LGG_2025v16n3

Legume Genomics and Genetics 2025, Vol.16 http://cropscipublisher.com/index.php/lgg © 2025 CropSci Publisher, registered at the publishing platform that is operated by Sophia Publishing Group, founded in British Columbia of Canada. All Rights Reserved.

Legume Genomics and Genetics 2025, Vol.16 http://cropscipublisher.com/index.php/lgg © 2025 CropSci Publisher, registered at the publishing platform that is operated by Sophia Publishing Group, founded in British Columbia of Canada. All Rights Reserved. CropSci Publisher is an international Open Access publishing specializing in crop genome, trait-controlling, crop gene expression and regulation at the publishing platform that is operated by Sophia Publishing Group (SPG), founded in British Columbia of Canada. . Publisher Cropsci Publisher Edited by Editorial Team of Legume Genomics and Genetics Email: edit@lgg.cropscipublisher.com Website: http://cropscipublisher.com/index.php/lgg Address: 11388 Stevenston Hwy, PO Box 96016, Richmond, V7A 5J5, British Columbia Canada Legume Genomics and Genetics (ISSN 1925-1580) is an open access, peer reviewed journal published online by CropSci Publisher. The journal is committed to publishing grain/forage legume studies, as well as research on model legume plants such as Lotus japonicus and Medicago truncatula. The aims are to feature innovative research findings in the basic and applied fields of legume biology. Topics include (but are not limited to) genome structure, genome-scale analysis, comparative and functional genomics, proteomics and epigenomics, gene discovery and function, gene expression and evolution, as well as legume genetics from the molecular level to whole plant level. All the articles published in Legume Genomics and Genetics are Open Access, and are distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. CropSci Publisher uses CrossCheck service to identify academic plagiarism through the world’s leading plagiarism prevention tool, iParadigms, and to protect the original authors’ copyrights.

Legume Genomics and Genetics (online), 2025, Vol. 16, No.3 ISSN 1925-1580 http://cropscipublisher.com/index.php/lgg © 2025 CropSci Publisher, registered at the publishing platform that is operated by Sophia Publishing Group, founded in British Columbia of Canada. All Rights Reserved. Latest Content Genetic Diversity of Legume Germplasm Resources and Their Application in High-Yield Breeding Chunxia Wu, Weiguo Lu, Lijun Qiu Legume Genomics and Genetics, 2025, Vol.16, No.3, 100-107 Discussion on the Symbiotic Relationship between Legume Crops and Soil Microorganisms and Their Ecological Benefits Ming Li, Fumin Gao Legume Genomics and Genetics, 2025, Vol.16, No.3, 108-127 Analysis of NBS-LRR Gene Family in Adzuki Bean Evolution and Disease Resistance Potential Xiaoxi Zhou, Tianxia Guo Legume Genomics and Genetics, 2025, Vol.16, No.3, 128-134 CRISPR Activation System for Flowering Regulation in Mung Bean Dandan Huang Legume Genomics and Genetics, 2025, Vol.16, No.3, 135-142 Application of Single-Cell RNA-Seq in Legume Root Development Studies Hongpeng Wang, Weichang Wu Legume Genomics and Genetics, 2025, Vol.16, No.3, 143-152

Legume Genomics and Genetics 2025, Vol.16, No.3, 100-107 http://cropscipublisher.com/index.php/lgg 100 Feature Review Open Access Genetic Diversity of Legume Germplasm Resources and Their Application in High-Yield Breeding Chunxia Wu, Weiguo Lu, Lijun Qiu Modern Agricultural Research Center, Cuixi Academy of Biotechnology, Zhuji, 311800, Zhejiang, China Corresponding email: lijun.qiu@cuixi.org Legume Genomics and Genetics, 2025 Vol.16, No.3 doi: 10.5376/lgg.2025.16.0011 Received: 02 Mar., 2025 Accepted: 18 Apr., 2025 Published: 05 May, 2025 Copyright © 2025 Wu et al., This is an open access article published under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Preferred citation for this article: Wu C.X., Liu W.G., and Qiu L.J., 2025, Genetic diversity of legume germplasm resources and their application in high-yield breeding, Legume Genomics and Genetics, 16(3): 100-107 (doi: 10.5376/lgg.2025.16.0011) Abstract As an important food and feed resource, legume crops play an important role in ensuring food security, improving soil fertility and promoting sustainable agricultural development. Rich germplasm resources provide a key genetic basis for high-yield breeding of legumes. This study systematically sorted out the diversity characteristics of the current main germplasm resources of legumes, covering their geographical distribution, phenotypic variation and genetic background, and focused on analyzing important agronomic traits related to high yield, such as pod number, grain weight, stress resistance and nitrogen fixation ability. It further explored the specific application paths of diversity resources in modern breeding, including the introduction of excellent alleles, the development of pre-breeding materials, and the integration of marker-assisted selection and genomic selection technology. At the same time, the actual value of diversity germplasm in improving breeding efficiency and yield performance was explained through typical high-yield breeding cases. Fully exploring and accurately utilizing the genetic diversity of legumes is one of the core strategies to promote high-yield, stable yield and green development of legumes. This study hopes to provide theoretical support and practical reference for the construction of efficient breeding systems and the creation of new germplasm in the future. Keywords Germplasm diversity; Legume crops; High-yield breeding; Trait improvement; Molecular breeding techniques 1 Introduction Legumes are very important in global agriculture. They contribute about 27% of global food production (Coyne et al., 2020). A large part of the protein people eat comes from legumes. Legumes are also a component of many animal feeds. Legumes also have a very practical function. They can "move" nitrogen from the air into the soil. This ability makes the soil more fertile and is very helpful for agriculture. This is especially important in areas where fertilizers are scarce, resources are scarce, or people are malnourished (Smýkal et al., 2015). There are many germplasm resources of legumes, including excellent varieties, local varieties and wild relatives. These resources contain a large number of different genes. They can provide "good genes" required for important traits such as drought resistance, disease resistance and high yield. These genes are particularly helpful for breeding new varieties with strong stress resistance and high yield (Sharma et al., 2013; Coyne et al., 2020; Rajpal et al., 2023). Now, scientists use these valuable genes in breeding through gene introgression, pre-breeding, and genomic technology. This will enable the breeding of leguminous crops with greater adaptability and better traits (Dwivedi et al., 2017; Pratap et al., 2021). This study will systematically analyze legume germplasm diversity to identify and utilize genetic resources that can drive high-yield breeding. This includes evaluating and utilizing functional diversity, discovering new alleles and quantitative trait loci (QTLs) associated with yield and stress resistance, and integrating them into breeding programs using modern genomics and phenotyping tools. By leveraging the full range of genetic variation, this study hopes to optimize breeding strategies and breed legume varieties that meet the needs of the global food system, address climate change challenges, and promote sustainable agricultural productivity.

Legume Genomics and Genetics 2025, Vol.16, No.3, 100-107 http://cropscipublisher.com/index.php/lgg 101 2 Diversity of Legume Germplasm Resources 2.1 Geographic distribution and species diversity in legumes Leguminous plants are distributed all over the world. Their diversity is mainly concentrated in East Asia, the Near East, Africa and the Americas. There are more than 800 genera and more than 20 000 species of legumes recorded so far, making it the third largest flowering plant family in the world. They are also a very important type of plant in global food production (Smýkal et al., 2015). For example, wild soybeans (Glycine soja) are mainly distributed in East Asia, especially the Korean Peninsula, where wild resources are very rich and are also important for the domestication process of soybeans. For example, white lupins (Lupinus albus) and beans (Phaseolus vulgaris) have adapted to a variety of climates and soil conditions. Their germplasm resources are spread across multiple continents and show rich genetic and trait differences (Tanwar et al., 2024). 2.2 Wild relatives and landraces as reservoirs of rare alleles Wild relatives and local varieties preserve many valuable genes. These genes are often lost during crop domestication, but they are useful for breeding, helping to increase yields, and improving adaptability such as disease and pest resistance and drought and salt resistance (Nawaz et al., 2020). For example, wild soybeans and wild peas (such as P. fulvum and P. sativum subsp. elatius) retain more genetic variation than cultivated varieties. These variations can provide some unique genetic resources for breeding programs (Smýkal et al., 2017). The same is true for local varieties. After long-term selection and adaptation by farmers, varieties in different places have different characteristics. For example, common beans in Portugal and the Himalayas contain many new genetic combinations, including some hybrids and hybrids (Jan et al., 2021). 2.3 Agro-morphological variation among accessions Leguminous germplasm resources differ in many agronomic traits. These differences are critical for selecting good varieties. Studies have found that crops such as beans, rice beans, adzuki beans, and cowpeas (Vigna stipulacea) show wide variation in growth patterns, leaf shape, flower color, pod and seed appearance, and nutritional content (Gore et al., 2022; Divakara et al., 2024). For example, beans from the Himalayas and Portugal vary greatly in seed size, shape, and nutritional content. Rice beans and adzuki beans from Asia also vary in flowering time, number of pods, and yield. If these trait data are analyzed together with molecular markers, useful materials can be found more quickly. This not only allows targeted breeding, but also establishes a core germplasm bank with strong representativeness and genetic diversity (Leitão et al., 2017). 3 High-Yield Related Traits in Legumes 3.1 Major yield components: pods per plant, seed size, biomass The yield of legumes is mainly related to several aspects, such as the number of pods per plant, the size of the seeds, and the biomass of the whole plant. Taking mung beans and broad beans as examples, studies have found that the number of effective pods per plant, the total number of seeds, and the weight of each seed will directly affect the final yield. Moreover, there are obvious differences in these traits between different varieties, which is a genetic difference. Some studies have also used meta-QTL analysis to find gene regions related to yield. These regions can affect traits such as the number of pods and seed weight. This kind of information is particularly useful for breeding work and can help breed new varieties with higher yields (Arriagada et al., 2022). In addition to these, researchers often use biomass and total seed production to judge whether the variety is good or not. Different varieties perform differently in different environments. Some varieties can grow more plants and seeds, while others are less so (Papastylianou et al., 2021). 3.2 Stress-resilient traits linked to yield stability The stress resistance of leguminous plants, such as drought resistance and heat resistance, is very important for maintaining stable yields. There are several physiological indicators related to these abilities, such as high chlorophyll content, strong leaf cooling ability, and good cell membrane stability, which are all related to high yields under harsh conditions (Sofi et al., 2021; Jha et al., 2025). For example, in drought resistance research, the "stress resistance index" is often used to measure, that is, to consider the yield performance of crops under normal

Legume Genomics and Genetics 2025, Vol.16, No.3, 100-107 http://cropscipublisher.com/index.php/lgg 102 and water-deficient conditions. For example, the number of seeds per plant and the number of pods per plant are often used as key indicators for variety selection (Balko et al., 2023). Now, scientists have also found many stress-related genes through transcriptome and physiological experiments. These genes are important for breeding varieties that are resistant to harsh environments and can also have high yields (Araújo et al., 2015; Abdelrahman et al., 2018). 3.3 Physiological efficiencies: nitrogen fixation and source-sink relationships In order for leguminous plants to have high yields, they must not only grow fast, but also have "high internal efficiency". A key point is that they can coexist with rhizobia to fix nitrogen in the air, which not only helps their own growth, but also improves the soil and reduces the use of chemical fertilizers. After producing nutrients, plants need to transport these "goods" reasonably to leaves, roots, seeds and other places. Whether this distribution is efficient is directly related to whether more biomass and seeds can be produced. The structure of the roots, water use efficiency, and photosynthesis ability are also very important (Duc et al., 2015; Sofi et al., 2021). Current breeding work is also paying more and more attention to these "invisible" physiological traits. Scientists hope to select new leguminous varieties that are both high-yielding and use fewer resources by integrating these characteristics (Dutta et al., 2022). 4 Utilization of Germplasm in Breeding Programs 4.1 Trait introgression from exotic or wild donors In breeding, scientists often introduce wild relatives, local varieties or exotic species into excellent legume crops. This practice is called gene introgression breeding. Doing so can bring new genetic variation, help us improve varieties, improve disease resistance, drought tolerance, and yield. There are many successful examples, such as hybridization with wild or exotic species to breed better chickpeas, pigeon peas, peanuts, lentils, mung beans, urdu beans and kidney beans. These varieties not only grow better, but are also more disease-resistant and stress-resistant. In order to transfer these complex traits faster, many people now use some "specially designed" breeding populations in combination with new tools such as molecular markers. These methods can reduce the problem of unwanted traits being transferred in together. Now, gene introgression breeding has become a common method for improving legume crops (Sharma et al., 2013; Pratap et al., 2021; Gore et al., 2022). 4.2 Development of pre-breeding lines and core collections In the early stages of breeding, researchers will first introduce excellent genes from wild species or local varieties, and then introduce them into those strains that are more suitable for breeding. This step can solve the problem of incompatibility during hybridization and avoid bringing in some unwanted traits. They will first collect a lot of germplasm materials, then evaluate and screen them one by one, and finally establish a core germplasm bank. This germplasm bank retains many useful genes and alleles for subsequent breeding. Taking cowpea breeding as an example, the core germplasm has helped us find a lot of good materials with potential. These resources are also critical because they can support subsequent improvement work and help varieties better adapt to different environments (Egan et al., 2021; Gayacharan et al., 2023; Chaudhary et al., 2025). 4.3 Marker-assisted and genomic selection approaches Now many breeding projects have begun to use some modern methods, such as marker-assisted selection (MAS), marker-assisted backcrossing, and genomic selection. These methods can speed up the process of finding good traits and breed new high-yield and disease-resistant varieties more quickly. With high-density genetic maps, complete genomic information and molecular markers, we can more accurately find the genetic locations (QTLs) related to yield, disease resistance and stress tolerance, and then transfer them to the target varieties. GWAS (genome-wide association analysis) and next-generation sequencing can also enable us to improve the entire population faster and achieve continuous genetic progress. Now we can also combine omics technology and artificial intelligence to more efficiently explore traits and assist decision-making, thereby supporting the breeding of high-yield and stress-resistant legume varieties (Varshney et al., 2018; Singh et al., 2021; Jha et al., 2022; Biswas et al., 2023).

Legume Genomics and Genetics 2025, Vol.16, No.3, 100-107 http://cropscipublisher.com/index.php/lgg 103 5 Case Studies in High-Yield Legume Breeding 5.1 Soybean: Chinese landraces for elite yield traits China has a wide variety of soybean local varieties and rich genetic diversity. These varieties contain some unique and excellent genes that are very helpful in increasing yields. Introducing them into breeding projects can find and utilize these useful traits, while also expanding the source of genes for breeding. Studies have found that if local varieties and wild soybeans can be used for pre-breeding, combined with genomic tools, it can help soybeans break through the yield bottleneck and further improve breeding results (Figure 1) (Singh et al., 2022; Rubiales, 2023). Figure 1 Integrated approaches for accelerating trait introgression and achieving higher genetic gain in legumes (Adopted from Singh et al., 2022) Image caption: (A) high-throughput phenotyping (SPAD-meter, green seeker, prostrate tester, junior PAM, drones, scanners, IRGA, etc.) to take full advantage of large-scale genomic data sets built by next-generation sequencing (NGS) tools; (B) bringing genomic tools like, marker-assisted selection (MAS), marker-assisted backcrossing (MABC), advanced backcross quantitative trait loci mapping (AB-QTL), marker-assisted recurrent selection (MARS), genomic selection (GS), and genome wide association studies (GWAS) to identify and introgress desirable genes or QTLs into legumes with high efficacy; (C) biotechnology (gene gun, particle bombardment, microinjection, and Agrobacterium) mediated transformation of alien genes to produce pest, disease and herbicide resilient transgenic crops; (D) dialling physiology of plants with protracted photoperiod, elevated temperature and CO2 coupled with immature seed harvest to accelerate generation advancement; (E) developing tailor-made crop varieties by using haplotype-based breeding; (F) targeted genome editing using meganucleases, zinc finger nucleases (ZFNs), transcription activator-like effector nucleases (TALENs), and clustered Regularly Interspaced Short Palindromic Repeats (CRISPRs) to produce non-transgenic, genome edited crops (Adopted from Singh et al., 2022) 5.2 Cowpea: enhancing productivity under drought-prone regions In cowpea breeding, scientists used the genetic differences between wild relatives and local varieties to improve cowpea yield and adaptability in arid areas. They first did pre-breeding and slowly introduced drought-tolerant traits. Gradually, they selected varieties that could maintain stable yields even in water-scarce environments. This breeding method is particularly useful in areas with a lot of climate change and common droughts. Now, new technologies such as genomics, phenomics, and rapid breeding have also been added. These methods make breeding faster and the selected varieties more reliable (Varshney et al., 2018; Singh et al., 2022). 5.3 Faba bean: cold-adaptive lines improving yield in temperate zones In broad bean breeding, breeders selected cold-resistant strains so that broad beans can produce high yields in areas with lower temperatures. These cold-resistant and variable maturity genetic resources not only increase

Legume Genomics and Genetics 2025, Vol.16, No.3, 100-107 http://cropscipublisher.com/index.php/lgg 104 yields, but also allow broad beans to be planted in places that could not be planted before. In order to make broad beans more adaptable to abiotic stresses such as cold, breeding work needs to pay special attention to selecting strains with strong resistance. This is critical to improving the planting effect in temperate regions (Duc et al., 2015; Rubiales, 2023). 6 Integration of Multi-Omics for Trait Mining 6.1 Use of transcriptomics and GWAS to identify yield QTLs Transcriptome and GWAS are commonly used methods to study yield and other complex traits in legumes. Combining these two types of data can find genes related to yield, seed composition, stress resistance, and quantitative trait loci (QTL). These methods have been used in soybeans and other crops. The results are also good. Not only have many important genes been found, but some useful molecular markers have also been developed (Chaudhary et al., 2015; Yang et al., 2021). Now, with multi-omics databases and platforms, it has become more convenient to find these candidate genes and understand their regulatory mechanisms. These tools have greatly improved the efficiency of identifying traits (Yang et al., 2023). 6.2 Genomic prediction models for complex traits If only one type of data is used for prediction, the effect is usually not ideal. But if several different data are put together, such as genome, transcriptome and methylation group data, the prediction results will be more accurate. This approach can help us understand more clearly which genes are affecting trait changes, how they interact and how they are regulated. Studies have also found that this multi-omics approach performs better than traditional methods in various environments (Wang et al., 2024). Now, many breeding projects have also begun to use machine learning and statistical methods to process these data. Methods such as random forests and multi-kernel learning can make predictions more stable and reliable (Acharjee et al., 2016; Briscik et al., 2024). 6.3 Combining metabolomic and phenomic data for precision breeding If we use metabolome and phenotypic data together with other omics data, we can see more clearly which molecules and physiological mechanisms affect yield and quality. In this way, a predictive model from genes to traits can be established to help us identify important metabolic pathways and biomarkers (Hu et al., 2021). This information can help us improve target traits faster, shorten breeding time, and make it easier to breed legumes with good performance. 7 Concluding Remarks Legumes have rich genetic diversity, which is the basis for their improvement. These genetic differences can help us increase yields, enhance disease resistance, and improve nutritional quality. In particular, wild species and local varieties carry many unique genes. These genes are very helpful for breeding. Using these variations, we can cultivate legumes that can adapt to climate change, resist pests and diseases, and adapt to different environments. This diversity also affects some important traits, such as some varieties have well-developed root systems and strong drought resistance; some can coexist with rhizobia to help plants fix nitrogen. These characteristics not only increase yields, but also protect soil and the environment. In the future, breeding should combine traditional methods with modern technologies. For example, genomic tools, phenotyping, and rapid breeding can be used to make breeding more efficient. Introducing good genes from wild species, that is, pre-breeding, can help increase genetic diversity. This can solve the problem of stagnant yield growth. There are many advanced tools now, such as high-throughput phenotyping, modeling software, gene editing, etc., which can help us find good traits faster and improve breeding efficiency. Breeders, agricultural experts and farmers also need to work together. They have to jointly decide the breeding goals, considering both yield and sustainable development. In terms of technology, digitizing germplasm resources is an important step. If combined with multi-omics data, artificial intelligence and some intelligent analysis tools, we can greatly change the way of breeding. Through these databases and models, we can find useful traits and excellent genes faster and make more scientific choices.

Legume Genomics and Genetics 2025, Vol.16, No.3, 100-107 http://cropscipublisher.com/index.php/lgg 105 These new methods are expected to help us breed new legume varieties that are high-yielding, resistant to stress, and adaptable to climate change, ensuring food and nutrition security for humans in the future. Acknowledgments We would like to express our gratitude to the reviewers for their valuable feedback, which helped improve the manuscript. Conflict of Interest Disclosure The authors affirm that this research was conducted without any commercial or financial relationships that could be construed as a potential conflict of interest. References Abdelrahman M., Jogaiah S., Burritt D., and Tran L., 2018, Legume genetic resources and transcriptome dynamics under abiotic stress conditions, Plant, Cell & Environment, 41(9): 1972-1983. https://doi.org/10.1111/pce.13123 Acharjee A., Kloosterman B., Visser R., and Maliepaard C., 2016, Integration of multi-omics data for prediction of phenotypic traits using random forest, BMC Bioinformatics, 17: 180. https://doi.org/10.1186/s12859-016-1043-4 Araújo S., Beebe S., Crespi M., Delbreil B., Gonzalez E., Gruber V., Lejeune-Hénaut I., Link W., Monteros M., Prats E., Rao I., Vadez V., and Patto M., 2015, Abiotic stress responses in legumes: strategies used to cope with environmental challenges, Critical Reviews in Plant Sciences, 34: 237-280. https://doi.org/10.1080/07352689.2014.898450 Arriagada O., Arévalo B., Cabeza R., Carrasco B., and Schwember A., 2022, Meta-QTL analysis for yield components in common bean (Phaseolus vulgaris L.), Plants, 12(1): 117. https://doi.org/10.3390/plants12010117 Balko C., Torres A., and Gutiérrez N., 2023, Variability in drought stress response in a panel of 100 faba bean genotypes, Frontiers in Plant Science, 14: 1236147. https://doi.org/10.3389/fpls.2023.1236147 Biswas M., Patil A., and Sunkad G., 2023, Enhancing legume cultivars through agronomy, breeding, and genetics, Agronomy, 13(4): 1035. https://doi.org/10.3390/agronomy13041035 Briscik M., Tazza G., Dillies M., Vid'acs L., and Déjean S., 2024, Supervised multiple kernel learning approaches for multi-omics data integration, BioData Mining, 17: 53. https://doi.org/10.1186/s13040-024-00406-9 Chaudhary D., Gore P., Wankhede D., Patil D., Choudhary S., Rao A., Gautam R., Singh G., and Tripathi K., 2025, Morphological variability and genetic diversity assessment of agronomic traits in cowpea (Vigna unguiculata (L.) Walp.) core collection using multivariate analysis, Genetic Resources and Crop Evolution, 72: 6027-6042. https://doi.org/10.1007/s10722-024-02299-3 Chaudhary J., Patil G., Sonah H., Deshmukh R., Vuong T., Valliyodan B., and Nguyen H., 2015, Expanding omics resources for improvement of soybean seed composition traits, Frontiers in Plant Science, 6: 1021. https://doi.org/10.3389/fpls.2015.01021 Coyne C., Kumar S., Wettberg E., Marques E., Berger J., Redden R., Ellis T., Brus J., ZablatzkáL., and Smýkal P., 2020, Potential and limits of exploitation of crop wild relatives for pea, lentil, and chickpea improvement, Legume Science, 2(2): e36. https://doi.org/10.1002/leg3.36 Divakara D., Gore P., Tripathi K., Katral A., Choudhury D., Abhishek G., Ragi S., Thippeswamy D., Muthusamy V., Sharma D., Singh R., and Bhatt K., 2024, Exploring genetic diversity of potential legume, Vigna angularis (Willd.) Ohwi and Ohashi through agro-morphological traits and SSR markers analysis, PLOS ONE, 19(12): e0312845. https://doi.org/10.1371/journal.pone.0312845 Duc G., Agrama H., Bao S., Berger J., Bourion V., De Ron A., Gowda C., Mikić A., Millot D., Singh K., Tullu A., Vandenberg A., Patto M., Warkentin T., and Zong X., 2015, Breeding annual grain legumes for sustainable agriculture: new methods to approach complex traits and target new cultivar ideotypes, Critical Reviews in Plant Sciences, 34: 381-411. https://doi.org/10.1080/07352689.2014.898469 Dutta A., Trivedi A., Nath C., Gupta D., and Hazra K., 2022, A comprehensive review on grain legumes as climate-smart crops: challenges and prospects, Environmental Challenges, 7: 100479. https://doi.org/10.1016/j.envc.2022.100479 Dwivedi S., Scheben A., Edwards D., Spillane C., and Ortiz R., 2017, Assessing and exploiting functional diversity in germplasm pools to enhance abiotic stress adaptation and yield in cereals and food legumes, Frontiers in Plant Science, 8: 1461. https://doi.org/10.3389/fpls.2017.01461 Egan L., Hofmann R., Ghamkhar K., and Hoyos-Villegas V., 2021, Prospects for Trifolium improvement through germplasm characterisation and pre-breeding in New Zealand and Beyond, Frontiers in Plant Science, 12: 653191. https://doi.org/10.3389/fpls.2021.653191

Legume Genomics and Genetics 2025, Vol.16, No.3, 100-107 http://cropscipublisher.com/index.php/lgg 106 Gayacharan, Parida S., Mondal N., Yadav R., Vishwakarma H., and Rana J., 2023, Mining legume germplasm for genetic gains: an Indian perspective, Frontiers in Genetics, 14: 996828. https://doi.org/10.3389/fgene.2023.996828 Gore P., Gupta V., Singh R., Tripathi K., Kumar R., Kumari G., Madhavan L., Dikshit H., Venkateswaran K., Pandey A., Singh N., Bhat K., Nair R., and Pratap A., 2022, Insights into the genetic diversity of an underutilized Indian legume, Vigna stipulacea (Lam.) Kuntz., using morphological traits and microsatellite markers, PLoS ONE, 17(1): e0262634. https://doi.org/10.1371/journal.pone.0262634 Hu H., Campbell M., Yeats T., Zheng X., Runcie D., Covarrubias-Pazaran G., Broeckling C., Yao L., Caffe‐Treml M., Gutiérrez L., Smith K., Tanaka J., Hoekenga O., Sorrells M., Gore M., and Jannink J., 2021, Multi-omics prediction of oat agronomic and seed nutritional traits across environments and in distantly related populations, Theoretical and Applied Genetics, 134: 4043-4054. https://doi.org/10.1007/s00122-021-03946-4 Jan S., Rather I., Sofi P., Wani M., Sheikh F., Bhat M., and Mir R., 2021, Characterization of common bean (Phaseolus vulgaris L.) germplasm for morphological and seed nutrient traits from Western Himalayas, Legume Science, 3(2): e86. https://doi.org/10.1002/leg3.86 Jha U., Shafi S., Tallury S., Nayyar H., Ciampitti I., Siddique K., and Prasad P., 2025, Differential physiological and yield responses of selected mung bean (Vigna radiata (L.) R. Wilczek) genotypes to various high-temperature stress regimes, Scientific Reports, 15: 1034. https://doi.org/10.1038/s41598-024-84615-6 Jha U., Sharma K., Nayyar H., Parida S., and Siddique K., 2022, Breeding and genomics interventions for developing ascochyta blight resistant grain legumes, International Journal of Molecular Sciences, 23(4): 2217. https://doi.org/10.3390/ijms23042217 Leitão S., Dinis M., Veloso M., Šatović Z., and Patto M., 2017, Establishing the bases for introducing the unexplored portuguese common bean germplasm into the breeding world, Frontiers in Plant Science, 8: 1296. https://doi.org/10.3389/fpls.2017.01296 Nawaz M., Lin X., Chan T., Ham J., Shin T., Ercişli S., Golokhvast K., Lam H., and Chung G., 2020, Korean wild soybeans (Glycine soja Sieb & Zucc.): geographic distribution and germplasm conservation, Agronomy, 10(2): 214. https://doi.org/10.3390/agronomy10020214 Ohm H., Åstrand J., Ceplitis A., Bengtsson D., Hammenhag C., Chawade A., and Grimberg Å., 2024, Novel SNP markers for flowering and seed quality traits in faba bean (Vicia faba L.): characterization and GWAS of a diversity panel, Frontiers in Plant Science, 15: 1348014. https://doi.org/10.3389/fpls.2024.1348014 Papastylianou P., Vlachostergios D., Dordas C., Tigka E., Papakaloudis P., Kargiotidou A., Pratsinakis E., Koskosidis A., Pankou C., Kousta A., Mylonas I., Tani E., Abraham E., Karatassiou M., and Kostoula S., 2021, Genotype X environment interaction analysis of faba bean (Vicia faba L.) for biomass and seed yield across different environments, Sustainability, 13(5): 2586. https://doi.org/10.3390/SU13052586 Pratap A., Das A., Kumar S., and Gupta S., 2021, Current perspectives on introgression breeding in food legumes, Frontiers in Plant Science, 11: 589189. https://doi.org/10.3389/fpls.2020.589189 Rajpal V., Singh A., Kathpalia R., Thakur R., Khan M., Pandey A., Hamurcu M., and Raina S., 2023, The prospects of gene introgression from crop wild relatives into cultivated lentil for climate change mitigation, Frontiers in Plant Science, 14: 1127239. https://doi.org/10.3389/fpls.2023.1127239 Rubiales D., 2023, Plant breeding is needed to meet agroecological requirements: legume crops as a case study, Outlook on Agriculture, 52: 294-302. https://doi.org/10.1177/00307270231195641 Sharma S., Upadhyaya H., Varshney R., and Gowda C., 2013, Pre-breeding for diversification of primary gene pool and genetic enhancement of grain legumes, Frontiers in Plant Science, 4: 309. https://doi.org/10.3389/fpls.2013.00309 Singh G., Gudi S., Amandeep, Upadhyay P., Shekhawat P., Nayak G., Goyal L., Kumar D., Kumar P., Kamboj A., Thada A., Shekhar S., Koli G., Dp M., Halladakeri P., Kaur R., Kumar S, Saini P., Singh I., and Ayoubi H., 2022, Unlocking the hidden variation from wild repository for accelerating genetic gain in legumes, Frontiers in Plant Science, 13: 1035878. https://doi.org/10.3389/fpls.2022.1035878 Singh V., Chaudhary P., Taunk J., Singh C., Singh D., Tomar R., Aski M., Konjengbam N., Raje R., Singh S., Sengar R., Yadav R., and Pal M., 2021, Fab advances in Fabaceae for abiotic stress resilience: from ‘Omics’ to artificial intelligence, International Journal of Molecular Sciences, 22(19): 10535. https://doi.org/10.3390/ijms221910535 Smýkal P., Coyne C., Ambrose M., Maxted N., Schaefer H., Blair M., Berger J., Greene S., Nelson M., Besharat N., VymyslickýT., Toker C., Saxena R., Roorkiwal M., Pandey M., Hu J., Li Y., Wang L., Guo Y., Qiu L., Redden R., and Varshney R., 2015, Legume crops phylogeny and genetic diversity for science and breeding, Critical Reviews in Plant Sciences, 34: 104-143. https://doi.org/10.1080/07352689.2014.897904 Smýkal P., Hradilová I., Trněný O., Brus J., Rathore A., Bariotakis M., Das R., Bhattacharyya D., Richards C., Coyne C., and Pirintsos S., 2017, Genomic diversity and macroecology of the crop wild relatives of domesticated pea, Scientific Reports, 7: 17384. https://doi.org/10.1038/s41598-017-17623-4

Legume Genomics and Genetics 2025, Vol.16, No.3, 100-107 http://cropscipublisher.com/index.php/lgg 107 Sofi P., Rehman K., Gull M., Kumari J., Djanaguiraman M., and Prasad P., 2021, Integrating root architecture and physiological approaches for improving drought tolerance in common bean (Phaseolus vulgaris L.), Plant Physiology Reports, 26: 4-22. https://doi.org/10.1007/s40502-021-00570-8 Tanwar U., Tomaszewska M., Czepiel K., Neji M., Jamil H., Rocchetti L., Pieri A., Bitocchi E., Bellucci E., Pipan B., Meglič V., Kroc M., Papa R., and Susek K., 2024, Genetic and phenotypic characterization of global Lupinus albus genetic resources for the development of a CORE collection, bioRxiv, 614894: 1-45. https://doi.org/10.1101/2024.09.25.614894 Varshney R., Pandey M., Bohra A., Singh V., Thudi M., and Saxena R., 2018, Toward the sequence-based breeding in legumes in the post-genome sequencing era, Theoretical and Applied Genetics, 132: 797-816. https://doi.org/10.1007/s00122-018-3252-x Wang P., Lehti-Shiu M., Lotreck S., AbáK., and Shiu S., 2024, Prediction of plant complex traits via integration of multi-omics data, Nature Communications, 15: 6856. https://doi.org/10.1038/s41467-024-50701-6 Yang Y., Saand M., Huang L., Abdelaal W., Zhang J., Wu Y., Li J., Sirohi M., and Wang F., 2021, Applications of multi-omics technologies for crop improvement, Frontiers in Plant Science, 12: 563953. https://doi.org/10.3389/fpls.2021.563953 Yang Z., Wang S., Wei L., Huang Y., Liu D., Jia Y., Luo C., Lin Y., Liang C., Hu Y., Dai C., Guo L., Zhou Y., and Yang Q., 2023, BnIR: a multi-omics database with various tools for Brassica napus research and breeding, bioRxiv, 523736: 1-37. https://doi.org/10.1101/2023.01.12.523736

Legume Genomics and Genetics 2025, Vol.16, No.3, 108-127 http://cropscipublisher.com/index.php/lgg 108 Research Insight Open Access Discussion on the Symbiotic Relationship between Legume Crops and Soil Microorganisms and Their Ecological Benefits Ming Li, Fumin Gao Tropical Microbial Resources Research Center, Hainan Institute of Tropical Agricultural Resources, Sanya, 572025, Hainan, China Corresponding email: fumin.gao@hitar.org Legume Genomics and Genetics, 2025 Vol.16, No.3 doi: 10.5376/lgg.2025.16.0012 Received: 22 Mar., 2025 Accepted: 08 May, 2025 Published: 26 May, 2025 Copyright © 2025 Li and Gao, This is an open access article published under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Preferred citation for this article: Li M., and Gao F.M., 2025, Discussion on the symbiotic relationship between legume crops and soil microorganisms and their ecological benefits, Legume Genomics and Genetics, 16(3): 108-127 (doi: 10.5376/lgg.2025.16.0012) Abstract Leguminous crops form a unique symbiotic system with soil microorganisms (especially nitrogen-fixing rhizobia and arbuscular mycorrhizal fungi), which plays an important role in agricultural ecosystems. This study reviews the biological basis of leguminous crop-microorganism symbiosis and its significance to soil microecology and agricultural sustainable development, introduces the mechanism of symbiotic nitrogen fixation, discusses how leguminous crops promote soil microecological balance by increasing soil organic matter, improving soil enzyme activity and improving soil physical and chemical properties, and explains the supporting role of microbial symbiosis on nutrient absorption and stress resistance of leguminous plants, such as improving nitrogen fixation efficiency, enhancing plant drought and salt tolerance, inducing plant immunity and biological control potential. Furthermore, from the perspective of ecological benefits, the contribution of leguminous-microorganism symbiosis in reducing fertilizer dependence and greenhouse gas emissions, restoring degraded soil functions and enhancing the stability of agricultural ecosystems is analyzed, and illustrated by cases such as soybean-rhizobium, peanut inoculants and leguminous rotation. This study hopes to provide a theoretical basis and practical reference for the role of leguminous crops and soil microbial symbiosis in sustainable agriculture. Keywords Legume crops; Soil microorganisms; Symbiotic nitrogen fixation; Ecological benefits; Sustainable agriculture 1 Introduction Symbiotic nitrogen fixation between legumes and soil microorganisms is an important source of nitrogen supply in agricultural ecosystems and has the potential to replace some chemical nitrogen fertilizers. It is estimated that the symbiosis between legumes and rhizobia can fix a large amount of nitrogen for terrestrial ecosystems every year, thereby reducing dependence on chemical fertilizers. However, environmental problems caused by long-term excessive application of chemical fertilizers are becoming increasingly prominent, such as increased greenhouse gas emissions, eutrophication of water bodies, and soil degradation. Therefore, making full use of the mutualistic symbiotic relationship between legumes and soil microorganisms to achieve the biological cycle of nutrients in the soil is of great practical significance for the development of sustainable agriculture. In addition, legumes are rich in protein and bioactive substances, and they also play a key role in ensuring food security and nutrition. Their symbiotic nitrogen fixation ability enables them to survive in poor environments and improve soil fertility (Fahde et al., 2023). Legumes have outstanding value in ecological agriculture. On the one hand, legumes provide nitrogen sources for subsequent crops through symbiotic nitrogen fixation, reduce the application of chemical fertilizers, and realize the green cycle of agricultural production (Mahama et al., 2020). For example, the introduction of leguminous crops into the crop rotation system of corn and other food crops can increase crop yields and nitrogen use efficiency, and reduce nitrogen fertilizer input and nitrogen loss (Yu et al., 2021). On the other hand, leguminous crops are often used as green manure and cover crops to improve soil, increase soil organic matter and nutrient content, promote soil microbial diversity, and thus improve the biological cycle function of farmland ecosystems. Leguminous crops have well-developed root systems and extensive symbiosis with mycorrhizal fungi, and also play a positive role in improving soil structure, preventing soil erosion, and restoring degraded soils. Therefore,

Legume Genomics and Genetics 2025, Vol.16, No.3, 108-127 http://cropscipublisher.com/index.php/lgg 109 planting and making good use of leguminous crops in the ecological agricultural model has an important role in promoting the realization of weight loss and efficiency, soil fertility, and sustainable agricultural development. This study will systematically explore the symbiotic relationship between leguminous crops and soil microorganisms (mainly nitrogen-fixing rhizobia and arbuscular mycorrhizal fungi) and the ecological benefits they bring, and explain the role of leguminous crops in improving soil microecology, such as increasing soil organic matter, enzyme activity, and improving soil physical and chemical properties. Then, the supporting role of soil microorganisms on nutrient absorption and stress resistance of legumes is analyzed, including nitrogen fixation to improve nitrogen utilization, high drought and salt tolerance, and induction of plant immunity and biological control potential. On this basis, from the perspective of ecological and environmental benefits, the role of legume-microorganism symbiosis in reducing fertilizer use and greenhouse gas emissions, repairing degraded soil functions, and enhancing the stability of agricultural ecosystems is discussed. The above viewpoints are confirmed through specific case studies (such as soybean-rhizobium long-term positioning experiments, peanut microbial inoculation yield increase experiments, and the role of legumes in crop rotation). This study summarizes the role of symbiotic relationships in sustainable agriculture and proposes directions for future research and practice to promote its better application in agriculture. 2 Symbiotic Basis between Legumes and Soil Microbes 2.1 Classification and symbiotic mechanism of rhizobia Nitrogen-fixing rhizobia are a type of soil bacteria that can infect the roots of legumes and form nodules. They mainly belong to the α- and β-subgroups of the Proteobacteria, including multiple taxa such as Rhizobium, Bradyrhizobium, and Bacillus thuringiensis (now Ensifer/Sintoferria). Different legumes tend to form symbiotic relationships with specific types of rhizobia. For example, soybeans usually coexist with Bradyrhizobium strains, while alfalfa prefers Rhizobia strains. The process of symbiotic nitrogen fixation between rhizobia and legumes is very complex, involving strict species or strain matching and a series of exquisite "molecular dialogues". At the beginning of the symbiosis, the roots of legumes secrete flavonoids to attract rhizobia in the soil to swim toward the roots. Matching rhizobia regulate the nodulation (nod) gene through NodD, synthesize and release specific "nodulation factor" (Nod factor), which is a modified oligosaccharide signal molecule. After the receptor kinase complex on the epidermal cells of the plant roots (such as NFR1/NFR5 of Lotus japonicus, LYK3/NFP of Medicago truncatula, etc.) senses the nodulation factor, it activates the downstream symbiotic signaling pathway, induces the root hair to bend and be invaded by bacteria. Subsequently, the root hair cell wall is partially degraded to form an infection line for the rhizobia to enter. The bacteria elongate and divide continuously along the infection line, and finally invade the cortical cells. At the same time, the cortical cells divide again to form the initial flowering meristem and develop into nodules. In the nodule, the rhizobia are wrapped by the plant cell membrane to become bacteroids, and begin to efficiently fix atmospheric nitrogen and reduce it to ammonium nitrogen for plant use. The entire symbiotic process requires strict coordination between the two parties: the plant provides a carbon source and a shelter environment, the microorganisms provide nitrogen, and through complex signal exchanges to ensure the establishment and maintenance of a mutually beneficial symbiotic relationship. 2.2 Role of mycorrhizal fungi in synergistic interaction In addition to rhizobia, many legumes also establish symbiosis (i.e., mycorrhizal symbiosis) with arbuscular mycorrhizal fungi (AM fungi) in the soil, which is of great significance to the nutrient acquisition and environmental adaptability of plants. Interestingly, there is a high degree of commonality in the signal transduction pathway between mycorrhizal symbiosis and nodule symbiosis: the receptors and downstream signals of mycorrhizal factors (Myc factors) secreted by AM fungi that plants recognize partially overlap with the pathways for recognizing nodulation factors, which is considered to be the result of legumes using evolutionary commonalities to establish two symbiotic relationships. Studies have shown that arbuscular mycorrhizal symbiosis appeared in terrestrial plants more than 400 million years ago, and legumes later "borrowed" the signal mechanism of this ancient symbiosis to develop a new symbiosis with rhizobia. Therefore, there is synergy and a common signal network between AM fungi symbiosis and nodule symbiosis.

Legume Genomics and Genetics 2025, Vol.16, No.3, 108-127 http://cropscipublisher.com/index.php/lgg 110 In actual function, mycorrhizal fungi significantly expand the effective absorption area of legume roots through their hyphae networks, helping to absorb nutrients (such as phosphorus) and water that are difficult to move in the soil. At the same time, AM bacteria can also change the rhizosphere microbial community. Studies have found that the hyphae of arbuscular mycorrhizal fungi can serve as a "bridge" to help rhizobia spread in the soil and reach the roots of legumes faster, thereby improving nodulation efficiency. For example, a microcosm experiment on peanuts showed that in the presence of an endophytic fungus (Phomopsis liquidambaris) hyphae, the enrichment of rhizobia and the number of nodules in the peanut rhizosphere increased significantly; the fungal hyphae provided a "highway" for rhizobia, making it easier for them to migrate to the roots and induce the formation of more nodules. The study also found that rhizobia exhibited special chemotaxis and proliferation behaviors when moving along the hyphae, and hyphal secretions may promote this process (Figure 1) (Zhang et al., 2020). It can be seen that the presence of AM bacteria can assist rhizobia in colonization and nodulation at the physical and chemical levels. Other studies have shown that the simultaneous inoculation of rhizobia and mycorrhizal fungi has a synergistic effect on the growth of legumes: for example, in alfalfa, the double inoculation treatment significantly increased the plant's nitrogen and phosphorus absorption and biomass accumulation, which was more conducive to nutrient cycling than the single inoculation treatment. This shows that the interaction between arbuscular mycorrhizal fungi and rhizobia can form a more functional microbial consortium in the rhizosphere of legumes, helping plants to fully obtain a variety of nutrients. More profoundly, recent molecular evolutionary studies have revealed that legume-rhizobium symbiosis and AM bacteria symbiosis may have a synergistic relationship in evolution. Some key genes (such as SymRK receptor kinase, etc.) were found to be involved in regulating both symbioses. In their study of the evolutionary mechanism of the legume symbiotic system, Wang and Zhang (2021) proposed that it was precisely because early terrestrial plants already had the ability of mycorrhizal symbiosis that legumes evolved a new symbiosis with nitrogen-fixing rhizobia on this basis, and the two symbioses influenced each other and improved synergistically during the evolution process. This view is supported by symbiotic biogenomics research: the presence of mycorrhizal symbiosis affects the response of legumes to rhizobia and the nodulation characteristics, and legumes without AM bacteria are often more difficult to nodulate efficiently. Therefore, the legume crop symbiotic system can be regarded as a complex tripartite interaction network including plants, fungi, and bacteria, and each component promotes each other, ultimately improving the nutrient utilization and environmental adaptability of plants. 2.3 Recognition and regulation of symbiotic signal molecules The establishment of a symbiotic relationship between legumes and microorganisms requires a fine balance between the exchange of signal molecules and the regulation of the plant's own defense response. In the rhizobium-legume symbiosis, the most critical signal molecule is the aforementioned nodulation factor (Nod factor). After the plant recognizes the Nod factor through the NFR1/NFR5 receptor located on the surface of the root hair, it activates the downstream cascade reaction including calcium ion oscillation and symbiosis-related gene expression, triggering the nodulation process. At the same time, the plant needs to suppress its own immune system to allow the invasion and colonization of symbiotic bacteria, otherwise the rhizobia may be regarded as pathogens and blocked by the plant's defense response. Studies have shown that legumes have functionally differentiated the pathways for identifying symbiotic microorganisms and pathogens: on the one hand, plants trigger symbiotic signals through a unique Nod factor receptor pathway, thereby bypassing the strong immune response induced by typical pathogen-associated molecular patterns (MAMPs); on the other hand, plants still use some immune mechanisms to monitor the symbiotic process to ensure that only the correct strains can successfully nodulate without harming the health of the host. For example, the plant microbial receptor kinase EPR3 can bind to the surface polysaccharide signal on the surface of rhizobia to distinguish whether it is a suitable symbiotic strain. If an "unqualified" signal is detected, a defense response is triggered to limit its infection. For another example, plants produce reactive oxygen and antimicrobial substances to inhibit excessive bacterial growth, but symbiotic rhizobia have evolved tolerance

RkJQdWJsaXNoZXIy MjQ4ODYzNA==