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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. Mol Breed 2023; 43:60. [PMID: 37496825 PMCID: PMC10366068 DOI: 10.1007/s11032-023-01406-z] [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] [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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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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Gong L, Li X, Wu S, Jiang L. Prediction of potential distribution of soybean in the frigid region in China with MaxEnt modeling. ECOL INFORM 2022. [DOI: 10.1016/j.ecoinf.2022.101834] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
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Li C, Wang W, Pan Y, Liu F, He J, Liu C, Cao J, Zhang X, Zhao J, Gai J. Germplasm Sources, Genetic Richness, and Population Differentiation of Modern Chinese Soybean Cultivars Based on Pedigree Integrated With Genomic-Marker Analysis. Front Plant Sci 2022; 13:945839. [PMID: 35898228 PMCID: PMC9309878 DOI: 10.3389/fpls.2022.945839] [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] [Figures] [Subscribe] [Scholar Register] [Received: 05/17/2022] [Accepted: 06/15/2022] [Indexed: 06/15/2023]
Abstract
Soybean is a native crop in China for ≈ 5,000 years. The 560 cultivars released in 2006-2015, commercialized with seeds available publicly, were collected (designated modern Chinese soybean cultivars, MCSCs), as a part of 2,371 ones released during ~100 years' breeding history. The MCSCs with their parental pedigrees were gathered, including 279, 155, and 126 cultivars from Northeast and Northwest China (NNC), Huang-Huai-Hai Valleys (HHH), and Southern China (SC), respectively. The MCSCs were tested in the field, genotyped with sequencing, and analyzed for their germplasm sources, genetic richness, and population differentiation based on pedigree integrated with genomic-marker analysis. The main results were as follows: (i) The MCSCs covering 12 of the global 13 MGs (maturity groups) showing different ecoregions with different cropping systems caused their different MG constitutions. (ii) Parental pedigree analysis showed 718 immediate parents and 604 terminal ancestors involved in MCSCs, from which 41 core-terminal ancestors were identified. (iii) NNC was richer in allele number and specific present/deficient alleles, and genetically distant from HHH and SC. (iv) The geographic grouping of MCSCs was partially consistent with marker-based clustering, indicating multiple genetic backgrounds in three eco-subpopulations. (v) Eleven major core-terminal ancestor-derived families were identified, including four derived from ancestors in NNC, four from HHH, and three from SC, containing 463 (82.68%) MCSCs with some cross-distribution among ecoregions. (vi) CGS (coefficient of genetic similarity) calculated from genomic markers showed more precision than COP (coefficient of parentage) using pedigree information in evaluating genetic relationship/differentiation. Overall, through pedigree and genomic-marker analyses, the germplasm constitutions of the three eco-subpopulations were relatively self-sufficient, and germplasm exchange is seriously required for further improvement.
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Affiliation(s)
- Chunyan Li
- 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 & Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing, China
- MARA Key Laboratory of Germplasm Enhancement and Breeding Technology of Soybean, Jiaxiang, 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 & Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing, 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 & Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing, China
| | - Fangdong 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 & Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing, China
| | - Jianbo He
- Soybean Research Institute & MARA National Center for Soybean Improvement & MARA Key Laboratory of Biology and Genetic Improvement of Soybean (General) & State Key Laboratory for Crop Genetics and Germplasm Enhancement & Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing, China
| | - Chuanxiang Liu
- MARA Key Laboratory of Germplasm Enhancement and Breeding Technology of Soybean, Jiaxiang, China
| | - Jiqiu Cao
- MARA Key Laboratory of Germplasm Enhancement and Breeding Technology of Soybean, Jiaxiang, China
| | - Xiaoyan Zhang
- MARA Key Laboratory of Germplasm Enhancement and Breeding Technology of Soybean, Jiaxiang, 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 & Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing, China
| | - Junyi Gai
- Soybean Research Institute & MARA National Center for Soybean Improvement & MARA Key Laboratory of Biology and Genetic Improvement of Soybean (General) & State Key Laboratory for Crop Genetics and Germplasm Enhancement & Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing, China
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Jia H, Liang X, Zhang L, Zhang J, Sapey E, Liu X, Sun Y, Sun S, Yan H, Lu W, Han T. Improving Ultra-Low Temperature Preservation Technologies of Soybean Pollen for Off-Season and Off-Site Hybridization. Front Plant Sci 2022; 13:920522. [PMID: 35845709 PMCID: PMC9280911 DOI: 10.3389/fpls.2022.920522] [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] [Figures] [Subscribe] [Scholar Register] [Received: 04/14/2022] [Accepted: 06/01/2022] [Indexed: 06/15/2023]
Abstract
Preserving viable pollen is of great interest to breeders to maintain desirable germplasm for future inbreeding. Ultra-low temperature preservation of pollen is an effective and safe way for long-term storage of plant germplasm resources. In this study, we improved methods for the preservation of soybean pollen at ultra-low temperature. Soybean flowers at the initially-open stage were collected at 6-10 a.m. during the fully-bloom stage of soybean plants and were dehydrated for 10 h and then frozen and stored at -196 or -80°C. In vitro culture experiments showed that the viability of preserved pollen remained as high as about 90%. The off-season (local site Heihe) and off-site (Beijing, after long-distance express delivery from Heihe) hybridization verification was conducted, and no significant difference in true hybrid rate was founded between the preserved pollen and the fresh pollen. The ultra-low temperature preservation technology for soybean pollen could break the spatiotemporal limit of soybean hybridization and facilitate the development of engineered soybean breeding.
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Affiliation(s)
- Hongchang Jia
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
- Heihe Branch, Heilongjiang Academy of Agricultural Sciences, Heihe, China
| | - Xin Liang
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Lixin Zhang
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Jinmei Zhang
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Enoch Sapey
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
- Council for Scientific and Industrial Research (CSIR)-Oil Palm Research Institute, Kade, Ghana
| | - Xianyuan Liu
- Heihe Branch, Heilongjiang Academy of Agricultural Sciences, Heihe, China
| | - Yanhui Sun
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Shi Sun
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Hongrui Yan
- Heihe Branch, Heilongjiang Academy of Agricultural Sciences, Heihe, China
| | - Wencheng Lu
- Heihe Branch, Heilongjiang Academy of Agricultural Sciences, Heihe, China
| | - Tianfu Han
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
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6
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Gebregziabher BS, Zhang S, Ghosh S, Shaibu AS, Azam M, Abdelghany AM, Qi J, Agyenim-boateng KG, Htway HTP, Feng Y, Ma C, Li Y, Li J, Li B, Qiu L, Sun J. Origin, Maturity Group and Seed Coat Color Influence Carotenoid and Chlorophyll Concentrations in Soybean Seeds. Plants 2022; 11:848. [PMID: 35406828 PMCID: PMC9003432 DOI: 10.3390/plants11070848] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/16/2022] [Revised: 03/18/2022] [Accepted: 03/20/2022] [Indexed: 01/30/2023]
Abstract
Soybean (Glycine max (L.) Merrill) seeds are abundant in physiologically active metabolites, including carotenoids and chlorophylls, and are used as an affordable source of functional foods that promote and maintain human health. The distribution and variation of soybean seed metabolites are influenced by plant genetic characteristics and environmental factors. Here, we investigated the effects of germplasm origin, genotype, seed coat color and maturity group (MG) on the concentration variation of carotenoid and chlorophyll components in 408 soybean germplasm accessions collected from China, Japan, the USA and Russia. The results showed that genotype, germplasm origin, seed color, and MG were significant variation sources of carotenoid and chlorophyll contents in soybean seeds. The total carotenoids showed about a 25-fold variation among the soybean germplasms, with an overall mean of 12.04 µg g−1. Russian soybeans yielded 1.3-fold higher total carotenoids compared with Chinese and Japanese soybeans. Similarly, the total chlorophylls were substantially increased in Russian soybeans compared to the others. Soybeans with black seed coat color contained abundant concentrations of carotenoids, with mainly lutein (19.98 µg g−1), β-carotene (0.64 µg g−1) and total carotenoids (21.04 µg g−1). Concentrations of lutein, total carotenoids and chlorophylls generally decreased in late MG soybeans. Overall, our results demonstrate that soybean is an excellent dietary source of carotenoids, which strongly depend on genetic factors, germplasm origin, MG and seed coat color. Thus, this study suggests that soybean breeders should consider these factors along with environmental factors in developing carotenoid-rich cultivars and related functional food resources.
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Awal Khan MA, Zhang S, Emon RM, Chen F, Song W, Wu T, Yuan S, Wu C, Hou W, Sun S, Fu Y, Jiang B, Han T. CONSTANS Polymorphism Modulates Flowering Time and Maturity in Soybean. Front Plant Sci 2022; 13:817544. [PMID: 35371153 PMCID: PMC8969907 DOI: 10.3389/fpls.2022.817544] [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] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/18/2021] [Accepted: 02/15/2022] [Indexed: 06/01/2023]
Abstract
CONSTANS (CO) plays a critical role in the photoperiodic flowering pathway. However, the function of soybean CO orthologs and the molecular mechanisms in regulating flowering remain largely unknown. This study characterized the natural variations in CO family genes and their association with flowering time and maturity in soybeans. A total of 21 soybean CO family genes (GmCOLs) were cloned and sequenced in 128 varieties covering 14 known maturity groups (MG 0000-MG X from earliest to latest maturity). Regarding the whole genomic region involving these genes, GmCOL1, GmCOL3, GmCOL8, GmCOL9, GmCOL10, and GmCOL13 were conserved, and the remaining 15 genes showed genetic variation that was brought about by mutation, namely, all single-nucleotide polymorphisms (SNPs) and insertions-deletions (InDels). In addition, a few genes showed some strong linkage disequilibrium. Point mutations were found in 15 GmCOL genes, which can lead to changes in the potential protein structure. Early flowering and maturation were related to eight genes (GmCOL1/3/4/8/13/15/16/19). For flowering and maturation, 11 genes (GmCOL2/5/6/14/20/22/23/24/25/26/28) expressed divergent physiognomy. Haplotype analysis indicated that the haplotypes of GmCOL5-Hap2, GmCOL13-Hap2/3, and GmCOL28-Hap2 were associated with flowering dates and soybean maturity. This study helps address the role of GmCOL family genes in adapting to diverse environments, particularly when it is necessary to regulate soybean flowering dates and maturity.
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Affiliation(s)
- Mohammad Abdul Awal Khan
- MARA Key Laboratory of Soybean Biology (Beijing), Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Shouwei Zhang
- MARA Key Laboratory of Soybean Biology (Beijing), Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Reza Mohammad Emon
- MARA Key Laboratory of Soybean Biology (Beijing), Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
- Plant Breeding Division, Bangladesh Institute of Nuclear Agriculture, Mymensingh, Bangladesh
| | - Fulu Chen
- MARA Key Laboratory of Soybean Biology (Beijing), Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Wenwen Song
- MARA Key Laboratory of Soybean Biology (Beijing), Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Tingting Wu
- MARA Key Laboratory of Soybean Biology (Beijing), Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Shan Yuan
- MARA Key Laboratory of Soybean Biology (Beijing), Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Cunxiang Wu
- MARA Key Laboratory of Soybean Biology (Beijing), Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Wensheng Hou
- MARA Key Laboratory of Soybean Biology (Beijing), Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Shi Sun
- MARA Key Laboratory of Soybean Biology (Beijing), Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Yongfu Fu
- MARA Key Laboratory of Soybean Biology (Beijing), Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Bingjun Jiang
- MARA Key Laboratory of Soybean Biology (Beijing), Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Tianfu Han
- MARA Key Laboratory of Soybean Biology (Beijing), Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
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Ghosh S, Zhang S, Azam M, Gebregziabher BS, Abdelghany AM, Shaibu AS, Qi J, Feng Y, Agyenim-Boateng KG, Liu Y, Feng H, Li Y, Li J, Li B, Sun J. Natural Variation of Seed Tocopherol Composition in Diverse World Soybean Accessions from Maturity Group 0 to VI Grown in China. Plants (Basel) 2022; 11:206. [PMID: 35050094 PMCID: PMC8779575 DOI: 10.3390/plants11020206] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [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: 12/09/2021] [Revised: 01/04/2022] [Accepted: 01/07/2022] [Indexed: 06/14/2023]
Abstract
Tocopherols are natural antioxidants that increase the stability of fat-containing foods and are well known for their health benefits. To investigate the variation in seed tocopherol composition of soybeans from different origins, 493 soybean accessions from different countries (China, USA, Japan, and Russia) belonging to 7 maturity groups (MG 0-VI) were grown in 2 locations (Beijing and Hainan Provinces of China) for 2 years (2017 and 2018). The results showed that significant differences (p < 0.001) were observed among the accessions and origins for individual and total tocopherol contents. The total tocopherol content ranged from 118.92 μg g-1 to 344.02 μg g-1. Accessions from the USA had the highest average concentration of γ- and total tocopherols (152.92 and 238.21 μg g-1, respectively), whereas a higher level of α-tocopherol (12.82 μg g-1) was observed in the Russian accessions. The maturity group of the accession significantly (p < 0.001) influenced all tocopherol components, and higher levels of α-, γ-, and total tocopherols were observed in early maturing accessions, while late-maturing accessions exhibited higher levels of δ-tocopherol. The inclination of tocopherol concentrations with various MGs provided further evidence of the significance of MG in soybean breeding for seed tocopherol components. Furthermore, the correlation between the seed tocopherol components and geographical factors revealed that α-, γ-, and total tocopherols had significant positive correlations with latitude, while δ-tocopherol showed an opposite trend. The elite accessions with high and stable tocopherol concentrations determined could be used to develop functional foods, industrial materials, and breeding lines to improve tocopherol composition in soybean seeds.
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Affiliation(s)
- Suprio Ghosh
- The National Engineering Laboratory for Crop Molecular Breeding, MARA Key Laboratory of Soybean Biology (Beijing), Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, 12 Zhongguancun South Street, Beijing 100081, China; (S.G.); (S.Z.); (M.A.); (B.S.G.); (A.M.A.); (A.S.S.); (J.Q.); (Y.F.); (K.G.A.-B.); (Y.L.); (H.F.); (Y.L.); (J.L.)
- Bangladesh Agricultural Research Institute, Gazipur 1701, Bangladesh
| | - Shengrui Zhang
- The National Engineering Laboratory for Crop Molecular Breeding, MARA Key Laboratory of Soybean Biology (Beijing), Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, 12 Zhongguancun South Street, Beijing 100081, China; (S.G.); (S.Z.); (M.A.); (B.S.G.); (A.M.A.); (A.S.S.); (J.Q.); (Y.F.); (K.G.A.-B.); (Y.L.); (H.F.); (Y.L.); (J.L.)
| | - Muhammad Azam
- The National Engineering Laboratory for Crop Molecular Breeding, MARA Key Laboratory of Soybean Biology (Beijing), Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, 12 Zhongguancun South Street, Beijing 100081, China; (S.G.); (S.Z.); (M.A.); (B.S.G.); (A.M.A.); (A.S.S.); (J.Q.); (Y.F.); (K.G.A.-B.); (Y.L.); (H.F.); (Y.L.); (J.L.)
| | - Berhane S. Gebregziabher
- The National Engineering Laboratory for Crop Molecular Breeding, MARA Key Laboratory of Soybean Biology (Beijing), Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, 12 Zhongguancun South Street, Beijing 100081, China; (S.G.); (S.Z.); (M.A.); (B.S.G.); (A.M.A.); (A.S.S.); (J.Q.); (Y.F.); (K.G.A.-B.); (Y.L.); (H.F.); (Y.L.); (J.L.)
- Crop Sciences Research Department, Mehoni Agricultural Research Center, Maichew 7020, Ethiopia
| | - Ahmed M. Abdelghany
- The National Engineering Laboratory for Crop Molecular Breeding, MARA Key Laboratory of Soybean Biology (Beijing), Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, 12 Zhongguancun South Street, Beijing 100081, China; (S.G.); (S.Z.); (M.A.); (B.S.G.); (A.M.A.); (A.S.S.); (J.Q.); (Y.F.); (K.G.A.-B.); (Y.L.); (H.F.); (Y.L.); (J.L.)
- Crop Science Department, Faculty of Agriculture, Damanhour University, Damanhour 22516, Egypt
| | - Abdulwahab S. Shaibu
- The National Engineering Laboratory for Crop Molecular Breeding, MARA Key Laboratory of Soybean Biology (Beijing), Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, 12 Zhongguancun South Street, Beijing 100081, China; (S.G.); (S.Z.); (M.A.); (B.S.G.); (A.M.A.); (A.S.S.); (J.Q.); (Y.F.); (K.G.A.-B.); (Y.L.); (H.F.); (Y.L.); (J.L.)
- Department of Agronomy, Bayero University, Kano 700001, Nigeria
| | - Jie Qi
- The National Engineering Laboratory for Crop Molecular Breeding, MARA Key Laboratory of Soybean Biology (Beijing), Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, 12 Zhongguancun South Street, Beijing 100081, China; (S.G.); (S.Z.); (M.A.); (B.S.G.); (A.M.A.); (A.S.S.); (J.Q.); (Y.F.); (K.G.A.-B.); (Y.L.); (H.F.); (Y.L.); (J.L.)
| | - Yue Feng
- The National Engineering Laboratory for Crop Molecular Breeding, MARA Key Laboratory of Soybean Biology (Beijing), Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, 12 Zhongguancun South Street, Beijing 100081, China; (S.G.); (S.Z.); (M.A.); (B.S.G.); (A.M.A.); (A.S.S.); (J.Q.); (Y.F.); (K.G.A.-B.); (Y.L.); (H.F.); (Y.L.); (J.L.)
| | - Kwadwo Gyapong Agyenim-Boateng
- The National Engineering Laboratory for Crop Molecular Breeding, MARA Key Laboratory of Soybean Biology (Beijing), Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, 12 Zhongguancun South Street, Beijing 100081, China; (S.G.); (S.Z.); (M.A.); (B.S.G.); (A.M.A.); (A.S.S.); (J.Q.); (Y.F.); (K.G.A.-B.); (Y.L.); (H.F.); (Y.L.); (J.L.)
| | - Yitian Liu
- The National Engineering Laboratory for Crop Molecular Breeding, MARA Key Laboratory of Soybean Biology (Beijing), Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, 12 Zhongguancun South Street, Beijing 100081, China; (S.G.); (S.Z.); (M.A.); (B.S.G.); (A.M.A.); (A.S.S.); (J.Q.); (Y.F.); (K.G.A.-B.); (Y.L.); (H.F.); (Y.L.); (J.L.)
| | - Huoyi Feng
- The National Engineering Laboratory for Crop Molecular Breeding, MARA Key Laboratory of Soybean Biology (Beijing), Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, 12 Zhongguancun South Street, Beijing 100081, China; (S.G.); (S.Z.); (M.A.); (B.S.G.); (A.M.A.); (A.S.S.); (J.Q.); (Y.F.); (K.G.A.-B.); (Y.L.); (H.F.); (Y.L.); (J.L.)
| | - Yecheng Li
- The National Engineering Laboratory for Crop Molecular Breeding, MARA Key Laboratory of Soybean Biology (Beijing), Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, 12 Zhongguancun South Street, Beijing 100081, China; (S.G.); (S.Z.); (M.A.); (B.S.G.); (A.M.A.); (A.S.S.); (J.Q.); (Y.F.); (K.G.A.-B.); (Y.L.); (H.F.); (Y.L.); (J.L.)
| | - Jing Li
- The National Engineering Laboratory for Crop Molecular Breeding, MARA Key Laboratory of Soybean Biology (Beijing), Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, 12 Zhongguancun South Street, Beijing 100081, China; (S.G.); (S.Z.); (M.A.); (B.S.G.); (A.M.A.); (A.S.S.); (J.Q.); (Y.F.); (K.G.A.-B.); (Y.L.); (H.F.); (Y.L.); (J.L.)
| | - Bin Li
- The National Engineering Laboratory for Crop Molecular Breeding, MARA Key Laboratory of Soybean Biology (Beijing), Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, 12 Zhongguancun South Street, Beijing 100081, China; (S.G.); (S.Z.); (M.A.); (B.S.G.); (A.M.A.); (A.S.S.); (J.Q.); (Y.F.); (K.G.A.-B.); (Y.L.); (H.F.); (Y.L.); (J.L.)
| | - Junming Sun
- The National Engineering Laboratory for Crop Molecular Breeding, MARA Key Laboratory of Soybean Biology (Beijing), Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, 12 Zhongguancun South Street, Beijing 100081, China; (S.G.); (S.Z.); (M.A.); (B.S.G.); (A.M.A.); (A.S.S.); (J.Q.); (Y.F.); (K.G.A.-B.); (Y.L.); (H.F.); (Y.L.); (J.L.)
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9
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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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10
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Schogolev AS, Raievska IM. Role of nitrogen deficiency on growth and development near isogenic by E genes lines of soybean co-inoculated with nitrogen-fixing bacteria. Regul Mech Biosyst 2021. [DOI: 10.15421/022144] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2023] Open
Abstract
Nitrogen deficiency is a limiting factor in increasing efficiency of crop production in terrestrial ecosystems, and the transformation of inert nitrogen to forms that can be assimilated by plants is mediated by soil microorganisms. Symbiotic nitrogen-fixing bacteria and roots depend on each other and have developed various mechanisms for symbiotic coexistence. The aim of this work was to investigate the role of nitrogen deficiency on growth and development near isogenic by E genes lines of soybean (Glycine max (L.) Merr.): short-day (SD) line with genotype Е1е2е3(Е4е5Е7), and photoperiodic insensitive (PPI) line with genotype е1е2е3(Е4е5Е7) grown from seeds inoculated with active strains of Bradyrhizobium japonicum against the background of local populations of diazotrophs of the genus Azotobacter spp. and establish how the soybean – Bradyrhizobium symbiosis will develop as the genes of both microsymbionts and macrosymbionts are responsible for the formation of the symbiotic complex. Plants were grown in a vegetation chamber, in sand culture. To assess the quantitative composition of microorganisms in the rhizosphere and rhizoplanes, 6 plants were selected from each soybean line, then separation of the zones of the rhizosphere and rhizoplanes was performed using the method of washing and the resulting suspension was used for inoculation on dense nutrient media (mannitol-yeast agar medium and Ashby medium). The results of study showed that seed inoculation and co-inoculation provides faster formation of the symbiotic soybean – Bradyrhizobium complex. Differences in nodulation rates between the short-day line with genotype Е1е2е3(Е4е5Е7), and a photoperiodic insensitive line with genotype е1е2е3(Е4е5Е7) were identified. Determination of the amount of B. japonicum on the medium of mannitol-yeast agar in the rhizosphere and rhizoplane showed that inoculation by B. japonicum strain 634b caused a significant increase in the amount B. japonicum in the rhizosphere and rhizoplane in both soybean lines, comparison with non-inoculated seeds. Then, co-inoculation by B. japonicum strain 634b + Azotobacter chroococcum significantly increased the amount of B. japonicum only in the rhizoplane and decreased their number in the rhizosphere. Determination of the amount of A. chroococcum on the Ashby elective medium in the rhizosphere and rhizoplane showed that the inoculation by B. japonicum strain 634b caused a significant decrease in the amount of A. chroococcum both in the rhizosphere and in the rhizoplane of the PPI line of soybean, and in the rhizosphere the SD line, in comparison with non-inoculated seeds. That can testify to the competitive interaction of these microorganisms. However, the co-inoculation by B. japonicum strain 634b + A. chroococcum in the SD line significantly increased the number of A. chroococcum in the rhizoplane and decreased their number in the rhizosphere, in the PPI line their number decreased in the rhizoplane and increased in the rhizosphere, in comparison with non-inoculated seeds. Probably, the E genes (their dominant or recessive state) of soybean isogenic lines affect the regulation of the content and distribution of sugars. It was established that the nitrogen deficiency stimulated development of the root system of plants and the synthesized sugars were distributed predominantly to the root system growth. We suppose that the seeds’ inoculation had extended sugar consumption to the symbiont, due to which it compensates the lack of nitrogen, but leads to a slower growth of the root system.
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11
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Fu M, Wang Y, Ren H, Du W, Wang D, Bao R, Yang X, Tian Z, Fu L, Cheng Y, Su J, Sun B, Zhao J, Gai J. Genetic dynamics of earlier maturity group emergence in south-to-north extension of Northeast China soybeans. Theor Appl Genet 2020; 133:1839-1857. [PMID: 32030467 DOI: 10.1007/s00122-020-03558-4] [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] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/22/2019] [Accepted: 01/24/2020] [Indexed: 06/10/2023]
Abstract
KEY MESSAGE This population genetic study is characterized with direct comparisons of days to flowering QTL-allele matrices between newly evolved and originally old maturity groups of soybeans to explore its evolutionary dynamics using the RTM-GWAS procedure. The Northeast China (NEC) soybeans are the major germplasm source of modern soybean production in Americas (> 80% of the world total). NEC is a relatively new soybean area in China, expanded after its nomadic status in the seventeenth century. At nine sites of four ecoregions in NEC, 361 varieties were tested for their days to flowering (DTF), a geography-sensitive trait as an indicator for maturity groups (MGs). The DTF reduced obviously along with soybeans extended to higher latitudes, ranging in 41-83 days and MG 000-III. Using the RTM-GWAS (restricted two-stage multi-locus model genome-wide association study) procedure, 81 QTLs with 342 alleles were identified, accounting for 77.85% genetic contribution (R2 = 0.01-7.74%/locus), and other 20.75% (98.60-77.85%, h2 = 98.60%) genetic variation was due to a collective of unmapped QTLs. With soybeans northward, breeding effort made the original MG I-III evolved to MG 0-00-000. In direct comparisons of QTL-allele matrices among MGs, the genetic dynamics are identified with local exotic introduction/migration (58.48%) as the first and selection against/exclusion of positive alleles causing new recombination (40.64%) as the second, while only a few allele emergence/mutation happened (0.88%, limited in MG 0, not in MG 00-000). In new MG emergence, 24 QTLs with 19 candidate genes are the major sources. A genetic potential of further DTF shortening (13-21 days) is predicted for NEC population. The QTL detection in individual ecoregions showed various ecoregion-specific QTLs-alleles/genes after co-localization treatment (removing the random environment shifting ones).
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Affiliation(s)
- Mengmeng Fu
- Soybean Research Institute; MARA National Center for Soybean Improvement; MARA Key Laboratory of Biology and Genetic Improvement of Soybean; National Key Laboratory for Crop Genetics and Germplasm Enhancement; Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing, 210095, Jiangsu, China
| | - Yanping Wang
- Mudanjiang Research and Development Center for Soybean; Mudanjiang Experiment Station of the National Center for Soybean Improvement, Mudanjiang Branch of Heilongjiang Academy of Agricultural Sciences, Mudanjiang, 157041, Heilongjiang, China
| | - Haixiang Ren
- Mudanjiang Research and Development Center for Soybean; Mudanjiang Experiment Station of the National Center for Soybean Improvement, Mudanjiang Branch of Heilongjiang Academy of Agricultural Sciences, Mudanjiang, 157041, Heilongjiang, China
| | - Weiguang Du
- Mudanjiang Research and Development Center for Soybean; Mudanjiang Experiment Station of the National Center for Soybean Improvement, Mudanjiang Branch of Heilongjiang Academy of Agricultural Sciences, Mudanjiang, 157041, Heilongjiang, China
| | - Deliang Wang
- Heilongjiang Academy of Land-reclamation Sciences, Jiamusi, 154007, Heilongjiang, China
| | - Rongjun Bao
- Bei'an Branch of Heilongjiang Academy of Agricultural Sciences, Bei'an, 164009, Heilongjiang, China
| | - Xingyong Yang
- Keshan Branch of Heilongjiang Academy of Agricultural Sciences, Keshan, 161606, Heilongjiang, China
| | - Zhongyan Tian
- Daqing Branch of Heilongjiang Academy of Agricultural Sciences, Daqing, 163316, Heilongjiang, China
| | - Lianshun Fu
- Tieling Academy of Agricultural Sciences, Tieling, 112616, Liaoning, China
| | - Yanxi Cheng
- Changchun Academy of Agricultural Sciences, Changchun, 130111, Jilin, China
| | - Jiangshun Su
- Baicheng Academy of Agricultural Sciences, Baicheng, 137000, Jinlin, China
| | - Bincheng Sun
- Hulunbeier Academy of Agricultural Sciences, Hulunbeier, 162650, Inner Mongolia, China
| | - Jinming Zhao
- Soybean Research Institute; MARA National Center for Soybean Improvement; MARA Key Laboratory of Biology and Genetic Improvement of Soybean; National Key Laboratory for Crop Genetics and Germplasm Enhancement; Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing, 210095, Jiangsu, China
- Mudanjiang Research and Development Center for Soybean; Mudanjiang Experiment Station of the National Center for Soybean Improvement, Mudanjiang Branch of Heilongjiang Academy of Agricultural Sciences, Mudanjiang, 157041, Heilongjiang, China
| | - Junyi Gai
- Soybean Research Institute; MARA National Center for Soybean Improvement; MARA Key Laboratory of Biology and Genetic Improvement of Soybean; National Key Laboratory for Crop Genetics and Germplasm Enhancement; Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing, 210095, Jiangsu, China.
- Mudanjiang Research and Development Center for Soybean; Mudanjiang Experiment Station of the National Center for Soybean Improvement, Mudanjiang Branch of Heilongjiang Academy of Agricultural Sciences, Mudanjiang, 157041, Heilongjiang, China.
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12
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Kumagai E, Yamada T, Hasegawa T. Is the yield change due to warming affected by photoperiod sensitivity? Effects of the soybean
E4
locus. Food Energy Secur 2020. [DOI: 10.1002/fes3.186] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023] Open
Affiliation(s)
- Etsushi Kumagai
- Agricultural Meteorology Group Agro‐Environmental Research Division Tohoku Agricultural Research Center NARO Morioka Japan
| | - Tetsuya Yamada
- Soybean Breeding Unit Institute of Crop Science NARO Tsukuba Japan
| | - Toshihiro Hasegawa
- Agricultural Meteorology Group Agro‐Environmental Research Division Tohoku Agricultural Research Center NARO Morioka Japan
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13
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Li M, Liu Y, Wang C, Yang X, Li D, Zhang X, Xu C, Zhang Y, Li W, Zhao L. Identification of Traits Contributing to High and Stable Yields in Different Soybean Varieties Across Three Chinese Latitudes. Front Plant Sci 2020; 10:1642. [PMID: 32038668 PMCID: PMC6985368 DOI: 10.3389/fpls.2019.01642] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/22/2019] [Accepted: 11/21/2019] [Indexed: 06/01/2023]
Abstract
Soybean yield is a complex quantitative trait, which is greatly affected by environmental conditions. The main objective of this study is not only to identify specific traits contributing to yield in different latitudes, which can be further used in breeding, but also to identify the outperforming varieties, as this can help to select new lines with these traits. One hundred and seventy-three soybean genotypes were tested in three different ecological environments, including Harbin, Changchun, and Shenyang in China during 2015-2016 cropping seasons. The evaluation on the different agronomic and physiological traits indicated that the soybean varieties with higher plant height, more nodes of main stem, branches, pods, grains, and 100-grain weight, or longer growth periods may have higher yield. Pods, grains and 100-grain weight can be used as direct selection criteria for yield increase, and likewise the other traits such as plant height, nodes of main stem, branches, growth periods indirectly affected yield by affecting the three traits above. The effect of genotype × environment (G × E) interaction on different agronomic traits was significant. The representativeness and discriminability for grains yield per plant was the most significant in Harbin, which could be used to screen varieties with high yield and wider adaptability. Genotype "Suinong 1" was considered stable with higher value of grain yield per plant than other genotypes used in this study. As the yield of certain soybean cultivars may be significantly reduced if they are grown in a region as little as 2°N beyond its normal cultivation latitudes, therefore, the identification and analysis on the stable and widely adaptive soybean genotypes would be very important, and it would provide the significant reference accordance of soybean variety selection for the soybean breeders.
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Affiliation(s)
| | | | | | | | | | | | | | | | - Wenbin Li
- *Correspondence: Wenbin Li, ; Lin Zhao,
| | - Lin Zhao
- *Correspondence: Wenbin Li, ; Lin Zhao,
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14
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Abdelghany AM, Zhang S, Azam M, Shaibu AS, Feng Y, Qi J, Li Y, Tian Y, Hong H, Li B, Sun J. Natural Variation in Fatty Acid Composition of Diverse World Soybean Germplasms Grown in China. Agronomy 2020; 10:24. [DOI: 10.3390/agronomy10010024] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
Soybean (Glycine max L. Merr.) is one of the most important crops in the world. Its major content of vegetable oil made it widely used for human consumption and several food industries. To investigate the variation in seed fatty acid composition of soybeans from different origins, a set of 633 soybean accessions originated from four diverse germplasm collections—including China, United States of America (USA), Japan, and Russia—were grown in three locations, Beijing, Anhui, and Hainan for two years. The results showed significant differences (P < 0.001) among the four germplasm origins for all fatty acid contents investigated. Higher levels, on average, of palmitic acid (PA) and linolenic acid (LNA) were observed in Russian germplasm (12.31% and 8.15%, respectively), whereas higher levels of stearic acid (SA) and oleic acid (OA) were observed in Chinese germplasm (3.95% and 21.95%, respectively). The highest level of linoleic acid (LA) was noticed in the USA germplasm accessions (56.34%). The largest variation in fatty acid composition was found in LNA, while a large variation was observed between Chinese and USA germplasms for LA level. Maturity group (MG) significantly (P < 0.0001) affected all fatty acids and higher levels of PA, SA, and OA were observed in early maturing accessions, while higher levels of LA and LNA were observed in late maturing accessions. The trends of fatty acids concentrations with different MG in this study further provide an evidence of the importance of MG in breeding for such soybean seed components. Collectively, the unique accessions identified in this study can be used to strengthen the soybean breeding programs for meeting various human nutrition patterns around the globe.
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15
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Volpato L, Alves RS, Teodoro PE, Vilela de Resende MD, Nascimento M, Nascimento ACC, Ludke WH, Lopes da Silva F, Borém A. Multi-trait multi-environment models in the genetic selection of segregating soybean progeny. PLoS One 2019; 14:e0215315. [PMID: 30998705 PMCID: PMC6472761 DOI: 10.1371/journal.pone.0215315] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2018] [Accepted: 03/30/2019] [Indexed: 11/19/2022] Open
Abstract
At present, single-trait best linear unbiased prediction (BLUP) is the standard method for genetic selection in soybean. However, when genetic selection is performed based on two or more genetically correlated traits and these are analyzed individually, selection bias may arise. Under these conditions, considering the correlation structure between the evaluated traits may provide more-accurate genetic estimates for the evaluated parameters, even under environmental influences. The present study was thus developed to examine the efficiency and applicability of multi-trait multi-environment (MTME) models by the residual maximum likelihood (REML/BLUP) and Bayesian approaches in the genetic selection of segregating soybean progeny. The study involved data pertaining to 203 soybean F2:4 progeny assessed in two environments for the following traits: number of days to maturity (DM), 100-seed weight (SW), and average seed yield per plot (SY). Variance components and genetic and non-genetic parameters were estimated via the REML/BLUP and Bayesian methods. The variance components estimated and the breeding values and genetic gains predicted with selection through the Bayesian procedure were similar to those obtained by REML/BLUP. The frequentist and Bayesian MTME models provided higher estimates of broad-sense heritability per plot (or heritability of total effects of progeny; [Formula: see text]) and mean accuracy of progeny than their respective single-trait versions. Bayesian analysis provided the credibility intervals for the estimates of [Formula: see text]. Therefore, MTME led to greater predicted gains from selection. On this basis, this procedure can be efficiently applied in the genetic selection of segregating soybean progeny.
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Affiliation(s)
- Leonardo Volpato
- Federal University of Viçosa—Department of Plant Science, University Campus, Viçosa, Minas Gerais, Brazil
| | - Rodrigo Silva Alves
- Federal University of Viçosa—Department of General Biology, University Campus, Viçosa, Minas Gerais, Brazil
| | - Paulo Eduardo Teodoro
- Federal University of Mato Grosso do Sul—Department of Plant Science, University Campus, Chapadão do Sul, Mato Grosso do Sul, Brazil
| | | | - Moysés Nascimento
- Federal University of Viçosa—Department of Statistics, University Campus, Viçosa, Minas Gerais, Brazil
| | | | - Willian Hytalo Ludke
- Federal University of Viçosa—Department of Plant Science, University Campus, Viçosa, Minas Gerais, Brazil
| | - Felipe Lopes da Silva
- Federal University of Viçosa—Department of Plant Science, University Campus, Viçosa, Minas Gerais, Brazil
| | - Aluízio Borém
- Federal University of Viçosa—Department of Plant Science, University Campus, Viçosa, Minas Gerais, Brazil
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