A genome-wide perspective on translation of proteins

A genome-wide perspective on translation of proteins

Dec 2012Regulatory GenomicsLecturer: Prof. Yitzhak Pilpel

Teaching assistant: Idan Frumkin

idan.frumkin@weizmann.ac.il

Submit Sunday at midnight

The Central Dogma of Molecular BiologyExpressing the genome

DNA mRNA Protein

f f

Inactive DNA

RNA

http://esg-www.mit.edu:8001/esgbio/pge/lac.html

In the presence of Lactose

The Lac Operon (Jacob and Monod)

4

Catabolism (breakdown of molecules, e.g.

lactose)

Anabolism (synthesis of

molecules, e.g. amino acids)

Gene is ON when substrate is present

Gene is OFF when substrate is absent

Gene is ON when substrate is absent

Gene is OFF when substrate is present

The basic logic of metabolic control

A combined transcription -translation control switch

At the Attenuation mechanism

Charles Yanofsky

The trp operon in e. coli

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

How not to make too much triptophene?

• A fail safe mechanism complements transcription control

• At the translation level!

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

The various palindromic pairings

1-2, and 3-42-3

Transcription terminator!

Not aterminator!

High Trp Low Trp

The structure of the Attenuation switch

RibosomeRibosome

RNA pol

RNA pol

Could that be implemented in eukaryotes as well?

• No! because requires co transcription-translation

Where does translation take place?

Spatial organization of the flow of geneticinformation in bacteria (Llopis Nature 2010)

DN

A

=DNA=mRNA=Protein

Translation consists of initiation, elongation and termination

5’ 3’STOP

Codon

Anti-codon

The dynamics of translation

The ribosome reads nucleotide sequence and produces amino acid sequence based on the

genetic codeSome 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

The tRNAThe generic form A specific form In 3D

Aminoacyl tRNA synthetase:The really “smart” part

20 amino acids, 61 codons, 20 Aminoacyl tRNA synthetases

Error rate: 1/10,000-1/100,000(in-vitro; higher in-vivo)

The 20 canonical amino acids

Possible mechanisms of translational regulation

• optimality of ribosomal attachment site• mRNA secondary structure• codon usage

Multiple codons for the same amino acid

C1 C2 C3 C4 C5 C6Serine: UCU UCC UCA UCG AGC AGUCysteine: UGU UGCMethionine: UGG

STOP: UAA, UAG UGA

G T R Y E C Q A S F DC1C1C1C1C1C1C1C1C1C1C1C2C2C2C2C2C2C2C2C2C2C2C1C1C2C1C1C2C1C1C2C1C1C2C2C2C2C1C1C1C1C1C1C1C1C1C1C1C1C1C1C2C2C2C2

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 themBut are they all really equivalent??

The codon bias in genomes

Two potential types of sources for codon bias

Mutation pattern(neutral)

Selection

Codon bias

The effect of (or on?) GC content

Nucleotide composition

Codon bias

Coding CodingInter-genic

Inter-genic composition (esp in bacteria) explain codon bias

Mutation pressure

Selection Amino acidcomposition

Selection of codons might affect:AccuracyThroughput

CostsFolding

RNA-structure

AAA CCA GAA UCG AAG … ……

A simple model for translation efficiency

8 2 5 4 1 Average: 4AA Codon AmountLys AAA 8 Asp AAC 6Lys AAG 1Asp AAUThr ACAThr ACC..Phe UUU

5’ 3’

The same protein can be encoded in many ways…

amino acid sequence: MPKSNFRFGE

ATG

ATGCCT

ATGCCC

ATGCCA

ATGCCG

most efficient

least efficient

intermediate efficiency

intermediate efficiency

relative concentration of tRNA in the cell

1

0

5

0

Scoring coding sequences for efficiency in translation

ATC CCA AAA TCG AAT

coding sequence translation efficiency score( (geometric) average of all tRNA gene copy numbers)

… ………

Efficient intermediate non-efficient

10 10 7 2 6tRNAGene copies

(dos Reis et al. Nucleic Acids Res, 2004)

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

Correlation of tAI with experimentally determined protein levelsr=0.63

Predicted translation efficiency

Mea

sure

d pr

otei

n ab

unda

nce

(Ghaemmaghami et al. Nature 2003)

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

gg

kk

ig wtAI /1

1

The effective number of codons (Nc) - a measure of overall synonymous codon usage bias

AA...

GlyGlyGlyGly

.

.

.

codon...

GGTGGCGGAGGG

.

.

.

Codon count...0

1200...

Highly biased synonymous codon usage (Nc=20)

Gene1AA...

GlyGlyGlyGly

.

.

.

codon...

GGTGGCGGAGGG

.

.

.

Codon count...3333...

No bias in synonymous codon usage (Nc≥61)

Gene2

Wright, F. (1990). "The 'effective number of codons' used in a gene." Gene 87(1): 23-9.

Codon usage bias is correlated with translation efficiency

r=-0.79 (p<0.001)

Mutation pattern(neutral)

Selection

Codon bias

But not in all species(e.g. A. gossypii)

r=-0.48 (p=0.218)

Mutation pattern(neutral)

Selection

Codon bias

S. cerevisiae S. bayanus C. glabrata A. gossypii D. hansenii C. albicans Y. lipolytica S. pombe

r -0.79 -0.73 -0.79 -0.48 -0.75 -0.65 -0.84 -0.66

p <0.001 <0.001 <0.001 0.218 <0.001 0.005 <0.001 <0.001

Translation selection acts in some but not all species (e.g. debate on human…)

Correlation does not imply causality!!

r=0.63

Predicted translation efficiency

Mea

sure

d pr

otei

n ab

unda

nce

(Ghaemmaghami et al. Nature 2003)

Evolutionary

Physiological

Z