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Comprehensive exon array data processing method for quantitative analysis of alternative spliced variants.

ABSTRACT: Alternative splicing of pre-mRNA generates protein diversity. Dysfunction of splicing machinery and expression of specific transcripts has been linked to cancer progression and drug response. Exon microarray technology enables genome-wide quantification of expression levels of the majority of exons and facilitates the discovery of alternative splicing events. Analysis of exon array data is more challenging than the analysis of gene expression data and there is a need for reliable quantification of exons and alternatively spliced variants. We introduce a novel, computationally efficient methodology, Multiple Exon Array Preprocessing (MEAP), for exon array data pre-processing, analysis and visualization. We compared MEAP with existing pre-processing methods, and validation of six exons and two alternatively spliced variants with qPCR corroborated MEAP expression estimates. Analysis of exon array data from head and neck squamous cell carcinoma (HNSCC) cell lines revealed several transcripts associated with 11q13 amplification, which is related with decreased survival and metastasis in HNSCC patients. Our results demonstrate that MEAP produces reliable expression values at exon, alternatively spliced variant and gene levels, which allows generating novel experimentally testable predictions.

SUBMITTER: Chen P

PROVIDER: S-EPMC3185423 | biostudies-literature | 2011 Oct

REPOSITORIES: biostudies-literature

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Comprehensive exon array data processing method for quantitative analysis of alternative spliced variants.

Chen Ping P Lepikhova Tatiana T Hu Yizhou Y Monni Outi O Hautaniemi Sampsa S

Nucleic acids research 20110710 18

Alternative splicing of pre-mRNA generates protein diversity. Dysfunction of splicing machinery and expression of specific transcripts has been linked to cancer progression and drug response. Exon microarray technology enables genome-wide quantification of expression levels of the majority of exons and facilitates the discovery of alternative splicing events. Analysis of exon array data is more challenging than the analysis of gene expression data and there is a need for reliable quantification ...[more]

PMID: 21745820

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Project description:We have examined the regulation of mutually exclusive Cav2.2 exon 37a and b variants by the mouse ?-opioid receptor (mMOR) C-terminal splice variants 1, 1C and 1O in tsA-201 cells. Electrophysiological analyses revealed that both channel isoforms exhibit DAMGO-induced voltage-dependent (G??-mediated) inhibition and its recovery by voltage pre-pulses, as well as a voltage-independent component. However, the two channel isoforms differ in their relative extent of voltage-dependent and independent inhibition, with Cav2.2-37b showing significantly more voltage-dependent inhibition upon activation of the three mMOR receptors studied. In addition, coexpression of either mMOR1 or mMOR1C results in an agonist-independent reduction in the peak current density of Cav2.2-37a channels, whereas the peak current density of Cav2.2-37b does not appear to be affected. Interestingly, this decrease is not due to an effect on channel expression at the plasma membrane, as demonstrated by biotinylation experiments. We further examined the mechanism underlying the agonist-independent modulation of Cav2.2-37a by mMOR1C. Incubation of cells with pertussis toxin did not affect the mMOR1C mediated inhibition of Cav2.2-37a currents, indicating a lack of involvement of Gi/o signaling. However, when a Src tyrosine kinase inhibitor was applied, the effect of mMOR1C was lost. Moreover, when we recorded currents using a Cav2.2-37a mutant in which tyrosine 1747 was replaced with phenylalanine (Y1747F), the agonist independent effects of mMOR1C were abolished. Altogether our findings show that Cav2.2-37a and Cav2.2-37b isoforms are subject to differential regulation by C-terminal splice variants of mMORs, and that constitutive mMOR1C activity and downstream tyrosine kinase activity exert a selective inhibition of the Cav2.2-37a splice variant, an N-type channel isoform that is highly enriched in nociceptors. Our study provides new insights into the roles of the MOR full-length C-terminal variants in modulating Cav2.2 channel isoform activities.

Project description:BackgroundThe Agilent microRNA microarray platform interrogates each microRNA with several copies of distinct oligonucleotide probes and integrates the results into a total gene signal (TGS), using a proprietary algorithm that makes use of the background subtracted signal. The TGS can be normalized between arrays, and the Agilent recommendation is either not to normalize or to normalize to the 75th percentile signal intensity. The robust multiarray average algorithm (RMA) is an alternative method, originally developed to obtain a summary measure of mRNA Affymetrix gene expression arrays by using a linear model that takes into account the probe affinity effect. The RMA method has been shown to improve the accuracy and precision of expression measurements relative to other competing methods. There is also evidence that it might be preferable to use non-corrected signals for the processing of microRNA data, rather than background-corrected signals. In this study we assess the use of the RMA method to obtain a summarized microRNA signal for the Agilent arrays.FindingsWe have adapted the RMA method to obtain a processed signal for the Agilent arrays and have compared the RMA summarized signal to the TGS generated with the image analysis software provided by the vendor. We also compared the use of the RMA algorithm with uncorrected and background-corrected signals, and compared quantile normalization with the normalization method recommended by the vendor. The pre-processing methods were compared in terms of their ability to reduce the variability (increase precision) of the signals between biological replicates. Application of the RMA method to non-background corrected signals produced more precise signals than either the RMA-background-corrected signal or the quantile-normalized Agilent TGS. The Agilent TGS normalized to the 75% percentile showed more variation than the other measures.ConclusionsUsed without background correction, a summarized signal that takes into account the probe effect might provide a more precise estimate of microRNA expression. The variability of quantile normalization was lower compared with the normalization method recommended by the vendor.

Project description:BackgroundIt is known from recent studies that more than 90% of human multi-exon genes are subject to Alternative Splicing (AS), a key molecular mechanism in which multiple transcripts may be generated from a single gene. It is widely recognized that a breakdown in AS mechanisms plays an important role in cellular differentiation and pathologies. Polymerase Chain Reactions, microarrays and sequencing technologies have been applied to the study of transcript diversity arising from alternative expression. Last generation Affymetrix GeneChip Human Exon 1.0 ST Arrays offer a more detailed view of the gene expression profile providing information on the AS patterns. The exon array technology, with more than five million data points, can detect approximately one million exons, and it allows performing analyses at both gene and exon level. In this paper we describe BEAT, an integrated user-friendly bioinformatics framework to store, analyze and visualize exon arrays datasets. It combines a data warehouse approach with some rigorous statistical methods for assessing the AS of genes involved in diseases. Meta statistics are proposed as a novel approach to explore the analysis results. BEAT is available at http://beat.ba.itb.cnr.it.ResultsBEAT is a web tool which allows uploading and analyzing exon array datasets using standard statistical methods and an easy-to-use graphical web front-end. BEAT has been tested on a dataset with 173 samples and tuned using new datasets of exon array experiments from 28 colorectal cancer and 26 renal cell cancer samples produced at the Medical Genetics Unit of IRCCS Casa Sollievo della Sofferenza.To highlight all possible AS events, alternative names, accession Ids, Gene Ontology terms and biochemical pathways annotations are integrated with exon and gene level expression plots. The user can customize the results choosing custom thresholds for the statistical parameters and exploiting the available clinical data of the samples for a multivariate AS analysis.ConclusionsDespite exon array chips being widely used for transcriptomics studies, there is a lack of analysis tools offering advanced statistical features and requiring no programming knowledge. BEAT provides a user-friendly platform for a comprehensive study of AS events in human diseases, displaying the analysis results with easily interpretable and interactive tables and graphics.

Dataset Information

Comprehensive exon array data processing method for quantitative analysis of alternative spliced variants.

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Comprehensive exon array data processing method for quantitative analysis of alternative spliced variants.

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