Recovery and analysis of transcriptome subsets from pooled single-cell RNA-seq libraries

Nucleic Acids Res. 2019 Feb 28;47(4):e20. doi: 10.1093/nar/gky1204.


Single-cell RNA sequencing (scRNA-seq) methods generate sparse gene expression profiles for thousands of single cells in a single experiment. The information in these profiles is sufficient to classify cell types by distinct expression patterns but the high complexity of scRNA-seq libraries often prevents full characterization of transcriptomes from individual cells. To extract more focused gene expression information from scRNA-seq libraries, we developed a strategy to physically recover the DNA molecules comprising transcriptome subsets, enabling deeper interrogation of the isolated molecules by another round of DNA sequencing. We applied the method in cell-centric and gene-centric modes to isolate cDNA fragments from scRNA-seq libraries. First, we resampled the transcriptomes of rare, single megakaryocytes from a complex mixture of lymphocytes and analyzed them in a second round of DNA sequencing, yielding up to 20-fold greater sequencing depth per cell and increasing the number of genes detected per cell from a median of 1313 to 2002. We similarly isolated mRNAs from targeted T cells to improve the reconstruction of their VDJ-rearranged immune receptor mRNAs. Second, we isolated CD3D mRNA fragments expressed across cells in a scRNA-seq library prepared from a clonal T cell line, increasing the number of cells with detected CD3D expression from 59.7% to 100%. Transcriptome resampling is a general approach to recover targeted gene expression information from single-cell RNA sequencing libraries that enhances the utility of these costly experiments, and may be applicable to the targeted recovery of molecules from other single-cell assays.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animals
  • Cluster Analysis
  • DNA, Complementary / genetics
  • Gene Expression Profiling / methods
  • Gene Library
  • High-Throughput Nucleotide Sequencing
  • Humans
  • Leukocytes, Mononuclear / metabolism
  • Mice
  • RNA, Messenger / genetics*
  • Sequence Analysis, RNA / methods*
  • Single-Cell Analysis*
  • Software
  • Transcriptome / genetics*


  • DNA, Complementary
  • RNA, Messenger