bims-gerecp Biomed News
on Gene regulatory networks of epithelial cell plasticity
Issue of 2026–10–04
eight papers selected by
Xiao Qin, University of Oxford
  1. Bigger than CRISPR? A guide to the latest genome editors.
  2. A single-nucleus multi-omic atlas of gene regulation across 21 adult human tissues.
  3. Population-scale immune multiome atlas reveals regulatory disease mechanisms.
  4. A meta-interaction basis for cell-cell communication in tissues.
  5. Subepithelial myofibroblasts enhance stem cell regeneration after intestinal epithelial damage.
  6. CytoVI: deep generative modeling of antibody-based single cell data.
  7. A tumor suppressor shuts down a signal gradient.
  8. PhenoMapR: scalable mapping of sample phenotypes to single-cell, spatial, and bulk transcriptomics data.
  1. Nature. 2026 Oct;658(8134): 281-283
    Bigger than CRISPR? A guide to the latest genome editors.
    Heidi Ledford.
      
    Keywords:  Biological techniques; CRISPR-Cas9 genome editing; Epigenetics; Genomics; Technology
    DOI:  https://doi.org/10.1038/d41586-026-02964-w
  2. bioRxiv. 2026 Sep 26. pii: 2026.09.25.754561. [Epub ahead of print]
    A single-nucleus multi-omic atlas of gene regulation across 21 adult human tissues.
    Kaili Fan, Amrita Sule, Amy Guillaumet-Adkins, Ruochi Zhang, Tianxiong Yu, Zhijie Cao, Xuting Zhang, Neva Durand, MaryKate Tellier, Laura Domenech, Francois Aguet, Jason D Buenrostro, Kristin G Ardlie.
      Diverse human cell types establish specialized functions through lineage- and context-specific regulatory programs. Interpreting non-coding genetic risk requires integrated multi-omic reference maps that directly connect regulatory DNA to cellular expression across human tissues. Here we present a single-nucleus multi-omic atlas comprising 459,856 transcriptomic and chromatin accessibility profiles from 21 adult human tissues and four donors, including paired measurements from 160,688 nuclei. The atlas resolves nine cell lineages, 61 broad cell types and 313 subclusters, and identifies 1,085,062 candidate cis-regulatory elements (cCREs), including 161,270 novel elements absent from ENCODE. Regulatory activity was dominated by cell identity but refined by tissue context. Joint profiling enabled 871,177 cCRE-gene associations and revealed lineage-specific regulatory architectures. Cross-tissue accessibility further identified lineage-restricted and constitutively inaccessible chromatin domains, the latter showing preferential hypomethylation across human cancers. Furthermore, we leverage this dataset to train sequence-to-function models to predict chromatin-accessibility effects for 548,656 fine-mapped variants, identifying 18,133 high-effect variants, including 1,120 broadly active variants. Models trained for eight endothelial subtypes further resolve predicted variant effects across vascular beds. Together, this atlas provides a comprehensive cellular and computational framework for interpreting regulatory sequence, context-dependent gene control, and complex trait genetics across the human body.
    DOI:  https://doi.org/10.64898/2026.09.25.754561
  3. Nature. 2026 Sep 30.
    Population-scale immune multiome atlas reveals regulatory disease mechanisms.
    BioBank Japan Project
      Most disease-associated genetic variants lie in non-coding regions1,2, yet mechanistic insights are limited by the lack of an empirical framework for characterizing the molecular consequences of regulatory variation. Single-cell molecular quantitative trait locus (QTL) mapping3,4 connects variants to gene regulation but lacks the power and simultaneous measurements to trace mechanisms from chromatin to expression5. Here we show that population-scale simultaneous profiling of chromatin accessibility and gene expression across immune cells reveals regulatory architectures connecting variants to disease. From paired single-nucleus assay for transposase-accessible chromatin-sequencing (snATAC-seq) and single-nucleus RNA-sequencing (snRNA-seq) analysis of 10 million peripheral blood mononuclear cells in 1,108 Finnish individuals6, we identify 51,083 cis-expression QTLs for 20,829 genes, 338,100 cis-chromatin accessibility QTLs for 210,584 peaks, 119,094 putative causal variants and 593,765 peak-gene links. Variants completing chromatin-to-expression cascades show twice the disease colocalization of chromatin-only effects, with massively parallel reporter assays7 validating 10,428 fine-mapped molecular QTLs. At evolutionarily constrained genes, we identify multilayered regulatory buffering, in which chromatin accessibility changes occur with normal effect sizes, but transmission to expression is attenuated through weaker, more numerous enhancer-gene links. This reconciles why disease variants preferentially target constrained genes despite apparent expression QTL depletion8-11. Analysis using a massively parallel reporter assay7 confirms that this buffering acts downstream of the regulatory element, with constraint operating at the chromatin-to-expression interface rather than on intrinsic cis-regulatory activity. Our atlas provides testable hypotheses for over half of immune disease associations, illustrated by cascades at autoimmune loci (TICAM1 and RHOH) and Finnish-enriched variants (TNRC18 and IL21R).
    DOI:  https://doi.org/10.1038/s41586-026-11078-2
  4. bioRxiv. 2026 Sep 27. pii: 2026.09.21.753369. [Epub ahead of print]
    A meta-interaction basis for cell-cell communication in tissues.
    Junjie Tang, Shaoheng Liang, Shahul Alam, Wenduo Cheng, Yang Zhang, Jian Ma.
      Tissue function depends on signals exchanged between cells and the responses they elicit. Yet whether diverse cell-cell interactions in situ form recurrent sender-receiver programs remains unclear. We present SpiderNet, an interpretable representation-learning framework that discovers such directed programs as a compact basis of cell-cell meta-interactions (MIs) from spatial transcriptomics. SpiderNet jointly learns which sender regulators, ligand-receptor pairs, and receiver targets define each MI and where each program is active across neighboring cell pairs. The resulting representation traces multicellular relays and links communication to cell states, perturbation responses, and phenotypes. SpiderNet recovers ground-truth MIs and their molecular components in simulations and, in real tissues, shows stronger direction-specific agreement with independently curated regulatory programs in senders and receivers than alternative methods. Across more than 5.8 million spatially profiled cells, SpiderNet resolves an SPP1-THBS relay linking monocytes, fibroblasts, and tumor cells within an immune-suppressive ovarian cancer niche, predicts T-cell responses to held-out melanoma-cell perturbations, and identifies a T-cell-associated brain-aging program and age-predictive signals that transfer across regions and platforms. It reveals a recurrent pan-cancer COLLAGEN-linked fibroblast-tumor program whose projected abundance in independent cohorts is associated with poorer survival and non-response to immunotherapy. SpiderNet thus establishes MIs as a reusable organizational layer between molecular interactions and tissue phenotypes, providing a framework to resolve, compare, trace, and perturb multicellular regulation in situ.
    DOI:  https://doi.org/10.64898/2026.09.21.753369
  5. Development. 2026 09 15. pii: dev205629. [Epub ahead of print]153(18):
    Subepithelial myofibroblasts enhance stem cell regeneration after intestinal epithelial damage.
    Neil McCarthy, Camila Mendez Jimenez, Guodong Tie, Gizelle McCarthy, Shariq Madha-Krause, Ruiyang He, Ramesh A Shivdasani.
      When intestinal stem cells (ISCs) are damaged, other epithelial cells de-differentiate to restore the ISC compartment. Immune, nerve and lymphatic endothelial cells contribute signals that promote this response, but it is unclear whether or how the native mesenchymal niche senses and responds to ISC loss. In homeostasis, trophocytes and smooth muscle beneath intestinal crypts secrete BMP inhibitors (BMPi) and R-spondins to foster ISC self-renewal, whereas sub-epithelial myofibroblasts (SEMFs) concentrated at crypt tops promote differentiation through bone morphogenetic proteins (BMPs). We assessed transcriptional responses in mouse sub-epithelial populations after ablating ISCs with whole-body irradiation and treating Lgr5DTR mice with diphtheria toxin. More than any other cell type, SEMFs modulated expression of genes related to ISC expansion. However, the BMPi gene Smoc1 and non-canonical Wnt signals, both expressed in SEMFs after whole-body irradiation, were dispensable for ISC restoration. Instead, SEMFs appear to support ISC regeneration through factors that are not induced by ISC attrition per se but by local inflammation. These findings reveal unexpectedly limited transcriptional modulation of the native niche after ISC losses and context-dependent signaling functions for SEMFs.
    Keywords:  Intestinal stem cell regeneration; Niche-stem cell interactions; PDGFRA fibroblasts; Subepithelial myofibroblasts; Telocytes
    DOI:  https://doi.org/10.1242/dev.205629
  6. Nat Methods. 2026 Sep 30.
    CytoVI: deep generative modeling of antibody-based single cell data.
    Florian Ingelfinger, Nathan Levy, Can Ergen, Artemy Bakulin, Alexander Becker, Pierre Boyeau, Martin Kim, Diana Ditz, Jan Dirks, Jonas Maaskola, Tobias Wertheimer, Robert Zeiser, Corinne C Widmer, Ido Amit, Nir Yosef.
      Antibody-based single-cell technologies, such as flow cytometry, mass cytometry and CITE-seq, have become widely used in clinical diagnostics and basic research; however, their analysis is complicated by technical noise, batch effects, platform differences and restricted antibody panels. Here we present CytoVI, a probabilistic generative model for statistically rigorous unified analysis of antibody-based single-cell data. CytoVI generates informative cell embeddings, imputes missing measurements, performs differential protein expression testing and automates annotation of cells in a single probabilistic model. We applied CytoVI to build an integrated B cell maturation atlas spanning 350 proteins and identified proteins associated with immunoglobulin class-switching. In a cohort of patients with B cell non-Hodgkin lymphoma profiled by flow cytometry and CITE-seq, CytoVI uncovered disease-associated T cell states. CytoVI is available as open-source software at scvi-tools.org .
    DOI:  https://doi.org/10.1038/s41592-026-03224-5
  7. Science. 2026 Oct;394(6819): 32
    A tumor suppressor shuts down a signal gradient.
    Dan Engelman, Cédric Blanpain.
      p53 shuts down the spatial signaling of a morphogen and prevents clonal cell expansion.
    DOI:  https://doi.org/10.1126/science.ael7341
  8. bioRxiv. 2026 Sep 09. pii: 2026.09.08.749933. [Epub ahead of print]
    PhenoMapR: scalable mapping of sample phenotypes to single-cell, spatial, and bulk transcriptomics data.
    Brooks A Benard, Chinmay K Lalgudi, Armon Azizi, Andrew J Gentles.
      Single-cell and spatial transcriptomic studies often lack sufficient sample size to compute robust statistical associations between a sample-level phenotype and cell types or spatial locations. In contrast, lower resolution methods such as bulk gene expression profiling have been applied at scale in large, annotated datasets, providing reliable signatures for phenotype associations. We introduce PhenoMapR, a semi-supervised method designed to integrate the phenotypic rigor of large-scale bulk expression studies with the cellular and spatial granularity of single-cell and spatial transcriptomics. PhenoMapR achieves this by deriving and mapping bulk gene expression signatures onto cells and spatial locations in a computationally efficient and scalable manner. The framework is broadly applicable across biological contexts, supporting the mapping of binary, continuous, and survival phenotypes derived from bulk expression studies across transcriptomic data modalities. This enables the identification of biologically-relevant cellular populations and spatial niches for experimental validation and therapeutic intervention.
    DOI:  https://doi.org/10.64898/2026.09.08.749933
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