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Next-Generation Sequencing of the Porcine Skeletal Muscle Transcriptome for Computational Prediction of MicroRNA Gene Targets
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...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2012
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3407067/ https://www.ncbi.nlm.nih.gov/pubmed/22848698 http://dx.doi.org/10.1371/journal.pone.0042039 |
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author | McDaneld, Tara G. Smith, Tim P. L. Harhay, Gregory P. Wiedmann, Ralph T. |
author_facet | McDaneld, Tara G. Smith, Tim P. L. Harhay, Gregory P. Wiedmann, Ralph T. |
author_sort | McDaneld, Tara G. |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-3407067 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-34070672012-07-30 Next-Generation Sequencing of the Porcine Skeletal Muscle Transcriptome for Computational Prediction of MicroRNA Gene Targets McDaneld, Tara G. Smith, Tim P. L. Harhay, Gregory P. Wiedmann, Ralph T. PLoS One Research Article 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. Public Library of Science 2012-07-27 /pmc/articles/PMC3407067/ /pubmed/22848698 http://dx.doi.org/10.1371/journal.pone.0042039 Text en https://creativecommons.org/publicdomain/zero/1.0/ This is an open-access article distributed under the terms of the Creative Commons Public Domain declaration, which stipulates that, once placed in the public domain, this work may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. |
spellingShingle | Research Article McDaneld, Tara G. Smith, Tim P. L. Harhay, Gregory P. Wiedmann, Ralph T. Next-Generation Sequencing of the Porcine Skeletal Muscle Transcriptome for Computational Prediction of MicroRNA Gene Targets |
title | Next-Generation Sequencing of the Porcine Skeletal Muscle Transcriptome for Computational Prediction of MicroRNA Gene Targets |
title_full | Next-Generation Sequencing of the Porcine Skeletal Muscle Transcriptome for Computational Prediction of MicroRNA Gene Targets |
title_fullStr | Next-Generation Sequencing of the Porcine Skeletal Muscle Transcriptome for Computational Prediction of MicroRNA Gene Targets |
title_full_unstemmed | Next-Generation Sequencing of the Porcine Skeletal Muscle Transcriptome for Computational Prediction of MicroRNA Gene Targets |
title_short | Next-Generation Sequencing of the Porcine Skeletal Muscle Transcriptome for Computational Prediction of MicroRNA Gene Targets |
title_sort | next-generation sequencing of the porcine skeletal muscle transcriptome for computational prediction of microrna gene targets |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3407067/ https://www.ncbi.nlm.nih.gov/pubmed/22848698 http://dx.doi.org/10.1371/journal.pone.0042039 |
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