Chromatin Signature and Transcription Factor Binding Provide a Predictive Basis for Understanding Plant Gene Expression
Chromatin Signature and Transcription Factor Binding Provide a Predictive Basis for Understanding Plant Gene Expression
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染色质特征和转录因子结合为了解植物基因表达提供预测基础
DOI：
10.1093/pcp/pcz051
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发表时间：
2019
期刊：
影响因子：
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通讯作者：
杨若林
中科院分区：
文献类型：
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作者：
武泽峰;唐静;卓俊杰;田玉寒;赵飞扬;李昭宏;宴瑜斌;杨若林
染色质可及性和转录后组蛋白修饰在基因表达调控中起着重要作用。然而，尽管单独的组蛋白标记如H3K4me3在基因表达中的调节作用已经得到了很好的证明，但关于多种染色质修饰对植物基因表达水平的联合影响却知之甚少。利用机器学习方法，我们基于拟南芥和水稻的多个染色质修饰数据，系统地进行了基因表达水平的预测。我们发现，只需四次组蛋白修饰就足以产生良好的预测性能，H3K4me3和H3K36me3是最重要的两个预测因子，它们分别与转录起始和延伸有关。我们证明了蛋白质编码基因和非编码基因以及CpG富集型和CpG缺陷型基因之间的预测能力不同。我们还表明，在一个组织或物种中训练的预测模型也可以应用于另一个组织或物种，这表明了共同的潜在机制。更有趣的是，保守的同源基因的基因表达水平比物种特有基因更容易预测。此外，远端增强子的染色质状态与基因表达有适度的相关性，但如果考虑到基因近端区域的染色质特征，则是可有可无的。我们进一步将分析扩展到转录因子(TF)结合数据。令人惊讶的是，只有少数几种转录因子的组合效应大致符合拟南芥的基因表达水平。总而言之，通过使用定量模型，我们对表观遗传和TF介导的植物基因表达调控提供了一个全面和公正的视角。
Chromatin accessibility and post-transcriptional histone modifications play important roles in gene expression regulation. However, little is known about the joint effect of multiple chromatin modifications on the gene expression level in plants, despite that the regulatory roles of individual histone marks such as H3K4me3 in gene expression have been well-documented. By using machine-learning methods, we systematically performed gene expression level prediction based on multiple chromatin modifications data inArabidopsisand rice. We found that as few as four histone modifications were sufficient to yield good prediction performance, and H3K4me3 and H3K36me3 being the top two predictors with known functions related to transcriptional initiation and elongation, respectively. We demonstrated that the predictive powers differed between protein-coding and non-coding genes as well as between CpG-enriched and CpG-depleted genes. We also showed that the predictive model trained in one tissue or species could be applied to another tissue or species, suggesting shared underlying mechanisms. More interestingly, the gene expression levels of conserved orthologs are easier to predict than the species-specific genes. In addition, chromatin state of distal enhancers was moderately correlated to gene expression but was dispensable if given the chromatin features of the proximal regions of genes. We further extended the analysis to transcription factor (TF) binding data. Strikingly, the combinatorial effects of only a few TFs were roughly fit to gene expression levels inArabidopsis. Overall, by using quantitative modeling, we provide a comprehensive and unbiased perspective on the epigenetic and TF-mediated regulation of gene expression in plants.