Spatial Transcriptomics

What is Spatial Transcriptomics?

Spatial transcriptomics provides a comprehensive roadmap of transcriptional activity within intact tissue sections. Depending on the approach, this method can detect transcriptional activity using hybridization techniques or RNA sequencing (RNA-Seq) technology powered by next-generation sequencing (NGS) with high sensitivity. Regardless of the method, spatial transcriptomics allows you to accurately resolve mRNA expression at the cellular level in structurally preserved tissues.

Spatial Transcriptomics of Complex Tissues

Learn about high-resolution, high-throughput spatial transcriptomics of kidney tissues using the NanoString GeoMx Digital Spatial Profiler and Illumina sequencing systems.

Benefits of Spatial Transcriptomics

A key benefit of spatial transcriptomics is that it provides a topographical arrangement of gene expression patterns mapped onto tissue sections to link structure and activity. This capability allows researchers to articulate biological interactions at the cellular level to gain novel insights into complex tissues, such as tumor microenvironments.

With this method, you’ll be able to chart cellular activity in normal vs. diseased tissues, discover previously unknown interactions, create quantitative atlases of cell activity, and beyond. Illumina offers sequencing platforms and software analysis tools that integrate with partnered solutions to provide a seamless, end-to-end spatial transcriptomics solution with reliability, scalability, and sensitivity.

How Does Spatial Transcriptomics Work?

To spatially resolve mRNA expression in tissue sections, transcripts from sectioned frozen or formalin-fixed, paraffin-embedded tissues are either captured on slides using spatially localized probes or are detected directly in specific regions of interest using photoactive in-situ hybridization probes. cDNA libraries are sequenced and analyzed to quantify expression levels. Depending on the method of choice, expression of 1,200–21,000 protein-coding genes can be quantitatively analyzed in a single readout and accurately mapped to provide transcriptional information on tissue sections.

Transcriptional Profiling of Tissue Sections

Leverage Visium Spatial Gene Expression from 10x Genomics for transcriptional profiling of entire tissue sections.

The Power of Multiomics

Download our in-depth eBook on how multiomic methods have revolutionized research through cutting-edge sequencing and array technology.

A Multiomic Approach to Spatial Biology

Spatial biology can incorporate other analytical methods such as epigenomic, genomic, and proteomic information at the cellular level while similarly providing contextual information within preserved tissues. These methods collectively fall under the term spatial multiomics and offer a multidimensional approach to comprehensively understand biological systems. For many spatial multiomic applications, Illumina offers NGS-powered technologies that can link structural, functional, and spatial insights to enable your next discoveries.

Research Highlights Using Spatial Transcriptomics

Immunological Atlas

Read how investigators use spatial transcriptomics to create an atlas of developing immune systems in humans.

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Understanding the Tumor Microenvironment

Learn how researchers use spatial transcriptomics in tumors to identify differences in microenvironments, gene expression, and therapeutic responses.

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Spatially Mapping Diverse Tissues

See how scientists discovered the spatial layout of diverse cells in various tissues using spatial transcriptomics.

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Highlighted Solutions

Sequencing Instruments

Compare Illumina sequencing instruments by application, throughput, and other key specifications, and determine which platform is right for your needs.

FFPE RNA-Seq From Degraded Tissues

Get high-quality results from formalin-fixed, paraffin-embedded (FFPE) tissues using Illumina RNA-Seq solutions.

Spatial Proteomic and Proteogenomic Insights

Combine the spatial analyses of RNA and protein using the Nanostring GeoMx DSP and Illumina sequencing to understand the heterogeneous pathology of human astrocytoma and glioblastoma samples.

Single-cell and spatial sequencing on NextSeq 1000 and 2000 Systems

Learn how XLEAP-SBS chemistry combined with 10x Genomics single-cell and spatial solutions enable high-resolution genomics on the NextSeq 1000 and NextSeq 2000 Systems.

Featured Webinars

Resolving Dynamic Microenvironments in Cancer Research

Learn how NGS-based solutions and NanoString’s GeoMx assays deliver deep insights into tumors and microenvironments.

Building a Tumor Immune Atlas

Watch how researchers link tissue morphology and biological activity to create a reference atlas for tumor pathology.

Spatial Resolution of the Developing Human Cortex

See how scientists are using 10x technologies, single-cell RNA-Seq, and Visium with Illumina sequencing to reveal the spatial resolution of the developing human fetal cortex.

Advances in Spatial Biology and Cancer Research

Scientific experts highlight the historic journey of cancer research using solutions from NanoString and Illumina from a spatial biology perspective.

Spatiotemporal Changes in Cardiac Tissue

Learn about transcriptional changes in different regions of cardiac tissue during early-onset acute myocardial infarction.

Single-Cell Transcriptomic Landscape in Alzheimer’s

See how Dr. Vivek Swarup’s application of spatial transcriptomics has led to advancements in understanding late-stage Alzheimer’s diease.

Explore NextSeq 1000 and NextSeq 2000 Systems and Reagents

With over 75 breakthrough innovations, these sequencing systems offer dry instrumentation, easier run setup, and fast secondary analysis with DRAGEN software onboard. Experience our simplest workflows yet, and perform a broad range of emerging and mid-throughput sequencing applications.

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Customer Stories and Resources

Visualizing Cell Interactions

Read how researchers used spatial insights to add another dimension to their single-cell transcriptomic data.

Understanding the Tumor Microenvironment

Read how the tumor microenvironment can provide essential clues about the behavior of diseased cells.

Precision Immunotherapies

Read how a three-pronged analytical approach is helping researchers identify promising immune targets for cancer immunotherapies.

Sequencing-Based Spatial Genomic Analysis

Learn how spatial multiomic profiling can provide unprecedented molecular information in cancer biopsy samples.

Future of Multiomic Research

Read how spatial information is providing next-generation improvements in multiomic data for cancer research.

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Multiomics

Want to learn how you can integrate multiple levels of data into your research? Find out how multiomics can provide a more comprehensive understanding of biological systems.

Cell & Molecular Biology

We offer technologies to go beyond traditional cell and molecular biology research techniques so you can harness the power of genomic, transcriptomic, and epigenomic data efficiently and accurately.

Single-Cell RNA Sequencing

Single-cell RNA sequencing can provide solutions to unravel complex biological systems at high resolution with minimal sample input.

FFPE Sequencing and Arrays

Learn how to analyze FFPE samples using a comprehensive range of Illumina FFPE sequencing and microarray solutions.

NGS in Cancer Research

Your methods guide for NGS-based applications in cancer research, including spatial transcriptomics, is available now.

Single-Cell Workflow Guide

Download our eBook guide and learn how to enable higher discovery power through single-cell sequencing.

Gene Expression and Regulation Research

See how Illumina RNA-Seq solutions can empower transcriptomic and epigenetic methods to advance discoveries in biology.

Gene Expression and Transcriptomic Analysis

See how a comprehensive view of gene expression and transcriptional activity (coding and non-coding) can help you get a deeper understanding of biology using NGS-based RNA-Seq.

Spatial Transcriptomic Analysis with Partek Flow

Partek Flow software provides an easy‑to‑use interface, advanced statistical algorithms, and rich interactive visualizations for start‑to‑finish spatial transcriptomics analysis. Characterize gene and protein expression in their native spatial context or analyze and integrate other data types.