Detecting outlier microarray arrays by correlation and percentage of outliers spots.

We developed a quality assurance (QA) tool, namely microarray outlier filter (MOF), and have applied it to our microarray datasets for the identification of problematic arrays. Our approach is based on the comparison of the arrays using the correlation coefficient and the number of outlier spots generated on each array to reveal outlier arrays. For a human universal reference (HUR) dataset, which is used as a technical control in our standard hybridization procedure, 3 outlier arrays were identified out of 35 experiments. For a human blood dataset, 12 outlier arrays were identified from 185 experiments. In general, arrays from human blood samples displayed greater variation in their gene expression profiles than arrays from HUR samples. As a result, MOF identified two distinct patterns in the occurrence of outlier arrays. These results demonstrate that this methodology is a valuable QA practice to identify questionable microarray data prior to downstream analysis.

Gene expression profiling of bone marrow stromal cells from juvenile, adult, aged and osteoporotic rats: with an emphasis on osteoporosis.

PURPOSE: Osteoporosis is a multi-factorial, age-related disease with a complex etiology and mode of regulation involving a large numbers of genes. To better understand the possible relationships among genes, we fingerprinted genes in a rat model induced by ovariectomy to determine differences among osteoporotic, non-osteoporotic, aged and juvenile rats. METHODS: We applied genome wide cDNA microarray technology to analyze genes expressed in bone marrow mesenchymal stromal cells (BMSC) and compared non-osteoporotic adult vs. osteoporotic, non-osteoporotic adult vs. aged, and non-osteoporotic adult vs. juvenile. Rigorous statistical analysis of functional annotation (EASE program) identified over-represented biological and molecular functions with significant group wide changes (p< or =0.05). Some of the expressed genes were further confirmed by quantitative RT-PCR (reverse transcription-polymerase chain reaction). RESULTS: Differences in gene expression were observed by identifying transcripts selected by t-test that were consistently changed by a minimum of two-fold. There were 195 transcripts that showed an increased expression and 109 transcripts that showed decreased expression relative to the osteoporotic condition. Of these, 75% transcripts were unknown gene products or ESTs (expressed sequence tag). A number of genes found in the aged and juvenile groups were not present in the osteoporotic rats. Functional clustering of the genes using the EASE bioinformatics program revealed that transcripts in osteoporosis were associated with signal transduction, lipid metabolism, protein metabolism, ionic and protein transport, neuropeptide and G protein signaling pathways. Although some of the genes have previously been shown to play a key role in osteoporosis, several genes were uniquely identified in this study and likely play a role in developing aged related osteoporosis that could have compelling implications in the development of new diagnostic strategies and therapeutics for osteoporosis. CONCLUSIONS: These data suggest that osteoporosis is associated with changes of multiple novel gene expression and that numerous pathways could play important roles in osteoporosis pathogenesis.

Hierarchical model of gene regulation by transforming growth factor beta.

Transforming growth factor betas (TGF-betas) regulate key aspects of embryonic development and major human diseases. Although Smad2, Smad3, and extracellular signal-regulated kinase (ERK) mitogen-activated protein kinases (MAPKs) have been proposed as key mediators in TGF-beta signaling, their functional specificities and interactivity in controlling transcriptional programs in different cell types and (patho)physiological contexts are not known. We investigated expression profiles of genes controlled by TGF-beta in fibroblasts with ablations of Smad2, Smad3, and ERK MAPK. Our results suggest that Smad3 is the essential mediator of TGF-beta signaling and directly activates genes encoding regulators of transcription and signal transducers through Smad3/Smad4 DNA-binding motif repeats that are characteristic for immediate-early target genes of TGF-beta but absent in intermediate target genes. In contrast, Smad2 and ERK predominantly transmodulated regulation of both immediate-early and intermediate genes by TGF-beta/Smad3. These results suggest a previously uncharacterized hierarchical model of gene regulation by TGF-beta in which TGF-beta causes direct activation by Smad3 of cascades of regulators of transcription and signaling that are transmodulated by Smad2 and/or ERK.