The source of laterally transferred genes in bacterial genomes

BACKGROUND: Laterally transferred genes have often been identified on the basis of compositional features that distinguish them from ancestral genes in the genome. These genes are usually A+T-rich, arguing either that there is a bias towards acquiring genes from donor organisms having low G+C contents or that genes acquired from organisms of similar genomic base compositions go undetected in these analyses. RESULTS: By examining the genome contents of closely related, fully sequenced bacteria, we uncovered genes confined to a single genome and examined the sequence features of these acquired genes. The analysis shows that few transfer events are overlooked by compositional analyses. Most observed lateral gene transfers do not correspond to free exchange of regular genes among bacterial genomes, but more probably represent the constituents of phages or other selfish elements. CONCLUSIONS: Although bacteria tend to acquire large amounts of DNA, the origin of these genes remains obscure. We have shown that contrary to what is often supposed, their composition cannot be explained by a previous genomic context. In contrast, these genes fit the description of recently described genes in lambdoid phages, named 'morons'. Therefore, results from genome content and compositional approaches to detect lateral transfers should not be cited as evidence for genetic exchange between distantly related bacteria

Evolutionary history of phosphatidylinositol- 3-kinases: ancestral origin in eukaryotes and complex duplication patterns

BACKGROUND: Phosphatidylinositol-3-kinases (PI3Ks) are a family of eukaryotic enzymes modifying phosphoinositides in phosphatidylinositols-3-phosphate. Located upstream of the AKT/mTOR signalling pathway, PI3Ks activate secondary messengers of extracellular signals. They are involved in many critical cellular processes such as cell survival, angiogenesis and autophagy. PI3K family is divided into three classes, including 14 human homologs. While class II enzymes are composed of a single catalytic subunit, class I and III also contain regulatory subunits. Here we present an in-depth phylogenetic analysis of all PI3K proteins. RESULTS: We confirmed that PI3K catalytic subunits form a monophyletic group, whereas regulatory subunits form three distinct groups. The phylogeny of the catalytic subunits indicates that they underwent two major duplications during their evolutionary history: the most ancient arose in the Last Eukaryotic Common Ancestor (LECA) and led to the emergence of class III and class I/II, while the second – that led to the separation between class I and II – occurred later, in the ancestor of Unikonta (i.e., the clade grouping Amoebozoa, Fungi, and Metazoa). These two major events were followed by many lineage specific duplications in particular in vertebrates, but also in various protist lineages. Major loss events were also detected in Vidiriplantae and Fungi. For the regulatory subunits, we identified homologs of class III in all eukaryotic groups indicating that, for this class, both the catalytic and the regulatory subunits were presents in LECA. In contrast, homologs of the regulatory class I have a more recent origin. CONCLUSIONS: The phylogenetic analysis of the PI3K shed a new light on the evolutionary history of these enzymes. We found that LECA already contained a PI3K class III composed of a catalytic and a regulatory subunit. Absence of class II regulatory subunits and the recent origin of class I regulatory subunits is puzzling given that the class I/II catalytic subunit was present in LECA and has been conserved in most present-day eukaryotic lineages. We also found surprising major loss and duplication events in various eukaryotic lineages. Given the functional specificity of PI3K proteins, this suggests dynamic adaptation during the diversification of eukaryotes. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12862-015-0498-7) contains supplementary material, which is available to authorized users

Cross-platform comparison and visualisation of gene expression data using co-inertia analysis

BACKGROUND: Rapid development of DNA microarray technology has resulted in different laboratories adopting numerous different protocols and technological platforms, which has severely impacted on the comparability of array data. Current cross-platform comparison of microarray gene expression data are usually based on cross-referencing the annotation of each gene transcript represented on the arrays, extracting a list of genes common to all arrays and comparing expression data of this gene subset. Unfortunately, filtering of genes to a subset represented across all arrays often excludes many thousands of genes, because different subsets of genes from the genome are represented on different arrays. We wish to describe the application of a powerful yet simple method for cross-platform comparison of gene expression data. Co-inertia analysis (CIA) is a multivariate method that identifies trends or co-relationships in multiple datasets which contain the same samples. CIA simultaneously finds ordinations (dimension reduction diagrams) from the datasets that are most similar. It does this by finding successive axes from the two datasets with maximum covariance. CIA can be applied to datasets where the number of variables (genes) far exceeds the number of samples (arrays) such is the case with microarray analyses. RESULTS: We illustrate the power of CIA for cross-platform analysis of gene expression data by using it to identify the main common relationships in expression profiles on a panel of 60 tumour cell lines from the National Cancer Institute (NCI) which have been subjected to microarray studies using both Affymetrix and spotted cDNA array technology. The co-ordinates of the CIA projections of the cell lines from each dataset are graphed in a bi-plot and are connected by a line, the length of which indicates the divergence between the two datasets. Thus, CIA provides graphical representation of consensus and divergence between the gene expression profiles from different microarray platforms. Secondly, the genes that define the main trends in the analysis can be easily identified. CONCLUSIONS: CIA is a robust, efficient approach to coupling of gene expression datasets. CIA provides simple graphical representations of the results making it a particularly attractive method for the identification of relationships between large datasets

Molecular and functional evolution of the fungal diterpene synthase genes

BackgroundTerpenes represent one of the largest and most diversified families of natural compounds and are used in numerous industrial applications. Terpene synthase (TPS) genes originated in bacteria as diterpene synthase (di-TPS) genes. They are also found in plant and fungal genomes. The recent availability of a large number of fungal genomes represents an opportunity to investigate how genes involved in diterpene synthesis were acquired by fungi, and to assess the consequences of this process on the fungal metabolism.ResultsIn order to investigate the origin of fungal di-TPS, we implemented a search for potential fungal di-TPS genes and identified their presence in several unrelated Ascomycota and Basidiomycota species. The fungal di-TPS phylogenetic tree is function-related but is not associated with the phylogeny based on housekeeping genes. The lack of agreement between fungal and di-TPS-based phylogenies suggests the presence of Horizontal Gene Transfer (HGTs) events. Further evidence for HGT was provided by conservation of synteny of di-TPS and neighbouring genes in distantly related fungi.ConclusionsThe results obtained here suggest that fungal di-TPSs originated from an ancient HGT event of a single di-TPS gene from a plant to a fungus in Ascomycota. In fungi, these di-TPSs allowed for the formation of clusters consisting in di-TPS, GGPPS and P450 genes to create functional clusters that were transferred between fungal species, producing diterpenes acting as hormones or toxins, thus affecting fungal development and pathogenicity

Horizontal Gene Transfer Regulation in Bacteria as a “Spandrel” of DNA Repair Mechanisms

Horizontal gene transfer (HGT) is recognized as the major force for bacterial genome evolution. Yet, numerous questions remain about the transferred genes, their function, quantity and frequency. The extent to which genetic transformation by exogenous DNA has occurred over evolutionary time was initially addressed by an in silico approach using the complete genome sequence of the Ralstonia solanacearum GMI1000 strain. Methods based on phylogenetic reconstruction of prokaryote homologous genes families detected 151 genes (13.3%) of foreign origin in the R. solanacearum genome and tentatively identified their bacterial origin. These putative transfers were analyzed in comparison to experimental transformation tests involving 18 different genomic DNA positions in the genome as sites for homologous or homeologous recombination. Significant transformation frequency differences were observed among these positions tested regardless of the overall genomic divergence of the R. solanacearum strains tested as recipients. The genomic positions containing the putative exogenous DNA were not systematically transformed at the highest frequencies. The two genomic “hot spots”, which contain recA and mutS genes, exhibited transformation frequencies from 2 to more than 4 orders of magnitude higher than positions associated with other genes depending on the recipient strain. These results support the notion that the bacterial cell is equipped with active mechanisms to modulate acquisition of new DNA in different genomic positions. Bio-informatics study correlated recombination “hot-spots” to the presence of Chi-like signature sequences with which recombination might be preferentially initiated. The fundamental role of HGT is certainly not limited to the critical impact that the very rare foreign genes acquired mainly by chance can have on the bacterial adaptation potential. The frequency to which HGT with homologous and homeologous DNA happens in the environment might have led the bacteria to hijack DNA repair mechanisms in order to generate genetic diversity without losing too much genomic stability

Databases of homologous gene families for comparative genomics

International audienceBackground: Comparative genomics is a central step in many sequence analysis studies, from gene annotation and the identification of new functional regions in genomes, to the study of evolutionary processes at the molecular level (speciation, single gene or whole genome duplications, etc.) and phylogenetics. In that context, databases providing users high quality homologous families and sequence alignments as well as phylogenetic trees based on state of the art algorithms are becoming indispensable. Methods: We developed an automated procedure allowing massive all-against-all similarity searches, gene clustering, multiple alignments computation, and phylogenetic trees construction and reconciliation. The application of this procedure to a very large set of sequences is possible through parallel computing on a large computer cluster. Results: Three databases were developed using this procedure: HOVERGEN, HOGENOM and HOMOLENS. These databases share the same architecture but differ in their content. HOVERGEN contains sequences from vertebrates, HOGENOM is mainly devoted to completely sequenced microbial organisms, and HOMOLENS is devoted to metazoan genomes from Ensembl. Access to the databases is provided through Web query forms, a general retrieval system and a client-server graphical interface. The later can be used to perform tree-pattern based searches allowing, among other uses, to retrieve sets of orthologous genes. The three databases, as well as the software required to build and query them, can be used or downloaded from the PBIL (Pôle Bioinformatique Lyonnais) site at http://pbil.univ-lyon1.fr/

Toward community standards in the quest for orthologs

The identification of orthologs—genes pairs descended from a common ancestor through speciation, rather than duplication—has emerged as an essential component of many bioinformatics applications, ranging from the annotation of new genomes to experimental target prioritization. Yet, the development and application of orthology inference methods is hampered by the lack of consensus on source proteomes, file formats and benchmarks. The second ‘Quest for Orthologs' meeting brought together stakeholders from various communities to address these challenges. We report on achievements and outcomes of this meeting, focusing on topics of particular relevance to the research community at large. The Quest for Orthologs consortium is an open community that welcomes contributions from all researchers interested in orthology research and applications. Contact: [email protected]

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