Dataset Information

Benchmarking of RNA-sequencing analysis workflows using whole-transcriptome RT-qPCR expression data

ABSTRACT: RNA-sequencing has become the gold standard for whole-transcriptome gene expression quantification. Multiple algorithms have been developed to derive gene counts from sequencing reads. While a number of benchmarking studies have been conducted, the question remains how individual methods perform at accurately quantifying gene expression levels from RNA-sequencing reads. We performed an independent benchmarking study using RNA-sequencing data from the well established MAQCA and MAQCB reference samples. RNA-sequencing reads were processed using five popular workflows (Tophat-HTSeq, Tophat-Cufflinks, STAR-HTSeq, Kallisto and Salmon) and resulting gene expression measurements were compared to expression data generated by wet-lab validated qPCR assays for all protein coding genes. All methods showed high gene expression rank correlations with qPCR data. When comparing gene expression fold changes between MAQCA and MAQCB samples, about 85% of the genes showed consistent results between RNA-sequencing and qPCR data. Of note, each method revealed a small but specific set of genes with inconsistent expression measurements. A significant proportion of these method-specific inconsistent genes were reproducibly identified in independent datasets. These genes were typically smaller, had fewer exons and were lower expressed compared to genes with consistent expression measurements. We propose that careful validation is warranted when evaluating RNA-seq based expression profiles for this specific set of genes.

ORGANISM(S): Homo sapiens

PROVIDER: GSE83402 | GEO | 2017/01/31

SECONDARY ACCESSION(S): PRJNA325812

REPOSITORIES: GEO

ACCESS DATA

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Project description:Purpose: the goal of this study is to investigate the consequences of USP3 deletion on gene expression in mouse LSK hematopoietic progenitors and in splenic B cells Methods: mRNA profiles of 8 weeks-old wild-type (WT) and ubiquitin specific protease 3 knockout (Usp3−/−) mice were generated by deep sequencing, in duplicate, using Illumina Hiseq2000. The sequence reads that passed quality filters were mapped with TopHat and the gene expressions were calculated using HTSeq-count. qRT–PCR validation was performed using SYBR Green assays Results: We assigned about 8-16 million reads per sample uniquely to a gene of the mouse reference genome (mm9). We identified 23,429 genes in the LSKs, naive B cells and activate B cells of WT and USP3−/− mice using TopHat in combination with HTSeq-count. Comparison of the RNAseq data from LSK with naive or activated B cells show that both the wt and the Usp3-/- LSKs largely exibited a gene expression profile that is specific for wt LSK and distinct from B cells (as supported by statistical significant difference between the transciptional profile of LSK versus naive or activated B cells, p value<0.0001 by Student t test). Comparison of normalized gene expression data for Wt LSKs versus naive B cells of one representative experiment shows Pearson coefficient of r=0.874, and R2=0.763. Distinct LSK-specific expressed genes (such as the MlI receptor and the Kit receptor) and B cells specific genes (such as the MS4A1/CD20 and Spi-B transcription factors) are identified. Expression of a set of 19 genes was assessed by RT-qPCR in three independent LSK mRNA per each genotype. qRT-PCR and the RNA-seq normalized expression data for these genes had a good linear relationship, validating the RNAseq analysis. Comparison of normalized gene expression data for Usp3-/- versus Wt LSK show Pearson coefficient r=0.986; R2=0.9738), naive B cells (Pearson coefficient r=0.987, R2=0.974) and LPS activated B cells (Pearson coefficient r=0.991, R2=0.983). RT-qPCR of a subset of hematopoietic stem cell genes, including Mlp2, ENg, Tek and Fdzl3, show no significant difference beteewn wt and Usp3-/- LSK cells. Less than 100 genes showed differential expression (up or down regulated) between the Wt and Usp3-/- LSK, with a fold change ≥1.5 and p value <0.05. Conclusions: Our results represent the first detailed analyis of the consequences of USP3 deletion on gene expression in hematopoietic populations such as LSKs progenitors and B cells by genome wide expression profiling in wt and Usp3-/- mice. RNAseq of two freshly isolated biological replicas of sorted LSKs from 8 weeks old Usp3-/- animals showed a very limited number of genes either slighly up or down regulated (<100 out of about 25.000) in Usp3-/- LSKs, none of which are reported to be directly involved in hematopoietic stem cell maintenance or to be linked to premature differentiation. We confirmed that Usp3-/- and wt LSKs express hematopoietic stem cell-specific genes to a similar extent. We conclude that young adult hematopoietic stem and progenitor cells (LSKs) perpetuated a stable gene expression program regardless of the homozygous deletion of USP3. mRNA profiles of 8 weeks-old wild type (WT) and Usp3-/- mice were generated by deep sequencing, in duplicate, using Illumina Hiseq2000. For each experiment wt n=4, Usp3-/- n=4 mice were analized. FACS sorted cells from from individual animals were pooled and subjected to deep sequencing. Cells were: LSK (Lin- Sca1+ cKit+) from bone marrow, sorted naive B cells from spleens (CD19+) and activated B cells harvested and FACS sorted after 4 days stimulation with lipopolysaccharide (LPS) in culture.

Dataset Information

Benchmarking of RNA-sequencing analysis workflows using whole-transcriptome RT-qPCR expression data

Dataset's files

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets