Comparison of relative efficiency of genomic SSR and EST-SSR markers in estimating genetic diversity in sugarcane.

Twenty-five primer pairs developed from genomic simple sequence repeats (SSR) were compared with 25 expressed sequence tags (EST) SSRs to evaluate the efficiency of these two sets of primers using 59 sugarcane genetic stocks. The mean polymorphism information content (PIC) of genomic SSR was higher (0.72) compared to the PIC value recorded by EST-SSR marker (0.62). The relatively low level of polymorphism in EST-SSR markers may be due to the location of these markers in more conserved and expressed sequences compared to genomic sequences which are spread throughout the genome. Dendrogram based on the genomic SSR and EST-SSR marker data showed differences in grouping of genotypes. A total of 59 sugarcane accessions were grouped into 6 and 4 clusters using genomic SSR and EST-SSR, respectively. The highly efficient genomic SSR could subcluster the genotypes of some of the clusters formed by EST-SSR markers. The difference in dendrogram observed was probably due to the variation in number of markers produced by genomic SSR and EST-SSR and different portion of genome amplified by both the markers. The combined dendrogram (genomic SSR and EST-SSR) more clearly showed the genetic relationship among the sugarcane genotypes by forming four clusters. The mean genetic similarity (GS) value obtained using EST-SSR among 59 sugarcane accessions was 0.70, whereas the mean GS obtained using genomic SSR was 0.63. Although relatively lower level of polymorphism was displayed by the EST-SSR markers, genetic diversity shown by the EST-SSR was found to be promising as they were functional marker. High level of PIC and low genetic similarity values of genomic SSR may be more useful in DNA fingerprinting, selection of true hybrids, identification of variety specific markers and genetic diversity analysis. Identification of diverse parents based on cluster analysis can be effectively done with EST-SSR as the genetic similarity estimates are based on functional attributes related to morphological/agronomical traits.