Increasing Genome Sampling and Improving SNP Genotyping for Genotyping-by-Sequencing with New Combinations of Restriction Enzymes

Genotyping-by-sequencing (GBS) has emerged as a useful genomic approach for exploring genome-wide genetic variation. However, GBS commonly samples a genome unevenly and can generate a substantial amount of missing data. These technical features would limit the power of various GBS-based genetic and...

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Main Authors: Fu, Yong-Bi, Peterson, Gregory W., Dong, Yibo
Format: Online
Language:English
Published: Genetics Society of America 2016
Online Access:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4825655/
id pubmed-4825655
recordtype oai_dc
spelling pubmed-48256552016-04-11 Increasing Genome Sampling and Improving SNP Genotyping for Genotyping-by-Sequencing with New Combinations of Restriction Enzymes Fu, Yong-Bi Peterson, Gregory W. Dong, Yibo Investigations Genotyping-by-sequencing (GBS) has emerged as a useful genomic approach for exploring genome-wide genetic variation. However, GBS commonly samples a genome unevenly and can generate a substantial amount of missing data. These technical features would limit the power of various GBS-based genetic and genomic analyses. Here we present software called IgCoverage for in silico evaluation of genomic coverage through GBS with an individual or pair of restriction enzymes on one sequenced genome, and report a new set of 21 restriction enzyme combinations that can be applied to enhance GBS applications. These enzyme combinations were developed through an application of IgCoverage on 22 plant, animal, and fungus species with sequenced genomes, and some of them were empirically evaluated with different runs of Illumina MiSeq sequencing in 12 plant species. The in silico analysis of 22 organisms revealed up to eight times more genome coverage for the new combinations consisted of pairing four- or five-cutter restriction enzymes than the commonly used enzyme combination PstI + MspI. The empirical evaluation of the new enzyme combination (HinfI + HpyCH4IV) in 12 plant species showed 1.7–6 times more genome coverage than PstI + MspI, and 2.3 times more genome coverage in dicots than monocots. Also, the SNP genotyping in 12 Arabidopsis and 12 rice plants revealed that HinfI + HpyCH4IV generated 7 and 1.3 times more SNPs (with 0–16.7% missing observations) than PstI + MspI, respectively. These findings demonstrate that these novel enzyme combinations can be utilized to increase genome sampling and improve SNP genotyping in various GBS applications. Genetics Society of America 2016-01-27 /pmc/articles/PMC4825655/ /pubmed/26818077 http://dx.doi.org/10.1534/g3.115.025775 Text en Copyright © 2016 Fu et al. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
repository_type Open Access Journal
institution_category Foreign Institution
institution US National Center for Biotechnology Information
building NCBI PubMed
collection Online Access
language English
format Online
author Fu, Yong-Bi
Peterson, Gregory W.
Dong, Yibo
spellingShingle Fu, Yong-Bi
Peterson, Gregory W.
Dong, Yibo
Increasing Genome Sampling and Improving SNP Genotyping for Genotyping-by-Sequencing with New Combinations of Restriction Enzymes
author_facet Fu, Yong-Bi
Peterson, Gregory W.
Dong, Yibo
author_sort Fu, Yong-Bi
title Increasing Genome Sampling and Improving SNP Genotyping for Genotyping-by-Sequencing with New Combinations of Restriction Enzymes
title_short Increasing Genome Sampling and Improving SNP Genotyping for Genotyping-by-Sequencing with New Combinations of Restriction Enzymes
title_full Increasing Genome Sampling and Improving SNP Genotyping for Genotyping-by-Sequencing with New Combinations of Restriction Enzymes
title_fullStr Increasing Genome Sampling and Improving SNP Genotyping for Genotyping-by-Sequencing with New Combinations of Restriction Enzymes
title_full_unstemmed Increasing Genome Sampling and Improving SNP Genotyping for Genotyping-by-Sequencing with New Combinations of Restriction Enzymes
title_sort increasing genome sampling and improving snp genotyping for genotyping-by-sequencing with new combinations of restriction enzymes
description Genotyping-by-sequencing (GBS) has emerged as a useful genomic approach for exploring genome-wide genetic variation. However, GBS commonly samples a genome unevenly and can generate a substantial amount of missing data. These technical features would limit the power of various GBS-based genetic and genomic analyses. Here we present software called IgCoverage for in silico evaluation of genomic coverage through GBS with an individual or pair of restriction enzymes on one sequenced genome, and report a new set of 21 restriction enzyme combinations that can be applied to enhance GBS applications. These enzyme combinations were developed through an application of IgCoverage on 22 plant, animal, and fungus species with sequenced genomes, and some of them were empirically evaluated with different runs of Illumina MiSeq sequencing in 12 plant species. The in silico analysis of 22 organisms revealed up to eight times more genome coverage for the new combinations consisted of pairing four- or five-cutter restriction enzymes than the commonly used enzyme combination PstI + MspI. The empirical evaluation of the new enzyme combination (HinfI + HpyCH4IV) in 12 plant species showed 1.7–6 times more genome coverage than PstI + MspI, and 2.3 times more genome coverage in dicots than monocots. Also, the SNP genotyping in 12 Arabidopsis and 12 rice plants revealed that HinfI + HpyCH4IV generated 7 and 1.3 times more SNPs (with 0–16.7% missing observations) than PstI + MspI, respectively. These findings demonstrate that these novel enzyme combinations can be utilized to increase genome sampling and improve SNP genotyping in various GBS applications.
publisher Genetics Society of America
publishDate 2016
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4825655/
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