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1.
Bioinformatics ; 34(4): 585-591, 2018 02 15.
Artículo en Inglés | MEDLINE | ID: mdl-29040406

RESUMEN

Motivation: Advances in the sequencing of uncultured environmental samples, dubbed metagenomics, raise a growing need for accurate taxonomic assignment. Accurate identification of organisms present within a community is essential to understanding even the most elementary ecosystems. However, current high-throughput sequencing technologies generate short reads which partially cover full-length marker genes and this poses difficult bioinformatic challenges for taxonomy identification at high resolution. Results: We designed MATAM, a software dedicated to the fast and accurate targeted assembly of short reads sequenced from a genomic marker of interest. The method implements a stepwise process based on construction and analysis of a read overlap graph. It is applied to the assembly of 16S rRNA markers and is validated on simulated, synthetic and genuine metagenomes. We show that MATAM outperforms other available methods in terms of low error rates and recovered fractions and is suitable to provide improved assemblies for precise taxonomic assignments. Availability and implementation: https://github.com/bonsai-team/matam. Contact: pierre.pericard@gmail.com or helene.touzet@univ-lille1.fr. Supplementary information: Supplementary data are available at Bioinformatics online.


Asunto(s)
Microbioma Gastrointestinal/genética , Secuenciación de Nucleótidos de Alto Rendimiento/métodos , Metagenoma , Filogenia , Programas Informáticos , Algoritmos , Humanos , Metagenómica/métodos , ARN Ribosómico 16S/genética , Análisis de Secuencia de ADN/métodos
2.
Bioinformatics ; 31(9): 1493-5, 2015 May 01.
Artículo en Inglés | MEDLINE | ID: mdl-25527831

RESUMEN

SUMMARY: The complex, rapidly evolving field of computational metabolomics calls for collaborative infrastructures where the large volume of new algorithms for data pre-processing, statistical analysis and annotation can be readily integrated whatever the language, evaluated on reference datasets and chained to build ad hoc workflows for users. We have developed Workflow4Metabolomics (W4M), the first fully open-source and collaborative online platform for computational metabolomics. W4M is a virtual research environment built upon the Galaxy web-based platform technology. It enables ergonomic integration, exchange and running of individual modules and workflows. Alternatively, the whole W4M framework and computational tools can be downloaded as a virtual machine for local installation. AVAILABILITY AND IMPLEMENTATION: http://workflow4metabolomics.org homepage enables users to open a private account and access the infrastructure. W4M is developed and maintained by the French Bioinformatics Institute (IFB) and the French Metabolomics and Fluxomics Infrastructure (MetaboHUB). CONTACT: contact@workflow4metabolomics.org.


Asunto(s)
Metabolómica/métodos , Programas Informáticos , Algoritmos , Biología Computacional , Flujo de Trabajo
3.
Nat Commun ; 12(1): 116, 2021 01 07.
Artículo en Inglés | MEDLINE | ID: mdl-33414462

RESUMEN

Apicomplexan parasites have evolved efficient and distinctive strategies for intracellular replication where the timing of emergence of the daughter cells (budding) is a decisive element. However, the molecular mechanisms that provide the proper timing of parasite budding remain unknown. Using Toxoplasma gondii as a model Apicomplexan, we identified a master regulator that controls the timing of the budding process. We show that an ApiAP2 transcription factor, TgAP2IX-5, controls cell cycle events downstream of centrosome duplication. TgAP2IX-5 binds to the promoter of hundreds of genes and controls the activation of the budding-specific cell cycle expression program. TgAP2IX-5 regulates the expression of specific transcription factors that are necessary for the completion of the budding cycle. Moreover, TgAP2IX-5 acts as a limiting factor that ensures that asexual proliferation continues by promoting the inhibition of the differentiation pathway. Therefore, TgAP2IX-5 is a master regulator that controls both cell cycle and developmental pathways.


Asunto(s)
Ciclo Celular/fisiología , División Celular/fisiología , Proteínas Protozoarias/genética , Proteínas Protozoarias/metabolismo , Toxoplasma/genética , Toxoplasma/fisiología , Proliferación Celular , Centrosoma , Replicación del ADN , Regulación de la Expresión Génica , Técnicas de Silenciamiento del Gen , Humanos , Organismos Modificados Genéticamente , Factores de Transcripción/genética , Factores de Transcripción/metabolismo
4.
Mar Genomics ; 52: 100740, 2020 Aug.
Artículo en Inglés | MEDLINE | ID: mdl-31937506

RESUMEN

Brown algae are multicellular photosynthetic stramenopiles that colonize marine rocky shores worldwide. Ectocarpus sp. Ec32 has been established as a genomic model for brown algae. Here we present the genome and metabolic network of the closely related species, Ectocarpus subulatus Kützing, which is characterized by high abiotic stress tolerance. Since their separation, both strains show new traces of viral sequences and the activity of large retrotransposons, which may also be related to the expansion of a family of chlorophyll-binding proteins. Further features suspected to contribute to stress tolerance include an expanded family of heat shock proteins, the reduction of genes involved in the production of halogenated defence compounds, and the presence of fewer cell wall polysaccharide-modifying enzymes. Overall, E. subulatus has mainly lost members of gene families down-regulated in low salinities, and conserved those that were up-regulated in the same condition. However, 96% of genes that differed between the two examined Ectocarpus species, as well as all genes under positive selection, were found to encode proteins of unknown function. This underlines the uniqueness of brown algal stress tolerance mechanisms as well as the significance of establishing E. subulatus as a comparative model for future functional studies.


Asunto(s)
Genoma/genética , Phaeophyceae/genética , Estrés Fisiológico/genética , Proteínas Algáceas/genética , Redes y Vías Metabólicas/genética , Familia de Multigenes/genética , Victoria
5.
Nat Commun ; 6: 6686, 2015 Mar 30.
Artículo en Inglés | MEDLINE | ID: mdl-25819227

RESUMEN

Left-right asymmetries in the epithalamic region of the brain are widespread across vertebrates, but their magnitude and laterality varies among species. Whether these differences reflect independent origins of forebrain asymmetries or taxa-specific diversifications of an ancient vertebrate feature remains unknown. Here we show that the catshark Scyliorhinus canicula and the lampreys Petromyzon marinus and Lampetra planeri exhibit conserved molecular asymmetries between the left and right developing habenulae. Long-term pharmacological treatments in these species show that nodal signalling is essential to their generation, rather than their directionality as in teleosts. Moreover, in contrast to zebrafish, habenular left-right differences are observed in the absence of overt asymmetry of the adjacent pineal field. These data support an ancient origin of epithalamic asymmetry, and suggest that a nodal-dependent asymmetry programme operated in the forebrain of ancestral vertebrates before evolving into a variable trait in bony fish.


Asunto(s)
Lateralidad Funcional/genética , Regulación del Desarrollo de la Expresión Génica , Ligandos de Señalización Nodal/genética , Petromyzon/genética , Prosencéfalo/embriología , Tiburones/genética , Animales , Secuencia de Bases , Diencéfalo/embriología , Diencéfalo/metabolismo , Embrión no Mamífero , Factores de Crecimiento de Fibroblastos/genética , Factores de Crecimiento de Fibroblastos/metabolismo , Proteínas de Homeodominio/genética , Proteínas de Homeodominio/metabolismo , Lampreas/genética , Factores de Determinación Derecha-Izquierda/genética , Factores de Determinación Derecha-Izquierda/metabolismo , Datos de Secuencia Molecular , Proteína Nodal/genética , Proteína Nodal/metabolismo , Ligandos de Señalización Nodal/metabolismo , Prosencéfalo/metabolismo , Transducción de Señal , Factor de Crecimiento Transformador beta/genética , Factor de Crecimiento Transformador beta/metabolismo
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