Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

Quantitative single-cell RNA-seq

ABSTRACT: Purpose: We applied cDNA molecule counting using unique molecular identifiers combined with high-throughput sequencing to study the transcriptome of individual mouse embryonic stem cells, with spike-in controls to monitor technical performance. We further examined transcriptional noise in the embryonic stem cells. One 96-well plate of single-stranded cDNA libraries generated from 96 single R1 mouse embryonic stem cells sequenced on two lanes, and one 96-well plate of the same libraries further amplified by 9 PCR cycles sequenced on one lane.

ORGANISM(S): Mus musculus

SUBMITTER: Sten Linnarsson

PROVIDER: E-GEOD-46980 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Quantitative single-cell RNA-seq with unique molecular identifiers.

Islam Saiful S Zeisel Amit A Joost Simon S La Manno Gioele G Zajac Pawel P Kasper Maria M Lönnerberg Peter P Linnarsson Sten S

Nature methods 20131222 2

Single-cell RNA sequencing (RNA-seq) is a powerful tool to reveal cellular heterogeneity, discover new cell types and characterize tumor microevolution. However, losses in cDNA synthesis and bias in cDNA amplification lead to severe quantitative errors. We show that molecular labels--random sequences that label individual molecules--can nearly eliminate amplification noise, and that microfluidic sample preparation and optimized reagents produce a fivefold improvement in mRNA capture efficiency. ...[more]

PMID: 24363023

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Project description:To accelerate previous RNA structure probing approaches, which focus on analyzing one RNA sequence at a time, we have developed FragSeq, a high-throughput RNA structure probing method that uses high-throughput RNA sequencing to identify single-stranded RNA (ssRNA) regions from fragments generated by nuclease P1, which is specific for single-stranded nucleic acids. In the accompanying study, we show that we can accurately and simultaneously map ssRNA regions in multiple non-coding RNAs with known structure in experiments probing the entire mouse nuclear transcriptome. We carried out probing in two cell types to assess reproducibility. We also identified and experimentally validated structured regions in ncRNAs never previously probed. We examined mouse nuclear RNA from two cell types: undifferentiated embryonic stem cells (UNDIFF) and cells differentiated into neural precursors (D5NP). For each cell type, nuclear RNA was purified and deproteinized, denatured, and refolded in vitro, from which we prepared three barcoded samples: "nuclease" (RNA partially digested with P1 ssRNA-specific nuclease, yielding 5'-PO4/3'-OH end chemistry at each cleavage site), "control" (control for "nuclease" sample to idenfity endogenous 5'-PO4/3'-OH), and "PNK" (same as "control" but followed by a polynucleotide kinase treatment to convert 5'-OH/3'-cyclic-phosphate ends to clonable 5'-PO4/3'-OH ends). Resulting RNA fragments were cloned using the SOLiD Small RNA Expression Kit (SREK) protocol, which ligates linkers only to 5'-PO4/3'-OH containing RNA, enriching for clones of products resulting from P1 cleavage in "nuclease" sample and selecting against random degradation. Two cell types, three treatments each, thus resulted in six barcoded samples total (barcodes 01, 02, 04, 05, 07, 08). Four other barcoded samples were prepared for separate experiments not used in our study (barcodes 03, 06, 09, 10), so their preparation is not described here. The total run of ten barcodes was done on the ABI SOLiD3 platform and a custom algorithm (FragSeq v0.0.1) was used to compute "cutting scores" (as described in our paper) that show ssRNA regions in hundreds of ncRNAs.

Dataset Information

Quantitative single-cell RNA-seq

Publications

Quantitative single-cell RNA-seq with unique molecular identifiers.

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