Modelling chromosome-wide target search

The most common gene regulation mechanism is when a transcription factor (TF) protein binds to a regulatory sequence to increase or decrease RNA transcription. However, TFs face two main challenges when searching for these sequences. First, the sequences are vanishingly short relative to the genome length. Second, there are many nearly identical sequences scattered across the genome, causing proteins to suspend the search. But as pointed out in a computational study of LacI regulation in Escherichia coli, such almost-targets may lower search times if considering DNA looping. In this paper, we explore if this also occurs over chromosome-wide distances. To this end, we developed a cross-scale computational framework that combines established facilitated-diffusion models for basepair-level search and a network model capturing chromosome-wide leaps. To make our model realistic, we used Hi-C data sets as a proxy for 3D proximity between long-ranged DNA segments and binding profiles for more than 100 TFs. Using our cross-scale model, we found that median search times to individual targets critically depend on a network metric combining node strength (sum of link weights) and local dissociation rates. Also, by randomizing these rates, we found that some actual 3D target configurations stand out as considerably faster or slower than their random counterparts. This finding hints that chromosomes' 3D structure funnels essential TFs to relevant DNA regions.

Automated summary

The most common gene regulation mechanism involves transcription factor proteins binding to regulatory sequences to regulate RNA transcription. However, transcription factors face challenges in finding these sequences due to their short length and the presence of many similar sequences in the genome. A computational study suggests that considering DNA looping can reduce search times for these sequences. This research explores if this phenomenon occurs over longer distances in chromosomes. A cross-scale computational framework combining basepair-level search models and a network model capturing chromosome-wide leaps was developed and used to analyze Hi-C data sets and binding profiles for over 100 transcription factors. The results indicate that the 3D structure of chromosomes plays a role in guiding essential transcription factors to relevant DNA regions.