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AP Biology Notes

5.3.3 Probability rules in single-gene inheritance

AP Syllabus focus:

‘Rules of probability predict the likelihood that particular alleles, and therefore single-gene traits, will be passed to offspring.’

Probability provides a precise way to predict inheritance patterns from meiosis and fertilisation. In single-gene crosses, allele segregation creates measurable chances for specific gametes, genotypes, and phenotypes in offspring.

Probability basics for single-gene inheritance

Events, outcomes, and genetic “chance”

Probability: The likelihood that a particular outcome will occur, expressed from 0 (impossible) to 1 (certain).

In genetics, an event might be “a gamete carries allele A” or “an offspring is aa.” Probabilities are built from the possible outcomes of allele segregation and random fertilisation.

Independent vs. dependent events

Independent events: Two events where the occurrence of one does not change the probability of the other.

For many AP Biology single-gene problems, the allele a parent contributes in one gamete is treated as independent of what the other parent contributes at fertilisation. Independence is what allows multiplication of probabilities across parents.

Core probability rules used in inheritance

Genetic predictions commonly rely on the multiplication (AND) rule, the addition (OR) rule, and the complement rule.

P(A and B)=P(A)×P(B) P(A \text{ and } B) = P(A)\times P(B)

P(A) P(A) = probability of event A (unitless)

P(B) P(B) = probability of event B (unitless)

P(A or B)=P(A)+P(B)P(A and B) P(A \text{ or } B) = P(A)+P(B)-P(A \text{ and } B)

P(A or B) P(A \text{ or } B) = probability that A occurs, or B occurs, or both (unitless)

P(not A)=1P(A) P(\text{not }A) = 1 - P(A)

P(not A) P(\text{not }A) = probability that A does not occur (unitless)

These rules let you translate segregation and fertilisation into predicted genotype or phenotype likelihoods without needing to list every possibility.

The multiplication rule (AND) in genetics

Use AND when multiple conditions must happen together, such as:

  • A parent produces a gamete with a specific allele and the other parent produces a gamete with a specific allele.

  • An offspring must inherit a particular allele from the mother and a particular allele from the father.

Key idea: multiplying probabilities assumes the events are independent (common when combining parental contributions at fertilisation).

The addition rule (OR) and mutually exclusive outcomes

Use OR when there are multiple alternative ways to obtain the same result, such as:

  • An offspring genotype that could arise from more than one gamete combination.

  • A phenotype that results from more than one genotype (for example, a dominant phenotype from either homozygous dominant or heterozygous genotypes).

If the alternatives cannot happen at the same time (they are mutually exclusive), then P(A or B)=P(A)+P(B)P(A\text{ or }B)=P(A)+P(B) because P(A and B)=0P(A\text{ and }B)=0. In inheritance, “offspring is AA” and “offspring is Aa” are mutually exclusive outcomes for a single child.

The complement rule (NOT) for “at least one”

The complement is especially useful for statements like “at least one offspring shows the recessive phenotype.” Instead of adding many separate cases, you often find:

  • Probability of none showing the phenotype

  • Then subtract from 1 to get “at least one”

This approach is powerful when the number of offspring is large or when multiple outcomes would be tedious to enumerate.

Connecting probability to allele segregation

Gamete probabilities come from segregation

During meiosis, alleles of a gene separate so each gamete receives one allele.

Pasted image

This diagram summarizes the major stages of meiosis (I and II), highlighting how one diploid cell produces four haploid gametes. It reinforces the mechanistic basis for segregation: each gamete receives only one allele per gene after homologous chromosomes (meiosis I) and sister chromatids (meiosis II) separate. Source

For a heterozygote, segregation produces two gamete types in equal proportions (a 1:1 probability split), assuming fair segregation and no selection.

Segregation: The separation of the two alleles of a gene into different gametes during meiosis, so each gamete carries only one allele.

For a homozygote, all gametes carry the same allele (probability 1 for that allele).

Zygote probabilities combine two independent gamete draws

Fertilisation can be treated as a random union of one gamete from each parent. In probability terms:

  • Choose an allele from parent 1 (based on that parent’s gamete probabilities)

  • Choose an allele from parent 2

  • Combine them to form an offspring genotype

When you need the probability of a specific genotype, you often:

  • Use multiplication to combine the required parental contributions (AND)

  • Use addition if there are multiple gamete pairings that produce the same genotype (OR)

Phenotype probabilities depend on genotype-to-phenotype rules

Single-gene traits often involve dominance, where different genotypes may map to the same phenotype.

Pasted image

This figure contrasts phenotype vs. genotype outcomes for a classic single-gene Mendelian scenario, showing how offspring genotypes (e.g., YYYY, YyYy, yyyy) translate into phenotype proportions. It visually reinforces why phenotype prediction can require summing multiple genotype probabilities (an “OR” calculation) when more than one genotype produces the same phenotype. Source

Then phenotype prediction becomes a probability “OR” problem:

  • Add probabilities of all genotypes that yield the phenotype of interest

  • Or use the complement rule to compute “not that phenotype” and subtract from 1

Common pitfalls in AP Biology probability problems

  • Confusing OR with AND: “offspring is Aa” requires a specific allele from each parent (AND), not an alternative (OR).

  • Forgetting to subtract overlap in the general OR rule: if outcomes can occur together, use P(A)+P(B)P(A and B)P(A)+P(B)-P(A\text{ and }B).

  • Treating non-independent events as independent: independence is typically valid when combining parental gametes at fertilisation, but dependence can arise within a single parent’s set of gametes under special constraints.

  • Mixing up probability and expected ratio: ratios summarise typical outcomes over many offspring; probability describes the chance for a single offspring.

FAQ

Dependence is relevant when one outcome changes the sample space for the next outcome.

Examples include:

  • Sampling without replacement from a very small set of gametes (a contrived situation)

  • Any explicit constraint such as “one child is known to be affected”

In typical fertilisation predictions, allele contribution from each parent is treated as independent.

Conditional probability is used when new information is given (e.g., an offspring already shows a phenotype). You update the probability space to include only outcomes consistent with that information.

Formally: $P(A\mid B)=\dfrac{P(A\text{ and }B)}{P(B)}$.

A Punnett square enumerates all equally likely gamete combinations, while probability rules compute the same totals algebraically.

They agree when:

  • Gamete types are correctly assigned probabilities

  • Each fertilisation outcome is appropriately counted once

  • Assumptions of random fertilisation and fair segregation hold

If segregation is distorted, the gamete probabilities are not $0.5$ and $0.5$. You still use the same AND/OR/complement rules, but with the altered gamete probabilities (for example, $P(A)=0.6$, $P(a)=0.4$). The structure of the calculation remains the same; only the inputs change.

Use OR when you can list a small number of mutually exclusive outcomes that lead to the result.

Use the complement rule when:

  • The desired outcome is “at least one”

  • There are many ways to achieve it

  • The “none” case is simpler to express and compute

Practice Questions

In a single-gene cross, explain how the multiplication rule is used to find the probability of a specific offspring genotype. (2 marks)

  • States that the required alleles must be inherited from both parents / two events must occur together (1)

  • States that for independent events the probabilities are multiplied, e.g. P(A and B)=P(A)×P(B)P(A \text{ and } B)=P(A)\times P(B) (1)

Describe how the addition rule and the complement rule can be used to predict the probability of an offspring showing a particular phenotype in single-gene inheritance. (5 marks)

  • Links phenotype probability to one or more underlying genotypes (1)

  • Uses addition rule to combine mutually exclusive genotype outcomes that produce the same phenotype (1)

  • Correct general addition statement, including overlap term, e.g. P(A or B)=P(A)+P(B)P(A and B)P(A\text{ or }B)=P(A)+P(B)-P(A\text{ and }B) (1)

  • Explains complement approach for “at least one” or “not phenotype”, e.g. P(not A)=1P(A)P(\text{not }A)=1-P(A) (1)

  • Applies complement logic appropriately (compute “none” then subtract from 1, or compute recessive then subtract from 1 for dominant) without a worked calculation (1)

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