With the growth of the global population and the increasing emphasis on healthy dietary choices, the demand for vegetable crops is on a continuous upward trend. As a crucial source of nutrition, vegetables play an essential role in ensuring global food security and meeting the growing nutritional needs. Facing this increasing demand, agricultural production faces multiple challenges, such as improving production efficiency, enhancing crop adaptability to the environment, and increasing resistance to pests and diseases (Basile et al., 2023). These challenges have driven the development and application of genetic improvement techniques, a strategy aimed at optimizing crop genetic characteristics to increase yield, enhance disease resistance, and enrich nutritional value. Genetic improvement not only helps improve overall crop performance but is also crucial for the sustainable development of agriculture. Research has shown that through scientific genetic improvement strategies, these challenges can be effectively addressed, thereby stabilizing and increasing global vegetable production (Zhao et al., 2019). This approach is not only significant for current agricultural production models but also lays the foundation for future food supply chains and nutritional security.

Genome-Wide Association Studies (GWAS) is a powerful genetic method that elucidates the link between genes and phenotypes by identifying genetic variations associated with specific traits across the entire genome. The basic principle of GWAS is to utilize natural genetic variations in a large sample population and use statistical analysis to determine which genetic markers are closely associated with the target trait. Over the past few decades, GWAS has made significant progress in crop improvement research, particularly in elucidating the genetic factors affecting crop yield, disease resistance, and nutritional composition. For example, in soybeans, GWAS identified genes associated with resistance to charcoal rot (Macrophomina phaseolina), providing new information for improving soybean varieties (Coser et al., 2017). Furthermore, the application of GWAS is not limited to the improvement of a single trait. In terms of comprehensive multi-trait improvement, such as simultaneously improving crop yield, disease resistance, and nutritional composition, GWAS has also shown tremendous potential. For instance, GWAS studies on tomatoes have not only revealed genes influencing fruit size and yield but have also identified key genetic factors affecting nutritional components such as lycopene content (Rodriguez et al., 2020).

This study aims to analyze in depth how GWAS impacts the yield and nutritional value of vegetable crops and explores how to optimize vegetable crop traits from a genetic perspective. The main focus is on the key genetic markers identified using the GWAS method and how to apply these genetic findings to the breeding process to promote the improvement of vegetable crop traits. Through this study, we hope to fill the gap in the existing literature regarding the practical application and evaluation of using GWAS for genetic improvement of vegetable crops. Additionally, the study aims to provide insights into the future direction of crop genetic improvement, particularly on how to effectively utilize genetic resources to address global food supply challenges.

1 Overview of Genome-Wide Association Studies (GWAS)

1.1 Principles and workflow of GWAS

Genome-Wide Association Studies (GWAS) is a population genetics-based method aimed at identifying associations between genetic variations and specific traits (Yoon et al., 2018). The core of GWAS is to analyze the genetic data (typically single nucleotide polymorphisms, SNPs) and phenotypic data (such as yield, disease resistance, nutritional components, etc.) of a large number of individuals to find which genetic variations are associated with the target trait.

The workflow of Genome-Wide Association Studies (GWAS) includes several key steps. First, a sample population with genetic diversity needs to be selected, and its whole-genome data obtained through high-throughput sequencing techniques to ensure that the samples cover sufficient genetic variation. Subsequently, the phenotypic data of each sample, such as plant height, fruit size, nutrient content, etc., is recorded in detail to prepare for the association analysis. Using biostatistical methods, such as association analysis, the genetic markers (e.g., single nucleotide polymorphisms, SNPs, or other forms of genetic variation) that are significantly associated with the target trait are determined. Based on these statistically significant genetic markers, candidate genes that may affect the specific trait are identified. Finally, through experimental methods such as gene knockout or overexpression studies, the actual impact of these candidate genes on the trait is verified to ensure that the discovered associations have biological significance (Cirillo et al., 2018).

1.2 History and development of GWAS in plant science

The development of Genome-Wide Association Studies (GWAS) in plant science has gone through several important stages. GWAS was initially used for genetic research on human diseases, such as heart disease, diabetes, autoimmune diseases, and mental disorders, proving its value in elucidating the genetic basis of complex traits (Abdellaoui et al., 2023). In the early 2000s, GWAS techniques began to be applied to plant science research (Figure 1), marking the expansion of its application scope (Fang and Luo, 2018).

In 2005, the first GWAS study on plants was published on the model plant Arabidopsis thaliana, marking the successful initial application of GWAS in plant science (Aranzana et al., 2005). Subsequently, research gradually expanded to major economic crops. For example, in rice, GWAS revealed the genetic basis for controlling mineral and micronutrient composition, providing an important foundation for further research into plant genetics and molecular mechanisms (Yang et al., 2018). Shortly after, important food crops such as maize and wheat also began GWAS research.

These early studies primarily focused on elucidating the genetic basis of key agronomic traits affecting crop yield, disease resistance, and stress tolerance. With technological advances, particularly the development and cost reduction of high-throughput sequencing technologies, the application of GWAS has significantly expanded. In the 2010s, more vegetable crops such as tomatoes, carrots, and spinach were included in GWAS studies, which not only focused on yield and disease resistance but also gradually involved complex traits such as nutritional quality (Harish et al., 2023).

By the second decade of the 21st century, GWAS had become an indispensable research tool in the field of plant science, capable of utilizing larger sample sizes and more abundant genetic diversity to provide more precise and comprehensive genetic information. Furthermore, the methodologies of GWAS have also been constantly evolving, such as through the integration of phenotypic, genotypic, and environmental data in multi-omics analysis, further improving the accuracy and depth of research (Kao et al., 2017). These advances have not only deepened our understanding of crop genetic mechanisms but have also provided richer and more precise genetic resources for crop genetic improvement.

1.3 Comparison of GWAS with other genetic improvement methods

GWAS provides a more comprehensive and in-depth approach to plant genetic improvement, enabling researchers to explore the complex relationships between genetic variations and traits across the entire genome (Tibbs Cortes et al., 2021). Compared to traditional genetic improvement methods such as selective breeding and hybridization, GWAS offers a more precise and efficient approach to identifying genetic variations associated with specific traits. Traditional breeding relies on phenotypic selection and visual assessment of genetic diversity, while GWAS can precisely locate genes or genetic regions associated with traits using genetic markers. Compared to marker-assisted selection (MAS), GWAS covers a broader range of the genome, enabling the exploration of more unknown relationships between genetic variations and traits. MAS typically relies on known associations between genetic markers and traits, while GWAS can identify new associations without bias.

The application of GWAS has also led to a series of innovations in the fields of plant genetics and breeding, including the development of multi-omics integrated analysis, precision breeding, and gene-editing technologies. Research has found that combining GWAS with genomic selection (GS) provides new methods for crop improvement, particularly in long-cycle fruit tree breeding, where GWAS can identify genetic markers associated with important agronomic traits (Iwata et al., 2016). These developments further enhance the potential of GWAS in crop improvement, enabling researchers to more rapidly translate genetic discoveries into practical applications. In practice, GWAS results can be directly applied to marker-assisted breeding (MAS), allowing for rapid and accurate selection of plants with desired traits during the breeding process. Additionally, the candidate genes identified through GWAS provide precise targets for gene editing, enabling researchers to directly modify specific genes to improve crop traits.

GWAS has played an important role not only in scientific research but also in providing powerful tools for practical crop genetic improvement. Through comparison and integration with other genetic improvement methods, GWAS is expected to play a greater role in global agricultural production, particularly in increasing crop yield, improving nutritional quality, and enhancing environmental adaptability.

2 Current Status and Challenges in Vegetable Crop Genetic Improvement

Genetic improvement of vegetable crops not only needs to consider the goals of increasing production and improving quality but also needs to overcome technical and methodological challenges, and gain a deep understanding of the complex interactions between genetic and environmental factors to meet the growing global food demand and environmental challenges. To overcome these challenges, researchers can adopt a comprehensive approach, combining traditional breeding techniques with knowledge from molecular genetics, ecology, and environmental science.

2.1 Major improvement goals and research trends

Genetic improvement of vegetable crops is primarily focused on improving yield, enhancing nutritional quality, increasing disease resistance, and improving stress tolerance. With the growth of the global population and rising food demand, increasing yield has become one of the core objectives. Researchers are striving to achieve higher crop yields per unit area through genetic improvement while maintaining or improving the nutritional value of vegetables. Sardar (2023) found that the use of gene-editing techniques such as CRISPR/Cas9 can improve the quality, yield, and overall productivity of vegetables and fruits, while improving stress tolerance and meeting biosafety standards.

In terms of disease resistance, as diseases can significantly reduce the yield and quality of vegetable crops, researchers seek to identify and introduce disease resistance genes to increase crop resistance to specific pathogens (Samal and Rout, 2018). Furthermore, with the increasingly significant impact of global climate change, the stress tolerance of vegetable crops, such as drought, heat, and salt-alkali tolerance, has also become an important target for genetic improvement.

2.2 Technical and methodological challenges in genetic improvement

Despite significant progress in genetic improvement, technical and methodological challenges still exist. One major issue is the limitation of genetic diversity, particularly for economically valuable specialized vegetable varieties, which may lack sufficient genetic diversity, limiting the available genetic resources for improvement (Bate et al., 2021). Additionally, vegetable crop genetic improvement often involves complex traits, which are typically controlled by multiple genes and influenced by environmental factors. This means that identifying and manipulating the multiple genes affecting these complex traits is a technical challenge, especially in the absence of complete genetic maps and functional genomic data.

Efficient genotyping and phenotyping methods are crucial in the genetic improvement process, requiring accurate and high-throughput techniques to handle large numbers of samples, rapidly and accurately identifying genetic markers for target traits. There are also challenges in data management and analysis, as large-scale GWAS studies and the integration of genotypic and phenotypic data generate massive amounts of data, requiring efficient data management and analysis tools for processing and interpretation. Furthermore, for some vegetable crops that have not been widely studied, the lack of complete reference genomes, annotated databases, and functional verification tools limits research into the genetic improvement of these crops. Addressing these challenges requires the integrated application of methods and techniques from various disciplines, including genetics, molecular biology, computational biology, and statistics.

2.3 Influence of environmental factors and genetic complexity

The phenotypic expression of vegetable crops is influenced by both genetic and environmental factors, increasing the complexity of genetic improvement. On one hand, environmental conditions can significantly affect gene expression and phenotypic variation of traits; on the other hand, the genetic control of traits may exhibit different genetic mechanisms under different environmental conditions. Geshnizjani et al. (2020) found that the quality of tomato seeds and the establishment of seedlings are influenced by genetic background and maternal environment. Through a study of a tomato hybrid population, they revealed how seed quality is controlled by adverse maternal conditions, which may aid in improving the production of high-performance seeds. Research has shown that wheat traits are significantly influenced by genotype, while sowing date has the greatest impact on early developmental stages, indicating that environmental conditions such as sowing time significantly impact plant traits (Kiss et al., 2019).

The improvement of environmental adaptability requires considering crop performance in different geographic locations and climatic conditions. With the exacerbation of global climate change, cultivating crops with stronger adaptability has become increasingly important, requiring researchers to consider a broader range of environmental factors and climate variations in the genetic improvement process. Therefore, breeding strategies need to be highly flexible and foresighted to ensure that vegetable crops can adapt to potential future environmental changes.

3 Application of GWAS in Vegetable Genetic Improvement

3.1 Vegetable yield

In research aimed at increasing vegetable yield, GWAS has been successfully applied to identify key genes associated with yield. For example, in GWAS studies conducted on tomatoes, scientists have been able to identify multiple genetic loci associated with fruit size and yield. Among these loci, key genes were further analyzed, revealing their involvement in fundamental physiological processes of plant growth and development. For instance, The GWAS analysis conducted by Rodriguez et al. (2020) revealed valuable genetic diversity in local varieties of tomatoes and identified genomic regions controlling fruit characteristics. Kim et al. (2021) conducted a genome-wide association study (GWAS) on 162 tomato accessions, exploring quantitative trait loci (QTLs) influencing eight fruit traits, providing a useful resource for the genetic dissection of tomato fruit traits.

Through functional analysis, researchers can determine the specific mechanisms of these genes, thereby providing specific targets for the breeding program. This not only deepens our understanding of the mechanisms of yield formation but also provides potential pathways for improving yield in other vegetable crops.

3.2 Disease resistance

In genetic improvement, enhancing disease resistance in vegetable crops is a critical task. Genome-Wide Association Studies (GWAS) provide an effective means to elucidate the genetic basis of crop-pathogen interactions. Researchers have successfully identified disease resistance-related genes in various vegetable crops using GWAS. For example, in Brassica napus, GWAS analysis revealed multiple genetic markers associated with blackleg disease resistance. Fikere et al. (2020) used a GWAS integrating whole-genome sequence (WGS) to analyze genes and genomic regions associated with blackleg resistance (Leptosphaeria maculans) in Brassica napus. The study identified 79 genomic regions associated with L. maculans resistance and revealed new potential resistance regions. GWAS has also identified multiple loci associated with Al3+ resistance in rapeseed, which helps improve plant tolerance to aluminum stress and provides new genetic resources and markers for enhancing Al3+ resistance in rapeseed through genomic and marker-assisted selection (Du et al., 2022). The identification of these genetic markers not only promotes the understanding of disease resistance mechanisms, such as the role of plant immune signaling pathways, but also provides specific molecular targets for breeding. This enables breeders to precisely improve disease resistance in vegetable crops through marker-assisted selection or gene-editing technologies, thereby enhancing their defense against pathogens.

Furthermore, the application of GWAS has extended to in-depth research into the mechanisms of disease occurrence, including the host-pathogen interaction mechanisms during the pathogen invasion process. By analyzing these interactions in depth, researchers can develop new strategies to enhance crops' natural resistance, reducing reliance on chemical pesticides. Additionally, GWAS can help predict crop resistance to emerging or evolving pathogens, enabling proactive measures in crop protection.

GWAS has played a significant role in improving disease resistance in vegetable crops, providing important scientific foundations and technical support for modern agricultural production, and contributing to the realization of more sustainable and environmentally-friendly crop management strategies.

3.3 Improved adaptability

Environmental adaptability is a crucial trait for vegetable crops to survive and thrive under changing environmental conditions. GWAS has played an important role in identifying genes associated with drought tolerance, salt tolerance, and other environmental stress response mechanisms. For drought tolerance studies, GWAS can identify genes affecting plant water use efficiency and transpiration rates. In sesame drought and salt tolerance studies, GWAS revealed significant single nucleotide polymorphisms (SNPs) and potential candidate genes associated with these stress responses (Li et al., 2018). In barley, Tu et al. (2021) used GWAS and transcriptomic analysis to identify salt-responsive genes with altered expression under salt stress, primarily involved in metabolic and transport processes, which could aid in improving crop salt tolerance.

In some vegetable crops, GWAS has successfully identified multiple genes associated with drought tolerance, often involving physiological processes such as water regulation, root development, and osmotic adjustment. For example, in maize GWAS research, the natural variation in the ZmVPP1 gene was found to significantly contribute to seedling drought tolerance through enhanced photosynthetic efficiency and root development (Wang et al., 2016). By understanding the mechanisms of these genes, more drought-tolerant vegetable varieties can be cultivated, enhancing the sustainability of agricultural production.

GWAS plays a crucial role in the genetic improvement of vegetable crops, from increasing yield to enhancing disease resistance and improving environmental adaptability. This methodological approach continues to drive scientific progress and practical applications in vegetable breeding. By precisely identifying key genetic factors, GWAS accelerates the process of improving vegetable varieties, providing robust scientific support to meet the growing global food demand.

4 The Role of GWAS in Improving Nutritional Value of Vegetable Crops

GWAS plays a significant role in improving the nutritional value of vegetable crops. By precisely identifying and functionally validating nutrition-related genes, GWAS provides powerful genetic and molecular biology tools for the nutritional improvement of vegetable crops, thereby promoting the development and adoption of healthier dietary patterns.

4.1 Genetic basis of nutrition-related traits

The nutritional value of vegetable crops, including the content of vitamins, minerals, antioxidants, and dietary fiber, is a multi-genic trait controlled by complex genetic networks. The formation and expression of these traits depend on intricate biochemical pathways and metabolic networks within plants, which interact and regulate through various mechanisms during plant growth and development. For example, the synthesis of carotenoids involves multiple biochemical reactions controlled by a series of enzyme-coding genes, whose activities and expression levels are jointly regulated by multiple genes through complex regulatory networks, affecting the final carotenoid content (Saini et al., 2015).

The genetic basis of nutrition-related traits is also significantly influenced by environmental factors, such as soil type, water conditions, sunlight exposure, and temperature, which can significantly affect plant metabolic processes and the accumulation of nutrients. Therefore, the interaction between genetics and environment is crucial for understanding and improving the nutritional value of vegetable crops.

Understanding the genetic and environmental basis of traits related to nutritional value not only helps scientists and breeders select or design improved vegetable varieties more effectively, but also aids in developing vegetable products that meet the nutritional needs and preferences of consumers. This requires the use of advanced tools in genetics, molecular biology, and bioinformatics to identify and utilize genes and genetic variations that significantly impact nutritional value.

4.2 The role of GWAS in identifying nutrition-related genes

Genome-Wide Association Studies (GWAS) play a crucial role in elucidating the connections between vegetable crop nutritional traits and genotypes. Through association analysis, GWAS can identify genetic markers closely associated with variations in nutrient content, providing important clues for in-depth investigation of gene function and regulatory mechanisms. For example, in studies of local and modern tomato varieties, GWAS not only effectively identified genomic regions controlling fruit traits using the SNP diversity from RNA sequencing but also discovered variations associated with climate change adaptability (Rodriguez et al., 2020).

Research has also revealed the genetic basis of other nutrition-related traits, such as chlorophyll content, vitamin and mineral levels, which typically involve complex biochemical pathways and metabolic networks. By identifying the key genes and genetic variations controlling these important nutritional traits, researchers can better understand the mechanisms of plant nutritional metabolism and strategically enhance crop nutritional value through genetic improvement (Guo et al., 2023).

These findings have not only deepened our understanding of the genetic control of crop nutritional traits but have also facilitated the development of new breeding strategies focused on improving crop nutritional value and consumer acceptance. Consequently, GWAS plays a crucial role in identifying nutrition-related genes, significantly impacting nutritional improvement and enhancing the market value of vegetable crops.

4.3 Applications of GWAS in enhancing vegetable nutritional value

In the application of GWAS to enhance vegetable nutritional value, the identified gene information is used to guide molecular marker-assisted selection or gene-editing breeding strategies, aiming to enhance the nutritional quality of vegetables. The effectiveness of these strategies has been demonstrated in various vegetable crops. A study on wheat varieties using meta-GWAS methods revealed marker-trait associations for processing and end-use quality traits, which can aid in selecting markers during the breeding process (Battenfield et al., 2018). Additionally, other studies have applied GWAS in tropical rice and other crops, demonstrating the potential of using whole-genome data to predict the breeding value of progeny, thereby accelerating the pace of genetic improvement (Spindel et al., 2015). Through the application of GWAS, researchers have been able to identify genetic markers associated with important agronomic traits in soybeans and other crops, which can be used for marker-assisted selection in breeding programs (Yoosefzadeh-Najafabadi et al., 2023).

Such studies further demonstrate the application value of GWAS in identifying genes associated with vegetable nutritional quality, supporting its effectiveness in enhancing the nutritional and antioxidant properties of vegetables. By precisely identifying the genes controlling the synthesis of these secondary metabolites, breeding programs can strategically improve the nutritional characteristics of vegetable crops, providing consumers with healthier food choices. This approach not only enhances the nutritional value of vegetables but also contributes to increasing crop diversity and market competitiveness, thereby supporting the development of sustainable agriculture and food systems.

5 Case Study

5.1 Case study of GWAS application in specific vegetable crops

Taking tomato as an example, it is one of the major vegetables widely cultivated and consumed globally. In tomato genetic improvement, the application of GWAS has successfully revealed key genetic markers influencing lycopene content. Lycopene is an important antioxidant with numerous benefits for human health. By conducting genome-wide association analysis on different tomato varieties, researchers have successfully identified several genetic markers significantly associated with tomato lycopene content. For instance, Tiwari et al. (2023) increased lycopene content in tomatoes using the CRISPR/Cas9 gene-editing technique, demonstrating the tremendous potential of gene-editing technologies in genetic improvement, whose applications are not limited to improving nutritional value but also include enhancing stress tolerance and disease resistance, among other aspects (Figure 2). Through these studies, researchers can precisely modify specific genes in plant breeding to achieve specific breeding goals.

Furthermore, GWAS has made significant progress in elucidating the genetic basis of multiple traits affecting tomato fruit quality, such as editing and functionalizing various traits like plant structure, floral characteristics, fruit ripening, quality and nutrition, and disease resistance in tomatoes. These findings have provided important molecular markers for tomato genetic improvement, contributing to the development of superior tomato varieties (Ruggieri et al., 2014).

5.2 Impact and improvement effectiveness of the case study

In the case of tomato breeding, the results of GWAS research have significantly impacted breeding strategies and effectiveness. Through GWAS, scientists precisely located the key genes controlling lycopene synthesis in tomatoes, enabling breeders to use marker-assisted selection (MAS) techniques to cultivate new tomato varieties with high lycopene content. This genetic improvement not only significantly enhanced the nutritional value of tomatoes but also increased their market competitiveness and consumer preference due to their more vibrant color and improved flavor. Additionally, tomato varieties rich in lycopene are beneficial for health as lycopene is believed to have antioxidant properties that can reduce the risk of chronic diseases. Therefore, these breeding achievements have not only enhanced the intrinsic quality of tomatoes as a vegetable but have also had a positive impact on public health.

The application of GWAS in tomato breeding demonstrates its powerful potential in genetic improvement, capable of improving not only the nutritional and sensory quality of crops but also enhancing their economic value and market performance. This scientifically driven breeding approach provides a viable pathway for the future improvement of vegetable crops, contributing to the sustainable development of agricultural production and the improvement of food nutrition.

5.3 Key findings and technical applications in the case study

One of the key findings in this case study is that a specific gene locus variation significantly affects the accumulation of lycopene in tomatoes. This discovery not only revealed the molecular mechanisms underlying lycopene synthesis in tomatoes but also provided a clear breeding target. The study also demonstrated the importance of combining high-throughput genotyping and precise phenotyping, enabling researchers to effectively screen and identify genetic variations associated with the target trait.

In terms of technical applications, this research utilized the latest genomic sequencing techniques, bioinformatics analysis, statistical genetics methods, and advanced phenotyping techniques. The fusion of this multidisciplinary approach not only accelerated the process of genetic marker discovery but also improved the efficiency and precision of breeding. Through such GWAS studies, scientists and breeders can conduct crop improvement in a more systematic and precise manner, ultimately promoting innovation and sustainable development in agricultural production.

6 Technical Challenges and Future Trends

6.1 Technical challenges

Despite significant achievements in the field of plant genetics through Genome-Wide Association Studies (GWAS), several technical challenges remain to be overcome. The complexity of genetic backgrounds is a primary challenge, as it may obscure or confound the true associations between traits and genetic variations. For plant species with large genomes, conducting large-scale GWAS not only requires substantial financial support but also demands processing and analyzing vast amounts of data, placing high demands on data processing capabilities (Kao et al., 2017). Furthermore, translating GWAS discoveries into practical applications through biological validation is a time-consuming and complex process, requiring in-depth functional genomics research (Yoon et al., 2018).

To address these challenges, researchers are developing and optimizing various technical approaches. More efficient sequencing technologies are being developed to reduce costs and increase the speed of data acquisition. Simultaneously, more precise statistical analysis methods are being explored to improve the resolution of complex genetic data. High-throughput phenotyping techniques are also continuously improving, aiming to measure and record plant traits more rapidly and accurately. Additionally, the application of machine learning and artificial intelligence technologies is becoming a powerful tool for improving data analysis speed and accuracy. These technological advancements are expected to greatly improve the efficiency and effectiveness of GWAS, better serving plant genetics research and crop improvement projects.

6.2 Future trends

In future trends, gene-editing technologies, particularly the CRISPR-Cas system, are expected to play an increasingly central role in GWAS research, making genetic research more precise and efficient (Li et al., 2016). Advances in CRISPR technology will allow researchers to directly edit target genes, not only accelerating the functional validation process of GWAS-discovered candidate genes but also enabling direct application to crop trait improvement, thereby achieving more direct and rapid genetic improvement.

In the future, the application of GWAS will increasingly be combined with other advanced technologies, such as transcriptomics, proteomics, and metabolomics. This multi-omics integration will provide a more comprehensive perspective to understand how genetic variations influence complex traits at the molecular level. By elucidating the detailed molecular mechanisms controlling these traits, researchers can more accurately predict the results of gene editing and the potential for crop improvement. Additionally, the development of data analysis and artificial intelligence technologies will further promote the depth and breadth of GWAS research. With the application of machine learning and deep learning algorithms, large-scale genomic data can be processed and analyzed more effectively, revealing new associations and patterns in genetic research.

The future development of GWAS will be a multidisciplinary and highly integrated process, involving not only advances in gene-editing technologies but also the comprehensive utilization of multi-omics data and the application of advanced data analysis techniques. These advancements will provide a strong scientific foundation for uncovering new opportunities and challenges in crop genetic improvement.

6.3 Ethical and regulatory considerations

Ethical and regulatory considerations are an important part of research on genetically improved crops, particularly those improved through gene-editing technologies. The ethical and legal controversies surrounding these technologies span multiple areas, including food safety, biodiversity protection, intellectual property rights, and technology accessibility. Regarding food safety, the public is concerned about whether gene-edited crops are safe and reliable and whether they will impact human health or the environment. In terms of biodiversity protection, there are concerns that gene-editing technologies may have unknown impacts on natural ecosystems, for example, through transgene escape or gene pollution. Intellectual property issues involve the ownership and usage rights of genetic resources and new varieties, as well as how these rights affect technology sharing and technology transfer between countries in the global North and South. The accessibility of technology is a concern about ensuring that all farmers, including smallholders in developing countries, have fair access to advanced genetic improvement technologies.

Facing these challenges, the international community is striving to reach a consensus and regulate the application of these technologies through international treaties such as the Nagoya Protocol and the Cartagena Protocol on Biosafety (Ishii and Araki, 2017). National laws and policies are also continuously evolving to adapt to the pace of scientific and technological development and ensure that the research and application of genetically improved crops comply with scientific requirements, ethical principles, and public interests. These regulations and policies aim to ensure that the development process of genetically improved crops is transparent and responsible, covering the entire process from laboratory research to field application, including conducting appropriate risk assessments and public consultations.

7 Conclusion and Outlook

Genome-Wide Association Studies (GWAS) have achieved significant accomplishments in the genetic improvement of vegetable crops, significantly driving the progress of crop science. Through GWAS, scientists have successfully identified numerous key genes affecting vegetable crop yield, disease resistance, adaptability, and nutritional value. These findings have not only deepened our understanding of the genetic basis of vegetables but have also directly promoted increased breeding efficiency, enabling the cultivation of higher-yielding, healthier, and more environmentally adaptable crop varieties.

Future research may further explore the relationships between genetic variations and complex traits, particularly the influence of environmental variations on the expression of these traits. With the further development of gene-editing technologies such as CRISPR-Cas9, combined with GWAS results, more precise genetic improvement can be achieved, overcoming challenges that traditional breeding has struggled to address. Additionally, more interdisciplinary research is expected to emerge, combining knowledge and techniques from fields such as ecology, genetics, molecular biology, and computational biology, to comprehensively understand the complex mechanisms of crop growth and development.

GWAS and its applications in vegetable crop genetic improvement have profound implications for agricultural production. By improving crop yield and nutritional value, GWAS contributes to meeting the growing global food demand, positively impacting food security and nutritional health. Meanwhile, by cultivating crop varieties more adaptable to environmental changes, GWAS can also enhance the sustainability of agricultural production and reduce its negative impact on the environment.

In summary, GWAS has opened new possibilities for vegetable crop genetic improvement, and its potential in scientific research and practical applications is gradually unfolding. With continuous technological advancements and expanding applications, GWAS will continue to play a crucial role in addressing global agricultural and food challenges.

References

Abdellaoui A., Yengo L., Verweij K.J., and Visscher P.M., 2023, 15 years of GWAS discovery: realizing the promise, The American Journal of Human Genetics, 110(2): 179-194.

https://doi.org/10.1016/j.ajhg.2022.12.011

PMid:36634672 PMCid:PMC9943775

Aranzana M.J., Kim S., Zhao K., et al., 2005, Genome-wide association mapping in Arabidopsis identifies previously known flowering time and pathogen resistance genes, PLoS genetics, 1(5): e60.

https://doi.org/10.1371/journal.pgen.0010060

Basile B., Andreotti C., Rogers H., and Rouphael Y., 2023, The role of horticultural research in mitigating global food and economic crises, Italus Hortus, 30(1): 1-2.

https://doi.org/10.26353/j.itahort/2023.1.0102

Bate N., Dardick C., Maagd R., and Williams R., 2021, Opportunities and challenges applying gene editing to specialty crops, In Vitro Cellular & Developmental Biology-Plant, 57(4): 709-719. 

https://doi.org/10.1007/s11627-021-10208-x

Battenfield S., Sheridan J., Silva L., Miclaus K., Dreisigacker S., Wolfinger R., Peña R., Singh R., Jackson E., Fritz A., Guzmán C., and Poland J., 2018, Breeding-assisted genomics: Applying meta-GWAS for milling and baking quality in CIMMYT wheat breeding program, PLoS ONE, 13(11): e0204757.

https://doi.org/10.1371/journal.pone.0204757

PMid:30496187 PMCid:PMC6264898

Cirillo E., Kutmon M., Hernández M., Hooimeijer T., Adriaens M., Eijssen L., Parnell L., Coort S., and Evelo C., 2018, From SNPs to pathways: Biological interpretation of type 2 diabetes (T2DM) genome wide association study (GWAS) results, PLoS ONE, 13(4): e0193515.

https://doi.org/10.1371/journal.pone.0193515

PMid:29617380 PMCid:PMC5884486

Coser S., Reddy R., Zhang J., Mueller D., Mengistu A., Wise K., Allen T., Singh A., and Singh A., 2017, Genetic architecture of charcoal rot (Macrophomina phaseolina) resistance in soybean revealed using a diverse panel, Frontiers in Plant Science, 8: 1626.

https://doi.org/10.3389/fpls.2017.01626

PMid:28983305 PMCid:PMC5613161

Du H., Raman H., Kawasaki A., Perera G., Diffey S., Snowdon R., Raman R., and Ryan P., 2022, A genome-wide association study (GWAS) identifies multiple loci linked with the natural variation for Al3+ resistance in Brassica napus, Functional Plant Biology, 49(10): 845-860.

https://doi.org/10.1071/FP22073

PMid:35753342

Fang C., and Luo J., 2018, Metabolic GWAS-based dissection of genetic bases underlying the diversity of plant metabolism, The Plant Journal, 97(1): 91-100.

https://doi.org/10.1111/tpj.14097

PMid:30231195

Fikere M., Fikere M., Barbulescu D., Malmberg M., Spangenberg G., Cogan N., and Daetwyler H., 2020, Meta-analysis of GWAS in canola blackleg (Leptosphaeria maculans) disease traits demonstrates increased power from imputed whole-genome sequence, Scientific Reports, 10(1): 14300.

https://doi.org/10.1038/s41598-020-71274-6

PMid:32868838 PMCid:PMC7459325

Geshnizjani N., Snoek B., Willems L., Rienstra J., Nijveen H., Hilhorst H., and Ligterink W., 2020, Detection of QTLs for genotype× environment interactions in tomato seeds and seedlings, Plant, cell & environment, 43(8), 1973-1988.

https://doi.org/10.1111/pce.13788

PMid:32419153 PMCid:PMC7496158

Guo K., Chen T., Zhang P., Liu Y., Che Z., Shahinnia F., and Yang D., 2023, Meta‐QTL analysis and in‐silico transcriptome assessment for controlling chlorophyll traits in common wheat, The Plant Genome, 16(1): e20294.

https://doi.org/10.1002/tpg2.20294

PMid:36636827

Harish A., Ramesh Kumar A., Manivannan S., and Senthil Kumar S., 2023, An outlook on GWAS with a special focus on solanaceous vegetable crops-A Review, International Journal of Plant & Soil Science, 35(20): 209-220.

https://doi.org/10.9734/ijpss/2023/v35i203800

Ishii T., and Araki M., 2017, A future scenario of the global regulatory landscape regarding genome-edited crops, GM crops & food, 8(1): 44-56.

https://doi.org/10.1080/21645698.2016.1261787

PMid:27960622 PMCid:PMC5592978

Iwata H., Minamikawa M.F., Kajiya-Kanegae H., Ishimori M., and Hayashi T., 2016, Genomics-assisted breeding in fruit trees. Breeding Science, 66(1): 100-115.

https://doi.org/10.1270/jsbbs.66.100

PMid:27069395 PMCid:PMC4780794

Kao P., Leung K., Chan L., Yip S., and Yap M., 2017, Pathway analysis of complex diseases for GWAS, extending to consider rare variants, multi-omics and interactions, Biochimica et Biophysica Acta (BBA)-General Subjects, 1861(2): 335-353.

https://doi.org/10.1016/j.bbagen.2016.11.030

PMid:27888147

Kiss T., Bányai J., Balla K., Mayer M., Berki Z., Horváth Á., Veisz O., Bedo Z., and Karsai I., 2019, Comparative study of the developmental traits and yield components of bread wheat under field conditions in several years of multi-sowing time experiments, Crop Science, 59(2), 591-604.

https://doi.org/10.2135/cropsci2018.09.0531

Li D., Dossa K., Zhang Y., Wei X., Wang L., Zhang Y., Liu A., Zhou R., and Zhang X., 2018, GWAS uncovers differential genetic bases for drought and salt tolerances in sesame at the germination stage, Genes, 9(2): 87.

https://doi.org/10.3390/genes9020087

PMid:29443881 PMCid:PMC5852583

Li M., Li X., Zhou Z., Wu P., Fang M., Pan X., Lin Q., Luo W., Wu G., and Li H., 2016, Reassessment of the Four Yield-related Genes Gn1a, DEP1, GS3, and IPA1 in Rice Using a CRISPR/Cas9 System, Frontiers in Plant Science, 7: 377.

https://doi.org/10.3389/fpls.2016.00377

Rodriguez M., Scintu A., Posadinu C., Xu Y., Nguyen C., Sun H., Bitocchi E., Bellucci E., Papa R., Fei, Z., Giovannoni J., Rau D., and Attene G., 2020, GWAS based on RNA-Seq SNPs and high-throughput phenotyping combined with climatic data highlights the reservoir of valuable genetic diversity in regional tomato landraces, Genes, 11(11): 1387.

https://doi.org/10.3390/genes11111387

PMid:33238469 PMCid:PMC7709041

Ruggieri V., Francese G., Sacco A., D’Alessandro A., Rigano M.M., Parisi M., Milone M., Cardi T., Mennella G., and Barone A., 2014, An association mapping approach to identify favourable alleles for tomato fruit quality breeding, BMC Plant Biology, 14: 1-15.

https://doi.org/10.1186/s12870-014-0337-9

PMid:25465385 PMCid:PMC4266912

Saini R., Nile S., and Park S., 2015, Carotenoids from fruits and vegetables: Chemistry, analysis, occurrence, bioavailability and biological activities, Food Research International, 76(3): 735-750.

https://doi.org/10.1016/j.foodres.2015.07.047

PMid:28455059

Samal K., and Rout G., 2018, Genetic improvement of vegetables using transgenic technology, In Genetic engineering of horticultural crops, pp. 193-224, Academic Press.

https://doi.org/10.1016/B978-0-12-810439-2.00010-6

Sardar A., 2023, Genetic amelioration of fruit and vegetable crops to increase biotic and abiotic stress resistance through CRISPR Genome Editing, Frontiers in Plant Science, 14: 1260102.

https://doi.org/10.3389/fpls.2023.1260102

PMid:37841604 PMCid:PMC10570431

Spindel J., Begum H., Akdemir D., Virk P., Collard B., Redoña E., Atlin G., Jannink J., and McCouch S., 2015, Genomic selection and association mapping in rice (Oryza sativa): effect of trait genetic architecture, training population composition, marker number and statistical model on accuracy of rice genomic selection in elite, tropical rice breeding lines. PLoS genetics, 11(2): e1004982.

https://doi.org/10.1371/journal.pgen.1004982

PMid:25689273 PMCid:PMC4334555

Tibbs Cortes L., Zhang Z., and Yu J., 2021, Status and prospects of genome‐wide association studies in plants, The plant genome, 14(1): e20077.

https://doi.org/10.1002/tpg2.20077

PMid:33442955

Tiwari J.K., Singh A.K., and Behera T.K., 2023, CRISPR/Cas genome editing in tomato improvement: Advances and applications, Frontiers in Plant Science, 14: 1121209.

https://doi.org/10.3389/fpls.2023.1121209

PMid:36909403 PMCid:PMC9995852

Tu Y., Fu L., Wang F., Wu D., Shen Q., and Zhang G., 2021, GWAS and transcriptomic integrating analysis reveals key salt-responding genes controlling Na+ content in barley roots, Plant Physiology and Biochemistry, 167: 596-606.

https://doi.org/10.1016/j.plaphy.2021.08.038

Wang X., Wang H., Liu S., Ferjani A., Li J., Yan J., Yang X., and Qin F., 2016, Genetic variation in ZmVPP1 contributes to drought tolerance in maize seedlings. Nature Genetics, 48(10): 1233-1241.

https://doi.org/10.1038/ng.3636

PMid:27526320

Yang M., Lu K., Zhao F., Xie W., Ramakrishna P., Wang G., Du Q., Liang L., Sun C., Zhao H., Zhang Z., Liu Z., Tian J., Huang X., Wang W., Dong H., Hu J., Ming L., Xing Y., Wang G., Xiao J., Salt D., and Lian X., 2018, Genome-wide association studies reveal the genetic basis of ionomic variation in rice, Plant Cell, 30(11): 2720-2740.

https://doi.org/10.1105/tpc.18.00375

PMid:30373760 PMCid:PMC6305983

Yoon S., Nguyen H., Yoo Y., Kim J., Baik B., Kim S., Kim J., Kim S., and Nam D., 2018, Efficient pathway enrichment and network analysis of GWAS summary data using GSA-SNP2, Nucleic Acids Research, 46(10): e60-e60.

https://doi.org/10.1093/nar/gky175

PMid:29562348 PMCid:PMC6007455

Yoosefzadeh-Najafabadi M., Torabi S., Tulpan D., Rajcan I., and Eskandari M., 2023, Application of SVR-Mediated GWAS for Identification of Durable Genetic Regions Associated with Soybean Seed Quality Traits, Plants, 12(14): 2659

https://doi.org/10.3390/plants12142659

Zhao Y., Yang X., Zhou G., and Zhang T., 2020, Engineering plant virus resistance: from RNA silencing to genome editing strategies. Plant Biotechnology Journal, 18(2): 328-336.

https://doi.org/10.1111/pbi.13278

PMid:31618513 PMCid:PMC6953188