Evolution by natural selection and the three patterns of selection (stabilising, directional and disruptive), the role of gene transfer and genetic drift, speciation, and the use of genomic sequencing and phylogenetics to compare organisms.

What this key area is asking

The SQA wants you to explain evolution by natural selection, describe the three patterns of selection, explain vertical and horizontal gene transfer and genetic drift, describe how new species arise (speciation), and explain how genomic sequencing and phylogenetics are used to compare organisms.

Natural selection and its patterns

There are three patterns of selection:

• Stabilising selection favours the average phenotype and selects against both extremes, reducing variation. Human birth weight is a classic example: very small and very large babies historically had lower survival, so the average is favoured.
• Directional selection favours one extreme, shifting the population in that direction (for example antibiotic resistance in bacteria, or the peppered moth becoming darker during industrial pollution).
• Disruptive selection favours both extremes over the average and can split a population into two groups, which can be a first step towards forming new species.

Gene transfer and genetic drift

In small populations, genetic drift changes allele frequencies by chance rather than by selection, which can have a large effect when numbers are low. For example, if a small group founds a new population, the alleles they happen to carry may become common simply by chance, not because they are advantageous.

Speciation

Most commonly an isolation barrier (such as a geographical barrier) prevents gene flow between two populations; this is called allopatric speciation. Speciation can also occur without a geographical barrier, for example through behavioural or ecological isolation within the same area (sympatric speciation). In each case, mutation, natural selection and genetic drift then act independently on each population until they become separate species.

Genomic sequencing and phylogenetics

Comparing the sequences of genomes allows scientists to:

• Build phylogenetic trees showing how species are related and when they diverged. The more similar the sequences, the more recently the species shared a common ancestor.
• Identify the three domains of life (bacteria, archaea and eukaryotes), a classification that came directly from comparing genetic sequences rather than appearance.
• Use a molecular clock to estimate the time since two species shared a common ancestor, by assuming that mutations accumulate at a roughly constant rate.
• Apply personalised (pharmacogenetic) medicine, where an individual's genome guides the choice and dose of their treatment.

Examples in context

Example 1. Antibiotic resistance and directional selection. When a bacterial population is exposed to an antibiotic, the few cells carrying a resistance allele survive while the rest die. These survivors reproduce, so the next generation is more resistant: the population has shifted towards one extreme. Horizontal gene transfer can then spread the resistance allele rapidly to other bacteria, which is why antibiotic resistance has become a serious global health problem.

Example 2. The molecular clock and human origins. By comparing genome sequences from humans and other primates, scientists estimated that humans and chimpanzees shared a common ancestor roughly six million years ago. Because genetic differences accumulate at a fairly steady rate, the number of differences between the genomes acts as a molecular clock, allowing the timing of divergence to be calculated. This shows how genomic sequencing reveals evolutionary relationships that fossils alone could not.

Try this

Q1. Name the three patterns of natural selection. [1 mark]

• Cue. Stabilising, directional and disruptive.

Q2. Explain how genomic sequencing can show how closely two species are related. [2 marks]

• Cue. The more similar their base sequences, the more recently they shared a common ancestor; phylogenetic trees are built from this data.