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Han D, Zhao X, Zhang D, Wang Z, Zhu Z, Sun H, Qu Z, Wang L, Liu Z, Zhu X, Yuan M. Genome-wide association studies reveal novel QTLs for agronomic traits in soybean. FRONTIERS IN PLANT SCIENCE 2024; 15:1375646. [PMID: 38807775 PMCID: PMC11132100 DOI: 10.3389/fpls.2024.1375646] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/24/2024] [Accepted: 04/15/2024] [Indexed: 05/30/2024]
Abstract
Introduction Soybean, as a globally significant crop, has garnered substantial attention due to its agricultural importance. The utilization of molecular approaches to enhance grain yield in soybean has gained popularity. Methods In this study, we conducted a genome-wide association study (GWAS) using 156 Chinese soybean accessions over a two-year period. We employed the general linear model (GLM) and the mixed linear model (MLM) to analyze three agronomic traits: pod number, grain number, and grain weight. Results Our findings revealed significant associations between qgPNpP-98, qgGNpP-89 and qgHGW-85 QTLs and pod number, grain number, and grain weight, respectively. These QTLs were identified on chromosome 16, a region spanning 413171bp exhibited associations with all three traits. Discussion These QTL markers identified in this study hold potential for improving yield and agronomic traits through marker-assisted selection and genomic selection in breeding programs.
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Affiliation(s)
- Dongwei Han
- Qiqihar Branch of Heilongjiang Academy of Agricultural Science, Qiqihar, Heilongjiang, China
- Heilongjiang Chinese Academy of Sciences Qiuying Zhang Soybean Scientist Studio, Qiqihar, Heilongjiang, China
| | - Xi Zhao
- Biotechnology Institute, Heilongjiang Academy of Agricultural Science, Harbin, Heilongjiang, China
| | - Di Zhang
- Qiqihar Branch of Heilongjiang Academy of Agricultural Science, Qiqihar, Heilongjiang, China
| | - Zhen Wang
- Qiqihar Branch of Heilongjiang Academy of Agricultural Science, Qiqihar, Heilongjiang, China
| | - Zhijia Zhu
- Qiqihar Branch of Heilongjiang Academy of Agricultural Science, Qiqihar, Heilongjiang, China
| | - Haoyue Sun
- Qiqihar Branch of Heilongjiang Academy of Agricultural Science, Qiqihar, Heilongjiang, China
| | - Zhongcheng Qu
- Qiqihar Branch of Heilongjiang Academy of Agricultural Science, Qiqihar, Heilongjiang, China
| | - Lianxia Wang
- Qiqihar Branch of Heilongjiang Academy of Agricultural Science, Qiqihar, Heilongjiang, China
| | - Zhangxiong Liu
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Xu Zhu
- Department of Research and Development, Ruibiotech Co., Ltd, Beijing, China
| | - Ming Yuan
- Qiqihar Branch of Heilongjiang Academy of Agricultural Science, Qiqihar, Heilongjiang, China
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Yu H, Bhat JA, Li C, Zhao B, Bu M, Zhang Z, Guo T, Feng X. Identification of superior and rare haplotypes to optimize branch number in soybean. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2024; 137:93. [PMID: 38570354 PMCID: PMC10991007 DOI: 10.1007/s00122-024-04596-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/30/2023] [Accepted: 03/07/2024] [Indexed: 04/05/2024]
Abstract
KEY MESSAGE Using the integrated approach in the present study, we identified eleven significant SNPs, seven stable QTLs and 20 candidate genes associated with branch number in soybean. Branch number is a key yield-related quantitative trait that directly affects the number of pods and seeds per soybean plant. In this study, an integrated approach with a genome-wide association study (GWAS) and haplotype and candidate gene analyses was used to determine the detailed genetic basis of branch number across a diverse set of soybean accessions. The GWAS revealed a total of eleven SNPs significantly associated with branch number across three environments using the five GWAS models. Based on the consistency of the SNP detection in multiple GWAS models and environments, seven genomic regions within the physical distance of ± 202.4 kb were delineated as stable QTLs. Of these QTLs, six QTLs were novel, viz., qBN7, qBN13, qBN16, qBN18, qBN19 and qBN20, whereas the remaining one, viz., qBN12, has been previously reported. Moreover, 11 haplotype blocks, viz., Hap4, Hap7, Hap12, Hap13A, Hap13B, Hap16, Hap17, Hap18, Hap19A, Hap19B and Hap20, were identified on nine different chromosomes. Haplotype allele number across the identified haplotype blocks varies from two to five, and different branch number phenotype is regulated by these alleles ranging from the lowest to highest through intermediate branching. Furthermore, 20 genes were identified underlying the genomic region of ± 202.4 kb of the identified SNPs as putative candidates; and six of them showed significant differential expression patterns among the soybean cultivars possessing contrasting branch number, which might be the potential candidates regulating branch number in soybean. The findings of this study can assist the soybean breeding programs for developing cultivars with desirable branch numbers.
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Affiliation(s)
- Hui Yu
- Key Laboratory of Soybean Molecular Design Breeding, State Key Laboratory of Black Soils Conservation and Utilization, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun, 130102, China
- Zhejiang Lab, Hangzhou, 310012, China
| | | | - Candong Li
- Jiamusi Branch Academy of Heilongjiang Academy of Agricultural Sciences, Jiamusi, 154007, China
| | - Beifang Zhao
- Key Laboratory of Soybean Molecular Design Breeding, State Key Laboratory of Black Soils Conservation and Utilization, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun, 130102, China
| | - Moran Bu
- Key Laboratory of Soybean Molecular Design Breeding, State Key Laboratory of Black Soils Conservation and Utilization, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun, 130102, China
- College of Advanced Agricultural Sciences, University of Chinese Academy of Sciences, Beijing, 101408, China
| | - Zhirui Zhang
- Key Laboratory of Soybean Molecular Design Breeding, State Key Laboratory of Black Soils Conservation and Utilization, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun, 130102, China
| | - Tai Guo
- Jiamusi Branch Academy of Heilongjiang Academy of Agricultural Sciences, Jiamusi, 154007, China
| | - Xianzhong Feng
- Key Laboratory of Soybean Molecular Design Breeding, State Key Laboratory of Black Soils Conservation and Utilization, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun, 130102, China.
- Zhejiang Lab, Hangzhou, 310012, China.
- College of Advanced Agricultural Sciences, University of Chinese Academy of Sciences, Beijing, 101408, China.
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Singer WM, Lee YC, Shea Z, Vieira CC, Lee D, Li X, Cunicelli M, Kadam SS, Khan MAW, Shannon G, Mian MAR, Nguyen HT, Zhang B. Soybean genetics, genomics, and breeding for improving nutritional value and reducing antinutritional traits in food and feed. THE PLANT GENOME 2023; 16:e20415. [PMID: 38084377 DOI: 10.1002/tpg2.20415] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/21/2023] [Revised: 10/25/2023] [Accepted: 10/27/2023] [Indexed: 12/22/2023]
Abstract
Soybean [Glycine max (L.) Merr.] is a globally important crop due to its valuable seed composition, versatile feed, food, and industrial end-uses, and consistent genetic gain. Successful genetic gain in soybean has led to widespread adaptation and increased value for producers, processors, and consumers. Specific focus on the nutritional quality of soybean seed composition for food and feed has further elucidated genetic knowledge and bolstered breeding progress. Seed components are historical and current targets for soybean breeders seeking to improve nutritional quality of soybean. This article reviews genetic and genomic foundations for improvement of nutritionally important traits, such as protein and amino acids, oil and fatty acids, carbohydrates, and specific food-grade considerations; discusses the application of advanced breeding technology such as CRISPR/Cas9 in creating seed composition variations; and provides future directions and breeding recommendations regarding soybean seed composition traits.
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Affiliation(s)
- William M Singer
- School of Plant and Environmental Sciences, Virginia Polytechnic Institute and State University, Blacksburg, Virginia, USA
| | - Yi-Chen Lee
- Department of Agriculture, Fort Hays State University, Hays, Kansas, USA
| | - Zachary Shea
- School of Plant and Environmental Sciences, Virginia Polytechnic Institute and State University, Blacksburg, Virginia, USA
| | - Caio Canella Vieira
- Department of Crop, Soil, and Environmental Sciences, University of Arkansas, Fayetteville, Arkansas, USA
| | - Dongho Lee
- Fisher Delta Research, Extension, and Education Center, University of Missouri, Portageville, Missouri, USA
| | - Xiaoying Li
- School of Plant and Environmental Sciences, Virginia Polytechnic Institute and State University, Blacksburg, Virginia, USA
| | - Mia Cunicelli
- Soybean and Nitrogen Fixation Research Unit, USDA-ARS, Raleigh, North Carolina, USA
| | - Shaila S Kadam
- Division of Plant Science and Technology, University of Missouri, Columbia, Missouri, USA
| | | | - Grover Shannon
- Fisher Delta Research, Extension, and Education Center, University of Missouri, Portageville, Missouri, USA
| | - M A Rouf Mian
- Soybean and Nitrogen Fixation Research Unit, USDA-ARS, Raleigh, North Carolina, USA
| | - Henry T Nguyen
- Division of Plant Science and Technology, University of Missouri, Columbia, Missouri, USA
| | - Bo Zhang
- School of Plant and Environmental Sciences, Virginia Polytechnic Institute and State University, Blacksburg, Virginia, USA
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Joshi B, Singh S, Tiwari GJ, Kumar H, Boopathi NM, Jaiswal S, Adhikari D, Kumar D, Sawant SV, Iquebal MA, Jena SN. Genome-wide association study of fiber yield-related traits uncovers the novel genomic regions and candidate genes in Indian upland cotton ( Gossypium hirsutum L.). FRONTIERS IN PLANT SCIENCE 2023; 14:1252746. [PMID: 37941674 PMCID: PMC10630025 DOI: 10.3389/fpls.2023.1252746] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/04/2023] [Accepted: 09/11/2023] [Indexed: 11/10/2023]
Abstract
Upland cotton (Gossypium hirsutum L.) is a major fiber crop that is cultivated worldwide and has significant economic importance. India harbors the largest area for cotton cultivation, but its fiber yield is still compromised and ranks 22nd in terms of productivity. Genetic improvement of cotton fiber yield traits is one of the major goals of cotton breeding, but the understanding of the genetic architecture underlying cotton fiber yield traits remains limited and unclear. To better decipher the genetic variation associated with fiber yield traits, we conducted a comprehensive genome-wide association mapping study using 117 Indian cotton germplasm for six yield-related traits. To accomplish this, we generated 2,41,086 high-quality single nucleotide polymorphism (SNP) markers using genotyping-by-sequencing (GBS) methods. Population structure, PCA, kinship, and phylogenetic analyses divided the germplasm into two sub-populations, showing weak relatedness among the germplasms. Through association analysis, 205 SNPs and 134 QTLs were identified to be significantly associated with the six fiber yield traits. In total, 39 novel QTLs were identified in the current study, whereas 95 QTLs overlapped with existing public domain data in a comparative analysis. Eight QTLs, qGhBN_SCY_D6-1, qGhBN_SCY_D6-2, qGhBN_SCY_D6-3, qGhSI_LI_A5, qGhLI_SI_A13, qGhLI_SI_D9, qGhBW_SCY_A10, and qGhLP_BN_A8 were identified. Gene annotation of these fiber yield QTLs revealed 2,509 unique genes. These genes were predominantly enriched for different biological processes, such as plant cell wall synthesis, nutrient metabolism, and vegetative growth development in the gene ontology (GO) enrichment study. Furthermore, gene expression analysis using RNAseq data from 12 diverse cotton tissues identified 40 candidate genes (23 stable and 17 novel genes) to be transcriptionally active in different stages of fiber, ovule, and seed development. These findings have revealed a rich tapestry of genetic elements, including SNPs, QTLs, and candidate genes, and may have a high potential for improving fiber yield in future breeding programs for Indian cotton.
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Affiliation(s)
- Babita Joshi
- Plant Genetic Resources and Improvement, CSIR-National Botanical Research Institute, Lucknow, India
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, India
| | - Sanjay Singh
- Division of Agricultural Bioinformatics, ICAR-Indian Agricultural Statistics Research Institute, New Delhi, India
| | - Gopal Ji Tiwari
- Plant Genetic Resources and Improvement, CSIR-National Botanical Research Institute, Lucknow, India
| | - Harish Kumar
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Regional Research Station, Faridkot, Punjab, India
| | - Narayanan Manikanda Boopathi
- Department of Plant Biotechnology, Centre for Plant Molecular Biology and Biotechnology, Tamil Nadu Agricultural University, Coimbatore, Tamil Nadu, India
| | - Sarika Jaiswal
- Division of Agricultural Bioinformatics, ICAR-Indian Agricultural Statistics Research Institute, New Delhi, India
| | - Dibyendu Adhikari
- Plant Ecology and Climate Change Science, CSIR-National Botanical Research Institute, Lucknow, India
| | - Dinesh Kumar
- Division of Agricultural Bioinformatics, ICAR-Indian Agricultural Statistics Research Institute, New Delhi, India
| | - Samir V. Sawant
- Molecular Biology & Biotechnology, CSIR-National Botanical Research Institute, Lucknow, India
| | - Mir Asif Iquebal
- Division of Agricultural Bioinformatics, ICAR-Indian Agricultural Statistics Research Institute, New Delhi, India
| | - Satya Narayan Jena
- Plant Genetic Resources and Improvement, CSIR-National Botanical Research Institute, Lucknow, India
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Li S, Cao Y, Wang C, Yan C, Sun X, Zhang L, Wang W, Song S. Genome-wide association mapping for yield-related traits in soybean (Glycine max) under well-watered and drought-stressed conditions. FRONTIERS IN PLANT SCIENCE 2023; 14:1265574. [PMID: 37877078 PMCID: PMC10593458 DOI: 10.3389/fpls.2023.1265574] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/23/2023] [Accepted: 09/18/2023] [Indexed: 10/26/2023]
Abstract
Soybean (Glycine max) productivity is significantly reduced by drought stress. Breeders are aiming to improve soybean grain yields both under well-watered (WW) and drought-stressed (DS) conditions, however, little is known about the genetic architecture of yield-related traits. Here, a panel of 188 soybean germplasm was used in a genome wide association study (GWAS) to identify single nucleotide polymorphism (SNP) markers linked to yield-related traits including pod number per plant (PN), biomass per plant (BM) and seed weight per plant (SW). The SLAF-seq genotyping was conducted on the population and three phenotype traits were examined in WW and DS conditions in four environments. Based on best linear unbiased prediction (BLUP) data and individual environmental analyses, 39 SNPs were significantly associated with three soybean traits under two conditions, which were tagged to 26 genomic regions by linkage disequilibrium (LD) analysis. Of these, six QTLs qPN-WW19.1, qPN-DS8.8, qBM-WW1, qBM-DS17.4, qSW-WW4 and qSW-DS8 were identified controlling PN, BM and SW of soybean. There were larger proportions of favorable haplotypes for locus qPN-WW19.1 and qSW-WW4 rather than qBM-WW1, qBM-DS17.4, qPN-DS8.8 and qSW-DS8 in both landraces and improved cultivars. In addition, several putative candidate genes such as Glyma.19G211300, Glyma.17G057100 and Glyma.04G124800, encoding E3 ubiquitin-protein ligase BAH1, WRKY transcription factor 11 and protein zinc induced facilitator-like 1, respectively, were predicted. We propose that the further exploration of these locus will facilitate accelerating breeding for high-yield soybean cultivars.
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Affiliation(s)
| | | | | | | | | | | | - Wenbin Wang
- Institute of Crop Research, Liaoning Academy of Agricultural Sciences, Shenyang, China
| | - Shuhong Song
- Institute of Crop Research, Liaoning Academy of Agricultural Sciences, Shenyang, China
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Zhang Q, Sun T, Wang J, Fei J, Liu Y, Liu L, Wang P. Genome-wide association study and high-quality gene mining related to soybean protein and fat. BMC Genomics 2023; 24:596. [PMID: 37805454 PMCID: PMC10559447 DOI: 10.1186/s12864-023-09687-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2023] [Accepted: 09/20/2023] [Indexed: 10/09/2023] Open
Abstract
BACKGROUND Soybean is one of the most important oil crops in the world, and its protein and fat are the primary sources of edible oil and vegetable protein. The effective components in soybean protein and fat have positive effects on improving human immunity, anti-tumor, and regulating blood lipids and metabolism. Therefore, increasing the contents of protein and fat in soybeans is essential for improving the quality of soybeans. RESULTS This study selected 292 soybean lines from different regions as experimental materials, based on SLAF-seq sequencing technology, and performed genome-wide association study (GWAS) on the phenotype data from 2019-2021 Planted at the experimental base of Jilin Agricultural University, such as the contents of protein and fat of soybeans. Through the GLM model and MLM model, four SNP sites (Gm09_39012959, Gm12_35492373, Gm16_9297124, and Gm20_24678362) that were significantly related to soybean fat content were associated for three consecutive years, and two SNP sites (Gm09_39012959 and Gm20_24678362) that were significantly related to soybean protein content were associated. By the annotation and enrichment of genes within the 100 Kb region of SNP loci flanking, two genes (Glyma.09G158100 and Glyma.09G158200) related to soybean protein synthesis and one gene (Glyma.12G180200) related to lipid metabolism were selected. By the preliminary verification of expression levels of genes with qPCR, it is found that during the periods of R6 and R7 of the accumulation of soybean protein and fat, Glyma.09G158100 and Glyma.09G158200 are positive regulatory genes that promote protein synthesis and accumulation, while Glyma.12G180200 is the negative regulatory gene that inhibits fat accumulation. CONCLUSIONS These results lay the basis for further verifying the gene function and studying the molecular mechanisms regulating the accumulation of protein and fat in soybean seeds.
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Affiliation(s)
- Qi Zhang
- Jilin Agricultural University, Changchun, China
| | | | - Jiabao Wang
- Jilin Agricultural University, Changchun, China
| | - JianBo Fei
- JiLin Agricultural Science and Technology University, Jilin, China
| | - Yufu Liu
- Jilin Provincial Seed Management Station, Jilin, China
| | - Lu Liu
- Jilin Agricultural University, Changchun, China
| | - Peiwu Wang
- Jilin Agricultural University, Changchun, China.
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Rani R, Raza G, Ashfaq H, Rizwan M, Razzaq MK, Waheed MQ, Shimelis H, Babar AD, Arif M. Genome-wide association study of soybean ( Glycine max [L.] Merr.) germplasm for dissecting the quantitative trait nucleotides and candidate genes underlying yield-related traits. FRONTIERS IN PLANT SCIENCE 2023; 14:1229495. [PMID: 37636105 PMCID: PMC10450938 DOI: 10.3389/fpls.2023.1229495] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/30/2023] [Accepted: 07/25/2023] [Indexed: 08/29/2023]
Abstract
Soybean (Glycine max [L.] Merr.) is one of the most significant crops in the world in terms of oil and protein. Owing to the rising demand for soybean products, there is an increasing need for improved varieties for more productive farming. However, complex correlation patterns among quantitative traits along with genetic interactions pose a challenge for soybean breeding. Association studies play an important role in the identification of accession with useful alleles by locating genomic sites associated with the phenotype in germplasm collections. In the present study, a genome-wide association study was carried out for seven agronomic and yield-related traits. A field experiment was conducted in 2015/2016 at two locations that include 155 diverse soybean germplasm. These germplasms were genotyped using SoySNP50K Illumina Infinium Bead-Chip. A total of 51 markers were identified for node number, plant height, pods per plant, seeds per plant, seed weight per plant, hundred-grain weight, and total yield using a multi-locus linear mixed model (MLMM) in FarmCPU. Among these significant SNPs, 18 were putative novel QTNs, while 33 co-localized with previously reported QTLs. A total of 2,356 genes were found in 250 kb upstream and downstream of significant SNPs, of which 17 genes were functional and the rest were hypothetical proteins. These 17 candidate genes were located in the region of 14 QTNs, of which ss715580365, ss715608427, ss715632502, and ss715620131 are novel QTNs for PH, PPP, SDPP, and TY respectively. Four candidate genes, Glyma.01g199200, Glyma.10g065700, Glyma.18g297900, and Glyma.14g009900, were identified in the vicinity of these novel QTNs, which encode lsd one like 1, Ergosterol biosynthesis ERG4/ERG24 family, HEAT repeat-containing protein, and RbcX2, respectively. Although further experimental validation of these candidate genes is required, several appear to be involved in growth and developmental processes related to the respective agronomic traits when compared with their homologs in Arabidopsis thaliana. This study supports the usefulness of association studies and provides valuable data for functional markers and investigating candidate genes within a diverse germplasm collection in future breeding programs.
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Affiliation(s)
- Reena Rani
- Agricultural Biotechnology Division, National Institute for Biotechnology and Genetic Engineering (NIBGE), Constituent College Pakistan Institute of Engineering and Applied Sciences (PIEAS), Faisalabad, Pakistan
| | - Ghulam Raza
- Agricultural Biotechnology Division, National Institute for Biotechnology and Genetic Engineering (NIBGE), Constituent College Pakistan Institute of Engineering and Applied Sciences (PIEAS), Faisalabad, Pakistan
| | - Hamza Ashfaq
- Agricultural Biotechnology Division, National Institute for Biotechnology and Genetic Engineering (NIBGE), Constituent College Pakistan Institute of Engineering and Applied Sciences (PIEAS), Faisalabad, Pakistan
| | - Muhammad Rizwan
- Plant Breeding and Genetics Division, Nuclear Institute of Agriculture (NIA), Tando Jam, Pakistan
| | - Muhammad Khuram Razzaq
- Soybean Research Institute, National Center for Soybean Improvement, Nanjing Agricultural University, Nanjing, China
| | - Muhammad Qandeel Waheed
- Plant Breeding and Genetics Division, Nuclear Institute for Agriculture and Biology (NIAB), Constituent College Pakistan Institute of Engineering and Applied Sciences (PIEAS), Faisalabad, Pakistan
| | - Hussein Shimelis
- School of Agricultural, Earth and Environmental Sciences, African Centre for Crop Improvement, University of KwaZulu-Natal, Pietermaritzburg, South Africa
| | - Allah Ditta Babar
- Agricultural Biotechnology Division, National Institute for Biotechnology and Genetic Engineering (NIBGE), Constituent College Pakistan Institute of Engineering and Applied Sciences (PIEAS), Faisalabad, Pakistan
| | - Muhammad Arif
- Agricultural Biotechnology Division, National Institute for Biotechnology and Genetic Engineering (NIBGE), Constituent College Pakistan Institute of Engineering and Applied Sciences (PIEAS), Faisalabad, Pakistan
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Crop germplasm: Current challenges, physiological-molecular perspective, and advance strategies towards development of climate-resilient crops. Heliyon 2023; 9:e12973. [PMID: 36711267 PMCID: PMC9880400 DOI: 10.1016/j.heliyon.2023.e12973] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2022] [Revised: 01/01/2023] [Accepted: 01/10/2023] [Indexed: 01/18/2023] Open
Abstract
Germplasm is a long-term resource management mission and investment for civilization. An estimated ∼7.4 million accessions are held in 1750 plant germplasm centres around the world; yet, only 2% of these assets have been utilized as plant genetic resources (PGRs). According to recent studies, the current food yield trajectory will be insufficient to feed the world's population in 2050. Additionally, possible negative effects in terms of crop failure because of climate change are already being experienced across the world. Therefore, it is necessary to reconciliation of research advancement and innovation of practices for further exploration of the potential of crop germplasm especially for the complex traits associated with yield such as water- and nitrogen use efficiency. In this review, we tried to address current challenges, research gaps, physiological and molecular aspects of two broad spectrum complex traits such as water- and nitrogen-use efficiency, and advanced integrated strategies that could provide a platform for combined stress management for climate-smart crop development. Additionally, recent development in technologies that are directly related to germplasm characterization was highlighted for further molecular utilization towards the development of elite varieties.
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