Coverage recommendation for genotyping analysis of highly heterologous species using next-generation sequencing technology

Next-generation sequencing (NGS) technology is being applied to an increasing number of non-model species and has been used as the primary approach for accurate genotyping in genetic and evolutionary studies. However, inferring genotypes from sequencing data is challenging, particularly for organism...

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Published in:Scientific Reports
Main Authors: Song, Kai, Li, Li, Zhang, Guofan
Format: Text
Language:English
Published: Nature Publishing Group 2016
Subjects:
Online Access:http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5071758/
http://www.ncbi.nlm.nih.gov/pubmed/27760996
https://doi.org/10.1038/srep35736
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spelling ftpubmed:oai:pubmedcentral.nih.gov:5071758 2023-05-15T15:58:43+02:00 Coverage recommendation for genotyping analysis of highly heterologous species using next-generation sequencing technology Song, Kai Li, Li Zhang, Guofan 2016-10-20 http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5071758/ http://www.ncbi.nlm.nih.gov/pubmed/27760996 https://doi.org/10.1038/srep35736 en eng Nature Publishing Group http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5071758/ http://www.ncbi.nlm.nih.gov/pubmed/27760996 http://dx.doi.org/10.1038/srep35736 Copyright © 2016, The Author(s) http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ CC-BY Article Text 2016 ftpubmed https://doi.org/10.1038/srep35736 2016-10-30T00:14:36Z Next-generation sequencing (NGS) technology is being applied to an increasing number of non-model species and has been used as the primary approach for accurate genotyping in genetic and evolutionary studies. However, inferring genotypes from sequencing data is challenging, particularly for organisms with a high degree of heterozygosity. This is because genotype calls from sequencing data are often inaccurate due to low sequencing coverage, and if this is not accounted for, genotype uncertainty can lead to serious bias in downstream analyses, such as quantitative trait locus mapping and genome-wide association studies. Here, we used high-coverage reference data sets from Crassostrea gigas to simulate sequencing data with different coverage, and we evaluate the influence of genotype calling rate and accuracy as a function of coverage. Having initially identified the appropriate parameter settings for filtering to ensure genotype accuracy, we used two different single-nucleotide polymorphism (SNP) calling pipelines, single-sample and multi-sample. We found that a coverage of 15× was suitable for obtaining sufficient numbers of SNPs with high accuracy. Our work provides guidelines for the selection of sequence coverage when using NGS to investigate species with a high degree of heterozygosity and rapid decay of linkage disequilibrium. Text Crassostrea gigas PubMed Central (PMC) Scientific Reports 6 1
institution Open Polar
collection PubMed Central (PMC)
op_collection_id ftpubmed
language English
topic Article
spellingShingle Article
Song, Kai
Li, Li
Zhang, Guofan
Coverage recommendation for genotyping analysis of highly heterologous species using next-generation sequencing technology
topic_facet Article
description Next-generation sequencing (NGS) technology is being applied to an increasing number of non-model species and has been used as the primary approach for accurate genotyping in genetic and evolutionary studies. However, inferring genotypes from sequencing data is challenging, particularly for organisms with a high degree of heterozygosity. This is because genotype calls from sequencing data are often inaccurate due to low sequencing coverage, and if this is not accounted for, genotype uncertainty can lead to serious bias in downstream analyses, such as quantitative trait locus mapping and genome-wide association studies. Here, we used high-coverage reference data sets from Crassostrea gigas to simulate sequencing data with different coverage, and we evaluate the influence of genotype calling rate and accuracy as a function of coverage. Having initially identified the appropriate parameter settings for filtering to ensure genotype accuracy, we used two different single-nucleotide polymorphism (SNP) calling pipelines, single-sample and multi-sample. We found that a coverage of 15× was suitable for obtaining sufficient numbers of SNPs with high accuracy. Our work provides guidelines for the selection of sequence coverage when using NGS to investigate species with a high degree of heterozygosity and rapid decay of linkage disequilibrium.
format Text
author Song, Kai
Li, Li
Zhang, Guofan
author_facet Song, Kai
Li, Li
Zhang, Guofan
author_sort Song, Kai
title Coverage recommendation for genotyping analysis of highly heterologous species using next-generation sequencing technology
title_short Coverage recommendation for genotyping analysis of highly heterologous species using next-generation sequencing technology
title_full Coverage recommendation for genotyping analysis of highly heterologous species using next-generation sequencing technology
title_fullStr Coverage recommendation for genotyping analysis of highly heterologous species using next-generation sequencing technology
title_full_unstemmed Coverage recommendation for genotyping analysis of highly heterologous species using next-generation sequencing technology
title_sort coverage recommendation for genotyping analysis of highly heterologous species using next-generation sequencing technology
publisher Nature Publishing Group
publishDate 2016
url http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5071758/
http://www.ncbi.nlm.nih.gov/pubmed/27760996
https://doi.org/10.1038/srep35736
genre Crassostrea gigas
genre_facet Crassostrea gigas
op_relation http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5071758/
http://www.ncbi.nlm.nih.gov/pubmed/27760996
http://dx.doi.org/10.1038/srep35736
op_rights Copyright © 2016, The Author(s)
http://creativecommons.org/licenses/by/4.0/
This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/
op_rightsnorm CC-BY
op_doi https://doi.org/10.1038/srep35736
container_title Scientific Reports
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