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Dissecting Key Adaptation Traits in the Polyploid Perennial Medicago sativa Using GBS-SNP Mapping

Understanding key adaptation traits is crucial to developing new cultivars with broad adaptations. The main objective of this research is to understand the genetic basis of winter hardiness (WH) and fall dormancy (FD) in alfalfa and the association between the two traits. QTL analysis was conducted...

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Autores principales: Adhikari, Laxman, Lindstrom, Orville M., Markham, Jonathan, Missaoui, Ali M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6039623/
https://www.ncbi.nlm.nih.gov/pubmed/30022989
http://dx.doi.org/10.3389/fpls.2018.00934
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author Adhikari, Laxman
Lindstrom, Orville M.
Markham, Jonathan
Missaoui, Ali M.
author_facet Adhikari, Laxman
Lindstrom, Orville M.
Markham, Jonathan
Missaoui, Ali M.
author_sort Adhikari, Laxman
collection PubMed
description Understanding key adaptation traits is crucial to developing new cultivars with broad adaptations. The main objective of this research is to understand the genetic basis of winter hardiness (WH) and fall dormancy (FD) in alfalfa and the association between the two traits. QTL analysis was conducted in a pseudo-testcross F1 population developed from two cultivars contrasting in FD (3010 with FD = 2 and CW 1010 with FD = 10). The mapping population was evaluated in three replications at two locations (Watkinsville and Blairsville, GA). FD levels showed low to moderate correlations with WH (0.22–0.57). Assessing dormancy in winter is more reliable than in the fall in southern regions with warm winters. The mapping population was genotyped using Genotyping-by-sequencing (GBS). Single dose allele SNPs (SDA) were used for constructing linkage maps. The parental map (CW 1010) consisted of 32 linkage groups spanning 2127.5 cM with 1377 markers and an average marker density of 1.5 cM/SNP. The maternal map (3010) had 32 linkage groups spanning 2788.4 cM with 1837 SDA SNPs with an average marker density of 1.5 cM/SNP. Forty-five significant (P < 0.05) QTLs for FD and 35 QTLs for WH were detected on both male and female linkage maps. More than 75% (22/28) of the dormancy QTL detected from the 3010 parent did not share genomic regions with WH QTLs and more than 70% (12/17) dormancy QTLs detected from CW 1010 parent were localized in different genomic regions than WH QTLs. These results suggest that the two traits have independent inheritance and therefore can be improved separately in breeding programs.
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spelling pubmed-60396232018-07-18 Dissecting Key Adaptation Traits in the Polyploid Perennial Medicago sativa Using GBS-SNP Mapping Adhikari, Laxman Lindstrom, Orville M. Markham, Jonathan Missaoui, Ali M. Front Plant Sci Plant Science Understanding key adaptation traits is crucial to developing new cultivars with broad adaptations. The main objective of this research is to understand the genetic basis of winter hardiness (WH) and fall dormancy (FD) in alfalfa and the association between the two traits. QTL analysis was conducted in a pseudo-testcross F1 population developed from two cultivars contrasting in FD (3010 with FD = 2 and CW 1010 with FD = 10). The mapping population was evaluated in three replications at two locations (Watkinsville and Blairsville, GA). FD levels showed low to moderate correlations with WH (0.22–0.57). Assessing dormancy in winter is more reliable than in the fall in southern regions with warm winters. The mapping population was genotyped using Genotyping-by-sequencing (GBS). Single dose allele SNPs (SDA) were used for constructing linkage maps. The parental map (CW 1010) consisted of 32 linkage groups spanning 2127.5 cM with 1377 markers and an average marker density of 1.5 cM/SNP. The maternal map (3010) had 32 linkage groups spanning 2788.4 cM with 1837 SDA SNPs with an average marker density of 1.5 cM/SNP. Forty-five significant (P < 0.05) QTLs for FD and 35 QTLs for WH were detected on both male and female linkage maps. More than 75% (22/28) of the dormancy QTL detected from the 3010 parent did not share genomic regions with WH QTLs and more than 70% (12/17) dormancy QTLs detected from CW 1010 parent were localized in different genomic regions than WH QTLs. These results suggest that the two traits have independent inheritance and therefore can be improved separately in breeding programs. Frontiers Media S.A. 2018-07-04 /pmc/articles/PMC6039623/ /pubmed/30022989 http://dx.doi.org/10.3389/fpls.2018.00934 Text en Copyright © 2018 Adhikari, Lindstrom, Markham and Missaoui. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Plant Science
Adhikari, Laxman
Lindstrom, Orville M.
Markham, Jonathan
Missaoui, Ali M.
Dissecting Key Adaptation Traits in the Polyploid Perennial Medicago sativa Using GBS-SNP Mapping
title Dissecting Key Adaptation Traits in the Polyploid Perennial Medicago sativa Using GBS-SNP Mapping
title_full Dissecting Key Adaptation Traits in the Polyploid Perennial Medicago sativa Using GBS-SNP Mapping
title_fullStr Dissecting Key Adaptation Traits in the Polyploid Perennial Medicago sativa Using GBS-SNP Mapping
title_full_unstemmed Dissecting Key Adaptation Traits in the Polyploid Perennial Medicago sativa Using GBS-SNP Mapping
title_short Dissecting Key Adaptation Traits in the Polyploid Perennial Medicago sativa Using GBS-SNP Mapping
title_sort dissecting key adaptation traits in the polyploid perennial medicago sativa using gbs-snp mapping
topic Plant Science
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6039623/
https://www.ncbi.nlm.nih.gov/pubmed/30022989
http://dx.doi.org/10.3389/fpls.2018.00934
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