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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

DeNoFo: a file format and toolkit for standardized, comparable de novo gene annotation.

MOTIVATION: De novo genes emerge from previously non-coding regions of the genome, challenging the traditional view that new genes primarily arise through duplication and adaptation of existing ones. Characterized by their rapid evolution and their novel structural properties or functional roles, de novo genes represent a young area of research. Therefore, the field currently lacks established standards and methodologies, leading to inconsistent terminology and challenges in comparing and reproducing results. RESULTS: This work presents a standardized annotation format to document the methodology of de novo gene datasets in a reproducible way. We developed DeNoFo, a toolkit to provide easy access to this format that simplifies annotation of datasets and facilitates comparison across studies. Unifying the different protocols and methods in one standardized format, while providing integration into established file formats, such as fasta or gff, ensures comparability of studies and advances new insights in this rapidly evolving field. AVAILABILITY AND IMPLEMENTATION: DeNoFo is available through the official Python Package Index (PyPI) and at https://github.com/EDohmen/denofo. All tools have a graphical user interface and a command line interface. The toolkit is implemented in Python3, available for all major platforms and installable with pip and uv.

Software↗

PubMed2026

Segzoo: a turnkey system that summarizes genome annotations.

MOTIVATION: Segmentation and automated genome annotation (SAGA) techniques, such as Segway and ChromHMM, assign labels to every part of the genome, identifying similar patterns across multiple genomic input signals. Inferring biological meaning in these patterns remains challenging. Doing so requires a time-consuming process of manually downloading reference data, running multiple analysis methods, and interpreting many individual results. RESULTS: To simplify these tasks, we developed the turnkey system Segzoo. As input, Segzoo only requires a genome annotation file in browser extensible data (BED) format. It automatically downloads the rest of the data required for comparisons. Segzoo performs analyses using these data and summarizes results in a single visualization. AVAILABILITY AND IMPLEMENTATION: The source code for Python ≥ 3.7 on Linux is freely available for download at https://github.com/hoffmangroup/segzoo under the GNU General Public License (GPL) version 2. Segzoo is also available in the Bioconda package segzoo: https://anaconda.org/bioconda/segzoo. We have deposited in Zenodo the version of the Segzoo source which produced the results in this article (https://doi.org/10.5281/zenodo.10988775), other code and data used to produce the results (https://doi.org/10.5281/zenodo.10477083), and the results (https://doi.org/10.5281/zenodo.10477106).

Software↗

PubMed2026

needLR: long-read structural variant annotation with population-scale frequency estimation.

SUMMARY: We present needLR, a structural variant (SV) annotation tool that can be used for filtering and prioritization of candidate pathogenic SVs from long-read sequencing data using population allele frequencies, annotations for genomic context, and gene-phenotype associations. When using population data from 500 presumably healthy individuals to evaluate nine test cases with known pathogenic SVs, needLR assigned allele frequencies to over 97.5% of all detected SVs and reduced the average number of novel genic SVs to 121 per case while retaining all known pathogenic variants. AVAILABILITY AND IMPLEMENTATION: needLR is implemented in bash with dependencies including Truvari v4.2.2, BEDTools v2.31.1, and BCFtools v1.19. Source code, documentation, and pre-computed population allele frequency data are freely available at https://github.com/jgust1/needLR under an MIT license and archived on Zenodo at https://zenodo.org/records/19463479.

Software↗

PubMed2026

Chromosome-Level Genome Assembly and Annotation of the Chinese Lizard Gudgeon (Saurogobio dabryi).

The Chinese lizard gudgeon (Saurogobio dabryi) is an economically important freshwater species within the Cyprinidae family, abundant in the middle and lower reaches of the Yangtze River and its adjacent basins. As a promising species suitable for aquaculture in China, the lack of genomic resources has rendered the genetic breeding and conservation research. Here, we present the first chromosome-level genome assembly of S. dabryi using PacBio HiFi long reads, short reads, and Hi-C sequencing data. The final assembly reaches a total size of 1.09 Gb and Hi-C scaffolding anchors 99.55% of the assembled contigs onto 25 chromosomes, with a scaffold N50 reaching 43.15 Mb. The final genome assembly shows a BUSCO completeness of 98.39%. We annotated 659.55 Mb repetitive sequences and 26,036 protein-coding genes, 99.47% of which are functionally annotated. Comparative phylogenomic analysis clarifies the phylogenetic position of Saurogobio within Gobioninae. This high-quality genome provides a critical genetic basis for exploring cyprinid phylogeny, benthic adaptive evolution, genetic improvement, and conservation efforts of S. dabryi.

Saurogobio dabryi↗

PubMed2026

Large-scale functional annotation establishes a reference framework for human LRRK2 variants.

Pathogenic variants in leucine-rich repeat kinase 2 (LRRK2)1are among the most frequent monogenic causes of Parkinson's disease (PD)2 and act through a gain-of-function mechanism of increased kinase activity. LRRK2-targeted therapies are in clinical development, but interpretation of the rapidly expanding catalogue of rare LRRK2 variants remains a barrier to translation. Here, we present functionally annotated data on >350 LRRK2 coding variants using a standardized cellular assay with Rab10 phosphorylation as a readout of kinase activity and integrated these data with curated genetic and clinical annotations from the Movement Disorders Society Genetic Mutation Database (MDSGene). Variants differed in activation magnitude, ranging from modest increases (e.g., p.G2019S) to strongly activating substitutions such as p.Y1699C or p.L1795F. Activating variants occurred across the full length of LRRK2, although the largest effects clustered within the ROC-COR regulatory hub, where structural analysis identified subdomains forming an allosteric scaffold controlling kinase output. All known/established pathogenic variants showed increased activity, whereas benign and likely benign variants remained within the wild-type range. Functional effect sizes correlated with pathway activation in patient-derived immune cells, altogether providing a framework for ACMG-based variant interpretation in which kinase activation can support PS3 functional evidence for reclassification of variants.

Protein phosphorylation↗

PubMed2001

Annotation of glycoproteins in the SWISS-PROT database.

SWISS-PROT is a protein sequence database, which aims to be nonredundant, fully annotated and highly cross-referenced. Most eukaryotic gene products undergo co- and/or post-translational modifications, and these need to be included in the database in order to describe the mature protein. SWISS-PROT includes information on many types of different protein modifications. As glycosylation is the most common type of post-translational protein modification, we are currently placing an emphasis on annotation of protein glycosylation in SWISS-PROT. Information on the position of the sugar within the polypeptide chain, the reducing terminal linkage as well as additional information on biological function of the sugar is included in the database. In this paper we describe how we account for the different types of protein glycosylation, namely N-linked glycosylation, O-linked glycosylation, proteoglycans, C-linked glycosylation and the attachment of glycosyl-phosphatidylinosital anchors to proteins.

Amino Acid Sequence↗

PubMed2004

Profiling and functional annotation of mRNA gene expression in pediatric rhabdomyosarcoma and Ewing's sarcoma.

Using Affymetrix oligonucleotide microarrays, we analyzed mRNA gene expression patterns of 12 primary pediatric rhabdomyosarcomas (RMS) and 11 Ewing's sarcomas (EWS), which belong to the small round blue cell tumors (SRBCTs). Diagnostic classification of these cancers is frequently complicated by the highly similar appearance in routine histology, and additional molecular markers could significantly improve tumor classification. A combination of three independent statistical approaches (t-test, SAM, k-nearest neighborhood analysis) resulted in 101 highly significant probe sets that clearly discriminate between EWS and RMS. We identified novel marker transcripts that have not been previously associated with either RMS or EWS yet, including CITED2, glypican 3 (GPC3), and cyclin D1 (CCND1). Expression levels for selected candidate genes were validated by quantitative real-time reverse-transcription PCR. Furthermore, to identify biologically meaningful trends, functional annotations were assigned to 946 genes differentially expressed between EWS and RMS (t-test). Genes involved in protein biosynthesis (n = 28) and complex assembly (n = 9), lipid metabolism (n = 23), energy generation (n = 22), and mRNA processing (n = 11) were expressed significantly higher in EWS. Thus, functional annotation of tumor-specific genes reveals detailed insights into tumor biology and differentiation-specific expression patterns and gives important clues related to the possible cellular origin of these pediatric tumors. Supplementary material for this article is available at the International Journal of Cancer website at http://www.interscience.wiley.com/jpages/0020-7136/suppmat/index.html.

Biomarkers, Tumor↗

PubMed2007

RNAs everywhere: genome-wide annotation of structured RNAs.

Starting with the discovery of microRNAs and the advent of genome-wide transcriptomics, non-protein-coding transcripts have moved from a fringe topic to a central field research in molecular biology. In this contribution we review the state of the art of "computational RNomics", i.e., the bioinformatics approaches to genome-wide RNA annotation. Instead of rehashing results from recently published surveys in detail, we focus here on the open problem in the field, namely (functional) annotation of the plethora of putative RNAs. A series of exploratory studies are used to provide non-trivial examples for the discussion of some of the difficulties.

Biological Evolution↗

PubMed2004

Proteogenomic mapping as a complementary method to perform genome annotation.

The accelerated rate of genomic sequencing has led to an abundance of completely sequenced genomes. Annotation of the open reading frames (ORFs) (i.e., gene prediction) in these genomes is an important task and is most often performed computationally based on features in the nucleic acid sequence. Using recent advances in proteomics, we set out to predict the set of ORFs for an organism based principally on expressed protein-based evidence. Using a novel search strategy, we mapped peptides detected in a whole-cell lysate of Mycoplasma pneumoniae onto a genomic scaffold and extended these "hits" into ORFs bound by traditional genetic signals to generate a "proteogenomic map". We were able to generate an ORF model for M. pneumoniae strain FH using proteomic data with a high correlation to models based on sequence features. Ultimately, we detected over 81% of the genomically predicted ORFs in M. pneumoniae strain M129 (the originally sequenced strain). We were also able to detect several new ORFs not originally predicted by genomic methods, various N-terminal extensions, and some evidence that would suggest that certain predicted ORFs are bogus. Some of these differences may be a result of the strain analyzed but demonstrate the robustness of protein analysis across closely related genomes. This technique is a cost-effective means to add value to genome annotation, and a prerequisite for proteome quantitation and in vivo interaction measures.

Chromosome Mapping↗

PubMed1997

A tool for analyzing and annotating genomic sequences.

We describe a tool for analyzing and annotating large genomic sequences containing introns. The analysis and annotation tool (AAT) includes two sets of programs, one for comparing the query sequence with a protein database and the other for comparing the query with a cDNA database. Each set contains a fast database search program and a rigorous alignment program. The database search program quickly identifies regions of the query sequence that are similar to a database sequence. Then the alignment program constructs an optimal alignment for each region and the database sequence. The alignment program also reports the coordinates of exons in the query sequence. Pairwise alignments of the query sequence with protein and cDNA database sequences are combined into multiple sequence alignments, which provide a view of all protein and cDNA sequences matching a query region. On a data set of 570 DNA sequences, AAT identified 94% of coding nucleotides correctly and 74% of exons exactly. Results of analyzing a human BAC sequence with the AAT tool are also presented. The AAT tool reduces the labor-intensive work of locating the exons of the query sequence and improves the process of defining intron-exon boundaries by using the wealth of available protein and cDNA data.

Amino Acid Sequence↗

PubMed2002

Annotation of human chromosome 21 for relevance to Down syndrome: gene structure and expression analysis.

Down syndrome is caused by an extra copy of human chromosome 21 and the resultant dosage-related overexpression of genes contained within it. To efficiently direct experiments to determine specific gene-phenotype correlations, it is necessary to identify all genes within 21q and assess their functional associations and expression patterns. Analysis of the complete finished sequence of 21q resulted in annotated 225 genes and gene models, most of which were incomplete and/or had little or no experimental verification. Here we correct or complete the genomic structures of 16 genes, 4 of which were not reported in the annotation of the complete sequence. Our data include the identification of six genes encoding short or ambiguous open reading frames; the identification of three cases in which alternative splicing produces two structurally unrelated protein sequences; and the identification of six genes encoding proteins with functional motifs, two genes with unusually low similarity to their orthologous mouse proteins, and four genes with significant conservation in Drosophila melanogaster. We further demonstrate that an additional nine gene models represent bona fide transcripts and develop expression patterns for these genes plus nine additional novel chromosome 21 genes and four paralogous genes mapping elsewhere in the human genome. These data have implications for generating complete transcript maps of chromosome 21 and for the entire human genome, and for defining expression abnormalities in Down syndrome and mouse models.

Animals↗

PubMed2000

Assessing annotation transfer for genomics: quantifying the relations between protein sequence, structure and function through traditional and probabilistic scores.

Measuring in a quantitative, statistical sense the degree to which structural and functional information can be "transferred" between pairs of related protein sequences at various levels of similarity is an essential prerequisite for robust genome annotation. To this end, we performed pairwise sequence, structure and function comparisons on approximately 30,000 pairs of protein domains with known structure and function. Our domain pairs, which are constructed according to the SCOP fold classification, range in similarity from just sharing a fold, to being nearly identical. Our results show that traditional scores for sequence and structure similarity have the same basic exponential relationship as observed previously, with structural divergence, measured in RMS, being exponentially related to sequence divergence, measured in percent identity. However, as the scale of our survey is much larger than any previous investigations, our results have greater statistical weight and precision. We have been able to express the relationship of sequence and structure similarity using more "modern scores," such as Smith-Waterman alignment scores and probabilistic P-values for both sequence and structure comparison. These modern scores address some of the problems with traditional scores, such as determining a conserved core and correcting for length dependency; they enable us to phrase the sequence-structure relationship in more precise and accurate terms. We found that the basic exponential sequence-structure relationship is very general: the same essential relationship is found in the different secondary-structure classes and is evident in all the scoring schemes. To relate function to sequence and structure we assigned various levels of functional similarity to the domain pairs, based on a simple functional classification scheme. This scheme was constructed by combining and augmenting annotations in the enzyme and fly functional classifications and comparing subsets of these to the Escherichia coli and yeast classifications. We found sigmoidal relationships between similarity in function and sequence, with clear thresholds for different levels of functional conservation. For pairs of domains that share the same fold, precise function appears to be conserved down to approximately 40 % sequence identity, whereas broad functional class is conserved to approximately 25 %. Interestingly, percent identity is more effective at quantifying functional conservation than the more modern scores (e.g. P-values). Results of all the pairwise comparisons and our combined functional classification scheme for protein structures can be accessed from a web database at http://bioinfo.mbb.yale.edu/alignCopyright 2000 Academic Press.

Animals↗

PubMed2001

Automated structure-based prediction of functional sites in proteins: applications to assessing the validity of inheriting protein function from homology in genome annotation and to protein docking.

A major problem in genome annotation is whether it is valid to transfer the function from a characterised protein to a homologue of unknown activity. Here, we show that one can employ a strategy that uses a structure-based prediction of protein functional sites to assess the reliability of functional inheritance. We have automated and benchmarked a method based on the evolutionary trace approach. Using a multiple sequence alignment, we identified invariant polar residues, which were then mapped onto the protein structure. Spatial clusters of these invariant residues formed the predicted functional site. For 68 of 86 proteins examined, the method yielded information about the observed functional site. This algorithm for functional site prediction was then used to assess the validity of transferring the function between homologues. This procedure was tested on 18 pairs of homologous proteins with unrelated function and 70 pairs of proteins with related function, and was shown to be 94 % accurate. This automated method could be linked to schemes for genome annotation. Finally, we examined the use of functional site prediction in protein-protein and protein-DNA docking. The use of predicted functional sites was shown to filter putative docked complexes with a discrimination similar to that obtained by manually including biological information about active sites or DNA-binding residues.

Algorithms↗

PubMed2002

Ab initio gene identification: prokaryote genome annotation with GeneScan and GLIMMER.

We compare the annotation of three complete genomes using the ab initio methods of gene identification GeneScan and GLIMMER. The annotation given in GenBank, the standard against which these are compared, has been made using GeneMark. We find a number of novel genes which are predicted by both methods used here, as well as a number of genes that are predicted by GeneMark, but are not identified by either of the nonconsensus methods that we have used. The three organisms studied here are all prokaryotic species with fairly compact genomes. The Fourier measure forms the basis for an efficient non-consensus method for gene prediction, and the algorithm GeneScan exploits this measure. We have bench-marked this program as well as GLIMMER using 3 complete prokaryotic genomes. An effort has also been made to study the limitations of these techniques for complete genome analysis. GeneScan and GLIMMER are of comparable accuracy insofar as gene-identification is concerned, with sensitivities and specificities typically greater than 0.9. The number of false predictions (both positive and negative) is higher for GeneScan as compared to GLIMMER, but in a significant number of cases, similar results are provided by the two techniques. This suggests that there could be some as-yet unidentified additional genes in these three genomes, and also that some of the putative identifications made hitherto might require re-evaluation. All these cases are discussed in detail.

Algorithms↗

PubMed2002

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↗

PubMed2001

An automated annotation tool for genomic DNA sequences using GeneScan and BLAST.

Genomic sequence data are often available well before the annotated sequence is published. We present a method for analysis of genomic DNA to identify coding sequences using the GeneScan algorithm and characterize these resultant sequences by BLAST. The routines are used to develop a system for automated annotation of genome DNA sequences.

Algorithms↗

PubMed2004

Annotation of a 95-kb Populus deltoides genomic sequence reveals a disease resistance gene cluster and novel class I and class II transposable elements.

Poplar has become a model system for functional genomics in woody plants. Here, we report the sequencing and annotation of the first large contiguous stretch of genomic sequence (95 kb) of poplar, corresponding to a bacterial artificial chromosome clone mapped 0.6 centiMorgan from the Melampsora larici-populina resistance locus. The annotation revealed 15 putative genetic objects, of which five were classified as hypothetical genes that were similar only with expressed sequence tags from poplar. Ten putative objects showed similarity with known genes, of which one was similar to a kinase. Three other objects corresponded to the toll/interleukin-1 receptor/nucleotide-binding site/leucine-rich repeat class of plant disease resistance genes, of which two were predicted to encode an amino terminal nuclear localization signal. Four objects were homologous to the Ty1/ copia family of class I transposable elements, one of which was designated Retropop and interrupted one of the disease resistance genes. Two other objects constituted a novel Spm-like class II transposable element, which we designated Magali.

Amino Acid Sequence↗