Dataset Information

Digital transcriptome profiling from attomole-level RNA samples.

ABSTRACT: Accurate profiling of minute quantities of RNA in a global manner can enable key advances in many scientific and clinical disciplines. Here, we present low-quantity RNA sequencing (LQ-RNAseq), a high-throughput sequencing-based technique allowing whole transcriptome surveys from subnanogram RNA quantities in an amplification/ligation-free manner. LQ-RNAseq involves first-strand cDNA synthesis from RNA templates, followed by 3' polyA tailing of the single-stranded cDNA products and direct single molecule sequencing. We applied LQ-RNAseq to profile S. cerevisiae polyA+ transcripts, demonstrate the reproducibility of the approach across different sample preparations and independent instrument runs, and establish the absolute quantitative power of this method through comparisons with other reported transcript profiling techniques and through utilization of RNA spike-in experiments. We demonstrate the practical application of this approach to define the transcriptional landscape of mouse embryonic and induced pluripotent stem cells, observing transcriptional differences, including over 100 genes exhibiting differential expression between these otherwise very similar stem cell populations. This amplification-independent technology, which utilizes small quantities of nucleic acid and provides quantitative measurements of cellular transcripts, enables global gene expression measurements from minute amounts of materials and offers broad utility in both basic research and translational biology for characterization of rare cells.

SUBMITTER: Ozsolak F

PROVIDER: S-EPMC2847755 | biostudies-literature | 2010 Apr

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Digital transcriptome profiling from attomole-level RNA samples.

Ozsolak Fatih F Goren Alon A Gymrek Melissa M Guttman Mitchell M Regev Aviv A Bernstein Bradley E BE Milos Patrice M PM

Genome research 20100204 4

Accurate profiling of minute quantities of RNA in a global manner can enable key advances in many scientific and clinical disciplines. Here, we present low-quantity RNA sequencing (LQ-RNAseq), a high-throughput sequencing-based technique allowing whole transcriptome surveys from subnanogram RNA quantities in an amplification/ligation-free manner. LQ-RNAseq involves first-strand cDNA synthesis from RNA templates, followed by 3' polyA tailing of the single-stranded cDNA products and direct single ...[more]

PMID: 20133332

Similar Datasets

Project description:This study aims to compare the potential of standard RNA-sequencing (RNA-Seq) and 3' massive analysis of c-DNA ends (MACE) RNA-sequencing for the analysis of fresh tissue and describes transcriptome profiling of formalin-fixed paraffin-embedded (FFPE) archival human samples by MACE. To compare MACE to standard RNA-Seq on fresh tissue, four healthy conjunctiva from four subjects were collected during vitreoretinal surgery, halved and immediately transferred to RNA lysis buffer without prior fixation and then processed for either standard RNA-Seq or MACE RNA-Seq analysis. To assess the impact of FFPE preparation on MACE, a third part was fixed in formalin and processed for paraffin embedding, and its transcriptional profile was compared with the unfixed specimens analyzed by MACE. To investigate the impact of FFPE storage time on MACE results, 24 FFPE-treated conjunctival samples from 24 patients were analyzed as well. Nineteen thousand six hundred fifty-nine transcribed genes were detected by both MACE and standard RNA-Seq on fresh tissue, while 3251 and 2213 transcripts were identified explicitly by MACE or RNA-Seq, respectively. Standard RNA-Seq tended to yield longer detected transcripts more often than MACE technology despite normalization, indicating that the MACE technology is less susceptible to a length bias. FFPE processing revealed negligible effects on MACE sequencing results. Several quality-control measurements showed that long-term storage in paraffin did not decrease the diversity of MACE libraries. We noted a nonlinear relation between storage time and the number of raw reads with an accelerated decrease within the first 1000 days in paraffin, while the numbers remained relatively stable in older samples. Interestingly, the number of transcribed genes detected was independent on FFPE storage time. RNA of sufficient quality and quantity can be extracted from FFPE samples to obtain comprehensive transcriptome profiling using MACE technology. We thus present MACE as a novel opportunity for utilizing FFPE samples stored in histological archives.

Dataset Information

Digital transcriptome profiling from attomole-level RNA samples.

Publications

Digital transcriptome profiling from attomole-level RNA samples.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets