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染色质状态能准确地对细胞分化阶段进行分类。

Chromatin states accurately classify cell differentiation stages.

机构信息

Department of Biostatistics, Harvard School of Public Health, Boston, Massachusetts, United States of America.

出版信息

PLoS One. 2012;7(2):e31414. doi: 10.1371/journal.pone.0031414. Epub 2012 Feb 20.

DOI:10.1371/journal.pone.0031414
PMID:22363642
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3282719/
Abstract

Gene expression is controlled by the concerted interactions between transcription factors and chromatin regulators. While recent studies have identified global chromatin state changes across cell-types, it remains unclear to what extent these changes are co-regulated during cell-differentiation. Here we present a comprehensive computational analysis by assembling a large dataset containing genome-wide occupancy information of 5 histone modifications in 27 human cell lines (including 24 normal and 3 cancer cell lines) obtained from the public domain, followed by independent analysis at three different representations. We classified the differentiation stage of a cell-type based on its genome-wide pattern of chromatin states, and found that our method was able to identify normal cell lines with nearly 100% accuracy. We then applied our model to classify the cancer cell lines and found that each can be unequivocally classified as differentiated cells. The differences can be in part explained by the differential activities of three regulatory modules associated with embryonic stem cells. We also found that the "hotspot" genes, whose chromatin states change dynamically in accordance to the differentiation stage, are not randomly distributed across the genome but tend to be embedded in multi-gene chromatin domains, and that specialized gene clusters tend to be embedded in stably occupied domains.

摘要

基因表达受转录因子和染色质调控因子的协同作用控制。虽然最近的研究已经确定了细胞类型之间的全基因组染色质状态变化,但在细胞分化过程中这些变化在多大程度上受到共同调控仍不清楚。在这里,我们通过组装一个大型数据集进行了全面的计算分析,该数据集包含来自公共领域的 27 个人类细胞系(包括 24 个正常细胞系和 3 个癌细胞系)中 5 种组蛋白修饰的全基因组占有率信息,然后在三个不同的表示形式上进行独立分析。我们根据细胞类型的全基因组染色质状态模式对其分化阶段进行分类,并发现我们的方法能够以近 100%的准确率识别正常细胞系。然后,我们将我们的模型应用于癌细胞系的分类,发现每个癌细胞系都可以明确地归类为分化细胞。这些差异部分可以用与胚胎干细胞相关的三个调节模块的差异活性来解释。我们还发现,染色质状态根据分化阶段动态变化的“热点”基因不是随机分布在基因组中的,而是倾向于嵌入多基因染色质域中,并且专门的基因簇倾向于嵌入稳定占据的域中。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/517e/3282719/19697f553d9d/pone.0031414.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/517e/3282719/067c75830157/pone.0031414.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/517e/3282719/6e5dbf9e9110/pone.0031414.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/517e/3282719/ea5b32d9b09a/pone.0031414.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/517e/3282719/d55766d7914e/pone.0031414.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/517e/3282719/19697f553d9d/pone.0031414.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/517e/3282719/067c75830157/pone.0031414.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/517e/3282719/6e5dbf9e9110/pone.0031414.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/517e/3282719/ea5b32d9b09a/pone.0031414.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/517e/3282719/d55766d7914e/pone.0031414.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/517e/3282719/19697f553d9d/pone.0031414.g005.jpg

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