33 research outputs found

    Long-range regulation is a major driving force in maintaining genome integrity

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    <p>Abstract</p> <p>Background</p> <p>The availability of newly sequenced vertebrate genomes, along with more efficient and accurate alignment algorithms, have enabled the expansion of the field of comparative genomics. Large-scale genome rearrangement events modify the order of genes and non-coding conserved regions on chromosomes. While certain large genomic regions have remained intact over much of vertebrate evolution, others appear to be hotspots for genomic breakpoints. The cause of the non-uniformity of breakpoints that occurred during vertebrate evolution is poorly understood.</p> <p>Results</p> <p>We describe a machine learning method to distinguish genomic regions where breakpoints would be expected to have deleterious effects (called breakpoint-refractory regions) from those where they are expected to be neutral (called breakpoint-susceptible regions). Our predictor is trained using breakpoints that took place along the human lineage since amniote divergence. Based on our predictions, refractory and susceptible regions have very distinctive features. Refractory regions are significantly enriched for conserved non-coding elements as well as for genes involved in development, whereas susceptible regions are enriched for housekeeping genes, likely to have simpler transcriptional regulation.</p> <p>Conclusion</p> <p>We postulate that long-range transcriptional regulation strongly influences chromosome break fixation. In many regions, the fitness cost of altering the spatial association between long-range regulatory regions and their target genes may be so high that rearrangements are not allowed. Consequently, only a limited, identifiable fraction of the genome is susceptible to genome rearrangements.</p

    Anopheles gambiae Immune Responses to Human and Rodent Plasmodium Parasite Species

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    Transmission of malaria is dependent on the successful completion of the Plasmodium lifecycle in the Anopheles vector. Major obstacles are encountered in the midgut tissue, where most parasites are killed by the mosquito's immune system. In the present study, DNA microarray analyses have been used to compare Anopheles gambiae responses to invasion of the midgut epithelium by the ookinete stage of the human pathogen Plasmodium falciparum and the rodent experimental model pathogen P. berghei. Invasion by P. berghei had a more profound impact on the mosquito transcriptome, including a variety of functional gene classes, while P. falciparum elicited a broader immune response at the gene transcript level. Ingestion of human malaria-infected blood lacking invasive ookinetes also induced a variety of immune genes, including several anti-Plasmodium factors. Twelve selected genes were assessed for effect on infection with both parasite species and bacteria using RNAi gene silencing assays, and seven of these genes were found to influence mosquito resistance to both parasite species. An MD2-like receptor, AgMDL1, and an immunolectin, FBN39, showed specificity in regulating only resistance to P. falciparum, while the antimicrobial peptide gambicin and a novel putative short secreted peptide, IRSP5, were more specific for defense against the rodent parasite P. berghei. While all the genes that affected Plasmodium development also influenced mosquito resistance to bacterial infection, four of the antimicrobial genes had no effect on Plasmodium development. Our study shows that the impact of P. falciparum and P. berghei infection on A. gambiae biology at the gene transcript level is quite diverse, and the defense against the two Plasmodium species is mediated by antimicrobial factors with both universal and Plasmodium-species specific activities. Furthermore, our data indicate that the mosquito is capable of sensing infected blood constituents in the absence of invading ookinetes, thereby inducing anti-Plasmodium immune responses

    SNPServer: a real-time SNP discovery tool

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    SNPServer is a real-time flexible tool for the discovery of SNPs (single nucleotide polymorphisms) within DNA sequence data. The program uses BLAST, to identify related sequences, and CAP3, to cluster and align these sequences. The alignments are parsed to the SNP discovery software autoSNP, a program that detects SNPs and insertion/deletion polymorphisms (indels). Alternatively, lists of related sequences or pre-assembled sequences may be entered for SNP discovery. SNPServer and autoSNP use redundancy to differentiate between candidate SNPs and sequence errors. For each candidate SNP, two measures of confidence are calculated, the redundancy of the polymorphism at a SNP locus and the co-segregation of the candidate SNP with other SNPs in the alignment. SNPServer is available at

    BASC: an integrated bioinformatics system for Brassica research

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    The BASC system provides tools for the integrated mining and browsing of genetic, genomic and phenotypic data. This public resource hosts information on Brassica species supporting the Multinational Brassica Genome Sequencing Project, and is based upon five distinct modules, ESTDB, Microarray, MarkerQTL, CMap and EnsEMBL. ESTDB hosts expressed gene sequences and related annotation derived from comparison with GenBank, UniRef and the genome sequence of Arabidopsis. The Microarray module hosts gene expression information related to genes annotated within ESTDB. MarkerQTL is the most complex module and integrates information on genetic markers, maps, individuals, genotypes and traits. Two further modules include an Arabidopsis EnsEMBL genome viewer and the CMap comparative genetic map viewer for the visualization and integration of genetic and genomic data. The database is accessible at

    Combining Computational Prediction of Cis-Regulatory Elements with a New Enhancer Assay to Efficiently Label Neuronal Structures in the Medaka Fish

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    The developing vertebrate nervous system contains a remarkable array of neural cells organized into complex, evolutionarily conserved structures. The labeling of living cells in these structures is key for the understanding of brain development and function, yet the generation of stable lines expressing reporter genes in specific spatio-temporal patterns remains a limiting step. In this study we present a fast and reliable pipeline to efficiently generate a set of stable lines expressing a reporter gene in multiple neuronal structures in the developing nervous system in medaka. The pipeline combines both the accurate computational genome-wide prediction of neuronal specific cis-regulatory modules (CRMs) and a newly developed experimental setup to rapidly obtain transgenic lines in a cost-effective and highly reproducible manner. 95% of the CRMs tested in our experimental setup show enhancer activity in various and numerous neuronal structures belonging to all major brain subdivisions. This pipeline represents a significant step towards the dissection of embryonic neuronal development in vertebrates

    An evolutionary approach to long-range regulation

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    Long-range regulatory regions play important functions in the regulation of transcription and are particularly involved in the precise spatio-temporal expression of target genes. Such regions have specific characteristics, among which is their ability to regulate many target genes that can be located up to 1Mb from the transcription start site. The prediction and functional characterization of such regions remains an open problem. Evolutionary approaches have been developed to detect regulatory regions that are under purifying selection. However, little has been done with regards to the impact of long-range regulation on genome evolution.This thesis focuses on three different aspects of long-range regulation: i/ First we develop a method that predicts regions particularly prone to the fixation of evolutionary breakpoints. We discuss the results obtained in the context of long-range regulation and show that this type of regulation is a major factor shaping vertebrate genomes in evolution. ii/ The second project aims at predicting functional interactions between regulatory regions and target genes based on the observation of evolutionary rearrangements in various vertebrate species. We show how this approach produces a biologically meaningful prediction dataset that will be useful to researchers working on regulation. iii/ Third, we focus on the in vivo characterization of regulatory regions. We present a powerful and reliable enhancer detection pipeline composed of an in silico approach to predict putative enhancers and an in vivo method to functionally characterize the expression specificity of predicted regions in the developing medaka fish.The results presented in this thesis contribute to different areas of research such as a better understanding of evolutionary dynamics related to evolutionary rearrangements and to a better in silico and in vivo characterization of cis-regulatory regions.La régulation longue distance a d'importantes fonctions dans la régulation de la transcription et est particulièrement impliquée dans la régulation spatiale et temporelle des gènes cibles. Ces régions ont des caractèristiques spécifiques telles que la capacité de contrôler different gènes à des distances jusqu'a 1Mb du site d'initiation de la transcription. La prédiction et la caractérisation fonctionelle de ces regions restent un problème d'actualité. Des approches évolutionaires ont été d´eveloppées pour détecter les régions sous pression de sélection. En revanche, peu a été fait en rapport avec l'impact de la régulation de longue distance sur l'évolution du génome.Cette thèse se concentre sur trois differents aspects de la régulation longue distance: i/ Premièrement, nous developpons une méthode de prédiction des regions particulièrement sujettes à la fixation des réarrangements de l'évolution. Nous étudions les résultats obtenus dans le contexte de la régulation longue distance et nous montrons que ce type de régulation est un composant majeur dans le façonnement du génome au cours de l'évolution. ii/ Le second projet à pour but de prédire les interactions fonctionnelles entre les régions de régulation et leur gènes cible à partir de l'observation de réarrangements de l'évolution dans differentes espèces. Nous montrons comment une telle approche produit des resultants biologiquement significatifs qui seront particulièrement utiles aux chercheurs travaillant dans le domaine de la régulation. iii/ Troisièmement, nous nous concentrons sur la caractérisation fonctionnelle in vivo des regions régulatrices. Nous présentons une méthode fiable de détection des enhancers composée d'une approche informatique pour la prédiction de ces régions et d'une approche biologique pour caractériser fonctionnellement les spécificités d'expression de ces régions dans le poisson medaka.Les résultats présentés dans cette thèse contribuent à une meilleure comprehension des dynamiques d'évolution en relation avec la régulation longue distance et une meilleure prédiction et caractérisation fonctionnelle de ces régions régulatrices
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