SP19

Principal Investigator: Steve Hoffmann & Alena van Bömmel (FLI Jena)

Tushar Patel (PhD): Development of novel epigenetic clocks based on posttranslational modifications of histones

Posttranslational modifications of histone proteins belong to key remodelers of chromatin. The chromatin state can be altered by environmental stimuli, which subsequently affects the expression of genes associated with aging and longevity. As shown in recent studies, various histone modifications undergo dynamic changes during aging. Some active (e.g., H3K9ac and H4K16ac) or repressive marks (e.g., H3K9me3 and H3K27me3) may be globally increased or decreased, respectively, during the aging process. In this project we will develop integrative bioinformatic approaches to model the dynamical changes of different histone modifications during aging. Using machine learning techniques, we aim to develop a novel epigenetic clock based on the posttranslational modifications of histones. The integration with further epigenomic layers such as open chromatin, DNA methylation together with the transcriptome will help us to better understand the epigenetic mechanisms of aging and longevity. 

Elina Wiechens (PhD): Bioinformatics analysis of transcriptional and epigenomic responses to posttranslational modifications

Posttranslational modification (PTMs) of transcription factors (TFs) and histones are critical mechanisms for regulating the genomic activity. For some TFs, chemical alterations of lysines are known to influence the protein localisation and affect essential protein-protein interactions as well as promoter and transcription factor binding site (TFBS) affinities. We develop bioinformatic approaches to better investigate the influence of such modifications on genome regulation. In this project, we will develop computational methods to better detect differential binding of TFs as well as differential start site usage. We will also measure the impact of various PTMs on TF-binding and isoform-specific expression levels. The computational integration of the ChIP and RNA data within ProMoAge will allow us to better understand the impact of certain PTMs on genome activity and to identify relevant functional networks. Besides, we provide solutions to integrate other layers of information such as DNA methylation systematically.