Accurate Inference of Phylogenetic Relationships from Multi-locus Data

Luay Nakhleh of Rice University presented a lecture on March 9, 2010 at 2:00 pm in room 1116 E of the Klaus Advanced Computing Building on the Georgia Tech campus.Runtime: 58:03 minutesAccurate inference of phylogenetic relationships of species, and understanding their relationships with gene trees are two central themes in molecular and evolutionary biology. Traditionally, a species tree is inferred by (1) sequencing a genomic region of interest from the group of species under study, (2) reconstructing its evolutionary history, and (3) declaring it to be the estimate of the species tree. However, recent analyses of increasingly available multi-locus data from various groups of organisms have demonstrated that different genomic regions may have evolutionary histories (called "oegene trees") that may disagree with each other, as well as with that of the species. This observation has called into question the suitability of the traditional approach to species tree inference. Further, when some, or all, of these disagreements are caused by reticulate evolutionary events, such as hybridization, then the phylogenetic relationship of the species is more appropriately modeled by a phylogenetic network than a tree. As a result, a new, post-genomic paradigm has emerged, in which multiple genomic regions are analyzed simultaneously, and their evolutionary histories are reconciled in order to infer the evolutionary history of the species, which may not necessarily be treelike. In this talk, I will describe our recent work on developing mathematical criteria and algorithmic techniques for analyzing incongruence among gene trees, and inferring phylogenetic relationships among species despite such incongruence. This includes work on lineage sorting, reticulate evolution, as well as simultaneous treatment of both. If time permits, I will describe our recent work on population genomic analysis of bacterial data, and the implications on the evolutionary forces shaping the genomic diversity in these populations