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Fan G, Jiang J, Long Y, Wang R, Liang F, Liu H, Xu J, Qiu X, Li Z. Generation of Two-Line Restorer Line with Low Chalkiness Using Knockout of Chalk5 through CRISPR/Cas9 Editing. BIOLOGY 2024; 13:617. [PMID: 39194555 DOI: 10.3390/biology13080617] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/13/2024] [Revised: 08/06/2024] [Accepted: 08/12/2024] [Indexed: 08/29/2024]
Abstract
Chalkiness is an important grain quality trait in rice. Chalk5, encoding a vacuolar H+-translocating pyrophosphatase, is a major gene affecting both the percentage of grains with chalkiness (PGWC) and chalkiness degree (DEC) in rice. Reducing its expression can decrease both PGEC and DEC. In this study, the first exon of Chalk5 was edited in the elite restorer line 9311 using the CRISPR/Cas9 system and two knockout mutants were obtained, one of which did not contain the exogenous Cas9 cassette. PGWC and DEC were both significantly reduced in both mutants, while the seed setting ratio (SSR) was also significantly decreased. Staggered sowing experiments showed that the chalkiness of the mutants was insensitive to temperature during the grain-filling stage, and the head milled rice rate (HMRR) could be improved even under high-temperature conditions. Finally, in the hybrid background, the mutants showed significantly reduced PGWC and DEC without changes in other agronomic traits. The results provide important germplasm and allele resources for breeding high-yield rice varieties with superior quality, especially for high-yield indica hybrid rice varieties with superior quality in high-temperature conditions.
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Affiliation(s)
- Gucheng Fan
- Engineering Research Center of Ecology and Agricultural Use of Wetland, Ministry of Education, College of Agriculture, Yangtze University, Jingzhou 434025, China
- MARA Key Laboratory of Sustainable Crop Production in the Middle Researches of the Yangtze River (Co-Construction by Ministry and Province), College of Agriculture, Yangtze University, Jingzhou 434025, China
| | - Jiefeng Jiang
- Ningbo Academy of Agricultural Science, Ningbo 315101, China
| | - Yu Long
- Engineering Research Center of Ecology and Agricultural Use of Wetland, Ministry of Education, College of Agriculture, Yangtze University, Jingzhou 434025, China
- MARA Key Laboratory of Sustainable Crop Production in the Middle Researches of the Yangtze River (Co-Construction by Ministry and Province), College of Agriculture, Yangtze University, Jingzhou 434025, China
| | - Run Wang
- Engineering Research Center of Ecology and Agricultural Use of Wetland, Ministry of Education, College of Agriculture, Yangtze University, Jingzhou 434025, China
- MARA Key Laboratory of Sustainable Crop Production in the Middle Researches of the Yangtze River (Co-Construction by Ministry and Province), College of Agriculture, Yangtze University, Jingzhou 434025, China
| | - Famao Liang
- Yichang Academy of Agricultural Sciences, Yichang 443004, China
| | - Haiyang Liu
- Engineering Research Center of Ecology and Agricultural Use of Wetland, Ministry of Education, College of Agriculture, Yangtze University, Jingzhou 434025, China
- MARA Key Laboratory of Sustainable Crop Production in the Middle Researches of the Yangtze River (Co-Construction by Ministry and Province), College of Agriculture, Yangtze University, Jingzhou 434025, China
| | - Junying Xu
- Engineering Research Center of Ecology and Agricultural Use of Wetland, Ministry of Education, College of Agriculture, Yangtze University, Jingzhou 434025, China
- MARA Key Laboratory of Sustainable Crop Production in the Middle Researches of the Yangtze River (Co-Construction by Ministry and Province), College of Agriculture, Yangtze University, Jingzhou 434025, China
| | - Xianjin Qiu
- Engineering Research Center of Ecology and Agricultural Use of Wetland, Ministry of Education, College of Agriculture, Yangtze University, Jingzhou 434025, China
- MARA Key Laboratory of Sustainable Crop Production in the Middle Researches of the Yangtze River (Co-Construction by Ministry and Province), College of Agriculture, Yangtze University, Jingzhou 434025, China
| | - Zhixin Li
- Engineering Research Center of Ecology and Agricultural Use of Wetland, Ministry of Education, College of Agriculture, Yangtze University, Jingzhou 434025, China
- MARA Key Laboratory of Sustainable Crop Production in the Middle Researches of the Yangtze River (Co-Construction by Ministry and Province), College of Agriculture, Yangtze University, Jingzhou 434025, China
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Emelin M, Qiu X, Fan F, Alamin M, Faruquee M, Hu H, Xu J, Yang J, Xu H, Ali J, Liu B, Shi Y, Li Z, Zhang L, Zheng T, Xu J. Identification of reliable QTLs and designed QTL breeding for grain shape and milling quality in the reciprocal introgression lines in rice. BMC PLANT BIOLOGY 2024; 24:38. [PMID: 38191321 PMCID: PMC10775519 DOI: 10.1186/s12870-023-04707-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/20/2023] [Accepted: 12/26/2023] [Indexed: 01/10/2024]
Abstract
Milling quality (MQ) and grain shape (GS) of rice (Oryza sativa L.) are correlated traits, both determine farmers' final profit. More than one population under multiple environments may provide valuable information for breeding selection on these MQ-GS correlations. However, suitable analytical methods for reciprocal introgression lines with linkage map for this kind of correlation remains unclear. In this study, our major tasks were (1) to provide a set of reciprocal introgression lines (composed of two BC2RIL populations) suitable for mapping by linkage mapping using markers/bins with physical positions; (2) to test the mapping effects of different methods by using MQ-GS correlation dissection as sample case; (3) to perform genetic and breeding simulation on pyramiding favorite alleles of QTLs for representative MQ-GS traits. Finally, with four analysis methods and data collected under five environments, we identified about 28.4 loci on average for MQ-GS traits. Notably, 52.3% of these loci were commonly detected by different methods and eight loci were novel. There were also nine regions harboring loci for different MQ-GS traits which may be underlying the MQ-GS correlations. Background independent (BI) loci were also found for each MQ and GS trait. All these information may provide useful resources for rice molecular breeding.
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Affiliation(s)
- Mwenda Emelin
- Institute of Crop Sciences/State Key Laboratory of Crop Gene Resources and Breeding/National Key Facility for Crop Gene Resources and Genetic Improvement, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Xianjin Qiu
- Ministry of Agriculture and Rural Affairs (MARA) Key Laboratory of Sustainable Crop Production in the Middle Reaches of the Yangtze River (Co-Construction By Ministry and Province), College of Agriculture, Yangtze University, Jingzhou, 434025, China
| | - Fangjun Fan
- Institute of Food Crops, Jiangsu Academy of Agricultural Sciences, Jiangsu High Quality Rice Research and Development Center, Nanjing Branch of China National Center for Rice Improvement, Nanjing, 210014, China
| | - Md Alamin
- Institute of Crop Science and Institute of Bioinformatics, College of Agriculture and Biotechnology, Zhejiang University, Hangzhou, 310058, China
| | - Muhiuddin Faruquee
- International Rice Research Institute, Bangladesh Office, Dhaka, 1213, Bangladesh
| | - Hui Hu
- Ministry of Agriculture and Rural Affairs (MARA) Key Laboratory of Sustainable Crop Production in the Middle Reaches of the Yangtze River (Co-Construction By Ministry and Province), College of Agriculture, Yangtze University, Jingzhou, 434025, China
| | - Junying Xu
- Ministry of Agriculture and Rural Affairs (MARA) Key Laboratory of Sustainable Crop Production in the Middle Reaches of the Yangtze River (Co-Construction By Ministry and Province), College of Agriculture, Yangtze University, Jingzhou, 434025, China
| | - Jie Yang
- Institute of Food Crops, Jiangsu Academy of Agricultural Sciences, Jiangsu High Quality Rice Research and Development Center, Nanjing Branch of China National Center for Rice Improvement, Nanjing, 210014, China
| | - Haiming Xu
- Institute of Crop Science and Institute of Bioinformatics, College of Agriculture and Biotechnology, Zhejiang University, Hangzhou, 310058, China
| | - Jauhar Ali
- International Rice Research Institute, DAPO Box 7777, 1301, Metro Manila, Philippines
| | - Bailong Liu
- Rice Research Institute, Guangxi Academy of Agricultural Sciences, Nanning, 530007, China
| | - Yumin Shi
- Rice Research Institute, Guangxi Academy of Agricultural Sciences, Nanning, 530007, China
| | - Zhikang Li
- Institute of Crop Sciences/State Key Laboratory of Crop Gene Resources and Breeding/National Key Facility for Crop Gene Resources and Genetic Improvement, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Luyan Zhang
- Institute of Crop Sciences/State Key Laboratory of Crop Gene Resources and Breeding/National Key Facility for Crop Gene Resources and Genetic Improvement, Chinese Academy of Agricultural Sciences, Beijing, 100081, China.
| | - Tianqing Zheng
- Institute of Crop Sciences/State Key Laboratory of Crop Gene Resources and Breeding/National Key Facility for Crop Gene Resources and Genetic Improvement, Chinese Academy of Agricultural Sciences, Beijing, 100081, China.
- National Nanfan Research InstituteChinese Academy of Agricultural Sciences, Sanya, 572024, China.
| | - Jianlong Xu
- Institute of Crop Sciences/State Key Laboratory of Crop Gene Resources and Breeding/National Key Facility for Crop Gene Resources and Genetic Improvement, Chinese Academy of Agricultural Sciences, Beijing, 100081, China.
- National Nanfan Research InstituteChinese Academy of Agricultural Sciences, Sanya, 572024, China.
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3
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Sun H, Yuan Z, Li F, Zhang Q, Peng T, Li J, Du Y. Mapping of qChalk1 controlling grain chalkiness in japonica rice. Mol Biol Rep 2023:10.1007/s11033-023-08537-8. [PMID: 37231212 DOI: 10.1007/s11033-023-08537-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2023] [Accepted: 05/17/2023] [Indexed: 05/27/2023]
Abstract
BACKGROUND Rice grain chalkiness is an undesirable characteristic that affects grain quality. The aim of this study was to map QTLs controlling grain chalkiness in japonica rice. METHODS AND RESULTS In this study, two japonica rice cultivars with similar grain shapes but different grain chalkiness rates were crossed and the F2 and BC1F2 populations were subjected to QTL-seq analysis to map the QTLs controlling the grain chalkiness rate. QTL-seq analysis revealed SNP index differences on chromosome 1 in both of the segregating populations. Using polymorphic markers between the two parents, QTL mapping was conducted on 213 individual plants in the BC1F2 population. QTL mapping confined a QTL controlling grain chalkiness, qChalk1, to a 1.1 Mb genomic region on chromosome 1. qChalk1 explained 19.7% of the phenotypic variation. CONCLUSION A QTL controlling grain chalkiness qChalk1 was detected in both F2 and BC1F2 segregating populations by QTL-Seq and QTL mapping methods. This result would be helpful for further cloning of the genes controlling grain chalkiness in japonica rice.
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Affiliation(s)
- Hongzheng Sun
- College of Agronomy, Henan Agricultural University, Zhengzhou, 450046, People's Republic of China
| | - Zeke Yuan
- Henan Zhumadian Agricultural School, Zhumadian, 463000, People's Republic of China
| | - Fuhao Li
- College of Agronomy, Henan Agricultural University, Zhengzhou, 450046, People's Republic of China
| | - Qianqian Zhang
- Xinxiang Academy of Agricultural Sciences, Xinxiang, 453004, People's Republic of China
| | - Ting Peng
- College of Agronomy, Henan Agricultural University, Zhengzhou, 450046, People's Republic of China
| | - Junzhou Li
- College of Agronomy, Henan Agricultural University, Zhengzhou, 450046, People's Republic of China
| | - Yanxiu Du
- College of Agronomy, Henan Agricultural University, Zhengzhou, 450046, People's Republic of China.
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4
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Li J, Zhang C, Luo X, Zhang T, Zhang X, Liu P, Yang W, Lei Y, Tang S, Kang L, Huang L, Li T, Wang Y, Chen W, Yuan H, Qin P, Li S, Ma B, Tu B. Fine mapping of the grain chalkiness quantitative trait locus qCGP6 reveals the involvement of Wx in grain chalkiness formation. JOURNAL OF EXPERIMENTAL BOTANY 2023:erad112. [PMID: 36964899 DOI: 10.1093/jxb/erad112] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/11/2022] [Indexed: 06/18/2023]
Abstract
Grain chalkiness is an important index of rice appearance quality and is negatively associated with rice processing and eating qualities. However, the genetic mechanism underlying chalkiness formation is largely unknown. To identify the genetic basis of chalkiness, 410 recombinant inbred lines (RILs) derived from two representative indica rice varieties, Shuhui498 (R498) and Yihui3551 (R3551), were used to discover quantitative trait loci (QTL). The two parental lines and RILs were grown in three locations in China under three controlled fertilizer application level. Analyses indicated that chalkiness was significantly affected by genotype, the environment, and the interaction between the two, and that heritability was high. Several QTLs were isolated, including the two stable QTLs, i.e., qCGP6 and qCGP8. Fine mapping and candidate gene verification of qCGP6 showed that Wx may play a key role in chalkiness formation. Chromosomal segment substitution lines (CSSLs) and near-isogenic lines (NILs) carrying the Wxa or Wxin allele produced more chalky grain than the R498 parent. A similar result was also observed in the 3611 background. Notably, the effect of the Wx genotype on rice chalkiness was shown to be dependent on environmental conditions and Wx alleles exhibited different sensitivities to shading treatment. Using CRISPR/Cas9, the Wxa promoter region was successfully edited, down-regulating Wx alleviates chalkiness formation in NILR498-Wxa. This study developed a new strategy for synergistic improvement of eating and appearance qualities in rice, and created a novel Wx allele with great potential in breeding applications.
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Affiliation(s)
- Jialian Li
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Chengdu 611130, China
- Rice Research Institute of Sichuan Agricultural University, Chengdu 611130, China
| | - Cheng Zhang
- Liaoning Rice Research Institute, Shenyang, Liaoning 110101, China
| | - Xia Luo
- Rice Research Institute of Sichuan Agricultural University, Chengdu 611130, China
| | - Tao Zhang
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Chengdu 611130, China
- Rice Research Institute of Sichuan Agricultural University, Chengdu 611130, China
| | - Xiaoyu Zhang
- Rice Research Institute of Sichuan Agricultural University, Chengdu 611130, China
| | - Pin Liu
- Rice Research Institute of Sichuan Agricultural University, Chengdu 611130, China
| | - Wen Yang
- Rice Research Institute of Sichuan Agricultural University, Chengdu 611130, China
| | - Yuekun Lei
- Chengdu Juannong Intelligent Agriculture Technology Development Co., Ltd
| | - Siwen Tang
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Chengdu 611130, China
| | - Liangzhu Kang
- Rice Research Institute of Sichuan Agricultural University, Chengdu 611130, China
| | - Lin Huang
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Chengdu 611130, China
| | - Ting Li
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Chengdu 611130, China
| | - Yuping Wang
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Chengdu 611130, China
| | - Weilan Chen
- Rice Research Institute of Sichuan Agricultural University, Chengdu 611130, China
| | - Hua Yuan
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Chengdu 611130, China
| | - Peng Qin
- Rice Research Institute of Sichuan Agricultural University, Chengdu 611130, China
| | - Shigui Li
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Chengdu 611130, China
- Rice Research Institute of Sichuan Agricultural University, Chengdu 611130, China
| | - Bingtian Ma
- Rice Research Institute of Sichuan Agricultural University, Chengdu 611130, China
| | - Bin Tu
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Chengdu 611130, China
- Rice Research Institute of Sichuan Agricultural University, Chengdu 611130, China
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5
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Jin SK, Xu LN, Yang QQ, Zhang MQ, Wang SL, Wang RA, Tao T, Hong LM, Guo QQ, Jia SW, Song T, Leng YJ, Cai XL, Gao JP. High-resolution quantitative trait locus mapping for rice grain quality traits using genotyping by sequencing. FRONTIERS IN PLANT SCIENCE 2023; 13:1050882. [PMID: 36714703 PMCID: PMC9878556 DOI: 10.3389/fpls.2022.1050882] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/22/2022] [Accepted: 12/23/2022] [Indexed: 06/18/2023]
Abstract
Rice is a major food crop that sustains approximately half of the world population. Recent worldwide improvements in the standard of living have increased the demand for high-quality rice. Accurate identification of quantitative trait loci (QTLs) for rice grain quality traits will facilitate rice quality breeding and improvement. In the present study, we performed high-resolution QTL mapping for rice grain quality traits using a genotyping-by-sequencing approach. An F2 population derived from a cross between an elite japonica variety, Koshihikari, and an indica variety, Nona Bokra, was used to construct a high-density genetic map. A total of 3,830 single nucleotide polymorphism markers were mapped to 12 linkage groups spanning a total length of 2,456.4 cM, with an average genetic distance of 0.82 cM. Seven grain quality traits-the percentage of whole grain, percentage of head rice, percentage of area of head rice, transparency, percentage of chalky rice, percentage of chalkiness area, and degree of chalkiness-of the F2 population were investigated. In total, 15 QTLs with logarithm of the odds (LOD) scores >4 were identified, which mapped to chromosomes 6, 7, and 9. These loci include four QTLs for transparency, four for percentage of chalky rice, four for percentage of chalkiness area, and three for degree of chalkiness, accounting for 0.01%-61.64% of the total phenotypic variation. Of these QTLs, only one overlapped with previously reported QTLs, and the others were novel. By comparing the major QTL regions in the rice genome, several key candidate genes reported to play crucial roles in grain quality traits were identified. These findings will expedite the fine mapping of these QTLs and QTL pyramiding, which will facilitate the genetic improvement of rice grain quality.
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Affiliation(s)
- Su-Kui Jin
- JiangsuKey Laboratory of Crop Genomics and Molecular Breeding, College of Agriculture, Yangzhou University, Yangzhou, China
- Key Laboratory of Plant Functional Genomics of the Ministry of Education, College of Agriculture, Yangzhou University, Yangzhou, China
- Jiangsu Key Laboratory of Crop Genetics and Physiology, College of Agriculture, Yangzhou University, Yangzhou, China
- Jiangsu Co-Innovation Center for Modern Production Technology of Grain Crops, College of Agriculture, Yangzhou University, Yangzhou, China
- National Key Laboratory of Plant Molecular Genetics, Chinese Academy of Sciences (CAS) Center for Excellence in Molecular Plant Sciences, Shanghai Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai, China
| | - Li-Na Xu
- National Key Laboratory of Plant Molecular Genetics, Chinese Academy of Sciences (CAS) Center for Excellence in Molecular Plant Sciences, Shanghai Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai, China
| | - Qing-Qing Yang
- JiangsuKey Laboratory of Crop Genomics and Molecular Breeding, College of Agriculture, Yangzhou University, Yangzhou, China
- Key Laboratory of Plant Functional Genomics of the Ministry of Education, College of Agriculture, Yangzhou University, Yangzhou, China
- Jiangsu Key Laboratory of Crop Genetics and Physiology, College of Agriculture, Yangzhou University, Yangzhou, China
- Jiangsu Co-Innovation Center for Modern Production Technology of Grain Crops, College of Agriculture, Yangzhou University, Yangzhou, China
| | - Ming-Qiu Zhang
- JiangsuKey Laboratory of Crop Genomics and Molecular Breeding, College of Agriculture, Yangzhou University, Yangzhou, China
- Key Laboratory of Plant Functional Genomics of the Ministry of Education, College of Agriculture, Yangzhou University, Yangzhou, China
- Jiangsu Key Laboratory of Crop Genetics and Physiology, College of Agriculture, Yangzhou University, Yangzhou, China
- Jiangsu Co-Innovation Center for Modern Production Technology of Grain Crops, College of Agriculture, Yangzhou University, Yangzhou, China
| | - Shui-Lian Wang
- National Key Laboratory of Plant Molecular Genetics, Chinese Academy of Sciences (CAS) Center for Excellence in Molecular Plant Sciences, Shanghai Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai, China
- Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, Beijing, China
| | - Ruo-An Wang
- National Key Laboratory of Plant Molecular Genetics, Chinese Academy of Sciences (CAS) Center for Excellence in Molecular Plant Sciences, Shanghai Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai, China
| | - Tao Tao
- JiangsuKey Laboratory of Crop Genomics and Molecular Breeding, College of Agriculture, Yangzhou University, Yangzhou, China
- Key Laboratory of Plant Functional Genomics of the Ministry of Education, College of Agriculture, Yangzhou University, Yangzhou, China
- Jiangsu Key Laboratory of Crop Genetics and Physiology, College of Agriculture, Yangzhou University, Yangzhou, China
- Jiangsu Co-Innovation Center for Modern Production Technology of Grain Crops, College of Agriculture, Yangzhou University, Yangzhou, China
| | - Lian-Min Hong
- JiangsuKey Laboratory of Crop Genomics and Molecular Breeding, College of Agriculture, Yangzhou University, Yangzhou, China
- Key Laboratory of Plant Functional Genomics of the Ministry of Education, College of Agriculture, Yangzhou University, Yangzhou, China
- Jiangsu Key Laboratory of Crop Genetics and Physiology, College of Agriculture, Yangzhou University, Yangzhou, China
- Jiangsu Co-Innovation Center for Modern Production Technology of Grain Crops, College of Agriculture, Yangzhou University, Yangzhou, China
| | - Qian-Qian Guo
- JiangsuKey Laboratory of Crop Genomics and Molecular Breeding, College of Agriculture, Yangzhou University, Yangzhou, China
- Key Laboratory of Plant Functional Genomics of the Ministry of Education, College of Agriculture, Yangzhou University, Yangzhou, China
- Jiangsu Key Laboratory of Crop Genetics and Physiology, College of Agriculture, Yangzhou University, Yangzhou, China
- Jiangsu Co-Innovation Center for Modern Production Technology of Grain Crops, College of Agriculture, Yangzhou University, Yangzhou, China
| | - Shu-Wen Jia
- National Key Laboratory of Plant Molecular Genetics, Chinese Academy of Sciences (CAS) Center for Excellence in Molecular Plant Sciences, Shanghai Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai, China
| | - Tao Song
- National Key Laboratory of Plant Molecular Genetics, Chinese Academy of Sciences (CAS) Center for Excellence in Molecular Plant Sciences, Shanghai Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai, China
- Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, Beijing, China
| | - Yu-Jia Leng
- JiangsuKey Laboratory of Crop Genomics and Molecular Breeding, College of Agriculture, Yangzhou University, Yangzhou, China
- Key Laboratory of Plant Functional Genomics of the Ministry of Education, College of Agriculture, Yangzhou University, Yangzhou, China
- Jiangsu Key Laboratory of Crop Genetics and Physiology, College of Agriculture, Yangzhou University, Yangzhou, China
- Jiangsu Co-Innovation Center for Modern Production Technology of Grain Crops, College of Agriculture, Yangzhou University, Yangzhou, China
| | - Xiu-Ling Cai
- JiangsuKey Laboratory of Crop Genomics and Molecular Breeding, College of Agriculture, Yangzhou University, Yangzhou, China
- Key Laboratory of Plant Functional Genomics of the Ministry of Education, College of Agriculture, Yangzhou University, Yangzhou, China
- Jiangsu Key Laboratory of Crop Genetics and Physiology, College of Agriculture, Yangzhou University, Yangzhou, China
- Jiangsu Co-Innovation Center for Modern Production Technology of Grain Crops, College of Agriculture, Yangzhou University, Yangzhou, China
- National Key Laboratory of Plant Molecular Genetics, Chinese Academy of Sciences (CAS) Center for Excellence in Molecular Plant Sciences, Shanghai Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai, China
| | - Ji-Ping Gao
- JiangsuKey Laboratory of Crop Genomics and Molecular Breeding, College of Agriculture, Yangzhou University, Yangzhou, China
- Key Laboratory of Plant Functional Genomics of the Ministry of Education, College of Agriculture, Yangzhou University, Yangzhou, China
- Jiangsu Key Laboratory of Crop Genetics and Physiology, College of Agriculture, Yangzhou University, Yangzhou, China
- Jiangsu Co-Innovation Center for Modern Production Technology of Grain Crops, College of Agriculture, Yangzhou University, Yangzhou, China
- National Key Laboratory of Plant Molecular Genetics, Chinese Academy of Sciences (CAS) Center for Excellence in Molecular Plant Sciences, Shanghai Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai, China
- Innovation Academy for Seed Design, Chinese Academy of Sciences, Beijing, China
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6
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Wang W, Zhang F, Liu D, Chen K, Du B, Qiu X, Xu J, Xing D. Distribution characteristics of selenium, cadmium and arsenic in rice grains and their genetic dissection by genome-wide association study. Front Genet 2022; 13:1007896. [PMCID: PMC9612882 DOI: 10.3389/fgene.2022.1007896] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2022] [Accepted: 10/03/2022] [Indexed: 11/13/2022] Open
Abstract
High selenium (Se) and low cadmium (Cd) and arsenic (As) contents in rice grains were good for human health. The genetic basis and relationship of Se, Cd and As concentrations in rice grains are still largely unknown. In the present study, large variations were observed in Se, Cd and As concentrations in brown and milled rice in normal and Se treatment conditions in 307 rice accessions from 3K Rice Genomes Project. Se fertilizer treatment greatly increased Se concentrations but had no obvious changes in concentrations of Cd and As both in brown and milled rice. Total of 237 QTL were identified for Se, Cd and As concentrations in brown and milled rice in normal and Se treatment conditions as well as ratio of concentrations under Se treatment to normal conditions. Only 19 QTL (13.4%) were mapped for concentrations of Se and Cd, Se and As, and Se, Cd and As in the same or adjacent regions, indicating that most Se concentration QTL are independent of Cd and As concentration QTL. Forty-three favorable alleles were identified for 40 candidate genes by gene-based association study and haplotype analysis in 14 important QTL regions. Se-enriched rice variety will be developed by pyramiding favorable alleles at different Se QTL and excluding undesirable alleles at Cd and As QTL, or combining favorable alleles at Se QTL with the alleles at Se-sensitive QTL by marker-assisted selection.
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Affiliation(s)
- Wenxi Wang
- College of Economy and Management, Hubei University of Technology, Wuhan, China
- MARA Key Laboratory of Sustainable Crop Production in the Middle Reaches of the Yangtze River (Co-construction by Ministry and Province), College of Agriculture, Yangtze University, Jingzhou, China
| | - Fan Zhang
- Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Dapu Liu
- Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Kai Chen
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
| | - Bin Du
- MARA Key Laboratory of Sustainable Crop Production in the Middle Reaches of the Yangtze River (Co-construction by Ministry and Province), College of Agriculture, Yangtze University, Jingzhou, China
| | - Xianjin Qiu
- MARA Key Laboratory of Sustainable Crop Production in the Middle Reaches of the Yangtze River (Co-construction by Ministry and Province), College of Agriculture, Yangtze University, Jingzhou, China
- *Correspondence: Xianjin Qiu, ; Jianlong Xu,
| | - Jianlong Xu
- Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, China
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
- National Nanfan Research Institute (Sanya), Chinese Academy of Agricultural Sciences, Sanya, China
- *Correspondence: Xianjin Qiu, ; Jianlong Xu,
| | - Danying Xing
- MARA Key Laboratory of Sustainable Crop Production in the Middle Reaches of the Yangtze River (Co-construction by Ministry and Province), College of Agriculture, Yangtze University, Jingzhou, China
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7
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Zafar S, You H, Zhang F, Zhu SB, Chen K, Shen C, Wu H, Zhu F, Zhang C, Xu J. Genetic dissection of grain traits and their corresponding heterosis in an elite hybrid. FRONTIERS IN PLANT SCIENCE 2022; 13:977349. [PMID: 36275576 PMCID: PMC9581170 DOI: 10.3389/fpls.2022.977349] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/24/2022] [Accepted: 09/14/2022] [Indexed: 06/16/2023]
Abstract
Rice productivity has considerably improved due to the effective employment of heterosis, but the genetic basis of heterosis for grain shape and weight remains uncertain. For studying the genetic dissection of heterosis for grain shape/weight and their relationship with grain yield in rice, quantitative trait locus (QTL) mapping was performed on 1,061 recombinant inbred lines (RILs), which was developed by crossing xian/indica rice Quan9311B (Q9311B) and Wu-shan-si-miao (WSSM). Whereas, BC1F1 (a backcross F1) was developed by crossing RILs with Quan9311A (Q9311A) combined with phenotyping in Hefei (HF) and Nanning (NN) environments. Overall, 114 (main-effect, mQTL) and 359 (epistatic QTL, eQTL) were identified in all populations (RIL, BC1F1, and mid-parent heterosis, HMPs) for 1000-grain weight (TGW), grain yield per plant (GYP) and grain shape traits including grain length (GL), grain width (GW), and grain length to width ratio (GLWR). Differential QTL detection revealed that all additive loci in RILs population do not show heterotic effects, and few of them affect the performance of BC1F1. However, 25 mQTL not only contributed to BC1F1's performance but also contributed to heterosis. A total of seven QTL regions was identified, which simultaneously affected multiple grain traits (grain yield, weight, shape) in the same environment, including five regions with opposite directions and two regions with same directions of favorable allele effects, indicating that partial genetic overlaps are existed between different grain traits. This study suggested different approaches for obtaining good grain quality with high yield by pyramiding or introgressing favorable alleles (FA) with the same direction of gene effect at the QTL regions affecting grain shape/weight and grain yield distributing on different chromosomes, or introgressing or pyramiding FA in the parents instead of fixing additive effects in hybrid as well as pyramiding the polymorphic overdominant/dominant loci between the parents and eliminating underdominant loci from the parents. These outcomes offer valuable information and strategy to develop hybrid rice with suitable grain type and weight.
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Affiliation(s)
- Sundus Zafar
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
| | - Hui You
- The National Key Facility for Crop Gene Resources and Genetic Improvement, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Fan Zhang
- The National Key Facility for Crop Gene Resources and Genetic Improvement, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Shuang Bin Zhu
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
| | - Kai Chen
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
| | - Congcong Shen
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
| | - Hezhou Wu
- Hunan Tao-Hua-Yuan Agricultural Technologies Co., LTD., Hunan, China
| | - Fangjin Zhu
- Hunan Tao-Hua-Yuan Agricultural Technologies Co., LTD., Hunan, China
| | | | - Jianlong Xu
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
- The National Key Facility for Crop Gene Resources and Genetic Improvement, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
- Hainan Yazhou Bay Seed Lab/National Nanfan Research Institute (Sanya), Chinese Academy of Agricultural Sciences, Sanya, China
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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: 5] [Impact Index Per Article: 1.7] [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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Genetic Dissection of Rice Ratooning Ability Using an Introgression Line Population and Substitution Mapping of a Pleiotropic Quantitative Trait Locus qRA5. PLANTS 2022; 11:plants11091134. [PMID: 35567135 PMCID: PMC9100519 DOI: 10.3390/plants11091134] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/10/2022] [Revised: 04/20/2022] [Accepted: 04/20/2022] [Indexed: 11/17/2022]
Abstract
Ratooning ability is a key factor that influences ratoon rice yield, in the area where light and temperature are not enough for second season rice. In the present study, an introgression line population derived from Minghui 63 as the recipient parent and 02428 as the donor parent was developed, and a high-density bin map containing 4568 bins was constructed. Nine ratooning-ability-related traits were measured, including maximum tiller number, panicle number, and grain yield per plant in the first season and ratoon season, as well as three secondary traits, maximum tiller number ratio, panicle number ratio, and grain yield ratio. A total of 22 main-effect QTLs were identified and explained for 3.26–18.63% of the phenotypic variations in the introgression line population. Three genomic regions, including 14.12–14.65 Mb on chromosome 5, 4.64–5.76 Mb on chromosome 8, and 10.64–15.52 Mb on chromosome 11, were identified to simultaneously control different ratooning-ability-related traits. Among them, qRA5 in the region of 14.12–14.65 Mb on chromosome 5 was validated for its pleiotropic effects on maximum tiller number and panicle number in the first season, as well as its maximum tiller number ratio, panicle number ratio, and grain yield ratio. Moreover, qRA5 was independent of genetic background and delimited into a 311.16 kb region by a substitution mapping approach. These results will help us better understand the genetic basis of rice ratooning ability and provide a valuable gene resource for breeding high-yield ratoon rice varieties.
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10
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Mapping combined with principal component analysis identifies excellent lines with increased rice quality. Sci Rep 2022; 12:5969. [PMID: 35396526 PMCID: PMC8993813 DOI: 10.1038/s41598-022-09976-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2021] [Accepted: 03/30/2022] [Indexed: 11/11/2022] Open
Abstract
Quality-related traits are some of the most important traits in rice, and screening and breeding rice lines with excellent quality are common ways for breeders to improve the quality of rice. In this study, we used 151 recombinant inbred lines (RILs) obtained by crossing the northern cultivated japonica rice variety ShenNong265 (SN265) with the southern indica rice variety LuHui99 (LH99) and simplified 18 common rice quality-related traits into 8 independent principal components (PCs) by principal component analysis (PCA). These PCs included peak and hot paste viscosity, chalky grain percentage and chalkiness degree, brown and milled rice recovery, width length rate, cooked taste score, head rice recovery, milled rice width, and cooked comprehensive score factors. Based on the weight ratio of each PC score, the RILs were classified into five types from excellent to poor, and five excellent lines were identified. Compared with SN265, these 5 lines showed better performance regarding the chalky grain percentage and chalkiness degree factor. Moreover, we performed QTL localization on the RIL population and identified 94 QTLs for quality-related traits that formed 6 QTL clusters. In future research, by combining these QTL mapping results, we will be using backcrossing to aggregate excellent traits and achieve quality improvement of SN265.
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Jiang L, Zhong H, Jiang X, Zhang J, Huang R, Liao F, Deng Y, Liu Q, Huang Y, Wang H, Tao Y, Zheng J. Identification and Pleiotropic Effect Analysis of GSE5 on Rice Chalkiness and Grain Shape. FRONTIERS IN PLANT SCIENCE 2022; 12:814928. [PMID: 35126437 PMCID: PMC8810533 DOI: 10.3389/fpls.2021.814928] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/14/2021] [Accepted: 12/20/2021] [Indexed: 05/31/2023]
Abstract
Chalkiness is one of several major restricting factors for the improvement of rice quality. Although many chalkiness-related quantitative trait loci have been mapped, only a small number of genes have been cloned to date. In this study, the candidate gene GSE5 of a major quantitative trait locus (QTL) for rice chalkiness, qDEC5, was identified by map-based cloning. Phenotyping and haplotype analysis of proActin:GSE5 transgenic line, gse5-cr mutant, and 69 rice varieties further confirmed that GSE5 had the pleiotropic effects and regulated both chalkiness and grain shape. Genetic analysis showed GSE5 was a dominant gene for grain length and a semi-dominant gene for grain width and chalkiness. The DNA interval closely linked to GSE5 was introgressed to Zhenshan 97B (ZB) based on molecular marker-assisted selection, and the improved ZB showed lower chalkiness and longer but smaller grains, which showed that GSE5 played an important role in breeding rice varieties with high yield and good quality. Transcriptomics, proteomics, and qRT-PCR analyses showed that thirty-nine genes associated with carbon and protein metabolism are regulated by GSE5 to affect the formation of chalkiness, including some newly discovered genes, such as OsCESA9, OsHSP70, OsTPS8, OsPFK04, OsSTA1, OsERdj3A, etc. The low-chalkiness lines showed higher amino sugar and nucleotide sugar metabolism at 10 days after pollination (DAP), lower carbohydrate metabolism at 15 DAP, and lower protein metabolism at 10 and 15 DAP. With heat shock at 34/30°C, rice chalkiness increased significantly; OsDjC10 and OsSUS3 were upregulated at 6 and 12 DAP, respectively, and OsGSTL2 was downregulated at 12 DAP. Our results identified the function and pleiotropic effects of qDEC5 dissected its genetic characteristics and the expression profiles of the genes affecting the chalkiness formation, and provided a theoretical basis and application value to harmoniously pursue high yield and good quality in rice production.
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Affiliation(s)
- Liangrong Jiang
- Xiamen Plant Genetics Key Laboratory, School of Life Sciences, Xiamen University, Xiamen, China
| | - Hui Zhong
- Xiamen Plant Genetics Key Laboratory, School of Life Sciences, Xiamen University, Xiamen, China
| | - Xianbin Jiang
- Guangxi Rice Genetics and Breeding Key Laboratory, Rice Research Institute, Guangxi Academy of Agricultural Sciences, Nanning, China
| | - Jiaoping Zhang
- National Key Laboratory for Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, China
| | - Rongyu Huang
- Xiamen Plant Genetics Key Laboratory, School of Life Sciences, Xiamen University, Xiamen, China
| | - Furong Liao
- Xiamen Entry-Exit Inspection and Quarantine Bureau, Xiamen, China
| | - Yaqin Deng
- Xiamen Plant Genetics Key Laboratory, School of Life Sciences, Xiamen University, Xiamen, China
| | - Qingqing Liu
- Xiamen Plant Genetics Key Laboratory, School of Life Sciences, Xiamen University, Xiamen, China
| | - Yumin Huang
- Xiamen Plant Genetics Key Laboratory, School of Life Sciences, Xiamen University, Xiamen, China
| | - Houcong Wang
- Xiamen Plant Genetics Key Laboratory, School of Life Sciences, Xiamen University, Xiamen, China
| | - Yi Tao
- Xiamen Plant Genetics Key Laboratory, School of Life Sciences, Xiamen University, Xiamen, China
| | - Jingsheng Zheng
- Xiamen Plant Genetics Key Laboratory, School of Life Sciences, Xiamen University, Xiamen, China
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12
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Su Y, Xiao LT. 3D Visualization and Volume-Based Quantification of Rice Chalkiness In Vivo by Using High Resolution Micro-CT. RICE (NEW YORK, N.Y.) 2020; 13:69. [PMID: 32936382 PMCID: PMC7494727 DOI: 10.1186/s12284-020-00429-w] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/22/2020] [Accepted: 09/09/2020] [Indexed: 05/05/2023]
Abstract
BACKGROUND Rice quality research attracts attention worldwide. Rice chalkiness is one of the key indexes determining rice kernel quality. The traditional rice chalkiness measurement methods only use milled rice as materials and are mainly based on naked-eye observation or area-based two-dimensional (2D) image analysis and the results could not represent the three-dimensional (3D) characteristics of chalkiness in the rice kernel. These methods are neither in vivo thus are unable to analyze living rice seeds for high throughput screening of rice chalkiness phenotype. RESULTS Here, we introduced a novel method for 3D visualization and accurate volume-based quantification of rice chalkiness in vivo by using X-ray microcomputed tomography (micro-CT). This approach not only develops a novel volume-based method to measure the 3D rice chalkiness index, but also provides a high throughput solution for rice chalkiness phenotype analysis by using living rice seeds. CONCLUSIONS Our method could be a new powerful tool for rice chalkiness measurement, especially for high throughput chalkiness phenotype screening using living rice seeds. This method could be used in chalkiness phenotype identification and screening, and would greatly promote the basic research in rice chalkiness regulation as well as the quality evaluation in rice production practice.
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Affiliation(s)
- Yi Su
- College of Bioscience and Biotechnology, Hunan Agricultural University, Changsha, China
| | - Lang-Tao Xiao
- College of Bioscience and Biotechnology, Hunan Agricultural University, Changsha, China.
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13
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Shi Y, Liu A, Li J, Zhang J, Li S, Zhang J, Ma L, He R, Song W, Guo L, Lu Q, Xiang X, Gong W, Gong J, Ge Q, Shang H, Deng X, Pan J, Yuan Y. Examining two sets of introgression lines across multiple environments reveals background-independent and stably expressed quantitative trait loci of fiber quality in cotton. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2020; 133:2075-2093. [PMID: 32185421 PMCID: PMC7311500 DOI: 10.1007/s00122-020-03578-0] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/25/2019] [Accepted: 03/07/2020] [Indexed: 05/29/2023]
Abstract
Background-independent (BI) and stably expressed (SE) quantitative trait loci (QTLs) were identified using two sets of introgression lines across multiple environments. Genetic background more greatly affected fiber quality traits than environmental factors. Sixty-one SE-QTLs, including two BI-QTLs, were novel and 48 SE-QTLs, including seven BI-QTLs, were previously reported. Cotton fiber quality traits are controlled by QTLs and are susceptible to environmental influence. Fiber quality improvement is an essential goal in cotton breeding but is hindered by limited knowledge of the genetic basis of fiber quality traits. In this study, two sets of introgression lines of Gossypium hirsutum × G. barbadense were used to dissect the QTL stability of three fiber quality traits (fiber length, strength and micronaire) across environments using 551 simple sequence repeat markers selected from our high-density genetic map. A total of 76 and 120 QTLs were detected in the CCRI36 and CCRI45 backgrounds, respectively. Nine BI-QTLs were found, and 78 (41.71%) of the detected QTLs were reported previously. Thirty-nine and 79 QTLs were SE-QTLs in at least two environments in the CCRI36 and CCRI45 backgrounds, respectively. Forty-eight SE-QTLs, including seven BI-QTLs, were confirmed in previous reports, and 61 SE-QTLs, including two BI-QTLs, were considered novel. These results indicate that genetic background more strongly impacts on fiber quality traits than environmental factors. Twenty-three clusters with BI- and/or SE-QTLs were identified, 19 of which harbored favorable alleles from G. barbadense for two or three fiber quality traits. This study is the first report using two sets of introgression lines to identify fiber quality QTLs across environments in cotton, providing insights into the effect of genetic backgrounds and environments on the QTL expression of fiber quality and important information for the genetic basis underlying fiber quality traits toward QTL cloning and molecular breeding.
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Affiliation(s)
- Yuzhen Shi
- State Key Laboratory of Cotton Biology, Key Laboratory of Biological and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, Henan, China
| | - Aiying Liu
- State Key Laboratory of Cotton Biology, Key Laboratory of Biological and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, Henan, China
| | - Junwen Li
- State Key Laboratory of Cotton Biology, Key Laboratory of Biological and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, Henan, China
| | - Jinfa Zhang
- Department of Plant and Environmental Sciences, New Mexico State University, Las Cruces, NM, 88003, USA
| | - Shaoqi Li
- State Key Laboratory of Cotton Biology, Key Laboratory of Biological and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, Henan, China
| | - Jinfeng Zhang
- State Key Laboratory of Cotton Biology, Key Laboratory of Biological and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, Henan, China
| | - Liujun Ma
- State Key Laboratory of Cotton Biology, Key Laboratory of Biological and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, Henan, China
| | - Rui He
- State Key Laboratory of Cotton Biology, Key Laboratory of Biological and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, Henan, China
| | - Weiwu Song
- State Key Laboratory of Cotton Biology, Key Laboratory of Biological and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, Henan, China
| | - Lixue Guo
- State Key Laboratory of Cotton Biology, Key Laboratory of Biological and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, Henan, China
| | - Quanwei Lu
- State Key Laboratory of Cotton Biology, Key Laboratory of Biological and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, Henan, China
| | - Xianghui Xiang
- State Key Laboratory of Cotton Biology, Key Laboratory of Biological and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, Henan, China
| | - Wankui Gong
- State Key Laboratory of Cotton Biology, Key Laboratory of Biological and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, Henan, China
| | - Juwu Gong
- State Key Laboratory of Cotton Biology, Key Laboratory of Biological and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, Henan, China
| | - Qun Ge
- State Key Laboratory of Cotton Biology, Key Laboratory of Biological and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, Henan, China
| | - Haihong Shang
- State Key Laboratory of Cotton Biology, Key Laboratory of Biological and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, Henan, China
| | - Xiaoying Deng
- State Key Laboratory of Cotton Biology, Key Laboratory of Biological and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, Henan, China
| | - Jingtao Pan
- State Key Laboratory of Cotton Biology, Key Laboratory of Biological and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, Henan, China
| | - Youlu Yuan
- State Key Laboratory of Cotton Biology, Key Laboratory of Biological and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, Henan, China.
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Balakrishnan D, Surapaneni M, Yadavalli VR, Addanki KR, Mesapogu S, Beerelli K, Neelamraju S. Detecting CSSLs and yield QTLs with additive, epistatic and QTL×environment interaction effects from Oryza sativa × O. nivara IRGC81832 cross. Sci Rep 2020; 10:7766. [PMID: 32385410 PMCID: PMC7210974 DOI: 10.1038/s41598-020-64300-0] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2019] [Accepted: 04/10/2020] [Indexed: 12/25/2022] Open
Abstract
Chromosome segment substitution lines (CSSLs) are useful tools for precise mapping of quantitative trait loci (QTLs) and the evaluation of gene action and interaction in inter-specific crosses. In this study, a set of 90 back cross lines at BC2F8 generation derived from Swarna x Oryza nivara IRGC81832 was evaluated for yield traits under irrigated conditions in wet seasons of 3 consecutive years. We identified a set of 70 chromosome segment substitution lines, using genotyping data from 140 SSR markers covering 94.4% of O. nivara genome. Among these, 23 CSSLs were significantly different for 7 traits. 22 QTLs were detected for 11 traits with 6.51 to 46.77% phenotypic variation in 90 BILs. Three pleiotropic genomic regions associated with yield traits were mapped on chromosomes 1, 8 and 11. The marker interval RM206-RM144 at chromosome 11 was recurrently detected for various yield traits. Ten QTLs were identified consistently in the three consecutive years of testing. Seventeen pairs of significant epistatic QTLs (E-QTLs) were detected for days to flowering, days to maturity and plant height. Chromosome segments from O. nivara contributed trait enhancing alleles. The significantly improved lines and the stable QTLs identified in this study are valuable resource for gene discovery and yield improvement.
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Yu S, Ali J, Zhang C, Li Z, Zhang Q. Genomic Breeding of Green Super Rice Varieties and Their Deployment in Asia and Africa. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2020; 133:1427-1442. [PMID: 31915875 PMCID: PMC7214492 DOI: 10.1007/s00122-019-03516-9] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/12/2019] [Accepted: 12/17/2019] [Indexed: 05/22/2023]
Abstract
KEY MESSAGE The "Green Super Rice" (GSR) project aims to fundamentally transform crop production techniques and promote the development of green agriculture based on functional genomics and breeding of GSR varieties by whole-genome breeding platforms. Rice (Oryza sativa L.) is one of the leading food crops of the world, and the safe production of rice plays a central role in ensuring food security. However, the conflicts between rice production and environmental resources are becoming increasingly acute. For this reason, scientists in China have proposed the concept of Green Super Rice for promoting resource-saving and environment-friendly rice production, while still achieving a yield increase and quality improvement. GSR is becoming one of the major goals for agricultural research and crop improvement worldwide, which aims to mine and use vital genes associated with superior agronomic traits such as high yield, good quality, nutrient efficiency, and resistance against insects and stresses; establish genomic breeding platforms to breed and apply GSR; and set up resource-saving and environment-friendly cultivation management systems. GSR has been introduced into eight African and eight Asian countries and has contributed significantly to rice cultivation and food security in these countries. This article mainly describes the GSR concept and recent research progress, as well as the significant achievements in GSR breeding and its application.
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Affiliation(s)
- Sibin Yu
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, 430070, China
| | - Jauhar Ali
- International Rice Research Institute, DAPO Box 7777, Metro Manila, Philippines
| | - Chaopu Zhang
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, 430070, China
| | - Zhikang Li
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China.
- College of Agronomy, Anhui Agricultural University, Hefei, China.
| | - Qifa Zhang
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, 430070, China.
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Performance of a Set of Eggplant (Solanum melongena) Lines With Introgressions From Its Wild Relative S. incanum Under Open Field and Screenhouse Conditions and Detection of QTLs. AGRONOMY-BASEL 2020. [DOI: 10.3390/agronomy10040467] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
Introgression lines (ILs) of eggplant (Solanum melongena) represent a resource of high value for breeding and the genetic analysis of important traits. We have conducted a phenotypic evaluation in two environments (open field and screenhouse) of 16 ILs from the first set of eggplant ILs developed so far. Each of the ILs carries a single marker-defined chromosomal segment from the wild eggplant relative S. incanum (accession MM577) in the genetic background of S. melongena (accession AN-S-26). Seventeen agronomic traits were scored to test the performance of ILs compared to the recurrent parent and of identifying QTLs for the investigated traits. Significant morphological differences were found between parents, and the hybrid was heterotic for vigour-related traits. Despite the presence of large introgressed fragments from a wild exotic parent, individual ILs did not display differences with respect to the recipient parent for most traits, although significant genotype × environment interaction (G × E ) was detected for most traits. Heritability values for the agronomic traits were generally low to moderate. A total of ten stable QTLs scattered across seven chromosomes was detected. For five QTLs, the S. incanum introgression was associated with higher mean values for plant- and flower-related traits, including vigour prickliness and stigma length. For one flower- and four fruit-related-trait QTLs, including flower peduncle and fruit pedicel lengths and fruit weight, the S. incanum introgression was associated with lower mean values for fruit-related traits. Evidence of synteny to other previously reported in eggplant populations was found for three of the fruit-related QTLs. The other seven stable QTLs are new, demonstrating that eggplant ILs are of great interest for eggplant breeding under different environments.
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McClung AM, Chen M, Jodari F, Famoso AN, Addison CK, Linscombe SD, Ottis BV, Moldenhauer KAK, Walker TW, Wilson LT, McKenzie KS. Use of objective imaging systems to assess subjective grain appearance traits important to the US rice industry. Cereal Chem 2020. [DOI: 10.1002/cche.10251] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Affiliation(s)
- Anna M. McClung
- Dale Bumpers National Rice Research Center USDA, ARS Stuttgart AR USA
| | - Ming‐Hsuan Chen
- Dale Bumpers National Rice Research Center USDA, ARS Stuttgart AR USA
| | - Farman Jodari
- California Cooperative Rice Research Foundation, Inc. Rice Experiment Station Biggs CA USA
| | - Adam N. Famoso
- Rice Research Station Louisiana State University Rayne LA USA
| | | | | | | | | | | | - Lloyd T. Wilson
- AgriLife Research Texas A&M University System Beaumont TX USA
| | - Kent S. McKenzie
- California Cooperative Rice Research Foundation, Inc. Rice Experiment Station Biggs CA USA
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Saxena RK, Kale S, Mir RR, Mallikarjuna N, Yadav P, Das RR, Molla J, Sonnappa M, Ghanta A, Narasimhan Y, Rathore A, Kumar CVS, Varshney RK. Genotyping-by-sequencing and multilocation evaluation of two interspecific backcross populations identify QTLs for yield-related traits in pigeonpea. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2020; 133:737-749. [PMID: 31844966 DOI: 10.1007/s00122-019-03504-z] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/26/2019] [Accepted: 12/06/2019] [Indexed: 06/10/2023]
Abstract
This study has identified single-nucleotide polymorphism (SNP) markers associated with nine yield-related traits in pigeonpea by using two backcross populations (BP) developed through interspecific crosses and evaluating them at two locations and 3 years. In both the populations, markers have shown strong segregation distortion; therefore, a quantitative trait locus (QTL) mapping mixed model was used. A total of 86 QTLs explaining 12-21% phenotypic variation were detected in BP-1. On the other hand, 107 QTLs explaining 11-29% phenotypic variation were detected in BP-2. Although most QTLs were environment and trait specific, few stable and consistent QTLs were also detected. Interestingly, 11 QTLs in BP-2 were associated with more than one trait. Among these QTLs, eight QTLs associated with days to 50% flowering and days to 75% maturity were located on CcLG07. One SNP "S7_14185076" marker in BP-2 population has been found associated with four traits, namely days to 50% flowering, days to 75% maturity, primary branches per plant and secondary branches per plant with positive additive effect. Hence, the present study has not only identified QTLs for yield-related traits, but also discovered novel alleles from wild species, which can be used for improvement of traits through genomics-assisted breeding.
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Affiliation(s)
- Rachit K Saxena
- International Crops Research Institute for the Semi-Arid Tropics (ICRSAT), Patancheru, Telangana, 502324, India
| | - Sandip Kale
- The Leibniz-Institute of Plant Genetics and Crop Plant Research (IPK), Corrensstr. 3, 06466, Seeland, OT Gatersleben, Germany
| | - Reyazul Rouf Mir
- Sher-E-Kashmir University of Agricultural Sciences and Technology of Kashmir (SKUAST-K), Wadura Campus, Sopore, Kashmir, 193201, India
| | - Nalini Mallikarjuna
- International Crops Research Institute for the Semi-Arid Tropics (ICRSAT), Patancheru, Telangana, 502324, India
| | - Pooja Yadav
- International Crops Research Institute for the Semi-Arid Tropics (ICRSAT), Patancheru, Telangana, 502324, India
| | - Roma Rani Das
- International Crops Research Institute for the Semi-Arid Tropics (ICRSAT), Patancheru, Telangana, 502324, India
| | - Johiruddin Molla
- International Crops Research Institute for the Semi-Arid Tropics (ICRSAT), Patancheru, Telangana, 502324, India
| | - Muniswamy Sonnappa
- Agricultural Research Station (UAS-Raichur), Gulbarga, Karnataka, 585101, India
| | - Anuradha Ghanta
- Professor Jayashankar Telangana State Agricultural University, Rajendranagar, Hyderabad, Telangana, 500030, India
| | - Yamini Narasimhan
- Professor Jayashankar Telangana State Agricultural University, Rajendranagar, Hyderabad, Telangana, 500030, India
| | - Abhishek Rathore
- International Crops Research Institute for the Semi-Arid Tropics (ICRSAT), Patancheru, Telangana, 502324, India
| | - C V Sameer Kumar
- Professor Jayashankar Telangana State Agricultural University, Rajendranagar, Hyderabad, Telangana, 500030, India
| | - Rajeev K Varshney
- International Crops Research Institute for the Semi-Arid Tropics (ICRSAT), Patancheru, Telangana, 502324, India.
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19
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Quantitative trait loci (QTL) underlying phenotypic variation in bioethanol-related processes in Neurospora crassa. PLoS One 2020; 15:e0221737. [PMID: 32017762 PMCID: PMC6999864 DOI: 10.1371/journal.pone.0221737] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2019] [Accepted: 01/09/2020] [Indexed: 11/19/2022] Open
Abstract
Bioethanol production from lignocellulosic biomass has received increasing attention over the past decade. Many attempts have been made to reduce the cost of bioethanol production by combining the separate steps of the process into a single-step process known as consolidated bioprocessing. This requires identification of organisms that can efficiently decompose lignocellulose to simple sugars and ferment the pentose and hexose sugars liberated to ethanol. There have been many attempts in engineering laboratory strains by adding new genes or modifying genes to expand the capacity of an industrial microorganism. There has been less attention in improving bioethanol-related processes utilizing natural variation existing in the natural ecotypes. In this study, we sought to identify genomic loci contributing to variation in saccharification of cellulose and fermentation of glucose in the fermenting cellulolytic fungus Neurospora crassa through quantitative trait loci (QTL) analysis. We identified one major QTL contributing to fermentation of glucose and multiple putative QTL's underlying saccharification. Understanding the natural variation of the major QTL gene would provide new insights in developing industrial microbes for bioethanol production.
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Okada S, Yamasaki M. Validation of a quantitative trait locus for the white-core expression rate of grain on chromosome 6 in a brewing rice cultivar and development of DNA markers for marker-assisted selection. BREEDING SCIENCE 2019; 69:401-409. [PMID: 31598072 PMCID: PMC6776145 DOI: 10.1270/jsbbs.18166] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/18/2018] [Accepted: 04/01/2019] [Indexed: 05/25/2023]
Abstract
Sake-brewing cultivars among varieties of Japanese rice (Oryza sativa L.) have traits adapted to the sake-brewing process, such as a high white-core expression rate (WCE). Our previous study detected putative quantitative trait loci (QTLs) associated with a high WCE derived from Yamadanishiki, a popular brewing rice cultivar. Because the occurrence of white-core grains depends on air temperature and the position of the grain on the panicle, phenotyping of WCE must consider these variable conditions. In this study, qWCE6, a QTL for the WCE on chromosome 6, was validated for the first time, and the phenotyping method examined for its suitability in fine-mapping. A clear tendency towards high WCE was observed in late-heading substituted lines which headed under low daily mean temperature at the experimental location. White-core grains were often expressed by the primary spikelets on the upper panicle, producing a high percentage of superior grains. The segregating population for qWCE6 in late heading revealed a distinct difference in WCE between the Koshihikari and Yamadanishiki homozygous alleles at qWCE6 as determined from that locality. Further, two insertion/deletion markers were developed for the marker-assisted selection of qWCE6. Our results will be useful for informing the breeding of sake-brewing rice cultivars.
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Affiliation(s)
- Satoshi Okada
- Food Resources Education and Research Center, Graduate School of Agricultural Science, Kobe University,
Kasai, Hyogo 675-2103,
Japan
| | - Masanori Yamasaki
- Food Resources Education and Research Center, Graduate School of Agricultural Science, Kobe University,
Kasai, Hyogo 675-2103,
Japan
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Balakrishnan D, Surapaneni M, Mesapogu S, Neelamraju S. Development and use of chromosome segment substitution lines as a genetic resource for crop improvement. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2019; 132:1-25. [PMID: 30483819 DOI: 10.1007/s00122-018-3219-y] [Citation(s) in RCA: 39] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/04/2017] [Accepted: 10/24/2018] [Indexed: 05/27/2023]
Abstract
CSSLs are a complete library of introgression lines with chromosomal segments of usually a distant genotype in an adapted background and are valuable genetic resources for basic and applied research on improvement of complex traits. Chromosome segment substitution lines (CSSLs) are genetic stocks representing the complete genome of any genotype in the background of a cultivar as overlapping segments. Ideally, each CSSL has a single chromosome segment from the donor with a maximum recurrent parent genome recovered in the background. CSSL development program requires population-wide backcross breeding and genome-wide marker-assisted selection followed by selfing. Each line in a CSSL library has a specific marker-defined large donor segment. CSSLs are evaluated for any target phenotype to identify lines significantly different from the parental line. These CSSLs are then used to map quantitative trait loci (QTLs) or causal genes. CSSLs are valuable prebreeding tools for broadening the genetic base of existing cultivars and harnessing the genetic diversity from the wild- and distant-related species. These are resources for genetic map construction, mapping QTLs, genes or gene interactions and their functional analysis for crop improvement. In the last two decades, the utility of CSSLs in identification of novel genomic regions and QTL hot spots influencing a wide range of traits has been well demonstrated in food and commercial crops. This review presents an overview of how CSSLs are developed, their status in major crops and their use in genomic studies and gene discovery.
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Affiliation(s)
- Divya Balakrishnan
- ICAR- National Professor Project, ICAR- Indian Institute of Rice Research, Hyderabad, India
| | - Malathi Surapaneni
- ICAR- National Professor Project, ICAR- Indian Institute of Rice Research, Hyderabad, India
| | - Sukumar Mesapogu
- ICAR- National Professor Project, ICAR- Indian Institute of Rice Research, Hyderabad, India
| | - Sarla Neelamraju
- ICAR- National Professor Project, ICAR- Indian Institute of Rice Research, Hyderabad, India.
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Zhu A, Zhang Y, Zhang Z, Wang B, Xue P, Cao Y, Chen Y, Li Z, Liu Q, Cheng S, Cao L. Genetic Dissection of qPCG1 for a Quantitative Trait Locus for Percentage of Chalky Grain in Rice ( Oryza sativa L.). FRONTIERS IN PLANT SCIENCE 2018; 9:1173. [PMID: 30147703 PMCID: PMC6095994 DOI: 10.3389/fpls.2018.01173] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/10/2018] [Accepted: 07/23/2018] [Indexed: 05/18/2023]
Abstract
Rice is a pivotal cereal crop that provides the staple food for more than half of the world's population. Along with improvements in the standard of living, people not only pay attention to the grain yield but also to the grain quality. Chalkiness is one of the most important index of grain quality. In this study, qPCG1, a QTL for percentage of chalky grain, was mapped in an interval with a physical distance about 139 kb on chromosome 1 by residual heterozygous line (RHL) method. qPCG1 was incomplete dominant and the additive effect plays a major role and explained 6.8-21.9% of phenotypic variance within the heterogeneous region on chromosome 1. The effect of allele from Zhonghui9308 was decreasing the percentage of chalky grains (PCG). Microscope observation results indicated that there are great differences in the shape, structure and arrangement of starch granule between the chalky part and transparent part. Analysis of starch physicochemical properties showed that the total starch content, amylose content and chain length distribution of amylopectin changed while the protein contents were not apparently affected with the changed chalkiness. qPCG1 had little influence on main agronomic traits and it might be useful in rice breeding for it did not bring negative effect on grain yield while reducing the chalkiness.
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Affiliation(s)
- Aike Zhu
- Key Laboratory for Zhejiang Super Rice Research, State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, China
- Nanchong Academy of Agricultural Sciences, Nanchong, China
| | - Yingxin Zhang
- Key Laboratory for Zhejiang Super Rice Research, State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, China
| | - Zhenhua Zhang
- Key Laboratory for Zhejiang Super Rice Research, State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, China
| | - Beifang Wang
- Key Laboratory for Zhejiang Super Rice Research, State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, China
| | - Pao Xue
- Key Laboratory for Zhejiang Super Rice Research, State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, China
| | - Yongrun Cao
- Key Laboratory for Zhejiang Super Rice Research, State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, China
- Crop Genetic Breeding Department, Henan Agricultural University, Zhengzhou, China
| | - Yuyu Chen
- Key Laboratory for Zhejiang Super Rice Research, State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, China
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China
| | - Zihe Li
- Key Laboratory for Zhejiang Super Rice Research, State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, China
| | - Qunen Liu
- Key Laboratory for Zhejiang Super Rice Research, State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, China
| | - Shihua Cheng
- Key Laboratory for Zhejiang Super Rice Research, State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, China
| | - Liyong Cao
- Key Laboratory for Zhejiang Super Rice Research, State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, China
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Okada S, Suehiro M, Ebana K, Hori K, Onogi A, Iwata H, Yamasaki M. Genetic dissection of grain traits in Yamadanishiki, an excellent sake-brewing rice cultivar. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2017; 130:2567-2585. [PMID: 28887658 DOI: 10.1007/s00122-017-2977-2] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/18/2017] [Accepted: 09/01/2017] [Indexed: 05/20/2023]
Abstract
The grain traits of Yamadanishiki, an excellent sake-brewing rice cultivar in Japan, are governed by multiple QTLs, namely, a total of 42 QTLs including six major QTLs. Japanese rice wine (sake) is produced using brewing rice (Oryza sativa L.) that carries traits desirable for sake-brewing, such as a larger grain size and higher white-core expression rate (WCE) compared to cooking rice cultivars. However, the genetic basis for these traits in brewing rice cultivars is still unclear. We performed analyses of quantitative trait locus (QTL) of grain and days to heading over 3 years on populations derived from crosses between Koshihikari, a cooking rice, and Yamadanishiki, an excellent sake-brewing rice. A total of 42 QTLs were detected for the grain traits, and the Yamadanishiki alleles at 16 QTLs contributed to larger grain size. Two major QTLs essential for regulating both 100-grain weight (GWt) and grain width (GWh) were harbored in the same regions on chromosomes 5 and 10. An interaction was noted between the environment and the QTL associated with WCE on chromosome 6, which was detected in two of 3 years. In addition, two QTLs for WCE on chromosomes 3 and 10 overlapped with the QTLs for GWt and GWh, suggesting that QTLs associated with grain size also play an important role in the formation of white-core. Despite differences in the rate of grain growth in both Koshihikari and Yamadanishiki across 2 years, the WCE in Yamadanishiki remained consistent, thus demonstrating that the formation of white-core does not depend on grain filling speed. These data can be informative for programs involved in breeding better cooking and brewing rice cultivars.
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Affiliation(s)
- Satoshi Okada
- Food Resources Education and Research Center, Graduate School of Agricultural Science, Kobe University, 1348 Uzurano, Kasai, Hyogo, 675-2103, Japan
| | - Miki Suehiro
- Food Resources Education and Research Center, Graduate School of Agricultural Science, Kobe University, 1348 Uzurano, Kasai, Hyogo, 675-2103, Japan
| | - Kaworu Ebana
- Genetic Resources Center, National Agriculture and Food Research Organization, Ibaraki, Japan
| | - Kiyosumi Hori
- Institute of Crop Science, National Agriculture and Food Research Organization, Ibaraki, Japan
| | - Akio Onogi
- Department of Agricultural and Environmental Biology, Graduate School of Agricultural and Life Sciences, The University of Tokyo, Tokyo, 113-8657, Japan
| | - Hiroyoshi Iwata
- Department of Agricultural and Environmental Biology, Graduate School of Agricultural and Life Sciences, The University of Tokyo, Tokyo, 113-8657, Japan
| | - Masanori Yamasaki
- Food Resources Education and Research Center, Graduate School of Agricultural Science, Kobe University, 1348 Uzurano, Kasai, Hyogo, 675-2103, Japan.
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