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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.

Project description:North American monarch butterflies (Danaus plexippus) undergo a spectacular fall migration. In contrast to summer butterflies, migrants are juvenile hormone (JH) deficient, which leads to reproductive diapause and increased longevity. Migrants also utilize time-compensated sun compass orientation to help them navigate to their overwintering grounds. Here, we describe a brain expressed sequence tag (EST) resource to identify genes involved in migratory behaviors. A brain EST library was constructed from summer and migrating butterflies. Of 9,484 unique sequences, 6068 had positive hits with the non-redundant protein database; the EST database likely represents approximately 52% of the gene-encoding potential of the monarch genome. The brain transcriptome was cataloged using Gene Ontology and compared to Drosophila. Monarch genes were well represented, including those implicated in behavior. Three genes involved in increased JH activity (allatotropin, juvenile hormone acid methyltransfersase, and takeout) were upregulated in summer butterflies, compared to migrants. The locomotion-relevant turtle gene was marginally upregulated in migrants, while the foraging and single-minded genes were not differentially regulated. Many of the genes important for the monarch circadian clock mechanism (involved in sun compass orientation) were in the EST resource, including the newly identified cryptochrome 2. The EST database also revealed a novel Na+/K+ ATPase allele predicted to be more resistant to the toxic effects of milkweed than that reported previously. Potential genetic markers were identified from 3,486 EST contigs and included 1599 double-hit single nucleotide polymorphisms (SNPs) and 98 microsatellite polymorphisms. These data provide a template of the brain transcriptome for the monarch butterfly. Our "snap-shot" analysis of the differential regulation of candidate genes between summer and migratory butterflies suggests that unbiased, comprehensive transcriptional profiling will inform the molecular basis of migration. The identified SNPs and microsatellite polymorphisms can be used as genetic markers to address questions of population and subspecies structure.

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

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

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