Bivalent-like chromatin markers are predictive for transcription start site distribution in human.
Bivalent-like chromatin markers are predictive for transcription start site distribution in human.
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DOI：
10.1371/journal.pone.0038112
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发表时间：
2012
期刊：
影响因子：
3.7
通讯作者：
Zhang MQ
中科院分区：
文献类型：
--
作者：
Zhang Z;Ma X;Zhang MQ
5′加帽转录物的深度测序揭示了多种转录起始模式，从窄的、集中的启动子到宽的、宽的启动子。已经尝试了经验分类模式的模型，但几乎没有转录起始的定量模型已被报道。尽管遗传和表观遗传因素都与这种模式有关，但调控因素的组织在很大程度上是未知的。在这里，线性回归模型是从一个池的调控元件，包括基因组DNA特征，核小体组织，和组蛋白修饰，预测转录起始位点（TSS）的分布。重要的是，包括活性和抑制性组蛋白修饰标记物（例如H3K4me3和H4K20me1）的模型一致地被发现比仅具有单一类型组蛋白修饰标记物的模型更具预测性，这表明转录起始的“二价样”表观遗传控制的可能性。核小体的位置被提出编码在这样的二价样组蛋白修饰标记的活性组分中。最后，我们证明了在一种细胞类型上训练的模型可以成功地预测其他细胞类型中的TSS分布，这表明这些模型可能具有更广泛的应用范围。
Deep sequencing of 5′ capped transcripts has revealed a variety of transcription initiation patterns, from narrow, focused promoters to wide, broad promoters. Attempts have already been made to model empirically classified patterns, but virtually no quantitative models for transcription initiation have been reported. Even though both genetic and epigenetic elements have been associated with such patterns, the organization of regulatory elements is largely unknown. Here, linear regression models were derived from a pool of regulatory elements, including genomic DNA features, nucleosome organization, and histone modifications, to predict the distribution of transcription start sites (TSS). Importantly, models including both active and repressive histone modification markers, e.g. H3K4me3 and H4K20me1, were consistently found to be much more predictive than models with only single-type histone modification markers, indicating the possibility of “bivalent-like” epigenetic control of transcription initiation. The nucleosome positions are proposed to be coded in the active component of such bivalent-like histone modification markers. Finally, we demonstrated that models trained on one cell type could successfully predict TSS distribution in other cell types, suggesting that these models may have a broader application range.
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影响因子：
9.8
作者：
ENCODE Project Consortium
通讯作者：
ENCODE Project Consortium
影响因子：
56.9
作者：
Carninci, P;Kasukawa, T;Hayashizaki, Y
通讯作者：
Hayashizaki, Y
DOI：
10.1126/science.1181421
发表时间：
2010-01-15
期刊：
Science (New York, N.Y.)
影响因子：
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作者：
Nechaev S;Fargo DC;dos Santos G;Liu L;Gao Y;Adelman K
通讯作者：
Adelman K
影响因子：
64.5
作者：
Guenther, Matthew G.;Levine, Stuart S.;Young, Richard A.
通讯作者：
Young, Richard A.
影响因子：
16
作者：
Nishioka, K;Rice, JC;Reinberg, D
通讯作者：
Reinberg, D