In Silico Mining of EST-SSRs in Jatropha curcas L. towards Assessing Genetic Polymorphism and Marker Development for Selection of High Oil Yielding Clones
Neeraj Jain, Ganesh B. Patil, Poonam Bhargava, Rajani S. Nadgauda
In recent years, Jatropha curcas L. has gained popularity as a potential biodiesel plant. The varying oil content, reported between accessions belonging to different agroclimatic zones, has necessitated the assessment of the existing genetic variability to generate reliable molecular markers for selection of high oil yielding variety. EST derived SSR markers are more useful than genomic markers as they represent the transcriptome, thus, directly linked to functional genes. The present report describes the in silico mining of the microsatellites (SSRs) using J. curcas ESTs from various tissues viz. embryo, root, leaf and seed available in the public domain of NCBI. A total of 13,513 ESTs were downloaded. From these ESTs, 7552 unigenes were obtained and 395 SSRs were generated from 377 SSR-ESTs. These EST-SSRs can be used as potential microsatellite markers for diversity analysis, MAS etc. Since the Jatropha genes carrying SSRs have been identified in this study, thus, EST-SSRs directly linked to genes will be useful for developing trait linked markers.