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micro RNA’s. Computational biology seminar Ariel Jaimovich November 17 th 2005. Transcription. Translation. Protein. RNA. The central dogma of biology. This is not always the case: First ‘life forms’ viruses. Dioxy ribo @#$%##@?!. Rna performs many functions . Ribosomes tRNA
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micro RNA’s Computational biology seminar Ariel Jaimovich November 17th 2005
Transcription Translation Protein RNA The central dogma of biology • This is not always the case: • First ‘life forms’ • viruses
Rna performs many functions • Ribosomes • tRNA • Nuclear detaining • RNAi
Micro RNA • ~22nt rna • Precursor stem& loop • Post-transcription regulation
miRNA History • Lin-4 inhibits LIN14, but no LIN 4 protein was found (1993)
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
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.
Expression • Stage\tissue specific • Large number of copies (robust transcription \ slow decay)
miRNA – biogenesis Highly conserved in evolution
Sequence recognition • Positions 2-8 are most important • How do we know • Why ?
Base pairing Function How do we know which process is active ?
3’ utr Protein coding rna Function (cont) • Plants vs animals • Number of target seq. on 3’ utr ? • Some miRNA target the same mRNA in different sites
siRNA vs miRNA • Genomic origin – • miRNA from genes • siRNA from mRNAs, transposons, viruses... • Synthesis • One siRNA duplex many siRNA • Conservation
miRNA in plants • Near-perfect complementarity • mRNA cleavage, usually of TF’s related to developmental processes • Conservation between Arabidopsis and rice • Defend against viruses
miRNA in animals • mRNA cleavage or translational silencing • Conservation is also high (?) • Different numbers of paralogs
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
Goal Find new human micro RNAs
Motivation Current gene search techniques: • Hairpins • Conservation Try to search with a wider scope
~ 11 milion hairpins Magic box ~ 430,000 hairpins Prediction (1) Fold the genome
Build a classifier Magic box • Structure features • Hairpin length • Loop length • Stability score • Free energy per nucleotide • Matching pairs • Bulge size • Sequence features • Sequence repetitiveness • Regular internal repeat • Inverted internal repeat
Non- conserved conserved sample 800 clustered 3000 non-clustered 1500 clustered 7500control Prediction (2) ~ 430,000 hairpins sample
Micro array in five tissue cultures 886 confirmed miRNA Sample 69 ‘adjacent’ miRNA 359 miRNA Validate (clone and sequence) Prediction (3) 800 clustered 3000 non-clustered 1500 clustered 7500control
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
Goal Location on chromosome Expression ?
Design microRNA chip • Normalization by synthetic samples • Melting temperature
55bp Is Expression correlated with distance between microRNA’s?
Caveats • 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
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 ?