Effective Mutation Rate Research Articles

Low genetic differentiation despite high habitat fragmentation in an endemic and endangered species of Iridaceae from South America: implications for conservation

Abstract To conserve threatened species effectively, it is crucial to map the genetic variation of the remaining populations. Thus, using 15 microsatellites markers, from which 10 were specially developed for this study, we investigated genetic structure and gene flow patterns of Herbertia zebrina Deble, a critically endangered species endemic from grasslands of southern Brazil. We also investigated the degree of habitat fragmentation and the impacts on levels of genetic diversity, mating system and pollinators of the species. STRUCTURE and discriminant analysis of principal components identified the existence of three genetic clusters. Populations were not isolated by distance, and genetic differentiation among populations was low (7.0%). Migration rates were also low, but no evidence of genetic bottlenecks was found. However, effective population-scaled mutation rates (Θ) were < 1, suggesting that populations could be experiencing genetic drift, but the reason remains unknown. The results indicate that measurements of habitat fragmentation were not significantly correlated with genetic diversity estimates, which tend to increase with fragment size. H. zebrina was identified as an outcrossing species and specialized pollinators, such as Chalepogenus goeldianus and Lanthanomelissa betinae were rarely observed. Our findings suggest that genetic differentiation across multiple populations within the entire geographic distribution of H. zebrina is very low and populations may struggle to adapt to the current environmental and pollination changes. However, habitat fragmentation is still too recent to detect significant impacts on the levels of genetic variation. Thus, conservation plans are necessary to avoid further declines of this species.

Modeling the mosaic structure of bacterial genomes to infer their evolutionary history

The chronology and phylogeny of bacterial evolution are difficult to reconstruct due to a scarce fossil record. The analysis of bacterial genomes remains challenging because of large sequence divergence, the plasticity of bacterial genomes due to frequent gene loss, horizontal gene transfer, and differences in selective pressure from one locus to another. Therefore, taking advantage of the rich and rapidly accumulating genomic data requires accurate modeling of genome evolution. An important technical consideration is that loci with high effective mutation rates may diverge beyond the detection limit of the alignment algorithms used, biasing the genome-wide divergence estimates toward smaller divergences. In this article, we propose a novel method to gain insight into bacterial evolution based on statistical properties of genome comparisons. We find that the length distribution of sequence matches is shaped by the effective mutation rates of different loci, by the horizontal transfers, and by the aligner sensitivity. Based on these inputs, we build a model and show that it accounts for the empirically observed distributions, taking the Enterobacteriaceae family as an example. Our method allows to distinguish segments of vertical and horizontal origins and to estimate the time divergence and exchange rate between any pair of taxa from genome-wide alignments. Based on the estimated time divergences, we construct a time-calibrated phylogenetic tree to demonstrate the accuracy of the method.

Diversity and metabolic energy in bacteria.

Why are some groups of bacteria more diverse than others? We hypothesize that the metabolic energy available to a bacterial functional group (a biogeochemical group or 'guild') has a role in such a group's taxonomic diversity. We tested this hypothesis by looking at the metacommunity diversity of functional groups in multiple biomes. We observed a positive correlation between estimates of a functional group's diversity and their metabolic energy yield. Moreover, the slope of that relationship was similar in all biomes. These findings could imply the existence of a universal mechanism controlling the diversity of all functional groups in all biomes in the same way. We consider a variety of possible explanations from the classical (environmental variation) to the 'non-Darwinian' (a drift barrier effect). Unfortunately, these explanations are not mutually exclusive, and a deeper understanding of the ultimate cause(s) of bacterial diversity will require us to determine if and how the key parameters in population genetics (effective population size, mutation rate, and selective gradients) vary between functional groups and with environmental conditions: this is a difficult task.

Sheltering of deleterious mutations explains the stepwise extension of recombination suppression on sex chromosomes and other supergenes.

Many organisms have sex chromosomes with large nonrecombining regions that have expanded stepwise, generating "evolutionary strata" of differentiation. The reasons for this remain poorly understood, but the principal hypotheses proposed to date are based on antagonistic selection due to differences between sexes. However, it has proved difficult to obtain empirical evidence of a role for sexually antagonistic selection in extending recombination suppression, and antagonistic selection has been shown to be unlikely to account for the evolutionary strata observed on fungal mating-type chromosomes. We show here, by mathematical modeling and stochastic simulation, that recombination suppression on sex chromosomes and around supergenes can expand under a wide range of parameter values simply because it shelters recessive deleterious mutations, which are ubiquitous in genomes. Permanently heterozygous alleles, such as the male-determining allele in XY systems, protect linked chromosomal inversions against the expression of their recessive mutation load, leading to the successive accumulation of inversions around these alleles without antagonistic selection. Similar results were obtained with models assuming recombination-suppressing mechanisms other than chromosomal inversions and for supergenes other than sex chromosomes, including those without XY-like asymmetry, such as fungal mating-type chromosomes. However, inversions capturing a permanently heterozygous allele were found to be less likely to spread when the mutation load segregating in populations was lower (e.g., under large effective population sizes or low mutation rates). This may explain why sex chromosomes remain homomorphic in some organisms but are highly divergent in others. Here, we model a simple and testable hypothesis explaining the stepwise extensions of recombination suppression on sex chromosomes, mating-type chromosomes, and supergenes in general.

Evaluation of methods for estimating coalescence times using ancestral recombination graphs.

The ancestral recombination graph is a structure that describes the joint genealogies of sampled DNA sequences along the genome. Recent computational methods have made impressive progress toward scalably estimating whole-genome genealogies. In addition to inferring the ancestral recombination graph, some of these methods can also provide ancestral recombination graphs sampled from a defined posterior distribution. Obtaining good samples of ancestral recombination graphs is crucial for quantifying statistical uncertainty and for estimating population genetic parameters such as effective population size, mutation rate, and allele age. Here, we use standard neutral coalescent simulations to benchmark the estimates of pairwise coalescence times from 3 popular ancestral recombination graph inference programs: ARGweaver, Relate, and tsinfer+tsdate. We compare (1) the true coalescence times to the inferred times at each locus; (2) the distribution of coalescence times across all loci to the expected exponential distribution; (3) whether the sampled coalescence times have the properties expected of a valid posterior distribution. We find that inferred coalescence times at each locus are most accurate in ARGweaver, and often more accurate in Relate than in tsinfer+tsdate. However, all 3 methods tend to overestimate small coalescence times and underestimate large ones. Lastly, the posterior distribution of ARGweaver is closer to the expected posterior distribution than Relate's, but this higher accuracy comes at a substantial trade-off in scalability. The best choice of method will depend on the number and length of input sequences and on the goal of downstream analyses, and we provide guidelines for the best practices.

植物交配系统与分子进化理论及其应用研究

<p indent="0mm">With the transition of plant mating system from outcrossing to selfing, both the flower traits and genomic structure develop into selfing syndromes. Here we systematically discussed the theoretical basis and the molecular mechanisms that form these characteristics, and analyzed the basic theory of the interactions between mating system and different evolutionary processes. Selfing results in decrease in the effective population size, mutation rate, recombination rate and selection efficacy, but increase in genetic drift effects and linkage disequilibrium. These theories are effective in explaining the patterns of the relative rate of nonsynonymous to synonymous mutations, the change of the number of transposable elements, the genetic correlation between multigene family members and the pattern of genomic structure. Although molecular markers are often employed to score mating system, studies of mating system and molecular evolution have been mainly in different research fields. Some questions of biological significance could arise from an integration of these two research fields, such as the mode of driving or reinforcing molecular mechanism of speciation that the mating system operates, the different models of molecular evolution between populations of selfing versus outcrossing system, and the distinct genomic structure between populations of the same species with different mating systems. Clarification of these questions aids in our understanding of the role that mating system plays in affecting molecular evolution within and between species.

A nearly-neutral biallelic Moran model with biased mutation and linear and quadratic selection

In this article, a biallelic reversible mutation model with linear and quadratic selection is analysed. The approach reconnects to one proposed by Kimura (1979), who starts from a diffusion model and derives its equilibrium distribution up to a constant. We use a boundary-mutation Moran model, which approximates a general mutation model for small effective mutation rates, and derive its equilibrium distribution for polymorphic and monomorphic variants in small to moderately sized populations. Using this model, we show that biased mutation rates and linear selection alone can cause patterns of polymorphism within and substitution rates between populations that are usually ascribed to balancing or overdominant selection. We illustrate this using a data set of short introns and fourfold degenerate sites from Drosophila simulans and Drosophila melanogaster.

Rethinking Our COVID-19 Strategy

&lt;img src=” https://s3.amazonaws.com/production.scholastica/article/21569/large/prnano_632021ga03022100.jpg?1616106284”&gt; As of Feb 21, 2021, the COVID-19 pandemic claimed over half a million lives in the U.S., and over half of the country’s population likely had an infection. Our strategy to deal with the COVID-19 pandemic to date has been to rely very heavily on vaccination while testing and anti-viral development was given short shrift. Initial results of vaccines appeared promising, but there have been increased numbers of new variants than expected due to a high effective muta-tion rate. These new variants show the strong possibility of mutational escape from existing an-tibodies, whether these antibodies are generated from natural infection or a vaccine. Increasing infection rates in the UK and Manaus, Brazil, has shown that even high seroprevalence from previous infection waves may not block these new variants. The development of new vaccines for COVID-19 has now become exponentially more challenging for several reasons. Given our partial success with the current vaccination strategy, it is time to revisit the idea of antiviral de-velopment combined with significantly increased testing as a means of controlling this pandem-ic. Only a more balanced strategy involving all available control technologies: testing, antiviral drugs, and vaccination will effectively end this pandemic.

A game-theoretical dynamic imitation model on networks.

A game-theoretical model is constructed to capture the effect of imitation on the evolution of cooperation. This imitation describes the case where successful individuals are more likely to be imitated by newcomers who will employ their strategies and social networks. Two classical repeated strategies 'always defect (ALLD)' and 'tit-for-tat (TFT)' are adopted. Mathematical analyses are mainly conducted by the method of coalescence theory. Under the assumption of a large population size and weak selection, the results show that the evolution of cooperation is promoted in this dynamic network. As we observed that the critical benefit-to-cost ratio is smaller compared to that in well-mixed populations. The critical benefit-to-cost ratio approaches a specific value which depends on three parameters, the repeated rounds of the game, the effective strategy mutation rate, and the effective link mutation rate. Specifically, for a very high value of the effective link mutation rate, the critical benefit-to-cost ratio approaches 1. Remarkably, for a low value of the effective link mutation rate, by letting the effective strategy mutation is nearly equal to zero, the critical benefit-to-cost ratio approaches [Formula: see text] for the resulting highly connected networks, which allows TFT to be evolutionary stable. It illustrates that dominance of TFTs is associated with more connected networks. This research can enrich the theory of the coevolution of game strategy and network structure with dynamic imitation.

Recurrent evolution of high virulence in isolated populations of a DNA virus.

Hosts and viruses are constantly evolving in response to each other: as a host attempts to suppress a virus, the virus attempts to evade and suppress the host's immune system. Here, we describe the recurrent evolution of a virulent strain of a DNA virus, which infects multiple Drosophila species. Specifically, we identified two distinct viral types that differ 100-fold in viral titer in infected individuals, with similar differences observed in multiple species. Our analysis suggests that one of the viral types recurrently evolved at least four times in the past ~30,000 years, three times in Arizona and once in another geographically distinct species. This recurrent evolution may be facilitated by an effective mutation rate which increases as each prior mutation increases viral titer and effective population size. The higher titer viral type suppresses the host-immune system and an increased virulence compared to the low viral titer type.

The inflated mitochondrial genomes of siphonous green algae reflect processes driving expansion of noncoding DNA and proliferation of introns

Within the siphonous green algal order Bryopsidales, the size and gene arrangement of chloroplast genomes has been examined extensively, while mitochondrial genomes have been mostly overlooked. The recently published mitochondrial genome of Caulerpa lentillifera is large with expanded noncoding DNA, but it remains unclear if this is characteristic of the entire order. Our study aims to evaluate the evolutionary forces shaping organelle genome dynamics in the Bryopsidales based on the C. lentillifera and Ostreobium quekettii mitochondrial genomes. In this study, the mitochondrial genome of O. quekettii was characterised using a combination of long and short read sequencing, and bioinformatic tools for annotation and sequence analyses. We compared the mitochondrial and chloroplast genomes of O. quekettii and C. lentillifera to examine hypotheses related to genome evolution. The O. quekettii mitochondrial genome is the largest green algal mitochondrial genome sequenced (241,739 bp), considerably larger than its chloroplast genome. As with the mtDNA of C. lentillifera, most of this excess size is from the expansion of intergenic DNA and proliferation of introns. Inflated mitochondrial genomes in the Bryopsidales suggest effective population size, recombination and/or mutation rate, influenced by nuclear-encoded proteins, differ between the genomes of mitochondria and chloroplasts, reducing the strength of selection to influence evolution of their mitochondrial genomes.

Extensive subclonal mutational diversity in human colorectal cancer and its significance

Human colorectal cancers (CRCs) contain both clonal and subclonal mutations. Clonal driver mutations are positively selected, present in most cells, and drive malignant progression. Subclonal mutations are randomly dispersed throughout the genome, providing a vast reservoir of mutant cells that can expand, repopulate the tumor, and result in the rapid emergence of resistance, as well as being a major contributor to tumor heterogeneity. Here, we apply duplex sequencing (DS) methodology to quantify subclonal mutations in CRC tumor with unprecedented depth (104) and accuracy (<10-7). We measured mutation frequencies in genes encoding replicative DNA polymerases and in genes frequently mutated in CRC, and found an unexpectedly high effective mutation rate, 7.1 × 10-7. The curve of subclonal mutation accumulation as a function of sequencing depth, using DNA obtained from 5 different tumors, is in accord with a neutral model of tumor evolution. We present a theoretical approach to model neutral evolution independent of the infinite-sites assumption (which states that a particular mutation arises only in one tumor cell at any given time). Our analysis indicates that the infinite-sites assumption is not applicable once the number of tumor cells exceeds the reciprocal of the mutation rate, a circumstance relevant to even the smallest clinically diagnosable tumor. Our methods allow accurate estimation of the total mutation burden in clinical cancers. Our results indicate that no DNA locus is wild type in every malignant cell within a tumor at the time of diagnosis (probability of all cells being wild type, 10-308).

On the feasibility of saltational evolution

Is evolution always gradual or can it make leaps? We examine a mathematical model of an evolutionary process on a fitness landscape and obtain analytic solutions for the probability of multimutation leaps, that is, several mutations occurring simultaneously, within a single generation in 1 genome, and being fixed all together in the evolving population. The results indicate that, for typical, empirically observed combinations of the parameters of the evolutionary process, namely, effective population size, mutation rate, and distribution of selection coefficients of mutations, the probability of a multimutation leap is low, and accordingly the contribution of such leaps is minor at best. However, we show that, taking sign epistasis into account, leaps could become an important factor of evolution in cases of substantially elevated mutation rates, such as stress-induced mutagenesis in microbes. We hypothesize that stress-induced mutagenesis is an evolvable adaptive strategy.

Efficient generation of GHR knockout Bama minipig fibroblast cells using CRISPR/Cas9-mediated gene editing.

Dwarfism, also known as growth hormone deficiency (GHD), is a disease caused by genetic mutations that result in either a lack of growth hormone or insufficient secretion of growth hormone, resulting in a person's inability to grow normally. In the past, many studies focusing on GHD have made use of models of other diseases such as metabolic or infectious diseases. A viable GHD specific model system has not been used previously, thus limiting the interpretation of GHD results. The Bama minipig is unique to Guangxi province and has strong adaptability and disease resistance, and an incredibly short stature, which is especially important for the study of GHD. In addition, studies of GHR knockout Bama minipigs and GHR knockout Bama minipig fibroblast cells generated using CRISPR/Cas9 have not been previously reported. Therefore, the Bama minipig was selected as an animal model and as a tool for the study of GHD in this work. In this study, a Cas9 plasmid with sgRNA targeting the first exon of the GHR gene was transfected into Bama minipig kidney fibroblast cells to generate 22 GHR knockout Bama minipig kidney fibroblast cell lines (12 male monoclonal cells and 10 female monoclonal cells). After culture and identification, 11 of the 12 male clone cell lines showed double allele mutations, and the rate of positive alteration of GHR was 91.67%. Diallelic mutation of the target sequence occurred in 10 female clonal cell lines, with an effective positive mutation rate of 100%. Our experimental results not only showed that CRISPR/Cas9 could efficiently be used for gene editing in Bama minipig cells but also identified a highly efficient target site for the generation of a GHR knockout in other porcine models. Thus, the generation of GHR knockout male and female Bama fibroblast cells could lay a foundation for the birth of a future dwarfism model pig. We anticipate that the "mini" Bama minipig will be of improved use for biomedical and agricultural scientific research and for furthering our understanding of the genetic underpinnings of GHD.

Multi-Lineage Evolution in Viral Populations Driven by Host Immune Systems.

Viruses evolve in the background of host immune systems that exert selective pressure and drive viral evolutionary trajectories. This interaction leads to different evolutionary patterns in antigenic space. Examples observed in nature include the effectively one-dimensional escape characteristic of influenza A and the prolonged coexistence of lineages in influenza B. Here, we use an evolutionary model for viruses in the presence of immune host systems with finite memory to obtain a phase diagram of evolutionary patterns in a two-dimensional antigenic space. We find that, for small effective mutation rates and mutation jump ranges, a single lineage is the only stable solution. Large effective mutation rates combined with large mutational jumps in antigenic space lead to multiple stably co-existing lineages over prolonged evolutionary periods. These results combined with observations from data constrain the parameter regimes for the adaptation of viruses, including influenza.

Sex-ratio bias induced by mutation.

A question in evolutionary biology is why the number of males is approximately equal to that of females in many species, and Fisher's theory of equal investment answers that it is the evolutionarily stable state. The Fisherian mechanism can be given a concrete form by a genetic model based on the following assumptions: (1) Males and females mate at random. (2) An allele acts on the father to determine the expected progeny sex ratio. (3) The offspring inherits the allele from either side of the parents with equal probability. The model is known to achieve the 1:1 sex ratio due to the invasion of mutant alleles with different progeny sex ratios. In this study, however, we argue that mutation plays a more subtle role in that fluctuations caused by mutation renormalize the sex ratio and thereby keep it away from 1:1 in general. This finding shows how the sex ratio is affected by mutation in a systematic way, whereby the effective mutation rate can be estimated from an observed sex ratio.

The Red Queen model of recombination hot-spot evolution: a theoretical investigation.

In humans and many other species, recombination events cluster in narrow and short-lived hot spots distributed across the genome, whose location is determined by the Zn-finger protein PRDM9. To explain these fast evolutionary dynamics, an intra-genomic Red Queen model has been proposed, based on the interplay between two antagonistic forces: biased gene conversion, mediated by double-strand breaks, resulting in hot-spot extinction, followed by positive selection favouring new PRDM9 alleles recognizing new sequence motifs. Thus far, however, this Red Queen model has not been formalized as a quantitative population-genetic model, fully accounting for the intricate interplay between biased gene conversion, mutation, selection, demography and genetic diversity at the PRDM9 locus. Here, we explore the population genetics of the Red Queen model of recombination. A Wright–Fisher simulator was implemented, allowing exploration of the behaviour of the model (mean equilibrium recombination rate, diversity at the PRDM9 locus or turnover rate) as a function of the parameters (effective population size, mutation and erosion rates). In a second step, analytical results based on self-consistent mean-field approximations were derived, reproducing the scaling relations observed in the simulations. Empirical fit of the model to current data from the mouse suggests both a high mutation rate at PRDM9 and strong biased gene conversion on its targets.This article is part of the themed issue ‘Evolutionary causes and consequences of recombination rate variation in sexual organisms’.

Population Genomics of Daphnia pulex.

Using data from 83 isolates from a single population, the population genomics of the microcrustacean Daphnia pulex are described and compared to current knowledge for the only other well-studied invertebrate, Drosophila melanogaster These two species are quite similar with respect to effective population sizes and mutation rates, although some features of recombination appear to be different, with linkage disequilibrium being elevated at short ([Formula: see text] bp) distances in D. melanogaster and at long distances in D. pulex The study population adheres closely to the expectations under Hardy-Weinberg equilibrium, and reflects a past population history of no more than a twofold range of variation in effective population size. Fourfold redundant silent sites and a restricted region of intronic sites appear to evolve in a nearly neutral fashion, providing a powerful tool for population genetic analyses. Amino acid replacement sites are predominantly under strong purifying selection, as are a large fraction of sites in UTRs and intergenic regions, but the majority of SNPs at such sites that rise to frequencies [Formula: see text] appear to evolve in a nearly neutral fashion. All forms of genomic sites (including replacement sites within codons, and intergenic and UTR regions) appear to be experiencing an [Formula: see text] higher level of selection scaled to the power of drift in D. melanogaster, but this may in part be a consequence of recent demographic changes. These results establish D. pulex as an excellent system for future work on the evolutionary genomics of natural populations.

Performance of genomic selection under a single-step approach in autochthonous Spanish beef cattle populations.

This study evaluated different strategies for implementing a single-step genomic selection programme in two autochthonous Spanish beef cattle populations (Pirenaica-Pi and Rubia Gallega-RG). The strategies were compared in terms of accuracy attained under different scenarios by simulating genomic data over the known genealogy. Several genotyping approaches were tested, as well as, other factors like marker density, effective population size, mutation rate and heritability of the trait. The results obtained showed gains in accuracy with respect to pedigree BLUP evaluation in all cases. The greatest benefit was obtained when the candidates to selection had their genotypes included in the evaluation. Moreover, genotyping the individuals with the most accurate predictions maximized the gains but other suboptimal strategies also yielded satisfactory results. Furthermore, the gains in accuracy increased with the marker density reaching a plateau at around 50,000 markers. Likewise, the effective population size and the mutation rate have also shown an effect, both increasing the accuracy with decreasing values of these population parameters. Finally, the results obtained for the RG population showed greater gains compared to the Pi population, probably attributed to the wider implantation of artificial insemination.

The genetic structure of populations of orchids and its evolutionary importance: understanding processes from patterns

&lt;div class="page" title="Page 1"&gt;&lt;div class="layoutArea"&gt;&lt;div class="column"&gt;&lt;p&gt;&lt;span&gt;Evolution through either natural selection or genetic drift is dependent on variation at the genetic and mor- phological levels. Processes that influence the genetic structure of populations include mating systems, effective population size, mutation rates and gene flow among populations. &lt;/span&gt;&lt;/p&gt;&lt;/div&gt;&lt;/div&gt;&lt;/div&gt;