Adaptationism%20and%20the%20Adaptive%20Landscape

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Adaptationism and the Adaptive Landscape

• Genomic imprinting, mathematical models, and
  notions of optimality in evolution

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Overview

• Adaptationism
• Zoom and Grain in the adaptive landscape
• Mathematical models of genomic imprinting

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Adaptationism

• Primary role for natural selection in evolution
• versus drift, historical and developmental
  constraints, etc.
• Modern debate framed by the Sociobiology wars
  (Wilson, Dawkins, Lewontin, Gould, etc.)
• Continuation with Evolutionary Psychology, but
• Partial reconciliation in most fields
• Tests of selection, contemporary systematics

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Types of adaptationism

• Empirical
• Central causal role for selection
• Explanatory
• Selection answers the big questions
• Methodological
• Selection is a good organizing concept
• Godfrey-Smith (2001)

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The Adaptive Landscape

• Natural selection is conceived of as a
  hill-climbing algorithm

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Caveats

• Units (genotype vs. phenotype, population vs.
  individual fitness)
• High dimensionality
• Topology of the landscape
• Dependence on other organisms
• Hill-climbing metaphor implies a deterministic
  process

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Zoom level 1

• High level analyses invoke rugged landscapes,
  which emphasize the role of historical contingency

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Zoom level 2

• Intermediate levels of analysis focus on local
  regions with a small number of peaks, emphasizing
  optimization

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Zoom level 3

• Low-level analyses reveal the discontinuities in
  the fitness landscape, emphasizing drift,
  recombination, etc.

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Zoom level 3

• Low-level analyses reveal the discontinuities in
  the fitness landscape, emphasizing drift,
  recombination, etc.

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Sickle-cell anemia

• HbA / HbA
• Susceptible
• HbA / HbS
• Resistant
• HbS / HbS
• Sickle-cell

Resistant parents
Susceptible
Resistant
Sickle-cell
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Population-genetic timescale
HbA / HbS
HbA / HbA
HbS / HbS
100 generations

• Mendelian segregation recreates sub-optimal
  phenotypes every generation

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Mutation timescale
HbA HbS
HbA
104 generations

• The mutation giving rise to the HbS allele
  represents a partial adaptation to malaria

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Chromosomal rearrangement timescale
108 generations

• A (hypothetical) rearrangement could give rise to
  a single chromosome containing both the HbA and
  HbS alleles. This new allele should sweep to
  fixation.

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Immune-system evolution timescale
IgM IgA IgG IgE
HbAS
Ig-??
HbA HbS
HbA
1010 generations

• In principle, we could ask why our immune system
  is susceptible to malaria at all.

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Genomic Imprinting

• Non-equivalence of maternal and paternal genomes
• Normal development in mammals requires both

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Genomic Imprinting
Oogenesis
Spermatogenesis

• Epigenetic differences result in differences in
  expression
• DNA methylation
• reversible chemical modification of the DNA

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Reciprocal heterozygotes are non-equivalent
?
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Conflict over resources
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Asymmetries in relatedness
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Conflict over resources
Growth-enhancing locus
Unimprinted gene
Cis-acting maternal modifiers
Maternal expression
Maternal optimum
Cis-acting paternal modifiers
Paternal optimum
Paternal expression
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Conflict over resources
Growth-suppressing locus
Unimprinted gene
Cis-acting maternal modifiers
Maternal expression
Paternal optimum
Cis-acting paternal modifiers
Maternal optimum
Paternal expression
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Game-theoretic / stability analysis models of
imprinting

• X - expression level
• Wm - matrilineal fitness
• Wp - patrilineal fitness
• U - individual fitness
• V - fitness of other offspring
• G - resource demand
• C - cost of gene expression
• 2p - fraction of mothers offspring with the same
  father

Growth enhancer
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Population-genetic models

• Two sibs, paternal imprinting
• A - unimprinted allele
• a - imprintable allele
• a A when maternally inherited
• a -gt (a) when paternally inherited
• AA aA
• a(a) A(a)

• Fitness of unimprinted sibs 1
• e.g., AA, AA
• Fitness if both imprinted 1u
• e.g., a(a), A(a)
• If only one is imprinted
• e.g., AA A(a)
• Imprinted fitness 1-s for A(a)
• Unimprinted fitness 1t for AA

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Population-genetic models

• Parameters allele frequencies, fitnesses,
  frequency of multiple paternity
• Spencer, Feldman, and Clark 1998 Genetics

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Population-genetic models

• Two sibs, paternal imprinting
• A - unimprinted allele
• a - imprintable allele
• a A when maternally inherited
• a -gt (a) when paternally inherited
• AA aA
• a(a) A(a)

• Fitness of unimprinted sibs 1
• e.g., AA, AA
• Fitness if both imprinted 1u
• e.g., a(a), A(a)
• If only one is imprinted
• e.g., AA A(a)
• Imprinted fitness 1-s for A(a)
• Unimprinted fitness 1t for AA
• Monandrous females
• a invades A if u gt s
• a stable if u gt t/2
• Polyandrous females
• a invades A if s lt 0
• a stable if u gt t/2

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Predictions and contradictions

• Game-theoretic
• Imprinting requires multiple paternity (p lt 1/2)
• Allele favoring lower expression will be
  completely silenced
• maternal silencing of growth enhancers
• paternal silencing of growth suppressors

• Population-genetic
• Particular combinations of s, t, and u can
  produce stable polymorphisms
• Multiple paternity is not required
• Maternal silencing for growth enhancers is more
  likely, but paternal silencing can occur

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Paternally silenced growth enhancer
Growth-enhancing locus
Unimprinted gene
Cis-acting maternal modifiers
Reduced paternal expression would be favored
from these points
Maternal expression
Cis-acting paternal modifiers
Maternal optimum
Paternal optimum
Paternal expression
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Key assumption

• Game-theoretic models assume that the unimprinted
  expression level is at its optimum before the
  introduction of an imprinted allele
• Is this assumption a good one?
• Gene expression array analyses of
  population-level variation reveal a high level of
  variation
• This implies a good opportunity for selection to
  find the optimum

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Separation of timescales in the evolution of
imprinting
Imprinting opens up a new dimension in strategy
space
Unimprinted alleles are restricted to a subspace
in the fitness landscape
If mutations that quantitatively change gene
expression are much more common than those that
give rise to imprinting, imprinting will always
arise in the context of an optimized expression
level
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Take-home message

• Choice of a particular modeling framework implies
  certain assumptions that can affect your
  interpretation of your results
• When smart people doing reasonable things
  disagree, there is probably something interesting
  going on