HCA Data Explorer

Highly Parallel Genome-wide Expression Profiling of Individual Cells Using Nanoliter Droplets.

Updated August 30, 2022

Cells, the basic units of biological structure and function, vary broadly in type and state. Single-cell genomics can characterize cell identity and function, but limitations of ease and scale have prevented its broad application. Here we describe Drop-seq, a strategy for quickly profiling thousands of individual cells by separating them into nanoliter-sized aqueous droplets, associating a different barcode with each cell's RNAs, and sequencing them all together. Drop-seq analyzes mRNA transcripts from thousands of individual cells simultaneously while remembering transcripts' cell of origin. We analyzed transcriptomes from 44,808 mouse retinal cells and identified 39 transcriptionally distinct cell populations, creating a molecular atlas of gene expression for known retinal cell classes and novel candidate cell subtypes. Drop-seq will accelerate biological discovery by enabling routine transcriptional profiling at single-cell resolution.

Steven A McCarrollDepartment of Genetics, Harvard Medical School, Boston, MA 02115, USA; Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA; Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA. Electronic address: mccarroll@genetics.med.harvard.edu.mccarroll@genetics.med.harvard.edu
Evan Z Macosko1
Anindita Basu2
Rahul Satija3
James Nemesh4
Karthik Shekhar5
Melissa Goldman6
Itay Tirosh5
Allison R Bialas7
Nolan Kamitaki4
Emily M Martersteck8
John J Trombetta5
David A Weitz9
Joshua R Sanes8
Alex K Shalek10
Aviv Regev11
Steven A McCarroll12
1Department of Genetics, Harvard Medical School, Boston, MA 02115, USA; Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA; Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA. Electronic address: emacosko@genetics.med.harvard.edu.
2Klarman Cell Observatory, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA; School of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138, USA.
3Klarman Cell Observatory, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA; New York Genome Center, New York, NY 10013, USA; Department of Biology, New York University, New York, NY 10003, USA.
4Department of Genetics, Harvard Medical School, Boston, MA 02115, USA; Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA; Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA.
5Klarman Cell Observatory, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA.
6Department of Genetics, Harvard Medical School, Boston, MA 02115, USA; Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA.
7The Program in Cellular and Molecular Medicine, Children's Hospital Boston, Boston, MA 02115, USA.
8Department of Molecular and Cellular Biology and Center for Brain Science, Harvard University, Cambridge, MA 02138, USA.
9School of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138, USA; Department of Physics, Harvard University, Cambridge, MA 02138, USA.
10Klarman Cell Observatory, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA; Ragon Institute of MGH, MIT, and Harvard, Cambridge, MA 02139, USA; Institute for Medical Engineering and Science and Department of Chemistry, MIT, Cambridge, MA 02139, USA.
11Klarman Cell Observatory, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA; Department of Biology, MIT, Cambridge, MA 02139, USA; Howard Hughes Medical Institute, Chevy Chase, MD 20815, USA.
12Department of Genetics, Harvard Medical School, Boston, MA 02115, USA; Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA; Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA. Electronic address: mccarroll@genetics.med.harvard.edu.
Ami Day

To reference this project, please use the following link:

https://explore.data.humancellatlas.org/projects/3c9d586e-bd26-4b46-8690-3faaa18ccf38
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Analysis Portals

None

Project Label

HighlyParallelExpressionProfiling

Species

Mus musculus

Sample Type

specimens

Anatomical Entity

eye

Organ Part

retina

Selected Cell Types

Unspecified

Disease Status (Specimen)

normal

Disease Status (Donor)

normal

Development Stage

Theiler stage 28

Library Construction Method

Drop-seq

Nucleic Acid Source

single cell

Paired End

false

Analysis Protocol

analysis_protocol_normalization, analysis_protocol_quantification

File Format

3 file formats

Cell Count Estimate

44.8k

Donor Count

7
fastq.gz12 file(s)txt.gz9 file(s)xlsx1 file(s)