Sánchez-Gaya Víctor, Casaní-Galdón Salvador, Ugidos Manuel, Kuang Zheng, Mellor Jane, Conesa Ana, Tarazona Sonia
Genomics of Gene Expression Laboratory Centro de Investigación Príncipe Felipe, Valencia, Spain.
BioBam Bioinformatics S.L., Valencia, Spain.
Front Genet. 2018 Nov 30;9:578. doi: 10.3389/fgene.2018.00578. eCollection 2018.
The Yeast Metabolic Cycle (YMC) is a model system in which levels of around 60% of the yeast transcripts cycle over time. The spatial and temporal resolution provided by the YMC has revealed that changes in the yeast metabolic landscape and chromatin status can be related to cycling gene expression. However, the interplay between histone modifications and transcription factor activity during the YMC is still poorly understood. Here we apply an innovative statistical approach to integrate chromatin state (ChIP-seq) and gene expression (RNA-seq) data to investigate the transcriptional control during the YMC. By using the multivariate regression models N-PLS (Partial Least Squares) and MORE (Multi-Omics REgulation) methodologies, we assessed the contribution of histone marks and transcription factors to the regulation of gene expression in the YMC. We found that H3K18ac and H3K9ac were the most important histone modifications, whereas Sfp1, Hfi1, Pip2, Mig2, and Yhp1 emerged as the most relevant transcription factors. A significant association in the co-regulation of gene expression was found between H3K18ac and the transcription factors Pip2 (involved in fatty acids metabolism), Xbp1 (cyclin implicated in the regulation of carbohydrate and amino acid metabolism), and Hfi1 (involved in the formation of the SAGA complex). These results evidence the crucial role of histone lysine acetylation levels in the regulation of gene expression in the YMC through the coordinated action of transcription factors and lysine acetyltransferases.
酵母代谢周期(YMC)是一种模型系统,其中约60%的酵母转录本水平会随时间周期性变化。YMC提供的时空分辨率揭示了酵母代谢格局和染色质状态的变化可能与周期性基因表达有关。然而,在YMC过程中组蛋白修饰与转录因子活性之间的相互作用仍知之甚少。在此,我们应用一种创新的统计方法整合染色质状态(ChIP-seq)和基因表达(RNA-seq)数据,以研究YMC过程中的转录调控。通过使用多元回归模型N-PLS(偏最小二乘法)和MORE(多组学调控)方法,我们评估了组蛋白标记和转录因子对YMC中基因表达调控的贡献。我们发现H3K18ac和H3K9ac是最重要的组蛋白修饰,而Sfp1、Hfi1、Pip2、Mig2和Yhp1则是最相关的转录因子。在H3K18ac与转录因子Pip2(参与脂肪酸代谢)、Xbp1(参与碳水化合物和氨基酸代谢调控的细胞周期蛋白)和Hfi1(参与SAGA复合物形成)之间发现了基因表达共调控中的显著关联。这些结果证明了组蛋白赖氨酸乙酰化水平通过转录因子和赖氨酸乙酰转移酶的协同作用在YMC基因表达调控中的关键作用。