How does social complexity depend on population size and cultural transmission? Kinship structures in traditional societies provide a fundamental illustration, where cultural rules between clans determine people\'s marriage possibilities. Here, we propose a simple model of kinship interactions that considers kin and in-law cooperation and sexual rivalry. In this model, multiple societies compete. Societies consist of multiple families with different cultural traits and mating preferences. These values determine interactions and hence the growth rate of families and are transmitted to offspring with mutations. Through a multilevel evolutionary simulation, family traits and preferences are grouped into multiple clans with interclan mating preferences. It illustrates the emergence of kinship structures as the spontaneous formation of interdependent cultural associations. Emergent kinship structures are characterized by the cycle length of marriage exchange and the number of cycles in society. We numerically and analytically clarify their parameter dependence. The relative importance of cooperation versus rivalry determines whether attraction or repulsion exists between families. Different structures evolve as locally stable attractors. The probabilities of formation and collapse of complex structures depend on the number of families and the mutation rate, showing characteristic scaling relationships. It is now possible to explore macroscopic kinship structures based on microscopic interactions, together with their environmental dependence and the historical causality of their evolution. We propose the basic causal mechanism of the formation of typical human social structures by referring to ethnographic observations and concepts from statistical physics and multilevel evolution. Such interdisciplinary collaboration will unveil universal features in human societies.

Somatic cells accumulate genomic alterations with age; however, our understanding of mitochondrial DNA (mtDNA) mosaicism remains limited. Here we investigated the genomes of 2,096 clones derived from three cell types across 31 donors, identifying 6,451 mtDNA variants with heteroplasmy levels of ≳0.3%. While the majority of these variants were unique to individual clones, suggesting stochastic acquisition with age, 409 variants (6%) were shared across multiple embryonic lineages, indicating their origin from heteroplasmy in fertilized eggs. The mutational spectrum exhibited replication-strand bias, implicating mtDNA replication as a major mutational process. We evaluated the mtDNA mutation rate (5.0 × 10-8 per base pair) and a turnover frequency of 10-20 per year, which are fundamental components shaping the landscape of mtDNA mosaicism over a lifetime. The expansion of mtDNA-truncating mutations toward homoplasmy was substantially suppressed. Our findings provide comprehensive insights into the origins, dynamics and functional consequences of mtDNA mosaicism in human somatic cells.

During each cell cycle, the process of DNA replication timing is tightly regulated to ensure the accurate duplication of the genome. The extent and significance of alterations in this process during malignant transformation have not been extensively explored. Here, we assess the impact of altered replication timing (ART) on cancer evolution by analysing replication-timing sequencing of cancer and normal cell lines and 952 whole-genome sequenced lung and breast tumours. We find that 6%-18% of the cancer genome exhibits ART, with regions with a change from early to late replication displaying an increased mutation rate and distinct mutational signatures. Whereas regions changing from late to early replication contain genes with increased expression and present a preponderance of APOBEC3-mediated mutation clusters and associated driver mutations. We demonstrate that ART occurs relatively early during cancer evolution and that ART may have a stronger correlation with mutation acquisition than alterations in chromatin structure.

The best predictive marker for the expected efficacy of PARP inhibitor therapy is mutations in BRCA1/2 or other homologous recombination repair genes. These tests are part of routine molecular pathology diagnostics. Among 281 patients with prostate adenocarcinoma, somatic pathogenic mutations in one of these genes were identified in 21.4% of patients. In 28.5% of the patients, the test was unsuccessful; the main limitation of successful testing was the age of the paraffin blocks and low DNA concentration. In the case of BRCA1/2 testing, the success rate was significantly reduced for samples older than 5 years, while in tests involving a broader set of homologous recombination repair genes, the success rate was significantly reduced for samples older than 2 years. Therefore, it is very important to test high-risk prostate cancers at the time of primary diagnosis, and probably also liquid biopsy testing of circulating tumor DNA will play an important role in safe diagnosis in the near future.

Mutagenesis is responsive to many environmental factors. Evolution therefore depends on the environment not only for selection but also in determining the variation available in a population. One such environmental dependency is the inverse relationship between mutation rates and population density in many microbial species. Here, we determine the mechanism responsible for this mutation rate plasticity. Using dynamical computational modelling and in culture mutation rate estimation, we show that the negative relationship between mutation rate and population density arises from the collective ability of microbial populations to control concentrations of hydrogen peroxide. We demonstrate a loss of this density-associated mutation rate plasticity (DAMP) when Escherichia coli populations are deficient in the degradation of hydrogen peroxide. We further show that the reduction in mutation rate in denser populations is restored in peroxide degradation-deficient cells by the presence of wild-type cells in a mixed population. Together, these model-guided experiments provide a mechanistic explanation for DAMP, applicable across all domains of life, and frames mutation rate as a dynamic trait shaped by microbial community composition.

High spontaneous mutation rate is crucial for obtaining ideal phenotype and exploring the relationship between genes and phenotype. How to break the genetic stability of organisms and increase the mutation frequency has become a research hotspot. Here, we present a practical and controllable evolutionary tool (oMut-Cgts) based on dual genetic level modification engineering for Corynebacterium glutamicum. Firstly, the modification engineering of transcription and replication levels based on RNA polymerase α subunit and DNA helicase Cgl0854 as the \'dock\' of cytidine deaminase (pmCDA1) significantly increased the mutation rate, proving that the localization of pmCDA1 around transient ssDNA is necessary for genome mutation. Then, the combined modification and optimization of engineering at dual genetic level achieved 1.02 × 104-fold increased mutation rate. The genome sequencing revealed that the oMut-Cgts perform uniform and efficient C:G→T:A transitions on a genome-wide scale. Furthermore, oMut-Cgts-mediated rapid evolution of C. glutamicum with stress (acid, oxidative and ethanol) tolerance proved that the tool has powerful functions in multi-dimensional biological engineering (rapid phenotype evolution, gene function mining and protein evolution). The strategies for rapid genome evolution provided in this study are expected to be applicable to a variety of applications in all prokaryotic cells.

Mismatch repair (MMR)-deficient cancer evolves through the stepwise erosion of coding homopolymers in target genes. Curiously, the MMR genes MutS homolog 6 (MSH6) and MutS homolog 3 (MSH3) also contain coding homopolymers, and these are frequent mutational targets in MMR-deficient cancers. The impact of incremental MMR mutations on MMR-deficient cancer evolution is unknown. Here we show that microsatellite instability modulates DNA repair by toggling hypermutable mononucleotide homopolymer runs in MSH6 and MSH3 through stochastic frameshift switching. Spontaneous mutation and reversion modulate subclonal mutation rate, mutation bias and HLA and neoantigen diversity. Patient-derived organoids corroborate these observations and show that MMR homopolymer sequences drift back into reading frame in the absence of immune selection, suggesting a fitness cost of elevated mutation rates. Combined experimental and simulation studies demonstrate that subclonal immune selection favors incremental MMR mutations. Overall, our data demonstrate that MMR-deficient colorectal cancers fuel intratumor heterogeneity by adapting subclonal mutation rate and diversity to immune selection.

Plant cells harbor two membrane-bound organelles containing their own genetic material-plastids and mitochondria. Although the two organelles coexist and coevolve within the same plant cells, they differ in genome copy number, intracellular organization, and mode of segregation. How these attributes affect the time to fixation or, conversely, loss of neutral alleles is currently unresolved. Here, we show that mitochondria and plastids share the same mutation rate, yet plastid alleles remain in a heteroplasmic state significantly longer compared with mitochondrial alleles. By analyzing genetic variants across populations of the marine flowering plant Zostera marina and simulating organelle allele dynamics, we examine the determinants of allele segregation and allele fixation. Our results suggest that the bottlenecks on the cell population, e.g. during branching or seeding, and stratification of the meristematic tissue are important determinants of mitochondrial allele dynamics. Furthermore, we suggest that the prolonged plastid allele dynamics are due to a yet unknown active plastid partition mechanism. The dissimilarity between plastid and mitochondrial novel allele fixation at different levels of organization may manifest in differences in adaptation processes. Our study uncovers fundamental principles of organelle population genetics that are essential for further investigations of long-term evolution and molecular dating of divergence events.

The mutation rate is a pivotal biological characteristic, intricately governed by natural selection and historically garnering considerable attention. Recent advances in high-throughput sequencing and analytical methodologies have profoundly transformed our understanding in this domain, ushering in an unprecedented era of mutation rate research. This paper aims to provide a comprehensive overview of the key concepts and methodologies frequently employed in the study of mutation rates. It examines various types of mutations, explores the evolutionary dynamics and associated theories, and synthesizes both classical and contemporary hypotheses. Furthermore, this review comprehensively explores recent advances in understanding germline and somatic mutations in animals and offers an overview of experimental methodologies, mutational patterns, molecular mechanisms, and driving forces influencing variations in mutation rates across species and tissues. Finally, it proposes several potential research directions and pressing questions for future investigations.
突变率是生命演化过程中的一个重要参数。它受到自然选的择精细调控，因此在演化生物学的研究历史上备受关注。近年来，随着高通量测序的发展和突变分析方法的进步，我们对突变率的理解有了显著地加深，突变的研究进入了一个前所未有的新时代。该文总结和讨论了突变研究中常见的演化生物学概念和经典的理论方法：我们首先详细介绍了突变的类型；之后，在此基础上探索前人提出的与演化动力学相关的理论模型；最后对经典假说与当代理论进行深入探讨和比较。此外，该文全面总结了动物生殖细胞和体细胞突变的最新进展：我们概述了这些研究过程中使用的实验方法、突变模式、突变的分子机制以及影响突变率变化的因素，并探讨了物种间和相同个体不同组织间突变率的差异。最终，我们概述了突变研究中未来潜在的研究方向和亟待解决的科学问题。.

Antiviral therapy is constantly challenged by the emergence of resistant pathogens. At the same time, experimental approaches to understand and predict resistance are limited by long periods required for evolutionary processes. Here, we present a herpes simplex virus 1 mutant with impaired proofreading capacity and consequently elevated mutation rates. Comparing this hypermutator to parental wild type virus, we study the evolution of antiviral drug resistance in vitro. We model resistance development and elucidate underlying genetic changes against three antiviral substances. Our analyzes reveal no principle difference in the evolutionary behavior of both viruses, adaptive processes are overall similar, however significantly accelerated for the hypermutator. We conclude that hypermutator viruses are useful for modeling adaptation to antiviral therapy. They offer the benefit of expedited adaptation without introducing apparent bias and can therefore serve as an accelerator to predict natural evolution.