A genome-wide perspective on translation of proteins

1. A genome-wide perspective on translation of proteins Dec 2012 Regulatory Genomics Lecturer: Prof. Yitzhak Pilpel

2. Teaching assistant: Idan Frumkin idan.frumkin@weizmann.ac.il Submit Sunday at midnight

3. The Central Dogma of Molecular Biology Expressing the genome RNA Inactive DNA DNA mRNA Protein f f

4. The Lac Operon (Jacob and Monod) In the presence of Lactose http://esg-www.mit.edu:8001/esgbio/pge/lac.html

5. The basic logic of metabolic control Catabolism (breakdown of molecules, e.g. lactose) Anabolism (synthesis of molecules, e.g. amino acids) Gene is ON when substrate is absent Gene is OFF when substrate is present Gene is ON when substrate is present Gene is OFF when substrate is absent

6. A combined transcription -translation control switchAt the Attenuation mechanism Charles Yanofsky

7. The trp operon in e. coli

8. A negative control at the transcription level (similar and different from the lac operon)

9. How not to make too much triptophene? • A fail safe mechanism complements transcription control • At the translation level!

10. The up-stream ORF structure of the trp operon An uORF Mutual palindromes 1-2 are complementary 2-3 are complementary 3-4 are complementary

11. The various palindromic pairings 2-3 1-2, and 3-4 Transcription terminator! Not a terminator!

12. High Trp The structure of the Attenuation switch Low Trp RNA pol RNA pol Ribosome Ribosome

13. Could that be implemented in eukaryotes as well? • No! because requires co transcription-translation

14. Where does translation take place?

15. Spatial organization of the flow of geneticinformation in bacteria (Llopis Nature 2010) DNA =DNA =mRNA =Protein

16. Translation consists of initiation, elongation and termination STOP 3’ 5’ Anti-codon Codon

17. The dynamics of translation

18. The ribosome reads nucleotide sequence and produces amino acid sequence based on the genetic code • Some important properties of the code • The code is (almost) universal • There are 61 amino acid codons, and 3 STOP codons • The code is “redundant” - many amino acids have more than one codon • The genetic code is optimal wrt to many properties, such as error tolerance

19. The tRNA The generic form A specific form In 3D

20. Aminoacyl tRNA synthetase:The really “smart” part Error rate: 1/10,000-1/100,000 (in-vitro; higher in-vivo) 20 amino acids, 61 codons, 20 Aminoacyl tRNA synthetases

21. The 20 canonical amino acids

22. Possible mechanisms of translational regulation • optimality of ribosomal attachment site • mRNA secondary structure • codon usage

23. Multiple codons for the same amino acid C1 C2 C3 C4 C5 C6 Serine: UCU UCC UCA UCG AGC AGU Cysteine: UGU UGC Methionine: UGG STOP: UAA, UAG UGA

24. G T R Y E C Q A S F D C1C1C1C1C1C1C1C1C1C1C1 C2C2C2C2C2C2C2C2C2C2C2 C1C1C2C1C1C2C1C1C2C1C1 C2C2C2C2C1C1C1C1C1C1C1 C1C1C1C1C1C1C1C2C2C2C2 For a hypothetical protein of 300 amino acids with two-codon each, There are 2^300 possible nucleotide sequences These variants will code for the same protein, and are thus considered “synonymous”. Indeed evolution would easily exchange between them But are they all really equivalent??

25. The codon bias in genomes

26. Two potential types of sources for codon bias Mutation pattern (neutral) Selection Codon bias

27. The effect of (or on?) GC content Mutation pressure Selection Amino acid composition Nucleotide composition Inter-genic composition (esp in bacteria) explain codon bias Codon bias Inter- genic Coding Coding

28. Selection of codons might affect: Accuracy Throughput RNA-structure Costs Folding

29. AAA CCA GAA UCG AAG A simple model for translation efficiency 5’ 3’ … … … 8 2 5 4 1 Average: 4 AA Codon Amount Lys AAA 8 Asp AAC 6 Lys AAG 1 Asp AAU Thr ACA Thr ACC . . Phe UUU

30. relative concentration of tRNA in thecell ATGCCT 1 0 5 0 intermediate efficiency ATGCCC least efficient ATGCCA most efficient ATGCCG intermediate efficiency The same protein can be encoded in many ways… amino acid sequence: MPKSNFRFGE ATG

31. tRNA Gene copies 10 10 7 2 6 coding sequence translation efficiency score ( (geometric) average of all tRNA gene copy numbers) ATC CCA AAA TCG AAT Scoring coding sequences for efficiency in translation Efficient intermediate non-efficient … … … … (dos Reis et al. Nucleic Acids Res, 2004)

32. Wobble Interaction { Wi/Wmaxif Wi0 wi = wmeanelse ATC CCA AAA TCG AAT A simple model for translation efficiency … … … The tRNA Adaptation Index (tAI) dos Reis et al. NAR 2004

33. Physiological Correlation of tAI with experimentally determined protein levels r=0.63 Measured protein abundance Predicted translation efficiency (Ghaemmaghami et al. Nature 2003)

34. The correlation is quite high, but why not even higher? • The limitations of the model • tRNA gene copy numbers • Model only capture elongation • Difference in mRNA levels • Protein are also degraded at different rates

35. Gene1 Gene2 AA . . . Gly Gly Gly Gly . . . codon . . . GGT GGC GGA GGG . . . Codon count . . . 0 12 0 0 . . . AA . . . Gly Gly Gly Gly . . . codon . . . GGT GGC GGA GGG . . . Codon count . . . 3 3 3 3 . . . Highly biased synonymous codon usage (Nc=20) No bias in synonymous codon usage (Nc≥61) The effective number of codons (Nc) - a measure of overall synonymous codon usage bias Wright, F. (1990). "The 'effective number of codons' used in a gene." Gene 87(1): 23-9.

36. Codon usage bias is correlated with translation efficiency r=-0.79 (p<0.001) Mutation pattern (neutral) Selection Codon bias

37. But not in all species(e.g. A. gossypii) r=-0.48 (p=0.218) Mutation pattern (neutral) Selection Codon bias

38. A. gossypii D. hansenii S. cerevisiae S. bayanus C. glabrata C. albicans Y. lipolytica S. pombe Translation selection acts in some but not all species (e.g. debate on human…)

39. Physiological Correlation does not imply causality!! r=0.63 Z Measured protein abundance Physiological Evolutionary Predicted translation efficiency (Ghaemmaghami et al. Nature 2003)