Cargando…

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

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Schierenbeck, Matías, Alqudah, Ahmad M., Lohwasser, Ulrike, Tarawneh, Rasha A., Simón, María Rosa, Börner, Andreas
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8431894/
https://www.ncbi.nlm.nih.gov/pubmed/34507551
http://dx.doi.org/10.1186/s12870-021-03183-3
_version_ 1783751041979777024
author Schierenbeck, Matías
Alqudah, Ahmad M.
Lohwasser, Ulrike
Tarawneh, Rasha A.
Simón, María Rosa
Börner, Andreas
author_facet Schierenbeck, Matías
Alqudah, Ahmad M.
Lohwasser, Ulrike
Tarawneh, Rasha A.
Simón, María Rosa
Börner, Andreas
author_sort Schierenbeck, Matías
collection PubMed
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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12870-021-03183-3.
format Online
Article
Text
id pubmed-8431894
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-84318942021-09-10 Genetic dissection of grain architecture-related traits in a winter wheat population Schierenbeck, Matías Alqudah, Ahmad M. Lohwasser, Ulrike Tarawneh, Rasha A. Simón, María Rosa Börner, Andreas BMC Plant Biol Research Article 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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12870-021-03183-3. BioMed Central 2021-09-10 /pmc/articles/PMC8431894/ /pubmed/34507551 http://dx.doi.org/10.1186/s12870-021-03183-3 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research Article
Schierenbeck, Matías
Alqudah, Ahmad M.
Lohwasser, Ulrike
Tarawneh, Rasha A.
Simón, María Rosa
Börner, Andreas
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
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_short 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
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8431894/
https://www.ncbi.nlm.nih.gov/pubmed/34507551
http://dx.doi.org/10.1186/s12870-021-03183-3
work_keys_str_mv AT schierenbeckmatias geneticdissectionofgrainarchitecturerelatedtraitsinawinterwheatpopulation
AT alqudahahmadm geneticdissectionofgrainarchitecturerelatedtraitsinawinterwheatpopulation
AT lohwasserulrike geneticdissectionofgrainarchitecturerelatedtraitsinawinterwheatpopulation
AT tarawnehrashaa geneticdissectionofgrainarchitecturerelatedtraitsinawinterwheatpopulation
AT simonmariarosa geneticdissectionofgrainarchitecturerelatedtraitsinawinterwheatpopulation
AT bornerandreas geneticdissectionofgrainarchitecturerelatedtraitsinawinterwheatpopulation