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PubMed1996

Applications of network BLAST server.

The sequence databases continue to grow at an extraordinary rate. Contributions come from both small laboratories and large-scale projects, such as the Merck EST project. This growth has placed new demands on computational sequence comparison tools such as BLAST. Even now it is no longer practical to evaluate some BLAST reports manually; it is necessary to filter the output by, for example, organism, source, or degree of annotation. The new network BLAST service makes such tools possible. It is also possible to present BLAST output in different formats, such as BLANCE. Perhaps most important of all, it becomes simple to call BLAST from another application, making it one step within an integrated system. This makes the automated preparation of sequence evaluations that include BLAST runs possible. In the near future we expect to see a number of applications that use the network BLAST interface to help molecular biologists search against a database that is growing not only in size but in biological richness.

Algorithms↗
PubMed2003

Multifunctional proteins: examples of gene sharing.

Adding to the difficulty of interpreting the human genome sequence and annotating protein sequence databases is the observation that a single protein can 'moonlight' or perform multiple, apparently unrelated, functions. This review summarizes examples of moonlighting proteins in cellular activities and biochemical pathways important in cancer and other diseases. The proteins include a variety of combinations of functions and mechanisms to switch between functions. Moonlighting proteins can be beneficial to the organism, such as by coordinating cellular activities. However, moonlighting proteins can potentially make more difficult the determination of the molecular mechanisms of disease and the process of rational drug design.

Binding Sites↗
PubMed2003

Sequence analysis of a rainbow trout cDNA library and creation of a gene index.

Expressed sequence tag (EST) projects have produced extremely valuable resources for identifying genes affecting phenotypes of interest. A large-scale EST sequencing project for rainbow trout was initiated to identify and functionally annotate as many unique transcripts as possible. Over 45,000 5' ESTs were obtained by sequencing clones from a single normalized library constructed using mRNA from six tissues. The production of this sequence data and creation of a rainbow trout Gene Index eliminating redundancy and providing annotation for these sequences will facilitate research in this species.

Animals↗
PubMed2002

Peptidomics of the larval Drosophila melanogaster central nervous system.

Neuropeptides regulate most, if not all, biological processes in the animal kingdom, but only seven have been isolated and sequenced from Drosophila melanogaster. In analogy with the proteomics technology, where all proteins expressed in a cell or tissue are analyzed, the peptidomics approach aims at the simultaneous identification of the whole peptidome of a cell or tissue, i.e. all expressed peptides with their posttranslational modifications. Using nanoscale liquid chromatography combined with tandem mass spectrometry and data base mining, we analyzed the peptidome of the larval Drosophila central nervous system at the amino acid sequence level. We were able to provide biochemical evidence for the presence of 28 neuropeptides using an extract of only 50 larval Drosophila central nervous systems. Eighteen of these peptides are encoded in previously cloned or annotated precursor genes, although not all of them were predicted correctly. Eleven of these peptides were never purified before. Eight other peptides are entirely novel and are encoded in five different, not yet annotated genes. This neuropeptide expression profiling study also opens perspectives for other eukaryotic model systems, for which genome projects are completed or in progress.

Amino Acid Sequence↗
PubMed2005

Precise and parallel characterization of coding polymorphisms, alternative splicing, and modifications in human proteins by mass spectrometry.

The human proteome is a highly complex extension of the genome wherein a single gene often produces distinct protein forms due to alternative splicing, RNA editing, polymorphisms, and posttranslational modifications. Such biological variation compounded by the high sequence identity within gene families currently overwhelms the complete and routine characterization of mammalian proteins by MS. A new data base of human proteins (and their possible variants) was created and searched using tandem mass spectrometric data from intact proteins. This first application of top down MS/MS to wild-type human proteins demonstrates both gene-specific identification and the unambiguous characterization of multifaceted mass shifts (Deltam values). Such Deltam values found from the precise identification of 45 protein forms from HeLa cells reveal 34 coding single nucleotide polymorphisms, two protein forms from alternative splicing, and 12 diverse modifications (not including simple N-terminal processing), including a previously unknown phosphorylation at 10% occupancy. Automated protein identification was achieved with a median expectation value of 10(-13) and often occurred simultaneously with dissection of diverse sources of protein variability as they occur in combination. Top down MS therefore has a bright future for enabling precise annotation of gene products expressed from the human genome by non-mass spectrometrists.

Alternative Splicing↗
PubMed2000

T(E)Xtopo: shaded membrane protein topology plots in LAT(E)X2epsilon.

UNLABELLED: T(E)Xtopo is a LAT(E)X2epsilon macro package for plotting topology data directly from PHD predictions or SwissProt database files in publication-ready quality. The plot can be shaded automatically to emphasize conserved residues or functional properties of the residue sidechains. The addition of rich decorations, such as labels, annotations and legends, is easily accomplished. AVAILABILITY: The T(E)Xtopo macro package and a full on-line documentation are freely available at http://homepages.uni-tuebingen.de/beitz/ CONTACT: eric.beitz@uni-tuebingen.de

Amino Acid Sequence↗
PubMed2003

Improving gene annotation of complete viral genomes.

Gene annotation in viruses often relies upon similarity search methods. These methods possess high specificity but some genes may be missed, either those unique to a particular genome or those highly divergent from known homologs. To identify potentially missing viral genes we have analyzed all complete viral genomes currently available in GenBank with a specialized and augmented version of the gene finding program GeneMarkS. In particular, by implementing genome-specific self-training protocols we have better adjusted the GeneMarkS statistical models to sequences of viral genomes. Hundreds of new genes were identified, some in well studied viral genomes. For example, a new gene predicted in the genome of the Epstein-Barr virus was shown to encode a protein similar to alpha-herpesvirus minor tegument protein UL14 with heat shock functions. Convincing evidence of this similarity was obtained after only 12 PSI-BLAST iterations. In another example, several iterations of PSI-BLAST were required to demonstrate that a gene predicted in the genome of Alcelaphine herpesvirus 1 encodes a BALF1-like protein which is thought to be involved in apoptosis regulation and, potentially, carcinogenesis. New predictions were used to refine annotations of viral genomes in the RefSeq collection curated by the National Center for Biotechnology Information. Importantly, even in those cases where no sequence similarities were detected, GeneMarkS significantly reduced the number of primary targets for experimental characterization by identifying the most probable candidate genes. The new genome annotations were stored in VIOLIN, an interactive database which provides access to similarity search tools for up-to-date analysis of predicted viral proteins.

Amino Acid Sequence↗
PubMed2004

Quantitative evolutionary genomics: differential gene expression and male reproductive success in Drosophila melanogaster.

We combined traditional quantitative genetics and oligonucleotide microarrays to examine within-population genetic variation in a trait closely related to fitness. The trait, male reproductive success under competitive conditions (MCRS), is of central importance to both life-history and sexual-selection theory. We identified 27 candidate genes whose expression levels were associated with within-population variation in MCRS. "High" MCRS was associated with low expression of a cytochrome P450 that causes pesticide resistance, suggesting a fitness cost to resistance. Two groups of metabolic proteins (glutathione transferases and phosphatases) were significantly over-represented, and a large portion of the candidates are genes involved in oxidative stress resistance, energy acquisition or energy storage. Genes expressed in accessory glands and testes were not over-represented among differentially expressed genes, but testis-expressed genes were significantly more likely to be upregulated in high MCRS genotypes. Finally, nine candidate genes that we identified had no previous functional annotation, and this experiment suggests that they play a role in male reproductive success.

Animals↗
PubMed2002

Evidence suggesting that a fifth of annotated Caenorhabditis elegans genes may be pseudogenes.

Only a minority of the genes, identified in the Caenorhabditis elegans genome sequence data by computer analysis, have been characterized experimentally. We attempted to determine the expression patterns for a random sample of the annotated genes using reporter gene fusions. A low success rate was obtained for evolutionarily recently duplicated genes. Analysis of the data suggests that this is not due to conditional or low-level expression. The remaining explanation is that most of the annotated genes in the recently duplicated category are pseudogenes, a proportion corresponding to 20% of all of the annotated C. elegans genes. Further support for this surprisingly high figure was sought by comparing sequences for families of recently duplicated C. elegans genes. Although only a preliminary analysis, clear evidence for a gene having been recently inactivated by genetic drift was found for many genes in the recently duplicated category. At least 4% of the annotated C. elegans genes can be recognized as pseudogenes simply from closer inspection of the sequence data. Lessons learned in identifying pseudogenes in C. elegans could be of value in the annotation of the genomes of other species where, although there may be fewer pseudogenes, they may be harder to detect.

Amino Acid Sequence↗
PubMed2006

Hedgehog Signaling Pathway Database: a repository of current annotation efforts and resources for the Hh research community.

The Hedgehog Signaling Pathway Database is a curated repository of information pertaining to the Hedgehog developmental pathway. It was designed to provide centralized access to a wide range of relevant information in an organism-agnostic manner. Data are provided for all genes and gene targets known to be involved in the Hh pathway across various organisms. The data provided include DNA and protein sequences as well as domain structure motifs. All known human diseases associated with the Hh pathway are indexed including experimental data on therapeutic agents and their molecular targets. Hh researchers will find useful information on relevant protocols, tissue cell lines and reagents used in current Hh research projects. Curated content is also provided for publications, grants and patents relating to the Hh pathway. The database can be accessed at http://www.hedgehog.sfsu.edu.

Animals↗
PubMed2006

The identification of nucleic acid-interacting proteins using a simple proteomics-based approach that directly incorporates the electrophoretic mobility shift assay.

Proteins that interact with nucleic acids are central to numerous cellular processes, and their continuing characterization represents one of the foremost challenges in the postgenomic era. Here we describe a simple proteomics-based approach for the identification by mass spectrometry of proteins in crude extracts that interact with nucleic acids. It incorporates the electrophoretic mobility shift assay and is based on the finding that when a protein forms a complex with nucleic acid its electrophoretic mobility is affected as well as that of the nucleic acid. Our method should greatly reduce and in some cases may even eliminate the need for extensive protein purification and as such should contribute significantly to the functional annotation of the proteome. Furthermore it requires no prior knowledge of the molecular mass, quaternary structure, or pI of the interacting protein. Proof of principle is demonstrated using a recently discovered transcription factor; however, the approach should also have application in the identification of proteins that interact with RNA.

Amino Acid Sequence↗
PubMed2006

Automated SNP detection from a large collection of white spruce expressed sequences: contributing factors and approaches for the categorization of SNPs.

BACKGROUND: High-throughput genotyping technologies represent a highly efficient way to accelerate genetic mapping and enable association studies. As a first step toward this goal, we aimed to develop a resource of candidate Single Nucleotide Polymorphisms (SNP) in white spruce (Picea glauca [Moench] Voss), a softwood tree of major economic importance. RESULTS: A white spruce SNP resource encompassing 12,264 SNPs was constructed from a set of 6,459 contigs derived from Expressed Sequence Tags (EST) and by using the bayesian-based statistical software PolyBayes. Several parameters influencing the SNP prediction were analysed including the a priori expected polymorphism, the probability score (PSNP), and the contig depth and length. SNP detection in 3' and 5' reads from the same clones revealed a level of inconsistency between overlapping sequences as low as 1%. A subset of 245 predicted SNPs were verified through the independent resequencing of genomic DNA of a genotype also used to prepare cDNA libraries. The validation rate reached a maximum of 85% for SNPs predicted with either PSNP > or = 0.95 or > or = 0.99. A total of 9,310 SNPs were detected by using PSNP > or = 0.95 as a criterion. The SNPs were distributed among 3,590 contigs encompassing an array of broad functional categories, with an overall frequency of 1 SNP per 700 nucleotide sites. Experimental and statistical approaches were used to evaluate the proportion of paralogous SNPs, with estimates in the range of 8 to 12%. The 3,789 coding SNPs identified through coding region annotation and ORF prediction, were distributed into 39% nonsynonymous and 61% synonymous substitutions. Overall, there were 0.9 SNP per 1,000 nonsynonymous sites and 5.2 SNPs per 1,000 synonymous sites, for a genome-wide nonsynonymous to synonymous substitution rate ratio (Ka/Ks) of 0.17. CONCLUSION: We integrated the SNP data in the ForestTreeDB database along with functional annotations to provide a tool facilitating the choice of candidate genes for mapping purposes or association studies.

Algorithms↗
PubMed2006

Differential expression of genes related to HFE and iron status in mouse duodenal epithelium.

Iron absorption, distribution, use, and storage are thought to be tightly regulated since altered iron stores may lead to cellular damage and disease. HFE, the hereditary hemochromatosis gene product, is expressed in the crypts of the duodenum, but the molecular mechanism by which it contributes to the inhibition of iron absorption is still unknown. In this study we aimed to identify transcriptional profiles in the duodenal epithelium of Hfe(-/-) mice. We used dedicated microarrays to compare gene expression among the duodenum of Hfe(-/-) mice, induced iron overload mice, and control mice. We found 151 differentially expressed genes and unknown sequences between Hfe(-/-) mice and normal littermates. Gene profiling revealed a gene subset more specific for Hfe inactivation. The functional annotation of upregulated genes highlighted that mucus production and cell maintenance may account for the influence of Hfe on epithelium integrity and luminal iron uptake.

Animals↗
PubMed2006

VIRGO: computational prediction of gene functions.

Dramatic advances in sequencing technology and sophisticated experimental assays that interrogate the cell, combined with the public availability of the resulting data, herald the era of systems biology. However, the biological functions of more than 40% of the genes in sequenced genomes are unknown, posing a fundamental barrier to progress in systems biology. The large scale and diversity of available data requires the development of techniques that can automatically utilize these datasets to make quantified and robust predictions of gene function that can be experimentally verified. We present a service called the VIRtual Gene Ontology (VIRGO) that (i) constructs a functional linkage network (FLN) from gene expression and molecular interaction data, (ii) labels genes in the FLN with their functional annotations in the Gene Ontology and (iii) systematically propagates these labels across the FLN in order to precisely predict the functions of unlabelled genes. VIRGO assigns confidence estimates to predicted functions so that a biologist can prioritize predictions for further experimental study. For each prediction, VIRGO also provides an informative 'propagation diagram' that traces the flow of information in the FLN that led to the prediction. VIRGO is available at http://whipple.cs.vt.edu:8080/virgo.

Algorithms↗
PubMed2006

Assessing protein similarity with Gene Ontology and its use in subnuclear localization prediction.

BACKGROUND: The accomplishment of the various genome sequencing projects resulted in accumulation of massive amount of gene sequence information. This calls for a large-scale computational method for predicting protein localization from sequence. The protein localization can provide valuable information about its molecular function, as well as the biological pathway in which it participates. The prediction of localization of a protein at subnuclear level is a challenging task. In our previous work we proposed an SVM-based system using protein sequence information for this prediction task. In this work, we assess protein similarity with Gene Ontology (GO) and then improve the performance of the system by adding a module of nearest neighbor classifier using a similarity measure derived from the GO annotation terms for protein sequences. RESULTS: The performance of the new system proposed here was compared with our previous system using a set of proteins resided within 6 localizations collected from the Nuclear Protein Database (NPD). The overall MCC (accuracy) is elevated from 0.284 (50.0%) to 0.519 (66.5%) for single-localization proteins in leave-one-out cross-validation; and from 0.420 (65.2%) to 0.541 (65.2%) for an independent set of multi-localization proteins. The new system is available at http://array.bioengr.uic.edu/subnuclear.htm. CONCLUSION: The prediction of protein subnuclear localizations can be largely influenced by various definitions of similarity for a pair of proteins based on different similarity measures of GO terms. Using the sum of similarity scores over the matched GO term pairs for two proteins as the similarity definition produced the best predictive outcome. Substantial improvement in predicting protein subnuclear localizations has been achieved by combining Gene Ontology with sequence information.

Algorithms↗
PubMed2002

The characterisation of novel secreted Ly-6 proteins from rat urine by the combined use of two-dimensional gel electrophoresis, microbore high performance liquid chromatography and expressed sequence tag data.

A proteomic study of rat urine was undertaken using two-dimensional gel electrophoresis, microbore high performance liquid chromatography, mass spectrometry and N-terminal sequencing. Five known urinary proteins were identified but two novel peptide fragments matched a large number of rat expressed sequence tags (ESTs) from a liver library. By combining protein chemical and nucleotide data, two 101-residue open reading frames with 90% amino acid identity were determined, rat urinary protein 1 (RUP-1) and RUP-2. The data established signal peptide removal and provided evidence for N-glycosylation. A third related sequence, rat spleen protein (RSP-1) was confirmed from EST searches. These three proteins have been submitted to SWISS-PROT as P81827, P81828 and Q9QXN2, respectively. A fourth novel homologue was found in porcine and bovine ESTs from embryo libraries. Alignment with known homologues showed conserved cysteine positions characteristic of a secreted subfamily of Ly-6 proteins. In two cases, antineoplastic urinary protein and caltrin, these homologues have unverified functional annotations. The RUP sequences showed high scoring matches to three unrelated rat mRNAs subsequently established to be chimeric. Two of these share extended sectional identity to RUP-1 but the third may represent another novel Ly-6 homologue. These chimeras have caused serious annotation errors in secondary databases.

Amino Acid Sequence↗
PubMed2004

Towards a reference map of Eimeria tenella sporozoite proteins by two-dimensional electrophoresis and mass spectrometry.

Eimeria tenella is a parasite of great importance as a disease causing agent in the poultry industry. Until recently, biological studies have focused on specific proteins, some of which play an important role in the parasite life cycle. Post-genomic studies will make it possible to understand the complexity of the parasites and their interactions with host cells. Here we present a systematic reference map of the proteins from E. tenella sporozoites. The proteins expressed at the sporozoite stage were resolved between isoelectric points 3-10 and 4-7. They were systematically identified using mass spectrometry and 16 known Eimeria sporozoite proteins were identified on two-dimensional maps. Peptide fragmentation data from mass spectrometry were compared to single and consensus expression sequence tags in databases and to the E. tenella genome (not annotated). Among the set of unknown proteins analysed, 12 new assignments were proposed on the basis of similarities with Apicomplexa proteins. In order to define sporozoite proteins as potential targets for coccidiosis therapy, proteins were studied according to their relative abundance and immunogenicity in the sporozoite. Immunoblots of sporozoite 2D maps with chicken sera were performed and approximately 50 proteins were defined as antigens. It was shown that abundance and immunogenicity are not related in the sporozoite stage. Perspectives of gene prediction and completion of the genome annotation by a proteomic approach is discussed.

Amino Acid Sequence↗
PubMed2024

WilsonGenAI a deep learning approach to classify pathogenic variants in Wilson Disease.

BACKGROUND: Advances in Next Generation Sequencing have made rapid variant discovery and detection widely accessible. To facilitate a better understanding of the nature of these variants, American College of Medical Genetics and Genomics and the Association of Molecular Pathologists (ACMG-AMP) have issued a set of guidelines for variant classification. However, given the vast number of variants associated with any disorder, it is impossible to manually apply these guidelines to all known variants. Machine learning methodologies offer a rapid way to classify large numbers of variants, as well as variants of uncertain significance as either pathogenic or benign. Here we classify ATP7B genetic variants by employing ML and AI algorithms trained on our well-annotated WilsonGen dataset. METHODS: We have trained and validated two algorithms: TabNet and XGBoost on a high-confidence dataset of manually annotated, ACMG & AMP classified variants of the ATP7B gene associated with Wilson's Disease. RESULTS: Using an independent validation dataset of ACMG & AMP classified variants, as well as a patient set of functionally validated variants, we showed how both algorithms perform and can be used to classify large numbers of variants in clinical as well as research settings. CONCLUSION: We have created a ready to deploy tool, that can classify variants linked with Wilson's disease as pathogenic or benign, which can be utilized by both clinicians and researchers to better understand the disease through the nature of genetic variants associated with it.

Hepatolenticular Degeneration↗