Dataset Information

Next-generation sequencing of the porcine skeletal muscle transcriptome for computational prediction of microRNA gene targets.

ABSTRACT: BACKGROUND: MicroRNA are a class of small RNAs that regulate gene expression by inhibiting translation of protein encoding transcripts through targeting of a microRNA-protein complex by base-pairing of the microRNA sequence to cognate recognition sequences in the 3' untranslated region (UTR) of the mRNA. Target identification for a given microRNA sequence is generally accomplished by informatics analysis of predicted mRNA sequences present in the genome or in databases of transcript sequence for the tissue of interest. However, gene models for porcine skeletal muscle transcripts in current databases, specifically complete sequence of the 3' UTR, are inadequate for this exercise. METHODOLOGY/PRINCIPAL FINDINGS: To provide data necessary to identify gene targets for microRNA in porcine skeletal muscle, normalized cDNA libraries were sequenced using Roche 454 GS-FLX pyrosequencing and de novo assembly of transcripts enriched in the 3' UTR was performed using the MIRA sequence assembly program. Over 725 million bases of sequence were generated, which assembled into 18,202 contigs. Sequence reads were mapped to a 3' UTR database containing porcine sequences. The 3' UTR that mapped to the database were examined to predict targets for previously identified microRNA that had been separately sequenced from the same porcine muscle sample used to generate the cDNA libraries. For genes with microRNA-targeted 3' UTR, KEGG pathways were computationally determined in order to identify potential functional effects of these microRNA-targeted transcripts. CONCLUSIONS: Through next-generation sequencing of transcripts expressed in skeletal muscle, mapping reads to a 3' UTR database, and prediction of microRNA target sites in the 3' UTR, our results identified genes expressed in porcine skeletal muscle and predicted the microRNA that target these genes. Additionally, identification of pathways regulated by these microRNA-targeted genes provides us with a set of genes that can be further evaluated for their potential role in skeletal muscle development and growth.

SUBMITTER: McDaneld TG

PROVIDER: S-EPMC3407067 | biostudies-other | 2012

REPOSITORIES: biostudies-other

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Next-generation sequencing of the porcine skeletal muscle transcriptome for computational prediction of microRNA gene targets.

McDaneld Tara G TG Smith Tim P L TP Harhay Gregory P GP Wiedmann Ralph T RT

PloS one 20120727 7

<h4>Background</h4>MicroRNA are a class of small RNAs that regulate gene expression by inhibiting translation of protein encoding transcripts through targeting of a microRNA-protein complex by base-pairing of the microRNA sequence to cognate recognition sequences in the 3' untranslated region (UTR) of the mRNA. Target identification for a given microRNA sequence is generally accomplished by informatics analysis of predicted mRNA sequences present in the genome or in databases of transcript seque ...[more]

PMID: 22848698

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Project description:BackgroundThe gilthead sea bream (Sparus aurata L.) occurs around the Mediterranean and along Eastern Atlantic coasts from Great Britain to Senegal. It is tolerant of a wide range of temperatures and salinities and is often found in brackish coastal lagoons and estuarine areas, particularly early in its life cycle. Gilthead sea bream are extensively cultivated in the Mediterranean with an annual production of 125,000 metric tonnes. Here we present a de novo assembly of the fast skeletal muscle transcriptome of gilthead sea bream using 454 reads and identify gene paralogues, splice variants and microsatellite repeats. An annotated transcriptome of the skeletal muscle will facilitate understanding of the genetic and molecular basis of traits linked to production in this economically important species.ResultsAround 2.7 million reads of mRNA sequence data were generated from the fast myotomal of adult fish (~2 kg) and juvenile fish (~0.09 kg) that had been either fed to satiation, fasted for 3-5d or transferred to low (11°C) or high (33°C) temperatures for 3-5d. Newbler v2.5 assembly resulted in 43,461 isotigs >100 bp. The number of sequences annotated by searching protein and gene ontology databases was 10,465. The average coverage of the annotated isotigs was x40 containing 5655 unique gene IDs and 785 full-length cDNAs coding for proteins containing 58-1536 amino acids. The v2.5 assembly was found to be of good quality based on validation using 200 full-length cDNAs from GenBank. Annotated isotigs from the reference transcriptome were attributable to 344 KEGG pathway maps. We identified 26 gene paralogues (20 of them teleost-specific) and 43 splice variants, of which 12 had functional domains missing that were likely to affect their biological function. Many key transcription factors, signaling molecules and structural proteins necessary for myogenesis and muscle growth have been identified. Physiological status affected the number of reads that mapped to isotigs, reflecting changes in gene expression between treatments.ConclusionsWe have produced a comprehensive fast skeletal muscle transcriptome for the gilthead sea bream, which will provide a resource for SNP discovery in genes with a large effect on production traits of commercial interest and for expression studies of growth and adaptation.

Project description:BACKGROUND:Next-Generation Sequencing (NGS) technology has exceptionally increased the ability to sequence DNA in a massively parallel and cost-effective manner. Nevertheless, NGS data analysis requires bioinformatics skills and computational resources well beyond the possibilities of many "wet biology" laboratories. Moreover, most of projects only require few sequencing cycles and standard tools or workflows to carry out suitable analyses for the identification and annotation of genes, transcripts and splice variants found in the biological samples under investigation. These projects can take benefits from the availability of easy to use systems to automatically analyse sequences and to mine data without the preventive need of strong bioinformatics background and hardware infrastructure. RESULTS:To address this issue we developed an automatic system targeted to the analysis of NGS data obtained from large-scale transcriptome studies. This system, we named NGS-Trex (NGS Transcriptome profile explorer) is available through a simple web interface http://www.ngs-trex.org and allows the user to upload raw sequences and easily obtain an accurate characterization of the transcriptome profile after the setting of few parameters required to tune the analysis procedure. The system is also able to assess differential expression at both gene and transcript level (i.e. splicing isoforms) by comparing the expression profile of different samples.By using simple query forms the user can obtain list of genes, transcripts, splice sites ranked and filtered according to several criteria. Data can be viewed as tables, text files or through a simple genome browser which helps the visual inspection of the data. CONCLUSIONS:NGS-Trex is a simple tool for RNA-Seq data analysis mainly targeted to "wet biology" researchers with limited bioinformatics skills. It offers simple data mining tools to explore transcriptome profiles of samples investigated taking advantage of NGS technologies.

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Dataset Information

Next-generation sequencing of the porcine skeletal muscle transcriptome for computational prediction of microRNA gene targets.

Publications

Next-generation sequencing of the porcine skeletal muscle transcriptome for computational prediction of microRNA gene targets.

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