A microfluidic platform enabling single-cell RNA-seq of multigenerational lineages
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Author
Kimmerling, Robert J.
Szeto, Gregory Lee
Li, Jennifer W.
Genshaft, Alex S.
Kazer, Samuel W.
Payer, Kristofor R.
de Riba Borrajo, Jacob
Blainey, Paul C.
Irvine, Darrell J.
Shalek, Alex K.
Manalis, Scott R.
Note: Order does not necessarily reflect citation order of authors.
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https://doi.org/10.1038/ncomms10220Metadata
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Kimmerling, R. J., G. L. Szeto, J. W. Li, A. S. Genshaft, S. W. Kazer, K. R. Payer, J. de Riba Borrajo, et al. 2016. “A microfluidic platform enabling single-cell RNA-seq of multigenerational lineages.” Nature communications 7 (1): 10220. doi:10.1038/ncomms10220. http://dx.doi.org/10.1038/ncomms10220.Abstract
We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multi-generational lineage tracking under controlled culture conditions. We use this platform to generate whole-transcriptome profiles of primary, activated murine CD8+ T-cell and lymphocytic leukemia cell line lineages. Here we report that both cell types have greater intra- than inter-lineage transcriptional similarity. For CD8+ T-cells, genes with functional annotation relating to lymphocyte differentiation and function—including Granzyme B—are enriched among the genes that demonstrate greater intra-lineage expression level similarity. Analysis of gene expression covariance with matched measurements of time since division reveals cell type-specific transcriptional signatures that correspond with cell cycle progression. We believe that the ability to directly measure the effects of lineage and cell cycle-dependent transcriptional profiles of single cells will be broadly useful to fields where heterogeneous populations of cells display distinct clonal trajectories, including immunology, cancer, and developmental biology.Other Sources
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4729820/pdf/Terms of Use
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