Recombination and genome evolution – Recombination and selection Sylvain Glémin Institut des Sciences de l’Evolution - Montpellier [email protected]

Recombination and genome evolution – Recombination and selection

Sylvain GléminInstitut des Sciences de l’Evolution - [email protected]

Introduction

Recombination: (mostly) universal Key role in genetic process genome

evolution Variations in patterns of recombination

Between species (sexual/asexual, outcrossing/selfing,…)

Between genomic compartments (nuclear/organelles)

Between chromosomes (sexual/autosomes, size,…) Along chromosomes (recombination gradients,

hotspots,…)

Introduction

Direct effects of recombination Possible mutagenic effects Genic conversion

At the initiation sites (see Hotspot paradox, Boulton et al. 1997)

At flanking regions [gBGC, see L. Duret’ lecture]

Indirect effects of recombination Crossing-over: mixing alleles between

genes

Outline

I. Effects of genetic linkage on selection: general predictions

II. Evolution of non-recombining genomic regions: the example of mtDNA

III. The surprising effects of gBGC on selection

IV. Using genomes to study breeding system evolution

I. Effects of genetic linkage on selection: general predictions

I.1 Recombination and linkage disequilibriumI.2 Genetic hitch-hiking effectsI.3 Consequences for genomic patterns

I.1 Recombination and linkage disequilibrium LD: non-random

association between alleles at two (or more) loci

f(AB) = f(A)f(B) +D f(Ab) = f(A)f(b) – D f(aB) = f(a)f(B) – D f(ab) = f(a)f(b) + D

b

b

B

B

A

a

A

a

I.1 Recombination and linkage disequilibrium LD: non-random

association between alleles at two (or more) loci

Created by Drift Selection Population structure …

Removed by Recombination (Mutation)

f(AB) = f(A)f(B) +D f(Ab) = f(A)f(b) – D f(aB) = f(a)f(B) – D f(ab) = f(a)f(b) + D

b

b

B

B

A

a

A

a

Genomic patterns of linkage disequilibrium

Maize (Outcrosser)

Arabidopsis thaliana(selfer)

(Remington et al. 2001)

(Nordborg et al. 2005)

I.2. Genetic hitch-hiking effects

“The hitch-hiking effect of a favorable gene” (Maynard-smith and Haig, 1974)

Two-locus dynamics Genotypes: AA Aa aa BB Bb

bbFitness: 1 1+s 1+2s1 11

A aa

p p sp

W

b

Dsp

W

The different forms of genetic hitch-hiking effects

Strongly advantageous Mildly deleterious Weakly deleteriousWeakly advantageous Neutral

Genetic drift of haplotypes

Hill-Robertson interferenc

e

Loss of advantageous mutations

(Hill & Robertson 1966)





e


Selection of strongly advantageous mutations

Selective sweep

Loss of polymorphism and fixation of weakly deleterious mutations

(Hill & Robertson 1966)(Maynard-

Smith & Haig 1974)





e



Selective sweep


Random loss (by drif) of crhomosomes free of

mutation

Muller’s ratchet

Accumulation of deleterious mutations


Smith & Haig 1974)

(Muller 1932)





e



Selective sweep


Random loss (by drif) of crhomosomes free of

mutation

Muller’s ratchet

Accumulation of deleterious mutations

Selection against deleterious mutations

Background selection

Loss of neutral and weakly advantageous

variants


Smith & Haig 1974)

(Charlesworth et al. 1993)(Muller 1932)

Hitch-hiking effects: formalisation

Roughly equivalent to reducing effective size


Neutral alleles

Deleterious allele

Background selection

time


Roughly equivalent to reducing effective size Background selection (Charlesworth et al. 1993)

Ne = Nf0 avec f0 = exp(-U/s) (haploid)


Advantageous allele

Neutral alleles

Deleterious allele

Neutral alleles

Background selection Selective sweep

time time


Roughly equivalent to reducing effective size Background selection (Charlesworth et al. 1993)

Ne = Nf0 avec f0 = exp(-U/s) (haploid) Recurrent selective sweep (genetic draft)

(Gillespie 2000)

Ne = N/(1+2Nρ) Rq: for some processes the effect of draft cannot

be simply summarized by an effect on Ne

I.3 Consequences for genomic patterns Neutral mutations (synonymous, introns,…)

Polymorphism π = 4Neµ Divergence D = µT

Indirect effects

Direct effects

I.3 Consequences for genomic patterns Neutral mutations (synonymous, introns,…)

Polymorphism π = 4Neµ Divergence D = µT

Selected mutations (non-synonymous, regulatory sequences,…) Polymorphism π = 4Nefnµ + πweak selection

Divergence D = µTfn + Dweak selection + Dadvantageous

Indirect effects

Direct effects

Indirect effects

Interaction between selection and drift

3 2 1 1 2

1

2

3

4

S = 4Nes

Dn/Ds

n/s

Low recHigh rec High rec

( )1 S

SF S u

e

Substitution rate

Summary of predictions

πn/πS

πS/DS

rec

rec

rec

Dn/DS Stabilizing

selectionPositiv

e selectio

n

Recombination and genomic patterns: polymorphism

(Nordborg et al. 2005)

C. elegans A. thaliana

Significant effect after controlling for divergence

(Cutter et al. 2003)

Recombination and genomic patterns: polymorphism

(Hellmann et al. 2003)

Human: an example of the confounding effects of recombination

Recombination and genomic patterns: Dn/Ds

(Bullaughey et al. 2008)

Human/chimp divergence

Recombination classes

Dn/Ds per classes

Recombination and genomic patterns: Dn/Ds

~ 7600 genes Recombination

classes High Intermediate Low NA: no recombination N4: 4th chromosome

D. melanogaster/ D. yacuba divergence

(Haldrill et al. 2007)

NO

Summary

Globally: weak effects of recombination gradients

Strong contrast between recombining and non-recombining regions

Weak recombination is sufficient to counteract Hill-Robertson effects (if c/u > 1)

II. Evolution of non-recombining genomic regions:the example of mtDNAII.1 mtDNA characteristics and classical

assumptionsII.2 Patterns of mtDNA polymorphism in animalsII.3 The genetic draft hypothesis

II.1 mtDNA characteristics and classical assumptions

Mitochondrial genome in animals Small genome ~13 to 20 kb Non-recombining High gene density High mutation rates

Classical assumptions Strong purifying selection Observed polymorphism ~neutral Good marker for molecular biodiversity

II.1 mtDNA characteristics and classical assumptions

Tests of these assumptions Does mtDNA polymorphism correlate with

Ne through life history/ecological traits effects

~ Ne .

demography

structure

selection

Life history traitsEcological traits

II.2 Patterns of mtDNA polymorphism in animals The Polymorphix data base (Bazin et al.

2005)

Homologous sequences within species + outgroups

Several homology criteria

Database cleaning Remove genome projects, transposons,

specific genes (MHC, rRNA,…) Manually check highly polymorphic genes

II.2 Patterns of mtDNA polymorphism in animals Data set available in Polymorphix

mtDNA ~1350 species nucDNA ~100 species

Allozyme diversity (Nevo et al. 1984) ~750 species

Computation of s

Average over loci within species Average over species within taxa / ecological

groups Comparison with allozimic diversity

Global comparison

synonymo

us

Allozyme heterozygosity

Vertebrates Invertebrates

(Bazin et al. 2006)

nucDNA

Global comparison

synonymo

us

Allozyme heterozygosity

Vertebrates Invertebrates

(Bazin et al. 2006)

mtDNA

nucDNA

Life history traits and diversity

Crustaceans

Branch.Dec.

0.30

H

Allozymes Allozymes

0.40

H

continent marine

Molluscs

Allozymes

Fishes

H

0.08

***

*

(Bazin et al. 2006)

Fresh-watermarine

Life history traits and diversity

Crustaceans

Branch.Dec. Branch.Dec.

0.10

s

0.30

H

Allozymes mtDNA ADNmtAllozymes

0.400.08

sH

continent marine continentmarine

Molluscs

ADNmtAllozymes

Fishes

H s

0.08 0.08

***

*

Fresh-watermarine

(Bazin et al. 2006)

Fresh-watermarine

II.3 The genetic draft hypothesis(Gillespie 2000, 2001)

Advantageous mutationsNeutral alleles

Recurrent selective sweeps

temps

1 1 0 1 0 0 1 0 0 0 1 0 4 1 0 5 1 0 6

1 0

1 0 0

1 0 0 0

1 0 4

1 0 5

1 0 6

DraftzoneDrift zone

N

Ne Pure drift

Continuous adaptation

Ne = N / (1+ 2N)

Signature of positive selection on mtDNA

(Bazin et al. 2006)

Neutrality index: NI = (N / S) / (dN / dS)

Vert. Invert. Vert. Invert.

mtDNA nuclear DNA

0

1

5

10

NI (log scale)

adaptative

purifying

neutral


(Bazin et al. 2006)



mtDNA nuclear DNA

0

1

5

10

NI (log scale)

adaptative

purifying

neutral


(Bazin et al. 2006)



mtDNA nuclear DNA

0

1

5

10

NI (log scale)

adaptative

purifying

neutral

The effect of draft on the whole mtDNA genome

(Bazin et al. 2006)

Complete mitochondrial genomes:

Groups of closely related species (max dS < 50%)

Patterns of selection on the whole mtDNA genome

Recurrent selective sweeps in large population Fixation of weakly

deleterious alleles (dN/dS)


Selective sweep


(Maynard-Smith & Haig

1974)

Summary

Importance of linkage in the evolution of mtDNA Classical assumptions

Strong purifying selection + recurrent positive selection Observed polymorphism ~neutral but not related to global

Ne

Good Bad marker for molecular biodiversity What is mtDNA (in large populations) adapting to ?

Metabolism adaptations? Selfish genes? (two-level selection) Cyto-nuclear interactions Association with maternal-inherited endosymbionts

(Wolbachia,…) …?

III. The surprising effect of gBGC on selection

III.1 The population genetics of gBGC/selection interferenceIII.2 The fitness consequences of gBGC

II.1 The population genetics of gBGC/selection interference gBGC ~ meiotic distortion: formally

equivalent to genic selection for GC alleles (Nagylaki 1983) pGC = pGC (1 – pGC)b Selection: p = p (1 – p)s / W (W ~ 1)

(Normalized) substitution rates Selection alone

gBGC alone B = 4Neb

gBGC + selection( )1 B S

B SF

e

1 B

BF

e

Indirect effects

Direct effects

1 S

SF

e

gBGC/selection: substitution rates

1 S

SF

e

3 2 1 1 2

1

2

3

4

S = 4Ne s


( )1 B S

B SF

e

1 S

SF

e

3 2 1 1 2

1

2

3

4

S = 4Ne s

GC AT mutations (B < 0)

gBGC helps purging deleterious mutations


( )1 B S

B SF

e

1 S

SF

e

3 2 1 1 2

1

2

3

4

S = 4Ne s

AT GC mutations (B > 0)

gBGC contribute to fixing deleterious mutations


3 2 1 1 2

1

2

3

4

S = 4Ne s

Fixation > purging

Achilles’ heel (Galtier and Duret 2007)

gBGC/selection: from dominance to overdominance

(Partially) recessive deleterious ATGC mutations Genotypes: WW WS SS Fitness: 1 1- hs 1 – s gBGC: 1 - b 1 1 + b Total effects: 1 – b 1 – hs 1

+ b – s If hs < b < (1 – h)s : overdominance-like

dynamics

III.2 The fitness consequences of gBGC Fixation of weakly deleterious GC alleles

Increases Dn/Ds: false signature of relaxed or positive selection [see L. Duret’s lecture]

GC-associated fixation load Increase in the frequency and ages of

GC deleterious alleles Increases the frequency of genetic diseases Increases deleterious standing variation

inbreeding depression

The gBGC-associated load

106 105 104 0.001 0.01 0.1s

0.1

1

10

100

load

Genetic structure of the load (without gBGC)

L = 1 - W


106 105 104 0.001 0.01 0.1s

0.1

1

10

100

load


L = 1 - W

Load due to segregating mutations

L = 2u


106 105 104 0.001 0.01 0.1s

0.1

1

10

100

load


L = 1 - W


L = 2u

Load due to fixed mutations

L = s

Fixed mutations but nearly

neutral


106 105 104 0.001 0.01 0.1s

0.1

1

10

100

load


L = 1 - W


L = 2u

Load due to fixed mutations

L = s

~ 1/Ne

Fixed mutations but nearly

neutral

Most damaging ones


1 0 6 1 0 5 1 0 4 0 .0 0 1 0 .0 1 0 .1s

0 .1

1

1 0

1 0 0

load

N = 100 000

N = 50 000

N = 10 000

N = 5 000

(x10-6)

Whithout gBGC

The load is higher in small populationsMost damaging mutations ~ 1/Ne

(Glémin submitted)


1 0 6 1 0 5 1 0 4 0 .0 0 1 0 .0 1 0 .1s

0 .1

1

1 0

1 0 0

load

1 0 6 1 0 5 1 0 4 0 .0 0 1 0 .0 1 0 .1s

0 .1

1

1 0

1 0 0

load

N = 100 000

N = 50 000

N = 10 000

N = 5 000

(x10-6) (x10-6)

Whithout gBGC With gBGC (b = 0.0002)

~ 2b

The load is higher in small populationsMost damaging mutations ~ 1/Ne

The load is independent of Ne

Most damaging mutations ~ 2b

(Glémin submitted)


(Glémin submitted)

Drift loadgBGC

fixation loadSegregating load

s0 ~2b~1/2N

Structure of the load with gBGC

Large population size

Small population size

Quantification of the load

Without gBGC With gBGC-1 With gBGC-2

N = 10 000 0.634 0.689 0.865N = 50 000 0.143 0.301 0.708N = 100 000 0.074 0.248 0.687

Load

1: 3% of gBGC hotspot with b = 0.0002 (Human data, e.g. Spencer et al. 2006)2: 5% of gBGC hotspot with b = 0.0005

(Glémin submitted)

Gamma distribution of fitness effectsMean = 0.03 shape = 0.2 (Human data, e.g. Eyre-Walker et al. 2006)

IV. Using genomes to study breeding system evolution

IV.1 The genetic consequences of selfing and the “dead-end hypothesis”IV. 2 An integrated test of the “dead-end hypothesis” in TriticeaeIV.3 gBGC: another cost of outcrossing ?

IV.1 The genetic consequences of selfing and the “dead-end hypothesis” SelferOutcrosser

Effective size

- Sampling- + ecology 2N gametes

Heterozygosity

N individuals

Effective recombination

~ 0

~ 0

Genomic consequences of selfing

Reduced Ne and re

Low polymorphism levels Low S

High LD Weak efficacy of selection

Increase in DN/DS and N/S

- Low adaptive potential- Accumulation of deleterious alleles

Evolutionary dead-end?(Stebbins 1957)

Genomic consequences of selfing

Reduced Ne and re

Low polymorphism levels Low S

High LD Weak efficacy of selection

Increase in DN/DS and N/S

High homozygosity gBGC ineffective

- Low adaptive potential- Accumulation of deleterious alleles

Evolutionary dead-end?(Stebbins 1957)

GC marker of selfing evolution ?

The effect of selfing on patterns of polymorphism in plant

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

Allozymes(Hamrick & Godt1990)

Microsatellites(Nybom2004)

Sequence(Gléminet al. 2006)

Outcrossers Selfers

He

He

S(x 10)

p= 0.002n= 108

p -value Allogames Autogames

r² 0.014 0.401 0.561 = 4Nec 0.049 6.24 1.55

n

9686

LD patterns

(Glémin et al. 2006)

The effect of selfing on patterns of polymorphism in plant

0n

s

πf =

πWeakly deleterious mutations


Lower selection efficacy in selfers ?

IV.2 An integrated test of the “dead-end hypothesis” in Triticeae

19 species 10 outcrossers

9 selfers

27 genes 21 along one

chromosome (strong recombination gradient) (Akhunov et al. 2003)


19 species 10 outcrossers

9 selfers

27 genes 21 along one

chromosome (strong recombination gradient) (Akhunov et al. 2003)


Variations between selfing and outcrossing branches Dn/Ds GC*

Variations along the recombination gradient Dn/Ds GC*

S. cereale

Ae. speltoides

T. monococcum

T. urartu

H. vulgare

S. cereale

Ae. speltoides

T. monococcum

T. urartu

H. vulgare

S. cereale

Ae. speltoides

T. monococcum

T. urartu

H. vulgare

S. cereale

Ae. speltoides

T. monococcum

T. urartu

H. vulgareModel 1

Model 0

Mating systems have no effect…

(Escobar et al. soumis)

… but recombination does

rspearman= -0.47, p = 0.03 rspearman= 0.41, p = 0.04

(Escobar et al. soumis)

The tempo of selfing evolution in Triticeae

Strong and stable recombination gradient

Very recent transition to selfing Similar results in Arabidopsis (Wright et al.

2002) and Caenorhabditis (Cutter et al. 2008) [Dn/Ds, Codon usage]

?


p = 0.03

Analyses of a single transition 52 genes

S. cereale

Ae. speltoides

T. monococcum

T. urartu

H. vulgare

(Haudry et al. 2008)

GC GC*

Outcrossers 0.473 0.453

Selfers 0.3530.471

GC* marker of the shift to selfing…


p = 0.03

Analyses of a single transition 52 genes

S. cereale

Ae. speltoides

T. monococcum

T. urartu

H. vulgare


GC GC*

Outcrossers 0.473 0.453

Selfers 0.3530.471

… but still no effect of selfing on Dn/DsDn/Ds

Outcrossers 0.150

Selfers 0.105p > 0.03

GC* marker of the shift to selfing…

IV.3 gBGC: another cost of outcrossing? gBGC: probably strong in grasses Achilles’ heel in outcrossing grasses ?

Poaceae Others

GC


Test of the Achilles’ heel hypothesis

S. cereale

Ae. speltoides

T. monococcum

T. urartu

H. vulgareTwo classes of genes-GC* < 0.45 (median)-GC* > 0.45

ωself

ωout

GC* < 0.45 GC* > 0.45

ωself0.111 0.099

ωout0.126 0.180

p-value 0.664 0.032


Conclusion

Several evidences of recent origin of selfing (Triticées, Medicago, Polemoniaceae,…)

But no (or few) evidence of genomic degradation

Conclusion

Differences between selfing/asexual lineages

Taxonomic group Groups compared Dataset dN/dS N/S

Angiosperms 29 selfers / 42 outcrossers Meta-analysis (polymorphism) +/-Arabidopsis 1 selfer / 1 outcrosser 23 nuclear genes + 1 chloroplastic gene -Caenorhabditis 2 selfers / 4 outcrossers > 1000 nuclear genes -Triticeae 2 selfers / 2 outcrossers 52 nuclear genes + 1 chloroplastic gene -Rotifers 3 asexuals / 2 sexuals Hsp82 -

3 asexuals / 4 sexuals Cox I +/- +Campeloma 6 asexuals / 12 sexuals Cytb +Daphnia 14 asexuals / 14 sexuals Complete mitocondrial genome +

Outcrossing/Selfing

Sexuals/Asexuals

Conclusion

Differences between selfing/asexual lineages

Recombination

Segregation

Asexuality Selfing

Outcrossing

Effective population size

General conclusion Effects of recombination on selection

Through crossing-over: hitch-hiking effects Through gBGC

Genomic approaches to understand recombination and breeding system evolution

Open questions Drift vs draft Extinction of self-fertilizing species? Role of gBGC in the evolution of genetic systems

(recombination, breeding systems) Evolution of gBGC

Documents

Recombination and genome evolution – Recombination and selection Sylvain Glémin Institut des Sciences de l’Evolution - Montpellier [email protected]