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Li X, Tan P, Xiong G, Ma R, Gao W, Jiang A, Liu J, Du C, Zhang J, Zhang X, Zhang L, Yi Z, Fang X, Zhang J. Densification of Genetic Map and Stable Quantitative Trait Locus Analysis for Amino Acid Content of Seed in Soybean ( Glycine max L.). PLANTS (BASEL, SWITZERLAND) 2024; 13:2020. [PMID: 39124138 PMCID: PMC11314226 DOI: 10.3390/plants13152020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/30/2024] [Revised: 07/06/2024] [Accepted: 07/18/2024] [Indexed: 08/12/2024]
Abstract
Soybean, a primary vegetable protein source, boasts favorable amino acid profiles; however, its composition still falls short of meeting human nutritional demands. The soybean amino acid content is a quantitative trait controlled by multiple genes. In this study, an F2 population of 186 individual plants derived from the cross between ChangJiangChun2 and JiYu166 served as the mapping population. Based on the previously published genetic map of our lab, we increased the density of the genetic map and constructed a new genetic map containing 518 SSR (simple sequence repeats) markers and 64 InDel (insertion-deletion) markers, with an average distance of 5.27 cm and a total length of 2881.2 cm. The content of eight essential amino acids was evaluated in the F2:5, F2:6, and BLUP (best linear unbiased prediction). A total of 52 QTLs (quantitative trait loci) were identified, and 13 QTL clusters were identified, among which loci02.1 and loci11.1 emerged as stable QTL clusters, exploring candidate genes within these regions. Through GO enrichment and gene annotation, 16 candidate genes associated with soybean essential amino acid content were predicted. This study would lay the foundation for elucidating the regulatory mechanisms of essential amino acid content and contribute to germplasm innovation in soybeans.
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Affiliation(s)
- Xi Li
- College of Agronomy and Biotechnology, Southwest University, Chongqing 400715, China
| | - Pingting Tan
- College of Agronomy and Biotechnology, Southwest University, Chongqing 400715, China
| | - Guoxi Xiong
- College of Agronomy and Biotechnology, Southwest University, Chongqing 400715, China
| | - Ronghan Ma
- College of Agronomy and Biotechnology, Southwest University, Chongqing 400715, China
| | - Weiran Gao
- College of Agronomy and Biotechnology, Southwest University, Chongqing 400715, China
| | - Aohua Jiang
- College of Agronomy and Biotechnology, Southwest University, Chongqing 400715, China
| | - Jiaqi Liu
- College of Agronomy and Biotechnology, Southwest University, Chongqing 400715, China
| | - Chengzhang Du
- Institute of Specialty Crop, Chongqing Academy of Agricultural Sciences, Chongqing 402160, China
| | - Jijun Zhang
- Institute of Specialty Crop, Chongqing Academy of Agricultural Sciences, Chongqing 402160, China
| | - Xiaochun Zhang
- Institute of Specialty Crop, Chongqing Academy of Agricultural Sciences, Chongqing 402160, China
| | - Li Zhang
- Chongqing Three Gorges Academy of Agricultural Sciences, Chongqing 404100, China
| | - Zelin Yi
- College of Agronomy and Biotechnology, Southwest University, Chongqing 400715, China
| | - Xiaomei Fang
- College of Agronomy and Biotechnology, Southwest University, Chongqing 400715, China
| | - Jian Zhang
- College of Agronomy and Biotechnology, Southwest University, Chongqing 400715, China
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Guo G, Li W, Zheng J, Liu A, Zhang Q, Wang Y. PhI(OAc) 2-Promoted 1,2-Transfer Reaction between 1,1-Disubstituted Allylic Alcohols and Thiophenols. Molecules 2024; 29:3112. [PMID: 38999064 PMCID: PMC11243614 DOI: 10.3390/molecules29133112] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2024] [Revised: 06/25/2024] [Accepted: 06/25/2024] [Indexed: 07/14/2024] Open
Abstract
The PhI(OAc)2-promoted 1,2-transfer reaction between allylic alcohols and thiophenols, conducted in an argon atmosphere, has proven to be effective in producing β-carbonyl sulfides from 1,1-disubstituted allylic alcohols in high yields. This method offers a fast and efficient way to synthesize β-carbonyl sulfides, which are valuable intermediates in organic synthesis. This discussion focuses on the effects of the oxidizer, temperature, and solvent on the reaction. A proposed tentative mechanism for this reaction is also discussed.
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Affiliation(s)
- Guozhe Guo
- Gansu Key Laboratory of Efficient Utilization of Oil and Gas Resources, College of Petroleum and Chemical Engineering, Longdong University, Qingyang 745000, China
| | - Wenduo Li
- Gansu Key Laboratory of Efficient Utilization of Oil and Gas Resources, College of Petroleum and Chemical Engineering, Longdong University, Qingyang 745000, China
| | - Jingjing Zheng
- Gansu Key Laboratory of Efficient Utilization of Oil and Gas Resources, College of Petroleum and Chemical Engineering, Longdong University, Qingyang 745000, China
| | - Aping Liu
- Gansu Key Laboratory of Efficient Utilization of Oil and Gas Resources, College of Petroleum and Chemical Engineering, Longdong University, Qingyang 745000, China
| | - Qi Zhang
- Gansu Key Laboratory of Efficient Utilization of Oil and Gas Resources, College of Petroleum and Chemical Engineering, Longdong University, Qingyang 745000, China
| | - Yatao Wang
- Gansu Key Laboratory of Efficient Utilization of Oil and Gas Resources, College of Petroleum and Chemical Engineering, Longdong University, Qingyang 745000, China
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Nagesh CR, Prashat G R, Goswami S, Bharadwaj C, Praveen S, Ramesh SV, Vinutha T. Sulfate transport and metabolism: strategies to improve the seed protein quality. Mol Biol Rep 2024; 51:242. [PMID: 38300326 DOI: 10.1007/s11033-023-09166-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2023] [Accepted: 12/15/2023] [Indexed: 02/02/2024]
Abstract
Sulfur-containing amino acids (SAA), namely methionine, and cysteine are crucial essential amino acids (EAA) considering the dietary requirements of humans and animals. However, a few crop plants, especially legumes, are characterized with suboptimal levels of these EAA thereby limiting their nutritive value. Hence, improved comprehension of the mechanistic perspective of sulfur transport and assimilation into storage reserve, seed storage protein (SSP), is imperative. Efforts to augment the level of SAA in seed storage protein form an integral component of strategies to balance nutritive quality and quantity. In this review, we highlight the emerging trends in the sulfur biofortification approaches namely transgenics, genetic and molecular breeding, and proteomic rebalancing with sulfur nutrition. The transgenic 'push and pull strategy' could enhance sulfur capture and storage by expressing genes that function as efficient transporters, sulfate assimilatory enzymes, sulfur-rich foreign protein sinks, or by suppressing catabolic enzymes. Modern molecular breeding approaches that adopt high throughput screening strategies and machine learning algorithms are invaluable in identifying candidate genes and alleles associated with SAA content and developing improved crop varieties. Sulfur is an essential plant nutrient and its optimal uptake is crucial for seed sulfur metabolism, thereby affecting seed quality and yields through proteomic rebalance between sulfur-rich and sulfur-poor seed storage proteins.
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Affiliation(s)
- C R Nagesh
- Division of Biochemistry, ICAR-Indian Agricultural Research Institute, New Delhi, 110012, India
| | - Rama Prashat G
- Division of Genetics, ICAR-Indian Agricultural Research Institute, New Delhi, 110012, India
| | - Suneha Goswami
- Division of Biochemistry, ICAR-Indian Agricultural Research Institute, New Delhi, 110012, India
| | - C Bharadwaj
- Division of Genetics, ICAR-Indian Agricultural Research Institute, New Delhi, 110012, India
| | - Shelly Praveen
- Division of Biochemistry, ICAR-Indian Agricultural Research Institute, New Delhi, 110012, India
| | - S V Ramesh
- ICAR-Central Plantation Crops Research Institute, 671 124, Kasaragod, Kerala, India.
| | - T Vinutha
- Division of Biochemistry, ICAR-Indian Agricultural Research Institute, New Delhi, 110012, India.
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Soybean sorting based on protein content using X-ray fluorescence spectrometry. Food Chem 2023; 412:135548. [PMID: 36738531 DOI: 10.1016/j.foodchem.2023.135548] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2022] [Revised: 01/13/2023] [Accepted: 01/21/2023] [Indexed: 01/30/2023]
Abstract
The purpose of this research was to evaluate performance of an energy-dispersive X-ray fluorescence (XRF) sensor to classify soybean based on protein content. The hypothesis was that sulfur signals and other XRF spectral features can be used as proxies to infer soybean protein content. Sample preparation and equipment settings to optimize detection of S and other specific emission lines were tested for this application. A logistic regression model for classifying soybean as high- or low-protein was developed based on XRF spectra and protein contents. Additionally, the model was validated with an independent set of samples. Global accuracies of the method were 0.83 (training set) and 0.81 (test set) and the corresponding kappa indices were 0.66 and 0.61, respectively. These numbers indicated satisfactory performance of the sensor, suggesting that XRF spectral features can be applied for screening protein content in soybean.
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Kafer JM, Molinari MDC, Henning FA, Koltun A, Marques VV, Marin SRR, Nepomuceno AL, Mertz-Henning LM. Transcriptional Profile of Soybean Seeds with Contrasting Seed Coat Color. PLANTS (BASEL, SWITZERLAND) 2023; 12:1555. [PMID: 37050181 PMCID: PMC10097363 DOI: 10.3390/plants12071555] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/07/2023] [Revised: 03/25/2023] [Accepted: 03/29/2023] [Indexed: 06/19/2023]
Abstract
Soybean is the primary source of vegetable protein and is used for various purposes, mainly to feed animals. This crop can have diverse seed coat colors, varying from yellow, black, brown, and green to bicolor. Black seed coat cultivars have already been assigned as favorable for both seed and grain production. Thus, this work aimed to identify genes associated with soybean seed quality by comparing the transcriptomes of soybean seeds with contrasting seed coat colors. The results from RNA-seq analyses were validated with real-time PCR using the cultivar BRS 715A (black seed coat) and the cultivars BRS 413 RR and DM 6563 IPRO (yellow seed coat). We found 318 genes differentially expressed in all cultivars (freshly harvested seeds and seeds stored in cold chamber). From the in silico analysis of the transcriptomes, the following genes were selected and validated with RT-qPCR: ACS1, ACSF3, CYP90A1, CYP710A1, HCT, CBL, and SAHH. These genes are genes induced in the black seed coat cultivar and are part of pathways responsible for ethylene, lipid, brassinosteroid, lignin, and sulfur amino acid biosynthesis. The BRSMG 715A gene has almost 4times more lignin than the yellow seed coat cultivars. These attributes are related to the BRSMG 715A cultivar's higher seed quality, which translates to more longevity and resistance to moisture and mechanical damage. Future silencing studies may evaluate the knockout of these genes to better understand the biology of soybean seeds with black seed coat.
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Affiliation(s)
- João M. Kafer
- Biotechnology Department, Londrina State University, Londrina 86057-970, PR, Brazil
| | - Mayla D. C. Molinari
- Arthur Bernardes Foundation, Embrapa Soja, Londrina 86085-981, PR, Brazil; (M.D.C.M.); (V.V.M.)
| | - Fernando A. Henning
- Embrapa Soja, Londrina 86085-981, PR, Brazil; (F.A.H.); (S.R.R.M.); (A.L.N.)
| | - Alessandra Koltun
- Agronomy Department, State University of Maringá, Maringá 87020-900, PR, Brazil;
| | - Viviani V. Marques
- Arthur Bernardes Foundation, Embrapa Soja, Londrina 86085-981, PR, Brazil; (M.D.C.M.); (V.V.M.)
| | - Silvana R. R. Marin
- Embrapa Soja, Londrina 86085-981, PR, Brazil; (F.A.H.); (S.R.R.M.); (A.L.N.)
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Zhong Y, Wen K, Li X, Wang S, Li S, Zeng Y, Cheng Y, Ma Q, Nian H. Identification and Mapping of QTLs for Sulfur-Containing Amino Acids in Soybean ( Glycine max L.). JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY 2023; 71:398-410. [PMID: 36574335 DOI: 10.1021/acs.jafc.2c05896] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/17/2023]
Abstract
Soybean is a major source of high-quality protein for humans and animals. The content of sulfur-containing amino acids (SAA) in soybean is insufficient, which has become the main factor limiting soybean nutrition. In this study, we used the high-density genetic maps derived from Guizao 1 and Brazil 13 to evaluate the quantitative trait loci of cysteine (Cys), methionine (Met), SAA, glycinin (7S), β-conglycinin (11S), ratio of glycinin to β-conglycinin (RGC), and protein content (PC). In genetic map linkage analysis, the major and stable 44 QTLs were detected, which shared nine bin intervals. Among them, the bin interval (bin157-bin160) on chromosome 5 was detected in multiple environments as a stable QTL, which was linked to 11S, 7S, RGC, and SSA. Based on the analysis of bioinformatics and RNA-sequencing data, 16 differentially expressed genes (DEGs) within these QTLs were selected as candidate genes. These results will help to elucidate the genetic mechanism of soybean SAA-related traits and provide the basis for the gene mining of sulfur-containing amino acids.
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Affiliation(s)
- Yiwang Zhong
- The State Key Laboratory for Conservation and Utilization of Subtropical Agro-bioresources, South China Agricultural University, Guangzhou 510642, Guangdong, People's Republic of China
- Guangdong Laboratory for Lingnan Modern Agriculture, Guangzhou 510642, Guangdong, People's Republic of China
- The Guangdong Subcenter of the National Center for Soybean Improvement, College of Agriculture, South China Agricultural University, Guangzhou 510642, Guangdong, People's Republic of China
| | - Ke Wen
- The State Key Laboratory for Conservation and Utilization of Subtropical Agro-bioresources, South China Agricultural University, Guangzhou 510642, Guangdong, People's Republic of China
- Guangdong Laboratory for Lingnan Modern Agriculture, Guangzhou 510642, Guangdong, People's Republic of China
- The Guangdong Subcenter of the National Center for Soybean Improvement, College of Agriculture, South China Agricultural University, Guangzhou 510642, Guangdong, People's Republic of China
- Key Laboratory of Vegetable Biology of Hainan Province, Vegetable Research Institute of Hainan Academy of Agricultural Sciences, Haikou 570228, Hainan, People's Republic of China
- Hainan Yazhou Bay Seed Laboratory, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Sanya 572025, Hainan, People's Republic of China
| | - Xingang Li
- The State Key Laboratory for Conservation and Utilization of Subtropical Agro-bioresources, South China Agricultural University, Guangzhou 510642, Guangdong, People's Republic of China
- Guangdong Laboratory for Lingnan Modern Agriculture, Guangzhou 510642, Guangdong, People's Republic of China
- The Guangdong Subcenter of the National Center for Soybean Improvement, College of Agriculture, South China Agricultural University, Guangzhou 510642, Guangdong, People's Republic of China
| | - Shasha Wang
- The State Key Laboratory for Conservation and Utilization of Subtropical Agro-bioresources, South China Agricultural University, Guangzhou 510642, Guangdong, People's Republic of China
- Guangdong Laboratory for Lingnan Modern Agriculture, Guangzhou 510642, Guangdong, People's Republic of China
- The Guangdong Subcenter of the National Center for Soybean Improvement, College of Agriculture, South China Agricultural University, Guangzhou 510642, Guangdong, People's Republic of China
| | - Sansan Li
- The State Key Laboratory for Conservation and Utilization of Subtropical Agro-bioresources, South China Agricultural University, Guangzhou 510642, Guangdong, People's Republic of China
- Guangdong Laboratory for Lingnan Modern Agriculture, Guangzhou 510642, Guangdong, People's Republic of China
- The Guangdong Subcenter of the National Center for Soybean Improvement, College of Agriculture, South China Agricultural University, Guangzhou 510642, Guangdong, People's Republic of China
| | - Yuhong Zeng
- The State Key Laboratory for Conservation and Utilization of Subtropical Agro-bioresources, South China Agricultural University, Guangzhou 510642, Guangdong, People's Republic of China
- Guangdong Laboratory for Lingnan Modern Agriculture, Guangzhou 510642, Guangdong, People's Republic of China
- The Guangdong Subcenter of the National Center for Soybean Improvement, College of Agriculture, South China Agricultural University, Guangzhou 510642, Guangdong, People's Republic of China
| | - Yanbo Cheng
- The State Key Laboratory for Conservation and Utilization of Subtropical Agro-bioresources, South China Agricultural University, Guangzhou 510642, Guangdong, People's Republic of China
- Guangdong Laboratory for Lingnan Modern Agriculture, Guangzhou 510642, Guangdong, People's Republic of China
- The Guangdong Subcenter of the National Center for Soybean Improvement, College of Agriculture, South China Agricultural University, Guangzhou 510642, Guangdong, People's Republic of China
| | - Qibin Ma
- The State Key Laboratory for Conservation and Utilization of Subtropical Agro-bioresources, South China Agricultural University, Guangzhou 510642, Guangdong, People's Republic of China
- Guangdong Laboratory for Lingnan Modern Agriculture, Guangzhou 510642, Guangdong, People's Republic of China
- The Guangdong Subcenter of the National Center for Soybean Improvement, College of Agriculture, South China Agricultural University, Guangzhou 510642, Guangdong, People's Republic of China
| | - Hai Nian
- The State Key Laboratory for Conservation and Utilization of Subtropical Agro-bioresources, South China Agricultural University, Guangzhou 510642, Guangdong, People's Republic of China
- Guangdong Laboratory for Lingnan Modern Agriculture, Guangzhou 510642, Guangdong, People's Republic of China
- The Guangdong Subcenter of the National Center for Soybean Improvement, College of Agriculture, South China Agricultural University, Guangzhou 510642, Guangdong, People's Republic of China
- Hainan Yazhou Bay Seed Laboratory, Sanya Nanfan Research Institute of Hainan University, Sanya 572025, Hainan, People's Republic of China
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Yuan W, Huang J, Li H, Ma Y, Gui C, Huang F, Feng X, Yu D, Wang H, Kan G. Genetic dissection reveals the complex architecture of amino acid composition in soybean seeds. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2023; 136:17. [PMID: 36670242 DOI: 10.1007/s00122-023-04280-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/14/2022] [Accepted: 11/26/2022] [Indexed: 06/17/2023]
Abstract
Five loci related to soybean protein and amino acid contents were colocated by performing linkage mapping and GWAS. The haplotype analysis showed that Glyma.08G109100 may be useful to improve the soybean seed composition. Soybean (Glycine max (L.) Merr.) seeds are good protein sources. Although genetic variation is abundant, natural variation in seed amino acids and their derived traits is lacking across soybean accessions. Here, we determined the contents of protein and 17 amino acids, obtained 36 derived traits based on the protein and total amino acid contents, and derived 34 traits based on seven amino acid family groups. Furthermore, we performed a linkage analysis of the contents of 17 amino acids and 73 amino acid-derived traits based on the recombinant inbred line (RIL)-derived Kefeng No. 1 × Nannong 1138-2. Six hundred thirty-nine quantitative trait loci (QTLs) were identified, explaining 6.07-39.00% of the phenotypic variation. Among these loci, five were detected in diverse soybean accessions using a genome-wide association study. A network analysis revealed that some loci that were significantly associated with multiple amino acids were tightly linked on chromosome 8 based on linkage disequilibrium values, which also further confirmed the results of the correlation analysis among amino acid traits. Through a combination of a genome-wide association study, linkage analysis, qRT-PCR, and genomic polymorphism comparison, Glyma.08G109100 on chromosome 8, which may affect amino acid contents, was selected. The haplotype analysis showed that Hap-T of Glyma.08G109100 may be useful to improve the contents of protein and 16 amino acids in soybean. This study provides new insights into the genetic basis of the amino acid composition in soybean seeds and may facilitate marker-based breeding of soybean with improved nutritional value.
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Affiliation(s)
- Wenjie Yuan
- National Key Laboratory of Crop Genetics and Germplasm Enhancement, National Center for Soybean Improvement, Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing, China
| | - Jie Huang
- National Key Laboratory of Crop Genetics and Germplasm Enhancement, National Center for Soybean Improvement, Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing, China
| | - Haiyang Li
- National Key Laboratory of Crop Genetics and Germplasm Enhancement, National Center for Soybean Improvement, Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing, China
- School of Life Sciences, Guangzhou University, Guangzhou, China
| | - Yujie Ma
- Key Laboratory of Plant Molecular Physiology, Institute of Botany, Chinese Academy of Sciences, Beijing, China
| | - Chunju Gui
- National Key Laboratory of Crop Genetics and Germplasm Enhancement, National Center for Soybean Improvement, Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing, China
| | - Fang Huang
- National Key Laboratory of Crop Genetics and Germplasm Enhancement, National Center for Soybean Improvement, Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing, China
| | - Xianzhong Feng
- Key Laboratory of Soybean Molecular Design Breeding, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun, China
| | - Deyue Yu
- National Key Laboratory of Crop Genetics and Germplasm Enhancement, National Center for Soybean Improvement, Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing, China
| | - Hui Wang
- National Key Laboratory of Crop Genetics and Germplasm Enhancement, National Center for Soybean Improvement, Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing, China.
| | - Guizhen Kan
- National Key Laboratory of Crop Genetics and Germplasm Enhancement, National Center for Soybean Improvement, Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing, China.
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Zhang S, Du H, Ma Y, Li H, Kan G, Yu D. Linkage and association study discovered loci and candidate genes for glycinin and β-conglycinin in soybean (Glycine max L. Merr.). TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2021; 134:1201-1215. [PMID: 33464377 DOI: 10.1007/s00122-021-03766-6] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/07/2020] [Accepted: 01/06/2021] [Indexed: 06/12/2023]
Abstract
KEY MESSAGE Linkage mapping and GWAS identified 67 QTLs related to soybean glycinin, β-conglycinin and relevant traits. Polymorphisms of the candidate gene Gy1 promoter were associated with the glycinin content in soybean. The major components of storage proteins in soybean seeds are glycinin and β-conglycinin, which play important roles in determining protein nutrition and soy food processing properties. Increasing the protein content while improving the ratio of glycinin to β-conglycinin is substantially important for soybean protein improvement. To investigate the genetic mechanism of storage protein subunits, 184 recombinant inbred lines (RILs) derived from a cross of Kefeng No. 1 and Nannong 1138-2 and 211 diverse soybean cultivars were used to detect loci related to glycinin (11S), β-conglycinin (7S), the sum of glycinin and β-conglycinin (SGC), and the ratio of glycinin to β-conglycinin (RGC). Sixty-seven QTLs and 11 hot genomic regions were identified as affecting the four traits. One genetic region (q10-1) on chromosome 10 was associated with multiple traits by both linkage and association analysis. Eight genes in 11 hot genomic regions might be related to soybean protein subunit. The candidate gene analysis showed that polymorphisms in Gy1 promoters were significantly correlated with the 11S content. The QTLs and candidate genes identified in the present study allow for further understanding the genetic basis of 11S and 7S regulation and provide useful information for marker-assisted selection (MAS) in soybean quality improvement.
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Affiliation(s)
- Shanshan Zhang
- National Center for Soybean Improvement, National Key Laboratory of Crop Genetics and Germplasm Enhancement, Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing, 210095, China
| | - Hongyang Du
- National Center for Soybean Improvement, National Key Laboratory of Crop Genetics and Germplasm Enhancement, Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing, 210095, China
| | - Yujie Ma
- National Center for Soybean Improvement, National Key Laboratory of Crop Genetics and Germplasm Enhancement, Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing, 210095, China
| | - Haiyang Li
- National Center for Soybean Improvement, National Key Laboratory of Crop Genetics and Germplasm Enhancement, Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing, 210095, China
- School of Life Sciences, Guangzhou University, Guangzhou, 510006, China
| | - Guizhen Kan
- National Center for Soybean Improvement, National Key Laboratory of Crop Genetics and Germplasm Enhancement, Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing, 210095, China.
| | - Deyue Yu
- National Center for Soybean Improvement, National Key Laboratory of Crop Genetics and Germplasm Enhancement, Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing, 210095, China.
- School of Life Sciences, Guangzhou University, Guangzhou, 510006, China.
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Gaikwad KB, Rani S, Kumar M, Gupta V, Babu PH, Bainsla NK, Yadav R. Enhancing the Nutritional Quality of Major Food Crops Through Conventional and Genomics-Assisted Breeding. Front Nutr 2020; 7:533453. [PMID: 33324668 PMCID: PMC7725794 DOI: 10.3389/fnut.2020.533453] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2020] [Accepted: 09/03/2020] [Indexed: 01/14/2023] Open
Abstract
Nutritional stress is making over two billion world population malnourished. Either our commercially cultivated varieties of cereals, pulses, and oilseed crops are deficient in essential nutrients or the soils in which these crops grow are becoming devoid of minerals. Unfortunately, our major food crops are poor sources of micronutrients required for normal human growth. To overcome the problem of nutritional deficiency, greater emphasis should be laid on the identification of genes/quantitative trait loci (QTLs) pertaining to essential nutrients and their successful deployment in elite breeding lines through marker-assisted breeding. The manuscript deals with information on identified QTLs for protein content, vitamins, macronutrients, micro-nutrients, minerals, oil content, and essential amino acids in major food crops. These QTLs can be utilized in the development of nutrient-rich crop varieties. Genome editing technologies that can rapidly modify genomes in a precise way and will directly enrich the nutritional status of elite varieties could hold a bright future to address the challenge of malnutrition.
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Affiliation(s)
- Kiran B. Gaikwad
- Division of Genetics, Indian Council of Agricultural Research (ICAR)-Indian Agricultural Research Institute, New Delhi, India
| | - Sushma Rani
- Indian Council of Agricultural Research (ICAR)-National Institute for Plant Biotechnology, New Delhi, India
| | - Manjeet Kumar
- Division of Genetics, Indian Council of Agricultural Research (ICAR)-Indian Agricultural Research Institute, New Delhi, India
| | - Vikas Gupta
- Division of Genetics, Indian Council of Agricultural Research (ICAR)-Indian Institute of Wheat and Barley Research, Karnal, India
| | - Prashanth H. Babu
- Division of Genetics, Indian Council of Agricultural Research (ICAR)-Indian Agricultural Research Institute, New Delhi, India
| | - Naresh Kumar Bainsla
- Division of Genetics, Indian Council of Agricultural Research (ICAR)-Indian Agricultural Research Institute, New Delhi, India
| | - Rajbir Yadav
- Division of Genetics, Indian Council of Agricultural Research (ICAR)-Indian Agricultural Research Institute, New Delhi, India
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