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Results for “genomics”

Search indexed bioRxiv preprints in genomics, neuroscience, cell biology and bioinformatics. Read source abstracts and check manuscript versions; preprints are not peer reviewed.

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bioRxiv2024

Saccharomyces Genome Database: Advances in Genome Annotation, Expanded Biochemical Pathways, and Other Key Enhancements

Budding yeast (Saccharomyces cerevisiae) is the most extensively characterized eukaryotic model organism and has long been used to gain insight into the fundamentals of genetics, cellular biology, and the functions of specific genes and proteins. The Saccharomyces Genome Database (SGD) is a scientific resource that provides information about the genome and biology of S. cerevisiae. For more than 30 years, SGD has maintained the genetic nomenclature, chromosome maps, and functional annotation for budding yeast along with search and analysis tools to explore these data. Here we describe recent updates at SGD, including the two most recent reference genome annotation updates, expanded biochemical pathways representation, changes to SGD search and data files, and other enhancements to the SGD website and user interface. These activities are part of our continuing effort to promote insights gained from yeast to enable the discovery of functional relationships between sequence and gene products in fungi and higher eukaryotes.

genetics↗

bioRxiv2025

Basin-scale dynamics and enrichment-enabled genomics of marine nitrifiers: seasonality, niches, interactions, and genomic uniqueness

Nitrification occurs widely from the deep sea to animal holobionts, but the eco-evolutionary forces shaping the niches and dynamics of the lineages of the chemoautotrophic bacteria and archaea responsible remain largely unknown. To make strides towards this goal in a rapidly changing, exemplar marine ecosystem, the Baltic Sea, we studied basin-scale nitrifier spatio-temporal dynamics, coupled with enrichment-enabled comparative genomics. Based on metagenomes and rRNA gene sequencing, we found nitrifiers to be persistently relatively abundant throughout deep depths (>25 m), and from late-fall to spring in surface waters, as revealed by twice-weekly sampling across two years in the southwest Baltic Sea surface waters. In these surface waters, we observed time-lagged dynamics between ammonia- and nitrite-oxidizers, which were positively correlated with nitrite, nitrate, and diverse other prokaryotes, and negatively correlated with day length, light, and chlorophyll. For the dominant nitrifiers, ammonia-oxidizing archaea (AOA), we enriched five novel species including the dominant deep Baltic Sea species, and obtained genomes from all dominant AOA phylotypes. Among these genomes, which enabled fine-scale niche-differentiation, we observed a high degree of gene conservation, with most differences related to genes associated with interactions with the external environment, including genes involved in signal transduction, cell wall/membrane biogenesis, and inorganic ion transport, indicating these may be the primary drivers of strain-variability. We also observed differences in nitrogen and phosphorus metabolism between two dominant surface types. Together our study provides key insights into the niche of nitrifiers, and begins the process of understanding the mechanisms and functional implications of these patterns.

microbiology↗

bioRxiv2025

First Genomic Insights into an Aeshnidae Dragonfly: Unveiling the Genome of a Holarctic Species, Aeshna juncea

Temperature oscillations in the Arctic may present a unique opportunity to study how insect species respond to such changes. Aeshna juncea, a Holarctic species of the family Aeshnidae thrives in this environment; molecular adaptations that allow it to survive in the Arctic have yet to be evaluated. Here, we present the first assembled and annotated draft genome assembly and annotation of A. juncea. The assembly is both highly contiguous and complete. This resource is presented and used here to provide further evidence that transposons and unclassified repetitive elements are a major driver behind genome size variation in Odonata and show that the effective population size of A. juncea populations from Alaska went through bottlenecks during the most recent ice age. We believe this genome will be an important resource in understanding how species like Aeshna juncea survive in Arctic habitats.

evolutionary biology↗

bioRxiv2025

A chromosome-scale genome assembly of Hordeumerectifolium: genomic, transcriptomic and anatomicaladaptations to drought in a wild barley relative

O_LIWild crop relatives are valuable genetic resources for improving stress adaptation in cultivated species, but their effective use depends on high-quality reference genomes integrated with phenotypic and molecular datasets. Hordeum erectifolium, a wild relative of barley (H. vulgare), is adapted to intermittent and prolonged drought and saline soils, making it an excellent model for stress-adaptation research. C_LIO_LIWe assembled a chromosome-scale, annotated reference genome of H. erectifolium comprising 3.85 Gbp, and identified 71,475 genes supported by a tissue-specific gene expression atlas. Comparative morphological, physiological, and transcriptomic analyses under water limitation were conducted with cultivated and wild barley. C_LIO_LIH. erectifolium displayed a greater density of leaf veins and sclerenchyma cells, alongside rapid leaf rolling upon dehydration. Genomic comparisons revealed structural variations, independent transposon-driven evolution, and copy number expansions of desiccation-responsive gene families relative to barley. The transcriptional responses of H. erectifolium and barley to water limitation suggested contrasting drought-adaptation strategies: metabolic down-regulation and survival prioritization in H. erectifolium versus maintenance of metabolic activity and competitiveness in barley. C_LIO_LIOur data suggest that H. erectifolium is genetically primed for survival under drought through anatomical adaptations, gene family expansion, efficient shutdown of growth-related metabolism, and rapid recovery upon rehydration. C_LI

evolutionary biology↗

bioRxiv2025

Whole genome analyses of the endangered Northern abalone (Haliotis kamtschatkana) reveal population differentiation and a genomic signature of a dramatic population decline

Despite widespread declines of many wildlife species, the effects of population decline on the genetic health and the recovery potential of affected species is still poorly understood, especially beyond a few charismatic species. The Northern abalone (or Pinto abalone; Haliotis kamtschatkana) is a marine gastropod mollusc of social, cultural and historical economic importance in the Pacific Northwest of North America that experienced a decline in population density due to commercial harvest and is currently listed as endangered in Canada under the Species at Risk Act. Previous genetic investigations based on microsatellites and reduced-representation approaches concluded that Northern abalone is panmictic throughout its range, from Alaska to California, and identified high levels of genetic variation with no indication of population decline. Using whole genome resequencing data from Northern abalone sampled across the northern part of the species range, we instead identified both: 1) significant differentiation between two genetic groups, albeit very concentrated in the genome; and 2) a strong signature of a dramatic population decline, without evidence of genetic inbreeding. Even though demographic reconstructions showed a timid signal of recent population expansion, the pervasive excess of rare alleles identified (including a high occurrence of singletons) may pose a genetic load risk, potentially hindering the species recovery. We also found evidence of historical, rather than current, connectivity throughout the area investigated. These results are important for management decisions and highlight the utility of whole genome data in conservation, especially in species with historically large effective population sizes like the Northern abalone.

evolutionary biology↗

bioRxiv2025

Population Genomics of P. miniata along the Pacific Coastline Reveal Subtly Diverging Genomics Along an Extensive Range Gap

Many marine species exhibit range gaps, patchy distributions, or genetic disjunctions throughout their ranges. These discontinuities can result from various interacting mechanisms, though directly linking ecological and historical factors to observed distributions or genetic disjunctions often proves challenging. Intriguingly, substantial research has demonstrated that these spatial and genetic discontinuities frequently occur in species with long-lived planktonic larvae, which possess the capacity for extensive oceanic dispersal. This study investigates the population genetics of one such species, the bat star Patiria miniata. Despite its long-lived planktonic larval stage of six to ten weeks, P. miniata maintains both a range gap and a, geographically separate, strong genetic disjunction throughout its distribution from Alaska to Baja California. Utilizing low-coverage whole-genome sequencing of over 200 individuals collected throughout P. miniatas range between the early 2000s and 2023, we corroborate previous findings of a significant genetic disjunction across Queen Charlotte Sound, north of Vancouver Island. Additionally, we present new evidence of strong divergence at several genomic loci across an extensive range gap in Washington and Oregon, despite subtle genetic population structure at most loci here. Such differences may reflect more recent ecological or oceanographic barriers, rather than historical processes. Our results demonstrate that while marine invertebrate populations may appear panmictic based on genome-wide metrics of population structure alone, strong local selection for specific gene segments may be maintained in some populations. This research contributes to our understanding of the complex interplay between dispersal potential and local adaptation in marine ecosystems and highlights the importance of considering both genetic structure and finer-scale adaptation in coastal marine populations.

evolutionary biology↗

bioRxiv2025

DNA extraction free whole genome sequencing of bacteriophage genomes from a single plaque

DNA sequencing is at the core of genome characterization, proteomics, and identification of novel organisms. For microorganisms such as bacteriophages, sequencing their DNA can provide key insights into their tropism, infectivity, and virulence. There remains however a critical lack of rapid sequencing techniques with the traditional process of replating and incubating individual plaques, collecting lysate, extracting DNA, preparing the DNA library, and sequencing that is labor intensive. Herein, we demonstrate the use of an adapted Nanopore Rapid PCR Barcoding protocol to sequence the bacteriophage genome directly from individual plaques. This technique provides sequencing genome assemblies with 99.88-100% (mean 99.97%) average nucleotide identity (ANI) scores when compared to the traditional methods involving phage amplification, extraction, and sequencing using Illumina. The optimization of bacteriophage identification by the technique of tagmentation directly to isolated plaques will enable rapid and cost-effective sequencing of novel phages.

microbiology↗

bioRxiv2018

The Complete Chloroplast Genome of Dendrobium nobile, an endangered medicinal orchid from Northeast India and its comparison with related chloroplast genomes of Dendrobium species.

The medicinal orchid genus Dendrobium belonging to the Orchidaceae family is the largest genus comprising about 800-1500 species. To better illustrate the species status in the genus Dendrobium, a comparative analysis of 33 newly sequenced chloroplast genomes retrieved from NCBI Refseq database was compared with that of the first complete chloroplast genome of D. nobile from north-east India based on next-generation sequencing methods (Illumina HiSeq 2500-PE150). Our results provide comparative chloroplast genomic information for taxonomical identification, alignment-free phylogenomic inference and other statistical features of Dendrobium plastomes, which can also provide valuable information on their mutational events and sequence divergence.

evolutionary biology↗

bioRxiv2018

Genomic diversity and novel genome-wide association with fruit morphology in Capsicum, from 746k polymorphic sites.

BackgroundCapsicum is one of the major vegetable crops grown world-wide. Current subdivision in clades and species is based on morphological traits and coarse sets of genetic markers. Fruits broad variability has been driven by breeding programs and has been mainly studied by linkage analysis.\n\nResultsWe discovered 746k variable sites by sequencing 1.8% of the genome in a collection of 373 accessions belonging to 11 Capsicum species from 51 countries. We describe genomic variation at population-level, confirm major subdivision in clades and species, and show that the known subdivision of C. annuum in two groups separates large and bulky fruits form small ones. In C. annuum, we identify four novel loci associated with phenotypes determining the fruit shape, including a non-synonymous mutation in the gene Longifolia 1-like (CA03g16080).\n\nConclusionsOur collection covers all the economically important species of Capsicum widely used in breeding programs, and represent the widest and largest study so far in terms of the number of species and genetic variants analyzed. We identified a large set of markers that can be used for population genetic studies and genetic association analyses. Our results foster fine genetic association studies and foresee genomic variability at population-level.

genetics↗

bioRxiv2019

Universal trends of post-duplication evolution revealed by the genomes of 13 Paramecium species sharing an ancestral whole-genome duplication.

Whole-Genome Duplications (WGDs) have shaped the gene repertoire of many eukaryotic lineages. The redundancy created by WGDs typically results in a phase of massive gene loss. However, some WGD-derived paralogs are maintained over long evolutionary periods and the relative contributions of different selective pressures to their maintenance is still debated. Previous studies have revealed a history of three successive WGDs in the lineage of the ciliate Paramecium tetraurelia and two of its sister species from the P. aurelia complex. Here, we report the genome sequence and analysis of 10 additional P. aurelia species and one additional outgroup, allowing us to track post-WGD evolution in 13 species that share a common ancestral WGD. We found similar biases in gene retention compatible with dosage constraints playing a major role opposing post-WGD gene loss across all 13 species. Interestingly we found that post-WGD gene loss was slower in Paramecium than in other species having experienced genome duplication, suggesting that the selective pressures against post-WGD gene loss are especially strong in Paramecium. We also report a lack of recent segmental duplications in Paramecium, which we interpret as additional evidence for strong selective pressures against individual genes dosage changes. Finally, we hope that this exceptional dataset of 13 species sharing an ancestral WGD and two closely related outgroup species will be a useful resource for future studies and will help establish Paramecium as a major model organism in the study of post-WGD evolution.

evolutionary biology↗

bioRxiv2019

Ancient genomic regulatory blocks are a major source for gene deserts in vertebrates after whole genome duplications

We investigated how the two rounds of whole genome duplication that occurred at the base of the vertebrate lineage have impacted ancient microsyntenic associations involving developmental regulators (known as genomic regulatory blocks, GRBs). We showed that the majority of GRBs present in the last common ancestor of chordates have been maintained as a single copy in humans. We found evidence that dismantling of the additional GRB copies occurred early in vertebrate evolution often through the differential retention of the regulatory gene but loss of the bystander genes exonic sequences. Despite the large evolutionary scale, the presence of duplicated highly conserved non-coding regions provided unambiguous proof for this scenario for dozens of ancient GRBs. Remarkably, the dismantling of ancient GRB duplicates has contributed to the creation of large gene deserts associated with regulatory genes in vertebrates, providing a widespread mechanism for the origin of these enigmatic genomic traits.

evolutionary biology↗

bioRxiv2026

GLADE: Accurate inference of Gains, Losses, Ancestral genomes, and Duplication Events for comparative genomics

Changes in gene content through gain and loss play a key role in the adaptation and diversification of species. Accordingly, our ability to detect and accurately document the history of these changes is important for our understanding the evolutionary trajectories of life on Earth. Here we present GLADE, a tool that accurately reconstructs gene gains, losses, and duplications for a set of species under consideration and uses this information to infer ancestral gene contents for every speciation event in the species tree. GLADE requires as input only a standard OrthoFinder results directory, and outputs the full evolutionary history of every orthogroup, including branch-specific changes and reconstructed ancestral genomes. We benchmark GLADE using both real and simulated data and show that GLADE accurately identifies orthogroup gains, losses, and duplications, and reconstructs ancestral orthogroup sizes with higher precision and overall accuracy than any competitor method. To illustrate the utility of the method, we apply GLADE to a dataset of 78 mammalian genomes and uncover repeated contractions in orthogroups associated with tooth formation on branches leading to ant- and termite-eating mammals - revealing convergent genomic signatures underlying this dietary specialization. GLADE and accompanying documentation and tutorials are freely available at https://github.com/lauriebelch/GLADE/.

evolutionary biology↗

bioRxiv2026

Epidemiology of Legionella: Genome-bAsed Typing (el_gato) - a new bioinformatic tool for identifying sequence-based types of Legionella pneumophila from whole genome sequencing data

Sequence-based typing (SBT) via Sanger sequencing has been the standard for describing Legionella pneumophila relationships for two decades. SBT involves sequencing seven loci, identifying alleles using the United Kingdom Health Security Agency (UKHSA) database, and inferring the corresponding sequence type (ST). While similar SBT approaches for other organisms can be easily adapted to whole genome sequencing (WGS), L. pneumophila presents two known challenges for this adaptation: multiple copies of one locus (mompS) and extensive heterogeneity in a second locus (neuA/neuAh). Although several computational methods have been proposed to address these issues, a WGS-based replacement with equal resolution to traditional SBT has been elusive. To address this gap, we developed el_gato (Epidemiology of Legionella: Genome-bAsed Typing; https://github.com/CDCgov/el_gato), which offers several advantages over existing methods: (1) a novel approach for resolving multiple mompS alleles identified in the same isolate, (2) the ability to capture diverse neuA/neuAh alleles, (3) fast runtime with an average of 27.7 seconds per sample, (4) easy installation via Bioconda or Docker and (5) an updated database as of March 2025. el_gato works with either paired-end short reads or genome assemblies, performing more accurately with paired-end short reads at least 250 base pairs (bp) in length. We compared el_gato against two other in silico SBT tools ("mompS", hereafter referred to as mompS tool and "legsta") using a dataset of 441 isolates with sequence types (STs) previously determined by Sanger-based sequencing. el_gato correctly identified the ST for 98.9% of the test isolates, compared to 95.2% for the mompS tool and 42.2% for legsta, demonstrating a significant improvement compared to the mompS tool (adjusted p = 1.06e-3) and legsta (adjusted p = 4.24e-55) in ST identification. Furthermore, el_gatos determination of ST was not significantly different from Sanger sequencing (adjusted p = 0.442). In summary, el_gato significantly improves in silico SBT and given its growing adoption, is poised to support the public health community.

bioinformatics↗

bioRxiv2026

Chemosensory landscape of order Vibrionales: Genome-scale phylogenomics uncovers four chemosensory architectures driven by bipartite genome organization

Chemosensory systems (CSSs) are multi-protein assemblies regulating bacterial motility and diverse alternative cellular functions. Despite extensive study of chemotaxis in Vibrio cholerae, a comprehensive evolutionary analysis of CSSs across order Vibrionales has been lacking. Using 116 curated representative genomes across 28 Vibrio clades and ~10,000 RefSeq/metagenome-assembled genomes, we characterized the chemosensory toolkit of Vibrionales. CheA-based phylogenetics, CSS architecture, sequence similarity networks, structural comparisons, and synteny analysis identified four discrete CSS types: F6, F7, F9, and an experimentally unexplored F8. F6 is universally conserved on chromosome I and essential for flagellar motility (chemotaxis), while F7, F8, and F9 show patchy, replicon-flexible distributions reflecting lineage-specific retention or horizontal acquisition. F6, F7, and F8 were vertically inherited from Gammaproteobacteria and retained in selected species, whereas F9 was horizontally acquired from Alphaproteobacteria in only selected species. Structural analysis further reveals conserved CheA folds despite sequence divergence, with lineage-specific insertions in F8 and F9 CheA proteins. Collectively, this study reveals a two-tier chemosensory architecture within order Vibrionales: 1) a chromosomally stable F6 motility core under purifying selection, 2) overlaid by dynamically evolving F7, F8, and F9 accessory systems, wherein multipartite genome organization might serve as an evolutionary key for sensory innovation in order Vibrionales, enabling rapid niche adaptation without compromising core chemotactic fidelity.

microbiology↗

bioRxiv2026

Hidden State Genomics: Graph-Based Analysis of Sparse Auto-Encoder Feature Activity in Genomic Language Models

Pre-trained genomic language model (gLM) representations have been anticipated to enable enhanced deep learning predictions on several genomics tasks, but current benchmarking has led to questions over what they actually encode. We studied this with mechanistic interpretability on InstaDeeps Nucleotide Transformer v2 (500M), training sparse autoencoders across all 24 encoder layers to probe latent features. Correlation-based annotation against reference regulatory tracks was inconsistent across layers and insufficient for causal interpretation. We therefore built typed sequence-to-feature knowledge graphs to explore the SAE feature space and compared cisplatin-binding versus non-binding genomic DNA sequence communities by PageRank centrality, validating candidate features with decoder-based interventions and a CNN binding classifier. Interventions showed asymmetric effects: suppressive features could collapse predictive signal, while binding-associated features shifted predictions cumulatively with the presence of other binding-associated signals. Dependency maps further indicated strong local feature sensitivity within sequences. Together, these results provide evidence that gLM representations encode highly granular sequence syntax and conservation patterns, aligning more strongly with tightly coupled molecular interactions and local biophysical constraints than with complex, distributed regulatory logic. Within the scope of our intervention setting, this pattern is consistent with stronger performance on selected molecular tasks and weaker performance on broader regulatory inference, motivating scalable methods for causal feature annotation.

bioinformatics↗

bioRxiv2026

biomeStat: Using Agentic AI for Scalable Genomic Epidemiology Demonstrated Through End-to-End Analysis of 1,000 Asian Dengue Virus Genomes

Genomic epidemiology workflows typically require expert curation of multiple specialized tools, extensive manual parameter tuning, and access to heterogeneous compute infrastructure. While standard generative AI models often hallucinate in complex biological domains, we introduce biomeStat: an autonomous AI agent that functions as a strict deterministic orchestrator. By automatically writing code to execute established bioinformatics tools in sandboxed environments, biomeStat dynamically provisions compute resources (CPU and GPU) and guarantees reproducibility, making it immediately useful for scientists without requiring command-line expertise. To demonstrate the platform, we performed a fully autonomous genomic epidemiology and structural analysis of 1,000 Dengue virus (DENV) genomes sampled from 16 Asian countries between 2000 and 2025. The agent seamlessly orchestrated phylogenetic reconstruction (IQ-TREE, TreeTime), Bayesian phylodynamics (BEAST2 via NVIDIA H200 GPU), selection pressure analysis (HyPhy), and structural mapping (PyMOL). The analysis was completed in under 24 hours of wall-clock time, revealing endemic stability (R_e [~]1.0) and identifying 1,869 candidate immune escape sites structurally colocalized with B-cell and T-cell epitopes. Furthermore, the agent validated 176 highly conserved drug target residues across the viral replication complex, confirming that resistance-associated positions for emerging antivirals JNJ-1802 and NITD-688 remain absolutely conserved across all four serotypes. By bridging the gap between natural language intent and deterministic computational execution, biomeStat reduces weeks of expert effort into a single-session analysis with full methodological transparency.

bioinformatics↗

bioRxiv2026

Rice bacterial blight resistance in Burkina Faso through genome editing: Evaluating pathogen and agro-morphological compatibility of genome-edited elite rice varieties

Bacterial leaf blight (BB), caused by Xanthomonas oryzae pv. oryzae (Xoo), causes yield losses exceeding 50% in affected areas, including the Bagre rice plain in Burkina Faso. Genome-edited (GEd) rice lines have been successful in tackling BB. Modifications in the Xoo virulence protein target site upstream of three SWEET susceptibility genes in two elite rice varieties, IR64 and Ciherang-Sub1, have been demonstrated to confer broad-spectrum resistance to Asian and East African Xoo strains. Here, we evaluate the potential of the GEd lines as a solution for BB management in Burkina Faso. We challenged the GEd lines against five locally collected Burkinabe Xoo strains under controlled green-house conditions and assessed their agro-morphological performance under field conditions representative of local agroecological conditions. Greenhouse pathogen assays demonstrated that GEd IR64 and Ciherang-Sub1 lines were resistant to all tested local Xoo strains across three successive generations. We identified TalC as the primary disease-causing effector in the local Xoo populations. Irrigated field trials conducted over two seasons in the Kou Valley, Burkina Faso, revealed absence of agro-morphological penalties in GEd lines compared to their parental wild-type lines. Observed trait variation was attributable to environmental fluctuations rather than genomic modifications. Collectively, our findings demonstrate that genome editing of the rice lines does not impose growth penalties, and support the suitability of GEd IR64 and Ciherang-Sub1 for large-scale adoption in Burkina Faso, pending multi-location validation and introgression into locally adapted varieties.

Plant Biology↗

bioRxiv2026

PlantGeneAnn: a strand-specific genome foundation model for ab initio gene structure annotation of plant genomes

High-quality plant genome assemblies are rapidly increasing, but accurate structural annotation remains reliant on transcript and homology evidence, limiting applications in newly sequenced and non-model species. Here, we present PlantGeneAnn, a plant-optimized, strand-specific genome foundation model for ab initio gene structure annotation. Fine-tuned on only nine high-quality model plant annotations, PlantGeneAnn outperformed a multi-species model trained on 42 species, showing that annotation quality is more important than token volume. On a stringent 13-species benchmark covering rosids, asterids, and monocots, PlantGeneAnn surpassed four state-of-the-art baselines across five evaluation levels, from base-level classification to complete transcript recovery. It achieved higher intron precision and better captured complex gene structures. In zero-shot variant effect prediction, PlantGeneAnn identified cryptic splice donors and premature stop codons in maize and rice, with saturation mutagenesis confirming single-nucleotide, context-dependent sensitivity. It also retained generalizability for epigenomic track prediction, highlighting its value for pan-genomics, crop improvement, and non-model plant research.

bioinformatics↗