bioRxivMolecular BiologyPreprint
Determinants of Transcription Initiation Directionality in Metazoans
Mahmoud M. IbrahimiD, Aslıhan Karabacak CalvielloiD, Alexander GlahsiD, Ena KolundžićiD, Antje Hirsekorn, Alexa Carda, Baris TursuniD, Robert P. ZinzeniD, Scott Allen LacadieiD, Uwe OhleriD
Abstract
Divergent transcription from promoters and enhancers is pervasive in many species, but it remains unclear if it is a general and passive feature of all eukaryotic cis regulatory elements. To address this, we define promoters and enhancers in C. elegans, D. melanogaster and H. sapiens using ATAC-Seq and investigate the determinants of their transcription initiation directionalities by analyzing genome-wide nascent, cap-selected, polymerase run-on assays. All three species initiate divergent transcription from separate core promoter sequences. Sequence asymmetry downstream of forward and reverse initiation sites, known to be important for termination and stability in H. sapiens, is unique in each species. Chromatin states of divergent promoters are not entirely conserved, but in all three species, the levels of histone modifications on the +1 nucleosome are independent from those on the -1 nucleosome, arguing for independent initiation events. This is supported by an integrative model of H3K4me3 levels and core promoter sequence that is highly predictive of promoter directionality and of two types of promoters: those with balanced initiation directionality and those with skewed directionality. Lastly, D. melanogaster enhancers display variation in chromatin architecture depending on enhancer location, and D. melanogaster promoter regions with dual enhancer/promoter potential are enriched for divergent transcription. Our results point to a high degree of variation in regulatory element transcription initiation directionality within and between metazoans, and to non-passive regulatory mechanisms of transcription initiation directionality in those species.
- organism: C. elegans
- organism: Drosophila
- organism: human
- assay: ATAC-seq
- research focus: gene regulatory network inference
- approach: statistical model
- Citations
- 0
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