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Genome-wide association study of rust traits in orchardgrass using SLAF-seq technology

BACKGROUND: While orchardgrass (Dactylis glomerata L.) is a well-known perennial forage species, rust diseases cause serious reductions in the yield and quality of orchardgrass; however, genetic mechanisms of rust resistance are not well understood in orchardgrass. RESULTS: In this study, a genome-w...

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Autores principales: Zeng, Bing, Yan, Haidong, Liu, Xinchun, Zang, Wenjing, Zhang, Ailing, Zhou, Sifan, Huang, Linkai, Liu, Jinping
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5322626/
https://www.ncbi.nlm.nih.gov/pubmed/28250720
http://dx.doi.org/10.1186/s41065-017-0027-3
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author Zeng, Bing
Yan, Haidong
Liu, Xinchun
Zang, Wenjing
Zhang, Ailing
Zhou, Sifan
Huang, Linkai
Liu, Jinping
author_facet Zeng, Bing
Yan, Haidong
Liu, Xinchun
Zang, Wenjing
Zhang, Ailing
Zhou, Sifan
Huang, Linkai
Liu, Jinping
author_sort Zeng, Bing
collection PubMed
description BACKGROUND: While orchardgrass (Dactylis glomerata L.) is a well-known perennial forage species, rust diseases cause serious reductions in the yield and quality of orchardgrass; however, genetic mechanisms of rust resistance are not well understood in orchardgrass. RESULTS: In this study, a genome-wide association study (GWAS) was performed using specific-locus amplified fragment sequencing (SLAF-seq) technology in orchardgrass. A total of 2,334,889 SLAF tags were generated to produce 2,309,777 SNPs. ADMIXTURE analysis revealed unstructured subpopulations for 33 accessions, indicating that this orchardgrass population could be used for association analysis. Linkage disequilibrium (LD) analysis revealed an average r(2) of 0.4 across all SNP pairs, indicating a high extent of LD in these samples. Through GWAS, a total of 4,604 SNPs were found to be significantly (P < 0.01) associated with the rust trait. The bulk analysis discovered a number of 5,211 SNPs related to rust trait. Two candidate genes, including cytochrome P450, and prolamin were implicated in disease resistance through prediction of functional genes surrounding each high-quality SNP (P < 0.01) associated with rust traits based on GWAS analysis and bulk analysis CONCLUSIONS: The large number of SNPs associated with rust traits and these two candidate genes may provide the basis for further research on rust resistance mechanisms and marker-assisted selection (MAS) for rust-resistant lineages. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s41065-017-0027-3) contains supplementary material, which is available to authorized users.
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spelling pubmed-53226262017-03-01 Genome-wide association study of rust traits in orchardgrass using SLAF-seq technology Zeng, Bing Yan, Haidong Liu, Xinchun Zang, Wenjing Zhang, Ailing Zhou, Sifan Huang, Linkai Liu, Jinping Hereditas Research BACKGROUND: While orchardgrass (Dactylis glomerata L.) is a well-known perennial forage species, rust diseases cause serious reductions in the yield and quality of orchardgrass; however, genetic mechanisms of rust resistance are not well understood in orchardgrass. RESULTS: In this study, a genome-wide association study (GWAS) was performed using specific-locus amplified fragment sequencing (SLAF-seq) technology in orchardgrass. A total of 2,334,889 SLAF tags were generated to produce 2,309,777 SNPs. ADMIXTURE analysis revealed unstructured subpopulations for 33 accessions, indicating that this orchardgrass population could be used for association analysis. Linkage disequilibrium (LD) analysis revealed an average r(2) of 0.4 across all SNP pairs, indicating a high extent of LD in these samples. Through GWAS, a total of 4,604 SNPs were found to be significantly (P < 0.01) associated with the rust trait. The bulk analysis discovered a number of 5,211 SNPs related to rust trait. Two candidate genes, including cytochrome P450, and prolamin were implicated in disease resistance through prediction of functional genes surrounding each high-quality SNP (P < 0.01) associated with rust traits based on GWAS analysis and bulk analysis CONCLUSIONS: The large number of SNPs associated with rust traits and these two candidate genes may provide the basis for further research on rust resistance mechanisms and marker-assisted selection (MAS) for rust-resistant lineages. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s41065-017-0027-3) contains supplementary material, which is available to authorized users. BioMed Central 2017-02-23 /pmc/articles/PMC5322626/ /pubmed/28250720 http://dx.doi.org/10.1186/s41065-017-0027-3 Text en © The Author(s) 2017 Open AccessThis article is 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 you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Zeng, Bing
Yan, Haidong
Liu, Xinchun
Zang, Wenjing
Zhang, Ailing
Zhou, Sifan
Huang, Linkai
Liu, Jinping
Genome-wide association study of rust traits in orchardgrass using SLAF-seq technology
title Genome-wide association study of rust traits in orchardgrass using SLAF-seq technology
title_full Genome-wide association study of rust traits in orchardgrass using SLAF-seq technology
title_fullStr Genome-wide association study of rust traits in orchardgrass using SLAF-seq technology
title_full_unstemmed Genome-wide association study of rust traits in orchardgrass using SLAF-seq technology
title_short Genome-wide association study of rust traits in orchardgrass using SLAF-seq technology
title_sort genome-wide association study of rust traits in orchardgrass using slaf-seq technology
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5322626/
https://www.ncbi.nlm.nih.gov/pubmed/28250720
http://dx.doi.org/10.1186/s41065-017-0027-3
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