Use este identificador para citar ou linkar para este item: https://repositorio.ufrn.br/jspui/handle/123456789/26433
Título: Uncovering association networks through an eQTL analysis involving human miRNAs and lincRNAs
Autor(es): Branco, Paulo R.
Araújo, Gilderlanio S. de
Barrera, Júnior
Suarez-Kurtz, Guilherme
Souza, Sandro José de
Palavras-chave: genetic;human genome;long intergenic noncoding RNA;microRNA;non-coding RNA;eQTL
Data do documento: 9-Out-2018
Referência: BRANCO, P. R. et al. Uncovering association networks through an eQTL analysis involving human miRNAs and lincRNAs. Sci Rep., v. 8, p. 15050, out. 2018. doi: 10.1038/s41598-018-33420-z
Resumo: Non-coding RNAs (ncRNA) have an essential role in the complex landscape of human genetic regulatory networks. One area that is poorly explored is the effect of genetic variations on the interaction between ncRNA and their targets. By integrating a significant amount of public data, the present study cataloged the vast landscape of the regulatory effect of microRNAs (miRNA) and long intergenic noncoding RNAs (lincRNA) in the human genome. An expression quantitative trait loci (eQTL) analysis was used to identify genetic variants associated with miRNA and lincRNA and whose genotypes affect gene expression. Association networks were built for eQTL associated to traits of clinical and/or pharmacological relevance.
URI: https://repositorio.ufrn.br/jspui/handle/123456789/26433
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