BIO II - Chapter 3

Drift, Mutation, Recombination, and the Mechanisms of Evolution

• Overview: Evolutionary change in populations can be caused by multiple mechanisms. While natural selection drives adaptive changes, other forces also alter allele frequencies in ways that may be non-adaptive and random.

• Key mechanisms discussed: drift (random sampling error), mutation (random genetic changes), recombination (shuffling existing genetic material), and selection (differential reproduction). Natural selection remains the primary source of adaptive change, but the others continually shape variation and population structure.

Drift and Random Processes

• Drift definition: sampling error that introduces random changes in allele frequencies across generations.

• Effect on variation: drift can alter allele frequencies in many ways, sometimes dramatically in small populations.

• Classic intuition: in finite populations, variation in allele frequencies arises from chance events rather than selection.

• Population size dependence: drift is most pronounced in small populations and diminishes as population size grows toward infinity.

• Example intuition: random events (like a storm, disease, or accident) can disproportionately affect certain alleles regardless of their impact on fitness.

Mutation: Source of New Variation

• Mutation basic idea: random changes in DNA introduce new alleles; most mutations are neutral or deleterious, a smaller fraction may be advantageous.

• Consequence for variation: mutation increases potential variation, providing material for selection and recombination to act upon.

• Negative mutations and selection: deleterious mutations are often purged by negative or purifying selection, reducing their frequency over time.

• Mutation-selection balance: new mutations continually enter the population and deleterious alleles are removed by selection, reaching a balance where harmful alleles persist at low frequencies.

• Example discussion: a harmful mutation that reduces fitness is expected to be selected against, reducing its frequency but not necessarily eliminating it entirely due to ongoing new mutations.

• Not all mutations are beneficial: in real populations, most new mutations are not advantageous; however, recombination among existing genes can still generate useful variation even without new genes arising.

Recombination and Sexual Reproduction

• Recombination role: sexual reproduction reshuffles existing genetic variation into new combinations each generation.

• Crucial point: recombination creates diversity by rearranging existing alleles, not by creating new genes per se.

• Consequence for variation: even without any new mutations, sexual reproduction can generate a wide array of offspring genotypes.

• Evolutionary significance: recombination is one of the key reasons sex evolved, as it increases the potential for advantageous gene combinations to arise.

Natural Selection, Variation, and Heritability

• Components of natural selection: requires variation, heritability, and differential reproduction.

• Variation in fitness: individuals with certain traits have higher reproductive success, altering allele frequencies over generations.

• Heritability concept: proportion of phenotypic variation that is due to genetic variation; essential for predicting response to selection.

• The breeder’s perspective: breeders care about heritability because they want traits that respond to selection (e.g., coat color in dogs, growth in crops).

• Heritability equation (conceptual): $h^2 = rac{R}{S}$ where $R$ is the response to selection (change in offspring mean) and $S$ is the selection differential (difference between population mean of parents and offspring mean).

• Breeder’s equation (practical form): $R = h^2 S$

• Heritability in practice: high heritability means a trait will respond well to selection; low heritability means selection will have little effect.

• Real-world nuance: environmental contributions influence phenotype; a trait can be highly heritable yet strongly environmentally influenced, or vice versa.

• Example illustration (heritable trait): if selected parents produce offspring that are, on average, heavier (e.g., 6 lb mean vs. 5 lb parents), the degree to which this increase reflects genetics vs. environment informs heritability.

• Link to Hardy–Weinberg (for a baseline): Hardy–Weinberg equilibrium describes genetic stability under no evolution; deviations indicate forces like selection, drift, mutation, or gene flow are acting.

Hardy–Weinberg Equilibrium (Baseline Genetics)

• Core idea: in an ideal population with no evolutionary forces and random mating, allele and genotype frequencies remain constant across generations.

• Notation: let p be the frequency of allele A and q be the frequency of allele a, with p + q = 1.

• Genotype frequencies under HW: $p^2 + 2pq + q^2 = 1$

  • $p^2$: frequency of AA

  • $2pq$: frequency of Aa

  • $q^2$: frequency of aa

• Practical use: HW provides a baseline expectation to compare real populations; deviations signal evolutionary processes in action.

• Limitations: HW assumes infinite population size, no selection, no mutation, no migration, random mating; real populations rarely meet all these conditions.

Population Genetics: Drift via Bottlenecks and Founder Effects

• Bottleneck: drastic reduction in population size due to chance events or selective pressures, followed by recovery. This can drastically alter allele frequencies and reduce genetic diversity.

• Founder effect: a new population is started by a small subset of individuals leaving a larger population. The new population’s allele frequencies reflect only the founders’ alleles, not the original population's full diversity.

• Consequences of both: reduced genetic diversity, potential fixation of some alleles, and strong drift effects in the small surviving group.

• Example concepts from the lecture:

  • Island example with a single gene showing dominant/recessive dynamics (A vs a). Drift can shift allele frequencies dramatically in a small surviving group after a random event (e.g., a subset survives a disaster).

  • Fixation: after drift, one allele can reach frequency 1.0 (fixed) while the other goes extinct, not necessarily due to selection.

• Human population context: human genetic diversity is relatively low compared to some tropical species; drift and historical bottlenecks have shaped modern human variation.

• Practical medical/research relevance: founder effects can influence the prevalence of certain genetic disorders in isolated communities (e.g., founder populations).

Real-world Illustrations: Founder Effects and Traits

• Amish community example (founder effect):

  • Origin: founded by a small group of European settlers; introduced traits from the founders that remain enriched in the population.

  • Polydactyly example: a dominant trait (polydactyly) is more common in the Amish because one or a few founders carried the allele; over time, it remains overrepresented due to drift/founder effects.

  • Conceptual takeaway: an initially small founder population can carry and disproportionately propagate certain alleles, leading to higher frequencies of some traits than in the general population.

• Mormon example: similar founder-effect logic discussed in the lecture; founder alleles can become overrepresented in a new population, shaping trait frequencies.

• Practical takeaway: founder effects can maintain or increase certain traits in isolated populations even in the absence of ongoing selection.

Stabilizing Selection and Trait Maintenance

• Stabilizing selection: selection that favors intermediate trait values, reducing extremes and maintaining a population mean.

• Contrast with directional selection: directional selection pushes the mean toward one extreme; stabilizing selection keeps the trait in a narrow range.

• In the lecture example: a trait like birth weight could be optimally balanced; too big or too small reduces fitness, so extreme values are selected against, maintaining the mean around a favorable range.

• Consequence for variation: stabilizing selection reduces phenotypic variance for the trait over time, while selection for extremes can increase variance in other contexts.

Population, Disease, and Evolution in Public Health Context

• Pathogen evolution and genetic diversity: higher genetic diversity in a pathogen population makes it more adaptable to changing environments or vaccines.

• Vaccination and genetic diversity: vaccines can reduce pathogen population size and genetic diversity, limiting the ability of the virus to evolve resistance; high coverage reduces spread and mutation opportunities.

• Herd immunity concept (practical): achieving a high fraction of immune individuals reduces transmission; a common proxy threshold is $H ext{ (herd immunity)} \approx 1 - rac{1}{R<em>0}$, where $R</em>0$ is the basic reproduction number of the pathogen.

• Varied mutation rates by pathogen: some pathogens (e.g., COVID-19, HIV) mutate rapidly and pose ongoing challenges; others (e.g., polio) mutate less and can be controlled more effectively with vaccination.

• Public health nuance: high vaccination coverage reduces the effective population size of the pathogen and constrains its genetic diversity, reducing the likelihood that vaccine-evading strains arise; incomplete coverage can allow escape mutants to emerge.

• Important caveat discussed: broad vaccination helps protect others (not just the individual) by limiting transmission and reducing opportunities for viral evolution; partial adherence can undermine public health benefits.

Key Takeaways and Connections

• Multiple forces shape populations beyond natural selection: drift, mutation, and recombination all contribute to variation and allele frequency changes.

• Natural selection requires variation and heritability to drive adaptive change; its effect on variation can sometimes reduce diversity (e.g., by removing deleterious alleles or by fixing advantageous ones).

• Recombination amplifies genetic variation by reshuffling existing alleles, supporting evolutionary potential even without new mutations.

• Hardy–Weinberg provides a baseline to detect evolutionary forces acting on a population.

• Drift is a powerful force in small populations and can lead to fixation of alleles regardless of fitness; bottlenecks and founder effects are practical demonstrations of drift in nature.

• Mutation–selection balance explains why deleterious mutations persist at low frequencies despite ongoing purifying selection.

• Stabilizing selection maintains traits around an optimal value, reducing variance rather than shifting the mean.

• In real-world scenarios, population genetics concepts inform public health strategies (e.g., vaccination programs) and provide insight into the genetic structure of human populations and isolates like founder communities.