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PubMed2006

Identification of mouse mslp2 gene from EST databases by repeated searching, comparison, and assembling.

The NPHS2 gene is expressed in podocytes and encodes the integral membrane protein called podocin, which is believed to play an important role in the renal function of glomerular filtration. Mutations in this gene can cause serious renal function disorders. In this study, we used data-mining techniques and bioinformatic tools to search for the mouse ortholog of the NPHS2-related gene. It might be valuable for future studies of renal diseases. We employed repeated cycles of searching, comparison, and assembling to extend the assembled EST sequences. The discovered gene sequence mslp2, an ortholog of the human SLP2 gene, was found to have a total length of 1253 bp with the amino acid coding region located in 32-1093 nt. It was further verified using the RT-PCR and RACE techniques to ensure its biological accuracy and then registered with the GenBank. When ClustalW was used for comparing the mslp2 and human SLP2 genes for similarities, the similarities were as high as 88% for nucleotide and 92% for amino acid sequences. In conclusion, we propose a method for rapid identification of the mouse ortholog gene from the human genome.

Animals↗
PubMed2006

Automatic pathway building in biological association networks.

BACKGROUND: Scientific literature is a source of the most reliable and comprehensive knowledge about molecular interaction networks. Formalization of this knowledge is necessary for computational analysis and is achieved by automatic fact extraction using various text-mining algorithms. Most of these techniques suffer from high false positive rates and redundancy of the extracted information. The extracted facts form a large network with no pathways defined. RESULTS: We describe the methodology for automatic curation of Biological Association Networks (BANs) derived by a natural language processing technology called Medscan. The curated data is used for automatic pathway reconstruction. The algorithm for the reconstruction of signaling pathways is also described and validated by comparison with manually curated pathways and tissue-specific gene expression profiles. CONCLUSION: Biological Association Networks extracted by MedScan technology contain sufficient information for constructing thousands of mammalian signaling pathways for multiple tissues. The automatically curated MedScan data is adequate for automatic generation of good quality signaling networks. The automatically generated Regulome pathways and manually curated pathways used for their validation are available free in the ResNetCore database from Ariadne Genomics, Inc. 1. The pathways can be viewed and analyzed through the use of a free demo version of PathwayStudio software. The Medscan technology is also available for evaluation using the free demo version of PathwayStudio software.

Databases, Bibliographic↗
PubMed2006

Automated recognition of malignancy mentions in biomedical literature.

BACKGROUND: The rapid proliferation of biomedical text makes it increasingly difficult for researchers to identify, synthesize, and utilize developed knowledge in their fields of interest. Automated information extraction procedures can assist in the acquisition and management of this knowledge. Previous efforts in biomedical text mining have focused primarily upon named entity recognition of well-defined molecular objects such as genes, but less work has been performed to identify disease-related objects and concepts. Furthermore, promise has been tempered by an inability to efficiently scale approaches in ways that minimize manual efforts and still perform with high accuracy. Here, we have applied a machine-learning approach previously successful for identifying molecular entities to a disease concept to determine if the underlying probabilistic model effectively generalizes to unrelated concepts with minimal manual intervention for model retraining. RESULTS: We developed a named entity recognizer (MTag), an entity tagger for recognizing clinical descriptions of malignancy presented in text. The application uses the machine-learning technique Conditional Random Fields with additional domain-specific features. MTag was tested with 1,010 training and 432 evaluation documents pertaining to cancer genomics. Overall, our experiments resulted in 0.85 precision, 0.83 recall, and 0.84 F-measure on the evaluation set. Compared with a baseline system using string matching of text with a neoplasm term list, MTag performed with a much higher recall rate (92.1% vs. 42.1% recall) and demonstrated the ability to learn new patterns. Application of MTag to all MEDLINE abstracts yielded the identification of 580,002 unique and 9,153,340 overall mentions of malignancy. Significantly, addition of an extensive lexicon of malignancy mentions as a feature set for extraction had minimal impact in performance. CONCLUSION: Together, these results suggest that the identification of disparate biomedical entity classes in free text may be achievable with high accuracy and only moderate additional effort for each new application domain.

Algorithms↗
PubMed2000

Production of C20 polyunsaturated fatty acids (PUFAs) by pathway engineering: identification of a PUFA elongase component from Caenorhabditis elegans.

Using a combination of database-mining and functional characterization, we have identified a component of the polyunsaturated fatty acid (PUFA) elongase. Co-expression of this elongating activity with fatty acid desaturases has allowed us to heterologously reconstitute the PUFA biosynthetic pathway. Both these enzymes (desaturases and elongase components) have undergone gene-duplication events which provide a paradigm for the diverged nature of PUFA biosynthetic activities.

Acetyltransferases↗
PubMed2005

The search for candidate genes of alcoholism: evidence from expression profiling studies.

Alcoholism is the outcome of complex interactions between the environment and multiple gene loci, which may encode pre-existing susceptibility, or contribute to the neuroadaptations underlying the process of developing dependence. Because of this, the prospect of simultaneous, genome wide, high-throughput analysis of gene expression allowed by microarray technology has met with great expectations. The hope has been that new insights into pathogenesis of substance disorders will rapidly be gained, leading to identification of novel treatment targets. The usefulness of this approach as a discovery tool in addiction research will be critically reviewed here. In this article, we describe the evolution of our experimental approaches, from first generation Affymetrix expression arrays to present high-density arrays, and from the use of original Affymetrix software to more advanced analysis of the probe signal, and different statistical approaches to creating candidate gene lists. Further, we address some methodological issues critical to the study of brain samples by microarray technology. We also summarize findings from several expression profiling experiments involving different animal models of alcoholism. The accumulation of expression data from different animal models allows mining the database for patterns of overlap. Such second level analysis depends on the generation of uniform and reliable datasets.

Alcoholism↗
PubMed2000

A new set of Arabidopsis expressed sequence tags from developing seeds. The metabolic pathway from carbohydrates to seed oil.

Large-scale single-pass sequencing of cDNAs from different plants has provided an extensive reservoir for the cloning of genes, the evaluation of tissue-specific gene expression, markers for map-based cloning, and the annotation of genomic sequences. Although as of January 2000 GenBank contained over 220,000 entries of expressed sequence tags (ESTs) from plants, most publicly available plant ESTs are derived from vegetative tissues and relatively few ESTs are specifically derived from developing seeds. However, important morphogenetic processes are exclusively associated with seed and embryo development and the metabolism of seeds is tailored toward the accumulation of economically valuable storage compounds such as oil. Here we describe a new set of ESTs from Arabidopsis, which has been derived from 5- to 13-d-old immature seeds. Close to 28,000 cDNAs have been screened by DNA/DNA hybridization and approximately 10,500 new Arabidopsis ESTs have been generated and analyzed using different bioinformatics tools. Approximately 40% of the ESTs currently have no match in dbEST, suggesting many represent mRNAs derived from genes that are specifically expressed in seeds. Although these data can be mined with many different biological questions in mind, this study emphasizes the import of photosynthate into developing embryos, its conversion into seed oil, and the regulation of this pathway.

Arabidopsis↗
PubMed2002

Mining Bacillus subtilis chromosome heterogeneities using hidden Markov models.

We present here the use of a new statistical segmentation method on the Bacillus subtilis chromosome sequence. Maximum likelihood parameter estimation of a hidden Markov model, based on the expectation-maximization algorithm, enables one to segment the DNA sequence according to its local composition. This approach is not based on sliding windows; it enables different compositional classes to be separated without prior knowledge of their content, size and localization. We compared these compositional classes, obtained from the sequence, with the annotated DNA physical map, sequence homologies and repeat regions. The first heterogeneity revealed discriminates between the two coding strands and the non-coding regions. Other main heterogeneities arise; some are related to horizontal gene transfer, some to t-enriched composition of hydrophobic protein coding strands, and others to the codon usage fitness of highly expressed genes. Concerning potential and established gene transfers, we found 9 of the 10 known prophages, plus 14 new regions of atypical composition. Some of them are surrounded by repeats, most of their genes have unknown function or possess homology to genes involved in secondary catabolism, metal and antibiotic resistance. Surprisingly, we notice that all of these detected regions are a + t-richer than the host genome, raising the question of their remote sources.

Bacillus subtilis↗
PubMed2003

A path from primary protein sequence to ligand recognition.

A novel method to organize protein structural information based solely on sequence is presented. The method clusters proteins into families that correlate with the three-dimensional protein structure and the conformation of the bound ligands. This procedure was applied to nicotinamide adenine dinucleotide [NAD(P)]-utilizing enzymes to identify a total of 94 sequence families, 53 of which are structurally characterized. Each of the structurally characterized proteins within a sequence family correlates to a single protein fold and to a common bound conformation of NAD(P). A wide range of structural folds is identified that recognize NAD(P), including Rossmann folds and beta/alpha barrels. The defined sequence families can be used to identify the type and prevalence of NAD(P)-utilizing enzymes in the proteomes of sequenced organisms. The proteome of Mycobacterium tuberculosis was mined to generate a proteome-wide profile of NAD(P)-utilizing enzymes coded by this organism. This enzyme family comprises approximately 6% of the open reading frames, with the largest subgroup being the Rossmann fold, short-chain dehydrogenases. The preponderance of short-chain dehydrogenases correlates strongly with the phenotype of M. tuberculosis, which is characterized as having one of the most complex prokaryotic cell walls.

Amino Acid Sequence↗
PubMed2004

Biomedical informatics: development of a comprehensive data warehouse for clinical and genomic breast cancer research.

The Windber Research Institute is an integrated high-throughput research center employing clinical, genomic and proteomic platforms to produce terabyte levels of data. We use biomedical informatics technologies to integrate all of these operations. This report includes information on a multi-year, multi-phase hybrid data warehouse project currently under development in the Institute. The purpose of the warehouse is to host the terabyte-level of internal experimentally generated data as well as data from public sources. We have previously reported on the phase I development, which integrated limited internal data sources and selected public databases. Currently, we are completing phase II development, which integrates our internal automated data sources and develops visualization tools to query across these data types. This paper summarizes our clinical and experimental operations, the data warehouse development, and the challenges we have faced. In phase III we plan to federate additional manual internal and public data sources and then to develop and adapt more data analysis and mining tools. We expect that the final implementation of the data warehouse will greatly facilitate biomedical informatics research.

Breast Neoplasms↗
PubMed2001

Three aberrant splicing variants of the HMGIC gene transcribed in uterine leiomyomas.

Cytogenetic aberrations involving chromosome region 12q13-15 occur frequently among benign mesenchymal tumors in humans, e.g., pleomorphic adenomas of the parotid gland, pulmonary chondroid hamartomas, lipomas, or uterine leiomyomas. HMGIC, a gene encoding a protein of the high-mobility group, has been identified as a target of those events. Using the 3' rapid amplification of cDNA ends (RACE) technique, we identified six different fusion transcripts of the HMGIC gene among 13 uterine leiomyomas; three of these variants had not been described before. Radiation-hybrid mapping located all three of the novel fusion transcripts in the same chromosomal region as the HMGIC gene. Cloning of the entire HMGIC gene in a genomic contig of P1-derived artificial chromosomes and cosmids revealed that the 3' portion of each novel fusion transcript contained cryptic exonic sequences (designated a, b, and c) present in intron 3 of the HMGIC gene. Thus, aberrant alternative splicing was responsible for abnormal HMGIC isoforms in those myomas. Identification of these novel variants suggested that aberrant splicing can join chromosomal translocation and inversion as a mechanism for producing abnormal HMGIC transcripts, and that separation of the DNA binding domains of HMGIC from its acidic carboxyl-terminal regulatory domain can lead to development of benign mesenchymal tumors.

Alternative Splicing↗
PubMed2005

A compendium of signals and responses triggered by prodeath and prosurvival cytokines.

Cell-signaling networks consist of proteins with a variety of functions (receptors, adaptor proteins, GTPases, kinases, proteases, and transcription factors) working together to control cell fate. Although much is known about the identities and biochemical activities of these signaling proteins, the ways in which they are combined into networks to process and transduce signals are poorly understood. Network-level understanding of signaling requires data on a wide variety of biochemical processes such as posttranslational modification, assembly of macromolecular complexes, enzymatic activity, and localization. No single method can gather such heterogeneous data in high throughput, and most studies of signal transduction therefore rely on series of small, discrete experiments. Inspired by the power of systematic datasets in genomics, we set out to build a systematic signaling dataset that would enable the construction of predictive models of cell-signaling networks. Here we describe the compilation and fusion of approximately 10,000 signal and response measurements acquired from HT-29 cells treated with tumor necrosis factor-alpha, a proapoptotic cytokine, in combination with epidermal growth factor or insulin, two prosurvival growth factors. Nineteen protein signals were measured over a 24-h period using kinase activity assays, quantitative immunoblotting, and antibody microarrays. Four different measurements of apoptotic response were also collected by flow cytometry for each time course. Partial least squares regression models that relate signaling data to apoptotic response data reveal which aspects of compendium construction and analysis were important for the reproducibility, internal consistency, and accuracy of the fused set of signaling measurements. We conclude that it is possible to build self-consistent compendia of cell-signaling data that can be mined computationally to yield important insights into the control of mammalian cell responses.

Amino Acid Sequence↗
PubMed2006

BioWarehouse: a bioinformatics database warehouse toolkit.

BACKGROUND: This article addresses the problem of interoperation of heterogeneous bioinformatics databases. RESULTS: We introduce BioWarehouse, an open source toolkit for constructing bioinformatics database warehouses using the MySQL and Oracle relational database managers. BioWarehouse integrates its component databases into a common representational framework within a single database management system, thus enabling multi-database queries using the Structured Query Language (SQL) but also facilitating a variety of database integration tasks such as comparative analysis and data mining. BioWarehouse currently supports the integration of a pathway-centric set of databases including ENZYME, KEGG, and BioCyc, and in addition the UniProt, GenBank, NCBI Taxonomy, and CMR databases, and the Gene Ontology. Loader tools, written in the C and JAVA languages, parse and load these databases into a relational database schema. The loaders also apply a degree of semantic normalization to their respective source data, decreasing semantic heterogeneity. The schema supports the following bioinformatics datatypes: chemical compounds, biochemical reactions, metabolic pathways, proteins, genes, nucleic acid sequences, features on protein and nucleic-acid sequences, organisms, organism taxonomies, and controlled vocabularies. As an application example, we applied BioWarehouse to determine the fraction of biochemically characterized enzyme activities for which no sequences exist in the public sequence databases. The answer is that no sequence exists for 36% of enzyme activities for which EC numbers have been assigned. These gaps in sequence data significantly limit the accuracy of genome annotation and metabolic pathway prediction, and are a barrier for metabolic engineering. Complex queries of this type provide examples of the value of the data warehousing approach to bioinformatics research. CONCLUSION: BioWarehouse embodies significant progress on the database integration problem for bioinformatics.

Computational Biology↗
PubMed2026

Systematic functional evaluation of CNGA1 missense variants associated with retinitis pigmentosa.

BACKGROUND: Missense variants are frequently classified as variants of uncertain significance (VUS) according to the guidelines of the American College of Medical Genetics and Genomics and the Association of Molecular Pathology (ACMG/AMP). Consequently, disease relevance remains elusive, impeding molecular genetic diagnostics, patients` and family genetic counseling, and identification of patients eligible for clinical trials. Functional studies are critical for resolving the clinical significance of VUS. CNGA1 encodes the main subunit of the rod cyclic nucleotide-gated (CNG) channel, a vital component of the phototransduction cascade. Variants in CNGA1 are a rare cause of autosomal recessive retinitis pigmentosa and a phase I/II gene augmentation trial (NCT06291935) is currently ongoing highlighting the necessity to differentiate benign from pathogenic variants. METHODS: CNGA1 missense variants compiled from retinal disease patient cohorts, public databases and literature were functionally investigated using a medium-throughput aequorin-based assay and in vitro minigene splice assays for predicted exonic spliceogenic variants. Functional data were correlated with the in silico prediction of five variant effect predictors (VEPs) and applied to support or revise variants' ACMG/AMP classification. RESULTS: Data mining revealed 86 missense CNGA1 variants - including three novel - most of them lacking functional data; 65.1% of the variants were initially classified as VUS. The aequorin-based assay showed that 72.1% of tested variants significantly impaired CNG channel function and were classified as functionally abnormal, while 23.3% were functionally normal and 5% remained functionally uncertain. Correlation of the functional data with in silico predictions identified AlphaMissense and CPT-1 to be the most suitable tools for assessing CNGA1 missense variants. Using in vitro minigene splice assays, two putative missense variants were shown to induce missplicing. Based on the functional findings, 62.1% of the variants initially classified as VUS were re-categorized as likely pathogenic or likely benign. Furthermore, 93.3% of the variants initially classified as likely pathogenic showed an effect on CNGA1 channel function, confirming their disease relevance and supporting their reclassification as pathogenic. CONCLUSION: This study represents the first comprehensive functional assessment of disease-associated CNGA1 missense variants, thus significantly advancing the understanding of their disease relevance and improving molecular genetic diagnostics in patients.

Humans↗
PubMed2006

Data mining of VDJ genes reveals interesting clues.

Hypervariability of the complementary determining regions in characteristic structure of Immunoglobulins and the distinct, cell-specific expressions of the genes coding for this important class of proteins pose intriguing problems in experimental and computational/informatics research requiring a special approach different from those for the other proteins. We present here an Average Linkage Hierarchical Clustering of the Homosapien VDJ genes and the Immunoglobulin polypeptides generated by them using special kind of data structures and correlation matrices in place of the microarray data. The results reveal interesting clues on the heterogeneity of exon - intron locations in these gene-families and its possible role in hypervariability of the Immunoglobulins.

Chromosome Mapping↗
PubMed2000

Acidisphaera rubrifaciens gen. nov., sp. nov., an aerobic bacteriochlorophyll-containing bacterium isolated from acidic environments.

Four strains of aerobic, mesophilic, acidophilic bacteria that produced bacteriochlorophyll (BChl) a were isolated from acidic hot springs and mine drainage. The characteristics of the four isolates were almost identical. The isolates were strictly aerobic and chemo-organotrophic. They were gram-negative, non-motile cocci and coccobacilli, formed salmon-pink colonies on solidified media and produced BChl a and carotenoids only under aerobic growth conditions. The cells also produced small amounts of zinc-substituted BChl a when grown in the presence of 1 mM zinc sulfate. Anaerobic growth in the light was not found, but aerobic growth was stimulated by continuous incandescent illumination. The isolates grew in a pH range of 3.5-6.0, with pH optima of 4.5-5.0. A phylogenetic analysis based on 16S rDNA sequences showed that the isolates clustered in the major acidophilic group of the class Proteobacteria, which includes species of the genera Acidiphilium and Rhodopila. The anaerobic phototrophic bacterium Rhodopila globiformis was the closest relative to the new isolates (95% level of sequence similarity). The G+C content of the genomic DNA of the isolates was 69.1-69.8 mol%. On the basis of these results, it was concluded that the four isolates should be classified into a new genus and a new species, for which the name Acidisphaera rubrifaciens is proposed. The type strain is strain HS-AP3T (= JCM 10600T).

Acids↗
PubMed2006

A comprehensive mouse IBD database for the efficient localization of quantitative trait loci.

Traditional fine-mapping approaches in mouse genetics that go from a linkage region to a candidate gene are very costly and time consuming. Shared ancestry regions, along with the combination of genetics and genomics approaches, provide a powerful tool to shorten the time and effort required to identify a causative gene. In this article we present a novel methodology that predicts IBD (identical by descent) regions between pairs of inbred strains using single nucleotide polymorphism (SNP) maps. We have validated this approach by comparing the IBD regions, estimated using different algorithms, to the results derived using the sequence information in the strains present in the Celera Mouse Database. We showed that based on the current publicly available SNP genotypes, large IBD regions (>1 Mb) can be identified successfully. By assembling a list of 21,514 SNPs in 61 common inbred strains, we inferred IBD regions between all pairs of strains and confirmed, for the first time, that existing quantitative trait genes (QTG) and susceptibility genes all lie outside of IBD regions. We also illustrated how knowledge of IBD structures can be applied to strain selection for future crosses. We have made our results available for data mining and download through a public website ( http://www.mouseibd.florida.scripps.edu ).

Algorithms↗
PubMed2005

Adaptation of Saccharomyces cerevisiae to high hydrostatic pressure causing growth inhibition.

Genome-wide mRNA expression profiles of Saccharomyces cerevisiae growing under hydrostatic pressure were characterized. We selected a hydrostatic pressure of 30 MPa at 25 degrees C because yeast cells were able to grow under these conditions, while cell size and complexity were increased after decompression. Functional characterization of pressure-induced genes suggests that genes involved in protein metabolism and membrane metabolism were induced. The response to 30 MPa was significantly different from that observed under lethal conditions because protein degradation was not activated under 30 MPa pressure. Strongly induced genes those that contribute to membrane metabolism and which are also induced by detergents, oils, and membrane stabilizers.

Adaptation, Physiological↗
PubMed2005

Resolving tylenchid evolutionary relationships through multiple gene analysis derived from EST data.

Sequence-based phylogenetic analyses typically are based on a small number of character sets and report gene trees which may not reflect the true species tree. We employed an EST mining strategy to suppress such incongruencies, and recovered the most robust phylogeny for five species of plant-parasitic nematode (Meloidogyne arenaria, M. chitwoodi, M. hapla, M. incognita, and M. javanica), three closely related tylenchid taxa (Heterodera glycines, Globodera pallida, and G. rostochiensis) and a distant taxon, Caenorhabditis elegans. Our multiple-gene approach is based on sampling more than 80,000 publicly available tylenchid EST sequences to identify phylum-wide orthologues. Bayesian inference, minimum evolution, maximum likelihood and protein distance methods were employed for phylogenetic reconstruction and hypothesis tests were constructed to elucidate differential selective pressures across the phylogeny for each gene. Our results place M. incognita and M. javanica as sister taxa, with M. arenaria as the next closely related nematode. Significant differences in selective pressure were revealed for some genes under some hypotheses, though all but one gene are exclusively under purifying selection, indicating conservation across the orthologous groups. This EST-based multi-gene analysis is a first step towards accomplishing genome-wide coverage for tylenchid evolutionary analyses.

Animals↗