Over the last decade, gene expression microarrays have had a profound impact on biomedical research. The diversity of platforms and analytical methods available to researchers have made the comparison of data from multiple platforms challenging. In this study, we describe a framework for comparisons across platforms and laboratories. We have attempted to include nearly all the available commercial and 'in-house' platforms. Using probe sequences matched at the exon level improved consistency of measurements across the different microarray platforms compared to annotation-based matches. Generally, consistency was good for highly expressed genes, and variable for genes with lower expression values as confirmed by quantitative real-time (QRT)-PCR. Concordance of measurements was higher between laboratories on the same platform than across platforms. We demonstrate that, after stringent preprocessing, commercial arrays were more consistent than in-house arrays, and by most measures, one-dye platforms were more consistent than two-dye platforms.
X-chromosome dosage compensation in Drosophila requires the male-specific lethal (MSL) complex, which up-regulates gene expression from the single male X chromosome. Here, we define X-chromosome-specific MSL binding at high resolution in two male cell lines and in late-stage embryos. We find that the MSL complex is highly enriched over most expressed genes, with binding biased toward the 3' end of transcription units. The binding patterns are largely similar in the distinct cell types, with approximately 600 genes clearly bound in all three cases. Genes identified as clearly bound in one cell type and not in another indicate that attraction of MSL complex correlates with expression state. Thus, sequence alone is not sufficient to explain MSL targeting. We propose that the MSL complex recognizes most X-linked genes, but only in the context of chromatin factors or modifications indicative of active transcription. Distinguishing expressed genes from the bulk of the genome is likely to be an important function common to many chromatin organizing and modifying activities.
Dosage compensation in Drosophila serves as a model system for understanding the targeting of chromatin-modifying complexes to their sites of action. The MSL (male-specific lethal) complex up-regulates transcription of the single male X chromosome, thereby equalizing levels of transcription of X-linked genes between the sexes. Recruitment of the MSL complex to its binding sites on the male X chromosome requires each of the MSL proteins and at least one of the two large noncoding roX RNAs. To better understand how the MSL complex specifically targets the X chromosome, we have defined the binding using high-resolution genomic tiling arrays. Our results indicate that the MSL complex largely associates with transcribed genes that are present in clusters along the X chromosome. We hypothesize that after initial recruitment of the MSL complex to the X chromosome by unknown mechanisms, nascent transcripts or chromatin marks associated with active transcription attract the MSL complex to its final targets. Defining MSL-complex-binding sites will provide a tool for understanding functions of large noncoding RNAs that have remained elusive.
MOTIVATION: Several statistical methods that combine analysis of differential gene expression with biological knowledge databases have been proposed for a more rapid interpretation of expression data. However, most such methods are based on a series of univariate statistical tests and do not properly account for the complex structure of gene interactions. RESULTS: We present a simple yet effective multivariate statistical procedure for assessing the correlation between a subspace defined by a group of genes and a binary phenotype. A subspace is deemed significant if the samples corresponding to different phenotypes are well separated in that subspace. The separation is measured using Hotelling's T(2) statistic, which captures the covariance structure of the subspace. When the dimension of the subspace is larger than that of the sample space, we project the original data to a smaller orthonormal subspace. We use this method to search through functional pathway subspaces defined by Reactome, KEGG, BioCarta and Gene Ontology. To demonstrate its performance, we apply this method to the data from two published studies, and visualize the results in the principal component space.
In mammals, the X and Y chromosomes are subject to meiotic sex chromosome inactivation (MSCI) during prophase I in the male germline, but their status thereafter is currently unclear. An abundance of X-linked spermatogenesis genes has spawned the view that the X must be active . On the other hand, the idea that the imprinted paternal X of the early embryo may be preinactivated by MSCI suggests that silencing may persist longer . To clarify this issue, we establish a comprehensive X-expression profile during mouse spermatogenesis. Here, we discover that the X and Y occupy a novel compartment in the postmeiotic spermatid and adopt a non-Rabl configuration. We demonstrate that this postmeiotic sex chromatin (PMSC) persists throughout spermiogenesis into mature sperm and exhibits epigenetic similarity to the XY body. In the spermatid, 87% of X-linked genes remain suppressed postmeiotically, while autosomes are largely active. We conclude that chromosome-wide X silencing continues from meiosis to the end of spermiogenesis, and we discuss implications for proposed mechanisms of imprinted X-inactivation.
BACKGROUND: Broader understanding of diverse angiogenic pathways in a particular cancer can lead to better utilization of anti-angiogenic therapies. The aim of this study was to develop profiles of angiogenesis-related gene and protein expression for various histologic subtypes of soft tissue sarcomas (STS) growing in different sites. MATERIALS AND METHODS: Plasma levels of vascular endothelial growth factor (VEGF), basic fibroblast growth factor (bFGF), angiopoietin 2 (Ang2), and leptin were determined in 108 patients with primary STS. Gene expression patterns were analyzed in 38 STS samples and 13 normal tissues using oligonucleotide microarrays. RESULTS: VEGF and bFGF plasma levels were elevated 10-13 fold in STS patients compared to controls. VEGF levels were broadly elevated while bFGF levels were higher in patients with fibrosarcomas and leiomyosarcomas. Ang2 levels correlated with tumor size and were most elevated for tumors located in the trunk, while leptin levels were highest in patients with liposarcomas. Hierarchical clustering of microarray data based on angiogenesis-related gene expression demonstrated that histologic subtypes of STS often shared similar expression patterns, and these patterns were distinctly different from those of normal tissues. Matrix metalloproteinase 2, platelet-derived growth factor receptor, alpha and Notch 4 were among several genes that were up-regulated at least 7-fold in STS. CONCLUSIONS: STS demonstrate significant heterogeneity in their angiogenic profiles based on size, histologic subtype, and location of tumor growth, which may have implications for anti-angiogenic strategies. Comparison of STS to normal tissues reveals a panel of upregulated genes that may be targets for future therapies.
A novel genome-wide screen that combines patient outcome analysis with array comparative genomic hybridization and mRNA expression profiling was developed to identify genes with copy number alterations, aberrant mRNA expression, and relevance to survival in glioblastoma. The method led to the discovery of physical gene clusters within the cancer genome with boundaries defined by physical proximity, correlated mRNA expression patterns, and survival relatedness. These boundaries delineate a novel genomic interval called the functional common region (FCR). Many FCRs contained genes of high biological relevance to cancer and were used to pinpoint functionally significant DNA alterations that were too small or infrequent to be reliably identified using standard algorithms. One such FCR contained the EphA2 receptor tyrosine kinase. Validation experiments showed that EphA2 mRNA overexpression correlated inversely with patient survival in a panel of 21 glioblastomas, and ligand-mediated EphA2 receptor activation increased glioblastoma proliferation and tumor growth via a mitogen-activated protein kinase-dependent pathway. This novel genome-wide approach greatly expanded the list of target genes in glioblastoma and represents a powerful new strategy to identify the upstream determinants of tumor phenotype in a range of human cancers.