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Liu J, Lou X, Zhang L, Hou T, Xin X, Wang Y, Wang S, Huang Y, Zhou C, Jia B, Feng Y. Correlation of rice yield based on RILs population QTL analysis. BMC Genom Data 2025; 26:27. [PMID: 40229679 PMCID: PMC11995468 DOI: 10.1186/s12863-025-01316-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2024] [Accepted: 03/21/2025] [Indexed: 04/16/2025] Open
Abstract
Rice production has been a primary concern in crop quality breeding. In this study, India japonica variety M494 and indica variety Z9B were used as parents. Hybridization and selfing were conducted to obtain recombinant inbred lines (RILs) as the experimental material. The F3 and F7 populations were analyzed to determine six yield-related traits, including panicle length, effective panicle number, number of grains per panicle, seed setting rate, yield per plant, and grain density. QTL mapping of rice yield-related traits and tillering angle was performed using the SSR molecular marker linkage map, resulting in the identification of 19 QTLs controlling panicle length, grain number per panicle, effective panicle number, seed setting rate, grain density.Additionally, multiple regression analysis and path analysis were employed to investigate the relationship between different agronomic traits and rice yield in the F7 population. An optimal regression equation, YYPP = -24.515 + 0.694XPL + 1.273XPN + 0.007XPPG + 18.981XSSR was derived, and it was concluded that SSR was the trait with the greatest impact on YPP, followed by PL.
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Affiliation(s)
- Junrong Liu
- Agricultural College, Shenyang Agricultural University, Shenyang, Liaoning, 110866, China
| | - Xinyi Lou
- Agricultural College, Shenyang Agricultural University, Shenyang, Liaoning, 110866, China
| | - Lin Zhang
- Agricultural College, Shenyang Agricultural University, Shenyang, Liaoning, 110866, China
| | - Tiangang Hou
- College of Engineering, Shenyang Agricultural University, Shenyang, 110866, China
| | - Xin Xin
- Agricultural College, Shenyang Agricultural University, Shenyang, Liaoning, 110866, China
| | - Yan Wang
- Agricultural College, Shenyang Agricultural University, Shenyang, Liaoning, 110866, China
| | - Shu Wang
- Agricultural College, Shenyang Agricultural University, Shenyang, Liaoning, 110866, China
| | - Yuancai Huang
- Agricultural College, Shenyang Agricultural University, Shenyang, Liaoning, 110866, China
| | - Chanchan Zhou
- Agricultural College, Shenyang Agricultural University, Shenyang, Liaoning, 110866, China
| | - Baoyan Jia
- Agricultural College, Shenyang Agricultural University, Shenyang, Liaoning, 110866, China.
| | - Yue Feng
- Chinese National Center for Rice Improvement and State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, Zhejiang, 311401, China.
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Kumar P, Choudhary M, Sheoran S, Longmei N, Kumar B, Jat BS, Dagla MC, Bhushan B, Aggarwal SK, Bagaria PK, Sharma A, Singh SB. Teosinte-Derived Advanced Backcross Population Harbors Genomic Regions for Grain Yield Attributing Traits in Maize. Int J Mol Sci 2024; 25:10300. [PMID: 39408630 PMCID: PMC11476406 DOI: 10.3390/ijms251910300] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2024] [Revised: 09/18/2024] [Accepted: 09/20/2024] [Indexed: 10/20/2024] Open
Abstract
Maize is a highly versatile crop holding significant importance in global food, feed and nutritional security. Grain yield is a complex trait and difficult to improve without targeting the improvement of grain yield attributing traits, which are relatively less complex in nature. Hence, considering the erosion in genetic diversity, there is an urgent need to use wild relatives for genetic diversification and unravel the genomic regions for grain yield attributing traits in maize. Thus, the current study aimed to identify quantitative trait loci (QTLs) linked with grain yield and yield attributing traits. Two BC2F2 populations developed from the cross of LM13 with Zea parviglumis (population 1) and LM14 with Zea parviglumis (population 2) were genotyped and phenotyped in field conditions in the kharif season. BC2F2:3 lines in both populations were phenotyped again for grain yield and attributing traits in the spring season. In total, three QTLs each for ear height (EH), two QTLs for flag leaf length (FLL) and one QTL each for ear diameter (ED), plant height, flag leaf length (FLL), flag leaf width and 100 kernel-weight were identified in population 1. In population 2, two QTLs for kernel row per ear (KRPE) and one QTL for FLL were detected in. QTLs for EH, FLL and KPRE showed consistency across seasons. Among the identified QTLs, six QTLs were found to be co-localized near identified genomic regions in previous studies, validating their potential in contributing to trait expression. The identified QTLs can be utilized for marker assisted selection, transferring favorable alleles from wild relatives in modern maize.
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Affiliation(s)
- Pardeep Kumar
- ICAR-Indian Institute of Maize Research, Ludhiana 141004, India; (P.K.); (N.L.); (B.K.); (B.S.J.); (M.C.D.); (B.B.); (S.K.A.); (P.K.B.); (A.S.); (S.B.S.)
| | - Mukesh Choudhary
- ICAR-Indian Institute of Maize Research, Ludhiana 141004, India; (P.K.); (N.L.); (B.K.); (B.S.J.); (M.C.D.); (B.B.); (S.K.A.); (P.K.B.); (A.S.); (S.B.S.)
| | - Seema Sheoran
- ICAR-Indian Agricultural Research Institute Regional Station, Karnal 132001, India;
| | - Ningthai Longmei
- ICAR-Indian Institute of Maize Research, Ludhiana 141004, India; (P.K.); (N.L.); (B.K.); (B.S.J.); (M.C.D.); (B.B.); (S.K.A.); (P.K.B.); (A.S.); (S.B.S.)
| | - Bhupender Kumar
- ICAR-Indian Institute of Maize Research, Ludhiana 141004, India; (P.K.); (N.L.); (B.K.); (B.S.J.); (M.C.D.); (B.B.); (S.K.A.); (P.K.B.); (A.S.); (S.B.S.)
| | - Bahadur Singh Jat
- ICAR-Indian Institute of Maize Research, Ludhiana 141004, India; (P.K.); (N.L.); (B.K.); (B.S.J.); (M.C.D.); (B.B.); (S.K.A.); (P.K.B.); (A.S.); (S.B.S.)
| | - Manesh Chander Dagla
- ICAR-Indian Institute of Maize Research, Ludhiana 141004, India; (P.K.); (N.L.); (B.K.); (B.S.J.); (M.C.D.); (B.B.); (S.K.A.); (P.K.B.); (A.S.); (S.B.S.)
| | - Bharat Bhushan
- ICAR-Indian Institute of Maize Research, Ludhiana 141004, India; (P.K.); (N.L.); (B.K.); (B.S.J.); (M.C.D.); (B.B.); (S.K.A.); (P.K.B.); (A.S.); (S.B.S.)
| | - Sumit Kumar Aggarwal
- ICAR-Indian Institute of Maize Research, Ludhiana 141004, India; (P.K.); (N.L.); (B.K.); (B.S.J.); (M.C.D.); (B.B.); (S.K.A.); (P.K.B.); (A.S.); (S.B.S.)
| | - Pravin Kumar Bagaria
- ICAR-Indian Institute of Maize Research, Ludhiana 141004, India; (P.K.); (N.L.); (B.K.); (B.S.J.); (M.C.D.); (B.B.); (S.K.A.); (P.K.B.); (A.S.); (S.B.S.)
| | - Ankush Sharma
- ICAR-Indian Institute of Maize Research, Ludhiana 141004, India; (P.K.); (N.L.); (B.K.); (B.S.J.); (M.C.D.); (B.B.); (S.K.A.); (P.K.B.); (A.S.); (S.B.S.)
| | - Shyam Bir Singh
- ICAR-Indian Institute of Maize Research, Ludhiana 141004, India; (P.K.); (N.L.); (B.K.); (B.S.J.); (M.C.D.); (B.B.); (S.K.A.); (P.K.B.); (A.S.); (S.B.S.)
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3
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Aloryi KD, Okpala NE, Amo A, Bello SF, Akaba S, Tian X. A meta-quantitative trait loci analysis identified consensus genomic regions and candidate genes associated with grain yield in rice. FRONTIERS IN PLANT SCIENCE 2022; 13:1035851. [PMID: 36466247 PMCID: PMC9709451 DOI: 10.3389/fpls.2022.1035851] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/03/2022] [Accepted: 10/19/2022] [Indexed: 06/17/2023]
Abstract
Improving grain yield potential in rice is an important step toward addressing global food security challenges. The meta-QTL analysis offers stable and robust QTLs irrespective of the genetic background of mapping populations and phenotype environment and effectively narrows confidence intervals (CI) for candidate gene (CG) mining and marker-assisted selection improvement. To achieve these aims, a comprehensive bibliographic search for grain yield traits (spikelet fertility, number of grains per panicle, panicles number per plant, and 1000-grain weight) QTLs was conducted, and 462 QTLs were retrieved from 47 independent QTL research published between 2002 and 2022. QTL projection was performed using a reference map with a cumulative length of 2,945.67 cM, and MQTL analysis was conducted on 313 QTLs. Consequently, a total of 62 MQTLs were identified with reduced mean CI (up to 3.40 fold) compared to the mean CI of original QTLs. However, 10 of these MQTLs harbored at least six of the initial QTLs from diverse genetic backgrounds and environments and were considered the most stable and robust MQTLs. Also, MQTLs were compared with GWAS studies and resulted in the identification of 16 common significant loci modulating the evaluated traits. Gene annotation, gene ontology (GO) enrichment, and RNA-seq analyses of chromosome regions of the stable MQTLs detected 52 potential CGs including those that have been cloned in previous studies. These genes encode proteins known to be involved in regulating grain yield including cytochrome P450, zinc fingers, MADs-box, AP2/ERF domain, F-box, ubiquitin ligase domain protein, homeobox domain, DEAD-box ATP domain, and U-box domain. This study provides the framework for molecular dissection of grain yield in rice. Moreover, the MQTLs and CGs identified could be useful for fine mapping, gene cloning, and marker-assisted selection to improve rice productivity.
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Affiliation(s)
- Kelvin Dodzi Aloryi
- Hubei Collaborative Innovation Centre for Grain Industry, College of Agriculture, Yangtze University, Jingzhou, China
| | - Nnaemeka Emmanuel Okpala
- Hubei Collaborative Innovation Centre for Grain Industry, College of Agriculture, Yangtze University, Jingzhou, China
| | - Aduragbemi Amo
- Institute of Plant Breeding, Genetics and Genomics University of Georgia, Athens, GA, United States
| | - Semiu Folaniyi Bello
- Department of Animal Genetics, Breeding and Reproduction, College of Animal Science, South China Agricultural University, Guangzhou, Guangdong, China
| | - Selorm Akaba
- School of Agriculture, University of Cape Coast, Cape Coast, Ghana
| | - Xiaohai Tian
- Hubei Collaborative Innovation Centre for Grain Industry, College of Agriculture, Yangtze University, Jingzhou, China
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Xu Z, Li M, Du Y, Li X, Wang R, Chen Z, Tang S, Liu Q, Zhang H. Characterization of qPL5: a novel quantitative trait locus (QTL) that controls panicle length in rice ( Oryza sativa L.). MOLECULAR BREEDING : NEW STRATEGIES IN PLANT IMPROVEMENT 2022; 42:70. [PMID: 37313475 PMCID: PMC10248689 DOI: 10.1007/s11032-022-01339-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/06/2022] [Accepted: 10/20/2022] [Indexed: 06/15/2023]
Abstract
Panicle length (PL) is an important trait that determines panicle architecture and strongly affects grain yield and quality in rice. However, this trait has not been well characterized genetically, and its contribution to yield improvement is not well understood. Characterization of novel genes related to PL is of great significance for breeding high-yielding rice varieties. In our previous research, we identified qPL5, a quantitative trait locus for PL. In this study, we aimed to determine the exact position of qPL5 in the rice genome and identify the candidate gene. Through substitution mapping, we mapped qPL5 to a region of 21.86 kb flanked by the molecular marker loci STS5-99 and STS5-106 in which two candidate genes were predicted. By sequence analysis and relative expression analysis, LOC-Os05g41230, which putatively encodes a BRASSINOSTEROID INSENSITIVE 1-associated receptor kinase 1 precursor, was considered to be the most likely candidate gene for qPL5. In addition, we successfully developed a pair of near-isogenic lines (NILs) for qPL5 in different genetic backgrounds to evaluate the genetic effects of qPL5. Agronomic trait analysis of the NILs indicated that qPL5 positively contributes to plant height, grain number per panicle, panicle length, grain yield per plant, and flag leaf length, but it had no influence on heading date and grain-size-related traits. Therefore, qPL5 and the markers tightly linked to it should be available for molecular breeding of high-yielding varieties. Supplementary Information The online version contains supplementary material available at 10.1007/s11032-022-01339-z.
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Affiliation(s)
- Zuopeng Xu
- Jiangsu Key Laboratory of Crop Genetics and Physiology/Key Laboratory of Plant Functional Genomics of the Ministry of Education/Jiangsu Key Laboratory of Crop Genomics and Molecular Breeding, Agricultural College of Yangzhou University, Yangzhou, 225009 China
- Jiangsu Co-Innovation Center for Modern Production Technology of Grain Crops, Yangzhou University, Yangzhou, 225009 China
| | - Meng Li
- Jiangsu Key Laboratory of Crop Genetics and Physiology/Key Laboratory of Plant Functional Genomics of the Ministry of Education/Jiangsu Key Laboratory of Crop Genomics and Molecular Breeding, Agricultural College of Yangzhou University, Yangzhou, 225009 China
| | - Yuanyue Du
- Jiangsu Key Laboratory of Crop Genetics and Physiology/Key Laboratory of Plant Functional Genomics of the Ministry of Education/Jiangsu Key Laboratory of Crop Genomics and Molecular Breeding, Agricultural College of Yangzhou University, Yangzhou, 225009 China
| | - Xixu Li
- Jiangsu Key Laboratory of Crop Genetics and Physiology/Key Laboratory of Plant Functional Genomics of the Ministry of Education/Jiangsu Key Laboratory of Crop Genomics and Molecular Breeding, Agricultural College of Yangzhou University, Yangzhou, 225009 China
| | - Ruixuan Wang
- Jiangsu Key Laboratory of Crop Genetics and Physiology/Key Laboratory of Plant Functional Genomics of the Ministry of Education/Jiangsu Key Laboratory of Crop Genomics and Molecular Breeding, Agricultural College of Yangzhou University, Yangzhou, 225009 China
| | - Zhiai Chen
- Jiangsu Key Laboratory of Crop Genetics and Physiology/Key Laboratory of Plant Functional Genomics of the Ministry of Education/Jiangsu Key Laboratory of Crop Genomics and Molecular Breeding, Agricultural College of Yangzhou University, Yangzhou, 225009 China
| | - Shuzhu Tang
- Jiangsu Key Laboratory of Crop Genetics and Physiology/Key Laboratory of Plant Functional Genomics of the Ministry of Education/Jiangsu Key Laboratory of Crop Genomics and Molecular Breeding, Agricultural College of Yangzhou University, Yangzhou, 225009 China
- Jiangsu Co-Innovation Center for Modern Production Technology of Grain Crops, Yangzhou University, Yangzhou, 225009 China
| | - Qiaoquan Liu
- Jiangsu Key Laboratory of Crop Genetics and Physiology/Key Laboratory of Plant Functional Genomics of the Ministry of Education/Jiangsu Key Laboratory of Crop Genomics and Molecular Breeding, Agricultural College of Yangzhou University, Yangzhou, 225009 China
- Jiangsu Co-Innovation Center for Modern Production Technology of Grain Crops, Yangzhou University, Yangzhou, 225009 China
| | - Honggen Zhang
- Jiangsu Key Laboratory of Crop Genetics and Physiology/Key Laboratory of Plant Functional Genomics of the Ministry of Education/Jiangsu Key Laboratory of Crop Genomics and Molecular Breeding, Agricultural College of Yangzhou University, Yangzhou, 225009 China
- Jiangsu Co-Innovation Center for Modern Production Technology of Grain Crops, Yangzhou University, Yangzhou, 225009 China
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5
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Zhang B, Ma L, Wu B, Xing Y, Qiu X. Introgression Lines: Valuable Resources for Functional Genomics Research and Breeding in Rice ( Oryza sativa L.). FRONTIERS IN PLANT SCIENCE 2022; 13:863789. [PMID: 35557720 PMCID: PMC9087921 DOI: 10.3389/fpls.2022.863789] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/27/2022] [Accepted: 04/01/2022] [Indexed: 05/14/2023]
Abstract
The narrow base of genetic diversity of modern rice varieties is mainly attributed to the overuse of the common backbone parents that leads to the lack of varied favorable alleles in the process of breeding new varieties. Introgression lines (ILs) developed by a backcross strategy combined with marker-assisted selection (MAS) are powerful prebreeding tools for broadening the genetic base of existing cultivars. They have high power for mapping quantitative trait loci (QTLs) either with major or minor effects, and are used for precisely evaluating the genetic effects of QTLs and detecting the gene-by-gene or gene-by-environment interactions due to their low genetic background noise. ILs developed from multiple donors in a fixed background can be used as an IL platform to identify the best alleles or allele combinations for breeding by design. In the present paper, we reviewed the recent achievements from ILs in rice functional genomics research and breeding, including the genetic dissection of complex traits, identification of elite alleles and background-independent and epistatic QTLs, analysis of genetic interaction, and genetic improvement of single and multiple target traits. We also discussed how to develop ILs for further identification of new elite alleles, and how to utilize IL platforms for rice genetic improvement.
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Affiliation(s)
- Bo Zhang
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research, Huazhong Agricultural University, Wuhan, China
| | - Ling Ma
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research, Huazhong Agricultural University, Wuhan, China
| | - Bi Wu
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research, Huazhong Agricultural University, Wuhan, China
| | - Yongzhong Xing
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research, Huazhong Agricultural University, Wuhan, China
| | - Xianjin Qiu
- College of Agriculture, Yangtze University, Jingzhou, China
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Sagare DB, Abbai R, Jain A, Jayadevappa PK, Dixit S, Singh AK, Challa V, Alam S, Singh UM, Yadav S, Sandhu N, Kabade PG, Singh VK, Kumar A. More and more of less and less: Is genomics-based breeding of dry direct-seeded rice (DDSR) varieties the need of hour? PLANT BIOTECHNOLOGY JOURNAL 2020; 18:2173-2186. [PMID: 32725933 PMCID: PMC7589319 DOI: 10.1111/pbi.13454] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/20/2019] [Revised: 06/07/2020] [Accepted: 07/13/2020] [Indexed: 06/02/2023]
Abstract
Rice is a staple food for half of the world's population. Changing climatic conditions, water and labour scarcity are the major challenges that shall limit future rice production. Dry direct-seeded rice (DDSR) is emerging as an efficient, resources conserving, mechanized, climate smart and economically viable strategy to be adopted as an alternative to puddled transplanted rice (TPR) with the potential to address the problem of labour-water shortages and ensure sustainable rice cultivation. Despite these benefits, several constraints obstruct the adoption of DDSR. In principle, the plant type for DDSR should be different from one for TPR, which could be achieved by developing rice varieties that combine the traits of upland and lowland varieties. In this context, recent advances in precise phenotyping and NGS-based trait mapping led to identification of promising donors and QTLs/genes for DDSR favourable traits to be employed in genomic breeding. This review discusses the important traits influencing DDSR, research studies to clarify the need for breeding DDSR-specific varieties to achieve enhanced grain yield, climate resilience and nutrition demand. We anticipate that in the coming years, genomic breeding for developing DDSR-specific varieties would be a regular practice and might be further strengthened by combining superior haplotypes regulating important DDSR traits by haplotype-based breeding.
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Affiliation(s)
- Deepti B. Sagare
- International Rice Research Institute (IRRI)South‐Asia Hub (SAH)HyderabadIndia
| | - Ragavendran Abbai
- International Rice Research Institute (IRRI)South‐Asia Hub (SAH)HyderabadIndia
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK)GaterslebenGermany
| | - Abhinav Jain
- International Rice Research Institute (IRRI)South‐Asia Hub (SAH)HyderabadIndia
| | | | - Shilpi Dixit
- International Rice Research Institute (IRRI)South‐Asia Hub (SAH)HyderabadIndia
| | - Arun Kumar Singh
- International Rice Research Institute (IRRI)South‐Asia Hub (SAH)HyderabadIndia
| | | | - Shamshad Alam
- International Rice Research Institute (IRRI)South‐Asia Hub (SAH)HyderabadIndia
| | - Uma Maheshwar Singh
- International Rice Research Institute (IRRI)South‐Asia Hub (SAH)HyderabadIndia
| | - Shailesh Yadav
- International Rice Research Institute (IRRI)Metro ManilaPhilippines
| | | | - Pramod G. Kabade
- International Rice Research Institute (IRRI)South‐Asia Hub (SAH)HyderabadIndia
| | - Vikas Kumar Singh
- International Rice Research Institute (IRRI)South‐Asia Hub (SAH)HyderabadIndia
- International Rice Research Institute (IRRI)Metro ManilaPhilippines
| | - Arvind Kumar
- International Rice Research Institute (IRRI)Metro ManilaPhilippines
- International Rice Research Institute (IRRI)South‐Asia Regional Centre (SARC)VaranasiIndia
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Cobb JN, Biswas PS, Platten JD. Back to the future: revisiting MAS as a tool for modern plant breeding. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2019; 132:647-667. [PMID: 30560465 PMCID: PMC6439155 DOI: 10.1007/s00122-018-3266-4] [Citation(s) in RCA: 74] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/25/2018] [Accepted: 12/07/2018] [Indexed: 05/04/2023]
Abstract
KEY MESSAGE New models for integration of major gene MAS with modern breeding approaches stand to greatly enhance the reliability and efficiency of breeding, facilitating the leveraging of traditional genetic diversity. Genetic diversity is well recognised as contributing essential variation to crop breeding processes, and marker-assisted selection is cited as the primary tool to bring this diversity into breeding programs without the associated genetic drag from otherwise poor-quality genomes of donor varieties. However, implementation of marker-assisted selection techniques remains a challenge in many breeding programs worldwide. Many factors contribute to this lack of adoption, such as uncertainty in how to integrate MAS with traditional breeding processes, lack of confidence in MAS as a tool, and the expense of the process. However, developments in genomics tools, locus validation techniques, and new models for how to utilise QTLs in breeding programs stand to address these issues. Marker-assisted forward breeding needs to be enabled through the identification of robust QTLs, the design of reliable marker systems to select for these QTLs, and the delivery of these QTLs into elite genomic backgrounds to enable their use without associated genetic drag. To enhance the adoption and effectiveness of MAS, rice is used as an example of how to integrate new developments and processes into a coherent, efficient strategy for utilising genetic variation. When processes are instituted to address these issues, new genes can be rolled out into a breeding program rapidly and completely with a minimum of expense.
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Affiliation(s)
- Joshua N Cobb
- International Rice Research Institute, National Road, Los Banos, Laguna, Philippines
| | - Partha S Biswas
- International Rice Research Institute, National Road, Los Banos, Laguna, Philippines
- Bangladesh Rice Research Institute, Gazipur, 1701, Bangladesh
| | - J Damien Platten
- International Rice Research Institute, National Road, Los Banos, Laguna, Philippines.
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Descalsota-Empleo GI, Noraziyah AAS, Navea IP, Chung C, Dwiyanti MS, Labios RJD, Ikmal AM, Juanillas VM, Inabangan-Asilo MA, Amparado A, Reinke R, Cruz CMV, Chin JH, Swamy BPM. Genetic Dissection of Grain Nutritional Traits and Leaf Blight Resistance in Rice. Genes (Basel) 2019; 10:E30. [PMID: 30626141 PMCID: PMC6356647 DOI: 10.3390/genes10010030] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2018] [Revised: 12/27/2018] [Accepted: 12/28/2018] [Indexed: 11/16/2022] Open
Abstract
Colored rice is rich in nutrition and also a good source of valuable genes/quantitative trait loci (QTL) for nutrition, grain quality, and pest and disease resistance traits for use in rice breeding. Genome-wide association analysis using high-density single nucleotide polymorphism (SNP) is useful in precisely detecting QTLs and genes. We carried out genome-wide association analysis in 152 colored rice accessions, using 22,112 SNPs to map QTLs for nutritional, agronomic, and bacterial leaf blight (BLB) resistance traits. Wide variations and normal frequency distributions were observed for most of the traits except anthocyanin content and BLB resistance. The structural and principal component analysis revealed two subgroups. The linkage disequilibrium (LD) analysis showed 74.3% of the marker pairs in complete LD, with an average LD distance of 1000 kb and, interestingly, 36% of the LD pairs were less than 5 Kb, indicating high recombination in the panel. In total, 57 QTLs were identified for ten traits at p < 0.0001, and the phenotypic variance explained (PVE) by these QTLs varied from 9% to 18%. Interestingly, 30 (53%) QTLs were co-located with known or functionally-related genes. Some of the important candidate genes for grain Zinc (Zn) and BLB resistance were OsHMA9, OsMAPK6, OsNRAMP7, OsMADS13, and OsZFP252, and Xa1, Xa3, xa5, xa13 and xa26, respectively. Red rice genotype, Sayllebon, which is high in both Zn and anthocyanin content, could be a valuable material for a breeding program for nutritious rice. Overall, the QTLs identified in our study can be used for QTL pyramiding as well as genomic selection. Some of the novel QTLs can be further validated by fine mapping and functional characterization. The results show that pigmented rice is a valuable resource for mineral elements and antioxidant compounds; it can also provide novel alleles for disease resistance as well as for yield component traits. Therefore, large opportunities exist to further explore and exploit more colored rice accessions for use in breeding.
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Affiliation(s)
- Gwen Iris Descalsota-Empleo
- International Rice Research Institute (IRRI), Laguna 4031, Philippines.
- University of the Southern Mindanao, Kabacan, Cotabato 9407, Philippines.
| | | | - Ian Paul Navea
- International Rice Research Institute (IRRI), Laguna 4031, Philippines.
- Nousbo Corp. #4-107, 89 Seohoro, Gwonsun, Suwon 16614, Gyeonggi, Korea.
| | - Chongtae Chung
- Chungcheongnam-do Agricultural Research and Extension Services, 167, Chusa-ro, Shinam-myeon, Yesan-gun 32418, Chungcheongnam-do, Korea.
| | - Maria Stefanie Dwiyanti
- International Rice Research Institute (IRRI), Laguna 4031, Philippines.
- Applied Plant Genome Laboratory, Hokkaido University, Kita 9, Nishi 9, Kita-ku, Sapporo 060-8589, Japan.
| | | | - Asmuni Mohd Ikmal
- Faculty of Science and Technology, Universiti Kebangsaan Malaysia, 43600 Bangi, Selangor, Malaysia.
| | | | | | - Amery Amparado
- International Rice Research Institute (IRRI), Laguna 4031, Philippines.
| | - Russell Reinke
- International Rice Research Institute (IRRI), Laguna 4031, Philippines.
| | | | - Joong Hyoun Chin
- Department of Integrative Bio-Industrial Engineering, Sejong University, 209, Neungdong-ro, Gwangjin-gu, Seoul 05006, Korea.
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Zhu Z, Li X, Wei Y, Guo S, Sha A. Identification of a Novel QTL for Panicle Length From Wild Rice ( Oryza minuta) by Specific Locus Amplified Fragment Sequencing and High Density Genetic Mapping. FRONTIERS IN PLANT SCIENCE 2018; 9:1492. [PMID: 30459776 PMCID: PMC6232755 DOI: 10.3389/fpls.2018.01492] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/01/2018] [Accepted: 09/25/2018] [Indexed: 05/17/2023]
Abstract
Wild rice possesses a large number of valuable genes that have been lost or do not exist in cultivated rice. To exploit the desirable gene controlling panicle length (PL) in wild rice Oryza minuta, a recombinant inbred line (RIL) population was constructed that was derived from a cross between the long panicle introgression line K1561 with Oryza minuta segments and a short panicle accession G1025. Specific Locus Amplified Fragment (SLAF) sequencing technology was used to uncover single nucleotide polymorphisms (SNPs) and construct the high-density genetic linkage map. Using 201 RIL populations, a high-density genetic map was developed, and spanned 2781.76 cM with an average genetic distance 0.45 cM. The genetic map was composed of 5, 521 markers on 12 chromosomes. Based on this high-density genome map, quantitative trait loci (QTL) for PL were analyzed for 2 years under four environments. Seven QTLs were detected, which were distributed within chromosomes 4, 9, and 10, respectively. pl4.1 was detected twice, and pl10.1 was only detected once. Although pl9.1 was only detected once, it was very near pl9.2 in the genetic map which was detected three times. Thus, we speculate one major QTL exists in the region of pl9.1 and pl9.2 to control PL (temporarily referred to as pl9). pl9 is a potentially novel allele derived from Oryza minuta, and it can be used for genetic improvement of cultivar rice.
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Affiliation(s)
- Zhengzheng Zhu
- Hubei Collaborative Innovation Center for Grain Industry, Yangtze University, Jingzhou, China
| | - Xiaoqiong Li
- Guangxi Key Laboratory of Rice Genetics and Breeding, Rice Research Institute, Guangxi Academy of Agricultural Science, Nanning, China
| | - Yu Wei
- Guangxi Key Laboratory of Rice Genetics and Breeding, Rice Research Institute, Guangxi Academy of Agricultural Science, Nanning, China
| | - Sibin Guo
- Guangxi Key Laboratory of Rice Genetics and Breeding, Rice Research Institute, Guangxi Academy of Agricultural Science, Nanning, China
- *Correspondence: Sibin Guo, Aihua Sha,
| | - Aihua Sha
- Hubei Collaborative Innovation Center for Grain Industry, Yangtze University, Jingzhou, China
- *Correspondence: Sibin Guo, Aihua Sha,
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