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At least 1,711 records · Page 95Linked to original sources

Analysis of the Saccharomyces cerevisiae proteome with PeptideAtlas.

We present the Saccharomyces cerevisiae PeptideAtlas composed from 47 diverse experiments and 4.9 million tandem mass spectra. The observed peptides align to 61% of Saccharomyces Genome Database (SGD) open reading frames (ORFs), 49% of the uncharacterized SGD ORFs, 54% of S. cerevisiae ORFs with a Gene Ontology annotation of 'molecular function unknown', and 76% of ORFs with Gene names. We highlight the use of this resource for data mining, construction of high quality lists for targeted proteomics, validation of proteins, and software development.

Codon↗

A hybrid and cost-efficient barcoding strategy for full-length 16S rRNA gene nanopore sequencing of environmental samples.

BACKGROUND: Accurate species-level identification of bacteria in complex environmental samples is essential for applications in biotechnology, ecological monitoring, and clinical diagnostics. Short-read platforms such as Illumina frequently truncate the 16S rRNA gene, limiting taxonomic resolution. In this work, we applied Oxford Nanopore Technology (ONT) long-read sequencing to full-length 16S rRNA amplicon in samples from natural soil amended with lignocellulosic biomass and a simplified microbial community derived from cultures grown on selective and differential carboxymethyl cellulose (CMC)-based substrates, with the aim to evaluate the difference in performance between a real, complex community and a less complex system. To reduce consumable costs, we substituted the standard ONT Barcoding kits with an in-house hybrid barcoding workflow. Specifically, PacBio PCR-based barcoding protocol was used for sample indexing, followed by library preparation using the ONT Ligation Sequencing Kit. This simplified approach retained compatibility with MinION and Flongle flow cells and supported accurate downstream demultiplexing while lowering barcode costs substantially. Additionally, a new bioinformatic workflow tailored to ONT data was implemented. RESULTS: Overall, the hybrid protocol significantly reduced per-sample barcoding costs while preserving high sequencing quality and throughput. The sequencing run yielded over 5 Gb of quality-filtered data (Q-score ≥ 10). Furthermore, the new bioinformatic workflow allowed taxonomic assignment at the species level for 49.38% of annotated taxa, compared to just 4.59% using Illumina NovaSeq sequencing of the V3-V4 region. ONT also recovered 2.3 times more genera and 1.3 times more families. Although 16S rRNA gene sequencing often cannot distinguish between closely related species, particularly within taxonomically complex groups, in this work, full-length reads substantially improved both taxonomic resolution and database matching. CONCLUSIONS: These results show that full-length 16S rRNA sequencing with ONT, paired with a low-cost barcoding strategy, enhanced taxonomic resolution compared to short-read workflows. This approach also offers a scalable and cost-effective option for high-resolution microbiome profiling in research and applied settings.

RNA, Ribosomal, 16S↗

Tackling non-canonical splicing in arrhythmogenic cardiomyopathy to reduce the uncertain significance variants burden.

BACKGROUND: Splice-altering variants (SAVs), particularly those outside canonical splice sites, are an underappreciated contributor to inherited cardiovascular diseases. In arrhythmogenic cardiomyopathy (ACM), these variants frequently remain classified as of uncertain significance (VUS) due to limited predictive power and lack of transcript-level evidence, constraining genetic yield and clinical management. Our study aimed to determine the functional impact of SAVs in ACM genes and refine their classification using ACMG/AMP and ClinGen SVI criteria. METHODS: SAVs identified in 200 ACM probands underwent SpliceAI prediction, GTEx cardiac exon-usage annotation, and functional assessment using pSPL3-based minigene assays. Aberrant transcripts were quantified using Percent Splicing Alteration (PSA). Segregation data and ACMG/AMP criteria refined by ClinGen SVI were applied to integrate functional and clinical evidence for classification. RESULTS: Aberrant splicing was confirmed in 9/20 variants (45%), including synonymous, missense, and non-canonical intronic changes. SpliceAI scores correlated strongly with PSA values (R²=0.86). Case-control burden testing revealed significant enrichment of splice-altering variants in DSP, DSG2, DSC2 and FLNC. Integrating predictive algorithms with experimental validation and segregation analysis markedly enhances reclassification of 16/20 variants (80%). CONCLUSION: Splicing defects beyond canonical sites significantly shape ACM genetic landscape. Integrating predictive models with experimental validation clarifies uncertain variants bridging the gap between genomic uncertainty and clinical decision-making.

Humans↗

The chromosomal genome sequence of the maze coral, Meandrina meandrites (Linnaeus, 1758) (Scleractinia: Meandrinidae) and its associated microbial metagenome sequences.

We present a genome assembly from a specimen of Meandrina meandrites (maze coral; Cnidaria; Anthozoa; Scleractinia; Meandrinidae). The genome sequence has a total length of 551.16 megabases. Most of the assembly (99.25%) is scaffolded into 14 chromosomal pseudomolecules. The mitochondrial genome has also been assembled, with a length of 17.2 kilobases. Gene annotation of this assembly by Ensembl identified 30 464 protein-coding genes. We recovered two bins from the metagenome data.

Meandrina meandrites↗

Computer-generated holograms of a real three-dimensional object based on stereoscopic video images.

A novel method of using stereoscopic video images to synthesize the computer-generated hologram (CGH) patterns of a real 3D object is proposed. Stereoscopic video images of a real 3D object are captured by a 3D camera system. Disparity maps between the captured stereo image pairs are estimated and from these estimated maps the depth data for each pixel of the object can be extracted on a frame basis. By using these depth data and original color images, hologram patterns of a real object can be computationally generated. In experiments, stereoscopic video images of a real 3D object, a wooden rhinoceros doll, are captured by using the Wasol 3D adapter system and its depth data are extracted from them. Then, CGH patterns of 1280 pixels x 1024 pixels are generated with these depth-annotated images of the wooden rhinoceros doll, and the CGH patterns are experimentally displayed via a holographic display system.

Journal Article↗

Discovery of local packing motifs in protein structures.

We present a language for describing structural patterns of residues in protein structures and a method for the discovery of such patterns that recur in a set of protein structures. The patterns impose restrictions on the spatial position of each residue, their order along the amino acid chain, and which amino acids are allowed in each position. Unlike other methods for comparing sets of protein structures, our method is not based on the use of pairwise structure comparisons which is often time consuming and can produce inconsistent results. Instead, the method simultaneously takes into account information from all structures in the search for conserved structure patterns which are potential structure motifs. The method is based on describing the spatial neighborhoods of each residue in each structure as a string and applying a sequence pattern discovery method to find patterns common to subsets of these strings. Finally it is checked whether the similarities between the neighborhood strings correspond to spatially similar substructures. We apply the method to analyze sets of very disparate proteins from the four different protein families: serine proteases, cuprodoxins, cysteine proteinases, and ferredoxins. The motifs found by the method correspond well to the site and motif information given in the annotation of these proteins in PDB, Swiss-Prot, and PROSITE. Furthermore, the motifs are confirmed by using the motif data to constrain the structural alignment of the proteins obtained with the program SAP. This gave the best superposition/alignment of the proteins given the motif assignment.

Algorithms↗

Unraveling Neuronal Identities Using SIMS: A Deep Learning Label Transfer Tool for Single-Cell RNA Sequencing Analysis.

Large single-cell RNA datasets have contributed to unprecedented biological insight. Often, these take the form of cell atlases and serve as a reference for automating cell labeling of newly sequenced samples. Yet, classification algorithms have lacked the capacity to accurately annotate cells, particularly in complex datasets. Here we present SIMS (Scalable, Interpretable Machine Learning for Single-Cell), an end-to-end data-efficient machine learning pipeline for discrete classification of single-cell data that can be applied to new datasets with minimal coding. We benchmarked SIMS against common single-cell label transfer tools and demonstrated that it performs as well or better than state of the art algorithms. We then use SIMS to classify cells in one of the most complex tissues: the brain. We show that SIMS classifies cells of the adult cerebral cortex and hippocampus at a remarkably high accuracy. This accuracy is maintained in trans-sample label transfers of the adult human cerebral cortex. We then apply SIMS to classify cells in the developing brain and demonstrate a high level of accuracy at predicting neuronal subtypes, even in periods of fate refinement, shedding light on genetic changes affecting specific cell types across development. Finally, we apply SIMS to single cell datasets of cortical organoids to predict cell identities and unveil genetic variations between cell lines. SIMS identifies cell-line differences and misannotated cell lineages in human cortical organoids derived from different pluripotent stem cell lines. When cell types are obscured by stress signals, label transfer from primary tissue improves the accuracy of cortical organoid annotations, serving as a reliable ground truth. Altogether, we show that SIMS is a versatile and robust tool for cell-type classification from single-cell datasets.

Brain organoids↗

Digital archival and exchange of events in a simple format for polygraphic recordings with application in event related potential studies.

This paper describes a simple method of event encoding as an extension to a previously defined standard format, the European Data Format (EDF). The specification ensures full backward compatibility with the existing definition. By using this extension, the format can be used to store both continuous recordings and selected epochs of recordings. The encoding is performed in a channel of event-codes or in a pseudo-channel for annotations. Standardisation of event encoding is discussed. Decoding of events or annotations from the extended format is implemented at the application level. Existing programs that do not support the new encoding scheme still operate correctly and can simply ignore the new channels in processing 'extended' data files. The event encoding is also compatible with EDF's capability to encode channels of different sampling frequency.

Data Interpretation, Statistical↗

The human biological resource centres network. A key infrastructure for biomedical research in Europe.

Continuing advances in life sciences and medical research are the result of the remarkable achievements of cell and molecular biology. In the post-sequencing era, the quality of the huge amount of data continuously generated by biotechnology, i.e. genomics, proteomics and high-throughput screening, depends on the quality assurance and the traceability of the original biological materials, including the annotations linked to these materials. Thus, biological resource centres are key infrastructures supporting biotechnology, bioprocessing and the development of new approaches in the prevention, diagnosis and treatment of diseases.

Biomedical Research↗

Network approaches to genome annotation and the challenge of Anopheles gambiae.

The rapid advancement of current sequencing projects has provided significant challenges for the swift and accurate processing, integration and analysis of biological data. Such challenges will only become greater as a new round of organisms, both well known and obscure, await sequencing and further study. While perhaps less well studied at the molecular level than Drosophila melanogaster, the recently sequenced mosquito, Anopheles gambiae, provides an example of what will be faced by many of these awaiting projects. This review presents a brief overview of some of the challenges associated with these future genome projects (including Anopheles) as well as a description of recent computational approaches that utilize genome context for the prediction of gene and/or protein function. Such approaches show promise not only for the study of Anopheles, but also in the study of biological processes in general.

Animals↗

GenBank.

The GenBank (Registered Trademark symbol) sequence database incorporates DNA sequences from all available public sources, primarily through the direct submission of sequence data from individual laboratories and from large-scale sequencing projects. Most submitters use the BankIt (Web) or Sequin programs to format and send sequence data. Data exchange with the EMBL Data Library and the DNA Data Bank of Japan helps ensure comprehensive worldwide coverage. GenBank data is accessible through NCBI's integrated retrieval system, Entrez, which integrates data from the major DNA and protein sequence databases along with taxonomy, genome and protein structure information. MEDLINE (Registered Trademark symbol) s from published articles describing the sequences are included as an additional source of biological annotation through the PubMed search system. Sequence similarity searching is offered through the BLAST series of database search programs. In addition to FTP, Email, and server/client versions of Entrez and BLAST, NCBI offers a wide range of World Wide Web retrieval and analysis services based on GenBank data. The GenBank database and related resources are freely accessible via the URL: http://www.ncbi.nlm.nih.gov

Amino Acid Sequence↗

The FunCat, a functional annotation scheme for systematic classification of proteins from whole genomes.

In this paper, we present the Functional Catalogue (FunCat), a hierarchically structured, organism-independent, flexible and scalable controlled classification system enabling the functional description of proteins from any organism. FunCat has been applied for the manual annotation of prokaryotes, fungi, plants and animals. We describe how FunCat is implemented as a highly efficient and robust tool for the manual and automatic annotation of genomic sequences. Owing to its hierarchical architecture, FunCat has also proved to be useful for many subsequent downstream bioinformatic applications. This is illustrated by the analysis of large-scale experiments from various investigations in transcriptomics and proteomics, where FunCat was used to project experimental data into functional units, as 'gold standard' for functional classification methods, and also served to compare the significance of different experimental methods. Over the last decade, the FunCat has been established as a robust and stable annotation scheme that offers both, meaningful and manageable functional classification as well as ease of perception.

Abstracting and Indexing↗

Advances in the Exon-Intron Database (EID).

Investigation of exon-intron gene structures is a non-trivial task due to enormous expansions of the eukaryotic genomes, great variety of gene forms, and the imperfectness in sequence data. A number of available informational systems on various gene characteristics complement each other and are indispensable for many genomic studies. Among them, the Exon-Intron Database (EID) is a good choice for large-scale computational examination of exon/intron structure and splicing. It has many internal filters that control for sequence quality, consistency of gene descriptions, accordance to standards, and possible errors. New innovations in EID are described. The collection of exons and introns has been extended beyond coding regions and current versions of EID contain data on untranslated regions of gene sequences as well. Intron-less genes are included as a special part of EID. For species with entirely sequenced genomes, species-specific databases have been generated. A novel Mammalian Orthologous Intron Database (MOID) has been introduced which includes the full set of introns that come from orthologous genes that have the same positions relative to the reading frames. Examples of statistical analyses of gene sequences using EID are provided. We present the latest data on our comparison of intron positions in 11,025 orthologous genes of human, mouse and rat, and find no convincing cases of intron gain. We discuss relevant data-quality issues of genomic databases. In particular, 5% of genes in genomic databases contain internal stop codons. This fact is due to a combination of biological reasons and also to errors in sequence annotations. The EID is freely available at www.meduohio.edu/bioinfo/eid/.

Base Sequence↗

TransportDB: a comprehensive database resource for cytoplasmic membrane transport systems and outer membrane channels.

TransportDB (http://www.membranetransport.org/) is a comprehensive database resource of information on cytoplasmic membrane transporters and outer membrane channels in organisms whose complete genome sequences are available. The complete set of membrane transport systems and outer membrane channels of each organism are annotated based on a series of experimental and bioinformatic evidence and classified into different types and families according to their mode of transport, bioenergetics, molecular phylogeny and substrate specificities. User-friendly web interfaces are designed for easy access, query and download of the data. Features of the TransportDB website include text-based and BLAST search tools against known transporter and outer membrane channel proteins; comparison of transporter and outer membrane channel contents from different organisms; known 3D structures of transporters, and phylogenetic trees of transporter families. On individual protein pages, users can find detailed functional annotation, supporting bioinformatic evidence, protein/DNA sequences, publications and cross-referenced external online resource links. TransportDB has now been in existence for over 10 years and continues to be regularly updated with new evidence and data from newly sequenced genomes, as well as having new features added periodically.

Bacterial Outer Membrane Proteins↗

ViTa: prediction of host microRNAs targets on viruses.

MicroRNAs (miRNAs) are involved in various biological processes by suppressing gene expression. A recent work has indicated that host miRNAs are also capable of regulating viral gene expression by targeting the virus genomes. To investigate regulatory relationships between host miRNAs and related viruses, we present a novel database, namely ViTa, to curate the known virus miRNA genes and the known/putative target sites of human, mice, rat and chicken miRNAs. Known miRNAs are obtained from miRBase. Virus data are collected and referred from ICTVdB, VBRC and VirGen. Experimentally validated miRNA targets on viruses were derived from literatures. Then, miRanda and TargetScan are utilized to predict miRNA targets within virus genomes. ViTa also provides the virus annotations, virus-infected tissues and tissue specificity of host miRNAs. This work also facilitates the comparisons between subtypes of viruses, such as influenza viruses, human liver viruses and the conserved regions between viruses. Both textual and graphical web interfaces are provided to facilitate the data retrieves in the ViTa database. The database is now freely available at http://vita.mbc.nctu.edu.tw/.

Animals↗

Comparing functional annotation analyses with Catmap.

BACKGROUND: Ranked gene lists from microarray experiments are usually analysed by assigning significance to predefined gene categories, e.g., based on functional annotations. Tools performing such analyses are often restricted to a category score based on a cutoff in the ranked list and a significance calculation based on random gene permutations as null hypothesis. RESULTS: We analysed three publicly available data sets, in each of which samples were divided in two classes and genes ranked according to their correlation to class labels. We developed a program, Catmap (available for download at http://bioinfo.thep.lu.se/Catmap), to compare different scores and null hypotheses in gene category analysis, using Gene Ontology annotations for category definition. When a cutoff-based score was used, results depended strongly on the choice of cutoff, introducing an arbitrariness in the analysis. Comparing results using random gene permutations and random sample permutations, respectively, we found that the assigned significance of a category depended strongly on the choice of null hypothesis. Compared to sample label permutations, gene permutations gave much smaller p-values for large categories with many coexpressed genes. CONCLUSIONS: In gene category analyses of ranked gene lists, a cutoff independent score is preferable. The choice of null hypothesis is very important; random gene permutations does not work well as an approximation to sample label permutations.

Classification↗

Tempo and mode of ERV-K evolution in human and chimpanzee genomes.

Several families of endogenous retrovirus (ERV) exist in copious numbers in the genomes of primate species. Therefore, we undertook a systematic search for endogenous retrovirus sequences from the ERV-K family, comparing across both human (Homo sapiens) and chimpanzee (Pan troglodytes) genomes. Using conserved motifs of the ERV-K as query we identified and characterized 76 complete ERV-K elements, 54 in human (HERV-K), 34 of which were described previously, and 21 in the chimpanzee (CERV-K). Phylogenetic analysis using coding regions and LTRs showed the existence of two main branches. Group I was the most heterogeneous and had an average integration time of 18.3 MYBP (million years before present), using rates ranging from 1.5 to 4.0 x 10(-9) s/s/y (substitution per site per year). Group O/N integrated around 19.4 MYBP and nested Group N integrated about 14 MYBP. We found evidence for strong positive selection on the gag, pol and env coding regions and for A/T hypermutation. Our data suggest that the endogenous elements were possibly involved in chromosomal rearrangements and retained a great deal of information from their active stage, most likely as a consequence of host interactions. This study also contributes to the annotation effort of both human and chimpanzee genomes.

Animals↗