4.8 Article

A microfluidic platform enabling single-cell RNA-seq of multigenerational lineages

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NATURE COMMUNICATIONS
卷 7, 期 -, 页码 -

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NATURE PUBLISHING GROUP
DOI: 10.1038/ncomms10220

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资金

  1. US National Institutes of Health [R21AI110787]
  2. Physical Sciences Oncology Center from the National Cancer Institute [U54CA143874]
  3. Koch Institute Support (core) grant from the National Cancer Institute [P30-CA14051]
  4. National Science Foundation GRFP fellowships
  5. National Institutes of Health under Ruth L. Kirchstein National Research Service Award [F32CA1800586]
  6. Searle Scholars Program
  7. Beckman Young Investigator Program
  8. NIH New Innovator Award [DP2 OD020839]
  9. NATIONAL CANCER INSTITUTE [F32CA180586, P30CA014051, U54CA143874] Funding Source: NIH RePORTER
  10. NATIONAL HUMAN GENOME RESEARCH INSTITUTE [RM1HG006193] Funding Source: NIH RePORTER
  11. NATIONAL INSTITUTE OF ALLERGY AND INFECTIOUS DISEASES [R21AI110787] Funding Source: NIH RePORTER
  12. NATIONAL INSTITUTE OF GENERAL MEDICAL SCIENCES [DP2GM119419] Funding Source: NIH RePORTER

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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.

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