GEO DataSets

(Submitter supplied) Single cell RNA sequencing so far only depicts cellular transcriptomes at a single time point with low temporal resolution for kinetic changes. Here, we present a single-cell approach based on metabolic RNA labelling for combined sequencing of total and newly transcribed RNA as well as computational analysis of the RNA present prior to labelling. We apply it to cytomegalovirus infection of fibroblasts and reveal its potential for delineating alterations in transcriptional activity and decay in single cells under perturbed experimental conditions.

Organism:

Homo sapiens; Mus musculus; Murid betaherpesvirus 1

Type:

Expression profiling by high throughput sequencing

Platforms:

GPL25867 GPL25526 GPL19057

124 Samples

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