How do you classify the miRNAs? What is the best way to classify miRNAs hypothetical using Blastn-short or RFAM? [doubts]
Hello everyone. Let's me explain my doubts. I mean about 200 sequences which was predicted by mir-Bag (pre-microRNA) before. Then I used this pre-micros with the miRdup in order to obtain the microRNAs. Now, I want to know which have been listed above. Firstly, I did a blastn -task blastn-short -evalue 10
(v. 2.2.30) against the mature miRNAs from mirBase.org. I wonder if you use this strategy and what options you usually use like:
-evalue 10
-penalty -4?
-word_size 4 or 7?
-ungapped?
-reward 1?
Because it is not neccesary to have a full coverage of the query, therefore there are some isomeRs with slightly mismatches. But if the seed region (2nt-7nt) is covered fully then it is the same family miRNA. Isn't it? Or I have to do the RFAM. Regards.
I attach one example and some options of blastn (v. 2.2.30.)
query= ENTRY327687_trypsinogen_354_553
Length=22
Score E
Sequences producing significant alignments: (Bits) Value
dme-miR-4941-5p MIMAT0020148 Drosophila melanogaster miR-4941-5p 24.3 0.21
dvi-miR-9538-3p MIMAT0035619 Drosophila virilis miR-9538-3p 22.3 0.83
mmu-miR-7677-5p MIMAT0029868 Mus musculus miR-7677-5p 22.3 0.83
mmu-miR-6922-3p MIMAT0027745 Mus musculus miR-6922-3p 22.3 0.83
gga-miR-6708-5p MIMAT0025818 Gallus gallus miR-6708-5p 22.3 0.83
mtr-miR2590j MIMAT0021334 Medicago truncatula miR2590j 20.3 3.3
mtr-miR2590i MIMAT0021333 Medicago truncatula miR2590i 20.3 3.3
mtr-miR2590h MIMAT0021332 Medicago truncatula miR2590h 20.3 3.3
tca-miR-3813-5p MIMAT0018648 Tribolium castaneum miR-3813-5p 20.3 3.3
mtr-miR2598 MIMAT0013301 Medicago truncatula miR2598 20.3 3.3
oan-miR-181c-3p MIMAT0007059 Ornithorhynchus anatinus miR-181c-3p 20.3 3.3
Query_29 2 TGGCGGTGAGCAGAATAATTG 22
20244 19 GGCGGTGAGCAG 8
34141 12 CAGAATAATTG 22
28818 4 GGTGAGCAGAA 14
26045 13 GGTGAGCAGAA 3
25597 11 GCGGTGAGCAG 21
21071 12 GCAGAATAAT 21
21070 12 GCAGAATAAT 21
21069 12 GCAGAATAAT 21
18383 10 GAGCAGAATA 1
13217 19 GCAGAATAAT 10
7532 10 TGGCGGTGAG 1
Lambda K H
1.37 0.711 1.31
Gapped
Lambda K H
1.37 0.711 1.31
Effective search space used: 4258254
Hi,
I don't totally understand the goal. Do you have some sequences? a lot of sequences? Do you want to know which of them are miRNAs, or do you want to predict new miRNAs?
Do you want to know to which miRNA is most similar, or the family only?
There are a bunch of tools, but all are different and depends on the final goal. There are some tool you can use depending on your type of data. If you add this information, maybe I can tell u more.
cheers
Hi. I mean about 200 sequences which was predicted by mir-Bag (pre-microRNA) before. Then I used this pre-micros with the miRdup in order to obtain the microRNAs. Now, I want to know which have been listed above.