In this paper we establish a large deviation principle for the entropy production rate of possible non-stationary, centered stable Gauss-Markov chains, verifying the Gallavotti-Cohen symmetry. We reach this goal by developing a large deviation theory for quasi-Toeplitz quadratic functionals of multivariate centered stable Gauss-Markov chains, which differ from a perfect Toeplitz form by the addition of quadratic boundary terms.
Within each human cell, different kinds of RNA polymerases and a panoply of transcription factors bind chromatin to simultaneously determine 3D chromosome structure and transcriptional programme. Experiments show that, in some cases, different proteins segregate to form specialised transcription factories; in others they mix together, binding promiscuously the same chromatin stretch. Here, we use Brownian dynamics simulations to study a polymer model for chromosomes accounting for multiple types ("colours") of chromatin-binding proteins. Our multi-colour model shows the spontaneous emergence of both segregated and mixed clusters of chromatin-bound proteins, depending mainly on their size, thereby reconciling the previous experimental observations. Additionally, remarkable small-world networks emerge; in these, positive and negative correlations in activities of transcription units provide simple explanations of why adjacent units in large domains are co-transcribed so often, and how one eQTL (expression quantitative trait locus) can up-regulate some genes and down-regulate others. We also explain how local genome edits induce distant omnigenic and pangenomic effects, and develop ways to predict activities of all transcription units on human chromosomes. All results point to 1D location being a key determinant of transcription, consistently with the conservation of synteny seen between rapidly-evolving enhancers and their more stable target genes.
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