Scaling Spatial Transcriptomics with ATLAS: High-Throughput Tissue Mapping

Scaling Spatial Transcriptomics with ATLAS | Roy Wollman, PhD | High-Throughput Tissue Mapping How can spatial transcriptomics be scaled from detailed single datasets to high-throughput, organ-scale studies? In this video, Roy Wollman, Ph.D. (UCLA) presents an advanced framework for scalable spatial transcriptomics, designed to enable large comparative studies of tissue organization across multiple samples and conditions. Building on established single-cell reference atlases such as the mouse brain, this approach transforms spatial mapping into a high-throughput, computationally driven workflow. The core technology, ATLAS (Atlas-scale Transcriptome Localization using Aggregate Signatures), introduces a novel strategy: Encode gene expression into low-dimensional transcriptional signatures Measure aggregate signals instead of individual RNA transcripts Integrate spatial data with single-cell RNA sequencing (scRNA-seq) references Use computational decoding and imputation to reconstruct full transcriptomes This approach enables efficient imaging, reduced data complexity, and scalable spatial analysis without sacrificing biological accuracy. Core Concepts Covered: Low-dimensional encoding of gene expression for efficient spatial imaging Integration of spatial transcriptomics and single-cell sequencing data Reconstruction of full gene expression profiles from partial measurements Benchmarking against existing spatial transcriptomics technologies for validation Applications: Brain mapping and neuroscience research Systems biology and tissue organization studies Disease research using large-scale spatial datasets Video Chapters: 00:00 - Introduction from Ramalakshmi Ramasamy 01:22 - Introduction to Scalable Spatial Transcriptomics 04:29 - Atlas-Based Encoding of Gene Expression 09:41 - Integrating Spatial Data with Single-Cell References 16:36 - Applications in Brain Mapping and Disease Research 20:32 - Questions and Answers with Ramalkshmi Ramasamy, Roy Wollman, and Fei Chen 🌐 Learn more: https://wollmanlab.ucla.edu/index.html #SpatialTranscriptomics #ComputationalBiology #systemsbiology 👍Like, subscribe, and hit the notification bell to stay updated on our latest content! Disclaimer: Genome TDCC does not endorse or recommend any commercial products or services. Inclusion of a speaker's views or opinions on our channel does not constitute endorsement by Genome TDCC, The Jackson Laboratory (JAX), National Human Genome Research Institute (NHGRI), or the U.S. Government. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise, does not constitute or imply its endorsement, recommendation, or favoring to the exclusion of other available products, processes, or services.