Research

An important goal in evolutionary biology is to understand evolutionary relationships between species. Much recent research has focused on developing methods to infer these relationships from the types of data now available from molecular sequences. These include full-genome DNA sequences, sequences of many different genetic loci, and multi-locus gene trees.

One of the main challenges in inferring these species relationships arises from the fact that many data sets involving different species exhibit gene tree incongruence:  some genes relate taxa differently. A common source for this is incomplete lineage sorting (ILS).

Phylogenetic networks are a way to depict species relationships but allow hybridization between species. The Network Multispecies Coalescent model (NMSC) models the formation of gene histories in the presence of Hybridization and ILS. 

My research focuses on understanding what network features are identifiable from distinct sources of data under NMSC. I am also interested in developing statistically consistent network inference methods. 

The origin of the eukaryotic cell was one of the most important transitions in the evolutionary history of life. We now know that the last eukaryotic common ancestral (LECA) cell possessed most ‘modern’ eukaryotic features including a nucleus, a complex endomembrane system, mitosis, etc.

Studying these ancient evolutionary events requires inferring relationships between lineages that diverged over 1.5 billion years ago. However, such deep phylogenetic analyses are often plagued by artifacts. One common challenge is long-branch attraction (LBA), a bias in tree estimation that can incorrectly group distantly related lineages with long branches. Addressing these issues necessitates the development and application of realistic substitution models.

My research focuses on assessing and improving models to accurately reconstruct phylogenetic relationships among ancient organisms, enabling a deeper understanding of evolutionary history.