Transcription is a complex phenomenon that permits the conversion of genetic information into phenotype by means of an enzyme called RNA polymerase, which erratically moves along and scans the DNA template. We perform Bayesian inference over a paradigmatic mechanistic model of non-equilibrium statistical physics, i.e., the asymmetric exclusion processes in the hydrodynamic limit, assuming a Gaussian process prior for the polymerase progression rate as a latent variable. Our framework allows us to infer the speed of polymerases during transcription given their spatial distribution, whilst avoiding the explicit inversion of the system's dynamics. The results, which show processing rates strongly varying with genomic position and minor role of traffic-like congestion, may have strong implications for the understanding of gene expression.

翻译：转录是一种复杂现象，通过名为RNA聚合酶的酶将遗传信息转化为表型。该酶沿DNA模板随机移动并扫描。我们基于非平衡统计物理学的典范机制模型——流体动力学极限下的非对称排斥过程——进行贝叶斯推断，假设聚合酶延伸速率为潜变量且服从高斯过程先验。该框架使我们能够根据聚合酶的空间分布推断其在转录过程中的速度，同时避免显式反转系统动力学。结果显示，处理速率随基因组位置剧烈变化，而交通式拥堵的影响较小，这对理解基因表达具有重要启示。