Extrapolative microRNA precursor based SSR mining from tea EST database in respect to agronomic traits

Abstract

Tea (Camellia sinensis, (L.) Kuntze) is considered as most popular drink across the world and it is widely consumed beverage for its several health-benefit characteristics. These positive traits primarily rely on its regulatory networks of different metabolic pathways. Development of microsatellite markers from the conserved genomic regions are being worthwhile for reviewing the genetic diversity of closely related species or self-pollinated species. Although several SSR markers have been reported, in tea, the trait-specific Simple Sequence Repeat (SSR) markers, leading to be useful in marker assisted breeding technique, are yet to be identified. Micro RNAs are short, non-coding RNA molecules, involved in post transcriptional mode of gene regulation and thus effects on related phenotype. Present study deals with identification of the microsatellite motifs within the reported and predicted miRNA precursors that are effectively followed by designing of primers from SSR flanking regions in order to PCR validation. In addition to the earlier reports, two new miRNAs are predicting here from tea expressed tag sequence database. Furthermore, 18 SSR motifs are found to be in 13 of all 33 predicted miRNAs. Trinucleotide motifs are most abundant among all followed by dinucleotides. Since, miRNA based SSR markers are evidenced to have significant role on genetic fingerprinting study, these outcomes would pave the way in developing novel markers for tagging tea specific agronomic traits as well as substantiating non-conventional breeding program.