Mutational Bias Research Articles

Interdisciplinary approaches to predicting evolutionary biology.

Interdisciplinary approaches to predicting evolutionary biology.

Transient mutation bias increases the predictability of evolution on an empirical genotype-phenotype landscape.

Predicting how a population will likely navigate a genotype-phenotype landscape requires consideration of selection in combination with mutation bias, which can skew the likelihood of following a particular trajectory. Strong and persistent directional selection can drive populations to ascend toward a peak. However, with a greater number of peaks and more routes to reach them, adaptation inevitably becomes less predictable. Transient mutation bias, which operates only on one mutational step, can influence landscape navigability by biasing the mutational trajectory early in the adaptive walk. This sets an evolving population upon a particular path, constraining the number of accessible routes and making certain peaks and routes more likely to be realized than others. In this work, we employ a model system to investigate whether such transient mutation bias can reliably and predictably place populations on a mutational trajectory to the strongest selective phenotype or usher populations to realize inferior phenotypic outcomes. For this we use motile mutants evolved from ancestrally non-motile variants of the microbe Pseudomonas fluorescens SBW25, of which one trajectory exhibits significant mutation bias. Using this system, we elucidate an empirical genotype-phenotype landscape, where the hill-climbing process represents increasing strength of the motility phenotype, to reveal that transient mutation bias can facilitate rapid and predictable ascension to the strongest observed phenotype in place of equivalent and inferior trajectories. This article is part of the theme issue 'Interdisciplinary approaches to predicting evolutionary biology'.

Mutation bias and the predictability of evolution.

Predicting evolutionary outcomes is an important research goal in a diversity of contexts. The focus of evolutionary forecasting is usually on adaptive processes, and efforts to improve prediction typically focus on selection. However, adaptive processes often rely on new mutations, which can be strongly influenced by predictable biases in mutation. Here, we provide an overview of existing theory and evidence for such mutation-biased adaptation and consider the implications of these results for the problem of prediction, in regard to topics such as the evolution of infectious diseases, resistance to biochemical agents, as well as cancer and other kinds of somatic evolution. We argue that empirical knowledge of mutational biases is likely to improve in the near future, and that this knowledge is readily applicable to the challenges of short-term prediction. This article is part of the theme issue 'Interdisciplinary approaches to predicting evolutionary biology'.

Mutational Bias and Natural Selection Driving the Synonymous Codon Usage of Single-Exon Genes in Rice (Oryza sativa L.)

The relative abundance of single-exon genes (SEGs) in higher plants is perplexing. Uncovering the synonymous codon usage pattern of SEGs will benefit for further understanding their underlying evolutionary mechanism in plants. Using internal correspondence analysis (ICA), we reveal a significant difference in synonymous codon usage between SEGs and multiple-exon genes (MEGs) in rice. But the effect is weak, accounting for only 2.61% of the total codon usage variability. SEGs and MEGs contain remarkably different base compositions, and are under clearly differential selective constraints, with the former having higher GC content, and evolving relatively faster during evolution. In the group of SEGs, the variability in synonymous codon usage among genes is partially due to the variations in GC content, gene function, and gene expression level, which accounts for 22.03%, 5.99%, and 3.32% of the total codon usage variability, respectively. Therefore, mutational bias and natural selection should work on affecting the synonymous codon usage of SEGs in rice. These findings may deepen our knowledge for the mechanisms of origination, differentiation and regulation of SEGs in plants.

SNP-based Computational Analysis Reveals Recombination-associated Genome Evolution in Humans

Background: Meiotic recombination is an important source of genetic variation, but how recombination shapes the genome is not clearly understood yet. Objective: Here, we investigate the roles of recombination on human genome evolution from two aspects: How does recombination shape single nucleotide polymorphism (SNP)-related genomic variation features? Whether recombination drives genome evolution through a neighbor-dependent mutational bias? Methods: We analyzed the relationship of recombination rate with mutational bias and selection effect at SNP sites derived from the 1000 Genomes Project. Results: Our results show that SNP density, Ts/Tv, nucleotide diversity, and Tajima's D were positively correlated with the recombination rate, while Ka/Ks were negatively correlated with the recombination rate. Moreover, compared with non-coding regions, gene exonic regions have lower nucleotide diversity but higher Tajima's D, suggesting that coding regions are subject to stronger negative selection but have fewer rare alleles. Gene set enrichment analysis of the protein-coding genes with extreme Ka/Ks ratio implies that under the effect of high recombination rates, the genes involved in the cell cycle, RNA processing, and oocyte meiosis are subject to strong negative selection. Our data also support S (G or C) > W (A or T) mutational bias and W>S fixation bias in high recombination regions. In addition, the neighbor-dependent mutational bias was found to be stronger at high recombination regions. Conclusion: Our data suggest that genetic variation patterns, particularly the neighbor-dependent mutational bias at SNP sites in the human genome, are mediated by recombination.

Biased mutations and gene losses underlying diploidization of the tetraploid broomcorn millet genome.

Broomcorn millet (Panicum miliaceum L.) is one of the earliest domesticated crops, and is a valuable resource to secure food diversity and combat drought stresses under the global warming scenario. However, due to the absence of extant diploid progenitors, the polyploidy genome of broomcorn millet remains poorly understood. Here, we report the chromosome-scale genome assembly of broomcorn millet. We divided the broomcorn millet genome into two subgenomes using the genome sequence of Panicum hallii, a diploid relative of broomcorn millet. Our analyses revealed that the two subgenomes diverged at ~4.8million years ago (Mya), while the allotetraploidization of broomcorn millet may have occurred about ~0.48Mya, suggesting that broomcorn millet is a relatively recent allotetraploid. Comparative analyses showed that subgenome B was larger than subgenome A in size, which was caused by the biased accumulation of long terminal repeat retrotransposons in the progenitor of subgenome B before polyploidization. Notably, the accumulation of biased mutations in the transposable element-rich subgenome B led to more gene losses. Although no significant dominance of either subgenome was observed in the expression profiles of broomcorn millet, we found the minimally expressed genes in P. hallii tended to be lost during diploidization of broomcorn millet. These results suggest that broomcorn millet is at the early stage of diploidization and that mutations likely occurred more on genes that were marked with lower expression levels.

Transcriptional and mutational signatures of the Drosophila ageing germline.

Ageing is a complex biological process that is accompanied by changes in gene expression and mutational load. In many species, including humans, older fathers pass on more paternally derived de novo mutations; however, the cellular basis and cell types driving this pattern are still unclear. To explore the root causes of this phenomenon, we performed single-cell RNA sequencing on testes from young and old male Drosophila and genomic sequencing (DNA sequencing) on somatic tissues from the same flies. We found that early germ cells from old and young flies enter spermatogenesis with similar mutational loads but older flies are less able to remove mutations during spermatogenesis. Mutations in old cells may also increase during spermatogenesis. Our data reveal that old and young flies have distinct mutational biases. Many classes of genes show increased postmeiotic expression in the germlines of older flies. Late spermatogenesis-biased genes have higher dN/dS (ratio of non-synonymous to synonymous substitutions) than early spermatogenesis-biased genes, supporting the hypothesis that late spermatogenesis is a source of evolutionary innovation. Surprisingly, genes biased in young germ cells show higher dN/dS than genes biased in old germ cells. Our results provide new insights into the role of the germline in de novo mutation.

Supply-driven evolution: Mutation bias and trait-fitness distributions can drive macro-evolutionary dynamics

Many well-documented macro-evolutionary phenomena still challenge current evolutionary theory. Examples include long-term evolutionary trends, major transitions in evolution, conservation of certain biological features such ashoxgenes, and the episodic creation of new taxa. Here, we present a framework that may explain these phenomena. We do so by introducing a probabilistic relationship between trait value and reproductive fitness. This integration allows mutation bias to become a robust driver of long-term evolutionary trends against environmental bias, in a way that is consistent with all current evolutionary theories. In cases where mutation bias is strong, such as when detrimental mutations are more common than beneficial mutations, a regime called “supply-driven” evolution can arise. This regime can explain the irreversible persistence of higher structural hierarchies, which happens in the major transitions in evolution. We further generalize this result in the long-term dynamics of phenotype spaces. We show how mutations that open new phenotype spaces can become frozen in time. At the same time, new possibilities may be observed as a burst in the creation of new taxa.

Atypical Mutational Spectrum of SARS-CoV-2 Replicating in the Presence of Ribavirin.

We report that ribavirin exerts an inhibitory and mutagenic activity on SARS-CoV-2-infecting Vero cells, with a therapeutic index higher than 10. Deep sequencing analysis of the mutant spectrum of SARS-CoV-2 replicating in the absence or presence of ribavirin indicated an increase in the number of mutations, but not in deletions, and modification of diversity indices, expected from a mutagenic activity. Notably, the major mutation types enhanced by replication in the presence of ribavirin were A→G and U→C transitions, a pattern which is opposite to the dominance of G→A and C→U transitions previously described for most RNA viruses. Implications of the inhibitory activity of ribavirin, and the atypical mutational bias produced on SARS-CoV-2, for the search for synergistic anti-COVID-19 lethal mutagen combinations are discussed.

Mutational signature of mtDNA confers mechanistic insight into oxidative metabolism remodeling in colorectal cancer.

Rationale: Mitochondrial dysfunction caused by mitochondrial DNA (mtDNA) mutations and subsequent metabolic defects are closely involved in tumorigenesis and progression in a cancer-type specific manner. To date, the mutational pattern of mtDNA somatic mutations in colorectal cancer (CRC) tissues and its clinical implication are still not completely clear. Methods: In the present study, we generated a large mtDNA somatic mutation dataset from three CRC cohorts (432, 1,015, and 845 patients, respectively) and then most comprehensively characterized the CRC-specific evolutionary pattern and its clinical implication. Results: Our results showed that the mtDNA control region (mtCTR) with a high mutation density exhibited a distinct mutation spectrum characterizing a high enrichment of L-strand C > T mutations, which was contrary to the H-strand C > T mutational bias observed in the mtDNA coding region (mtCDR) (P < 0.001). Further analysis clearly confirmed the relaxed evolutionary selection of mtCTR mutations, which was mainly characterized by the similar distribution of hypervariable region (HVS) and non-HVS mutation density. Moreover, significant negative selection was identified in mutations of mtDNA complex V (ATP6/ATP8) and tRNA loop regions. Although our data showed that oxidative metabolism was commonly increased in CRC cells, mtDNA somatic mutations in CRC tissues were not closely associated with mitochondrial biogenesis, oxidative metabolism, and clinical progression, suggesting a cancer-type specific relationship between mtDNA mutations and mitochondrial metabolic functions in CRC cells. Conclusion: Our study identified the CRC-specific evolutionary mode of mtDNA mutations, which is possibly matched to specific mitochondrial metabolic remodeling and confers new mechanic insight into CRC tumorigenesis.

Genomic Legacies of Ancient Adaptation Illuminate GC-Content Evolution in Bacteria.

Bacterial evolution is characterized by strong purifying selection as well as rapid adaptive evolution in changing environments. In this context, the genomic GC content (genomic GC) varies greatly but presents some level of phylogenetic stability, making it challenging to explain based on current hypotheses. To illuminate the evolutionary mechanisms of the genomic GC, we analyzed the base composition and functional inventory of 11,083 representative genomes. A phylogenetically constrained bimodal distribution of the genomic GC, which mainly originated from parallel divergences in the early evolution, was demonstrated. Such variation of the genomic GC can be well explained by DNA replication and repair (DRR), in which multiple pathways correlate with the genomic GC. Furthermore, the biased conservation of various stress-related genes, especially the DRR-related ones, implies distinct adaptive processes in the ancestral lineages of high- or low-GC clades which are likely induced by major environmental changes. Our findings support that the mutational biases resulting from these legacies of ancient adaptation have changed the course of adaptive evolution and generated great variation in the genomic GC. This highlights the importance of indirect effects of natural selection, which indicates a new model for bacterial evolution. IMPORTANCE GC content has been shown to be an important factor in microbial ecology and evolution, and the genomic GC of bacteria can be characterized by great intergenomic heterogeneity, high intragenomic homogeneity, and strong phylogenetic inertia, as well as being associated with the environment. Current hypotheses concerning direct selection or mutational biases cannot well explain these features simultaneously. Our findings of the genomic GC showing that ancient adaptations have transformed the DRR system and that the resulting mutational biases further contributed to a bimodal distribution of it offer a more reasonable scenario for the mechanism. This would imply that, when thinking about the evolution of life, diverse processes of adaptation exist, and combined effects of natural selection should be considered.

A bias of Asparagine to Lysine mutations in SARS-CoV-2 outside the receptor binding domain affects protein flexibility.

COVID-19 pandemic has been threatening public health and economic development worldwide for over two years. Compared with the original SARS-CoV-2 strain reported in 2019, the Omicron variant (B.1.1.529.1) is more transmissible. This variant has 34 mutations in its Spike protein, 15 of which are present in the Receptor Binding Domain (RBD), facilitating viral internalization via binding to the angiotensin-converting enzyme 2 (ACE2) receptor on endothelial cells as well as promoting increased immune evasion capacity. Herein we compared SARS-CoV-2 proteins (including ORF3a, ORF7, ORF8, Nucleoprotein (N), membrane protein (M) and Spike (S) proteins) from multiple ancestral strains. We included the currently designated original Variant of Concern (VOC) Omicron, its subsequent emerged variants BA.1, BA2, BA3, BA.4, BA.5, the two currently emerging variants BQ.1 and BBX.1, and compared these with the previously circulating VOCs Alpha, Beta, Gamma, and Delta, to better understand the nature and potential impact of Omicron specific mutations. Only in Omicron and its subvariants, a bias toward an Asparagine to Lysine (N to K) mutation was evident within the Spike protein, including regions outside the RBD domain, while none of the regions outside the Spike protein domain were characterized by this mutational bias. Computational structural analysis revealed that three of these specific mutations located in the central core region, contribute to a preference for the alteration of conformations of the Spike protein. Several mutations in the RBD which have circulated across most Omicron subvariants were also analysed, and these showed more potential for immune escape. This study emphasizes the importance of understanding how specific N to K mutations outside of the RBD region affect SARS-CoV-2 conformational changes and the need for neutralizing antibodies for Omicron to target a subset of conformationally dependent B cell epitopes.

Competition for DNA binding between the genome protector replication protein A and the genome modifying APOBEC3 single-stranded DNA deaminases.

The human APOBEC family of eleven cytosine deaminases use RNA and single-stranded DNA (ssDNA) as substrates to deaminate cytosine to uracil. This deamination event has roles in lipid metabolism by altering mRNA coding, adaptive immunity by causing evolution of antibody genes, and innate immunity through inactivation of viral genomes. These benefits come at a cost where some family members, primarily from the APOBEC3 subfamily (APOBEC3A-H, excluding E), can cause off-target deaminations of cytosine to form uracil on transiently single-stranded genomic DNA, which induces mutations that are associated with cancer evolution. Since uracil is only promutagenic, the mutations observed in cancer genomes originate only when uracil is not removed by uracil DNA glycosylase (UNG) or when the UNG-induced abasic site is erroneously repaired. However, when ssDNA is present, replication protein A (RPA) binds and protects the DNA from nucleases or recruits DNA repair proteins, such as UNG. Thus, APOBEC enzymes must compete with RPA to access their substrate. Certain APOBEC enzymes can displace RPA, bind and scan ssDNA efficiently to search for cytosines, and can become highly overexpressed in tumor cells. Depending on the DNA replication conditions and DNA structure, RPA can either be in excess or deficient. Here we discuss the interplay between these factors and how despite RPA, multiple cancer genomes have a mutation bias at cytosines indicative of APOBEC activity.

Prediction of Recurrent Mutations in SARS-CoV-2 Using Artificial Neural Networks

Predicting SARS-CoV-2 mutations is difficult, but predicting recurrent mutations driven by the host, such as those caused by host deaminases, is feasible. We used machine learning to predict which positions from the SARS-CoV-2 genome will hold a recurrent mutation and which mutations will be the most recurrent. We used data from April 2021 that we separated into three sets: a training set, a validation set, and an independent test set. For the test set, we obtained a specificity value of 0.69, a sensitivity value of 0.79, and an Area Under the Curve (AUC) of 0.8, showing that the prediction of recurrent SARS-CoV-2 mutations is feasible. Subsequently, we compared our predictions with updated data from January 2022, showing that some of the false positives in our prediction model become true positives later on. The most important variables detected by the model's Shapley Additive exPlanation (SHAP) are the nucleotide that mutates and RNA reactivity. This is consistent with the SARS-CoV-2 mutational bias pattern and the preference of some host deaminases for specific sequences and RNA secondary structures. We extend our investigation by analyzing the mutations from the variants of concern Alpha, Beta, Delta, Gamma, and Omicron. Finally, we analyzed amino acid changes by looking at the predicted recurrent mutations in the M-pro and spike proteins.

Integrated gene analyses of de novo variants from 46,612 trios with autism and developmental disorders

Most genetic studies consider autism spectrum disorder (ASD) and developmental disorder (DD) separately despite overwhelming comorbidity and shared genetic etiology. Here, we analyzed de novo variants (DNVs) from 15,560 ASD (6,557 from SPARK) and 31,052 DD trios independently and also combined as broader neurodevelopmental disorders (NDDs) using three models. We identify 615 NDD candidate genes (false discovery rate [FDR] < 0.05) supported by ≥1 models, including 138 reaching Bonferroni exome-wide significance (P < 3.64e-7) in all models. The genes group into five functional networks associating with different brain developmental lineages based on single-cell nuclei transcriptomic data. We find no evidence for ASD-specific genes in contrast to 18 genes significantly enriched for DD. There are 53 genes that show mutational bias, including enrichments for missense (n = 41) or truncating (n = 12) DNVs. We also find 10 genes with evidence of male- or female-bias enrichment, including 4 X chromosome genes with significant female burden (DDX3X, MECP2, WDR45, and HDAC8). This large-scale integrative analysis identifies candidates and functional subsets of NDD genes.

Evolutionary dynamics of pseudoautosomal region 1 in humans and great apes

BackgroundThe pseudoautosomal region 1 (PAR1) is a 2.7 Mb telomeric region of human sex chromosomes. PAR1 has a crucial role in ensuring proper segregation of sex chromosomes during male meiosis, exposing it to extreme recombination and mutation processes. We investigate PAR1 evolution using population genomic datasets of extant humans, eight populations of great apes, and two archaic human genome sequences.ResultsWe find that PAR1 is fast evolving and closer to evolutionary nucleotide equilibrium than autosomal telomeres. We detect a difference between substitution patterns and extant diversity in PAR1, mainly driven by the conflict between strong mutation and recombination-associated fixation bias at CpG sites. We detect excess C-to-G mutations in PAR1 of all great apes, specific to the mutagenic effect of male recombination. Despite recent evidence for Y chromosome introgression from humans into Neanderthals, we find that the Neanderthal PAR1 retained similarity to the Denisovan sequence. We find differences between substitution spectra of these archaics suggesting rapid evolution of PAR1 in recent hominin history. Frequency analysis of alleles segregating in females and males provided no evidence for recent sexual antagonism in this region. We study repeat content and double-strand break hotspot regions in PAR1 and find that they may play roles in ensuring the obligate X-Y recombination event during male meiosis.ConclusionsOur study provides an unprecedented quantification of population genetic forces governing PAR1 biology across extant and extinct hominids. PAR1 evolutionary dynamics are predominantly governed by recombination processes with a strong impact on mutation patterns across all species.

Examining the Effects of Hibernation on Germline Mutation Rates in Grizzly Bears.

A male mutation bias is observed across vertebrates, and, where data are available, this bias is accompanied by increased per-generation mutation rates with parental age. While continuing mitotic cell division in the male germline post puberty has been proposed as the major cellular mechanism underlying both patterns, little direct evidence for this role has been found. Understanding the evolution of the per-generation mutation rate among species requires that we identify the molecular mechanisms that change between species. Here, we study the per-generation mutation rate in an extended pedigree of the brown (grizzly) bear, Ursus arctos horribilis. Brown bears hibernate for one-third of the year, a period during which spermatogenesis slows or stops altogether. The reduction of spermatogenesis is predicted to lessen the male mutation bias and to lower the per-generation mutation rate in this species. However, using whole-genome sequencing, we find that both male bias and per-generation mutation rates are highly similar to that expected for a non-hibernating species. We also carry out a phylogenetic comparison of substitution rates along the lineage leading to brown bear and panda (a non-hibernating species) and find no slowing of the substitution rate in the hibernator. Our results contribute to accumulating evidence that suggests that male germline cell division is not the major determinant of mutation rates and mutation biases. The results also provide a quantitative basis for improved estimates of the timing of carnivore evolution.

Effects of replication domains on genome-wide UV-induced DNA damage and repair.

Nucleotide excision repair is the primary repair mechanism that removes UV-induced DNA lesions in placentals. Unrepaired UV-induced lesions could result in mutations during DNA replication. Although the mutagenesis of pyrimidine dimers is reasonably well understood, the direct effects of replication fork progression on nucleotide excision repair are yet to be clarified. Here, we applied Damage-seq and XR-seq techniques and generated replication maps in synchronized UV-treated HeLa cells. The results suggest that ongoing replication stimulates local repair in both early and late replication domains. Additionally, it was revealed that lesions on lagging strand templates are repaired slower in late replication domains, which is probably due to the imbalanced sequence context. Asymmetric relative repair is in line with the strand bias of melanoma mutations, suggesting a role of exogenous damage, repair, and replication in mutational strand asymmetry.

Reciprocal abrogation of PKM isoforms: contradictory outcomes and differing impact of splicing signal on CRISPR/Cas9 mediates gene editing in keratinocytes.

The healing of wounded skin is a highly organized process involving a massive cell in- and outflux, proliferation and tissue remodelling. It is well accepted that metabolic constraints such as diabetes mellitus, overweight or anorexia impairs wound healing. Indeed, wound inflammation involves a boost of overall metabolic changes. As wound healing converges inflammatory processes that are also common to transformation, we investigate the functional role of the pro-neoplastic factor pyruvate kinase (PK) M2 and its metabolic active splice variant PKM1 in keratinocytes. Particularly, we challenge the impact of reciprocal ablation of PKM1 or two expression. Here, CRISPR/Cas9 genome editing of the PKM gene in HaCaT reveals an unexpected mutational bias at the 3'SS of exon 9, whereas no preference for any particular kind of mutation at exon 10 3' splice, despite the close vicinity (400 nucleotides apart) and sequence similarity between the two sites. Furthermore, as opposed to transient silencing of PKM2, exclusion splicing of PKM2 via genome editing mutually increases PKM1 mRNA and protein expression and compensates for the absence of PKM2, whereas the reciprocal elimination of PKM1 splicing reduces PKM2 expression and impedes cell proliferation, thus unveiling an essential role for PKM1 in growth and metabolic balance of HaCaT keratinocytes.

Polymorphism‐aware estimation of species trees and evolutionary forces from genomic sequences with RevBayes

Abstract The availability of population genomic data through new sequencing technologies gives unprecedented opportunities for estimating important evolutionary forces such as genetic drift, selection and mutation biases across organisms. Yet, analytical methods that can handle polymorphisms jointly with sequence divergence across species are rare and not easily accessible to empiricists. We implemented polymorphism‐aware phylogenetic models (PoMos), an alternative approach for species tree estimation, in the Bayesian phylogenetic software RevBayes. PoMos naturally account for incomplete lineage sorting, which is known to cause difficulties for phylogenetic inference in species radiations, and scale well with genome‐wide data. Simultaneously, PoMos can estimate mutation and selection biases. We have applied our methods to resolve the complex phylogenetic relationships of a young radiation of Chorthippus grasshoppers, based on coding sequences. In addition to establishing a well‐supported species tree, we found a mutation bias favouring AT alleles and selection bias promoting the fixation of GC alleles, the latter consistent with GC‐biased gene conversion. The selection bias is two orders of magnitude lower than genetic drift, validating the critical role of nearly neutral evolutionary processes in species radiation. PoMos offer a wide range of models to reconstruct phylogenies and can be easily combined with existing models in RevBayes—for example, relaxed clock and divergence time estimation—offering new insights into the evolutionary processes underlying molecular evolution and, ultimately, species diversification.