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Transcriptome analysis of banana (Musa balbisiana) basedon next-generation sequencing technology
Author(s) -
S. Backiyarani,
S. Uma,
M. S. Saraswathi,
Asoor Santhanam SARAVANAKUMAR,
A. Chandrasekar
Publication year - 2015
Publication title -
turkish journal of agriculture and forestry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.624
H-Index - 43
eISSN - 1303-6173
pISSN - 1300-011X
DOI - 10.3906/tar-1406-171
Subject(s) - biology , musa acuminata , genome , transcriptome , gene , genetics , sequence assembly , dna sequencing , gene annotation , reference genome , expressed sequence tag , computational biology , rna seq , gene expression
Banana (Musa spp.) is an important tropical fruit with high commercial potential. Musa balbisiana (B genome) is a progenitor of one of the most cultivated banana species and exhibits unique traits, including resistance or tolerance to many biotic and abiotic stresses. RNA sequencing of the Musa B genome would provide a vast array of transcriptomic information that could lead to the development of trait-specific markers and the discovery of new genes and regulatory sequences involved in resistance mechanisms. Thus, transcriptome sequencing was performed in Musa B genome accession Attikol using the Ion Torrent platform. This led to the generation of about 4.5 million paired-end reads, which were assembled using the MIRA assembler. The assembly produced 82,413 unique transcripts with a mean length of approximately 113 bp. The sequence similarity search against the Swiss-Prot database resulted in the identification of 35,783 unique transcripts (62.18%). Out of these, 193,826 gene ontology terms were assigned to unique transcripts. Functional annotation against PlantCYC pathway database identified 20,696 unique transcripts, which were mapped to 455 pathways. About 4780 simple sequence repeats (SSRs) were obtained from 82,413 unique transcripts. Primers could be designed for only 2628 SSRs, out of which 30 primers were randomly selected from defense-related genes to confirm their efficiency. This information will make the improvement of banana cultivars easier by facilitating the selection of resistance genes as well as the development of trait-specific markers.

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