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1.  A meta-approach for improving the prediction and the functional annotation of ortholog groups 
BMC Genomics  2014;15(Suppl 6):S16.
In comparative genomics, orthologs are used to transfer annotation from genes already characterized to newly sequenced genomes. Many methods have been developed for finding orthologs in sets of genomes. However, the application of different methods on the same proteome set can lead to distinct orthology predictions.
We developed a method based on a meta-approach that is able to combine the results of several methods for orthologous group prediction. The purpose of this method is to produce better quality results by using the overlapping results obtained from several individual orthologous gene prediction procedures. Our method proceeds in two steps. The first aims to construct seeds for groups of orthologous genes; these seeds correspond to the exact overlaps between the results of all or several methods. In the second step, these seed groups are expanded by using HMM profiles.
We evaluated our method on two standard reference benchmarks, OrthoBench and Orthology Benchmark Service. Our method presents a higher level of accurately predicted groups than the individual input methods of orthologous group prediction. Moreover, our method increases the number of annotated orthologous pairs without decreasing the annotation quality compared to twelve state-of-the-art methods.
The meta-approach based method appears to be a reliable procedure for predicting orthologous groups. Since a large number of methods for predicting groups of orthologous genes exist, it is quite conceivable to apply this meta-approach to several combinations of different methods.
PMCID: PMC4240552  PMID: 25573073
ortholog; homolog; meta-approach; sequences-profile comparison
2.  Profiling the orphan enzymes 
Biology Direct  2014;9:10.
The emergence of Next Generation Sequencing generates an incredible amount of sequence and great potential for new enzyme discovery. Despite this huge amount of data and the profusion of bioinformatic methods for function prediction, a large part of known enzyme activities is still lacking an associated protein sequence. These particular activities are called “orphan enzymes”. The present review proposes an update of previous surveys on orphan enzymes by mining the current content of public databases. While the percentage of orphan enzyme activities has decreased from 38% to 22% in ten years, there are still more than 1,000 orphans among the 5,000 entries of the Enzyme Commission (EC) classification. Taking into account all the reactions present in metabolic databases, this proportion dramatically increases to reach nearly 50% of orphans and many of them are not associated to a known pathway. We extended our survey to “local orphan enzymes” that are activities which have no representative sequence in a given clade, but have at least one in organisms belonging to other clades. We observe an important bias in Archaea and find that in general more than 30% of the EC activities have incomplete sequence information in at least one superkingdom. To estimate if candidate proteins for local orphans could be retrieved by homology search, we applied a simple strategy based on the PRIAM software and noticed that candidates may be proposed for an important fraction of local orphan enzymes. Finally, by studying relation between protein domains and catalyzed activities, it appears that newly discovered enzymes are mostly associated with already known enzyme domains. Thus, the exploration of the promiscuity and the multifunctional aspect of known enzyme families may solve part of the orphan enzyme issue. We conclude this review with a presentation of recent initiatives in finding proteins for orphan enzymes and in extending the enzyme world by the discovery of new activities.
This article was reviewed by Michael Galperin, Daniel Haft and Daniel Kahn.
PMCID: PMC4084501  PMID: 24906382
Orphan enzyme activities; Enzyme discovery; Metabolic pathways; Enzyme promiscuity; Data survey; Biological databases; Local orphan enzymes
3.  Comparative genomics of emerging pathogens in the Candida glabrata clade 
BMC Genomics  2013;14:623.
Candida glabrata follows C. albicans as the second or third most prevalent cause of candidemia worldwide. These two pathogenic yeasts are distantly related, C. glabrata being part of the Nakaseomyces, a group more closely related to Saccharomyces cerevisiae. Although C. glabrata was thought to be the only pathogenic Nakaseomyces, two new pathogens have recently been described within this group: C. nivariensis and C. bracarensis. To gain insight into the genomic changes underlying the emergence of virulence, we sequenced the genomes of these two, and three other non-pathogenic Nakaseomyces, and compared them to other sequenced yeasts.
Our results indicate that the two new pathogens are more closely related to the non-pathogenic N. delphensis than to C. glabrata. We uncover duplications and accelerated evolution that specifically affected genes in the lineage preceding the group containing N. delphensis and the three pathogens, which may provide clues to the higher propensity of this group to infect humans. Finally, the number of Epa-like adhesins is specifically enriched in the pathogens, particularly in C. glabrata.
Remarkably, some features thought to be the result of adaptation of C. glabrata to a pathogenic lifestyle, are present throughout the Nakaseomyces, indicating these are rather ancient adaptations to other environments. Phylogeny suggests that human pathogenesis evolved several times, independently within the clade. The expansion of the EPA gene family in pathogens establishes an evolutionary link between adhesion and virulence phenotypes. Our analyses thus shed light onto the relationships between virulence and the recent genomic changes that occurred within the Nakaseomyces.
Sequence Accession Numbers
Nakaseomyces delphensis: CAPT01000001 to CAPT01000179
Candida bracarensis: CAPU01000001 to CAPU01000251
Candida nivariensis: CAPV01000001 to CAPV01000123
Candida castellii: CAPW01000001 to CAPW01000101
Nakaseomyces bacillisporus: CAPX01000001 to CAPX01000186
PMCID: PMC3847288  PMID: 24034898
Candida glabrata; Fungal pathogens; Nakaseomyces; Yeast genomes; Yeast evolution
4.  A general framework for optimization of probes for gene expression microarray and its application to the fungus Podospora anserina 
BMC Research Notes  2010;3:171.
The development of new microarray technologies makes custom long oligonucleotide arrays affordable for many experimental applications, notably gene expression analyses. Reliable results depend on probe design quality and selection. Probe design strategy should cope with the limited accuracy of de novo gene prediction programs, and annotation up-dating. We present a novel in silico procedure which addresses these issues and includes experimental screening, as an empirical approach is the best strategy to identify optimal probes in the in silico outcome.
We used four criteria for in silico probe selection: cross-hybridization, hairpin stability, probe location relative to coding sequence end and intron position. This latter criterion is critical when exon-intron gene structure predictions for intron-rich genes are inaccurate. For each coding sequence (CDS), we selected a sub-set of four probes. These probes were included in a test microarray, which was used to evaluate the hybridization behavior of each probe. The best probe for each CDS was selected according to three experimental criteria: signal-to-noise ratio, signal reproducibility, and representative signal intensities. This procedure was applied for the development of a gene expression Agilent platform for the filamentous fungus Podospora anserina and the selection of a single 60-mer probe for each of the 10,556 P. anserina CDS.
A reliable gene expression microarray version based on the Agilent 44K platform was developed with four spot replicates of each probe to increase statistical significance of analysis.
PMCID: PMC2908635  PMID: 20565839
5.  FUNGIpath: a tool to assess fungal metabolic pathways predicted by orthology 
BMC Genomics  2010;11:81.
More and more completely sequenced fungal genomes are becoming available and many more sequencing projects are in progress. This deluge of data should improve our knowledge of the various primary and secondary metabolisms of Fungi, including their synthesis of useful compounds such as antibiotics or toxic molecules such as mycotoxins. Functional annotation of many fungal genomes is imperfect, especially of genes encoding enzymes, so we need dedicated tools to analyze their metabolic pathways in depth.
FUNGIpath is a new tool built using a two-stage approach. Groups of orthologous proteins predicted using complementary methods of detection were collected in a relational database. Each group was further mapped on to steps in the metabolic pathways published in the public databases KEGG and MetaCyc. As a result, FUNGIpath allows the primary and secondary metabolisms of the different fungal species represented in the database to be compared easily, making it possible to assess the level of specificity of various pathways at different taxonomic distances. It is freely accessible at
As more and more fungal genomes are expected to be sequenced during the coming years, FUNGIpath should help progressively to reconstruct the ancestral primary and secondary metabolisms of the main branches of the fungal tree of life and to elucidate the evolution of these ancestral fungal metabolisms to various specific derived metabolisms.
PMCID: PMC2829015  PMID: 20122162
6.  SynteBase/SynteView: a tool to visualize gene order conservation in prokaryotic genomes 
BMC Bioinformatics  2008;9:536.
It has been repeatedly observed that gene order is rapidly lost in prokaryotic genomes. However, persistent synteny blocks are found when comparing more or less distant species. These genes that remain consistently adjacent are appealing candidates for the study of genome evolution and a more accurate definition of their functional role. Such studies require visualizing conserved synteny blocks in a large number of genomes at all taxonomic distances.
After comparing nearly 600 completely sequenced genomes encompassing the whole prokaryotic tree of life, the computed synteny data were assembled in a relational database, SynteBase. SynteView was designed to visualize conserved synteny blocks in a large number of genomes after choosing one of them as a reference. SynteView functions with data stored either in SynteBase or in a home-made relational database of personal data. In addition, this software can compute on-the-fly and display the distribution of synteny blocks which are conserved in pairs of genomes. This tool has been designed to provide a wealth of information on each positional orthologous gene, to be user-friendly and customizable. It is also possible to download sequences of genes belonging to these synteny blocks for further studies. SynteView is accessible through Java Webstart at .
SynteBase answers queries about gene order conservation and SynteView visualizes the obtained results in a flexible and powerful way which provides a comparative overview of the conserved synteny in a large number of genomes, whatever their taxonomic distances.
PMCID: PMC2667195  PMID: 19087285
7.  The genome sequence of the model ascomycete fungus Podospora anserina 
Genome Biology  2008;9(5):R77.
A 10X draft sequence of Podospora anserina genome shows highly dynamic evolution since its divergence from Neurospora crassa.
The dung-inhabiting ascomycete fungus Podospora anserina is a model used to study various aspects of eukaryotic and fungal biology, such as ageing, prions and sexual development.
We present a 10X draft sequence of P. anserina genome, linked to the sequences of a large expressed sequence tag collection. Similar to higher eukaryotes, the P. anserina transcription/splicing machinery generates numerous non-conventional transcripts. Comparison of the P. anserina genome and orthologous gene set with the one of its close relatives, Neurospora crassa, shows that synteny is poorly conserved, the main result of evolution being gene shuffling in the same chromosome. The P. anserina genome contains fewer repeated sequences and has evolved new genes by duplication since its separation from N. crassa, despite the presence of the repeat induced point mutation mechanism that mutates duplicated sequences. We also provide evidence that frequent gene loss took place in the lineages leading to P. anserina and N. crassa. P. anserina contains a large and highly specialized set of genes involved in utilization of natural carbon sources commonly found in its natural biotope. It includes genes potentially involved in lignin degradation and efficient cellulose breakdown.
The features of the P. anserina genome indicate a highly dynamic evolution since the divergence of P. anserina and N. crassa, leading to the ability of the former to use specific complex carbon sources that match its needs in its natural biotope.
PMCID: PMC2441463  PMID: 18460219
8.  Assessing the evolutionary rate of positional orthologous genes in prokaryotes using synteny data 
Comparison of completely sequenced microbial genomes has revealed how fluid these genomes are. Detecting synteny blocks requires reliable methods to determining the orthologs among the whole set of homologs detected by exhaustive comparisons between each pair of completely sequenced genomes. This is a complex and difficult problem in the field of comparative genomics but will help to better understand the way prokaryotic genomes are evolving.
We have developed a suite of programs that automate three essential steps to study conservation of gene order, and validated them with a set of 107 bacteria and archaea that cover the majority of the prokaryotic taxonomic space. We identified the whole set of shared homologs between two or more species and computed the evolutionary distance separating each pair of homologs. We applied two strategies to extract from the set of homologs a collection of valid orthologs shared by at least two genomes. The first computes the Reciprocal Smallest Distance (RSD) using the PAM distances separating pairs of homologs. The second method groups homologs in families and reconstructs each family's evolutionary tree, distinguishing bona fide orthologs as well as paralogs created after the last speciation event. Although the phylogenetic tree method often succeeds where RSD fails, the reverse could occasionally be true. Accordingly, we used the data obtained with either methods or their intersection to number the orthologs that are adjacent in for each pair of genomes, the Positional Orthologous Genes (POGs), and to further study their properties. Once all these synteny blocks have been detected, we showed that POGs are subject to more evolutionary constraints than orthologs outside synteny groups, whichever the taxonomic distance separating the compared organisms.
The suite of programs described in this paper allows a reliable detection of orthologs and is useful for evaluating gene order conservation in prokaryotes whichever their taxonomic distance. Thus, our approach will make easy the rapid identification of POGS in the next few years as we are expecting to be inundated with thousands of completely sequenced microbial genomes.
PMCID: PMC2238764  PMID: 18047665
9.  ORENZA: a web resource for studying ORphan ENZyme activities 
BMC Bioinformatics  2006;7:436.
Despite the current availability of several hundreds of thousands of amino acid sequences, more than 36% of the enzyme activities (EC numbers) defined by the Nomenclature Committee of the International Union of Biochemistry and Molecular Biology (NC-IUBMB) are not associated with any amino acid sequence in major public databases. This wide gap separating knowledge of biochemical function and sequence information is found for nearly all classes of enzymes. Thus, there is an urgent need to explore these sequence-less EC numbers, in order to progressively close this gap.
We designed ORENZA, a PostgreSQL database of ORphan ENZyme Activities, to collate information about the EC numbers defined by the NC-IUBMB with specific emphasis on orphan enzyme activities. Complete lists of all EC numbers and of orphan EC numbers are available and will be periodically updated. ORENZA allows one to browse the complete list of EC numbers or the subset associated with orphan enzymes or to query a specific EC number, an enzyme name or a species name for those interested in particular organisms. It is possible to search ORENZA for the different biochemical properties of the defined enzymes, the metabolic pathways in which they participate, the taxonomic data of the organisms whose genomes encode them, and many other features. The association of an enzyme activity with an amino acid sequence is clearly underlined, making it easy to identify at once the orphan enzyme activities. Interactive publishing of suggestions by the community would provide expert evidence for re-annotation of orphan EC numbers in public databases.
ORENZA is a Web resource designed to progressively bridge the unwanted gap between function (enzyme activities) and sequence (dataset present in public databases). ORENZA should increase interactions between communities of biochemists and of genomicists. This is expected to reduce the number of orphan enzyme activities by allocating gene sequences to the relevant enzymes.
PMCID: PMC1609188  PMID: 17026747

Results 1-9 (9)