Submitted to: PLoS One
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: July 2, 2012
Publication Date: July 27, 2012
Citation: McDaneld, T.G., Smith, T.P.L., Harhay, G.P., and Wiedmann, R.T. 2012. Next-generation sequencing of the porcine skeletal muscle transcriptome for computational prediction of microRNA gene targets. PLoS One. 7(7):e42039. doi:10.1371/journal.pone.0042039. Interpretive Summary: MicroRNA (miRNA) are small RNA sequences that regulate abundance of gene transcripts and are involved in developmental processes of the animal. To evaluate the role of miRNA in skeletal muscle of swine, the transcriptome of genes expressed in skeletal muscle was sequenced using Roche 454 GS-FLX pyrosequencing and reconstructed using the MIRA genome assembler. Over 725 million bases of sequence were generated, which assembled into 18,202 sequence contigs that were compared to mRNA and protein databases. Sequence data was also mapped to a 3’ untranslated region (UTR) database. The 3’ UTR of the gene harbors the recognition sequence for miRNA, and therefore by mapping our sequence data to the 3’ UTR database we were able to identify genes from the reconstructed transcriptome that were miRNA-targeted genes. Overall, data from the current experiment have identified a set of miRNA-targeted genes that can be evaluated further for regulation of skeletal muscle growth and development.
Technical Abstract: MicroRNA are a class of small RNAs that regulate gene expression by inhibiting translation of protein encoding transcripts. Inhibition is exerted 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 are inadequate for this exercise. 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 a 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 that were compared to RefSeq mRNA and protein databases. Sequence reads were also mapped to a 3’ UTR database containing porcine sequences. The identified 3’ UTR were then 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. Through de novo reconstruction of transcripts expressed in skeletal muscle and mapping sequence reads to a 3’ UTR database, our results determine the percentage of genes expressed and identify genes targeted by highly expressed microRNA in porcine skeletal muscle. Additionally, identification of pathways regulated by these microRNA-targeted genes provides us with a set of genes that have a potential role in skeletal muscle development and growth.