Spatially resolved, highly multiplexed RNA profiling in single cells

• Published in: Science (American Association for the Advancement of Science) Vol. 348; no. 6233; p. 412
• Main Authors: Chen, Kok Hao, Boettiger, Alistair N., Moffitt, Jeffrey R., Wang, Siyuan, Zhuang, Xiaowei
• Format: Journal Article
• Language: English
• Published: Washington American Association for the Advancement of Science 24.04.2015; The American Association for the Advancement of Science
• Subjects: Cells; Cellular; Correlation; Correlation analysis; Distribution patterns; Encoding; Error Correction; Fluorescence; Gene expression; Gene loci; Genes; Government regulations; Hybridization; Imaging; Molecules; Multiplexing; Numbers; Probes; RESEARCH ARTICLE SUMMARY; Ribonucleic acid; Ribonucleic acids; RNA; Spatial distribution
• ISSN: 0036-8075; 1095-9203
• DOI: 10.1126/science.aaa6090

The basis of cellular function is where and when proteins are expressed and in what quantities. Single-molecule fluorescence in situ hybridization (smFISH) experiments quantify the copy number and location of mRNA molecules; however, the numbers of RNA species that can be simultaneously measured by smFISH has been limited. Using combinatorial labeling with error-robust encoding schemes, Chen et al. simultaneously imaged 100 to 1000 RNA species in a single cell. Such large-scale detection allows regulatory interactions to be analyzed at the transcriptome scale. Science , this issue p. 10.1126/science.aaa6090 A single-molecule imaging method allows simultaneous measurement of 1000 RNA species in single cells. Knowledge of the expression profile and spatial landscape of the transcriptome in individual cells is essential for understanding the rich repertoire of cellular behaviors. Here, we report multiplexed error-robust fluorescence in situ hybridization (MERFISH), a single-molecule imaging approach that allows the copy numbers and spatial localizations of thousands of RNA species to be determined in single cells. Using error-robust encoding schemes to combat single-molecule labeling and detection errors, we demonstrated the imaging of 100 to 1000 distinct RNA species in hundreds of individual cells. Correlation analysis of the ~10 4 to 10 6 pairs of genes allowed us to constrain gene regulatory networks, predict novel functions for many unannotated genes, and identify distinct spatial distribution patterns of RNAs that correlate with properties of the encoded proteins.