We're interested in the factors that shape diversity.
We're interested in the factors that shape diversity.
We are interested in understanding the evolutionary history of communities, species, populations, and individuals; the effects of genetic diversity on community structure; and the effects of variable genotypes on phenotypes under strong selection. To address questions in each of these areas, we generally use non-model organisms because their biology offers elegant tests of the hypotheses in which we're interested. Because we often work with non-model species, we also develop and use genomic and computational tools to facilitate our work with these organisms, and much of our work is "integrative" or "cross-disciplinary" - we use theory and tools from the fields of evolutionary biology, computational biology, molecular biology, organismal biology, genetics (few genetic regions), and genomics (many/all genetic regions) to help us address our questions. Below are general descriptions of several projects on which we're currently working. If you have any questions about these projects or any of our other work, please contact us.
Historically, the identification of a large suite of universal genetic markers shared among divergent, non-model taxa was viewed as a sort of molecular or phylogenetic "Holy Grail". This type of marker would allow us to collect data from thousands of loci across thousands of taxa rather easily, perform genetic analyses at different time scales, and ideally provide us a mechanism to understand how evolutionary history shapes genetic diversity among species subject to the same environment (or how different environments shape the genetic diversity of species having similar evolutionary histories). In 2004, the discovery of highly conserved elements shared among the genomes of taxa spanning millions of years of evolutionary history (ultraconserved elements or UCEs) offered the intriguing possibility that UCEs are, outside of their putative, functional importance, one class of this idealized, universal, genetic marker.
During the previous five years, much of our research has centered on developing methodological and computational techniques using UCEs to answer these types of questions. We have shown that UCEs are universally conserved within major taxonomic groups like amniotes and ray-finned fishes (Faircloth et al. 2012, Faircloth et al. 2013), and we have demonstrated that UCEs record sufficient evolutionary history to reconstruct phylogeny (McCormack et al. 2012). We have combined our identification of UCEs with target enrichment, library multiplexing, and massively parallel sequencing to demonstrate that UCEs contain and are flanked by variable and informative sequence, even at the population (Smith et al. 2013) and individual-levels (Faircloth et al. 2012).
Using these techniques, we have clarified several historically contentious evolutionary hypotheses including the phylogenetic position of turtles (Crawford et al. 2012), the relationships among species comprising the Neoaves (McCormack et al. 2013), and the branching order of the early diverging teleosts (Faircloth et al. 2013).
Our ongoing work in this area focuses on: (1) continuing to resolve relationships among species comprising the Neoaves (as part of the BGI/Duke/Copenhagen Avian Phylogenomics Project); (2) understanding the reduced rate of molecular evolution in crocodilians (as part of the Crocodilian Genomes Project (St. John et al. 2012), and (3) using the conservation of UCEs across divergent taxa, and the apples-to-apples genetic comparisons they allow, to understand how evolutionary history and environment shape genetic diversity at the community, clade, species, population, and individual levels.
Tropical rainforests harbor an incredible diversity of tree species, and the source of this diversity is poorly understood. We have developed a new hypothesis, the Enemy Susceptibility Hypothesis or ESH, which states that tropical tree species diversity is driven by the susceptibility of different species to their pathogenic invaders, particularly basidiomycete fungi - which are the root cause of death in many tropical trees. While the ESH has many predictions, one over-arching prediction is that rare tree species are infected by a larger number of fungal pathogens than common tree species and that the fungi infecting rare tree species are more phylogenetically diverse. Using support from the National Science Foundation Dimensions of Biodiversity program, we are combining field tomography of tree stems (to identify infected trees having heart-rot) with stem sampling, pathogencity tests of fungi cultured from stem samples, genetic estimates of pathogens occupying stem samples, and phylogenetic analyses of pathogens to test this primary prediction of the ESH.
Additionally, we are using de novo whole genome and transcriptome sequencing to test a secondary prediction of the ESH - that common pathogenic fungi are more genetically and phenotypically diverse than their rare counterparts. Specifically, we are testing the effects of genomic and transcriptomic diversity on host range and pathogen virulence by sequencing the genomes of 24 phylogenetically diverse fungal pathogens and the transcription products of these pathogens when applied to 12 wood cultures derived from numerically and phylogenetically diverse host tree species (a host x pathogen matrix).
Recent increases in sequencing efficiency, combined with recent advances in remote-sensing techniques, allow us to identify individuals and collect genotype, phenotype, and environmental data at the landscape scale. As part of an NSF-funded team, we are using these gains in efficiency to sequence the genomes of two tropical forest trees and sequence the transcription products of leaf tissue collected from each species. We are using these genomic data as the base against which we will analyze low-cost SNP genotypes (of coding and non-coding regions) relative to remotely-collected measurements of foliar chemical properties and canopy structure across a tropical forest landscape.
The goal of this laboratory and field work is to better-understand the relationship between genealogy, genetic variation, environmental variation, and phenotypic plasticity. Specifically, we are integrating these different data sources to test whether functional genetic diversity of tree lineages is associated with environment, functional genetic diversity of lineages is associated with lineage abundance, foliar chemical phenotypes are associated with functional genetic variation, foliar chemical phenotypes are associated with environmental variation, and/or lineages are associated with environmental variation.