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Abstract
Most of the breeding targets are quantitative traits. In exploring the quantitative trait locus (QTL) system of a trait, linkage mapping was established using sparse polymerase chain reaction (PCR) markers. With the genome-wide sequencing technology advanced, genome-wide association study (GWAS) was developed for natural (germplasm) populations using dense genomic markers, which facilitates the identification of the complete QTL system with their multiple alleles on genomic locations. GWAS makes use of the linkage disequilibrium (LD) due to historical saturate recombination and high-density genomic markers to detect QTLs through statistical test for the association between molecular markers and phenotypes. However, due to inbreeding and mixture of source populations, the germplasm population often has complex and unknown structure, which leads to false positives/negatives in GWAS. Various GWAS methods have been proposed to reduce false positives/negatives, including those of the general linear model and the mixed linear model, which focused mainly on finding a handful of major QTLs under single-locus model for major gene cloning and could not detect directly the multiple alleles using bi-allelic single-nucleotide polymorphism (SNP) marker. As a relatively thorough detection of QTLs with their multiple alleles is required for germplasm population, the restricted two-stage multi-locus multi-allele GWAS (RTM-GWAS) procedure was proposed for identifying the QTL system with varying multiple alleles. From the RTM-GWAS results, a QTL-allele matrix is constructed as a compact form of the population genetic constitution, which can be further used for crop genetic and breeding studies, including major gene mining, population evolution, and breeding by genetic design.
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Ouyang W, Chen L, Ma J, Liu X, Chen H, Yang H, Guo W, Shan Z, Yang Z, Chen S, Zhan Y, Zhang H, Cao D, Zhou X. Identification of Quantitative Trait Locus and Candidate Genes for Drought Tolerance in a Soybean Recombinant Inbred Line Population. Int J Mol Sci 2022; 23:10828. [PMID: 36142739 PMCID: PMC9504156 DOI: 10.3390/ijms231810828] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2022] [Revised: 09/09/2022] [Accepted: 09/10/2022] [Indexed: 12/18/2022] Open
Abstract
With global warming and regional decreases in precipitation, drought has become a problem worldwide. As the number of arid regions in the world is increasing, drought has become a major factor leading to significant crop yield reductions and food crises. Soybean is a crop that is relatively sensitive to drought. It is also a crop that requires more water during growth and development. The aim of this study was to identify the quantitative trait locus (QTL) that affects drought tolerance in soybean by using a recombinant inbred line (RIL) population from a cross between the drought-tolerant cultivar 'Jindou21' and the drought-sensitive cultivar 'Zhongdou33'. Nine agronomic and physiological traits were identified under drought and well-watered conditions. Genetic maps were constructed with 923,420 polymorphic single nucleotide polymorphism (SNP) markers distributed on 20 chromosomes at an average genetic distance of 0.57 centimorgan (cM) between markers. A total of five QTLs with a logarithm of odds (LOD) value of 4.035-8.681 were identified on five chromosomes. Under well-watered conditions and drought-stress conditions, one QTL related to the main stem node number was located on chromosome 16, accounting for 17.177% of the phenotypic variation. Nine candidate genes for drought resistance were screened from this QTL, namely Glyma.16G036700, Glyma.16G036400, Glyma.16G036600, Glyma.16G036800, Glyma.13G312700, Glyma.13G312800, Glyma.16G042900, Glyma.16G043200, and Glyma.15G100700. These genes were annotated as NAC transport factor, GATA transport factor, and BTB/POZ-MATH proteins. This result can be used for molecular marker-assisted selection and provide a reference for breeding for drought tolerance in soybean.
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Affiliation(s)
- Wenqi Ouyang
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture and Rural Affairs, Oil Crops Research Institute of Chinese Academy of Agricultural Sciences, Wuhan 430062, China
| | - Limiao Chen
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture and Rural Affairs, Oil Crops Research Institute of Chinese Academy of Agricultural Sciences, Wuhan 430062, China
| | - Junkui Ma
- The Industrial Crop Institute, Shanxi Academy of Agricultural Sciences, Taiyuan 030006, China
| | - Xiaorong Liu
- The Industrial Crop Institute, Shanxi Academy of Agricultural Sciences, Taiyuan 030006, China
| | - Haifeng Chen
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture and Rural Affairs, Oil Crops Research Institute of Chinese Academy of Agricultural Sciences, Wuhan 430062, China
| | - Hongli Yang
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture and Rural Affairs, Oil Crops Research Institute of Chinese Academy of Agricultural Sciences, Wuhan 430062, China
| | - Wei Guo
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture and Rural Affairs, Oil Crops Research Institute of Chinese Academy of Agricultural Sciences, Wuhan 430062, China
| | - Zhihui Shan
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture and Rural Affairs, Oil Crops Research Institute of Chinese Academy of Agricultural Sciences, Wuhan 430062, China
| | - Zhonglu Yang
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture and Rural Affairs, Oil Crops Research Institute of Chinese Academy of Agricultural Sciences, Wuhan 430062, China
| | - Shuilian Chen
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture and Rural Affairs, Oil Crops Research Institute of Chinese Academy of Agricultural Sciences, Wuhan 430062, China
| | - Yong Zhan
- Crop Research Institute, Xinjiang Academy of Agricultural and Reclamation Science, Key Laboratory of Cereal Quality Research and Genetic Improvement, Xinjiang Production and Construction Crops, Shihezi 832000, China
| | - Hengbin Zhang
- Crop Research Institute, Xinjiang Academy of Agricultural and Reclamation Science, Key Laboratory of Cereal Quality Research and Genetic Improvement, Xinjiang Production and Construction Crops, Shihezi 832000, China
| | - Dong Cao
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture and Rural Affairs, Oil Crops Research Institute of Chinese Academy of Agricultural Sciences, Wuhan 430062, China
| | - Xinan Zhou
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture and Rural Affairs, Oil Crops Research Institute of Chinese Academy of Agricultural Sciences, Wuhan 430062, China
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Feng W, Fu L, Fu M, Sang Z, Wang Y, Wang L, Ren H, Du W, Hao X, Sun L, Zhang J, Wang W, Xing G, He J, Gai J. Transgressive Potential Prediction and Optimal Cross Design of Seed Protein Content in the Northeast China Soybean Population Based on Full Exploration of the QTL-Allele System. FRONTIERS IN PLANT SCIENCE 2022; 13:896549. [PMID: 35903228 PMCID: PMC9317943 DOI: 10.3389/fpls.2022.896549] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/15/2022] [Accepted: 06/09/2022] [Indexed: 06/12/2023]
Abstract
Northeast China is a major soybean production region in China. A representative sample of the Northeast China soybean germplasm population (NECSGP) composed of 361 accessions was evaluated for their seed protein content (SPC) in Tieling, Northeast China. This SPC varied greatly, with a mean SPC of 40.77%, ranging from 36.60 to 46.07%, but it was lower than that of the Chinese soybean landrace population (43.10%, ranging from 37.51 to 50.46%). The SPC increased slightly from 40.32-40.97% in the old maturity groups (MG, MGIII + II + I) to 40.93-41.58% in the new MGs (MG0 + 00 + 000). The restricted two-stage multi-locus genome-wide association study (RTM-GWAS) with 15,501 SNP linkage-disequilibrium block (SNPLDB) markers identified 73 SPC quantitative trait loci (QTLs) with 273 alleles, explaining 71.70% of the phenotypic variation, wherein 28 QTLs were new ones. The evolutionary changes of QTL-allele structures from old MGs to new MGs were analyzed, and 97.79% of the alleles in new MGs were inherited from the old MGs and 2.21% were new. The small amount of new positive allele emergence and possible recombination between alleles might explain the slight SPC increase in the new MGs. The prediction of recombination potentials in the SPC of all the possible crosses indicated that the mean of SPC overall crosses was 43.29% (+2.52%) and the maximum was 50.00% (+9.23%) in the SPC, and the maximum transgressive potential was 3.93%, suggesting that SPC breeding potentials do exist in the NECSGP. A total of 120 candidate genes were annotated and functionally classified into 13 categories, indicating that SPC is a complex trait conferred by a gene network.
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Affiliation(s)
- Weidan Feng
- Soybean Research Institute/MARA National Center for Soybean Improvement/MARA Key Laboratory of Biology and Genetic Improvement of Soybean (General), Nanjing Agricultural University, Nanjing, China
- State Key Laboratory for Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, China
| | - Lianshun Fu
- Tieling Academy of Agricultural Sciences, Tieling, China
| | - Mengmeng Fu
- Soybean Research Institute/MARA National Center for Soybean Improvement/MARA Key Laboratory of Biology and Genetic Improvement of Soybean (General), Nanjing Agricultural University, Nanjing, China
| | - Ziqian Sang
- Soybean Research Institute/MARA National Center for Soybean Improvement/MARA Key Laboratory of Biology and Genetic Improvement of Soybean (General), Nanjing Agricultural University, Nanjing, China
| | - Yanping Wang
- Mudanjiang Research and Development Center for Soybean/Mudanjiang Experiment Station of the National Center for Soybean Improvement, Mudanjiang Branch of Heilongjiang Academy of Agricultural Sciences, Mudanjiang, China
| | - Lei Wang
- Soybean Research Institute/MARA National Center for Soybean Improvement/MARA Key Laboratory of Biology and Genetic Improvement of Soybean (General), Nanjing Agricultural University, Nanjing, China
- State Key Laboratory for Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, China
| | - Haixiang Ren
- Mudanjiang Research and Development Center for Soybean/Mudanjiang Experiment Station of the National Center for Soybean Improvement, Mudanjiang Branch of Heilongjiang Academy of Agricultural Sciences, Mudanjiang, China
| | - Weiguang Du
- Mudanjiang Research and Development Center for Soybean/Mudanjiang Experiment Station of the National Center for Soybean Improvement, Mudanjiang Branch of Heilongjiang Academy of Agricultural Sciences, Mudanjiang, China
| | - Xiaoshuai Hao
- Soybean Research Institute/MARA National Center for Soybean Improvement/MARA Key Laboratory of Biology and Genetic Improvement of Soybean (General), Nanjing Agricultural University, Nanjing, China
- State Key Laboratory for Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, China
| | - Lei Sun
- Soybean Research Institute/MARA National Center for Soybean Improvement/MARA Key Laboratory of Biology and Genetic Improvement of Soybean (General), Nanjing Agricultural University, Nanjing, China
- State Key Laboratory for Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, China
| | - Jiaoping Zhang
- Soybean Research Institute/MARA National Center for Soybean Improvement/MARA Key Laboratory of Biology and Genetic Improvement of Soybean (General), Nanjing Agricultural University, Nanjing, China
- State Key Laboratory for Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, China
| | - Wubin Wang
- Soybean Research Institute/MARA National Center for Soybean Improvement/MARA Key Laboratory of Biology and Genetic Improvement of Soybean (General), Nanjing Agricultural University, Nanjing, China
- State Key Laboratory for Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, China
| | - Guangnan Xing
- Soybean Research Institute/MARA National Center for Soybean Improvement/MARA Key Laboratory of Biology and Genetic Improvement of Soybean (General), Nanjing Agricultural University, Nanjing, China
- State Key Laboratory for Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, China
| | - Jianbo He
- Soybean Research Institute/MARA National Center for Soybean Improvement/MARA Key Laboratory of Biology and Genetic Improvement of Soybean (General), Nanjing Agricultural University, Nanjing, China
- State Key Laboratory for Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, China
| | - Junyi Gai
- Soybean Research Institute/MARA National Center for Soybean Improvement/MARA Key Laboratory of Biology and Genetic Improvement of Soybean (General), Nanjing Agricultural University, Nanjing, China
- State Key Laboratory for Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, China
- Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing, China
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Liu X, Li C, Cao J, Zhang X, Wang C, He J, Xing G, Wang W, Zhao J, Gai J. Growth period QTL-allele constitution of global soybeans and its differential evolution changes in geographic adaptation versus maturity group extension. THE PLANT JOURNAL : FOR CELL AND MOLECULAR BIOLOGY 2021; 108:1624-1643. [PMID: 34618996 DOI: 10.1111/tpj.15531] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/11/2021] [Accepted: 09/27/2021] [Indexed: 06/13/2023]
Abstract
Soybean (Glycine max (L.) Merr.) has been disseminated globally as a photoperiod/temperature-sensitive crop with extremely diverse days to flowering (DTF) and days to maturity (DTM) values. A population with 371 global varieties covering 13 geographic regions and 13 maturity groups (MGs) was analyzed for its DTF and DTM QTL-allele constitution using restricted two-stage multi-locus genome-wide association study (RTM-GWAS). Genotypes with 20 701 genome-wide SNPLDBs (single-nucleotide polymorphism linkage disequilibrium blocks) containing 55 404 haplotypes were observed, and 52 DTF QTLs and 59 DTM QTLs (including 29 and 21 new ones) with 241 and 246 alleles (two to 13 per locus) were detected, explaining 84.8% and 74.4% of the phenotypic variance, respectively. The QTL-allele matrix characterized with all QTL-allele information of each variety in the global population was established and subsequently separated into geographic and MG set submatrices. Direct comparisons among them revealed that the genetic adaptation from the origin to geographic subpopulations was characterized by new allele/new locus emergence (mutation) but little allele exclusion (selection), while that from the primary MG set to emerged early and late MG sets was characterized by allele exclusion without allele emergence. The evolutionary changes involved mainly 72 DTF and 71 DTM alleles on 28 respective loci, 10-12 loci each with three to six alleles being most active. Further recombination potential for faster maturation (12-21 days) or slower maturation (14-56 days) supported allele convergence (recombination) as a constant genetic factor in addition to migration (inheritance). From the QTLs, 44 DTF and 36 DTM candidate genes were annotated and grouped respectively into nine biological processes, indicating multi-functional DTF/DTM genes are involved in a complex gene network. In summary, we identified QTL-alleles relatively thoroughly using RTM-GWAS for direct matrix comparisons and subsequent analysis.
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Affiliation(s)
- Xueqin Liu
- Soybean Research Institute & MOA National Center for Soybean Improvement & MOA Key Laboratory of Biology and Genetic Improvement of Soybean (General) & State Key Laboratory for Crop Genetics and Germplasm Enhancement & Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing, 210095, China
- Department of Agronomy and Horticulture, Jiangsu Vocational College of Agriculture and Forestry, Jurong, 212400, China
| | - Chunyan Li
- Soybean Research Institute & MOA National Center for Soybean Improvement & MOA Key Laboratory of Biology and Genetic Improvement of Soybean (General) & State Key Laboratory for Crop Genetics and Germplasm Enhancement & Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing, 210095, China
- Shengfeng Experiment station, Shengfeng Seed Company Limited, Jining, 272100, China
| | - Jiqiu Cao
- Shengfeng Experiment station, Shengfeng Seed Company Limited, Jining, 272100, China
| | - Xiaoyan Zhang
- Soybean Research Institute & MOA National Center for Soybean Improvement & MOA Key Laboratory of Biology and Genetic Improvement of Soybean (General) & State Key Laboratory for Crop Genetics and Germplasm Enhancement & Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing, 210095, China
- Shengfeng Experiment station, Shengfeng Seed Company Limited, Jining, 272100, China
| | - Can Wang
- Soybean Research Institute & MOA National Center for Soybean Improvement & MOA Key Laboratory of Biology and Genetic Improvement of Soybean (General) & State Key Laboratory for Crop Genetics and Germplasm Enhancement & Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing, 210095, China
| | - Jianbo He
- Soybean Research Institute & MOA National Center for Soybean Improvement & MOA Key Laboratory of Biology and Genetic Improvement of Soybean (General) & State Key Laboratory for Crop Genetics and Germplasm Enhancement & Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing, 210095, China
| | - Guangnan Xing
- Soybean Research Institute & MOA National Center for Soybean Improvement & MOA Key Laboratory of Biology and Genetic Improvement of Soybean (General) & State Key Laboratory for Crop Genetics and Germplasm Enhancement & Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing, 210095, China
| | - Wubin Wang
- Soybean Research Institute & MOA National Center for Soybean Improvement & MOA Key Laboratory of Biology and Genetic Improvement of Soybean (General) & State Key Laboratory for Crop Genetics and Germplasm Enhancement & Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing, 210095, China
| | - Jinming Zhao
- Soybean Research Institute & MOA National Center for Soybean Improvement & MOA Key Laboratory of Biology and Genetic Improvement of Soybean (General) & State Key Laboratory for Crop Genetics and Germplasm Enhancement & Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing, 210095, China
| | - Junyi Gai
- Soybean Research Institute & MOA National Center for Soybean Improvement & MOA Key Laboratory of Biology and Genetic Improvement of Soybean (General) & State Key Laboratory for Crop Genetics and Germplasm Enhancement & Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing, 210095, China
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