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Gene regulatory networks (GRNs) govern many core developmental and biological processes underlying human complex traits. Even with broad-scale efforts to characterize the effects of molecular perturbations and interpret gene coexpression, it remains challenging to infer the architecture of gene regulation in a precise and efficient manner. Key properties of GRNs, like hierarchical structure, modular organization, and sparsity, provide both challenges and opportunities for this objective. Here, we seek to better understand properties of GRNs using a new approach to simulate their structure and model their function. We produce realistic network structures with a novel generating algorithm based on insights from small-world network theory, and we model gene expression regulation using stochastic differential equations formulated to accommodate modeling molecular perturbations. With these tools, we systematically describe the effects of gene knockouts within and across GRNs, finding a subset of networks that recapitulate features of a recent genome-scale perturbation study. With deeper analysis of these exemplar networks, we consider future avenues to map the architecture of gene expression regulation using data from cells in perturbed and unperturbed states, finding that while perturbation data are critical to discover specific regulatory interactions, data from unperturbed cells may be sufficient to reveal regulatory programs.

The rates at which mutations accumulate across human cell types vary. To identify causes of this variation, mutations are often decomposed into a combination of the single-base substitution (SBS) "signatures" observed in germline, soma, and tumors, with the idea that each signature corresponds to one or a small number of underlying mutagenic processes. Two such signatures turn out to be ubiquitous across cell types: SBS signature 1, which consists primarily of transitions at methylated CpG sites thought to be caused by spontaneous deamination, and the more diffuse SBS signature 5, which is of unknown etiology. In cancers, the number of mutations attributed to these 2 signatures accumulates linearly with age of diagnosis, and thus the signatures have been termed "clock-like." To better understand this clock-like behavior, we develop a mathematical model that includes DNA replication errors, unrepaired damage, and damage repaired incorrectly. We show that mutational signatures can exhibit clock-like behavior because cell divisions occur at a constant rate and/or because damage rates remain constant over time, and that these distinct sources can be teased apart by comparing cell lineages that divide at different rates. With this goal in mind, we analyze the rate of accumulation of mutations in multiple cell types, including soma as well as male and female germline. We find no detectable increase in SBS signature 1 mutations in neurons and only a very weak increase in mutations assigned to the female germline, but a significant increase with time in rapidly dividing cells, suggesting that SBS signature 1 is driven by rounds of DNA replication occurring at a relatively fixed rate. In contrast, SBS signature 5 increases with time in all cell types, including postmitotic ones, indicating that it accumulates independently of cell divisions; this observation points to errors in DNA repair as the key underlying mechanism. Thus, the two "clock-like" signatures observed across cell types likely have distinct origins, one set by rates of cell division, the other by damage rates., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Spisak et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Background: Kidney transplantation constitutes the most effective therapeutic option for patients suffering from end-stage renal disease but remains burdened by a high incidence of cardiovascular disease. To date, exercise is an important preventive strategy that has been underestimated; in kidney transplant patients, exercise programs lead to an improvement in cardiorespiratory performance, muscle strength, arterial stiffness, and patients' quality of life perception., Summary: The nephrology and transplant community have moved from generic suggestions to specific indications regarding frequency, intensity, time, type, volume, and progression of physical exercise both in the pre- and posttransplant phase. The latest guidelines from the World Health Organization for patients with chronic conditions propose a combination of aerobic, muscle-strengthening, and multicomponent exercises (e.g., balance) to improve health. Based on recent evidence, a combined exercise program (aerobic and strength exercise) is largely proposed to kidney transplant recipients. Aerobic exercise should be performed at an intensity >60% of theoretical maximum heart rate or maximum oxygen uptake possibly every day, and strength training should be performed at a >60% the estimate single maximum repetition, at least 2 times per week., Key Messages: Physical exercise should be personalized in relation to the patient's baseline performance; increases must be progressive and gradual. Regular physical activity should also be recommended to patients awaiting for a transplant. Eventually, organizational models based on a network of nephrology units, transplant centers, sports medicine centers, and fitness center or outdoor gym are essential elements for overcoming the logistical barriers for prescribing and carrying out regular physical activity., (© 2024 The Author(s). Published by S. Karger AG, Basel.)