By the end of this practical you will be able to:
Plant breeders want to combine desirable traits (for example disease resistance, drought tolerance, or high yield) into a single crop variety.
Traditionally this is done by crossing plants and simply looking at which offspring look the best. This is called phenotypic selection. It is slow: some traits only show up late in a plant's life, and some are expensive or destructive to measure (you would have to expose a plant to salt stress just to see if it survives).
Genetic markers offer a shortcut. A marker is a specific, measurable position in a plant's DNA where individuals can differ from one another. Here we simplify this to just two possible values, 0 and 1, for every marker:
If we know that a marker is reliably linked to a trait we care about, we can screen very young plants (often from a small leaf sample, days after germination) instead of waiting months. This is the core idea behind marker assisted selection. In this practical we will:
We want to breed plants that are salt resistant, but also have a high yield. To study what makes plants salt resistant, we first need a population that is genetically diverse: the plants differ from one another at many marker positions, and also differ in the trait we care about.
This is essential: if every plant were genetically identical, we could never work out which marker is responsible for a trait, because there would be nothing to compare.
Scroll sideways to see all the markers.
To find out which marker(s) are responsible for salt resistance, we run a Genome-Wide Association Study (GWAS). A GWAS statistically tests, separately for each marker, whether plants with a 1 at that marker tend to have a different phenotype than plants with a 0.
The result of each test is a p-value. A small p-value means it is unlikely that the difference we observe happened purely by chance, so it is more likely to reflect a real, biological effect. Because p-values can become extremely small, we usually plot -log10(p-value) instead: this turns tiny p-values into large, easy-to-compare bars. The higher the bar, the stronger the evidence that a marker is associated with the trait. This plot is called a Manhattan plot, because the tall bars resemble a city skyline.
👆 Click a bar to inspect that marker below.
Now that we have pinpointed a marker for salt resistance, we want to move that specific piece of DNA into a plant that farmers already grow: one with a high yield, but which lacks the marker. This process is called introgression: transferring a gene (or a small region of a chromosome) from one variety into another through repeated crossing and selection.
We use two starting populations:
Now it is your turn to run the breeding programme. Backcrossing means: take the population you are currently holding, cross it with one other population, then keep only some of the offspring based on a marker. The offspring you keep become the population you hold for the next round. Repeat for a few rounds.
You start out holding the resilient donor. Each round, you decide which population to cross it with, and which marker (and allele) to keep the offspring on. Use what you found in steps 2 and 3. After each round, watch the scheme and the graph to see how salt resistance and yield change.
So far we selected for salt resistance. Now let's run exactly the same GWAS approach for yield and see what we find. As before, drag the slider to grow the population, then investigate the Manhattan plot yourself.
Manhattan plot for Yield, instead of Salt Resistance. 👆 Click a bar to inspect that marker below.