Probalistic Reconciliation Analysis of Genes and Pseudogenes
Tid: On 2015-04-15 kl 09.00
Plats: Air, SciLifeLab
Phylogeneticists have studied the evolution of life from single celled organisms
to the astonishing biodiversity around us for a long time now. The
relationship between species is often expressed as a binary tree - the tree of
life. Availability of fully sequenced genomes across species provides us the
opportunity to investigate and understand the evolutionary processes, and to
reconstruct the gene and species phylogeny in greater detail and more accurately.
However, the effect of interacting evolutionary processes, such as gene
duplications, gene losses, pseudogenizations, and lateral gene transfers, makes
the inference of gene phylogenies challenging.
In this thesis, probabilistic Bayesian methods are introduced to infer gene
phylogenies in the guidance of species phylogeny. The distinguishing feature
of this work from the earlier reconciliation-based methods is that evolutionary
events are mapped to detailed time intervals on the evolutionary time-scale.
The proposed probabilistic approach reconciles the evolutionary events to the
species phylogeny by integrating gene duplications, gene losses, lateral gene
transfers and sequence evolution under a relaxed molecular clock. Genomewide
gene families for vertebrates and prokaryotes are analyzed using this
approach that provides interesting insight into the evolutionary processes.
Finally, a probabilistic model is introduced that models evolution of genes
and pseudogenes simultaneously. The model incorporates birth-death process
according to which genes are duplicated, pseudogenized and lost under
a sequence evolution model with a relaxed molecular clock. To model the
evolutionary scenarios realistically, the model employs two different sequence
evolution models for the evolution of genes and pseudogenes. The reconciliation
of evolutionary events to the species phylogenies enable us to infer
the evolutionary scenario with a higher resolution. Some subfamilies of two
interesting gene superfamilies, i.e. olfactory receptors and zinc fingers, are
analyzed using this approach, which provides interesting insights.
Ämnesområde: Computer Science
Respondent: Muhammad Owais Mahmudi, CB
Opponent: Assoc. Prof. Cedric Chauve, Simon Fraser University
Handledare: Prof. Jens Lagergren