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Functional genomics, new tools in malaria research.

The mosquito-transmitted unicellular parasite Plasmodium falciparum, the agent of malaria disease, still causes more than one million deaths every year in the tropical and subtropical areas of the world. New intervention strategies are needed to contrast the insurgence of resistance to effective drugs and insecticides. The complete annotated genomes of the human parasite P. falciparum and the rodent model P. yoelii is now available thus providing a prediction of their possible gene products. This makes feasible the application of functional genomics to malaria research with the final goal of providing a complete survey of Plasmodium life cycle. Genome-wide approaches to the study of transcriptome or proteome were successfully applied to malaria parasite with the promise for new drug and vaccine candidates in the next future.

Animals↗

Global molecular and morphological effects of 24-hour chromium(VI) exposure on Shewanella oneidensis MR-1.

The biological impact of 24-h ("chronic") chromium(VI) [Cr(VI) or chromate] exposure on Shewanella oneidensis MR-1 was assessed by analyzing cellular morphology as well as genome-wide differential gene and protein expression profiles. Cells challenged aerobically with an initial chromate concentration of 0.3 mM in complex growth medium were compared to untreated control cells grown in the absence of chromate. At the 24-h time point at which cells were harvested for transcriptome and proteome analyses, no residual Cr(VI) was detected in the culture supernatant, thus suggesting the complete uptake and/or reduction of this metal by cells. In contrast to the untreated control cells, Cr(VI)-exposed cells formed apparently aseptate, nonmotile filaments that tended to aggregate. Transcriptome profiling and mass spectrometry-based proteomic characterization revealed that the principal molecular response to 24-h Cr(VI) exposure was the induction of prophage-related genes and their encoded products as well as a number of functionally undefined hypothetical genes that were located within the integrated phage regions of the MR-1 genome. In addition, genes with annotated functions in DNA metabolism, cell division, biosynthesis and degradation of the murein (peptidoglycan) sacculus, membrane response, and general environmental stress protection were upregulated, while genes encoding chemotaxis, motility, and transport/binding proteins were largely repressed under conditions of 24-h chromate treatment.

Bacterial Proteins↗

Large-scale analysis of the human and mouse transcriptomes.

High-throughput gene expression profiling has become an important tool for investigating transcriptional activity in a variety of biological samples. To date, the vast majority of these experiments have focused on specific biological processes and perturbations. Here, we have generated and analyzed gene expression from a set of samples spanning a broad range of biological conditions. Specifically, we profiled gene expression from 91 human and mouse samples across a diverse array of tissues, organs, and cell lines. Because these samples predominantly come from the normal physiological state in the human and mouse, this dataset represents a preliminary, but substantial, description of the normal mammalian transcriptome. We have used this dataset to illustrate methods of mining these data, and to reveal insights into molecular and physiological gene function, mechanisms of transcriptional regulation, disease etiology, and comparative genomics. Finally, to allow the scientific community to use this resource, we have built a free and publicly accessible website (http://expression.gnf.org) that integrates data visualization and curation of current gene annotations.

Animals↗

Odon: an ultra-fast viewer for spatial proteomics.

MOTIVATION: Multiplexed spatial proteomics and spatial transcriptomics generate large, high-dimensional imaging datasets that are challenging to visualize efficiently, particularly at whole-slide and cohort scale. Visualization is an essential step for rapid detection of staining artefacts, such as protein aggregates or non-specific staining. RESULTS: Here, we present Odon, a native Rust desktop viewer designed for rapid, interactive exploration of multiplex imaging data on a standard laptop. Odon is primarily built around the OME-Zarr imaging format, and supports annotations via GeoJSON and GeoParquet, with secondary support for SpatialData, Xenium containers, and TIFF. Data can be stored locally or streamed directly from HTTP or S3-compatible object storage using viewport-driven tile loading. Odon incorporates a highly optimized rendering engine designed for viewport-driven tile loading and GPU-based compositing. In scripted benchmarks using synthetic multiplex OME-Zarr datasets, Odon showed lower peak memory use, lower affine-derived zoom-step error, and faster warm-start image loading than napari and QuPath under the tested conditions. Its GPU-based compositing pipeline also enables smooth rendering and interaction with >1 000 000 segmented cells. Odon further supports integrated visual analytics, including live thresholding and cell selection, and a mosaic mode for simultaneous viewing of hundreds of regions of interest in cohort and tissue microarray studies. Together, these features establish Odon as a high-performance platform for scalable visualization of spatial proteomics data. AVAILABILITY AND IMPLEMENTATION: Source code and compiled installers are available at https://github.com/alexcoulton/odon.

Proteomics↗

Transcriptome profiling of adult zebrafish at the late stage of chronic tuberculosis due to Mycobacterium marinum infection.

The Mycobacterium marinum-zebrafish infection model was used in this study for analysis of a host transcriptome response to mycobacterium infection at the organismal level. RNA isolated from adult zebrafish that showed typical signs of fish tuberculosis due to a chronic progressive infection with M. marinum was compared with RNA from healthy fish in microarray analyses. Spotted oligonucleotide sets (designed by Sigma-Compugen and MWG) and Affymetrix GeneChips were used, in total comprising 45,465 zebrafish transcript annotations. Based on a detailed comparative analysis and quantitative reverse transcriptase-PCR analysis, we present a validated reference set of 159 genes whose regulation is strongly affected by mycobacterial infection in the three types of microarrays analyzed. Furthermore, we analyzed the separate datasets of the microarrays with special emphasis on the expression profiles of immune-related genes. Upregulated genes include many known components of the inflammatory response and several genes that have previously been implicated in the response to mycobacterial infections in cell cultures of other organisms. Different marker genes of the myeloid lineage that have been characterized in zebrafish also showed increased expression. Furthermore, the zebrafish homologs of many signal transduction genes with relationship to the immune response were induced by M. marinum infection. Future functional analysis of these genes may contribute to understanding the mechanisms of mycobacterial pathogenesis. Since a large group of genes linked to immune responses did not show altered expression in the infected animals, these results suggest specific responses in mycobacterium-induced disease.

Animals↗

A method for automated detection of gene expression required for the establishment of a digital transcriptome-wide gene expression atlas.

Acquiring information about the expression of a gene in different cell populations and tissues can provide key insight into the function of the gene. A high-throughput in situ hybridization (ISH) method was recently developed for rapid and reproducible acquisition of gene expression patterns in serial tissue sections at cellular resolution. Characterizing and analysing expression patterns on thousands of sections requires efficient methods for locating cells and estimating the level of expression in each cell. Such cellular quantification is an essential step in both annotating and quantitatively comparing high-throughput ISH results. Here we describe a novel automated and efficient methodology for performing this quantification on postnatal mouse brain.

Animals↗

Age-specific hormonal decline is accompanied by transcriptional changes in human sebocytes in vitro.

The importance of hormones in endogenous aging has been displayed by recent studies performed on animal models and humans. To decipher the molecular mechanisms involved in aging we maintained human sebocytes at defined hormone-substituted conditions that corresponded to average serum levels of females from 20 (f20) to 60 (f60) years of age. The corresponding hormone receptor expression was demonstrated by reverse transcription-polymerase chain reaction (RT-PCR), Western blotting and immunocytochemistry. Cells at f60 produced significantly lower lipids than at f20. Increased mRNA and protein levels of c-Myc and increased protein levels of FN1, which have been associated with aging, were detected in SZ95 sebocytes at f60 compared to those detected at f20 after 5 days of treatment. Expression profiling employing a cDNA microarray composed of 15 529 cDNAs identified 899 genes with altered expression levels at f20 vs. f60. Confirmation of gene regulation was performed by real-time RT-PCR. The functional annotation of these genes according to the Gene Ontology identified pathways related to mitochondrial function, oxidative stress, ubiquitin-mediated proteolysis, cell cycle, immune responses, steroid biosynthesis and phospholipid degradation - all hallmarks of aging. Twenty-five genes in common with those identified in aging kidneys and several genes involved in neurodegenerative diseases were also detected. This is the first report describing the transcriptome of human sebocytes and its modification by a cocktail of hormones administered in age-specific levels and provides an in vitro model system, which approximates some of the hormone-dependent changes in gene transcription that occur during aging in humans.

Aging↗

Colorectal Liver Metastasis Pathomics Model: Integrating Single-Cell and Spatial Transcriptome Analysis With Pathomics for Predicting Liver Metastasis in Colorectal Cancer.

The liver is the primary target organ for hematologic metastasis of colorectal cancer (CRC), and CRC liver metastasis (CRLM) often precludes radical resection, making it the leading cause of death in patients with CRC. To improve the identification and prediction of liver metastasis risk, we identified a cell type of liver metastasis--triggering malignant cells (LMTMCs) through integrating single-cell RNA sequencing and spatial transcriptome analysis. Multiomics cell communication analysis indicated that the interaction between fibroblasts and LMTMCs through the COL1A1-CD44/SDC4 and LAMA4-CD44 signaling axes could promote CRLM. By applying the one-class logistic regression algorithm, we developed a CRLM scoring system in the bulk RNA-sequencing data according to the abundance of LMTMCs in each individual. Using the grouping labels derived from the CRLM scoring system in the bulk data and the corresponding whole-slide images without any manual annotations at the region or pixel level, processed via slide-level weakly supervised learning, a deep-learning model based on the ResNet18 architecture, called Colorectal Liver Metastasis Pathomics Model, was developed to predict the risk of liver metastasis in patients with CRC. The Colorectal Liver Metastasis Pathomics Model achieved an area under the curve of 0.84 at the internal test set of The Cancer Genome Atlas-CRC histology images. In the external independent validation sets, namely the Affiliated Hospital of Southwest Medical University and the Affiliated Traditional Chinese Medicine Hospital of Southwest Medical University cohorts, the areas under the curve were 0.89 and 0.72, respectively, indicating effective classification performances. This study provided new insights and tools for the early identification of CRLM and demonstrated the potential of combining multiomics with deep learning-based pathomics in cancer research.

Humans↗

Regulation of gene expression in RAW 264.7 macrophage cell line by interferon-gamma.

Macrophages play an important role in immune responses and in inflammatory disease states such as atherosclerosis. Interferon-gamma (IFN-gamma) is a major cytokine involved in the activation of macrophages. To elucidate the primary response of various genes and biological pathways regulated by IFN-gamma in macrophage, we analyzed the gene expression profile in RAW 264.7 macrophage cells treated with IFN-gamma for 4h. Microarray analysis revealed that about 400 genes were differentially expressed, of which about 250 genes were up-regulated and 150 were down-regulated. Functional organization of the transcriptome revealed that induced genes are involved in antimicrobial and antiviral responses, antigen presentation, chemokine and cytokine signaling, and inhibition of cell growth. We also found that expression of genes involved in cell-cycle control, DNA repair, and lipid metabolism was suppressed by IFN-gamma. We also identified induction of multiple transcription factors by IFN-gamma in RAW 264.7 cells. Functional annotation of genes regulated by IFN-gamma in RAW 264.7 cells may provide novel insights into the role of macrophages in immunity and in inflammatory disease.

Animals↗

Head and neck squamous cell carcinoma transcriptome analysis by comprehensive validated differential display.

Head and neck squamous cell carcinoma (HNSCC) is common worldwide and is associated with a poor rate of survival. Identification of new markers and therapeutic targets, and understanding the complex transformation process, will require a comprehensive description of genome expression, that can only be achieved by combining different methodologies. We report here the HNSCC transcriptome that was determined by exhaustive differential display (DD) analysis coupled with validation by different methods on the same patient samples. The resulting 820 nonredundant sequences were analysed by high throughput bioinformatics analysis. Human proteins were identified for 73% (596) of the DD sequences. A large proportion (>50%) of the remaining unassigned sequences match ESTs (expressed sequence tags) from human tumours. For the functionally annotated proteins, there is significant enrichment for relevant biological processes, including cell motility, protein biosynthesis, stress and immune responses, cell death, cell cycle, cell proliferation and/or maintenance and transport. Three of the novel proteins (TMEM16A, PHLDB2 and ARHGAP21) were analysed further to show that they have the potential to be developed as therapeutic targets.

Amino Acid Sequence↗

Identifying Co-Expressed lncRNAs Correlated With Traits of Interest in an Animal Model for Metabolic Diseases in Humans.

Nutrigenomics investigates how nutrients modulate gene expression. Among them, fatty acids (FA) play important roles in regulating gene transcription, while long non-coding RNAs (lncRNAs) may be associated with gene regulation and metabolic diseases. This study aimed to analyze the hepatic transcriptome of pigs, a species frequently used as a model for nutrigenomic studies, to identify novel lncRNAs and their potential target genes in response to diets containing different sources of FA. Seventy-two pigs were fed four diets supplemented with 1.5% soybean oil (control), 3% canola oil, 3% fish oil, and 3% soybean oil. RNA sequencing of liver samples was performed to identify novel lncRNAs. Weighted Gene Co-expression Network Analysis (WGCNA) was used to identify modules associated with phenotypic traits related to lipid metabolism and inflammation. Functional enrichment analyses were then conducted to annotate genes within these modules using Gene Ontology (GO) terms and to assess overlap with Quantitative Trait Loci (QTL). The results revealed 106 novel lncRNAs potentially regulating genes associated with lipid metabolism and immune responses in pigs fed diets with different FA sources. These findings enhance understanding of the regulatory role of lncRNAs in pigs and reinforce their relevance as models for human metabolic diseases.

Animals↗

ForestTreeDB: a database dedicated to the mining of tree transcriptomes.

ForestTreeDB is intended as a resource that centralizes large-scale expressed sequence tag (EST) sequencing results from several tree species (http://foresttree.org/ftdb). It currently encompasses 344,878 quality sequences from 68 libraries, from diverse organs of conifer and hybrid poplar trees. It utilizes the Nimbus data model to provide a hosting system for multiple projects, and uses object-relational mapping APIs in Java and Perl for data accesses within an Oracle database designed to be scalable, maintainable and extendable. Transcriptome builds or unigene sets occupy the focal point of the system. Several of the five current species-specific unigenes were used to design microarrays and SNP resources. The ForestTreeDB web application provides the means for multiple combination database queries. It presents the user with a list of discrete queries to retrieve and download large EST datasets or sequences from precompiled unigene assemblies. Functional annotation assignment is not trivial in conifers which are distantly related to angiosperm model plants. Optimal annotations are achieved through database queries that integrate results from several procedures based open-source tools. ForestTreeDB aims to facilitate sequence mining of coherent annotations in multiple species to support comparative genomic approaches. We plan to continuously enrich ForestTreeDB with other resources through collaborations with other genomic projects.

Databases, Nucleic Acid↗

The disparate nature of "intergenic" polyadenylation sites.

The termination of mature eukaryotic mRNAs occurs at specific polyadenylation sites located downstream from stop codons in the 3'-untranslated region (UTR). An accurate delineation of these sites is essential for the study of 3'-UTR-based gene regulation and for the design of pertinent probes for transcriptome analysis. Although typical poly(A) sites are located between 0 and 2 kb from the stop codon, EST sequence analyses have identified sites located at unexpectedly long ranges (5-10 kb) in a number of genes. Here we perform a complete mapping of EST and full-length cDNA sequences on the mouse and human genome to observe putative poly(A) sites extending beyond annotated 3'-ends and into the intergenic regions. We introduce several quality parameters for poly(A) site prediction and train a classification tree to associate P-values to predicted sites. We observe a higher than background level of high-scoring sites up to 12-15 kb past the stop codon, both in human and mouse. This leads to an estimate of about 5000 human genes having unreported 3'-end extensions and about 3500 novel polyadenylated transcripts lying in present "intergenic" regions. These high-scoring, long-range poly(A) sites corresponding to novel transcripts and gene extensions should be incorporated into current human and mouse gene repositories.

3' Untranslated Regions↗

RIKEN Arabidopsis full-length (RAFL) cDNA and its applications for expression profiling under abiotic stress conditions.

Full-length cDNAs are essential for the correct annotation of genomic sequences and for the functional analysis of genes and their products. 155,144 RIKEN Arabidopsis full-length (RAFL) cDNA clones were isolated. The 3'-end expressed sequence tags (ESTs) of all 155,144 RAFL cDNAs were clustered into 14,668 non-redundant cDNA groups, about 60% of predicted genes. The sequence database of the RAFL cDNAs is useful for promoter analysis and the correct annotation of predicted transcription units and gene products. Recently, cDNA microarray analysis has been developed for quantitative analysis of global and simultaneous analysis of expression profiles. RAFL cDNA microarrays were prepared, containing independent full-length cDNA groups for analysing the expression profiles of genes under various stress- and hormone-treatment conditions and in various mutants and transgenic plants. In this review, recent progress on transcriptome analysis using the RAFL cDNA microarray is highlighted.

Arabidopsis↗

Iron-related transcriptomic variations in CaCo-2 cells, an in vitro model of intestinal absorptive cells.

Regulation of iron absorption by duodenal enterocytes is essential for the maintenance of homeostasis by preventing iron deficiency or overload. Despite the identification of a number of genes implicated in iron absorption and its regulation, it is likely that further factors remain to be identified. For that purpose, we used a global transcriptomic approach, using the CaCo-2 cell line as an in vitro model of intestinal absorptive cells. Pangenomic screening for variations in gene expression correlating with intracellular iron content allowed us to identify 171 genes. One hundred nine of these genes are clustered into five types of expression profile. This is the first time that most of these genes have been associated with iron metabolism. Functional annotation of these five clusters indicates potential links between the immune response, proteolysis processes, and iron depletion. In contrast, iron overload is associated with cellular metabolism, especially that of lipids and glutathione involving redox function and electron transfer.

Caco-2 Cells↗

Multi-omics analysis reveals distinct spatial compartmentalization of lung repair niches in pediatric ARDS.

BACKGROUND: Pediatric acute respiratory distress syndrome (PARDS), often triggered by viral infections, is a life-threatening condition. Despite its severity, children demonstrate significantly better survival rates and superior lung repair compared to adults. However, the mechanisms underlying this age-specific advantage remain incompletely understood. PATIENTS AND METHODS: We conducted a pilot multi-omics study of influenza-associated PARDS integrating single-cell RNA sequencing (scRNA-seq) of pediatric lung tissue and bronchoalveolar lavage fluid (BALF), spatial transcriptomics, and plasma proteomics. Analyses were harmonized with the Human Lung Cell Atlas (HLCA) reference, reanalysis of public pediatric PARDS airway scRNA-seq, and contextual comparisons to adult lethal COVID-19 lung. RESULTS: Tissue scRNA-seq and spatial data indicated outcome-linked divergence in PARDS. Survivor showed spatially restricted repair with preserved alveolar type II (AT2) cells, AT2-to-alveolar type I (AT1) differentiation signatures, and higher KRT17, whereas fatal case and adults exhibited diffuse immune activation with pro-fibrotic and pro-apoptotic signaling. In BALF, KRT17-positive airway stress–repair epithelial cells (hillock-like) increased from the acute to recovery phase, and plasma proteomics showed higher circulating KRT17 in survivors. HLCA-based label transfer strengthened cell-type definitions and enabled pediatric–adult comparisons suggesting biological and developmental differences; the adult lethal COVID-19 atlas provided a benchmark with attenuated epithelial repair and prominent collagen CTHRC1-pathologic fibroblasts. Fibroblast programs were regionally compartmentalized, with injury-enriched CTHRC1+ states versus alveolar fibroblasts in preserved areas, and showed stronger injury–homeostasis anti-correlation in fatalities. Myeloid remodeling included BALF transitions from FCN1-high inflammatory states toward FABP4-positive resident-like states, consistent with public pediatric datasets showing reduced inflammatory and interferon-stimulated gene (ISG) modules and severity-linked increases in aged neutrophils. CONCLUSIONS: This pilot multi-omics case series outlines putative pediatric lung repair niches in influenza-associated PARDS. KRT17-positive transitional epithelium, preserved AT2 differentiation, and restoration of resident-like macrophages may align with recovery, whereas diffuse immune activation and CTHRC1-enriched fibroblast programs may accompany worse outcomes. HLCA-guided annotations and adult benchmarks indicate possible age-related differences, warranting validation in larger multi-center cohorts.

Humans↗

Gene expression profiles during beta cell maturation and after IL-1beta exposure reveal important roles of Pdx-1 and Nkx6.1 for IL-1beta sensitivity.

AIM/HYPOTHESIS: Maturation of the beta cells in the islets of Langerhans is dependent upon sequential activation of different transcription factors such as Pdx-1 and Nkx6.1. This maturation is associated with an acquired sensitivity to cytokines and may eventually lead to type 1 diabetes. The aims of this study were to characterise changes in mRNA expression during beta cell maturation as well as after interleukin-1beta (IL-1beta) exposure. METHODS: Transcriptome analyses were performed on two phenotypes characterised as a glucagon-producing pre-beta-cell phenotype (NHI-glu), which matures to an IL-1beta-sensitive insulin-producing beta cell phenotype (NHI-ins). Beta cell lines over-expressing Pdx-1 or Nkx6.1, respectively, were used for functional characterisation of acquired IL-1beta sensitivity. RESULTS: During beta cell maturation 98 fully annotated mRNAs changed expression levels. Of these, 50 were also changed after 24 h of IL-1beta exposure. In addition, 522 and 197 fully annotated mRNAs, not affected by maturation, also changed expression levels following IL-1beta exposure of the beta cell and the pre-beta-cell phenotype, respectively. Beta cell maturation was associated with an increased expression of Nkx6.1, whereas both Pdx-1 and Nkx6.1 expression were decreased following IL-1beta exposure. Over-expression of Nkx6.1 or Pdx-1 in cell lines resulted in a significantly increased sensitivity to IL-1beta. CONCLUSIONS/INTERPRETATION: These results suggest that the final beta cell maturation accompanied by increased IL-1beta sensitivity is, in part, dependent upon the expression of genes regulated by Pdx-1 and Nkx6.1. Future classification of the genes regulated by these transcription factors and changed during beta cell maturation should elucidate their role in the acquired sensitivity to IL-1beta and may be helpful in identifying new targets for intervention/prevention strategies.

Animals↗

ARISE: RNA-anchored shared-edge topology and hierarchical fusion for spatial multi-omics integration.

MOTIVATION: Spatial multi-omics technologies jointly profile transcriptomes, proteins and chromatin accessibility in situ, enabling integrative analysis of tissue organization across molecular layers. However, most existing graph-based integration methods rely on independently constructed modality-specific k-nearest-neighbor graphs. When auxiliary modalities are sparse or noisy, these graphs can become topologically discordant, propagate spurious edges, weaken cross-modal alignment, and reduce spatial domain resolution. RESULTS: We present Anchored RNA for Integrated Spatial Embedding (ARISE), an RNA expression anchored framework for spatial multi-omics integration. ARISE defines a shared-edge topology by intersecting RNA feature-similarity and spatial-proximity graphs, encodes auxiliary modalities on this common scaffold, and integrates them through inside-out hierarchical fusion. We further show theoretically that graph intersection minimizes false-positive edges within a broad class of k-of-r graph fusion rules, providing a principled basis for topology anchoring. Across various spatial multi-omics benchmarks spanning simulated and real datasets in bi-modal and tri-modal settings, ARISE improves spatial domain identification, cross-modal consistency, and preservation of tissue structure relative to existing methods. Furthermore, the learned representation supports biologically meaningful downstream analyses, including marker-based domain annotation, pathway enrichment, and cis-regulatory inference, indicating that ARISE yields a robust and interpretable framework for spatial multi-omics integration. AVAILABILITY AND IMPLEMENTATION: The source code is available at https://github.com/XiangxiangWang-code/ARISE. The archived version used in this study is available at https://doi.org/10.6084/m9.figshare.32686137.v2.

Multiomics↗