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Results for “Spatial transcriptomics”

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PubMed2005

Antiquity of microRNAs and their targets in land plants.

MicroRNAs (miRNAs) affect the morphology of flowering plants by the posttranscriptional regulation of genes involved in critical developmental events. Understanding the spatial and temporal dynamics of miRNA activity during development is therefore central for understanding miRNA functions. We describe a microarray suitable for detection of plant miRNAs. Profiling of Arabidopsis thaliana miRNAs during normal development extends previous expression analyses, highlighting differential expression of miRNA families within specific organs and tissue types. Comparison of our miRNA expression data with existing mRNA microarray data provided a global intersection of plant miRNA and mRNA expression profiles and revealed that tissues in which a given miRNA is highly expressed are unlikely to also show high expression of the corresponding targets. Expression profiling was also used in a phylogenetic survey to test the depth of plant miRNA conservation. Of the 23 families of miRNAs tested, expression of 11 was detected in a gymnosperm and eight in a fern, directly demonstrating that many plant miRNAs have remained essentially unchanged since before the emergence of flowering plants. We also describe an empirical strategy for detecting miRNA target genes from unsequenced transcriptomes and show that targets in nonflowering plants as deeply branching as ferns and mosses are homologous to the targets in Arabidopsis. Therefore, several individual miRNA regulatory circuits have ancient origins and have remained intact throughout the evolution and diversification of plants.

Arabidopsis↗

PubMed2004

Transcriptome profiling in root nodules and arbuscular mycorrhiza identifies a collection of novel genes induced during Medicago truncatula root endosymbioses.

Transcriptome profiling based on cDNA array hybridizations and in silico screening was used to identify Medicago truncatula genes induced in both root nodules and arbuscular mycorrhiza (AM). By array hybridizations, we detected several hundred genes that were upregulated in the root nodule and the AM symbiosis, respectively, with a total of 75 genes being induced during both interactions. The second approach based on in silico data mining yielded several hundred additional candidate genes with a predicted symbiosis-enhanced expression. A subset of the genes identified by either expression profiling tool was subjected to quantitative real-time reverse-transcription polymerase chain reaction for a verification of their symbiosis-induced expression. That way, induction in root nodules and AM was confirmed for 26 genes, most of them being reported as symbiosis-induced for the first time. In addition to delivering a number of novel symbiosis-induced genes, our approach identified several genes that were induced in only one of the two root endosymbioses. The spatial expression patterns of two symbiosis-induced genes encoding an annexin and a beta-tubulin were characterized in transgenic roots using promoter-reporter gene fusions.

Annexins↗

PubMed2026

Cucurbitacins in Plant-Insect Interactions: Biosynthesis, Regulation, Ecological Functions, and Prospects for Crop Protection.

Cucurbitacins are highly oxygenated tetracyclic triterpenoids characterized by intense bitterness, substantial structural diversity, and important consequences for plant-herbivore interactions. Although best known from Cucurbitaceae, cucurbitacins and related cucurbitane-type metabolites also occur in phylogenetically distant herbaceous and woody plants. Genetic and biochemical studies have validated several core biosynthetic steps, including cucurbitadienol formation by oxidosqualene cyclases and subsequent modification by cytochrome P450 monooxygenases, acyltransferases, and glycosyltransferases. Tissue-preferential basic helix-loop-helix transcription factors constitute the best-characterized regulatory layer, whereas the evidence supporting accessory regulators, transporters, and environmental responses varies from functional validation to transcriptomic or genomic prediction. From the plant perspective, cucurbitacins deter feeding or impair performance in many generalist and non-adapted herbivores. By contrast, their use as host-recognition cues and feeding stimulants by specialist diabroticite beetles reflects evolved herbivore adaptations involving perception, tolerance, metabolism, or sequestration rather than a second defensive function of the plant trait. Herbivore-induced cucurbitacin accumulation has been demonstrated in particular systems, although its regulatory mechanisms and ecological generality remain unresolved. Unlike previous reviews centered primarily on cucurbitacin chemistry, pharmacological activity, or individual biosynthetic pathways, this review integrates evidence-graded pathway reconstruction and molecular regulation with taxonomic distribution, insect adaptation, domestication, and agroecological consequences. Mechanistically, this review traces how scaffold formation, oxidative tailoring, conjugation, tissue-specific regulation, and transport give rise to contrasting ecological outcomes through herbivore-specific perception, tolerance, metabolism, and sequestration. We conclude that uniformly increasing or eliminating cucurbitacins is unlikely to provide broadly effective crop resistance because either direction may favor a different herbivore group. Future priorities include functional validation of candidate genes, spatially resolved metabolite analysis, comparative investigation of non-cucurbit lineages, and field evaluation involving generalist and specialist herbivores, crop quality, and non-target organisms. These advances will support context-specific fruit-quality improvement, behavioral pest control, and integrated pest management strategies rather than cucurbitacin manipulation as a stand-alone resistance approach.

agroecology↗

PubMed2026

TFPI-high myofibroblast states and a meta-program-related five-gene prognostic signature in breast cancer.

Intratumoral heterogeneity and tumor-microenvironment interactions limit prognostic stratification in breast cancer, but the prognostic relevance and cellular context of recurrent transcriptional meta-programs remain unclear. We aimed to derive a meta-program-related prognostic signature and characterize its component transcripts at single-cell resolution. Six paired institutional tumors and adjacent non-tumor tissues served as a proof-of-concept comparison. Univariable Cox screening and least absolute shrinkage and selection operator Cox regression were used to derive a five-gene score from a prespecified meta-program-related candidate set in The Cancer Genome Atlas Breast Invasive Carcinoma (TCGA-BRCA) training cohort; the score was tested internally and assessed in GSE20685 using fixed coefficients and cohort-specific median cutoffs. GSE161529 single-cell transcriptomic data were used to map signature transcripts across 136,526 quality-controlled cells, while donor-aware pseudobulk analysis compared upper- and lower-quartile TFPI expression states in annotated myofibroblasts. The score comprised TCN1, FOXJ1, PIGR, SLAIN1, and TFPI and was associated with overall survival in the training, testing, and external cohorts, with concordance indices of 0.782, 0.756, and 0.721, respectively. TFPI transcripts were detected across endothelial, fibroblast, and myofibroblast compartments. TFPI-high myofibroblasts showed transcriptional enrichment of extracellular matrix and collagen fibril organization, transforming growth factor beta signaling, epithelial-mesenchymal transition, and myogenesis, together with lower oxidative phosphorylation and fatty acid metabolism programs. In bulk TCGA-BRCA tissue, TFPI expression correlated positively with stromal (r = 0.48), immune (r = 0.25), and composite microenvironment scores (r = 0.40; all p < 0.001). These findings identify a hypothesis-generating five-gene bulk-tissue prognostic signature and an expression-associated TFPI-high myofibroblast state but do not establish a discrete lineage, the cellular source of bulk TFPI, a TFPI-dependent mechanism, or clinical utility. Independent prospective cohorts, spatial and protein-level validation, and functional perturbation studies are required.

Journal Article↗

PubMed2003

Peptidomics: A new approach to affinity protein microarrays.

Protein microarrays for diagnostic and proteomic analyses are being developed using a number of different techniques for each of the steps required including immobilisation methods, assay and detection systems. This is extremely different to the development of DNA microarrays which is now a well established technology that has demonstrated the capabilities of transcriptomics to deliver validated differential transcripts. As mRNA and protein levels do not always correlate, protein microarrays would seem to be an obvious successor to DNA arrays. Unlike nucleic acids, however, protein targets are typically nonhomogeneous in physicochemical properties and affinity capture agents are often poorly characterised making the experiments difficult to perfect and reproduce. Moreover, running multiple affinity assays in parallel (multiplexing) is compromised by the heterogeneity of antibody affinities to their protein targets. In the peptidomic approach presented here the assayed mixture of proteins is enzymatically digested prior to affinity capture to form a mixture of short peptides that are more similar in their physicochemical properties than intact proteins. These peptides can be predicted by in silico digestion of individual proteins, e.g. from protein databases allowing design of nonhomologous reagents for the screening of affinity agent libraries. The use of mass spectrometry (e.g. matrix-assisted laser desorption/ionization-time of flight mass spectrometry) for a direct confirmation of the identity of the species captured, provides a further advantage compared to the more usual method of detection in which fluorescently labelled captured species are scanned to give a spatially resolved image of the array.

Peptides↗

PubMed2005

Economy, speed and size matter: evolutionary forces driving nuclear genome miniaturization and expansion.

BACKGROUND: Nuclear genome size varies 300 000-fold, whereas transcriptome size varies merely 17-fold. In the largest genomes nearly all DNA is non-genic secondary DNA, mostly intergenic but also within introns. There is now compelling evidence that secondary DNA is functional, i.e. positively selected by organismal selection, not the purely neutral or 'selfish' outcome of mutation pressure. The skeletal DNA theory argued that nuclear volumes are genetically determined primarily by nuclear DNA amounts, modulated somewhat by genes affecting the degree of DNA packing or unfolding; the huge spread of nuclear genome sizes is the necessary consequence of the origin of the nuclear envelope and the nucleation of its assembly by DNA, plus the adaptively significant 300 000-fold range of cell volumes and selection for balanced growth by optimizing karyoplasmic volume ratios (essentially invariant with cell volume in growing/multiplying cells). This simple explanation of the C-value paradox is refined here in the light of new insights into the nature of heterochromatin and the nuclear lamina, the genetic control of cell volume, and large-scale eukaryote phylogeny, placing special emphasis on protist test cases of the basic principles of nuclear genome size evolution. GENOME MINIATURIZATION: and Expansion Intracellular parasites (e.g. Plasmodium, microsporidia) dwarfed their genomes by gene loss and eliminating virtually all secondary DNA. The primary driving forces for genome reduction are metabolic and spatial economy and cell multiplication speed. Most extreme nuclear shrinkage yielded genomes as tiny as 0.38 Mb (making the nuclear genome size range effectively 1.8 million-fold!) in some minute enslaved nuclei (nucleomorphs) of cryptomonads and chlorarachneans, chimaeric cells that also retain a separate normal large nucleus. The latter shows typical correlation between genome size and cell volume, but nucleomorphs do not despite co-existing in the same cell for >500 My. Thus mutation pressure does not inexorably increase genome size; selection can eliminate essentially all non-coding DNA if need be. Nucleomorphs and microsporidia even reduced gene size. Expansion of secondary DNA in the main nucleus, and in large-celled eukaryotes generally, must be positively selected for function. Ciliate nuclear dimorphism provides a key test that refutes the selfish DNA and strongly supports the skeletal DNA/karyoplasmic ratio interpretation of genome size evolution. GENETIC CONTROL OF CELL VOLUME IS MULTIGENIC: The quantitatively proportional correlation between genome size and cell size cannot be explained by purely mutational theories, as eukaryote cell volumes are causally determined by cell cycle control genes, not by DNA amounts.

Animals↗

PubMed2026

Spatially resolved single-cell atlas reveals the macroevolutionary trajectory of animal hearts.

Animal hearts display diverse anatomical structures during adaptive evolution. Here, we present a multiomics atlas of adult hearts from 27 species across chordates, arthropods, and mollusks. Joint analysis indicates that Bilateria hearts share a core gene repertoire, taking a stepwise "add-on" approach as a universal evolutionary strategy. The "proto-heart" is populated by key cell types, including cardiomyocytes, fibroblasts, endothelial cells, and neural cells, which maintained core signatures while evolving with shifts in living environments and corresponding adaptations in the cardiovascular system. Additionally, we reveal an evolutionarily conserved cardiomyocyte state dynamic potentially linked to cardiac development and stress responses. Finally, we identify a common molecular program underpinning chamber evolution from a ventricular foundation. This work establishes a resource for understanding the intrinsic mechanisms of heart evolution.

Animals↗