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微小RNA模块倾向于结合弱的和非常规的靶位点。

MicroRNA modules prefer to bind weak and unconventional target sites.

作者信息

Ding Jun, Li Xiaoman, Hu Haiyan

机构信息

Department of Electrical Engineering and Computer Science and Burnett School of Biomedical Science, College of Medicine, University of Central Florida, Orlando, FL 32816, USA.

出版信息

Bioinformatics. 2015 May 1;31(9):1366-74. doi: 10.1093/bioinformatics/btu833. Epub 2014 Dec 18.

DOI:10.1093/bioinformatics/btu833
PMID:25527098
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC4410656/
Abstract

MOTIVATION

MicroRNAs (miRNAs) play critical roles in gene regulation. Although it is well known that multiple miRNAs may work as miRNA modules to synergistically regulate common target mRNAs, the understanding of miRNA modules is still in its infancy.

RESULTS

We employed the recently generated high throughput experimental data to study miRNA modules. We predicted 181 miRNA modules and 306 potential miRNA modules. We observed that the target sites of these predicted modules were in general weaker compared with those not bound by miRNA modules. We also discovered that miRNAs in predicted modules preferred to bind unconventional target sites rather than canonical sites. Surprisingly, contrary to a previous study, we found that most adjacent miRNA target sites from the same miRNA modules were not within the range of 10-130 nucleotides. Interestingly, the distance of target sites bound by miRNAs in the same modules was shorter when miRNA modules bound unconventional instead of canonical sites. Our study shed new light on miRNA binding and miRNA target sites, which will likely advance our understanding of miRNA regulation.

AVAILABILITY AND IMPLEMENTATION

The software miRModule can be freely downloaded at http://hulab.ucf.edu/research/projects/miRNA/miRModule.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

CONTACT

haihu@cs.ucf.edu or xiaoman@mail.ucf.edu.

摘要

动机

微小RNA（miRNA）在基因调控中发挥着关键作用。尽管众所周知多个miRNA可能作为miRNA模块协同调控共同的靶标mRNA，但对miRNA模块的理解仍处于起步阶段。

结果

我们利用最近生成的高通量实验数据来研究miRNA模块。我们预测了181个miRNA模块和306个潜在的miRNA模块。我们观察到，与未被miRNA模块结合的靶位点相比，这些预测模块的靶位点总体上较弱。我们还发现，预测模块中的miRNA更倾向于结合非常规靶位点而非典型位点。令人惊讶的是，与之前的一项研究相反，我们发现来自同一miRNA模块的大多数相邻miRNA靶位点不在10 - 130个核苷酸的范围内。有趣的是，当miRNA模块结合非常规位点而非典型位点时，同一模块中miRNA结合的靶位点之间的距离更短。我们的研究为miRNA结合和miRNA靶位点提供了新的见解，这可能会增进我们对miRNA调控的理解。

可用性与实现方式

软件miRModule可从http://hulab.ucf.edu/research/projects/miRNA/miRModule免费下载。

补充信息

补充数据可在《生物信息学》在线获取。

联系方式

haihu@cs.ucf.edu或xiaoman@mail.ucf.edu。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c71d/4410656/2b175b2197ba/btu833f3p.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c71d/4410656/90b7c9707736/btu833f1p.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c71d/4410656/9774ada5c4d0/btu833f2p.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c71d/4410656/2b175b2197ba/btu833f3p.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c71d/4410656/90b7c9707736/btu833f1p.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c71d/4410656/9774ada5c4d0/btu833f2p.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c71d/4410656/2b175b2197ba/btu833f3p.jpg

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3
SIOMICS: a novel approach for systematic identification of motifs in ChIP-seq data.
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4
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Genomics. 2011 Dec;98(6):445-52. doi: 10.1016/j.ygeno.2011.09.004. Epub 2011 Oct 2.
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