Minimal absent words in prokaryotic and eukaryotic genomes

Minimal absent words have been computed in genomes of organisms from all domains of life. Here, we explore different sets of minimal absent words in the genomes of 22 organisms (one archaeota, thirteen bacteria and eight eukaryotes). We investigate if the mutational biases that may explain the deficit of the shortest absent words in vertebrates are also pervasive in other absent words, namely in minimal absent words, as well as to other organisms. We find that the compositional biases observed for the shortest absent words in vertebrates are not uniform throughout different sets of minimal absent words. We further investigate the hypothesis of the inheritance of minimal absent words through common ancestry from the similarity in dinucleotide relative abundances of different sets of minimal absent words, and find that this inheritance may be exclusive to vertebrates.     

MRD: a microsatellite repeats database for prokaryotic and eukaryotic genomes

MRD is a database system to access the microsatellite repeats information of genomes such as archea, eubacteria, and other eukaryotic genomes whose sequence information is available in public domains. MRD stores information about simple tandemly repeated k-mer sequences where k= 1 to 6, i.e. monomer to hexamer. The web interface allows the users to search for the repeat of their interest and to know about the association of the repeat with genes and genomic regions in the specific organism. The data contains the abundance and distribution of microsatellites in the coding and non-coding regions of the genome. The exact location of repeats with respect to genomic regions of interest (such as UTR, exon, intron or intergenic regions) whichever is applicable to organism is highlighted. MRD is available on the World Wide Web at and/or . The database is designed as an open-ended system to accommodate the microsatellite repeats information of other genomes whose complete sequences will be available in future through public domain.     

Prophinder: a computational tool for prophage prediction in prokaryotic genomes

Prophinder is a prophage prediction tool coupled with a prediction database, a web server and web service. Predicted prophages will help to fill the gaps in the current sparse phage sequence space, which should cover an estimated 100 million species. Systematic and reliable predictions will enable further studies of prophages contribution to the bacteriophage gene pool and to better understand gene shuffling between prophages and phages infecting the same host. AVAILABILITY: Softare is available at http://aclame.ulb.ac.be/prophinder     

Periodicity in prokaryotic and eukaryotic genomes identified by power spectrum analysis

We used a power spectrum method to identify periodic patterns in nucleotide sequence, and characterized nucleotide sequences that confer periodicities to prokaryotic and eukaryotic genomes and genomes. A 10-bp periodicity was prevalent in hyperthermophilic bacteria and archaebacteria, and an 11-bp periodicity was prevalent in eubacteria. The 10-bp periodicity was also prevalent in the eukaryotes such as the worm Caenorhabditis elegans. Additionally, in the worm genome, a 68-bp periodicity in chromosome I, a 59-bp periodicity in chromosome II, and a 94-bp periodicity in chromosome III were found. In human chromosomes 21 and 22, approximately 167- or 84-bp periodicity was detected along the entire length of these chromosomes. Because the 167-bp is identical to the length of DNA that forms two complete helical turns in nucleosome organization, we speculated that the respective sequences may correspond to arrays of a special compact form of nucleosomes clustered in specific regions of the human chromosomes. This periodic element contained a high frequency of TGG. TGG-rich sequences are known to form a specific subset of folded DNA structures, and therefore, the sequences might have potential to form specific higher order structures related to the clustered occurrence of a specific form of the speculated nucleosomes.     

CONSORF: a consensus prediction system for prokaryotic coding sequences

CONSORF is a fully automatic high-accuracy identification system that provides consensus prokaryotic CDS information. It first predicts the CDSs supported by consensus alignments. The alignments are derived from multiple genome-to-proteome comparisons with other prokaryotes using the FASTX program. Then, it fills the empty genomic regions with the CDSs supported by consensus ab initio predictions. From those consensus results, CONSORF provides prediction reliability scores, predicted frame-shifts, alternative start sites and best pair-wise match information against other prokaryotes. These results are easily accessed from a website.     

Intragenic spatial patterns of codon usage bias in prokaryotic and eukaryotic genomes

To study the roles of translational accuracy, translational efficiency, and the Hill-Robertson effect in codon usage bias, we studied the intragenic spatial distribution of synonymous codon usage bias in four prokaryotic (Escherichia coli, Bacillus subtilis, Sulfolobus tokodaii, and Thermotoga maritima) and two eukaryotic (Saccharomyces cerevisiae and Drosophila melanogaster) genomes. We generated supersequences at each codon position across genes in a genome and computed the overall bias at each codon position. By quantitatively evaluating the trend of spatial patterns using isotonic regression, we show that in yeast and prokaryotic genomes, codon usage bias increases along translational direction, which is consistent with purifying selection against nonsense errors. Fruit fly genes show a nearly symmetric M-shaped spatial pattern of codon usage bias, with less bias in the middle and both ends. The low codon usage bias in the middle region is best explained by interference (the Hill-Robertson effect) between selections at different codon positions. In both yeast and fruit fly, spatial patterns of codon usage bias are characteristically different from patterns of GC-content variations. Effect of expression level on the strength of codon usage bias is more conspicuous than its effect on the shape of the spatial distribution.     

Glucanase gene diversity in prokaryotic and eukaryotic organisms

A number of bacteria and eukaryotes produce extracellular enzymes that degrade various types of polysaccharides including the glucans starch, cellulose and hemicellulose (xylan). The similarities in the modes of expression and specificity of enzyme classes, such as amylase, cellulose and xylanase, suggest common genetic origins for particular activities. Our determination of the extent of similarity between these glucanases suggests that such data may be of very limited use in describing the early evolution of these proteins. The great diversity of these proteins does allow identification of their most highly conserved (and presumably functionally important) regions.     

GlycoPP: a webserver for prediction of N- and O-glycosites in prokaryotic protein sequences

Glycosylation is one of the most abundant post-translational modifications (PTMs) required for various structure/function modulations of proteins in a living cell. Although elucidated recently in prokaryotes, this type of PTM is present across all three domains of life. In prokaryotes, two types of protein glycan linkages are more widespread namely, N- linked, where a glycan moiety is attached to the amide group of Asn, and O- linked, where a glycan moiety is attached to the hydroxyl group of Ser/Thr/Tyr. For their biologically ubiquitous nature, significance, and technology applications, the study of prokaryotic glycoproteins is a fast emerging area of research. Here we describe new Support Vector Machine (SVM) based algorithms (models) developed for predicting glycosylated-residues (glycosites) with high accuracy in prokaryotic protein sequences. The models are based on binary profile of patterns, composition profile of patterns, and position-specific scoring matrix profile of patterns as training features. The study employ an extensive dataset of 107 N-linked and 116 O-linked glycosites extracted from 59 experimentally characterized glycoproteins of prokaryotes. This dataset includes validated N-glycosites from phyla Crenarchaeota, Euryarchaeota (domain Archaea), Proteobacteria (domain Bacteria) and validated O-glycosites from phyla Actinobacteria, Bacteroidetes, Firmicutes and Proteobacteria (domain Bacteria). In view of the current understanding that glycosylation occurs on folded proteins in bacteria, hybrid models have been developed using information on predicted secondary structures and accessible surface area in various combinations with training features. Using these models, N-glycosites and O-glycosites could be predicted with an accuracy of 82.71% (MCC 0.65) and 73.71% (MCC 0.48), respectively. An evaluation of the best performing models with 28 independent prokaryotic glycoproteins confirms the suitability of these models in predicting N- and O-glycosites in potential glycoproteins from aforementioned organisms, with reasonably high confidence. A web server GlycoPP, implementing these models is available freely at http:/www.imtech.res.in/raghava/glycopp/.     

Evidence for a prokaryotic insertion-sequence contamination in eukaryotic sequences registered in different databases

An insertion-sequence of prokaryotic origin was detected in a genomic clone obtained from a Phaseolus vulgaris bacterial artificial chromosome (BAC) library. This BAC clone, characterized as part of a contig constructed near a virus resistance gene, exhibited restriction fragment length polymorphism with an overlapping clone of the contig. Restriction analysis of DNA obtained from individual colonies of the stock culture indicated the presence of a mixed population of wild-type and insertional mutants. Sequence analysis of both members of the population revealed the presence of IS10R, an insertion-sequence from Escherichia coli. A BLAST search for IS10-like sequences detected unexpected homologies with a large number of eukaryotic sequences from Homo sapiens, Arabidopsis thaliana, Drosophila melanogaster and Caenorhabditis elegans. Southern analysis of a random sample of BAC clones failed to detect IS10 in the BAC DNA. However, prolonged sub-culturing of a set of 15 clones resulted in transposition into the BAC DNA. Eventually, all cultures acquired a 2.3-kb fragment that hybridized strongly with IS10. Sequence analysis revealed the presence of a preferred site for transposition in the BAC vector. These results indicate that a large number, if not all, of the BAC libraries from different organisms are contaminated with IS10R. The source of this element has been identified as the DH10B strain of E. coli used as the host for BAC libraries. Received: 5 December 2000 / Accepted: 25 April 2001     

UNIREP: A microcomputer program to find unique and repetitive nucleotide sequences in genomes

We present a program UNIREP, written in PowerBASIC for IBM-PCs,that identifies repetitive and unique nucleotide sequences ingenomes or parts of genomes. A key feature of the algorithmis an oligonucleotide representation in a numerical code tomake possible a comparison of all pairs of oligonucleotides(including overlaps) occurring in the analyzed sequence. Thiscomparison assigns a score to each oligo nucleotide, reflectingits similarity/dissimilarity to other oligonucleotides of thesame length in the analyzed sequence. The score is plotted alongthe sequence so that peaks in the plot indicate repetitive regionsand very low values reflect unique sequences. The scores arefiltered to suppress or enhance the unique or repetitive sequencesaccording to the user's wish. UNIREP is extended by auxiliaryprograms HIGHER and LOWER to list nucleotide sequences thathave scores higher or lower than given limits. The potentialof UNIREP is demonstrated using several long nucleotide sequencesincluding the complete genomic sequence of EBV.     

Prophage Finder: a prophage loci prediction tool for prokaryotic genome sequences

Prophage loci often remain under-annotated or even unrecognized in prokaryotic genome sequencing projects. A PHP application, Prophage Finder, has been developed and implemented to predict prophage loci, based upon clusters of phage-related gene products encoded within DNA sequences. This application provides results detailing several facets of these clusters to facilitate rapid prediction and analysis of prophage sequences. Prophage Finder was tested using previously annotated prokaryotic genomic sequences with manually curated prophage loci as benchmarks. Additional analyses from Prophage Finder searches of several draft prokaryotic genome sequences are available through the Web site (http://bioinformatics.uwp.edu/~phage/DOEResults.php) to illustrate the potential of this application.     

A compression-based approach for coding sequences identification. I. Application to prokaryotic genomes.

Most of the gene prediction algorithms for prokaryotes are based on Hidden Markov Models or similar machine-learning approaches, which imply the optimization of a high number of parameters. The present paper presents a novel method for the classification of coding and non-coding regions in prokaryotic genomes, based on a suitably defined compression index of a DNA sequence. The main features of this new method are the non-parametric logic and the costruction of a dictionary of words extracted from the sequences. These dictionaries can be very useful to perform further analyses on the genomic sequences themselves. The proposed approach has been applied on some prokaryotic complete genomes, obtaining optimal scores of correctly recognized coding and non-coding regions. Several false-positive and false-negative cases have been investigated in detail, which have revealed that this approach can fail in the presence of highly structured coding regions (e.g., genes coding for modular proteins) or quasi-random non-coding regions (e.g., regions hosting non-functional fragments of copies of functional genes; regions hosting promoters or other protein-binding sequences). We perform an overall comparison with other gene-finder software, since at this step we are not interested in building another gene-finder system, but only in exploring the possibility of the suggested approach.     

Computational approaches for the analysis of gene neighbourhoods in prokaryotic genomes

Gene order in prokaryotes is conserved to a much lesser extent than protein sequences. Only some operons, primarily those that encode physically interacting proteins, are conserved in all or most of the bacterial and archaeal genomes. Nevertheless, even the limited conservation of operon organisation that is observed provides valuable evolutionary and functional clues through multiple genome comparisons. With the rapid growth in the number and diversity of sequenced prokaryotic genomes, functional inferences for uncharacterized genes located in the same conserved gene neighborhood with well-studied genes are becoming increasingly important. In this review, we discuss various computational approaches for identification of conserved gene strings and construction of local alignments of gene orders in prokaryotic genomes.     

Transfer and expression of plasmids containing human cytomegalovirus immediate-early gene 1 promoter-enhancer sequences in eukaryotic and prokaryotic cells

The human cytomegalovirus immediate-early gene region 1 promoter-enhancer is active in bacteria and in many mammalian cells. Recombinant plasmids containing portions of this DNA can be used to promote the expression of foreign proteins in many cells. In this communication, we report the optimal conditions for transfer of plasmid DNA to cells by electroporation and the transient expression assays which document the activity of different promoter constructions. The observed activity of the human cytomegalovirus promoter is more than 100-fold higher than the activity of the early promoter of SV40.     

Genome SEGE: A database for 'intronless' genes in eukaryotic genomes

Background  

A number of completely sequenced eukaryotic genome data are available in the public domain. Eukaryotic genes are either 'intron containing' or 'intronless'. Eukaryotic 'intronless' genes are interesting datasets for comparative genomics and evolutionary studies. The SEGE database containing a collection of eukaryotic single exon genes is available. However, SEGE is derived using GenBank. The redundant, incomplete and heterogeneous qualities of GenBank data are a bottleneck for biological investigation in comparative genomics and evolutionary studies. Such studies often require representative gene sets from each genome and this is possible only by deriving specific datasets from completely sequenced genome data. Thus Genome SEGE, a database for 'intronless' genes in completely sequenced eukaryotic genomes, has been constructed.     

A fast and flexible approach to oligonucleotide probe design for genomes and gene families

MOTIVATION: With hundreds of completely sequenced microbial genomes available, and advancements in DNA microarray technology, the detection of genes in microbial communities consisting of hundreds of thousands of sequences may be possible. The existing strategies developed for DNA probe design, geared toward identifying specific sequences, are not suitable due to the lack of coverage, flexibility and efficiency necessary for applications in metagenomics. METHODS: ProDesign is a tool developed for the selection of oligonucleotide probes to detect members of gene families present in environmental samples. Gene family-specific probe sequences are generated based on specific and shared words, which are found with the spaced seed hashing algorithm. To detect more sequences, those sharing some common words are re-clustered into new families, then probes specific for the new families are generated. RESULTS: The program is very flexible in that it can be used for designing probes for detecting many genes families simultaneously and specifically in one or more genomes. Neither the length nor the melting temperature of the probes needs to be predefined. We have found that ProDesign provides more flexibility, coverage and speed than other software programs used in the selection of probes for genomic and gene family arrays. AVAILABILITY: ProDesign is licensed free of charge to academic users. ProDesign and Supplementary Material can be obtained by contacting the authors. A web server for ProDesign is available at http://www.uhnresearch.ca/labs/tillier/ProDesign/ProDesign.html. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.     

A computational approach for identifying pathogenicity islands in prokaryotic genomes

Background  

Pathogenicity islands (PAIs), distinct genomic segments of pathogens encoding virulence factors, represent a subgroup of genomic islands (GIs) that have been acquired by horizontal gene transfer event. Up to now, computational approaches for identifying PAIs have been focused on the detection of genomic regions which only differ from the rest of the genome in their base composition and codon usage. These approaches often lead to the identification of genomic islands, rather than PAIs.     

A neural network method for identification of prokaryotic and eukaryotic signal peptides and prediction of their cleavage sites

We have developed a new method for the identification of signal peptides and their cleavage sites based on neural networks trained on separate sets of prokaryotic and eukaryotic sequences. The method performs significantly better than previous prediction schemes, and can easily be applied to genome-wide data sets. Discrimination between cleaved signal peptides and uncleaved N-terminal signal-anchor sequences is also possible, though with lower precision. Predictions can be made on a publicly available WWW server: http://www.cbs.dtu.dk/services/SignalP/.