Bhagya Chattanahalli Thimmappa
Philosophiae doctor (Ph.D.) in Bioinformatics
Interactions between the endophytic fungus Codinaeella sp. EC4 and its cranberry plant host.
Most plants associate with microbes, either living within plant tissues (endophytes) or on the plant surface (exophytes). Such microorganisms can play a vital role in plant health and growth. Some endophytes, referred to as biocontrol agents, protect plants from pathogens, while others, known as biofertilizers, promote plant growth. The best-studied endophytes are Arbuscular mycorrhizal fungi (AMF), which colonize about 90% of all plant species. In turn, the most investigated groups of plant hosts are Poaceae and Gramineae. Ericaceae are a large family of flowering plants and one of the few groups that do not associate with AMF but a diverse collection of other so-called ericoid mycorrhizal fungi. Ericaceae thrive in nutrient-poor, acidic soil, probably facilitated by endosymbionts. While endosymbionts of certain ericaceous plants, such as blueberries, have been well investigated, research on a commercially important North American crop, cranberry (Vaccinium Macrocarpon Aiton) plants, is still in its early stages. Our group isolated and characterized numerous fungal and bacterial endosymbionts from the roots of cranberry plants cultivated in Québec, Canada, and identified endophytes with plant growth promotion or biocontrol potential. One of the fungal isolates, Endophytic Champignon 4 (EC4), is notable because it promotes growth and suppresses pathogens of cranberry plants. By phylogenetic analyses, we demonstrate that EC4 is a Codinaeella sp. from the Chaetospheriaceae family of Sordariomycetes (Ascomycota). EC4 colonizes plant roots intracellularly, with hyphae around roots. EC4 encodes nutrient transport and phytohormone genes in its nuclear genome and expresses some of them when in contact with cranberry plant roots. EC4 potentially controls the growth of fungal and oomycete plant pathogens by secreting hydrolytic enzymes and secondary metabolites, as observed from genomic and transcriptomic studies. Further, EC4 encodes and expresses secreted effector proteins (molecules that are involved in the microbe-host interactions), which are likely involved in communication and establishment of symbiosis with its host. We observed a variation in the transcriptome when the pathogen Diaporthe is co-cultured with EC4. This provides a unique opportunity to investigate the molecular dynamics of interactions between microbe species sharing the same plant host. Our findings also open new avenues for comparing the gene complement of the endosymbiotic EC4 with non-symbiotic Codinaeella species. With a potential biofertilization and biocontrol ability, EC4 holds promise for sustainable agriculture.
Primary supervisor:
Gertraud Burger, Université de Montréal
Permalink:
https://hdl.handle.net/1866/33762
2018-2024
Aseel Awdeh
Philosophiae doctor (Ph.D.) in Computer Science
Wide Scale Analysis of Transcription Factor Biases and Specificity
Cell type specific states are maintained via the binding of multiple regulatory proteins to different locations along the genome in a process known as transcriptional regulation. Additionally, disruptions to the transcriptional regulation process may lead to the development of disease. Hence, uncovering the complex interplay of protein-DNA interactions along the genome is of critical importance. The first part of the thesis involves the study of the biases and noise associated with ChIP-seq experiments. Another aspect we explore in this thesis is the ability to uncover cell type specificity of transcription factor binding from the ChIP-seq data. A transcription factor may bind to various parts of the genome in different cell types, due to modifications in the DNA-binding preferences of the transcription factor, or other mechanisms, such as chromatin accessibility or cooperative binding, thus leading to a "DNA signature" of differential binding. We develop a deep learning approach, called SigTFB (Signatures of TF Binding) and conduct a wide scale analysis of hundreds of transcription factors to identify and quantify the varying degrees of cell type specific DNA signatures of various transcription factors across cell types. We also assess the consistency of cell type specificity for a specific transcription factor when assayed by different antibodies. We show that many transcription factors are indeed cell type specific, while others are more general with lower cell type specificity. Finally, to further explain the biology behind a transcription factor's cell type specificity, or lack that of, we conduct a wide scale motif enrichment analysis of all transcription factors in question. We show that cell type specific transcription factors are typically associated with corresponding differences in motif enrichment and gene expression. Together, these contributions deepen our knowledge of transcription factor binding, and how experimental and cell type specific variations can be uncovered.
Primary supervisor:
Theodore J. Perkins, Ottawa Hospital Research Institute
Permalink:
https://ruor.uottawa.ca/handle/10393/44298
2015-2022
Kevin Sutanto
Master of Computer Science (M.C.S.) Specialization in Bioinformatics
RNA Sequence Classification using Secondary Structure Fingerprints, Sequence-Based Features,
and Deep Learning. Like proteins, functional RNAs are able to fold into complex structures
in order to perform specific functions throughout their lifecycle. We hypothesized that
using a representation that includes the multiple possible secondary structures of an RNA
for classification purposes may improve the classification performance.
Permalink:
http://hdl.handle.net/10393/41876
2019-2021
Amirhossein Hajianpour
Master of Computer Science (M.C.S.) Specialization in Bioinformatics
ExonHunter
(EH): Simple
and Fast
Homology-based
Gene
Prediction in
Mitochondrial
Genomes. With
the abundance
of genomic
data after the
Human Genome
Project, the
need for
analysis, and
annotation of
these data
arise. Annotation
of genomes
helps us
understand the
functionality
of different
parts of the
genomes of
various
species. In
this thesis,
we propose a
simple, and
fast
homology-based
gene
prediction
method called
Exon Hunter
(EH) that
achieves a
performance
comparable
with
state-of-the-art
methods in
mitochondrial
genomes. Mitochondria
are crucial
for a
eukaryotic
cell, and
mutation in
its DNA has
connections
with disorders
such as
Alzheimer and
cancer. We
used Hidden
Markov Model
(HMM) Protein
Profile of a
number of
genes to
search for
protein-coding
genes in
different
genomes. Our
method forms
every subset
of the hit
set, and
calculates a
score for each
subset
according to
an objective
function. Then
it chooses the
subset with
the highest
score. Finally,
we analyze the
codon usage
bias of our
dataset, and
we discuss how
it can help us
improve this
prediction. ExonHunter
is written in
Python and is
publicly
available on
github.com/amirh-hajianpour/ExonHunter.
Permalink:
https://hdl.handle.net/10393/43057
2018-2021
Sandrine Moreira Rousseau
Philosophiae doctor (Ph.D.) in Bioinformatics
Discovery of new strategies for encrypting genetic information in eukaryotes, and the
identification of molecular decoding processes in a group of poorly studied marine protists,
the Diplonemids.
Primary supervisor:
Gertraud Burger, Université de Montréal
Permalink:
http://hdl.handle.net/1866/18548
2010-2016
Manuel Belmadani
MASTER OF COMPUTER SCIENCE (M.C.S.) SPECIALIZATION IN BIOINFORMATICS
MotifGP is a multiobjective motif discovery tool evolving regular expressions that
characterize overrepresented motifs in a given input dataset. This thesis describes and
evaluates a multiobjective strongly typed genetic programming algorithm for the discovery of
network expressions in DNA sequences.
Permalink:
http://hdl.handle.net/10393/34213
2012-2016
Julien Horwood
Undergraduate Student Summer Internship
Python implementation of Fast Text Searching for Regular Expressions on Tries
2015
Aseel Awdeh
MASTER OF COMPUTER SCIENCE (M.C.S.) SPECIALIZATION IN BIOINFORMATICS
Inferring regulatory relationships between genes, including the direction and the nature of
influence between them, is the foremost problem in the field of genetics. The thesis
explores the possibility of dynamic epistasis analysis.
Primary supervisor:
Theodore J. Perkins, Ottawa Hospital Research Institute
Permalink:
http://hdl.handle.net/10393/32747
2013-2015
Alexander Gawronski
MASTER OF COMPUTER SCIENCE (M.C.S.) SPECIALIZATION IN BIOINFORMATICS
Frequent subgraph mining is a useful method for extracting biologically relevant patterns
from a set of graphs or a single large graph. In this thesis, the graph represents all
possible RNA structures and interactions. The algorithm was applied to the mitochondrial
genome of the kinetoplastid species Trypanosoma brucei.
Permalink:
http://hdl.handle.net/10393/26296
2011-2013
Victor Hugo Sperle Campos
Undergraduate International Student from Brazil Internship
Multiple Protein Sequence Alignment, Tree Length, Median String Problem, Asymmetrical
Substitution Score.
2013
Oksana Korol
MASTER OF COMPUTER SCIENCE (M.C.S.) SPECIALIZATION IN BIOINFORMATICS
An approach aimed at discovering patterns in a set of DNA sequences based on the location of
transcription factor binding sites or any other biological markers with the emphasis of
discovering relationships. A variety of statistical and computational methods exists to
analyze such data. However, they either require an initial hypothesis, which is later
tested, or classify the data based on its attributes. This approach does not require an
initial hypothesis and the classification it produces is based on the relationships between
attributes.
Permalink:
http://hdl.handle.net/10393/20320
2009-2011
Etienne Elie
Philosophiae doctor (Ph.D.) in Computer Science
Approche efficace pour la conception des architectures multiprocesseurs sur puce
électronique. Nous nous intéressons à un modèle architectural, appelé architecture
isométrique de systèmes multiprocesseurs sur puce, qui permet d'évaluer, de prédire et
d'optimiser les systèmes OCM en misant sur une organisation efficace des nœuds (processeurs
et mémoires), et à des méthodologies qui permettent d'utiliser efficacement ces
architectures.
Primary supervisor:
Abedl Hakim Hafid, Université de Montréal
Co-supervisor:
Jacques Ferland, Université de Montréal
Permalink:
http://hdl.handle.net/1866/6841
2006-2011
Mikhail (Misha) Jiline
Philosophiae doctor (Ph.D.) in Computer Science
The thesis proposes a novel logic-based Annotation Concept Synthesis and Enrichment Analysis
(ACSEA) approach. In this approach, the source annotation information, experimental data and
uncovered enriched annotations are represented as First-Order Logic (FOL) statements.
Primary supervisor:
Stan Matwin, Dalhousie University
Permalink:
http://hdl.handle.net/10393/19712
2006-2010
Ghada Badr
Postdoctoral Fellow
We proposed two algorithms for locating all the occurrences of a given interaction pattern
in a set of RNA sequences. The baseline algorithm implements an exhaustive backtracking
search. The second algorithm also finds all the matches, but uses additional data structures
in order to considerably decrease the execution time, sometimes by one order of magnitude.
2009-2011
Predrag Mizdrak
Master of Computer Science (M.C.S.)
Multiple sequence alignment (MSA) and phylogeny tree reconstruction are two imporant
problems in bioinformatics. In some respect, they represent "two sides of the same coin",
since solving either of the two problems would be easier if the solution to the other
problem was given. The thesis proposes a new method that addresses these shortcomings by
iteratively improving the starting alignment and its corresponding evolutionary tree based
on maximum likelihood scores.
Co-supervisor:
Stéphane Aris-Brosou
Permalink:
http://hdl.handle.net/10393/28253
2008-2009
Sivakumar Kannan
Postdoctoral Fellow
RNA sequence and structure motif discovery in Diplonema papillatum.
Primary supervisor:
Gertraud Burger, Université de Montréal
2008
Stephen Baird
Philosophiae doctor (Ph.D.) in Microbiology and Immunology Specialization in Human and
Molecular Genetics
The standard method of translation initiation, where the ribosome binding onto mRNA is
mediated by initiation factors that congregate at the 5' "cap-nucleotide" of the RNA, is at
times, partially disabled. For example, during viral infection, mitosis, and cellular
stress, the efficiency of this form of initiation is reduced relative to an alternate
mechanism of initiation that utilizes Internal Ribosome Entry Sites (IRESes) contained in
the 5' UTR sequence of viral and cellular RNA transcripts. The thesis investigates the
structure of cellular IRES.
Primary supervisor:
Robert Korneluk
Cosupervisor:
Martin Holcik
Permalink:
http://hdl.handle.net/10393/29386
2000-2006
Amelia Bellamy-Royds
Undergraduate Student Summer Internship
Progressive simultaneous alignment and structure prediction of multiple RNA sequences. The
research presented here investigates the possibility of applying a progressive, pairwise
approach to the alignment of multiple RNA sequences by simultaneously predicting an
energy-optimized consensus secondary structure. We take an existing algorithm for finding
the secondary structure common to two RNA sequences, Dynalign, and alter it to align
profiles of multiple sequences. We then explore the relative successes of different
approaches to designing the tree that will guide progressive alignments of sequence profiles
to create a multiple alignment and prediction of conserved structure.
PubMed ID:
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1904245/
2006
Mohammad Anwar
Master of Computer Science (M.C.S.)
Implementation and evaluation of scoring schemes for the automated discovery of nucleic acid
structures. Extends the work of Nguyen (M.A.Sc thesis, Electrical Engineering, University of
Ottawa, 2004) who introduced a novel approach for discovering consensus secondary structure
motifs in a set of unaligned RNA sequences. The algorithm has been implemented in a software
system called Seed. The aim of this thesis is to devise, implement and evaluate (3) scoring
schemes for the software system.
Permalink:
http://hdl.handle.net/10393/27220
2004-2006
Mohak Shah
Philosophiae doctor (Ph.D.) in Computer Science
Sample compression, margins and generalization: Extensions to the set covering machine. This
thesis studies the generalization behavior of algorithms in Sample Compression Settings. It
extends the study of the Sample Compression framework to derive data-dependent bounds that
give tighter guarantees to the algorithms where data-independent bounds such as the VC
bounds are not applicable.
Primary supervisor:
Mario Marchand, Université Laval
Permalink:
http://hdl.handle.net/10393/29372
2004-2006
Beeta Masoumi
Master of Computer Science (M.C.S.)
Simultaneous alignment and structure prediction for three ribonucleic acid sequences. Using
more input sequences should improve the accuracy, reduce the likelihood that bad predictions
are made, but also lower the sensitivity. To investigate these claims, we have extended the
software system Dynalign to use three input sequences, rather than two, and tested our
algorithm with 10 tRNAs and 13 5S rRNAs.
Permalink:
http://hdl.handle.net/10393/26974
2003-2005
Truong Nguyen
Master of Applied Science (M.A.Sc.) in Electrical Engineering
Transcription and translation are critical steps through which genetic expression occurs.
Whereas there exists research for computationally determining the primary structure binding
sites for transcription, research into the computational elucidation of secondary structure
binding sites for translation has not been as thoroughly conducted. The approach proposed
involves first selecting a single sequence from a set of data sequences. From this sequence,
all biological palindromes are determined. Using these palindromes, all possible candidate
secondary structure motifs with minimum support are assembled, formulating the solution
space. The motifs in the solution space are reduced to structural form. These structures are
searched against the remaining sequences.
Permalink:
http://hdl.handle.net/10393/26727
2002-2004
Chunfang Zheng
NSERC Undergraduate Student Research Awards (USRA)
Covariation analyses for the study of protein contacts.
2003
Victor Jin
Master of Computer Science (M.C.S.)
A Computational Approach to the Analysis of Localized Interspersed Motifs in Complete
Genomic Sequences.
2000-2003
(