Back

Stochastic Gene Expression under Sequestration: Noise Reduction and Emergent Distributions

Morozova, O.; Oravcova, I.; Zabaikina, I.; Bokes, P.; Singh, A.

2025-11-26 systems biology
10.1101/2025.11.24.690157 bioRxiv
Show abstract

Gene expression noise can be modulated by protein sequestration, a mechanism we investigate through a stochastic modeling framework. We examine how the distribution of free (non-sequestered) protein depends on sequestration cooperativity (monomers, dimers, multimers) and on the timescale separation between sequestration and protein turnover. For non-cooperative sequestration, faster kinetics drive the distribution from a high-noise to a lower-noise gamma form, while the right-tail remains governed by the high-noise limit -- revealing a non-commutativity between tail asymptotics and fast sequestration. For cooperative sequestration, the distribution departs from gamma, exhibiting left skewness or multi-modality. These results highlight how sequestration mechanisms shape protein variability in nontrivial ways.

Matching journals

The top 5 journals account for 50% of the predicted probability mass.

50% of probability mass above

"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.