3.4.7 - Investigating diversity

From observable characteristics to DNA

Counting visible characteristics gives a quick picture of genetic diversity, but appearance is only indirect evidence.

Diversity can be investigated within one species or between species, and your conclusion must match your sample.

Inter- means between, and intra- means within.

Comparing frequencies of characteristics

One method compares the frequency of measurable or observable characteristics: how common each form of a characteristic is in a population. Imagine two populations of the same beetle species:

The populations have different frequencies of each form. That suggests different allele frequencies, so they may differ genetically.

Samples differ in size, so compare frequencies, not counts. 18 dark beetles out of 60 is a relative frequency of 0.30, or 30%; 18 out of 200 is only 9%.

Why appearance is indirect evidence

Appearance is a poor guide to DNA, so an observed colour frequency is not automatically an allele frequency:

• Environment: the leaves of one tree carry essentially the same DNA, yet sunlit leaves are usually thicker than shaded ones.
• Polygenic characteristics: one visible difference may reflect several genes.
• Dominance: a dominant allele can mask a recessive one.
• Independent evolution: analogous characteristics, which you met in 3.4.5, evolved separately, so similar appearance can mislead.

So gene technology has changed the method: inferring DNA differences from characteristics has been replaced by direct comparison of DNA sequences, which examines the genetic material itself. You won't be tested on how the technologies work.

Comparing DNA, mRNA, and protein sequences

Each step from gene to protein gives you a sequence to compare, and each step can hide differences that DNA would show.

Information passes from DNA → mRNA → protein, so differences in proteins can be used to infer differences in genes.

What each sequence shows

• Base sequence of DNA: the most direct method. Mutations build up over time, so organisms that split from a common ancestor more recently tend to have fewer differences in their DNA.
• Base sequence of mRNA: mRNA is transcribed from DNA, so similar mRNA from the same gene suggests similar DNA for that gene.
• Amino acid sequence of a protein: this depends on the DNA base sequence, via mRNA, so very similar sequences in the same protein suggest two organisms are closely related.

What each comparison can miss

The genetic code is degenerate: more than one codon can specify the same amino acid. So two DNA sequences can differ while their proteins are identical, and identical protein sequences do not establish identical DNA.

Cover the table, then explain what each comparison can miss.

Interpreting sequence data

Count the differences at matching positions, then claim only what those sequences can support.

Counting differences fairly

Compare the same homologous gene or protein, inherited from a common ancestor. Align corresponding positions, and use equal lengths or a proportion of differing sites: a longer region can look more different simply because more sites were checked.

A nine-base fragment is too short to establish a complete evolutionary history, and sequence similarity alone does not show that two organisms can interbreed to produce fertile offspring.

Reading a table of differences

1. Find the smallest number of differences: the most similar pair for the region examined.
2. Find the largest number of differences: the most distantly related pair or most genetically distinct population.
3. Look for clusters of low values, which suggest closely related groups.
4. State the meaning: fewer differences means more similarity, so the organisms share a more recent common ancestor or are more genetically similar within the species.

Between species. These are amino acid differences in one protein. Each number appears twice, because A against B is also B against A.

A and D are the most closely related, differing by only 3 amino acids. C differs from the others by 17–20, which supports it being the most distant lineage, although one protein is not a whole-genome test.

Within a species. Scientists compared the base sequence of the same gene in three populations of one lizard species:

This is within a species, so you judge how similar the populations are, not whether they are separate species. A and B differ by only 1 base. C differs from both by 4–5, which suggests greater genetic diversity between C and the others than between A and B.

Within a population, sample several individuals: differences among three specimens do not reveal the frequency of every allele in the population.

Random sampling and leaf position

You can rarely measure a whole population, so you measure a sample selected at random to keep it fair.

A sample is a subset used to estimate the characteristics of a defined population. Sampling bias is a systematic preference in what is selected, such as picking the largest leaves; random sampling reduces it.

Sampling variation is the difference that arises by chance between random samples. A larger sample usually reduces the influence of chance, but does not correct a biased method.

Two ways to select at random

If you can list a small population:

1. Number all the plants.
2. Use a random-number generator to select numbers without replacement, so no plant is chosen twice.
3. Take one fully expanded, undamaged leaf at a stated stem position per plant, so many leaves from one plant do not count as independent plants.
4. Measure from the same points, excluding the stalk, with the same ruler and units, so the lengths are comparable.

When a full list is impractical, use random coordinates:

1. Overlay a coordinate grid on the whole study area.
2. Generate random x and y coordinates, so you cannot favour spots by eye.
3. Place a fixed-size quadrat at each position, with a predefined rule for plants on the edge.
4. Measure all eligible plants in the quadrat, or select from them at random, not the largest or most visible.

Investigating leaf position

Leaves on one plant share essentially the same DNA, so comparing upper and lower leaves investigates the effect of position on growth:

1. Randomly select many plants of one species, so the results represent the population.
2. On each plant, randomly select one leaf from a predefined upper region and one from a predefined lower region, so size cannot decide the choice.
3. Control leaf maturity and the measurement method, so age and technique do not cause a false difference.
4. Keep each plant's upper and lower results together: these are paired observations, not two unrelated samples.
5. Measure light or record shading. Position is linked to light, age and other factors, so a difference does not alone establish its cause.

There is no universally correct sample number, but a pilot sample can reveal whether more sampling is needed. Repeating measurements of the same leaf checks measurement consistency, while measuring more randomly selected plants improves population sampling.