PubMed HealthSearch

SEARCH · PubMed Health

Results for “Molecular Sequence Annotation”

Explore indexed PubMed citations for clinical trials, systematic reviews and public health research. Read source abstracts and follow each citation to its original PubMed record.

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

At least 55 records · Page 3Linked to original sources

Chromosome-Level Assembly and Annotation of the Grey Reef Shark (Carcharhinus amblyrhynchos) Genome.

To date less than 5% of shark species have nuclear reference genomes, despite next-generation sequencing advances. Particularly for threatened shark species, there is a lack of reliable genomes which are crucial in facilitating research and conservation applications. We assembled the first nuclear reference genome of the endangered grey reef shark (Carcharhinus amblyrhynchos) using long-read PacBio HiFi and Omni-C sequencing to reach chromosome-level contiguity (36 pseudochromosomes; 2.9 Gbp) and high completeness (94% complete BUSCOs). BRAKER3 annotated 16,505 protein-coding genes after masking repetitive elements which accounted for 59% of the genome. We identified potential X and Y sex chromosomes on pseudochromosomes 36 and 57, respectively. The quality and completeness of the draft genome of C. amblyrhynchos will enable researchers to investigate genetic variations and adaptations specific to this species as well as across other Carcharhinus spp., opening new venues for comparative genomics and advancing conservation genetic applications.

Animals

Characterization of a draft chromosome-scale genome assembly for the mutton snapper, Lutjanus analis.

BACKGROUND: The mutton snapper (Lutjanus analis) is a reef fish commonly found in tropical waters of the Western Atlantic Ocean. Genomic studies of this species are needed to support conservation efforts and breeding programs. OBJECTIVE: Here, we report the development of a chromosome-scale reference assembly for the mutton snapper and conduct an initial comparative genomic analysis with other lutjanids. METHODS: The genome of one mutton snapper specimen was sequenced using PAC-Bio HiFi long reads and Illumina short reads. Contigs and scaffolds were assembled in the Flye pipeline and anchored using Hi-C proximity guided assembly. Gene prediction and functional annotations were obtained in AUGUSTUS and eggNOG-mapper, respectively. The mutton snapper genome was compared to those of other lutjanids to infer gene family evolution and chromosome synteny conservation. RESULTS: Assembly and polishing yielded 946 contigs and 926 scaffolds (N50 of 3.16 Mb, complete BUSCO score 98.1%) that were anchored using Hi-C scaffolding in 24 draft chromosomes. The anchored assembly featured a N50 of 42.47 Mb and contained 97.6% of the unanchored assembly length. The 24 mutton snapper chromosomes showed a one-to-one syntenic relationship with their counterparts in medaka, and other Lutjanids. AUGUSTUS predicted 29,023 genes, 24,335 of which (83.85%) could be functionally annotated. Gene family evolution analysis revealed 1,014 significantly expanded or contracted hierarchical ortholog groups in mutton snapper. Expansions and contractions were linked to several biological functions including growth, oocyte maturation, and response to exogenous stressors. CONCLUSION: The draft genome will be a valuable tool for forthcoming applied genomic studies of mutton snapper.

Animals

Large-scale benchmarking of prokaryotic annotation tools across thousands of species.

BACKGROUND: Genome annotation is an important step in deriving functional meaning from prokaryotic sequencing data, yet systematic evaluations guiding tool selection are lacking. We present the first large-scale investigation of four prominent open-source annotation tools (Prokka, Bakta, EggNOG-mapper, and PGAP) across 156,033 diverse genomes. This includes Escherichia coli strains for baseline performance, thousands of archaea and bacteria genomes, as well as frameshifted and metagenome-assembled genomes. RESULTS: Bakta excels in annotating high-quality bacterial genomes, while PGAP was better for archaeal genomes and challenging bacterial assemblies, including metagenome-assembled, fragmented, or contaminated samples. For Gene Ontology annotation, PGAP consistently provides broader term coverage, whereas EggNOG-mapper offers more terms per feature. CONCLUSIONS: Our findings highlight tool-specific strengths crucial for selecting optimal solutions based on genome quality, taxonomy, and origin (e.g. MAGs). This study provides an evidence-based guide for users and informs future tool development.

Molecular Sequence Annotation

Missense variants pathogenicity annotation from homologous proteins.

MOTIVATION: High-throughput DNA sequencing has revealed millions of single nucleotide variants (SNVs) in the human genome, with a small fraction linked to disease. The effect of missense variants, which alter the protein sequence, is particularly challenging to interpret due to the scarcity of clinical annotations and experimental information. While using conservation and structural information, current prediction tools still struggle to predict variant pathogenicity. In this study, we explored the pathogenicity of homologous missense variants-variants in equivalent positions across homologous proteins-focusing on proteins involved in autosomal dominant diseases. RESULTS: Our analysis of 2976 pathogenic and 17 555 non-pathogenic homologous variants demonstrated that pathogenicity can be extrapolated with 95% accuracy within a family, or up to 98% for closer homologs. Remarkably, the evaluation of 27 commonly used mutation predictor methods revealed that they were not fully capturing this biological feature. To facilitate the exploration of homologous variants, we created HomolVar, a web server that computationally predicts the pathogenesis of missense variants using annotations from homologous variants, freely available at https://rarevariants.org/HomolVar. Overall, these findings and the accompanying tool offer a robust method for predicting the pathogenicity of unannotated variants, enhancing genotype-phenotype correlations, and contributing to diagnosing rare genetic disorders. AVAILABILITY AND IMPLEMENTATION: HomolVar is freely available at https://rarevariants.org/HomolVar.

Mutation, Missense

Functional Annotation Routines Used by ABRF Bioinformatics Core Facilities - Observations, Comparisons, and Considerations.

The functional annotation of gene lists is a common analysis routine required for most genomics experiments, and bioinformatics core facilities must support these analyses. In contrast to methods such as the quantitation of RNA-Seq reads or differential expression analysis, our research group noted a lack of consensus in our preferred approaches to functional annotation. To investigate this observation, we selected 4 experiments that represent a range of experimental designs encountered by our cores and analyzed those data with 6 tools used by members of the Association of Biomolecular Resource Facilities (ABRF) Genomic Bioinformatics Research Group (GBIRG). To facilitate comparisons between tools, we focused on a single biological result for each experiment. These results were represented by a gene set, and we analyzed these gene sets with each tool considered in our study to map the result to the annotation categories presented by each tool. In most cases, each tool produces data that would facilitate identification of the selected biological result for each experiment. For the exceptions, Fisher's exact test parameters could be adjusted to detect the result. Because Fisher's exact test is used by many functional annotation tools, we investigated input parameters and demonstrate that, while background set size is unlikely to have a significant impact on the results, the numbers of differentially expressed genes in an annotation category and the total number of differentially expressed genes under consideration are both critical parameters that may need to be modified during analyses. In addition, we note that differences in the annotation categories tested by each tool, as well as the composition of those categories, can have a significant impact on results.

Computational Biology

VDJ-Insights: simplifying the annotation of genomic immunoglobulin and T cell receptor regions.

MOTIVATION: Accurate annotation of germline immunoglobulin (IG) and T cell receptor (TCR) loci is critical for understanding adaptive immunity. RESULTS: VDJ-Insights provides a user-friendly software package for characterizing these complex immune regions. In addition, it assesses gene segment functionality, identifies recombination signal sequences, and annotates complementarity-determining regions 1 and 2. VDJ-Insights achieved over 99% concordance with curated annotations from multiple species, outperforming existing annotation tools. When applied to 95 haplotypes from the Human Pangenome Reference Consortium, VDJ-Insights identified 652 and 275 novel IG and TCR alleles, respectively, highlighting its scalability for large immunogenetic studies. AVAILABILITY AND IMPLEMENTATION: Datasets and software package are available in the VDJ-insights repository, https://github.com/BPRC-Bioinfo and https://doi.org/10.5281/zenodo.17588835. Additional intermediate datasets used and analyzed during the current study are available from the corresponding authors upon reasonable request.

Software

Chromosome-level genome assembly and annotation of Petunia hybrida.

Petunia hybrida is the world's most popular garden plant and is regarded as a supermodel for studying the biology associated with the Asterid clade, the largest of the two major groups of flowering plants. Unlike other Solanaceae, petunia has a base chromosome number of seven, not 12. This along with recombination suppression has previously hindered efforts to assemble its genome to chromosome level. Here we achieve a chromosome-level assembly for P. hybrida using a combination of short-read and long-read sequencing, optical mapping (Bionano) and Hi-C technologies. The resulting assembly spans 1253.6 Mb with a BUSCO score of 99.8%. A total of 35,089 genes were predicted and of those 29,655 were functionally annotated. Syntenic regions between petunia, tomato and pepper were identified, highlighting rearrangements that have occurred since their divergence indicating that the 12 chromosomes of Solanaceae did not originate from whole genome duplication of an ancestral species with seven chromosomes like petunia. This assembly will enhance trait mapping efficiency and serve as a valuable resource for functional genomic studies.

Petunia

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

Genome analysis of the glycosphingolipid-producing green alga tetraselmis sp. NKG400013.

Microalgae are gaining attention as sustainable resources for the production of valuable compounds, including biofuels, pigments, and bioactive metabolites. To support metabolic engineering and genome editing approaches aimed at enhancing these traits, high-quality genome assemblies are essential; however, genomic information remains limited for many microalgal lineages. Tetraselmis sp. NKG400013 is a green alga known for high glycosphingolipid accumulation with distinctive structural features. Here, we report a draft genome assembly of this strain generated using PacBio HiFi sequencing and transcriptome-supported annotation. The assembled genome spans 423.7 Mbp, with 74.5% repetitive sequences and 15,322 predicted protein-coding genes. Comparative analyses across 11 green algal species revealed a positive correlation between genome sizes and repeat contents, indicating that transposable element expansion, particularly long terminal repeat retrotransposons, has substantially contributed to genome enlargement in Tetraselmis. Genome-wide functional annotation and ortholog inference identified core enzymes required for glycosylceramide biosynthesis. Both sphingolipid Δ4 and Δ8 desaturases were identified in Tetraselmis and their coexistence suggests an expanded capacity for long-chain base modification that may underlie its distinctive glycosphingolipid profile. These results establish a genomic framework for understanding the high glycosphingolipid-producing capacity of NKG400013 and provide insights into the evolutionary diversification of sphingolipid metabolism in green algae.

Chlorophyta

PubMind: literature-based genetic variant extraction and functional annotation using large language models.

Biomedical literature contains extensive functional knowledge on genetic variants, but much remains inaccessible in unstructured text. Existing resources such as ClinVar and HGMD remain limited by coverage, submission bias, update frequency, and sparse annotation. We develop PubMind, an artificial intelligence (AI) framework that uses large language models (LLMs) to triage and extract variant-function-disease associations and supporting evidence from biomedical text. PubMind captures single-nucleotide, copy-number, structural, and gene-fusion variants, and normalizes records to genomic and transcriptomic coordinates. Benchmarking shows >90% accuracy for variant recognition and 99% precision for disease extraction. Applied to >41 million PubMed abstracts and >5 million full-text articles, PubMind generates PubMind-DB, a database of ~1.3 million unique variants with contextual annotations, accessible via web interface and API. Only ~10% of PubMind variants overlap with ClinVar, and >80% of them show concordant pathogenicity labels. PubMind transforms unstructured biomedical text into structured genomic knowledge, advancing variant interpretation for precision medicine.

Large Language Models

PICRUSt2-SC: an update to the reference database used for functional prediction within PICRUSt2.

SUMMARY: PICRUSt2 is a bioinformatic tool that predicts microbial functions in amplicon sequencing data using a database of annotated reference genomes. We have constructed an updated database for PICRUSt2 that has substantially increased the number of bacterial (19,493 to 26,868) and archaeal (406 to 1,002) genomes as well as the number of functional annotations present. The previous PICRUSt2 database relied on many timely and computationally intensive manual processes that made it difficult to update. We constructed a new streamlined process to allow regular upgrades to the PICRUSt2 database on an ongoing basis, and used this process to create a new database, PICRUSt2-SC (Sugar-Coated). Additionally, we have shown that this updated database contains genomes that more closely match study sequences from a range of different environments. The genomes contained in the database therefore better represent these environments and this leads to an improvement in the predicted functional annotations obtained from PICRUSt2. AVAILABILITY AND IMPLEMENTATION: PICRUSt2 source code is freely available at https://github.com/picrust/picrust2 and at https://anaconda.org/bioconda/picrust2. The latest version of PICRUSt2 at the time of writing is also archived: https://doi.org/10.5281/zenodo.15119781. The PICRUSt2-SC database comes pre-installed with PICRUSt2 from version 2.6.0 onwards. Step-by-step instructions for making the updated database are at https://github.com/picrust/picrust2/wiki/Updating-the-PICRUSt2-database. All code used for the analyses and figures in this manuscript is at https://github.com/R-Wright-1/PICRUSt2-SC_application_note and https://doi.org/10.5281/zenodo.15119770.

Software

Conditional Diffusion Model-Based Method for Annotation of Antibiotic Resistance Gene Properties.

The crisis of bacterial antibiotic resistance, which has led to a decline in the effectiveness of antibiotics originally used to combat bacterial infections, has emerged as an urgent challenge for public health. Antibiotic resistance genes (ARGs) are one of the key reasons for bacteria to develop resistance to antibiotics. Therefore, accurately identifying and annotating the critical properties of ARGs is of great importance for addressing the antibiotic resistance emergency. Although existing deep learning models demonstrate remarkable effectiveness in extracting local features from sequence data, they still face limitations in the capacity to further gain the enriched latent representations within the data. To address the critical challenge of extracting higher-quality representations from ARGs sequence data, we propose a novel ARGs properties annotation method based on the conditional diffusion model which is used to learn latent representations through domain-specific knowledge injection. Specifically, during the conditional information integration phase, we systematically incorporate ARGs' domain knowledge to guide the diffusion process in generating high-quality latent representations. To overcome information redundancy caused by direct concatenation of conditional information and intermediate features, we design a cross-attention mechanism that enables feature fusion between heterogeneous information sources, thereby enhancing further the quality of obtained representations. Experimental results on widely used data sets demonstrate the framework's effectiveness in achieving superior prediction performance compared to existing methods.

Anti-Bacterial Agents

High-Resolution Chromosome-Level Genome Assembly and Annotation of Triplophysa stewarti, an Endemic Plateau Loach from the Qinghai-Tibet Plateau.

The bottom-dwelling fish Triplophysa stewarti, endemic to the Qinghai-Tibet Plateau, is a valuable model for studying high-altitude adaptation in aquatic ecosystems. However, the lack of a high-quality reference genome has hindered comparative genomic and evolutionary studies within this genus. Here, we present a chromosome-level genome assembly for T. stewarti, generated using PacBio HiFi long-read sequencing and Hi-C scaffolding. The 697.9 Mb assembly is highly continuous (scaffold N50 of 253.58 Mb) and encompasses 25 chromosomes, representing 92.65% of the genome. BUSCO analysis indicated a 98.4% completeness, supporting the high quality of the assembly. We annotated 28,009 protein-coding genes, with 97.04% being functionally assigned across multiple databases (NR, UniProt, KEGG, GO, Pfam and InterPro). Additionally, repetitive elements constituted 42.47% of the genome, and we identified 52,709 non-coding RNAs. This high-quality reference genome provides a fundamental resource for exploring the adaptive evolution, population structure, and conservation genetics of T. stewarti and related species on the Qinghai-Tibet Plateau.

Animals

Annotation of RxLR Effectors in Oomycete Genomes.

Pathogens have evolved effector proteins to suppress host immunity and facilitate plant infections. RxLR effectors are small, secreted effector proteins with conserved RxLR and dEER amino acid motifs at the N terminus and highly variable C termini and are commonly found in oomycete species. We provide computational approaches to annotate RxLR candidate effector genes in a genome assembly in FASTA format with an available GFF file. Hidden Markov Modeling (HHM) is used in combination with regular expressions to search for RxLR and EER amino acid patterns.

Oomycetes

Gencube: centralized retrieval and integration of multi-omics resources from leading databases.

MOTIVATION: The volume of multi-omics data for diverse species is growing at an unprecedented rate, with new genome assemblies, related annotations, and high-throughput sequencing resources being submitted daily to various genomic data repositories. In response to this data influx, both existing and new databases are establishing optimized hierarchical structures to manage the vast amount of information. However, the lack of accessible command-line tools, combined with the functional limitations and unintuitive design of existing options, presents significant challenges for researchers. This gap underscores a critical need for a tool that enables streamlined retrieval and integration of omics data across these diverse repositories. RESULTS: We have developed Gencube, a command-line tool that enables centralized retrieval and integration of a comprehensive set of six different data types-genome assemblies, gene sets, annotations, sequences, comparative genomic data, and NGS-based omics resources-from various leading databases. AVAILABILITY AND IMPLEMENTATION: Gencube is a free and open-source tool, with its code available on GitHub: https://github.com/snu-cdrc/gencube and also archived on Zenodo: https://doi.org/10.5281/zenodo.14607649.

Databases, Genetic

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

The chromosome-level genome assembly and annotation of the silver-lipped pearl oyster, Pinctada maxima.

The silver-lipped pearl oyster (Pinctada maxima) is a valuable tropical aquaculture species, playing a crucial economic role in the global pearl industry. However, the lack of genomic reference limits our in-depth understanding of this species in genome-based breeding, conservation, evolution and adaptation. Here, annotated chromosome-level reference genome for P. maxima was generated by integrating PacBio long-read sequencing, Illumina short-read sequencing, and Hi-C sequencing data. The total genome size is 1,264.93&#x2009;Mb, with contig N50 and scaffold N50 of 649&#x2009;kb and 89.19&#x2009;Mb, respectively. The majority (97.94%) of the assembled genome was anchored to the 14 chromosomes by Hi-C analysis. The relatively high genome completeness was observed, with 97.38% (metazoa_odb10 database) and 95.26% (mollusca_odb10 database) in BUSCO analysis. Genome annotation revealed approximately 65.46% of the repeat sequences and 26,315 protein-coding genes. Comparative genome analysis revealed 28 expanded and 48 contracted families (p&#x2009;<&#x2009;0.05) in P. maxima, with 3.2% of genes (894) being species-specific. This chromosome-level genome serves as an essential resource for research in evolutionary genomics, phylogenetics, and biomineralization.

Animals

Haplotype-resolved genome assembly and implementation of VitExpress, an open interactive transcriptomic platform for grapevine.

Haplotype-resolved genome assemblies were produced for Chasselas and Ugni Blanc, two heterozygous Vitis vinifera cultivars by combining high-fidelity long-read sequencing and high-throughput chromosome conformation capture (Hi-C). The telomere-to-telomere full coverage of the chromosomes allowed us to assemble separately the two haplo-genomes of both cultivars and revealed structural variations between the two haplotypes of a given cultivar. The deletions/insertions, inversions, translocations, and duplications provide insight into the evolutionary history and parental relationship among grape varieties. Integration of de novo single long-read sequencing of full-length transcript isoforms (Iso-Seq) yielded a highly improved genome annotation. Given its higher contiguity, and the robustness of the IsoSeq-based annotation, the Chasselas assembly meets the standard to become the annotated reference genome for V. vinifera. Building on these resources, we developed VitExpress, an open interactive transcriptomic platform, that provides a genome browser and integrated web tools for expression profiling, and a set of statistical tools (StatTools) for the identification of highly correlated genes. Implementation of the correlation finder tool for MybA1, a major regulator of the anthocyanin pathway, identified candidate genes associated with anthocyanin metabolism, whose expression patterns were experimentally validated as discriminating between black and white grapes. These resources and innovative tools for mining genome-related data are anticipated to foster advances in several areas of grapevine research.

Vitis