Welcome to our webinar series
Advancing discovery with spatial multiomics—accessible tools for high-resolution insights
Many researchers rely on spatial platforms that are not capturing cells at the right scale or resolution, requiring complex algorithms and semantic interpretation—which means mislabeled cells and misleading conclusions. Takara Bio’s spatial kits cut through this complexity to deliver clarity.
- Trekker technology: seamlessly integrate spatial insights upstream of your standard single-cell workflow—unlocking true, biologically relevant resolution through a simple, straightforward process. No specialized instruments, cell segmentation, or deconvolution required.
- Seeker technology: achieve single-cell resolution and enjoy true unbiased discovery unconstrained by predetermined targets to obtain a continuous view of your region of interest at 10 μm resolution by using standard molecular biology techniques. No specialized instrumentation or microscopy expertise required.
Does your spatial technology:
- Capture cells at true single-cell resolution, eliminating the need for computational guessing,
- Maintain native spatial context, essential for understanding complex tissues, tumor microenvironments, and immune infiltration, and
- Obtain unbiased, robust gene expression profiles and multiomics profiling, without the limitation of predesigned probes?
Seeker and Trekker kits deliver flexible, high-definition single-cell mapping solutions that are species agnostic.
Get the full story from your sample with the Trekker and Seeker workflows! Watch our webinars to hear from researchers across multiple disciplines and how these technologies are accelerating spatial biology discoveries.
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Tracing the spatiotemporal evolution of cancer
- Hypoxic microenvironment associated with immunosuppressive and fibrotic cell states
- Origin of metastases from spatially confined subclones and their remodeling of the distant metastatic niche
- Integration of sequential changes in cancer cell state and microenvironmental structure that promote tumor progression
Matthew Jones, PhD
Postdoctoral Fellow, Stanford University
Dr. Matt Jones conducts research to develop computational and technological approaches to better understand dynamic biological systems, as applied to cancer. Currently, his projects include developing computational approaches for spatially-resolved lineage tracing technologies, and studying the mechanisms by which oncogene amplifications contribute to tumor progression and drug resistance.
Whole transcriptome spatial analysis of dysfunctional brain circuits at single-cell resolution
Conor Liston, MD, PhD
Professor of Neuroscience and Psychiatry, Weill Cornell Medicine
- Cell type-specific effects of transcranial magnetic stimulation (TMS) on neurons in the prelimbic cortex
- Whole-brain mapping of responses to accelerated intermittent theta burst stimulation
- Mechanistic insights into TMS-induced plasticity uncovered through multimodal spatial analysis
Transitioning to the bioinformatics cloud portal
Takara Bio, USA
LatchBio
- Introduction to the Takara Bioinformatics Cloud Portal powered by LatchBio
- Step-by-step guidance on workspace setup, data processing, and data exploration within the LatchBio environment
- Efficient, infrastructure-free analysis of Trekker and Seeker spatial transcriptomics data for bench scientists and bioinformaticians
Transforming pipeline outputs into biological insights: Best practices for Seeker data analysis
Wanxin Wang, PhD
Staff Scientist, Bioinformatics Spatial Genomics R&D, Takara Bio USA
- Transforming Seeker spatial transcriptomics data into meaningful biological insights
- Processing and annotating spatial data, including background removal, normalization, deconvolution, and interactive ROI selection
- Analyzing data, including H&E alignment, cell-cell communication, and time-series exploration
Spatial genomics approaches for systematic studies of brain function and dysfunction
Evan Macosko, MD, PhD
Associate Professor of Psychiatry, Mass General, Broad Institute of MIT and Harvard
- Spatial transcriptomics tools developed for defining brain cell types and their spatial organization
- Genomic technologies for identifying novel cell types and investigating their roles in disease
- High-resolution cytoarchitectural phenotyping of the human brain
Mapping immune cell interactions in dense secondary lymphoid organ
Ashraful Haque, PhD
Associate Professor, Dept of Microbiology & Immunology, The University of Melbourne, Doherty Institute for Infection & Immunity
- Spatial mapping of mouse spleen architecture and cell-cell interactions during malaria infection
- Discovery of a novel receptor regulating T-cell immunity through resolution of spatially continuous T-cell states
- Visualization of tissue structure and function through spatial data transformed into intuitive visual tools
Spatially resolved transcriptomics at high resolution
Iwijn De Vlaminck, PhD
Associate Professor of Biomedical Engineering, Cornell University
- Application of Seeker technology to study pathogenesis, organ development, and molecular processes at cellular resolution
- Best practices for spatial transcriptomics data generation and analysis
- Development of methods for high-resolution spatial mapping of the total transcriptome
Spatiotemporal architecture of mouse embryogenesis at single-cell resolution
Abhishek Sampath Kumar, PhD
Postdoctoral Scientist, Harvard University
- High-resolution spatiotemporal mapping of the mouse embryo during gastrulation and early organogenesis
- Precise molecular definition of cell states and early regulatory dynamics during embryonic development
- Identification of gene expression patterns driving the formation of complex embryonic structures
Slide-seq: a platform for understanding cellular circuits in tissue
Fei Chen, PhD
Assistant Professor, Stem Cell & Regenerative Biology, Harvard University
- Transcriptome-wide spatial measurements at near single-cell resolution
- Experimental and computational advances supporting spatial analysis of molecular signals in tissue formation and function
- Opportunities and challenges in applying spatial transcriptomics to research in tissue genomics
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