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Dissection of QTL effects for root traits using a chromosome arm-specific mapping population in bread wheat
A high-resolution chromosome arm-specific mapping population was used in an attempt to locate/detect gene(s)/QTL for different root traits on the short arm of rye chromosome 1 (1RS) in bread wheat. This population consisted of induced homoeologous recombinants of 1RS with 1BS, each originating from...
Autores principales: | , , , , , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
Springer-Verlag
2010
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3037480/ https://www.ncbi.nlm.nih.gov/pubmed/21153397 http://dx.doi.org/10.1007/s00122-010-1484-5 |
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author | Sharma, Sundrish Xu, Shizhong Ehdaie, Bahman Hoops, Aaron Close, Timothy J. Lukaszewski, Adam J. Waines, J. Giles |
author_facet | Sharma, Sundrish Xu, Shizhong Ehdaie, Bahman Hoops, Aaron Close, Timothy J. Lukaszewski, Adam J. Waines, J. Giles |
author_sort | Sharma, Sundrish |
collection | PubMed |
description | A high-resolution chromosome arm-specific mapping population was used in an attempt to locate/detect gene(s)/QTL for different root traits on the short arm of rye chromosome 1 (1RS) in bread wheat. This population consisted of induced homoeologous recombinants of 1RS with 1BS, each originating from a different crossover event and distinct from all other recombinants in the proportions of rye and wheat chromatin present. It provides a simple and powerful approach to detect even small QTL effects using fewer progeny. A promising empirical Bayes method was applied to estimate additive and epistatic effects for all possible marker pairs simultaneously in a single model. This method has an advantage for QTL analysis in minimizing the error variance and detecting interaction effects between loci with no main effect. A total of 15 QTL effects, 6 additive and 9 epistatic, were detected for different traits of root length and root weight in 1RS wheat. Epistatic interactions were further partitioned into inter-genomic (wheat and rye alleles) and intra-genomic (rye–rye or wheat–wheat alleles) interactions affecting various root traits. Four common regions were identified involving all the QTL for root traits. Two regions carried QTL for almost all the root traits and were responsible for all the epistatic interactions. Evidence for inter-genomic interactions is provided. Comparison of mean values supported the QTL detection. |
format | Text |
id | pubmed-3037480 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2010 |
publisher | Springer-Verlag |
record_format | MEDLINE/PubMed |
spelling | pubmed-30374802011-03-16 Dissection of QTL effects for root traits using a chromosome arm-specific mapping population in bread wheat Sharma, Sundrish Xu, Shizhong Ehdaie, Bahman Hoops, Aaron Close, Timothy J. Lukaszewski, Adam J. Waines, J. Giles Theor Appl Genet Original Paper A high-resolution chromosome arm-specific mapping population was used in an attempt to locate/detect gene(s)/QTL for different root traits on the short arm of rye chromosome 1 (1RS) in bread wheat. This population consisted of induced homoeologous recombinants of 1RS with 1BS, each originating from a different crossover event and distinct from all other recombinants in the proportions of rye and wheat chromatin present. It provides a simple and powerful approach to detect even small QTL effects using fewer progeny. A promising empirical Bayes method was applied to estimate additive and epistatic effects for all possible marker pairs simultaneously in a single model. This method has an advantage for QTL analysis in minimizing the error variance and detecting interaction effects between loci with no main effect. A total of 15 QTL effects, 6 additive and 9 epistatic, were detected for different traits of root length and root weight in 1RS wheat. Epistatic interactions were further partitioned into inter-genomic (wheat and rye alleles) and intra-genomic (rye–rye or wheat–wheat alleles) interactions affecting various root traits. Four common regions were identified involving all the QTL for root traits. Two regions carried QTL for almost all the root traits and were responsible for all the epistatic interactions. Evidence for inter-genomic interactions is provided. Comparison of mean values supported the QTL detection. Springer-Verlag 2010-12-11 2011 /pmc/articles/PMC3037480/ /pubmed/21153397 http://dx.doi.org/10.1007/s00122-010-1484-5 Text en © The Author(s) 2010 https://creativecommons.org/licenses/by-nc/4.0/ This article is distributed under the terms of the Creative Commons Attribution Noncommercial License which permits any noncommercial use, distribution, and reproduction in any medium, provided the original author(s) and source are credited. |
spellingShingle | Original Paper Sharma, Sundrish Xu, Shizhong Ehdaie, Bahman Hoops, Aaron Close, Timothy J. Lukaszewski, Adam J. Waines, J. Giles Dissection of QTL effects for root traits using a chromosome arm-specific mapping population in bread wheat |
title | Dissection of QTL effects for root traits using a chromosome arm-specific mapping population in bread wheat |
title_full | Dissection of QTL effects for root traits using a chromosome arm-specific mapping population in bread wheat |
title_fullStr | Dissection of QTL effects for root traits using a chromosome arm-specific mapping population in bread wheat |
title_full_unstemmed | Dissection of QTL effects for root traits using a chromosome arm-specific mapping population in bread wheat |
title_short | Dissection of QTL effects for root traits using a chromosome arm-specific mapping population in bread wheat |
title_sort | dissection of qtl effects for root traits using a chromosome arm-specific mapping population in bread wheat |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3037480/ https://www.ncbi.nlm.nih.gov/pubmed/21153397 http://dx.doi.org/10.1007/s00122-010-1484-5 |
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