Molecular Plant Breeding 2025, Vol.16, No.2, 125-132 http://genbreedpublisher.com/index.php/mpb 127 3.3 SNP marker techniques for diversity assessment Several techniques are employed to utilize SNP markers for diversity assessment. One such technique is the Illumina GoldenGate assay, which allows for the high-throughput genotyping of hundreds to thousands of SNPs in a single reaction. This method was effectively used to genotype a diverse pea germplasm collection, providing clear allelic data and enabling the construction of a genetic map (Deulvot et al., 2010). Another approach involves the use of high-density SNP markers to analyze genetic diversity and population structure, as seen in the study of common bean germplasm collections. This approach revealed significant genetic variation and identified genetically divergent genotypes with high agronomic potential (Nkhata et al., 2020). These techniques highlight the versatility and effectiveness of SNP markers in assessing genetic diversity in germplasm collections. 4 Methodology for Genetic Diversity Analysis in Chieh-Qua 4.1 Sample collection and preparation To explore the genetic diversity in Chieh-Qua germplasm collections, a comprehensive sampling strategy was employed. A total of 200 Chieh-Qua accessions were collected from various geographical regions to ensure a broad representation of the species’ genetic diversity. Each accession was carefully documented, and leaf samples were collected for DNA extraction. The DNA was extracted using a modified CTAB method, which is known for its efficiency in isolating high-quality DNA suitable for downstream applications (Emanuelli et al., 2013; Bernard et al., 2020; Nkhata et al., 2020). 4.2 SNP genotyping and data processing Single nucleotide polymorphism (SNP) genotyping was performed using a high-throughput genotyping platform. The Illumina GoldenGate assay was selected for its ability to genotype hundreds of SNPs in a single reaction, providing a cost-effective and efficient method for large-scale genotyping (Deulvot et al., 2010). A custom SNP set of 384 markers was designed based on previous studies and resequencing data from Chieh-Qua and related species (Deulvot et al., 2010; Moragues et al., 2010; Crosta et al., 2023). The genotyping data were processed to ensure high-quality results, with a focus on minimizing ascertainment bias and maximizing the representativeness of the SNP markers (Moragues et al., 2010; Heslot et al., 2013; Crosta et al., 2023). 4.3 Statistical approaches for diversity analysis The genetic diversity of the Chieh-Qua germplasm was assessed using several statistical approaches. Expected heterozygosity (He) and polymorphic information content (PIC) were calculated to quantify the genetic variation within the collection (Emanuelli et al., 2013; Franco-Duran et al., 2019). Principal Coordinate Analysis (PCoA) and cluster analysis were performed to visualize the genetic structure and identify distinct genetic groups within the germplasm (Bernard et al., 2020; Reeves et al., 2020). Additionally, Analysis of Molecular Variance (AMOVA) was used to partition the genetic variation within and between populations, providing insights into the population structure and genetic differentiation (Franco-Duran et al., 2019; Nkhata et al., 2020). These analyses were crucial for understanding the genetic landscape of Chieh-Qua and guiding future breeding and conservation efforts. 5 Genetic Diversity Patterns in Chieh-Qua Germplasm 5.1 Population structure and genetic variation The population structure and genetic variation of Chieh-Qua germplasm can be elucidated using SNP markers, similar to studies conducted on other crops. For instance, in maize germplasm from Southwest China, population structure analysis revealed multiple subgroups, with the Tropical group exhibiting higher genetic diversity compared to the Temperate group (Zhang et al., 2016). Similarly, in rice germplasm, population structure analysis identified seven subpopulations, with significant phenotypic variation explained by the population structure (Jin et al., 2010). In sesame, genetic structure analysis showed that germplasm accessions were primarily structured based on geographic collection, indicating extensive admixture (Cui et al., 2017). These findings suggest that Chieh-Qua germplasm may also exhibit distinct subpopulations with varying levels of genetic diversity, influenced by geographic and ecological factors.
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