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Identification of coexpressed gene clusters in a comparative analysis of transcriptome and proteome in mouse tissues

机译:在小鼠组织中转录组和蛋白质组的比较分析中鉴定共表达的基因簇

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A major advantage of the mouse model lies in the increasing information on its genome, transcriptome, and proteome, as well as in the availability of a fast growing number of targeted and induced mutant alleles. However, data from comparative transcriptome and proteome analyses in this model organism are very limited. We use DNA chip-based RNA expression profiling and 2D gel electrophoresis, combined with peptide mass fingerprinting of liver and kidney, to explore the feasibility of such comprehensive gene expression analyses. Although protein analyses mostly identify known metabolic enzymes and structural proteins, transcriptome analyses reveal the differential expression of functionally diverse and not yet described genes. The comparative analysis suggests correlation between transcriptional and translational expression for the majority of genes. Significant exceptions from this correlation confirm the complementarities of both approaches. Based on RNA expression data from the 200 most differentially expressed genes, we identify chromosomal colocalization of known, as well as not yet described, gene clusters. The determination of 29 such clusters may suggest that coexpression of colocalizing genes is probably rather common.
机译:小鼠模型的主要优势在于其基因组,转录组和蛋白质组上信息的不断增加,以及快速增长的靶向和诱导突变等位基因的可用性。但是,在这种模式生物中来自比较转录组和蛋白质组分析的数据非常有限。我们使用基于DNA芯片的RNA表达谱和2D凝胶电泳,并结合肝和肾的肽质量指纹图谱,来探索这种全面基因表达分析的可行性。尽管蛋白质分析主要鉴定已知的代谢酶和结构蛋白,但转录组分析揭示了功能多样且尚未描述的基因的差异表达。比较分析表明,大多数基因的转录和翻译表达之间存在相关性。这种相关性的重大例外情况证实了这两种方法的互补性。基于来自200个差异最大的表达基因的RNA表达数据,我们确定了已知的和尚未描述的基因簇的染色体共定位。 29个这样的簇的确定可能表明共定位基因的共表达可能相当普遍。

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