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Genetic background- and environment-independent QTL and candidate gene identification of appearance quality in three MAGIC populations of rice
Many QTL have been identified for grain appearance quality by linkage analysis (LA) in bi-parental mapping populations and by genome-wide association study (GWAS) in natural populations in rice. However, few of the well characterized genes/QTL have been successfully applied in molecular rice breedin...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2022
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9697191/ https://www.ncbi.nlm.nih.gov/pubmed/36438096 http://dx.doi.org/10.3389/fpls.2022.1074106 |
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author | Chen, Huizhen Zhai, Laiyuan Chen, Kai Shen, Congcong Zhu, Shuangbing Qu, Pingping Tang, Jie Liu, Jianping He, Haohua Xu, Jianlong |
author_facet | Chen, Huizhen Zhai, Laiyuan Chen, Kai Shen, Congcong Zhu, Shuangbing Qu, Pingping Tang, Jie Liu, Jianping He, Haohua Xu, Jianlong |
author_sort | Chen, Huizhen |
collection | PubMed |
description | Many QTL have been identified for grain appearance quality by linkage analysis (LA) in bi-parental mapping populations and by genome-wide association study (GWAS) in natural populations in rice. However, few of the well characterized genes/QTL have been successfully applied in molecular rice breeding due to genetic background (GB) and environment effects on QTL expression and deficiency of favorable alleles. In this study, GWAS and LA were performed to identify QTL for five grain appearance quality-related traits using three multi-parent advanced generation inter-cross (MAGIC) populations. A total of 22 QTL on chromosomes 1-3, 5-8 were identified by GWAS for five traits in DC1, DC2 and 8way, and four combined populations DC12 (DC1+DC2), DC18 (DC1+8way), DC28 (DC2+8way) and DC128 (DC1+DC2+8way). And a total of 42 QTL were identified on all 12 chromosomes except 10 by LA in the three single populations. Among 20 QTL identified by GWAS in DC1, DC2 and 8way, 10, four and three QTL were commonly detected in DC18, DC28, and DC128, respectively. Similarly, among 42 QTL detected by LA in the three populations, four, one and two QTL were commonly detected in DC18, DC28, and DC128, respectively. There was no QTL mapped together in DC12 by both two mapping methods, indicating that GB could greatly affect the mapping results, and it was easier to map the common QTL among populations with similar GB. The 8way population was more powerful for QTL mapping than the DC1, DC2 and various combined populations. Compared with GWAS, LA can not only identify large-effect QTL, but also identify minor-effect ones. Among 11 QTL simultaneously detected by the two methods in different GBs and environments, eight QTL corresponded to known genes, including AqGL3b and AqGLWR3a for GL and GLWR, AqGW5a, AqGLWR5, AqDEC5 and AqPGWC5 for GW, GLWR, DEC and PGWC, and AqDEC6b and AqPGWC6b for DEC and PGWC, respectively. AqGL7, AqGL3c/AqGLWR3b, AqDEC6a/AqPGWC6a, and AqPGWC7 were newly identified and their candidate genes were analyzed and inferred. It was discussed to further improve grain appearance quality through designed QTL pyramiding strategy based on the stable QTL identified in the MAGIC populations. |
format | Online Article Text |
id | pubmed-9697191 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-96971912022-11-26 Genetic background- and environment-independent QTL and candidate gene identification of appearance quality in three MAGIC populations of rice Chen, Huizhen Zhai, Laiyuan Chen, Kai Shen, Congcong Zhu, Shuangbing Qu, Pingping Tang, Jie Liu, Jianping He, Haohua Xu, Jianlong Front Plant Sci Plant Science Many QTL have been identified for grain appearance quality by linkage analysis (LA) in bi-parental mapping populations and by genome-wide association study (GWAS) in natural populations in rice. However, few of the well characterized genes/QTL have been successfully applied in molecular rice breeding due to genetic background (GB) and environment effects on QTL expression and deficiency of favorable alleles. In this study, GWAS and LA were performed to identify QTL for five grain appearance quality-related traits using three multi-parent advanced generation inter-cross (MAGIC) populations. A total of 22 QTL on chromosomes 1-3, 5-8 were identified by GWAS for five traits in DC1, DC2 and 8way, and four combined populations DC12 (DC1+DC2), DC18 (DC1+8way), DC28 (DC2+8way) and DC128 (DC1+DC2+8way). And a total of 42 QTL were identified on all 12 chromosomes except 10 by LA in the three single populations. Among 20 QTL identified by GWAS in DC1, DC2 and 8way, 10, four and three QTL were commonly detected in DC18, DC28, and DC128, respectively. Similarly, among 42 QTL detected by LA in the three populations, four, one and two QTL were commonly detected in DC18, DC28, and DC128, respectively. There was no QTL mapped together in DC12 by both two mapping methods, indicating that GB could greatly affect the mapping results, and it was easier to map the common QTL among populations with similar GB. The 8way population was more powerful for QTL mapping than the DC1, DC2 and various combined populations. Compared with GWAS, LA can not only identify large-effect QTL, but also identify minor-effect ones. Among 11 QTL simultaneously detected by the two methods in different GBs and environments, eight QTL corresponded to known genes, including AqGL3b and AqGLWR3a for GL and GLWR, AqGW5a, AqGLWR5, AqDEC5 and AqPGWC5 for GW, GLWR, DEC and PGWC, and AqDEC6b and AqPGWC6b for DEC and PGWC, respectively. AqGL7, AqGL3c/AqGLWR3b, AqDEC6a/AqPGWC6a, and AqPGWC7 were newly identified and their candidate genes were analyzed and inferred. It was discussed to further improve grain appearance quality through designed QTL pyramiding strategy based on the stable QTL identified in the MAGIC populations. Frontiers Media S.A. 2022-11-11 /pmc/articles/PMC9697191/ /pubmed/36438096 http://dx.doi.org/10.3389/fpls.2022.1074106 Text en Copyright © 2022 Chen, Zhai, Chen, Shen, Zhu, Qu, Tang, Liu, He and Xu https://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 Chen, Huizhen Zhai, Laiyuan Chen, Kai Shen, Congcong Zhu, Shuangbing Qu, Pingping Tang, Jie Liu, Jianping He, Haohua Xu, Jianlong Genetic background- and environment-independent QTL and candidate gene identification of appearance quality in three MAGIC populations of rice |
title | Genetic background- and environment-independent QTL and candidate gene identification of appearance quality in three MAGIC populations of rice |
title_full | Genetic background- and environment-independent QTL and candidate gene identification of appearance quality in three MAGIC populations of rice |
title_fullStr | Genetic background- and environment-independent QTL and candidate gene identification of appearance quality in three MAGIC populations of rice |
title_full_unstemmed | Genetic background- and environment-independent QTL and candidate gene identification of appearance quality in three MAGIC populations of rice |
title_short | Genetic background- and environment-independent QTL and candidate gene identification of appearance quality in three MAGIC populations of rice |
title_sort | genetic background- and environment-independent qtl and candidate gene identification of appearance quality in three magic populations of rice |
topic | Plant Science |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9697191/ https://www.ncbi.nlm.nih.gov/pubmed/36438096 http://dx.doi.org/10.3389/fpls.2022.1074106 |
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