Multi-platform assessment of transcriptional profiling technologies utilizing a precise probe mapping methodology.

BACKGROUND: The arrival of RNA-seq as a high-throughput method competitive to the established microarray technologies has necessarily driven a need for comparative evaluation. To date, cross-platform comparisons of these technologies have been relatively few in number of platforms analyzed and were typically gene name annotation oriented. Here, we present a more extensive and yet precise assessment to elucidate differences and similarities in performance of numerous aspects including dynamic range, fidelity of raw signal and fold-change with sample titration, and concordance with qRT-PCR (TaqMan). To ensure that these results were not confounded by incompatible comparisons, we introduce the concept of probe mapping directed "transcript pattern". A transcript pattern identifies probe(set)s across platforms that target a common set of transcripts for a specific gene. Thus, three levels of data were examined: entire data sets, data derived from a subset of 15,442 RefSeq genes common across platforms, and data derived from the transcript pattern defined subset of 7,034 RefSeq genes. RESULTS: In general, there were substantial core similarities between all 6 platforms evaluated; but, to varying degrees, the two RNA-seq protocols outperformed three of the four microarray platforms in most categories. Notably, a fourth microarray platform, Agilent with a modified protocol, was comparable, or marginally superior, to the RNA-seq protocols within these same assessments, especially in regards to fold-change evaluation. Furthermore, these 3 platforms (Agilent and two RNA-seq methods) demonstrated over 80% fold-change concordance with the gold standard qRT-PCR (TaqMan). CONCLUSIONS: This study suggests that microarrays can perform on nearly equal footing with RNA-seq, in certain key features, specifically when the dynamic range is comparable. Furthermore, the concept of a transcript pattern has been introduced that may minimize potential confounding factors of multi-platform comparison and may be useful for similar evaluations.

Identification of NR1I2 genetic variation using resequencing.

OBJECTIVE: The nuclear receptor NR1I2 (also called PXR or SXR) is primarily expressed in mouse and human liver and intestines. Direct activation of NR1I2 occurs in response to a range of xenobiotics, which causes the formation of a heterodimer with the RXR receptor. This heterodimer binds to the nuclear receptor response elements of downstream genes such as ABCB1, CYP2C, and CYP3A. This study determined the extent of NR1I2 variation in three world populations. METHODS: Variation in NR1I2 was identified by pooled resequencing in African, Asian, and European populations. Validation was performed in European and African populations using PCR and Pyrosequencing technology. RNA expression of NR1I2, ABCB1 and CYP3A4 was assessed using real-time PCR. RESULTS: Of 36 single nucleotide polymorphisms (SNPs) identified, 24 were in the untranslated region, 8 were intronic, and 4 exonic. Thirty-six percent were unique to the African population. In comparison with previously published data, we identified 13 novel polymorphisms. The NR1I2 -566A > C polymorphism was significantly associated with ABCB1 and CYP3A4 RNA expression in colon tumor (P = 0.04 in both cases), however, this polymorphism was not associated with NR1I2 expression. CONCLUSION: With NR1I2 playing such a large role in the regulation of genes involved in drug metabolism and transport, genetic variation contributing to altered NR1I2 function may have an important clinical impact.