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Operon information improves gene expression estimation for cDNA microarrays.

ABSTRACT: In prokaryotic genomes, genes are organized in operons, and the genes within an operon tend to have similar levels of expression. Because of co-transcription of genes within an operon, borrowing information from other genes within the same operon can improve the estimation of relative transcript levels; the estimation of relative levels of transcript abundances is one of the most challenging tasks in experimental genomics due to the high noise level in microarray data. Therefore, techniques that can improve such estimations, and moreover are based on sound biological premises, are expected to benefit the field of microarray data analysisIn this paper, we propose a hierarchical Bayesian model, which relies on borrowing information from other genes within the same operon, to improve the estimation of gene expression levels and, hence, the detection of differentially expressed genes. The simulation studies and the analysis of experiential data demonstrated that the proposed method outperformed other techniques that are routinely used to estimate transcript levels and detect differentially expressed genes, including the sample mean and SAM t statistics. The improvement became more significant as the noise level in microarray data increases.By borrowing information about transcriptional activity of genes within classified operons, we improved the estimation of gene expression levels and the detection of differentially expressed genes.

SUBMITTER: Xiao G

PROVIDER: S-EPMC1513396 | biostudies-literature | 2006 Apr

REPOSITORIES: biostudies-literature

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Operon information improves gene expression estimation for cDNA microarrays.

Xiao Guanghua G Martinez-Vaz Betsy B Pan Wei W Khodursky Arkady B AB

BMC genomics 20060421

<h4>Background</h4>In prokaryotic genomes, genes are organized in operons, and the genes within an operon tend to have similar levels of expression. Because of co-transcription of genes within an operon, borrowing information from other genes within the same operon can improve the estimation of relative transcript levels; the estimation of relative levels of transcript abundances is one of the most challenging tasks in experimental genomics due to the high noise level in microarray data. Therefo ...[more]

PMID: 16630355

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Project description:BackgroundSpotted cDNA microarrays generally employ co-hybridization of fluorescently-labeled RNA targets to produce gene expression ratios for subsequent analysis. Direct comparison of two RNA samples in the same microarray provides the highest level of accuracy; however, due to the number of combinatorial pair-wise comparisons, the direct method is impractical for studies including large number of individual samples (e.g., tumor classification studies). For such studies, indirect comparisons using a common reference standard have been the preferred method. Here we evaluated the precision and accuracy of reconstructed ratios from three indirect methods relative to ratios obtained from direct hybridizations, herein considered as the gold-standard.ResultsWe performed hybridizations using a fixed amount of Cy3-labeled reference oligonucleotide (RefOligo) against distinct Cy5-labeled targets from prostate, breast and kidney tumor samples. Reconstructed ratios between all tissue pairs were derived from ratios between each tissue sample and RefOligo. Reconstructed ratios were compared to (i) ratios obtained in parallel from direct pair-wise hybridizations of tissue samples, and to (ii) reconstructed ratios derived from hybridization of each tissue against a reference RNA pool (RefPool). To evaluate the effect of the external references, reconstructed ratios were also calculated directly from intensity values of single-channel (One-Color) measurements derived from tissue sample data collected in the RefOligo experiments. We show that the average coefficient of variation of ratios between intra- and inter-slide replicates derived from RefOligo, RefPool and One-Color were similar and 2 to 4-fold higher than ratios obtained in direct hybridizations. Correlation coefficients calculated for all three tissue comparisons were also similar. In addition, the performance of all indirect methods in terms of their robustness to identify genes deemed as differentially expressed based on direct hybridizations, as well as false-positive and false-negative rates, were found to be comparable.ConclusionRefOligo produces ratios as precise and accurate as ratios reconstructed from a RNA pool, thus representing a reliable alternative in reference-based hybridization experiments. In addition, One-Color measurements alone can reconstruct expression ratios without loss in precision or accuracy. We conclude that both methods are adequate options in large-scale projects where the amount of a common reference RNA pool is usually restrictive.

Project description:The Paramyxovirus respiratory syncytial virus (RSV) is the primary etiologic agent of serious epidemic lower respiratory tract disease in infants, immunosuppressed patients, and the elderly. Lower tract infection with RSV is characterized by a pronounced peribronchial mononuclear infiltrate, with eosinophilic and basophilic degranulation. Because RSV replication is restricted to airway epithelial cells, where RSV replication induces potent expression of chemokines, the epithelium is postulated to be a primary initiator of pulmonary inflammation in RSV infection. The spectrum of RSV-induced chemokines expressed by alveolar epithelial cells has not been fully investigated. In this report, we profile the kinetics and patterns of chemokine expression in RSV-infected lower airway epithelial cells (A549 and SAE). In A549 cells, membrane-based cDNA macroarrays and high-density oligonucleotide probe-based microarrays identified inducible expression of CC (I-309, Exodus-1, TARC, RANTES, MCP-1, MDC, and MIP-1 alpha and -1 beta), CXC (GRO-alpha, -beta, and -gamma, ENA-78, interleukin-8 [IL-8], and I-TAC), and CX(3)C (Fractalkine) chemokines. Chemokines not previously known to be expressed by RSV-infected cells were independently confirmed by multiprobe RNase protection assay, Northern blotting, and reverse transcription-PCR. High-density microarrays performed on SAE cells confirmed a similar pattern of RSV-inducible expression of CC chemokines (Exodus-1, RANTES, and MIP-1 alpha and -1 beta), CXC chemokines (I-TAC, GRO-alpha, -beta, and -gamma, and IL-8), and Fractalkine. In contrast, TARC, MCP-1, and MDC were not induced, suggesting the existence of distinct genetic responses for different types of airway-derived epithelial cells. Hierarchical clustering by agglomerative nesting and principal-component analyses were performed on A549-expressed chemokines; these analyses indicated that RSV-inducible chemokines are ordered into three related expression groups. These data profile the temporal changes in expression by RSV-infected lower airway epithelial cells of chemokines, chemotactic proteins which may be responsible for the complex cellular infiltrate in virus-induced respiratory inflammation.

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Operon information improves gene expression estimation for cDNA microarrays.

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Operon information improves gene expression estimation for cDNA microarrays.

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