A time-resolved meta-analysis of consensus gene expression profiles during human T-cell activation

The coordinated transcriptional regulation of activated T-cells is based on a complex dynamic behavior of signaling networks. Given an external stimulus, T-cell gene expression is characterized by impulse and sustained patterns over the course. Here, we analyzed the temporal pattern of activation across different T-cell populations to develop consensus gene signatures for T-cell activation. We applied a meta-analysis of anti-CD3/CD28 induced CD4+ T-cell activation kinetics of publicly available transcriptome-wide time series using a random effects model. We used non-negative matrix factorization, an unsupervised deconvolution method, to infer changes in biological patterns over time. For verification and to further map a wider variety of the T-cell landscape, we performed a time series of transcriptome-wide RNA sequencing on activated Pan T-cells. We performed a time-course experiment with anti-CD3/CD28 beads activated Pan T-cells from 4 healthy individuals. RNA-seq was performed before activation (0 hours) and 6, 12, 24, 48, 72 hours after activation. In addition, as a control, we sequenced Pan T-cells for the same time series without activation condition. ***Submitter statement concerning raw data availability: 'we do not have informed consent from the donors to publish the raw sequencing data.'***