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Title: Computational methods to resolve deep species phylogenies
Author: Levy, Jeremy Mark Jian Ming
ISNI:       0000 0004 7660 7087
Awarding Body: UCL (University College London)
Current Institution: University College London (University of London)
Date of Award: 2019
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The Lophotrochozoa superphylum is amongst the largest in the animal kingdom, leading to many polarising key features of character evolution. Since it was first proposed as a superphylum based on 18S rDNA analysis in 1995, a number of molecular studies have resulted in conflicting phylogenies, further confounding hypotheses on the intrarelationships of its composite phyla. In this thesis, I aim to resolve the Lophotrochozoa phylogeny by implementing a phylogenetic inference pipeline on 129 taxa, including 97 lophotrochozoans. There are five key steps in the process of performing phylogenetic analysis: molecular marker selection, alignment, model selection, tree construction, and method evaluation. This thesis aims to improve, and better our understanding, on four of these stages. Fundamental to tree inference is using high quality phylogenetic markers. I assessed a number of orthology inference methods for their suitability in resolving a difficult to resolve superphyla. I performed a series of tests in order to determine howwell orthologous groups inferred by a series of methods were able to recover the phylogeny of the Lophotrochozoa. To address the problem of optimal model selection, I performed an empirical assessment of partitioning approaches to phylogenetic analysis. Here I found that, despite partitioning techniques being widely used, they do not necessarily improve phylogenetic inference. I present a new distance based phylogenetic inference method. I validated the method on simulated data, and compared its performance to other tree construction methods, assessing its suitability for phylogenetic inference on deep species phylogenies. In order to benchmark and evaluate phylogenetic trees, I developed a new method for assessing their performance at recovering known phylogenetic clades. I also developed a means of visualising distances between phylogenetic trees, allowing us to better evaluate discrepancies in methods and data. Finally, usingmy newly established phylogenetic pipeline, I reconstructed the phylogenetic tree of the Lophotrochozoa.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available