I aim to understand why organisms have adapted to their environments in such remarkably diverse ways. Unfortunately, achieving this goal is difficult: most evolution has occurred in the past, and ongoing evolution often takes longer than a human lifetime to observe. Therefore, answers to very basic questions – why do some organisms have sex? why do some outcross and others self-fertilise? why are some haploid and others diploid? does adaptation rely on pre-existing variation or new mutations? – remain elusive. Fortunately, we have tools to overcome this: a century of mathematical models of evolution, allied with new genomic datasets and experimental systems where we can manipulate and observe evolution. I use these tools to investigate principles of evolutionary adaptation.
I have particularly focussed on the following topics:
Genetic constraints on sexual dimorphism
Sexual dimorphism is a particularly dramatic form of adaptation, yet males and females share a near-identical genome. To better understand the genetic constraints on the evolution of sexual dimorphism, I have studied sexually antagonistic variants, which are a type of genetic variant that arises due to constraints on the evolution of sexual dimorphism. I identified sexually antagonistic variants in the Drosophila melanogaster genome using a genome-wide association study, described the biological functions of associated genes, and used population genomic analyses to examine global patterns of polymorphism associated with these genes (Ruzicka et al. 2019). I also helped develop new theory to detect sexually antagonistic variation across a complete life-cycle. I tested this theory on human genomic datasets (Ruzicka & Connallon 2022, Ruzicka et al. 2022), as well as datasets from flycatchers and pipefish (Ruzicka et al. 2020).
Sex chromosomes as a lens to quantify aspects of genetics
Sex chromosomes provide a unique opportunity to study evolution because of their asymmetric transmission between the sexes. Using contrasts of X chromosomes and autosomes, I have examined the evolution of deleterious mutations (Ruzicka et al. 2021), the genomic distribution of sexually antagonistic variation (Ruzicka and Connallon 2020, Ruzicka and Connallon 2022), the genomic distribution of inversions that capture locally-adaptive alleles (Connallon et al. 2018), and made inferences about genetic dominance (McDonough et al. 2024).
Linking mathematical theory with data
In evolutionary biology, the connections between theory and data are often loose (e.g., empiricists often rely on verbal models; theoreticians do not always generate empirically testable models; see Haller et al. 2014 and Fitzpatrick et al. 2018, BioScience). My research focuses on bringing mathematical models and data analyses together as much as possible. For example, I helped develop models for metrics of genetic variation on autosomes and the X chromosome, and applied these metrics to human and fruit fly genomic datasets (Ruzicka et al. 2021, Ruzicka and Connallon 2022).