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GwEEP - A comprehensive approach for genome-wide efficiency profiling of DNA modifying enzymes
bioRxiv - Genomics Pub Date : 2021-11-25 , DOI: 10.1101/2020.08.06.236307
Pascal Giehr , Charalampos Kyriakopoulos , Karl Nordström , Abduhlrahman Salhab , Fabian Müller , Ferdinand von Meyenn , Gabriella Ficz , Wolf Reik , Verena Wolf , Jörn Walter

A precise understanding of DNA methylation dynamics on a genome wide scale is of great importance for the comprehensive investigation of a variety of biological processes such as reprogramming of somatic cells to iPSCs, cell differentiation and also cancer development. To date, a complex integration of multiple and distinct genome wide data sets is required to derive the global activity of DNA modifying enzymes. We present GwEEP - Genome-wide Epigenetic Efficiency Profiling as a versatile approach to infer dynamic efficiency changes of DNA modifying enzymes at base pair resolution on a genome wide scale. GwEEP relies on genome wide oxidative Hairpin Bisulfite sequencing (HPoxBS) data sets, which are translated by a sophisticated hidden Markov model into quantitative enzyme efficiencies with reported confidence around the estimates. GwEEP in its present form predicts de novo and maintenance methylation efficiencies of Dnmts, as well as the hydroxylation efficiency of Tets but its purposefully flexible design allows to capture further oxidation processes such as formylation and carboxylation given available data in the future. Applied to a well characterized ES cell model, GwEEP precisely predicts the complex epigenetic changes following a Serum-to-2i shift i.e., (i) instant reduction in maintenance efficiency (ii) gradually decreasing de novo methylation efficiency and (iii) increasing Tet efficiencies. In addition, a complementary analysis of Tet triple knock-out ES cells confirms the previous hypothesized mutual interference of Dnmts and Tets. GwEEP is applicable to a wide range of biological samples including cell lines, but also tissues and primary cell types.

中文翻译:

GwEEP - DNA 修饰酶全基因组效率分析的综合方法

在基因组范围内精确了解 DNA 甲基化动态对于全面研究各种生物过程非常重要,例如将体细胞重编程为 iPSC、细胞分化和癌症发展。迄今为止,需要对多个不同的全基因组数据集进行复杂的整合,才能获得 DNA 修饰酶的全局活性。我们将 GwEEP -全基因组表观遗传效率分析作为一种通用方法,在基因组范围内以碱基对分辨率推断 DNA 修饰酶的动态效率变化。GwEEP 依赖于全基因组氧化发夹亚硫酸氢测序(HPoxBS) 数据集,由复杂的隐马尔可夫模型转换为定量酶效率,并报告估计值的置信度。目前形式的 GwEEP 可从头预测和维持 Dnmts 的甲基化效率,以及 Tets 的羟基化效率,但其有目的的灵活设计允许在未来获得可用数据的情况下捕获进一步的氧化过程,例如甲酰化和羧化。应用于充分表征的 ES 细胞模型,GwEEP 可精确预测 Serum-to-2i 转变后复杂的表观遗传变化,即 (i) 维持效率立即降低 (ii) 逐渐降低从头甲基化效率和 (iii) 提高 Tet 效率. 此外,对 Tet 三重敲除 ES 细胞的补充分析证实了先前假设的 Dnmts 和 Tets 相互干扰。GwEEP 适用于广泛的生物样品,包括细胞系、组织和原代细胞类型。
更新日期:2021-11-28
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