Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

Single-cell RNA-sequencing of Platynereis dumerilii larval brain cells

ABSTRACT: Understanding cell type identity in complex tissues or organisms requires integration of each cell's expression profile with its spatial location within the tissue under study. We developed a high-throughput method that combines in vitro single-cell RNA-sequencing with a gene expression atlas to map single cells back to their location within the tissue of interest. We used the developing brain of a marine annelid, Platynereis dumerilii that is an important model system for studying bilaterian brain evolution, to benchmark our approach. To generate the single-cell mRNA-sequencing data, P. dumerilii larval brains were dissociated, followed by cell capture, cDNA synthesis and amplification on the C1 Single-Cell Auto Prep IFC for 10-17 um cells (Fluidigm). Sequencing libraries were produced using Nexera XT DNA kit (Illumina). In total, we sequenced 213 samples, of which 129 correspond to single, alive cells (as judged by visual inspection of the captured cells) with the remainder consisting of a variety of single dead cells (n=18), wells containing extracellular matrix contaminants (n=8) or multiple cells (n=17), as well as a negative controls where no cells were observed (n=41). For this dataset, we achieved ~90% success rate for the spatial mapping of the single-cell RNA-seq data to P. dumerilii brain atlas. NOTE: 72 additional samples were added on 13th December 2014.

INSTRUMENT(S): C1 Single-Cell Auto Prep System, Fluidigm, Illumina HiSeq 2000

ORGANISM(S): Platynereis dumerilii

SUBMITTER: John Marioni

PROVIDER: E-MTAB-2865 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Publications

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

Achim Kaia K Pettit Jean-Baptiste JB Saraiva Luis R LR Gavriouchkina Daria D Larsson Tomas T Arendt Detlev D Marioni John C JC

Nature biotechnology 20150413 5

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 ...[more]

PMID: 25867922

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Dataset Information

Single-cell RNA-sequencing of Platynereis dumerilii larval brain cells

Publications

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

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