Raphaël Helaers

MetaPIGA v2.0 : maximum likelihood large phylogeny estimation using the metapopulation genetic algorithm and other stochastic heuristics

BackgroundThe development, in the last decade, of stochastic heuristics implemented in robust application softwares has made large phylogeny inference a key step in most comparative studies involving molecular sequences. Still, the choice of a phylogeny inference software is often dictated by a combination of parameters not related to the raw performance of the implemented algorithm(s) but rather by practical issues such as ergonomics and/or the availability of specific functionalities.ResultsHere, we present MetaPIGA v2.0, a robust implementation of several stochastic heuristics for large phylogeny inference (under maximum likelihood), including a Simulated Annealing algorithm, a classical Genetic Algorithm, and the Metapopulation Genetic Algorithm (metaGA) together with complex substitution models, discrete Gamma rate heterogeneity, and the possibility to partition data. MetaPIGA v2.0 also implements the Likelihood Ratio Test, the Akaike Information Criterion, and the Bayesian Information Criterion for automated selection of substitution models that best fit the data. Heuristics and substitution models are highly customizable through manual batch files and command line processing. However, MetaPIGA v2.0 also offers an extensive graphical user interface for parameters setting, generating and running batch files, following run progress, and manipulating result trees. MetaPIGA v2.0 uses standard formats for data sets and trees, is platform independent, runs in 32 and 64-bits systems, and takes advantage of multiprocessor and multicore computers.ConclusionsThe metaGA resolves the major problem inherent to classical Genetic Algorithms by maintaining high inter-population variation even under strong intra-population selection. Implementation of the metaGA together with additional stochastic heuristics into a single software will allow rigorous optimization of each heuristic as well as a meaningful comparison of performances among these algorithms. MetaPIGA v2.0 gives access both to high customization for the phylogeneticist, as well as to an ergonomic interface and functionalities assisting the non-specialist for sound inference of large phylogenetic trees using nucleotide sequences. MetaPIGA v2.0 and its extensive user-manual are freely available to academics at http://www.metapiga.org.

Somatic Activating PIK3CA Mutations Cause Venous Malformation

Somatic mutations in TEK, the gene encoding endothelial cell tyrosine kinase receptor TIE2, cause more than half of sporadically occurring unifocal venous malformations (VMs). Here, we report that somatic mutations in PIK3CA, the gene encoding the catalytic p110α subunit of PI3K, cause 54% (27 out of 50) of VMs with no detected TEK mutation. The hotspot mutations c.1624G>A, c.1633G>A, and c.3140A>G (p.Glu542Lys, p.Glu545Lys, and p.His1047Arg), frequent in PIK3CA-associated cancers, overgrowth syndromes, and lymphatic malformation (LM), account for >92% of individuals who carry mutations. Like VM-causative mutations in TEK, the PIK3CA mutations cause chronic activation of AKT, dysregulation of certain important angiogenic factors, and abnormal endothelial cell morphology when expressed in human umbilical vein endothelial cells (HUVECs). The p110α-specific inhibitor BYL719 restores all abnormal phenotypes tested, in PIK3CA- as well as TEK-mutant HUVECs, demonstrating that they operate via the same pathogenic pathways. Nevertheless, significant genotype-phenotype correlations in lesion localization and histology are observed between individuals with mutations in PIK3CA versus TEK, pointing to gene-specific effects.

2× genomes - depth does matter

BackgroundGiven the availability of full genome sequences, mapping gene gains, duplications, and losses during evolution should theoretically be straightforward. However, this endeavor suffers from overemphasis on detecting conserved genome features, which in turn has led to sequencing multiple eutherian genomes with low coverage rather than fewer genomes with high-coverage and more even distribution in the phylogeny. Although limitations associated with analysis of low coverage genomes are recognized, they have not been quantified.ResultsHere, using recently developed comparative genomic application systems, we evaluate the impact of low-coverage genomes on inferences pertaining to gene gains and losses when analyzing eukaryote genome evolution through gene duplication. We demonstrate that, when performing inference of genome content evolution, low-coverage genomes generate not only a massive number of false gene losses, but also striking artifacts in gene duplication inference, especially at the most recent common ancestor of low-coverage genomes. We show that the artifactual gains are caused by the low coverage of genome sequence per se rather than by the increased taxon sampling in a biased portion of the species tree.ConclusionsWe argue that it will remain difficult to differentiate artifacts from true changes in modes and tempo of genome evolution until there is better homogeneity in both taxon sampling and high-coverage sequencing. This is important for broadening the utility of full genome data to the community of evolutionary biologists, whose interests go well beyond widely conserved physiologies and developmental patterns as they seek to understand the generative mechanisms underlying biological diversity.

Reptilian-transcriptome v1.0, a glimpse in the brain transcriptome of five divergent Sauropsida lineages and the phylogenetic position of turtles

BackgroundReptiles are largely under-represented in comparative genomics despite the fact that they are substantially more diverse in many respects than mammals. Given the high divergence of reptiles from classical model species, next-generation sequencing of their transcriptomes is an approach of choice for gene identification and annotation.ResultsHere, we use 454 technology to sequence the brain transcriptome of four divergent reptilian and one reference avian species: the Nile crocodile, the corn snake, the bearded dragon, the red-eared turtle, and the chicken. Using an in-house pipeline for recursive similarity searches of >3,000,000 reads against multiple databases from 7 reference vertebrates, we compile a reptilian comparative transcriptomics dataset, with homology assignment for 20,000 to 31,000 transcripts per species and a cumulated non-redundant sequence length of 248.6 Mbases. Our approach identifies the majority (87%) of chicken brain transcripts and about 50% of de novo assembled reptilian transcripts. In addition to 57,502 microsatellite loci, we identify thousands of SNP and indel polymorphisms for population genetic and linkage analyses. We also build very large multiple alignments for Sauropsida and mammals (two million residues per species) and perform extensive phylogenetic analyses suggesting that turtles are not basal living reptiles but are rather associated with Archosaurians, hence, potentially answering a long-standing question in the phylogeny of Amniotes.ConclusionsThe reptilian transcriptome (freely available at http://www.reptilian-transcriptomes.org) should prove a useful new resource as reptiles are becoming important new models for comparative genomics, ecology, and evolutionary developmental genetics.

Blue Rubber Bleb Nevus (BRBN) Syndrome Is Caused by Somatic TEK (TIE2) Mutations.

Blue rubber bleb nevus syndrome (Bean syndrome) is a rare, severe disorder of unknown cause, characterized by numerous cutaneous and internal venous malformations; gastrointestinal lesions are pathognomonic. We discovered somatic mutations in TEK, the gene encoding TIE2, in 15 of 17 individuals with blue rubber bleb nevus syndrome. Somatic mutations were also identified in five of six individuals with sporadically occurring multifocal venous malformations. In contrast to common unifocal venous malformation, which is most often caused by the somatic L914F TIE2 mutation, multifocal forms are predominantly caused by double (cis) mutations, that is, two somatic mutations on the same allele of the gene. Mutations are identical in all lesions from a given individual. T1105N-T1106P is recurrent in blue rubber bleb nevus, whereas Y897C-R915C is recurrent in sporadically occurring multifocal venous malformation: both cause ligand-independent activation of TIE2, and increase survival, invasion, and colony formation when expressed in human umbilical vein endothelial cells.

Germline loss-of-function mutations in EPHB4 cause a second form of capillary malformation-arteriovenous malformation (CM-AVM2) deregulating RAS-MAPK signaling

Background: Most arteriovenous malformations (AVMs) are localized and occur sporadically. However, they also can be multifocal in autosomal-dominant disorders, such as hereditary hemorrhagic telangiectasia and capillary malformation (CM)-AVM. Previously, we identified RASA1 mutations in 50% of patients with CM-AVM. Herein we studied non-RASA1 patients to further elucidate the pathogenicity of CMs and AVMs. Methods: We conducted a genome-wide linkage study on a CM-AVM family. Whole-exome sequencing was also performed on 9 unrelated CM-AVM families. We identified a candidate gene and screened it in a large series of patients. The influence of several missense variants on protein function was also studied in vitro. Results: We found evidence for linkage in 2 loci. Whole-exome sequencing data unraveled 4 distinct damaging variants in EPHB4 in 5 families that cosegregated with CM-AVM. Overall, screening of EPHB4 detected 47 distinct mutations in 54 index patients: 27 led to a premature stop codon or splice-site alteration, suggesting loss of function. The other 20 are nonsynonymous variants that result in amino acid substitutions. In vitro expression of several mutations confirmed loss of function of EPHB4. The clinical features included multifocal CMs, telangiectasias, and AVMs. Conclusions: We found EPHB4 mutations in patients with multifocal CMs associated with AVMs. The phenotype, CM-AVM2, mimics RASA1-related CM-AVM1 and also hereditary hemorrhagic telangiectasia. RASA1-encoded p120RASGAP is a direct effector of EPHB4. Our data highlight the pathogenetic importance of this interaction and indicts EPHB4-RAS-ERK signaling pathway as a major cause for AVMs.

Historical constraints on vertebrate genome evolution.

Recent analyses indicated that genes with larger effect of knockout or mutation and with larger probability to revert to single copy after whole genome duplication are expressed earlier in development. Here, we further investigate whether tissue specificity of gene expression is constrained by the age of origin of the corresponding genes. We use 38 metazoan genomes and a comparative genomic application system to integrate inference of gene duplication with expression data from 17,503 human genes into a strictly phylogenetic framework. We show that the number of anatomical systems in which genes are expressed decreases steadily with decreased age of the genes’ first appearance in the phylogeny: the oldest genes are expressed, on average, in twice as many anatomical systems than the genes gained recently in evolution. These results are robust to different sources of expression data, to different levels of the anatomical system hierarchy, and to the use of gene families rather than duplication events. Finally, we show that the rate of increase in gene tissue specificity correlates with the relative rate of increase in the maximum number of cell types in the corresponding taxa. Although subfunctionalization and increase in cell type number throughout evolution could constitute, respectively, the proximal and ultimate causes of this correlation, the two phenomena are intermingled. Our analyses identify a striking historical constraint in gene expression: the number of cell types in existence at the time of a gene appearance (through duplication or de novo origination) tends to determine its level of tissue specificity for tens or hundreds of millions of years.

PDGFRB gain-of-function mutations in sporadic infantile myofibromatosis.

&NA; Infantile myofibromatosis is one of the most prevalent soft tissue tumors of infancy and childhood. Multifocal nodules with visceral lesions are associated with a poor prognosis. A few familial cases have been linked to mutations in various genes including PDGFRB. In this study, we sequenced PDGFRB, which encodes a receptor tyrosine kinase, in 16 cases of myofibromatosis or solitary myofibroma. Mutations in the coding sequence of PDGFRB were identified in 6 out of 8 patients with the sporadic multicentric form of the disease and in 1 out of 8 patients with isolated myofibroma. Two patients had the same mutation in multiple separated lesions. By contrast, a third patient had three different PDGFRB mutations in the three nodules analyzed. Mutations were located in the transmembrane, juxtamembrane and kinase domains of the receptor. We showed that these mutations activated receptor signaling in the absence of ligand and transformed fibroblasts. In one case, a weakly‐activating germline variant was associated with a stronger somatic mutation, suggesting a two‐hit model for familial myofibromatosis. Furthermore, the mutant receptors were sensitive to the tyrosine kinase inhibitor imatinib, except D850V, which was inhibited by dasatinib and ponatinib, suggesting a targeted therapy for severe myofibromatosis. In conclusion, we identified gain‐of‐function PDGFRB mutations in the majority of multifocal infantile myofibromatosis cases, shedding light on the mechanism of disease development, which is reminiscent of multifocal venous malformations induced by TIE2 mutations. Our results provide a genetic test to facilitate diagnosis, and preclinical data for development of molecular therapies.

Meta-Analysis of Microarray Data of Rainbow Trout Fry Gonad Differentiation Modulated by Ethynylestradiol

Sex differentiation in fish is a highly labile process easily reversed by the use of exogenous hormonal treatment and has led to environmental concerns since low doses of estrogenic molecules can adversely impact fish reproduction. The goal of this study was to identify pathways altered by treatment with ethynylestradiol (EE2) in developing fish and to find new target genes to be tested further for their possible role in male-to-female sex transdifferentiation. To this end, we have successfully adapted a previously developed bioinformatics workflow to a meta-analysis of two datasets studying sex reversal following exposure to EE2 in juvenile rainbow trout. The meta-analysis consisted of retrieving the intersection of the top gene lists generated for both datasets, performed at different levels of stringency. The intersecting gene lists, enriched in true positive differentially expressed genes (DEGs), were subjected to over-representation analysis (ORA) which allowed identifying several statistically significant enriched pathways altered by EE2 treatment and several new candidate pathways, such as progesterone-mediated oocyte maturation and PPAR signalling. Moreover, several relevant key genes potentially implicated in the early transdifferentiation process were selected. Altogether, the results show that EE2 has a great effect on gene expression in juvenile rainbow trout. The feminization process seems to result from the altered transcription of genes implicated in normal female gonad differentiation, resulting in expression similar to that observed in normal females (i.e. the repression of key testicular markers cyp17a1, cyp11b, tbx1), as well as from other genes (including transcription factors) that respond specifically to the EE2 treatment. The results also showed that the bioinformatics workflow can be applied to different types of microarray platforms and could be generalized to (eco)toxicogenomics studies for environmental risk assessment purposes.

KIF1B and NF1 are the most frequently mutated genes in paraganglioma tumors

3 Lucie Evenepoel 1,2 , Raphaël Helaers 2 , Laurent Vroonen 3 , Selda Aydin 4 , Marc Hamoir 5 , 4 Dominique Maiter, Miikka Vikkula, Alexandre Persu 5 6 1 Pole of Cardiovascular Research, Institut de Recherche Expérimentale et Clinique, Université catholique de 7 Louvain, Brussels, Belgium, 2 Human Molecular Genetics, de Duve Institute, Université catholique de Louvain, 8 Brussels, Belgium, 3 Department of Endocrinology, Centre Hospitalier Universitaire de Liège, University of 9 Liège, Domaine Universitaire du Sart-Tilman, Belgium, 4 Pathology Department, Cliniques universitaires Saint 10 Luc, Université catholique de Louvain, Brussels, Belgium, 5 Otolaryngology Department, Cliniques 11 Universitaires Saint-Luc, Université catholique de Louvain, Brussels, Belgium, 6 Endocrinology Department, 12 Cliniques Universitaires Saint-Luc, Université catholique de Louvain, Brussels, Belgium, 7 Cardiology 13 Department, Cliniques Universitaires Saint-Luc, Université catholique de Louvain, Brussels, Belgium. 14 15 The authors declare no conflict of interest. 16