evidence of selection on genomic gc content in bacteria falk hildebrand adam eyre-walker

Evidence of Selection on Genomic GC Content in Bacteria

Falk Hildebrand

Adam Eyre-Walker

Genomic G+C content

Genomic GC content

Codons

GCT123

ATA CCCCTA CCT

Non-synonymous

Synonymous

2-fold : TTT TTC

4-fold : CCT CCC CCA CCG

Genomic GC content

Variation

Correlations

Explanations

• Mutation bias• Suoeka (1961) & Freese (1962)• Intrinsic and/or extrinsic

• Selection• Many authors

• Biased gene conversion• Anonymous referees

Correlates

• Genome size• positive correlation

• Lifestyle• higher GC in free living

• Aerobiosis• higher GC in aerobic

• Nitrogen utilization• higher amongst N fixers

• Temperature • higher amongst thermophiles?

Evidence of selection I

• Escherichia coli• Mutation pattern

• 273 GCAT versus 131 ATGC

• Predicted GC content = 0.32• Observed GC content = 0.50• Observed GC at neutral sites = 0.58

Lynch (2007) Origins of genome architecture

Evidence of selection II

• Phylogenetic analyses• Mycobacterium leprae (Lynch 2007)• Escherichia coli (Balbi et al. 2009)• 5 pathogenic bacteria (Hershberg and

Petrov 2010)

Phylogenetic analysis

G A A G G G

Evidence of selection II

• Phylogenetic analyses• Mycobacterium leprae (Lynch 2007)• Escherichia coli (Balbi et al. 2009)• 5 pathogenic bacteria (Hershberg and

Petrov 2010) • Excess of GC AT

Test of mutation bias

• If GC content is• Due to mutation bias alone• Stationary• And the infinite sites assumption holds

• Then• # GCAT mutations = # ATGC mutations

Why?

• If GC stationary

• #GCAT subs = #ATGC subs

• All neutral mutations have same chance of fixation

• #GCAT muts = #ATGC muts

Identifying mutations

Strain 1 ACT GCT TTG GCT TTA TGGStrain 2 ACT GCT TTG GCT TTA TGAStrain 3 ACT GCT TTG GCT TTA TGGStrain 4 ACT GCT TTC GCT TTA TGAStrain 5 ACC GCT TTC GCT TTA TGGStrain 6 ACT GCT TTG GCT TTA TGG

TC CG GA

Orienting mutations

Outgroup ACT GCT TTC GCT TTA TGGStrain 1 ACT GCT TTG GCT TTA TGGStrain 2 ACT GCT TTG GCT TTA TGAStrain 3 ACT GCT TTG GCT TTA TGGStrain 4 ACT GCT TTC GCT TTA TGAStrain 5 ACC GCT TTC GCT TTA TGGStrain 6 ACT GCT TTG GCT TTA TGG

TC CG GA

GCAT = 1ATGC = 1

Orienting mutations

Strain 1 ACT GCT TTG GCT TTA TGGStrain 2 ACT GCT TTG GCT TTA TGAStrain 3 ACT GCT TTG GCT TTA TGGStrain 4 ACT GCT TTC GCT TTA TGAStrain 5 ACC GCT TTC GCT TTA TGGStrain 6 ACT GCT TTG GCT TTA TGG

TC GC GA

GCAT = 1ATGC = 1

Test of mutation bias

• If GC content is• Due to mutation bias alone• Stationary• And the infinite sites assumption holds

• Then• # GCAT = # ATGC

Four-fold synonymous sites

Codons

GCT123

ATA CCCCTA CCT

Non-synonymous

Synonymous

2-fold : TTT TTC

4-fold : CCT CCC CCA CCG

Data

• Popset• Keyword “bacteria”• 8 or more sequences from same species• 149 bacterial species

• 8 phyla, 15 classes and 77 genera• 1 or more genes• 10 or more synonymous polymorphisms• 4-fold diversity < 0.1

Overall result

No. of SNPs

GCAT 11045

ATGC 8309

P<0.0001

Bias versus GC4

Z = GCAT

GCAT

No. species Z > 0.5 P-value

GC-rich 82 69 <0.0001

GC-poor 67 25 0.050

Phylogenetic distribution

Phylum Class No. of species GC4 range Mean Z

(GC4<0.34)

Mean Z

(GC4>0.34)

Actinobacteria Actinobacteria 3 0.64-0.93 no species 0.64

Bacteroidetes Bacteroidetes 3 0.12-0.46 0.43 0.36

Chlamydiae+ Chlamydiae 2 0.21-0.30 0.45 no species

Cyanobacteria Chroococcales 2 0.38-0.51 no species 0.53

Cyanobacteria Nostocales 3 0.26-0.31 0.45 no species

Cyanobacteria Oscillatoriales 2 0.41 no species 0.38

Cyanobacteria Stigonemales 1 0.40 no species 0.59

Firmicutes Bacilli 27 0.085-0.68 0.44 0.58

Firmicutes Clostridia 5 0.050-0.28 0.34 no species

Proteobacteria Alphaproteobacteria16 0.099-0.94 0.43 0.65

Proteobacteria Betaproteobacteria6 0.66-0.96 no species 0.67

Proteobacteria delta/epsilon6 0.15-0.99 0.49 0.78

ProteobacteriaGammaproteobacteria

62 0.095-0.95 0.50 0.66

Spirochaetes Spirochaetes 7 0.12-0.60 0.45 0.54

Tenericutes Mollicutes 4 0.023-0.24 0.33 no species

Potential problems

• Infinite sites assumption

• Sequencing error

Infinite sites assumption

• Each mutation occurs at a site which is not polymorphic

Infinite sites assumption

• If GC content stationary




Finite sites assumption

• If GC content stationary




• But some mutations not evident as poly

Finite sites

• GC rich sequence

• Implies• rate of ATGC > rate of GCAT

• Mutation rate low• #ATGC poly = # GCAT poly

• Mutation rate high• #ATGC poly < # GCAT poly

Finite sites theory

GC ATuμ

vμ

€

H(x) =J(x)

J(x)dx0

1

∫

€

J(x) = xV −1(1− x)U −1

€

U = 2Neμ(1 − f ) V = 2Neμf f = v /(u+ v)

Assume :

stationary popn stationary GC

Finite sites theory

€

H(x) =J(x)

J(x)dx0

1

∫

€

G(n,i) = H(x)Q(n,i,x)dx0

1

∫

€

Q(n,i,x) =n!

i!(n − i)!x i(1− x)n−i

Finite sites theory

0.6

0.7

0.80.90.95

Predicting Z

• Assume • finite sites• neutrality

• Use GC4 to get f

• Use observed diversity to estimate μ

• Predict Z

Z-Zpred

No. of species Z-Zpred > 0 P-value

GC-rich 82 61 <0.0001

GC-poor 67 38 0.33

Mutation rate variation

€

H(x) =J(x)

J(x)dx0

1

∫

€

G(n,i) = H(x)Q(n,i,x)dx0

1

∫

€

Q(n,i,x) =n!

i!(n − i)!x i(1− x)n−i

Z-Zpred (exponential rates)

No. of species Z-Zpred > 0 P-value

GC-rich 82 56 0.0012

GC-poor 67 46 0.003

Sequencing error

No. of species Z > 0.5 P-value

GC-rich 82 60 <0.0001

Explanations

• Non-stationary base composition

• Selection for translational efficiency

• Biased gene conversion

• Selection upon base composition

Non-stationary GC content

€

GCpred =

AT →GC

(1 −GC)

⎛

⎝ ⎜

⎞

⎠ ⎟

AT →GC

(1 −GC)+GC →AT

GC

⎛

⎝ ⎜

⎞

⎠ ⎟

Non-stationary base composition

Explanations





Selection on codon usage

Amino Acid Codon High usage Low usage

Phenylalanine UUU 0.22 0.71

UUC 0.78 0.29

Valine GUU 0.46 0.36

GUC 0.09 0.19

GUA 0.24 0.23

GUG 0.21 0.23

Translational efficiency

No. of species Z > 0.5 P-value

GC-rich 31 29 <0.0001

Explanations





Biased gene conversion

AT

CG

AG

CT

CG

CG

Four gamete test

G AG TC A

G AG TC AC T

No recombinationRecombination


No. species Z > 0.5 P-value

GC-rich 28 19 0.087

GCAT ATGC P-value

No. of SNPs 1079 844 <0.0001


GC AT-ww

if New >> 1 BGC effectiveif New << 1 BGC ineffective


r / m p-value

GC4 -0.076 0.67

Z 0.003 0.99

Z-Zpred 0.026 0.88

GC4pred -0.115 0.52

34 species with estimate of r / mVos & Didelot (2009) ISME J.


θ r / m p-value

GC4 0.039 0.83

Z 0.11 0.55

Z-Zpred 0.18 0.30

GC4pred -0.031 0.86

€

πsr

m= 2Neu

r

m= 2Nerk

Explanations





Selection on GC content

€

H(x) =J(x)

J(x)dx0

1

∫

GC ATuμ

vμ

€

J(x) = eSxxV −1(1 − x)U −1

€

S = 2Nes U = 2Neμ(1 − f ) V = 2Neμf f = v /(u+ v)

+s -s

Selection on GC content

Selection on GC4

Selection on GC4

f = α + β GC4

f = 0.2 + 0.35 GC4

Summary

• Large excess of GCAT mutations at 4-fold sites• Particularly in GC-rich species

• Not due to• Infinite sites• Sequencing error• Translational selection• Biased gene conversion

• Therefore• Selection on GC4

Selection on genomic GC

Genomic GC

GC4

Environmental meta-genomics

Foerstner et al. (2005) EMBO Reports

Environmental meta-genomics

Correlates

• Genome size• positive correlation

• Lifestyle• higher GC in free living

• Aerobiosis• higher GC in aerobic

• Nitrogen utilization• higher GC amongst N fixers

• Temperature • higher amongst thermophiles?

Thanks

Falk HildebrandAxel Meyer

Further reading

• Hildebrand et al. (2010) PLoS Genetics

• Hershberg and Petrov (2010) PLoS Genetics

• Rocha and Feil (2010) PLoS Genetics

Protein coding sites

evidence of selection on genomic gc content in bacteria falk hildebrand adam eyre-walker

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