University of Illinois at Chicago
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Bioinformatic resources of microRNA sequences, gene targets, and genetic variation

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journal contribution
posted on 2012-06-27, 00:00 authored by Wenbo Mu, Wei Zhang
Variation in quantitative gene expression has been observed in natural populations and associated with various complex traits/phenotypes such as risks for common diseases and drug response. MicroRNAs (miRNAs), a family of small, non-coding RNA molecules, have been demonstrated to be an important class of gene regulators that mostly downregulate gene expression at the post-transcriptional level. A comprehensive and reliable catalogue of miRNAs and miRNA gene targets is critical to understanding the gene regulatory networks.Though experimental approaches have been used to identify many miRNAs and their gene targets, due to cost and efficiency, currently miRNA and target identification still largely relies on computational algorithms. We reviewed several widely used bioinformatic resources of miRNA sequences and gene targets that take advantage of the unique characteristics of miRNA–mRNA interactions, experimental validation, as well as the integration of sequence-based evidence and microarray expression data. Furthermore, given the importance of miRNAs in regulating gene expression, elucidating expression quantitative trait loci involved with miRSNPs or miR-polymorphisms will help improve our understanding of complex traits.We reviewed the available resources of miRNA genetic variation, and the current progress (e.g., the 1000 Genomes Project) in detailing the genetic variation in miRNA-related single nucleotide polymorphisms (SNPs).We also provided our perspectives of the potential impact of next-generation sequencing on the research of miRNAs, gene targets, and miRSNPs. These bioinformatic resources may help interpret experimental and association study results, thus enhancing our knowledge of the dynamic gene regulatory networks and the physiological pathways for complex traits/phenotypes. Prospectively, these bioinformatic resources of miRNAs will need to address the challenges raised by the application of next-generation sequencing in miRNA research.


Thiswork was supported, in part, by a grant fromthe NHGRI/NIH (R21HG006367).


Publisher Statement

Copyright: © 2012 Mu and Zhang. This is an open-access article distributed under the terms of the Creative Commons Attribution Non Commercial License, which permits non-commercial use, distribution, and reproduction in other forums, provided the original authors and source are credited. This Document is Protected by copyright and was first published by Frontiers. All rights reserved. it is reproduced with permission. doi: 10.3389/fgene.2012.00031


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