We present primary results from the Sequencing Quality Control (SEQC) project, coordinated by the United States Food and Drug Administration. Examining Illumina HiSeq, Life Technologies SOLiD and Roche 454 platforms at multiple laboratory sites using reference RNA samples with built-in controls, we assess RNA sequencing (RNA-seq) performance for junction discovery and differential expression profiling and compare it to microarray and quantitative PCR (qPCR) data using complementary metrics. At all sequencing depths, we discover unannotated exon-exon junctions, with >80% validated by qPCR. We find that measurements of relative expression are accurate and reproducible across sites and platforms if specific filters are used. In contrast, RNA-seq and microarrays do not provide accurate absolute measurements, and gene-specific biases are observed, for these and qPCR. Measurement performance depends on the platform and data analysis pipeline, and variation is large for transcript-level profiling. The complete SEQC data sets, comprising >100 billion reads (10Tb), provide unique resources for evaluating RNA-seq analyses for clinical and regulatory settings.

ClinicalTrials.gov identifier: NCT01375842.

Background: The development of microarrays permits us to monitor transcriptomes on a genome-wide scale. To validate microarray measurements, quantitative-real time-reverse transcription PCR (Q-RT-PCR) is one of the most robust and commonly used approaches. The new challenge in gene quantification analysis is how to explicitly incorporate statistical estimation in such studies. In the realm of statistical analysis, the various available methods of the probe level normalization for microarray analysis may result in distinctly different target selections and variation in the scores for the correlation between microarray and Q-RT-PCR. Moreover, it remains a major challenge to identify a proper internal control for Q-RT-PCR when confirming microarray measurements.

Steady-state gene expression is a coordination of synthesis and decay of RNA through epigenetic regulation, transcription factors, micro RNAs (miRNAs), and RNA-binding proteins. Here, we present bromouride labeling and sequencing (Bru-Seq) and bromouridine pulse-chase and sequencing (BruChase-Seq) to assess genomewide changes to RNA synthesis and stability in human fibroblasts at homeostasis and after exposure to the proinflammatory tumor necrosis factor (TNF). The inflammatory response in human cells involves rapid and dramatic changes in gene expression, and the Bru-Seq and BruChase-Seq techniques revealed a coordinated and complex regulation of gene expression both at the transcriptional and posttranscriptional levels. The combinatory analysis of both RNA synthesis and stability using Bru-Seq and BruChase-Seq allows for a much deeper understanding of mechanisms of gene regulation than afforded by the analysis of steady-state total RNA and should be useful in many biological settings.T he acute inflammatory response is critical for the defense against infections and in the healing of damaged tissues (1). The orchestration of the reprogramming of gene expression associated with the acute inflammatory response is complex and involves both transcriptional and posttranscriptional regulation (2-5). Conventional exploration of gene expression using total RNA does not fully capture this complexity because it does not provide insight into the contribution of nascent RNA synthesis or RNA decay to steady-state RNA changes. A number of different approaches have recently been developed to assess nascent RNA synthesis in cells such as global run-on and sequencing (GROSeq) (6), native elongating transcript sequencing (NET-Seq) (7), nascent RNA sequencing (Nascent-Seq) (8), and metabolic labeling of nascent RNA by using microarrays (9) or RNA-Seq (10, 11). By comparing the data obtained with metabolically labeled nascent RNA with the steady-state RNA levels, the rates of degradation of all transcripts can be computationally estimated. The stability of steady-state RNA can also be estimated from the decay rate of steady-state RNA after transcription inhibition (12)(13)(14) or by immunoprecipitation of metabolically labeled steady-state RNA after different chase periods (15, 16). These approaches work well when the system is at homeostasis, but not when conditions are altered by environmental stimuli or stress, such as the induction of the acute inflammatory response, when the rates of decay of transcripts are expected to change (10,11).In this study, we present Bru-Seq and BruChase-Seq based on bromouridine pulse labeling of nascent RNA followed by chases in uridine to obtain RNA populations of specific ages. The Brulabeled RNA is then immunocaptured followed by deep sequencing. These techniques allowed us to assess changes in the rates of both synthesis and degradation of RNA globally after the activation of the proinflammatory response by TNF. Our results provide a comprehensive and complex picture of the contribution of tr...

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