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人类细胞周期的全基因组转录分析确定了在正常细胞和癌细胞中差异调节的基因。

Genome-wide transcriptional analysis of the human cell cycle identifies genes differentially regulated in normal and cancer cells.

作者信息

Bar-Joseph Ziv, Siegfried Zahava, Brandeis Michael, Brors Benedikt, Lu Yong, Eils Roland, Dynlacht Brian D, Simon Itamar

机构信息

Department of Computer Science, School of Computer Science and Lane Center for Computational Biology, Carnegie Mellon University, Pittsburgh, PA 15213, USA.

出版信息

Proc Natl Acad Sci U S A. 2008 Jan 22;105(3):955-60. doi: 10.1073/pnas.0704723105. Epub 2008 Jan 14.

Abstract

Characterization of the transcriptional regulatory network of the normal cell cycle is essential for understanding the perturbations that lead to cancer. However, the complete set of cycling genes in primary cells has not yet been identified. Here, we report the results of genome-wide expression profiling experiments on synchronized primary human foreskin fibroblasts across the cell cycle. Using a combined experimental and computational approach to deconvolve measured expression values into "single-cell" expression profiles, we were able to overcome the limitations inherent in synchronizing nontransformed mammalian cells. This allowed us to identify 480 periodically expressed genes in primary human foreskin fibroblasts. Analysis of the reconstructed primary cell profiles and comparison with published expression datasets from synchronized transformed cells reveals a large number of genes that cycle exclusively in primary cells. This conclusion was supported by both bioinformatic analysis and experiments performed on other cell types. We suggest that this approach will help pinpoint genetic elements contributing to normal cell growth and cellular transformation.

摘要

表征正常细胞周期的转录调控网络对于理解导致癌症的扰动至关重要。然而,原代细胞中完整的循环基因集尚未被确定。在此,我们报告了在整个细胞周期中同步化的原代人包皮成纤维细胞的全基因组表达谱实验结果。使用实验与计算相结合的方法将测量的表达值解卷积为“单细胞”表达谱,我们能够克服同步未转化哺乳动物细胞所固有的局限性。这使我们能够在原代人包皮成纤维细胞中鉴定出480个周期性表达的基因。对重建的原代细胞谱的分析以及与来自同步化转化细胞的已发表表达数据集的比较揭示了大量仅在原代细胞中循环的基因。这一结论得到了生物信息学分析以及在其他细胞类型上进行的实验的支持。我们认为这种方法将有助于确定对正常细胞生长和细胞转化有贡献的遗传元件。

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