Adaptationism and the Adaptive Landscape Genomic imprinting, mathematical models, and notions of optimality in evolution

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

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

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)

The Adaptive Landscape Natural selection is conceived of as a hill-climbing algorithm

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

Zoom level 1 High level analyses invoke rugged landscapes, which emphasize the role of historical contingency

Zoom level 2 Intermediate levels of analysis focus on local regions with a small number of peaks, emphasizing optimization

Zoom level 3 Low-level analyses reveal the discontinuities in the fitness landscape, emphasizing drift, recombination, etc.

Zoom level 3 Low-level analyses reveal the discontinuities in the fitness landscape, emphasizing drift, recombination, etc.

Sickle-cell anemia HbA / HbA HbA / HbS HbS / HbS Susceptible Resistant parents Susceptible Resistant Sickle-cell

Population-genetic timescale HbA / HbS HbA / HbA HbS / HbS ~100 generations Mendelian segregation recreates sub-optimal phenotypes every generation

Mutation timescale ~104 generations HbA + HbS HbA The mutation giving rise to the HbS allele represents a partial adaptation to malaria

Chromosomal rearrangement timescale HbA + HbS HbA HbAS ~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.

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.

Genomic Imprinting Non-equivalence of maternal and paternal genomes Normal development in mammals requires both a1 a2 ≠ a2 a1 additional information besides DNA cloning

Genomic Imprinting Oogenesis Spermatogenesis Epigenetic differences result in differences in expression DNA methylation reversible chemical modification of the DNA gene 1 gene 2 gene 1 gene 2 stop signs gene 1 gene 2 gene 1 gene 2

Reciprocal heterozygotes are non-equivalent ≠

Conflict over resources make this better inclusive fitness first

Asymmetries in relatedness Maternal optimum Paternal optimum Growth factor expression level Inclusive fitness Fitness increases as more resources are acquired for self Fitness decreases as cost to siblings becomes too great

Conflict over resources Growth-enhancing locus Unimprinted gene Cis-acting maternal modifiers Maternal expression Maternal optimum Cis-acting paternal modifiers Paternal optimum more time explaining this one maybe have things show up piece by piece no imprinting first Paternal expression

Conflict over resources Growth-suppressing locus Unimprinted gene Cis-acting maternal modifiers Maternal expression Paternal optimum Cis-acting paternal modifiers Maternal optimum Paternal expression

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 mother’s offspring with the same father Growth enhancer:

Population-genetic models Two sibs, paternal imprinting A - unimprinted allele a - imprintable allele a = A when maternally inherited a -> (a) when paternally inherited AA = aA a(a) = A(a) Fitness of unimprinted sibs: 1 e.g., AA, AA Fitness if both imprinted: 1+u 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: 1+t for AA

Population-genetic models Parameters: allele frequencies, fitnesses, frequency of multiple paternity Spencer, Feldman, and Clark 1998 Genetics

Population-genetic models Two sibs, paternal imprinting A - unimprinted allele a - imprintable allele a = A when maternally inherited a -> (a) when paternally inherited AA = aA a(a) = A(a) Fitness of unimprinted sibs: 1 e.g., AA, AA Fitness if both imprinted: 1+u 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: 1+t for AA Monandrous females: a invades A if u > s a stable if u > t/2 Polyandrous females: a invades A if s < 0

Predictions and contradictions Game-theoretic Imprinting requires multiple paternity (p < 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

Paternally silenced growth enhancer Growth-enhancing locus Unimprinted gene Reduced paternal expression would be favored from these points Cis-acting maternal modifiers Maternal expression Cis-acting paternal modifiers Maternal optimum Paternal optimum more time explaining this one maybe have things show up piece by piece no imprinting first Paternal expression

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

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

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