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I aligned all miRNAs available to the supercontigs of a particular genome with certain parameters (e value of 0.01 and a word match of atleast 7 as suggested in this paper). I have also isolated the pre-miRNAs (+100 nucleotides from either end of the match area). What would you suggest as ideal ab-initio methods to confirm that these miRNAs do exist in that particular genome? Some papers I found use mFOLD like this.

What would you suggest as best steps to confirm if a predicted miRNA/pre-miRNA is really present in the genome.

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  • $\begingroup$ you can look at my answer in your previous post.. BTW, How did you obtain the miRNA sequences? $\endgroup$
    – WYSIWYG
    May 26, 2014 at 19:18
  • $\begingroup$ @WYSIWYG I downloaded all the available mature sequences in miRBase. Removing duplicates is an issue. What would you suggest is a good tool to remove duplicate miRNAs among 30,000 sequences. $\endgroup$
    – The Last Word
    May 27, 2014 at 4:28

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There won't be any duplicates in miRBase (for a given organism). Choose the taxon nearest to your organism if you are doing homology based discovery. If you want to take all/many organisms then you can use fastx_collapser to collapse redundant sequences. However you will lose the name of the miRNA. You can use awk also for this and it will keep the sequence header from the first organism in the list. 

awk '/>/{$0=h} !(/>/){if($0 in a){next} else{a[$0];print h"\n"$0}}' organism1.fa organism2.fa ... organismN.fa

Make sure that there are no extra newlines, otherwise you might need a small modification

To know if something is an expressed miRNA you would need to do a small RNA sequencing. There are some tools like mirdeep and mirSVR which you can use to discover miRNA sequences.

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  • $\begingroup$ Do I really need to use mirDeep now that I am trying to match the already existing list of all available miRNA to the genome rather than find new novel sequences. I thought that was what miRdeep was for. $\endgroup$
    – The Last Word
    May 27, 2014 at 6:22
  • $\begingroup$ It does not just find novel miRNAs but it also checks for the features such as hairpin formation and assigns scores. mirSVR uses a machine learning algorithm to find miRNAs (I have never used it though) $\endgroup$
    – WYSIWYG
    May 27, 2014 at 7:18

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