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

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2019
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Abstract
Availability of transcriptome datasets for use in accelerated molecular-based breeding in species is limited. Illumina Hiseq technology was employed to determine differential gene expression between the contrasting cultivars for three different stresses ( leaf spot -, root lesion nematode - and moisture deficit stress) under challenged and unchallenged conditions. An average of 34.72 million of reads was assembled into ~47629 contigs, and ~5,466 simple sequence repeats (SSR) from each library were identified. GO annotation and KEGG pathway analysis were carried for all the transcripts and the SSR, SNPs were also detected. Based on this information, a MusatransSSRDB has been developed. Currently, the database consists of 32,800 SSRs with the unique information like putative function of the SSR-containing genes and their metabolic pathway and expression profiling under various stress conditions. This database provides information on polymorphic SSRs (2830 SSRs) between the contrasting cultivars for each stress and within stress. Information on polymorphic SSRs specific to differentially expressed genes under challenged condition for each stress can also be accessed. This database facilitates the retrieval of results by navigating the tabs for cultivars, stress and polymorphism. This database was developed using HTML, Java and PHP; datasets are stored in MySQL database and accessible in the public domain . This unique information facilitates the banana breeder to select the SSR primers based on specific objectives. MusatransSSRDB along with other genomics databases will facilitate the genetic dissection and breeding for complex traits in banana. Thus, this database is a step forward in economizing cost, time, manpower and other resources. Keywords.
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backiyarani2019musatransssrdbjournal Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Backiyarani, Suthanthiram;Chandrasekar, Arumugam;Uma, Subbaraya;Saraswathi, Marimuthu Somasundaram;
Journal journal of biosciences
Year 2019
DOI
4
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