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Analytical workflow of double-digest restriction site-associated DNA sequencing based on empirical and in silico optimization in tomato

Double-digest restriction site-associated DNA sequencing (ddRAD-Seq) enables high-throughput genome-wide genotyping with next-generation sequencing technology. Consequently, this method has become popular in plant genetics and breeding. Although computational in silico prediction of restriction site...

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Autores principales: Shirasawa, Kenta, Hirakawa, Hideki, Isobe, Sachiko
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4833422/
https://www.ncbi.nlm.nih.gov/pubmed/26932983
http://dx.doi.org/10.1093/dnares/dsw004
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author Shirasawa, Kenta
Hirakawa, Hideki
Isobe, Sachiko
author_facet Shirasawa, Kenta
Hirakawa, Hideki
Isobe, Sachiko
author_sort Shirasawa, Kenta
collection PubMed
description Double-digest restriction site-associated DNA sequencing (ddRAD-Seq) enables high-throughput genome-wide genotyping with next-generation sequencing technology. Consequently, this method has become popular in plant genetics and breeding. Although computational in silico prediction of restriction sites from the genome sequence is recognized as an effective approach for choosing the restriction enzymes to be used, few reports have evaluated the in silico predictions in actual experimental data. In this study, we designed and demonstrated a workflow for in silico and empirical ddRAD-Seq analysis in tomato, as follows: (i) in silico prediction of optimum restriction enzymes from the reference genome, (ii) verification of the prediction by actual ddRAD-Seq data of four restriction enzyme combinations, (iii) establishment of a computational data processing pipeline for high-confidence single nucleotide polymorphism (SNP) calling, and (iv) validation of SNP accuracy by construction of genetic linkage maps. The quality of SNPs based on de novo assembly reference of the ddRAD-Seq reads was comparable with that of SNPs obtained using the published reference genome of tomato. Comparisons of SNP calls in diverse tomato lines revealed that SNP density in the genome influenced the detectability of SNPs by ddRAD-Seq. In silico prediction prior to actual analysis contributed to optimization of the experimental conditions for ddRAD-Seq, e.g. choices of enzymes and plant materials. Following optimization, this ddRAD-Seq pipeline could help accelerate genetics, genomics, and molecular breeding in both model and non-model plants, including crops.
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spelling pubmed-48334222016-04-18 Analytical workflow of double-digest restriction site-associated DNA sequencing based on empirical and in silico optimization in tomato Shirasawa, Kenta Hirakawa, Hideki Isobe, Sachiko DNA Res Full Papers Double-digest restriction site-associated DNA sequencing (ddRAD-Seq) enables high-throughput genome-wide genotyping with next-generation sequencing technology. Consequently, this method has become popular in plant genetics and breeding. Although computational in silico prediction of restriction sites from the genome sequence is recognized as an effective approach for choosing the restriction enzymes to be used, few reports have evaluated the in silico predictions in actual experimental data. In this study, we designed and demonstrated a workflow for in silico and empirical ddRAD-Seq analysis in tomato, as follows: (i) in silico prediction of optimum restriction enzymes from the reference genome, (ii) verification of the prediction by actual ddRAD-Seq data of four restriction enzyme combinations, (iii) establishment of a computational data processing pipeline for high-confidence single nucleotide polymorphism (SNP) calling, and (iv) validation of SNP accuracy by construction of genetic linkage maps. The quality of SNPs based on de novo assembly reference of the ddRAD-Seq reads was comparable with that of SNPs obtained using the published reference genome of tomato. Comparisons of SNP calls in diverse tomato lines revealed that SNP density in the genome influenced the detectability of SNPs by ddRAD-Seq. In silico prediction prior to actual analysis contributed to optimization of the experimental conditions for ddRAD-Seq, e.g. choices of enzymes and plant materials. Following optimization, this ddRAD-Seq pipeline could help accelerate genetics, genomics, and molecular breeding in both model and non-model plants, including crops. Oxford University Press 2016-04 2016-02-29 /pmc/articles/PMC4833422/ /pubmed/26932983 http://dx.doi.org/10.1093/dnares/dsw004 Text en © The Author 2016. Published by Oxford University Press on behalf of Kazusa DNA Research Institute. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Full Papers
Shirasawa, Kenta
Hirakawa, Hideki
Isobe, Sachiko
Analytical workflow of double-digest restriction site-associated DNA sequencing based on empirical and in silico optimization in tomato
title Analytical workflow of double-digest restriction site-associated DNA sequencing based on empirical and in silico optimization in tomato
title_full Analytical workflow of double-digest restriction site-associated DNA sequencing based on empirical and in silico optimization in tomato
title_fullStr Analytical workflow of double-digest restriction site-associated DNA sequencing based on empirical and in silico optimization in tomato
title_full_unstemmed Analytical workflow of double-digest restriction site-associated DNA sequencing based on empirical and in silico optimization in tomato
title_short Analytical workflow of double-digest restriction site-associated DNA sequencing based on empirical and in silico optimization in tomato
title_sort analytical workflow of double-digest restriction site-associated dna sequencing based on empirical and in silico optimization in tomato
topic Full Papers
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4833422/
https://www.ncbi.nlm.nih.gov/pubmed/26932983
http://dx.doi.org/10.1093/dnares/dsw004
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