QCE Biology - Unit 4 - Genetics and heredity

Inheritance Patterns and Genetic Data | QCE Biology

Learn dominant, recessive, autosomal, sex-linked, polygenic and multiple-allele inheritance using pedigrees, Punnett squares and histograms.

Updated 2026-05-18 - 7 min read

QCAA official coverage - Biology 2025 v1.3

Exact syllabus points covered

  1. Describe dominant, recessive, autosomal, sex-linked, polygenic and multiple-allele inheritance.
  2. Infer patterns of inheritance and predict frequencies of genotypes and phenotypes from genetic data, including histograms (polygenic inheritance).
  3. Infer patterns of inheritance and predict frequencies of genotypes and phenotypes from genetic data, including pedigrees (dominant/recessive, autosomal/sex-linked).
  4. Infer patterns of inheritance and predict frequencies of genotypes and phenotypes from genetic data, including Punnett squares (dominant/recessive, autosomal/sex-linked and multiple-allele inheritance).

Inheritance patterns and genetic data is part of the way QCE Biology turns living systems into evidence students can describe, analyse and evaluate. The safest way to study it is to connect each term to a data pattern, a biological mechanism and a limitation.

Inheritance evidence

Original Sylligence diagram for biology inheritance patterns.

Inheritance evidence

Core explanation

Dominant and recessive

A dominant allele is expressed when one copy is present. A recessive phenotype usually appears only when no dominant allele is present.

Autosomal and sex-linked

Autosomal genes are located on non-sex chromosomes. Sex-linked patterns often involve the X chromosome and can appear more frequently in males for recessive traits.

Multiple alleles and polygenic traits

Multiple-allele inheritance means more than two alleles exist in the population, even though each individual carries only two. Polygenic traits are controlled by many genes and often show continuous variation.

Genetic data

Pedigrees reveal family patterns, Punnett squares predict offspring probabilities, and histograms help recognise continuous polygenic distributions.

Pedigree clues for inheritance patterns

| Pattern | Typical pedigree clue | Important caution | | --- | --- | --- | | Autosomal dominant | Affected individuals often appear in every generation | Unaffected individuals usually do not pass on the trait | | Autosomal recessive | Unaffected parents can have affected children | Carriers are phenotypically unaffected | | X-linked recessive | More males affected; carrier mothers can have affected sons | No father-to-son transmission because fathers pass Y to sons | | X-linked dominant | Affected fathers pass the trait to all daughters and no sons | Affected mothers can pass it to sons or daughters | | Y-linked | Only males affected and affected fathers pass it to all sons | Rare; requires the gene to be on the Y chromosome | | Mitochondrial | Affected mothers can pass it to all children | Fathers do not pass mitochondrial DNA to offspring |

For autosomal recessive conditions, two carrier parents have a 25 percent chance of an affected child, a 50 percent chance of a carrier child and a 25 percent chance of a homozygous unaffected child for each pregnancy. These are probabilities, not guaranteed family ratios.

Non-Mendelian patterns

| Pattern | What happens | Example-style cue | | --- | --- | --- | | Codominance | Both alleles are expressed in the heterozygote | AB blood type expresses A and B antigens | | Incomplete dominance | Heterozygote has an intermediate phenotype | Red and white alleles producing pink flowers | | Multiple alleles | More than two alleles exist in the population | ABO blood group has IA, IB and i alleles | | Polygenic inheritance | Many genes contribute to one trait | Height or skin colour shows continuous variation | | Epistasis | One gene masks or modifies another gene's effect | A pigment gene can mask a colour-pattern gene |

Punnett squares predict expected probabilities under the model assumptions. Pedigrees and observed offspring counts may differ from expected ratios because of chance, small family size, incomplete penetrance, environmental effects or incorrect assumptions about genotypes.

Working with probabilities and data

Punnett squares give probabilities for each offspring, not promises about exact family counts. A 25 percent probability of an affected child does not mean every four-child family must have exactly one affected child. The expected ratio becomes more reliable with larger sample sizes.

Test crosses can help infer unknown genotypes. If an organism with a dominant phenotype is crossed with a homozygous recessive organism, the offspring phenotypes can reveal whether the dominant-phenotype parent was homozygous or heterozygous.

Pedigree evidence is strongest when multiple generations are shown and when enough individuals are included. Small pedigrees can fit more than one inheritance pattern. For example, an autosomal recessive trait and an X-linked recessive trait can look similar if few females are shown. A strong answer explains why one pattern is most likely and why alternatives are less likely.

Environmental effects can blur inheritance patterns. A genotype may create a susceptibility rather than a guaranteed phenotype. Penetrance describes the proportion of individuals with a genotype who express the phenotype. Expressivity describes variation in the degree of expression.

For polygenic traits, histograms usually show continuous variation because many genes and environmental factors contribute. A bell-shaped distribution suggests many small additive effects rather than a single dominant-recessive gene.

Classic pedigree examples help with pattern recognition. Huntington disease is often used as an autosomal dominant example because an affected person usually has an affected parent, unless the case is due to a new mutation or incomplete records. Haemophilia is often used as an X-linked recessive example because males are more commonly affected and carrier females can pass the allele to sons.

Use notation carefully. For autosomal traits, letters such as A and a are usually enough. For X-linked traits, show the chromosome, such as XH and Xh, because males have only one X chromosome. A male with XhY expresses an X-linked recessive phenotype because there is no second X allele to mask it.

Genotypic ratios describe allele combinations, such as 1AA:2Aa:1aa. Phenotypic ratios describe observable traits, such as 3 unaffected:1 affected. These ratios can differ when dominance, codominance, incomplete dominance or sex linkage changes how genotypes appear.

How to use this in data questions

Start by identifying what has been measured. In Biology, a graph or table is rarely just asking for a trend; it is asking whether you can connect the trend to a process. Quote enough data to show the pattern, then use the concept language from the syllabus. If the evidence is limited, name the limitation precisely: sample size, sampling method, uncontrolled variables, measurement precision, population choice or the time scale of the data.

A useful study habit is to turn each heading into a data prompt. Ask what you would expect to happen if the relevant variable increased, decreased or was removed. For ecology topics, think about abundance, distribution, biodiversity, biomass and carrying capacity. For genetics topics, think about genotype, phenotype, gene expression, allele frequency and inheritance pattern. For evolution topics, think about variation, selection pressure, gene flow, isolation and relatedness.

When a question asks you to evaluate, do not just list problems with the experiment. Link the limitation to the confidence of the conclusion. For example, a small sample size matters because a few unusual individuals can distort the pattern. An uncontrolled abiotic factor matters because it gives another possible explanation for the same biological trend. This is the difference between naming a limitation and using it scientifically.

Worked example

Common exam traps

Other traps to watch for:

  • using a general word when a syllabus term is available
  • ignoring units, sample size or time scale
  • treating a model as a perfect copy of the real ecosystem or cell
  • writing a memorised paragraph that does not use the given data

Quick check

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