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PubMed2026

Near-Whole-Genome Sequencing of Peste Des Petits Ruminants Virus Lineage IV From the Savannah District, Northern Côte d'Ivoire in 2023.

Peste des petits ruminants (PPR) is a highly contagious viral disease affecting sheep and goats, causing substantial economic losses in endemic countries. In the Savannah district of Côte d'Ivoire, knowledge of the genetic diversity and molecular epidemiology of the PPR virus (PPRV) remains limited. This study investigated the genetic diversity and phylogenetic relationships of PPRV circulating in this region using whole-genome sequencing (WGS). A cross-sectional survey was conducted between September and December 2023. Nasal swabs collected from sheep and goats were screened for PPRV ribonucleic acid (RNA) using real-time reverse transcription polymerase chain reaction (RT-qPCR). Samples with low quantification cycle (Cq) values of less than 35 and successful multiplex PCR amplification profiles were selected for sequencing using the Oxford Nanopore MinION platform. Near-complete consensus genomes were generated through reference-based assembly and analysed alongside representative strains from all recognised PPRV lineages. Of the 355 samples analysed, 25 (7.0%) tested positive for PPRV RNA, with positive detections in all three surveyed regions (Poro, Tchologo and Bagoué). The four samples with the lowest Cq values, originating from all three administrative regions, were successfully sequenced, generating genomes that covered 82.0%-86.2% of the reference genome at a depth of ≥ 10 ×. The missing regions were mainly located at the 5' and 3' genomic termini, as well as in limited internal regions associated with amplicon dropout. Phylogenetic analysis revealed that all four sequences belonged to lineage IV and exhibited high nucleotide similarity (98.1%-99.9%). The Ivorian strains clustered with recent lineage IV viruses from West, North and Central Africa, whereas historical Ivorian lineages I and II formed distinct clades. These findings confirm the predominance of lineage IV in northern Côte d'Ivoire and provide baseline genomic data to support molecular epidemiological surveillance in the region.

PPRV↗
PubMed2026

A modular class-aware workflow for small RNA sequencing analysis using mouse sperm as a case study.

BACKGROUND: Small RNA sequencing analysis is challenging because RNA classes differ in biogenesis, sequence redundancy, genomic organization, and annotation reliability. Integrated workflows accommodating these constraints remain limited, particularly for fragment-level and cluster-level analysis. METHODS: We present a reproducible, containerized, class-aware workflow for small RNA sequencing analysis, using mouse sperm as a case study. The workflow combines standardized preprocessing with complementary annotation and quantification strategies for microRNAs (miRNAs), transfer RNA-derived small RNAs (tsRNAs), ribosomal RNA-derived small RNAs (rsRNAs), and PIWI-interacting RNA (piRNA)-enriched genomic clusters. Using sperm small RNA data from offspring of lipopolysaccharide (LPS)-exposed male mice, we compared integrated-reference mapping, multi-class annotation, fragment-level tsRNA profiling, and genome-based piRNA cluster analysis, with custom modules for locus-aware harmonization and condition-specific cluster analysis. RESULTS: Integrated-reference mapping aligned 88.17% of reads and retained 690 features after filtering. It identified 11 differentially expressed miRNAs between LPS and controls, while other classes showed limited signal. Fragment-level profiling improved tsRNA resolution. piRNA cluster analysis identified 958 control and 940 LPS clusters, with 18 control-specific and no LPS-specific clusters. CONCLUSION: This workflow supports transparent, reproducible, class-aware interpretation of small RNA sequencing data while emphasizing cautious interpretation of piRNA-enriched signals from total small RNA sequencing.

Small non-coding RNA analysis↗
PubMed2024

Detecting inbreeding depression in structured populations.

Measuring inbreeding and its consequences on fitness is central for many areas in biology including human genetics and the conservation of endangered species. However, there is no consensus on the best method, neither for quantification of inbreeding itself nor for the model to estimate its effect on specific traits. We simulated traits based on simulated genomes from a large pedigree and empirical whole-genome sequences of human data from populations with various sizes and structures (from the 1,000 Genomes project). We compare the ability of various inbreeding coefficients ([Formula: see text]) to quantify the strength of inbreeding depression: allele-sharing, two versions of the correlation of uniting gametes which differ in the weight they attribute to each locus and two identical-by-descent segments-based estimators. We also compare two models: the standard linear model and a linear mixed model (LMM) including a genetic relatedness matrix (GRM) as random effect to account for the nonindependence of observations. We find LMMs give better results in scenarios with population or family structure. Within the LMM, we compare three different GRMs and show that in homogeneous populations, there is little difference among the different [Formula: see text] and GRM for inbreeding depression quantification. However, as soon as a strong population or family structure is present, the strength of inbreeding depression can be most efficiently estimated only if i) the phenotypes are regressed on [Formula: see text] based on a weighted version of the correlation of uniting gametes, giving more weight to common alleles and ii) with the GRM obtained from an allele-sharing relatedness estimator.

Humans↗
PubMed2026

URMD-Seq: A high-throughput method for scalable detection of ultra-rare mutations in the human mitochondrial genome.

The study of mitochondrial genetics has long been limited to polymorphisms and high frequency mutations owing in part to technical and technological limitations in reliably detecting and quantifying rare somatic mutations. Over the past decade or so, the study of rare somatic mitochondrial DNA (mtDNA) variants has expanded and continues to garner increasing interest in a wide range of research fields. Here, we describe Ultra-Rare Mutation Detection-Sequencing (URMD-Seq), a high-throughput method that combines unique molecular identifier (UMI)-based library preparation and Next Generation Sequencing (NGS) for the accurate and scalable detection of ultra-rare mutations in the mtDNA control region. Our method exploits degenerate primers to label individual mtDNA molecules. This is followed by several purification, quantification and amplification steps, to obtain high quality amplicons for sequencing on the Illumina MiSeq platform. Our approach enables the use of total genomic DNA extract as starting point for the assay, overcoming the need for organelle isolation and/or mtDNA enrichment, hence broadening the type of specimen that can be studied, while offering cost and time benefits. The assay described herein has been demonstrated to reliably measure variants present at on average 0.09%, but as low as 0.03%, variant allele frequency in a variety of tissues, including fresh and frozen biobanked specimens. Using this protocol, library preparation of 300 specimens can be completed by a single individual with general nucleic acid handling experience in approximately 20 days. Given its flexibility and scalability, URMD-Seq is particularly well suited for epidemiological studies using a large number of specimens.

Humans↗
PubMed2025

Analytical and clinical performance validation of HPV-SEQ, a novel NGS-based liquid biopsy platform for detection and quantification of human papilloma virus circulating tumor DNA.

BACKGROUND: Human papillomavirus (HPV) is the primary causative driver of oropharyngeal squamous cell carcinoma (OPSCC). Accurate detection of HPV-DNA is critical for risk stratification and management of OPSCC. However, assays designed to detect HPV in primary tumors do not allow monitoring of HPV-DNA over time, whereas commercially available droplet digital PCR-based methods for assessment of circulating cell free (cf)HPV-DNA in plasma remain suboptimal, hindering adaptation into clinical practice. We have developed HPV-SEQ, a novel next-generation-sequencing (NGS) based method for detection and quantification of HPV16/18 DNA in plasma of patients with OPSCC. METHODS: The assay uses primers targeting the L1 gene of HPV16 and HPV18 viral genomes and strain specific calibrators at a defined concentration to determine the ratio of native HPV to a known standard, enabling accurate reporting of patient-derived HPV16/18 viral load in a sample. This study was conducted using two different patient populations in addition to healthy donors and contrived material. All experiments were performed to fulfill several applicable analytical, performance and validation guidelines. RESULTS: A thorough analytical characterization and clinical validation of this platform demonstrates that HPV-SEQ detects cfHPV-DNA with exceptional limit of quantification and high precision, providing a foundation for integrating this platform into clinical settings. CONCLUSIONS: This ultra-sensitive HPV profiling method with optimal analytical performance may represent a significant advancement in risk stratification, treatment management, and post-treatment surveillance for patients with OPSCC.

Humans↗
PubMed2026

Improvement the accuracy and reproducibility of telomere length measurement utilizing qPCR.

Telomere length serves as a well-established molecular biomarker for evaluating aging and age-associated diseases. Among various methods, quantitative PCR for telomere length detection is convenient, rapid, cost-effective, and capable of high-throughput analysis in large epidemiological cohorts. However, numerous studies have indicated that issues related to differences in DNA quality caused by DNA extraction process significantly affect the accuracy and reproducibility of qPCR-based telomere length quantification. Initially, we established a model of DNA integrity variation, by utilizing nucleic acid endonucleases of serial activity units to cleave genomic DNA, generating DNA with varying degrees of degradation. The integrity of DNA templates decreases, the reduction of long fragments and the increase of short fragments in the mixed telomere products are the causes of the disruption in Ct values. Moreover, compared with longer reference gene amplicons, the short-segment internal gene reference can reduce the impact of genomic integrity on its amplification. Subsequently, we utilized additional gel excision purification to reduce degradation products. It was found that gel excision processing provides the best stability for telomere length detection with the lowest coefficient of variation. Additionally, the introduce of another calibrator sample, which is used for to adjust the T/S value of the test sample, narrows the deviation between qPCR-derived telomere length and gold-standard Terminal Restriction Fragment (TRF) measurements. Collectively, these results reveal that gel excision purification supports stable telomere detection. Calculating the correction coefficient incorporating the short internal reference and calibrator minimizes measurement deviations relative to sample TRF values.

Telomere↗
PubMed2026

Dogme: a nextflow pipeline for reprocessing nanopore RNA and DNA modifications.

MOTIVATION: Oxford Nanopore (ONT) sequencing allows for the direct detection of RNA and DNA modifications from unamplified nucleic acids, which is a significant advantage over other platforms. However, the rapid updates to ONT basecalling models and the evolving landscape of computational tools for modification detection bring about challenges for reproducible and standardized analyses. To address these challenges, we developed Dogme to automate basecalling, alignment, modification detection, and transcript quantification. Dogme automates the reprocessing of ONT POD5 files by integrating basecalling using Dorado, read mapping using minimap2 and subsequent analysis steps such as running modkit. The pipeline supports three major types of sequencing data-direct RNA (dRNA), complementary DNA (cDNA), and genomic DNA (gDNA). Dogme facilitates detection of diverse RNA modifications supported by Dorado such as N6-methyladenosine (m6A), 5-methylcytosine (m5C), inosine, pseudouridine, 2'-O-methylation (Nm) and DNA methylation, while concurrently quantifying full-length transcript isoforms LR-Kallisto for transcript quantification for dRNA and cDNA. RESULTS: We applied Dogme to three separate mouse C2C12 myoblast replicates using direct RNA sequencing on MinION flow cells. We detected 96 603 m6A, 43 476 m5C, 8829 inosine, 10 055 pseudouridine, and 30 320 Nm sites in three biological replicates. The pipeline produced reproducible modification profiles and transcript expression levels across replicates, demonstrating its utility for integrative long-read transcriptomic and epigenomic analyses. AVAILABILITY AND IMPLEMENTATION: Dogme is implemented in Nextflow and is freely available under the MIT license at https://github.com/mortazavilab/dogme, with documentation provided for installation and usage.

RNA↗
PubMed2026

Multi-season analysis reveals hundreds of drought-responsive genes in sorghum.

Persistent drought affects global crop production and is becoming more severe in many parts of the world in recent decades. Deciphering how plants respond to drought will facilitate the development of flexible mitigation strategies. Sorghum bicolor L. Moench (sorghum), a major cereal crop and an emerging bioenergy crop, exhibits remarkable resilience to drought. To better understand the molecular traits that underlie sorghum's remarkable drought tolerance, we undertook a large-scale sorghum gene expression profiling effort, totaling nearly 1500 transcriptome profiles, across a 3-year field study with replicated plots in California's Central Valley. This study included time-resolved gene expression data from roots and leaves of two sorghum genotypes, BTx642 and RTx430, with different pre-flowering and post-flowering drought-tolerance adaptations under control and drought conditions. Quantification of genotype-specific drought tolerance effects was enabled by de novo sequencing, assembly, and annotation of both BTx642 and RTx430 genomes. These reference-quality genomes were used to construct a pangene set for characterizing conserved and genotype-specific expression. By integrating time-resolved transcriptomic responses to drought in the field across three consecutive years, we identified a set of 726 drought-responsive genes that responded similarly in all 3 years of our field study. Functional enrichment analysis identified abiotic stress, secondary cell wall-related processes and metabolism as particularly affected under both types of drought stress. We also found that some glyoxylate cycle pathway genes, including malate synthase and isocitrate lyase, are differentially regulated particularly during post-flowering drought stress, implicating this pathway as potentially important for drought responsiveness. This expansive dataset represents a unique resource for sorghum and drought research communities and provides a methodological framework for the integration of multi-faceted time-resolved transcriptomic datasets.

Sorghum↗
PubMed2026

Receptor-defined targeting of a genomically unique melanoma-enriched noncanonical antigen.

Effective T cell-based immunotherapies require functional receptors that can be engineered and redeployed to recognize tumor-restricted antigens. Noncanonical peptides arising from transcription outside annotated protein-coding regions expand the antigenic landscape of cancer; however, systematic strategies to biologically prioritize and functionally validate such targets remain underdeveloped. Here, we integrated de novo transcript analysis, exon-resolved quantification, RNA in situ hybridization, and immunopeptidomics to identify melanoma-associated noncanonical transcripts and advance candidates through receptor-level validation. Among three recurrent melanoma-associated transcripts, EVA003 emerged as a lead target based on its distinct repeat-enriched genomic architecture, consistent tumor-enriched exon-level expression across independent datasets, and a genomically unique immunogenic core sequence. We demonstrate endogenous presentation of EVA003-derived peptides on HLA-A*03:01 and detect specific reactivity in patient-derived tumor-infiltrating lymphocytes. Single-cell transcriptomic profiling identified a dominant peptide-reactive clonotype, enabling isolation of a naturally occurring T cell receptor. Transfer of this receptor into healthy donor T cells conferred antigen-dependent activation and cytotoxicity against both peptide-pulsed targets and melanoma cells expressing EVA003 endogenously. Together, these findings establish a biologically informed strategy for prioritizing noncanonical tumor antigens and demonstrate that genomically unique, tumor-enriched noncanonical peptides can be presented to molecularly defined receptors capable of mediating cancer cell killing. These findings support the integration of prioritized noncanonical antigens into engineered T cell therapeutic strategies.

Humans↗
PubMed2026

Cytonuclear conflict and reticulate evolution in the Morelloid clade (Solanum, Solanaceae): Insights from genome skimming and network Phylogenomics.

The Morelloid clade (black nightshades) is one of the most strongly supported clades within the megadiverse Solanum genus. It comprises 76 globally distributed, non-spiny herbaceous and suffrutescent species. While often erroneously considered poisonous weeds, several species are economically important as orphan crops. The clade is closely related to tomato and potato but, due to a lack of focused breeding efforts, remains a putative reservoir of genetic diversity for crop improvement. Despite this potential, we lack fundamental knowledge on the evolution of the Morelloid clade. The group includes polyploid species with unknown parental origins-likely reflecting reticulate processes such as hybridization, introgression, and associated backcrossing events. Prior analyses have been unable to disentangle these processes, leaving the mechanisms underlying reticulate evolution in the Morelloid clade poorly understood. Here, we use genome skimming to produce a well-supported maximum likelihood plastid phylogeny from complete circularized plastomes and a coalescent-based species tree from combined Angiosperms353 and conserved ortholog set nuclear markers. Our dataset, composed of previously published data and deep genome skimming from herbarium samples, spans 26 Morelloid species. To investigate phylogenetic discordance, we used a nuclear phylogenetic network, multispecies coalescent simulations, a fused rooted nuclear chloroplast tree, and quantification of nuclear gene tree concordance. We show that incongruence between nuclear and plastid trees is pervasive and cannot be explained by incomplete lineage sorting alone. Instead, our results demonstrate that events consistent with repeated chloroplast capture have shaped the reticulate evolutionary history of the clade, especially among African polyploid and Pan-American diploid lineages.

Phylogeny↗
PubMed2026

Alternative End Joining Dependency Imposed by miR-21-5p Defines Radiation Resistance and a Targetable Vulnerability in Oral Squamous Cell Carcinoma.

PURPOSE: Clinical control of oral squamous cell carcinoma (OSCC) is constrained by heterogeneous radiosensitivity driven by divergent DNA damage response programs. The architecture and functional contribution of alternative end joining (Alt-EJ), an error-prone DNA double-strand break (DSB) repair pathway frequently upregulated in cancer, to radiation resistance remains poorly defined. METHODS AND MATERIALS: We profiled microRNAs in radioresistant OSCC clones and performed multiomic integration across an institutional OSCC cohort, an external OSCC cohort from the Gene Expression Omnibus, The Cancer Genome Atlas pan-cancer tumors, and cell lines characterized by Sanger Genomics of Drug Sensitivity in Cancer to infer DNA damage response characteristics, genomic scar features, drug sensitivity, and radiation therapy outcomes. DSB repair capacity and pathway usage were validated using functional assays, including Alt-EJ reporters and droplet digital PCR quantification of microhomology-mediated repair events. Core Alt-EJ effectors such as PARP1 and POLQ were perturbed genetically and pharmacologically. Therapeutic efficacy of PARP or POLQ inhibition with or without irradiation was tested in a syngeneic OSCC model, followed by bulk tumor transcriptomics to assess pathway engagement. RESULTS: Upregulation of miR-21-5p was not only selectively detected in radioresistant OSCC, but also modulated radiosensitivity in vitro and in vivo, and was associated with inferior postradiation therapy survival. A calibrated miR-21-5p target-gene signature tracked Alt-EJ activity across patient and mouse tumors and cancer cell lines, correlated with microhomology-mediated indels and broader genomic scarring, and predicted sensitivity to clinically available PARP inhibitors. Functionally, enforced miR-21-5p expression increased Alt-EJ usage and accelerated DSB repair, whereas inhibition or depletion of key Alt-EJ effectors reduced repair efficiency and restored radiosensitivity. In vivo, Alt-EJ targeting with PARP or POLQ inhibitor abrogated miR-21-5p-driven radiation resistance; transcriptomic profiling supported suppression of Alt-EJ programs as the operative mechanism. CONCLUSIONS: These findings establish a mechanistic link between miR-21-5p activity and Alt-EJ dependence, provide a clinically deployable signature to identify Alt-EJ-dependent OSCC, and support rational combinations of Alt-EJ targeting agents with radiation therapy to overcome treatment failure and advance precision radiation oncology.

MicroRNAs↗
PubMed2025

FootprintCharter: unsupervised detection and quantification of footprints in single molecule footprinting data.

SUMMARY: Single molecule footprinting profiles the heterogeneity of TF occupancy at cis-regulatory elements across cell populations at unprecedented resolution. The single molecule nature of the data in principle allows for observing the footprint of individual transcription factors and nucleosomes. However, we currently lack algorithms to quantify these occupancy patterns of chromatin binding factors in an automated way and without prior assumptions on their genomic location. Here we present FootprintCharter, an unsupervised tool to detect and quantify footprints for transcription factors (TFs) and nucleosomes from single molecule footprinting data. After detection, TF footprints can be labeled with orthogonal motif annotations provided by the user. FootprintCharter allows for the quantification of complex molecular states such as positioning of unphased nucleosomes and combinatorial co-binding of multiple TFs. AVAILABILITY AND IMPLEMENTATION: FootprintCharter is freely available on Bioconductor with version 2.2.0 of https://bioconductor.org/packages/SingleMoleculeFootprinting through the functions FootprintCharter, PlotFootprints, and Plot_FootprintCharter_SM.

Transcription Factors↗
PubMed2026

Target Antigen Identification for Antibody Drug Conjugate Therapy in Biliary Tract Cancer.

BACKGROUND: Data on antibody-drug conjugates (ADCs) target expression prevalence, intertumoral heterogeneity, genomic concordance, and its effect on clinical outcomes is limited in biliary tract cancers (BTC). METHODS: Resected primary BTC specimens, and when available, matched metastatic samples were assembled into tissue microarrays and tested for CLDN18.2, c-MET, Nectin-4, TROP2, and HER2 expression by immunohistochemistry (IHC). A subset underwent targeted next-generation sequencing using MSK-IMPACT (NCT01775072). Exploratory associations of target expression with clinicopathologic parameters, genomic alterations, recurrence-free (RFS), and overall (OS) survival were evaluated. RESULTS: 65 patients with resected BTC and 18 paired metastatic sites were identified-43% extrahepatic cholangiocarcinoma, 40% intrahepatic cholangiocarcinoma, and 17% gallbladder cancer. All evaluated target antigens were expressed; percent positivity and H-score ≥200 were: TROP2 (83%, 26%), c-MET (75%, 26%), Nectin-4 (66%, 35%), and CLDN18.2 (46%, 7.7%). HER2 overexpression occurred in 3.1% of tumors. Overall agreement among paired primary and metastatic samples on calling either positive or negative ranged from 43% to 75% with the highest observed for HER2 [75%; κ=0.29 (95%CI: -0.32 to 0.91)] and TROP2 (71%; κ not available) and lowest for c-MET, CLDN18.2, and Nectin-4. Frequently altered genes included TP53 (36%), SMAD4 (27%), ELF3 (21%). We observed no significant association between target antigen expression with genomics, RFS, or OS. CONCLUSIONS: BTC displays frequent but heterogeneous expression of multiple ADC targets. These hypothesis generating findings suggest inherent complexity of target protein quantification, target threshold determination, and target sampling discordance. Future studies will be required to refine our understanding the utlitiy of ADCs in BTC.

Journal Article↗
PubMed2025

Using homologous network to identify reassortment risk in H5Nx avian influenza viruses.

The resurgence of H5Nx reassortment has caused multiple epidemics resulting in severe disease even death in wild birds and poultry. Assessing H5Nx reassortment risk is crucial for designing targeted interventions and enhancing preparedness efforts to manage H5Nx outbreaks effectively. However, the complexity in H5Nx reassortment, driven by the diversity of influenza A viruses (IAVs) and wide range of hosts, has hindered the effective quantification of reassortment risk. In this study, we utilized a network approach to explore the reassortment history using a large-scale dataset. By inferring genomic homogeneity among IAVs, we constructed an IAVs homologous network with reassortment history embedded within it. We estimated the communities within the IAVs homologous network to represent the reassortment risk of various viruses, revealing diverse reassortment risks across different H5Nx viruses. Our analysis also identified the primary hosts contributing to reassortment: domestic poultry in China, and wild birds in North America and Europe. These primary hosts are critical targets for future H5Nx reassortment interventions. Our study provides a framework for quantifying and ranking H5Nx reassortment risk, contributing to enhanced preparedness and prevention efforts.

Animals↗
PubMed2025

Quantitative temporal analysis of pancreatic islet T lymphocyte and macrophage infiltration heralded by serum IgE in congenic BioBreeding (BB) Gimap5-/- rats at risk for insulitis and acute onset diabetes.

OBJECTIVE AND DESIGN: The objective was to determine the association between serum IgE levels and the infiltration order of T lymphocytes and macrophages in pancreatic islets in relation to the loss of insulin and glucagon cells in presymptomatic congenic BB Gimap5-DP (Diabetes Prone) rats. MATERIAL: Congenic prediabetes BB Gimap5-DP and control Gimap5-DR (Diabetes Resistant) rats were followed every other day from 29 to 32 days of age until peak serum IgE (≤ 55 days of age). METHODS: Serum IgE was measured using ELISA. The HALO™ platform facilitated quantitative image analysis of infiltrating T lymphocytes, macrophages, and target organ insulin and glucagon cells. Whole genome sequencing (WGS) was employed to identify candidate type 1 diabetes genes. RESULTS: Serum IgE levels increased with age in normoglycemic BB Gimap5-DP rats. Quantification of infiltrating cells per mm2 in and around the islets indicated that T lymphocytes are the initial infiltrators, followed by macrophages. Elevated serum IgE levels inversely correlated with beta-cell mass (total mg insulin/mg pancreas). WGS refined the risk segment for islet inflammation to 1.02 Mbp, leaving 10 candidate genes, including Gimap4 and Gimap5. CONCLUSIONS: Elevated IgE levels herald T lymphocyte and macrophage infiltration. Pancreatic islet inflammation was linked to Gimap4, Gimap5, and other potential candidate genes on rat chromosome 4.

Animals↗
PubMed2026

Potato Black Scurf and Stem Canker: Pathogen Biology, Global Distribution, and Traditional and Modern Diagnostics.

Rhizoctonia solani is a soil- and seed-borne fungal pathogen of potatoes. It is a persistent threat to potato production worldwide. The symptoms appear as black scurf on tubers and stem canker, causing severe yield and quality losses of potatoes. The pathogen reproduces asexually via hyphae and sclerotia. Its genetic diversity is organized into anastomosis groups (AGs), with AG3-PT being the predominant group on potato. The global trade of seed potatoes is very important for agricultural development; however, it has facilitated the dissemination of the pathogen across regions. Moreover, disease development is affected by environmental and agronomic factors, causing variable symptom severity and differential economic impacts. Given the pathogen's genetic complexity, accurate diagnosis is very important, necessitating a transition from traditional culture-based and biochemical methods toward molecular, genomic, and emerging digital technologies. Methods such as PCR, isothermal amplification, sequencing, sensor-based biosensing, and artificial intelligence-driven imaging have improved the detection, quantification, and noninvasive monitoring of the pathogen. Combining these diagnostic methods into a tiered framework will be helpful for precision disease surveillance, informed disease management decision-making, and the development of sustainable potato production systems.

black scurf↗
PubMed2026

De Novo Genome Sequence Assembly of the Algal Endosymbiont Micractinium conductrix Derived From Its Host Paramecium bursaria 186b.

Endosymbiosis is a major driver of evolutionary innovation and underpins the function of diverse ecosystems. The origins and evolution of endosymbiosis are challenging to study experimentally due to the short-lived culturability of many microbial strains derived from endosymbiotic interactions. The facultative endosymbiosis between the ciliate, Paramecium bursaria, and the green alga, Micractinium conductrix (Chlorellaceae, Trebouxiophyceae), is ecologically widespread and has emerged as a powerful lab-tractable model system. This endosymbiosis is founded upon a reciprocal nutrient exchange, but each of the species can be cultured independently enabling quantification of symbiotic fitness effects, new partnerships to be generated in the lab, and co-associations to be subject to experimental evolution. To date, evolve-and-resequence approaches have been limited due to a lack of high-quality genome assemblies enabling gene variants to be identified. Here, we report a near telomere-to-telomere genome assembly for M. conductrix 186b, using a range of sequencing technologies. Comparative analysis shows that this is one of the most complete Chlorellaceae algal genome assemblies available to date. To aid accurate gene calling and annotation, we conducted both RNAseq and Iso-Seq transcriptome sequencing experiments. Collectively, these 'omics datasets will facilitate: (i) comparative genomics studies of endosymbiont evolution, (ii) evolve-and-resequence experiments, (iii) genome-scale metabolic modeling studies, and (iv) identification of targets for genetic modification experiments and biotechnological applications.

Symbiosis↗
PubMed2026

Uniform processing and analysis of IGVF massively parallel reporter assay data with MPRAsnakeflow.

As researchers and clinicians seek to identify human genomic alterations relevant to traits and disorders, identifying and aggregating evidence providing mechanistic support for associations between alterations and phenotypes remains challenging. In particular, the study of noncoding genomic variation remains a major challenge because of the lack of accurate functional annotation for activity in a given context and across alleles. Experimental evidence is critical for prioritizing and interpreting functional effects of genetic alterations. Massively parallel reporter assays (MPRAs) have emerged as a powerful high-throughput approach, enabling quantification of regulatory element activity and allelic effects, as well as systematic dissection of gene regulatory logic and variant effects across different contexts. However, the diversity of MPRA designs, lack of standardized formats, and many potential processing parameters hamper data integration, reproducibility, and meta-analyses across studies. To address these challenges, the Impact of Genomic Variation on Function (IGVF) Consortium established an MPRA focus group to develop community standards, including harmonized file formats, and robust analysis pipelines for a wide range of library types and experimental designs. Here, we present these formats and comprehensive computational tools, MPRAlib and MPRAsnakeflow, for uniform processing from raw sequencing reads to counts, processing, and visualization. Using diverse MPRA data sets, we investigated technical variability sources including barcode sequence bias, outlier barcodes, and delivery method (episomal vs. lentiviral). Our results establish best practices for MPRA data generation and analysis, facilitating robust, reproducible research and large-scale integration. The presented tools and standards are publicly available, providing a foundation for future collaborative efforts in regulatory genomics.

Humans↗