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At least 19 recordsLinked to original sources

Whole metagenome sequencing: not deep enough for complete microbial function recovery.

BACKGROUND: Whole metagenome shotgun sequencing (WMS) is widely used to profile microbial function. However, technical variability in sequencing and analysis often obscures true biological patterns. Large-scale studies are particularly susceptible to batch effects, such as differences in sequencing depth and platform and annotation strategies, as well as sample-to-flow-cell assignments. However, the relative effects of these factors on functional inference in such studies have yet to be systematically evaluated. We analyzed oral-rinse WMS data from 671 Nigerian youths aged 9-18, sequenced on two Illumina platforms. Microbial molecular functionality encoded in these data was annotated using the mi-faser/Fusion pipeline, to capture the broad functional repertoire, and HUMAnN 3/EC numbers pipeline to characterize curated enzymatic activities. We then quantified how technical factors and batch effects shaped the recovery of microbial functionality. RESULTS: Three findings of our work were most salient. First, we observed that the choice of annotation strategy traded off between breadth and specificity of functional coverage. Second, we found that low-prevalence functions were disproportionately lost at shallow sequencing depths, indicating that in, e.g., case-control studies with few representatives of the minor class, sequencing depth could critically impact study resolution. Finally, using our newly developed model relating sequencing depth to functional recovery, we demonstrated that increasing sequencing depth does not directly or proportionally improve functional recall. That is, at as little as 10% of this study's sequencing depth, 30% of the estimated complete microbiome functional repertoire was detectable. However, even at the full depth used in this study, we were only able to recover an estimated 60% of that complete functional repertoire. We further showed that despite biomes differences in functional diversity and host contamination levels (e.g., soil, fecal), incomplete functional recovery at commonly used sequencing depths was consistently observed. CONCLUSIONS: Together, these findings and our depth-to-function mapping framework provide practical guidelines for the design and interpretation of WMS studies. Coordinating sequencing depth planning with annotation strategy, experimental design, and rigorous batch control is thus essential for robust detection of microbial functions and for ensuring reproducible microbiome insights. Video Abstract.

Humans

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

A chromosome-level reference genome assembly of the Small snakehead (Channa asiatica).

The Small snakehead (Channa asiatica) is an economically important species in both aquaculture and ornamental trade, mainly distributed in South China and Southeast Asia. Despite its significance, limited genomic resources have impeded in-depth genetic studies and breeding programs. In this study, we used PacBio HiFi long-read sequencing, Illumina short-read sequencing, and Hi-C technologies to generate a high-quality chromosome-level genome of the C. asiatica. The final genome spans 659.44 Mb, with an impressive 98.18% anchored to 23 chromosomes. Notably, the contig N50 and scaffold N50 are 23.92 Mb and 29.61 Mb, validated by a BUSCO completeness score of 98.93%. Genome annotation identified 26,603 protein-coding genes, 99.29% of which were confirmed by BUSCO analysis, and 93.68% were functionally annotated. Approximately 27.72% of the genome sequences were classified as repeat elements. This high-fidelity genome assembly provides a robust foundation for advancing molecular breeding, comparative genomics, and evolutionary studies of C. asiatica and related species.

Animals

Ulmus minor response to Dutch elm disease: de novo transcriptome assembly and annotation.

Dutch elm disease (DED), caused by Ophiostoma novo-ulmi (ONU), has devastated elm populations across Europe and North America since the 20th century. In this work, a de novo transcriptome assembly of Ulmus minor in response to ONU is presented. We used two DED-resistant genotypes, MDV2.3 and VAD2, and one DED-susceptible genotype, MDV1, to capture responses to ONU at four time points post-inoculation (6, 24, 72, and 144 hours). RNA from collected samples was isolated and sequenced producing 60.88 M 100 bp paired-end reads per sample. We performed a de novo transcriptome assembly combining data from the three genotypes. The assembly was functionally annotated and validated through differential gene expression analysis of the response. This dataset provides a valuable resource for studying molecular mechanisms of DED resistance in elms, contributing to broadening our understanding of tree immunity and facilitating potential applications in functional annotation of future genome assemblies.

Transcriptome

ProtPen Combines Sequence- and Structure-based Approaches to Facilitate Protein Function Predictions on a Proteome-wide Scale.

Proteins of unknown function represent a significant gap in our understanding of biological processes, encompassing large portions of the proteomes of many organisms, especially prokaryotes. Addressing this gap is critical to understanding the biology and pathogenicity of such organisms. We introduce ProtPen, an open-source pipeline that facilitates protein function prediction by combining eggNOG-mapper for sequence-based annotation with Foldseek for rapid structural similarity searches using AlphaFold-predicted protein structures. Annotation results from both tools are merged and enriched with UniProt metadata to produce a comprehensive output suitable for downstream analysis. The pipeline requires only a FASTA input file with UniProt identifiers, and is designed to analyze data sets on the scale of whole proteomes. Benchmarking on a curated data set of well-characterized Pseudomonas aeruginosa proteins demonstrated an annotation accuracy of >90%, and highlighted the complementarity of sequence- and structure-based methods. Further evaluation of ProtPen included its application to biologically relevant data sets, comprising proteins of unknown function that exhibited significant differential abundances in a proteomics data set of P. aeruginosa, and uncharacterized glycoproteins from Haloferax volcanii. ProtPen is readily extensible to incorporate additional protein function prediction tools. In summary, this pipeline facilitates the systemwide annotation of proteins of unknown function from proteomic data sets and whole proteomes.

Pseudomonas aeruginosa

Federated learning for the pathogenicity annotation of genetic variants in multi-site clinical settings.

MOTIVATION: Rare diseases collectively affect 5% of the population. However, fewer than 50% of rare disease patients receive a molecular diagnosis after whole genome sequencing. Supervised machine learning is a valuable approach for the pathogenicity scoring of human genetic variants. However, existing methods are often trained on curated but limited central repositories, resulting in poor accuracy when tested on external cohorts. Yet, large collections of variants generated at hospitals and research institutions remain inaccessible to machine-learning purposes because of privacy and legal constraints. Federated learning (FL) algorithms have been recently developed enabling institutions to collaboratively train models without sharing their local datasets. RESULTS: Here, we present a proof-of-concept study evaluating the effectiveness of FL for the clinical classification of genetic variants. A comprehensive array of diverse FL strategies was assessed for coding and non-coding Single Nucleotide Variants as well as Copy Number Variants. Our results showed that federated models generally achieved comparable or superior performance to traditional centralized learning. In addition, federated models reached a robust generalization to independent sets with smaller data fractions as compared to their centralized model counterparts. Our findings support the adoption of FL to establish secure multi-institutional collaborations in human variant interpretation. AVAILABILITY AND IMPLEMENTATION: All source code required to reproduce the results presented in this article, implemented in Python, is available under the GNU General Public License v3 at https://github.com/RausellLab/FedLearnVar.

Humans

The chromosome-level genome assembly of Prunus cerasifera 'Atropurpurea'.

Prunus cerasifera 'Atropurpurea' (Purpleleaf Plum), known for its unique purple-red foliage, is an important ornamental plant that enhances the aesthetic value of urban greening. To explore the molecular mechanisms underlying leaf color changes, this study assembled the Purpleleaf Plum genome, providing new insights for related research. We used HiFi sequencing data to assemble its genome. After chromosome anchoring, the final genome size was 244.89 Mb, with a contig N50 of 26.60 Mb, and approximately 97.10% of sequences were anchored to 8 chromosomes. Genome annotation identified 28,231 protein-coding genes, with LTR transposons comprising 27.93% of the genome. BUSCO assessment revealed a genome completeness of 98.9%. Telomeric repeat analysis identified 14 telomeres, with six chromosomes capped by double telomeres and two chromosomes containing a single telomere. This high-quality Purpleleaf Plum genome provides a solid foundation for future gene function analysis, cultivar improvement, and genetic research, offering valuable resources for related fields.

Genome, Plant

NAVIP: Unraveling the influence of neighboring small sequence variants on functional impact prediction.

Once a suitable reference sequence has been generated, intra-species variation is often assessed by re-sequencing. Variant calling processes can reveal all differences between strains, accessions, genotypes, or individuals. These variants can be enriched with predictions about their functional implications based on available structural annotations, i.e., gene models. Although these functional impact predictions on a per-variant basis are often accurate, some challenging cases require the simultaneous incorporation of multiple adjacent variants into this prediction process. Examples include neighboring variants which modify each other's functional impact. The Neighborhood-Aware Variant Impact Predictor (NAVIP) considers all variants within a given protein coding sequence when predicting the effect. As a proof of concept, variants between the Arabidopsis thaliana accessions Columbia-0 and Niederzenz-1 were annotated. NAVIP is freely available on GitHub (https://github.com/bpucker/NAVIP) and accessible through a web server (https://pbb-tools.de).

Arabidopsis

A chromosome-level genome assembly and annotation of Cercis chuniana (Fabaceae).

The genus Cercis L., at the base of the subfamily Cercidoideae of Fabaceae, is known for its ecological adaptability and significant medicinal, ornamental, and economic value. However, the lack of a high-quality genome hinders the understanding of the evolution of Cercis and Fabaceae. In this study, we present a chromosome-level genome of Cercis chuniana by combining Illumina short reads, PacBio HiFi long reads, and Hi-C data. The final genome size is 355.53 Mb, consisting of 12 contigs with a N50 of 42.34 Mb. Notably, 344.24 Mb, corresponding to 96.82% of the genome, was anchored to seven chromosomes. The assembly comprises 24.83% repetitive sequences, including 19.32% long terminal repeats. Additionally, a total of 33,837 protein-coding genes were predicted in the genome, with 32,709 (96.67%) genes successfully annotated. The high-quality genome assembly of C. chuniana not only bridges the existing gap in genomic data and offers important resources for molecular studies of this species, but also provides essential insights for future studies on speciation, functional and comparative genomics within the Fabaceae family.

Genome, Plant

Improving the Annotations of JCVI-Syn3a Proteins.

The JCVI-Syn3 organism is a minimal organism derived from Mycoplasma mycoides capri, which is capable of self-replication. While the ancestor has 863 genes, the synthetic progeny has only 473, with 434 of these coding for proteins. Despite initial efforts to understand all functions of the organism, a significant number of these protein-coding genes still have unknown functions, and subsequent studies have been only partially successful in elucidating their roles. In this study, we employ our innovative method PROST to identify homologs and better understand these previously unidentified genes. PROST employs protein language embeddings and enables the identification of remote homologs with as low as 16% sequence identity. PROST successfully finds functionally annotated homologs for 93% of the minimal genome with a high level of accuracy, both confirming previously identified functions, as well as proposing new functions for others. The results of our study can be accessed at https://bit.ly/prost-syn3a .

Molecular Sequence Annotation

Chromosome-level genome assembly of Nothapodytes nimmoniana.

Nothapodytes nimmoniana is a plant species belonging to the genus Nothapodytes in the family Icacinaceae. This species holds significant medicinal value due to its camptothecin content. In this study, we present the first chromosome-level genome assembly of N. nimmoniana constructed using NGS, Hi-C, and HiFi sequencing technologies. The assembled genome spans 3.53 Gb across 14 chromosomes, with an N50 length of 248.74 Mb. Genome annotation revealed that repetitive sequences constitute 80.82% of the genome size, and 83,269 protein-coding genes were predicted. Additionally, 4,360,538 bp of non-coding RNA were annotated. This genomic resource provides a foundation for further investigation into camptothecin biosynthesis pathways and plant phylogeny in N. nimmoniana.

Genome, Plant

Chromosome-level genome assembly and annotation of Spinibarbus caldwelli.

Spinibarbus caldwelli 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 southern China, the lack of genomic resources has hampered the genetic breeding and conservation. Here, we release a chromosome-level genome assembly for S. caldwelli using PacBio HiFi long-reads, Illumina short-reads, and Hi-C sequencing data. The final genome assembly is 1.77 Gb in size, with a contig N50 of 24.27 Mb. Using Hi-C scaffolding, 99.14% of the contigs were successfully anchored to 50 chromosomes, resulting in a scaffold N50 of 35.29 Mb. The final genome assembly shows a BUSCO completeness of 98.27%. The assembled genome contains 49.41% repetitive sequences and 51,505 predicted genes, 90.83% of which have been functionally annotated. This genome provides a genetic basis for S. caldwelli, facilitating the exploration of Cyprinid phylogeny, genetic improvement, and conservation efforts.

Animals

Chromosome-level assembly and annotation of the Jaguar (Panthera onca) genome.

OBJECTIVES: The Jaguar (Panthera onca) is a large cat species native to the Americas. Despite being successful predators, jaguar populations have declined due to habitat loss. Genome resources can help in conservation efforts as well as in understanding the interesting biology of these Felids. Beside contiguity, a well annotated reference genome provides contextual information for variants that will benefit the design of appropriate conservation programs. DATA DESCRIPTION: We sequenced material from two individuals using a combination of ONT reads and Illumina PE. The resulting nuclear genome assembly has a larger contig N50 (48.04 Mb) compared with the existing annotated chromosome-level assembly published by the DNA Zoo project. Using public Hi-C data, we obtained an improved chromosome-level assembly of the Jaguar genome (mPanOnc3.5) with larger contigs, 99.85% of the sequence assigned to chromosomes and 25,267 protein coding genes annotated. Overall, this improved assembly provides a better reference to study this threatened species.

Animals

Leveraging functional annotations to map rare variants associated with Alzheimer disease with gruyere.

Increased availability of whole-genome sequencing (WGS) has facilitated the study of rare variants (RVs) in complex diseases. Multiple RV association tests are available to study the relationship between genotype and phenotype, but most do not fully leverage the availability of variant-level functional annotations. We propose genome-wide rare variant enrichment evaluation (gruyere), an empirical Bayesian framework that complements existing methods by learning global, trait-specific weights for functional annotations to improve variant prioritization. We apply gruyere to WGS data from the Alzheimer's Disease Sequencing Project to identify Alzheimer disease (AD)-associated genes and annotations. Growing evidence suggests that the disruption of microglial regulation is a key contributor to AD risk, yet existing methods have not examined rare non-coding effects that incorporate such cell-type-specific information. To address this gap, we (1) define per-gene non-coding RV test sets using predicted enhancer and promoter regions in microglia and other brain cell types (oligodendrocytes, astrocytes, and neurons) and (2) include cell-type-specific variant effect predictions (VEPs) as functional annotations. gruyere identifies 13 significant genetic associations not detected by other RV methods, four of which remain significant in omnibus tests. We find that deep-learning-based VEPs for splicing, transcription factor binding, and chromatin state are highly predictive of functional non-coding RVs. Our study establishes a robust framework incorporating functional annotations, coding RVs, and cell-type-associated non-coding RVs to perform genome-wide association tests, uncovering AD-relevant genes and annotations.

Alzheimer Disease

Microbiome Datahub: an open-access platform integrating environmental metadata, taxonomy, and functional annotation for comprehensive metagenome-assembled genome datasets.

BACKGROUND: Metagenome-assembled genomes (MAGs) provide crucial insights into the genomic diversity of uncultured microbes. However, MAG datasets deposited in public repositories such as INSDC are often difficult to reuse due to heterogeneous quality, inconsistent taxonomic and functional annotations, and insufficiently curated environmental metadata. While secondary MAG databases such as MGnify, IMG/M, and SPIRE provide standardized resources, they reconstruct MAGs de novo from public metagenomic reads and therefore do not represent the original MAGs reported in publications. RESULTS: To address this gap, we developed Microbiome Datahub, an open-access platform that systematically aggregates and re-annotates original MAGs from INSDC. We collected 214,427 MAGs, predicted genes by DFAST, performed quality assessment with CheckM, standardized taxonomic assignments with GTDB-Tk, inferred 27 phenotypic traits using Bac2Feature, assigned proteins to MBGD ortholog clusters and KEGG Orthology IDs using PZLAST, and annotated environmental metadata with the Metagenome and Microbes Environmental Ontology. Across these MAGs, the average completeness was 80.5% and contamination 1.8%; notably, the most frequent values were&#x2009;>95% completeness and&#x2009;<1% contamination, indicating that the majority of MAGs are of high quality. Comparative analyses showed that Microbiome Datahub provides phylogenetically and environmentally diverse MAGs: while the majority originated from vertebrate gut environments, a substantial number were also recovered from other habitats such as groundwater, including nearly 10,000 MAGs from the Patescibacteria. Inference of 27 phenotypic traits, including optimum growth temperature, further revealed ecological differentiation across phyla. Protein clustering revealed 56 million identity 40% clusters, with the majority unique compared with MGnify and GlobDB, and&#x2009;~19% of proteins unassigned to MBGD ortholog clusters, underscoring their novelty. CONCLUSIONS: Microbiome Datahub integrates MAG genome sequences, gene and protein predictions, quality metrics, environmental and taxonomic annotations, ortholog cluster assignments, and phenotype predictions, all accessible via a web interface, API, and bulk downloads. By combining original MAGs with curated metadata and functional annotations, Microbiome Datahub constitutes a comprehensive and reusable resource that will accelerate microbiome and microbial genomics research. Video Abstract.

Metagenome

FANTASIA suite: a reproducible and configurable framework for embedding-based functional annotation of proteins.

Embedding-based annotation transfer is increasingly used for protein function inference due to protein language models capture sequence, structural, and functional signals that may extend beyond conventional pairwise similarity. However, systematic application of these approaches requires control over model choice, reference composition, lookup parameters, evidence traceability, and output formats. We developed the FANTASIA suite, a configurable framework for embedding-based functional annotation of proteins. The suite combines a database-backed implementation for reproducible and extensible analyses with a portable flat-file implementation for rapid local annotation and pipeline integration. Using non-model and model-organism proteomes, we show that larger neighbourhood sizes remain practical for proteome-scale analyses and that taxonomy and sequence-identity filtering support leakage-aware benchmarking. We also compare the supported models with baseline methods through external CAFA5 evaluation and provide practical guidance based on empirical evidence variables. FANTASIA provides a controlled, scalable, and reproducible framework for extending functional annotation across the rapidly expanding diversity of sequenced organisms.

Software

Orthopoxvirus Genome Sequencing, Assembly, and Analysis.

Poxviruses have exceptionally large genomes compared to most other viruses, which represent unique challenges to sequencing and assembly due to complex features such as repeat elements and low complexity sequences. The 2022 global mpox outbreak led to an unprecedented level of poxvirus sequencing as public health and research institutions faced with large sample numbers and demand for fast turnaround, merged NGS protocols designed for small RNA viruses with poxvirus expertise. Traditional manual assembly, checking, and editing of genomes was not feasible. Here, we present a protocol for metagenomic sequencing and orthopoxvirus genome assembly directly from DNA extracted from a patient lesion swab with no viral enrichment or host depletion. This sequencing approach is cost effective when using high throughput sequencing instruments and allows for detection of genomic insertions, deletions, and large rearrangement with confidence. We describe usage of two publicly available bioinformatic pipelines for genome assembly, quality control, annotation, and submission to sequence repositories.

Orthopoxvirus

Chromosome-level genome assembly of Ceroplastes pseudoceriferus Green, 1935 (Hemiptera: Coccidae).

Soft scales (Hemiptera: Coccidae) are significant polyphagous pests and majority of which are invasive species. The 364.14&#x2009;Mb chromosome-level genome of Ceroplastes pseudoceriferus was assembled in this work, with a contig N50 length of 6.16&#x2009;Mb and scafold N50 length of 21.24&#x2009;Mb. Approximately 99.89% of assembled sequences were anchored into 18 chromosomes with the assistance of Hi-C reads. Furthermore, approximately 53.98% of the genome was composed of repetitive elements. In total, 10,475 protein-coding genes were predicted, of which 9503 (90.72%) genes were functionally annotated. The BUSCO analysis demonstrated the completeness of the genome annotation is 92.54%. This genome represents first high-quality chromosome level assembly of Coccidae, thereby advancing our knowledge of Coccidae insects and developing effective management strategies that protect crops, forests, and natural ecosystems.

Animals