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In silico expressed sequence tag analysis in identification of probable diabetic genes as virtual therapeutic targets.

ABSTRACT: The expressed sequence tags (ESTs) are major entities for gene discovery, molecular transcripts, and single nucleotide polymorphism (SNPs) analysis as well as functional annotation of putative gene products. In our quest for identification of novel diabetic genes as virtual targets for type II diabetes, we searched various publicly available databases and found 7 reported genes. The in silico EST analysis of these reported genes produced 6 consensus contigs which illustrated some good matches to a number of chromosomes of the human genome. Again the conceptual translation of these contigs produced 3 protein sequences. The functional and structural annotations of these proteins revealed some important features which may lead to the discovery of novel therapeutic targets for the treatment of diabetes.

SUBMITTER: Behera PM

PROVIDER: S-EPMC3582052 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

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In silico expressed sequence tag analysis in identification of probable diabetic genes as virtual therapeutic targets.

Behera Pabitra Mohan PM Behera Deepak Kumar DK Panda Aparajeya A Dixit Anshuman A Padhi Payodhar P

BioMed research international 20130211

The expressed sequence tags (ESTs) are major entities for gene discovery, molecular transcripts, and single nucleotide polymorphism (SNPs) analysis as well as functional annotation of putative gene products. In our quest for identification of novel diabetic genes as virtual targets for type II diabetes, we searched various publicly available databases and found 7 reported genes. The in silico EST analysis of these reported genes produced 6 consensus contigs which illustrated some good matches to ...[more]

PMID: 23509765

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Project description:BACKGROUND AND AIMS:Banana (Musa acuminata) is a crop contributing to global food security. Many varieties lack resistance to biotic stresses, due to sterility and narrow genetic background. The objective of this study was to develop an expressed sequence tag (EST) database of transcripts expressed during compatible and incompatible banana-Mycosphaerella fijiensis (Mf) interactions. Black leaf streak disease (BLSD), caused by Mf, is a destructive disease of banana. Microsatellite markers were developed as a resource for crop improvement. METHODOLOGY:cDNA libraries were constructed from in vitro-infected leaves from BLSD-resistant M. acuminata ssp. burmaniccoides Calcutta 4 (MAC4) and susceptible M. acuminata cv. Cavendish Grande Naine (MACV). Clones were 5'-end Sanger sequenced, ESTs assembled with TGICL and unigenes annotated using BLAST, Blast2GO and InterProScan. Mreps was used to screen for simple sequence repeats (SSRs), with markers evaluated for polymorphism using 20 diploid (AA) M. acuminata accessions contrasting in resistance to Mycosphaerella leaf spot diseases. PRINCIPAL RESULTS:A total of 9333 high-quality ESTs were obtained for MAC4 and 3964 for MACV, which assembled into 3995 unigenes. Of these, 2592 displayed homology to genes encoding proteins with known or putative function, and 266 to genes encoding proteins with unknown function. Gene ontology (GO) classification identified 543 GO terms, 2300 unigenes were assigned to EuKaryotic orthologous group categories and 312 mapped to Kyoto Encyclopedia of Genes and Genomes pathways. A total of 624 SSR loci were identified, with trinucleotide repeat motifs the most abundant in MAC4 (54.1 %) and MACV (57.6 %). Polymorphism across M. acuminata accessions was observed with 75 markers. Alleles per polymorphic locus ranged from 2 to 8, totalling 289. The polymorphism information content ranged from 0.08 to 0.81. CONCLUSIONS:This EST collection offers a resource for studying functional genes, including transcripts expressed in banana-Mf interactions. Markers are applicable for genetic mapping, diversity characterization and marker-assisted breeding.

Dataset Information

In silico expressed sequence tag analysis in identification of probable diabetic genes as virtual therapeutic targets.

Publications

In silico expressed sequence tag analysis in identification of probable diabetic genes as virtual therapeutic targets.

Similar Datasets

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