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Analysis of p53-regulated gene expression patterns using oligonucleotide arrays.

ABSTRACT: Oligonucleotide microarrays were employed to quantitate mRNA levels from a large number of genes regulated by the p53 transcription factor. Responses to DNA damage and to zinc-inducible p53 were compared for their transcription patterns in cell culture. A cluster analysis of these data demonstrates that genes induced by gamma radiation, UV radiation, and the zinc-induced p53 form distinct sets and subsets with a few genes in common to all these treatments. Cell type- or cell line-specific p53 responses were detected. When p53 proteins were induced with zinc, the kinetics of induction or repression of mRNAs from p53-responsive genes fell into eight distinct classes, five different kinetics of induction, and three different kinetics of repression. In addition, low levels of p53 in a cell induced or repressed only a subset of genes observed at higher p53 levels. The results of this study demonstrate that the nature of the p53 response in diverse mRNA species depends on the levels of p53 protein in a cell, the type of inducing agent or event, and the cell type employed. Of 6000 genes examined for p53 regulatory responses, 107 induced and 54 repressed genes fell into categories of apoptosis and growth arrest, cytoskeletal functions, growth factors and their inhibitors, extracellular matrix, and adhesion genes.

SUBMITTER: Zhao R

PROVIDER: S-EPMC316542 | biostudies-literature | 2000 Apr

REPOSITORIES: biostudies-literature

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Analysis of p53-regulated gene expression patterns using oligonucleotide arrays.

Zhao R R Gish K K Murphy M M Yin Y Y Notterman D D Hoffman W H WH Tom E E Mack D H DH Levine A J AJ

Genes & development 20000401 8

Oligonucleotide microarrays were employed to quantitate mRNA levels from a large number of genes regulated by the p53 transcription factor. Responses to DNA damage and to zinc-inducible p53 were compared for their transcription patterns in cell culture. A cluster analysis of these data demonstrates that genes induced by gamma radiation, UV radiation, and the zinc-induced p53 form distinct sets and subsets with a few genes in common to all these treatments. Cell type- or cell line-specific p53 re ...[more]

PMID: 10783169

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Project description:BackgroundOne of the important challenges in microarray analysis is to take full advantage of previously accumulated data, both from one's own laboratory and from public repositories. Through a comparative analysis on a variety of datasets, a more comprehensive view of the underlying mechanism or structure can be obtained. However, as we discover in this work, continual changes in genomic sequence annotations and probe design criteria make it difficult to compare gene expression data even from different generations of the same microarray platform.ResultsWe first describe the extent of discordance between the results derived from two generations of Affymetrix oligonucleotide arrays, as revealed in cluster analysis and in identification of differentially expressed genes. We then propose a method for increasing comparability. The dataset we use consists of a set of 14 human muscle biopsy samples from patients with inflammatory myopathies that were hybridized on both HG-U95Av2 and HG-U133A human arrays. We find that the use of the probe set matching table for comparative analysis provided by Affymetrix produces better results than matching by UniGene or LocusLink identifiers but still remains inadequate. Rescaling of expression values for each gene across samples and data filtering by expression values enhance comparability but only for few specific analyses. As a generic method for improving comparability, we select a subset of probes with overlapping sequence segments in the two array types and recalculate expression values based only on the selected probes. We show that this filtering of probes significantly improves the comparability while retaining a sufficient number of probe sets for further analysis.ConclusionsCompatibility between high-density oligonucleotide arrays is significantly affected by probe-level sequence information. With a careful filtering of the probes based on their sequence overlaps, data from different generations of microarrays can be combined more effectively.

Project description:BACKGROUND: Alternative splicing and isoform level expression profiling is an emerging field of interest within genomics. Splicing sensitive microarrays, with probes targeted to individual exons or exon-junctions, are becoming increasingly popular as a tool capable of both expression profiling and finer scale isoform detection. Despite their intuitive appeal, relatively little is known about the performance of such tools, particularly in comparison with more traditional 3' targeted microarrays. Here, we use the well studied Microarray Quality Control (MAQC) dataset to benchmark the Affymetrix Exon Array, and compare it to two other popular platforms: Illumina, and Affymetrix U133. RESULTS: We show that at the gene expression level, the Exon Array performs comparably with the two 3' targeted platforms. However, the interplatform correlation of the results is slightly lower than between the two 3' arrays. We show that some of the discrepancies stem from the RNA amplification protocols, e.g. the Exon Array is able to detect expression of non-polyadenylated transcripts. More importantly, we show that many other differences result from the ability of the Exon Array to monitor more detailed isoform-level changes; several examples illustrate that changes detected by the 3' platforms are actually isoform variations, and that the nature of these variations can be resolved using Exon Array data. Finally, we show how the Exon Array can be used to detect alternative isoform differences, such as alternative splicing, transcript termination, and alternative promoter usage. We discuss the possible pitfalls and false positives resulting from isoform-level analysis. CONCLUSION: The Exon Array is a valuable tool that can be used to profile gene expression while providing important additional information regarding the types of gene isoforms that are expressed and variable. However, analysis of alternative splicing requires much more hands on effort and visualization of results in order to correctly interpret the data, and generally results in considerably higher false positive rates than expression analysis. One of the main sources of error in the MAQC dataset is variation in amplification efficiency across transcripts, most likely caused by joint effects of elevated GC content in the 5' ends of genes and reduced likelihood of random-primed first strand synthesis in the 3' ends of genes. These effects are currently not adequately corrected using existing statistical methods. We outline approaches to reduce such errors by filtering out potentially problematic data.

Dataset Information

Analysis of p53-regulated gene expression patterns using oligonucleotide arrays.

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Analysis of p53-regulated gene expression patterns using oligonucleotide arrays.

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