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PubMed2006

PhosphoregDB: the tissue and sub-cellular distribution of mammalian protein kinases and phosphatases.

BACKGROUND: Protein kinases and protein phosphatases are the fundamental components of phosphorylation dependent protein regulatory systems. We have created a database for the protein kinase-like and phosphatase-like loci of mouse http://phosphoreg.imb.uq.edu.au that integrates protein sequence, interaction, classification and pathway information with the results of a systematic screen of their sub-cellular localization and tissue specific expression data mined from the GNF tissue atlas of mouse. RESULTS: The database lets users query where a specific kinase or phosphatase is expressed at both the tissue and sub-cellular levels. Similarly the interface allows the user to query by tissue, pathway or sub-cellular localization, to reveal which components are co-expressed or co-localized. A review of their expression reveals 30% of these components are detected in all tissues tested while 70% show some level of tissue restriction. Hierarchical clustering of the expression data reveals that expression of these genes can be used to separate the samples into tissues of related lineage, including 3 larger clusters of nervous tissue, developing embryo and cells of the immune system. By overlaying the expression, sub-cellular localization and classification data we examine correlations between class, specificity and tissue restriction and show that tyrosine kinases are more generally expressed in fewer tissues than serine/threonine kinases. CONCLUSION: Together these data demonstrate that cell type specific systems exist to regulate protein phosphorylation and that for accurate modelling and for determination of enzyme substrate relationships the co-location of components needs to be considered.

Amino Acid Sequence↗
PubMed2005

Characterization and mapping of NBS-LRR resistance gene analogs in apricot (Prunus armeniaca L.).

Genomic DNA sequences sharing homology with the NBS-LRR (nucleotide binding site-leucine-rich repeat) resistance genes were isolated and cloned from apricot (Prunus armeniaca L.) using a PCR approach with degenerate primers designed from conserved regions of the NBS domain. Restriction digestion and sequence analyses of the amplified fragments led to the identification of 43 unique amino acid sequences grouped into six families of resistance gene analogs (RGAs). All of the RGAs identified belong to the Toll-Interleukin receptor (TIR) group of the plant disease resistance genes (R-genes). RGA-specific primers based on non-conserved regions of the NBS domain were developed from the consensus sequences of each RGA family. These primers were used to develop amplified fragment length polymorphism (AFLP)-RGA markers by means of an AFLP-modified procedure where one standard primer is substituted by an RGA-specific primer. Using this method, 27 polymorphic markers, six of which shared homology with the TIR class of the NBS-LRR R-genes, were obtained from 17 different primer combinations. Of these 27 markers, 16 mapped in an apricot genetic map previously constructed from the self-pollination of the cultivar Lito. The development of AFLP-RGA markers may prove to be useful for marker-assisted selection and map-based cloning of R-genes in apricot.

Amino Acid Sequence↗
PubMed2005

A variational Bayesian mixture modelling framework for cluster analysis of gene-expression data.

MOTIVATION: Accurate subcategorization of tumour types through gene-expression profiling requires analytical techniques that estimate the number of categories or clusters rigorously and reliably. Parametric mixture modelling provides a natural setting to address this problem. RESULTS: We compare a criterion for model selection that is derived from a variational Bayesian framework with a popular alternative based on the Bayesian information criterion. Using simulated data, we show that the variational Bayesian method is more accurate in finding the true number of clusters in situations that are relevant to current and future microarray studies. We also compare the two criteria using freely available tumour microarray datasets and show that the variational Bayesian method is more sensitive to capturing biologically relevant structure.

Algorithms↗
PubMed2002

Analysis of common k-mers for whole genome sequences using SSB-tree.

As sequenced genomes become larger and sequencing process becomes faster, there is a need to develop a tool to analyze sequences in the whole genomic scale. However, on-memory algorithms such as suffix tree and suffix array are not applicable to the analysis of whole genome sequence set, since the size of individual whole genome ranges from several million base pairs to hundreds billion base pairs. In order to effectively manipulate the huge sequence data, it is necessary to use the indexed data structure for external memory. In this paper, we introduce a workbench called SequeX for the analysis and visualization of whole genome sequences using SSB-tree (Static SB-tree). It consists of two parts: the analysis query subsystem and the visualization subsystem. The query subsystem supports various transactions such as pattern matching, k-occurrence, and k-mer analysis. The visualization subsystem helps biologists to easily understand whole genome structure and feature by sequence viewer, annotation viewer, CGR (Chaos Game Representation) viewer, and k-mer viewer. The system also supports a user-friendly programming interface based on Java script for batch processing and the extension for a specific purpose of a user. SequeX can be used to identify conserved genes or sequences by the analysis of the common k-mers and annotation. We analyze the common k-mer for 72 microbial genomes announced by Entrez, and find an interesting biological fact that the longest common k-mer for 72 sequences is 11-mer, and only 11 such sequences exist. Finally we note that many common k-mers occur in conserved region such as CDS, rRNA, and tRNA.

Archaea↗
PubMed1992

Genome canalization: the coevolution of transposable and interspersed repetitive elements with single copy DNA.

Transposable and interspersed repetitive elements (TIREs) are ubiquitous features of both prokaryotic and eukaryotic genomes. However, controversy has arisen as to whether these sequences represent useless 'selfish' DNA elements, with no cellular function, as opposed to useful genetic units. In this review, we selected two insect species, the Dipteran Drosophila and the Lepidopteran Bombyx mori (the silkmoth), in an attempt to resolve this debate. These two species were selected on the basis of the special interest that our laboratory has had over the years in Bombyx with its well known molecular and developmental biology, and the wealth of genetic data that exist for Drosophila. In addition, these two species represent contrasting repetitive element types and patterns of distribution. On one hand, Bombyx exhibits the short interspersion pattern in which Alu-like TIREs predominate while Drosophila possesses the long interspersion pattern in which retroviral-like TIREs are prevalent. In Bombyx, the main TIRE family is Bm-1 while the Drosophila group contains predominantly copia-like elements, non-LTR retroposons, bacterial-type retroposons and fold-back transposable elements sequences. Our analysis of the information revealed highly non-random patterns of both TIRE biology and evolution, more indicative of these sequences acting as genomic symbionts under cellular regulation rather than useless or selfish junk DNA. In addition, we extended our analysis of potential TIRE functionality to what is known from other eukaryotic systems. From this study, it became apparent that these DNA elements may have originated as innocuous or selfish sequences and then adopted functions. The mechanism for this conversion from non-functionality to specific roles is a process of coevolution between the repetitive element and other cellular DNA often times in close physical proximity. The resulting interdependence between repetitive elements and other cellular sequences restrict the number of evolutionarily successful mutational changes for a given function or cistron. This mutual limitation is what we call genome canalization. Well documented examples are discussed to support this hypothesis and a mechanistic model is presented for how such genomic canalization can occur. Also proposed are empirical studies which would support or invalidate aspects of this hypothesis.

Animals↗
PubMed2006

Systems analysis of circadian time-dependent neuronal epidermal growth factor receptor signaling.

BACKGROUND: Identifying the gene regulatory networks governing physiological signal integration remains an important challenge in circadian biology. Epidermal growth factor receptor (EGFR) has been implicated in circadian function and is expressed in the suprachiasmatic nuclei (SCN), the core circadian pacemaker. The transcription networks downstream of EGFR in the SCN are unknown but, by analogy to other SCN inputs, we expect the response to EGFR activation to depend on circadian timing. RESULTS: We have undertaken a systems-level analysis of EGFR circadian time-dependent signaling in the SCN. We collected gene-expression profiles to study how the SCN response to EGFR activation depends on circadian timing. Mixed-model analysis of variance (ANOVA) was employed to identify genes with circadian time-dependent EGFR regulation. The expression data were integrated with transcription-factor binding predictions through gene group enrichment analyses to generate robust hypotheses about transcription-factors responsible for the circadian phase-dependent EGFR responses. CONCLUSION: The analysis results suggest that the transcriptional response to EGFR signaling in the SCN may be partly mediated by established transcription-factors regulated via EGFR transcription-factors (AP1, Ets1, C/EBP), transcription-factors involved in circadian clock entrainment (CREB), and by core clock transcription-factors (Ror alpha). Quantitative real-time PCR measurements of several transcription-factor expression levels support a model in which circadian time-dependent EGFR responses are partly achieved by circadian regulation of upstream signaling components. Our study suggests an important role for EGFR signaling in SCN function and provides an example for gaining physiological insights through systems-level analysis.

Animals↗
PubMed2002

Two separate domains in the golli myelin basic proteins are responsible for nuclear targeting and process extension in transfected cells.

The golli products of the myelin basic protein (MBP) gene are expressed in neurons and oligodendrocytes (OLs). In certain neuronal populations, golli proteins undergo translocation between the nucleus and cytoplasm/processes during development. The proteins consist of two domains, a golli domain of 133 amino acids and an MBP domain of variable length. One objective of this study was to identify the sequences responsible for nuclear targeting. Site-directed mutagenesis and deletion analyses were used to generate a series of golli-green fluorescent protein (GFP) DNA constructs that were transfected into OL and neuronal cell lines to follow localization by confocal microscopy. The results indicated that a 36-residue stretch in the MBP domain is essential for nuclear targeting, and the sequence appears to be a nontraditional localization signal motif. The studies also revealed that overexpression of golli proteins could induce dramatic changes in cell morphology. In OL lines, overexpression of intact golli proteins, or golli peptide alone, caused an increase in the length and number of processes, and the elaboration of membrane sheets. In the neuronal lines, there was a dramatic increase in number and length of extensions. The results, consistent with the timing of golli expression in cells during neural development, suggest that golli proteins may be involved in process formation/extension in OLs and neurons during development. These studies have defined two functional domains in the golli protein. Sequences in the MBP domain target the protein into the nucleus and sequences within the golli domain induce process sheet extension in OLs and neurons.

Amino Acid Sequence↗
PubMed2006

An application of statistics to comparative metagenomics.

BACKGROUND: Metagenomics, sequence analyses of genomic DNA isolated directly from the environments, can be used to identify organisms and model community dynamics of a particular ecosystem. Metagenomics also has the potential to identify significantly different metabolic potential in different environments. RESULTS: Here we use a statistical method to compare curated subsystems, to predict the physiology, metabolism, and ecology from metagenomes. This approach can be used to identify those subsystems that are significantly different between metagenome sequences. Subsystems that were overrepresented in the Sargasso Sea and Acid Mine Drainage metagenome when compared to non-redundant databases were identified. CONCLUSION: The methodology described herein applies statistics to the comparisons of metabolic potential in metagenomes. This analysis reveals those subsystems that are more, or less, represented in the different environments that are compared. These differences in metabolic potential lead to several testable hypotheses about physiology and metabolism of microbes from these ecosystems.

Algorithms↗
PubMed2025

Emerging protein sequencing technologies: proteomics without mass spectrometry?

INTRODUCTION: Liquid chromatography-tandem mass spectrometry (LC-MS/MS) has been a leading method for proteomics for 30 years. Advantages provided by LC-MS/MS are offset by significant disadvantages, including cost. Recently, several non-mass spectrometric methods have emerged, but little information is available about their capacity to analyze the complex mixtures routine for mass spectrometry. AREAS COVERED: We review recent non-mass-spectrometric methods for sequencing proteins and peptides, including those using nanopores, sequencing by degradation, reverse translation, and short-epitope mapping, with comments on bioinformatics challenges, fundamental limitations, and areas where new technologies will be more or less competitive with LC-MS/MS. In addition to conventional literature searches, instrument vendor websites, patents, webinars, and preprints were also consulted to give a more up-to-date picture. EXPERT OPINION: Many new technologies are promising. However, demonstrations that they outperform mass spectrometry in terms of peptides and proteins identified have not yet been published, and astute observers note important disadvantages, especially relating to the dynamic range of single-molecule measurements of complex mixtures. Still, even if the performance of emerging methods proves inferior to LC-MS/MS, their low cost could create a different kind of revolution: a dramatic increase in the number of biology laboratories engaging in new forms of proteomics research.

Proteomics↗
PubMed1997

Complete sequence and genomic analysis of murine gammaherpesvirus 68.

Murine gammaherpesvirus 68 (gammaHV68) infects mice, thus providing a tractable small-animal model for analysis of the acute and chronic pathogenesis of gammaherpesviruses. To facilitate molecular analysis of gammaHV68 pathogenesis, we have sequenced the gammaHV68 genome. The genome contains 118,237 bp of unique sequence flanked by multiple copies of a 1,213-bp terminal repeat. The GC content of the unique portion of the genome is 46%, while the GC content of the terminal repeat is 78%. The unique portion of the genome is estimated to encode at least 80 genes and is largely colinear with the genomes of Kaposi's sarcoma herpesvirus (KSHV; also known as human herpesvirus 8), herpesvirus saimiri (HVS), and Epstein-Barr virus (EBV). We detected 63 open reading frames (ORFs) homologous to HVS and KSHV ORFs and used the HVS/KSHV numbering system to designate these ORFs. gammaHV68 shares with HVS and KSHV ORFs homologous to a complement regulatory protein (ORF 4), a D-type cyclin (ORF 72), and a G-protein-coupled receptor with close homology to the interleukin-8 receptor (ORF 74). One ORF (K3) was identified in gammaHV68 as homologous to both ORFs K3 and K5 of KSHV and contains a domain found in a bovine herpesvirus 4 major immediate-early protein. We also detected 16 methionine-initiated ORFs predicted to encode proteins at least 100 amino acids in length that are unique to gammaHV68 (ORFs M1 to 14). ORF M1 has striking homology to poxvirus serpins, while ORF M11 encodes a potential homolog of Bcl-2-like molecules encoded by other gammaherpesviruses (gene 16 of HVS and KSHV and the BHRF1 gene of EBV). In addition, clustered at the left end of the unique region are eight sequences with significant homology to bacterial tRNAs. The unique region of the genome contains two internal repeats: a 40-bp repeat located between bp 26778 and 28191 in the genome and a 100-bp repeat located between bp 98981 and 101170. Analysis of the gammaHV68, HVS, EBV, and KSHV genomes demonstrated that each of these viruses have large colinear gene blocks interspersed by regions containing virus-specific ORFs. Interestingly, genes associated with EBV cell tropism, latency, and transformation are all contained within these regions encoding virus-specific genes. This finding suggests that pathogenesis-associated genes of gammaherpesviruses, including gammaHV68, may be contained in similarly positioned genome regions. The availability of the gammaHV68 genomic sequence will facilitate analysis of critical issues in gammaherpesvirus biology via integration of molecular and pathogenetic studies in a small-animal model.

Amino Acid Sequence↗
PubMed2006

Bioconductor: an open source framework for bioinformatics and computational biology.

This chapter describes the Bioconductor project and details of its open source facilities for analysis of microarray and other high-throughput biological experiments. Particular attention is paid to concepts of container and workflow design, connections of biological metadata to statistical analysis products, support for statistical quality assessment, and calibration of inference uncertainty measures when tens of thousands of simultaneous statistical tests are performed.

Animals↗
PubMed2026

VisPan: real-time visualisation of multiplex amplicon-based sequencing panels for rapid syndromic surveillance and pathogen detection.

MOTIVATION: Infectious diseases persist as a major global public health challenge. Diverse factors, including climate change, globalization, deforestation, human-animal interactions, lifestyle choices, and various biological factors, can contribute to their emergence and reemergence. Rapid detection and characterization of (re)emerging pathogens are therefore critical for effective outbreak management and for enhancing our understanding of epidemics by monitoring the transmission, spread, evolution, and genomics of pathogens. In this context, next-generation sequencing technologies (NGS), particularly long-read platforms such as Oxford Nanopore Technologies (ONT), have opened new avenues for real-time pathogen monitoring. However, the bioinformatics bottleneck remains a challenge, emphasizing the need for efficient, accessible, and user-friendly analysis tools. RESULTS: Here, we present a tool adapted from the RAMPART software that enables real-time data visualisation of multiplex PCR syndromic panels combined with Oxford Nanopore sequencing. This real-time analysis enables rapid pathogen detection, from raw data acquisition to taxonomic assignment, within minutes. The interface offers dynamic visual tracking of the sequencing run and amplicon coverage, facilitating immediate insights during diagnostic workflows. Validation experiments confirmed the system's reliability, accurately identifying all pathogens present in complex clinical or environmental samples. This tool provides an integrated, user-friendly solution for genomic pathogen surveillance in field or clinical settings.

Software↗
PubMed2004

Cluster-C, an algorithm for the large-scale clustering of protein sequences based on the extraction of maximal cliques.

Although the characterization of proteins cannot solely rely upon sequence similarity, it has been widely proved that all-vs-all massive sequence comparisons may be an effective approach and a good basis for the prediction of biochemical functions or for the delineation of common shared properties. The program Cluster-C presented here enables a stand-alone and efficient construction of protein families within whole proteomes. The algorithm, which is based on the detection of cliques, ensures a high level of connectivity within the clusters. As opposed to the single transitive linkage method, Cluster-C allows a large number of sequences to be classified in such a way that the multidomain proteins do not produce a chain-grouping effect resulting in meaningless clusters. Moreover, some proteins can be present in several different but relevant clusters, which is of help in the determination of their functional domains. In the present analysis we used the Z-value, an evaluation of the significance of the similarity score, as the criterion for connecting sequences (the user can freely define the threshold of the similarity criterion). The clusters built with a rather low threshold (Z= 14) include more than 97% of the sequences and are consistent with known protein families and PROSITE patterns.

Algorithms↗
PubMed2005

Prediction and validation of microRNAs and their targets.

MicroRNAs are short non-coding RNAs that inhibit translation of target genes by binding to their mRNAs, and have been shown to play a central role in gene regulation in health and disease. Sophisticated computer-based prediction approaches of microRNAs and of their targets, and effective biological validation techniques for validating these predictions, now play a central role in discovery of microRNAs and elucidating their functions.

Algorithms↗
PubMed2006

A phylogenomic analysis of the Ascomycota.

An automated procedure was developed to extract orthologous sequences from fungal genomes and incorporate them into phylogenomic analyses in a timely and efficient manner. This approach involves parsing an all versus all BLASTP search of 17 proteomes and creating a similarity matrix from e-values, which is then used to cluster proteins into related groups by means of a Markov Clustering algorithm. After performing this analysis at different stringency levels, 854 single copy protein clusters, which were ubiquitously distributed in all 17 proteomes, were identified. These clusters were culled to include only those clusters where all proteins had best hits to and received hits from a protein within the same cluster. The final data set included gapless alignments for 781 clusters of orthologous sequences that were concatenated into one super alignment containing 195,664 amino acid characters. Neighbor-joining distance and maximum likelihood analyses resulted in identical topologies and all except one node received 100% bootstrap support. The node supporting Stagonospora nodorum's position received 83% support or higher; it was also the only taxon differentially resolved in the maximum parsimony analyses. All analyses resolved the two derived subphyla Pezizomycotina and Saccharomycotina, and Schizosaccharomyces pombe as an early diverging lineage of the Ascomycota. Importantly, these analyses resolved the Leotiomycetes as the sister group to the Sordariomycetes, a region of the Ascomycota phylogeny that has remained problematic in molecular phylogenetic studies of more limited character sampling. Additional phylogenetic analyses which included orthologous sequences from an unannotated ascomycotan genome (e.g., Coccidioides immitis) and subsets of orthologs with different characteristics supported this topology. Phylogenetic analyses of the 595 orthologs which included C. immitis resulted in an identical topology to the previous 781 ortholog analysis and correctly placed C. immitis in the Eurotiomycetes. This demonstrated the correct identification of orthologs and the ability to incorporate unannotated genomic data into a common phylogenetic analysis.

Ascomycota↗
PubMed1999

Induction of the rat Cu/Zn superoxide dismutase gene through the peroxisome proliferator-responsive element by arachidonic acid.

The Cu/Zn superoxide dismutase (SOD1) catalyzes the dismutation of superoxide radicals produced from biological oxidation and environmental stresses. From the sequence analysis of transcription factor binding sites, the peroxisome proliferator-responsive element (PPRE) was located between nt -797 and -786 of the 5'-flanking sequence of the SOD1 gene. A promoter region was fused to a chloramphenicol acetyl-transferase gene, and the resultant construct was transiently transfected into HepG2 cells. The expression of the SOD1 gene was induced by arachidonic acid (AA). Functional analyses of the PPRE site by deletion, mutations, and the heterologous promoter system confirmed the induction of the SOD1 gene by AA through the PPRE site. Gel mobility shift assays showed AA inducible binding of the peroxisome proliferator-activated receptor (PPAR) to the PPRE. The intensity of PPAR binding was also increased by the treatment of retinoic acid (RA) and 9-cis retinoic acid (9-cis RA). These results suggest that the PPRE participates in the induction of the rat SOD1 gene by the peroxisome proliferator.

Animals↗