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Wang P, Yang Y, Li D, Yu Z, zhang B, Zhou X, Xiong L, Zhang J, Wang L, Xing Y. Powerful QTL mapping and favorable allele mining in an all-in-one population: a case study of heading date. Natl Sci Rev 2024; 11:nwae222. [PMID: 39210988 PMCID: PMC11360186 DOI: 10.1093/nsr/nwae222] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2024] [Revised: 06/18/2024] [Accepted: 06/19/2024] [Indexed: 09/04/2024] Open
Abstract
The multiparent advanced generation intercross (MAGIC) population is characterized with great potentials in power and resolution of quantitative trait locus (QTL) mapping, but single nucleotide polymorphism (SNP)-based GWAS does not fully reach its potential. In this study, a MAGIC population of 1021 lines was developed from four Xian and four Geng varieties from five subgroups of rice. A total of 44 000 genes showed functional polymorphisms among eight parents, including frameshift variations or premature stop codon variations, which provides the potential to map almost all genes of the MAGIC population. Principal component analysis results showed that the MAGIC population had a weak population structure. A high-density bin map of 24 414 bins was constructed. Segregation distortion occurred in the regions possessing the genes underlying genetic incompatibility and gamete development. SNP-based association analysis and bin-based linkage analysis identified 25 significant loci and 47 QTLs for heading date, including 14 known heading date genes. The mapping resolution of genes is dependent on genetic effects with offset distances of <55 kb for major effect genes and <123 kb for moderate effect genes. Four causal variants and noncoding structure variants were identified to be associated with heading date. Three to four types of alleles with strong, intermediate, weak, and no genetic effects were identified from eight parents, providing flexibility for the improvement of rice heading date. In most cases, japonica rice carries weak alleles, and indica rice carries strong alleles and nonfunctional alleles. These results confirm that the MAGIC population provides the exceptional opportunity to detect QTLs, and its use is encouraged for mapping genes and mining favorable alleles for breeding.
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Affiliation(s)
- Pengfei Wang
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China
- Institute of Tropical Crop Genetic Resources, Chinese Academy of Tropical Agricultural Sciences, Haikou 571101, China
| | - Ying Yang
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China
| | - Daoyang Li
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China
| | - Zhichao Yu
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China
| | - Bo zhang
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China
| | - Xiangchun Zhou
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China
| | - Lizhong Xiong
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China
| | - Jianwei Zhang
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China
| | - Lei Wang
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China
| | - Yongzhong Xing
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China
- Yazhouwan National Laboratory, Sanya 572024, China
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Wang P, Ma L, Li D, Zhang B, Zhou T, Zhou X, Xing Y. Fine mapping of the panicle length QTL qPL5 in rice. MOLECULAR BREEDING : NEW STRATEGIES IN PLANT IMPROVEMENT 2024; 44:6. [PMID: 38261843 PMCID: PMC10794681 DOI: 10.1007/s11032-024-01443-2] [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: 11/08/2023] [Accepted: 12/02/2023] [Indexed: 01/25/2024]
Abstract
Panicle length is a crucial trait tightly associated with spikelets per panicle and grain yield in rice. To dissect the genetic basis of panicle length, a population of 161 recombinant inbred lines (RILs) was developed from the cross between an aus variety Chuan 7 (C7) and a tropical Geng variety Haoboka (HBK). C7 has a panicle length of 30 cm, 7 cm longer than that of HBK, and the panicle length was normally distributed in the RIL population. A total of six quantitative trait loci (QTLs) for panicle length were identified, and single QTLs explained the phenotypic variance from 4.9 to 18.1%. Among them, three QTLs were mapped to the regions harbored sd1, DLT, and Ehd1, respectively. To validate the genetic effect of a minor QTL qPL5, a near-isogenic F2 (NIF2) population segregated at qPL5 was developed. Interestingly, panicle length displayed bimodal distribution, and heading date also exhibited significant variation in the NIF2 population. qPL5 accounted for 66.5% of the panicle length variance. The C7 allele at qPL5 increased panicle length by 2.4 cm and promoted heading date by 5 days. Finally, qPL5 was narrowed down to an 80-kb region flanked by markers M2197 and M2205 using a large NIF2 population of 7600 plants. LOC_Os05g37540, encoding a phytochrome signal protein whose homolog in Arabidopsis enlarges panicle length, is regarded as the candidate gene because a single-nucleotide mutation (C1099T) caused a premature stop codon in HBK. The characterization of qPL5 with enlarging panicle length but promoting heading date makes its great value in breeding early mature varieties without yield penalty in rice. Supplementary Information The online version contains supplementary material available at 10.1007/s11032-024-01443-2.
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Affiliation(s)
- Pengfei Wang
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan, 430070 China
| | - Ling Ma
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan, 430070 China
| | - Daoyang Li
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan, 430070 China
| | - Bo Zhang
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan, 430070 China
| | - Tianhao Zhou
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan, 430070 China
| | - Xiangchun Zhou
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan, 430070 China
| | - Yongzhong Xing
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan, 430070 China
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Sun Y, Jing D, Zhang J, Du L, Li C, Lan Y, Lin F, Zhou T. Yield components affected by rice black-streaked dwarf virus disease in rice cultivars with different resistance levels. Front Microbiol 2023; 14:1323569. [PMID: 38156012 PMCID: PMC10752958 DOI: 10.3389/fmicb.2023.1323569] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2023] [Accepted: 11/15/2023] [Indexed: 12/30/2023] Open
Abstract
Introduction Rice black-streaked dwarf virus disease (RBSDVD) is one of the most destructive rice viral diseases, leading to severe yield losses in rice production. However, little is known about the yield-related components associated with the disease and no resistance cultivars have been successfully used in rice breeding. Methods Seven rice cultivars were analyzed in this study, including six commercial rice varieties and a new line Zhongjian No. 201 (ZJ201) containing the resistance gene OsAP47. Resistance levels of these cultivars were evaluated by artificial inoculation and yield components were collected, including panicle length (PL), spikelets per panicle (SPP), ripened grains per panicle (RGPP), as well as panicles per square meter (PPSM) and 1000-grain weight (TGW). Seed setting rate (SSR) were calculated with the data of SPP and RGPP. Results and discussion The results showed that ZJ201 displayed the highest resistance level and most of the commercial rice cultivars exhibited susceptible to RBSDVD. Yields of all the rice cultivars were significantly declined except ZJ201 and yield losses produced by RBSDVD were mainly due to the reduction of PL, SPP, RGPP, and TGW, suggesting that developments of these traits are associated with RBSDV infection. Resistant rice cultivar could reduce yield losses by maintaining normal development of these traits. Significant correlations were identified between resistance levels and the yield components except SSR and PPSM. The results provided useful clues for understanding the mechanisms of RBSDV invasion and its effect on rice production. ZJ201 was demonstrated as a resistance material that could be used in rice breeding.
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Affiliation(s)
- Yue Sun
- Jiangsu Key Laboratory for Food Quality and Safety-State Key Laboratory Cultivation Base, Institute of Plant Protection, Jiangsu Academy of Agricultural Sciences, Nanjing, Jiangsu, China
- College of Food Science, Shenyang Agricultural University, Shenyang, Liaoning, China
| | - Dedao Jing
- Zhenjiang Institute of Agricultural Sciences of the Ning-Zhen Hilly District, Zhenjiang, Jiangsu, China
| | - Jiayuan Zhang
- Jiangsu Key Laboratory for Food Quality and Safety-State Key Laboratory Cultivation Base, Institute of Plant Protection, Jiangsu Academy of Agricultural Sciences, Nanjing, Jiangsu, China
- College of Food Science, Shenyang Agricultural University, Shenyang, Liaoning, China
| | - Linlin Du
- Jiangsu Key Laboratory for Food Quality and Safety-State Key Laboratory Cultivation Base, Institute of Plant Protection, Jiangsu Academy of Agricultural Sciences, Nanjing, Jiangsu, China
| | - Chenyang Li
- Jiangsu Key Laboratory for Food Quality and Safety-State Key Laboratory Cultivation Base, Institute of Plant Protection, Jiangsu Academy of Agricultural Sciences, Nanjing, Jiangsu, China
| | - Ying Lan
- Jiangsu Key Laboratory for Food Quality and Safety-State Key Laboratory Cultivation Base, Institute of Plant Protection, Jiangsu Academy of Agricultural Sciences, Nanjing, Jiangsu, China
| | - Feng Lin
- Jiangsu Key Laboratory for Food Quality and Safety-State Key Laboratory Cultivation Base, Institute of Plant Protection, Jiangsu Academy of Agricultural Sciences, Nanjing, Jiangsu, China
- College of Food Science, Shenyang Agricultural University, Shenyang, Liaoning, China
| | - Tong Zhou
- Jiangsu Key Laboratory for Food Quality and Safety-State Key Laboratory Cultivation Base, Institute of Plant Protection, Jiangsu Academy of Agricultural Sciences, Nanjing, Jiangsu, China
- International Joint Center for Japonica Rice Research, Nanjing, Jiangsu, China
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Genetic Mapping to Detect Stringent QTLs Using 1k-RiCA SNP Genotyping Platform from the New Landrace Associated with Salt Tolerance at the Seedling Stage in Rice. PLANTS 2022; 11:plants11111409. [PMID: 35684182 PMCID: PMC9183132 DOI: 10.3390/plants11111409] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/22/2022] [Revised: 05/20/2022] [Accepted: 05/23/2022] [Indexed: 12/02/2022]
Abstract
Rice is the world’s most important food crop, providing the daily calorie intake for more than half of the world’s population. Rice breeding has always been preoccupied with maximizing yield potential. However, numerous abiotic factors, such as salt, cold, drought, and heat, significantly reduce rice productivity. Salinity, one of the major abiotic stresses, reduces rice yield worldwide. This study was conducted to determine new quantitative trait loci (QTLs) that regulate salt tolerance in rice seedlings. One F2:3 mapping population was derived from a cross between BRRI dhan49 (a popular but sensitive rainfed rice variety) and Akundi (a salt-tolerant rice landrace in Bangladesh used as a donor parent). The 1k-Rice Custom Amplicon (1k-RiCA) single-nucleotide polymorphism (SNP) markers were used to genotype this mapping population. After removing segregation distortion and monomorphic markers, 884 SNPs generated a 1526.8 cM-long genetic linkage map with a mean marker density of 1.7 cM for the 12 linkage groups. By exploiting QGene and ICIM-ADD, a sum of 15 QTLs for nine traits was identified in salt stress on seven chromosomes. Four important genomic loci were identified (qSES1, qSL1, qSUR1 and qRL1) on chromosome 1. Out of these 15 QTLs, 14 QTLs are unique, as no other study has mapped in the same chromosomal location. We also detected 15 putative candidate genes and their functions. The ICIM-EPI approach identified 43 significant pairwise epistasis interactions between regions associated with and unassociated with QTLs. Apart from more well-known donors, Akundi serves as an important new donor source for global salt tolerance breeding initiatives, including Bangladesh. The introgression of the novel QTLs identified in this study will accelerate the development of new salt-tolerant varieties that are highly resistant to salt stress using marker-enabled breeding.
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Genetic Analysis of a Collection of Rice Germplasm (Oryza sativa L.) through High-Density SNP Array Provides Useful Information for Further Breeding Practices. Genes (Basel) 2022; 13:genes13050830. [PMID: 35627215 PMCID: PMC9141261 DOI: 10.3390/genes13050830] [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: 04/14/2022] [Revised: 04/30/2022] [Accepted: 05/04/2022] [Indexed: 11/17/2022] Open
Abstract
Traditional breeding strategies mainly focus on the evaluation of trait performance, but pay less attention to the changing genetic background. A comprehensive understanding of the genetic diversity of germplasms is crucial for the deliberate improvement of specific traits. A collection of 154 highland rice varieties were collected as the initial genetic resource in our breeding program to improve the pathogen resistance and eating and cooking qualities. These varieties were analyzed using a whole-genome SNP array and were clustered into three groups. Further analysis revealed that the favorable alleles of pathogen resistance genes are mostly absent in our collected varieties. However, it showed that most varieties possess favorable alleles of Waxy (Wx) and ALKALI DEGENERATION (ALK), which are able to enhance the eating and cooking qualities. Moreover, only about one fifth of all varieties harbors favorable the allele of fragrance gene Betainealdehyde dehydrogenase (BADH2). Together, these results give an overall view of the genetic constitution of the target traits, which provide useful information for future genetic improvement in breeding practices.
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Liang F, Zhan W, Hu G, Liu H, Xing Y, Li Z, Han Z. Five plants per RIL for phenotyping traits of high or moderate heritability ensure the power of QTL mapping in a rice MAGIC population. MOLECULAR BREEDING : NEW STRATEGIES IN PLANT IMPROVEMENT 2022; 42:28. [PMID: 37309531 PMCID: PMC10248629 DOI: 10.1007/s11032-022-01299-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/01/2022] [Accepted: 05/20/2022] [Indexed: 06/14/2023]
Abstract
Currently, the power of QTL mapping is mainly dependent on the quality of phenotypic data in a given population, regardless of the statistical method, as the quality of genotypic data is easily guaranteed in the laboratory. Increasing the sample size per line used for phenotyping is a good way to improve the quality of phenotypic data. However, accommodating a large-scale mapping population takes a large area of rice field, which frequently results in high costs and extra environmental noises. To acquire a reasonable small sample size without a penalty in mapping power, we conducted three experiments with a 4-way MAGIC population and measured phenotypes of 5, 10, and 20 plants per RIL. Three traits including heading date, plant height, and tillers per plant were focused. With SNP- and bin-based QTL mapping, 3 major and 3 minor QTLs for heading date with high heritability and 2 major QTLs for plant height with moderate heritability were commonly detected across the three experiments, but no QTL for tillers per plant with low heritability were commonly identified. In addition, bin-based QTL mapping was more powerful than SNP-based mapping and able to rank the genetic effects of parental alleles. Thus, 5 plants per RIL for phenotyping ensure the power of QTL mapping for traits of high or moderate heritability, and bin-based QTL mapping is recommended for multiparent populations.
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Affiliation(s)
- Famao Liang
- College of Agriculture, Yangtze University, Jingzhou, 434000 China
| | - Wei Zhan
- Hubei Provincial Key Laboratory for Protection and Application of Special Plant Germplasm in Wuling Area of China, South-Central University for Nationalities, Wuhan, 430074 China
| | - Gang Hu
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agriculture University, Wuhan, 430070 China
| | - Hua Liu
- College of Agriculture, Yangtze University, Jingzhou, 434000 China
| | - Yongzhong Xing
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agriculture University, Wuhan, 430070 China
| | - Zhixin Li
- College of Agriculture, Yangtze University, Jingzhou, 434000 China
| | - Zhongmin Han
- Key Laboratory of Soybean Molecular Design Breeding, Northeast Institute of Geography and Agroecology, The Innovative Academy of Seed Design, Chinese Academy of Sciences, 150081 Harbin, China
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agriculture University, Wuhan, 430070 China
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Chen J, Liu K, Zha W, Zhou L, Li M, Xu H, Li P, Chen Z, Yang G, Chen P, Li S, You A. Identification and verification of grain shape QTLs by SNP array in rice. PLoS One 2021; 16:e0260133. [PMID: 34807926 PMCID: PMC8608341 DOI: 10.1371/journal.pone.0260133] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2021] [Accepted: 11/04/2021] [Indexed: 11/21/2022] Open
Abstract
Grain shape strongly influences the economic value and grain yield of rice. Thus, identifying quantitative trait loci (QTLs) for grain shape has been a longstanding goal in rice genetic research and breeding programs. Single nucleotide polymorphism (SNP) markers are ubiquitous in the rice genome and are more abundant and evenly distributed on the 12 rice chromosomes than traditional markers. An F2 population was genotyped using the RICE6K SNP array to elucidate the mechanisms governing grain shape. Thirty-five QTLs for grain shape were detected on 11 of 12 chromosomes over 2 years. The major QTL cluster qGS7 was detected in both years and displayed strong genetic effects on grain length and width, showing consistency with GL7/GW7. Some minor QTLs were also detected, and the effects of four QTLs on seed size were then validated using BC1F6 populations with residual heterozygous lines in each QTL region. Our findings provide insights into the molecular basis of grain shape as well as additional resources and approaches for producing hybrid high-yield rice varieties.
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Affiliation(s)
- Junxiao Chen
- Hubei Key Laboratory of Food Crop Germplasm and Genetic Improvement, Food Crops Institute, Hubei Academy of Agricultural Sciences, Wuhan, China
| | - Kai Liu
- Hubei Key Laboratory of Food Crop Germplasm and Genetic Improvement, Food Crops Institute, Hubei Academy of Agricultural Sciences, Wuhan, China
| | - Wenjun Zha
- Hubei Key Laboratory of Food Crop Germplasm and Genetic Improvement, Food Crops Institute, Hubei Academy of Agricultural Sciences, Wuhan, China
| | - Lei Zhou
- Hubei Key Laboratory of Food Crop Germplasm and Genetic Improvement, Food Crops Institute, Hubei Academy of Agricultural Sciences, Wuhan, China
| | - Ming Li
- Hubei Key Laboratory of Food Crop Germplasm and Genetic Improvement, Food Crops Institute, Hubei Academy of Agricultural Sciences, Wuhan, China
| | - Huashan Xu
- Hubei Key Laboratory of Food Crop Germplasm and Genetic Improvement, Food Crops Institute, Hubei Academy of Agricultural Sciences, Wuhan, China
| | - Peide Li
- Hubei Key Laboratory of Food Crop Germplasm and Genetic Improvement, Food Crops Institute, Hubei Academy of Agricultural Sciences, Wuhan, China
| | - Zhijun Chen
- Hubei Key Laboratory of Food Crop Germplasm and Genetic Improvement, Food Crops Institute, Hubei Academy of Agricultural Sciences, Wuhan, China
| | - Guocai Yang
- Hubei Key Laboratory of Food Crop Germplasm and Genetic Improvement, Food Crops Institute, Hubei Academy of Agricultural Sciences, Wuhan, China
| | - Pingli Chen
- Guangdong Key Laboratory of New Technology in Rice Breeding, The Rice Research Institute of Guangdong Academy of Agricultural Sciences, Guangzhou, China
| | - Sanhe Li
- Hubei Key Laboratory of Food Crop Germplasm and Genetic Improvement, Food Crops Institute, Hubei Academy of Agricultural Sciences, Wuhan, China
- * E-mail: (AY); (SL)
| | - Aiqing You
- Hubei Key Laboratory of Food Crop Germplasm and Genetic Improvement, Food Crops Institute, Hubei Academy of Agricultural Sciences, Wuhan, China
- * E-mail: (AY); (SL)
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Hu W, Zhou T, Han Z, Tan C, Xing Y. Dominant complementary interaction between OsC1 and two tightly linked genes, Rb1 and Rb2, controls the purple leaf sheath in rice. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2020; 133:2555-2566. [PMID: 32458058 DOI: 10.1007/s00122-020-03617-w] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/18/2020] [Accepted: 05/16/2020] [Indexed: 05/20/2023]
Abstract
Two tightly linked genes for rice purple leaf sheath were identified via map-based cloning. Further analysis indicated that these two genes together with OsC1 co-regulating the purple leaf sheath. The purple color of the leaf sheath in rice is dependent on the accumulation of anthocyanins such as cyanidin 3-O-glucoside (C3G) and peonidin 3-O-glucoside (P3G). Although many genes related to leaf sheath color have been mapped, the genetic basis for leaf sheath color is not yet clear. Here, PSH1 (purple leaf sheath 1) was mapped to chromosome 1 using an F2 and a RIL population. Map-based cloning and transformation assays further divided PSH1 as two tightly linked bHLH genes, Rb1 and Rb2. Ectopic expression of these two genes resulted in substantial accumulation of C3G and P3G in the leaf blade, leaf sheath and pericarp. Single gene mutants displayed a faded purple leaf sheath or green leaf sheath in the top half of the leaf sheath, but double mutants displayed a green leaf sheath, indicating that both genes have dosage effects on anthocyanin synthesis. However, overexpression of Rb1 and Rb2 sharply decreased grain filling. A segregation ratio of green to purple was 15:1 observed in the F2 population from parents Minghui 63 and Xizang 2, which both had green leaf sheaths; these results demonstrate that dominant complementary interaction between OsC1 and Rb (Rb1 and Rb2) controls the purple leaf sheath. These findings systematically uncovered the genetic basis of leaf sheath color and provided alternative genes for breeding anthocyanin-rich rice.
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Affiliation(s)
- Wei Hu
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, 430070, China
| | - Tianhao Zhou
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, 430070, China
| | - Zhongmin Han
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, 430070, China
| | - Cong Tan
- China National GeneBank, Shenzhen, 518120, China
| | - Yongzhong Xing
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, 430070, China.
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Han Z, Hu G, Liu H, Liang F, Yang L, Zhao H, Zhang Q, Li Z, Zhang Q, Xing Y. Bin-based genome-wide association analyses improve power and resolution in QTL mapping and identify favorable alleles from multiple parents in a four-way MAGIC rice population. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2020; 133:59-71. [PMID: 31549182 DOI: 10.1007/s00122-019-03440-y] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/28/2019] [Accepted: 09/17/2019] [Indexed: 05/25/2023]
Abstract
A whole genome bin map was developed for a MAGIC population. Association studies for heading date at bin level exhibited powerful QTL mapping and identified favorable alleles. The presumed advantages of multiparent advanced generation intercross (MAGIC) population in quantitative trait locus (QTL) mapping were not fully utilized in the previous studies in which genome-wide association studies (GWAS) were conducted at only single nucleotide polymorphism level. In this study, we genotyped a rice four-way MAGIC population of 247 F7 lines and their parents by sequencing. A total of 5934 bins with an average length of 65 kb were constructed and covered 97% of the genome. The MAGIC population showed low population structure and balanced parental contributions. A bin-based GWAS for heading date identified 4 QTLs in three environments. Three major QTLs were mapped exactly to the bins where the major heading date genes DTH3, Ghd7.1 and Ghd8 were located. Multiple comparisons showed that different parental alleles had varied genetic effects. Like DTH3, the alleles of the Guichao 2/YJSM, IR34 and Cypress had larger, intermediate and no effects, respectively. Based on comparative sequencing of 8 known heading date genes undetected in this MAGIC population, only Ghd7 exhibited diverse function among parents. The failure in Ghd7 mapping was well explained by its interaction with Hd1 because Ghd7 had no effects on heading date when combined with the nonfunctional hd1 carried by all four parents. Overall, bin-based GWAS have more mapping power and higher resolution with a MAGIC population and provide favorable alleles to breeders. The use of more diversified parents is encouraged to develop a MAGIC population for detecting more QTLs for important agronomical traits.
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Affiliation(s)
- Zhongmin Han
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agriculture University, Wuhan, 430070, China
| | - Gang Hu
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agriculture University, Wuhan, 430070, China
| | - Hua Liu
- College of Agriculture, Yangtze University, Hubei Collaborative Innovation Center for Grain Industry, Jingzhou, 434000, China
| | - Famao Liang
- College of Agriculture, Yangtze University, Hubei Collaborative Innovation Center for Grain Industry, Jingzhou, 434000, China
| | - Lin Yang
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agriculture University, Wuhan, 430070, China
| | - Hu Zhao
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agriculture University, Wuhan, 430070, China
| | - Qinghua Zhang
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agriculture University, Wuhan, 430070, China
| | - Zhixin Li
- College of Agriculture, Yangtze University, Hubei Collaborative Innovation Center for Grain Industry, Jingzhou, 434000, China
| | - Qifa Zhang
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agriculture University, Wuhan, 430070, China
| | - Yongzhong Xing
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agriculture University, Wuhan, 430070, China.
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Wang L, Cheng Y, Ma Q, Mu Y, Huang Z, Xia Q, Zhang G, Nian H. QTL fine-mapping of soybean (Glycine max L.) leaf type associated traits in two RILs populations. BMC Genomics 2019; 20:260. [PMID: 30940069 PMCID: PMC6444683 DOI: 10.1186/s12864-019-5610-8] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2018] [Accepted: 03/14/2019] [Indexed: 11/30/2022] Open
Abstract
BACKGROUND The different leaf type associated traits of soybean (Glycine max L.) including leaf area, leaf length, leaf width, leaf shape and petiole length are considered to be associated with seed yield. In order to identify quantitative trait loci (QTLs) affecting leaf type traits, two advanced recombinant inbred line (RIL, ZH, Zhonghuang 24 × Huaxia 3; GB, Guizao 1 × Brazil 13) populations were introduced to score phenotypic values in plants across nine different environments (years, seasons, locations and soybean growth stages). Two restriction site-associated DNA sequencing (RAD-seq) based high-density genetic linkage maps with an average distance of 1.00 centimorgan (cM) between adjacent bin markers were utilized for QTL fine mapping. RESULTS Correlation analysis showed that most of the traits were correlated with each other and regulated both by hereditary and environmental factors. A total of 190 QTLs were identified for leaf type associated traits in the two populations, of which 14 loci were found to be environmentally stable. Moreover, these detected QTLs were categorized into 34 QTL hotspots, and four important QTL hotspots with phenotypic variance ranging from 3.89-23.13% were highlighted. Furthermore, Glyma04g05840, Glyma19g37820, Glyma14g07140 and Glyma19g39340 were predicted in the intervals of the stable loci and important QTL hotspots for leaf type traits by adopting Gene Ontology (GO) enrichment analysis. CONCLUSIONS Our findings of the QTLs and the putative genes will be beneficial to gain new insights into the genetic basis for soybean leaf type traits and may further accelerate the breeding process for reasonable leaf type soybean.
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Affiliation(s)
- Liang Wang
- The State Key Laboratory for Conservation and Utilization of Subtropical Agro-bioresources South China Agricultural University, Guangzhou, 510642 Guangdong People’s Republic of China
- The Key Laboratory of Plant Molecular Breeding of Guangdong Province, College of Agriculture, South China Agricultural University, Guangzhou, 510642 Guangdong People’s Republic of China
- The Guangdong Subcenter of the National Center for Soybean Improvement, College of Agriculture, South China Agricultural University, Guangzhou, 510642 Guangdong People’s Republic of China
| | - Yanbo Cheng
- The State Key Laboratory for Conservation and Utilization of Subtropical Agro-bioresources South China Agricultural University, Guangzhou, 510642 Guangdong People’s Republic of China
- The Key Laboratory of Plant Molecular Breeding of Guangdong Province, College of Agriculture, South China Agricultural University, Guangzhou, 510642 Guangdong People’s Republic of China
- The Guangdong Subcenter of the National Center for Soybean Improvement, College of Agriculture, South China Agricultural University, Guangzhou, 510642 Guangdong People’s Republic of China
| | - Qibin Ma
- The State Key Laboratory for Conservation and Utilization of Subtropical Agro-bioresources South China Agricultural University, Guangzhou, 510642 Guangdong People’s Republic of China
- The Key Laboratory of Plant Molecular Breeding of Guangdong Province, College of Agriculture, South China Agricultural University, Guangzhou, 510642 Guangdong People’s Republic of China
- The Guangdong Subcenter of the National Center for Soybean Improvement, College of Agriculture, South China Agricultural University, Guangzhou, 510642 Guangdong People’s Republic of China
| | - Yinghui Mu
- The State Key Laboratory for Conservation and Utilization of Subtropical Agro-bioresources South China Agricultural University, Guangzhou, 510642 Guangdong People’s Republic of China
- The Key Laboratory of Plant Molecular Breeding of Guangdong Province, College of Agriculture, South China Agricultural University, Guangzhou, 510642 Guangdong People’s Republic of China
- The Guangdong Subcenter of the National Center for Soybean Improvement, College of Agriculture, South China Agricultural University, Guangzhou, 510642 Guangdong People’s Republic of China
| | - Zhifeng Huang
- The State Key Laboratory for Conservation and Utilization of Subtropical Agro-bioresources South China Agricultural University, Guangzhou, 510642 Guangdong People’s Republic of China
- The Key Laboratory of Plant Molecular Breeding of Guangdong Province, College of Agriculture, South China Agricultural University, Guangzhou, 510642 Guangdong People’s Republic of China
- The Guangdong Subcenter of the National Center for Soybean Improvement, College of Agriculture, South China Agricultural University, Guangzhou, 510642 Guangdong People’s Republic of China
| | - Qiuju Xia
- Beijing Genomics Institute (BGI)-Shenzhen, Shenzhen, 518086 People’s Republic of China
| | - Gengyun Zhang
- Beijing Genomics Institute (BGI)-Shenzhen, Shenzhen, 518086 People’s Republic of China
| | - Hai Nian
- The State Key Laboratory for Conservation and Utilization of Subtropical Agro-bioresources South China Agricultural University, Guangzhou, 510642 Guangdong People’s Republic of China
- The Key Laboratory of Plant Molecular Breeding of Guangdong Province, College of Agriculture, South China Agricultural University, Guangzhou, 510642 Guangdong People’s Republic of China
- The Guangdong Subcenter of the National Center for Soybean Improvement, College of Agriculture, South China Agricultural University, Guangzhou, 510642 Guangdong People’s Republic of China
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Genome-wide dissection of segregation distortion using multiple inter-subspecific crosses in rice. SCIENCE CHINA-LIFE SCIENCES 2019; 62:507-516. [DOI: 10.1007/s11427-018-9452-8] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/01/2018] [Accepted: 10/28/2018] [Indexed: 11/27/2022]
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12
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Wu B, Hu W, Ayaad M, Liu H, Xing Y. Intragenic recombination between two non-functional semi-dwarf 1 alleles produced a functional SD1 allele in a tall recombinant inbred line in rice. PLoS One 2017; 12:e0190116. [PMID: 29281725 PMCID: PMC5744974 DOI: 10.1371/journal.pone.0190116] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2017] [Accepted: 12/10/2017] [Indexed: 02/07/2023] Open
Abstract
Intragenic recombination is one of the most important sources of genetic variability. In our previous study, RI92 a tall line (160 cm of plant height) was observed in the cross progeny between two semi-dwarf indica cultivars Zhenshan 97 and Minghui 63. Genome-wide genotyping and sequencing indicated that the genome constitution of RI92 was completely from both parents. Bulk segregant analysis in a BC3F2 population revealed that “green revolution gene” semi-dwarf 1 (sd1) was most likely the gene controlling the tall plant height in RI92. Sequencing analysis of SD1 revealed that an intragenic recombination occurred between two parental non-functional sd1 alleles and generated a functional SD1 in RI92. Four-fold high recombination rate in SD1 located bins to the genome-wide average was observed in two RIL populations, indicating recombination hotspot in the SD1 region. Intragenic recombination creates new alleles in the progeny distinct from parental alleles and diversifies natural variation.
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Affiliation(s)
- Bi Wu
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China
| | - Wei Hu
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China
| | - Mohammed Ayaad
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China
- Nuclear Research Center, Egyptian Atomic Energy Authority, Cairo, Egypt
| | - Hongbo Liu
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China
| | - Yongzhong Xing
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China
- * E-mail:
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13
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Liu N, Li M, Hu X, Ma Q, Mu Y, Tan Z, Xia Q, Zhang G, Nian H. Construction of high-density genetic map and QTL mapping of yield-related and two quality traits in soybean RILs population by RAD-sequencing. BMC Genomics 2017; 18:466. [PMID: 28629322 PMCID: PMC5477377 DOI: 10.1186/s12864-017-3854-8] [Citation(s) in RCA: 25] [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: 03/03/2017] [Accepted: 06/09/2017] [Indexed: 02/07/2023] Open
Abstract
BACKGROUND One of the overarching goals of soybean breeding is to develop lines that combine increased yield with improved quality characteristics. High-density-marker QTL mapping can serve as an effective strategy to identify novel genomic information to facilitate crop improvement. In this study, we genotyped a recombinant inbred line (RIL) population (Zhonghuang 24 × Huaxia 3) using a restriction-site associated DNA sequencing (RAD-seq) approach. A high-density soybean genetic map was constructed and used to identify several QTLs that were shown to influence six yield-related and two quality traits. RESULTS A total of 47,472 single-nucleotide polymorphisms (SNPs) were detected for the RILs that were integrated into 2639 recombination bin units, with an average distance of 1.00 cM between adjacent markers. Forty seven QTLs for yield-related traits and 13 QTLs for grain quality traits were found to be distributed on 16 chromosomes in the 2 year studies. Among them, 18 QTLs were stable, and were identified in both analyses. Twenty six QTLs were identified for the first time, with a single QTL (qNN19a) in a 56 kb region explaining 32.56% of phenotypic variation, and an additional 10 of these were novel, stable QTLs. Moreover, 8 QTL hotpots on four different chromosomes were identified for the correlated traits. CONCLUSIONS With RAD-sequencing, some novel QTLs and important QTL clusters for both yield-related and quality traits were identified based on a new, high-density bin linkage map. Three predicted genes were selected as candidates that likely have a direct or indirect influence on both yield and quality in soybean. Our findings will be helpful for understanding common genetic control mechanisms of co-localized traits and to select cultivars for further analysis to predictably modulate soybean yield and quality simultaneously.
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Affiliation(s)
- Nianxi Liu
- The State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, South China Agricultural University, Guangzhou, 510642 People’s Republic of China
- The Key Laboratory of Plant Molecular Breeding, South China Agricultural University, Guangzhou, 510642 People’s Republic of China
- The Guangdong Subcenter of the National Center for Soybean Improvement, College of Agriculture, South China Agricultural University, Guangzhou, 510642 People’s Republic of China
- Joint Laboratory of Plant Breeding, South China Agricultural University-ShanDong Shofine Seed Technology Co. Ltd, Guangzhou, 510642 People’s Republic of China
| | - Mu Li
- The State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, South China Agricultural University, Guangzhou, 510642 People’s Republic of China
- The Key Laboratory of Plant Molecular Breeding, South China Agricultural University, Guangzhou, 510642 People’s Republic of China
- The Guangdong Subcenter of the National Center for Soybean Improvement, College of Agriculture, South China Agricultural University, Guangzhou, 510642 People’s Republic of China
- Joint Laboratory of Plant Breeding, South China Agricultural University-ShanDong Shofine Seed Technology Co. Ltd, Guangzhou, 510642 People’s Republic of China
| | - Xiangbao Hu
- The State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, South China Agricultural University, Guangzhou, 510642 People’s Republic of China
- The Key Laboratory of Plant Molecular Breeding, South China Agricultural University, Guangzhou, 510642 People’s Republic of China
- The Guangdong Subcenter of the National Center for Soybean Improvement, College of Agriculture, South China Agricultural University, Guangzhou, 510642 People’s Republic of China
- Joint Laboratory of Plant Breeding, South China Agricultural University-ShanDong Shofine Seed Technology Co. Ltd, Guangzhou, 510642 People’s Republic of China
| | - Qibin Ma
- The State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, South China Agricultural University, Guangzhou, 510642 People’s Republic of China
- The Key Laboratory of Plant Molecular Breeding, South China Agricultural University, Guangzhou, 510642 People’s Republic of China
- The Guangdong Subcenter of the National Center for Soybean Improvement, College of Agriculture, South China Agricultural University, Guangzhou, 510642 People’s Republic of China
- Joint Laboratory of Plant Breeding, South China Agricultural University-ShanDong Shofine Seed Technology Co. Ltd, Guangzhou, 510642 People’s Republic of China
| | - Yinghui Mu
- The State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, South China Agricultural University, Guangzhou, 510642 People’s Republic of China
- The Key Laboratory of Plant Molecular Breeding, South China Agricultural University, Guangzhou, 510642 People’s Republic of China
- The Guangdong Subcenter of the National Center for Soybean Improvement, College of Agriculture, South China Agricultural University, Guangzhou, 510642 People’s Republic of China
- Joint Laboratory of Plant Breeding, South China Agricultural University-ShanDong Shofine Seed Technology Co. Ltd, Guangzhou, 510642 People’s Republic of China
| | - Zhiyuan Tan
- The State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, South China Agricultural University, Guangzhou, 510642 People’s Republic of China
- The Key Laboratory of Plant Molecular Breeding, South China Agricultural University, Guangzhou, 510642 People’s Republic of China
- The Guangdong Subcenter of the National Center for Soybean Improvement, College of Agriculture, South China Agricultural University, Guangzhou, 510642 People’s Republic of China
- Joint Laboratory of Plant Breeding, South China Agricultural University-ShanDong Shofine Seed Technology Co. Ltd, Guangzhou, 510642 People’s Republic of China
| | - Qiuju Xia
- Beijing Genome Institute (BGI), Shenzhen, 518083 People’s Republic of China
| | - Gengyun Zhang
- Beijing Genome Institute (BGI), Shenzhen, 518083 People’s Republic of China
| | - Hai Nian
- The State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, South China Agricultural University, Guangzhou, 510642 People’s Republic of China
- The Key Laboratory of Plant Molecular Breeding, South China Agricultural University, Guangzhou, 510642 People’s Republic of China
- The Guangdong Subcenter of the National Center for Soybean Improvement, College of Agriculture, South China Agricultural University, Guangzhou, 510642 People’s Republic of China
- Joint Laboratory of Plant Breeding, South China Agricultural University-ShanDong Shofine Seed Technology Co. Ltd, Guangzhou, 510642 People’s Republic of China
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14
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QTLs for heading date and plant height under multiple environments in rice. Genetica 2017; 145:67-77. [PMID: 28070759 DOI: 10.1007/s10709-016-9946-6] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2016] [Accepted: 12/22/2016] [Indexed: 10/20/2022]
Abstract
Both heading date and plant height are important traits related to grain yield in rice. In this study, a recombinant inbred lines (RILs) population was used to map quantitative trait loci (QTLs) for both traits under 3 long-day (LD) environments and 1 short-day (SD) environment. A total of eight QTLs for heading date and three QTLs for plant height were detected by composite interval mapping under LD conditions. Additional one QTL for heading date and three QTLs for plant height were identified by Two-QTL model under LD conditions. Among them, major QTLs qHd7.1, qHd7.2 and qHd8 for heading date, and qPh1 and qPh7.1 for plant height were commonly detected. qHd7.1 and qHd7.2 were mapped to small regions of less than 1 cM. Genome position comparison of previously cloned genes with QTLs detected in this study revealed that qHd5 and qPh3.1 were two novel QTLs. The alleles of these QTLs increasing trait values were dispersed in both parents, which well explained the transgressive segregation observed in this population. In addition, the interaction between qHd7.1 and qHd8 was detected under all LD conditions. Multiple-QTL model analysis revealed that all QTLs and their interactions explained over 80% of heading date variation and 50% of plant height variation. Two heading date QTLs were detected under SD condition. Of them, qHd10 were commonly identified under LD condition. The difference in QTL detection between LD and SD conditions indicated most heading date QTLs are sensitive to photoperiod. These findings will benefit breeding design for heading date and plant height in rice.
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15
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Gimhani DR, Gregorio GB, Kottearachchi NS, Samarasinghe WLG. SNP-based discovery of salinity-tolerant QTLs in a bi-parental population of rice (Oryza sativa). Mol Genet Genomics 2016; 291:2081-2099. [PMID: 27535768 DOI: 10.1007/s00438-016-1241-9] [Citation(s) in RCA: 31] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2015] [Accepted: 08/10/2016] [Indexed: 02/02/2023]
Abstract
Breeding for salt tolerance is the most promising approach to enhance the productivity of saline prone areas. However, polygenic inheritance of salt tolerance in rice acts as a bottleneck in conventional breeding for salt tolerance. Hence, we set our goals to construct a single nucleotide polymorphism (SNP)-based molecular map employing high-throughput SNP marker technology and to investigate salinity tolerant QTLs with closest flanking markers using an elite rice background. Seedling stage salinity responses were assessed in a population of 281 recombinant inbred lines (RILs) derived from the cross between At354 (salt tolerant) and Bg352 (salt susceptible), by 11 morpho-physiological indices under a hydroponic system. Selected extreme 94 RILs were genotyped using Illumina Infinium rice 6K SNP array and densely saturated molecular map spanning 1460.81 cM of the rice genome with an average interval of 1.29 cM between marker loci was constructed using 1135 polymorphic SNP markers. The results revealed 83 significant QTLs for 11 salt responsive traits explaining 12.5-46.7 % of phenotypic variation in respective traits. Of them, 72 QTLs responsible for 10 traits were co-localized together forming 14 QTL hotspots at 14 different genomic regions. The all QTL hotspots were flanked less than 1 Mb intervals and therefore the SNP loci associated with these QTL hotspots would be important in candidate gene discovery for salt tolerance.
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Affiliation(s)
- D R Gimhani
- Department of Biotechnology, Faculty of Agriculture and Plantation Management, Wayamba Univesity of Sri Lanka, Makandura, Gonawila (NWP), 60170, Sri Lanka.
| | - Glenn B Gregorio
- International Rice Research Institute, DAPO Box 7777, Metro Manila, Philippines
- East-West Seed Company (EWS), Km. 54 Cagayan Valley Road, Sampaloc, San Rafael, 3008, Bulacan, Philippines
| | - N S Kottearachchi
- Department of Biotechnology, Faculty of Agriculture and Plantation Management, Wayamba Univesity of Sri Lanka, Makandura, Gonawila (NWP), 60170, Sri Lanka
| | - W L G Samarasinghe
- Rice Research and Development Institute, Batalagoda, Ibbagamuwa, Sri Lanka
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Chen S, Wang WJ, Su J, Wang CY, Feng AQ, Yang JY, Zeng LX, Zhu XY. Rapid identification of rice blast resistance gene by specific length amplified fragment sequencing. BIOTECHNOL BIOTEC EQ 2016. [DOI: 10.1080/13102818.2016.1159528] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022] Open
Affiliation(s)
- Shen Chen
- Guangdong Provincial Key Laboratory of High Technology for Plant Protection, Guangdong Academy of Agricultural Sciences, Plant Protection Research Institute, Guangzhou, China
| | - Wen-juan Wang
- Guangdong Provincial Key Laboratory of High Technology for Plant Protection, Guangdong Academy of Agricultural Sciences, Plant Protection Research Institute, Guangzhou, China
| | - Jing Su
- Guangdong Provincial Key Laboratory of High Technology for Plant Protection, Guangdong Academy of Agricultural Sciences, Plant Protection Research Institute, Guangzhou, China
| | - Cong-ying Wang
- Guangdong Provincial Key Laboratory of High Technology for Plant Protection, Guangdong Academy of Agricultural Sciences, Plant Protection Research Institute, Guangzhou, China
| | - Ai-qing Feng
- Guangdong Provincial Key Laboratory of High Technology for Plant Protection, Guangdong Academy of Agricultural Sciences, Plant Protection Research Institute, Guangzhou, China
| | - Jian-yuan Yang
- Guangdong Provincial Key Laboratory of High Technology for Plant Protection, Guangdong Academy of Agricultural Sciences, Plant Protection Research Institute, Guangzhou, China
| | - Lie-xian Zeng
- Guangdong Provincial Key Laboratory of High Technology for Plant Protection, Guangdong Academy of Agricultural Sciences, Plant Protection Research Institute, Guangzhou, China
| | - Xiao-yuan Zhu
- Guangdong Provincial Key Laboratory of High Technology for Plant Protection, Guangdong Academy of Agricultural Sciences, Plant Protection Research Institute, Guangzhou, China
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Houel C, Chatbanyong R, Doligez A, Rienth M, Foria S, Luchaire N, Roux C, Adivèze A, Lopez G, Farnos M, Pellegrino A, This P, Romieu C, Torregrosa L. Identification of stable QTLs for vegetative and reproductive traits in the microvine (Vitis vinifera L.) using the 18 K Infinium chip. BMC PLANT BIOLOGY 2015; 15:205. [PMID: 26283631 PMCID: PMC4539925 DOI: 10.1186/s12870-015-0588-0] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/11/2015] [Accepted: 08/06/2015] [Indexed: 05/20/2023]
Abstract
BACKGROUND The increasing temperature associated with climate change impacts grapevine phenology and development with critical effects on grape yield and composition. Plant breeding has the potential to deliver new cultivars with stable yield and quality under warmer climate conditions, but this requires the identification of stable genetic determinants. This study tested the potentialities of the microvine to boost genetics in grapevine. A mapping population of 129 microvines derived from Picovine x Ugni Blanc flb, was genotyped with the Illumina® 18 K SNP (Single Nucleotide Polymorphism) chip. Forty-three vegetative and reproductive traits were phenotyped outdoors over four cropping cycles, and a subset of 22 traits over two cropping cycles in growth rooms with two contrasted temperatures, in order to map stable QTLs (Quantitative Trait Loci). RESULTS Ten stable QTLs for berry development and quality or leaf area were identified on the parental maps. A new major QTL explaining up to 44 % of total variance of berry weight was identified on chromosome 7 in Ugni Blanc flb, and co-localized with QTLs for seed number (up to 76 % total variance), major berry acids at green lag phase (up to 35 %), and other yield components (up to 25 %). In addition, a minor QTL for leaf area was found on chromosome 4 of the same parent. In contrast, only minor QTLs for berry acidity and leaf area could be found as moderately stable in Picovine. None of the transporters recently identified as mutated in low acidity apples or Cucurbits were included in the several hundreds of candidate genes underlying the above berry QTLs, which could be reduced to a few dozen candidate genes when a priori pertinent biological functions and organ specific expression were considered. CONCLUSIONS This study combining the use of microvine and a high throughput genotyping technology was innovative for grapevine genetics. It allowed the identification of 10 stable QTLs, including the first berry acidity QTLs reported so far in a Vitis vinifera intra-specific cross. Robustness of a set of QTLs was assessed with respect to temperature variation.
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Affiliation(s)
- Cléa Houel
- Montpellier SupAgro, UMR AGAP, F-34060, Montpellier, France.
- INRA, UMR AGAP, F-34060, Montpellier, France.
| | - Ratthaphon Chatbanyong
- Montpellier SupAgro, UMR AGAP, F-34060, Montpellier, France.
- INRA, UMR AGAP, F-34060, Montpellier, France.
| | | | - Markus Rienth
- Montpellier SupAgro, UMR AGAP, F-34060, Montpellier, France.
- INRA, UMR AGAP, F-34060, Montpellier, France.
- Fondation Jean Poupelain, 30 rue Gâte Chien, F-16100, Javrezac, France.
- Changins, Haute Ecole de Viticulture et Oenologie, 1260, Nyon, Switzerland.
| | - Serena Foria
- Dipartimento di Scienze Agrarie e Ambientali, University of Udine, via delle Scienze 208, I-33100, Udine, Italy.
| | - Nathalie Luchaire
- Montpellier SupAgro, UMR AGAP, F-34060, Montpellier, France.
- Montpellier SupAgro, UMR LEPSE, F- 34060, Montpellier, France.
| | | | | | - Gilbert Lopez
- Montpellier SupAgro, UMR AGAP, F-34060, Montpellier, France.
| | - Marc Farnos
- INRA, UMR AGAP, F-34060, Montpellier, France.
| | - Anne Pellegrino
- Montpellier SupAgro, UMR LEPSE, F- 34060, Montpellier, France.
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Yu H, Xie W, Li J, Zhou F, Zhang Q. A whole-genome SNP array (RICE6K) for genomic breeding in rice. PLANT BIOTECHNOLOGY JOURNAL 2014; 12:28-37. [PMID: 24034357 DOI: 10.1111/pbi.12113] [Citation(s) in RCA: 74] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/26/2013] [Revised: 07/25/2013] [Accepted: 07/30/2013] [Indexed: 05/19/2023]
Abstract
The advances in genotyping technology provide an opportunity to use genomic tools in crop breeding. As compared to field selections performed in conventional breeding programmes, genomics-based genotype screen can potentially reduce number of breeding cycles and more precisely integrate target genes for particular traits into an ideal genetic background. We developed a whole-genome single nucleotide polymorphism (SNP) array, RICE6K, based on Infinium technology, using representative SNPs selected from more than four million SNPs identified from resequencing data of more than 500 rice landraces. RICE6K contains 5102 SNP and insertion-deletion (InDel) markers, about 4500 of which were of high quality in the tested rice lines producing highly repeatable results. Forty-five functional markers that are located inside 28 characterized genes of important traits can be detected using RICE6K. The SNP markers are evenly distributed on the 12 chromosomes of rice with the average density of 12 SNPs per 1 Mb and can provide information for polymorphisms between indica and japonica subspecies as well as varieties within indica and japonica groups. Application tests of RICE6K showed that the array is suitable for rice germplasm fingerprinting, genotyping bulked segregating pools, seed authenticity check and genetic background selection. These results suggest that RICE6K provides an efficient and reliable genotyping tool for rice genomic breeding.
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Affiliation(s)
- Huihui Yu
- Life Science and Technology Center, China National Seed Group Co., Ltd, Wuhan, China
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