Over the last decade, the introduction of microarray technology has had a profound impact on gene expression research. The publication of studies with dissimilar or altogether contradictory results, obtained using different microarray platforms to analyze identical RNA samples, has raised concerns about the reliability of this technology. The MicroArray Quality Control (MAQC) project was initiated to address these concerns, as well as other performance and data analysis issues. Expression data on four titration pools from two distinct reference RNA samples were generated at multiple test sites using a variety of microarray-based and alternative technology platforms. Here we describe the experimental design and probe mapping efforts behind the MAQC project. We show intraplatform consistency across test sites as well as a high level of interplatform concordance in terms of genes identified as differentially expressed. This study provides a resource that represents an important first step toward establishing a framework for the use of microarrays in clinical and regulatory settings.

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.

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We have utilized a validated (standardized) estrogen receptor (ER) competitive-binding assay to determine the ER affinity for a large, structurally diverse group of chemicals. Uteri from ovariectomized Sprague-Dawley rats were the ER source for the competitive-binding assay. Initially, test chemicals were screened at high concentrations to determine whether a chemical competed with [3H]-estradiol for the ER. Test chemicals that exhibited affinity for the ER in the first tier were subsequently assayed using a wide range of concentrations to characterize the binding curve and to determine each chemical's IC50 and relative binding affinity (RBA) values. Overall, we assayed 188 chemicals, covering a 1 x 10(6)-fold range of RBAs from several different chemical or use categories, including steroidal estrogens, synthetic estrogens, antiestrogens, other miscellaneous steroids, alkylphenols, diphenyl derivatives, organochlorines, pesticides, alkylhydroxybenzoate preservatives (parabens), phthalates, benzophenone compounds, and a number of other miscellaneous chemicals. Of the 188 chemicals tested, 100 bound to the ER while 88 were non-binders. Included in the 100 chemicals that bound to the ER were 4-benzyloxyphenol, 2,4-dihydroxybenzophenone, and 2,2'-methylenebis(4-chlorophenol), compounds that have not been shown previously to bind the ER. It was also evident that certain structural features, such as an overall ring structure, were important for ER binding. The current study provides the most structurally diverse ER RBA data set with the widest range of RBA values published to date.

PFOA is a peroxisome proliferator (PPAR agonist) and exerts morphological and biochemical effects characteristic of PPAR agonists. These effects include increased beta-oxidation of fatty acids, increases in several cytochrome P-450 (CYP450)-mediated reactions, and inhibition of the secretion of very low-density lipoproteins and cholesterol from the liver. These effects on lipid metabolism and transport result in a reduction of cholesterol and triglycerides in serum and an accumulation of lipids in the liver. The triad of tumors observed (liver, Leydig cell, and pancreatic acinar-cell) is typical of many PPAR agonists and is believed to involve nongenotoxic mechanisms. The hepatocellular tumors observed in rats are likely to have been the result of the activation of the peroxisome proliferator activated receptor alpha (PPARalpha). The tumors observed in the testis (Leydig-cell) have been hypothesized to be associated with an increased level of serum estradiol in concert with testicular growth factors. The mechanism responsible for the acinar-cell tumors of the pancreas in rats remains the subject of active investigation. The mechanism resulting in the hepatocellular tumors in rats (PPARalpha activation) is not likely to be relevant to humans. Similarly, the proposed mechanism for Leydig-cell tumor formation is of questionable relevance to humans. Acinar tumors of the pancreas are rare in humans, and the relevance of the these tumors, as found in rats, to humans is uncertain. Epidemiological investigations and medical surveillance of occupationally exposed workers have not found consistent associations between PFOA exposure and adverse health effects.