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PubMed2026

The domestication-associated WHP10 tandem cluster of amino acid transporter genes enhances whole-plant protein accumulation in maize.

Improving protein accumulation in maize is essential for sustainable agriculture, yet the regulatory mechanisms governing the intermediate "flow" of organic nitrogen remain elusive. Here, we show that the maize stem acts as a regulatory node for nitrogen allocation. By integrating spatial transcriptomics and metabolomics with quantitative genetics, we demonstrate that a transport-oriented stem program orchestrates the high-protein phenotype of the wild maize accession Ames21814. We identified a major locus, Whole-plant High Protein 10 (WHP10), that encodes a tandemly duplicated cluster of amino acid transporter genes. WHP10 exhibits strong vascular-biased expression, driven by promoter divergence that enhances the wild allele's activity. Functional assays and genetic validation support a model in which the WHP10 cluster facilitates the transport of multiple nitrogen-rich amino acids, thereby contributing to vascular-associated amino acid transport and post-uptake organic-nitrogen partitioning. Our findings establish stem flow as a regulatory layer for protein accumulation and identify WHP10 as a high-value target for precision breeding to enhance whole-plant protein accumulation without compromising grain yield.

Zea mays↗

PubMed2026

Multistage Genetic, Transcriptomic, and Single-Cell Evidence Prioritizes MAP1LC3A among Ferroptosis-Related Genes in Glioblastoma.

Glioblastoma (GBM) remains a highly aggressive malignancy, and the contribution of ferroptosis-related genes to disease susceptibility remains incompletely understood. A genetically anchored, multistage framework was applied to prioritize ferroptosis-related genes associated with GBM. Among 483 genes curated from FerrDb V2, 315 had candidate cis-expression quantitative trait loci (cis-eQTLs) in eQTLGen, 250 retained at least three independent instruments after linkage disequilibrium clumping, and 226 yielded valid inverse-variance weighted (IVW) Mendelian randomization estimates using a GBM genome-wide association study comprising 6,183 cases and 18,169 controls. Thirty-four genes met the exploratory discovery criteria of P < 0.05 and a Benjamini-Hochberg false discovery rate (BH-FDR) < 0.20, with directionally concordant Bayesian weighted Mendelian randomization (BWMR) estimates. Replication-stage Mendelian randomization using GTEx V10 whole-blood cis-eQTLs supported four genes: ATG7, RPTOR, MAP1LC3A, and CHMP6. Evaluation across three independent tumor-control transcriptomic cohorts demonstrated that MAP1LC3A was consistently downregulated in tumor tissue and showed a significant random-effects pooled estimate (log₂ fold change, -1.273; 95% confidence interval, -1.625 to -0.920; false discovery rate = 0.016), whereas the other three genes lacked comparable cross-cohort statistical support. Single-cell virtual knockout analysis was subsequently performed in a patient-balanced subset of 2,400 malignant cells selected from 4,916 eligible cells across 20 adult IDH-wild-type GBM tumors. Across five independently seeded runs, 3, 15, 4, and 7 robust downstream genes were identified for ATG7, RPTOR, MAP1LC3A, and CHMP6, respectively. The resulting consensus sets comprised 17 unique genes, with RND3 shared across all four targets. Gene Ontology analysis indicated enrichment of cell-adhesion and cell-surface processes, whereas no KEGG or Reactome pathways remained significant after multiple-testing correction. Collectively, these findings prioritize MAP1LC3A for future experimental investigation while distinguishing genetic association, tumor-expression concordance, and computational perturbation from definitive evidence of causality or mechanism.

Humans↗

PubMed2006

Functional genomic and metabolic studies of the adaptations of a prominent adult human gut symbiont, Bacteroides thetaiotaomicron, to the suckling period.

The adult human gut microbiota is dominated by two divisions of Bacteria, the Bacteroidetes and the Firmicutes. Assembly of this community begins at birth through processes that remain largely undefined. In this report, we examine the adaptations of Bacteroides thetaiotaomicron, a prominent member of the adult distal intestinal microbiota, during the suckling and weaning periods. Germ-free NMRI mice were colonized at birth from their gnotobiotic mothers, who harbored this anaerobic Gram-negative saccharolytic bacterium. B. thetaiotaomicron was then harvested from the ceca of these hosts during the suckling period (postnatal day 17) and after weaning (postnatal day 30). Whole genome transcriptional profiles were obtained at these two time points using custom B. thetaiotaomicron GeneChips. Transcriptome-based in silico reconstructions of bacterial metabolism and gas chromatography-mass spectrometry and biochemical assays of carbohydrate utilization in vivo indicated that in the suckling gut B. thetaiotaomicron prefers host-derived polysaccharides, as well as mono- and oligosaccharides present in mother's milk. After weaning, B. thetaiotaomicron expands its metabolism to exploit abundant, plant-derived dietary polysaccharides. The bacterium's responses to postnatal alterations in its nutrient landscape involve expression of gene clusters encoding environmental sensors, outer membrane proteins involved in binding and import of glycans, and glycoside hydrolases. These expression changes are interpreted in light of a phylogenetic analysis that revealed unique expansions of related polysaccharide utilization loci in three human alimentary tract-associated Bacteroidetes, expansions that likely reflect the evolutionary adaptations of these species to different nutrient niches.

Animals↗

PubMed2026

Wildlife Trade and Genetic Basis of Disease Susceptibility: A Review.

The surge in the trade of wildlife and wildlife products drives several species to extinction while coinciding with the increase in several zoonotic diseases. It is therefore essential to explore the roles of wildlife trade in disease transmission, and how the knowledge of genetics and immunogenetics can help in alleviating the attending challenges. Pathogen-driven selection plays a fundamental role in maintaining immune gene diversity, as individuals with alleles conferring resistance to endemic diseases have higher survival rate. However, anthropogenic disturbances, such as wildlife exploitation, can disrupt these evolutionary processes, leading to reduced genetic diversity and increased disease vulnerability. Advanced genomic tools, such as next-generation sequencing (NGS), whole-genome sequencing (WGS), CRISPR-Cas9 gene editing, genome-wide association studies (GWAS), epigenetics and transcriptomic analysis, can help identify immune gene variations and predict disease susceptibility in both wild and captive populations. Massive research targeting wildlife markets and the interface between the wild and the market players is necessary. It would be interesting to understand dynamics of pathogens and disease susceptibility, through the application of genetics and immunogenetics, thereby enhancing efforts to address the challenges posed by wildlife trade and zoonotic disease emergence.

Animals↗

PubMed2004

In vivo transcriptional profiling of Plasmodium falciparum.

BACKGROUND: Both host and pathogen factors contribute to disease outcome in Plasmodium falciparum infection. The feasibility of studying the P. falciparum in vivo transcriptome to understand parasite transcriptional response while it resides in the human host is presented. METHODS: A custom made oligonucleotide array with probes based on the P. falciparum 3D7 laboratory strain chromosome 2 sequence was used to detect in vivo P. falciparum transcripts. This study analyzed transcripts from total RNA derived from small blood samples of P. falciparum infected patients and compared the in vivo expression profile to the in vitro cultivated 3D7 strain transcriptome. RESULTS: The data demonstrated that in vivo transcription can be studied from a small blood sample, despite the abundance of human RNA. The in vivo transcriptome is similar to the 3D7 ring stage transcriptome, but there are significant differences in genes encoding a sexual stage antigen and surface proteins. CONCLUSIONS: Whole genome transcription analysis of P. falciparum can be carried out successfully and further studies in selected patient cohorts may provide insight into parasite in vivo biology and defense against host immunity.

Animals↗

PubMed2026

Phenotypic and transcriptomic characterization of biallelic RNU2-2 developmental and epileptic encephalopathy.

OBJECTIVE: A significant proportion of individuals with suspected genetic developmental and epileptic encephalopathies (DEEs) remain unsolved following whole genome sequencing (WGS). Here we describe biallelic RNU2-2 variants causing a recently reported, severe, recessive DEE. METHODS: We screened individuals who have received WGS analyses at the Genomic Medicine Centre Karolinska for Rare Diseases for biallelic RNU2-2 variants. Deep phenotyping was performed through reviewing entire medical histories and phenotypic traits were transcribed to their corresponding Human Phenotype Ontology (HPO) term. HPO terms were used to generate pairwise phenotypic similarity scores and assess for significantly shared phenotype enrichment in the RNU2-2 sub-cohort. RNA sequencing analyses were performed in fibroblast and blood tissues to compare splicing events between RNU2-2 individuals and two independent control groups. RESULTS: We identified 14 individuals from nine families with 12 ultra-rare biallelic RNU2-2 variants clustering in the conserved 5' domains. Genotype data from 13 of 14 individuals has been reported previously as part of a larger cohort. All individuals presented with a highly concordant, severe DEE, characterized by severe to profound intellectual disability, inability to walk or communicate, hyperkinesia, and refractory seizures. Infantile spasms and tonic seizures were the predominant seizure types and a Lennox-Gastaut syndrome-like phenotype was common. These individuals had a significantly similar phenotypic signature when compared with 703 individuals with complex pediatric epilepsies (two-sided Monte Carlo permutation test, p = .005). RNA sequencing analyses showed aberrant splicing, with the most pronounced effects in fibroblast tissues in mutually exclusive exon and alternate 3' splice-site events, which were not detectable in blood. SIGNIFICANCE: We present deep phenotyping data and transcriptomic analyses that provide support for rare, 5' clustering biallelic RNU2-2 variants causing this novel, severe DEE. We propose an RNA sequencing methodology on fibroblast tissue for future validation of RNU2-2 variants.

autosomal recessive disease↗

PubMed2001

Whole-cell simulation: a grand challenge of the 21st century.

Study of the cell will never be complete unless its dynamic behavior is understood. The complex behavior of the cell cannot be determined or predicted unless a computer model of the cell is constructed and computer simulation is undertaken. Rapid accumulation of biological data from genome, proteome, transcriptome and metabolome projects can bring us to the point where it is no longer purely speculative to discuss how to construct virtual cells in silico. This article describes attempts to construct whole cell models. The E-CELL project has completed a couple of virtual cell models, and computer simulations have revealed some biological surprises.

Anemia, Hemolytic, Congenital↗

PubMed2005

Arabidopsis thaliana full genome longmer microarrays: a powerful gene discovery tool for agriculture and forestry.

Sequenced plant genomes provide a large reservoir of known genes with potential for use in crop and tree improvement, but assignment of specific functions to annotated genes in sequenced plant genomes remains a challenge. Furthermore, most plant genes belong to families encoding proteins with related but distinct functions. In this commentary, we discuss our development of Arabidopsis spotted whole genome longmer oligonucleotide microarrays, and their use in global transcription profiling. We show that longmer array based transcriptome analysis in Arabidopsis can be used as an efficient and effective gene discovery and functional genomics tool, particularly for functional analyses of members of large gene families. We discuss experiments that focus on gene families involved in phenylpropanoid natural product biosynthesis and fiber differentiation. These analyses have helped to elucidate functions of individual gene family members, and have identified new candidate genes involved in fiber development and differentiation. Results obtained by these studies in Arabidopsis can be used as the basis for gene discovery in commercially important plants, and we have focused our attention on Populus trichocarpa (poplar), a species important in forestry and agroforestry for which complete genome sequence information is available.

Agriculture↗

PubMed2026

Genomic and transcriptomic quality control for an autologous iPSC-derived cell therapy for Parkinson's disease.

Toward development of an autologous, induced pluripotent stem cell (iPSC)-based cell therapy for Parkinson's disease (PD), we demonstrate successful, reproducible genomic and transcriptomic qualification of patient-derived dopaminergic neuron precursor cells (DANPCs) across multiple donors. Our analysis includes whole-genome sequencing data from fibroblasts, iPSCs, and DANPCs and the development of NeuriTest, an RNAseq-based bioinformatic analysis of DANPCs designed to predict cell quality based on empirical animal data. Autologous cell therapies are immune matched to the patient, potentially augmenting durability of benefit compared to allogeneic cells while negating the need for immunosuppression and accompanying side effects. Patient-specific iPSCs are an autologous cell source that can be differentiated to dopaminergic neurons, the cell type lost in PD. We report here our preclinical manufacturing strategy and results demonstrating efficacy in a PD rodent model and safety in a 9-month GLP toxicology study.

Parkinson’s disease↗

PubMed2004

What do microarrays really tell us about M. tuberculosis?

Bacterial pathogens adapt to their host environments to a large extent through switching on complex transcriptional programmes, and whole-genome microarray experiments promise to reveal this complexity. There has been a recent burst of articles reporting transcriptome analyses of Mycobacterium tuberculosis, including for the first time studies in macrophages and mice. We review gene expression reports, and compare them with each other and with microarray-based gene essentiality studies, revealing at times a startling lack of correlation. Additionally, we suggest a standardization format for the submission of processed data for publication, to facilitate cross-experiment analyses.

Animals↗

PubMed2003

Rank order metrics for quantifying the association of sequence features with gene regulation.

MOTIVATION: Genome sequences and transcriptome analyses allow the correlation between gene regulation and DNA sequence features to be studied at the whole-genome level. To quantify these correlations, metrics are needed that can be applied to any sequence feature, regardless of its statistical distribution. It is also desirable for the metric values to be determined objectively, that is, without the use of subjective threshold values. RESULTS: We compare two metrics for quantifying the correlation of DNA sequence features with gene regulation. Each of the metrics is calculated from a rank-ordering of genes based on the value of the sequence feature of interest. The first metric is the area under the curve for a receiver operator characteristic plot (ROC AUC), a common way of summarizing the tradeoff between sensitivity and specificity for different values of a prediction criterion. We call the second metric the mean normalized conditional probability (MNCP). The MNCP can be thought of as the predictive value of the sequence feature averaged over all regulated genes. The statistical significance (P-value) of each metric can be estimated from simulations. Importantly, the P-value of the MNCP metric is less dramatically affected by the presence of false positives among the set of co-regulated genes than is the ROC AUC. This is especially useful in analyzing gene sets identified by DNA microarray analysis because such data cannot distinguish direct regulation by transcription factor binding from indirect regulation. We demonstrate that these two metrics, taken together, are useful tools for defining the binding site representation and regulatory control regions that best explain the difference between genes that are regulated by a given transcription factor and those that are not. Applications to other gene features are also described. AVAILABILITY: A Python program for calculating the ROC AUC and MNCP metric values given input rank orders is available from ftp://ftp.bs.jhmi.edu/users/nclarke/MNCP/

Algorithms↗

PubMed2025

Methylation patterns of the nasal epigenome of hospitalized SARS-CoV-2 positive patients reveal insights into molecular mechanisms of COVID-19.

BACKGROUND: Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has varied presentations from asymptomatic to death. Efforts to identify factors responsible for differential COVID-19 severity include but are not limited to genome wide association studies (GWAS) and transcriptomic analysis. More recently, variability in host epigenomic profiles have garnered attention, providing links to disease severity. However, whole epigenome analysis of the respiratory tract, the target tissue of SARS-CoV-2, remains ill-defined. RESULTS: We interrogated the nasal methylome to identify pathophysiologic drivers in COVID-19 severity through whole genome bisulfite sequencing (WGBS) of nasal samples from COVID-19 positive individuals with severe and mild presentation of disease. We noted differential DNA methylation in intergenic regions and low methylated regions (LMRs), demonstrating the importance of distal regulatory elements in gene regulation in COVID-19 illness. Additionally, we demonstrated differential methylation of pathways implicated in immune cell recruitment and function, and the inflammatory response. We found significant hypermethylation of the FUT4 promoter implicating impaired neutrophil adhesion in severe disease. We also identified hypermethylation of ELF5 binding sites suggesting downregulation of ELF5 targets in the nasal cavity as a factor in COVID-19 phenotypic variability. CONCLUSIONS: This study demonstrated DNA methylation as a marker of the immune response to SARS-CoV-2 infection, with enhancer-like elements playing significant roles. It is difficult to discern whether this differential methylation is a predisposing factor to severe COVID-19, or if methylation differences occur in response to disease severity. These differences in the nasal methylome may contribute to disease severity, or conversely, the nasal immune system may respond to severe infection through differential immune cell recruitment and immune function, and through differential regulation of the inflammatory response.

Humans↗

PubMed2004

Integration of transcriptomics and metabolomics for understanding of global responses to nutritional stresses in Arabidopsis thaliana.

Plant metabolism is a complex set of processes that produce a wide diversity of foods, woods, and medicines. With the genome sequences of Arabidopsis and rice in hands, postgenomics studies integrating all "omics" sciences can depict precise pictures of a whole-cellular process. Here, we present, to our knowledge, the first report of investigation for gene-to-metabolite networks regulating sulfur and nitrogen nutrition and secondary metabolism in Arabidopsis, with integration of metabolomics and transcriptomics. Transcriptome and metabolome analyses were carried out, respectively, with DNA macroarray and several chemical analytical methods, including ultra high-resolution Fourier transform-ion cyclotron MS. Mathematical analyses, including principal component analysis and batch-learning self-organizing map analysis of transcriptome and metabolome data suggested the presence of general responses to sulfur and nitrogen deficiencies. In addition, specific responses to either sulfur or nitrogen deficiency were observed in several metabolic pathways: in particular, the genes and metabolites involved in glucosinolate metabolism were shown to be coordinately modulated. Understanding such gene-to-metabolite networks in primary and secondary metabolism through integration of transcriptomics and metabolomics can lead to identification of gene function and subsequent improvement of production of useful compounds in plants.

Arabidopsis↗

PubMed2006

Exploring glycopeptide-resistance in Staphylococcus aureus: a combined proteomics and transcriptomics approach for the identification of resistance-related markers.

BACKGROUND: To unravel molecular targets involved in glycopeptide resistance, three isogenic strains of Staphylococcus aureus with different susceptibility levels to vancomycin or teicoplanin were subjected to whole-genome microarray-based transcription and quantitative proteomic profiling. Quantitative proteomics performed on membrane extracts showed exquisite inter-experimental reproducibility permitting the identification and relative quantification of >30% of the predicted S. aureus proteome. RESULTS: In the absence of antibiotic selection pressure, comparison of stable resistant and susceptible strains revealed 94 differentially expressed genes and 178 proteins. As expected, only partial correlation was obtained between transcriptomic and proteomic results during stationary-phase. Application of massively parallel methods identified one third of the complete proteome, a majority of which was only predicted based on genome sequencing, but never identified to date. Several over-expressed genes represent previously reported targets, while series of genes and proteins possibly involved in the glycopeptide resistance mechanism were discovered here, including regulators, global regulator attenuator, hyper-mutability factor or hypothetical proteins. Gene expression of these markers was confirmed in a collection of genetically unrelated strains showing altered susceptibility to glycopeptides. CONCLUSION: Our proteome and transcriptome analyses have been performed during stationary-phase of growth on isogenic strains showing susceptibility or intermediate level of resistance against glycopeptides. Altered susceptibility had emerged spontaneously after infection with a sensitive parental strain, thus not selected in vitro. This combined analysis allows the identification of hundreds of proteins considered, so far as hypothetical protein. In addition, this study provides not only a global picture of transcription and expression adaptations during a complex antibiotic resistance mechanism but also unravels potential drug targets or markers that are constitutively expressed by resistant strains regardless of their genetic background, amenable to be used as diagnostic targets.

Anti-Bacterial Agents↗

PubMed2025

Single-cell profiling of trabecular meshwork identifies mitochondrial dysfunction in a glaucoma model that is protected by vitamin B3 treatment.

Since the trabecular meshwork (TM) is central to intraocular pressure (IOP) regulation and glaucoma, a deeper understanding of its genomic landscape is needed. We present a multimodal, single-cell resolution analysis of mouse limbal cells (includes TM). In total, we sequenced 9,394 wild-type TM cell transcriptomes. We discovered three TM cell subtypes with characteristic signature genes validated by immunofluorescence on tissue sections and whole-mounts. The subtypes are robust, being detected in datasets for two diverse mouse strains and in independent data from two institutions. Results show compartmentalized enrichment of critical pathways in specific TM cell subtypes. Distinctive signatures include increased expression of genes responsible for 1) extracellular matrix structure and metabolism (TM1 subtype), 2) secreted ligand signaling to support Schlemm's canal cells (TM2), and 3) contractile and mitochondrial/metabolic activity (TM3). ATAC-sequencing data identified active transcription factors in TM cells, including LMX1B. Mutations in LMX1B cause high IOP and glaucoma. LMX1B is emerging as a key transcription factor for normal mitochondrial function and its expression is much higher in TM3 cells than other limbal cells. To understand the role of LMX1B in TM function and glaucoma, we single-cell sequenced limbal cells from Lmx1b V265D/+ mutant mice (2,491 TM cells). In V265D/+ mice, TM3 cells were uniquely affected by pronounced mitochondrial pathway changes. Mitochondria in TM cells of V265D/+ mice are swollen with a reduced cristae area, further supporting a role for mitochondrial dysfunction in the initiation of IOP elevation in these mice. Importantly, treatment with vitamin B3 (nicotinamide), to enhance mitochondrial function and metabolic resilience, significantly protected Lmx1b mutant mice from IOP elevation.

Journal Article↗

PubMed2026

Spatially defined microenvironmental niches are associated with clinical outcome and tumor ecosystem diversity in head and neck cancer.

BACKGROUND: Head and neck squamous cell carcinoma (HNSCC) exhibits substantial biological heterogeneity that is not fully explained by human papillomavirus (HPV) status. The spatial organization of tumor, immune, and stromal cell populations and its relationship to clinical outcome remain incompletely understood. METHODS: We performed single-cell spatial transcriptomic and proteomic profiling of 44 primary HNSCC tumors, generating a spatial atlas of 19,471,501 cells across whole-slide tissue sections. Spatial niches and ecosystem states were identified through integrated computational analyses and evaluated for associations with tumor programs, clinicopathologic features, and patient outcomes. FINDINGS: HPV-negative tumors were enriched for fibroblast-rich, immune-poor niches associated with epithelial-mesenchymal transition and hypometabolic tumor programs, whereas HPV-positive tumors displayed more diverse immune, stromal, and vascular niche combinations and were enriched for immunogenic ecosystem states. Approximately 20% of HPV-positive tumors exhibited fibroblast-rich ecosystem architectures resembling HPV-negative disease and were associated with less favorable outcomes than other HPV-positive tumors of similar stage. In patient-derived co-culture models, extracellular matrix-associated fibroblasts were associated with epithelial-mesenchymal transition (EMT)-like tumor states, CD8+ T cell dysfunction, and chemotherapy resistance-associated phenotypes. CONCLUSIONS: Spatial ecosystem architecture is associated with clinically relevant heterogeneity beyond conventional HPV-based classification. Fibroblast-rich, immune-poor ecosystem states characterize a high-risk subset of HPV-positive tumors and may provide a framework for improved biological classification and risk stratification in HNSCC. FUNDING: This work was supported by the National Institutes of Health (R01CA291607 and R21CA267527-01) and the Feldstein Medical Foundation.

Humans↗

PubMed2006

Transcriptome analysis reveals link between proteasomal and mitochondrial pathways in Parkinson's disease.

There is growing evidence that dysfunction of the mitochondrial respiratory chain and failure of the cellular protein degradation machinery, specifically the ubiquitin-proteasome system, play an important role in the pathogenesis of Parkinson's disease. We now show that the corresponding pathways of these two systems are linked at the transcriptomic level in Parkinsonian substantia nigra. We examined gene expression in medial and lateral substantia nigra (SN) as well as in frontal cortex using whole genome DNA oligonucleotide microarrays. In this study, we use a hypothesis-driven approach in analysing microarray data to describe the expression of mitochondrial and ubiquitin-proteasomal system (UPS) genes in Parkinson's disease (PD). Although a number of genes showed up-regulation, we found an overall decrease in expression affecting the majority of mitochondrial and UPS sequences. The down-regulated genes include genes that encode subunits of complex I and the Parkinson's-disease-linked UCHL1. The observed changes in expression were very similar for both medial and lateral SN and also affected the PD cerebral cortex. As revealed by "gene shaving" clustering analysis, there was a very significant correlation between the transcriptomic profiles of both systems including in control brains. Therefore, the mitochondria and the proteasome form a higher-order gene regulatory network that is severely perturbed in Parkinson's disease. Our quantitative results also suggest that Parkinson's disease is a disease of more than one cell class, i.e. that it goes beyond the catecholaminergic neuron and involves glia as well.

Brain↗

PubMed2003

Global analysis of gene expression using GeneChip microarrays.

DNA microarray technology, especially the use of GeneChip microarrays, has become a standard tool for parallel gene expression analysis. Recent improvements in GeneChip microarrays enable whole-genome expression analysis, and thus open a new avenue for studies of the composition, dynamics, and regulation of the transcriptome in plants.

Computational Biology↗