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PubMed2026

Holistic approaches for improvement of maize resistance against lodging stress: current status and future perspective.

Lodging is a major constraint in maize production, causing significant yield losses, reduced grain quality, and harvesting inefficiencies, thereby posing a serious challenge to global food security and climate-resilient agriculture. This review synthesizes current knowledge on the genetic, physiological, and agronomic determinants of maize lodging resistance and evaluates holistic strategies for improving tolerance to lodging stress. Recent advances in quantitative trait locus (QTL) mapping, genome-wide association studies (GWAS), functional gene characterization, genome editing, high-throughput phenotyping, and precision agronomy have provided powerful tools to enhance stalk biomechanics, root anchorage, and adaptive plant architecture. Integrating genomic discovery with advanced phenomics and optimized agronomic management offers a scalable framework for accelerating the development of high-yielding, lodging-resilient maize cultivars. However, critical gaps remain in understanding the genetic coordination between stalk strength and root system architecture, integrating multi-omics approaches to unravel regulatory networks, validating genome-editing interventions across diverse agro-ecologies, and developing environment-responsive predictive breeding models and cost-effective phenotyping tools, particularly for stress-prone regions. Addressing these challenges through coordinated multi-environment trials and integrative molecular-agronomic strategies will facilitate the translation of genomic discoveries into climate-resilient, high-performing maize cultivars. By consolidating molecular insights with applied breeding and management practices, this review provides a comprehensive framework that guides researchers in designing genome-informed and field-validated approaches to improve maize resistance to lodging stress and support sustainable crop production systems.

Zea mays↗

PubMed2026

The emerging impact of CRISPR and gene editing on global crop improvement.

The advent of CRISPR-based genome editing has revolutionized crop improvement, offering unprecedented precision and efficiency in modifying key agronomic traits. This review comprehensively examines the mechanisms, applications, and future potential of CRISPR technology in enhancing global crop production. CRISPR-Cas systems, originally identified as adaptive immune mechanisms in bacteria and archaea, have been repurposed for targeted genome editing in plants. The CRISPR-Cas9 system, in particular, has emerged as a powerful tool for introducing site-specific double-strand breaks, enabling precise genetic modifications. The three-stage process of adaptation, expression, and interference underlies the CRISPR mechanism, with guide RNAs directing Cas endonucleases to specific genomic loci. Advances in CRISPR technology have expanded its applications beyond gene knockouts, encompassing base editing, prime editing, and epigenome editing. These innovations have facilitated the development of crops with enhanced yield, stress tolerance, disease resistance, nutritional content, and post-harvest quality. However, challenges related to off-target effects, regulatory hurdles, ethical concerns, and public acceptance must be addressed to fully harness the potential of CRISPR in agriculture. Integration of CRISPR with other cutting-edge technologies, such as synthetic biology, artificial intelligence, and high-throughput phenotyping, holds immense promise for accelerating crop improvement efforts. As research continues to refine CRISPR tools and expand their applicability across diverse plant species, this transformative technology is poised to play a pivotal role in shaping a sustainable, resilient, and productive global food system for future generations.

Gene Editing↗

PubMed2026

Barcoded mutant library enables high-throughput functional genomics in a filamentous fungus.

Advances in sequencing technology enabling rapid and inexpensive whole-genome sequencing highlight how few genes are functionally characterized. This problem is particularly acute in filamentous fungi, where even in the best studied organisms upward of half of genes are poorly characterized or unannotated. High-throughput tools to identify gene function exist for single-celled organisms, like yeast and bacteria. However, filamentous fungi present challenges to high-throughput gene characterization, including low transformation efficiency and multinucleate cells. Filamentous fungi are critical components of nutrient cycling in ecosystems, form symbioses with plants that improve nutrient uptake, and are devastating human, plant, and animal pathogens causing millions of deaths and substantial crop loss each year. Thus, it is critical to overcome challenges to rapid gene characterization in filamentous fungi. We generated a library of hundreds of millions of uniquely barcoded plasmids containing a broad host-range drug resistance marker for ectopic insertion into filamentous fungal genomes by Agrobacterium tumefaciens. We then optimized A. tumefaciens mediated transformation of the biocontrol agent Trichoderma atroviride and made an insertional mutagenesis library containing 83,311 barcoded insertions, disrupting 5,331 of 11,863 predicted genes. This library enables high-throughput screens to rapidly connect genotype to phenotype. Quantifying relative barcode abundance in the pooled library before and after exposure to experimental conditions identified candidate genes and recovered known pathway components in amino acid biosynthetic, fructose utilization, and xylose utilization pathways. This resource establishes a scalable platform for high-throughput functional genomics in filamentous fungi, enabling investigations of fungal biology to improve medical outcomes, biotechnology, and sustainable agriculture.

Genomics↗

PubMed2026

Analysis of deep-resequencing data of 984 soybean accessions reveals structural variations underlying agronomic traits.

Genomic structural variants (SVs) are major sources of genetic variation and have profound impacts on phenotypic traits. However, their functional effects remain largely unexplored in soybean. Here, we resequence 940 soybean accessions. Together with 44 publicly available datasets, we identify 602,281 SVs. Using a graph-based genome, we detect an additional 58,760 presence/absence variations (PAVs) that broadly affect gene expression. Population genomic analyses reveal that SVs serve as a core driving force for soybean domestication and improvement. Integrating SVs with QTLs for oil and protein content, and performing GWAS on 27 traits, we identify key functional SVs. These include transposable element insertions altering seed coat color, multiple insertions within a cytochrome P450 gene modifying flower and hypocotyl color, and a GmMATE1 deletion enhancing seed size. Together, our study establishes a comprehensive SV map of soybean, offering a valuable resource for dissecting the genetic basis of complex traits to accelerate molecular breeding.

Glycine max↗

PubMed2026

Comprehensive Analysis of miRNAs and Predicted Protein Interaction Networks in Skeletal Muscle Development of Myostatin-Deficient Rabbits.

Myostatin (MSTN), encoded by the MSTN gene, is a critical negative regulator of skeletal muscle mass. This study aims to identify and characterize the miRNAs involved in the development of the double-muscling phenotype in MSTN-deficient rabbits. We performed high-throughput sequencing to analyze the miRNA expression profiles in gluteus maximus tissue from wild type (MSTN+/+) and MSTN-KO (MSTN+/- and MSTN-/- inclusive) rabbits. Differentially expressed miRNAs (DEmiRNAs) were identified, and their potential target genes were predicted. Functional enrichment analysis of these target mRNAs was conducted using Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) database to elucidate the involved biological pathways and regulatory networks. A total of 25 DEmiRNAs (13 downregulated and 12 upregulated, |log2FC| ≥ 1.0, adjusted p < 0.05) and 1178 differentially expressed mRNAs (408 upregulated and 770 downregulated, |log2FC| ≥ 2.0, adjusted p < 0.05) were identified in MSTN-KO compared to MSTN+/+ rabbits. Bioinformatics analysis revealed that the target genes of these DEmiRNAs were significantly enriched in key pathways governing muscle growth and metabolism, including the PI3K-Akt signaling pathway, MAPK signaling pathway, and pathways related to ECM-receptor interaction and insulin signaling. Notably, many predicted target mRNAs are expressed by genes that encode key inhibitors of myogenesis (e.g., HDAC4) and major extracellular matrix components (e.g., COL4A3, POSTN). Our results demonstrate that MSTN deficiency induces a distinct and widespread change in the miRNA expression landscape of skeletal muscle.

Animals↗

PubMed2026

Pilot study identifying distinct circulating proteomic profiles associated with longitudinal CT-defined fibrotic and inflammatory sarcoidosis.

INTRODUCTION: Pulmonary sarcoidosis exhibits heterogeneous clinical trajectories ranging from self-limited disease resolution to chronic progressive fibrosis, yet reliable biomarkers capable of distinguishing these disease patterns remain lacking. Whether longitudinal CT-defined sarcoidosis phenotypes are associated with distinct circulating molecular signatures remains unknown. METHODS: We performed high-throughput plasma proteomics (SomaScan 11K) in participants with pulmonary sarcoidosis classified into longitudinal chest CT-defined progressive fibrosis, progressive nodular inflammatory disease, or resolving disease trajectories, along with healthy controls. CT phenotypes were assigned based on predefined longitudinal changes in reticulation, traction bronchiectasis, nodular involvement, and mediastinal lymphadenopathy across serial CT scans. One plasma sample per participant was selected from the study visit corresponding to the CT time point at which criteria for the assigned longitudinal phenotype were met. Principal component analysis, hierarchical clustering, pathway enrichment, and correlation-based analyses linking protein expression to quantitative CT features were used to evaluate whether distinct longitudinal CT phenotypes were associated with divergent proteomic signatures. RESULTS: Principal component analysis and hierarchical clustering suggested partial segregation by CT-defined phenotype. Longitudinal CT phenotypes were associated with distinct pathway-level proteomic signatures, with progressive fibrosis enriched for epithelial-mesenchymal transition signaling, and progressive nodular inflammatory disease enriched for mTORC1, MYC, oxidative phosphorylation, adipogenesis, and fatty acid metabolism pathways. Correlation analyses showed coordinated protein-expression patterns associated with fibrotic CT features and mediastinal lymph node enlargement. DISCUSSION: These findings suggest that longitudinal CT-defined fibrotic and inflammatory sarcoidosis phenotypes are associated with distinct pathway-level proteomic signatures. This pilot study provides preliminary proof-of-concept evidence that integrating longitudinal CT imaging phenotypes with plasma proteomics may serve as a framework for future mechanistic studies and biomarker discovery in pulmonary sarcoidosis.

Humans↗

PubMed2026

Molecular diagnostic yield and barriers in inherited retinal diseases: a retrospective cohort study.

OBJECTIVE: To evaluate the diagnostic yield of panel-based genetic testing for inherited retinal diseases (IRDs) and identify barriers to molecular resolution. DESIGN: Retrospective cohort. PARTICIPANTS: A total of 404 patients with clinically confirmed IRDs who were evaluated at the Adult Inherited Retinal Dystrophy Service, Ontario, Canada (October 2021-September 2024). METHODS: Patients underwent targeted massive parallel sequencing panel testing. Diagnostic yield was calculated, and unresolved cases were reviewed. Associations between yield, phenotype, ethnicity, and sex were assessed using χ² analysis. RESULTS: Of 685 referrals, 570 had confirmed IRDs. After we excluded 140 pending results and 26 patients who declined testing, 404 patients were analyzed. At referral, 94 patients (23.2%) had a previous molecular diagnosis, and 138 (34.0%) were diagnosed through clinic-initiated testing, giving an overall yield of 57.4%. Yield varied significantly by phenotype (χ², P = 1.4 × 10⁻⁶), from 94.4% in vitelliform macular dystrophies to 25.0% in vitreoretinopathies, with no sex association (P = 1.0). Disease-causing variants were identified in 83 IRD-associated genes, most frequently ABCA4, USH2A, and BEST1. Of 172 unresolved cases, 62 (36.0%) had negative panels, and 110 (63.9%) were inconclusive, including 30 with unphased pathogenic variants in recessive genes and 10 with high-suspicion variants of uncertain significance. Key barriers included limited family availability for phasing, restricted access to functional assays, and lack of public coverage for whole-exome or whole-genome sequencing. CONCLUSIONS: Massive parallel sequencing-based panel testing achieved a 57% diagnostic yield in this IRD population. Success was strongly phenotype-dependent with substantial heterogeneity. Whole-exome sequencing, whole-genome sequencing, family segregation, and functional genomics could improve diagnostic outcomes and management.

Humans↗

PubMed2026

ClearDepthIAS enables automated high-throughput quantification of roots in soil-grown taproot crops.

Understanding root system architecture is critical for improving crop productivity and resilience, yet phenotyping root traits such as root growth angle and rooting depth remains technically challenging, especially at high throughput. Here, we present ClearDepthIAS, a high-throughput imaging and analysis platform that enables nondestructive, automated quantification of root architecture traits in taproot system crops. By capturing and stitching 360° images of roots growing along the transparent walls of pots and applying deep learning-based segmentation (ClearDepth-WRT), we measured wall root shallowness (WRS)-a proxy for root growth angle-with high precision. We demonstrated for the tap root systems of soybean and canola that the system accurately detects root tips, quantifies their vertical distribution, and extracts biologically meaningful traits such as root area, distribution indices, and growth angles. Validation experiments in canola and soybean demonstrated that WRS can correlate with root crown architecture in mature plants, both in greenhouse and field settings. Furthermore, WRS and root distribution indices derived from ClearDepthIAS are predictors of early root architecture and can be correlated with root biomass distribution across soil depths under field conditions; however, environmental interactions may influence these relationships and weaken or even negate such correlations, as observed when comparing field to field variation in root system architecture. Our system enables efficient phenotyping of genetically diverse populations, with medium to high trait heritability, supporting its utility for genome-wide association studies and breeding. ClearDepthIAS accelerates the development of root ideotypes for improved resource acquisition and carbon sequestration, offering a scalable tool for supporting climate-resilient agriculture.

Plant Roots↗

PubMed2026

Human Systems Immunology in the Omics Era: Challenges, Methods, and Emerging Directions.

The human immune system is a highly complex, dynamic, and heterogeneous network shaped by genetic, environmental, and temporal influences. Advances in high-throughput omics technologies have transformed our ability to study this complexity directly and comprehensively in human cohorts. These developments have positioned systems immunology as a powerful framework for investigating coordinated immune responses, identifying regulatory mechanisms, and linking molecular patterns to clinical phenotypes. However, the analytical challenges inherent to large-scale, multimodal datasets-including batch effects, small sample sizes, high dimensionality, and substantial interindividual heterogeneity-require rigorous study design, robust statistical modeling, and thoughtful data analysis strategies. In this review, we summarize key technological foundations enabling modern human systems immunology, outline common analytical pitfalls and effective mitigation approaches, discuss data integration concepts, and highlight emerging opportunities in the field. Together, these technological and analytical advances are redefining how immune function is measured and interpreted in real-world human biology and hold significant promise for enhancing mechanistic insight, biomarker discovery, and precision medicine across immunological diseases and interventions.

Humans↗

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↗

PubMed2026

Zebrafish as a versatile model in biomedical research, from disease modeling to regenerative medicine: a review.

Zebrafish are an effective animal model widely utilized in biomedical research. They are known for their rapid reproduction and substantial genetic similarity to humans. Their transparent embryos directly enable the visualization of developmental processes and disease progression. This makes zebrafish invaluable for studying a broad range of human diseases, including cancer, cardiovascular disorders, and neurodegenerative conditions. Compared with other vertebrate models, zebrafish offer several advantages, including ease of genome editing, cost-effective maintenance, and suitability for high-throughput drug screening. Recent advancements have expanded the use of zebrafish in disease modeling and regenerative medicine, providing deeper insights into the genetic and cellular mechanisms underlying human pathologies. Zebrafish provide a robust platform for evaluating the safety, efficacy, and regenerative potential of both natural and synthetic biomaterials, including hydroxyapatite, bioactive glass nanoparticles, and bioceramics. This capability facilitates the creation of artificial tissues that closely resemble native structures. Additionally, integrating artificial intelligence technologies has improved automated data analysis and phenotyping in zebrafish studies, enhancing both accuracy and throughput. This review highlights current applications of zebrafish in disease modeling, drug discovery, regenerative medicine, and biomaterial assessment, emphasizing their evolving role as a versatile preclinical platform supported by advanced genetic and computational tools.

Animals↗

PubMed2026

DURABLE: A Workflow for Determining Corrosion-Driving and Protective Microbial Mechanisms.

Microbiologically influenced corrosion (MIC) threatens global infrastructure, causing billions of dollars in annual losses. Its persistence stems from unresolved mechanisms─particularly the metabolites produced by microorganisms that drive or inhibit corrosion─and the microbial community structures. Progress has been hindered by the absence of systematic workflows to rapidly and accurately identify MIC-relevant microorganisms and their functions. Here, we present DURABLE (Detection of Unique Corrosion Resistant or Accelerating Biologics in a Laboratory Environment), a pipeline that couples high-throughput microbial screening with genomic and metabolic workflows. We applied the DURABLE workflow to six diesel tank samples and revealed fuel-dependent microbial community structures, which showed greater diversity and evenness in bacterial communities than their fungal counterparts. The workflow used carbon steel beads to rapidly screen over 80 bacterial isolates for corrosive activity, reducing assay time to approximately 2 days compared with the conventional 30-day metal coupon test. More than 40 isolates were identified as corrosive. Further testing using mass spectrometry analysis revealed corrosion-associated metabolites, which were further validated using electrochemical assays. Thus, DURABLE achieved a ∼15-fold increase in screening speed and provided a scalable and mechanistic framework for dissecting MIC dynamics. We expect this advance will enable the development of precision mitigation strategies in hydrocarbon fuel infrastructure.

Bacteria↗

PubMed2026

The diagnostic potential of combined quantitative polymerase chain reaction and next-generation sequencing using the same primers for periprosthetic joint infection.

Next-generation sequencing (NGS) enables the detection of specific pathogens unidentifiable by conventional cultures, but its application in orthopedics remains inconsistent due to background contamination and irreproducible findings. This study evaluated the diagnostic performance of a novel workflow combining broad-range 16S rRNA gene quantitative PCR (qPCR) screening with downstream NGS, focusing on bacterial biomass thresholds. The qPCR assay demonstrated excellent intrarater reliability, with an intraclass correlation coefficient (ICC) of 0.961 (95% confidence interval, 0.881 to 0.997). Based on serially diluted positive controls, a quantitative threshold of 10⁵ CFU/mL was established as the minimum concentration required for the consistent detection of fastidious taxa, such as Escherichia coli. When evaluated against conventional cultures using 95 sonicate fluid and 276 pre/intraoperative tissue samples, the qPCR assay achieved a sensitivity of 80% and a specificity of 72%. Subsequent NGS sequencing of 26 clinical samples and 9 controls showed concordance in 4 of 6 culture-positive infected cases with NGS taxonomy, whereas the remaining discrepancies were likely attributable to culture-based phenotypic misidentification. Notably, among the qPCR-positive cases, three were culture-negative, including two hip prosthesis loosening cases exhibiting polymicrobial profiles, and one post-traumatic osteoarthritis case harboring low-level Staphylococcus. Crucially, this post-traumatic patient developed delayed periprosthetic joint infection (PJI) 2 years post-surgery, with cultures identifying Staphylococcus previously detected by the initial NGS analysis. Integrating qPCR screening with targeted NGS effectively refines pathogen identification, filters environmental artifacts, and overcomes the diagnostic limitations of culture-negative infections in orthopedic practice.IMPORTANCENext-generation sequencing (NGS) enables the detection of specific pathogens in clinical samples that are not identifiable by conventional methods. However, NGS applications in orthopedics have not been quantitatively evaluated, and findings have been inconsistent owing to contaminants and the presence of non-credible causative organisms. These factors primarily stem from the failure to evaluate low-biomass samples and the absence of proper controls, such as negative controls or mock community DNA samples. This study demonstrates that interpreting results from low-biomass samples requires careful consideration because NGS relies on relative bacterial abundances; distinguishing likely pathogens from contaminants is particularly challenging when bacterial loads are low. We demonstrated that combining NGS with quantitative PCR (qPCR) and applying a Cq cutoff can reduce false positives.

Humans↗

PubMed2026

Next-generation newborn screening: feasibility of combined genetic and biochemical testing for 95 treatable inherited metabolic disorders.

INTRODUCTION: Next-generation sequencing (NGS) is gaining attention in newborn screening (NBS) for its ability to detect treatable genetic disorders, especially those without a biochemical footprint. However, NGS-NBS requires interpreting variants without phenotype information or family trio analysis. Biochemical tests, preferably in dried blood spots (DBS), are therefore useful to confirm the pathogenicity of variants identified by NGS-NBS and increase its specificity and sensitivity. OBJECTIVES: We aimed to explore the potential of combined genetic-biochemical testing for 95 treatable Inherited Metabolic Disorders (IMD) considered eligible for NGS-NBS (100 genes) previously identified by our research group. METHODS: We reviewed the Collaborative Laboratory Integrated Reports (CLIR) and carried out systematic literature reviews in PubMed and Embase to identify biochemical tests for 95 IMD. Biochemical tests conducted on DBS were differentiated from tests that require referral. RESULTS: We identified DBS-biochemical tests for 72 of the 95 IMD (77/100 genes). DBS-based biochemical tests for 55 IMD (60 genes) are already implemented in NBS. For the other 23 IMD, biochemical tests in non-DBS specimens are reported, although some are less sensitive when measured at neonatal age in presymptomatic infants. CONCLUSION: We present a comprehensive overview of current biochemical tests for 95 IMD. These tests can be used to confirm inconclusive NGS-NBS results, and combined genetic-biochemical testing is expected to improve both the negative and positive predictive values of NBS programs.

Humans↗

PubMed2026

Obtaining a Diagnostic Yield via Scan findings prior to the introduction of SEquencing retrospectivelY (ODYSSEY): a cohort study.

OBJECTIVE: To determine the retrospective yield of prenatal exome sequencing (PES) by establishing the proportion of children with a postnatal monogenic diagnosis that could have been diagnosed prenatally if PES had been available. METHODS: The study cohort comprised a sample of children in Northern Ireland, born between January 2010 and January 2018 (predating routine availability of PES), who received a monogenic diagnosis postnatally via next generation sequencing as part of either of two UK-wide studies (the 100 000 Genomes Project (2015-2018) or the Deciphering Developmental Disorders study (2011-2015)). Clinical data were collected retrospectively and correlated with the current UK National Health Service PES protocol, including the phenotypic eligibility criteria for PES and the associated fetal anomalies gene panel. Cases were considered retrospective diagnoses if the fetal phenotype would have been eligible for PES and the diagnostic gene was included on the test panel, meaning prenatal diagnosis in this current era could have been feasible. RESULTS: Of 101 children, 17.8% (95% CI, 10.3-25.3%) had both an eligible fetal structural anomaly (FSA) (i.e. high-risk FSA) and a diagnostic gene on the associated test panel, meaning that they could have been diagnosed prenatally in the current clinical landscape. The median length of the diagnostic odyssey for this subgroup of children was 3.7 years (1354 (range, 822-2450) days). Moreover, 58.4% (n = 59) of cases had no anomalies detected prenatally and 19.8% (n = 20) had a FSA that would not meet the eligibility criteria for PES (low-risk FSA). Although these cases would have been ineligible for PES under the current clinical pathway, 89.9% (n = 71/79) were affected by severe or profound syndromes. Postnatally, the most common functional anomalies were neurodevelopmental delay/intellectual disability and/or behavioral abnormality, which were observed in 80.2% (n = 81) of the included children. However, 80.2% (n = 65/81) of these affected children did not present with fetal anomalies eligible for PES. CONCLUSIONS: Almost one-fifth of children with a monogenic condition included in this study could have received a diagnosis via modern PES, avoiding a diagnostic odyssey lasting almost 4 years. However, despite having a monogenic condition, over half of the children did not present with any structural anomalies in utero. This demonstrates the degree to which fetal imaging is limited in its ability to reassure parents of the absence of a fetal genetic syndrome. © 2026 The Author(s). Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.

Humans↗

PubMed2026

Integrating histology and spatial transcriptomics via multimodal transformers and contrastive representation learning for accurate gene expression prediction.

Predicting spatial gene expression from Histological images is a fundamental task in understanding tissue organization and molecular phenotypes. However, existing methods often rely on single-model representations or lack effective alignment between image and transcriptomic features. To address these limitations, we propose a unified multimodal learning framework that integrates histological imaging and spatial transcriptomics through a shared latent representation space. Specifically, histological H&E images are encoded by a ResNet50-based convolutional stem and a MobileViT Transformer backbone to extract hierarchical visual representations. Both modalities are projected into a shared latent space via linear-GELU-dropout transformation blocks, enabling cross-modal alignment through a contrastive learning objective that maximizes agreement between the corresponding image and the spot embeddings. Experimental results on the 10x Genomics Visium dataset of human liver tissue demonstrate that MViTGene achieves significantly higher prediction accuracy than existing methods across multiple gene subsets, with improvements of 20%, 33%, and 12% in predicting marker genes, highly expressed genes, and highly variable genes, respectively. The significant improvement in relevance indicates that the model can more accurately capture the true correspondence between tissue morphology and gene expression, therefore enabling more reliable biological interpretation. It provides a computational tool for high-throughput spatial gene expression prediction that balances performance and interpretability.

Humans↗

PubMed2026

Characterisation of Bordetella pertussis virulence and macrolide resistance in Australia by targeted culture-independent sequencing: a genomic epidemiology study.

BACKGROUND: Bordetella pertussis continues to circulate globally despite widespread vaccination, with a notable epidemic in 2024. Its resurgence is confounded by the emergence of pertactin-deficient, macrolide-resistant B pertussis strains in Asia and Europe, which are under-recognised by conventional diagnostics. We aimed to apply targeted culture-independent next-generation sequencing (tNGS) of respiratory specimens to improve global B pertussis diagnostic capability and genomic surveillance. METHODS: We did a nationwide genomic epidemiology study of B pertussis RT-PCR-positive respiratory specimens that were retrospectively and prospectively collected by diagnostic and public health laboratories in six of seven states and territories of Australia. Specimens underwent tNGS and macrolide-resistant B pertussis-specific PCR, and an opportunistic subset from New South Wales and Queensland were cultured for confirmatory susceptibility testing and whole-genome sequencing. Sequencing data were analysed for genome recovery, virulence profiles, and macrolide resistance mutations, and were compared with international macrolide-resistant B pertussis genomes and ancestral Australian genomes. The performance of the tNGS approach was assessed with logistic regression relative to RT-PCR cycle threshold values, and sensitivity and specificity values were calculated. FINDINGS: 255 respiratory specimens positive for B pertussis were included in the study. 64 (25%) were retrospectively collected between Jan 12, 2012, and Dec 31, 2023, and 191 (75%) were prospectively collected between Jan 1 and Oct 28, 2024. Of these 255 specimens, 148 (58%) yielded near-complete B pertussis genomes through tNGS. Seven co-circulating lineages of B pertussis were documented, including two associated with macrolide-resistance. Eight epidemiologically unrelated and geographically dispersed cases of macrolide-resistant B pertussis with a 23S rRNA 2037A→G mutation were identified by tNGS and confirmed by whole-genome sequencing. Three of these were further validated by phenotypic testing. The estimated prevalence of macrolide resistance among Australian cases positive for B pertussis was 4% (eight of 188). INTERPRETATION: tNGS can recover near-complete B pertussis genomes directly from clinical specimens, enabling identification of macrolide resistance mutations and high-resolution phylogenetic analysis. These findings show that tNGS complements PCR-based surveillance by providing genome-wide assessment of resistance, virulence, and genomic diversity in a single workflow. FUNDING: NSW Health Prevention Research Support Program.

Macrolides↗

PubMed2026

Performance of the IR Biotyper, Nanopore, and Illumina sequencing to discriminate Escherichia coli strains originating from poultry.

UNLABELLED: Escherichia coli is a highly diverse bacterial species that includes avian pathogenic E. coli (APEC), one of the most prevalent causative agents of disease in poultry worldwide. Rapid and accurate discrimination of E. coli strains is essential for outbreak management, antimicrobial resistance surveillance, and vaccine development. In this study, we compared the performance of Fourier Transform Infrared (FTIR) spectroscopy using the IR Biotyper system with Nanopore and Illumina whole-genome sequencing (WGS) for typing 200 E. coli isolates, originating from four poultry rearing farms in the Netherlands. From each farm, we sampled 10 one-day-old meat type rearing chicks, and from every chick, we isolated 5 E. coli strains. FTIR clustering showed strong concordance with WGS-based classifications, particularly serotyping and core-genome similarity determined by PopPUNK analysis (Adjusted Rand Index 0.75-0.92). While Nanopore and Illumina sequencing provided the highest genetic resolution, FTIR offered a faster (max 6 vs 12-28 days for 200 isolates) and more cost-effective alternative for assessing clonality. Across all methods, multiple strains were detected per farm, whereas most birds carried a single dominant E. coli strain. Our findings demonstrate that FTIR provides a reliable and scalable phenotypic method for rapid strain discrimination in E. coli, complementing WGS in diagnostic, surveillance, and epidemiological settings where speed and throughput are critical. IMPORTANCE: Escherichia coli is a major pathogen in poultry and a potential zoonotic risk for humans. Rapid and accurate discrimination of avian pathogenic E. coli (APEC) strains is critical for outbreak management, antimicrobial resistance surveillance, and the design of effective autogenous vaccines. In this study, we compared Fourier Transform Infrared (FTIR) spectroscopy with Nanopore and Illumina whole-genome sequencing for strain typing of E. coli isolates originating from poultry. The results show that FTIR provides comparable clustering accuracy to genomic approaches at a fraction of the time and costs. This work demonstrates that FTIR can serve as a practical, high-throughput alternative for routine monitoring of E. coli in veterinary diagnostics and food safety of poultry meat, enabling faster decision-making and more targeted interventions across the poultry production chain.

Animals↗