Question: Prediction Of Mirnas That Affect Tissue-Specific Gene Expression
1
gravatar for Jonathan Hsu
7.6 years ago by
Jonathan Hsu60
Jonathan Hsu60 wrote:

There are quite a large number of predicted miRNA binding sites in the 3'UTR of gene. However the number of actual functional miRNA may be very little. I wanna know if there are some computational tools to predict the functional miRNA that affect the tissue-specific gene expression?

gene prediction mirna • 2.8k views
ADD COMMENTlink modified 7.0 years ago by Madhan220 • written 7.6 years ago by Jonathan Hsu60
1
gravatar for Madhan
7.6 years ago by
Madhan220
United States
Madhan220 wrote:

You may try try the following tools for Pathway level analysis of miRNA and Gene association especially when you just have a list of miRNAs or Genes rather than Microarray expression fiels: 1. http://diana.cslab.ece.ntua.gr/pathways/ 2. http://sysbio.ustc.edu.cn/software/mirAct/ 3. http://www.proto.cs.huji.ac.il/mirror/

ADD COMMENTlink written 7.6 years ago by Madhan220

The second tool you mentioned still need the expression profile as the validation.The pathway level analysis however just get the enriched pathway for the predicted target genes. And I don't this method can provide a preciser prediction result for the miRNA-mRNA interactions.

ADD REPLYlink written 7.6 years ago by Jonathan Hsu60
1
gravatar for Larry_Parnell
7.6 years ago by
Larry_Parnell16k
Boston, MA USA
Larry_Parnell16k wrote:

It is important that you use only validated miRNA-mRNA interactions. There are databases of miRNA-mRNA interactions where the distinction between validated and predicted is made. So, use miRanda or Pictair or some other favorite miRNA database - or a combination of these - and select the validated interactions. Then, go onto Madhan's suggestion for teh pathway analysis.

Expression data. There is still not so much of these data for microRNAs as many would wish. An important paper has just been released on expression profiles of 863 microRNAs from 454 analyzed blood samples from individuals with lung cancer, prostate cancer, pancreatic ductal adenocarcinoma, melanoma, ovarian cancer, gastric tumors, Wilms tumor, pancreatic tumors, multiple sclerosis, chronic obstructive pulmonary disease (COPD), sarcoidosis, periodontitis, pancreatitis or acute myocardial infarction and from unaffected individuals (controls) (Keller, Meese et al 2011 Nature Methods, in press). While most would advocate that the microRNA and its target mRNA be co-expressed by cell type and by time, that may not necessarily be required. The HDL-cholesterol particle has been shown to transport microRNAs (Vickers, Remaley et al 2011 Nature Cell Biol 13:423-433) to it target tissues (those that take up HDL-C) and this may be a mechanism by which a microRNA can act at a distance, like a hormone.

Of course, you can scan GEO (NCBI) or ArrayExpress for microRNA expression sets - the 863 microRNAs mentioned above are in GEO. But it may be difficult to acquire from a public repository data taken under the precise conditions your research requires.

ADD COMMENTlink modified 7.6 years ago • written 7.6 years ago by Larry_Parnell16k

The co-expression may be the powerful proof of the interaction, however, the microRNA expression profiles among species are quite scarce. Maybe the pathway analysis suggested by Madhan can help.

ADD REPLYlink written 7.6 years ago by Jonathan Hsu60

The co-expression may be the powerful proof of the interaction, however, the microRNA expression profiles among species are quite scarce. The pathway level analysis mentioned by Madhan don't help to improve the precision of prediction in my view.

ADD REPLYlink written 7.6 years ago by Jonathan Hsu60

Which species are you studying?

ADD REPLYlink written 7.6 years ago by Larry_Parnell16k
0
gravatar for Madhan
7.6 years ago by
Madhan220
United States
Madhan220 wrote:

As Larry Pointed you should first try the databases that gives Validated Target information. I found miRecords and TarBase as two largest source for the same.

But unfortunately, the databases are largely incomplete. So you have to use the well known target prediction algorithms to select the best possible combinations. A recent nature review (Widespread changes in protein synthesis induced by microRNAs. Nature, 2008. 455(7209)) suggested TargetScan, DianaMicroT and miRanda/mirSVR for target prediction.

Functional enrichment databases which i pointed earlier also uses various combination of the target prediction algorithm and even some uses a scoring mechanism to select the best possible combination.

ADD COMMENTlink written 7.6 years ago by Madhan220
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