SynteBase/SynteView: a tool to visualize gene order conservation in prokaryotic genomes

<p>Abstract</p> <p>Background</p> <p>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.</p> <p>Results</p> <p>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 <it>on-the-fly </it>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 <url>http://www.synteview.u-psud.fr</url>.</p> <p>Conclusion</p> <p>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.</p

FUNGIpath: a tool to assess fungal metabolic pathways predicted by orthology

<p>Abstract</p> <p>Background</p> <p>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.</p> <p>Description</p> <p>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 <url>http://www.fungipath.u-psud.fr</url>.</p> <p>Conclusions</p> <p>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.</p

Assessing the evolutionary rate of positional orthologous genes in prokaryotes using synteny data

<p>Abstract</p> <p>Background</p> <p>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.</p> <p>Results</p> <p>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 <it>bona fide </it>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.</p> <p>Conclusion</p> <p>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.</p

ORENZA: a web resource for studying ORphan ENZyme activities

BACKGROUND: 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. DESCRIPTION: 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. CONCLUSION: 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

A general framework for optimization of probes for gene expression microarray and its application to the fungus Podospora anserina

<p>Abstract</p> <p>Background</p> <p>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 <it>de novo </it>gene prediction programs, and annotation up-dating. We present a novel <it>in silico </it>procedure which addresses these issues and includes experimental screening, as an empirical approach is the best strategy to identify optimal probes in the <it>in silico </it>outcome.</p> <p>Findings</p> <p>We used four criteria for <it>in silico </it>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 <it>Podospora anserina </it>and the selection of a single 60-mer probe for each of the 10,556 <it>P. anserina </it>CDS.</p> <p>Conclusions</p> <p>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.</p

Targeted Assembly of Short Sequence Reads

As next-generation sequence (NGS) production continues to increase, analysis is becoming a significant bottleneck. However, in situations where information is required only for specific sequence variants, it is not necessary to assemble or align whole genome data sets in their entirety. Rather, NGS data sets can be mined for the presence of sequence variants of interest by localized assembly, which is a faster, easier, and more accurate approach. We present TASR, a streamlined assembler that interrogates very large NGS data sets for the presence of specific variants, by only considering reads within the sequence space of input target sequences provided by the user. The NGS data set is searched for reads with an exact match to all possible short words within the target sequence, and these reads are then assembled strin-gently to generate a consensus of the target and flanking sequence. Typically, variants of a particular locus are provided as different target sequences, and the presence of the variant in the data set being interrogated is revealed by a successful assembly outcome. However, TASR can also be used to find unknown sequences that flank a given target. We demonstrate that TASR has utility in finding or confirming ge-nomic mutations, polymorphism, fusion and integration events. Targeted assembly is a powerful method for interrogating large data sets for the presence of sequence variants of interest. TASR is a fast, flexible and easy to use tool for targeted assembly

Decontamination of MDA Reagents for Single Cell Whole Genome Amplification

Single cell genomics is a powerful and increasingly popular tool for studying the genetic make-up of uncultured microbes. A key challenge for successful single cell sequencing and analysis is the removal of exogenous DNA from whole genome amplification reagents. We found that UV irradiation of the multiple displacement amplification (MDA) reagents, including the Phi29 polymerase and random hexamer primers, effectively eliminates the amplification of contaminating DNA. The methodology is quick, simple, and highly effective, thus significantly improving whole genome amplification from single cells

MycoRRdb: A Database of Computationally Identified Regulatory Regions within Intergenic Sequences in Mycobacterial Genomes

The identification of regulatory regions for a gene is an important step towards deciphering the gene regulation. Regulatory regions tend to be conserved under evolution that facilitates the application of comparative genomics to identify such regions. The present study is an attempt to make use of this attribute to identify regulatory regions in the Mycobacterium species followed by the development of a database, MycoRRdb. It consist the regulatory regions identified within the intergenic distances of 25 mycobacterial species. MycoRRdb allows to retrieve the identified intergenic regulatory elements in the mycobacterial genomes. In addition to the predicted motifs, it also allows user to retrieve the Reciprocal Best BLAST Hits across the mycobacterial genomes. It is a useful resource to understand the transcriptional regulatory mechanism of mycobacterial species. This database is first of its kind which specifically addresses cis-regulatory regions and also comprehensive to the mycobacterial species. Database URL: http://mycorrdb.uohbif.in

Host-Pathogen O-Methyltransferase Similarity and Its Specific Presence in Highly Virulent Strains of Francisella tularensis Suggests Molecular Mimicry

Whole genome comparative studies of many bacterial pathogens have shown an overall high similarity of gene content (>95%) between phylogenetically distinct subspecies. In highly clonal species that share the bulk of their genomes subtle changes in gene content and small-scale polymorphisms, especially those that may alter gene expression and protein-protein interactions, are more likely to have a significant effect on the pathogen's biology. In order to better understand molecular attributes that may mediate the adaptation of virulence in infectious bacteria, a comparative study was done to further analyze the evolution of a gene encoding an o-methyltransferase that was previously identified as a candidate virulence factor due to its conservation specifically in highly pathogenic Francisella tularensis subsp. tularensis strains. The o-methyltransferase gene is located in the genomic neighborhood of a known pathogenicity island and predicted site of rearrangement. Distinct o-methyltransferase subtypes are present in different Francisella tularensis subspecies. Related protein families were identified in several host species as well as species of pathogenic bacteria that are otherwise very distant phylogenetically from Francisella, including species of Mycobacterium. A conserved sequence motif profile is present in the mammalian host and pathogen protein sequences, and sites of non-synonymous variation conserved in Francisella subspecies specific o-methyltransferases map proximally to the predicted active site of the orthologous human protein structure. Altogether, evidence suggests a role of the F. t. subsp. tularensis protein in a mechanism of molecular mimicry, similar perhaps to Legionella and Coxiella. These findings therefore provide insights into the evolution of niche-restriction and virulence in Francisella, and have broader implications regarding the molecular mechanisms that mediate host-pathogen relationships

A Multi-Sample Based Method for Identifying Common CNVs in Normal Human Genomic Structure Using High-Resolution aCGH Data

BACKGROUND: It is difficult to identify copy number variations (CNV) in normal human genomic data due to noise and non-linear relationships between different genomic regions and signal intensity. A high-resolution array comparative genomic hybridization (aCGH) containing 42 million probes, which is very large compared to previous arrays, was recently published. Most existing CNV detection algorithms do not work well because of noise associated with the large amount of input data and because most of the current methods were not designed to analyze normal human samples. Normal human genome analysis often requires a joint approach across multiple samples. However, the majority of existing methods can only identify CNVs from a single sample. METHODOLOGY AND PRINCIPAL FINDINGS: We developed a multi-sample-based genomic variations detector (MGVD) that uses segmentation to identify common breakpoints across multiple samples and a k-means-based clustering strategy. Unlike previous methods, MGVD simultaneously considers multiple samples with different genomic intensities and identifies CNVs and CNV zones (CNVZs); CNVZ is a more precise measure of the location of a genomic variant than the CNV region (CNVR). CONCLUSIONS AND SIGNIFICANCE: We designed a specialized algorithm to detect common CNVs from extremely high-resolution multi-sample aCGH data. MGVD showed high sensitivity and a low false discovery rate for a simulated data set, and outperformed most current methods when real, high-resolution HapMap datasets were analyzed. MGVD also had the fastest runtime compared to the other algorithms evaluated when actual, high-resolution aCGH data were analyzed. The CNVZs identified by MGVD can be used in association studies for revealing relationships between phenotypes and genomic aberrations. Our algorithm was developed with standard C++ and is available in Linux and MS Windows format in the STL library. It is freely available at: http://embio.yonsei.ac.kr/~Park/mgvd.php