From reference genomes to population genomics: comparing three reference-aligned reduced-representation sequencing pipelines in two wildlife species
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Date Issued
2019Author
Wright, Belinda R.Farquharson, Katherine A.
McLennan, Elspeth A.
Belov, Katherine
Hogg, Carolyn J.
Grueber, Catherine E.
Common Name
1471-2164Journal
BMC GenomicsVolume
20Issue
1Start page
453
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https://doi.org/10.1186/s12864-019-5806-yAbstract
Recent advances in genomics have greatly increased research opportunities for non-model species. For wildlife, a growing availability of reference genomes means that population genetics is no longer restricted to a small set of anonymous loci. When used in conjunction with a reference genome, reduced-representation sequencing (RRS) provides a cost-effective method for obtaining reliable diversity information for population genetics. Many software tools have been developed to process RRS data, though few studies of non-model species incorporate genome alignment in calling loci. A commonly-used RRS analysis pipeline, Stacks, has this capacity and so it is timely to compare its utility with existing software originally designed for alignment and analysis of whole genome sequencing data. Here we examine population genetic inferences from two species for which reference-aligned reduced-representation data have been collected. Our two study species are a threatened Australian marsupial (Tasmanian devil Sarcophilus harrisii; declining population) and an Arctic-circle migrant bird (pink-footed goose Anser brachyrhynchus; expanding population). Analyses of these data are compared using Stacks versus two widely-used genomics packages, SAMtools and GATK. We also introduce a custom R script to improve the reliability of single nucleotide polymorphism (SNP) calls in all pipelines and conduct population genetic inferences for non-model species with reference genomes.Type
Articleae974a485f413a2113503eed53cd6c53
10.1186/s12864-019-5806-y
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Except where otherwise noted, this item's license is described as https://creativecommons.org/licenses/by/4.0/