Research Overview

Research

Rapid environmental change results in elevated extinction rates and thus poses a major threat to biodiversity. One way in which organisms might respond to these changes – and thus persist into the future – is through adaptive evolution. Our research investigates this possibility by connecting traits related to Darwinian fitness (i.e., survival and reproductive success) with their underlying genetic architecture in relevant ecological scenarios. The extent to which evolution is predictable is a major unresolved question in biology, and crucial for understanding how populations will evolve in response to rapidly changing environmental conditions. Although natural selection is a deterministic process, the predictability of evolution might be limited because the ecological sources of selection and the genetic basis of adaptation can be complex. Our research combines a variety of approaches and study systems to help understand this complexity. We generate and test hypotheses about the predictability of evolution through a combination of ecological field experiments, molecular biology, genomics, and computational biology. Our main study systems are threespine stickleback fish (Gasterosteus aculeatus), deer mice (Peromyscus maniculatus), and anolis lizards (A. sagrei and A. carolinensis), but we often work with other organisms too (such as bacteria, Galapagos finches, or Heliconius butterflies). We aim to quantify the contributions of genome-wide genetic variation to fitness, and to understand the ecological and evolutionary forces that have shaped these patterns of variation between individuals, populations, and closely related species.

You can find code that we have developed for our research on our lab GitHub page here.

Methods & Tools

Whole Genome Sequencing (WGS)

Whole-genome sequencing allows us to examine genetic variation across nearly the entire genome rather than focusing on a small number of candidate genes. We use genomic data to reconstruct population histories, measure genetic diversity and inbreeding, identify regions affected by natural selection, and discover variants associated with ecologically important traits. Its greatest value in our research comes from combining it with field experiments, ecological measurements, and information about survival or reproduction. This allows us to move beyond identifying statistical associations and instead connect genetic variation to phenotypes and fitness in natural populations.

Across our study systems, genome-scale approaches also allow us to ask how predictable adaptation is. They can reveal whether similar environments repeatedly favour the same genes and pathways or whether evolutionary outcomes depend on population history, gene flow, and the genetic variation available when selection begins. For example, our work has used these approaches to uncover genes responsible for colour-pattern variation in ball pythons and investigate repeated freshwater adaptation in sticklebacks.

DNA Methylation

DNA methylation is a chemical modification of DNA that can influence how genes are regulated without altering the underlying DNA sequence. We use bisulfite sequencing and related genomic methods to map methylation across the genome and determine how it varies among environments, populations, developmental stages, and experimental treatments.

A central goal of this work is to distinguish several processes that can produce differences in methylation. Some changes are rapid and environmentally induced, potentially contributing to phenotypic plasticity. Others are associated with underlying genetic variation, persist across generations, or have evolved among populations exposed to different environments. Experiments, common-garden studies, and genetic crosses are therefore essential for determining what a methylation difference represents.

We have used these approaches to study responses to predation in guppies, colonization of new environments by anole lizards, marine–freshwater adaptation in sticklebacks, and exposure to different sources of oil pollution in seabirds. Together, these systems allow us to examine how epigenetic variation contributes to organisms’ immediate responses to environmental change and, potentially, to longer-term evolutionary adaptation.

DNA Metabarcoding & eDNA

Many of our projects take advantage of DNA metabarcoding and environmental DNA (eDNA) to gain insights into community dynamics at various spatial scales. For instance, we use the 16S rRNA marker gene to detect microbial communities in both environmental samples (e.g. LEAP mesocosms, seawater in coral reefs) and those associated with living hosts (e.g. coral reef fishes, corals, seabirds). We use marker genes such as COI to survey the diversity of life on coral reefs. In other cases, we use metabarcoding to understand how organisms’ diets change in response to stressors.