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Genetic Basis Underlying Correlations Among Growth Duration and Yield Traits Revealed by GWAS in Rice (Oryza sativa L.)
Avoidance of disadvantageous genetic correlations among growth duration and yield traits is critical in developing crop varieties that efficiently use light and energy resources and produce high yields. To understand the genetic basis underlying the correlations among heading date and three major yi...
Autores principales: | , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5972282/ https://www.ncbi.nlm.nih.gov/pubmed/29872443 http://dx.doi.org/10.3389/fpls.2018.00650 |
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author | Li, Fengmei Xie, Jianyin Zhu, Xiaoyang Wang, Xueqiang Zhao, Yan Ma, Xiaoqian Zhang, Zhanying Rashid, Muhammad A. R. Zhang, Zhifang Zhi, Linran Zhang, Shuyang Li, Jinjie Li, Zichao Zhang, Hongliang |
author_facet | Li, Fengmei Xie, Jianyin Zhu, Xiaoyang Wang, Xueqiang Zhao, Yan Ma, Xiaoqian Zhang, Zhanying Rashid, Muhammad A. R. Zhang, Zhifang Zhi, Linran Zhang, Shuyang Li, Jinjie Li, Zichao Zhang, Hongliang |
author_sort | Li, Fengmei |
collection | PubMed |
description | Avoidance of disadvantageous genetic correlations among growth duration and yield traits is critical in developing crop varieties that efficiently use light and energy resources and produce high yields. To understand the genetic basis underlying the correlations among heading date and three major yield traits in rice, we investigated the four traits in a diverse and representative core collection of 266 cultivated rice accessions in both long-day and short-day environments, and conducted the genome-wide association study using 4.6 million single nucleotide polymorphisms (SNPs). There were clear positive correlation between heading date and grain number per panicle, and negative correlation between grain number per panicle and panicle number, as well as different degrees of correlations among other traits in different subspecies and environments. We detected 47 pleiotropic genes in 15 pleiotropic quantitative trait loci (pQTLs), 18 pleiotropic genes containing 37 pleiotropic SNPs in 8 pQTLs, 27 pQTLs with r(2) of linkage disequilibrium higher than 0.2, and 39 pairs of interactive genes from 8 metabolic pathways that may contribute to the above phenotypic correlations, but these genetic bases were different for correlations among different traits. Distributions of haplotypes revealed that selection for pleiotropic genes or interactive genes controlling different traits focused on genotypes with weak effect or on those balancing two traits that maximized production but sometimes their utilization strategies depend on the traits and environment. Detection of pQTLs and interactive genes and associated molecular markers will provide an ability to overcome disadvantageous correlations and to utilize the advantageous correlations among traits through marker-assisted selection in breeding. |
format | Online Article Text |
id | pubmed-5972282 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-59722822018-06-05 Genetic Basis Underlying Correlations Among Growth Duration and Yield Traits Revealed by GWAS in Rice (Oryza sativa L.) Li, Fengmei Xie, Jianyin Zhu, Xiaoyang Wang, Xueqiang Zhao, Yan Ma, Xiaoqian Zhang, Zhanying Rashid, Muhammad A. R. Zhang, Zhifang Zhi, Linran Zhang, Shuyang Li, Jinjie Li, Zichao Zhang, Hongliang Front Plant Sci Plant Science Avoidance of disadvantageous genetic correlations among growth duration and yield traits is critical in developing crop varieties that efficiently use light and energy resources and produce high yields. To understand the genetic basis underlying the correlations among heading date and three major yield traits in rice, we investigated the four traits in a diverse and representative core collection of 266 cultivated rice accessions in both long-day and short-day environments, and conducted the genome-wide association study using 4.6 million single nucleotide polymorphisms (SNPs). There were clear positive correlation between heading date and grain number per panicle, and negative correlation between grain number per panicle and panicle number, as well as different degrees of correlations among other traits in different subspecies and environments. We detected 47 pleiotropic genes in 15 pleiotropic quantitative trait loci (pQTLs), 18 pleiotropic genes containing 37 pleiotropic SNPs in 8 pQTLs, 27 pQTLs with r(2) of linkage disequilibrium higher than 0.2, and 39 pairs of interactive genes from 8 metabolic pathways that may contribute to the above phenotypic correlations, but these genetic bases were different for correlations among different traits. Distributions of haplotypes revealed that selection for pleiotropic genes or interactive genes controlling different traits focused on genotypes with weak effect or on those balancing two traits that maximized production but sometimes their utilization strategies depend on the traits and environment. Detection of pQTLs and interactive genes and associated molecular markers will provide an ability to overcome disadvantageous correlations and to utilize the advantageous correlations among traits through marker-assisted selection in breeding. Frontiers Media S.A. 2018-05-22 /pmc/articles/PMC5972282/ /pubmed/29872443 http://dx.doi.org/10.3389/fpls.2018.00650 Text en Copyright © 2018 Li, Xie, Zhu, Wang, Zhao, Ma, Zhang, Rashid, Zhang, Zhi, Zhang, Li, Li and Zhang. 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 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 Li, Fengmei Xie, Jianyin Zhu, Xiaoyang Wang, Xueqiang Zhao, Yan Ma, Xiaoqian Zhang, Zhanying Rashid, Muhammad A. R. Zhang, Zhifang Zhi, Linran Zhang, Shuyang Li, Jinjie Li, Zichao Zhang, Hongliang Genetic Basis Underlying Correlations Among Growth Duration and Yield Traits Revealed by GWAS in Rice (Oryza sativa L.) |
title | Genetic Basis Underlying Correlations Among Growth Duration and Yield Traits Revealed by GWAS in Rice (Oryza sativa L.) |
title_full | Genetic Basis Underlying Correlations Among Growth Duration and Yield Traits Revealed by GWAS in Rice (Oryza sativa L.) |
title_fullStr | Genetic Basis Underlying Correlations Among Growth Duration and Yield Traits Revealed by GWAS in Rice (Oryza sativa L.) |
title_full_unstemmed | Genetic Basis Underlying Correlations Among Growth Duration and Yield Traits Revealed by GWAS in Rice (Oryza sativa L.) |
title_short | Genetic Basis Underlying Correlations Among Growth Duration and Yield Traits Revealed by GWAS in Rice (Oryza sativa L.) |
title_sort | genetic basis underlying correlations among growth duration and yield traits revealed by gwas in rice (oryza sativa l.) |
topic | Plant Science |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5972282/ https://www.ncbi.nlm.nih.gov/pubmed/29872443 http://dx.doi.org/10.3389/fpls.2018.00650 |
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