1. Lecture 12: Effective Population Size and Gene Flow February 21, 2014

2. Midterm Survey Results uNot TOOO painful uMore in-class problems uBetter integration with lab uImprove lab lectures and orientation uImprove lab environment uMixed results on “active learning” activities in lecture uReading and discussing current papers: next year for grad students

3. Last Time uInteractions of drift and selection uEffective population size

4. Today uEffective population size calculations uHistorical importance of drift: shifting balance or noise? uPopulation structure

5. Factors Reducing Effective Population Size uUnequal number of breeding males and females uUnequal reproductive success uChanges in population size through time  Bottlenecks  Founder Effects

6. Table courtesy of K. Ritland Effective Population Size: Effects of Different Numbers of Males and Females See Hedrick (2011) page 213 for derivation

7. Elephant Seals uPractice extreme polygyny: one male has a harem with many females uExamined reproductive success of males using paternity analysis on Falkland Islands uResults:  7 harems with 334 females  32 mating males detected  What is N e ?  What if sneaky males were unsuccessful?  Assumptions? Fabiani et al. 2004: Behavioural Ecology 6: 961

8. uSmall population size in one generation can cause drastic reduction in diversity for many future generations uEffect is approximated by harmonic mean Variation of population size in different generations See Hedrick (2011) page 219 for derivation

9. Example: Effect of Varying Population Size Through Time: Golden Lion Tamarins (Leontopithecus rosalia) uNative to coastal Brazilian Rainforests uEstimated Population Censuses:  1940: 10,000  1970: 200  2000: 2,000 uWhat is current effective population size? http://en.wikipedia.org http://nationalzoo.si.edu

10. How will genetic diversity be affected in populations that have experienced bottlenecks and/or founder effects?

11. Time for an Allele to Become Fixed uUsing the Diffusion Approximation to model drift  Assume ‘random walk’ of allele frequencies behaves like directional diffusion: heat through a metal rod  Yields simple and intuitive equation for predicting time to fixation: uTime to fixation is linear function of population size and inversely associated with allele frequency

12. Drift and Heterozygosity uHeterozygosity declines over time in subpopulations uChange is inversely proportional to population size uExpressing previous equation in terms of heterozygosity: uRemembering: p and q are stable through time across subpopulations, so 2pq is the same on both sides of equation: cancels

13. uEffective population size is drastically reduced uEffect persists for a very long time uLow-frequency alleles go extinct quickly and take a long time to become fixed uReduced heterozygosity Genetic Implications of Bottlenecks and Founder Effects For small q

14. Populations Recovering from Founder Effects and Bottlenecks Have Elevated Heterozygosity uHeterozygosity recovers more quickly following bottleneck/founding event than number of alleles uRare alleles are preferentially lost, but these don’t affect heterozygosity much uBottleneck/founding event yields heterozygosity excess when taking number of alleles into account uFounder effect also causes enhanced genetic distance from source population uCalculated using Bottleneck program (http://www1.montpellier.inra.fr/URLB/bottleneck/bottleneck.html)

15. Historical View on Drift uFisher  Importance of selection in determining variation  Selection should quickly homogenize populations (Classical view)  Genetic drift is noise that obscures effects of selection uWright  Focused more on processes of genetic drift and gene flow  Argued that diversity was likely to be quite high (Balance view)

16. Genotype Space and Fitness Surfaces uAll combinations of alleles at a locus is genotype space uEach combination has an associated fitness A1A1 A2A2 A3A3 A4A4 A5A5 A1A1 A2A2 A3A3 A4A4 A5A5 A1A1A1A1 A1A2A1A2 A1A3A1A3 A1A4A1A4 A1A5A1A5 A1A2A1A2 A2A2A2A2 A2A3A2A3 A2A4A2A4 A2A5A2A5 A1A3A1A3 A2A3A2A3 A3A3A3A3 A3A4A3A4 A3A5A3A5 A1A4A1A4 A2A4A2A4 A3A4A3A4 A4A4A4A4 A4A5A4A5 A1A5A1A5 A2A5A2A5 A3A5A3A5 A4A5A4A5 A5A5A5A5

17. Fisherian View uFisher's fundamental theorem: The rate of change in fitness of a population is proportional to the genetic variation present uUltimate outcome of strong directional selection is no genetic variation uMost selection is directional uVariation should be minimal in natural populations

18. Wright's Adaptive Landscape uRepresentation of two sets of alleles along X and Y axis uVertical dimension is relative fitness of combined genotype

19. Wright's Shifting Balance Theory uGenetic drift within 'demes' to allow descent into fitness valleys uMass selection to climb new adaptive peak uInterdeme selection allows spread of superior demes across landscape Sewall Wright Beebe and Rowe 2004

20. Can the shifting balance theory apply to real species? How can you have demes with a widespread, abundant species?

21. What Controls Genetic Diversity Within Populations? 4 major evolutionary forces Diversity Mutation + Drift - Selection +/- Migration +

22. Migration is a homogenizing force  Differentiation is inversely proportional to gene flow  Use differentiation of the populations to estimate historic gene flow  Gene flow important determinant of effective population size  Estimation of gene flow important in ecology, evolution, conservation biology, and forensics

23. Isolation by Distance Simulation Random Mating: Neighborhood = 99 x 99 Isolation by Distance: Neighborhood = 3x3  Each square is a diploid with color determined by codominant, two-allele locuus  Random mating within “neighborhood”  Run for 200 generations (from Hamilton 2009 text)

24. Wahlund Effect Separate Subpopulations: H E = 2pq = 2(1)(0) = 2(0)(1) = 0 H E depends on how you define populations H E ALWAYS exceeds H O when randomly- mating, differentiated subpopulations are merged: Wahlund Effect ONLY if merged population is not randomly mating as a whole! Merged Subpopulations: H E = 2pq = 2(0.5)(0.5) = 0.5