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Series GSE131351 Query DataSets for GSE131351
Status Public on Apr 12, 2020
Title Characterizing the temporal dynamics of gene expression in single cells with sci-fate
Organisms Homo sapiens; Mus musculus
Experiment type Expression profiling by high throughput sequencing
Summary Gene expression is a dynamic process on multiple scales, e.g. the cell cycle, response to stimuli, normal differentiation and development, etc. However, nearly all techniques for profiling gene expression in single cells fail to directly capture these temporal dynamics, which limits the scope of biology that can be effectively investigated. Towards addressing this, we developed sci-fate, a new technique that combines S4U labeling of newly synthesized mRNA with single cell combinatorial indexing (sci-), in order to concurrently profile the whole and newly synthesized transcriptome in each of many single cells. As a proof-of-concept, we applied sci-fate to a model system of cortisol response, and characterized expression dynamics in over 6,000 single cells. From these data, we quantify the dynamics of the cell cycle and of glucocorticoid receptor activation, while also exploring their intersection. We furthermore use these data to develop a framework for estimating cell state transition probabilities, and to identify factors whose dynamic expression potentially regulates these transitions. The experimental and computational methods described here may be broadly applicable to quantitatively characterize cell state dynamics in in vitro systems.
Overall design sci-fate profiling for HEK293T cells, NIH/3T3 cells, A549 cells across different treatment conditions (DEX 0 hour, 2 hour, 4 hour, 6 hour, 8 hour and 10 hour treatment).

Please note that [1] the fastq files are generated from combined samples of different treatment samples [2] the processed cell information and transcriptome barcode are listed in the cell annotation file of processed data [3] the *gene_annotate.txt and *gene_annotate_newly_synthesised.txt files are identical, yet provided in duplicate as they are reference data for two different data sets.
Contributor(s) Cao J, Zhou W, Fields S, Steemers FJ, Trapnell C, Shendure J
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Submission date May 16, 2019
Last update date Apr 14, 2020
Contact name Junyue Cao
Organization name University of Washington
Department Department of Genome Sciences
Lab Shendure lab
Street address Foege Building S-210, 3720 15th Ave NE
City Seattle
State/province WA
ZIP/Postal code 98195-5065
Country USA
Platforms (2)
GPL18573 Illumina NextSeq 500 (Homo sapiens)
GPL19415 Illumina NextSeq 500 (Homo sapiens; Mus musculus)
Samples (2)
GSM3770929 HEK293T, NIH/3T3, sci-fate
GSM3770930 A549 cells, sci-fate
BioProject PRJNA543318
SRA SRP198662

Download family Format
SOFT formatted family file(s) SOFTHelp
MINiML formatted family file(s) MINiMLHelp
Series Matrix File(s) TXTHelp

Supplementary file Size Download File type/resource
GSE131351_RAW.tar 300.4 Mb (http)(custom) TAR (of TXT)
SRA Run SelectorHelp
Raw data are available in SRA
Processed data provided as supplementary file

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