Plant Gene and Traits 2024, Vol.15, No.4, 184-194 http://genbreedpublisher.com/index.php/pgt 186 genetic, physical, and sequence-based maps. SSRs are also known for their high transferability across species, as demonstrated in a study where SSR loci exhibited broad potential transferability among various angiosperms (Zhong et al., 2022). Figure 1 Genomic landscape of Dof genes among tenOryza genomes (Adopted from Tabassum et al., 2022) Image caption: Circular diagram from outside to inside are gene names and locations on individual species-specific colored chromosomal bands, density of high confidence protein-encoding genes (count/Mb; min=65, max=133), density of Dof genes (count/Mb; min=0.0, max=0.17) and links indicating duplicated genes among ten rice species (Adopted from Tabassum et al., 2022) 3.2 Single nucleotide polymorphisms (SNPs) Single nucleotide polymorphisms (SNPs) are the most abundant type of genetic variation in genomes. They involve a single base pair change and are highly stable, making them ideal for high-resolution genetic mapping and association studies. SNPs have been used in Oryza genomics to identify genetic variations associated with important agronomic traits (Duhan et al., 2023). The high density and widespread distribution of SNPs across the rice genome allow for detailed genetic analysis and the development of SNP-based markers for marker-assisted selection. Although the provided data does not include specific studies on SNPs in Oryza, their general utility in plant genomics is well-documented, and they are often used in conjunction with other markers like SSRs to provide a comprehensive understanding of genetic diversity and structure. 3.5 Comparative analysis of these markers in the context of Oryza When comparing SSRs and SNPs in the context of Oryza genomics, several key differences and complementary strengths emerge. SSRs are highly polymorphic and multiallelic, which makes them particularly useful for studies requiring high levels of genetic diversity detection, such as population genetics and phylogenetic studies. They are also relatively easy to develop and analyze, with a high degree of reproducibility and codominant inheritance (Kalia et al., 2011). However, SSRs can be less abundant than SNPs and may require more effort to develop species-specific markers. On the other hand, SNPs are more abundant and evenly distributed across the genome, providing higher resolution for genetic mapping and association studies. They are also more stable than SSRs, which can be advantageous for certain types of genetic analysis. The development of high-throughput SNP genotyping technologies has further enhanced their utility in large-scale genetic studies (Kumar et al., 2020).
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