Journal
SCIENCE
Volume 357, Issue 6352, Pages 661-667Publisher
AMER ASSOC ADVANCEMENT SCIENCE
DOI: 10.1126/science.aam8940
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Funding
- NIH [DP1HG007811, R01HG006283, U41HG007355, R01GM072675, DP2 HD088158]
- Paul G. Allen Family Foundation
- W. M. Keck Foundation
- Dale F. Frey Award for Breakthrough Scientists
- Alfred P. Sloan Foundation
- William Gates III Endowed Chair in Biomedical Sciences
- National Heart, Lung, and Blood Institute [T32HL007828]
- Illumina
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To resolve cellular heterogeneity, we developed a combinatorial indexing strategy to profile the transcriptomes of single cells or nuclei, termed sci-RNA-seq (single-cell combinatorial indexing RNA sequencing). We applied sci-RNA-seq to profile nearly 50,000 cells from the nematode Caenorhabditis elegans at the L2 larval stage, which provided >50-fold shotgun cellular coverage of its somatic cell composition. From these data, we defined consensus expression profiles for 27 cell types and recovered rare neuronal cell types corresponding to as few as one or two cells in the L2 worm. We integrated these profiles with whole-animal chromatin immunoprecipitation sequencing data to deconvolve the cell type-specific effects of transcription factors. The data generated by sci-RNA-seq constitute a powerful resource for nematode biology and foreshadow similar atlases for other organisms.
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