HSC Exam Practice

Sample response. A single nucleotide polymorphism (SNP) is a one-base difference at a specific position in DNA between individuals or populations, for example one individual carrying an A at a position where another carries a G.

Marking notes. 1 mark for identifying that it is a single-base difference; 1 mark for noting that it is at the same specific DNA position when sequences are aligned.

Sample response. Frequency = 20 ÷ 80 = 0.25 as a decimal, or 25% as a percentage.

Marking notes. 1 mark for the correct arithmetic (20/80 = 0.25); 1 mark for converting to a percentage (25%) and showing both forms.

Sample response. One limitation is small sample size: a small sample may not represent the wider population accurately, so the observed frequency may differ substantially from the population value. A second limitation is sampling bias, for example collecting data from only one location, age group or sub-population, this distorts the apparent frequency and weakens any conclusion about the wider population.

Marking notes. 2 marks per limitation (1 for naming the limitation, 1 for explaining why it weakens the conclusion). Accept other valid limitations such as observer bias, inconsistent trait definitions, treating one generation as the whole species, or relying on a single marker.

Sample response. A single SNP is only one position in the genome and may differ between two populations because of locus-specific selection, drift or chance, even when the rest of the genome is very similar. Comparing many SNPs samples many independent positions, so per-locus noise averages out and the resulting comparison better reflects overall genomic similarity. A relatedness conclusion drawn from many markers is therefore much more reliable than one drawn from a single marker.

Marking notes. 1 mark for stating that one SNP samples only one position / is influenced by locus-specific effects. 1 mark for stating that many SNPs sample many positions, averaging out per-locus variation. 1 mark for explicitly linking this to a more reliable overall similarity estimate.

Sample response. Group A: 45 ÷ 150 = 0.30 (30%). Group B: 90 ÷ 150 = 0.60 (60%). Cautious conclusion: in these sampled groups, the trait appears more common in Group B (60%) than in Group A (30%), suggesting a frequency difference; however, both samples are relatively small and from single locations, so this is a trend in the sampled data, not a proven difference across the whole population.

Marking notes. 1 mark, correct calculation for Group A (0.30); 1 mark, correct calculation for Group B (0.60); 1 mark, a cautious conclusion that references the trend ("more common in Group B") without overclaiming, using language such as "in this sample" or "suggests a trend".

Sample response (a). Population Q has the highest G-allele frequency at 0.62.

Sample response (b). Difference = 0.62 − 0.18 = 0.44 (44 percentage points).

Sample response (c). The data describe one SNP only, a single position in the genome. A difference at one locus is not sufficient evidence that two populations are different species, because populations of the same species routinely differ in allele frequency at individual SNPs due to selection, drift or migration. A stronger species-level claim would require comparison across many SNPs, larger and more representative samples, and other lines of evidence. Cautious wording (e.g. "in this sample") should be used rather than absolute claims.

Marking notes. (a) 1 mark, names Q and quotes 0.62. (b) 1 mark, correct subtraction (0.44). (c) 1 mark, recognises that one SNP is only one locus / one marker. 1 mark, explains that within-species variation at individual SNPs is normal (selection, drift, migration). 1 mark, proposes appropriate strengthening (more SNPs, larger / more representative samples) or uses cautious language consistent with the lesson.

Sample response (a). Total alleles = 2 × 100 = 200. Count of A = 2 × 49 + 42 = 140. Count of G = 2 × 9 + 42 = 60. So p(A) = 140 ÷ 200 = 0.70 and q(G) = 60 ÷ 200 = 0.30.

Sample response (b). The A allele is more common in this sample (frequency 0.70) than the G allele (frequency 0.30). This is visible in the genotype counts: 49 AA and 42 AG individuals carry at least one A allele, while only 9 GG individuals carry two G alleles. The data show a clear trend: in this sample, the A allele occurs at more than twice the frequency of the G allele.

Sample response (c). This is a single SNP in a sample of only 100 individuals. One marker cannot represent the full genetic variation of a population, the overall genome may show a completely different pattern at other positions. The sample may not be representative of the wider population if it was drawn from a single location or sub-group, and the observed frequency may differ from the true population value due to sampling variation.

Marking notes. (a) 1 mark, correct calculation of p; 1 mark, correct calculation of q (or notes q = 1 − p). (b) 1 mark, correctly identifies A as the more common allele; 1 mark, justifies using the frequency values calculated in (a). (c) 1 mark, names a valid limitation (one marker, small sample, single location, unrepresentative sample, or sampling variation). (Up to 6 marks total.)

Sample response. The claim that SNP frequency data alone is sufficient to determine the relatedness of two populations overstates what a single set of markers can show. A SNP is a one-base difference at a specific DNA position; its frequency in a sample can be calculated as p = (2 × homozygotes + heterozygotes) ÷ (2 × total individuals). At a single SNP, populations of the same species can differ dramatically because of locus-specific natural selection (for example, the lactase-persistence variant near LCT differs from frequency ~0.06 in East Asian samples to ~0.70 in Northern European samples), genetic drift in small populations, or recent migration. These differences are normal variation within a species and do not justify strong relatedness or non-relatedness claims. The reliability of any SNP frequency is also limited by sample size and bias: a sample of 30 from one location is far less informative than a stratified sample of thousands, and selecting only one location or sub-group introduces bias that can distort the estimate. Using multiple markers across the genome, a SNP panel of thousands of positions, averages out per-locus chance variation and locus-specific selection, giving a much more reliable estimate of overall similarity. SNP data are useful: they provide directly comparable markers across genomes and can show trends of similarity and difference, but they cannot, alone and at a single locus, prove either full relatedness or complete separation. A defensible conclusion is therefore that SNP frequency data are necessary but not sufficient evidence for relatedness, the strength of the inference depends on how many SNPs are compared, how many individuals are sampled, and how representative those samples are of each population.

Marking notes. 1 mark, defines a SNP and/or shows how its frequency is calculated. 1 mark, identifies that a single SNP can differ between same-species populations because of selection / drift / migration. 1 mark, links sample size to reliability of the estimate. 1 mark, links sample bias to reliability of the conclusion. 1 mark, explains the advantage of using multiple SNPs (averaging out per-locus variation). 1 mark, uses a named or worked example of locus-specific variation OR a numerical contrast between per-locus and genome-wide similarity. 1 mark, reaches an explicit evaluative judgement: SNP frequency data are necessary but not sufficient; relatedness conclusions must be proportional to the number of markers and the quality of the sample.