Dynamic RNA Polymerase compartments organize the transcription of gene clusters
Wang, Y.-H.; Hertz, H. L.; Tang, W.
Show abstract
Spatial organization of transcription machinery is emerging as a key regulator of gene expression, yet how RNA polymerases are organized at gene clusters remains unclear. Here, we show that RNA polymerases II and polymerase III form distinct nuclear foci at the 5S ribosomal DNA (rDNA)-Spliced leader 1 (SL1) cluster in C. elegans. Within this cluster, polymerase II binds to the SL1 gene, while polymerase III associates with 5S rDNA. Both polymerase foci display dynamic but distinct behaviors within the nucleus. The assembly of these polymerase foci is regulated across the cell cycle. ATTF-6, an AT-hook transcription factor, is essential for polymerases II foci formation but dispensable for polymerases III foci. While Pol III foci are largely resistant to temperature changes, Pol II foci are temperature-sensitive, and their dissolution correlates with reduced SL1 expression. Together, these results reveal a spatial and temporal regulation of two RNA polymerases that organize gene cluster transcription.
Matching journals
The top 6 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Nuclear Argonaute protein NRDE-3 switches small RNA partners during embryogenesis to mediate temporal-specific gene regulatory activity 97%
- H3K9me2 orchestrates inheritance of spatial positioning of peripheral heterochromatin through mitosis 97%
- An RNA Degradation Complex Required for Spreading and Epigenetic Inheritance of Heterochromatin 97%
Similar papers in this journal
Similar papers in this journal
- Specialization of the Drosophila nuclear export family protein, Nxf3, for piRNA precursor export 97%
- Hap2-Ino80 facilitated transcription promotes de novo establishment of CENP-A chromatin 96%
- An intrinsically disordered region of Drosha selectively promotes miRNA biogenesis, independent of tissue-specific Microprocessor condensates 96%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.