Document Type : Review
Authors
1
Department of Plant Production, Engineering, and Genetics, Faculty of Agriculture, Shahid Chamran University of Ahvaz, Ahvaz, Iran
2
Department of Plant Production Engineering and Genetics, Faculty of Agriculture, Shahid Chamran University of Ahvaz, Ahvaz, Iran
Abstract
Genetic diversity is a crucial component of biodiversity, essential for preserving gene banks and enriching plant genetic resources. One way to assess genetic diversity is using band patterns (0 and 1) produced by PCR-based DNA markers (such as RAPD, SSR, ISSR, AFLP, SCoT etc.). After achieving reproducibility, the bands are selected, scored, and analyzed. The data is analyzed using multivariate statistical methods, including cluster and principal coordinate analysis. Genetic similarity or dissimilarity coefficients are used based on 0 and 1 data (for dominant and codominant markers), and allelic frequency coefficients (for codominant markers). Some algorithms such as UPGMA and Ward are employed to group the studied individuals and investigate their genetic relationships. Quantifying polymorphism and assessing genetic diversity within and between populations will depend on the type of marker (dominant and codominant) and reproduction mode. Parameters such as polymorphic information content (PIC), resolving power (Rp), marker index (MI), polymorphic loci/marker ratio, heterozygosity (H)/gene diversity, allelic diversity (A), the effective number of alleles (Ae), Shannon's index (I), Wright’s F statistic (FIT, FST, FIS), Gst and analysis of molecular variance (AMOVA) are evaluated. Software tools (NTSYSpc, R, DARwin, PAST, Excel, PowerMarker, POPGENE, and GenAlEx) can assist with grouping and estimating genetic diversity.
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