Probe-level analysis of expression microarrays characterizes isoform-specific degradation during mouse oocyte maturation.

Probe-level analysis of expression microarrays characterizes isoform-specific degradation during mouse oocyte maturation.
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DOI:
10.1371/journal.pone.0007479
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发表时间:
2009-10-16
期刊:
影响因子:
3.7
通讯作者:
Graber JH
Graber JH
中科院分区:
综合性期刊3区
文献类型:
--
作者:
Salisbury J;Hutchison KW;Wigglesworth K;Eppig JJ;Graber JH

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Gene expression microarrays have provided many insights into changes in gene expression patterns between different tissue types, developmental stages, and disease states. Analyses of these data focused primarily measuring the relative abundance of transcripts of a gene, while treating most or all transcript isoforms as equivalent. Differences in the selection between transcript isoforms can, however, represent critical changes to either the protein product or the posttranscriptional regulation of the transcript. Novel analyses on existing microarray data provide fresh insights and new interpretations into transcriptome-wide changes in expression. A probe-level analysis of existing gene expression arrays revealed differences in mRNA processing, primarily affecting the 3′-untranslated region. Working with the example of microarrays drawn from a transcriptionally silent period of mouse oocyte development, probe-level analysis (implemented here as rmodel) identified genes whose transcript isoforms have differing stabilities. Comparison of micorarrays measuring cDNA generated from oligo-dT and random primers revealed further differences in the polyadenylation status of some transcripts. Additional analysis provided evidence for sequence-targeted cleavage, including putative targeting sequences, as one mechanism of degradation for several hundred transcripts in the maturing oocyte. The capability of probe-level analysis to elicit novel findings from existing expression microarray data was demonstrated. The characterization of differences in stability between transcript isoforms in maturing mouse oocytes provided some mechanistic details of degradation. Similar analysis of existing archives of expression microarray data will likely provide similar discoveries.
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