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Results for “functional annotations”

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PubMed2004

FREP: a database of functional repeats in mouse cDNAs.

The FREP database (http://facts.gsc.riken.go.jp/FREP/) contains 31 396 RepeatMasker-identified non-redundant variant repeat sequences derived from 16,527 mouse cDNAs with protein-coding potential. The repeats were computationally associated with potential effects on transcriptional variation, translation, protein function or involvement in disease to identify Functional REPeats (FREPs). FREPs are defined by the (i) occurrence of exon-exon boundaries in repeats, (ii) presence of polyadenylation sites in 3'UTR-located repeats, (iii) effect on translation, (iv) position in the protein- coding region or protein domains or (v) conditional association with disease MeSH terms. Currently the database contains 9261 (29.5%) inferred FREPs derived from 6861 (41.5%) mouse cDNAs. Integrated evidence of the functional assignments and dynamically generated sequence similarity search results support the exploration and annotation of functional, ancestral or taxon-specific repeats. Keyword and pre-selected feature searches (e.g. coding sequence-repeat or splice site-repeat relations) support intuitive database querying as well as the retrieval of repeat sequences. Integrated sequence search and alignment tools allow the analysis of known or identification of new functional repeat candidates. FREP is a unique resource for illuminating the role of transposons and repetitive sequences in shaping the coding part of the mouse transcriptome and for selecting the appropriate experimental model to study diseases with suspected repeat etiology contributions.

Animals↗
PubMed2001

Annotation: the cognitive neuroscience of face recognition: implications for developmental disorders.

Face recognition is often considered to be a modular (encapsulated) function. This annotation supports the proposal that faces are special, but suggests that their identification makes use of general-purpose cortical systems that are implicated in high-level vision and also in memory and learning more generally. These systems can be considered to function within two distinct cortical streams: a medial stream (for learning and salience of faces encountered) and a lateral stream (for distributed representations of visual properties and identities of faces). Function in the lateral stream, especially, may be critically dependent on the normal development of magnocellular vision. The relevance of face recognition anomalies in three developmental syndromes (Autism, Williams syndrome, and Turner syndrome) and the two-route model sketched above is considered.

Autistic Disorder↗
PubMed2003

Prediction of protein subcellular locations by support vector machines using compositions of amino acids and amino acid pairs.

MOTIVATION: The subcellular location of a protein is closely correlated to its function. Thus, computational prediction of subcellular locations from the amino acid sequence information would help annotation and functional prediction of protein coding genes in complete genomes. We have developed a method based on support vector machines (SVMs). RESULTS: We considered 12 subcellular locations in eukaryotic cells: chloroplast, cytoplasm, cytoskeleton, endoplasmic reticulum, extracellular medium, Golgi apparatus, lysosome, mitochondrion, nucleus, peroxisome, plasma membrane, and vacuole. We constructed a data set of proteins with known locations from the SWISS-PROT database. A set of SVMs was trained to predict the subcellular location of a given protein based on its amino acid, amino acid pair, and gapped amino acid pair compositions. The predictors based on these different compositions were then combined using a voting scheme. Results obtained through 5-fold cross-validation tests showed an improvement in prediction accuracy over the algorithm based on the amino acid composition only. This prediction method is available via the Internet.

Algorithms↗
PubMed2025

Deep learning-based annotation of plant abiotic stress resistance genes for crops.

The declining costs of DNA sequencing have expanded genomic data, crucial for understanding plant abiotic stress responses and crop improvement. However, accurate gene annotation remains challenging. To address this limitation, we propose the PASRGA, a deep learning approach that leverages transfer learning and contrastive learning to annotate genes related to drought, salt, cold, and UV resistance. PASRGA achieves high F1-scores, area under the receiver operating characteristic (AUROC), area under the precision-recall curve (AUPRC), and Matthews correlation coefficient (MCC) in annotating stress resistance genes, significantly outperforming the general protein annotation model CLEAN, the plant phosphatase gene annotation model PF-NET, the top-ranked model in the CAFA5 challenge NetGO 4.0, and four traditional machine learning methods. Its effectiveness was further validated with a salt stress treatment experiment in Eutrema salsugineum. To facilitate crop breeding practices, we utilized PASRGA to annotate the genomes of 17 major crops. To improve accessibility and utility, we incorporated both manually curated and PASRGA-predicted gene data, together with the PASRGA tool, into the PlantASRG database (https://bioinfor.nefu.edu.cn/PlantASRG/). This comprehensive resource aims to support crop breeding initiatives and ensure food security.

Crops, Agricultural↗
PubMed2004

Improved techniques for the identification of pseudogenes.

MOTIVATION: Pseudogenes are the remnants of genomic sequences of genes which are no longer functional. They are frequent in most eukaryotic genomes, and an important resource for comparative genomics. However, pseudogenes are often mis-annotated as functional genes in sequence databases. Current methods for identifying pseudogenes include methods which rely on the presence of stop codons and frameshifts, as well as methods based on the ratio of non-silent to silent nucleotide substitution rates (dN/dS). A recent survey concluded that 50% of human pseudogenes have no detectable truncation in their pseudo-coding regions, indicating that the former methods lack sensitivity. The latter methods have been used to find sets of genes enriched for pseudogenes, but are not specific enough to accurately separate pseudogenes from expressed genes. RESULTS: We introduce a program called pseudogene inference from loss of constraint (PSILC) which incorporates novel methods for separating pseudogenes from functional genes. The methods calculate the log-odds score that evolution along the final branch of the gene tree to the query gene has been according to the following constraints: A neutral nucleotide model compared to a Pfam domain encoding model (PSILC(nuc/dom)); A protein coding model compared to a Pfam domain encoding model (PSILC(prot/dom)). Using the manual annotation of human chromosome 6, we show that both these methods result in a more accurate classification of pseudogenes than dN/dS when a Pfam domain alignment is available. AVAILABILITY: PSILC is available from http://www.sanger.ac.uk/Software/PSILC

Algorithms↗
PubMed2002

Gramene, a tool for grass genomics.

Gramene (http://www.gramene.org) is a comparative genome mapping database for grasses and a community resource for rice (Oryza sativa). It combines a semi-automatically generated database of cereal genomic and expressed sequence tag sequences, genetic maps, map relations, and publications, with a curated database of rice mutants (genes and alleles), molecular markers, and proteins. Gramene curators read and extract detailed information from published sources, summarize that information in a structured format, and establish links to related objects both inside and outside the database, providing seamless connections between independent sources of information. Genetic, physical, and sequence-based maps of rice serve as the fundamental organizing units and provide a common denominator for moving across species and genera within the grass family. Comparative maps of rice, maize (Zea mays), sorghum (Sorghum bicolor), barley (Hordeum vulgare), wheat (Triticum aestivum), and oat (Avena sativa) are anchored by a set of curated correspondences. In addition to sequence-based mappings found in comparative maps and rice genome displays, Gramene makes extensive use of controlled vocabularies to describe specific biological attributes in ways that permit users to query those domains and make comparisons across taxonomic groups. Proteins are annotated for functional significance using gene ontology terms that have been adopted by numerous model species databases. Genetic variants including phenotypes are annotated using plant ontology terms common to all plants and trait ontology terms that are specific to rice. In this paper, we present a brief overview of the search tools available to the plant research community in Gramene.

Avena↗
PubMed2026

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↗
PubMed1998

Predicting functions from protein sequences--where are the bottlenecks?

The exponential growth of sequence data does not necessarily lead to an increase in knowledge about the functions of genes and their products. Prediction of function using comparative sequence analysis is extremely powerful but, if not performed appropriately, may also lead to the creation and propagation of assignment errors. While current homology detection methods can cope with the data flow, the identification, verification and annotation of functional features need to be drastically improved.

Amino Acid Sequence↗
PubMed2001

A comprehensive BAC resource.

The Human Genome Project has generated extensive map and sequence data for a large number of Bacterial Artificial Chromosome (BAC) clones. In order to maximize the efficient use of the data and to minimize the redundant work for the research community, The Institute for Genomic Research (TIGR) comprehensive BAC resource (cBACr) (http://www.tigr.org/tdb/BacResource/BAC_resourc e_intro. html) was built as an expansion of the TIGR human BAC ends database. This resource collects, integrates and reports the information on library, maps, sequence, annotation and functions for each human and mouse BAC. The current database contains 635 016 human BACs and 265 617 mouse BACs that were characterized by various approaches, among which 22 705 human clones and 1000 mouse clones have sequence and annotation data.

Animals↗
PubMed2004

Genome-wide high-throughput screens in functional genomics.

The availability of complete genome sequences from many organisms has yielded the ability to perform high-throughput, genome-wide screens of gene function. Within the past year, rapid advances have been made towards this goal in many major model systems, including yeast, worms, flies, and mammals. Yeast genome-wide screens have taken advantage of libraries of deletion strains, but RNA-interference has been used in other organisms to knockdown gene function. Examples of recent large-scale functional genetic screens include drug-target identification in yeast, regulators of fat accumulation in worms, growth and viability in flies, and proteasome-mediated degradation in mammalian cells. Within the next five years, such screens are likely to lead to annotation of function of most genes across multiple organisms. Integration of such data with other genomic approaches will extend our understanding of cellular networks.

Animals↗
PubMed2001

High-resolution BAC-based map of the central portion of mouse chromosome 5.

The current strategy for sequencing the mouse genome involves the combination of a whole-genome shotgun approach with clone-based sequencing. High-resolution physical maps will provide a foundation for assembling contiguous segments of sequence. We have established a bacterial artificial chromosome (BAC)-based map of a 5-Mb region on mouse Chromosome 5, encompassing three gene families: receptor tyrosine kinases (PdgfraKit-Kdr), nonreceptor protein-tyrosine type kinases (Tec-Txk), and type-A receptors for the neurotransmitter GABA (Gabra2, Gabrb1, Gabrg1, and Gabra4). The construction of a BAC contig was initiated by hybridization screening the C57BL/6J (RPCI-23) BAC library, using known genes and sequence tagged sites (STSs). Additional overlapping clones were identified by searching the database of available restriction fingerprints for the RPCI-23 and RPCI-24 libraries. This effort resulted in the selection of >600 BAC clones, 251 kb of BAC-end sequences, and the placement of 40 known and/or predicted genes within this 5-Mb region. We use this high-resolution map to illustrate the integration of the BAC fingerprint map with a radiation-hybrid map via assembled expressed sequence tags (ESTs). From annotation of three representative BAC clones we demonstrate that up to 98% of the draft sequence for each contig could be ordered and oriented using known genes, BAC ends, consensus sequences for transcript assemblies, and comparisons with orthologous human sequence. For functional studies, annotation of sequence fragments as they are assembled into 50-200-kb stretches will be remarkably valuable.

Animals↗
PubMed2001

PlantsP: a functional genomics database for plant phosphorylation.

The PlantsP database is a curated database that combines information derived from sequences with experimental functional genomics information. PlantsP focuses on plant protein kinases and protein phosphatases. The database will specifically provide a resource for information on a collection of T-DNA insertion mutants (knockouts) in each protein kinase and phosphatase in Arabidopsis thaliana. PlantsP also provides a curated view of each protein that includes a comprehensive annotation of functionally related sequence motifs, sequence family definitions, alignments and phylogenetic trees, and descriptive information drawn directly from the literature. PlantsP is available at http://PlantsP.sdsc.edu.

Arabidopsis↗
PubMed2000

From fold to function.

A number of recent advances have been made in deriving function information from protein structure. A fold relationship to an already characterized protein will often allow general information about function to be deduced. More detailed information can be obtained using sequence relationships to already studied proteins. Methods of deducing function directly from structure, without the use of evolutionary relationships, are developing rapidly. All such methods may be used with models of protein structure, rather than with experimentally determined ones, but model accuracy imposes limitations. The rapid expansion of the structural genomics field has created a new urgency for improved methods of structure-based annotation of function.

Animals↗
PubMed2025

CDACHIE: chromatin domain annotation by integrating chromatin interaction and epigenomic data with contrastive learning.

MOTIVATION: Chromatin domain annotation identifies functional genomic regions, such as active and inactive zones, based on epigenomic features like histone modifications, DNA methylation, and chromatin accessibility. While recent methods have utilized both chromatin interaction data (e.g. Hi-C) and epigenomic data, they often overlook the direct relationship between these data types. RESULTS: In this study, we introduce Chromatin Domain Annotation using Contrastive Learning for Hi-C and Epigenomic Data (CDACHIE), a method for identifying chromatin domains from Hi-C and epigenomic data. Our approach leverages contrastive learning to generate aligned representative vectors for both data types at each genomic bin. The concatenated vectors are then clustered using K-means to classify distinct chromatin domain types. CDACHIE achieves superior performance in Variance Explained, evaluated across gene expression, replication timing, and ChIA-PET data. This highlights its robust ability to integrate semantic associations between Hi-C and epigenomic features within the embedding space. AVAILABILITY AND IMPLEMENTATION: The source code is available at GitHub: https://github.com/maruyama-lab-design/CDACHIE. An archival snapshot of the code used in this study is available on Zenodo: https://doi.org/10.5281/zenodo.15751780.

Chromatin↗
PubMed2025

Fishing for a reelGene: evaluating gene models with evolution and machine learning.

Assembled genomes and their associated annotations have transformed our study of gene function. However, each new annotated assembly generates new gene models. Inconsistencies between annotations likely arise from biological and technical causes, including pseudogene misclassification, transposon activity, and intron retention from sequencing of unspliced transcripts. To evaluate gene model predictions, we developed reelGene, a pipeline of machine learning models focused on (1) transcription boundaries, (2) mRNA integrity, and (3) protein structure. The first two models leverage sequence characteristics and evolutionary conservation across related taxa to learn the grammar of conserved transcription boundaries and mRNA sequences, while the third uses the conserved evolutionary grammar of protein sequences to predict whether a gene can produce a protein. Evaluating 1.8 million transcript models in Zea mays ssp. mays (maize), reelGene classified 28% as incorrectly annotated or non-functional. We find that reelGene classifies 92.2% of genes in the maize proteome and 99.2% of genes within the maize classical gene list as functional. reelGene also provides a way to further investigate genome biology- for instance, reelGene indicates that 10.3% of dispensable genes in B73 are functional, and within retained duplicate genes, reelGene identifies a 30% bias toward the retention of the M1 subgenome when one copy is functional and the other is non-functional. As an annotation-evaluating tool, reelGene is directly applicable to species of the Andropogoneae tribe, including other important crops like sorghum and miscanthus. As a community resource, reelGene has been integrated onto MaizeGDB both as a browser track and as an individual Shiny App, allowing researchers to evaluate gene model accuracy and further investigate genome biology.

Machine Learning↗
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↗
PubMed2026

Transcriptomic responses of Porphyrophora sophorae larvae during licorice root colonization reveal coordinated remodeling of translation, mitochondrial energy metabolism and defense-related genes.

BACKGROUND: Porphyrophora sophorae is a subterranean piercing-sucking scale insect that damages licorice (Glycyrrhiza uralensis) roots, but the molecular responses associated with larval root colonization remain insufficiently defined. METHODS: We compared non-parasitic larvae (NP) and root-colonizing larvae (RC) using six RNA-seq libraries, de novo transcriptome assembly, DESeq2-based differential expression analysis, GO/KEGG enrichment, annotation-based candidate gene screening, and RT-qPCR validation of selected genes. RESULTS: Sequencing yielded 260.91 million clean reads, and de novo assembly produced 60,794 non-redundant transcripts. DESeq2 identified 703 FDR-significant DEGs, including 49 upregulated and 654 downregulated genes in RC larvae. Upregulated genes were mainly associated with translation- and ribosome-related processes, whereas downregulated genes were enriched in mitochondrial, oxidation-reduction, energy metabolism, and oxidative phosphorylation-related functions. Annotation-based screening identified 75 FDR-significant candidate genes associated with chemosensation, defense-related responses, and energy metabolism, with mitochondrial energy metabolism-related genes forming the largest module. RT-qPCR validation based on the raw Ct data showed concordant expression directions for ten selected transcript targets. CONCLUSIONS: Root colonization in P. sophorae larvae was associated with coordinated transcriptional remodeling involving selective activation of translation-related processes, adjustment of mitochondrial energy metabolism, and changes in defense-related gene expression. These results provide candidate molecular targets for future functional studies of host contact, feeding establishment, and physiological adjustment in this subterranean scale insect.

Animals↗
PubMed2001

Functional information in SWISS-PROT: the basis for large-scale characterisation of protein sequences.

With the rapid growth of sequence databases, there is an increasing need for reliable functional characterisation and annotation of newly predicted proteins. To cope with such large data volumes, faster and more effective means of protein sequence characterisation and annotation are required. One promising approach is automatic large-scale functional characterisation and annotation, which is generated with limited human interaction. However, such an approach is heavily dependent on reliable data sources. The SWISS-PROT protein sequence database plays an essential role here owing to its high level of functional information.

Animals↗