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Sachdeva S, Singh R, Maurya A, Singh VK, Singh UM, Kumar A, Singh GP. New insights into QTNs and potential candidate genes governing rice yield via a multi-model genome-wide association study. BMC Plant Biol 2024; 24:124. [PMID: 38373874 PMCID: PMC10877931 DOI: 10.1186/s12870-024-04810-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/15/2023] [Accepted: 02/08/2024] [Indexed: 02/21/2024]
Abstract
BACKGROUND Rice (Oryza sativa L.) is one of the globally important staple food crops, and yield-related traits are prerequisites for improved breeding efficiency in rice. Here, we used six different genome-wide association study (GWAS) models for 198 accessions, with 553,229 single nucleotide markers (SNPs) to identify the quantitative trait nucleotides (QTNs) and candidate genes (CGs) governing rice yield. RESULTS Amongst the 73 different QTNs in total, 24 were co-localized with already reported QTLs or loci in previous mapping studies. We obtained fifteen significant QTNs, pathway analysis revealed 10 potential candidates within 100kb of these QTNs that are predicted to govern plant height, days to flowering, and plot yield in rice. Based on their superior allelic information in 20 elite and 6 inferior genotypes, we found a higher percentage of superior alleles in the elite genotypes in comparison to inferior genotypes. Further, we implemented expression analysis and enrichment analysis enabling the identification of 73 candidate genes and 25 homologues of Arabidopsis, 19 of which might regulate rice yield traits. Of these candidate genes, 40 CGs were found to be enriched in 60 GO terms of the studied traits for instance, positive regulator metabolic process (GO:0010929), intracellular part (GO:0031090), and nucleic acid binding (GO:0090079). Haplotype and phenotypic variation analysis confirmed that LOC_OS09G15770, LOC_OS02G36710 and LOC_OS02G17520 are key candidates associated with rice yield. CONCLUSIONS Overall, we foresee that the QTNs, putative candidates elucidated in the study could summarize the polygenic regulatory networks controlling rice yield and be useful for breeding high-yielding varieties.
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Grants
- BT/PR32853/AGIII/103/1159/2019 Department of Biotechnology, Ministry of Science and Technology, India
- BT/PR32853/AGIII/103/1159/2019 Department of Biotechnology, Ministry of Science and Technology, India
- BT/PR32853/AGIII/103/1159/2019 Department of Biotechnology, Ministry of Science and Technology, India
- BT/PR32853/AGIII/103/1159/2019 Department of Biotechnology, Ministry of Science and Technology, India
- BT/PR32853/AGIII/103/1159/2019 Department of Biotechnology, Ministry of Science and Technology, India
- BT/PR32853/AGIII/103/1159/2019 Department of Biotechnology, Ministry of Science and Technology, India
- BT/PR32853/AGIII/103/1159/2019 Department of Biotechnology, Ministry of Science and Technology, India
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Affiliation(s)
- Supriya Sachdeva
- Division of Genomic Resources, ICAR-NBPGR, Pusa, New Delhi, India
| | - Rakesh Singh
- Division of Genomic Resources, ICAR-NBPGR, Pusa, New Delhi, India.
| | - Avantika Maurya
- Division of Genomic Resources, ICAR-NBPGR, Pusa, New Delhi, India
| | - Vikas K Singh
- International Rice Research Institute (IRRI), South Asia Hub, ICRISAT, Hyderabad, India
| | - Uma Maheshwar Singh
- International Rice Research Institute (IRRI), South Asia Regional Centre (ISARC), Varanasi, India
| | - Arvind Kumar
- International Crops Research Institute for the Semi-Arid Tropics, Patancheru, Telangana, India
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Yang X, Pan Y, Xia X, Qing D, Chen W, Nong B, Zhang Z, Zhou W, Li J, Li D, Dai G, Deng G. Molecular basis of genetic improvement for key rice quality traits in Southern China. Genomics 2023; 115:110745. [PMID: 37977332 DOI: 10.1016/j.ygeno.2023.110745] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2023] [Revised: 11/06/2023] [Accepted: 11/12/2023] [Indexed: 11/19/2023]
Abstract
Grain qualities including milling quality, appearance quality, eating and cooking quality, and nutritional quality are important indicators in rice breeding. Significant achievements in genetic improvement of rice quality have been made. In this study, we analyzed the variation patterns of 16 traits in 1570 rice varieties and found significant improvements in appearance quality and eating and cooking quality, particularly in hybrid rice. Through genome-wide association study and allelic functional nucleotide polymorphisms analysis of quality trait genes, we found that ALK, FGR1, FLO7, GL7/GW7, GLW7, GS2, GS3, ONAC129, OsGRF8, POW1, WCR1, and Wx were associated with the genetic improvement of rice quality traits in Southern China. Allelic functional nucleotide polymorphisms analysis of 13 important rice quality genes, including fragrance gene fgr, were performed using the polymerase chain reaction amplification refractory mutation system technology. The results showed that Gui516, Gui569, Gui721, Ryousi, Rsimiao, Rbasi, and Yuehui9802 possessed multiple superior alleles. This study elucidates the phenotypic changes and molecular basis of key quality traits of varieties in Southern China. The findings will provide guidance for genetic improvement of rice quality and the development of new varieties.
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Affiliation(s)
- Xinghai Yang
- Guangxi Key Laboratory of Rice Genetics and Breeding, Rice Research Institute, Guangxi Academy of Agricultural Sciences, Nanning, Guangxi 530007, China
| | - Yinghua Pan
- Guangxi Key Laboratory of Rice Genetics and Breeding, Rice Research Institute, Guangxi Academy of Agricultural Sciences, Nanning, Guangxi 530007, China
| | - Xiuzhong Xia
- Guangxi Key Laboratory of Rice Genetics and Breeding, Rice Research Institute, Guangxi Academy of Agricultural Sciences, Nanning, Guangxi 530007, China
| | - Dongjin Qing
- Guangxi Key Laboratory of Rice Genetics and Breeding, Rice Research Institute, Guangxi Academy of Agricultural Sciences, Nanning, Guangxi 530007, China
| | - Weiwei Chen
- Guangxi Key Laboratory of Rice Genetics and Breeding, Rice Research Institute, Guangxi Academy of Agricultural Sciences, Nanning, Guangxi 530007, China
| | - Baoxuan Nong
- Guangxi Key Laboratory of Rice Genetics and Breeding, Rice Research Institute, Guangxi Academy of Agricultural Sciences, Nanning, Guangxi 530007, China
| | - Zongqiong Zhang
- Guangxi Key Laboratory of Rice Genetics and Breeding, Rice Research Institute, Guangxi Academy of Agricultural Sciences, Nanning, Guangxi 530007, China
| | - Weiyong Zhou
- Guangxi Key Laboratory of Rice Genetics and Breeding, Rice Research Institute, Guangxi Academy of Agricultural Sciences, Nanning, Guangxi 530007, China
| | - Jingcheng Li
- Guangxi Key Laboratory of Rice Genetics and Breeding, Rice Research Institute, Guangxi Academy of Agricultural Sciences, Nanning, Guangxi 530007, China
| | - Danting Li
- Guangxi Key Laboratory of Rice Genetics and Breeding, Rice Research Institute, Guangxi Academy of Agricultural Sciences, Nanning, Guangxi 530007, China.
| | - Gaoxing Dai
- Guangxi Key Laboratory of Rice Genetics and Breeding, Rice Research Institute, Guangxi Academy of Agricultural Sciences, Nanning, Guangxi 530007, China.
| | - Guofu Deng
- Guangxi Key Laboratory of Rice Genetics and Breeding, Rice Research Institute, Guangxi Academy of Agricultural Sciences, Nanning, Guangxi 530007, China.
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