Background The relationship between transcription and the 3D chromatin structure is debated. Multiple studies have shown that transcription affects global Cohesin binding and 3D genome structures. However, several other studies have indicated that inhibited transcription does not alter chromatin conformations. Results We provide the most comprehensive evidence to date to demonstrate that transcription plays a relatively modest role in organizing the local, small-scale chromatin structures in mammalian cells. We show degraded Pol I, Pol II, and Pol III proteins in mESCs cause few or no changes in large-scale 3D chromatin structures, selected RNA polymerases with a high abundance of binding sites or active promoter-associated interactions appear to be relatively more affected after the degradation, transcription inhibition alters local, small loop domains, as indicated by high-resolution chromatin interaction maps, and loops with bound Pol II but without Cohesin or CTCF are identified and found to be largely unchanged after transcription inhibition. Interestingly, Pol II depletion for a longer time significantly affects the chromatin accessibility and Cohesin occupancy, suggesting that RNA polymerases are capable of affecting the 3D genome indirectly. These direct and indirect effects explain the previous inconsistent findings on the influence of transcription inhibition on the 3D genome. Conclusions We conclude that Pol I, Pol II, and Pol III loss alters local, small-scale chromatin interactions in mammalian cells, suggesting that the 3D chromatin structures are pre-established and relatively stable.

Retina ribbon synapses are the first synapses in the visual system. Unlike the conventional synapses in the central nervous system triggered by action potentials, ribbon synapses are uniquely driven by graded membrane potentials and are thought to transfer early sensory information faithfully. However, how ribbon synapses compress the visual signals and contribute to visual adaptation in retina circuits is less understood. To this end, we introduce a physiologically constrained module for the ribbon synapse, termed Ribbon Adaptive Block (RAB), and an extended "hierarchical Linear-Nonlinear-Synapse" (hLNS) framework for the retina circuit. Our models can elegantly reproduce a wide range of experimental recordings on synaptic and circuit-level adaptive behaviors across different cell types and species. In particular, it shows strong robustness to unseen stimulus protocols. Intriguingly, when using the hLNS framework to fit intra-cellular recordings from the retina circuit under stimuli similar to natural conditions, we revealed rich and diverse adaptive time constants of ribbon synapses. Furthermore, we predicted a frequency-sensitive gain-control strategy for the synapse between the photoreceptor and the CX bipolar cell, which differ from the classic contrast-based strategy in retina circuits. Overall, our framework provides a powerful analytical tool for exploring synaptic adaptation mechanisms in early sensory coding.

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