Single‐Cell Transcriptomics Comes of Age
暂无分享,去创建一个
the identity of the cell from which the RNA in the droplet was derived. The result is the simultaneous acquisition of transcriptomic information from each individual cell in the tissue. Of particular interest to transplant, these new methods may enable the transcriptional profiling of entire organs at much greater depth than what has been previously possible. These results have important implications for transplantation on many levels. First, they provide important data on the molecular mechanisms underlying heterogeneity within the immune response. The idea that immune responses (for dendritic cells, at least) may be regulated by a few “driver cells” is an important concept that could have therapeutic implications for immunosuppressive strategies following transplantation. Secondly, the use of high-throughput single-cell RNA-seq could be applied to molecular profiling of biopsies during episodes of suspected rejection or infection, or for the identification of tolerance. Currently, tissue-level transcriptomic analysis of biopsies is limited by the fact that it precludes the determination of whether elevated expression of a particular gene is the result of increased gene transcription within a subset of cells, or simply due to the increased presence of that subset within the biopsy. Single-cell RNA-seq will allow for the identification of the type, frequency, and gene expression profile of both graft-derived and infiltrating immune cells in order to better assess the molecular atlas of rejecting versus stable allografts following transplantation. One could even speculate that in the future, amalgamation of large single-cell transcriptomes with known spatial expression patterns of marker genes could facilitate the reconstruction of the complex 3D architecture of an entire kidney, heart, liver, or lung, essentially providing the instruction manual for de novo assembly of new organs for use in transplantation.
[1] Evan Z. Macosko,et al. Highly Parallel Genome-wide Expression Profiling of Individual Cells Using Nanoliter Droplets , 2015, Cell.
[2] Allon M. Klein,et al. Droplet Barcoding for Single-Cell Transcriptomics Applied to Embryonic Stem Cells , 2015, Cell.
[3] Rona S. Gertner,et al. Single cell RNA Seq reveals dynamic paracrine control of cellular variation , 2014, Nature.