Investigating Allele Frequencies

Probability and Expected Ratios: In a large population with equal allele frequencies ($p=0.5, q=0.5$), the expected genotype ratio for the next generation is $1:2:1$ ($25\% AA, 50\% Aa, 25\% aa$).

The Law of Large Numbers: This principle dictates that as the number of trials (sample size) increases, the observed results will converge toward the theoretical expected values.

Genetic Drift Mechanism: In small populations, random sampling error causes the actual allele frequencies to deviate significantly from the expected ratios, potentially leading to the loss of alleles by pure chance.

Cumulative Effect: Because each generation's gene pool is based on the actual (not theoretical) results of the previous generation, small deviations can compound over time, leading to rapid evolutionary change.

Theoretical vs. Observed: Theoretical frequencies are what math predicts (e.g., $50\%$), while observed frequencies are the actual counts recorded during the investigation.

Drift vs. Selection: Genetic drift is change due to random chance, whereas natural selection is change due to differential survival based on fitness.

Calculating Allele Totals: Always remember that each individual has two alleles. If you have $10$ homozygous dominant ($AA$) and $5$ heterozygous ($Aa$) individuals, the total number of $A$ alleles is $(10 \times 2) + (5 \times 1) = 25$.

Frequency as a Decimal: Exams often require frequencies to be expressed as a decimal between $0$ and $1$. Ensure your final answer for $p + q$ always equals $1$.

Identifying Drift: If a question describes a sudden change in allele frequency in a 'small' or 'isolated' population without mentioning survival advantages, the answer is likely genetic drift.

Sample Size Justification: When asked why results differ from the $1:2:1$ ratio, always point to the small sample size and the influence of chance.

Misconception: Drift is Selection: Students often assume an allele increased because it was 'better.' In small population models, an allele can become fixed (100%) even if it provides no advantage.

Error: Forgetting Replacement: In physical models, failing to return beads to the container changes the probability for the next draw, which invalidates the simulation of a stable gene pool.

Rounding Errors: Rounding allele frequencies too early in multi-generation calculations can lead to significant inaccuracies in the final result.