Towards the true tree: Bioinformatic approaches in the phylogenetics and molecular evolution of the Endopterygota
Author(s)
Chesters, Douglas
Type
Thesis
Abstract
In this thesis, I use bioinformatic approaches to address new and existing issues
surrounding large-scale phylogenetic analysis. A phylogenetic analysis pipeline is
developed to aid an investigation of the suitability of integrating Cytochrome Oxidase
Subunit 1 (cox1) into phylogenetic supermatrices. In the first two chapters I assess the
effect of varying cox1 sample size within a large variable phylogenetic context. As well
as intuitive results on increased quality with greater taxon sampling, there are clear
monophyly patters relating to local taxonomic sampling. Specifically, more monophyletic
resampled taxa in cases when fewer consubfamilials are represented, with a tendency for
these to remain unchanged in the degree of monophyly when rarefied. Sampling analyses
are extended in chapter two using a mined Scarabaeoidea multilocus dataset, where taxa
from given loci are used to improve existing matrices. Improvement in phylogenetic
signal is best achieved by targeting cox1 to existing taxa, which suggests minimum
parameters for cox1 adoption in large-scale phylogenetics.
In chapter 3 I address recently-arisen issues related to phyloinformatic analysis of
sequence-delineated matrices. There is ongoing work on setting species boundaries by
sequence variation alone, but incongruence results in methodological issues upon
integrating multiple loci delineated in this way.
In the final chapter I assess the impact of heterogeneous substitution rates on large scale
cox1 datasets. Although the number of heterogeneous sites in Coleoptera cox1 is
substantial, their presence is found to be beneficial, as their removal negatively impacts
the ability of the alignment to generate the 'known' topology. The homoplasy and
heterogeneous characteristics of cox1 have not substantially impacted its utility, thus the
cox1 datasets have potential to play a substantial role in the tree-of-life.
surrounding large-scale phylogenetic analysis. A phylogenetic analysis pipeline is
developed to aid an investigation of the suitability of integrating Cytochrome Oxidase
Subunit 1 (cox1) into phylogenetic supermatrices. In the first two chapters I assess the
effect of varying cox1 sample size within a large variable phylogenetic context. As well
as intuitive results on increased quality with greater taxon sampling, there are clear
monophyly patters relating to local taxonomic sampling. Specifically, more monophyletic
resampled taxa in cases when fewer consubfamilials are represented, with a tendency for
these to remain unchanged in the degree of monophyly when rarefied. Sampling analyses
are extended in chapter two using a mined Scarabaeoidea multilocus dataset, where taxa
from given loci are used to improve existing matrices. Improvement in phylogenetic
signal is best achieved by targeting cox1 to existing taxa, which suggests minimum
parameters for cox1 adoption in large-scale phylogenetics.
In chapter 3 I address recently-arisen issues related to phyloinformatic analysis of
sequence-delineated matrices. There is ongoing work on setting species boundaries by
sequence variation alone, but incongruence results in methodological issues upon
integrating multiple loci delineated in this way.
In the final chapter I assess the impact of heterogeneous substitution rates on large scale
cox1 datasets. Although the number of heterogeneous sites in Coleoptera cox1 is
substantial, their presence is found to be beneficial, as their removal negatively impacts
the ability of the alignment to generate the 'known' topology. The homoplasy and
heterogeneous characteristics of cox1 have not substantially impacted its utility, thus the
cox1 datasets have potential to play a substantial role in the tree-of-life.
Date Issued
2011
Date Awarded
2011-07
Advisor
Vogler, Alfried
Quickie, Donald
Creator
Chesters, Douglas
Publisher Department
Biology
Publisher Institution
Imperial College London
Qualification Level
Doctoral
Qualification Name
Doctor of Philosophy (PhD)