Our research focuses on a wide range of evolutionary and ecological questions, mostly involving the application of phylogenetic and population genetic tools to try to uncover the dynamics of the molecular evolutionary process within populations and between species.
A common theme to our research is that it involves some aspect of time, either using historical information from RNA viruses or ancient DNA to identify periods of population growth, decline or turnover, and integrating these analyses with climate and environmental data (ancient DNA) or epidemiological records (RNA viruses) to try to identify the causative factors behind the observed changes in genetic diversity.
DR BETH SHAPIRO, PI
The discovery two decades ago that DNA could be extracted and characterised from preserved biological remains motivated an entirely new field in moleular evolution. Using DNA sequences recovered from these remains, it was possible to trace molecular evolutionary processes in species and populations through time, actually watching evolution as it happens. Using DNA techniques, we aim to answer questions such as:
- How does the genetic diversity of populations or communities change in response to climate and other environmental changes?
- How frequent are demographic events such as local extinctions, population replacements and migration, and how do these affect our ability to accurately recover population history?
- How much are the genetic changes we observe due to species- or population-specific traits, such as habitat use, diet specialization, or population structure?
To address these questions, we use experimental and computational technique such as:
- DNA extraction
- PCR amplification
- DNA sequencing
- Phylogenetic analysis
- phylogeny-based population genetic analysis
- multi-proxy (isotope, DNA diversity, paleobotanical records) paleoenvironmental reconstruction
RNA virus evolution
RNA viruses demonstrate particularly high rates of mutation and adaptation, which makes their evolutionary dynamics challenging to understand, but accessible over relatively short periods of time. For examples, whereas it might take 50,000 years for a population of bison to generate sufficient polymorphism by mutation along to be able to trace these differences through time, an RNA viruses might generate similar amounts of diversity in only a few years. One of our main interests is to understand why these evolutionary rates differ so dramatically, both among RNA viruses and between viruses and other organisms. Our research aims to address questions such as:
- How adaptable are RNA viruses, and how do evolutionary constraints (such as epistasis, recombination, transmission bottlenecks, etc) influence rates of neutral and adaptive evolution?
- How old are RNA viruses, and can we use phylogenetic and comparative analyses to predict when and where new viruses are likely to emerge?
Flu virus structure. Click for image source
To address these questions, we technique such as:
- Comparative analyses of viral genomes
- Sequence-based phylogenetic and demographic analysis
- Incorporation of non-sequence data (e.g. structure, genome content, and genome organization) into phylogeny reconstruction
Phylogenetics and molecular evolution
We try to use an integrative approach to our research questions, and are always keen to develop and/or implement new experimental, analytical and bioinformatic techniques. Each data source has unique properties that will influence the utility of standard statistical methods in molecular evolution. Ancient DNA, for example, is characterized by being particularly susceptible to sequence artifacts, caused by DNA damage and the increased potential for contamination by modern sources of DNA. RNA viruses are under the pressure of different evolutionary constraints, for example vector-borne viruses may need to be able to survive the immune defenses of more than one host. We aim to explore how these differences influence the power of various analysis techniques, and to develop new techniques and extensions to existing techniques that will improve our ability to detect, understand, and predict how molecular evolution occurs.