Molecular Plant Breeding 2025, Vol.16, No.2, 125-132 http://genbreedpublisher.com/index.php/mpb 129 development of improved Chieh-Qua varieties with enhanced traits such as disease resistance and yield (Deulvot et al., 2010). The integration of SNP genotyping with other genomic tools, such as genome-wide association studies (GWAS) and genomic selection, can provide deeper insights into the genetic basis of complex traits in Chieh-Qua. This holistic approach can drive advancements in Chieh-Qua genomics and breeding. 7 Challenges in Assessing Genetic Diversity Using SNPs 7.1 Technical and methodological challenges Assessing genetic diversity using Single nucleotide polymorphisms (SNPs) presents several technical and methodological challenges. One primary issue is the selection of appropriate molecular markers. For instance, in the study of walnut germplasm, it was found that approximately 100 SNPs were needed to achieve similar clustering results to 13 SSRs in Principal Coordinate Analysis (PCoA) (Bernard et al., 2020). This indicates that the choice and number of SNPs are critical for accurate genetic diversity assessment. Additionally, the high-throughput nature of SNP genotyping, as demonstrated in pea germplasm studies, requires sophisticated technologies like the Illumina GoldenGate assay, which can genotype hundreds to thousands of SNPs in a single reaction (Deulvot et al., 2010). However, these technologies demand significant technical expertise and resources, which may not be readily available in all research settings. 7.2 Sample representativeness and collection limitations Another challenge lies in ensuring the representativeness of the samples and the limitations of the germplasm collections. Large germplasm collections, such as those of grapevine, often contain a high number of putative duplicates and extensive clonal relationships, which can complicate the assessment of genetic diversity (Emanuelli et al., 2013). Moreover, the uneven characterization of traits and unpredictable apportionment of allelic diversity among heterogeneous accessions, as seen in sorghum germplasm collections, further complicates the extraction of functional genetic diversity (Reeves et al., 2020). Ensuring that the samples are representative of the entire genetic diversity within a species is crucial for accurate assessments, yet it remains a significant challenge due to these inherent limitations. 7.3 Bioinformatic and computational constraints The analysis of SNP data also faces bioinformatic and computational constraints. The processing and interpretation of large-scale SNP data require advanced bioinformatic tools and computational power. For example, the extraction of functional genetic diversity from heterogeneous germplasm collections involves complex bioinformatic approaches, such as machine learning and keyword searches against the Gene Ontology, to identify relevant loci (Reeves et al., 2020). These methods demand substantial computational resources and expertise in bioinformatics, which can be a barrier for many researchers. Additionally, the integration of genotypic and phenotypic data, as performed in grape germplasm studies, requires sophisticated statistical analyses to ensure that the genetic core collections retain maximum genetic diversity while maintaining phenotypic variability (Emanuelli et al., 2013). These computational challenges highlight the need for robust bioinformatic infrastructure and expertise in the field of genetic diversity assessment using SNPs. 8 Future Directions for Genetic Diversity Studies in Chieh-Qua 8.1 Advances in genomic technologies The rapid advancement in genomic technologies, such as next-generation sequencing (NGS) and high-throughput genotyping platforms, offers unprecedented opportunities to explore genetic diversity in Chieh-Qua. These technologies enable the identification of single nucleotide polymorphisms (SNPs) across the genome, which can be used to fine-map traits of interest and identify candidate genes. For instance, the fine mapping of the gynoecy trait in Chieh-Qua has already identified a candidate gene, CqNET4 (Figure 1), which is regulated by a single recessive gene and is associated with a non-synonymous SNP (Wang et al., 2023). Utilizing these advanced genomic tools can significantly enhance our understanding of the genetic architecture of Chieh-Qua and facilitate the development of improved varieties.
RkJQdWJsaXNoZXIy MjQ4ODYzNA==