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At least 415 records · Page 23Linked to original sources
PubMed2025

nf-core/pacvar: a pipeline for analyzing long-read PacBio whole genome and repeat expansion sequencing data.

MOTIVATION: Pacific Biosciences (PacBio) single-molecule, long-read sequencing enables whole genome annotation and the characterization of 20 complex repetitive repeat regions, especially relevant to neurodegenerative diseases, through their PureTarget panel. Long-read whole-genome sequencing (WGS) also allows for the detection of structural variants that would be difficult to detect with traditional short-read sequencing. However, the raw unaligned Binary Alignment Map data need to be processed before analysis. There is a need for an intuitive comprehensive bioinformatic pipeline that can analyze these data. RESULTS: We present nf-core/pacvar, a comprehensive pipeline for analyzing both PacBio single-molecule PureTarget and WGS data that demultiplexes and parallelizes pre-processing, variant calling and repeat characterization. nf-core/pacvar is compatible with little configuration and has few dependencies. This pipeline enables rapid end-to-end, parallel processing of PacBio single-molecule whole genome and targeted repeat expansion sequencing. AVAILABILITY AND IMPLEMENTATION: nf-core/pacvar is available on nf-core website (https://nf-co.re/pacvar/) and on github (https://github.com/nf-core/pacvar) under MIT License (DOI: 10.5281/zenodo.14813048).

Software↗
PubMed2006

Identification of 17 Pseudomonas aeruginosa sRNAs and prediction of sRNA-encoding genes in 10 diverse pathogens using the bioinformatic tool sRNAPredict2.

sRNAs are small, non-coding RNA species that control numerous cellular processes. Although it is widely accepted that sRNAs are encoded by most if not all bacteria, genome-wide annotations for sRNA-encoding genes have been conducted in only a few of the nearly 300 bacterial species sequenced to date. To facilitate the efficient annotation of bacterial genomes for sRNA-encoding genes, we developed a program, sRNAPredict2, that identifies putative sRNAs by searching for co-localization of genetic features commonly associated with sRNA-encoding genes. Using sRNAPredict2, we conducted genome-wide annotations for putative sRNA-encoding genes in the intergenic regions of 11 diverse pathogens. In total, 2759 previously unannotated candidate sRNA loci were predicted. There was considerable range in the number of sRNAs predicted in the different pathogens analyzed, raising the possibility that there are species-specific differences in the reliance on sRNA-mediated regulation. Of 34 previously unannotated sRNAs predicted in the opportunistic pathogen Pseudomonas aeruginosa, 31 were experimentally tested and 17 were found to encode sRNA transcripts. Our findings suggest that numerous genes have been missed in the current annotations of bacterial genomes and that, by using improved bioinformatic approaches and tools, much remains to be discovered in 'intergenic' sequences.

Computational Biology↗
PubMed2006

A hybrid gene team model and its application to genome analysis.

It is well-known that functionally related genes occur in a physically clustered form, especially operons in bacteria. By leveraging on this fact, there has recently been an interesting problem formulation known as gene team model, which searches for a set of genes that co-occur in a pair of closely related genomes. However, many gene teams, even experimentally verified operons, frequently scatter within other genomes. Thus, the gene team model should be refined to reflect this observation. In this paper, we generalized the gene team model, that looks for gene clusters in a physically clustered form, to multiple genome cases with relaxed constraints. We propose a novel hybrid pattern model that combines the set and the sequential pattern models. Our model searches for gene clusters with and/or without physical proximity constraint. This model is implemented and tested with 97 genomes (120 replicons). The result was analyzed to show the usefulness of our model. We also compared the result from our hybrid model to those from the traditional gene team model. We also show that predicted gene teams can be used for various genome analysis: operon prediction, phylogenetic analysis of organisms, contextual sequence analysis and genome annotation. Our program is fast enough to provide a service on the web at http://platcom.informatics.indiana.edu/platcom/. Users can select any combination of 97 genomes to predict gene teams.

Algorithms↗
PubMed2005

Expanded metabolic reconstruction of Helicobacter pylori (iIT341 GSM/GPR): an in silico genome-scale characterization of single- and double-deletion mutants.

Helicobacter pylori is a human gastric pathogen infecting almost half of the world population. Herein, we present an updated version of the metabolic reconstruction of H. pylori strain 26695 based on the revised genome annotation and new experimental data. This reconstruction, iIT341 GSM/GPR, represents a detailed review of the current literature about H. pylori as it integrates biochemical and genomic data in a comprehensive framework. In total, it accounts for 341 metabolic genes, 476 intracellular reactions, 78 exchange reactions, and 485 metabolites. Novel features of iIT341 GSM/GPR include (i) gene-protein-reaction associations, (ii) elementally and charge-balanced reactions, (iii) more accurate descriptions of isoprenoid and lipopolysaccharide metabolism, and (iv) quantitative assessments of the supporting data for each reaction. This metabolic reconstruction was used to carry out in silico deletion studies to identify essential and conditionally essential genes in H. pylori. A total of 128 essential and 75 conditionally essential metabolic genes were identified. Predicted growth phenotypes of single knockouts were validated using published experimental data. In addition, in silico double-deletion studies identified a total of 47 synthetic lethal mutants involving 67 different metabolic genes in rich medium.

Biotin↗
PubMed2003

DNA microarrays in parasitology: strengths and limitations.

Genome sequencing efforts have provided a wealth of new biological information that promises to have a major impact on our understanding of parasites. Microarrays provide one of the major high-throughput platforms by which this information can be exploited in the laboratory. Many excellent reviews and technique articles have recently been published on applying microarrays to organisms for which fully annotated genomes are at hand. However, many parasitologists work on organisms whose genomes have been only partially sequenced and where little, if any, annotation is available. The focus of this review is on how to use and apply microarrays to these situations.

Animals↗
PubMed2005

The TIGR Gene Indices: clustering and assembling EST and known genes and integration with eukaryotic genomes.

Although the list of completed genome sequencing projects has expanded rapidly, sequencing and analysis of expressed sequence tags (ESTs) remain a primary tool for discovery of novel genes in many eukaryotes and a key element in genome annotation. The TIGR Gene Indices (http://www.tigr.org/tdb/tgi) are a collection of 77 species-specific databases that use a highly refined protocol to analyze gene and EST sequences in an attempt to identify and characterize expressed transcripts and to present them on the Web in a user-friendly, consistent fashion. A Gene Index database is constructed for each selected organism by first clustering, then assembling EST and annotated cDNA and gene sequences from GenBank. This process produces a set of unique, high-fidelity virtual transcripts, or tentative consensus (TC) sequences. The TC sequences can be used to provide putative genes with functional annotation, to link the transcripts to genetic and physical maps, to provide links to orthologous and paralogous genes, and as a resource for comparative and functional genomic analysis.

Animals↗
PubMed2003

DNannotator: Annotation software tool kit for regional genomic sequences.

Sequence annotation is essential for genomics-based research. Investigators of a specific genomic region who have developed abundant local discoveries such as genes and genetic markers, or have collected annotations from multiple resources, can be overwhelmed by the difficulty in creating local annotation and the complexity of integrating all the annotations. Presenting such integrated data in a form suitable for data mining and high-throughput experimental design is even more daunting. DNannotator, a web application, was designed to perform batch annotation on a sizeable genomic region. It takes annotation source data, such as SNPs, genes, primers, and so on, prepared by the end-user and/or a specified target of genomic DNA, and performs de novo annotation. DNannotator can also robustly migrate existing annotations in GenBank format from one sequence to another. Annotation results are provided in GenBank format and in tab-delimited text, which can be imported and managed in a database or spreadsheet and combined with existing annotation as desired. Graphic viewers, such as Genome Browser or Artemis, can display the annotation results. Reference data (reports on the process) facilitating the user's evaluation of annotation quality are optionally provided. DNannotator can be accessed at http://sky.bsd.uchicago.edu/DNannotator.htm.

Chromosomes, Human, Pair 13↗
PubMed2006

A large-scale full-length cDNA analysis to explore the budding yeast transcriptome.

We performed a large-scale cDNA analysis to explore the transcriptome of the budding yeast Saccharomyces cerevisiae. We sequenced two cDNA libraries, one from the cells exponentially growing in a minimal medium and the other from meiotic cells. Both libraries were generated by using a vector-capping method that allows the accurate mapping of transcription start sites (TSSs). Consequently, we identified 11,575 TSSs associated with 3,638 annotated genomic features, including 3,599 ORFs, to suggest that most yeast genes have two or more TSSs. In addition, we identified 45 previously undescribed introns, including those affecting current ORF annotations and those spliced alternatively. Furthermore, the analysis revealed 667 transcription units in the intergenic regions and transcripts derived from antisense strands of 367 known features. We also found that 348 ORFs carry TSSs in their 3'-halves to generate sense transcripts starting from inside the ORFs. These results indicate that the budding yeast transcriptome is considerably more complex than previously thought, and it shares many recently revealed characteristics with the transcriptomes of mammals and other higher eukaryotes. Thus, the genome-wide active transcription that generates novel classes of transcripts appears to be an intrinsic feature of the eukaryotic cells. The budding yeast will serve as a versatile model for the studies on these aspects of transcriptome, and the full-length cDNA clones can function as an invaluable resource in such studies.

5' Untranslated Regions↗
PubMed2005

Mining the probiotic genome: advanced strategies, enhanced benefits, perceived obstacles.

Recent advances in DNA sequencing has made it possible to accurately decipher the entire genetic complement of a probiotic bacterium. Increases in sequencing capabilities have been enhanced through improved computer software that can annotate, or identify, the majority of genes encoded by the sequence. The availability of annotated genome sequence will be important in defining the capabilities of the individual strains of probiotic bacteria. It will also form the platform for microarray and proteomic technologies that allow real-time analysis of RNA and protein expression in the bacterial cell. Investigation of probiotic organisms with these new and potentially powerful tools will facilitate the development of the bacteria as therapeutic agents, and provide the mechanisms to produce advanced probiotic strains. This paper addresses the core technologies in the rapidly growing area of genomics, and their application to the molecular characterisation of probiotic bacteria and host-microbe interactions.

Databases, Genetic↗
PubMed2006

Conservation patterns in different functional sequence categories of divergent Drosophila species.

We have explored the distributions of fully conserved ungapped blocks in genome-wide pair-wise alignments of recently completed species of Drosophila: D. melanogaster, D. yakuba, D. ananassae, D. pseudoobscura, D. virilis, and D. mojavensis. Based on these distributions we have found that nearly every functional sequence category possesses its own distinctive conservation pattern, sometimes independent of the overall sequence conservation level. In the coding and regulatory regions, the ungapped blocks were longer than in introns, UTRs, and nonfunctional sequences. At the same time, the blocks in the coding regions carried a 3N + 2 signature characteristic of synonymous substitutions in the third-codon position. Larger block sizes in transcription regulatory regions can be explained by the presence of conserved arrays of binding sites for transcription factors. We also have shown that the longest ungapped blocks, or "ultraconserved" sequences, are associated with specific gene groups, including those encoding ion channels and components of the cytoskeleton. We discuss how restraining conservation patterns may help in mapping functional sequence categories and improve genome annotation.

Animals↗
PubMed2004

Data mining parasite genomes.

The term 'data mining' can be used to describe any process where useful information is extracted from data with a large background of 'noise'. In the context of a genome project, several stages involve data mining. Amongst the sequence data, 'signals' need to be detected that indicate the presence of interesting features. Often this involves differentiating between transcribed and non-transcribed bases to predict coding regions. After detection, defining the roles of these sequences involves sifting through multiple lines of evidence. If these roles are accurately reflected in genome annotation, they can be used by researchers to frame queries and interrogate the data further.

Animals↗
PubMed2002

Prediction of signal recognition particle RNA genes.

We describe a method for prediction of genes that encode the RNA component of the signal recognition particle (SRP). A heuristic search for the strongly conserved helix 8 motif of SRP RNA is combined with covariance models that are based on previously known SRP RNA sequences. By screening available genomic sequences we have identified a large number of novel SRP RNA genes and we can account for at least one gene in every genome that has been completely sequenced. Novel bacterial RNAs include that of Thermotoga maritima, which, unlike all other non-gram-positive eubacteria, is predicted to have an Alu domain. We have also found the RNAs of Lactococcus lactis and Staphylococcus to have an unusual UGAC tetraloop in helix 8 instead of the normal GNRA sequence. An investigation of yeast RNAs reveals conserved sequence elements of the Alu domain that aid in the analysis of these RNAs. Analysis of the human genome reveals only two likely genes, both on chromosome 14. Our method for SRP RNA gene prediction is the first convenient tool for this task and should be useful in genome annotation.

Alu Elements↗
PubMed2006

DBD: a transcription factor prediction database.

Regulation of gene expression influences almost all biological processes in an organism; sequence-specific DNA-binding transcription factors are critical to this control. For most genomes, the repertoire of transcription factors is only partially known. Hitherto transcription factor identification has been largely based on genome annotation pipelines that use pairwise sequence comparisons, which detect only those factors similar to known genes, or on functional classification schemes that amalgamate many types of proteins into the category of 'transcription factor'. Using a novel transcription factor identification method, the DBD transcription factor database fills this void, providing genome-wide transcription factor predictions for organisms from across the tree of life. The prediction method behind DBD identifies sequence-specific DNA-binding transcription factors through homology using profile hidden Markov models (HMMs) of domains. Thus, it is limited to factors that are homologus to those HMMs. The collection of HMMs is taken from two existing databases (Pfam and SUPERFAMILY), and is limited to models that exclusively detect transcription factors that specifically recognize DNA sequences. It does not include basal transcription factors or chromatin-associated proteins, for instance. Based on comparison with experimentally verified annotation, the prediction procedure is between 95% and 99% accurate. Between one quarter and one-half of our genome-wide predicted transcription factors represent previously uncharacterized proteins. The DBD (www.transcriptionfactor.org) consists of predicted transcription factor repertoires for 150 completely sequenced genomes, their domain assignments and the hand curated list of DNA-binding domain HMMs. Users can browse, search or download the predictions by genome, domain family or sequence identifier, view families of transcription factors based on domain architecture and receive predictions for a protein sequence.

Animals↗
PubMed2026

Pseudomonas gebzensis sp. nov., a Carotenoid-Producing Species Isolated from Solar Panels in Türkiye.

Strain RP23018ST was isolated from the solar panels in Gebze, Türkiye. According to the phylogenetic analysis of 16S rRNA gene sequences, strain RP23018ST was classified as a member of the genus Pseudomonas, being most closely related to Pseudomonas cremoricolorata DSM 17059T (99.3%). Strain RP23018ST was Gram-stain-negative, rod-shaped, aerobic, motile, growing between temperature range of 4–35 °C. The polar lipids of strain RP23018ST consisted of phosphatidylethanolamine, di-phosphatidylglycerol, phosphatidylcholine, one unidentified phospholipid, and three unidentified aminolipids. It was determined that the main respiratory quinone of the RP23018ST strain was ubiquinone-9 (Q-9), which is a typical chemotaxonomic characteristic of the genus Pseudomonas. Major fatty acids were C16:0, summed feature 3 (C16:1 ω6c and/or C16:1 ω7c), summed feature 8 (C18:1 ω6c and/or C18:1 ω7c), and C17:0 cyclo. Strain RP23018ST had a genome size of 4,944,510 bp and a G + C ratio of 63.0%. The average nucleotide identity (ANI) and digital DNA–DNA hybridization (dDDH) values between RP23018ᵀ and related Pseudomonas species were below 86.4% and 26.7%, respectively, clearly falling below the thresholds for species delineation. Strain RP23018ST produced a deep yellow carotenoid pigment with absorption maxima at 455 and 482 nm. Genome annotation revealed key carotenoid biosynthesis genes (crtX, crtY, crtI, crtZ), and the extracted pigment showed antioxidant activity in DPPH and FRAP assays. Polyphasic characterization, including the determination of overall genome relatedness indices, revealed that strain RP23018ST represents a novel species of the genus Pseudomonas, for which the name Pseudomonas gebzensis sp. nov. is proposed. The type strain is RP23018ST (= LMG 33436T = DSM 117295T).

Turkey↗
PubMed2006

LC-MS/MS based proteomic analysis and functional inference of hypothetical proteins in Desulfovibrio vulgaris.

High efficiency capillary liquid chromatography-tandem mass spectrometry (LC-MS/MS) was used to examine the proteins extracted from Desulfovibrio vulgaris cells across six treatment conditions. While our previous study provided a proteomic overview of the cellular metabolism based on proteins with known functions [W. Zhang, M.A. Gritsenko, R.J. Moore, D.E. Culley, L. Nie, K. Petritis, E.F. Strittmatter, D.G. Camp II, R.D. Smith, F.J. Brockman, A proteomic view of the metabolism in Desulfovibrio vulgaris determined by liquid chromatography coupled with tandem mass spectrometry, Proteomics 6 (2006) 4286-4299], this study describes the global detection and functional inference for hypothetical D. vulgaris proteins. Using criteria that a given peptide of a protein is identified from at least two out of three independent LC-MS/MS measurements and that for any protein at least two different peptides are identified among the three measurements, 129 open reading frames (ORFs) originally annotated as hypothetical proteins were found to encode expressed proteins. Functional inference for the conserved hypothetical proteins was performed by a combination of several non-homology based methods: genomic context analysis, phylogenomic profiling, and analysis of a combination of experimental information, including peptide detection in cells grown under specific culture conditions and cellular location of the proteins. Using this approach we were able to assign possible functions to 20 conserved hypothetical proteins. This study demonstrated that a combination of proteomics and bioinformatics methodologies can provide verification of the expression of hypothetical proteins and improve genome annotation.

Amino Acid Sequence↗
PubMed2004

The Pseudomonas aeruginosa PA01 gene collection.

Pseudomonas aeruginosa, a common inhabitant of soil and water, is an opportunistic pathogen of growing clinical relevance. Its genome, one of the largest among bacteria [5570 open reading frames (ORFs)] approaches that of simple eukaryotes. We have constructed a comprehensive gene collection for this organism utilizing the annotated genome of P. aeruginosa PA01 and a highly automated and laboratory information management system (LIMS)-supported production line. All the individual ORFs have been successfully PCR-amplified and cloned into a recombination-based cloning system. We have isolated and archived four independent isolates of each individual ORF. Full sequence analysis of the first isolate for one-third of the ORFs in the collection has been completed. We used two sets of genes from this repository for high-throughput expression and purification of recombinant proteins in different systems. The purified proteins have been used to set up biochemical and immunological assays directed towards characterization of histidine kinases and identification of bacterial proteins involved in the immune response of cystic fibrosis patients. This gene repository provides a powerful tool for proteome- and genome-scale research of this organism, and the strategies adopted to generate this repository serve as a model for building clone sets for other bacteria.

Bacterial Proteins↗
PubMed2006

EPD in its twentieth year: towards complete promoter coverage of selected model organisms.

The Eukaryotic Promoter Database (EPD) is an annotated non-redundant collection of eukaryotic POL II promoters, experimentally defined by a transcription start site (TSS). Access to promoter sequences is provided by pointers to positions in the corresponding genomes. Promoter evidence comes from conventional TSS mapping experiments for individual genes, or, starting from release 73, from mass genome annotation projects. Subsets of promoter sequences with customized 5' and 3' extensions can be downloaded from the EPD website. The focus of current development efforts is to reach complete promoter coverage for important model organisms as soon as possible. To speed up this process, a new class of preliminary promoter entries has been introduced as of release 83, which requires less stringent admission criteria. As part of a continuous integration process, new web-based interfaces have been developed, which allow joint analysis of promoter sequences with other bioinformatics resources developed by our group, in particular programs offered by the Signal Search Analysis Server, and gene expression data stored in the CleanEx database. EPD can be accessed at http://www.epd.isb-sib.ch.

Animals↗
PubMed2000

Gene structure prediction by spliced alignment of genomic DNA with protein sequences: increased accuracy by differential splice site scoring.

Gene identification in genomic DNA from eukaryotes is complicated by the vast combinatorial possibilities of potential exon assemblies. If the gene encodes a protein that is closely related to known proteins, gene identification is aided by matching similarity of potential translation products to those target proteins. The genomic DNA and protein sequences can be aligned directly by scoring the implied residues of in-frame nucleotide triplets against the protein residues in conventional ways, while allowing for long gaps in the alignment corresponding to introns in the genomic DNA. We describe a novel method for such spliced alignment. The method derives an optimal alignment based on scoring for both sequence similarity of the predicted gene product to the protein sequence and intrinsic splice site strength of the predicted introns. Application of the method to a representative set of 50 known genes from Arabidopsis thaliana showed significant improvement in prediction accuracy compared to previous spliced alignment methods. The method is also more accurate than ab initio gene prediction methods, provided sufficiently close target proteins are available. In view of the fast growth of public sequence repositories, we argue that close targets will be available for the majority of novel genes, making spliced alignment an excellent practical tool for high-throughput automated genome annotation.

Algorithms↗