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Genomic prediction and GWAS of yield, quality and disease-related traits in spring barley and winter wheat

Genome-wide association study (GWAS) and genomic prediction (GP) are extensively employed to accelerate genetic gain and identify QTL in plant breeding. In this study, 1,317 spring barley and 1,325 winter wheat breeding lines from a commercial breeding program were genotyped with the Illumina 9 K ba...

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Autores principales: Tsai, Hsin-Yuan, Janss, Luc L., Andersen, Jeppe R., Orabi, Jihad, Jensen, Jens D., Jahoor, Ahmed, Jensen, Just
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7042356/
https://www.ncbi.nlm.nih.gov/pubmed/32099054
http://dx.doi.org/10.1038/s41598-020-60203-2
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author Tsai, Hsin-Yuan
Janss, Luc L.
Andersen, Jeppe R.
Orabi, Jihad
Jensen, Jens D.
Jahoor, Ahmed
Jensen, Just
author_facet Tsai, Hsin-Yuan
Janss, Luc L.
Andersen, Jeppe R.
Orabi, Jihad
Jensen, Jens D.
Jahoor, Ahmed
Jensen, Just
author_sort Tsai, Hsin-Yuan
collection PubMed
description Genome-wide association study (GWAS) and genomic prediction (GP) are extensively employed to accelerate genetic gain and identify QTL in plant breeding. In this study, 1,317 spring barley and 1,325 winter wheat breeding lines from a commercial breeding program were genotyped with the Illumina 9 K barley or 15 K wheat SNP-chip, and phenotyped in multiple years and locations. For GWAS, in spring barley, a QTL on chr. 4H associated with powdery mildew and ramularia resistance were found. There were several SNPs on chr. 4H showing genome-wide significance with yield traits. In winter wheat, GWAS identified two SNPs on chr. 6A, and one SNP on chr. 1B, significantly associated with quality trait moisture, as well as one SNP located on chr. 5B associated with starch content in the seeds. The significant SNPs identified by multiple trait GWAS were generally the same as those found in single trait GWAS. GWAS including genotype-location information in the model identified significant SNPs in each tested location, which were not found previously when including all locations in the GWAS. For GP, in spring barley, GP using the Bayesian Power Lasso model had higher accuracy than ridge regression BLUP in powdery mildew and yield traits, whereas the prediction accuracies were similar using Bayesian Power Lasso model and rrBLUP for yield traits in winter wheat.
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spelling pubmed-70423562020-03-03 Genomic prediction and GWAS of yield, quality and disease-related traits in spring barley and winter wheat Tsai, Hsin-Yuan Janss, Luc L. Andersen, Jeppe R. Orabi, Jihad Jensen, Jens D. Jahoor, Ahmed Jensen, Just Sci Rep Article Genome-wide association study (GWAS) and genomic prediction (GP) are extensively employed to accelerate genetic gain and identify QTL in plant breeding. In this study, 1,317 spring barley and 1,325 winter wheat breeding lines from a commercial breeding program were genotyped with the Illumina 9 K barley or 15 K wheat SNP-chip, and phenotyped in multiple years and locations. For GWAS, in spring barley, a QTL on chr. 4H associated with powdery mildew and ramularia resistance were found. There were several SNPs on chr. 4H showing genome-wide significance with yield traits. In winter wheat, GWAS identified two SNPs on chr. 6A, and one SNP on chr. 1B, significantly associated with quality trait moisture, as well as one SNP located on chr. 5B associated with starch content in the seeds. The significant SNPs identified by multiple trait GWAS were generally the same as those found in single trait GWAS. GWAS including genotype-location information in the model identified significant SNPs in each tested location, which were not found previously when including all locations in the GWAS. For GP, in spring barley, GP using the Bayesian Power Lasso model had higher accuracy than ridge regression BLUP in powdery mildew and yield traits, whereas the prediction accuracies were similar using Bayesian Power Lasso model and rrBLUP for yield traits in winter wheat. Nature Publishing Group UK 2020-02-25 /pmc/articles/PMC7042356/ /pubmed/32099054 http://dx.doi.org/10.1038/s41598-020-60203-2 Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as 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 images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Tsai, Hsin-Yuan
Janss, Luc L.
Andersen, Jeppe R.
Orabi, Jihad
Jensen, Jens D.
Jahoor, Ahmed
Jensen, Just
Genomic prediction and GWAS of yield, quality and disease-related traits in spring barley and winter wheat
title Genomic prediction and GWAS of yield, quality and disease-related traits in spring barley and winter wheat
title_full Genomic prediction and GWAS of yield, quality and disease-related traits in spring barley and winter wheat
title_fullStr Genomic prediction and GWAS of yield, quality and disease-related traits in spring barley and winter wheat
title_full_unstemmed Genomic prediction and GWAS of yield, quality and disease-related traits in spring barley and winter wheat
title_short Genomic prediction and GWAS of yield, quality and disease-related traits in spring barley and winter wheat
title_sort genomic prediction and gwas of yield, quality and disease-related traits in spring barley and winter wheat
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7042356/
https://www.ncbi.nlm.nih.gov/pubmed/32099054
http://dx.doi.org/10.1038/s41598-020-60203-2
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