1. Computational biology seminar
micro RNA’s
Computational biology seminar
Ariel Jaimovich
November 17th 2005

2. The central dogma of biology
Transcription
RNA
Translation
Protein
This is not always the case:
First ‘life forms’
viruses

3. Dioxy ribo

4. Rna performs many functions
Ribosomes
tRNA
Nuclear detaining
RNAi

5. Micro RNA
~22nt rna
Precursor stem& loop
Post-transcription regulation

7. miRNA History
Lin-4 inhibits LIN14, but no LIN 4 protein was found (1993)

8. miRNA appear in many organisms
Highly conserved, many ‘copies’ in each organism
4 paralogs of let7 4 in c elegans
15 in human
1 in drosophila

9. miRNA Genes ~1/3 Reside inside introns
~ 2/3 independent transcription units
Often in clusters.
Many times near the genes they regulate or inside them.

10. Expression Stage\tissue specific
Large number of copies (robust transcription \ slow decay)

11. miRNA – biogenesis
Highly conserved in evolution

12. Plants Vs Animals

13. miRNA - function

14. Sequence recognition Positions 2-8 are most important How do we know
Why ?

15. Base pairing  Function
How do we know which process is active ?

16. Function (cont) Plants vs animals Number of target seq. on 3’ utr ?
Some miRNA target the same mRNA in different sites
Protein coding rna
3’ utr

17. siRNA vs miRNA Genomic origin – miRNA from genes
siRNA from mRNAs, transposons, viruses...
Synthesis
One siRNA duplex  many siRNA
Conservation

18. miRNA vs siRNA

19. miRNA in plants Near-perfect complementarity
mRNA cleavage, usually of TF’s related to developmental processes
Conservation between Arabidopsis and rice
Defend against viruses

20. miRNA in animals mRNA cleavage or translational silencing
Conservation is also high (?)
Different numbers of paralogs

21. Identification of hundreds of conserved and nonconserved human microRNAs
Isaac Bentwich, Amir Avniel, Yael Karov, Ranit Aharonov Shlomit Gilad, Omer Barad, Adi Barzilai, Paz Einat, Uri Einav, Eti Meiri, Eilon Sharon, Yael Spector & Zvi Bentwich
Nature genetics - June 2005

22. Find new human micro RNAs
Goal
Find new human micro RNAs

23. Motivation Current gene search techniques: Hairpins Conservation
Try to search with a wider scope

24. Search algorithm

25. Prediction (1) Fold the genome ~ 11 milion hairpins Magic box

26. Magic box Structure features Sequence features Build a classifier
Hairpin length
Loop length
Stability score
Free energy per nucleotide
Matching pairs
Bulge size
Sequence features
Sequence repetitiveness
Regular internal repeat
Inverted internal repeat
Build a classifier

27. Prediction (2) ~ 430,000 hairpins conserved Non- conserved sample
800 clustered
3000 non-clustered
1500 clustered
7500 control
sample

28. Micro array in five tissue cultures Validate (clone and sequence)
Prediction (3)
800 clustered
3000 non-clustered
1500 clustered
7500 control
Micro array in five tissue cultures
886 confirmed miRNA
69 ‘adjacent’ miRNA
Sample
359 miRNA
Validate (clone and sequence)

29. Prediction (3) 69 ‘adjacent’ miRNA 359 miRNA
Validate (clone and sequence)
89 (33 ‘adjacent’) cloned and sequenced NEW miRNA
Of these:
1 from the control list
36 conserved miRNA’s (32 validated in other experiments)
43 in two new clusters

30. New cluster

31. The cluster conatin a few ‘seeds’

32. Results summary

34. Goal
Location on chromosome
Expression ?

35. Creating miRNA micro array

36. Design microRNA chip Normalization by synthetic samples
Melting temperature

37. Array Results

38. Is Expression correlated with distance between microRNA’s?
55bp

39. Is expression of micro RNA’s correlated with host genes ?

40. Caveats Conclusions Numbers of pairs ?
Quantitative comparison with host genes
Conclusions
Some miRNA are arranged in genes
miRNA that are located inside introns are expressed similarly to their hosts

41. Points for thought Is miRNA regulated ? On which levels ?
Is there a regulation on the RISC ‘loading’
Why is so many annotated miRNA related to differentiation ?
mRNA can be passed on during mitosis and need to cleaved
Control leaky transcription ?