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Title

Computational analysis of transcriptome of Indian major carp, Labeo rohita (Hamilton-Buchanan, 1822) for functional annotation

 

Authors

Naresh Sahebrao Nagpure, Iliyas Rashid, Ajey Kumar Pathak*, Mahender Singh, Shri Prakash Singh & Uttam Kumar Sarkar

 

Affiliation

National Bureau of Fish Genetic Resources, Canal Ring Road, P.O.- Dilkusha, Lucknow-226002, India.

 

Email

pathakajey@rediffmail.com; *Corresponding author

 

Article Type

Hypothesis

 

Date

Received September 21, 2012; Accepted October 01, 2012; Published October 31, 2012

 

Abstract

A total of 1671 ESTs of Labeo rohita were retrieved from dbEST database and analysed for functional annotation using various computational approaches. The result indicated 1387 non-redundant (184 contigs and 1203 singletons) putative transcripts with an average length of 542 bp. These 1387 transcript sequences were matched with Refseq_RNA, UniGene and Swiss-Prot on high threshold cut-off for functional annotation along with help of gene ontology and SSRs markers. We developed extensive Perl programming based modules for processing all alignment files, comparing and extracting common hits from all files on a threshold, evaluating statistics for alignment results and assigning gene ontology terms. In this study, 92 putative transcripts predicted as orthologous genes and among those, 44 putative transcripts were annotated with gene ontology terms. The annotated orthologous gene of our result associated with some very important proteins of L. rohita involved in biotic and abiotic stresses and glucose metabolism of spermatogenic cells etc. The unidentified transcripts, if found important in expression profiling can be vital resource after re-sequencing. The predicted genes can further be used for enhancing productivity and controlling disease of L. rohita.

 

Keywords

Expressed sequences tag, Functional annotation, Gene, Labeo rohita, Putative transcripts, Transcriptomen

 

Citation

Nagpure et al. Bioinformation 8(21): 1005-1011 (2012)
 

Edited by

P Kangueane

 

ISSN

0973-2063

 

Publisher

Biomedical Informatics

 

License

This is an Open Access article which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. This is distributed under the terms of the Creative Commons Attribution License.