Modélisation et comparaison de la structure de gènes

La bio-informatique est un domaine de recherche multi-disciplinaire, à la croisée de différents domaines : biologie, médecine, mathématiques, statistiques, chimie, physique et informatique. Elle a pour but de concevoir et d’appliquer des modèles et outils statistiques et computationnels visant l’avancement des connaissances en biologie et dans les sciences connexes. Dans ce contexte, la compréhension du fonctionnement et de l’évolution des gènes fait l’objet de nombreuses études en bio-informatique. Ces études sont majoritairement fondées sur la comparaison des gènes et en particulier sur l’alignement de séquences génomiques. Cependant, dans leurs calculs d’alignement de séquences génomiques, les méthodes existantes se basent uniquement sur la similarité des séquences et ne tiennent pas compte de la structure des gènes. L’alignement prenant en compte la structure des séquences offre l’opportunité d’en améliorer la précision ainsi que les résultats des méthodes développées à partir de ces alignements. C’est dans cette hypothèse que s’inscrit l’objectif de cette thèse de doctorat : proposer des modèles tenant compte de la structure des gènes lors de l’alignement des séquences de familles de gènes. Ainsi, par cette thèse, nous avons contribué à accroître les connaissances scientifiques en développant des modèles d’alignement de séquences biologiques intégrant des informations sur la structure de codage et d’épissage des séquences. Nous avons proposé un algorithme et une nouvelle fonction du score pour l’alignement de séquences codantes d’ADN (CDS) en tenant compte de la longueur des décalages du cadre de traduction. Nous avons aussi proposé un algorithme pour aligner des paires de séquences d’une famille de gènes en considérant leurs structures d’épissage. Nous avons également développé un algorithme pour assembler des alignements épissés par paire en alignements multiples de séquences. Enfin, nous avons développé un outil pour la visualisation d’alignements épissés multiples de famille de gènes. Dans cette thèse, nous avons souligné l’importance et démontré l’utilité de tenir compte de la structure des séquences en entrée lors du calcul de leur alignement

Assessing the impact of alternative splicing on the diversity and evolution of the proteome in plants

Splicing is one of the key processing steps during the maturation of a gene’s primary transcript into the mRNA molecule used as a template for protein production. Splicing involves the removal of segments called introns and re-joining of the remaining segments called exons. It is by now well established that not always the same segments are removed from a gene’s primary transcript during the splicing process. The consequence of this splicing variation, termed Alternative Splicing (AS), is that multiple distinct mature mRNA molecules can be produced from a single gene. One of the two biological roles that are ascribed to AS is that of a mechanism which enables an organism to produce multiple functionally distinct proteins from a single gene. Alternatively, AS can serve as a means for controlling gene expression at the post-transcriptional level. Although many clear examples have been reported for both roles, the extent to which AS increases the functional diversity of the proteome, regulates gene expression or simply reflects noise in splicing machinery is not well known. Determining the full functional impact of AS by designing and performing wet-lab experiments for all AS events is unfeasible and bioinformatics approaches have therefore widely been used for studying the impact of AS at a genome-wide scale. In this thesis four bioinformatics studies are presented that were aimed at determining the extent to which AS is used in plants as a mechanism for producing multiple distinct functional proteins from a single gene. Each chapter uses a different method for analyzing specific properties of AS. Under the premise that functional genetic features are more likely to be conserved than non-functional ones, AS events that are present in two or more species are more likely to be biologically relevant than those that are confined to a single species. In chapter 2 we analyzed the conservation of AS by performing a comparative analysis between three divergent plant species. The results of that study indicated that the vast majority of AS events does not persist over long periods of evolution. We concluded, based on this lack of conservation, that AS only has a limited impact on the functional diversity of the proteome in plants. Following this conclusion, it can hypothesized that the variation that AS induces at the transcriptome level is not likely to be manifested at the protein level. In chapter 3 we tested this hypothesis by analyzing two independent proteomics datasets. This type of data can be used to directly identify proteins present in a biological sample. Our results indicated that the variation induced by AS at the transcriptome level is also manifested at the protein level. We concluded that either many AS events have a confined species-specific (not conserved) function or simply produce protein variants that are stable enough to escape rapid turn-over. Another method for determining whether AS increases the functional diversity of the proteome is by determining whether protein sequence variations that are typically induced by AS are common within the plant kingdom. We found (chapter 4) that this is not the case in plants and concluded that novel functions do not frequently arise through AS. We also found that most of the AS-induced variation is lost, similarly as for redundant gene copies, within a very short evolutionary time period. One limitation of genome-wide analyses is that these capture only the more general patterns. However, the functional impact of AS can be very different in different genes or gene-families. In order fully assess the functional impact of AS, it is therefore important to also study the process within the functional context of individual genes or gene families. In chapter 5 we demonstrated this concept by performing a detailed analysis of AS within the MADS-box gene family. We were able to provide clues as to how AS might impact the protein-protein interaction capabilities of individual MADS proteins. Some of our predictions were supported by experimental evidence. We further showed how AS can serve as an evolutionary mechanism for experimenting with novel functions (novel interactions) without the explicit loss of existing functions. The overall conclusion, based on the performed analyses is as follows: AS primarily is a consequence of noise in the splicing machinery and results in an increased diversity of the proteome. However, only a small fraction of the proteins resulting from AS will have beneficial functions and are subsequently selected for during evolution. The large remaining fraction is, similarly as for redundant gene-copies, lost within a very short evolutionary time period after its emergence. </p

Noisy splicing, more than expression regulation, explains why some exons are subject to nonsense-mediated mRNA decay

<p>Abstract</p> <p>Background</p> <p>Nonsense-mediated decay is a mechanism that degrades mRNAs with a premature termination codon. That some exons have premature termination codons at fixation is paradoxical: why make a transcript if it is only to be destroyed? One model supposes that splicing is inherently noisy and spurious transcripts are common. The evolution of a premature termination codon in a regularly made unwanted transcript can be a means to prevent costly translation. Alternatively, nonsense-mediated decay can be regulated under certain conditions so the presence of a premature termination codon can be a means to up-regulate transcripts needed when nonsense-mediated decay is suppressed.</p> <p>Results</p> <p>To resolve this issue we examined the properties of putative nonsense-mediated decay targets in humans and mice. We started with a well-annotated set of protein coding genes and found that 2 to 4% of genes are probably subject to nonsense-mediated decay, and that the premature termination codon reflects neither rare mutations nor sequencing artefacts. Several lines of evidence suggested that the noisy splicing model has considerable relevance: 1) exons that are uniquely found in nonsense-mediated decay transcripts (nonsense-mediated decay-specific exons) tend to be newly created; 2) have low-inclusion level; 3) tend not to be a multiple of three long; 4) belong to genes with multiple splice isoforms more often than expected; and 5) these genes are not obviously enriched for any functional class nor conserved as nonsense-mediated decay candidates in other species. However, nonsense-mediated decay-specific exons for which distant orthologous exons can be found tend to have been under purifying selection, consistent with the regulation model.</p> <p>Conclusion</p> <p>We conclude that for recently evolved exons the noisy splicing model is the better explanation of their properties, while for ancient exons the nonsense-mediated decay regulated gene expression is a viable explanation.</p

Modèles et algorithmes pour la segmentation de séquences biologiques et la reconstruction de leurs histoires évolutives

L’informatique est de plus en plus utilisée pour résoudre des problèmes dans divers domaines. C’est ainsi qu’avec l’accroissement des données biologiques générées par les techniques expérimentales à haut débit, la bio-informatique intervient pour tirer profit de ces masses de données et contribuer à l’avancement des connaissances en sciences biologiques. La bio-informatique est un domaine interdisciplinaire ayant pour but d’étudier et de résoudre des problèmes computationnels issus des sciences biologiques. Un des problèmes intemporels étudié en bio-informatique est la reconstruction de l’histoire évolutive de génomes, qui sous-entend essentiellement celle des gènes. Les gènes sont le support de l’information génétique et sont les unités de base de l’hérédité. De nos jours, un grand nombre de maladies, telles les cancers, ont une base génétique. Une bonne compréhension de l’évolution des gènes permettrait de mieux comprendre les processus impliqués dans ces maladies pour mieux les traiter. De plus, les connaissances sur l’évolution de gènes sont utiles pour la prédiction et l’annotation de nouveaux gènes. Il a été montré que les gènes eucaryotes subissent un phénomène d’épissage alternatif qui permet aux gènes de produire plusieurs transcrits différents afin de se diversifier fonctionnellement. C’est dans ce contexte que se situe cette thèse de doctorat. L’objectif de la thèse est de définir des modèles et des algorithmes efficaces et précis pour la segmentation de séquences biologiques et la reconstruction de leurs histoires évolutives en tenant compte de l’épissage alternatif. Dans cette thèse, j'ai contribué à accroître les connaissances scientifiques en introduisant et en formalisant des modèles d’évolution de transcrits et de gènes. Nous avons proposé deux algorithmes pour la segmentation de transcrits alternatifs. Nous avons également proposé un outil de simulation de l’évolution des séquences biologiques et un outil de visualisation de coévolution. Pour chacun des modèles et algorithmes proposés, nous avons développé des applications pour permettre l’utilisation facile de nos outils

Relative Timing of Intron Gain and a New Marker for Phylogenetic Analyses

Despite decades of effort by molecular systematists, the trees of life of eukaryotic organisms still remain partly unresolved or in conflict with each other. An ever increasing number of fully-sequenced genomes of various eukaryotes allows to consider gene and species phylogenies at genome-scale. However, such phylogenomics-based approaches also revealed that more taxa and more and more gene sequences are not the ultimate solution to fully resolve these conflicts, and that there is a need for sequence-independent phylogenetic meta-characters that are derived from genome sequences. Spliceosomal introns are characteristic features of eukaryotic nuclear genomes. The relatively rare changes of spliceosomal intron positions have already been used as genome-level markers, both for the estimation of intron evolution and phylogenies, however with variable success. In this thesis, a specific subset of these changes is introduced and established as a novel phylogenetic marker, termed near intron pair (NIP). These characters are inferred from homologous genes that contain mutually-exclusive intron presences at pairs of coding sequence (CDS) positions in close proximity. The idea that NIPs are powerful characters is based on the assumption that both very small exons and multiple intron gains at the same position are rare. To obtain sufficient numbers of NIP character data from genomic and alignment data sets in a consistent and flexible way, the implementation of a computational pipeline was a main goal of this work. Starting from orthologous (or more general: homologous) gene datasets comprising genomic sequences and corresponding CDS transcript annotations, the multiple alignment generation is an integral part of this pipeline. The alignment can be calculated at the amino acid level utilizing external tools (e.g. transAlign) and results in a codon alignment via back-translation. Guided by the multiple alignment, the positionally homologous intron positions should become apparent when mapped individually for each transcript. The pipeline proceeds at this stage to output portions of the intron-annotated alignment that contain at least one candidate of a NIP character. In a subsequent pipeline script, these collected so-called NIP region files are finally converted to binary state characters representing valid NIPs in dependence of quality filter constraints concerning, e.g., the amino acid alignment conservation around intron loci and splice sites, to name a few. The computational pipeline tools provide the researcher to elaborate on NIP character matrices that can be used for tree inference, e.g., using the maximum parsimony approach. In a first NIP-based application, the phylogenetic position of major orders of holometabolic insects (more specifically: the Coleoptera-Hymenoptera-Mecopterida trifurcation) was evaluated in a cladistic sense. As already suggested during a study on the eIF2gamma gene based on two NIP cases (Krauss et al. 2005), the genome-scale evaluation supported Hymenoptera as sister group to an assemblage of Coleoptera and Mecopterida, in agreement with other studies, but contradicting the previously established view. As part of the genome paper describing a new species of twisted-wing parasites (Strepsiptera), the NIP method was employed to help to resolve the phylogenetic position of them within (holometabolic) insects. Together with analyses of sequence patterns and a further meta-character, it revealed twisted-wing parasites as being the closest relatives of the mega-diverse beetles. NIP-based reconstructions of the metazoan tree covering a broad selection of representative animal species also identified some weaknesses of the NIP approach that may suffer e.g. from alignment/ortholog prediction artifacts (depending on the depth of range of taxa) and systematic biases (long branch attraction artifacts, due to unequal evolutionary rates of intron gain/loss and the use of the maximum parsimony method). In a further study, the identification of NIPs within the recently diverged genus Drosophila could be utilized to characterize recent intron gain events that apparently involved several cases of intron sliding and tandem exon duplication, albeit the mechanisms of gain for the majority of cases could not be elucidated. Finally, the NIP marker could be established as a novel phylogenetic marker, in particular dedicated to complementarily explore the wealth of genome data for phylogenetic purposes and to address open questions of intron evolution

Meeting report: a workshop on Best Practices in Genome Annotation

Efforts to annotate the genomes of a wide variety of model organisms are currently carried out by sequencing centers, model organism databases and academic/institutional laboratories around the world. Different annotation methods and tools have been developed over time to meet the needs of biologists faced with the task of annotating biological data. While standardized methods are essential for consistent curation within each annotation group, methods and tools can differ between groups, especially when the groups are curating different organisms. Biocurators from several institutes met at the Third International Biocuration Conference in Berlin, Germany, April 2009 and hosted the ‘Best Practices in Genome Annotation: Inference from Evidence’ workshop to share their strategies, pipelines, standards and tools. This article documents the material presented in the workshop

SEDA: a desktop tool suite for FASTA files processing

SEDA (SEquence DAtaset builder) is a multiplatform desktop application for the manipulation of FASTA files containing DNA or protein sequences. The convenient graphical user interface gives access to a collection of simple (filtering, sorting, or file reformatting, among others) and advanced (BLAST searching, protein domain annotation, gene annotation, and sequence alignment) utilities not present in similar applications, which eases the work of life science researchers working with DNA and/or protein sequences, especially those who have no programming skills. This paper presents general guidelines on how to build efficient data handling protocols using SEDA, as well as practical examples on how to prepare high-quality datasets for single gene phylogenetic studies, the characterization of protein families, or phylogenomic studies. The user-friendliness of SEDA also relies on two important features: (i) the availability of easy-to-install distributable versions and installers of SEDA, including a Docker image for Linux, and (ii) the facility with which users can manage large datasets. SEDA is open-source, with GNU General Public License v3.0 license, and publicly available at GitHub (https://github.com/sing-group/seda). SEDA installers and documentation are available at https://www. sing-group.org/seda/.Xunta de Galicia | Ref. ED431C2018/55-GRCFundação para a Ciência e a Tecnologia | Ref. UIDB/04293/202

Polymorphism identification and improved genome annotation of Brassica rapa through Deep RNA sequencing.

The mapping and functional analysis of quantitative traits in Brassica rapa can be greatly improved with the availability of physically positioned, gene-based genetic markers and accurate genome annotation. In this study, deep transcriptome RNA sequencing (RNA-Seq) of Brassica rapa was undertaken with two objectives: SNP detection and improved transcriptome annotation. We performed SNP detection on two varieties that are parents of a mapping population to aid in development of a marker system for this population and subsequent development of high-resolution genetic map. An improved Brassica rapa transcriptome was constructed to detect novel transcripts and to improve the current genome annotation. This is useful for accurate mRNA abundance and detection of expression QTL (eQTLs) in mapping populations. Deep RNA-Seq of two Brassica rapa genotypes-R500 (var. trilocularis, Yellow Sarson) and IMB211 (a rapid cycling variety)-using eight different tissues (root, internode, leaf, petiole, apical meristem, floral meristem, silique, and seedling) grown across three different environments (growth chamber, greenhouse and field) and under two different treatments (simulated sun and simulated shade) generated 2.3 billion high-quality Illumina reads. A total of 330,995 SNPs were identified in transcribed regions between the two genotypes with an average frequency of one SNP in every 200 bases. The deep RNA-Seq reassembled Brassica rapa transcriptome identified 44,239 protein-coding genes. Compared with current gene models of B. rapa, we detected 3537 novel transcripts, 23,754 gene models had structural modifications, and 3655 annotated proteins changed. Gaps in the current genome assembly of B. rapa are highlighted by our identification of 780 unmapped transcripts. All the SNPs, annotations, and predicted transcripts can be viewed at http://phytonetworks.ucdavis.edu/

Insights into the rice and Arabidopsis genomes: intron fates, paralogs, and lineage-specific genes

With the availability of near-complete rice genome sequence, high-quality annotation data, and large expression profile datasets, we examined segmental duplication, intron turnover, and paralogous protein family composition in rice. These data suggest a large percentage of the rice genome was involved in segmental duplication creating a large number of paralogous families. We found that singleton and paralogous family genes differed substantially not only in their likelihood of encoding a protein of known or putative function but also in the distribution of specific gene function. We showed that a significant portion of the duplicated genes in rice show divergent expression although a correlation between sequence divergence and correlation of expression could be seen in very young genes. We observed that intron evolution within the rice genome following segmental duplication is dominated by intron loss rather than intron gain. In addition, with the availability of more complete or near-complete plant genomes and transcriptomes across a wide range of species, we identified and characterized conserved Brassicaceae-specific genes and Arabidopsis lineage-specific genes. Lineage specific genes in the Brassicaceae and within Arabidopsis were enriched in genes of no known function and appear to be fast evolving at the protein sequence level