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Sun C, Zhang Z, Liu M, Ceretta S, Zhang S, Guo B, Li Y, Liu Z, Gu Y, Ao X, Qiu L. Comparison of grain traits and genetic diversity between Chinese and Uruguayan soybeans ( Glycine max L.). FRONTIERS IN PLANT SCIENCE 2024; 15:1435881. [PMID: 39114471 PMCID: PMC11303235 DOI: 10.3389/fpls.2024.1435881] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/21/2024] [Accepted: 07/09/2024] [Indexed: 08/10/2024]
Abstract
Soybeans (Glycine max L.), originating in China, were introduced to South America in the late 19th century after passing through North America. South America is now a major soybean-producing region, accounting for approximately 40% of the global soybean production. Crops like soybeans gradually adapt to the local climate and human-selected conditions, resulting in beneficial variations during cultivation in different regions. Comparing the phenotypic and genetic variations in soybeans across different regions is crucial to determining the variations that may enhance soybean productivity. This study identified seed-related traits and conducted a genetic diversity analysis using 46 breeding soybean varieties from China and Uruguay. Compared to the Chinese soybean germplasm, the Uruguayan equivalent had a lower 100-grain weight, higher oil content, lower protein content, and higher soluble sugar content. Using ZDX1 gene chips, genetic typing was performed on the 46 breeding varieties. Cluster analysis based on SNP sites revealed significant differences in the genetic basis of Sino-Uruguayan soybean germplasm. Selection analysis, including nucleotide polymorphism (π) and fixation indexes (Fst), identified several genomic regions under selection between Sino-Uruguayan soybean germplasm. The selected intervals significantly enriched gene ontology (GO) terms related to protein metabolism. Additionally, differentiation occurred in genes associated with the oil content, seed weight, and cyst nematodes between Sino-Uruguayan soybean germplasm, such as GmbZIP123 and GmSSS1. These findings highlight the differences in seed-related phenotypes between Sino-Uruguay soybean germplasm and provide genomic-level insights into the mechanisms behind phenotypic differences, offering valuable references for understanding soybean evolution and molecular breeding.
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Affiliation(s)
- Chang Sun
- College of Agronomy, Shenyang Agricultural University, Shenyang, China
| | - Zhihao Zhang
- The National Key Facility for Crop Gene Resources and Genetic Improvement (NFCRI)/State Key Laboratory of Crop Gene Resources and Breeding/Key Laboratory of Crop Gene Resource and Germplasm Enhancement (MOA)/Key Laboratory of Grain Crop Genetic Resources Evaluation and Utilization, Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, China
- Key Laboratory of Soybean Biology in Chinese Ministry of Education (Key Laboratory of Soybean Biology and Breeding/Genetics of Chinese Agriculture Ministry), Northeast Agricultural University, Harbin, China
| | - Meiling Liu
- College of Agronomy, Shenyang Agricultural University, Shenyang, China
| | - Sergio Ceretta
- National Agricultural Research Institute (INIA), Soybean Breeding Program, Colonia, Uruguay
| | - Shengrui Zhang
- The National Engineering Research Center for Crop Molecular Breeding, Ministry of Agriculture and Rural Affairs (MARA) Key Laboratory of Soybean Biology (Beijing), Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Bingfu Guo
- Nanchang Branch of the National Center of Oilcrops Improvement, Jiangxi Province Key Laboratory for the Genetic Improvement of Oilcrops, Institute of Crops, Jiangxi Academy of Agricultural Sciences, Nanchang, China
| | - Yinghui Li
- The National Key Facility for Crop Gene Resources and Genetic Improvement (NFCRI)/State Key Laboratory of Crop Gene Resources and Breeding/Key Laboratory of Crop Gene Resource and Germplasm Enhancement (MOA)/Key Laboratory of Grain Crop Genetic Resources Evaluation and Utilization, Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Zhangxiong Liu
- The National Key Facility for Crop Gene Resources and Genetic Improvement (NFCRI)/State Key Laboratory of Crop Gene Resources and Breeding/Key Laboratory of Crop Gene Resource and Germplasm Enhancement (MOA)/Key Laboratory of Grain Crop Genetic Resources Evaluation and Utilization, Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Yongzhe Gu
- The National Key Facility for Crop Gene Resources and Genetic Improvement (NFCRI)/State Key Laboratory of Crop Gene Resources and Breeding/Key Laboratory of Crop Gene Resource and Germplasm Enhancement (MOA)/Key Laboratory of Grain Crop Genetic Resources Evaluation and Utilization, Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Xue Ao
- College of Agronomy, Shenyang Agricultural University, Shenyang, China
| | - Lijuan Qiu
- The National Key Facility for Crop Gene Resources and Genetic Improvement (NFCRI)/State Key Laboratory of Crop Gene Resources and Breeding/Key Laboratory of Crop Gene Resource and Germplasm Enhancement (MOA)/Key Laboratory of Grain Crop Genetic Resources Evaluation and Utilization, Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, China
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Wang J, Yang Q, Chen Y, Liu K, Zhang Z, Xiong Y, Yu H, Yu Y, Wang J, Song J, Qiu L. QTL mapping and genomic selection of stem and branch diameter in soybean ( Glycine max L.). FRONTIERS IN PLANT SCIENCE 2024; 15:1388365. [PMID: 38882575 PMCID: PMC11176531 DOI: 10.3389/fpls.2024.1388365] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/19/2024] [Accepted: 05/03/2024] [Indexed: 06/18/2024]
Abstract
Introduction Soybean stem diameter (SD) and branch diameter (BD) are closely related traits, and genetic clarification of SD and BD is crucial for soybean breeding. Methods SD and BD were genetically analyzed by a population of 363 RIL derived from the cross between Zhongdou41 (ZD41) and ZYD02878 using restricted two-stage multi-locus genome-wide association, inclusive composite interval mapping, and three-variance component multi-locus random SNP effect mixed linear modeling. Then candidate genes of major QTLs were selected and genetic selection model of SD and BD were constructed respectively. Results and discussion The results showed that SD and BD were significantly correlated (r = 0.74, P < 0.001). A total of 93 and 84 unique quantitative trait loci (QTL) were detected for SD and BD, respectively by three different methods. There were two and ten major QTLs for SD and BD, respectively, with phenotypic variance explained (PVE) by more than 10%. Within these loci, seven genes involved in the regulation of phytohormones (IAA and GA) and cell proliferation and showing extensive expression of shoot apical meristematic genes were selected as candidate genes. Genomic selection (GS) analysis showed that the trait-associated markers identified in this study reached 0.47-0.73 in terms of prediction accuracy, which was enhanced by 6.56-23.69% compared with genome-wide markers. These results clarify the genetic basis of SD and BD, which laid solid foundation in regulation gene cloning, and GS models constructed could be potentially applied in future breeding programs.
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Affiliation(s)
- Jing Wang
- 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
- The Shennong Laboratory, Zhengzhou, Henan, China
| | - Qichao Yang
- 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
- The Shennong Laboratory, Zhengzhou, Henan, China
| | - Yijie Chen
- 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
- The Shennong Laboratory, Zhengzhou, Henan, China
| | - Kanglin Liu
- 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
| | - Zhiqing Zhang
- 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
| | - Yajun Xiong
- 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
| | - Huan Yu
- 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
| | - Yingdong Yu
- 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
| | - Jun Wang
- 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
- The Shennong Laboratory, Zhengzhou, Henan, China
| | - Jian Song
- 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
| | - Lijuan Qiu
- State Key Laboratory of Crop Gene Resources and Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
- National Key Facility for Gene Resources and Genetic Improvement, Key Laboratory of Crop Germplasm Utilization, Ministry of Agriculture and Rural Affairs, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
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Han D, Zhao X, Zhang D, Wang Z, Zhu Z, Sun H, Qu Z, Wang L, Liu Z, Zhu X, Yuan M. Genome-wide association studies reveal novel QTLs for agronomic traits in soybean. FRONTIERS IN PLANT SCIENCE 2024; 15:1375646. [PMID: 38807775 PMCID: PMC11132100 DOI: 10.3389/fpls.2024.1375646] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/24/2024] [Accepted: 04/15/2024] [Indexed: 05/30/2024]
Abstract
Introduction Soybean, as a globally significant crop, has garnered substantial attention due to its agricultural importance. The utilization of molecular approaches to enhance grain yield in soybean has gained popularity. Methods In this study, we conducted a genome-wide association study (GWAS) using 156 Chinese soybean accessions over a two-year period. We employed the general linear model (GLM) and the mixed linear model (MLM) to analyze three agronomic traits: pod number, grain number, and grain weight. Results Our findings revealed significant associations between qgPNpP-98, qgGNpP-89 and qgHGW-85 QTLs and pod number, grain number, and grain weight, respectively. These QTLs were identified on chromosome 16, a region spanning 413171bp exhibited associations with all three traits. Discussion These QTL markers identified in this study hold potential for improving yield and agronomic traits through marker-assisted selection and genomic selection in breeding programs.
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Affiliation(s)
- Dongwei Han
- Qiqihar Branch of Heilongjiang Academy of Agricultural Science, Qiqihar, Heilongjiang, China
- Heilongjiang Chinese Academy of Sciences Qiuying Zhang Soybean Scientist Studio, Qiqihar, Heilongjiang, China
| | - Xi Zhao
- Biotechnology Institute, Heilongjiang Academy of Agricultural Science, Harbin, Heilongjiang, China
| | - Di Zhang
- Qiqihar Branch of Heilongjiang Academy of Agricultural Science, Qiqihar, Heilongjiang, China
| | - Zhen Wang
- Qiqihar Branch of Heilongjiang Academy of Agricultural Science, Qiqihar, Heilongjiang, China
| | - Zhijia Zhu
- Qiqihar Branch of Heilongjiang Academy of Agricultural Science, Qiqihar, Heilongjiang, China
| | - Haoyue Sun
- Qiqihar Branch of Heilongjiang Academy of Agricultural Science, Qiqihar, Heilongjiang, China
| | - Zhongcheng Qu
- Qiqihar Branch of Heilongjiang Academy of Agricultural Science, Qiqihar, Heilongjiang, China
| | - Lianxia Wang
- Qiqihar Branch of Heilongjiang Academy of Agricultural Science, Qiqihar, Heilongjiang, China
| | - Zhangxiong Liu
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Xu Zhu
- Department of Research and Development, Ruibiotech Co., Ltd, Beijing, China
| | - Ming Yuan
- Qiqihar Branch of Heilongjiang Academy of Agricultural Science, Qiqihar, Heilongjiang, China
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Dou T, Wang C, Ma Y, Chen Z, Zhang J, Guo G. CoreSNP: an efficient pipeline for core marker profile selection from genome-wide SNP datasets in crops. BMC PLANT BIOLOGY 2023; 23:580. [PMID: 37986037 PMCID: PMC10662547 DOI: 10.1186/s12870-023-04609-w] [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: 09/14/2023] [Accepted: 11/14/2023] [Indexed: 11/22/2023]
Abstract
BACKGROUND DNA marker profiles play a crucial role in the identification and registration of germplasm, as well as in the distinctness, uniformity, and stability (DUS) testing of new plant variety protection. However, selecting minimal marker sets from large-scale SNP dataset can be challenging to distinguish a maximum number of samples. RESULTS Here, we developed the CoreSNP pipeline using a "divide and conquer" strategy and a "greedy" algorithm. The pipeline offers adjustable parameters to guarantee the distinction of each sample pair with at least two markers. Additionally, it allows datasets with missing loci as input. The pipeline was tested in barley, soybean, wheat, rice and maize. A few dozen of core SNPs were efficiently selected in different crops with SNP array, GBS, and WGS dataset, which can differentiate thousands of individual samples. The core SNPs were distributed across all chromosomes, exhibiting lower pairwise linkage disequilibrium (LD) and higher polymorphism information content (PIC) and minor allele frequencies (MAF). It was shown that both the genetic diversity of the population and the characteristics of the original dataset can significantly influence the number of core markers. In addition, the core SNPs capture a certain level of the original population structure. CONCLUSIONS CoreSNP is an efficiency way of core marker sets selection based on Genome-wide SNP datasets of crops. Combined with low-density SNP chip or genotyping technologies, it can be a cost-effective way to simplify and expedite the evaluation of genetic resources and differentiate different crop varieties. This tool is expected to have great application prospects in the rapid comparison of germplasm and intellectual property protection of new varieties.
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Affiliation(s)
- Tingyu Dou
- Key Laboratory of Grain Crop Genetic Resources Evaluation and Utilization (MARA), The National Key Facility for Crop Gene Resources and Genetic Improvement, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (ICS-CAAS), Beijing, 100081, China
| | - Chunchao Wang
- Key Laboratory of Grain Crop Genetic Resources Evaluation and Utilization (MARA), The National Key Facility for Crop Gene Resources and Genetic Improvement, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (ICS-CAAS), Beijing, 100081, China
| | - Yanling Ma
- Key Laboratory of Grain Crop Genetic Resources Evaluation and Utilization (MARA), The National Key Facility for Crop Gene Resources and Genetic Improvement, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (ICS-CAAS), Beijing, 100081, China
| | - Zhaoyan Chen
- Key Laboratory of Grain Crop Genetic Resources Evaluation and Utilization (MARA), The National Key Facility for Crop Gene Resources and Genetic Improvement, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (ICS-CAAS), Beijing, 100081, China
| | - Jing Zhang
- Key Laboratory of Grain Crop Genetic Resources Evaluation and Utilization (MARA), The National Key Facility for Crop Gene Resources and Genetic Improvement, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (ICS-CAAS), Beijing, 100081, China
| | - Ganggang Guo
- Key Laboratory of Grain Crop Genetic Resources Evaluation and Utilization (MARA), The National Key Facility for Crop Gene Resources and Genetic Improvement, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (ICS-CAAS), Beijing, 100081, China.
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Wu T, Lu S, Cai Y, Xu X, Zhang L, Chen F, Jiang B, Zhang H, Sun S, Zhai H, Zhao L, Xia Z, Hou W, Kong F, Han T. Molecular breeding for improvement of photothermal adaptability in soybean. MOLECULAR BREEDING : NEW STRATEGIES IN PLANT IMPROVEMENT 2023; 43:60. [PMID: 37496825 PMCID: PMC10366068 DOI: 10.1007/s11032-023-01406-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/25/2023] [Accepted: 07/08/2023] [Indexed: 07/28/2023]
Abstract
Soybean (Glycine max (L.) Merr.) is a typical short-day and temperate crop that is sensitive to photoperiod and temperature. Responses of soybean to photothermal conditions determine plant growth and development, which affect its architecture, yield formation, and capacity for geographic adaptation. Flowering time, maturity, and other traits associated with photothermal adaptability are controlled by multiple major-effect and minor-effect genes and genotype-by-environment interactions. Genetic studies have identified at least 11 loci (E1-E4, E6-E11, and J) that participate in photoperiodic regulation of flowering time and maturity in soybean. Molecular cloning and characterization of major-effect flowering genes have clarified the photoperiod-dependent flowering pathway, in which the photoreceptor gene phytochrome A, circadian evening complex (EC) components, central flowering repressor E1, and FLOWERING LOCUS T family genes play key roles in regulation of flowering time, maturity, and adaptability to photothermal conditions. Here, we provide an overview of recent progress in genetic and molecular analysis of traits associated with photothermal adaptability, summarizing advances in molecular breeding practices and tools for improving these traits. Furthermore, we discuss methods for breeding soybean varieties with better adaptability to specific ecological regions, with emphasis on a novel strategy, the Potalaization model, which allows breeding of widely adapted soybean varieties through the use of multiple molecular tools in existing elite widely adapted varieties. Supplementary Information The online version contains supplementary material available at 10.1007/s11032-023-01406-z.
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Affiliation(s)
- Tingting Wu
- MARA Key Laboratory of Soybean Biology (Beijing), Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081 China
| | - Sijia Lu
- Guangdong Key Laboratory of Plant Adaptation and Molecular Design, Guangzhou Key Laboratory of Crop Gene Editing, Innovative Center of Molecular Genetics and Evolution, School of Life Sciences, Guangzhou University, Guangzhou, 510006 China
| | - Yupeng Cai
- MARA Key Laboratory of Soybean Biology (Beijing), Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081 China
| | - Xin Xu
- MARA Key Laboratory of Soybean Biology (Beijing), Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081 China
| | - Lixin Zhang
- MARA Key Laboratory of Soybean Biology (Beijing), Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081 China
| | - Fulu Chen
- MARA Key Laboratory of Soybean Biology (Beijing), Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081 China
| | - Bingjun Jiang
- MARA Key Laboratory of Soybean Biology (Beijing), Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081 China
| | - Honglei Zhang
- MARA Key Laboratory of Soybean Biology (Beijing), Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081 China
| | - Shi Sun
- MARA Key Laboratory of Soybean Biology (Beijing), Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081 China
| | - Hong Zhai
- Key Laboratory of Soybean Molecular Design Breeding, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Harbin, 150081 China
| | - Lin Zhao
- Key Laboratory of Soybean Biology of Ministry of Education of China, Northeast Agricultural University, Harbin, 150030 China
| | - Zhengjun Xia
- Key Laboratory of Soybean Molecular Design Breeding, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Harbin, 150081 China
| | - Wensheng Hou
- MARA Key Laboratory of Soybean Biology (Beijing), Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081 China
| | - Fanjiang Kong
- Guangdong Key Laboratory of Plant Adaptation and Molecular Design, Guangzhou Key Laboratory of Crop Gene Editing, Innovative Center of Molecular Genetics and Evolution, School of Life Sciences, Guangzhou University, Guangzhou, 510006 China
| | - Tianfu Han
- MARA Key Laboratory of Soybean Biology (Beijing), Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081 China
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Li D, Zhang Z, Gao X, Zhang H, Bai D, Wang Q, Zheng T, Li YH, Qiu LJ. The elite variations in germplasms for soybean breeding. MOLECULAR BREEDING : NEW STRATEGIES IN PLANT IMPROVEMENT 2023; 43:37. [PMID: 37312749 PMCID: PMC10248635 DOI: 10.1007/s11032-023-01378-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/31/2023] [Accepted: 04/03/2023] [Indexed: 06/15/2023]
Abstract
The genetic base of soybean cultivars (Glycine max (L.) Merr.) has been narrowed through selective domestication and specific breeding improvement, similar to other crops. This presents challenges in breeding new cultivars with improved yield and quality, reduced adaptability to climate change, and increased susceptibility to diseases. On the other hand, the vast collection of soybean germplasms offers a potential source of genetic variations to address those challenges, but it has yet to be fully leveraged. In recent decades, rapidly improved high-throughput genotyping technologies have accelerated the harness of elite variations in soybean germplasm and provided the important information for solving the problem of a narrowed genetic base in breeding. In this review, we will overview the situation of maintenance and utilization of soybean germplasms, various solutions provided for different needs in terms of the number of molecular markers, and the omics-based high-throughput strategies that have been used or can be used to identify elite alleles. We will also provide an overall genetic information generated from soybean germplasms in yield, quality traits, and pest resistance for molecular breeding.
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Affiliation(s)
- Delin Li
- The National Key Facility for Crop Gene Resources and Genetic Improvement (NFCRI)/Key Laboratory of Grain Crop Genetic Resources Evaluation and Utilization, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081 China
| | - Zhengwei Zhang
- The National Key Facility for Crop Gene Resources and Genetic Improvement (NFCRI)/Key Laboratory of Grain Crop Genetic Resources Evaluation and Utilization, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081 China
| | - Xinyue Gao
- The National Key Facility for Crop Gene Resources and Genetic Improvement (NFCRI)/Key Laboratory of Grain Crop Genetic Resources Evaluation and Utilization, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081 China
| | - Hao Zhang
- The National Key Facility for Crop Gene Resources and Genetic Improvement (NFCRI)/Key Laboratory of Grain Crop Genetic Resources Evaluation and Utilization, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081 China
| | - Dong Bai
- The National Key Facility for Crop Gene Resources and Genetic Improvement (NFCRI)/Key Laboratory of Grain Crop Genetic Resources Evaluation and Utilization, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081 China
| | - Qi Wang
- The National Key Facility for Crop Gene Resources and Genetic Improvement (NFCRI)/Key Laboratory of Grain Crop Genetic Resources Evaluation and Utilization, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081 China
- College of Agriculture, Northeast Agricultural University, Harbin, 150030 China
| | - Tianqing Zheng
- The National Key Facility for Crop Gene Resources and Genetic Improvement (NFCRI)/Key Laboratory of Grain Crop Genetic Resources Evaluation and Utilization, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081 China
| | - Ying-Hui Li
- The National Key Facility for Crop Gene Resources and Genetic Improvement (NFCRI)/Key Laboratory of Grain Crop Genetic Resources Evaluation and Utilization, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081 China
| | - Li-Juan Qiu
- The National Key Facility for Crop Gene Resources and Genetic Improvement (NFCRI)/Key Laboratory of Grain Crop Genetic Resources Evaluation and Utilization, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081 China
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Yang Q, Zhang J, Shi X, Chen L, Qin J, Zhang M, Yang C, Song Q, Yan L. Development of SNP marker panels for genotyping by target sequencing (GBTS) and its application in soybean. MOLECULAR BREEDING : NEW STRATEGIES IN PLANT IMPROVEMENT 2023; 43:26. [PMID: 37313526 PMCID: PMC10248699 DOI: 10.1007/s11032-023-01372-6] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/28/2022] [Accepted: 03/16/2023] [Indexed: 06/15/2023]
Abstract
A high-throughput genotyping platform with customized flexibility, high genotyping accuracy, and low cost is critical for marker-assisted selection and genetic mapping in soybean. Three assay panels were selected from the SoySNP50K, 40K, 20K, and 10K arrays, containing 41,541, 20,748, and 9670 SNP markers, respectively, for genotyping by target sequencing (GBTS). Fifteen representative accessions were used to assess the accuracy and consistency of the SNP alleles identified by the SNP panels and sequencing platform. The SNP alleles were 99.87% identical between technical replicates and 98.86% identical between the 40K SNP GBTS panel and 10× resequencing analysis. The GBTS method was also accurate in the sense that the genotypic dataset of the 15 representative accessions correctly revealed the pedigree of the accessions, and the biparental progeny datasets correctly constructed the linkage maps of the SNPs. The 10K panel was also used to genotype two parent-derived populations and analyze QTLs controlling 100-seed weight, resulting in the identification of the stable associated genetic locus Locus_OSW_06 on chromosome 06. The markers flanking the QTL explained 7.05% and 9.83% of the phenotypic variation, respectively. Compared with GBS and DNA chips, the 40K, 20K, and 10K panels reduced costs by 5.07% and 58.28%, 21.44% and 65.48%, and 35.74% and 71.76%, respectively. Low-cost genotyping panels could facilitate soybean germplasm assessment, genetic linkage map construction, QTL identification, and genomic selection. Supplementary Information The online version contains supplementary material available at 10.1007/s11032-023-01372-6.
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Affiliation(s)
- Qing Yang
- Hebei Laboratory of Crop Genetics and Breeding, National Soybean Improvement Center Shijiazhuang Sub-Center, Huang-Huai-Hai Key Laboratory of Biology and Genetic Improvement of Soybean, Ministry of Agriculture and Rural Affairs, Institute of Cereal and Oil Crops, Hebei Academy of Agricultural and Forestry Sciences, High-Tech Industrial Development Zone, 162 Hengshan St, Shijiazhuang, 050035 Hebei People’s Republic of China
| | - Jianan Zhang
- Mol Breeding Biotechnology Co., Ltd., 136 Huanghe Parkway, Shijiazhuang, 050035 Hebei People’s Republic of China
| | - Xiaolei Shi
- Hebei Laboratory of Crop Genetics and Breeding, National Soybean Improvement Center Shijiazhuang Sub-Center, Huang-Huai-Hai Key Laboratory of Biology and Genetic Improvement of Soybean, Ministry of Agriculture and Rural Affairs, Institute of Cereal and Oil Crops, Hebei Academy of Agricultural and Forestry Sciences, High-Tech Industrial Development Zone, 162 Hengshan St, Shijiazhuang, 050035 Hebei People’s Republic of China
| | - Lei Chen
- School of Life Sciences, Yantai University, 30# Qingquan Road, Lai Shan District, Yantai, 264005 Shandong People’s Republic of China
| | - Jun Qin
- Hebei Laboratory of Crop Genetics and Breeding, National Soybean Improvement Center Shijiazhuang Sub-Center, Huang-Huai-Hai Key Laboratory of Biology and Genetic Improvement of Soybean, Ministry of Agriculture and Rural Affairs, Institute of Cereal and Oil Crops, Hebei Academy of Agricultural and Forestry Sciences, High-Tech Industrial Development Zone, 162 Hengshan St, Shijiazhuang, 050035 Hebei People’s Republic of China
| | - Mengchen Zhang
- Hebei Laboratory of Crop Genetics and Breeding, National Soybean Improvement Center Shijiazhuang Sub-Center, Huang-Huai-Hai Key Laboratory of Biology and Genetic Improvement of Soybean, Ministry of Agriculture and Rural Affairs, Institute of Cereal and Oil Crops, Hebei Academy of Agricultural and Forestry Sciences, High-Tech Industrial Development Zone, 162 Hengshan St, Shijiazhuang, 050035 Hebei People’s Republic of China
| | - Chunyan Yang
- Hebei Laboratory of Crop Genetics and Breeding, National Soybean Improvement Center Shijiazhuang Sub-Center, Huang-Huai-Hai Key Laboratory of Biology and Genetic Improvement of Soybean, Ministry of Agriculture and Rural Affairs, Institute of Cereal and Oil Crops, Hebei Academy of Agricultural and Forestry Sciences, High-Tech Industrial Development Zone, 162 Hengshan St, Shijiazhuang, 050035 Hebei People’s Republic of China
| | - Qijian Song
- Soybean Genomics and Improvement Laboratory, USDA-ARS, Beltsville, MD USA
| | - Long Yan
- Hebei Laboratory of Crop Genetics and Breeding, National Soybean Improvement Center Shijiazhuang Sub-Center, Huang-Huai-Hai Key Laboratory of Biology and Genetic Improvement of Soybean, Ministry of Agriculture and Rural Affairs, Institute of Cereal and Oil Crops, Hebei Academy of Agricultural and Forestry Sciences, High-Tech Industrial Development Zone, 162 Hengshan St, Shijiazhuang, 050035 Hebei People’s Republic of China
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Guo B, Sun L, Jiang S, Ren H, Sun R, Wei Z, Hong H, Luan X, Wang J, Wang X, Xu D, Li W, Guo C, Qiu LJ. Soybean genetic resources contributing to sustainable protein production. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2022; 135:4095-4121. [PMID: 36239765 PMCID: PMC9561314 DOI: 10.1007/s00122-022-04222-9] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/22/2022] [Accepted: 09/10/2022] [Indexed: 06/12/2023]
Abstract
KEY MESSAGE Genetic resources contributes to the sustainable protein production in soybean. Soybean is an important crop for food, oil, and forage and is the main source of edible vegetable oil and vegetable protein. It plays an important role in maintaining balanced dietary nutrients for human health. The soybean protein content is a quantitative trait mainly controlled by gene additive effects and is usually negatively correlated with agronomic traits such as the oil content and yield. The selection of soybean varieties with high protein content and high yield to secure sustainable protein production is one of the difficulties in soybean breeding. The abundant genetic variation of soybean germplasm resources is the basis for overcoming the obstacles in breeding for soybean varieties with high yield and high protein content. Soybean has been cultivated for more than 5000 years and has spread from China to other parts of the world. The rich genetic resources play an important role in promoting the sustainable production of soybean protein worldwide. In this paper, the origin and spread of soybean and the current status of soybean production are reviewed; the genetic characteristics of soybean protein and the distribution of resources are expounded based on phenotypes; the discovery of soybean seed protein-related genes as well as transcriptomic, metabolomic, and proteomic studies in soybean are elaborated; the creation and utilization of high-protein germplasm resources are introduced; and the prospect of high-protein soybean breeding is described.
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Affiliation(s)
- Bingfu Guo
- Nanchang Branch of National Center of Oil crops Improvement, Jiangxi Province Key Laboratory of Oil crops Biology, Crops Research Institute of Jiangxi Academy of Agricultural Sciences, Nanchang, China
- The National Key Facility for Crop Gene Resources and Genetic Improvement (NFCRI) and MOA KeyLab of Soybean Biology (Beijing), Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Liping Sun
- Nanchang Branch of National Center of Oil crops Improvement, Jiangxi Province Key Laboratory of Oil crops Biology, Crops Research Institute of Jiangxi Academy of Agricultural Sciences, Nanchang, China
| | - Siqi Jiang
- Key Laboratory of Molecular Cytogenetics and Genetic Breeding, College of Life Science and Technology, Harbin Normal University, Harbin, China
- The National Key Facility for Crop Gene Resources and Genetic Improvement (NFCRI) and MOA KeyLab of Soybean Biology (Beijing), Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Honglei Ren
- Soybean Research Institute, Heilongjiang Academy of Agricultural Sciences, Harbin, China
| | - Rujian Sun
- The National Key Facility for Crop Gene Resources and Genetic Improvement (NFCRI) and MOA KeyLab of Soybean Biology (Beijing), Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Zhongyan Wei
- The National Key Facility for Crop Gene Resources and Genetic Improvement (NFCRI) and MOA KeyLab of Soybean Biology (Beijing), Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Huilong Hong
- The National Key Facility for Crop Gene Resources and Genetic Improvement (NFCRI) and MOA KeyLab of Soybean Biology (Beijing), Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, China
- Soybean Research Institute, Key Laboratory of Soybean Biology of Chinese Education Ministry, Northeast Agriculture University, Harbin, China
| | - Xiaoyan Luan
- Soybean Research Institute, Heilongjiang Academy of Agricultural Sciences, Harbin, China
| | - Jun Wang
- College of Agriculture, Yangtze University, Jingzhou, China
| | - Xiaobo Wang
- School of Agronomy, Anhui Agricultural University, Hefei, China
| | - Donghe Xu
- Biological Resources and Post-Harvest Division, Japan International Research Center for Agricultural Sciences, Tsukuba, Japan
| | - Wenbin Li
- Soybean Research Institute, Key Laboratory of Soybean Biology of Chinese Education Ministry, Northeast Agriculture University, Harbin, China
| | - Changhong Guo
- Key Laboratory of Molecular Cytogenetics and Genetic Breeding, College of Life Science and Technology, Harbin Normal University, Harbin, China
| | - Li-Juan Qiu
- The National Key Facility for Crop Gene Resources and Genetic Improvement (NFCRI) and MOA KeyLab of Soybean Biology (Beijing), Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, China.
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Lu Y, Zhang J, Guo X, Chen J, Chang R, Guan R, Qiu L. Identification of Genomic Regions Associated with Vine Growth and Plant Height of Soybean. Int J Mol Sci 2022; 23:5823. [PMID: 35628633 PMCID: PMC9146324 DOI: 10.3390/ijms23105823] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2022] [Revised: 05/09/2022] [Accepted: 05/20/2022] [Indexed: 11/16/2022] Open
Abstract
Vining growth (VG) and high plant height (PH) are the physiological traits of wild soybean that preclude their utilization for domesticated soybean breeding and improvement. To identify VG- and PH-related quantitative trait loci (QTLs) in different genetic resources, two populations of recombinant inbred lines (RILs) were developed by crossing a cultivated soybean, Zhonghuang39 (ZH39), with two wild soybean accessions, NY27-38 and NY36-87. Each line from the two crosses was evaluated for VG and PH. Three QTLs for VG and three for PH, detected in the ZH39 × NY27-38 population of the RILs, co-located on chromosomes 2, 17 and 19. The VG- and PH-related QTL in the ZH39 × NY36-87 population co-located on chromosome 19. A common QTL shared by the two populations was located on chromosome 19, suggesting that this major QTL was consistently selected for in different genetic backgrounds. The results suggest that different loci are involved in the domestication or adaptations of soybean of various genetic backgrounds. The molecular markers presented here would benefit the fine mapping and cloning of candidate genes underlying the VG and PH co-localized regions and thus facilitate the utilization of wild resources in breeding by avoiding undesirable traits.
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Affiliation(s)
| | | | | | | | | | - Rongxia Guan
- National Key Facility for Crop Gene Resources and Genetic Improvement, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China; (Y.L.); (J.Z.); (X.G.); (J.C.); (R.C.)
| | - Lijuan Qiu
- National Key Facility for Crop Gene Resources and Genetic Improvement, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China; (Y.L.); (J.Z.); (X.G.); (J.C.); (R.C.)
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