Breeding-assisted genomics: applying meta- GWAS for milling and baking quality in CIMMYT wheat breeding program

One of the biggest challenges for genetic studies on natural or unstructured populations is the unbalanced datasets where individuals are measured at different times and environments. This problem is also common in crop and animal breeding where many individuals are only evaluated for a single year and large but unbalanced datasets can be generated over multiple years. Many wheat breeding programs have focused on increasing bread wheat (Triticum aestivum L.) yield, but processing and end-use quality are critical components when considering its use in feeding the rising population of the next century. The challenges with end-use quality trait improvements are high cost and seed amounts for testing, the latter making selection in early breeding populations impossible. Here we describe a novel approach to identify marker-trait associations within a breeding program using a meta-genome wide association study (GWAS), which combines GWAS analysis from multiyear unbalanced breeding nurseries, in a manner reflecting meta-GWAS in humans. This method facilitated mapping of processing and end-use quality phenotypes from advanced breeding lines (n = 4,095) of the CIMMYT bread wheat breeding program from 2009 to 2014. Using the meta-GWAS we identified marker-trait associations, allele effects, candidate genes, and can select using markers generated in this process. Finally, the scope of this approach can be broadly applied in ‘breeding-assisted genomics’ across many crops to greatly increase our functional understanding of plant genomes.

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Main Authors: Battenfield, S.D., Sheridan, J.L., Silva, L.D.C.E., Miclaus, K.J., Dreisigacker, S., Wolfinger, R.D., Peña-Bautista, R.J., Singh, R.P., Jackson, E.W., Fritz, A.K., Guzman, C., Poland, J.A.
Format: Article biblioteca
Language:English
Published: Public Library of Science 2018
Subjects:Genome-Wide Association Study, Nutrient And Storage Proteins, WHEAT, BREEDING, GENOMICS, QUANTITATIVE TRAIT LOCI, AGRICULTURAL SCIENCES AND BIOTECHNOLOGY, BREAD, FLOUR, RHEOLOGY, HAPLOTYPES,
Online Access:https://hdl.handle.net/10883/19695
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spelling dig-cimmyt-10883-196952023-11-30T14:47:02Z Breeding-assisted genomics: applying meta- GWAS for milling and baking quality in CIMMYT wheat breeding program Battenfield, S.D. Sheridan, J.L. Silva, L.D.C.E. Miclaus, K.J. Dreisigacker, S. Wolfinger, R.D. Peña-Bautista, R.J. Singh, R.P. Jackson, E.W. Fritz, A.K. Guzman, C. Poland, J.A. Genome-Wide Association Study Nutrient And Storage Proteins WHEAT BREEDING GENOMICS QUANTITATIVE TRAIT LOCI AGRICULTURAL SCIENCES AND BIOTECHNOLOGY WHEAT BREAD QUANTITATIVE TRAIT LOCI FLOUR RHEOLOGY HAPLOTYPES One of the biggest challenges for genetic studies on natural or unstructured populations is the unbalanced datasets where individuals are measured at different times and environments. This problem is also common in crop and animal breeding where many individuals are only evaluated for a single year and large but unbalanced datasets can be generated over multiple years. Many wheat breeding programs have focused on increasing bread wheat (Triticum aestivum L.) yield, but processing and end-use quality are critical components when considering its use in feeding the rising population of the next century. The challenges with end-use quality trait improvements are high cost and seed amounts for testing, the latter making selection in early breeding populations impossible. Here we describe a novel approach to identify marker-trait associations within a breeding program using a meta-genome wide association study (GWAS), which combines GWAS analysis from multiyear unbalanced breeding nurseries, in a manner reflecting meta-GWAS in humans. This method facilitated mapping of processing and end-use quality phenotypes from advanced breeding lines (n = 4,095) of the CIMMYT bread wheat breeding program from 2009 to 2014. Using the meta-GWAS we identified marker-trait associations, allele effects, candidate genes, and can select using markers generated in this process. Finally, the scope of this approach can be broadly applied in ‘breeding-assisted genomics’ across many crops to greatly increase our functional understanding of plant genomes. art. e0204757 2018-12-20T19:24:13Z 2018-12-20T19:24:13Z 2018 Article 1932-6203 ESSN: 1932-6203 https://hdl.handle.net/10883/19695 10.1371/journal.pone.0204757 English Wheat http://hdl.handle.net/11529/10548148 https://ndownloader.figshare.com/articles/7402883/versions/1 CIMMYT manages Intellectual Assets as International Public Goods. The user is free to download, print, store and share this work. In case you want to translate or create any other derivative work and share or distribute such translation/derivative work, please contact CIMMYT-Knowledge-Center@cgiar.org indicating the work you want to use and the kind of use you intend; CIMMYT will contact you with the sutable license for that purpose. Open Access PDF San Francisco, Calif., U.S. Public Library of Science 11 13 PLoS ONE
institution CIMMYT
collection DSpace
country México
countrycode MX
component Bibliográfico
access En linea
databasecode dig-cimmyt
tag biblioteca
region America del Norte
libraryname CIMMYT Library
language English
topic Genome-Wide Association Study
Nutrient And Storage Proteins
WHEAT
BREEDING
GENOMICS
QUANTITATIVE TRAIT LOCI
AGRICULTURAL SCIENCES AND BIOTECHNOLOGY
WHEAT
BREAD
QUANTITATIVE TRAIT LOCI
FLOUR
RHEOLOGY
HAPLOTYPES
Genome-Wide Association Study
Nutrient And Storage Proteins
WHEAT
BREEDING
GENOMICS
QUANTITATIVE TRAIT LOCI
AGRICULTURAL SCIENCES AND BIOTECHNOLOGY
WHEAT
BREAD
QUANTITATIVE TRAIT LOCI
FLOUR
RHEOLOGY
HAPLOTYPES
spellingShingle Genome-Wide Association Study
Nutrient And Storage Proteins
WHEAT
BREEDING
GENOMICS
QUANTITATIVE TRAIT LOCI
AGRICULTURAL SCIENCES AND BIOTECHNOLOGY
WHEAT
BREAD
QUANTITATIVE TRAIT LOCI
FLOUR
RHEOLOGY
HAPLOTYPES
Genome-Wide Association Study
Nutrient And Storage Proteins
WHEAT
BREEDING
GENOMICS
QUANTITATIVE TRAIT LOCI
AGRICULTURAL SCIENCES AND BIOTECHNOLOGY
WHEAT
BREAD
QUANTITATIVE TRAIT LOCI
FLOUR
RHEOLOGY
HAPLOTYPES
Battenfield, S.D.
Sheridan, J.L.
Silva, L.D.C.E.
Miclaus, K.J.
Dreisigacker, S.
Wolfinger, R.D.
Peña-Bautista, R.J.
Singh, R.P.
Jackson, E.W.
Fritz, A.K.
Guzman, C.
Poland, J.A.
Breeding-assisted genomics: applying meta- GWAS for milling and baking quality in CIMMYT wheat breeding program
description One of the biggest challenges for genetic studies on natural or unstructured populations is the unbalanced datasets where individuals are measured at different times and environments. This problem is also common in crop and animal breeding where many individuals are only evaluated for a single year and large but unbalanced datasets can be generated over multiple years. Many wheat breeding programs have focused on increasing bread wheat (Triticum aestivum L.) yield, but processing and end-use quality are critical components when considering its use in feeding the rising population of the next century. The challenges with end-use quality trait improvements are high cost and seed amounts for testing, the latter making selection in early breeding populations impossible. Here we describe a novel approach to identify marker-trait associations within a breeding program using a meta-genome wide association study (GWAS), which combines GWAS analysis from multiyear unbalanced breeding nurseries, in a manner reflecting meta-GWAS in humans. This method facilitated mapping of processing and end-use quality phenotypes from advanced breeding lines (n = 4,095) of the CIMMYT bread wheat breeding program from 2009 to 2014. Using the meta-GWAS we identified marker-trait associations, allele effects, candidate genes, and can select using markers generated in this process. Finally, the scope of this approach can be broadly applied in ‘breeding-assisted genomics’ across many crops to greatly increase our functional understanding of plant genomes.
format Article
topic_facet Genome-Wide Association Study
Nutrient And Storage Proteins
WHEAT
BREEDING
GENOMICS
QUANTITATIVE TRAIT LOCI
AGRICULTURAL SCIENCES AND BIOTECHNOLOGY
WHEAT
BREAD
QUANTITATIVE TRAIT LOCI
FLOUR
RHEOLOGY
HAPLOTYPES
author Battenfield, S.D.
Sheridan, J.L.
Silva, L.D.C.E.
Miclaus, K.J.
Dreisigacker, S.
Wolfinger, R.D.
Peña-Bautista, R.J.
Singh, R.P.
Jackson, E.W.
Fritz, A.K.
Guzman, C.
Poland, J.A.
author_facet Battenfield, S.D.
Sheridan, J.L.
Silva, L.D.C.E.
Miclaus, K.J.
Dreisigacker, S.
Wolfinger, R.D.
Peña-Bautista, R.J.
Singh, R.P.
Jackson, E.W.
Fritz, A.K.
Guzman, C.
Poland, J.A.
author_sort Battenfield, S.D.
title Breeding-assisted genomics: applying meta- GWAS for milling and baking quality in CIMMYT wheat breeding program
title_short Breeding-assisted genomics: applying meta- GWAS for milling and baking quality in CIMMYT wheat breeding program
title_full Breeding-assisted genomics: applying meta- GWAS for milling and baking quality in CIMMYT wheat breeding program
title_fullStr Breeding-assisted genomics: applying meta- GWAS for milling and baking quality in CIMMYT wheat breeding program
title_full_unstemmed Breeding-assisted genomics: applying meta- GWAS for milling and baking quality in CIMMYT wheat breeding program
title_sort breeding-assisted genomics: applying meta- gwas for milling and baking quality in cimmyt wheat breeding program
publisher Public Library of Science
publishDate 2018
url https://hdl.handle.net/10883/19695
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