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Prediction and characterization of microRNAs from eleven fish species by computational methods

MicroRNAs (miRNAs) are a family of single-stranded RNA molecules about 22 nt in length, which can regulate protein-coding gene expression in various organisms by post-transcriptional repression of messenger. In this research, the potential miRNAs and their target genes were analyzed and predicted by...

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Detalles Bibliográficos
Autores principales: Huang, Yong, Zou, Quan, Ren, Hong Tao, Sun, Xi Hong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4486735/
https://www.ncbi.nlm.nih.gov/pubmed/26150741
http://dx.doi.org/10.1016/j.sjbs.2014.10.005
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author Huang, Yong
Zou, Quan
Ren, Hong Tao
Sun, Xi Hong
author_facet Huang, Yong
Zou, Quan
Ren, Hong Tao
Sun, Xi Hong
author_sort Huang, Yong
collection PubMed
description MicroRNAs (miRNAs) are a family of single-stranded RNA molecules about 22 nt in length, which can regulate protein-coding gene expression in various organisms by post-transcriptional repression of messenger. In this research, the potential miRNAs and their target genes were analyzed and predicted by computational methods from the EST and GSS databases of eleven fish species, 43 potential miRNAs were identified, they belong to 38 miRNA families, some miRNAs are highly conserved in animal kingdom, the predicted target genes are involved in development, signal transduction, response to environmental stress and pathogen invasion. Taken together, our data suggest that there are a plentiful of miRNAs in these eleven fish species, these miRNAs may play some important roles by regulating their target genes, and the data provide important information for further functional studies.
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spelling pubmed-44867352015-07-06 Prediction and characterization of microRNAs from eleven fish species by computational methods Huang, Yong Zou, Quan Ren, Hong Tao Sun, Xi Hong Saudi J Biol Sci Original Article MicroRNAs (miRNAs) are a family of single-stranded RNA molecules about 22 nt in length, which can regulate protein-coding gene expression in various organisms by post-transcriptional repression of messenger. In this research, the potential miRNAs and their target genes were analyzed and predicted by computational methods from the EST and GSS databases of eleven fish species, 43 potential miRNAs were identified, they belong to 38 miRNA families, some miRNAs are highly conserved in animal kingdom, the predicted target genes are involved in development, signal transduction, response to environmental stress and pathogen invasion. Taken together, our data suggest that there are a plentiful of miRNAs in these eleven fish species, these miRNAs may play some important roles by regulating their target genes, and the data provide important information for further functional studies. Elsevier 2015-07 2014-10-23 /pmc/articles/PMC4486735/ /pubmed/26150741 http://dx.doi.org/10.1016/j.sjbs.2014.10.005 Text en © 2014 The Authors http://creativecommons.org/licenses/by-nc-nd/3.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/).
spellingShingle Original Article
Huang, Yong
Zou, Quan
Ren, Hong Tao
Sun, Xi Hong
Prediction and characterization of microRNAs from eleven fish species by computational methods
title Prediction and characterization of microRNAs from eleven fish species by computational methods
title_full Prediction and characterization of microRNAs from eleven fish species by computational methods
title_fullStr Prediction and characterization of microRNAs from eleven fish species by computational methods
title_full_unstemmed Prediction and characterization of microRNAs from eleven fish species by computational methods
title_short Prediction and characterization of microRNAs from eleven fish species by computational methods
title_sort prediction and characterization of micrornas from eleven fish species by computational methods
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4486735/
https://www.ncbi.nlm.nih.gov/pubmed/26150741
http://dx.doi.org/10.1016/j.sjbs.2014.10.005
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