QTL stands for quantitative trait locus. Which raises even more questions. What is a quantitative trait? What is a locus?.
- A locus is simply a region within a genome. Anything from a part of a single gene to a large hunk of a chromosome.
- A quantitative trait is one where different individuals vary continuously (like height or weight) rather than falling into discrete categories (like whether a person has blue or brown eyes*).
A QTL is simply a part of the genome that has been show (using complicated statistical tests) to influence a quantitative trait like height. For example, people with one particular region of chromosome 8 tend to be slightly thinner than people with other versions.** Now a lot of qualities we’re very interested in as a society turn out to be quantitative traits. I’m not even going to touch the implications for human genetics, but within plant biology lots of the things people are really interested in changes, from flowering time, to drought or disease resistance, to the big kahuna of them all YIELD, are quantitative traits.
How are new QTLs discovered? It’s not as simple as classical genetics where you can simply run a mutant screen, pull out individual that look weird in a way that seems interesting, and identify the gene which was mutated to create the change you observed.*** Instead a researcher has to measure their specific trait in a bunch of individuals (easily done for something like height, less easily done for something like number of root hairs per centimeter of root or trichomes per leaf****) and then compare those measurements to a bunch of information about the genomes of each of those individuals. If the average height of all the individuals with version A of some part of the genome is higher than the average height for all individuals which have version B of that same part of the genome and that difference is significant after a whole bunch of statistical tests, then that region is a QTL.
Do all that and congratulations. You’re done now. You can go publish a paper describing your discovery of QTL controlling whatever trait you just measured! Depending on the species, the trait, and how many (and how small) the QTL you found, that paper could be anywhere from a major finding to something buried in a never-heard-of-the-name-before journal. QTLs are one of those weird case (like cell phones) where smaller is better.
Why? Because the logical next step, after identifying a QTL, is to figure out what it is about that region which influences the measured trait. If the QTL in question is too large, that could mean trying to take a list of dozens or hundreds of genes and, somehow, devising a test to prove: It’s this one! Gene AT1G15210 helps regulate height (or root hairs, or trichomes, or whatever it is being studied).
If you’d like to check out an example of what an actual QTL paper looks like, I really enjoyed a recent one in G3 (G3 is open access, so everyone should be able to access this) at measured the development of tassel like outgroups on the end of maize ears. I’ve run across this a few times in the field back when I did actual maize genetics and always wondered what was going on genetically to create such weird looking plants. I still don’t know for sure, but now I know there are real geneticists out there working to discover the answer:
* Yes, if you’ve spent any length of time staring into a number of women’s eyes (or men’s for that matter) you’ll know there’s a great deal of variation within those categories, but the point is there ARE obvious categories for eye color, while any attempt to group people by weight or height would rely on essentially arbitrary cut offs.
**This statement is used as example. I know absolutely NOTHING about human genetics. You have been warned!
***And to be honest, in practice there is nothing simple about classical genetics. I’ve been forcefully reminded of this in an ongoing e-mail discussion that has gotten into the long term pedigrees of individual maize seeds.
**** I’ve often wondered if grad students assigned to such QTL projects have significantly higher than average drop out rates.