Phylogenetic trees depict the evolutionary relationships among organisms, and we incorporate phylogenetic tree-thinking into all of our research. Our research in phylogenetics includes both simulation studies and empirical studies. Simulated data are useful for studying the performance of phylogenetic methods and to test assumptions about methods. For our empirical work, we estimate phylogenetic trees to study the systematics and evolutionary biology of our study organisms.
Simulations– We conduct computer simulations aimed at investigating the performance of phylogenetic inference methods. The goal is to identify the demographic situations that lead certain methods to outperform others, and to determine when the addition of data can increase accuracy. Our computer simulations have examined the impacts of migration on species tree inference, and the performance of species tree estimation under other difficult demographic conditions (e.g., rapid radiations, recent speciation, and the anomaly zone). Migration can impact population size and divergence time estimates dramatically, even in situations in which only a small proportion of loci in the genome are experiencing migration.
Empirical work– We are collecting new comparative genomics data for our study systems (reptiles and amphibians, including birds) using new sequencing technologies. Our goal is to assemble data matrices containing large numbers of loci without the need for developing any locus-specific PCR primers. Adopting new sequencing technologies into our research allows us to shift a heavy time-commitment away from labor-intensive data collection and towards more illuminating aspects of the research, including bioinformatics, data analysis, and hypothesis testing. We have conducted comparisons of targeted sequence capture using ultraconserved elements, protein-coding genes, and other highly-conserved loci, single nucleotide polymorphisms (SNPs) obtained with RADseq methods, as well as other reduced-representation library (RRL) approaches. We have also worked with statisticians and software developers to implement new models and methods for phylogenetic inference and species delimitation.
Linkem, C. W., Minin, V. N., and A. D. Leaché. 2016. Detecting the anomaly zone in species trees and evidence for a misleading signal in higher-level skink phylogeny (Squamata: Scincidae).
Systematic Biology, 65:465-477.
Edwards, S. V., Xi, Z., Janke, A., Faircloth, B. C., McCormack, J. E., Glenn, T. C., Zhong, B., Wu, S., Lemmon, E. M., Lemmon, A. R., Leaché, A. D., Liu, L., and C. C. Davis. 2016. Implementing and testing the multispecies coalescent model: a valuable paradigm for phylogenomics.
Molecular Phylogenetics and Evolution, 94:447-462.
Caviedes-Solis, I. W., Bouzid, N. M., Banbury, B. L., and A. D. Leaché. 2015. Uprooting phylogenetic uncertainty in coalescent species delimitation: a meta-analysis of empirical studies.
Current Zoology, 61:866-873. PDF
Leaché, A. D., Banbury, B. L., Felsenstein, J., Nieto-Montes de Oca, A., and A. Stamatakis. 2015. Short tree, long tree, right tree, wrong tree: new acquisition bias corrections for inferring SNP phylogenies.
Systematic Biology, 64:1032-1047. DOI: 10.1093/sysbio/syv053.
Leaché, A. D., Chavez, A. S., Jones, L. N., Grummer, J. A., Gottscho, A. D., and C. W. Linkem. 2015. Phylogenomics of phrynosomatid lizards: conflicting signals from sequence capture versus restriction site associated DNA sequencing.
Genome Biology and Evolution, 7:706-719. PDF
Leaché, A. D., Wagner, P., Linkem, C. W., Böhme, W., Papenfuss, T. J., Chong, R. A., Lavin, B. R., Bauer, A. M., Nielsen, S., Greenbaum, E., Rödel, M-O., Schmitz, A., LeBreton, M., Ineich, I., Chirio, L., Eniang, E. A., Baha El Din, S., Lemmon, A. R., and F. T. Burbrink. 2014. A hybrid phylogenetic-phylogenomic approach for species tree estimation in African Agama lizards with applications to biogeography, character evolution, and diversification.
Molecular Phylogenetics and Evolution, 79:215-230. PDF
Leaché, A. D., Fujita, M. K., Minin, V. N., and R. Bouckaert. 2014. Species delimitation using genome-wide SNP data.
Systematic Biology, 63:534-542. PDF
Leaché, A. D., Harris, R. B., Rannala, B., and Z. Yang. 2014. The influence of gene flow on species tree estimation: A simulation study.
Systematic Biology, 63:17-30. PDF
Leaché, A. D., and B. Rannala. 2011. The accuracy of species tree estimation under simulation: a comparison of methods.
Systematic Biology, 60:126-137. PDF
Brandley, M. C., Warren, D. L., Leaché, A. D., and J. A. McGuire. 2009. Homoplasy and clade support.
Systematic Biology, 58:184-198. PDF
Brandley, M. C., Leaché, A. D., Warren, D. L., and J. A. McGuire. 2006. Are unequal clade priors problematic for Bayesian phylogenetics?
Systematic Biology, 55:138-146. PDF