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QTL and QTL networks for cold tolerance at the reproductive stage detected using selective introgression in rice

Low temperature stress is one of the major abiotic stresses limiting the productivity of Geng (japonica) rice grown the temperate regions as well as in tropical high lands worldwide. To develop rice varieties with improved cold tolerance (CT) at the reproductive stage, 84 BC(2) CT introgression line...

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Autores principales: Liang, Yuntao, Meng, Lijun, Lin, Xiuyun, Cui, Yanru, Pang, Yunlong, Xu, Jianlong, Li, Zhikang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6141068/
https://www.ncbi.nlm.nih.gov/pubmed/30222760
http://dx.doi.org/10.1371/journal.pone.0200846
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author Liang, Yuntao
Meng, Lijun
Lin, Xiuyun
Cui, Yanru
Pang, Yunlong
Xu, Jianlong
Li, Zhikang
author_facet Liang, Yuntao
Meng, Lijun
Lin, Xiuyun
Cui, Yanru
Pang, Yunlong
Xu, Jianlong
Li, Zhikang
author_sort Liang, Yuntao
collection PubMed
description Low temperature stress is one of the major abiotic stresses limiting the productivity of Geng (japonica) rice grown the temperate regions as well as in tropical high lands worldwide. To develop rice varieties with improved cold tolerance (CT) at the reproductive stage, 84 BC(2) CT introgression lines (ILs) were developed from five populations through backcross breeding. These CT ILs plus 310 random ILs from the same BC populations were used for dissecting genetic networks underlying CT in rice by detecting QTLs and functional genetic units (FGUs) contributing to CT. Seventeen major QTLs for CT were identified using five selective introgression populations and the method of segregation distortion. Of them, three QTLs were confirmed using the random populations and seven others locate in the regions with previously reported CT QTLs/genes. Using multi-locus probability tests and linkage disequilibrium (LD) analyses, 46 functional genetic units (FGUs) (37 single loci and 9 association groups or AGs) distributed in 37 bins (~20%) across the rice genome for CT were detected. Together, each of the CT loci (bins) was detected in 1.7 populations, including 18 loci detected in two or more populations. Putative genetic networks (multi-locus structures) underlying CT were constructed based on strong non-random associations between or among donor alleles at the unlinked CT loci/FGUs identified in the CT ILs, suggesting the presence of strong epistasis among the detected CT loci. Our results demonstrated the power and usefulness of using selective introgression for simultaneous improvement and genetic dissection of complex traits such as CT in rice.
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spelling pubmed-61410682018-09-21 QTL and QTL networks for cold tolerance at the reproductive stage detected using selective introgression in rice Liang, Yuntao Meng, Lijun Lin, Xiuyun Cui, Yanru Pang, Yunlong Xu, Jianlong Li, Zhikang PLoS One Research Article Low temperature stress is one of the major abiotic stresses limiting the productivity of Geng (japonica) rice grown the temperate regions as well as in tropical high lands worldwide. To develop rice varieties with improved cold tolerance (CT) at the reproductive stage, 84 BC(2) CT introgression lines (ILs) were developed from five populations through backcross breeding. These CT ILs plus 310 random ILs from the same BC populations were used for dissecting genetic networks underlying CT in rice by detecting QTLs and functional genetic units (FGUs) contributing to CT. Seventeen major QTLs for CT were identified using five selective introgression populations and the method of segregation distortion. Of them, three QTLs were confirmed using the random populations and seven others locate in the regions with previously reported CT QTLs/genes. Using multi-locus probability tests and linkage disequilibrium (LD) analyses, 46 functional genetic units (FGUs) (37 single loci and 9 association groups or AGs) distributed in 37 bins (~20%) across the rice genome for CT were detected. Together, each of the CT loci (bins) was detected in 1.7 populations, including 18 loci detected in two or more populations. Putative genetic networks (multi-locus structures) underlying CT were constructed based on strong non-random associations between or among donor alleles at the unlinked CT loci/FGUs identified in the CT ILs, suggesting the presence of strong epistasis among the detected CT loci. Our results demonstrated the power and usefulness of using selective introgression for simultaneous improvement and genetic dissection of complex traits such as CT in rice. Public Library of Science 2018-09-17 /pmc/articles/PMC6141068/ /pubmed/30222760 http://dx.doi.org/10.1371/journal.pone.0200846 Text en © 2018 Liang et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Liang, Yuntao
Meng, Lijun
Lin, Xiuyun
Cui, Yanru
Pang, Yunlong
Xu, Jianlong
Li, Zhikang
QTL and QTL networks for cold tolerance at the reproductive stage detected using selective introgression in rice
title QTL and QTL networks for cold tolerance at the reproductive stage detected using selective introgression in rice
title_full QTL and QTL networks for cold tolerance at the reproductive stage detected using selective introgression in rice
title_fullStr QTL and QTL networks for cold tolerance at the reproductive stage detected using selective introgression in rice
title_full_unstemmed QTL and QTL networks for cold tolerance at the reproductive stage detected using selective introgression in rice
title_short QTL and QTL networks for cold tolerance at the reproductive stage detected using selective introgression in rice
title_sort qtl and qtl networks for cold tolerance at the reproductive stage detected using selective introgression in rice
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6141068/
https://www.ncbi.nlm.nih.gov/pubmed/30222760
http://dx.doi.org/10.1371/journal.pone.0200846
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