Search PubMed⌕ Search

SEARCH · Search PubMed

Results for “Data annotation”

Search indexed PubMed citations on genomics, clinical trials, systematic reviews and public health. Explore titles, authors and supplied subject terms, then open the PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,081 records · Page 60Linked to original sources

DNA transposons in vertebrate functional genomics.

Genome sequences of many model organisms of developmental or agricultural importance are becoming available. The tremendous amount of sequence data is fuelling the next phases of challenging research: annotating all genes with functional information, and devising new ways for the experimental manipulation of vertebrate genomes. Transposable elements are known to be efficient carriers of foreign DNA into cells. Notably, members of the Tc1/mariner and the hAT transposon families retain their high transpositional activities in species other than their hosts. Indeed, several of these elements have been successfully used for transgenesis and insertional mutagenesis, expanding our abilities in genome manipulations in vertebrate model organisms. Transposon-based genetic tools can help scientists to understand mechanisms of embryonic development and pathogenesis, and will likely contribute to successful human gene therapy. We discuss the possibilities of transposon-based techniques in functional genomics, and review the latest results achieved by the most active DNA transposons in vertebrates. We put emphasis on the evolution and regulation of members of the best-characterized and most widely used Tc1/mariner family.

Animals↗

Microdissection, mRNA amplification and microarray: a study of pleural mesothelial and malignant mesothelioma cells.

The studies of molecular alterations in tumor cells with microarrays are often hampered by inherent tissue heterogeneity. The emergence of Laser Capture Microdissection (LCM) allowed us to overcome this challenge since it gives selective access to cancer cells that are isolated from their native tissue environment. In this report, we microdissected mesothelial cells and malignant mesothelioma cells of ex vivo resected specimens using LCM. Amplified RNA from mesothelial and mesothelioma microdissected cells allowed us to measure global gene expression with 10 K-microarrays in four independent experiments. We screened 9850 annotated human genes, 1275 of which have satisfied our data analysis requirements. They included 302 overexpressed genes and 160 downregulated genes in mesothelioma microdissected cells as compared to mesothelial microdissected cells. Among them, the expression levels of eight genes, namely BF, FTL, IGFBP7, RARRES1, RARRES2, RBP1, SAT, and TXN according to HUGO nomenclature, were increased, whereas six: ALOX5AP, CLNS1A, EIF4A2, ELK3, REQ and SYPL, were found to be underexpressed in mesothelioma microdissected cells. The ferritin light polypeptide (FTL) gene overexpression was confirmed by real time quantitative PCR. Our approach allowed a comprehensive in situ examination of mesothelioma and provided an accurate way to find new marker genes that may be useful for diagnosis and treatment of malignant pleural mesothelioma.

Epithelium↗

Parasite genomes.

The availability of genome sequences and the associated transcriptome and proteome mapping projects has revolutionised research in the field of parasitology. As more parasite species are sequenced, comparative and phylogenetic comparisons are improving the quality of gene prediction and annotation. Genome sequences of parasites are also providing important data sets for understanding parasite biology and identifying new vaccine candidates and drug targets. We review some of the preliminary conclusions from examination of parasite genome sequences and discuss some of the bioinformatics approaches taken in this analysis.

Animals↗

The current and future perspective of ChickenGTEx project and its applications in precision breeding.

The Chicken Genotype-Tissue Expression (ChickenGTEx) project was established to systematically characterize the regulatory landscape of the chicken genome and to accelerate the translation of functional genomics into precision breeding. By integrating whole-genome sequencing with multi-tissue transcriptomic profiling, ChickenGTEx provides a comprehensive atlas of gene expression regulation across diverse tissues and physiological systems. Current findings demonstrate that complex production traits are governed by coordinated regulatory networks rather than isolated loci, with substantial contributions from tissue-specific gene expression, structural variation, and genotype-by-sex interactions. Sex-dependent regulatory effects further refine the genetic architecture of metabolic, immune, and reproductive traits, highlighting the importance of incorporating sex as a biological variable in genomic analyses. Application of integrative omics frameworks within elite layer populations has revealed multilayer regulatory mechanisms underlying extended laying performance, feed efficiency, metabolic health, and eggshell quality. By partitioning phenotypic variance into genetic, regulatory, and host-microbiome components, these approaches move beyond association-based mapping toward causal inference and biological interpretation. Importantly, validated regulatory loci identified through ChickenGTEx and related analyses provide actionable markers for genomic selection and rational targets for precision genome modification. Looking forward, continued expansion of regulatory atlases, incorporation of single-cell and longitudinal data in diverse environmental conditions, and integration of functional annotation into breeding pipelines will further enhance prediction accuracy and sustainable genetic improvement. The ChickenGTEx project thus represents a foundational platform bridging functional genomics and practical poultry breeding.

Animals↗

Fulfilling the promise: drug discovery in the post-genomic era.

The genomic era has brought with it a basic change in experimentation, enabling researchers to look more comprehensively at biological systems. The sequencing of the human genome coupled with advances in automation and parallelization technologies have afforded a fundamental transformation in the drug target discovery paradigm, towards systematic whole genome and proteome analyses. In conjunction with novel proteomic techniques, genome-wide annotation of function in cellular models is possible. Overlaying data derived from whole genome sequence, expression and functional analysis will facilitate the identification of causal genes in disease and significantly streamline the target validation process. Moreover, several parallel technological advances in small molecule screening have resulted in the development of expeditious and powerful platforms for elucidating inhibitors of protein or pathway function. Conversely, high-throughput and automated systems are currently being used to identify targets of orphan small molecules. The consolidation of these emerging functional genomics and drug discovery technologies promises to reap the fruits of the genomic revolution.

Animals↗

Chromosome-level genome assembly with telomeric repeats at scaffold ends for Rhabdosargus sarba.

Rhabdosargus sarba, the goldlined seabream, is a euryhaline marine fish of great aquaculture potential. Genome sequencing and assembly of R. sarba was carried utilizing a multi-platform sequencing strategy that included long-read sequencing (PacBio HiFi), short-read sequencing (Illumina), and chromatin interaction mapping (Hi-C). The final genome assembly size after scaffolding was 764.59 Mb in 31 scaffolds with an N50 length of 33.98 Mb. Repeat profiling of primary assembly showed that 28.71% of the genome comprises of repeat elements. Gene prediction utilising the evidence from ab initio prediction and transcriptome data revealed 26,913 protein encoding genes and functional annotation and pathway analysis showed their participation in 332 pathways. This genome is an excellent resource for future research on genetic improvement and molecular breeding programmes for R. sarba.

Animals↗

Gene expression during formation of earlywood and latewood in loblolly pine: expression profiles of 350 genes.

The natural variability of wood formation in trees affords opportunities to correlate transcript profiles with the resulting wood properties. We have used cDNA microarrays to study transcript abundance in developing secondary xylem of loblolly pine (Pinus taeda) over a growing season. The cDNAs were selected from a collection of 75 000 ESTs that have been sequenced and annotated (http://web.ahc.umn.edu/biodata/nsfpine/). Cell wall thickness and climatic data were related to earlywood and latewood formation at different time points during the growing season. Seventy-one ESTs showed preferential expression in earlywood or latewood, including 23 genes with no significant similarity to genes in GenBank. Seven genes involved in lignin synthesis were preferentially expressed in latewood. The studies have provided initial insights into the variation of expression patterns of some of the genes related to the wood formation process.

Expressed Sequence Tags↗

PRISM, a generic large scale proteomic investigation strategy for mammals.

We have developed a systematic analytical approach, termed PRISM (Proteomic Investigation Strategy for Mammals), that permits routine, large scale protein expression profiling of mammalian cells and tissues. PRISM combines subcellular fractionation, multidimensional liquid chromatography-tandem mass spectrometry-based protein shotgun sequencing, and two newly developed computer algorithms, STATQUEST and GOClust, as a means to rapidly identify, annotate, and categorize thousands of expressed mammalian proteins. The application of PRISM to adult mouse lung and liver resulted in the high confidence identification of over 2,100 unique proteins including more than 100 integral membrane proteins, 400 nuclear proteins, and 500 uncharacterized proteins, the largest proteome study carried out to date on this important model organism. Automated clustering of the identified proteins into Gene Ontology annotation groups allowed for streamlined analysis of the large data set, revealing interesting and physiologically relevant patterns of tissue and organelle specificity. PRISM therefore offers an effective platform for in-depth investigation of complex mammalian proteomes.

Animals↗

Serial analysis of gene expression in Plasmodium falciparum reveals the global expression profile of erythrocytic stages and the presence of anti-sense transcripts in the malarial parasite.

Serial analysis of gene expression (SAGE) was applied to the malarial parasite Plasmodium falciparum to characterize the comprehensive transcriptional profile of erythrocytic stages. A SAGE library of approximately 8335 tags representing 4866 different genes was generated from 3D7 strain parasites. Basic local alignment search tool analysis of high abundance SAGE tags revealed that a majority (88%) corresponded to 3D7 sequence, and despite the low complexity of the genome, 70% of these highly abundant tags matched unique loci. Characterization of these suggested the major metabolic pathways that are used by the organism under normal culture conditions. Furthermore several tags expressed at high abundance (30% of tags matching to unique loci of the 3D7 genome) were derived from previously uncharacterized open reading frames, demonstrating the use of SAGE in genome annotation. The open platform "profiling" nature of SAGE also lead to the important discovery of a novel transcriptional phenomenon in the malarial pathogen: a significant number of highly abundant tags that were derived from annotated genes (17%) corresponded to antisense transcripts. These SAGE data were validated by two independent means, strand specific reverse transcription-polymerase chain reaction and Northern analysis, where antisense messages were detected in both asexual and sexual stages. This finding has implications for transcriptional regulation of Plasmodium gene expression.

Animals↗

Utilization of long-read sequencing for the detection of structural rearrangements with AgileStructure.

MOTIVATION: Changes in genome organisation contribute to genetic disease when they disrupt gene function or regulation. Structural rearrangements may interrupt coding sequence or alter expression through promoter loss or gain, chromatin changes, copy-number variation, or disruption of short-range regulatory elements. Although short-read sequencing excels at detecting small variants, it performs poorly at resolving breakpoints of large rearrangements, especially in repetitive or low-complexity regions. Long-read sequencing overcomes these limitations, but analytical tools have not kept pace, making accurate identification and annotation of large structural variants challenging. RESULTS: We developed AgileStructure, a desktop application for locating and annotating large‑scale genomic rearrangements using aligned long‑read data. The software enables user‑guided exploration of breakpoint‑spanning reads, supporting accurate interpretation of complex events and filling a key gap in current structural variant analysis workflows. AVAILABILITY AND IMPLEMENTATION: Source code, binaries, user guide, and example aligned read data, are available on GitHub: https://github.com/msjimc/AgileStructure. An archived version is also available on Zenodo at https://doi.org/10.5281/zenodo.18610110.

Software↗

Mining gene expression data based on template theory.

MOTIVATION: It is understood that clustering genes are useful for exploring scientific knowledge from DNA microarray gene expression data. The explored knowledge can be finally used for annotating biological function for novel genes. Representing the explored knowledge in an efficient manner is then closely related to the classification accuracy. However, this issue has not yet been paid the attention it deserves. RESULT: A novel method based on template theory in cognitive psychology and pattern recognition is developed in this study for representing knowledge extracted from cluster analysis effectively. The basic principle is to represent knowledge according to the relationship between genes and a found cluster structure. Based on this novel knowledge representation method, a pattern recognition algorithm (the decision tree algorithm C4.5) is then used to construct a classifier for annotating biological functions of novel genes. The experiments on five published datasets show that this method has improved the classification performance compared with the conventional method. The statistical tests indicate that this improvement is significant. AVAILABILITY: The software package can be obtained upon request from the author.

Algorithms↗

Combo: a whole genome comparative browser.

SUMMARY: Combo is a comparative genome browser that provides a dynamic view of whole genome alignments along with their associated annotations. Combo provides two different visualization perspectives. The perpendicular (dot plot) view provides a dot plot of genome alignments synchronized with a display of genome annotations along each axis. The parallel view displays two genome annotations horizontally, synchronized through a panel displaying local alignments as trapezoids. Users can zoom to any resolution, from whole chromosomes to individual bases. They can select, highlight and view detailed information from specific alignments and annotations. Combo is an organism agnostic and can import data from a variety of file formats. AVAILABILITY: Combo is integrated as part of the Argo Genome Browser which also provides single-genome browsing and editing capabilities. Argo is written in Java, runs on multiple platforms and is freely available for download at http://www.broad.mit.edu/annotation/argo/.

Algorithms↗

PDBsum: summaries and analyses of PDB structures.

PDBsum is a web-based database providing a largely pictorial summary of the key information on each macromolecular structure deposited at the Protein Data Bank (PDB). It includes images of the structure, annotated plots of each protein chain's secondary structure, detailed structural analyses generated by the PROMOTIF program, summary PROCHECK results and schematic diagrams of protein-ligand and protein-DNA interactions. RasMol scripts highlight key aspects of the structure, such as the protein's domains, PROSITE patterns and protein-ligand interactions, for interactive viewing in 3D. Numerous links take the user to related sites. PDBsum is updated whenever any new structures are released by the PDB and is freely accessible via http://www.biochem.ucl.ac.uk/bsm/pdbsum.

Computer Graphics↗

ALFRED: the ALelle FREquency Database. Update.

Elaboration of ALFRED (http://alfred.med.yale.edu) is being continued in two directions. One of which is developing tools for efficiently annotating the entries and checking the integrity of the data already in the database while the other is to increase the quantity and accessibility of data. Information contained in ALFRED such as, polymorphic sites, number of populations and frequency tables (one sample typed for one site) has significantly increased.

Alleles↗

MGD: the Mouse Genome Database.

The Mouse Genome Database (MGD) (http://www.informatics.jax.org) one component of a community database resource for the laboratory mouse, a key model organism for interpreting the human genome and for understanding human biology. MGD strives to provide an extensively integrated information resource with experimental details annotated from both literature and on-line genomic data sources. MGD curates and presents the consensus representation of genotype (sequence) to phenotype information including highly detailed information about genes and gene products. Primary foci of integration are through representations of relationships between genes, sequences and phenotypes. MGD collaborates with other bioinformatics groups to curate a definitive set of information about the laboratory mouse. Recent developments include a general implementation of database structures for controlled vocabularies and the integration of a phenotype classification system.

Alleles↗

The ASAP II database: analysis and comparative genomics of alternative splicing in 15 animal species.

We have greatly expanded the Alternative Splicing Annotation Project (ASAP) database: (i) its human alternative splicing data are expanded approximately 3-fold over the previous ASAP database, to nearly 90,000 distinct alternative splicing events; (ii) it now provides genome-wide alternative splicing analyses for 15 vertebrate, insect and other animal species; (iii) it provides comprehensive comparative genomics information for comparing alternative splicing and splice site conservation across 17 aligned genomes, based on UCSC multigenome alignments; (iv) it provides an approximately 2- to 3-fold expansion in detection of tissue-specific alternative splicing events, and of cancer versus normal specific alternative splicing events. We have also constructed a novel database linking orthologous exons and orthologous introns between genomes, based on multigenome alignment of 17 animal species. It can be a valuable resource for studies of gene structure evolution. ASAP II provides a new web interface enabling more detailed exploration of the data, and integrating comparative genomics information with alternative splicing data. We provide a set of tools for advanced data-mining of ASAP II with Pygr (the Python Graph Database Framework for Bioinformatics) including powerful features such as graph query, multigenome alignment query, etc. ASAP II is available at http://www.bioinformatics.ucla.edu/ASAP2.

Alternative Splicing↗

Bioinformatics and genomic medicine.

Bioinformatics is a rapidly emerging field of biomedical research. A flood of large-scale genomic and postgenomic data means that many of the challenges in biomedical research are now challenges in computational science. Clinical informatics has long developed methodologies to improve biomedical research and clinical care by integrating experimental and clinical information systems. The informatics revolution in both bioinformatics and clinical informatics will eventually change the current practice of medicine, including diagnostics, therapeutics, and prognostics. Postgenome informatics, powered by high-throughput technologies and genomic-scale databases, is likely to transform our biomedical understanding forever, in much the same way that biochemistry did a generation ago. This paper describes how these technologies will impact biomedical research and clinical care, emphasizing recent advances in biochip-based functional genomics and proteomics. Basic data preprocessing with normalization and filtering, primary pattern analysis, and machine-learning algorithms are discussed. Use of integrative biochip informatics technologies, including multivariate data projection, gene-metabolic pathway mapping, automated biomolecular annotation, text mining of factual and literature databases, and the integrated management of biomolecular databases, are also discussed.

Computational Biology↗

Transcriptome-Wide Root Causal Inference.

Root causal genes correspond to the first gene expression levels perturbed during pathogenesis by genetic or non-genetic factors. Targeting root causal genes has the potential to alleviate disease entirely by eliminating pathology near its onset. No existing algorithm discovers root causal genes from observational data alone. We therefore propose the Transcriptome-Wide Root Causal Inference (TWRCI) algorithm that identifies root causal genes and their causal graph using a combination of genetic variant and unperturbed bulk RNA sequencing data. TWRCI uses a novel competitive regression procedure to annotate cis and trans-genetic variants to the gene expression levels they directly cause. The algorithm simultaneously recovers a causal ordering of the expression levels to pinpoint the underlying causal graph and estimate root causal effects. TWRCI outperforms alternative approaches across a diverse group of metrics by directly targeting root causal genes while accounting for distal relations, linkage disequilibrium, patient heterogeneity and widespread pleiotropy. We demonstrate the algorithm by uncovering the root causal mechanisms of two complex diseases, which we confirm by replication using independent genome-wide summary statistics.

Journal Article↗