistoric human populations.
PLoS Genetics
title The presence and impact of reference bias on population genomic studies of prehistoric human populations.
title_full The presence and impact of reference bias on population genomic studies of prehistoric human populations.
title_fullStr The presence and impact of reference bias on population genomic studies of prehistoric human populations.
title_full_unstemmed The presence and impact of reference bias on population genomic studies of prehistoric human populations.
title_short The presence and impact of reference bias on population genomic studies of prehistoric human populations.
title_sort presence and impact of reference bias on population genomic studies of prehistoric human populations
url https://doi.org/10.1371/journal.pgen.1008302
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