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Uncovering the genetic mechanisms regulating panicle architecture in rice with GPWAS and GWAS
BACKGROUND: The number of panicles per plant, number of grains per panicle, and 1000-grain weight are important factors contributing to the grain yield per plant in rice. The Rice Diversity Panel 1 (RDP1) contains a total of 421 purified, homozygous rice accessions representing diverse genetic varia...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BioMed Central
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7842007/ https://www.ncbi.nlm.nih.gov/pubmed/33509071 http://dx.doi.org/10.1186/s12864-021-07391-x |
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author | Zhong, Hua Liu, Shuai Meng, Xiaoxi Sun, Tong Deng, Yujuan Kong, Weilong Peng, Zhaohua Li, Yangsheng |
author_facet | Zhong, Hua Liu, Shuai Meng, Xiaoxi Sun, Tong Deng, Yujuan Kong, Weilong Peng, Zhaohua Li, Yangsheng |
author_sort | Zhong, Hua |
collection | PubMed |
description | BACKGROUND: The number of panicles per plant, number of grains per panicle, and 1000-grain weight are important factors contributing to the grain yield per plant in rice. The Rice Diversity Panel 1 (RDP1) contains a total of 421 purified, homozygous rice accessions representing diverse genetic variations within O. sativa. The release of High-Density Rice Array (HDRA, 700 k SNPs) dataset provides a new opportunity to discover the genetic variants of panicle architectures in rice. RESULTS: In this report, a new method genome-phenome wide association study (GPWAS) was performed with 391 individuals and 27 traits derived from RDP1 to scan the relationship between the genes and multi-traits. A total of 1985 gene models were linked to phenomic variation with a p-value cutoff of 4.49E-18. Besides, 406 accessions derived from RDP1 with 411,066 SNPs were used to identify QTLs associated with the total spikelets number per panicle (TSNP), grain number per panicle (GNP), empty grain number per panicle (EGNP), primary branch number (PBN), panicle length (PL), and panicle number per plant (PN) by GLM, MLM, FarmCPU, and BLINK models for genome-wide association study (GWAS) analyses. A total of 18, 21, 18, 17, 15, and 17 QTLs were identified tightly linked with TSNP, GNP, EGNP, PBN, PL, and PN, respectively. Then, a total of 23 candidate genes were mapped simultaneously using both GWAS and GPWAS methods, composed of 6, 4, 5, 4, and 4 for TSNP, GNP, EGNP, PBN, and PL. Notably, one overlapped gene (Os01g0140100) were further investigated based on the haplotype and gene expression profile, indicating this gene might regulate the TSNP or panicle architecture in rice. CONCLUSIONS: Nearly 30 % (30/106) QTLs co-located with the previous published genes or QTLs, indicating the power of GWAS. Besides, GPWAS is a new method to discover the relationship between genes and traits, especially the pleiotropy genes. Through comparing the results from GWAS and GPWAS, we identified 23 candidate genes related to panicle architectures in rice. This comprehensive study provides new insights into the genetic basis controlling panicle architectures in rice, which lays a foundation in rice improvement. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12864-021-07391-x. |
format | Online Article Text |
id | pubmed-7842007 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-78420072021-01-28 Uncovering the genetic mechanisms regulating panicle architecture in rice with GPWAS and GWAS Zhong, Hua Liu, Shuai Meng, Xiaoxi Sun, Tong Deng, Yujuan Kong, Weilong Peng, Zhaohua Li, Yangsheng BMC Genomics Research Article BACKGROUND: The number of panicles per plant, number of grains per panicle, and 1000-grain weight are important factors contributing to the grain yield per plant in rice. The Rice Diversity Panel 1 (RDP1) contains a total of 421 purified, homozygous rice accessions representing diverse genetic variations within O. sativa. The release of High-Density Rice Array (HDRA, 700 k SNPs) dataset provides a new opportunity to discover the genetic variants of panicle architectures in rice. RESULTS: In this report, a new method genome-phenome wide association study (GPWAS) was performed with 391 individuals and 27 traits derived from RDP1 to scan the relationship between the genes and multi-traits. A total of 1985 gene models were linked to phenomic variation with a p-value cutoff of 4.49E-18. Besides, 406 accessions derived from RDP1 with 411,066 SNPs were used to identify QTLs associated with the total spikelets number per panicle (TSNP), grain number per panicle (GNP), empty grain number per panicle (EGNP), primary branch number (PBN), panicle length (PL), and panicle number per plant (PN) by GLM, MLM, FarmCPU, and BLINK models for genome-wide association study (GWAS) analyses. A total of 18, 21, 18, 17, 15, and 17 QTLs were identified tightly linked with TSNP, GNP, EGNP, PBN, PL, and PN, respectively. Then, a total of 23 candidate genes were mapped simultaneously using both GWAS and GPWAS methods, composed of 6, 4, 5, 4, and 4 for TSNP, GNP, EGNP, PBN, and PL. Notably, one overlapped gene (Os01g0140100) were further investigated based on the haplotype and gene expression profile, indicating this gene might regulate the TSNP or panicle architecture in rice. CONCLUSIONS: Nearly 30 % (30/106) QTLs co-located with the previous published genes or QTLs, indicating the power of GWAS. Besides, GPWAS is a new method to discover the relationship between genes and traits, especially the pleiotropy genes. Through comparing the results from GWAS and GPWAS, we identified 23 candidate genes related to panicle architectures in rice. This comprehensive study provides new insights into the genetic basis controlling panicle architectures in rice, which lays a foundation in rice improvement. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12864-021-07391-x. BioMed Central 2021-01-28 /pmc/articles/PMC7842007/ /pubmed/33509071 http://dx.doi.org/10.1186/s12864-021-07391-x Text en © The Author(s) 2021 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Article Zhong, Hua Liu, Shuai Meng, Xiaoxi Sun, Tong Deng, Yujuan Kong, Weilong Peng, Zhaohua Li, Yangsheng Uncovering the genetic mechanisms regulating panicle architecture in rice with GPWAS and GWAS |
title | Uncovering the genetic mechanisms regulating panicle architecture in rice with GPWAS and GWAS |
title_full | Uncovering the genetic mechanisms regulating panicle architecture in rice with GPWAS and GWAS |
title_fullStr | Uncovering the genetic mechanisms regulating panicle architecture in rice with GPWAS and GWAS |
title_full_unstemmed | Uncovering the genetic mechanisms regulating panicle architecture in rice with GPWAS and GWAS |
title_short | Uncovering the genetic mechanisms regulating panicle architecture in rice with GPWAS and GWAS |
title_sort | uncovering the genetic mechanisms regulating panicle architecture in rice with gpwas and gwas |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7842007/ https://www.ncbi.nlm.nih.gov/pubmed/33509071 http://dx.doi.org/10.1186/s12864-021-07391-x |
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