Bentsen Mette, Goymann Philipp, Schultheis Hendrik, Klee Kathrin, Petrova Anastasiia, Wiegandt René, Fust Annika, Preussner Jens, Kuenne Carsten, Braun Thomas, Kim Johnny, Looso Mario
Bioinformatics Core Unit (BCU), Max Planck Institute for Heart and Lung Research, 61231, Bad Nauheim, Germany.
German Centre for Cardiovascular Research (DZHK), Partner Site Rhine-Main, 60596, Frankfurt am Main, Germany.
Nat Commun. 2020 Aug 26;11(1):4267. doi: 10.1038/s41467-020-18035-1.
While footprinting analysis of ATAC-seq data can theoretically enable investigation of transcription factor (TF) binding, the lack of a computational tool able to conduct different levels of footprinting analysis has so-far hindered the widespread application of this method. Here we present TOBIAS, a comprehensive, accurate, and fast footprinting framework enabling genome-wide investigation of TF binding dynamics for hundreds of TFs simultaneously. We validate TOBIAS using paired ATAC-seq and ChIP-seq data, and find that TOBIAS outperforms existing methods for bias correction and footprinting. As a proof-of-concept, we illustrate how TOBIAS can unveil complex TF dynamics during zygotic genome activation in both humans and mice, and propose how zygotic Dux activates cascades of TFs, binds to repeat elements and induces expression of novel genetic elements.
虽然从理论上讲,对ATAC-seq数据进行足迹分析能够研究转录因子(TF)的结合情况,但迄今为止,由于缺乏能够进行不同水平足迹分析的计算工具,这种方法的广泛应用受到了阻碍。在此,我们展示了TOBIAS,这是一个全面、准确且快速的足迹分析框架,能够同时对数百种转录因子的全基因组结合动态进行研究。我们使用配对的ATAC-seq和ChIP-seq数据对TOBIAS进行了验证,发现TOBIAS在偏差校正和足迹分析方面优于现有方法。作为概念验证,我们展示了TOBIAS如何揭示人类和小鼠合子基因组激活过程中复杂的转录因子动态,并提出合子Dux如何激活转录因子级联反应、结合重复元件并诱导新遗传元件的表达。