A genome-wide perspective on translation of proteins

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Dec 2012. Regulatory Genomics. Lecturer: Prof. Yitzhak Pilpel. Teaching assistant: Idan Frumkin. idan.frumkin@weizmann.ac.il. Submit Sunday at midnight. The Central Dogma of Molecular Biology. Expressing the genome. ID: 634845 Download Presentation

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A genome-wide perspective on translation of proteins




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Presentations text content in A genome-wide perspective on translation of proteins

Slide1

A genome-wide perspective on translation of proteins

Dec 2012Regulatory GenomicsLecturer: Prof. Yitzhak Pilpel

Slide2

Teaching assistant: Idan Frumkin

idan.frumkin@weizmann.ac.ilSubmit Sunday at midnight

Slide3

The Central Dogma of Molecular Biology

Expressing the genomeDNA

mRNA

Protein

f

f

Inactive

DNA

RNA

Slide4

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

In the presence of Lactose

The Lac Operon (Jacob and Monod)

4

Slide5

Catabolism (breakdown of molecules, e.g. lactose)

Anabolism (synthesis of molecules, e.g. amino acids)Gene is ON when substrate is presentGene 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

Slide6

A combined transcription -translation control switch

At the Attenuation mechanismCharles Yanofsky

Slide7

The trp operon in

e. coli

Slide8

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

Slide9

How not to make too much triptophene?

A fail safe mechanism complements transcription controlAt the translation level!

Slide10

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

Slide11

The various palindromic pairings

1-2, and 3-4

2-3

Transcription

terminator!

Not a

terminator!

Slide12

High Trp

Low

Trp

The structure of the Attenuation switch

Ribosome

Ribosome

RNA pol

RNA pol

Slide13

Could that be implemented in eukaryotes as well?

No! because requires co transcription-translation

Slide14

Where does translation take place?

Slide15

Spatial organization of the flow of genetic

information in bacteria (Llopis Nature 2010)

DNA

=DNA

=mRNA

=Protein

Slide16

Translation consists of initiation, elongation and termination

5’

3’

STOP

Codon

Anti-codon

Slide17

The dynamics of translation

Slide18

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

genetic codeSome important properties of the codeThe 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

Slide19

The tRNA

The generic form

A specific form

In 3D

Slide20

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)

Slide21

The 20 canonical amino acids

Slide22

Possible mechanisms of translational regulation

optimality of ribosomal attachment sitemRNA secondary structurecodon usage

Slide23

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

Slide24

G T R Y E C Q A S F D

C1C1C1C1C1C1C1C1C1C1C1C2C2C2C2C2C2C2C2C2C2C2

C1C1

C2

C1C1

C2

C1C1

C2

C1C1

C2C2C2C2

C1C1C1C1C1C1C1

C1C1C1C1C1C1C1

C2C2C2C2

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??

Slide25

The codon bias in genomes

Slide26

Two potential types of sources for codon bias

Mutation pattern

(neutral)

Selection

Codon bias

Slide27

The effect of (or on?) GC content

Nucleotide composition

Codon bias

Coding

Coding

Inter-

genic

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

Mutation

pressure

Selection

Amino acid

composition

Slide28

Selection of codons might affect:

Accuracy

Throughput

Costs

Folding

RNA-structure

Slide29

AAA

CCA

GAA

UCG

AAG

A simple model for translation efficiency

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

5’

3’

Slide30

The same protein can be encoded in many ways…

amino acid sequence: M

P

KSNFRFGE

ATG

ATG

CCT

ATG

CCC

ATG

CCA

ATG

CCG

most efficient

least efficient

intermediate efficiency

intermediate efficiency

relative concentration of tRNA in the

cell

1

0

5

0

Slide31

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

6

tRNA

Gene copies

(

dos Reis et al.

Nucleic Acids Res

, 2004)

Slide32

W

i

/W

max

if

W

i

0

w

i

=

w

mean

else

{

dos Reis et al.

NAR

2004

The tRNA Adaptation Index (tAI)

ATC

CCA

AAA

TCG

AAT

A simple model for translation efficiency

Wobble Interaction

Slide33

Correlation of tAI with experimentally determined protein levels

r=0.63

Predicted translation efficiency

Measured protein abundance

(Ghaemmaghami et al.

Nature 2003)

Physiological

Slide34

The correlation is quite high, but why not even higher?

The limitations of the modeltRNA gene copy numbers Model only capture elongationDifference in mRNA levelsProtein are also degraded at different rates

Slide35

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

AA

.

.

.

Gly

Gly

Gly

Gly

.

.

.

codon

.

.

.

GGT

GGC

GGA

GGG...

Codon count

.

..01200..

.

Highly biased synonymous codon usage (Nc=20)

Gene1

AA

.

.

.

Gly

Gly

Gly

Gly

.

.

.

codon

.

.

.

GGT

GGC

GGA

GGG

.

.

.

Codon count

.

.

.

3

3

3

3

.

.

.

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.

Slide36

Codon usage bias is correlated with translation efficiency

r=-0.79 (p<0.001)

Mutation pattern

(neutral)

Selection

Codon bias

Slide37

But not in all species

(e.g. A. gossypii)

r=-0.48 (p=0.218)

Mutation pattern

(neutral)

Selection

Codon bias

Slide38

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…)

Slide39

Correlation does not imply causality!!

r=0.63

Predicted translation efficiency

Measured protein abundance

(Ghaemmaghami et al.

Nature 2003)

Physiological

Evolutionary

Physiological

Z


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