Single Cell Genomics
Explore the genome, transcriptome, and epigenome with new spatial and single-cell technologies
Single Cell Genomics 2025 brought together leading experts across multiomics applications to address important issues encountered in biomedical research. We presented a featured talk on the first true single-cell spatial technology and three poster presentations sharing our newest spatial, long-read, and CUT&Tag technologies that enable researchers to make new discoveries from precious samples.
Featured talks
A new class of spatial technology
In this talk, Dr. Andrew Farmer discussed Trekker technology—a new class of spatial genomics designed to acquire spatial and single-cell data in a single experiment. Current spatial technologies sacrifice sensitivity compared to single-cell workflows, and present challenges with cell segmentation and deconvolution that lead to low confidence in resolution. Trekker technology overcomes these challenges, tagging the cell nucleus and providing visual data to enable high-sensitivity and high-resolution data acquisition without capital equipment requirements.
Poster presentations
Low-input RNA-seq to discover & quantify RNA isoforms: SMART-Seq mRNA Long Read
With this poster, Dr. Yue Yun presented data from a new long-read RNA sequencing (LR-RNA-seq) technology that enables full-length transcriptome analysis from a wide input range. With a 10 ng total RNA input, her team demonstrated the ability to reliably sequence at an average length (N50) of 2 kb and detect full-length transcripts as long as 10 kb. Performance at the single-cell level is substantially better than existing single-cell LR-RNA-seq methods. Furthermore, the data provides a more complete picture of isoform-switching events underlying true biological discovery. With the ability to process up to 96 samples at a time, this technology enables the processing of rare or valuable samples to uncover novel biomarkers beyond gene expression.
Profiling histone modifications in single cells to gain insight into the effects of epigenetic drug treatment on tumor cells
With this poster, Dr. Andrew Farmer presented a novel, high-throughput single-cell CUT&Tag (scCUT&Tag) method for complex epigenetic analysis. Shasta CUT&Tag provides a high-throughput, automated approach to scCUT&Tag, enabling discovery of gene regulatory changes for large samples at single-cell resolution. The Shasta CUT&Tag method applies the Takara Bio Shasta Single Cell System in conjunction with a CUT&Tag assay to profile histone modification patterns in thousands of individual cells and characterize global, cell type-specific acetylation patterns in A549 cells following epigenetic drug treatment.
Characterizing the tumor microenvironment using spatially barcoded archival FFPE tissue: Converting single-nucleus RNA-seq into spatial transcriptomics
In this poster, Dr. Bryan Bell discussed the advantages of spatial information in understanding tumor microenvironments (TME), which is crucial for evaluating tumor progression, immune infiltration, and therapeutic targets. Conventional single-cell sequencing lacks spatial context, but the FFPE-enabled Trekker Single-Cell Spatial Mapping Kit adds to sequencing workflows by using Slide-tags to spatially label nuclei within tissue sections, providing high-resolution spatial transcriptomics without the need for complex segmentation or deconvolution algorithms. Applied to archived FFPE breast cancer and other tumor samples, this tool allows for precise characterization of cellular heterogeneity and interactions, advancing disease analysis and therapeutic development.
Trekker Single-Cell Spatial Mapping Kit
Transform standard single-cell genomics data by incorporating a simple spatial transcriptomics kit upstream of your sequencing workflow.
Shasta Single Cell System introduction
Explore exciting new single-cell NGS technologies to usher in an era of novel biomarker discovery.
Long-read mRNA-seq
Generate high-quality, long-read, barcoded cDNA from 1–1,000 intact cells or 10 pg–100 ng of total RNA.
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