Recovery and analysis of transcriptome subsets from pooled single-cell RNA-seq libraries.
Nucleic Acids Res
; 47(4): e20, 2019 02 28.
Article
en En
| MEDLINE
| ID: mdl-30496484
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.
Texto completo:
1
Banco de datos:
MEDLINE
Asunto principal:
ARN Mensajero
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Análisis de Secuencia de ARN
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Análisis de la Célula Individual
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Transcriptoma
Límite:
Animals
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Humans
Idioma:
En
Revista:
Nucleic Acids Res
Año:
2019
Tipo del documento:
Article
País de afiliación:
Estados Unidos