Spatial mapping and functional genomics show how mouse cardiomyocytes mature.
Explore the source record for details and available documents.
Journal Article↗
SEARCH · Search PubMed
Results for “spatial genomics”
Search indexed PubMed citations on genomics, clinical trials, systematic reviews and public health. Explore titles, authors and supplied subject terms, then open the PubMed record.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Spatial separation of parental genomes in preimplantation mouse embryos.
We have used two different experimental approaches to demonstrate topological separation of parental genomes in preimplantation mouse embryos: mouse eggs fertilized with 5-bromodeoxyuridine (BrdU)-labeled sperm followed by detection of BrdU in early diploid embryos, and differential heterochromatin staining in mouse interspecific hybrid embryos. Separation of chromatin according to parental origin was preserved up to the four-cell embryo stage and then gradually disappeared. In F1 hybrid animals, genome separation was also observed in a proportion of somatic cells. Separate nuclear compartments during preimplantation development, when extreme chromatin remodelling occurs, and possibly in some differentiated cell types, may be associated with epigenetic reprogramming.
Animals↗
CoxFormer enables spatial omics inference with multimodal generative modeling.
Gene co-expression maps transcriptome-wide gene-gene relationships, yet high-quality estimates cover less than half the genome. Meanwhile, spatial omics either profiles restricted in situ panels or lacks cellular resolution. Extending co-expression transcriptome-wide could overcome these limitations by inferring unassayed gene expression at subcellular resolution. Here we show that CoxFormer integrates literature-derived gene knowledge with co-expression networks from bulk tissues and large-scale single-cell atlases to learn 512-dimensional representations for 32,016 human genes. These embeddings capture functional gene relationships and serve as a generative prior for spatial inference across platforms and modalities. Without requiring a matched single-cell RNA-sequencing reference, CoxFormer supports four applications beyond measured genes: histology-based expression imputation, gene activity prediction from chromatin accessibility, subcellular super-resolution inference, and pathological region detection. Together, CoxFormer extends gene embedding from gene- and cell-level tasks to whole-transcriptome spatial inference, providing a unified framework for biological analysis beyond the limited gene coverage of current spatial omics technologies.
Humans↗
The Spatial and Temporal Repeatability of Genomic Responses to Natural Selection as Demonstrated in Stickleback Populations Experiencing Highly Dynamic Environments.
The evolution of genotypic parallelism under shared environmental conditions provides strong evidence for the role of natural selection. However, analyses typically examine genomic signatures of selection long after the putative selection event and only assess the repeatability of responses across spatial population replicates. This impedes our ability to attribute a particular response to a given selection pressure and to distinguish non-parallel responses caused by stochastic processes from those caused by local selection. As such, the consistency of natural selection over space and time is unknown, and the role of persistent local selection pressures is unclear. Here, we leveraged the natural bar-built estuary system of Santa Cruz, California, to examine the repeatability of seasonal genomic change in threespine stickleback (Gasterosteus aculeatus) over space and time. By comparing allele-frequency shifts that are shared across locations (spatial repeatability) with those that are shared across years within locations (temporal repeatability), we identified both spatially shared and local components of putative selection. We found that repeated seasonal outlier responses occurred more often than expected under a neutral null model. Although repeatability declined as the number of estuaries sharing an outlier increased, enrichment above neutral expectations increased with broader spatial sharing, particularly for outliers repeated across both years. While the precise outlier SNPs varied across years, estuary-specific patterns of responses were broadly consistent, suggesting an important role for local conditions. Together, our findings show that temporal sampling can reveal components of putative selection that would be missed from spatial comparisons alone. More broadly, they highlight the importance of examining repeatability over both space and time to understand the parallel and non-parallel components of adaptive genomic change.
Animals↗
Spatially guided in vivo single-cell functional genomics of postnatal heart.
Understanding how spatial organization and cell-cell interactions shape gene regulatory programs is central to decoding tissue development and function. The transition at birth, marked by increased circulatory demands and rapid tissue growth, requires precise spatiotemporal coordination of cardiac maturation. In this study, we generated a high-resolution spatial and temporal atlas of the postnatal mouse heart by integrating single-nucleus RNA sequencing with image-based spatial transcriptomics. This framework revealed dynamic cellular interactions, niche-specific signaling and transcriptional programs guiding cardiomyocyte maturation. To functionally test prioritized regulators in vivo and at scale, we developed PIP-seq (probe-based indel-detectable Perturb-seq), a high-throughput platform that detects single guide RNA identity, infers gene editing and profiles transcription from fixed nuclei. Applying PIP-seq to the developing postnatal heart, we identified 21 previously uncharacterized regulators of cardiomyocyte maturation, including genes essential for sarcomere assembly, metabolic reprogramming and electrophysiological transitions. Together, our findings define how microenvironmental signals and intrinsic gene programs cooperate to guide heart maturation and establish a broadly applicable framework for functional genomics in complex tissues.
Animals↗
Genomic haplotype blocks may not accurately reflect spatial variation in historic recombination intensity.
Recently, genomic data have revealed a "block-like" structure of haplotype diversity on human chromosomes. This structure is anticipated to facilitate gene mapping studies, because strong associations among loci within a block may allow haplotype variation to be tagged with a limited number of markers. But its usefulness to mapping efforts depends on the consistency of the block structure within and among populations, which in turn depends on how the block structure arises. Recombination hot spots are generally thought to underlie the block structure, but haplotype blocks can also develop stochastically under random recombination, in which case the block structure will show limited consistency among populations. Using coalescent models, which we upscaled to simulate the evolution of haplotypes with many markers at fixed distances, we show that the relationship between block boundaries and historic recombination intensity may be surprisingly weak. The majority of historic recombinations do not leave a footprint in present-day linkage disequilibrium patterns, and the block structure is sensitive to factors that affect the timing of recombination relative to marker mutation events in the genealogy, such as marker frequency bias and historic population size changes. Our results give insight into the potential of stochastic events to affect haplotype block structure, which can limit the usefulness of the block structure to mapping studies.
Animals↗
Giotto Suite: a multiscale and technology-agnostic spatial multiomics analysis ecosystem.
Emerging spatial multiomics technologies provide an increasingly large amount of information content at multiple scales. However, it remains challenging to efficiently represent and harmonize diverse spatial datasets. Here we present Giotto Suite, a suite of modular packages that provides scalable and extensible end-to-end solutions for multiscale and multiomic data analysis, integration and visualization. At its core, Giotto Suite is centered around an innovative data framework, allowing the representation and integration of spatial omics data in a technology-agnostic manner. Giotto Suite integrates molecular, morphology, spatial and annotated feature information to create a responsive and flexible workflow, as demonstrated by applications to several state-of-the-art spatial technologies. Furthermore, Giotto Suite builds upon interoperable interfaces and data structures that bridge the established fields of genomics and spatial data science in R, thereby enabling independent developers to create custom-engineered pipelines. As such, Giotto Suite creates an immersive and multiscale ecosystem for spatial multiomic data analysis.
Genomics↗
Spatial organization of transcription by RNA polymerase III.
RNA polymerase III (pol III) transcribes many essential, small, noncoding RNAs, including the 5S rRNAs and tRNAs. While most pol III-transcribed genes are found scattered throughout the linear chromosome maps or in multiple linear clusters, there is increasing evidence that many of these genes prefer to be spatially clustered, often at or near the nucleolus. This association could create an environment that fosters the coregulation of transcription by pol III with transcription of the large ribosomal RNA repeats by RNA polymerase I (pol I) within the nucleolus. Given the high number of pol III-transcribed genes in all eukaryotic genomes, the spatial organization of these genes is likely to affect a large portion of the other genes in a genome. In this Survey and Summary we analyze the reports regarding the spatial organization of pol III genes and address the potential influence of this organization on transcriptional regulation.
Animals↗
Patient-Derived Organoid Models and Precision HIPEC in Diffuse Malignant Peritoneal Mesothelioma: Modeling Heterogeneity to Address Recurrence.
Diffuse malignant peritoneal mesothelioma (DMPM) is a rare malignancy for which cytoreductive surgery (CRS) with hyperthermic intraperitoneal chemotherapy (HIPEC) is central to treatment in appropriately selected patients. Recurrence remains common even after complete macroscopic cytoreduction. Current HIPEC regimens are protocolized at the institutional and population levels but are not individualized using site-specific molecular or functional tumor biology. We performed a narrative review of clinical, genomic, epigenetic, immune, microenvironmental, and patient-derived organoid evidence relevant to DMPM, CRS/HIPEC, and treatment resistance. Recurrence is multifactorial, with plausible contributions from spatial, histologic, genomic, epigenetic, immune, stromal, and pharmacokinetic heterogeneity. Three primary reports provide direct DMPM organoid evidence, including preliminary demonstrations of patient-specific drug response and discordant responses among anatomically distinct implants. However, these platforms differ biologically, and predictive thresholds, analytical reproducibility, turnaround time, and microenvironmental modeling remain unvalidated. Multi-site organoid pharmacotyping integrated with molecular profiling is therefore a plausible strategy for studying HIPEC resistance. Translation requires a staged pathway encompassing analytical validity, blinded clinical validity, and clinical-utility testing. Precision HIPEC should presently be considered an investigational, validation-ready framework rather than a standard of care.
Humans↗
Spatial Transcriptomics Identifies Characteristic Immunological Niches in Atopic Dermatitis.
BACKGROUND: Atopic dermatitis (AD) is primarily driven by a Type 2 immune response, with T helper (TH2) cells producing IL-4 and IL-13, thereby promoting inflammation, itch, and a compromised skin barrier. Yet, the spatial organization of pathogenic immune cells and their interactions with stromal and epithelial compartments in human AD skin remain incompletely understood. METHODS: We performed 10× Genomics Visium spatial transcriptomics on FFPE skin biopsies from patients with AD (n = 6), psoriasis (n = 2), and healthy controls (n = 5). Data were integrated with AD single-cell RNA sequencing (scRNA-seq) datasets and complemented by imaging mass cytometry (IMC) and multiplex immunofluorescence (IF) to validate the spatial localization of immune cells. Cell-cell communication analysis revealed putative signaling interactions within immune niches. RESULTS: Spatial clustering resolved tissue compartments and demonstrated transcriptional dysregulation in keratinocytes in AD and psoriasis. AD lesions showed a conserved spatial organization of immune aggregates within the superficial dermis. Integration of scRNA-seq signatures revealed spatially organized co-localization of T cells and mature migratory dendritic cells (mmDCs). We developed a ring-based neighborhood analysis to characterize the cellular organization of the immune-stromal niches, revealing T cell-enriched regions surrounded by inflammatory fibroblasts and activated keratinocytes. Intercellular communication analysis further identified putative signaling within mmDC-T cell niches that may promote pathogenic T cell recruitment and activation. Application of tertiary lymphoid structure (TLS) signatures indicated the presence of TLS-like regions. IMC and IF validated the close spatial proximity between activated TH2 cells and mmDCs. CONCLUSION: AD lesions contain spatially organized TLS-like immune niches at the dermal-epidermal junction, characterized by the close association of T cells and mmDCs and coordinated interactions with surrounding stromal and epithelial compartments. These mmDC-T cell niches may represent potential targets for future therapeutic strategies aimed at disrupting persistent local inflammatory pathways and improving long-term disease control.
atopic dermatitis↗
IL1RAP Is Associated With an Inflammation-Immunity-Related State in Skin Cutaneous Melanoma: Integrative Evidence From Pan-Cancer Data and Melanoma Immunotherapy Cohorts.
BACKGROUND: The crosstalk between inflammation and immunity plays a central role in tumor progression, immune evasion, and therapeutic response. Interleukin-1 receptor accessory protein (IL1RAP) is a key adaptor in inflammatory signaling, yet its immunological relevance and clinical implications in skin cutaneous melanoma (SKCM) remain largely unexplored. METHODS: We performed an integrative analysis combining pan-cancer and melanoma-focused datasets. Bulk transcriptomic, single-cell, spatial transcriptomic, genomic alteration, pharmacogenomic, and clinical survival data were obtained from TCGA, GTEx, GEO, ENA, and other public resources. IL1RAP expression was evaluated across cancer types in relation to diagnostic performance, immune subtypes, survival outcomes, functional pathway activity, immune-genomic states, somatic alterations, and drug-response metrics. Melanoma-focused analyses examined immune infiltration, methylation-derived tumor-infiltrating lymphocyte (MeTIL) scores, and exploratory survival associations in five treatment cohorts; the survival groups were defined using cohort-specific optimal cutoffs rather than median splits. RESULTS: IL1RAP expression differed between tumor and normal tissues in multiple cancers, although the direction and magnitude varied by cancer type. Pan-cancer survival associations were likewise context dependent. Single-cell and spatial transcriptomic resources indicated cell-type and spatial heterogeneity of IL1RAP expression within tumor microenvironments. Pathway, immune-genomic, and pharmacogenomic analyses identified exploratory associations with functional states, genomic features, and drug-response metrics. In SKCM, IL1RAP expression was associated with several immune-infiltration estimates and higher MeTIL scores. Across five melanoma immunotherapy cohorts, the direction and magnitude of the overall survival associations varied substantially. CONCLUSIONS: This retrospective integrative analysis suggests that IL1RAP may mark an inflammation-immunity-related state in SKCM. The heterogeneous associations across cancers and melanoma treatment cohorts support further validation but do not establish IL1RAP as a causal regulator, a treatment-response predictor, or a therapeutic target.
IL1RAP↗
Combined somatic mutation and transcriptome analysis reveals region-specific differences in clonal architecture in human cortex.
The human cerebral cortex is specialized into regions, but little is known about how human cellular lineages shape cortical regional variation and neuronal cell-type distribution during development. Here, we map single-cell lineages of human cortical regions and neuronal subtypes using >1,000 somatic single-nucleotide variants (sSNVs) identified from deep bulk whole-genome sequencing and analyzed over 25 regions and >72,000 single cells. In the fronto-parietal cortex, sSNVs are rarely restricted, marking neuron-generating clones that disperse into neighboring regions. In contrast, the primary visual cortex harbors 30%-70% more sSNVs than the neighboring secondary visual cortex. Clones at this border exhibit more restricted dispersion, suggesting late developmental lineage segregation. Single-nucleus sSNV and whole-transcriptome analysis reveal glutamatergic neuron clones with modest regional restrictions that share low-mosaic sSNVs with some GABAergic neurons, suggesting a recent dorsal cortical progenitor. Our analysis reveals human-specific cortical lineage patterns, regional differences in clonal patterns, and late divergence of some glutamatergic/GABAergic lineages.
Humans↗
Spatial positioning; a new dimension in genome function.
The eukaryotic cell nucleus is a heterogeneous organelle. Chromosomes are nonrandomly positioned within the nuclear space, and individual gene loci experience distinct local environments due to the presence of chromatin domains and subnuclear compartments. Recent observations have highlighted the important yet still largely mysterious role of spatial positioning in genome activity and stability.
Animals↗
Cyclin-dependent kinase 4 and 6 inhibitors and the breast cancer immune ecosystem: immune remodeling, resistance, and therapeutic reprogramming.
Cyclin-dependent kinase 4 and 6 inhibitors (CDK4/6 inhibitors) combined with endocrine therapy have become a therapeutic backbone for hormone receptor-positive, human epidermal growth factor receptor 2-negative breast cancer, yet durable disease control is frequently limited by intrinsic and acquired resistance. Canonical tumor-cell mechanisms, including retinoblastoma-pathway escape, cyclin E-cyclin-dependent kinase 2 (CDK2) activation, endocrine adaptation, and phosphoinositide 3-kinase (PI3K)-AKT-mechanistic target of rapamycin (mTOR) signaling, explain only part of this failure because they do not fully capture dynamic immune and stromal remodeling. Preclinical and translational studies indicate that early CDK4/6 inhibition can enhance antigen presentation, activate interferon-related programs, restrain regulatory T cells, and promote a T-cell-inflamed state. These effects are conditional and may not persist during prolonged treatment. Sustained therapy can instead drive heterogeneous resistant niches characterized by stromal remodeling, myeloid recruitment, checkpoint adaptation, and T-cell dysfunction. This immune-state dependence provides a rationale for immune checkpoint blockade, although clinical combinations have shown mixed efficacy and clinically relevant hepatic, pulmonary, and hematologic toxicities. Sequential or lead-in strategies therefore warrant prospective evaluation. Oxidative phosphorylation (OXPHOS) and redox adaptation may sustain selected resistant states and expose context-dependent ferroptotic vulnerabilities. Ferroptosis may connect tumor-cell killing with immune regulation, whereas nanomedicine may improve tumor-selective delivery. Both strategies remain largely preclinical and require further evaluation of pharmacokinetics, biodistribution, toxicity, manufacturability, and immune-cell safety. This Review distinguishes intrinsic from acquired resistance across interpatient, intratumoral, spatial, and temporal dimensions. It integrates tumor-cell escape with cytokine, immune, stromal, vascular, and metabolic remodeling and summarizes emerging therapeutic strategies. We further propose a candidate biomarker-informed framework that integrates genomic profiling, spatial immune architecture, circulating biomarkers, T-cell receptor (TCR) dynamics, transcriptomic and single-cell analyses, artificial intelligence (AI)-assisted multimodal integration, and longitudinal sampling. This framework is intended to support biomarker development and prospective trial design rather than current clinical decision-making, providing a translational basis for testing state-informed and sequence-aware therapeutic strategies.
Humans↗
A serpin-myeloid axis in pancreatic cancer heterogeneity and immune evasion.
Pancreatic ductal carcinoma (PDAC) is characterized by a highly immunosuppressive, extracellular matrix-rich microenvironment, yet tumours display marked heterogeneity1-4. This raises the question of whether immune resistance is a global tumour property or is organized within spatially restricted niches. Here, using Perturb-map spatial functional genomics, we determine how different genes shape the growth and cellular environments of PDAC clones across space and time. This analysis revealed early gene-driven remodelling of local immune neighbourhoods preceding late-stage spatial clonal dominance. We identify SERPINE1 (encoding plasminogen activator inhibitor 1 (PAI1)) and SERPINB2 (encoding PAI2) as dominant regulators of tumour microenvironment control and immune evasion. These serpins promote stabilization of fibrin-rich extracellular matrix niches that spatially retain and programme macrophages towards immunosuppressive states while excluding cytotoxic T cells. Loss of Serpine1 or Serpinb2, or pharmacological inhibition of PAI1 or CD18, improves tumour control in mice and synergizes with anti-PD-1. Multimodal spatial analysis of patient tumours revealed that immunosuppressive niches form around rare SERPINB2- and SERPINE1-expressing PDAC subpopulations, dominated by SPP1+/MARCO+ macrophages. These findings identify cancer-derived SERPINE1 and SERPINB2 as local spatial organizers of immune suppression, linking tumour-intrinsic heterogeneity to local microenvironmental control and immunotherapy resistance in PDAC.
Journal Article↗
Quantitative assessment of genomic similarity from restriction fragment patterns.
A quantitative algorithm for comparing restriction fragment patterns (RFPs) was developed and used to estimate the genomic similarity of 18 isolates of pseudorabies virus of known origin. Variants of this algorithm using either untransformed or square-root-transformed differences between fragment sizes were investigated with regard to their ability to classify RFPs. Multidimensional scaling was used to represent spatially the genomic relatedness among samples, with 3 dimensions producing the most meaningful results. The square-root transformation provided more interpretable dimensions. The first dimension differentiated samples geographically, separating North American from European isolates. The second and third dimensions differentiated isolates with specific gene deletions (gE and gG, respectively) from those not having these deletions. Clusters of isolates were identified that were related either by collection from the same geographic area during a specific time period, or by laboratory intervention to create vaccines. These methods offer increased precision in the determination of genetic relatedness based on RFPs, and thus offer increased diagnostic accuracy for the determination of sources of infection.
Algorithms↗
PASS2: an automated database of protein alignments organised as structural superfamilies.
BACKGROUND: The functional selection and three-dimensional structural constraints of proteins in nature often relates to the retention of significant sequence similarity between proteins of similar fold and function despite poor sequence identity. Organization of structure-based sequence alignments for distantly related proteins, provides a map of the conserved and critical regions of the protein universe that is useful for the analysis of folding principles, for the evolutionary unification of protein families and for maximizing the information return from experimental structure determination. The Protein Alignment organised as Structural Superfamily (PASS2) database represents continuously updated, structural alignments for evolutionary related, sequentially distant proteins. DESCRIPTION: An automated and updated version of PASS2 is, in direct correspondence with SCOP 1.63, consisting of sequences having identity below 40% among themselves. Protein domains have been grouped into 628 multi-member superfamilies and 566 single member superfamilies. Structure-based sequence alignments for the superfamilies have been obtained using COMPARER, while initial equivalencies have been derived from a preliminary superposition using LSQMAN or STAMP 4.0. The final sequence alignments have been annotated for structural features using JOY4.0. The database is supplemented with sequence relatives belonging to different genomes, conserved spatially interacting and structural motifs, probabilistic hidden markov models of superfamilies based on the alignments and useful links to other databases. Probabilistic models and sensitive position specific profiles obtained from reliable superfamily alignments aid annotation of remote homologues and are useful tools in structural and functional genomics. PASS2 presents the phylogeny of its members both based on sequence and structural dissimilarities. Clustering of members allows us to understand diversification of the family members. The search engine has been improved for simpler browsing of the database. CONCLUSIONS: The database resolves alignments among the structural domains consisting of evolutionarily diverged set of sequences. Availability of reliable sequence alignments of distantly related proteins despite poor sequence identity and single-member superfamilies permit better sampling of structures in libraries for fold recognition of new sequences and for the understanding of protein structure-function relationships of individual superfamilies. PASS2 is accessible at http://www.ncbs.res.in/~faculty/mini/campass/pass2.html
Amino Acid Sequence↗
Single-cell and spatial transcriptomics define a progenitor subpopulation and fibroinflammatory niche at the leading edge of parathyroid carcinoma.
Parathyroid carcinoma (PC) is a rare but clinically aggressive endocrine malignancy with limited treatment options and a poorly defined tumor microenvironment (TME). To elucidate its cellular heterogeneity and spatial architecture, we integrated single-cell and spatial transcriptomic profiling with whole-exome sequencing and multiplex immunohistochemistry on eight parathyroid neoplasm specimens, including PC, parathyroid adenoma, and atypical parathyroid tumor. We identified a distinct progenitor-like endocrine subpopulation (Ca-1) enriched in CDC73-mutant PC, exhibiting stem-like properties, elevated cell cycle activity, and pronounced genomic instability. Spatial mapping revealed that Ca-1 cells preferentially localize at the leading edge, forming a fibroinflammatory niche characterized by the enrichment of inflammatory cancer-associated fibroblasts (iCAFs) and SPP1+ macrophages. Within this niche, the dipeptidyl peptidase 4 (DPP4) is selectively expressed in Ca-1 cells and iCAFs, implicating a potential paracrine axis driving stromal remodeling and immunosuppression. These findings suggest that a spatially organized ecosystem may promote PC progression through TME remodeling and highlight the DPP4-CXCL2 axis as a candidate pathway for future investigation in aggressive parathyroid neoplasms.
Humans↗