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At least 181 records · Page 10Linked to original sources

TACT: Transcriptome Auto-annotation Conducting Tool of H-InvDB.

Transcriptome Auto-annotation Conducting Tool (TACT) is a newly developed web-based automated tool for conducting functional annotation of transcripts by the integration of sequence similarity searches and functional motif predictions. We developed the TACT system by integrating two kinds of similarity searches, FASTY and BLASTX, against protein sequence databases, UniProtKB (Swiss-Prot/TrEMBL) and RefSeq, and a unified motif prediction program, InterProScan, into the ORF-prediction pipeline originally designed for the 'H-Invitational' human transcriptome annotation project. This system successively applies these constituent programs to an mRNA sequence in order to predict the most plausible ORF and the function of the protein encoded. In this study, we applied the TACT system to 19 574 non-redundant human transcripts registered in H-InvDB and evaluated its predictive power by the degree of agreement with human-curated functional annotation in H-InvDB. As a result, the TACT system could assign functional description to 12 559 transcripts (64.2%), the remainder being hypothetical proteins. Furthermore, the overall agreement of functional annotation with H-InvDB, including those transcripts annotated as hypothetical proteins, was 83.9% (16 432/19 574). These results show that the TACT system is useful for functional annotation and that the prediction of ORFs and protein functions is highly accurate and close to the results of human curation. TACT is freely available at http://www.jbirc.aist.go.jp/tact/.

Amino Acid Motifs↗

Reannotation of Shewanella oneidensis genome.

As more and more complete bacterial genome sequences become available, the genome annotation of previously sequenced genomes may become quickly outdated. This is primarily due to the discovery and functional characterization of new genes. We have reannotated the recently published genome of Shewanella oneidensis with the following results: 51 new genes have been identified, and functional annotation has been added to the 97 genes, including 15 new and 82 existing ones with previously unassigned function. The identification of new genes was achieved by predicting the protein coding regions using the HMM-based program GeneMark.hmm. Subsequent comparison of the predicted gene products to the non-redundant protein database using BLAST and the COG (Clusters of Orthologous Groups) database using COGNITOR provided for the functional annotation.

Algorithms↗

Whole genome sequencing analysis and functional characterization of Lacticaseibacillus rhamnosus HP-B1083.

Lacticaseibacillus rhamnosus is an important strain for the biotransformation of natural products, and its crude extract exhibits biotransformation effect on glycosidic compounds such as baicalin. To further explore the potential of this strain, particularly given its previously demonstrated high-efficiency β-glucuronidase activity for baicalin conversion, whole-genome sequencing and functional annotation of Lacticaseibacillus rhamnosus HP-B1083 were performed in this study, and its acid tolerance, bile salt tolerance, short-term heat resistance and antibacterial activity were evaluated. The results showed that the strain possessed a circular chromosome with a full length of 3,090,505 bp and a GC content of 46.69%. Gene annotation revealed that the genome contained 2941 coding sequences (CDS) and 112 non-coding RNA genes, including 60 tRNA genes, 1 tmRNA gene, 36 misc_RNA genes and 15 rRNA genes. The functional annotations further reveal that this genome is rich in genes related to carbohydrate metabolism, hydrolases, and transferases, which is highly consistent with its phenotypic characteristics in glycoside transformation and the synthesis of antibacterial substances. In addition, acid tolerance, bile salt tolerance and short-term heat resistance experiments verified that HP-B1083 had acid resistance, bile salt resistance and short-term heat resistance. Antibacterial activity tests confirmed that HP-B1083 produced inhibition zone diameters over 10 mm against common foodborne pathogenic bacteria such as Escherichia coli and Bacillus cereus. Therefore, Lacticaseibacillus rhamnosus HP-B1083 has important application prospects in the development of functional foods, preparation of enzyme preparations and pharmaceutical industry.

Whole Genome Sequencing↗

Integrative bioinformatics for functional genome annotation: trawling for G protein-coupled receptors.

G protein-coupled receptors (GPCR) are amongst the best studied and most functionally diverse types of cell-surface protein. The importance of GPCRs as mediates or cell function and organismal developmental underlies their involvement in key physiological roles and their prominence as targets for pharmacological therapeutics. In this review, we highlight the requirement for integrated protocols which underline the different perspectives offered by different sequence analysis methods. BLAST and FastA offer broad brush strokes. Motif-based search methods add the fine detail. Structural modelling offers another perspective which allows us to elucidate the physicochemical properties that underlie ligand binding. Together, these different views provide a more informative and a more detailed picture of GPCR structure and function. Many GPCRs remain orphan receptors with no identified ligand, yet as computer-driven functional genomics starts to elaborate their functions, a new understanding of their roles in cell and developmental biology will follow.

Algorithms↗

PolyMAPr: programs for polymorphism database mining, annotation, and functional analysis.

Pharmacogenomic and disease-association studies rely on identifying a comprehensive set of polymorphisms within candidate genes. Public SNP databases are a rich source of polymorphism data, but mining them effectively requires overcoming at least four challenges: ensuring accurate annotations for genes and polymorphisms, eliminating both inter- and intra-database redundancy, integrating data from multiple public sources with data generated locally, and prioritizing the variants for further study. PolyMAPr (Polymorphism Mining and Annotation Programs)' was developed to overcome these challenges and to improve the efficiency of database mining and polymorphism annotation. PolyMAPr takes as input a file containing a list of genes to be processed and files containing each annotated gene sequence. Polymorphic sequences obtained from public databases (dbSNP, CGAP, and JSNP) or through local SNP discovery efforts, as well as oligonucleotide sequences (e.g., PCR primers), are mapped to the annotated gene sequences and named according to suggested nomenclature guidelines. The functional effects of nonsynonymous coding-region SNPs (cSNPs) and any variants that might alter exon splicing enhancer (ESE) sites, putative transcription factor binding sites, or intron-exon splice sites are predicted. The output files are accessible though a browser interface. In addition, the results are also provided in Extensible Markup Language (XML) format to facilitate uploading them into a local relational database. PolyMAPr increases the efficiency of mining public databases for genetic variants within candidate genes and provides a mechanism by which data from multiple sources (both public and private) can be uniformly integrated, thereby significantly reducing the effort required to obtain a comprehensive set of polymorphisms for pharmacogenomic and disease-association studies. PolyMAPr can be obtained from http://pharmacogenomics.wustl.edu.

Databases, Nucleic Acid↗

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↗

GEPAS, an experiment-oriented pipeline for the analysis of microarray gene expression data.

The Gene Expression Profile Analysis Suite, GEPAS, has been running for more than three years. With >76,000 experiments analysed during the last year and a daily average of almost 300 analyses, GEPAS can be considered a well-established and widely used platform for gene expression microarray data analysis. GEPAS is oriented to the analysis of whole series of experiments. Its design and development have been driven by the demands of the biomedical community, probably the most active collective in the field of microarray users. Although clustering methods have obviously been implemented in GEPAS, our interest has focused more on methods for finding genes differentially expressed among distinct classes of experiments or correlated to diverse clinical outcomes, as well as on building predictors. There is also a great interest in CGH-arrays which fostered the development of the corresponding tool in GEPAS: InSilicoCGH. Much effort has been invested in GEPAS for developing and implementing efficient methods for functional annotation of experiments in the proper statistical framework. Thus, the popular FatiGO has expanded to a suite of programs for functional annotation of experiments, including information on transcription factor binding sites, chromosomal location and tissues. The web-based pipeline for microarray gene expression data, GEPAS, is available at http://www.gepas.org.

Algorithms↗

Systematic gene function prediction from gene expression data by using a fuzzy nearest-cluster method.

BACKGROUND: Quantitative simultaneous monitoring of the expression levels of thousands of genes under various experimental conditions is now possible using microarray experiments. However, there are still gaps toward whole-genome functional annotation of genes using the gene expression data. RESULTS: In this paper, we propose a novel technique called Fuzzy Nearest Clusters for genome-wide functional annotation of unclassified genes. The technique consists of two steps: an initial hierarchical clustering step to detect homogeneous co-expressed gene subgroups or clusters in each possibly heterogeneous functional class; followed by a classification step to predict the functional roles of the unclassified genes based on their corresponding similarities to the detected functional clusters. CONCLUSION: Our experimental results with yeast gene expression data showed that the proposed method can accurately predict the genes' functions, even those with multiple functional roles, and the prediction performance is most independent of the underlying heterogeneity of the complex functional classes, as compared to the other conventional gene function prediction approaches.

Algorithms↗

DAVID: Database for Annotation, Visualization, and Integrated Discovery.

BACKGROUND: Functional annotation of differentially expressed genes is a necessary and critical step in the analysis of microarray data. The distributed nature of biological knowledge frequently requires researchers to navigate through numerous web-accessible databases gathering information one gene at a time. A more judicious approach is to provide query-based access to an integrated database that disseminates biologically rich information across large datasets and displays graphic summaries of functional information. RESULTS: Database for Annotation, Visualization, and Integrated Discovery (DAVID; http://www.david.niaid.nih.gov) addresses this need via four web-based analysis modules: 1) Annotation Tool - rapidly appends descriptive data from several public databases to lists of genes; 2) GoCharts - assigns genes to Gene Ontology functional categories based on user selected classifications and term specificity level; 3) KeggCharts - assigns genes to KEGG metabolic processes and enables users to view genes in the context of biochemical pathway maps; and 4) DomainCharts - groups genes according to PFAM conserved protein domains. CONCLUSIONS: Analysis results and graphical displays remain dynamically linked to primary data and external data repositories, thereby furnishing in-depth as well as broad-based data coverage. The functionality provided by DAVID accelerates the analysis of genome-scale datasets by facilitating the transition from data collection to biological meaning.

Computational Biology↗

dcHiChIP: a comprehensive Nextflow-based pipeline for multiscale analysis of chromatin architecture from HiChIP data.

MOTIVATION: Despite the growing use of HiChIP to investigate protein-directed chromatin architecture, a comprehensive and reproducible pipeline for analysing these datasets-from raw reads to multiscale 3D genome features-remains lacking. Existing tools often focus on isolated components, such as loop calling or matrix generation, but fall short in integrating structural annotation, functional enrichment, and spatial modeling within a unified framework. To address this gap, we developed dcHiChIP, a modular, scalable Nextflow-based workflow that streamlines the analysis of HiChIP data, enabling both routine processing and in-depth exploration of chromatin organization and regulatory interactions. RESULTS: dcHiChIP enables robust and reproducible analysis of HiChIP datasets across multiple scales of chromatin architecture. It accepts raw sequencing data as input and generates high-quality loop calls, domain annotations, and 3D genome models. It also performs functional annotation and motif enrichment analyses. Applied to benchmark CTCF HiChIP datasets, dcHiChIP identifies major chromatin architectural features such as TADs/CCDs, A/B compartments, and chromatin stripes, and offers efficient, end-to-end execution with support for batch processing and workflow resumability. AVAILABILITY: dcHiChIP is publicly available on GitHub at https://github.com/SFGLab/dcHiChIP, with documentation at https://sfglab.github.io/dcHiChIP/. The software version used in this study is archived at Zenodo: https://doi.org/10.5281/zenodo.22030542.

Chromatin↗

Integrating functional genomics data.

Functional annotation of fully sequenced genomes is still a major issue. High-throughput data sets could be used to provide more and better functional annotations. However differences in data quality need to be taken into account. For this purpose these high-throughput data sets need to be integrated so that the data quality can be assessed, hypotheses can be prioritized and existing annotations can be improved and extended.

Computational Biology↗

Complex functionality of gene groups identified from high-throughput data.

Relating experimental data to biological knowledge is necessary to cope with the avalanches of new data emerging from recent developments in high-throughput technologies. Automatic functional profiling becomes the de facto standard approach for the secondary analysis of high-throughput data. A number of tools employing available gene functional annotations have been developed for this purpose. However, current annotations are derived mostly from traditional analysis of the individual gene function. The complex biological phenomena carried out by the concerted activity of many genes often requires the definition of new complex functionality (related to a group of genes), which is, in many cases, not available in current annotation vocabularies. Functional profiling with annotation terms related to the description of individual biological functions of a gene may fail to provide reasonable interpretation of biological relationships in a set of genes involved in complex biological phenomena. We introduce a novel procedure to profile a complex functionality of a gene set. Complex functionality is constructed as a combination of available annotation terms. By profiling ChIP-chip data from Saccharomyces cerevisiae we demonstrate that this technique produces deeper insights into the results of high-throughput experiments that are beyond the known facts described in the functional classifications.

Animals↗

ProtoBee: hierarchical classification and annotation of the honey bee proteome.

The recently sequenced genome of the honey bee (Apis mellifera) has produced 10,157 predicted protein sequences, calling for a computational effort to extract biological insights from them. We have applied an unsupervised hierarchical protein-clustering method, which was previously used in the ProtoNet system, to nearly 200,000 proteins consisting of the predicted honey bee proteins, the SWISS-PROT protein database, and the complete set of proteins of the mouse (Mus musculus) and the fruit fly (Drosophila melanogaster). The hierarchy produced by this method has been entitled ProtoBee. In ProtoBee, the proteins are hierarchically organized into 18,936 separate tree hierarchies, each representing a protein functional family. By using the mouse and Drosophila complete proteomes as reference, we are able to highlight functional groups of putative gene-loss events, putative novel proteins of unique functionality, and bee-specific paralogs. We have studied some of the ProtoBee findings and suggest their biological relevance. Examples include novel opsin genes and intriguing nuclear matches of mitochondrial genes. The organization of bee sequences into functional clusters suggests a natural way of automatically inferring functional annotation. Following this notion, we were able to assign functional annotation to about 70% of the sequences. ProtoBee is available at http://www.protobee.cs.huji.ac.il.

Animals↗

Benchmarking ortholog identification methods using functional genomics data.

BACKGROUND: The transfer of functional annotations from model organism proteins to human proteins is one of the main applications of comparative genomics. Various methods are used to analyze cross-species orthologous relationships according to an operational definition of orthology. Often the definition of orthology is incorrectly interpreted as a prediction of proteins that are functionally equivalent across species, while in fact it only defines the existence of a common ancestor for a gene in different species. However, it has been demonstrated that orthologs often reveal significant functional similarity. Therefore, the quality of the orthology prediction is an important factor in the transfer of functional annotations (and other related information). To identify protein pairs with the highest possible functional similarity, it is important to qualify ortholog identification methods. RESULTS: To measure the similarity in function of proteins from different species we used functional genomics data, such as expression data and protein interaction data. We tested several of the most popular ortholog identification methods. In general, we observed a sensitivity/selectivity trade-off: the functional similarity scores per orthologous pair of sequences become higher when the number of proteins included in the ortholog groups decreases. CONCLUSION: By combining the sensitivity and the selectivity into an overall score, we show that the InParanoid program is the best ortholog identification method in terms of identifying functionally equivalent proteins.

Algorithms↗

Genome-wide annotation of human multi-nucleotide variants reveals widespread functional differences from single nucleotide variants.

Multi-nucleotide variants (MNVs) represent a crucial yet underexplored category of genetic variation. Despite previous studies highlighting the prevalence and potential biological impact of MNVs in populations, comprehensive identification and detailed functional annotation of MNVs remain challenging. Here, we develop MNVAnno, a toolbox for rapid identification and annotation of complex MNVs, and utilize it to identify 3,984,258 MNVs from 700,134 human samples, expanding the human MNV list to 8,199,654. Our analysis reveals that MNVs can not only lead to distinct amino acid changes from their constituent single-nucleotide variants, but also significantly impact the function of non-coding regions. Furthermore, through genome-wide association studies, we identify some MNVs associated with multiple cancers, and establish the Human MNV Database to facilitate MNV research. Our study emphasizes the importance of MNV annotation, broadens the human MNV landscape, and opens avenues for exploring genetic variation in phenotypes and diseases.

Humans↗

Accurate prediction of scorpion toxin functional properties from primary structures.

Scorpion toxins are common experimental tools for studies of biochemical and pharmacological properties of ion channels. The number of functionally annotated scorpion toxins is steadily growing, but the number of identified toxin sequences is increasing at much faster pace. With an estimated 100,000 different variants, bioinformatic analysis of scorpion toxins is becoming a necessary tool for their systematic functional analysis. Here, we report a bioinformatics-driven system involving scorpion toxin structural classification, functional annotation, database technology, sequence comparison, nearest neighbour analysis, and decision rules which produces highly accurate predictions of scorpion toxin functional properties.

Algorithms↗

SeqHound: biological sequence and structure database as a platform for bioinformatics research.

BACKGROUND: SeqHound has been developed as an integrated biological sequence, taxonomy, annotation and 3-D structure database system. It provides a high-performance server platform for bioinformatics research in a locally-hosted environment. RESULTS: SeqHound is based on the National Center for Biotechnology Information data model and programming tools. It offers daily updated contents of all Entrez sequence databases in addition to 3-D structural data and information about sequence redundancies, sequence neighbours, taxonomy, complete genomes, functional annotation including Gene Ontology terms and literature links to PubMed. SeqHound is accessible via a web server through a Perl, C or C++ remote API or an optimized local API. It provides functionality necessary to retrieve specialized subsets of sequences, structures and structural domains. Sequences may be retrieved in FASTA, GenBank, ASN.1 and XML formats. Structures are available in ASN.1, XML and PDB formats. Emphasis has been placed on complete genomes, taxonomy, domain and functional annotation as well as 3-D structural functionality in the API, while fielded text indexing functionality remains under development. SeqHound also offers a streamlined WWW interface for simple web-user queries. CONCLUSIONS: The system has proven useful in several published bioinformatics projects such as the BIND database and offers a cost-effective infrastructure for research. SeqHound will continue to develop and be provided as a service of the Blueprint Initiative at the Samuel Lunenfeld Research Institute. The source code and examples are available under the terms of the GNU public license at the Sourceforge site http://sourceforge.net/projects/slritools/ in the SLRI Toolkit.

Amino Acid Sequence↗

Annotation and BAC/PAC localization of nonredundant ESTs from drought-stressed seedlings of an indica rice.

To decipher the genes associated with drought stress response and to identify novel genes in rice, we utilized 1540 high-quality expressed sequence tags (ESTs) for functional annotation and mapping to rice genomic sequences. These ESTs were generated earlier by 3'-end single-pass sequencing of 2000 cDNA clones from normalized cDNA libraries constructed form drought-stressed seedlings of an indica rice. A rice UniGene set of 1025 transcripts was constructed from this collection through the BLASTN algorithm. Putative functions of 559 nonredundant ESTs were identified by BLAST similarity search against public databases. Putative functions were assigned at a stringency E value of 10(-6) in BLASTN and BLASTX algorithms. To understand the gene structure and function further, we have utilized the publicly available finished and unfinished rice BAC/PAC (BAC, bacterial artificial chromosome; PAC, P1 artificial chromosome) sequences for similarity search using the BLASTN algorithm. Further, 603 nonredundant ESTs have been mapped to BAC/PAC clones. BAC clones were assigned by a homology of above 95% identity along 90% of EST sequence length in the aligned region. In all, 700 ESTs showed rice EST hits in GenBank. Of the 325 novel ESTs, 128 were localized to BAC clones. In addition, 127 ESTs with identified putative functions but with no homology in IRGSP (International Rice Genome Sequencing Program) BAC/PAC sequences were mapped to the Chinese WGS (whole genome shotgun contigs) draft sequence of the rice genome. Functional annotation uncovered about a hundred candidate ESTs associated with abiotic stress in rice and Arabidopsis that were previously reported based on microarray analysis and other studies. This study is a major effort in identifying genes associated with drought stress response and will serve as a resource to rice geneticists and molecular biologists.

Chromosomes, Artificial, Bacterial↗