Dose anybody knows that, where miRNA bind in mRNA? I mean, it's just bind to 3' UTR of mRNA, or to 5' of mRNA or somewhere in the middle of mRNA transcript?
Dose anybody knows that, where miRNA bind in mRNA? I mean, it's just bind to 3' UTR of mRNA, or to 5' of mRNA or somewhere in the middle of mRNA transcript?
Honestly, this could be answered by searching pubmed (or even wikipedia) a bit. While miRNAs generally target the 3' UTR, they don't have to. Targeting of UTRs just allows more flexibility in targeting across tissues and developmental stages (you can have multiple UTRs without mucking with the protein sequence). Just so that there's a reference here, have a read through this open access paper, found by a trivial search of pubmed, that looks at how functional coding region target sites are.
The "classic" miRNA binding sites are located in the 3'UTR part of the mRNA.
Depending on the binding type they can destabilize the mRNA, cleave or induce translation suppression.
However, as dpryan79 already mentioned there are bona fide binding sites in the CDS region.
The latest version of the microT algorithm (DIANA-microT-CDS) can identify binding sites in 3'UTR and CDS regions as well.
You can find the tool at http://www.microrna.gr/microT-CDS/
More information about the last web server version (front-end) you can find in this open NAR paper: http://nar.oxfordjournals.org/content/41/W1/W169
For so many miRNAs, i would've downloaded the csv that is provided by microT-CDS. There you get miRNA, gene, chromosome, coordinates and interaction score.
Then you can filter the results based on your miRNAs/genes list and score of preference [0 is worse and 1 is best].
miRNAs can also bind on non-coding RNAs (there is lncBase in the same server for validated and predicted miRNA:lncRNA interactions).
Cheers,
IV
I've downloaded and I read the first few lines of it. but it's not clear what is the Gene ID, what is the transcript id,... it's kind of messy
I used
`read.csv("file", header= T, sep=",")`
> data[1:10,]
TranscriptId GeneId.name. Mirna.Name.miRBase.version. miTG.score
1 F52F10.2 F52F10.2(F52F10.2) cel-miR-62(33) 0.488
2 UTR3 V:1550484-1550512 0.00994712053496221 NA
3 F11A1.3a F11A1.3(daf-12) cel-miR-62(33) 0.702
4 UTR3 X:10665625-10665653 0.0247451317964074 NA
5 T11G6.5a T11G6.5(T11G6.5) cel-miR-62(33) 0.511
6 CDS IV:10841175-10841203 0.022290972286146 NA
7 CDS IV:10840760-10840788 0.0110658552017645 NA
8 F28H6.4 F28H6.4(F28H6.4) cel-miR-62(33) 0.494
9 UTR3 X:14133330-14133358 0.00425015346910806 NA
10 CDS X:14128414-14128442 0.0140299826282741 NA
I'll do an example first with c. elegans. It's not complicated but you need to get used to the notation,
It is one line: Transcript ID, GeneID and Name, miRNA name and the the interaction score (for the whole transcript and the miRNA)
The next lines that follow mark the specific binding sites within this transcript.
First is the region (UTR3 or CDS) and then the location (chromosome: coordinates) and the score for this specific binding site (MRE: miRNA Recognition Element).
Then you have as many lines as binding sites and then you get the next interaction.
Example:
TranscriptId | GeneId(name) | Mirna-Name(miRBase-version) | miTG-score
F41C3.4 | F41C3.4(F41C3.4) | cel-miR-62(33) | 0.955
We see that the transcript F41C3.4, from gene F41C3.4, with gene name F41C3.4, interacts with miRNA cel-miR-62, with a very high score: 0.955
Then two lines with two binding sites follow:
UTR3 | II:4741279-4741307 | 0.0604922999963247
CDS | II:4741074-4741102 | 0.0136810939277919
The first binding site is in the 3' UTR of the transcript. It's located in chromosome II, coordinates 4741279-4741307 and has an MRE (miRNA Recogintion Element) score of 0.0136810939277919.
The next binding site is in the CDS region of the transcript. Same chromosome as before (II) and the coordinates are: 4741074-4741102.. and so on.
One more example from human:
ENST00000399503 | ENSG00000095015(MAP3K1) | hsa-let-7c(33) |0.999
The first entry is the transcript ID from ENSEMBL (ENST00000399503), this is the transcript that is being analyzed.
Next is the gene: ENSG00000095015 and the gene name: MAP3K1
The microRNA responsible for the targeting is hsa-let-7c and the interaction has a really high score: 0.999
Then two lines with two binding sites follow:
UTR3 | 5:56191340-56191368 | 0.00515874737376934
UTR3 | 5:56191638-56191666 | 0.115647094645092
Both MREs are in the 3'UTR of the transcript and the their coordinates are:
1st MRE: 56191340-56191368, with score: 0.00515874737376934
2nd MRE: 56191638-56191666, with score: 0.115647094645092
I think that it gets pretty straightforward
All the species are in the same file.
It's easy to separate them, since miRNA names are unique for each species.
All the interactions that have miRNA names starting with "hsa" are for human
Another way to separate the species is from ENSG ID but I always use the miRNA identifier.
It's the same as having a species identifier.
I have problem with pre-processing of data, basically, I want to just one row for every transcript in my data matrix. I want just choose the CDS with hieghst score as well for CDS. like this. do you know, how can I do this kind of pre-processing in R? :
Transcript Id Gene Id(name) Mirna Name miTG score UTR3 MRE_score CDS
ENST00000286800 ENSG00000156273 (BACH1) hsa-let-7a-5p 1 21:30717414-30717442 0.13591267 21:30717444-30717453
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I have a list of 800 miRNA genes and big list of targets. I want to predict the binding site of miRNAs on given targets. is there any reliable tools to do this ? (I want for example upload 800 miRNA and few thousands targets)
You can filter miRNA-target interactions using AGO CLIP-Seq data. starBase ( http://starbase.sysu.edu.cn/ ) constructed CLIP-Seq supported miRNA-target (miRNA-mRNA, miRNA-lncRNA, miRNA-pseudogene, miRNA-sncRNA) interactions. You can download 111 CLIP-Seq data from starBase. starBase also developed Pan-Cancer miRNA-target interactions from 14 cancer types.