New Advance in Germplasm Resources, Biotechnology and Genetic Breeding of Vegetable Crops

The acquisition, characterization and exploitation of germplasm resources are fundamentally important for mining key genes, thereby providing critical genetic foundations for future improvements in productivity and quality of vegetable crops. This Special Issue, “New Advance in Germplasm Resources, Biotechnology and Genetic Breeding of Vegetable Crops”, published in the journal Horticulturae, features five original articles that exemplify the current advances in identification and application of germplasm resources. These studies enhance our understanding of the utilization of germplasm resources, which is essential for promoting the yield and quality of vegetable crops in the future.

1. Advances in Germplasm Resources, Biotechnology and Genetic Breeding Across Vegetable Crops

In recent years, with global population growth and increasing climate change, the breeding of vegetable crops for high yield, superior quality, and stress resistance has become a key focus in agricultural research. Advances in germplasm resource exploration, biotechnological innovations, and genetic breeding methods have provided new opportunities for improving the yield and quality of vegetable crops. Notably, the improvement of vegetable crop quality is closely associated with the breeding of superior varieties. The collection and evaluation of germplasm resources, along with elucidating variations in nutritional characteristics and stress resistance among different cultivars and geographical origins, provide key theoretical foundations for breeding high-quality vegetable varieties.

Researchers from different countries have identified and evaluated germplasm resources of various vegetable crops based on breeding objectives in different periods. The commonly used identification methods for crop germplasm resources include morphology and physicochemical analysis, DNA barcoding and fingerprinting, chloroplast genomics, and other approaches [1,2,3]. Furthermore, molecular-level identification technologies are rapidly advancing. Among these, multi-omics technologies (including genomics, transcriptomics, proteomics, and metabolomics) systematically characterize molecular features, providing revolutionary tools for the identification, evaluation, and utilization of vegetable crop germplasm resources [4,5,6]. And specialized databases have been developed to significantly accelerate the application of multi-omics technologies in germplasm resource evaluation and genetic breeding of vegetable crops. For example, GERDH (https://dphdatabase.com/, accessed on 15 April 2025) is a cross-species data mining platform for horticultural plants, integrating 12,961 uniformly processed omics datasets from over 150 horticultural plant accessions to enable gene discovery and functional analysis via interactive tools (e.g., co-expression, epigenetic regulation, phylogenetics) [7]. Pepper Full-Length Transcriptome Variation Database (PFTVD 1.0) (http://pepper-database.cn/, accessed on 15 April 2025) provides a user-friendly online platform for querying, visualizing, and analyzing pepper transcriptomic and genomic data (e.g., gene expression, alternative splicing, gene co-expression), facilitating research in pepper developmental biology and the mining of functional genes [8]. AlliumDB (https://allium.qau.edu.cn/, accessed on 15 April 2025) integrates comprehensive genomic, transcriptomic, and phenotypic datasets across Allium species and facilitates functional gene mining and molecular breeding in Allium species, while offering critical resources for genetic mechanism dissection and variety improvement [9]. LettuceDB (https://db.cngb.org/lettuce/, accessed on 15 April 2025) assembles multidimensional omics data (genome, variome, phenome, microbiome, and spatial transcriptome) for cultivated lettuce and its wild relatives, which serve as a one-stop platform for lettuce research and breeding [10]. Cucumber-DB (http://www.cucumberdb.com/#/home/, accessed on 15 April 2025) is a multi-omics database integrating near-complete genomic sequences, precise gene/transcript annotations, expression atlases, and analytical tools, enabling functional genomics and molecular breeding in cucumber, which facilitates germplasm evaluation and accelerate cucumber breeding [11].

Currently, the primary evaluation and analysis methods for vegetable crop germplasm resources include correlation analysis, grey relational analysis (GRA), principal component analysis (PCA), cluster analysis. They are widely utilized for evaluating and analyzing germplasm resources and have been extensively applied across diverse vegetable crops, such as eggplant [12], amaranth [13], carrot [14], celery [15], cucumber [16], broccoli [17], radish [18], pepper [19], and tomato [20,21], and so on. However, crop comprehensive evaluation is influenced by multiple parameters, and relying solely on a single criterion for assessment is inherently one-sided. Therefore, integrated evaluation methods are typically adopted based on research needs to holistically analyze the traits of vegetable crops.

Beyond generating novel germplasm through diverse methodologies, plant breeders employ two strategic methods to harness vegetable crop genetic resources. On one hand, newly introduced or locally developed accessions undergo rigorous evaluation for traits such as yield, stress tolerance, and quality, with top-performing candidates directly deployed in commercial cultivation after multi-location trials. On the other hand, germplasm carrying unique value-added traits (e.g., disease resistance genes or enhanced nutritional profiles) are subjected to advanced breeding strategies, with integrating conventional hybridization and precision genome editing tools (such as CRISPR-Cas9), which accelerates the development of market-ready varieties.

2. Highlights of the Contributions

2.1. Germplasm Screening and Evaluation

Sugar beet (Beta vulgaris L.), an important sugar crop originating from the Mediterranean region, was domesticated from wild sea beet (B. vulgaris ssp. maritima) and currently contributes approximately 20% of global sucrose production, serving as an indispensable economic crop and bioenergy feedstock in temperate zones. Peng et al. [22] comprehensively evaluated 129 sugar beet germplasms using 60 molecular markers (27 SSRs and 33 InDels) and 20 phenotypic traits, demonstrating that SSR markers’ superior discriminatory power over InDels for genetic studies and highlight petiole traits as key morphological indicators of diversity, which provide a scientific basis for selecting elite breeding materials and optimizing hybrid combinations in sugar beet improvement programs. The integrated molecular-phenotypic approach establishes a framework for efficient germplasm utilization to enhance sugar beet productivity and quality.

Field pea (Pisum sativum L.) is one of humanity’s oldest cultivated crops dating back to 7000–6000 BC in the Mediterranean, as well as the world’s second-most important food legume, valued as a nutritious, affordable protein source (25.1%) and a sustainable crop that enhances soil fertility through nitrogen fixation. Sharma et al. [23] identified superior field pea lines (Aman and HFP 715), the tester GP02/1108 and the crosses (HFP 715 × GP02/1108 and IPF 14-16 × GP02/1108) through combining ability analysis, revealing non-additive gene dominance for yield traits and validating GGE/PCA biplots as effective tools for combining ability evaluation. The findings demonstrate heterosis breeding’s potential for rapid genetic gains while establishing an integrated analytical framework to guide hybrid development in pea improvement programs.

2.2. Gene Function Research

EMS mutagenesis is a key tool for germplasm resource innovation, efficiently inducing genetic variation to provide resources for crop trait improvement and functional gene research. Zhou et al. [24] reported an EMS-induced cucumber mutant, se59, which exhibits virescent true leaves with reduced chlorophyll content and defective chloroplast development, leading to impaired photosynthetic capacity. CsSE59, encoding an Invertase/Pectin Methyl Esterase Inhibitor (INV/PMEI), was identified as the candidate gene via BSA-seq, and RNA-seq data revealed that differentially expressed genes (DEGs) were primarily enriched in photosynthesis and photosynthesis-antenna proteins, indicating CsSE59’s involvement in regulating chloroplast development and chlorophyll synthesis in cucumber.

Nitrogen (N) is essential for plant growth but over 60% of applied N fertilizers are lost to the environment, with plants preferentially assimilating NH₄⁺ via the energy-efficient GS-GOGAT pathway under high CO₂ or N-deficiency despite its toxicity at high concentrations. Zhu et al. [25] focused on BcAMT1;5, which encoded an AMT1-type ammonium transporter in flowering Chinese cabbage, demonstrating its predominant root/flower expression, upregulation under N-deficiency, and suppression by NH₄⁺ supply. Functional analysis revealed BcAMT1;5 enhances NH₄⁺ uptake, alters N-assimilation gene expression, and increases NH₄⁺/NO₃⁻ accumulation in low-N conditions, contrasting with other AMT1 genes. Unlike typical AMT1s, BcAMT1;5 exhibits unique tissue specificity and regulatory responses, highlighting its distinct role in adaptive N acquisition and potential for improving crop N-use efficiency.

2.3. Gene Family Identification

Meng et al. [26] systematically identified 9 YUC/FZY genes and 5 TAA/TAR genes in tomato through comprehensive bioinformatics analysis, and qRT-PCR results revealed that SlFZY2/3/4-1/5 and SlTAA3/5 exhibited predominant expression in floral organs, strongly suggesting their crucial regulatory roles in tomato floral development. These findings provide essential components for understanding the auxin biosynthesis pathway in tomato, and further investigation is required to determine whether these tomato genes exhibit functional redundancy similar to their Arabidopsis homologs.

3. Conclusions and Prospects

Germplasm resources serve as the fundamental basis for vegetable crop breeding. Globally, significant advancements have been made in recent years regarding the collection, identification, and utilization of germplasm resources in vegetable crops. This Special Issue aims to provide a comprehensive overview of advancements on the development of new varieties or germplasms with higher yields and quality and resistance to biotic and abiotic stresses or on the identification of new genes or specific alleles on the basis of multi-omics technologies, genomics and germplasm research, as well as breeding technologies for vegetable crops. We believe that the articles and insights discussed here will provide readers with relevant knowledge that the key technological framework of modern vegetable breeding, encompassing: (1) germplasm collection and core collection construction, (2) mining and functional characterization of key trait genes, (3) innovative applications of modern biotechnologies including gene editing (CRISPR-Cas9) and haplotype breeding, and (4) multi-omics driven precision breeding strategies. The integration of these cutting-edge technologies, particularly through interdisciplinary convergence with emerging fields like artificial intelligence and synthetic biology, is accelerating the transition toward intelligent and precision vegetable breeding, thereby providing crucial technological support for global food security and sustainable agricultural development.