Cross platform microarray analysis for robust identification of differentially expressed genes

<p>Abstract</p> <p>Background</p> <p>Microarrays have been widely used for the analysis of gene expression and several commercial platforms are available. The combined use of multiple platforms can overcome the inherent biases of each approach, and may represent an alternative that is complementary to RT-PCR for identification of the more robust changes in gene expression profiles.</p> <p>In this paper, we combined statistical and functional analysis for the cross platform validation of two oligonucleotide-based technologies, Affymetrix (AFFX) and Applied Biosystems (ABI), and for the identification of differentially expressed genes.</p> <p>Results</p> <p>In this study, we analysed differentially expressed genes after treatment of an ovarian carcinoma cell line with a cell cycle inhibitor. Treated versus control RNA was analysed for expression of 16425 genes represented on both platforms.</p> <p>We assessed reproducibility between replicates for each platform using CAT plots, and we found it high for both, with better scores for AFFX. We then applied integrative correlation analysis to assess reproducibility of gene expression patterns across studies, bypassing the need for normalizing expression measurements across platforms. We identified 930 genes as differentially expressed on AFFX and 908 on ABI, with ~80% common to both platforms. Despite the different absolute values, the range of intensities of the differentially expressed genes detected by each platform was similar. ABI showed a slightly higher dynamic range in FC values, which might be associated with its detection system. 62/66 genes identified as differentially expressed by Microarray were confirmed by RT-PCR.</p> <p>Conclusion</p> <p>In this study we present a cross-platform validation of two oligonucleotide-based technologies, AFFX and ABI. We found good reproducibility between replicates, and showed that both platforms can be used to select differentially expressed genes with substantial agreement. Pathway analysis of the affected functions identified themes well in agreement with those expected for a cell cycle inhibitor, suggesting that this procedure is appropriate to facilitate the identification of biologically relevant signatures associated with compound treatment. The high rate of confirmation found for both common and platform-specific genes suggests that the combination of platforms may overcome biases related to probe design and technical features, thereby accelerating the identification of trustworthy differentially expressed genes.</p

Cross-platform comparability of microarray technology: Intra-platform consistency and appropriate data analysis procedures are essential

BACKGROUND: The acceptance of microarray technology in regulatory decision-making is being challenged by the existence of various platforms and data analysis methods. A recent report (E. Marshall, Science, 306, 630–631, 2004), by extensively citing the study of Tan et al. (Nucleic Acids Res., 31, 5676–5684, 2003), portrays a disturbingly negative picture of the cross-platform comparability, and, hence, the reliability of microarray technology. RESULTS: We reanalyzed Tan's dataset and found that the intra-platform consistency was low, indicating a problem in experimental procedures from which the dataset was generated. Furthermore, by using three gene selection methods (i.e., p-value ranking, fold-change ranking, and Significance Analysis of Microarrays (SAM)) on the same dataset we found that p-value ranking (the method emphasized by Tan et al.) results in much lower cross-platform concordance compared to fold-change ranking or SAM. Therefore, the low cross-platform concordance reported in Tan's study appears to be mainly due to a combination of low intra-platform consistency and a poor choice of data analysis procedures, instead of inherent technical differences among different platforms, as suggested by Tan et al. and Marshall. CONCLUSION: Our results illustrate the importance of establishing calibrated RNA samples and reference datasets to objectively assess the performance of different microarray platforms and the proficiency of individual laboratories as well as the merits of various data analysis procedures. Thus, we are progressively coordinating the MAQC project, a community-wide effort for microarray quality control

Genomic Organization and Expression Demonstrate Spatial and Temporal Hox Gene Colinearity in the Lophotrochozoan Capitella sp. I

Hox genes define regional identities along the anterior–posterior axis in many animals. In a number of species, Hox genes are clustered in the genome, and the relative order of genes corresponds with position of expression in the body. Previous Hox gene studies in lophotrochozoans have reported expression for only a subset of the Hox gene complement and/or lack detailed genomic organization information, limiting interpretations of spatial and temporal colinearity in this diverse animal clade. We studied expression and genomic organization of the single Hox gene complement in the segmented polychaete annelid Capitella sp. I. Total genome searches identified 11 Hox genes in Capitella, representing 11 distinct paralog groups thought to represent the ancestral lophotrochozoan complement. At least 8 of the 11 Capitella Hox genes are genomically linked in a single cluster, have the same transcriptional orientation, and lack interspersed non-Hox genes. Studying their expression by situ hybridization, we find that the 11 Capitella Hox genes generally exhibit spatial and temporal colinearity. With the exception of CapI-Post1, Capitella Hox genes are all expressed in broad ectodermal domains during larval development, consistent with providing positional information along the anterior–posterior axis. The anterior genes CapI-lab, CapI-pb, and CapI-Hox3 initiate expression prior to the appearance of segments, while more posterior genes appear at or soon after segments appear. Many of the Capitella Hox genes have either an anterior or posterior expression boundary coinciding with the thoracic–abdomen transition, a major body tagma boundary. Following metamorphosis, several expression patterns change, including appearance of distinct posterior boundaries and restriction to the central nervous system. Capitella Hox genes have maintained a clustered organization, are expressed in the canonical anterior–posterior order found in other metazoans, and exhibit spatial and temporal colinearity, reflecting Hox gene characteristics that likely existed in the protostome–deuterostome ancestor