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II. Deviations from HWE A. Mutation B. Migration C. Non-Random Mating D. Genetic Drift - Sampling Error E. Selection 1. Measuring “fitness” – differential reproductive success. II. Deviations from HWE A. Mutation B. Migration C. Non-Random Mating D. Genetic Drift - Sampling Error
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II. Deviations from HWE A. Mutation B. Migration C. Non-Random Mating D. Genetic Drift - Sampling Error E. Selection 1. Measuring “fitness” – differential reproductive success
II. Deviations from HWE A. Mutation B. Migration C. Non-Random Mating D. Genetic Drift - Sampling Error E. Selection 1. Measuring “fitness” – differential reproductive success a. The mean number of reproducing offspring (or females)/female
II. Deviations from HWE A. Mutation B. Migration C. Non-Random Mating D. Genetic Drift - Sampling Error E. Selection 1. Measuring “fitness” – differential reproductive success a. The mean number of reproducing offspring (or females)/female b. Components of fitness:
II. Deviations from HWE A. Mutation B. Migration C. Non-Random Mating D. Genetic Drift - Sampling Error E. Selection 1. Measuring “fitness” – differential reproductive success a. The mean number of reproducing offspring (or females)/female b. Components of fitness - probability of female surviving to reproductive age
II. Deviations from HWE A. Mutation B. Migration C. Non-Random Mating D. Genetic Drift - Sampling Error E. Selection 1. Measuring “fitness” – differential reproductive success a. The mean number of reproducing offspring (or females)/female b. Components of fitness - probability of female surviving to reproductive age - number of offspring the female produces
II. Deviations from HWE A. Mutation B. Migration C. Non-Random Mating D. Genetic Drift - Sampling Error E. Selection 1. Measuring “fitness” – differential reproductive success a. The mean number of reproducing offspring (or females)/female b. Components of fitness - probability of female surviving to reproductive age - number of offspring the female produces - probability that offspring survive to reproductive age
II. Deviations from HWE A. Mutation B. Migration C. Non-Random Mating D. Genetic Drift - Sampling Error E. Selection 1. Measuring “fitness” – differential reproductive success a. The mean number of reproducing offspring (or females)/female b. Components of fitness - probability of female surviving to reproductive age - number of offspring the female produces - probability that offspring survive to reproductive age c. With a limited energy budget, selection cannot maximize all three components… there will necessarily be TRADE-OFFS.
E. Selection 1. Measuring “fitness” – differential reproductive success 2. Relationships with Energy Budgets
E. Selection 1. Measuring “fitness” – differential reproductive success 2. Relationships with Energy Budgets GROWTH METABOLISM REPRODUCTION
E. Selection 1. Measuring “fitness” – differential reproductive success 2. Relationships with Energy Budgets Maximize probability of survival Maximize reproduction GROWTH METABOLISM GROWTH REPRODUCTION METABOLISM REPRODUCTION
E. Selection 1. Measuring “fitness” – differential reproductive success 2. Relationships with Energy Budgets Trade-offs within reproduction METABOLISM REPRODUCTION REPRODUCTION METABOLISM A few large, high prob of survival Lots of small, low prob of survival
E. Selection 1. Measuring “fitness” – differential reproductive success 2. Relationships with Energy Budgets 3. Modeling Selection
3. Modeling Selection Selection for a Dominant Allele
3. Modeling Selection Selection for a Dominant Allele
3. Modeling Selection Selection for a Dominant Allele
3. Modeling Selection Selection for a Dominant Allele
3. Modeling Selection Selection for a Dominant Allele
3. Modeling Selection Selection for a Dominant Allele
3. Modeling Selection Selection for a Dominant Allele
3. Modeling Selection Selection for a Dominant Allele
3. Modeling Selection Selection for a Dominant Allele Δp declines with each generation.
3. Modeling Selection Selection for a Dominant Allele Δp declines with each generation. BECAUSE: as q declines, a greater proportion of q alleles are present in heterozygotes (and invisible to selection). As q declines, q2 declines more rapidly...
3. Modeling Selection Selection for a Dominant Allele Δp declines with each generation. So, in large populations, it is hard for selection to completely eliminate a deleterious allele....
3. Modeling Selection Selection for a Dominant Allele Δp declines with each generation. Rate of change depends on the strength of selection; the difference in reproductive success among genotypes. In this case, a new adaptive mutant allele has been produced in the population. The “selection differential”, s, is selection AGAINST the existing allele that had become ‘fixed’ in the population (f = 1.0) So, the “better” the new allele is (represented by the greater selective differential against the old allele), the faster the new mutant accumulates in the population.
3. Modeling Selection Selection for a Dominant Allele Selection for an allele where there is not complete dominance: - Consider incomplete dominance, codominance, or heterosis. In these situations, the heterozygote has a phenotype that differs from either of the homozygotes, and selection can favor one genotype over another: - Selection might favor one homozygote over the heterozygote and other homozygote (first example), or might favor the heterozygote over the homozygotes (second example), or might favor both homozygotes over the heterozygote (not considered here).
Selection for the homozygote of a ‘non-dominant’ allele (incomplete dominance, codominance, overdominance)
Selection for the homozygote of a non-dominant allele - deleterious alleles can no longer hide in the heterozygote; its presence always causes a reduction in fitness, and so it can be eliminated from a population (if the heterozygote is less ‘fit’ than the AA).
Selection for the heterozygote Maintains both genes in the gene pool peq = t/s+t = 0.75/1.25 = 0.6 AA Aa aa
Maintains both genes in the gene pool peq = t/s+t = 0.75/1.25 = 0.6
Selection for the Heterozygote Sickle cell caused by a SNP of valine for glutamic acid at the 6th position in the beta globin protein in hemoglobin (147 amino acids long). The malarial parasite (Plasmodium falciparum) cannot complete development in red blood cells with this hemoglobin, because O2 levels are too low in these cells. NN NS SS
E. Selection 1. Measuring “fitness” – differential reproductive success 2. Relationships with Energy Budgets 3. Modeling Selection 4. Types of Selection - Selection acts on phenotypes, which may be single gene traits, polygenic quantitative traits, and/or effected by epistatic interactions. - The different effects are measured by changes in the mean phenotype over time.
E. Selection 4. Types of Selection - Directional
E. Selection 4. Types of Selection - Directional
E. Selection 4. Types of Selection - Stabilizing
E. Selection 4. Types of Selection - Disruptive Lab experiment – “bidirectional selection” – create two lines by directionally selecting for extremes. Populations are ‘isolated’ and don’t reproduce.
E. Selection 4. Types of Selection - Disruptive African Fire-Bellied Seed Crackers