High-throughput spatial mapping of single-cell RNA-seq data to tissue of origin

• Verfasst von: Achim, Kaia [VerfasserIn]
• Verfasst von: Larsson, Tomas [VerfasserIn]
• Verfasst von: Arendt, Detlev [VerfasserIn]
• Titel: High-throughput spatial mapping of single-cell RNA-seq data to tissue of origin
• Verf.angabe: Kaia Achim, Jean-Baptiste Pettit, Luis R. Saraiva, Daria Gavriouchkina, Tomas Larsson, Detlev Arendt & John C. Marioni
• Umfang: 7 S.
• Fussnoten: Gesehen am 09.06.2017
• Titel Quelle: Enthalten in: Nature biotechnology
• Jahr Quelle: 2015
• Band/Heft Quelle: 33(2015), 5, S. 503-509
• ISSN Quelle: 1546-1696
• DOI: doi:10.1038/nbt.3209
• Datenträger: Online-Ressource
• Sprache: eng
• K10plus-PPN: 1559623780

Abstract

Understanding cell type identity in a multicellular organism requires the integration of gene expression profiles from individual cells with their spatial location in a particular tissue. Current technologies allow whole-transcriptome sequencing of spatially identified cells but lack the throughput needed to characterize complex tissues. Here we present a high-throughput method to identify the spatial origin of cells assayed by single-cell RNA-sequencing within a tissue of interest. Our approach is based on comparing complete, specificity-weighted mRNA profiles of a cell with positional gene expression profiles derived from a gene expression atlas. We show that this method allocates cells to precise locations in the brain of the marine annelid Platynereis dumerilii with a success rate of 81%. Our method is applicable to any system that has a reference gene expression database of sufficiently high resolution.