EvolutionaryGenetics_02

• Constant population size (i.e. equilibrium)
• Infinite-sites compatible, no recombination, no migration

• If D is significantly different than zero reject hypothesis of neutrality.
• General rule of thumb - values greater than +2 or less than -2 are likely to be significant.

• Selection acting on beneficial mutations (D > 0) with an excess of intermediate-frequency alleles increasing genetic variation (e.g., balancing selection) that benefit the population, sudden population contraction, or population subdivision.
• Selection removing or maintaining deleterious (i.e. lower fitness) mutations (D < 0) at a low frequency (e.g., population expansion, background selection, purifying or negative selection or selection sweeps)

• Inheritance scalar
• autosomal = 1
• haploid = 0.50
• X-linked = 0.75
• Y-linked = 0.25

• Equations
• autosomal/diploid... θ = 4Ne µ
• haploid... θ = 2Ne µ (haploid)
• X-linked... θ = 3Ne µ (X-linked)
• Y-linked... θ = Ne µ (mt or Y locus)

Selection acting on beneficial mutations (D > 0) with an excess of intermediate-frequency alleles increasing genetic variation (e.g., balancing selection) that benefit the population, sudden population contraction, or population subdivision.

Selection removing or maintaining deleterious (i.e. lower fitness) mutations (D < 0) at a low frequency (e.g., population expansion, background selection, purifying or negative selection or selection sweeps).

If D is significantly different than zero reject hypothesis of neutrality. General rule of thumb: values greater than +2 or less than -2 are likely to be significant.

detecting background selection (e.g., deleterious mutations and purifying or negative selection)

detecting background selection (e.g., deleterious mutations and purifying or negative selection)

for detecting population growth and genetic hitchhiking (e.g., beneficial mutations and positive selection)

for detecting population growth and genetic hitchhiking (e.g., beneficial mutations and positive selection)

If only Fu and Li’s tests are significant - suggests background selection

If only Tajima's D and Fs are significant - suggests population growth or genetic hitchhiking

• A phylogeographic approach
• statistical parsimony and SplitsTree graphs
• use if you want to assess geographical spread of molecular data without modeling

• A phylogeographic approach (Approximate Bayesian Computation)
• use if you want to model rates of spread and take into account geographical features

• A phylogeographic approach (mutation ages)
• use if you want information about population size, migration and geographical origins of mutations

• constant population size (equilibrium)
• Infinite-sites compatible
• no recombination
• no migration

• method for detecting historical recombination events
• Infers a recombination event under the assumption of infinite-series
• H4 is most likely ancestral because it:
• Shares fewer derived mutations compared to H2 and H3.
• Does not participate in recombination events in the ARG.
• Is in a "simpler" form compared to the recombinant haplotypes

• repeat mutations have 0 probability
• parallel evolution unlikely

• IMgc uses the four-gametes criteria to remove either sequences or variable sites containing evidence of recombination
• It tests for recombination and finds the largest non-recombining partition

population processes on different evolutionary time scales

randomness

The integration of multiple loci comprising mixed markers is more powerful for evolutionary inference than multiple loci of the same genetic marker (e.g., IMa3 allows analysis across multiple data types).

integrating multiple loci

a group of genes within an organism that was inherited together from a single parent

• IMrg can do this
• Example with Ancestral recombination graph
• The recombination event between sites 2 and 3 is shown in the oval
• H2 gets a prefix from H3 and the suffix from H1
• H4 is the ancestral haplotype

Different genetic markers (SNPs, SSRs, etc)

integrate over multiple loci