GENOME ASSEMBLY AND VARIANT DETECTION USING EMERGING SEQUENCING TECHNOLOGIES AND GRAPH BASED METHODS

The increased availability of genomic data and the increased ease and lower costs of DNA sequencing have revolutionized biomedical research. One of the critical steps in most bioinformatics analyses is the assembly of the genome sequence of an organism using the data generated from the sequencing machines. Despite the long length of sequences generated by third-generation sequencing technologies (tens of thousands of basepairs), the automated reconstruction of entire genomes continues to be a formidable computational task. Although long read technologies help in resolving highly repetitive regions, the contigs generated from long read assembly do not always span a complete chromosome or even an arm of the chromosome. Recently, new genomic technologies have been developed that can ''bridge" across repeats or other genomic regions that are difficult to sequence or assemble and improve genome assemblies by ''scaffolding" together large segments of the genome. The problem of scaffolding is vital in the context of both single genome assembly of large eukaryotic genomes and in metagenomics where the goal is to assemble multiple bacterial genomes in a sample simultaneously. First, we describe SALSA2, a method we developed to use interaction frequency between any two loci in the genome obtained using Hi-C technology to scaffold fragmented eukaryotic genome assemblies into chromosomes. SALSA2 can be used with either short or long read assembly to generate highly contiguous and accurate chromosome level assemblies. Hi-C data are known to introduce small inversion errors in the assembly, so we included the assembly graph in the scaffolding process and used the sequence overlap information to correct the orientation errors. Next, we present our contributions to metagenomics. We developed a scaffolding and variant detection method MetaCarvel for metagenomic datasets. Several factors such as the presence of inter-genomic repeats, coverage ambiguities, and polymorphic regions in the genomes complicate the task of scaffolding metagenomes. Variant detection is also tricky in metagenomes because the different genomes within these complex samples are not known beforehand. We showed that MetaCarvel was able to generate accurate scaffolds and find genome-wide variations de novo in metagenomic datasets. Finally, we present EDIT, a tool for clustering millions of DNA sequence fragments originating from the highly conserved 16s rRNA gene in bacteria. We extended classical Four Russians' speed up to banded sequence alignment and showed that our method clusters highly similar sequences efficiently. This method can also be used to remove duplicates or near duplicate sequences from a dataset. With the increasing data being generated in different genomic and metagenomic studies using emerging sequencing technologies, our software tools and algorithms are well timed with the need of the community

Computational Biology and Chemistry

The use of computers and software tools in biochemistry (biology) has led to a deep revolution in basic sciences and medicine. Bioinformatics and systems biology are the direct results of this revolution. With the involvement of computers, software tools, and internet services in scientific disciplines comprising biology and chemistry, new terms, technologies, and methodologies appeared and established. Bioinformatic software tools, versatile databases, and easy internet access resulted in the occurrence of computational biology and chemistry. Today, we have new types of surveys and laboratories including “in silico studies” and “dry labs” in which bioinformaticians conduct their investigations to gain invaluable outcomes. These features have led to 3-dimensioned illustrations of different molecules and complexes to get a better understanding of nature

Évolution des génomes par mutations locales et globales : une approche d’alignement

Durant leur évolution, les génomes accumulent des mutations pouvant affecter d’un nucléotide à plusieurs gènes. Les modifications au niveau du nombre et de l’organisation des gènes dans les génomes sont dues à des mutations globales, telles que les duplications, les pertes et les réarrangements. En comparant les ordres de gènes des génomes, il est possible d’inférer les événements évolutifs les plus fréquents, le contenu en gènes des espèces ancestrales ainsi que les histoires évolutives ayant menées aux ordres observés. Dans cette thèse, nous nous intéressons au développement de nouvelles méthodes algorithmiques, par approche d’alignement, afin d’analyser ces différents aspects de l’évolution des génomes. Nous nous intéressons à la comparaison de deux ou d’un ensemble de génomes reliés par une phylogénie, en tenant compte des mutations globales. Pour commencer, nous étudions la complexité théorique de plusieurs variantes du problème de l’alignement de deux ordres de gènes par duplications et pertes, ainsi que de l’approximabilité de ces problèmes. Nous rappelons ensuite les algorithmes exacts, en temps exponentiel, existants, et développons des heuristiques efficaces. Nous proposons, dans un premier temps, DLAlign, une heuristique quadratique pour le problème d’alignement de deux ordres de gènes par duplications et pertes. Ensuite, nous présentons, OrthoAlign, une extension de DLAlign, qui considère, en plus des duplications et pertes, les réarrangements et les substitutions. Nous abordons également le problème de l’alignement phylogénétique de génomes. Pour commencer, l’heuristique OrthoAlign est adaptée afin de permettre l’inférence de génomes ancestraux au noeuds internes d’un arbre phylogénétique. Nous proposons enfin, MultiOrthoAlign, une heuristique plus robuste, basée sur la médiane, pour l’inférence de génomes ancestraux et d’histoires évolutives d’un ensemble de génomes représentés aux feuilles d’un arbre phylogénétique.During the evolution process, genomes accumulate mutations that may affect the genome at different levels, ranging from one base to the overall gene content. Global mutations affecting gene content and organization are mainly duplications, losses and rearrangements. By comparing gene orders, it is possible to infer the most frequent events, the gene content in the ancestral genomes and the evolutionary histories of the observed gene orders. In this thesis, we are interested in developing new algorithmic methods based on an alignment approach for comparing two or a set of genomes represented as gene orders and related through a phylogenetic tree, based on global mutations. We study the theoretical complexity and the approximability of different variants of the two gene orders alignment problem by duplications and losses. Then, we present the existing exact exponential time algorithms, and develop efficient heuristics for these problems. First, we developed DLAlign, a quadratic time heuristic for the two gene orders alignment problem by duplications and losses. Then, we developed OrthoAlign, a generalization of DLAlign, accounting for most genome-wide evolutionary events such as duplications, losses, rearrangements and substitutions. We also study the phylogenetic alignment problem. First, we adapt our heuristic OrthoAlign in order to infer ancestral genomes at the internal nodes of a given phylogenetic tree. Finally, we developed MultiOrthoAlign, a more robust heuristic, based on the median problem, for the inference of ancestral genomes and evolutionary histories of extent genomes labeling leaves of a phylogenetic tree