We aim to understand the evolutionary forces that shape natural diversity within and between populations, by developing new population genetic theory and using novel statistical methods to analyze complex data. We have focused on phenomena driven by antagonistic genetic interactions, such as the evolution of sex chromosomes, regulatory divergence, and hybrid incompatibilities.
Evolution of sex chromosomes in plants
Sex is arguably the largest source of variance within species. Consequently, sex chromosomes are key elements of the biology and evolution in species with genetic sex determination. Sex chromosomes follow a fascinating evolutionary trajectory, involving the accumulation of sex-antagonistic genes followed by the suppression of recombination--often by chromosome inversions. The lack of recombination leads to high levels of divergence between the homologous pair and the degeneration of one of the chromosomes (e.g., the Y chromosome of mammals). However, many questions about this trajectory remain open, for example regarding the mode and tempo of sexual antagonism or the evolutionary forces that interact to favor or prevent the spread of chromosome inversions. We have contributed to some of these issues, specifically by generating models that predict levels of sequence divergence in sex chromosomes, describing the expected signatures of sex-antagonistic selection, and developing methods to estimate extremely low levels of recombination. Currently, we are working towards the application of these models to the study of recently evolved sex chromosome systems in plants. 'Young' sex chromosomes offer a unique perspective on the origin of sex and the dynamics of sex-linked genomic regions, and can tell us about the conditions that affect the evolution of recombination suppression, subsequent sex-chromosome divergence and potential degeneration.
Chromosomal variation plays an important role in many evolutionary processes, including local adaptation and speciation. Advances in sequencing technology have shown that rearrangements are ubiquitous in nature and have opened up the possibility of testing hypotheses about the evolutionary forces maintaining chromosomal polymorphism using population genomic data. However, we lack an adequate theoretical and statistical framework for such tests. To this end, we have developed models to study the conditions under which rearrangements evolve and the molecular signatures associated with these evolutionary histories. We were also involved in developing algorithms for the efficient simulation of polymorphic chromosome inversions and informative summary statistics for population genomic data from these regions, and in implementing likelihood approaches to quantifying the evolutionary forces that maintain inversion clines in nature.
Population divergence and speciation
As populations evolve, chance and natural selection drive them apart. We have contributed to our understanding of the speciation process in two ways. First, by defining how speciation can leave genetic signatures that can confound statistical searches for natural selection and developing methods to quantify these potential confounders. Second, by describing how the divergence process uncovers the dramatic extent to which genetic interactions are present throughout the genome. We have characterized these antagonistic interactions, manifest in the dysregulation of gene expression and inviability of hybrids. We found evidence of widespread antagonistic interactions among multiple loci involved in genetic incompatibility, which could have critical consequences for the tempo of speciation by decoupling the accumulation of isolation loci and phenotypes, therefore attenuating the rate of accumulation of hybrid infertility among lineages.
Genetic interactions & applications to disease and public health
We can leverage insights from evolutionary biology to better understand and prevent disease. For instance, we can gain power in the computational prediction of the pathogenicity of mutations by incorporating comparative and demographic data. In turn, many diseases represent fascinating cases to study genetic interactions. Abnormal pregnancy outcomes (such as preterm birth, pre-eclampsia, and heart disease) have been linked to an antagonistic interaction between maternal and fetal genes called maternal-fetal genotype incompatibility (MFGI). We are currently involved in multiple projects that apply evolutionary genetics in medicine, specifically studying epistatic interactions in the genetic basis of antibiotic resistance and metabolic diseases.