Lecture 11

1. http://cs273a.stanford.edu [Bejerano Fall10/11]

2. Lecture 11 HW1 Feedback (ours) (Upcoming Project – discuss Wed) Non-Coding RNAs Halfway Feedback (yours) http://cs273a.stanford.edu [Bejerano Fall10/11]

3. “non coding” RNAs http://cs273a.stanford.edu [Bejerano Fall10/11]

4. Central Dogma of Biology:

5. RNA is an Active Player: reverse transcription long ncRNA

6. What is ncRNA? • Non-coding RNA (ncRNA) is an RNA that functions without being translated to a protein. • Known roles for ncRNAs: • RNA catalyzes excision/ligation in introns. • RNA catalyzes the maturation of tRNA. • RNA catalyzes peptide bond formation. • RNA is a required subunit in telomerase. • RNA plays roles in immunity and development (RNAi). • RNA plays a role in dosage compensation. • RNA plays a role in carbon storage. • RNA is a major subunit in the SRP, which is important in protein trafficking. • RNA guides RNA modification. • In the beginning it is thought there was an RNA World, where RNA was both the information carrier and active molecule.

7. RNA Folds into (Secondary and) 3D Structures AAUUGCGGGAAAGGGGUCAA CAGCCGUUCAGUACCAAGUC UCAGGGGAAACUUUGAGAUG GCCUUGCAAAGGGUAUGGUA AUAAGCUGACGGACAUGGUC CUAACCACGCAGCCAAGUCC UAAGUCAACAGAUCUUCUGU UGAUAUGGAUGCAGUUCA We would like to predict them from sequence. Cate, et al. (Cech & Doudna). (1996) Science 273:1678. Waring & Davies. (1984) Gene 28: 277.

8. RNA structure rules • Canonical basepairs: • Watson-Crick basepairs: • G - C • A - U • Wobble basepair: • G – U • Stacks: continuous nested basepairs. (energetically favorable) • Non-basepaired loops: • Hairpin loop. • Bulge. • Internal loop. • Multiloop. • Pseudo-knots

9. RNA structure: Basics • Key: RNA is single-stranded. Think of a string over 4 letters, AC,G, and U. • The complementary bases form pairs. • Base-pairing defines a secondary structure. The base-pairing is usually non-crossing. Bafna

10. simple model: (i, j) = 1 Ab initio structure prediction: lots of Dynamic Programming • Maximizing the number of base pairs (Nussinov et al, 1978)

11. Pseudoknots drastically increase computational complexity

12. Nearest Neighbor Model for RNA Secondary Structure Free Energy at 37 OC: Mathews, Disney, Childs, Schroeder, Zuker, & Turner. 2004. PNAS 101: 7287. http://cs273a.stanford.edu [Bejerano Fall10/11]

13. Zuker’s algorithm MFOLD: computing loop dependent energies

14. Energy Landscape of Real & Inferred Structures http://cs273a.stanford.edu [Bejerano Fall10/11]

15. Unfortunately… • Random DNA (with high GC content) often folds into low-energy structures. • What other signals determine non-coding genes?

16. Evolution to the Rescue http://cs273a.stanford.edu [Bejerano Fall10/11]

17. http://cs273a.stanford.edu [Bejerano Fall10/11]

18. S S Stochastic context-free grammar (SCFG) S  aSu L  aL S  uSa L  cL S  gSc L  a S  cSg L  c S  L S S L L L L c g u u a g a a a c c u c u c c c c • Each derivation tree corresponds to a structure.

19. Stochastic context-free grammar (cont’) S  aSu S  cSg S  gSc S  uSa S  a S  c S  g S  u S  SS 1. A CFG S  aSu  acSgu  accSggu  accuSaggu  accuSSaggu  accugScSaggu  accuggSccSaggu  accuggaccSaggu  accuggacccSgaggu  accuggacccuSagaggu  accuggacccuuagaggu 2. A derivation of “accuggacccuuagaggu” 3. Corresponding structure

20. http://cs273a.stanford.edu [Bejerano Fall10/11]

21. MicroRNA http://cs273a.stanford.edu [Bejerano Fall10/11]

22. Genomic context known miRNAs in human intergenic intronic polycistronic monocistronic

23. tRNA

24. tRNA Activity

25. http://cs273a.stanford.edu [Bejerano Fall10/11]

26. http://cs273a.stanford.edu [Bejerano Fall10/11]

27. Human specific accelerated evolution rapid change Human Chimp conserved http://cs273a.stanford.edu [Bejerano Fall10/11]

28. Human Accelerated Regions rapid change Human • HAR1: • Novel ncRNA • Co-expressed in Cajal-Retzius cells with reelin. • Similar expression inhuman, chimp, rhesus. • 18 unique human substitutionsleading to novel conformation. • All weak (AT) to strong (GC). Chimp conserved Human Derived Chimp Ancestral Human-specific substitutions in conserved sequences 28 [Pollard, K. et al., Nature, 2006] [Beniaminov, A. et al., RNA, 2008]

29. Other Non Coding Transcripts http://cs273a.stanford.edu [Bejerano Fall10/11]

30. http://cs273a.stanford.edu [Bejerano Fall10/11]

31. mRNA http://cs273a.stanford.edu [Bejerano Fall10/11]

32. EST http://cs273a.stanford.edu [Bejerano Fall10/11]

33. lincRNAs (long intergenic non coding RNAs) http://cs273a.stanford.edu [Bejerano Fall10/11]

34. X Dosage compensation X chromosome inactivation in mammals X Y X X

35. Avner and Heard, Nat. Rev. Genetics 2001 2(1):59-67 Xist – X inactive-specific transcript

36. Microarrays, Next Gen(eration) Sequencing etc. http://cs273a.stanford.edu [Bejerano Fall10/11]

37. End Results http://cs273a.stanford.edu [Bejerano Fall10/11]

38. http://cs273a.stanford.edu [Bejerano Fall10/11]

39. http://cs273a.stanford.edu [Bejerano Fall10/11]

40. Transcripts, transcripts everywhere Human Genome Leaky tx? Functional? Transcribed (Tx) Tx from both strands http://cs273a.stanford.edu [Bejerano Fall10/11]

41. Or are they? http://cs273a.stanford.edu [Bejerano Fall10/11]

42. Halfway Feedback http://cs273a.stanford.edu [Bejerano Fall10/11]