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Owing to their roles in the arsenic (As) biogeochemical cycle, microorganisms and plants offer significant potential for developing innovative biotechnological applications able to remediate As pollutions. This possible use in bioremediation processes and phytomanagement is based on their ability to catalyse various biotransformation reactions leading to, e.g. the precipitation, dissolution, and sequestration of As, stabilisation in the root zone and shoot As removal. On the one hand, genomic studies of microorganisms and their communities are useful in understanding their metabolic activities and their interaction with As. On the other hand, our knowledge of molecular mechanisms and fate of As in plants has been improved by laboratory and field experiments. Such studies pave new avenues for developing environmentally friendly bioprocessing options targeting As, which worldwide represents a major risk to many ecosystems and human health.

A novel bacterial strain was isolated from industrially contaminated waste water. In the presence of crude oil, this strain was shown to reduce the rate of total petroleum hydrocarbons (TPH) up to 97.10% in 24 h. This bacterium was subsequently identified by 16S rRNA gene sequence analysis and affiliated to the Serratia genus by the RDP classifier. Its genome was sequenced and annotated, and genes coding for catechol 1,2 dioxygenase and naphthalene 1,2-dioxygenase system involved in aromatic hydrocarbon catabolism, and LadA-type monooxygenases involved in alkane degradation, were identified. Gas Chromatography-Mass Spectrometry (GC-MS) analysis of crude oil after biological treatment showed that Serratia sp. Tan611 strain was able to degrade n-alkanes (from C-13 to C-25). This bacterium was also shown to produce a biosurfactant, the emulsification index (E24) reaching 43.47% and 65.22%, against vegetable and crude oil, respectively. Finally, the formation of a biofilm was increased in the presence of crude oil. These observations make Serratia sp. Tan611 a good candidate for hydrocarbon bioremediation.

International audience; Amongst iron-oxidizing bacteria playing a key role in the natural attenuation of arsenic in acid mine drainages (AMDs), members of the Ferrovum genus were identified in mine effluent or water treatment plants, and were shown to dominate biogenic precipitates in field pilot experiments. In order to address the question of the in situ activity of the uncultivated Ferrovum sp. CARN8 strain in the Carnoul es AMD, we assembled its genome using metagenomic and metatranscriptomic sequences and we determined standardized expression values for protein-encoding genes. Our results showed that this microorganism was indeed metabolically active and allowed us to sketch out its metabolic activity in its natural environment. Expression of genes related to the respiratory chain and carbon fixation suggests aerobic energy production coupled to ferrous iron oxidation and chemolithoautotrophic growth. Notwithstanding the presence of nitrogenase genes in its genome, expression data also indicated that Ferrovum sp. CARN8 relied on ammonium import rather than nitrogen fixation. The expression of flagellum and chemotaxis genes hints that at least a proportion of this strain population was motile. Finally, apart from some genes related to metal resistance showing surprisingly low expression values, genes involved in stress response were well expressed as expected in AMDs.

International audience; Acid mine drainages (AMDs), metal‐rich acidic effluents generated by mining activities, are colonized by prokaryotic and eukaryotic microorganisms widely distributed among different phyla. We compared metatranscriptomic data from two sampling stations in the Carnoulès AMD and from a third station in the nearby Amous River, focussing on processes involved in primary production and litter decomposition. A synergistic relationship between the green and brown food webs was favoured in the AMD sediments by the low carbon content and the availability of mineral nutrients: primary production of organic matter would benefit C‐limited decomposers whose activity of organic matter mineralization would in turn profit primary producers. This balance could be locally disturbed by heterogeneous factors such as an input of plant debris from the riparian vegetation, strongly boosting the growth of Tremellales which would then outcompete primary producers. In the unpolluted Amous River on the contrary, the competition for limited mineral nutrients was dominated by the green food web, fish and bacterivorous protists having a positive effect on phytoplankton. These results suggest that in addition to direct effects of low pH and metal contamination, trophic conditions like carbon or mineral nutrient limitations also have a strong impact on assembly and activities of AMDs' microbial communities.

Microbacterium sp. strain Nx66 was isolated from waters contaminated by petrochemical effluents collected in Algeria. Its genome was sequenced using Illumina MiSeq (2 × 150-bp read pairs) and Oxford Nanopore (long reads) technologies and was assembled using Unicycler. It is composed of one chromosome of 3.42 Mb and one plasmid of 34.22 kb.

Arsenic is a toxic metalloid known to generate an important oxidative stress in cells. In the present study, we focused our attention on an alga related to the genus Coccomyxa, exhibiting an extraordinary capacity to resist high concentrations of arsenite and arsenate. The integrated analysis of high-throughput transcriptomic data and non-targeted metabolomic approaches highlighted multiple levels of protection against arsenite. Indeed, Coccomyxa sp. Carn induced a set of transporters potentially preventing the accumulation of this metalloid in the cells and presented a distinct arsenic metabolism in comparison to another species more sensitive to that compound, i.e. Euglena gracilis, especially in regard to arsenic methylation. Interestingly, Coccomyxa sp. Carn was characterized by a remarkable accumulation of the strong antioxidant glutathione (GSH). Such observation could explain the apparent low oxidative stress in the intracellular compartment, as suggested by the transcriptomic analysis. In particular, the high amount of GSH in the cell could play an important role for the tolerance to arsenate, as suggested by its partial oxidation into oxidized glutathione in presence of this metalloid. Our results therefore reveal that this alga has acquired multiple and original defence mechanisms allowing the colonization of extreme ecosystems such as acid mine drainages.

Microorganisms play a major role in biogeochemical cycles. As such they are attractive candidates for developing new or improving existing biotechnological applications, in order to deal with the accumulation and pollution of organic and inorganic compounds. Their ability to participate in bioremediation processes mainly depends on their capacity to metabolize toxic elements and catalyze reactions resulting in, for example, precipitation, biotransformation, dissolution, or sequestration. The contribution of genomics may be of prime importance to a thorough understanding of these metabolisms and the interactions of microorganisms with pollutants at the level of both single species and microbial communities. Such approaches should pave the way for the utilization of microorganisms to design new, efficient and environmentally sound remediation strategies, as exemplified by the case of arsenic contamination, which has been declared as a major risk for human health in various parts of the world.

Pseudomonas xanthomarina S11 is an arsenite-oxidizing bacterium isolated from an arsenic-contaminated former gold mine in Salsigne, France. This bacterium showed high resistance to arsenite and was able to oxidize arsenite to arsenate at concentrations up to 42.72 mM As[III]. The genome of this strain was sequenced and revealed the presence of three ars clusters. One of them is located on a plasmid and is organized as an “arsenic island” harbouring an aio operon and genes involved in phosphorous metabolism, in addition to the ars genes. Neither the aioXRS genes nor a specific sigma-54-dependent promoter located upstream of aioBA genes, both involved in regulation of arsenite oxidase expression in other arsenite-oxidizing bacteria, could be identified in the genome. This observation is in accordance with the fact that no difference was observed in expression of arsenite oxidase in P. xanthomarina S11, whether or not the strain was grown in the presence of As[III].

Arsenic is a toxic metalloid known to cause multiple and severe cellular damages, including lipid peroxidation, protein misfolding, mutagenesis and double and single-stranded DNA breaks. Thus, exposure to this compound is lethal for most organisms but some species such as the photosynthetic protist Euglena mutabilis are able to cope with very high concentrations of this metalloid. Our comparative transcriptomic approaches performed on both an arsenic hypertolerant protist, i.e. E. mutabilis, and a more sensitive one, i.e. E. gracilis, revealed multiple mechanisms involved in arsenic tolerance. Indeed, E. mutabilis prevents efficiently the accumulation of arsenic in the cell through the expression of several transporters. More surprisingly, this protist induced the expression of active DNA reparation and protein turnover mechanisms, which allow E. mutabilis to maintain functional integrity of the cell under challenging conditions. Our observations suggest that this protist has acquired specific functions regarding arsenic and has developed an original metabolism to cope with acid mine drainages-related stresses.

International audience; Euglena mutabilis is a protist ubiquitously found in extreme environments such as acid mine drainages which are often rich in arsenic. The response of E. mutabilis to this metalloid was compared to that of Euglena gracilis, a protist not found in such environments. Membrane fatty acid composition, cell surface properties, arsenic accumulation kinetics, and intracellular arsenic speciation were determined. The results revealed a modification in fatty acid composition leading to an increased membrane fluidity in both Euglena species under sublethal arsenic concentrations exposure. This increased membrane fluidity correlated to an induced gliding motility observed in E. mutabilis in the presence of this metalloid but did not affect the flagellar dependent motility of E. gracilis. Moreover, when compared to E. gracilis, E. mutabilis showed highly hydrophobic cell surface properties and a higher tolerance to water-soluble arsenical compounds but not to hydrophobic ones. Finally, E. mutabilis showed a lower accumulation of total arsenic in the intracellular compartment and an absence of arsenic methylated species in contrast to E. gracilis. Taken together, our results revealed the existence of a specific arsenical response of E. mutabilis that may play a role in its hypertolerance to this toxic metalloid.

Multiple sequence alignment is a fundamental tool in a number of different domains in modern molecular biology, including functional and evolutionary studies of a protein family. Multiple alignments also play an essential role in the new integrated systems for genome annotation and analysis. Thus, the development of new multiple alignment scores and statistics is essential, in the spirit of the work dedicated to the evaluation of pairwise sequence alignments for database searching techniques. We present here norMD, a new objective scoring function for multiple sequence alignments. NorMD combines the advantages of the column-scoring techniques with the sensitivity of methods incorporating residue similarity scores. In addition, norMD incorporates ab initio sequence information, such as the number, length and similarity of the sequences to be aligned. The sensitivity and reliability of the norMD objective function is demonstrated using structural alignments in the SCOP and BAliBASE databases. The norMD scores are then applied to the multiple alignments of the complete sequences (MACS) detected by BlastP with E-value

We report the genome sequence of Halomonas sp. strain A3H3, a bacterium with a high tolerance to arsenite, isolated from multicontaminated sediments of the l'Estaque harbor in Marseille, France. The genome is composed of a 5,489,893-bp chromosome and a 157,085-bp plasmid.

Arsenic is a toxic metalloid known to cause multiple and severe cellular damages, including lipid peroxidation, protein misfolding, mutagenesis and double and single-stranded DNA breaks. Thus, exposure to this compound is lethal for most organisms but some species such as the photosynthetic protist Euglena mutabilis are able to cope with very high concentrations of this metalloid. Our comparative transcriptomic approaches performed on both an arsenic hypertolerant protist, i.e. E. mutabilis, and a more sensitive one, i.e. E. gracilis, revealed multiple mechanisms involved in arsenic tolerance. Indeed, E. mutabilis prevents efficiently the accumulation of arsenic in the cell through the expression of several transporters. More surprisingly, this protist induced the expression of active DNA reparation and protein turnover mechanisms, which allow E. mutabilis to maintain functional integrity of the cell under challenging conditions. Our observations suggest that this protist has acquired specific functions regarding arsenic and has developed an original metabolism to cope with acid mine drainages-related stresses.

Chantier qualité GA; International audience; Microorganisms dwelling in sediments have a crucial role in biogeochemical cycles and are expected to have a strong influence on the cycle of arsenic, a metalloid responsible for severe water pollution and presenting major health risks for human populations. We present here a metagenomic study of the sediment from two harbours on the Mediterranean French coast, l'Estaque and St Mandrier. The first site is highly polluted with arsenic and heavy metals, while the arsenic concentration in the second site is below toxicity levels. The goal of this study was to elucidate the potential impact of the microbial community on the chemical parameters observed in complementary geochemical studies performed on the same sites. The metagenomic sequences, along with those from four publicly available metagenomes used as control data sets, were analysed with the RAMMCAP workflow. The resulting functional profiles were compared to determine the over-represented Gene Ontology categories in the metagenomes of interest. Categories related to arsenic resistance and dissimilatory sulphate reduction were over-represented in l'Estaque. More importantly, despite very similar profiles, the identification of specific sequence markers for sulphate-reducing bacteria and sulphur-oxidizing bacteria showed that sulphate reduction was significantly more associated with l'Estaque than with St Mandrier. We propose that biotic sulphate reduction, arsenate reduction and fermentation may together explain the higher mobility of arsenic observed in l'Estaque in previous physico-chemical studies of this site. This study also demonstrates that it is possible to draw sound conclusions from comparing complex and similar unassembled metagenomes at the functional level, even with very low sequence coverage

Proteins may be considered as the main effectors of biological responses of organisms to specific environmental conditions, instead of messenger RNAs. Indeed, a modulation in their activity does not always depend on a modified expression of the corresponding genes but rather on post-translational modifications. Proteome analysis may therefore constitute an appropriate approach to address the question of organism adaptation to environmental stresses or growth under extreme conditions. Recently, the knowledge of the organisms’ physiology has led to deep changes in the investigation methods, favouring the use of global analysis methods in complement with conventional strategies. Instead of studying individual proteins or metabolic products, the integral profile of organisms can now be established. This may be of importance when studying adaptive and stress responses in microorganisms because of their multifactorial character. In particular, the differential analysis in various growth conditions of the whole protein content (« proteome »), which allows the simultaneous quantification of gene products in an organism, represents part of the so-called integrative biology (Bertin et al., 2008). Genomics is a conceptual approach that aims to study the biology of microorganisms by analysing the complete genetic information they contain. This scientific discipline really emerged more than fifteen years ago with the characterization of the first complete genome of autonomous organisms (Bertin et al., 2008). An important reduction of sequencing costs associated with new high-throughput technologies has led to an explosion of genomic programs that now concern organisms in all domains of life (http://www.genomeonline.org). Most of the descriptive and functional genomic efforts initially focused on human pathogens, such as bacteria and parasites, and next, on higher eukaryotes. More recently, there has been a growing interest in microorganisms isolated from various habitats, including extreme ecological niches, to characterize specific properties that allow these organisms to grow in such environments. The field of application of proteomics thus expended in line with genomics. These works should lead not only to a

Acid Mine Drainages (AMDs) are extreme environments characterized by acidic and oligotrophic conditions and by metal contaminations. A function-based screening of an AMD-derived metagenomic library led to the discovery and partial characterization of two non-homologous endo-acting amylases sharing no sequence similarity with any known amylase nor glycosidase. None carried known amylolytic domains, nor could be assigned to any GH-family. One amylase displayed no similarity with any known protein, whereas the second one was similar to TraC proteins involved in the bacterial type IV secretion system. According to the scarce similarities with known proteins, 3D-structure modelling using I-TASSER was unsuccessful. This study underlined the utility of a function-driven metagenomic approach to obtain a clearer image of the bacterial community enzymatic landscape. More generally, this work points out that screening for microorganisms or biomolecules in a priori incongruous environments could provide unconventional and new exciting ways for bioprospecting.

In a single experiment, chromatin immunoprecipitation combined with high throughput sequencing (ChIP-seq) provides genome-wide information about a given covalent histone modification or transcription factor occupancy. However, time efficient bioinformatics resources for extracting biological meaning out of these gigabyte-scale datasets are often a limiting factor for data interpretation by biologists. We created an integrated portable ChIP-seq data interpretation platform called seqMINER, with optimized performances for efficient handling of multiple genome-wide datasets. seqMINER allows comparison and integration of multiple ChIP-seq datasets and extraction of qualitative as well as quantitative information. seqMINER can handle the biological complexity of most experimental situations and proposes methods to the user for data classification according to the analysed features. In addition, through multiple graphical representations, seqMINER allows visualization and modelling of general as well as specific patterns in a given dataset. To demonstrate the efficiency of seqMINER, we have carried out a comprehensive analysis of genome-wide chromatin modification data in mouse embryonic stem cells to understand the global epigenetic landscape and its change through cellular differentiation.

International audience; The traditional approach to bioinformatics analyses relies on independent task-specific services and applications, using different input and output formats, often idiosyncratic, and frequently not designed to inter-operate. In general, such analyses were performed by experts who manually verified the results obtained at each step in the process. Today, the amount of bioinformatics information continuously being produced means that handling the various applications used to study this information presents a major data management and analysis challenge to researchers. It is now impossible to manually analyse all this information and new approaches are needed that are capable of processing the large-scale heterogeneous data in order to extract the pertinent information. We review the recent use of integrated expert systems aimed at providing more efficient knowledge extraction for bioinformatics research. A general methodology for building knowledge-based expert systems is described, focusing on the unstructured information management architecture, UIMA, which provides facilities for both data and process management. A case study involving a multiple alignment expert system prototype called AlexSys is also presented.

International audience; With genome sequencing projects producing huge amounts of sequence data, database sequence similarity search has become a central tool in bioinformatics to identify potentially homologous sequences. It is thus widely used as an initial step for sequence characterization and annotation, phylogeny, genomics, transcriptomics, and proteomics studies. Database similarity search is based upon sequence alignment methods also used in pairwise sequence comparison. Sequence alignment can be global (whole sequence alignment) or local (partial sequence alignment) and there are algorithms to find the optimal alignment given particular comparison criteria. However, as database searches require the comparison of the query sequence with every single sequence in the database, heuristic algorithms have been designed to reduce the time required to build an alignment that has a reasonable chance to be the best one. Such algorithms have been implemented as fast and efficient programs (Blast, FastA) available in different types to address different kinds of problems. After searching the appropriate database, similarity search programs produce a list of similar sequences and local alignments. These results should be carefully examined before coming to any conclusion, as many traps await the similarity seeker: paralogues, multidomain proteins, pseudogenes, etc. This chapter presents points that should always be kept in mind when performing database similarity searches for various goals. It ends with a practical example of sequence characterization from a single protein database search using Blast.

SAGE (Serial Analysis of Gene Expression) experiments generate short nucleotide sequences called 'tags' which are assumed to map unambiguously to their original transcripts (1 tag to 1 transcript mapping). Nevertheless, many tags are generated that do not map to any transcript or map to multiple transcripts. Current bioinformatics resources, such as SAGEmap and TAGmapper, have focused on reducing the number of unmapped tags. Here, we describe SAGETTARIUS, a new high-throughput program that performs successive precise Nla3 and Sau3A tag to transcript mapping, based on specifically designed Virtual Tag (VT) libraries. First, SAGETTARIUS decreases the number of tags mapped to multiple transcripts. Among the various mapping resources compared, SAGETTARIUS performed the best in this respect by decreasing up to 11% the number of multiply mapped tags. Second, SAGETTARIUS allows the establishment of a guideline for SAGE experiment sequencing efforts through efficient mapping of the CRT (Cytoplasmic Ribosomal protein Transcripts)-specific tags. Using all publicly available human and mouse Nla3 SAGE experiments, we show that sequencing 100,000 tags is sufficient to map almost all CRT-specific tags and that four sequencing stages can be identified when carrying out a human or mouse SAGE project. SAGETTARIUS is web interfaced and freely accessible to academic users.

Bardet-Biedl syndrome (BBS) is primarily an autosomal recessive ciliopathy characterized by progressive retinal degeneration, obesity, cognitive impairment, polydactyly, and kidney anomalies. The disorder is genetically heterogeneous, with 11 BBS genes identified to date, which account for ~70% of affected families. We have combined single-nucleotide-polymorphism array homozygosity mapping with in silico analysis to identify a new BBS gene, BBS12. Patients from two Gypsy families were homozygous and haploidentical in a 6-Mb region of chromosome 4q27. FLJ35630 was selected as a candidate gene, because it was predicted to encode a protein with similarity to members of the type II chaperonin superfamily, which includes BBS6 and BBS10. We found pathogenic mutations in both Gypsy families, as well as in 14 other families of various ethnic backgrounds, indicating that BBS12 accounts for approximately 5% of all BBS cases. BBS12 is vertebrate specific and, together with BBS6 and BBS10, defines a novel branch of the type II chaperonin superfamily. These three genes are characterized by unusually rapid evolution and are likely to perform ciliary functions specific to vertebrates that are important in the pathophysiology of the syndrome, and together they account for about one-third of the total BBS mutational load. Consistent with this notion, suppression of each family member in zebrafish yielded gastrulation-movement defects characteristic of other BBS morphants, whereas simultaneous suppression of all three members resulted in severely affected embryos, possibly hinting at partial functional redundancy within this protein family.

Background In the post-genomic era, systems-level studies are being performed that seek to explain complex biological systems by integrating diverse resources from fields such as genomics, proteomics or transcriptomics. New information management systems are now needed for the collection, validation and analysis of the vast amount of heterogeneous data available. Multiple alignments of complete sequences provide an ideal environment for the integration of this information in the context of the protein family. Results MACSIMS is a multiple alignment-based information management program that combines the advantages of both knowledge-based and ab initio sequence analysis methods. Structural and functional information is retrieved automatically from the public databases. In the multiple alignment, homologous regions are identified and the retrieved data is evaluated and propagated from known to unknown sequences with these reliable regions. In a large-scale evaluation, the specificity of the propagated sequence features is estimated to be >99%, i.e. very few false positive predictions are made. MACSIMS is then used to characterise mutations in a test set of 100 proteins that are known to be involved in human genetic diseases. The number of sequence features associated with these proteins was increased by 60%, compared to the features available in the public databases. An XML format output file allows automatic parsing of the MACSIM results, while a graphical display using the JalView program allows manual analysis. Conclusion MACSIMS is a new information management system that incorporates detailed analyses of protein families at the structural, functional and evolutionary levels. MACSIMS thus provides a unique environment that facilitates knowledge extraction and the presentation of the most pertinent information to the biologist. A web server and the source code are available at http://bips.u-strasbg.fr/MACSIMS/.

International audience; MOTIVATION: Recent advances in gene sequencing have provided complete sequence information for a number of genomes and as a result the amount of data in the sequence databases is growing at an exponential rate. We introduce here a new program, DbW, to automate the update of a functional family-specific multiple alignment that tries to include relevant sequences. The program is based on the use of different sources of information: sequences and annotations in databases. RESULTS: The advantages of DbW are demonstrated using the 20 families of aminoacyl-tRNA synthetases, where DbW detects a maximum of homologous sequences in the Swiss-Prot and SPTREMBL databases. The global specificity of DbW in this test is 98.4% (1.6% of the sequences included in the alignment did not belong to the family according to their function), and the global sensitivity of DbW is estimated to be 95.2%. Thus, DbW provides a reliable basis for the many applications that rely on accurate multiple alignments, e.g. functional residue identification, 2D/3D structure prediction or homology modeling. AVAILABILITY: The DbW software is available for download at ftp://ftp-igbmc.u-strasbg.fr/pub/DbW/DbW.tar and online at http://titus.u-strasbg.fr/DbW CONTACT: prigent@igbmc.u-strasbg.fr.

Multiple alignment, since its introduction in the early seventies, has become a cornerstone of modern molecular biology. It has traditionally been used to deduce structure / function by homology, to detect conserved motifs and in phylogenetic studies. There has recently been some renewed interest in the development of multiple alignment techniques, with current opinion moving away from a single all-encompassing algorithm to iterative and / or co-operative strategies. The exploitation of multiple alignments in genome annotation projects represents a qualitative leap in the functional analysis process, opening the way to the study of the co-evolution of validated sets of proteins and to reliable phylogenomic analysis. However, the alignment of the highly complex proteins detected by today's advanced database search methods is a daunting task. In addition, with the explosion of the sequence databases and with the establishment of numerous specialized biological databases, multiple alignment programs must evolve if they are to successfully rise to the new challenges of the post-genomic era. The way forward is clearly an integrated system bringing together sequence data, knowledge-based systems and prediction methods with their inherent unreliability. The incorporation of such heterogeneous, often non-consistent, data will require major changes to the fundamental alignment algorithms used to date. Such an integrated multiple alignment system will provide an ideal workbench for the validation, propagation and presentation of this information in a format that is concise, clear and intuitive.

Motivation: Blast programs are very efficient in finding relatively strong similarities but some very distantly related sequences are given a very high Expect value and are ranked very low in Blast results. We have developed Ballast, a program to predict local maximum segments (LMSs—i.e. sequence segments conserved relatively to their flanking regions) from a single Blast database search and to highlight these divergent homologues. The TBlastN database searches can also be processed with the help of information from a joint BlastP search. Results: We have applied the Ballast algorithm to BlastP searches performed with sequences belonging to well described dispersed families (aminoacyl-tRNA synthetases; helicases) against the SwissProt 38 database. We show that Ballast is able to build an appropriate conservation profile and that LMSs are predicted that are consistent with the signatures and motifs described in the literature. Furthermore, by comparing the Blast, PsiBlast and Ballast results obtained on a well defined database of structurally related sequences, we show that the LMSs provide a scoring scheme that can concentrate on top ranking distant homologues better than Blast. Using the graphical user interface available on the Web, specific LMSs may be selected to detect divergent homologues sharing the corresponding properties with the query sequence without requiring any additional database search. Availability: Web service is at http://igbmc.u-strasbg.fr:8080/ballast.htmland source code is available at ftp://ftp-igbmc.u-strasbg.fr/Ballast/ Contact: plewniak@igbmc.u-strasbg.fr To whom correspondence should be addressed.

DbClustal addresses the important problem of the automatic multiple alignment of the top scoring full-length sequences detected by a database homology search. By combining the advantages of both local and global alignment algorithms into a single system, DbClustal is able to provide accurate global alignments of highly divergent, complex sequence sets. Local alignment information is incorporated into a ClustalW global alignment in the form of a list of anchor points between pairs of sequences. The method is demonstrated using anchors supplied by the Blast post-processing program, Ballast. The rapidity and reliability of DbClustal have been demonstrated using the recently annotated Pyrococcus abyssi proteome where the number of alignments with totally misaligned sequences was reduced from 20% to

Inherited neuromuscular disorders (NMD) are chronic genetic diseases posing a significant burden on patients and the health care system. Despite tremendous research and clinical efforts, the molecular causes remain unknown for nearly half of the patients, due to genetic heterogeneity and conventional molecular diagnosis based on a gene-by-gene approach. We aimed to test next generation sequencing (NGS) as an efficient and cost-effective strategy to accelerate patient diagnosis. We designed a capture library to target the coding and splice site sequences of all known NMD genes and used NGS and DNA multiplexing to retrieve the pathogenic mutations in patients with heterogeneous NMD with or without known mutations. We retrieved all known mutations, including point mutations and small indels, intronic and exonic mutations, and a large deletion in a patient with Duchenne muscular dystrophy, validating the sensitivity and reproducibility of this strategy on a heterogeneous subset of NMD with different genetic inheritance. Most pathogenic mutations were ranked on top in our blind bioinformatic pipeline. Following the same strategy, we characterized probable TTN, RYR1 and COL6A3 mutations in several patients without previous molecular diagnosis. The cost was less than conventional testing for a single large gene. With appropriate adaptations, this strategy could be implemented into a routine genetic diagnosis set-up as a first screening approach to detect most kind of mutations, potentially before the need of more invasive and specific clinical investigations. An earlier genetic diagnosis should provide improved disease management and higher quality genetic counseling, and ease access to therapy or inclusion into therapeutic trials. Electronic supplementary material The online version of this article (doi:10.1007/s00401-012-0982-8) contains supplementary material, which is available to authorized users.

National audience

National audience; Description of the project management activities within the GDR Génolevures