Search bioRxiv⌕ Search

Biology subjects

Markus, B.

Publications and source records attributed to Markus, B..

2 recordsLinked to original sources

C/EBPδ-induced epigenetic changes control the dynamic gene transcription of S100A8 and S100A9

The proinflammatory alarmins S100A8 and S100A9 are among the most abundant proteins in neutrophils and monocytes but completely silenced after differentiation to macrophages. The molecular mechanisms of the extraordinarily dynamic transcriptional regulation of s100a8 and s100a9 genes, however, are only barely understood. Using an unbiased genome-wide CRISPR/Cas9 knockout based screening approach in immortalized murine monocytes we identified the transcription factor C/EBP{delta} as a central regulator of S100A8 and S100A9 expression. S100a8 and S100a9 expression was further controlled by the C/EBP{delta}-antagonists ATF3 and FBXW7. We confirmed the clinical relevance of this regulatory network in subpopulations of human monocytes in a clinical cohort of cardiovascular patients. Moreover, we identified specific C/EBP{delta}-binding sites within s100a8 and s100a9 promoter regions, and demonstrated that C/EBP{delta}-dependent JMJD3-mediated demethylation of H3K27me3 is indispensable for their expression. Overall, our work uncovered C/EBP{delta} as a novel regulator of S100A8 and S100A9 expression. Therefore, C/EBP{delta} represents a promising target for modulation of inflammatory conditions that are characterised by S100A8 and S100A9 overexpression.

cell biology↗

Quantitative analysis of population-scale family trees using millions of relatives

Family trees have vast applications in multiple fields from genetics to anthropology and economics. However, the collection of extended family trees is tedious and usually relies on resources with limited geographical scope and complex data usage restrictions. Here, we collected 86 million profiles from publicly-available online data from genealogy enthusiasts. After extensive cleaning and validation, we obtained population-scale family trees, including a single pedigree of 13 million individuals. We leveraged the data to partition the genetic architecture of longevity by inspecting millions of relative pairs and to provide insights to population genetics theories on the dispersion of families. We also report a simple digital procedure to overlay other datasets with our resource in order to empower studies with population-scale genealogical data.\n\nOne Sentence SummaryUsing massive crowd-sourced genealogy data, we created a population-scale family tree resource for scientific studies.

genomics↗