Uncovering association networks through an eQTL analysis involving human miRNAs and lincRNAs
Gene expression. miRNA. lincRNA. Association networks. Polymorphism.
Variations in the level of gene expression are among the main causes of phenotypic diversity in organisms, including the development of pathologies and response to drugs in humans. Non-coding RNAs (ncRNAs) play an important role in the complex mechanism of regulatory networks. Although not yet fully understood, two representatives of the ncRNAs emerge in recent researches as protagonists in the development of clinical conditions. They are the microRNAs (miRNAs) and the long intergenic non-coding RNAs (lincRNAs). Thus, the present work integrated public data to catalog the vast landscape of the regulatory effects of miRNAs and lincRNAs in the human genome. Through expression Quantitative Trait Loci (eQTL) analysis, variations that had a putative effect on gene expression were identified. Association networks were also created relating the eQTL analysis results to traits of clinical and/or pharmacological relevance. Through this, associations that may continue to arouse the interest of new studies involving the theme were revealed. Mental and coronary disorders, in addition to cancer, were the most evidenced traits in the study results.