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PubMed1994

Globin gene server: a prototype E-mail database server featuring extensive multiple alignments and data compilation for electronic genetic analysis.

The sequence of virtually the entire cluster of beta-like globin genes has been determined from several mammals, and many regulatory regions have been analyzed by mutagenesis, functional assays, and nuclear protein binding studies. This very large amount of sequence and functional data needs to be compiled in a readily accessible and usable manner to optimize data analysis, hypothesis testing, and model building. We report a Globin Gene Server that will provide this service in a constantly updated manner when fully implemented. The Server has two principal functions. The first (currently available) provides an annotated multiple alignment of the DNA sequences throughout the gene cluster from representatives of all species analyzed. The second compiles data on functional and protein binding assays throughout the gene cluster. A prototype of this compilation using the aligned 5' flanking region of beta-globin genes from five species shows examples of (1) well-conserved regions that have demonstrated functions, including cases in which the functional data are in apparent conflict, (2) proposed functional regions that are not well conserved, and (3) conserved regions with no currently assigned function. Such an electronic genetic analysis leads to many readily testable hypotheses that were not immediately apparent without the multiple alignment and compilation. The Server is accessible via E-mail on computer networks, and printed results can be obtained by request to the authors. This prototype will be a helpful guide for developing similar tools for many genomic loci.

Animals↗
PubMed1998

The Eukaryotic Promoter Database EPD.

The Eukaryotic Promoter Database (EPD) is an annotated non-redundant collection of experimentally characterised eukaryotic POL II promoters. The underlying definition of a promoter is that of a transcription initiation site. All information presented in EPD results from an independent evaluation of primary experimental data shown in the biological literature. Sequences flanking transcription initiation sites are indirectly given by pointers to EMBL sequences. The annotation part of a promoter entry includes description of the promoter-defining evidence, cross-references to other databases, and bibliographic references. Being designed as a resource for comparative sequence analysis, EPD is structured in a way that facilitates dynamic extraction of biologically meaningful promoter subsets. The database is available through the World Wide Web at URL http://cmpteam4.unil.ch

Animals↗
PubMed2005

DPDB: a database for the storage, representation and analysis of polymorphism in the Drosophila genus.

MOTIVATION: Polymorphism studies are one of the main research areas of this genomic era. To date, however, no comprehensive secondary databases have been designed to provide searchable collections of polymorphic sequences with their associated diversity measures. RESULTS: We define a data model for the storage, representation and analysis of genotypic and haplotypic data. Under this model we have created DPDB, 'Drosophila Polymorphism Database', a web site that provides a daily updated repository of all well-annotated polymorphic sequences in the Drosophila genus. It allows the search for any polymorphic set according to different parameter values of nucleotide diversity, linkage disequilibrium and codon bias. For data collection, analysis and updating we use PDA, a pipeline that automates the process of sequence retrieval, grouping, alignment and estimation of nucleotide diversity from Genbank sequences in different functional regions. The web site also includes analysis tools for sequence comparison and the estimation of genetic diversity, a page with real-time statistics of the database contents, a help section and a collection of selected links. AVAILABILITY: DPDB is freely available at http://dpdb.uab.es and can be downloaded via FTP.

Animals↗
PubMed2026

Long-read, high-coverage reference genome of the nymphalid butterfly Catonephele acontius (Nymphalidae: Biblidinae).

Catonephele acontius (Nymphalidae:Biblidinae:Epicalinii) is a butterfly species with a wide distribution across the Neotropics including the Amazon. Here, we present a long-read high-coverage reference genome for this species to serve as a genomic resource for future studies on Biblidinae butterflies, a group that is the subject of ongoing studies of seasonal adaptation under climate change. We used PacBio HiFi and IsoSeq reads to generate a highly contiguous and well-annotated reference genome. Five libraries were constructed, 4 using RNA from different tissues and 1 using high molecular weight (HMW) DNA from a wild-caught female. The DNA was sequenced using PacBio HiFi technology, and the RNA was sequenced using long read PacBio IsoSeq technology. About 20 Gb of raw HiFi data were generated and assembled to an initial size of 520.7 Mb (39 × homozygous coverage) in 90 contigs. The assembly was then polished and decontaminated into 40 contigs with an N50 of 19.927 Mb (BUSCO completeness: 99.0%; duplication: 0.5%; fragmentation: 0.7%; and missing: 0.3%). Final assembly size was 519.2 Mb. Repeats were annotated, showing that the genome consisted of 40.4% transposable elements. IsoSeq transcriptome data from antennae, leg, ovary, and digestive tissue was then used to structurally and functionally annotate gene models for the softmasked genome, uncovering ∼18,500 genes, with 70% of them given functional annotation. This reference assembly joins many published genomes in the Nymphalidae family but represents one of the first high-quality genomes from the Biblidinae subfamily. It provides a valuable resource to study the evolution of plastic and seasonal traits and will help investigate the genetic processes that may influence these species' responses to rapid climate change.

Animals↗
PubMed2004

ELISA: a unified, multidimensional view of the protein domain universe.

ELISA (http://romi.bu.edu/elisa/) is a database that was designed for flexibility in defining interesting queries about protein domain evolution. We have defined and included both the inherent characteristics of the domains such as structure and function and comparisons of these characteristics between domains. Thus, the database is useful in defining structural and functional links between related protein domains and by extension sequences that encode them. In this database we introduce and employ a novel method of functional annotation and comparison. For each protein domain we create a probabilistic functional annotation tree using GO. We have designed an algorithm that accurately compares these trees and thus provides a measure of "functional distance" between two protein domains. Along with functional annotation, we have also included structural comparison between protein domains and best sequence comparisons to all known genomes. The latter enables researchers to dynamically do searches for domains sharing similar phylogenetic profiles. This combination of data and tools enables the researcher to design complex queries to carry out research in the areas of protein domain evolution, structure prediction and functional annotation of novel sequences.

Amino Acid Sequence↗
PubMed2006

Protein binding microarrays (PBMs) for rapid, high-throughput characterization of the sequence specificities of DNA binding proteins.

DNA binding proteins play a number of key roles in cells, in processes including transcriptional regulation, recombination, genome rearrangements, and DNA replication, repair, and modification. Of particular interest are the interactions between transcription factors and their DNA binding sites, as they are an integral part of the transcriptional regulatory networks that control gene expression. Despite their importance, the DNA binding specificities of most DNA binding proteins remain unknown, as earlier technologies aimed at characterizing DNA-protein interactions have been time consuming and not highly scalable. We have developed a new DNA microarray-based technology, termed protein binding microarrays (PBMs), that allows rapid, high-throughput characterization of the in vitro DNA binding site sequence specificities of transcription factors in a single day. The resulting DNA binding site data can be used in a number of ways, including for the prediction of the genes regulated by a given transcription factor, annotation of transcription factor function, and functional annotation of the predicted target genes.

Base Sequence↗
PubMed2026

StrainMake: reproducible hybrid metagenomics with MAG recovery and strain-level resolution.

SUMMARY: Metagenomic workflows involve complex multi-step analyses, from quality control and assembly to binning, annotation, and strain-level profiling. Few existing metagenomic pipelines achieve the combination of flexibility, reproducibility, and hybrid assembly support within a unified workflow. We present StrainMake, a Snakemake-based workflow for de novo metagenomic analysis from short, long, or hybrid sequencing data. StrainMake integrates widely used tools across all major steps-quality control, assembly, binning, dereplication, taxonomic and functional annotation-while also providing non-redundant gene catalogues, community-scale metabolic models, and strain-level microdiversity metrics. The modular design enables the use of alternative tools, scalable execution on HPC systems, and full reproducibility through Snakemake and Conda. RESULTS: Applied to the CAMI II strain-madness dataset, StrainMake produced high-quality assemblies and metagenome-assembled genomes (MAGs), while enabling strain-resolved comparisons across samples. Hybrid assemblies improved contiguity, whereas short-read assemblies offered faster runtimes, illustrating the workflow's benchmarking capacity. AVAILABILITY AND IMPLEMENTATION: StrainMake is open source and available at https://github.com/UMMISCO/strainmake, together with comprehensive documentation. Generated data are deposited in Zenodo (doi: 10.5281/zenodo.16950162).

Metagenomics↗
PubMed2000

INE: a rice genome database with an integrated map view.

The Rice Genome Research Program (RGP) launched a large-scale rice genome sequencing in 1998 aimed at decoding all genetic information in rice. A new genome database called INE (INtegrated rice genome Explorer) has been developed in order to integrate all the genomic information that has been accumulated so far and to correlate these data with the genome sequence. A web interface based on Java applet provides a rapid viewing capability in the database. The first operational version of the database has been completed which includes a genetic map, a physical map using YAC (Yeast Artificial Chromosome) clones and PAC (P1-derived Artificial Chromosome) contigs. These maps are displayed graphically so that the positional relationships among the mapped markers on each chromosome can be easily resolved. INE incorporates the sequences and annotations of the PAC contig. A site on low quality information ensures that all submitted sequence data comply with the standard for accuracy. As a repository of rice genome sequence, INE will also serve as a common database of all sequence data obtained by collaborating members of the International Rice Genome Sequencing Project (IRGSP). The database can be accessed at http://www. dna.affrc.go.jp:82/giot/INE. html or its mirror site at http://www.staff.or.jp/giot/INE.html

Chromosomes, Artificial, Yeast↗
PubMed2006

Origin of the tetraspanin uroplakins and their co-evolution with associated proteins: implications for uroplakin structure and function.

Genome level information coupled with phylogenetic analysis of specific genes and gene families allow for a better understanding of the structure and function of their protein products. In this study, we examine the mammalian uroplakins (UPs) Ia and Ib, members of the tetraspanin superfamily, that interact with uroplakins UPII and UPIIIa/IIIb, respectively, using a phylogenetic approach of these genes from whole genome sequences. These proteins interact to form urothelial plaques that play a central role in the permeability barrier function of the apical urothelial surface of the urinary bladder. Since these plaques are found exclusively in mammalian urothelium, it is enigmatic that UP-like genomic sequences were recently found in lower vertebrates without a typical urothelium. We have cloned full-length UP-related cDNAs from frog (Xenopus laevis), chicken (Gallus gallus), and zebrafish (Danio rerio), and combined these data with sequence information from their orthologs in all the available fully sequenced and annotated animal genomes. Phylogenetic analyses of all the available uroplakin sequences, and an understanding of their distribution in several animal taxa, suggest that: (i) the UPIa/UPIb and UPII/UPIII genes evolved by gene duplication in the common ancestor of vertebrates; (ii) uroplakins can be lost in different combinations in vertebrate lineages; and (iii) there is a strong co-evolutionary relationship between UPIa and UPIb and their partners UPII and UPIIIa/IIIb, respectively. The co-evolution of the tetraspanin UPs and their associated proteins may fine-tune the structure and function of uroplakin complexes enabling them to perform diverse species- and tissue-specific functions. The structure and function of uroplakins, which are also expressed in Xenopus kidney, oocytes and fat body, are much more versatile than hitherto appreciated.

Amino Acid Sequence↗
PubMed1991

Improved patient surveillance and data acquisition with a third generation implantable cardioverter defibrillator.

Thirteen patients were implanted with the Telectronics 4210 ATP implantable cardioverter defibrillator (ICD) for ventricular tachycardia or ventricular fibrillation. This device has multiprogrammable antitachycardia pacing, bradycardia pacing, and shock therapies. In addition, there is extensive data logging and ECG snapshot capability for arrhythmia confirmation and response to therapy. These features permit easy retrieval of all detected and treated events, whatever the eventual outcome. In this study, the data logged at predischarge electrophysiological testing was compared to the data recorded in a standard manner. The bulk of the data, however, was derived from long-term follow-up of spontaneous events over a mean period of 203 days (range 154-257). During this period, a total of 6,193 arrhythmia detections were made: 20 were classified as ventricular fibrillation, and 6,173 as ventricular tachycardia. The vast majority of these (93%) terminated spontaneously without ICD intervention (5,738), underscoring the benefit of a standard second confirmation prior to therapy delivery (noncommitted system). There were 394 arrhythmia episodes treated with antitachycardia pacing; of these a total of 8.3% accelerated to either more rapid ventricular tachycardia or ventricular fibrillation (4.3% and 4.0%, respectively). Events were reported in an "episode log" format, listing all arrhythmia detections with time/date annotation; or in a "sense history" format, detailing each episode from start to conclusion. These data demonstrate that this advanced, "tiered" ICD with data recall contributes to better patient management, and permits a more tailored termination prescription for the individual patient.

Cardiac Pacing, Artificial↗
PubMed2024

CLN3 transcript complexity revealed by long-read RNA sequencing analysis.

BACKGROUND: Batten disease is a group of rare inherited neurodegenerative diseases. Juvenile CLN3 disease is the most prevalent type, and the most common pathogenic variant shared by most patients is the "1-kb" deletion which removes two internal coding exons (7 and 8) in CLN3. Previously, we identified two transcripts in patient fibroblasts homozygous for the 1-kb deletion: the 'major' and 'minor' transcripts. To understand the full variety of disease transcripts and their role in disease pathogenesis, it is necessary to first investigate CLN3 transcription in "healthy" samples without juvenile CLN3 disease. METHODS: We leveraged PacBio long-read RNA sequencing datasets from ENCODE to investigate the full range of CLN3 transcripts across various tissues and cell types in human control samples. Then we sought to validate their existence using data from different sources. RESULTS: We found that a readthrough gene affects the quantification and annotation of CLN3. After taking this into account, we detected over 100 novel CLN3 transcripts, with no dominantly expressed CLN3 transcript. The most abundant transcript has median usage of 42.9%. Surprisingly, the known disease-associated 'major' transcripts are detected. Together, they have median usage of 1.5% across 22 samples. Furthermore, we identified 48 CLN3 ORFs, of which 26 are novel. The predominant ORF that encodes the canonical CLN3 protein isoform has median usage of 66.7%, meaning around one-third of CLN3 transcripts encode protein isoforms with different stretches of amino acids. The same ORFs could be found with alternative UTRs. Moreover, we were able to validate the translational potential of certain transcripts using public mass spectrometry data. CONCLUSION: Overall, these findings provide valuable insights into the complexity of CLN3 transcription, highlighting the importance of studying both canonical and non-canonical CLN3 protein isoforms as well as the regulatory role of UTRs to fully comprehend the regulation and function(s) of CLN3. This knowledge is essential for investigating the impact of the 1-kb deletion and rare pathogenic variants on CLN3 transcription and disease pathogenesis.

Humans↗
PubMed2026

[Applications and Challenges of Deep Learning in Human Genome Research].

In recent years, the advent of high-throughput omics technologies has fueled an explosive growth in human genomic data. Uncovering the latent functions within this vast data has become a significant challenge in functional genomics research. While traditional statistical methods have proved successful for analyzing smaller-scale datasets in the past, they exhibit clear limitations in analytical efficiency and integrating multi-dimensional data, struggling to meet the escalating demands of contemporary genomic analysis. The introduction of deep learning (DL) technologies offers a novel paradigm for this field. This review systematically examines the advances in applying deep learning to human genomics research. Studies demonstrate that when ample labeled data is available, discriminative DL computational methods-such as Convolutional Neural Networks (CNNs) and Long Short-Term Memory networks (LSTMs)-achieve high accuracy and efficiency in genomic variant discovery tasks. Furthermore, generative DL methods, particularly Large Language Models (LLMs) leveraging self-supervised pre-training strategies, effectively integrate complex genomic information and exhibit superior performance in functional genomic sequence annotation and gene regulation studies. This review also explores the application of LLMs in multi-omics data integration and prediction. Looking ahead, the continued accumulation of long-read sequencing and high-dimensional data is expected to enable DL technologies to integrate increasingly complex and heterogeneous genomic information, playing an increasingly crucial role in human genomics research.

Deep Learning↗
PubMed2006

ArrayExpress--a public database of microarray experiments and gene expression profiles.

UNLABELLED: ArrayExpress is a public database for high throughput functional genomics data. ArrayExpress consists of two parts--the ArrayExpress Repository, which is a MIAME supportive public archive of microarray data, and the ArrayExpress Data Warehouse, which is a database of gene expression profiles selected from the repository and consistently re-annotated. Archived experiments can be queried by experiment attributes, such as keywords, species, array platform, authors, journals or accession numbers. Gene expression profiles can be queried by gene names and properties, such as Gene Ontology terms and gene expression profiles can be visualized. ArrayExpress is a rapidly growing database, currently it contains data from >50,000 hybridizations and >1,500,000 individual expression profiles. ArrayExpress supports community standards, including MIAME, MAGE-ML and more recently the proposal for a spreadsheet based data exchange format: MAGE-TAB. AVAILABILITY: www.ebi.ac.uk/arrayexpress.

Animals↗
PubMed2025

EucaMOD: a comprehensive multi-omics database for functional genomics research and molecular breeding of fast-growing eucalyptus trees.

Eucalyptus, one of the most widely planted plantation tree species globally, is primarily found in tropical and subtropical regions and contributes significantly to economic and social benefits. With advances in sequencing technologies, there is an increasing demand for the systematic analysis of multi-omics data among Eucalyptus species to enhance genetic breeding efforts. Although several early genomic databases have been established for eucalyptus, they have not been updated in a timely manner and lack recent multi-omics data, rendering them insufficient for current research needs. To address this gap, we developed the eucalyptus multi-omics database (EucaMOD, http://eucalyptusggd.net/eucamod), a comprehensive resource for cross-omics studies. In this study, we functionally annotated 45 eucalyptus genomes and structurally annotated 15, conducting comparative genomics and pan-proteomics analyses across all genomes. Additionally, we analyzed eucalyptus transcriptome, epigenome, and variome data through standardized workflows, enabling the in-depth mining and reanalysis of multi-omics datasets. EucaMOD is the most comprehensive multi-omics database for eucalyptus to date and includes data from 45 genomes (39 species), 870 mRNA-seq samples, 17 miRNA-seq samples, 52 epigenomic datasets (histone modifications and transcription factor binding), and genetic variation data from 1219 samples. To support functional genomics and molecular breeding research, the database is organized into the following 11 modules: Home, Species, Genomics, Comparative genomics, Pan-proteomics, Transcriptomics, Epigenetics, Variomics, Tools, Download, and Help. EucaMOD also offers online analysis tools for data mining, providing free public services to aid eucalyptus gene function and genetic engineering studies.

Eucalyptus↗
PubMed1994

[Polish doctors graves at the cemeteries in Edinburgh].

The first part of the text reviews the cultural links between Poland and Scotland. These links were originated in the 14th century and were created by scottish students travelling to Poland to seek learning in the then polish centre of excellence Jagiellonian University in Cracow. There were also some learned Scots who ventured to Poland, seeking work. Some of them achieved positions of distinction. The first Polish medical men attended the University of Edinburgh in the 18th century. In the 19th century, following the suppression of the polish uprising against Russia, there were a small group of Poles seeking asylum in Scotland. A few of them enlisted at the University of Edinburgh at the medical faculty. The above history is described in detail in Annotations. In the second part of the paper all the polish medical and veterinary doctors whose graves are located in various cemeteries in Edinburgh are listed in chronological order of their deaths. As full as possible personal data, the kind of medical work, and location of their graves are given. Greater details, whenever obtainable, are dealt with in Annotations. The total of thirty deceased between 1942 and 1993 are described.

Burial↗
PubMed2006

Systematic identification of pseudogenes through whole genome expression evidence profiling.

The identification of pseudogenes is an integral and significant part of the genome annotation because of their abundance and their impact on the experimental analysis of functional genes. Most of the computational annotation systems are not optimized for systematic pseudogene recognition, often annotating pseudogenes as functional genes, and users then propagate these errors to subsequent analyses and interpretations. In order to validate gene annotations and to identify pseudogenes that are potentially mis-annotated, we developed a novel approach based on whole genome profiling of existing transcript and protein sequences. This method has two important features: (i) equally detects both processed and non-processed pseudogenes and (ii) can identify transcribed pseudogenes. Applying this method to the human Ensembl gene predictions, we discovered that 2011 (9% of total) Ensembl genes in the categories of known and novel might be pseudogenes based on expression evidence. Of these, 1200 genes are found to have no existing evidence of transcription, and 811 genes are found with transcription evidence but contain significant translation disruption. Approximately 40% of the 2011 identified pseudogenes presented a multi-exon structure, representing non-processed pseudogenes. We have demonstrated the power of whole genome profiling of expression sequences to improve the accuracy of gene annotations.

Computational Biology↗
PubMed2004

eL-DASionator: an LDAS upload file generator.

BACKGROUND: The Distributed Annotation System (DAS) allows merging of DNA sequence annotations from multiple sources and provides a single annotation view. A straightforward way to establish a DAS annotation server is to use the "Lightweight DAS" server (LDAS). Onto this type of server, annotations can be uploaded as flat text files in a defined format. The popular Ensembl ContigView uses the same format for the transient upload and display of user data. RESULTS: In order to easily generate LDAS upload files we developed a software tool that is accessible via a web-interface http://atgc.lirmm.fr/eldasionator.html. Users can submit their DNA sequences of interest. Our program (i) aligns these sequences to the reference sequences of Ensembl, (ii) determines start and end positions of each sequence on the reference sequence, and (iii) generates a formatted annotation file. This file can be used to load any LDAS annotation server or it can be uploaded to the Ensembl ContigView. CONCLUSION: The eL-DASionator is an on-line tool that is intended for life-science researchers with little bioinformatics background. It conveniently generates LDAS upload files, and makes it possible to generate annotations in a standard format that permits comfortable sharing of this data.

Base Sequence↗
PubMed2000

Phylogeny of related functions: the case of polyamine biosynthetic enzymes.

Genome annotation requires explicit identification of gene function. This task frequently uses protein sequence alignments with examples having a known function. Genetic drift, co-evolution of subunits in protein complexes and a variety of other constraints interfere with the relevance of alignments. Using a specific class of proteins, it is shown that a simple data analysis approach can help solve some of the problems posed. The origin of ureohydrolases has been explored by comparing sequence similarity trees, maximizing amino acid alignment conservation. The trees separate agmatinases from arginases but suggest the presence of unknown biases responsible for unexpected positions of some enzymes. Using factorial correspondence analysis, a distance tree between sequences was established, comparing regions with gaps in the alignments. The gap tree gives a consistent picture of functional kinship, perhaps reflecting some aspects of phylogeny, with a clear domain of enzymes encoding two types of ureohydrolases (agmatinases and arginases) and activities related to, but different from ureohydrolases. Several annotated genes appeared to correspond to a wrong assignment if the trees were significant. They were cloned and their products expressed and identified biochemically. This substantiated the validity of the gap tree. Its organization suggests a very ancient origin of ureohydrolases. Some enzymes of eukaryotic origin are spread throughout the arginase part of the trees: they might have been derived from the genes found in the early symbiotic bacteria that became the organelles. They were transferred to the nucleus when symbiotic genes had to escape Muller's ratchet. This work also shows that arginases and agmatinases share the same two manganese-ion-binding sites and exhibit only subtle differences that can be accounted for knowing the three-dimensional structure of arginases. In the absence of explicit biochemical data, extreme caution is needed when annotating genes having similarities to ureohydrolases.

Amino Acid Sequence↗