How do Replication and Transcription Change Genomes?

Andrey Grigoriev

Director, Center for Computational and Integrative Biology Rutgers University

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What are we going to do?

• Observe effects of fundamental processes• Estimate their relative contribution• Link them to genome features

• Analyze nucleotide composition

How do Replication and Transcription Change Genomes?

Well, do they?

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Replication and Transcription

• textbook view

faithful reproduction machinery

• basis for selection

parental DNA fitness advantages

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Replication and Transcription

• paradox

both systematically change genomes

which they faithfully reproduce

• and they leave traces

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What is in the sequence?

• The usual – coding, regulatory regions, exons, introns,

RNAs, etc.

• Biases in nucleotide composition– Traces of organism‘s „lifestyle“– Links to genome features

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Counting nucleotides: GC Skew

sw = ([G]-[C])/([G]+[C])

• Short sequence interval (window) w• Relative excess of G vs C [-1;1]

• Plot vs % of genome position [0;100]

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0 20 40 60 80 100

0 20 40 60 80 100

position, % genome length

Simian virus 40

Haemophilis influenzae

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Cumulative Skew Diagrams

sw = ([G]-[C])/([G]+[C])

S = W sw w/L

For W adjacent windows of size w << L

S is an integral of skew function

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0 20 40 60 80 100

0 20 40 60 80 100

position, % genome length

Simian virus 40

replication origin (ori)

replication terminus (ter)

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0 20 40 60 80 100

0 20 40 60 80 100

position, % genome length

Haemophilis influenzae

replication origin (ori)

replication terminus (ter)

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Genome of Escherichia coli

position, % genome length

0 20 40 60 80 100

Terminus

Origin

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Genome of Bacillus subtilis

0 20 40 60 80 100

position, % genome length

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Genome of Borellia burgdorferi

position, % genome length

0 20 40 60 80 100

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Cumulative Skew Diagrams

• Now widely used to predict ori and ter in novel and less studied microbial genomes

• Predictions confirmed experimentally

• Constant skews over half-genomes• oriter G>C terori G<C• Strand properties change at ori and ter

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Causes: Selection vs. Mutation

• Properties of encoded proteins• Regulatory sequences

• Most pronounced in 3rd codon position• Suggests mutation, not selection pressure

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DNA single-stranded, not protected

continuous DNA synthesis

discontinuous DNA synthesismRNA synthesis

template DNA

Transcription Replication

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Most Consistent Explanation

• spontaneous deamination of C or 5-MetC

– by far the most frequent mutation (rates raise over 100-fold when DNA is single-stranded)

– fixing the mutated base during the next round of replication

– depletion of cytosines vs guanines

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Cytosine Deamination

Cytosine

Uracil

Thymine

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Replication

• Leading strand exposed in replication bubble, generation after generation

• Unusual replication models consistent with the single-strand hypothesis– adenovirus– mitochondria

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0 20 40 60 80 100

Series1Poly. (Series1)

position, % genome length

Adenovirus Replicationorigins

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Replication or Transcription

• Leading-lagging switch at ori and ter• Consistent with replication models

• Transcription often colinear with replication• Direction often changes at ori and ter

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0 20 40 60 80 100

position, % genome length

Replication vs. Transcription

HPV-16

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Replication vs. Transcription

• Comparable contribution to skew

• [G]=900, [C]=690 in the same direction

additive effect on skew• [G]=758, [C]=773 in the opposite direction

cancel each other out

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Genome of Bacillus subtilis

0 20 40 60 80 100

position, % genome length

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Diagrams „jagged“

• Sequence constraints – amino acid composition, regulatory sequences,

etc.

• Sequence inversions – swaps strands and change the skew to its

opposite between the borders of the inversion

• Horizontal transfer between species

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5‘ 3‘

A B C D A C B D

3‘5‘

Inversion

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Rearrangements in two sequenced strains of Helicobacter pylori

Colored areas under the curve correspond to inversions and translocations

cagPAI – pathogenicity island (likely horizontal transfer)

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Conclusions

• Analyze nucleotide composition• Observe effects of fundamental processes• Link them to genome features• Estimate their relative contribution

• Start asking own questions