In the wild, each species may exist as one population or multiple populations. Different populations correspond to defined areas – habitats.
The sum of all present alleles for a given gene in a given population is known as the gene pool.
This is essentially a way of thinking about all the individuals in a population contributing their alleles towards the overall allele frequency. The extent of different alleles present gives the genetic diversity of a population.
The allele frequency in a population’s gene pool can change as a result of selection. The effectors of selection can be varied, yet the outcome is similar: advantageous or preferred alleles and the traits associated with them increase in frequency, while detrimental or disfavoured alleles and the traits associated with them decrease in frequency.
Here is an all-time classic example. The most frequent initial moth colour in a population landing on tree trunks was dark, to match that of the tree trunks. Few moths could get away with being light-coloured. Once the tree trunks were painted white, the former moths became very apparent to predators, and so the light-coloured moths evaded predation much better and survived to reproduce. Essentially, the tables had turned!
This resulted in the allele for light colour to spread and become the most frequent compared to that for dark colour. The latter sharply dropped in frequency and became the minority.
This is an example of directional selection. It tends towards an extreme, either the light-coloured or the dark-coloured, depending on scenario.
Selection can also tend towards a “happy medium” and avoid either extreme. This is stabilising selection. If really small lions don’t survive long, but really large lions can’t supply themselves enough food, then the average lions are selected for and achieve the highest frequency.
Directional selection also takes place when antibiotics are used against bacteria. The adaptive pressure favours bacteria that have the antibiotic resistance gene and can survive the hostile environment.
On the other hand, a scenario such as human birth weight showcases stabilising selection. The average weight is large enough to keep the newborn healthy and increasingly able to survive independently, but small enough to enable the actual birth.
Natural selection therefore results in species increasingly and consistently adapted to their environment via anatomical, physiological or behavioural changes.
As previously touched on, the genome is the entirety of genetic material carried by an individual or species and varies accordingly. The database of genomes of different species is growing and includes humans (the Human Genome Project). For example, the human genome, by chromosome, is viewable here: https://www.ncbi.nlm.nih.gov/genome/?term=homo+sapiens
Simple genomes such as those of viruses can enable a relatively straightforward effort of assigning proteins to each gene in the genome, and thus creating a database of them. This is known as a proteome.
The information gleaned from a virus proteome, for example, can inform vaccination targets by selecting appropriate antigens such as elements of the viral capsid.
Other exciting synthetic biology applications can be explored such as glowing beer, synthesising specific compounds useful in medicine or manufacturing using organisms to whom that product isn’t native in an attempt to boost production or create new products.
Analysing and storing information about more complex genomes is hindered by non-coding DNA and regulatory genes. Non-coding DNA and regulatory genes take up the vast majority of this type of genome. This means that the actual protein products that genes code for are in the minority.
The proteomes corresponding to complex genomes, human included, are therefore difficult to build. Sequencing methods themselves have witnessed, and continue to witness a rapid evolution towards faster, more efficient, automated techniques that can yield tremendous amounts of data.
If we have obtained a DNA sample or a few, what next? Well, nothing much can be done with that. We must obtain exponentially more DNA to use for any purpose. And it all of course must be identical. We must essentially clone our DNA. Considered the very staple of molecular biology, this technique for multiplying DNA many-fold was invented by a chap Kary Mullis who believes in astrology.
Essentially the DNA is denatured so the 2 strands break apart, short complementary bits called primers attach to the strands, the enzyme DNA polymerase binds to the primers and initiates the assembly of a new DNA strand, and finally the process is repeated many times over in a chain reaction. This is the polymerase chain reaction, PCR.
Soon enough, the few bits of DNA become thousands, and hundreds of thousands, and millions…
For example, Sanger sequencing has been the main method of sequencing DNA and yielded many variations of itself. The basic concept follows these steps:
1. Mix copies of your target DNA to be sequenced with radioactive nucleotides (with A, T, G or C bases)
2. These nucleotides also prevent further DNA lengthening, resulting in a mixture of different sequence DNA strands complementary to the template DNA
3. e.g. AATGGC creates TTACCG, TACCG, ACCG, CCG, CG and G
4. Run the DNA mixture on a gel to separate the different strands by size
5. Infer their sequence based on the results: the radioactive reading of the different bases (A, T, C or G) alongside the size sequence of the strands (smaller strands run further down the gel while larger strands stay towards the top, where they were loaded)
The sequence obtained can then be converted into the amino acid sequence of the protein it encodes, if the sequence belongs to a gene. Looking at the amino acid sequence can be used to compare various conditions, for example if a variation of a protein amino acid sequence is associated with a blood disorder.
Biodiversity can be measured using sequencing and genetic fingerprinting.