Ernur Saka, Benjamin J. Harrison, Kirk L. West, J. Petruska, E. Rouchka
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引用次数: 0
Abstract
Commercially developed microarrays, such as those from Agilent® and Affymetrix®, allow for the analysis of differential gene expression changes on a genome-wide scale. Publicly repositories of microarray data, most notably ArrayExpress and the Gene Expression Omnibus (GEO) have made available millions of microarray samples to researchers worldwide. One of the drawbacks of microarray technology is the static construction of probes based on current genomic knowledge and gene annotation information available at the design phase. As the knowledge base about genes expands, including alternative isoform formation and alternative polyadenylation signaling, the need for a dynamically changing approach to microarray expression analysis has become apparent. We have therefore designed a framework for the reanalysis of publicly available microarray datasets by updating probe set construction based on gene, transcript, and region-based (UTR, exon, CDS) annotations. Our analysis of two publicly available GEO series, GSE48611 and GSE72551, illustrate that the analysis of expression changes using different annotation groupings yields additional insight into changes in transcript expression, in particular, 3' UTR dynamics, which are likely to present phenotypical differences.
商业开发的微阵列,如来自Agilent®和Affymetrix®的微阵列,允许在全基因组范围内分析差异基因表达变化。公开的微阵列数据存储库,最著名的是ArrayExpress和Gene Expression Omnibus (GEO),已经为全世界的研究人员提供了数以百万计的微阵列样本。微阵列技术的缺点之一是在设计阶段基于现有的基因组知识和基因注释信息来静态构建探针。随着基因知识库的扩展,包括可选择的异构体形成和可选择的聚腺苷酸化信号,对微阵列表达分析的动态变化方法的需求已经变得明显。因此,我们设计了一个框架,通过更新基于基因、转录本和基于区域(UTR、外显子、CDS)注释的探针集构建来重新分析公开可用的微阵列数据集。我们对两个公开的GEO序列GSE48611和GSE72551的分析表明,使用不同的注释分组对表达变化的分析可以进一步了解转录物表达的变化,特别是3' UTR动态,这可能会呈现表型差异。