BIOL 336 is a ‘Fundamentals’ course in biology, this time focused on evolutionary biology. This was my first time teaching in an upper-year course. I was apprehensive at first, but I ended up teaching a lesson on quantitative genetics, which is a topic I am fairly specialised in. Quantitative genetics is a topic that always feels a little out of place in the courses in which it is taught. It often relies on principles and concepts that are disparate from the other concepts in the course. Thus, one of my goals in this lesson was to try to connect the topic with the broader objectives of the course so that students would be left feeling lost.

Quantitative genetics is a sub-field of population genetics. It specifically addresses the issue of biological traits that have quantitative characters, such as height and growth traits, agricultural yield, or milk yield and fat content in dairy cows. In fact, many of the principles of quantitative genetics were developed and elaborated upon by plant and animal breeders, making quantitative genetics a more applied field than the largely theoretical field of population genetics. Previously, when I taught the introductory population genetics class for BIOL 121 I remarked on how the unit by which evolution is measured is the population. Thus, I sought in this class to connect the principles of quantitative genetics back to population genetics and evolutionary biology as a whole.

I began by explaining that the origin of quantitative genetics came up from a long debate over the inheritance of traits. After Charles Darwin published his theory of evolution in 1857, one element that still eluded him and other researchers at the time was the mechanism by which evolution could occur. The rediscovery of Gregor Mendel’s work in 1900 seemingly cleared the air: traits would be controlled by an allele, and you would get one copy from either parent. Dominance of certain alleles could ensure that certain phenotypes would be more prevalent in the population. However, some researchers were not content with this approach to explaining inheritance of quantitative traits. Eventually, the statistician Ronald Fisher proposed a model that would help bridge the two groups: traits are controlled by a theoretically infinite number of alleles, each with a varying level of effect on the trait. This model still largely holds true today, and can help us see how quantitative traits might evolve or be selected for.

I continued by explaining how phenotypic variation in traits, that is, the differences that we see, are a product of genetics and the organism’s environment. I used iClicker questions to help illustrate how the genetic component can be further broken down, but only the additive effects of each allele controlling the trait can be easily or reliably estimated.

Because quantitative genetics has largely been driven by breeding practice, one of the fundamental values measured is the breeding value. This is a metric of the genetic value of an individual, based on the average value of their offspring. This is a difficult concept to approach for beginners. This is fundamentally another one of those concepts that I find are difficult to properly teach in a classroom setting, as you don’t get a good idea of how researchers use them in a real world setting. I worked through a few basic examples in this case, but I also explained to the class how in reality, these predictions need to be made using thousands of individuals, and can only be accurately obtained using advanced statistical models.

Finally, I tied the topic back to evolutionary biology on a larger scale by demonstrating how we can use the information about genetic and environmental components of traits to understand how populations respond to selection, whether it be artificial or natural. Overall, students seemed comfortable with the concepts. It helped that this is a third year course and thus they already have some of the necessary background. I did feel that this class ended up being a little less interactive than some of the others I’ve done. I’m beginning to feel that having a large active learning component is easier in first year courses, where the primary motive is to engage students and to help spark their interest in the field, versus in later courses where it may be necessary to impart more technical and in-depth information. This is of course a generalisation, but it is a patter that has emerged to me, at least.