MusatransSSRDB (a transcriptome derived SSR database) - An advanced tool for banana improvement

Area of Science:

• Plant Genomics
• Molecular Breeding
• Bioinformatics

Background:

• Limited transcriptome data hinders accelerated molecular breeding in Musa species.
• Understanding gene expression under stress is crucial for crop improvement.

Purpose of the Study:

• To develop a comprehensive database (MusatransSSRDB) for Musa transcriptome data.
• To identify simple sequence repeats (SSRs) and analyze gene expression under various stress conditions.
• To facilitate marker-assisted selection for banana breeding.

Main Methods:

• Illumina Hiseq technology for transcriptome sequencing.
• Bioinformatic analyses including GO annotation, KEGG pathway analysis, and SSR/SNP detection.
• Development of a web-accessible database (MusatransSSRDB) using HTML, Java, PHP, and MySQL.

Main Results:

• Generated an average of 34.72 million reads per library, assembled into ~47,629 contigs.
• Identified ~5,466 simple sequence repeats (SSRs) per library and detected SNPs.
• MusatransSSRDB contains 32,800 SSRs with functional and expression data, including 2,830 polymorphic SSRs.

Conclusions:

• MusatransSSRDB provides valuable information for banana breeders to select SSR primers for specific breeding objectives.
• The database supports the genetic dissection and breeding for complex traits in banana.
• This resource economizes resources in banana research and development.