1 / 23

Defensio Dissertationis Jörg Hackermüller

The RNA secondary structure dependence of RNA protein interactions and its implications for the post transcriptional regulation of gene expression. Defensio Dissertationis Jörg Hackermüller. AAAA. C. A A A A. A A A A. A A A A. C. C. C. degradation.

zariel
Télécharger la présentation

Defensio Dissertationis Jörg Hackermüller

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. The RNA secondary structure dependence of RNA protein interactions and its implications for the post transcriptional regulation of gene expression Defensio Dissertationis Jörg Hackermüller

  2. AAAA C A A A A A A A A A A A A C C C degradation Regulation of Eukaryotic Gene Expression

  3. RNA-protein interactions • highly relevant (involved in many biological pathways – particularly in post transcriptional regulation of gene expression ) • often dependent on recognition of RNA (secondary) structure features • despite the importance no systematic investigation of RNA secondary structure dependence

  4. Quantitative model of RPIA • Model: • proteins binds only RNAs that form secondary structure feature • 1:1 binding (can be extended at cost of more complex expressions) • non pseudo-knotted RNA secondary structures (can be extended at cost of higher computational effort)

  5. NNUUNNUUU • A2 Ways to calculate p • NNUUNNUUU • HuR target mRNA • 5‘ • A1 • S(s) • S(A1,A2,s) • S(A1,s) • S(A2,s)

  6. A statistical test for the influence of secondary structure • (i) calculate p* [] for any test conformation  for all sequences in the set • (ii) calculate correlation coefficient between and p* [] • (iii) test whether this correlation is significant: • k number of sequences in set • r empirical correlation coefficient • t(.) Student’s t-distribution for (k-2) degs. of freedom • a significance level

  7. AAAAA mRNA stability regulation by HuR HuR HuR AAAAA AAAAA NPC neg. regulators (AUF1, TTP, …) • decay • Quiescent cells

  8. AAAAA AAAAA AAAAA AAAAA mRNA stability regulation by HuR HuR HuR AAAAA AAAAA NPC neg. regulators (AUF1, TTP, …) • decay • upregulation • Trigger • Quiescent cells

  9. HuR RNA recognition • HuR to RNA binding: • diverse affinities to target RNA (sub) sequences (Kd 120 pM to 13 nM) • Sequence properties: • HuR’s degenerate binding motif: N-N-U-U-N-N-U-U-U • binds in “all or nothing” manner (U9 1nM, U8 “nothing”1) 1< 0.01% of RNA bound

  10. HuR binds NNUUNNUUU in single stranded conformation • x unpaired • | paired • . No constraint ( opening base pair ) closing basepair

  11. modRNA mechanism • manipulate RNA-protein interactions through manipulation of RNA secondary structure • RNA secondary structure can change significantly upon hybridization of a second RNA (heteroduplex formation)

  12. modRNA mechnism II • RNA-RNA hybridization thermodynamically well understood • no model currently available for influence on RNA-protein interactions • RNA-RNA hybridization biologically very relevant for RNA-ligand interactions (non-protein coding RNAs) • approximate model of ternary equilibrium RNA – protein – short RNA • modRNA selected by calculating for any possible exactly reverse complementary modRNA of a given length (20nt)

  13. . . . . . . . . . . . . . . . . . . opener Op1 Openers specifically stabilize mRNA

  14. Specificity puzzle and modRNAs • Science

  15. Specificity puzzle and modRNAs • Fiction

  16. Outlook • endogenous modRNAs? • potential origin • bioinformatic strategies to find ‘em • modRNAs as tools in biology • may serve as complementary technique for RNAi • issue of delivery • modRNAs in drug discovery • modRNAs as pharmaceutic agents • modRNAs as tools in pharma research

  17. Summary People involved NIBR DT - IST Volker Uhl Jan-Marcus SeifertMartin Hintersteiner Nicole-Claudia Meisner Manfred Auer NIBR IK@N-ISS Torsten SchindlerSiegfried Höfinger Markus Jaritz Jörg Hackermüller Andras Aszodi Univ. Leipzig Peter F. Stadler Univ. Salzburg Fatima Ferreira Univ. Vienna Christoph Flamm Ivo Hofacker Kurt Gruenberger OeAW DOC 11/2000

  18. Backup slides Backup slides

  19. A quantitative model for RNA - ligand binding • Ligand binds only to RNA which has a particular accessible conformation RNA* • Experiments can not distinguish between accessible and non-accessible • Probability of accessible structures p* expressedby partition functions:

  20. modRNA model • neglect multiple binding of oligo O to mRNA M • O is exactly reverse complementary to M • no significant self complementarityin O and M • excess of O • Computation by constrained partition functions:

  21. modRNA model II • Effect of modRNAs on affinity

More Related