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

Kaia Achim, Jean Baptiste Pettit, Luis Miguel Rodrigues Saraiva, Daria Gavriouchkina, Tomas Larsson, Detlev Arendt, John C. Marioni

Research output: Contribution to journalArticle

147 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)503-509
Number of pages7
JournalNature Biotechnology
Volume33
Issue number5
DOIs
Publication statusPublished - 12 May 2015
Externally publishedYes

Fingerprint

RNA
Gene expression
Throughput
Tissue
Transcriptome
Brain
RNA Sequence Analysis
Gene Expression
Atlases
Messenger RNA
Databases
Technology

ASJC Scopus subject areas

  • Biotechnology
  • Bioengineering
  • Medicine(all)
  • Molecular Medicine
  • Biomedical Engineering
  • Applied Microbiology and Biotechnology

Cite this

Achim, K., Pettit, J. B., Rodrigues Saraiva, L. M., Gavriouchkina, D., Larsson, T., Arendt, D., & Marioni, J. C. (2015). High-throughput spatial mapping of single-cell RNA-seq data to tissue of origin. Nature Biotechnology, 33(5), 503-509. https://doi.org/10.1038/nbt.3209

High-throughput spatial mapping of single-cell RNA-seq data to tissue of origin. / Achim, Kaia; Pettit, Jean Baptiste; Rodrigues Saraiva, Luis Miguel; Gavriouchkina, Daria; Larsson, Tomas; Arendt, Detlev; Marioni, John C.

In: Nature Biotechnology, Vol. 33, No. 5, 12.05.2015, p. 503-509.

Research output: Contribution to journalArticle

Achim, K, Pettit, JB, Rodrigues Saraiva, LM, Gavriouchkina, D, Larsson, T, Arendt, D & Marioni, JC 2015, 'High-throughput spatial mapping of single-cell RNA-seq data to tissue of origin', Nature Biotechnology, vol. 33, no. 5, pp. 503-509. https://doi.org/10.1038/nbt.3209
Achim, Kaia ; Pettit, Jean Baptiste ; Rodrigues Saraiva, Luis Miguel ; Gavriouchkina, Daria ; Larsson, Tomas ; Arendt, Detlev ; Marioni, John C. / High-throughput spatial mapping of single-cell RNA-seq data to tissue of origin. In: Nature Biotechnology. 2015 ; Vol. 33, No. 5. pp. 503-509.
@article{258b1bce2316407bad1c7c0c08fcf9b3,
title = "High-throughput spatial mapping of single-cell RNA-seq data to tissue of origin",
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.",
author = "Kaia Achim and Pettit, {Jean Baptiste} and {Rodrigues Saraiva}, {Luis Miguel} and Daria Gavriouchkina and Tomas Larsson and Detlev Arendt and Marioni, {John C.}",
year = "2015",
month = "5",
day = "12",
doi = "10.1038/nbt.3209",
language = "English",
volume = "33",
pages = "503--509",
journal = "Nature Biotechnology",
issn = "1087-0156",
publisher = "Nature Publishing Group",
number = "5",

}

TY - JOUR

T1 - High-throughput spatial mapping of single-cell RNA-seq data to tissue of origin

AU - Achim, Kaia

AU - Pettit, Jean Baptiste

AU - Rodrigues Saraiva, Luis Miguel

AU - Gavriouchkina, Daria

AU - Larsson, Tomas

AU - Arendt, Detlev

AU - Marioni, John C.

PY - 2015/5/12

Y1 - 2015/5/12

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=84929166604&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84929166604&partnerID=8YFLogxK

U2 - 10.1038/nbt.3209

DO - 10.1038/nbt.3209

M3 - Article

C2 - 25867922

AN - SCOPUS:84929166604

VL - 33

SP - 503

EP - 509

JO - Nature Biotechnology

JF - Nature Biotechnology

SN - 1087-0156

IS - 5

ER -