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Zong C, Zhao J, Wang Y, Wang L, Chen Z, Qi Y, Bai Y, Li W, Wang W, Ren H, Du W, Gai J. Identification of Gene-Allele System Conferring Alkali-Tolerance at Seedling Stage in Northeast China Soybean Germplasm. Int J Mol Sci 2024; 25:2963. [PMID: 38474209 DOI: 10.3390/ijms25052963] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2023] [Revised: 02/22/2024] [Accepted: 02/27/2024] [Indexed: 03/14/2024] Open
Abstract
Salinization of cultivated soils may result in either high salt levels or alkaline conditions, both of which stress crops and reduce performance. We sampled genotypes included in the Northeast China soybean germplasm population (NECSGP) to identify possible genes that affect tolerance to alkaline soil conditions. In this study, 361 soybean accessions collected in Northeast China were tested under 220 mM NaHCO3:Na2CO3 = 9:1 (pH = 9.8) to evaluate the alkali-tolerance (ATI) at the seedling stage in Mudanjiang, Heilongjiang, China. The restricted two-stage multi-locus model genome-wide association study (RTM-GWAS) with gene-allele sequences as markers (6503 GASMs) based on simplified genome resequencing (RAD-sequencing) was accomplished. From this analysis, 132 main effect candidate genes with 359 alleles and 35 Gene × Environment genes with 103 alleles were identified, explaining 90.93% and 2.80% of the seedling alkali-tolerance phenotypic variation, respectively. Genetic variability of ATI in NECSGP was observed primarily within subpopulations, especially in ecoregion B, from which 80% of ATI-tolerant accessions were screened out. The biological functions of 132 candidate genes were classified into eight functional categories (defense response, substance transport, regulation, metabolism-related, substance synthesis, biological process, plant development, and unknown function). From the ATI gene-allele system, six key genes-alleles were identified as starting points for further study on understanding the ATI gene network.
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Affiliation(s)
- Chunmei Zong
- Soybean Research Institute & MARA National Center for Soybean Improvement & MARA Key Laboratory of Biology and Genetic Improvement of Soybean (General) & State Key Laboratory for Crop Genetics and Germplasm Enhancement & State Innovation Platform for Integrated Production and Education in Soybean Bio-Breeding & Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing 210095, China
- Mudanjiang Soybean Research and Development Center, Mudanjiang Branch of Heilongjiang Academy of Agricultural Sciences, Mudanjiang 157041, China
| | - Jinming Zhao
- Soybean Research Institute & MARA National Center for Soybean Improvement & MARA Key Laboratory of Biology and Genetic Improvement of Soybean (General) & State Key Laboratory for Crop Genetics and Germplasm Enhancement & State Innovation Platform for Integrated Production and Education in Soybean Bio-Breeding & Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing 210095, China
- Mudanjiang Soybean Research and Development Center, Mudanjiang Branch of Heilongjiang Academy of Agricultural Sciences, Mudanjiang 157041, China
| | - Yanping Wang
- Mudanjiang Soybean Research and Development Center, Mudanjiang Branch of Heilongjiang Academy of Agricultural Sciences, Mudanjiang 157041, China
| | - Lei Wang
- Soybean Research Institute & MARA National Center for Soybean Improvement & MARA Key Laboratory of Biology and Genetic Improvement of Soybean (General) & State Key Laboratory for Crop Genetics and Germplasm Enhancement & State Innovation Platform for Integrated Production and Education in Soybean Bio-Breeding & Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing 210095, China
- Mudanjiang Soybean Research and Development Center, Mudanjiang Branch of Heilongjiang Academy of Agricultural Sciences, Mudanjiang 157041, China
| | - Zaoye Chen
- Soybean Research Institute & MARA National Center for Soybean Improvement & MARA Key Laboratory of Biology and Genetic Improvement of Soybean (General) & State Key Laboratory for Crop Genetics and Germplasm Enhancement & State Innovation Platform for Integrated Production and Education in Soybean Bio-Breeding & Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing 210095, China
| | - Yuxin Qi
- Mudanjiang Soybean Research and Development Center, Mudanjiang Branch of Heilongjiang Academy of Agricultural Sciences, Mudanjiang 157041, China
| | - Yanfeng Bai
- Mudanjiang Soybean Research and Development Center, Mudanjiang Branch of Heilongjiang Academy of Agricultural Sciences, Mudanjiang 157041, China
| | - Wen Li
- Mudanjiang Soybean Research and Development Center, Mudanjiang Branch of Heilongjiang Academy of Agricultural Sciences, Mudanjiang 157041, China
| | - Wubin Wang
- Soybean Research Institute & MARA National Center for Soybean Improvement & MARA Key Laboratory of Biology and Genetic Improvement of Soybean (General) & State Key Laboratory for Crop Genetics and Germplasm Enhancement & State Innovation Platform for Integrated Production and Education in Soybean Bio-Breeding & Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing 210095, China
- Mudanjiang Soybean Research and Development Center, Mudanjiang Branch of Heilongjiang Academy of Agricultural Sciences, Mudanjiang 157041, China
| | - Haixiang Ren
- Mudanjiang Soybean Research and Development Center, Mudanjiang Branch of Heilongjiang Academy of Agricultural Sciences, Mudanjiang 157041, China
| | - Weiguang Du
- Mudanjiang Soybean Research and Development Center, Mudanjiang Branch of Heilongjiang Academy of Agricultural Sciences, Mudanjiang 157041, China
| | - Junyi Gai
- Soybean Research Institute & MARA National Center for Soybean Improvement & MARA Key Laboratory of Biology and Genetic Improvement of Soybean (General) & State Key Laboratory for Crop Genetics and Germplasm Enhancement & State Innovation Platform for Integrated Production and Education in Soybean Bio-Breeding & Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing 210095, China
- Mudanjiang Soybean Research and Development Center, Mudanjiang Branch of Heilongjiang Academy of Agricultural Sciences, Mudanjiang 157041, China
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Mahmood A, Bilyeu KD, Škrabišová M, Biová J, De Meyer EJ, Meinhardt CG, Usovsky M, Song Q, Lorenz AJ, Mitchum MG, Shannon G, Scaboo AM. Cataloging SCN resistance loci in North American public soybean breeding programs. Front Plant Sci 2023; 14:1270546. [PMID: 38053759 PMCID: PMC10694258 DOI: 10.3389/fpls.2023.1270546] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Accepted: 10/16/2023] [Indexed: 12/07/2023]
Abstract
Soybean cyst nematode (SCN) is a destructive pathogen of soybeans responsible for annual yield loss exceeding $1.5 billion in the United States. Here, we conducted a series of genome-wide association studies (GWASs) to understand the genetic landscape of SCN resistance in the University of Missouri soybean breeding programs (Missouri panel), as well as germplasm and cultivars within the United States Department of Agriculture (USDA) Uniform Soybean Tests-Northern Region (NUST). For the Missouri panel, we evaluated the resistance of breeding lines to SCN populations HG 2.5.7 (Race 1), HG 1.2.5.7 (Race 2), HG 0 (Race 3), HG 2.5.7 (Race 5), and HG 1.3.6.7 (Race 14) and identified seven quantitative trait nucleotides (QTNs) associated with SCN resistance on chromosomes 2, 8, 11, 14, 17, and 18. Additionally, we evaluated breeding lines in the NUST panel for resistance to SCN populations HG 2.5.7 (Race 1) and HG 0 (Race 3), and we found three SCN resistance-associated QTNs on chromosomes 7 and 18. Through these analyses, we were able to decipher the impact of seven major genetic loci, including three novel loci, on resistance to several SCN populations and identified candidate genes within each locus. Further, we identified favorable allelic combinations for resistance to individual SCN HG types and provided a list of available germplasm for integration of these unique alleles into soybean breeding programs. Overall, this study offers valuable insight into the landscape of SCN resistance loci in U.S. public soybean breeding programs and provides a framework to develop new and improved soybean cultivars with diverse plant genetic modes of SCN resistance.
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Affiliation(s)
- Anser Mahmood
- Division of Plant Science and Technology, University of Missouri, Columbia, MO, United States
| | - Kristin D. Bilyeu
- Plant Genetics Research Unit, United States Department of Agriculture-Agricultural Research Service, University of Missouri, Columbia, MO, United States
| | - Mária Škrabišová
- Department of Biochemistry, Faculty of Science, Palacky University Olomouc, Olomouc, Czechia
| | - Jana Biová
- Department of Biochemistry, Faculty of Science, Palacky University Olomouc, Olomouc, Czechia
| | - Elizabeth J. De Meyer
- Division of Plant Science and Technology, University of Missouri, Columbia, MO, United States
| | - Clinton G. Meinhardt
- Division of Plant Science and Technology, University of Missouri, Columbia, MO, United States
| | - Mariola Usovsky
- Division of Plant Science and Technology, University of Missouri, Columbia, MO, United States
| | - Qijian Song
- Soybean Genomics and Improvement Laboratory, Beltsville Agricultural Research Center, United States Department of Agriculture-Agricultural Research Service (USDA-ARS), Beltsville, MD, United States
| | - Aaron J. Lorenz
- Department of Agronomy and Plant Genetics, University of Minnesota, St. Paul, MN, United States
| | - Melissa G. Mitchum
- Department of Plant Pathology and Institute of Plant Breeding, Genetics, and Genomics, University of Georgia, Athens, GA, United States
| | - Grover Shannon
- Division of Plant Science and Technology, University of Missouri, Columbia, MO, United States
| | - Andrew M. Scaboo
- Division of Plant Science and Technology, University of Missouri, Columbia, MO, United States
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Pan L, Gai J, Xing G. The Identification of a Quantative Trait Loci-Allele System of Antixenosis against the Common Cutworm ( Spodoptera litura Fabricius) at the Seedling Stage in the Chinese Soybean Landrace Population. Int J Mol Sci 2023; 24:16089. [PMID: 38003278 PMCID: PMC10671034 DOI: 10.3390/ijms242216089] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2023] [Revised: 10/20/2023] [Accepted: 10/31/2023] [Indexed: 11/26/2023] Open
Abstract
Common cutworm (CCW) is an omnivorous insect causing severe yield losses in soybean crops. The seedling-stage mini-tray identification system with the damaged leaf percentage (DLP) as an indicator was used to evaluate antixenosis against CCW in the Chinese soybean landrace population (CSLRP) under three environments. Using the innovative restricted two-stage multi-locus genome-wide association study procedure (RTM-GWAS), 86 DLP QTLs with 243 alleles (2-11/QTL) were identified, including 66 main-effect loci with 203 alleles and 57 QTL-environment interaction loci with 172 alleles. Among the main-effect loci, 12 large-contribution loci (R2 ≥ 1%) explained 25.45% of the phenotypic variation (PV), and 54 small-contribution loci (R2 < 1%) explained 16.55% of the PV. This indicates that the CSLRP can be characterized with a DLP QTL-allele system complex that has not been found before, except for a few individual QTLs without alleles involved. From the DLP QTL-allele matrix, the recombination potentials expressed in the 25th percentile of the DLP of all possible crosses were predicted to be reduced by 41.5% as the maximum improvement and 14.2% as the maximum transgression, indicating great breeding potential in the antixenosis of the CSLRP. From the QTLs, 62 candidate genes were annotated, which were involved in eight biological function categories as a gene network of the DLP. Changing from susceptible to moderate plus resistant varieties in the CSLRP, 26 QTLs had 32 alleles involved, in which 19 genes were annotated from 25 QTL-alleles, including eight increased negative alleles on seven loci and 11 decreased positive alleles on 11 loci, showing the major genetic constitution changes for the antixenosis enhancement at the seedling stage in the CSLRP.
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Affiliation(s)
| | - Junyi Gai
- Soybean Research Institute & MARA National Center for Soybean Improvement & MARA Key Laboratory of Biology and Genetic Improvement of Soybean & State Key Laboratory of Crop Genetics, Germplasm Enhancement and Utilization & State Innovation Platform for Industry-Education Integration in Soybean Bio-Breeding & Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing 210095, China
| | - Guangnan Xing
- Soybean Research Institute & MARA National Center for Soybean Improvement & MARA Key Laboratory of Biology and Genetic Improvement of Soybean & State Key Laboratory of Crop Genetics, Germplasm Enhancement and Utilization & State Innovation Platform for Industry-Education Integration in Soybean Bio-Breeding & Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing 210095, China
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4
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Wang C, Hao X, Liu X, Su Y, Pan Y, Zong C, Wang W, Xing G, He J, Gai J. An Improved Genome-Wide Association Procedure Explores Gene-Allele Constitutions and Evolutionary Drives of Growth Period Traits in the Global Soybean Germplasm Population. Int J Mol Sci 2023; 24:ijms24119570. [PMID: 37298521 DOI: 10.3390/ijms24119570] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2023] [Revised: 05/26/2023] [Accepted: 05/29/2023] [Indexed: 06/12/2023] Open
Abstract
In soybeans (Glycine max (L.) Merr.), their growth periods, DSF (days of sowing-to-flowering), and DFM (days of flowering-to-maturity) are determined by their required accumulative day-length (ADL) and active temperature (AAT). A sample of 354 soybean varieties from five world eco-regions was tested in four seasons in Nanjing, China. The ADL and AAT of DSF and DFM were calculated from daily day-lengths and temperatures provided by the Nanjing Meteorological Bureau. The improved restricted two-stage multi-locus genome-wide association study using gene-allele sequences as markers (coded GASM-RTM-GWAS) was performed. (i) For DSF and its related ADLDSF and AATDSF, 130-141 genes with 384-406 alleles were explored, and for DFM and its related ADLDFM and AATDFM, 124-135 genes with 362-384 alleles were explored, in a total of six gene-allele systems. DSF shared more ADL and AAT contributions than DFM. (ii) Comparisons between the eco-region gene-allele submatrices indicated that the genetic adaptation from the origin to the geographic sub-regions was characterized by allele emergence (mutation), while genetic expansion from primary maturity group (MG)-sets to early/late MG-sets featured allele exclusion (selection) without allele emergence in addition to inheritance (migration). (iii) Optimal crosses with transgressive segregations in both directions were predicted and recommended for breeding purposes, indicating that allele recombination in soybean is an important evolutionary drive. (iv) Genes of the six traits were mostly trait-specific involved in four categories of 10 groups of biological functions. GASM-RTM-GWAS showed potential in detecting directly causal genes with their alleles, identifying differential trait evolutionary drives, predicting recombination breeding potentials, and revealing population gene networks.
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Affiliation(s)
- Can Wang
- Soybean Research Institute, MARA National Center for Soybean Improvement, MARA Key Laboratory of Biology and Genetic Improvement of Soybean (General), State Key Laboratory for Crop Genetics and Germplasm Enhancement, State Innovation Platform for Integrated Production and Education in Soybean Bio-breeding, Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing 210095, China
| | - Xiaoshuai Hao
- Soybean Research Institute, MARA National Center for Soybean Improvement, MARA Key Laboratory of Biology and Genetic Improvement of Soybean (General), State Key Laboratory for Crop Genetics and Germplasm Enhancement, State Innovation Platform for Integrated Production and Education in Soybean Bio-breeding, Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing 210095, China
| | - Xueqin Liu
- Soybean Research Institute, MARA National Center for Soybean Improvement, MARA Key Laboratory of Biology and Genetic Improvement of Soybean (General), State Key Laboratory for Crop Genetics and Germplasm Enhancement, State Innovation Platform for Integrated Production and Education in Soybean Bio-breeding, Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing 210095, China
| | - Yanzhu Su
- Soybean Research Institute, MARA National Center for Soybean Improvement, MARA Key Laboratory of Biology and Genetic Improvement of Soybean (General), State Key Laboratory for Crop Genetics and Germplasm Enhancement, State Innovation Platform for Integrated Production and Education in Soybean Bio-breeding, Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing 210095, China
| | - Yongpeng Pan
- Soybean Research Institute, MARA National Center for Soybean Improvement, MARA Key Laboratory of Biology and Genetic Improvement of Soybean (General), State Key Laboratory for Crop Genetics and Germplasm Enhancement, State Innovation Platform for Integrated Production and Education in Soybean Bio-breeding, Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing 210095, China
| | - Chunmei Zong
- Soybean Research Institute, MARA National Center for Soybean Improvement, MARA Key Laboratory of Biology and Genetic Improvement of Soybean (General), State Key Laboratory for Crop Genetics and Germplasm Enhancement, State Innovation Platform for Integrated Production and Education in Soybean Bio-breeding, Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing 210095, China
| | - Wubin Wang
- Soybean Research Institute, MARA National Center for Soybean Improvement, MARA Key Laboratory of Biology and Genetic Improvement of Soybean (General), State Key Laboratory for Crop Genetics and Germplasm Enhancement, State Innovation Platform for Integrated Production and Education in Soybean Bio-breeding, Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing 210095, China
| | - Guangnan Xing
- Soybean Research Institute, MARA National Center for Soybean Improvement, MARA Key Laboratory of Biology and Genetic Improvement of Soybean (General), State Key Laboratory for Crop Genetics and Germplasm Enhancement, State Innovation Platform for Integrated Production and Education in Soybean Bio-breeding, Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing 210095, China
| | - Jianbo He
- Soybean Research Institute, MARA National Center for Soybean Improvement, MARA Key Laboratory of Biology and Genetic Improvement of Soybean (General), State Key Laboratory for Crop Genetics and Germplasm Enhancement, State Innovation Platform for Integrated Production and Education in Soybean Bio-breeding, Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing 210095, China
| | - Junyi Gai
- Soybean Research Institute, MARA National Center for Soybean Improvement, MARA Key Laboratory of Biology and Genetic Improvement of Soybean (General), State Key Laboratory for Crop Genetics and Germplasm Enhancement, State Innovation Platform for Integrated Production and Education in Soybean Bio-breeding, Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing 210095, China
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Xue J, Gao H, Xue Y, Shi R, Liu M, Han L, Gao Y, Zhou Y, Zhang F, Zhang H, Jia X, Li R. Functional Characterization of Soybean Diacylglycerol Acyltransferase 3 in Yeast and Soybean. Front Plant Sci 2022; 13:854103. [PMID: 35693158 PMCID: PMC9174931 DOI: 10.3389/fpls.2022.854103] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/13/2022] [Accepted: 04/08/2022] [Indexed: 06/15/2023]
Abstract
Diacylglycerol acyltransferases (DGAT) function as the key rate-limiting enzymes in de novo biosynthesis of triacylglycerol (TAG) by transferring an acyl group from acyl-CoA to sn-3 of diacylglycerol (DAG) to form TAG. Here, two members of the type 3 DGAT gene family, GmDGAT3-1 and GmDGAT3-2, were identified from the soybean (Glycine max) genome. Both of them were predicted to encode soluble cytosolic proteins containing the typical thioredoxin-like ferredoxin domain. Quantitative PCR analysis revealed that GmDGAT3-2 expression was much higher than GmDGAT3-1's in various soybean tissues such as leaves, flowers, and seeds. Functional complementation assay using TAG-deficient yeast (Saccharomyces cerevisiae) mutant H1246 demonstrated that GmDGAT3-2 fully restored TAG biosynthesis in the yeast and preferentially incorporated monounsaturated fatty acids (MUFAs), especially oleic acid (C18:1) into TAGs. This substrate specificity was further verified by fatty-acid feeding assays and in vitro enzyme activity characterization. Notably, transgenic tobacco (Nicotiana benthamiana) data showed that heterogeneous expression of GmDGAT3-2 resulted in a significant increase in seed oil and C18:1 levels but little change in contents of protein and starch compared to the EV-transformed tobacco plants. Taken together, GmDGAT3-2 displayed a strong enzymatic activity to catalyze TAG assembly with high substrate specificity for MUFAs, particularly C18:1, playing an important role in the cytosolic pathway of TAG synthesis in soybean. The present findings provide a scientific reference for improving oil yield and FA composition in soybean through gene modification, further expanding our knowledge of TAG biosynthesis and its regulatory mechanism in oilseeds.
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Affiliation(s)
- Jinai Xue
- College of Agriculture, Institute of Molecular Agriculture and Bioenergy, Shanxi Agricultural University, Taigu, China
| | - Huiling Gao
- College of Agriculture, Institute of Molecular Agriculture and Bioenergy, Shanxi Agricultural University, Taigu, China
| | - Yinghong Xue
- College of Agriculture, Institute of Molecular Agriculture and Bioenergy, Shanxi Agricultural University, Taigu, China
| | - Ruixiang Shi
- College of Landscape Architecture, Northeast Forestry University, Haerbin, China
| | - Mengmeng Liu
- College of Agriculture, Institute of Molecular Agriculture and Bioenergy, Shanxi Agricultural University, Taigu, China
| | - Lijun Han
- College of Agriculture, Institute of Molecular Agriculture and Bioenergy, Shanxi Agricultural University, Taigu, China
| | - Yu Gao
- College of Agriculture, Institute of Molecular Agriculture and Bioenergy, Shanxi Agricultural University, Taigu, China
| | - Yali Zhou
- College of Agriculture, Institute of Molecular Agriculture and Bioenergy, Shanxi Agricultural University, Taigu, China
| | - Fei Zhang
- College of Agriculture, Institute of Molecular Agriculture and Bioenergy, Shanxi Agricultural University, Taigu, China
| | - Haiping Zhang
- Center for Agricultural Genetic Resources Research, Shanxi Agricultural University (Institute of Crop Germplasm Resources, Shanxi Academy of Agricultural Sciences), Taiyuan, China
| | - Xiaoyun Jia
- College of Agriculture, Institute of Molecular Agriculture and Bioenergy, Shanxi Agricultural University, Taigu, China
| | - Runzhi Li
- College of Agriculture, Institute of Molecular Agriculture and Bioenergy, Shanxi Agricultural University, Taigu, 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. Plant J 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] [What about the content of this article? (0)] [Affiliation(s)] [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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Jiang H, Gu S, Li K, Gai J. Two TGA Transcription Factor Members from Hyper-Susceptible Soybean Exhibiting Significant Basal Resistance to Soybean mosaic virus. Int J Mol Sci 2021; 22:11329. [PMID: 34768757 PMCID: PMC8583413 DOI: 10.3390/ijms222111329] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2021] [Revised: 10/15/2021] [Accepted: 10/16/2021] [Indexed: 12/11/2022] Open
Abstract
TGA transcription factors (TFs) exhibit basal resistance in Arabidopsis, but susceptibility to a pathogen attack in tomatoes; however, their roles in soybean (Glycine max) to Soybean mosaic virus (SMV) are unknown. In this study, 27 TGA genes were isolated from a SMV hyper-susceptible soybean NN1138-2, designated GmTGA1~GmTGA27, which were clustered into seven phylogenetic groups. The expression profiles of GmTGAs showed that the highly expressed genes were mainly in Groups I, II, and VII under non-induction conditions, while out of the 27 GmTGAs, 19 responded to SMV-induction. Interestingly, in further transient N. benthamiana-SMV pathosystem assay, all the 19 GmTGAs overexpressed did not promote SMV infection in inoculated leaves, but they exhibited basal resistance except one without function. Among the 18 functional ones, GmTGA8 and GmTGA19, with similar motif distribution, nuclear localization sequence and interaction proteins, showed a rapid response to SMV infection and performed better than the others in inhibiting SMV multiplication. This finding suggested that GmTGA TFs may support basal resistance to SMV even from a hyper-susceptible source. What the mechanism of the genes (GmTGA8, GmTGA19, etc.) with basal resistance to SMV is and what their potential for the future improvement of resistance to SMV in soybeans is, are to be explored.
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Affiliation(s)
- Hua Jiang
- Soybean Research Institute, Nanjing Agricultural University, Nanjing 210095, China; (H.J.); (S.G.); (K.L.)
- MOA National Center for Soybean Improvement, Nanjing Agricultural University, Nanjing 210095, China
- MOA Key Laboratory of Biology and Genetic Improvement of Soybean (General), Nanjing Agricultural University, Nanjing 210095, China
- State Key Laboratory for Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing 210095, China
- Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing 210095, China
| | - Shengyu Gu
- Soybean Research Institute, Nanjing Agricultural University, Nanjing 210095, China; (H.J.); (S.G.); (K.L.)
- MOA National Center for Soybean Improvement, Nanjing Agricultural University, Nanjing 210095, China
- MOA Key Laboratory of Biology and Genetic Improvement of Soybean (General), Nanjing Agricultural University, Nanjing 210095, China
- State Key Laboratory for Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing 210095, China
- Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing 210095, China
| | - Kai Li
- Soybean Research Institute, Nanjing Agricultural University, Nanjing 210095, China; (H.J.); (S.G.); (K.L.)
- MOA National Center for Soybean Improvement, Nanjing Agricultural University, Nanjing 210095, China
- MOA Key Laboratory of Biology and Genetic Improvement of Soybean (General), Nanjing Agricultural University, Nanjing 210095, China
- State Key Laboratory for Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing 210095, China
- Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing 210095, China
| | - Junyi Gai
- Soybean Research Institute, Nanjing Agricultural University, Nanjing 210095, China; (H.J.); (S.G.); (K.L.)
- MOA National Center for Soybean Improvement, Nanjing Agricultural University, Nanjing 210095, China
- MOA Key Laboratory of Biology and Genetic Improvement of Soybean (General), Nanjing Agricultural University, Nanjing 210095, China
- State Key Laboratory for Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing 210095, China
- Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing 210095, China
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8
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Ding X, Guo J, Zhang Q, Yu L, Zhao T, Yang S. Heat-Responsive miRNAs Participate in the Regulation of Male Fertility Stability in Soybean CMS-Based F 1 under High Temperature Stress. Int J Mol Sci 2021; 22:2446. [PMID: 33671046 PMCID: PMC7957588 DOI: 10.3390/ijms22052446] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2020] [Revised: 02/10/2021] [Accepted: 02/24/2021] [Indexed: 11/18/2022] Open
Abstract
MicroRNAs (miRNAs), a class of noncoding small RNAs (sRNAs), are widely involved in the response to high temperature (HT) stress at both the seedling and flowering stages. To dissect the roles of miRNAs in regulating male fertility in soybean cytoplasmic male sterility (CMS)-based F1 under HT, sRNA sequencing was performed using flower buds from HT-tolerant and HT-sensitive CMS-based F1 combinations (NF1 and YF1, respectively). A total of 554 known miRNAs, 59 new members of known miRNAs, 712 novel miRNAs, and 1145 target genes of 580 differentially expressed miRNAs (DEMs) were identified under normal temperature and HT conditions. Further integrated analysis of sRNA and transcriptome sequencing found that 21 DEMs and 15 differentially expressed target genes, such as gma-miR397a/Laccase 2, gma-miR399a/Inorganic phosphate transporter 1-4, and gma-miR4413a/PPR proteins, mitochondrial-like, were negatively regulated under HT stress. Furthermore, all members of the gma-miR156 family were suppressed by HT stress in both NF1 and YF1, but were highly expressed in YF1 under HT condition. The negative correlation between gma-miR156b and its target gene squamosa promoter-binding protein-like 2b was confirmed by expression analysis, and overexpression of gma-miR156b in Arabidopsis led to male sterility under HT stress. With these results, we proposed that miRNAs play an important role in the regulation of male fertility stability in soybean CMS-based F1 under HT stress.
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Affiliation(s)
| | | | | | | | - Tuanjie Zhao
- Soybean Research Institute, National Center for Soybean Improvement, Key Laboratory of Biology and Genetic Improvement of Soybean (General, Ministry of Agriculture), State Key Laboratory of Crop Genetics and Germplasm Enhancement, Jiangsu Collaborative Innovation Center for Modern Crop Production, College of Agriculture, Nanjing Agricultural University, Nanjing 210095, China; (X.D.); (J.G.); (Q.Z.); (L.Y.)
| | - Shouping Yang
- Soybean Research Institute, National Center for Soybean Improvement, Key Laboratory of Biology and Genetic Improvement of Soybean (General, Ministry of Agriculture), State Key Laboratory of Crop Genetics and Germplasm Enhancement, Jiangsu Collaborative Innovation Center for Modern Crop Production, College of Agriculture, Nanjing Agricultural University, Nanjing 210095, China; (X.D.); (J.G.); (Q.Z.); (L.Y.)
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9
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Wang L, Sun S, Wu T, Liu L, Sun X, Cai Y, Li J, Jia H, Yuan S, Chen L, Jiang B, Wu C, Hou W, Han T. Natural variation and CRISPR/Cas9-mediated mutation in GmPRR37 affect photoperiodic flowering and contribute to regional adaptation of soybean. Plant Biotechnol J 2020; 18:1869-1881. [PMID: 31981443 PMCID: PMC7415786 DOI: 10.1111/pbi.13346] [Citation(s) in RCA: 53] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/04/2019] [Accepted: 01/20/2020] [Indexed: 05/07/2023]
Abstract
Flowering time is a critical determinant of the geographic distribution and regional adaptability of soybean (Glycine max) and is strongly regulated by photoperiod and temperature. In this study, quantitative trait locus (QTL) mapping and subsequent candidate gene analysis revealed that GmPRR37, encoding a pseudo-response regulator protein, is responsible for the major QTL qFT12-2, which was identified from a population of 308 recombinant inbred lines (RILs) derived from a cross between a very late-flowering soybean cultivar, 'Zigongdongdou (ZGDD)', and an extremely early-flowering cultivar, 'Heihe27 (HH27)', in multiple environments. Comparative analysis of parental sequencing data confirmed that HH27 contains a non-sense mutation that causes the loss of the CCT domain in the GmPRR37 protein. CRISPR/Cas9-induced Gmprr37-ZGDD mutants in soybean exhibited early flowering under natural long-day (NLD) conditions. Overexpression of GmPRR37 significantly delayed the flowering of transgenic soybean plants compared with wild-type under long photoperiod conditions. In addition, both the knockout and overexpression of GmPRR37 in soybean showed no significant phenotypic alterations in flowering time under short-day (SD) conditions. Furthermore, GmPRR37 down-regulated the expression of the flowering-promoting FT homologues GmFT2a and GmFT5a, and up-regulated flowering-inhibiting FT homologue GmFT1a expression under long-day (LD) conditions. We analysed haplotypes of GmPRR37 among 180 cultivars collected across China and found natural Gmprr37 mutants flower earlier and enable soybean to be cultivated at higher latitudes. This study demonstrates that GmPRR37 controls soybean photoperiodic flowering and provides opportunities to breed optimized cultivars with adaptation to specific regions and farming systems.
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Affiliation(s)
- Liwei Wang
- Ministry of Agriculture and Rural Affairs Key Laboratory of Soybean Biology (Beijing)Institute of Crop SciencesChinese Academy of Agricultural SciencesBeijingChina
| | - Shi Sun
- Ministry of Agriculture and Rural Affairs Key Laboratory of Soybean Biology (Beijing)Institute of Crop SciencesChinese Academy of Agricultural SciencesBeijingChina
| | - Tingting Wu
- Ministry of Agriculture and Rural Affairs Key Laboratory of Soybean Biology (Beijing)Institute of Crop SciencesChinese Academy of Agricultural SciencesBeijingChina
| | - Luping Liu
- Ministry of Agriculture and Rural Affairs Key Laboratory of Soybean Biology (Beijing)Institute of Crop SciencesChinese Academy of Agricultural SciencesBeijingChina
| | - Xuegang Sun
- Ministry of Agriculture and Rural Affairs Key Laboratory of Soybean Biology (Beijing)Institute of Crop SciencesChinese Academy of Agricultural SciencesBeijingChina
| | - Yupeng Cai
- Ministry of Agriculture and Rural Affairs Key Laboratory of Soybean Biology (Beijing)Institute of Crop SciencesChinese Academy of Agricultural SciencesBeijingChina
| | - Jicun Li
- Jining Academy of Agricultural SciencesJiningShandongChina
| | - Hongchang Jia
- Ministry of Agriculture and Rural Affairs Key Laboratory of Soybean Biology (Beijing)Institute of Crop SciencesChinese Academy of Agricultural SciencesBeijingChina
| | - Shan Yuan
- Ministry of Agriculture and Rural Affairs Key Laboratory of Soybean Biology (Beijing)Institute of Crop SciencesChinese Academy of Agricultural SciencesBeijingChina
| | - Li Chen
- Ministry of Agriculture and Rural Affairs Key Laboratory of Soybean Biology (Beijing)Institute of Crop SciencesChinese Academy of Agricultural SciencesBeijingChina
| | - Bingjun Jiang
- Ministry of Agriculture and Rural Affairs Key Laboratory of Soybean Biology (Beijing)Institute of Crop SciencesChinese Academy of Agricultural SciencesBeijingChina
| | - Cunxiang Wu
- Ministry of Agriculture and Rural Affairs Key Laboratory of Soybean Biology (Beijing)Institute of Crop SciencesChinese Academy of Agricultural SciencesBeijingChina
| | - Wensheng Hou
- Ministry of Agriculture and Rural Affairs Key Laboratory of Soybean Biology (Beijing)Institute of Crop SciencesChinese Academy of Agricultural SciencesBeijingChina
| | - Tianfu Han
- Ministry of Agriculture and Rural Affairs Key Laboratory of Soybean Biology (Beijing)Institute of Crop SciencesChinese Academy of Agricultural SciencesBeijingChina
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10
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Wang W, Zhou B, He J, Zhao J, Liu C, Chen X, Xing G, Chen S, Xing H, Gai J. Comprehensive Identification of Drought Tolerance QTL-Allele and Candidate Gene Systems in Chinese Cultivated Soybean Population. Int J Mol Sci 2020; 21:E4830. [PMID: 32650485 PMCID: PMC7402128 DOI: 10.3390/ijms21144830] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2020] [Revised: 07/03/2020] [Accepted: 07/03/2020] [Indexed: 12/29/2022] Open
Abstract
Drought is one of the most important factors affecting plant growth and productivity. The previous results on drought tolerance (DT) genetic system in soybean indicated a complex of genes not only few ones were involved in the trait. This study is featured with a relatively thorough identification of QTL-allele/candidate-gene system using an efficient restricted two-stage multi-locus multi-allele genome-wide association study, on two comprehensive DT indicators, membership index values of relative plant weight (MPW) and height (MPH), instead of a single biological characteristic, in a large sample (564 accessions) of the Chinese cultivated soybean population (CCSP). Based on 24,694 multi-allele markers, 75 and 64 QTL with 261 and 207 alleles (2-12/locus) were detected for MPW and MPH, explaining 54.7% and 47.1% of phenotypic variance, respectively. The detected QTL-alleles were organized into a QTL-allele matrix for each indicator, indicating DT is a super-trait conferred by two (even more) QTL-allele systems of sub-traits. Each CCSP matrix was separated into landrace (LR) and released cultivar (RC) sub-matrices, which showed significant differentiation in QTL-allele constitutions, with 58 LR alleles excluded and 16 new ones emerged in RC. Using the matrices, optimal crosses with great DT transgressive recombinants were predicted. From the detected QTL, 177 candidate genes were annotated and validated with quantitative Real-time PCR, and grouped into nine categories, with ABA and stress responders as the major parts. The key point of the above results is the establishment of relatively full QTL-allele matrices composed of numerous gene functions jointly conferring DT, therefore, demonstrates the complexity of DT genetic system and potential of CCSP in DT breeding.
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Affiliation(s)
- Wubin Wang
- Soybean Research Institute, Nanjing Agricultural University, Nanjing 210095, China; (W.W.); (B.Z.); (J.H.); (J.Z.); (C.L.); (X.C.); (G.X.); (H.X.)
- MOA National Center for Soybean Improvement, Nanjing Agricultural University, Nanjing 210095, China
- MOA Key Laboratory of Biology and Genetic Improvement of Soybean (General), Nanjing Agricultural University, Nanjing 210095, China
- State Key Laboratory for Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing 210095, China
| | - Bin Zhou
- Soybean Research Institute, Nanjing Agricultural University, Nanjing 210095, China; (W.W.); (B.Z.); (J.H.); (J.Z.); (C.L.); (X.C.); (G.X.); (H.X.)
- MOA National Center for Soybean Improvement, Nanjing Agricultural University, Nanjing 210095, China
| | - Jianbo He
- Soybean Research Institute, Nanjing Agricultural University, Nanjing 210095, China; (W.W.); (B.Z.); (J.H.); (J.Z.); (C.L.); (X.C.); (G.X.); (H.X.)
- MOA National Center for Soybean Improvement, Nanjing Agricultural University, Nanjing 210095, China
- MOA Key Laboratory of Biology and Genetic Improvement of Soybean (General), Nanjing Agricultural University, Nanjing 210095, China
- State Key Laboratory for Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing 210095, China
| | - Jinming Zhao
- Soybean Research Institute, Nanjing Agricultural University, Nanjing 210095, China; (W.W.); (B.Z.); (J.H.); (J.Z.); (C.L.); (X.C.); (G.X.); (H.X.)
- MOA National Center for Soybean Improvement, Nanjing Agricultural University, Nanjing 210095, China
- MOA Key Laboratory of Biology and Genetic Improvement of Soybean (General), Nanjing Agricultural University, Nanjing 210095, China
- State Key Laboratory for Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing 210095, China
- Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing 210095, China
| | - Cheng Liu
- Soybean Research Institute, Nanjing Agricultural University, Nanjing 210095, China; (W.W.); (B.Z.); (J.H.); (J.Z.); (C.L.); (X.C.); (G.X.); (H.X.)
- MOA National Center for Soybean Improvement, Nanjing Agricultural University, Nanjing 210095, China
| | - Xianlian Chen
- Soybean Research Institute, Nanjing Agricultural University, Nanjing 210095, China; (W.W.); (B.Z.); (J.H.); (J.Z.); (C.L.); (X.C.); (G.X.); (H.X.)
- MOA National Center for Soybean Improvement, Nanjing Agricultural University, Nanjing 210095, China
| | - Guangnan Xing
- Soybean Research Institute, Nanjing Agricultural University, Nanjing 210095, China; (W.W.); (B.Z.); (J.H.); (J.Z.); (C.L.); (X.C.); (G.X.); (H.X.)
- MOA National Center for Soybean Improvement, Nanjing Agricultural University, Nanjing 210095, China
- MOA Key Laboratory of Biology and Genetic Improvement of Soybean (General), Nanjing Agricultural University, Nanjing 210095, China
- State Key Laboratory for Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing 210095, China
- Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing 210095, China
| | - Shouyi Chen
- Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing 100101, China;
| | - Han Xing
- Soybean Research Institute, Nanjing Agricultural University, Nanjing 210095, China; (W.W.); (B.Z.); (J.H.); (J.Z.); (C.L.); (X.C.); (G.X.); (H.X.)
- MOA National Center for Soybean Improvement, Nanjing Agricultural University, Nanjing 210095, China
- MOA Key Laboratory of Biology and Genetic Improvement of Soybean (General), Nanjing Agricultural University, Nanjing 210095, China
- State Key Laboratory for Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing 210095, China
- Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing 210095, China
| | - Junyi Gai
- Soybean Research Institute, Nanjing Agricultural University, Nanjing 210095, China; (W.W.); (B.Z.); (J.H.); (J.Z.); (C.L.); (X.C.); (G.X.); (H.X.)
- MOA National Center for Soybean Improvement, Nanjing Agricultural University, Nanjing 210095, China
- MOA Key Laboratory of Biology and Genetic Improvement of Soybean (General), Nanjing Agricultural University, Nanjing 210095, China
- State Key Laboratory for Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing 210095, China
- Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing 210095, China
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11
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Zhao Q, Wang H, Du Y, Rogers HJ, Wu Z, Jia S, Yao X, Xie F, Liu W. MSH2 and MSH6 in Mismatch Repair System Account for Soybean ( Glycine max (L.) Merr.) Tolerance to Cadmium Toxicity by Determining DNA Damage Response. J Agric Food Chem 2020; 68:1974-1985. [PMID: 31971785 DOI: 10.1021/acs.jafc.9b06599] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/15/2023]
Abstract
Our aim was to investigate DNA mismatch repair (MMR) genes regulating cadmium tolerance in two soybean cultivars. Cultivars Liaodou 10 (LD10, Cd-sensitive) and Shennong 20 (SN20, Cd-tolerant) seedlings were grown hydroponically on Murashige and Skoog (MS) media containing 0-2.5 mg·L-1 Cd for 4 days. Cd stress induced less random amplified polymorphism DNA (RAPD) polymorphism in LD10 than in SN20 roots, causing G1/S arrest in LD10 and G2/M arrest in SN20 roots. Virus-induced gene silencing (VIGS) of MLH1 in LD10-TRV-MLH1 plantlets showed markedly diminished G1/S arrest but enhanced root length/area under Cd stress. However, an increase in G1/S arrest and reduction of G2/M arrest occurred in SN20-TRV-MSH2 and SN20-TRV-MSH6 plantlets with decreased root length/area under Cd stress. Taken together, we conclude that the low expression of MSH2 and MSH6, involved in the G2/M arrest, results in Cd-induced DNA damage recognition bypassing the MMR system to activate G1/S arrest with the assistance of MLH1. This then leads to repressed root growth in LD10, explaining the intervarietal difference in Cd tolerance in soybean.
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Affiliation(s)
- Qiang Zhao
- Agricultural College , Shenyang Agricultural University , Shenyang 110866 , PR China
| | - Hetong Wang
- College of Life Science and Bioengineering , Shenyang University , Shenyang 110044 , PR China
| | - Yanli Du
- Agricultural College , Shenyang Agricultural University , Shenyang 110866 , PR China
| | - Hilary J Rogers
- Cardiff University , School of Biosciences , Cardiff CF10 3TL , U.K
| | - Zhixin Wu
- Agricultural College , Shenyang Agricultural University , Shenyang 110866 , PR China
| | - Sen Jia
- Agricultural College , Shenyang Agricultural University , Shenyang 110866 , PR China
| | - Xingdong Yao
- Agricultural College , Shenyang Agricultural University , Shenyang 110866 , PR China
| | - Futi Xie
- Agricultural College , Shenyang Agricultural University , Shenyang 110866 , PR China
| | - Wan Liu
- Key Laboratory of Pollution Ecology and Environmental Engineering , Institute of Applied Ecology, Chinese Academy of Sciences , Shenyang 110016 , PR China
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12
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Tanaka S, Ario N, Nakagawa ACS, Tomita Y, Murayama N, Taniguchi T, Hamaoka N, Iwaya-Inoue M, Ishibashi Y. Effects of light quality on pod elongation in soybean (Glycine max (L.) Merr.) and cowpea (Vigna unguiculata (L.) Walp.). Plant Signal Behav 2017; 12:e1327495. [PMID: 28532320 PMCID: PMC5566249 DOI: 10.1080/15592324.2017.1327495] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/03/2017] [Revised: 04/29/2017] [Accepted: 05/01/2017] [Indexed: 05/29/2023]
Abstract
Soybean pods are located at the nodes, where they are in the shadow, whereas cowpea pods are located outside of the leaves and are exposed to sunlight. To compare the effects of light quality on pod growth in soybean and cowpea, we measured the length of pods treated with white, blue, red or far-red light. In both species, pods elongated faster during the dark period than during the light period in all light treatments except red light treatment in cowpea. Red light significantly suppressed pod elongation in soybean during the dark and light periods. On the other hand, the elongation of cowpea pods treated with red light markedly promoted during the light period. These results suggested that the difference in the pod set sites between soybean and cowpea might account for the difference in their red light responses for pod growth.
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Affiliation(s)
- Seiya Tanaka
- Graduate School of Bioresource and Bioenvironmental Sciences, Kyushu University, Hakozaki, Higashi-ku, Fukuoka, Japan
| | - Nobuyuki Ario
- Graduate School of Bioresource and Bioenvironmental Sciences, Kyushu University, Hakozaki, Higashi-ku, Fukuoka, Japan
| | | | - Yuki Tomita
- Graduate School of Bioresource and Bioenvironmental Sciences, Kyushu University, Hakozaki, Higashi-ku, Fukuoka, Japan
| | - Naoki Murayama
- Graduate School of Bioresource and Bioenvironmental Sciences, Kyushu University, Hakozaki, Higashi-ku, Fukuoka, Japan
| | - Takatoshi Taniguchi
- Graduate School of Bioresource and Bioenvironmental Sciences, Kyushu University, Hakozaki, Higashi-ku, Fukuoka, Japan
| | - Norimitsu Hamaoka
- Graduate School of Bioresource and Bioenvironmental Sciences, Kyushu University, Hakozaki, Higashi-ku, Fukuoka, Japan
- Faculty of Agriculture, Kyushu University, Hakozaki, Higashi-ku, Fukuoka, Japan
| | - Mari Iwaya-Inoue
- Graduate School of Bioresource and Bioenvironmental Sciences, Kyushu University, Hakozaki, Higashi-ku, Fukuoka, Japan
- Faculty of Agriculture, Kyushu University, Hakozaki, Higashi-ku, Fukuoka, Japan
| | - Yushi Ishibashi
- Graduate School of Bioresource and Bioenvironmental Sciences, Kyushu University, Hakozaki, Higashi-ku, Fukuoka, Japan
- Faculty of Agriculture, Kyushu University, Hakozaki, Higashi-ku, Fukuoka, Japan
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13
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Liu X, Wu JA, Ren H, Qi Y, Li C, Cao J, Zhang X, Zhang Z, Cai Z, Gai J. Genetic variation of world soybean maturity date and geographic distribution of maturity groups. Breed Sci 2017; 67:221-232. [PMID: 28744175 PMCID: PMC5515309 DOI: 10.1270/jsbbs.16167] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/12/2016] [Accepted: 02/19/2017] [Indexed: 06/02/2023]
Abstract
The maturity date of soybean (Glycine max (L.) Merr.) is sensitive to photoperiod, which varies with latitude and growing seasons. The maturity group (MG) system, composed of 13 MGs, is a major approach in characterizing varieties' ecological properties and adaptable areas. A total of 512 world soybean varieties, including 48 MG checks, were tested at a major site (Nanjing, 32.04°N) with portions tested in supplementary sites (Heihe, 50.22°N; Mudanjiang, 44.60°N; Jining, 35.38°N and Nanning, 22.84°N) in China to explore the world-wide MG distribution. The maturity date of the world soybean varied greatly (75-201 d) in Nanjing. Along with soybeans disseminated to new areas, the MGs further expanded during the last 70 years from MG I-VII to the early MG 0-000 in the north continents and to the late MG VIII-X in the south continents with the growth period structure differentiated into two subgroups in each MG 0-VIII except V. The cluster analysis among MGs and subgroups using genome-wide markers validated the MG sequential emergence order and the subgroup differentiation in eight MGs. For future evaluation, in addition to one major site (Nanjing), one supplementary southern site (Nanning) and one supplementary northern site (Heihe) are sufficient.
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Affiliation(s)
- Xueqin Liu
- Soybean Research Institute, Nanjing Agricultural University; MOA National Center for Soybean Improvement; MOA Key Laboratory of Biology and Genetic Improvement of Soybean; National Key Laboratory for Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University,
Nanjing 210095,
China
| | - Ji-an Wu
- Heihe Academy of Agricultural Sciences,
Heihe 164300,
China
| | - Haixiang Ren
- Mudanjiang Academy of Agricultural Sciences,
Mudanjiang 157041,
China
| | - Yuxin Qi
- Mudanjiang Academy of Agricultural Sciences,
Mudanjiang 157041,
China
| | - Chunyan Li
- Shengfeng Experiment Station,
Jining 272400,
China
| | - Jiqiu Cao
- Shengfeng Experiment Station,
Jining 272400,
China
| | | | - Zhipeng Zhang
- Soybean Research Institute, Nanjing Agricultural University; MOA National Center for Soybean Improvement; MOA Key Laboratory of Biology and Genetic Improvement of Soybean; National Key Laboratory for Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University,
Nanjing 210095,
China
| | - Zhaoyan Cai
- Guangxi Academy of Agricultural Sciences,
Nanning 530007,
China
| | - Junyi Gai
- Soybean Research Institute, Nanjing Agricultural University; MOA National Center for Soybean Improvement; MOA Key Laboratory of Biology and Genetic Improvement of Soybean; National Key Laboratory for Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University,
Nanjing 210095,
China
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