Génomique comparative

La génomique comparative est l'étude comparative de la structure en fonction des génomes de différentes espèces. Elle permet d'identifier et de comprendre les effets de la sélection sur l'organisation et l'évolution des génomes. Ce nouvel axe de recherche bénéficie de l'augmentation du nombre de génomes séquencés et de la puissance des outils informatiques. Une des applications majeures de la génomique comparative est la découverte de gènes et de leurs séquences régulatrices non codantes basée sur le principe de conservation. Gènes en commun Le séquençage de l'ADN a mis en évidence que près de 8 % du génome humain est constitué de séquences d'origine rétrovirale. Ces rétrovirus endogènes représentent des vestiges d'intégrations virales ancestrales qui font maintenant partie du génome des humains. La plupart de ces séquences ont subi plusieurs mutations dues à l'évolution, rendant le rétrovirus généralement défectif mais certains ont gardé leur pouvoir infectieux et jouent m

Improving Comparative Genomic Studies

Cristina Gabriela Ghiurcuta

Comparative genomics aims to understand the structure of genomes and the function of various genomic fragments, by transferring knowledge gained from well studied genomes, to the new object of study. Rapid and inexpensive high-throughput sequencing is making available more and more complete genome sequences. Despite the significant scientific advance, we still lack good models for the evolution of the genomic architecture, therefore analyzing these genomes presents formidable challenges. Early approaches used pairwise comparisons, but today researchers are attempting to leverage the larger potential of multiway comparisons. Current approaches are based on the identification of so called syntenic blocks: blocks of sequence that exhibit conserved features across the genomes under study. Syntenic blocks are in many ways analogous to genesâ -in many cases, the markers are used to constructing them are genes. Like genes they can exist in multiple copies, in which case we could define analogs of orthology and paralogy. However, whereas genes are studied at the sequence level, syntenic blocks are too large for that level of detail - it is their structure and function as a unit that makes them valuable for genome level comparative studies. Syntenic blocks are required for complex computations to scale to the billions of nucleotides present in many genomes; they enable comparisons across broad ranges of genomes because they filter outmuch of the individual variability; they highlight candidate regions for in-depth studies; and they facilitate whole-genome comparisons through visualization tools. The identification of such blocks is the first step in comparative studies, yet its effect on final results has not been well studied, nor has any formalization of syntenic blocks been proposed. Tools for the identification of syntenic blocks yield quite different results, thereby preventing a systematic assessment of the next steps in an analysis. Current tools do not include measurable quality objectives and thus cannot be benchmarked against themselves. Comparisons among tools have also been neglected - what few results are given use superficial measures unrelated to quality or consistency. In this thesis we address two major challenges, and present: (i) a theoretical model as well as an experimental basis for comparing syntenic blocks and thus also for improving the design of tools for the identification of syntenic blocks; (ii) a prototype model that serves as a basis for implementing effective synteny mining tools. We offer an overview of the milestones present in literature, on the development of concepts and tool related to synteny; we illustrate the application of the model and the measures by applying them to syntenic blocks produced by different contemporary tools on publicly available data sets. We have taken the first step towards a formal approach to the construction of syntenic blocks by developing a simple quality criterion based on sound evolutionary principles. Our experiments demonstrate widely divergent results among these tools, throwing into question the robustness of the basic approach in comparative genomics. Our findings highlight the need for a well founded, systematic approach to the decomposition of genomes into syntenic blocks and motivate the second part of the work - starting from the proposed model, we extend the concept with data dependent features and constraints, in order to test the concept on cases of interest.

EPFL2014

Evaluating synteny for improved comparative studies

Cristina Gabriela Ghiurcuta, Bernard Moret

Motivation: Comparative genomics aims to understand the structure and function of genomes by translating knowledge gained about some genomes to the object of study. Early approaches used pairwise comparisons, but today researchers are attempting to leverage the larger potential of multi-way comparisons. Comparative genomics relies on the structuring of genomes into syntenic blocks: blocks of sequence that exhibit conserved features across the genomes. Syntenic blocs are required for complex computations to scale to the billions of nucleotides present in many genomes; they enable comparisons across broad ranges of genomes because they filter out much of the individual variability; they highlight candidate regions for in-depth studies; and they facilitate whole-genome comparisons through visualization tools. However, the concept of syntenic block remains loosely defined. Tools for the identification of syntenic blocks yield quite different results, thereby preventing a systematic assessment of the next steps in an analysis. Current tools do not include measurable quality objectives and thus cannot be benchmarked against themselves. Comparisons among tools have also been neglected-what few results are given use superficial measures unrelated to quality or consistency. Results: We present a theoretical model as well as an experimental basis for comparing syntenic blocks and thus also for improving or designing tools for the identification of syntenic blocks. We illustrate the application of the model and the measures by applying them to syntenic blocks produced by three different contemporary tools (DRIMM-Synteny, i-ADHoRe and Cyntenator) on a dataset of eight yeast genomes. Our findings highlight the need for a well founded, systematic approach to the decomposition of genomes into syntenic blocks. Our experiments demonstrate widely divergent results among these tools, throwing into question the robustness of the basic approach in comparative genomics. We have taken the first step towards a formal approach to the construction of syntenic blocks by developing a simple quality criterion based on sound evolutionary principles.

Oxford University Press2014

Shachi Shailesh Deshpande, Bernard Moret

Many important questions in molecular biology, evolution, and biomedicine can be addressed by comparative genomic approaches. One of the basic tasks when comparing genomes is the definition of measures of similarity (or dissimilarity) between two genomes, for example, to elucidate the phylogenetic relationships between species. The power of different genome comparison methods varies with the underlying formal model of a genome. The simplest models impose the strong restriction that each genome under study must contain the same genes, each in exactly one copy. More realistic models allow several copies of a gene in a genome. One speaks of gene families, and comparative genomic methods that allow this kind of input are called gene family-based. The most powerfulbut also most complexmodels avoid this preprocessing of the input data and instead integrate the family assignment within the comparative analysis. Such methods are called gene family-free. In this article, we study an intermediate approach between family-based and family-free genomic similarity measures. Introducing this simpler model, called gene connections, we focus on the combinatorial aspects of gene family-free genome comparison. While in most cases, the computational costs to the general family-free case are the same, we also find an instance where the gene connections model has lower complexity. Within the gene connections model, we define three variants of genomic similarity measures that have different expression powers. We give polynomial-time algorithms for two of them, while we show NP-hardness for the third, most powerful one. We also generalize the measures and algorithms to make them more robust against recent local disruptions in gene order. Our theoretical findings are supported by experimental results, proving the applicability and performance of our newly defined similarity measures.

Mary Ann Liebert2017

Shachi Shailesh Deshpande, Bernard Moret

Mary Ann Liebert2017

Evaluating synteny for improved comparative studies

Cristina Gabriela Ghiurcuta, Bernard Moret

Oxford University Press2014

Improving Comparative Genomic Studies

Cristina Gabriela Ghiurcuta

EPFL2014

Improving Comparative Genomic Studies

Evaluating synteny for improved comparative studies

New Genome Similarity Measures based on Conserved Gene Adjacencies

New Genome Similarity Measures based on Conserved Gene Adjacencies

Evaluating synteny for improved comparative studies

Improving Comparative Genomic Studies