Identification and validation of suitable endogenous reference genes for gene expression studies in human peripheral blood.

BACKGROUND: Gene expression studies require appropriate normalization methods. One such method uses stably expressed reference genes. Since suitable reference genes appear to be unique for each tissue, we have identified an optimal set of the most stably expressed genes in human blood that can be used for normalization. METHODS: Whole-genome Affymetrix Human 2.0 Plus arrays were examined from 526 samples of males and females ages 2 to 78, including control subjects and patients with Tourette syndrome, stroke, migraine, muscular dystrophy, and autism. The top 100 most stably expressed genes with a broad range of expression levels were identified. To validate the best candidate genes, we performed quantitative RT-PCR on a subset of 10 genes (TRAP1, DECR1, FPGS, FARP1, MAPRE2, PEX16, GINS2, CRY2, CSNK1G2 and A4GALT), 4 commonly employed reference genes (GAPDH, ACTB, B2M and HMBS) and PPIB, previously reported to be stably expressed in blood. Expression stability and ranking analysis were performed using GeNorm and NormFinder algorithms. RESULTS: Reference genes were ranked based on their expression stability and the minimum number of genes needed for nomalization as calculated using GeNorm showed that the fewest, most stably expressed genes needed for acurate normalization in RNA expression studies of human whole blood is a combination of TRAP1, FPGS, DECR1 and PPIB. We confirmed the ranking of the best candidate control genes by using an alternative algorithm (NormFinder). CONCLUSION: The reference genes identified in this study are stably expressed in whole blood of humans of both genders with multiple disease conditions and ages 2 to 78. Importantly, they also have different functions within cells and thus should be expressed independently of each other. These genes should be useful as normalization genes for microarray and RT-PCR whole blood studies of human physiology, metabolism and disease.

Gene expression in blood of subjects with Duchenne muscular dystrophy.

The objective of this study was to examine RNA expression in blood of subjects with Duchenne muscular dystrophy (DMD). Whole blood was collected into PAX gene tubes and RNA was isolated for 3- to 20-year-old males with DMD (n = 34) and for age- and gender-matched normal healthy controls (n = 21). DMD was confirmed by genetic testing in all subjects. RNA expression was measured on Affymetrix whole-genome human U133 Plus 2.0 GeneChips. Using a Benjamini-Hochberg false discovery rate of 0.05 to correct for multiple comparisons, an unpaired t test for DMD versus controls yielded 10,763 regulated probes with no fold change cutoff, 1,467 probes with >|1.5|-fold change, 191 probes with >|2.0|-fold change, and 59 probes with a >|2.5|-fold change. These genes (probes) separated DMD from controls using cluster analyses. Almost all of the genes regulated in peripheral blood were different from the genes reported to be regulated in diseased muscle of subjects with DMD. It is proposed that the genes regulated in blood of subjects with Duchenne muscular dystrophy are indicative, at least in part, of the immune response to the diseased DMD muscle. The regulated genes might be used to monitor therapy or provide novel targets for immune-directed therapy for DMD.

Empirical Bayes accomodation of batch-effects in microarray data using identical replicate reference samples: application to RNA expression profiling of blood from Duchenne muscular dystrophy patients.

BACKGROUND: Non-biological experimental error routinely occurs in microarray data collected in different batches. It is often impossible to compare groups of samples from independent experiments because batch effects confound true gene expression differences. Existing methods can correct for batch effects only when samples from all biological groups are represented in every batch. RESULTS: In this report we describe a generalized empirical Bayes approach to correct for cross-experimental batch effects, allowing direct comparisons of gene expression between biological groups from independent experiments. The proposed experimental design uses identical reference samples in each batch in every experiment. These reference samples are from the same tissue as the experimental samples. This design with tissue matched reference samples allows a gene-by-gene correction to be performed using fewer arrays than currently available methods. We examine the effects of non-biological variation within a single experiment and between experiments. CONCLUSION: Batch correction has a significant impact on which genes are identified as differentially regulated. Using this method, gene expression in the blood of patients with Duchenne Muscular Dystrophy is shown to differ for hundreds of genes when compared to controls. The numbers of specific genes differ depending upon whether between experiment and/or between batch corrections are performed.

A novel method of Multiplexed Competitive Antibody Binning for the characterization of monoclonal antibodies.

We have developed a novel method of high-throughput Multiplexed Competitive Antibody Binning (MCAB). Using only a small amount of antibody and antigen, this method enables the sorting of a large, complex panel of monoclonal antibodies into different bins based on cross-competition for antigen binding. The MCAB assay builds on Luminex multiplexing bead-based technology to detect antibody competition. Because of its high sensitivity, the MCAB method is immediately applicable after identification of antigen-positive mAbs, providing information useful for advancing mAb candidates into further testing. The MCAB assay also can be used for sorting mAbs into binding groups after screening for functional activity.