2026-05-12 ロックフェラー大学
Researchers in the Cao lab developed two techniques—one for optics-free spatial mapping of tissue organization and the other for the enrichment of rare cell types—that open new ways to study aging and disease. (Credit: Science Photo Library)
＜関連情報＞
- https://www.rockefeller.edu/news/39664-technology-genomics-genetics-cells-aging-brain/
- https://www.nature.com/articles/s41593-026-02293-1
- https://www.cell.com/cell-genomics/fulltext/S2666-979X(25)00357-X
IRISeqを用いた哺乳類の脳老化マッピングのための光学不要空間ゲノミクス Optics-free spatial genomics for mapping mammalian brain aging by IRISeq
Abdulraouf Abdulraouf,Weirong Jiang,Zehao Zhang,Zihan Xu,Ziyu Lu,Tiffany Merlinsky,Andrew Liao,Ahmet Doymaz,Samuel Isakov,Tanvir Raihan,Wei Zhou & Junyue Cao
Nature Neuroscience Published:12 May 2026
DOI:https://doi.org/10.1038/s41593-026-02293-1
Abstract
Spatial transcriptomics has emerged as a transformative approach for in situ mapping of cellular heterogeneity and interactions, yet existing methods often compromise throughput, cost and tissue coverage. Here we introduce Imaging Reconstruction using Indexed Sequencing (IRISeq): an optics-free, cost-effective platform that leverages spatial interaction mapping by indexed sequencing to profile tissues at adjustable sizes and resolutions (5–50 µm). We applied IRISeq to map gene expression across more than 70 coronal sections from both adult and aged mouse brains, including wild-type and two lymphocyte-deficient models (Rag1 and Prkdc mutants) and generated more than 460,000 spatial transcriptome profiles. Our integrated analysis with 783,264 single-cell transcriptomes revealed region-specific aging signatures that are lymphocyte dependent, notably a downregulation of interferon signaling and inflammation in ventricular regions upon lymphocyte depletion, alongside mutant-specific upregulation of senescence pathways. Furthermore, lymphocyte deficiency was linked to preserved abundance of ependymal cells that line the brain’s ventricles and to distinct microglial state dynamics, highlighting a key role for lymphocytes in driving inflammatory processes during brain aging. Overall, IRISeq provides a high-throughput and cost-effective solution for spatially resolved transcriptomic profiling, opening new avenues for elucidating region-specific cellular mechanisms underlying aging and identifying potential therapeutic targets to preserve brain homeostasis.
転写産物誘導型標的細胞濃縮によるスケーラブルな単一核RNAシーケンス Transcript-guided targeted cell enrichment for scalable single-nucleus RNA sequencing
Andrew Liao ∙ Zehao Zhang ∙ Andras Sziraki ∙ … ∙ Manolis Maragkakis ∙ Wei Zhou ∙ Junyue Cao
Cell Genomics Published:December 11, 2025
DOI:https://doi.org/10.1016/j.xgen.2025.101101
Highlights
- EnrichSci enables antibody-free, targeted snRNA-seq of rare cell types
- Efficient profiling captured age-related shifts in rare oligodendrocyte subtypes
- EnrichSci detected gene- and exon-level expression changes in aged oligodendrocytes
- Exon dynamics are linked to isoform switching and splicing factor dysregulation
Summary
Large-scale single-cell atlases have revealed many aging- and disease-associated cell types, yet these populations are often underrepresented in heterogeneous tissues, limiting detailed molecular analyses. To address this, we developed EnrichSci—a scalable, microfluidics-free platform that combines hybridization chain reaction RNA fluorescence in situ hybridization (FISH) with combinatorial indexing to profile single-nucleus transcriptomes of target cell types with full gene-body coverage. Applied to oligodendrocytes in the aging mouse brain, EnrichSci uncovered aging-associated molecular dynamics across distinct oligodendrocyte subtypes, revealing both shared and subtype-specific gene expression changes. Additionally, we identified aging-associated exon-level signatures missed by conventional gene-level analyses, highlighting post-transcriptional regulation as a critical dimension of cell-state dynamics in aging. By coupling transcript-guided enrichment with a scalable sequencing workflow, EnrichSci provides a versatile approach to decode dynamic regulatory landscapes in diverse cell types from complex tissues.
