MusatransSSRDB is a web resource for exploring microsatellite markers (Simple Sequence repeat) specific transcribed regions of the Musa genome. It contains information on functional SSR markers for various banana cultivars of different genomic groups like AAA, AAB, ABB, BB. This database has been developed from the EST sequences available in the NCBI and transcriptome data available in National Research Centre for Banana – ICAR, Trichy. At NRCB, the transcriptome data was generated from the contrasting cultivarsfor resistance to various biotic (Mycosphaerellaeumusa,Pratylenchus.coffeae ) and abiotic (soil moisture deficit) stresses. Thus this database developed from these transcriptomedata provides information on putative function of the SSR containing genes, and their expression profiling under challenged and unchallenged conditions for various biotic and abiotic stresses apart from routine SSR details like forward and reverse primer sequences, product size and annealing temperature. This database alsoprovides information on in silicopolymorphic SSRs between the contrasting cultivars for each stress. Italso provide information on insilicopolymorphic SSRs specific to differentially expressed genes under challenged condition for each stress. This unique information is expected facilitate the banana breeder to select the SSR primers based on the specific objectives. Thus this database is a step forward in economizing cost, time, manpower and other resources.
MusatransSSRDB could be mined based on cultivars, repeat type (mono- to hexa-nucleotide),metabolic pathways,chromosomes,biotic and abiotic stresses, polymorphism at SSR level, differential expression levels for each stress. Integrated BLAST search enables one to search for existing SSR markers given a genomic sequence. Currently, the database contains48,298 SSRs and 2830 polymorphis SSRs and its differential expression profiles.
This provides information on their putative function, pattern of the repeat motif, primer sequences and their profile, product size, genomic locations, microsatelliterepeat type (mono- to hexa-nucleotide), copy number, microsatellite length and location of the SSR’s on the chromosome.
Transcriptome sequences are particularly attractive for marker development since they represent coding regions of the genome. Moreover, the frequency of microsatellites is significantly higher in the transcribed sequences than in genomic DNA. Transcriptome resources of different banana cultivars and ESTs available in the NCBI have been harnessed for mining of functional SSRs. Functional markers can lead to the development of gene-based maps, which helps in the identification of candidate genes and which could be used in marker assistedselection. The information pertaining to these functional markers will be a good source for the banana scientific community to develop trait specific markers especially for biotic and abiotic stresses, developing fingerprints, diversity and evolutionary studies.
Insilico polymorphism at SSR region
Transcriptome sequences covering SSR regions derived from contrasting cultivars for resistance to specific stress (M.eumusae, P.coffeae and drought )werecompared in silico to identify polymorphic SSRregions.This information is likely to increase the efficiency of marker development for biotic and abiotic stress resistance/tolerance.
Transcriptome sequences covering SSR regions of five banana cultivars were compared in silico to identify polymorphic regions. This can be utilized for theconstruction of high-density linkage maps, to identify the diverse parents at molecular level and to develop finger printing etc.
In silicopolymorhic SSR for differentially expressed genes
In silico polymorphic SSRs derivedfrom contrasting cultivars for resistance to each stress were compared in silico to identify the differentially expressed genes based on their FPKM value under challenged and unchallenged conditions for each stress. This will hasten the process for developing trait specific markers.