Genetic dissection of grain architecture-related traits in a winter wheat population

Autores
Schierenbeck, Matías; Alqudah, Ahmad M.; Lohwasser, Ulrike; Tarawneh, Rasha A.; Simón, María Rosa; Börner, Andreas
Año de publicación
2021
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Background: The future productivity of wheat (T. aestivum L.) as the most grown crop worldwide is of utmost importance for global food security. Thousand kernel weight (TKW) in wheat is closely associated with grain architecture-related traits, e.g. kernel length (KL), kernel width (KW), kernel area (KA), kernel diameter ratio (KDR), and factor form density (FFD). Discovering the genetic architecture of natural variation in these traits, identifying QTL and candidate genes are the main aims of this study. Therefore, grain architecture-related traits in 261 worldwide winter accessions over three field-year experiments were evaluated. Results: Genome-wide association analysis using 90K SNP array in FarmCPU model revealed several interesting genomic regions including 17 significant SNPs passing false discovery rate threshold and strongly associated with the studied traits. Four of associated SNPs were physically located inside candidate genes within LD interval e.g. BobWhite_c5872_589 (602,710,399 bp) found to be inside TraesCS6A01G383800 (602,699,767-602,711,726 bp). Further analysis reveals the four novel candidate genes potentially involved in more than one grain architecture-related traits with a pleiotropic effects e.g. TraesCS6A01G383800 gene on 6A encoding oxidoreductase activity was associated with TKW and KA. The allelic variation at the associated SNPs showed significant differences betweeen the accessions carying the wild and mutated alleles e.g. accessions carying C allele of BobWhite_c5872_589, TraesCS6A01G383800 had significantly higher TKW than the accessions carying T allele. Interestingly, these genes were highly expressed in the grain-tissues, demonstrating their pivotal role in controlling the grain architecture. Conclusions: These results are valuable for identifying regions associated with kernel weight and dimensions and potentially help breeders in improving kernel weight and architecture-related traits in order to increase wheat yield potential and end-use quality.
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Facultad de Ciencias Agrarias y Forestales
Materia
Ciencias Agrarias
Thousand kernel weight
Winter wheat
GWAS
Grain architecture
Candidate genes
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by/4.0/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/136420

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network_name_str SEDICI (UNLP)
spelling Genetic dissection of grain architecture-related traits in a winter wheat populationSchierenbeck, MatíasAlqudah, Ahmad M.Lohwasser, UlrikeTarawneh, Rasha A.Simón, María RosaBörner, AndreasCiencias AgrariasThousand kernel weightWinter wheatGWASGrain architectureCandidate genesBackground: The future productivity of wheat (T. aestivum L.) as the most grown crop worldwide is of utmost importance for global food security. Thousand kernel weight (TKW) in wheat is closely associated with grain architecture-related traits, e.g. kernel length (KL), kernel width (KW), kernel area (KA), kernel diameter ratio (KDR), and factor form density (FFD). Discovering the genetic architecture of natural variation in these traits, identifying QTL and candidate genes are the main aims of this study. Therefore, grain architecture-related traits in 261 worldwide winter accessions over three field-year experiments were evaluated. Results: Genome-wide association analysis using 90K SNP array in FarmCPU model revealed several interesting genomic regions including 17 significant SNPs passing false discovery rate threshold and strongly associated with the studied traits. Four of associated SNPs were physically located inside candidate genes within LD interval e.g. BobWhite_c5872_589 (602,710,399 bp) found to be inside TraesCS6A01G383800 (602,699,767-602,711,726 bp). Further analysis reveals the four novel candidate genes potentially involved in more than one grain architecture-related traits with a pleiotropic effects e.g. TraesCS6A01G383800 gene on 6A encoding oxidoreductase activity was associated with TKW and KA. The allelic variation at the associated SNPs showed significant differences betweeen the accessions carying the wild and mutated alleles e.g. accessions carying C allele of BobWhite_c5872_589, TraesCS6A01G383800 had significantly higher TKW than the accessions carying T allele. Interestingly, these genes were highly expressed in the grain-tissues, demonstrating their pivotal role in controlling the grain architecture. Conclusions: These results are valuable for identifying regions associated with kernel weight and dimensions and potentially help breeders in improving kernel weight and architecture-related traits in order to increase wheat yield potential and end-use quality.Este artículo tiene una corrección que puede verse haciendo clic en "Documentos relacionados".Facultad de Ciencias Agrarias y Forestales2021info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionArticulohttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfhttp://sedici.unlp.edu.ar/handle/10915/136420enginfo:eu-repo/semantics/altIdentifier/issn/1471-2229info:eu-repo/semantics/altIdentifier/doi/10.1186/s12870-021-03183-3info:eu-repo/semantics/altIdentifier/pmid/34507551info:eu-repo/semantics/reference/url/https://bmcplantbiol.biomedcentral.com/articles/10.1186/s12870-021-03216-xinfo:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by/4.0/Creative Commons Attribution 4.0 International (CC BY 4.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-29T11:31:58Zoai:sedici.unlp.edu.ar:10915/136420Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-29 11:31:58.359SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Genetic dissection of grain architecture-related traits in a winter wheat population
title Genetic dissection of grain architecture-related traits in a winter wheat population
spellingShingle Genetic dissection of grain architecture-related traits in a winter wheat population
Schierenbeck, Matías
Ciencias Agrarias
Thousand kernel weight
Winter wheat
GWAS
Grain architecture
Candidate genes
title_short Genetic dissection of grain architecture-related traits in a winter wheat population
title_full Genetic dissection of grain architecture-related traits in a winter wheat population
title_fullStr Genetic dissection of grain architecture-related traits in a winter wheat population
title_full_unstemmed Genetic dissection of grain architecture-related traits in a winter wheat population
title_sort Genetic dissection of grain architecture-related traits in a winter wheat population
dc.creator.none.fl_str_mv Schierenbeck, Matías
Alqudah, Ahmad M.
Lohwasser, Ulrike
Tarawneh, Rasha A.
Simón, María Rosa
Börner, Andreas
author Schierenbeck, Matías
author_facet Schierenbeck, Matías
Alqudah, Ahmad M.
Lohwasser, Ulrike
Tarawneh, Rasha A.
Simón, María Rosa
Börner, Andreas
author_role author
author2 Alqudah, Ahmad M.
Lohwasser, Ulrike
Tarawneh, Rasha A.
Simón, María Rosa
Börner, Andreas
author2_role author
author
author
author
author
dc.subject.none.fl_str_mv Ciencias Agrarias
Thousand kernel weight
Winter wheat
GWAS
Grain architecture
Candidate genes
topic Ciencias Agrarias
Thousand kernel weight
Winter wheat
GWAS
Grain architecture
Candidate genes
dc.description.none.fl_txt_mv Background: The future productivity of wheat (T. aestivum L.) as the most grown crop worldwide is of utmost importance for global food security. Thousand kernel weight (TKW) in wheat is closely associated with grain architecture-related traits, e.g. kernel length (KL), kernel width (KW), kernel area (KA), kernel diameter ratio (KDR), and factor form density (FFD). Discovering the genetic architecture of natural variation in these traits, identifying QTL and candidate genes are the main aims of this study. Therefore, grain architecture-related traits in 261 worldwide winter accessions over three field-year experiments were evaluated. Results: Genome-wide association analysis using 90K SNP array in FarmCPU model revealed several interesting genomic regions including 17 significant SNPs passing false discovery rate threshold and strongly associated with the studied traits. Four of associated SNPs were physically located inside candidate genes within LD interval e.g. BobWhite_c5872_589 (602,710,399 bp) found to be inside TraesCS6A01G383800 (602,699,767-602,711,726 bp). Further analysis reveals the four novel candidate genes potentially involved in more than one grain architecture-related traits with a pleiotropic effects e.g. TraesCS6A01G383800 gene on 6A encoding oxidoreductase activity was associated with TKW and KA. The allelic variation at the associated SNPs showed significant differences betweeen the accessions carying the wild and mutated alleles e.g. accessions carying C allele of BobWhite_c5872_589, TraesCS6A01G383800 had significantly higher TKW than the accessions carying T allele. Interestingly, these genes were highly expressed in the grain-tissues, demonstrating their pivotal role in controlling the grain architecture. Conclusions: These results are valuable for identifying regions associated with kernel weight and dimensions and potentially help breeders in improving kernel weight and architecture-related traits in order to increase wheat yield potential and end-use quality.
Este artículo tiene una corrección que puede verse haciendo clic en "Documentos relacionados".
Facultad de Ciencias Agrarias y Forestales
description Background: The future productivity of wheat (T. aestivum L.) as the most grown crop worldwide is of utmost importance for global food security. Thousand kernel weight (TKW) in wheat is closely associated with grain architecture-related traits, e.g. kernel length (KL), kernel width (KW), kernel area (KA), kernel diameter ratio (KDR), and factor form density (FFD). Discovering the genetic architecture of natural variation in these traits, identifying QTL and candidate genes are the main aims of this study. Therefore, grain architecture-related traits in 261 worldwide winter accessions over three field-year experiments were evaluated. Results: Genome-wide association analysis using 90K SNP array in FarmCPU model revealed several interesting genomic regions including 17 significant SNPs passing false discovery rate threshold and strongly associated with the studied traits. Four of associated SNPs were physically located inside candidate genes within LD interval e.g. BobWhite_c5872_589 (602,710,399 bp) found to be inside TraesCS6A01G383800 (602,699,767-602,711,726 bp). Further analysis reveals the four novel candidate genes potentially involved in more than one grain architecture-related traits with a pleiotropic effects e.g. TraesCS6A01G383800 gene on 6A encoding oxidoreductase activity was associated with TKW and KA. The allelic variation at the associated SNPs showed significant differences betweeen the accessions carying the wild and mutated alleles e.g. accessions carying C allele of BobWhite_c5872_589, TraesCS6A01G383800 had significantly higher TKW than the accessions carying T allele. Interestingly, these genes were highly expressed in the grain-tissues, demonstrating their pivotal role in controlling the grain architecture. Conclusions: These results are valuable for identifying regions associated with kernel weight and dimensions and potentially help breeders in improving kernel weight and architecture-related traits in order to increase wheat yield potential and end-use quality.
publishDate 2021
dc.date.none.fl_str_mv 2021
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Articulo
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info:eu-repo/semantics/altIdentifier/doi/10.1186/s12870-021-03183-3
info:eu-repo/semantics/altIdentifier/pmid/34507551
info:eu-repo/semantics/reference/url/https://bmcplantbiol.biomedcentral.com/articles/10.1186/s12870-021-03216-x
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
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Creative Commons Attribution 4.0 International (CC BY 4.0)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by/4.0/
Creative Commons Attribution 4.0 International (CC BY 4.0)
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