A human embryonic limb cell atlas resolved in space and time

Spatial multi-omics: deciphering technological landscape of integration of multi-omics and its applications

The emergence of spatial multi-omics has helped address the limitations of single-cell sequencing, which often leads to the loss of spatial context among cell populations. Integrated analysis of the genome, transcriptome, proteome, metabolome, and epigenome has enhanced our understanding of cell biology and the molecular basis of human diseases. Moreover, this approach offers profound insights into the interactions between intracellular and intercellular molecular mechanisms involved in the development, physiology, and pathogenesis of human diseases. In this comprehensive review, we examine current advancements in multi-omics technologies, focusing on their evolution and refinement over the past decade, including improvements in throughput and resolution, modality integration, and accuracy. We also discuss the pivotal contributions of spatial multi-omics in revealing spatial heterogeneity, constructing detailed spatial atlases, deciphering spatial crosstalk in tumor immunology, and advancing translational research and cancer therapy through precise spatial mapping.

Integrating gene expression and imaging data across Visium capture areas with visiumStitched

Background

Visium is a widely-used spatially-resolved transcriptomics assay available from 10x Genomics. Standard Visium capture areas (6.5mm by 6.5mm) limit the survey of larger tissue structures, but combining overlapping images and associated gene expression data allow for more complex study designs. Current software can handle nested or partial image overlaps, but is designed for merging up to two capture areas, and cannot account for some technical scenarios related to capture area alignment.

Results

We generated Visium data from a postmortem human tissue sample such that two capture areas were partially overlapping and a third one was adjacent. We developed the R/Bioconductor package visiumStitched, which facilitates stitching the images together with Fiji (ImageJ), and constructing SpatialExperiment R objects with the stitched images and gene expression data. visiumStitched constructs an artificial hexagonal array grid which allows seamless downstream analyses such as spatially-aware clustering without discarding data from overlapping spots. Data stitched with visiumStitched can then be interactively visualized with spatialLIBD.

Conclusions

visiumStitched provides a simple, but flexible framework to handle various multi-capture area study design scenarios. Specifically, it resolves a data processing step without disrupting analysis workflows and without discarding data from overlapping spots. visiumStiched relies on affine transformations by Fiji, which have limitations and are less accurate when aligning against an atlas or other situations. visiumStiched provides an easy-to-use solution which expands possibilities for designing multi-capture area study designs.

Skeletal stem and progenitor cells in bone development and repair

Bone development, growth, and repair are complex processes involving various cell types and interactions, with central roles played by skeletal stem and progenitor cells. Recent research brought new insights into the skeletal precursor populations that mediate intramembranous and endochondral bone development. Later in life, many of the cellular and molecular mechanisms determining development are reactivated upon fracture, with powerful trauma-induced signaling cues triggering a variety of postnatal skeletal stem/progenitor cells (SSPCs) residing near the bone defect. Interestingly, in this injury context, the current evidence suggests that the fates of both SSPCs and differentiated skeletal cells can be considerably flexible and dynamic, and that multiple cell sources can be activated to operate as functional progenitors generating chondrocytes and/or osteoblasts. The combined implementation of in vivo lineage tracing, cell surface marker-based cell selection, single-cell molecular analyses, and high-resolution in situ imaging has strongly improved our insights into the diversity and roles of developmental and reparative stem/progenitor subsets, while also unveiling the complexity of their dynamics, hierarchies, and relationships. Albeit incompletely understood at present, findings supporting lineage flexibility and possibly plasticity among sources of osteogenic cells challenge the classical dogma of a single primitive, self-renewing, multipotent stem cell driving bone tissue formation and regeneration from the apex of a hierarchical and strictly unidirectional differentiation tree. We here review the state of the field and the newest discoveries in the origin, identity, and fates of skeletal progenitor cells during bone development and growth, discuss the contributions of adult SSPC populations to fracture repair, and reflect on the dynamism and relationships among skeletal precursors and differentiated cell lineages. Further research directed at unraveling the heterogeneity and capacities of SSPCs, as well as the regulatory cues determining their fate and functioning, will offer vital new options for clinical translation toward compromised fracture healing and bone regenerative medicine.

Mechanisms of regeneration: to what extent do they recapitulate development?

One of the enduring debates in regeneration biology is the degree to which regeneration mirrors development. Recent technical advances, such as single-cell transcriptomics and the broad applicability of CRISPR systems, coupled with new model organisms in research, have led to the exploration of this longstanding concept from a broader perspective. In this Review, I outline the historical parallels between development and regeneration before focusing on recent research that highlights how dissecting the divergence between these processes can uncover previously unreported biological mechanisms. Finally, I discuss how these advances position regeneration as a more dynamic and variable process with expanded possibilities for morphogenesis compared with development. Collectively, these insights into mechanisms that orchestrate morphogenesis may reshape our understanding of the evolution of regeneration, reveal hidden biology activated by injury, and offer non-developmental strategies for restoring lost or damaged organs and tissues.

Spatial transcriptomics in embryonic mouse diaphragm muscle reveals regional gradients and subdomains of developmental gene expression

The murine embryonic diaphragm is a primary model for studying myogenesis and neuro-muscular synaptogenesis, both representing processes regulated by spatially organized genetic programs of myonuclei located in distinct myodomains. However, a spatial gene expression pattern of embryonic mouse diaphragm has not been reported. Here, we provide spatially resolved gene expression data for horizontally sectioned embryonic mouse diaphragms at embryonic days E14.5 and E18.5. These data reveal gene signatures for specific muscle regions with distinct maturity and fiber type composition, as well as for a central neuromuscular junction (NMJ) and a peripheral myotendinous junction (MTJ) compartment. Comparing spatial expression patterns of wild-type mice with those of transgenic mice lacking either the skeletal muscle calcium channel CaV1.1 or β-catenin, reveals curtailed muscle development and dysregulated expression of genes potentially involved in NMJ formation. Altogether, these datasets provide a powerful resource for further studies of muscle development and NMJ formation in the mouse.

Leveraging single cell multiomic analyses to identify factors that drive human chondrocyte cell fate

Cartilage plays a crucial role in skeletal development and function, and abnormal development contributes to genetic and age-related skeletal disease. To better understand how human cartilage develops in vivo , we jointly profiled the transcriptome and open chromatin regions in individual nuclei recovered from distal femurs at 2 fetal timepoints. We used these multiomic data to identify transcription factors expressed in distinct chondrocyte subtypes, link accessible regulatory elements with gene expression, and predict transcription factor-based regulatory networks that are important for growth plate or epiphyseal chondrocyte differentiation. We developed a human pluripotent stem cell platform for interrogating the function of predicted transcription factors during chondrocyte differentiation and used it to test NFATC2 . We expect new regulatory networks we uncovered using multiomic data to be important for promoting cartilage health and treating disease, and our platform to be a useful tool for studying cartilage development in vitro .

Statement of Significance

The identity and integrity of the articular cartilage lining our joints are crucial to pain-free activities of daily living. Here we identified a gene regulatory landscape of human chondrogenesis at single cell resolution, which is expected to open new avenues of research aimed at mitigating cartilage diseases that affect hundreds of millions of individuals world-wide.

Epigenetic mechanisms of osteoarthritis risk in human skeletal development

The epigenome, including the methylation of cytosine bases at CG dinucleotides, is intrinsically linked to transcriptional regulation. The tight regulation of gene expression during skeletal development is essential, with ~1/500 individuals born with skeletal abnormalities. Furthermore, increasing evidence is emerging to link age-associated complex genetic musculoskeletal diseases, including osteoarthritis (OA), to developmental factors including joint shape. Multiple studies have shown a functional role for DNA methylation in the genetic mechanisms of OA risk using articular cartilage samples taken from aged patients. Despite this, our knowledge of temporal changes to the methylome during human cartilage development has been limited. We quantified DNA methylation at ~700,000 individual CpGs across the epigenome of developing human articular cartilage in 72 samples ranging from 7-21 post-conception weeks, a time period that includes cavitation of the developing knee joint. We identified significant changes in 8% of all CpGs, and >9400 developmental differentially methylated regions (dDMRs). The largest hypermethylated dDMRs mapped to transcriptional regulators of early skeletal patterning including MEIS1 and IRX1. Conversely, the largest hypomethylated dDMRs mapped to genes encoding extracellular matrix proteins including SPON2 and TNXB and were enriched in chondrocyte enhancers. Significant correlations were identified between the expression of these genes and methylation within the hypomethylated dDMRs. We further identified 811 CpGs at which significant dimorphism was present between the male and female samples, with the majority (68%) being hypermethylated in female samples. Following imputation, we captured the genotype of these samples at >5 million variants and performed epigenome-wide methylation quantitative trait locus (mQTL) analysis. Colocalization analysis identified 26 loci at which genetic variants exhibited shared impacts upon methylation and OA genetic risk. This included loci which have been previously reported to harbour OA-mQTLs (including GDF5 and ALDH1A2), yet the majority (73%) were novel (including those mapping to CHST3, FGF1 and TEAD1). To our knowledge, this is the first extensive study of DNA methylation across human articular cartilage development. We identify considerable methylomic plasticity within the development of knee cartilage and report active epigenomic mediators of OA risk operating in prenatal joint tissues.

An integrated single-nucleus and spatial transcriptomics atlas reveals the molecular landscape of the human hippocampus

The hippocampus contains many unique cell types, which serve the structure's specialized functions, including learning, memory and cognition. These cells have distinct spatial topography, morphology, physiology, and connectivity, highlighting the need for transcriptome-wide profiling strategies that retain cytoarchitectural organization. Here, we generated spatially-resolved transcriptomics (SRT) and single-nucleus RNA-sequencing (snRNA-seq) data from adjacent tissue sections of the anterior human hippocampus across ten adult neurotypical donors. We defined molecular profiles for hippocampal cell types and spatial domains. Using non-negative matrix factorization and transfer learning, we integrated these data to define gene expression patterns within the snRNA-seq data and infer the expression of these patterns in the SRT data. With this approach, we leveraged existing rodent datasets that feature information on circuit connectivity and neural activity induction to make predictions about axonal projection targets and likelihood of ensemble recruitment in spatially-defined cellular populations of the human hippocampus. Finally, we integrated genome-wide association studies with transcriptomic data to identify enrichment of genetic components for neurodevelopmental, neuropsychiatric, and neurodegenerative disorders across cell types, spatial domains, and gene expression patterns of the human hippocampus. To make this comprehensive molecular atlas accessible to the scientific community, both raw and processed data are freely available, including through interactive web applications.

Mapping Cell Atlases at the Single-Cell Level

Recent advancements in single-cell technologies have led to rapid developments in the construction of cell atlases. These atlases have the potential to provide detailed information about every cell type in different organisms, enabling the characterization of cellular diversity at the single-cell level. Global efforts in developing comprehensive cell atlases have profound implications for both basic research and clinical applications. This review provides a broad overview of the cellular diversity and dynamics across various biological systems. In addition, the incorporation of machine learning techniques into cell atlas analyses opens up exciting prospects for the field of integrative biology.