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Cellular and Molecular Life Sciences :... Dec 2016The remarkable capacity of some viruses to adapt to new hosts and environments is highly dependent on their ability to generate de novo diversity in a short period of... (Review)
Review
The remarkable capacity of some viruses to adapt to new hosts and environments is highly dependent on their ability to generate de novo diversity in a short period of time. Rates of spontaneous mutation vary amply among viruses. RNA viruses mutate faster than DNA viruses, single-stranded viruses mutate faster than double-strand virus, and genome size appears to correlate negatively with mutation rate. Viral mutation rates are modulated at different levels, including polymerase fidelity, sequence context, template secondary structure, cellular microenvironment, replication mechanisms, proofreading, and access to post-replicative repair. Additionally, massive numbers of mutations can be introduced by some virus-encoded diversity-generating elements, as well as by host-encoded cytidine/adenine deaminases. Our current knowledge of viral mutation rates indicates that viral genetic diversity is determined by multiple virus- and host-dependent processes, and that viral mutation rates can evolve in response to specific selective pressures.
Topics: Genome, Viral; Mutation; Mutation Rate; Recombination, Genetic; Virus Replication; Viruses
PubMed: 27392606
DOI: 10.1007/s00018-016-2299-6 -
Nature Reviews. Genetics Oct 2016As one of the few cellular traits that can be quantified across the tree of life, DNA-replication fidelity provides an excellent platform for understanding fundamental... (Review)
Review
As one of the few cellular traits that can be quantified across the tree of life, DNA-replication fidelity provides an excellent platform for understanding fundamental evolutionary processes. Furthermore, because mutation is the ultimate source of all genetic variation, clarifying why mutation rates vary is crucial for understanding all areas of biology. A potentially revealing hypothesis for mutation-rate evolution is that natural selection primarily operates to improve replication fidelity, with the ultimate limits to what can be achieved set by the power of random genetic drift. This drift-barrier hypothesis is consistent with comparative measures of mutation rates, provides a simple explanation for the existence of error-prone polymerases and yields a formal counter-argument to the view that selection fine-tunes gene-specific mutation rates.
Topics: Biological Evolution; Genetic Drift; Genetic Variation; Humans; Models, Genetic; Mutation Rate; Selection, Genetic
PubMed: 27739533
DOI: 10.1038/nrg.2016.104 -
Genome Research Nov 2018Numerous large-scale genomic studies of matched tumor-normal samples have established the somatic landscapes of most cancer types. However, the downstream analysis of...
Numerous large-scale genomic studies of matched tumor-normal samples have established the somatic landscapes of most cancer types. However, the downstream analysis of data from somatic mutations entails a number of computational and statistical approaches, requiring usage of independent software and numerous tools. Here, we describe an R Bioconductor package, Maftools, which offers a multitude of analysis and visualization modules that are commonly used in cancer genomic studies, including driver gene identification, pathway, signature, enrichment, and association analyses. Maftools only requires somatic variants in Mutation Annotation Format (MAF) and is independent of larger alignment files. With the implementation of well-established statistical and computational methods, Maftools facilitates data-driven research and comparative analysis to discover novel results from publicly available data sets. In the present study, using three of the well-annotated cohorts from The Cancer Genome Atlas (TCGA), we describe the application of Maftools to reproduce known results. More importantly, we show that Maftools can also be used to uncover novel findings through integrative analysis.
Topics: Clonal Evolution; Humans; Mutation Rate; Neoplasms; Sequence Analysis, DNA; Software
PubMed: 30341162
DOI: 10.1101/gr.239244.118 -
The New Phytologist Feb 2019Contents Summary 1253 I. Introduction 1253 II. What is the rate and molecular spectrum of spontaneous epimutations? 1254 III. Do spontaneous epimutations have phenotypic... (Review)
Review
Contents Summary 1253 I. Introduction 1253 II. What is the rate and molecular spectrum of spontaneous epimutations? 1254 III. Do spontaneous epimutations have phenotypic consequences? 1257 IV. Conclusion and discussion 1258 Acknowledgements 1258 References 1258 SUMMARY: Heritable gains or losses of cytosine methylation can arise stochastically in plant genomes independently of DNA sequence changes. These so-called 'spontaneous epimutations' appear to be a byproduct of imperfect DNA methylation maintenance and epigenome reinforcement events that occur in specialized cell types. There is continued interest in the plant epigenetics community in trying to understand the broader implications of these stochastic events, as some have been shown to induce heritable gene expression changes, shape patterns of methylation diversity within and among plant populations, and appear to be responsive to multi-generational environmental stressors. In this paper we synthesized our current knowledge of the molecular basis and functional consequences of spontaneous epimutations in plants, discuss technical and conceptual challenges, and highlight emerging research directions.
Topics: Epigenesis, Genetic; Genetic Loci; Mutation; Mutation Rate; Phenotype; Plants
PubMed: 30216456
DOI: 10.1111/nph.15434 -
Journal of Theoretical Biology Sep 2023The cost of germline maintenance gives rise to a trade-off between lowering the deleterious mutation rate and investing in life history functions. Therefore, life...
The cost of germline maintenance gives rise to a trade-off between lowering the deleterious mutation rate and investing in life history functions. Therefore, life history and the mutation rate coevolve, but this coevolution is not well understood. We develop a mathematical model to analyse the evolution of resource allocation traits, which simultaneously affect life history and the deleterious mutation rate. First, we show that the invasion fitness of such resource allocation traits can be approximated by the basic reproductive number of the least-loaded class; the expected lifetime production of offspring without deleterious mutations born to individuals without deleterious mutations. Second, we apply the model to investigate (i) the coevolution of reproductive effort and germline maintenance and (ii) the coevolution of age-at-maturity and germline maintenance. This analysis provides two resource allocation predictions when exposure to environmental mutagens is higher. First, selection favours higher allocation to germline maintenance, even if it comes at the expense of life history functions, and leads to a shift in allocation towards reproduction rather than survival. Second, life histories tend to be faster, characterised by individuals with shorter lifespans and smaller body sizes at maturity. Our results suggest that mutation accumulation via the cost of germline maintenance can be a major force shaping life-history traits.
Topics: Humans; Mutation Rate; Basic Reproduction Number; Body Size; Life History Traits; Mutation Accumulation
PubMed: 37598761
DOI: 10.1016/j.jtbi.2023.111598 -
Journal of Virology Jul 2018Many viruses evolve rapidly. This is due, in part, to their high mutation rates. Mutation rate estimates for over 25 viruses are currently available. Here, we review the... (Review)
Review
Many viruses evolve rapidly. This is due, in part, to their high mutation rates. Mutation rate estimates for over 25 viruses are currently available. Here, we review the population genetics of virus mutation rates. We specifically cover the topics of mutation rate estimation, the forces that drive the evolution of mutation rates, and how the optimal mutation rate can be context-dependent.
Topics: Evolution, Molecular; Humans; Mutation; Mutation Rate; Virus Replication; Viruses
PubMed: 29720522
DOI: 10.1128/JVI.01031-17 -
Signal Transduction and Targeted Therapy Aug 2022
Topics: Longevity; Mutation Rate
PubMed: 35961971
DOI: 10.1038/s41392-022-01122-8 -
The New Phytologist Mar 2023Genetic mutations provide the heritable material for plant adaptation to their environments. At the same time, the environment can affect the mutation rate across plant... (Review)
Review
Genetic mutations provide the heritable material for plant adaptation to their environments. At the same time, the environment can affect the mutation rate across plant genomes. However, the extent to which environmental plasticity in mutation rates can facilitate or hinder adaptation remains a longstanding and unresolved question. Emerging discoveries of mechanisms affecting mutation rate variability provide opportunities to consider this question in a new light. Links between chromatin states, transposable elements, and DNA repair suggest cases of adaptive mutation rate plasticity could occur. Yet, numerous evolutionary and biological forces are expected to limit the impact of any such mutation rate plasticity on adaptive evolution. Persistent uncertainty about the significance of mutation rate plasticity on adaptation motivates new experimental and theoretical research relevant to understanding plant responses in changing environments.
Topics: Mutation Rate; Biological Evolution; Adaptation, Physiological; Mutation; Genome, Plant; Plants
PubMed: 36444532
DOI: 10.1111/nph.18640 -
Cells Jan 2024Driver mutations are considered the cornerstone of cancer initiation. They are defined as mutations that convey a competitive fitness advantage, and hence, their... (Review)
Review
Driver mutations are considered the cornerstone of cancer initiation. They are defined as mutations that convey a competitive fitness advantage, and hence, their mutation frequency in premalignant tissue is expected to exceed the basal mutation rate. In old terms, that translates to "the survival of the fittest" and implies that a selective process underlies the frequency of cancer driver mutations. In that sense, each tissue is its own niche that creates a molecular selective pressure that may favor the propagation of a mutation or not. At the heart of this stands one of the biggest riddles in cancer biology: the tissue-predisposition to cancer driver mutations. The frequency of cancer driver mutations among tissues is non-uniform: for instance, mutations in are particularly frequent in colorectal cancer, and 99% of chronic myeloid leukemia patients harbor the driver fusion mutation, which is rarely found in solid tumors. Here, we provide a mechanistic framework that aims to explain how tissue-specific features, ranging from epigenetic underpinnings to the expression of viral transposable elements, establish a molecular basis for selecting cancer driver mutations in a tissue-specific manner.
Topics: Humans; Precancerous Conditions; Disease Susceptibility; Leukemia, Myelogenous, Chronic, BCR-ABL Positive; Mutation; Mutation Rate
PubMed: 38247798
DOI: 10.3390/cells13020106 -
Current Opinion in Genetics &... Jun 2020Germline mutations are the source of all heritable variation. In the past few years, whole genome sequencing has allowed direct and comprehensive surveys of mutation... (Review)
Review
Germline mutations are the source of all heritable variation. In the past few years, whole genome sequencing has allowed direct and comprehensive surveys of mutation patterns in humans and other species. These studies have documented substantial variation in both mutation rates and spectra across primates, the causes of which remain unclear. Here, we review what is currently known about mutation rates in primates, highlight the factors proposed to explain the variation across species, and discuss some implications of these findings on our understanding of the chronology of primate evolution and the process of mutagenesis.
Topics: Animals; Biological Evolution; Genome; Genomics; Mutation; Mutation Rate; Primates
PubMed: 32634682
DOI: 10.1016/j.gde.2020.05.028