Spatially resolved transcriptomics and beyond.
Abstract
Considerable progress in sequencing technologies makes it now possible to study the genomic and transcriptomic landscape of single cells. However, to better understand the complexity of multicellular organisms, we must devise ways to perform high-throughput measurements while preserving spatial information about the tissue context or subcellular localization of analysed nucleic acids. In this Innovation article, we summarize pioneering technologies that enable spatially resolved transcriptomics and discuss how these methods have the potential to extend beyond transcriptomics to encompass spatially resolved genomics, proteomics and possibly other omic disciplines.
Keywords
Tomo-seq
smFISH
LCM-seq
ISS
Spatial Transcriptomics
FISSEQ
Spatial Genomics
MIBI
IMC
TIVA
MeSH terms
Gene Expression Profiling
High-Throughput Screening Assays
Molecular Imaging
Sequence Analysis
Single-Cell Analysis
Spatial Analysis
Authors
Recommend literature
1. RNA imaging. Spatially resolved, highly multiplexed RNA profiling in single cells.
2. Characterizing spatial gene expression heterogeneity in spatially resolved single-cell transcriptomic data with nonuniform cellular densities.
3. Imaging individual mRNA molecules using multiple singly labeled probes.
4. Highly multiplexed subcellular RNA sequencing in situ.
5. Single-cell in situ RNA profiling by sequential hybridization.
Similar data
1. Single-cell RNA-seq reveals dynamic paracrine control of cellular variation
2. High throughput quantitative whole transcriptome analysis of distal mouse lung epithelial cells from various developmental stages (E14.5, E16.5, E18.5 and adult)
3. Validation of noise models for single-cell transcriptomics
4. Comparative gene expression profiling of human PGP1 iPS, lymphocyte, donor fibroblasts
5. Single cell RNA-seq of primary human glioblastomas