The spatial organization of post-transcriptional regulation is a fundamental yet difficult to access layer of tissue biology. MicroRNAs (miRNAs) are small RNAs with a key role in post-transcriptional regulation, but their short length has excluded them from spatial profiling technologies, leaving them largely unexplored in spatial transcriptomics. Here, we introduce miR-Space, a method that converts individual miRNAs into extended, uniquely barcoded molecules directly in tissue, enabling their spatial detection by in situ sequencing. Across 30 mouse and human brain sections, miR-Space enabled highly multiplexed miRNA profiling at single-molecule and single-cell resolution, joint analysis with mRNA, and implementation on the automated Xenium platform. miR-Space resolved major anatomical regions and cell populations from spatial miRNA expression, identified reproducible cell-associated miRNA signatures, and uncovered previously unknown spatial and cellular distributions of multiple miRNAs. Together, these capabilities establish miR-Space as a framework for integrating miRNAs into spatial transcriptomics, enabling spatial miRNomics at anatomical and single-cell resolution.
How spatially structured cellular ecosystems, rather than individual cell types, determine therapeutic response and resistance in lung cancer is organized around a single question - and observations that are reproducible across independent cohorts and platforms are explicitly separate from those that remain confined to...
C. Braicu, R. Pîrlog, A. Nutu et al.· Biochimica et biophysica act...· 0 citations
Spatial transcriptomics is increasingly used to infer cellular phenotypes, molecular interactions, and functional tissue organization from RNA, although most of these biological processes are ultimately mediated by proteins. Here, we directly tested the interchangeability of spatial RNA and protein measurements using p...
Sergi Cervilla, D. Grases, Noelia Montesdeoca et al.· bioRxiv· 0 citations
This review provides a physiology-centered blueprint for applying single-cell RNA sequencing, single-nucleus RNA sequencing, and spatial transcriptomics to non-model species and critically evaluates dissociation and preservation bias, genome annotation, seasonal and ecological variation, biological replication, pseudor...
Adnan Amin, W. Zaman· Functional & Integrative Gen...· 0 citations
SMODER is presented, an RNA-anchored framework for spatial multi-omics deconvolution that treats transcriptomes as the primary determinant of cell identity while incorporating complementary molecular modalities in a constrained manner and consistently outperforms existing methods in both accuracy and spatial coherence.
Background Hematopoietic stem cells (HSCs) have the unique ability to produce all mature cell types in the blood and understanding the mechanisms governing their differentiation and renewal is a driving question in stem cell biology. While single-cell RNA sequencing has transformed our view of human hematopoiesis, mRNA...
J. Gollin, N. García-Gisbert, Tomoya Isobe et al.· bioRxiv· 0 citations