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A genome-wide perspective on translation of proteins
Dec 2012Regulatory GenomicsLecturer: Prof. Yitzhak Pilpel
Multiple codons for the same amino acid: opportunities for sophisticated
control
C1 C2 C3 C4 C5 C6Serine: UCU UCC UCA UCG AGC AGUCysteine: UGU UGCMethionine: UGG
STOP: UAA, UAG UGA
2
in
jijiji tRNAsW
1
)1(
Wi/Wmax if Wi0wi = wmean else{
tAIg wikk1
g
1/g
dos Reis et al. NAR 2004
The tRNA Adaptation Index (tAI)
ATC CCA AAA TCG AAT … ……
A simple model for translation efficiency
Wobble Interaction
3
Codon usage bias is correlated with translation efficiency
r=-0.79 (p<0.001)
Mutation pattern(neutral)
Selection
Codon bias
Selection of codons might affect:AccuracyThroughput
CostsFolding
RNA-structure
Kinetic proofreading – the problem
c + C AAc
d
dC
AAd
+cC C – codon
c – Cognate tRNAd – None-cognate tRNAcC, dC – tRNA codon pairAAc, AAd, correct and wrong
amino acidAssumptions:kc=kd,k’d=100*k’cvd=vc
Error rate, Fo= AAd/AAc = dC/cC = k’c/k;d= 0.01
Yet in reality error rate is 10^-4… How can we explain100 times more accurate translation
kc
k’c
vc
vd
kdk’d
Kinetic proofreading – the solution
c + C AAc
d
dC
AAd
+cC
C – codonC* – Modified Cognate tRNAd* – Modified None-cognate tRNAC*C, d*C – tRNA codon pairm- rate of tRNA modificationl’c, l’d – rate of unidirectional reaction
in which the modified tRNAsleave the site
Assumption:l’c*100=l’d
Corrected Error rate, F= (k’c/k’d) (l’c/l’d)= 10^-4
kc
k’c
vc
vd
kdk’d
c*C m
d*C
m
l’c
l’d
Cc d
dC
cC
Fo
d*C
c*C
Fre
e en
ergy
l’c
l’d
k’c
k’d
Cc C
d
The energy landscape of kinetic proofreading
Analogy: from mating in yeastA protease might help yeast find the right mate by degrading the signal and the noise
Barkai et al. Nature 1998
No protease: large error With protease: small error
Selection of codons might affect:AccuracyThroughput
CostsFolding
RNA-structure
Programmed “errors” in amino acid loading on tRNA in stress
Oxygen radicals – toxic !!! A non-Met tRNA
As a result, in times of oxidative stress the cell is more protected since it has more Met residues in its proteins !!
(Netzer et al Nature 2009)
Open questions
• Does select act to tune the “desired” error rate?
• How can we find places in genes where high error rate is selected for/against?
• Does controlling tRNA availability serve as a means to control error rate?
• Are there additional factors (e.g. location of codon within a gene)?
Selection of codons might affect:AccuracyThroughput
CostsFolding
RNA-structure
in
jijiji tRNAsW
1
)1(
Wi/Wmax if Wi0wi = wmean else{
tAIg wikk1
g
1/g
dos Reis et al. NAR 2004
The tRNA Adaptation Index (tAI)
ATC CCA AAA TCG AAT … ……
A simple model for translation efficiency
Wobble Interaction
15
Correlation does not imply causality!!
r=0.63
Predicted translation efficiency
Measu
red p
rote
in
abundance
(Ghaemmaghami et al. Nature 2003)
Evolutionary
Physiological
Z
Yet, mRNA also correlates with tAI… and with protein levels…
*
*
*
*
*
*
*
tAI
mRNA
tAI and protein levels correlate even among gene populations with same mRNA levels
Deletion of a gene with a duplicate has smaller effect on phenotype
(Gu et al Nature 2002)
• Single-copy genes have a tendency to be essential
• Genes with duplicates tend to be more dispensable
As always, correlation doesn’t guarantee causality
Duplication Dispensability
Z(??)
A synthetic library of GFP variants
Kudla et al. Science 2009
No correlation between CAI and protein expression
Pro
tein
ab
unda
nce
Correlation does not imply causality!!
r=0.63
Predicted translation efficiency
Measu
red p
rote
in
abundance
(Ghaemmaghami et al. Nature 2003)
Evolutionary
Physiological
Tight RNA structure reduce translation
Pro
tein
ab
unda
nce
The tightness at the 5’ matters
So if codon usage doesn’t affect protein level, what does effect such levels? – It’s the RNA structure and its
tightness!
Is tightness important throughout, or just at particular locations?
?
Natural sequences too show relaxed structure at 5’ (Tuller PNAS 2010)
Str
uctu
ral
tig
htne
ssS
truc
tura
l t
ight
ness
Yet, mRNA structure doesn’t predict expression at all
Structural Tightness
Pro
tein
/mR
NA
Bioinformatics vs. synthetic biology
Bioinformatics
Hundreds of thousands of genes
All passed through natural selection
Synthetic biology
Variability is controlled (few confounding factors)
No correlation between CAI and protein expression
Pro
tein
ab
unda
nce
Towards more sophisticated translation efficiency models
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