Cargando…
Computational prediction of disease microRNAs in domestic animals
BACKGROUND: The most important means of identifying diseases before symptoms appear is through the discovery of disease-associated biomarkers. Recently, microRNAs (miRNAs) have become highly useful biomarkers of infectious, genetic and metabolic diseases in human but they have not been well studied...
Autores principales: | , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2014
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4091757/ https://www.ncbi.nlm.nih.gov/pubmed/24970281 http://dx.doi.org/10.1186/1756-0500-7-403 |
_version_ | 1782480800884719616 |
---|---|
author | Buza, Teresia Arick, Mark Wang, Hui Peterson, Daniel G |
author_facet | Buza, Teresia Arick, Mark Wang, Hui Peterson, Daniel G |
author_sort | Buza, Teresia |
collection | PubMed |
description | BACKGROUND: The most important means of identifying diseases before symptoms appear is through the discovery of disease-associated biomarkers. Recently, microRNAs (miRNAs) have become highly useful biomarkers of infectious, genetic and metabolic diseases in human but they have not been well studied in domestic animals. It is probable that many of the animal homologs of human disease-associated miRNAs may be involved in domestic animal diseases. Here we describe a computational biology study in which human disease miRNAs were utilized to predict orthologous miRNAs in cow, chicken, pig, horse, and dog. RESULTS: We identified 287 human disease-associated miRNAs which had at least one 100% identical animal homolog. The 287 miRNAs were associated with 359 human diseases referenced in 2,863 Pubmed articles. Multiple sequence analysis indicated that over 60% of known horse mature miRNAs found perfect matches in human disease-associated miRNAs, followed by dog (50%). As expected, chicken had the least number of perfect matches (5%). Phylogenetic analysis of miRNA precursors indicated that 85% of human disease pre-miRNAs were highly conserved in animals, showing less than 5% nucleotide substitution rates over evolutionary time. As an example we demonstrated conservation of human hsa-miR-143-3p which is associated with type 2 diabetes and targets AKT1 gene which is highly conserved in pig, horse and dog. Functional analysis of AKT1 gene using Gene Ontology (GO) showed that it is involved in glucose homeostasis, positive regulation of glucose import, positive regulation of glycogen biosynthetic process, glucose transport and response to food. CONCLUSIONS: This data provides the animal and veterinary research community with a resource to assist in generating hypothesis-driven research for discovering animal disease-related miRNA from their datasets and expedite development of prophylactic and disease-treatment strategies and also influence research efforts to identify novel disease models in large animals. Integrated data is available for download at http://agbase.hpc.msstate.edu/cgi-bin/animal_mirna.cgi. |
format | Online Article Text |
id | pubmed-4091757 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-40917572014-07-11 Computational prediction of disease microRNAs in domestic animals Buza, Teresia Arick, Mark Wang, Hui Peterson, Daniel G BMC Res Notes Research Article BACKGROUND: The most important means of identifying diseases before symptoms appear is through the discovery of disease-associated biomarkers. Recently, microRNAs (miRNAs) have become highly useful biomarkers of infectious, genetic and metabolic diseases in human but they have not been well studied in domestic animals. It is probable that many of the animal homologs of human disease-associated miRNAs may be involved in domestic animal diseases. Here we describe a computational biology study in which human disease miRNAs were utilized to predict orthologous miRNAs in cow, chicken, pig, horse, and dog. RESULTS: We identified 287 human disease-associated miRNAs which had at least one 100% identical animal homolog. The 287 miRNAs were associated with 359 human diseases referenced in 2,863 Pubmed articles. Multiple sequence analysis indicated that over 60% of known horse mature miRNAs found perfect matches in human disease-associated miRNAs, followed by dog (50%). As expected, chicken had the least number of perfect matches (5%). Phylogenetic analysis of miRNA precursors indicated that 85% of human disease pre-miRNAs were highly conserved in animals, showing less than 5% nucleotide substitution rates over evolutionary time. As an example we demonstrated conservation of human hsa-miR-143-3p which is associated with type 2 diabetes and targets AKT1 gene which is highly conserved in pig, horse and dog. Functional analysis of AKT1 gene using Gene Ontology (GO) showed that it is involved in glucose homeostasis, positive regulation of glucose import, positive regulation of glycogen biosynthetic process, glucose transport and response to food. CONCLUSIONS: This data provides the animal and veterinary research community with a resource to assist in generating hypothesis-driven research for discovering animal disease-related miRNA from their datasets and expedite development of prophylactic and disease-treatment strategies and also influence research efforts to identify novel disease models in large animals. Integrated data is available for download at http://agbase.hpc.msstate.edu/cgi-bin/animal_mirna.cgi. BioMed Central 2014-06-27 /pmc/articles/PMC4091757/ /pubmed/24970281 http://dx.doi.org/10.1186/1756-0500-7-403 Text en Copyright © 2014 Buza et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/4.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Article Buza, Teresia Arick, Mark Wang, Hui Peterson, Daniel G Computational prediction of disease microRNAs in domestic animals |
title | Computational prediction of disease microRNAs in domestic animals |
title_full | Computational prediction of disease microRNAs in domestic animals |
title_fullStr | Computational prediction of disease microRNAs in domestic animals |
title_full_unstemmed | Computational prediction of disease microRNAs in domestic animals |
title_short | Computational prediction of disease microRNAs in domestic animals |
title_sort | computational prediction of disease micrornas in domestic animals |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4091757/ https://www.ncbi.nlm.nih.gov/pubmed/24970281 http://dx.doi.org/10.1186/1756-0500-7-403 |
work_keys_str_mv | AT buzateresia computationalpredictionofdiseasemicrornasindomesticanimals AT arickmark computationalpredictionofdiseasemicrornasindomesticanimals AT wanghui computationalpredictionofdiseasemicrornasindomesticanimals AT petersondanielg computationalpredictionofdiseasemicrornasindomesticanimals |