scholarly journals Considering Genomic Scans for Selection as Coalescent Model Choice

2020 ◽  
Vol 12 (6) ◽  
pp. 871-877
Author(s):  
Rebecca B Harris ◽  
Jeffrey D Jensen
Keyword(s):  
Genomic Analysis ◽  
Selective Sweeps ◽  
Demographic Parameter ◽  
Demographic Models ◽  
Sufficient Power ◽  
Selective Neutrality ◽  
Neutral Models ◽  
Modern Population ◽  
Theoretical Results ◽  
Genomic Scans

Abstract First inspired by the seminal work of Lewontin and Krakauer (1973. Distribution of gene frequency as a test of the theory of the selective neutrality of polymorphisms. Genetics 74(1):175–195.) and Maynard Smith and Haigh (1974. The hitch-hiking effect of a favourable gene. Genet Res. 23(1):23–35.), genomic scans for positive selection remain a widely utilized tool in modern population genomic analysis. Yet, the relative frequency and genomic impact of selective sweeps have remained a contentious point in the field for decades, largely owing to an inability to accurately identify their presence and quantify their effects—with current methodologies generally being characterized by low true-positive rates and/or high false-positive rates under many realistic demographic models. Most of these approaches are based on Wright–Fisher assumptions and the Kingman coalescent and generally rely on detecting outlier regions which do not conform to these neutral expectations. However, previous theoretical results have demonstrated that selective sweeps are well characterized by an alternative class of model known as the multiple-merger coalescent. Taken together, this suggests the possibility of not simply identifying regions which reject the Kingman, but rather explicitly testing the relative fit of a genomic window to the multiple-merger coalescent. We describe the advantages of such an approach, which owe to the branching structure differentiating selective and neutral models, and demonstrate improved power under certain demographic scenarios relative to a commonly used approach. However, regions of the demographic parameter space continue to exist in which neither this approach nor existing methodologies have sufficient power to detect selective sweeps.

scholarly journals How reliable are empirical genomic scans for selective sweeps?

2006 ◽  
Vol 16 (6) ◽  
pp. 702-712 ◽  
Author(s):  
K. M. Teshima
Keyword(s):  
Selective Sweeps ◽  
Genomic Scans

scholarly journals Selective Sweeps and Parallel Pathoadaptation Drive Pseudomonas aeruginosa Evolution in the Cystic Fibrosis Lung

mBio ◽  
2015 ◽  
Vol 6 (5) ◽  
Author(s):  
Julio Diaz Caballero ◽  
Shawn T. Clark ◽  
Bryan Coburn ◽  
Yu Zhang ◽  
Pauline W. Wang ◽  
...  
Keyword(s):  
Cystic Fibrosis ◽  
Pseudomonas Aeruginosa ◽  
Evolutionary Dynamics ◽  
Genomic Analysis ◽  
Opportunistic Pathogen ◽  
Ancestral Population ◽  
Selective Sweeps ◽  
Short Term ◽  
Evolutionary Patterns ◽  
Content Type

ABSTRACT Pulmonary infections caused by Pseudomonas aeruginosa are a recalcitrant problem in cystic fibrosis (CF) patients. While the clinical implications and long-term evolutionary patterns of these infections are well studied, we know little about the short-term population dynamics that enable this pathogen to persist despite aggressive antimicrobial therapy. Here, we describe a short-term population genomic analysis of 233 P. aeruginosa isolates collected from 12 sputum specimens obtained over a 1-year period from a single patient. Whole-genome sequencing and antimicrobial susceptibility profiling identified the expansion of two clonal lineages. The first lineage originated from the coalescence of the entire sample less than 3 years before the end of the study and gave rise to a high-diversity ancestral population. The second expansion occurred 2 years later and gave rise to a derived population with a strong signal of positive selection. These events show characteristics consistent with recurrent selective sweeps. While we cannot identify the specific mutations responsible for the origins of the clonal lineages, we find that the majority of mutations occur in loci previously associated with virulence and resistance. Additionally, approximately one-third of all mutations occur in loci that are mutated multiple times, highlighting the importance of parallel pathoadaptation. One such locus is the gene encoding penicillin-binding protein 3, which received three independent mutations. Our functional analysis of these alleles shows that they provide differential fitness benefits dependent on the antibiotic under selection. These data reveal that bacterial populations can undergo extensive and dramatic changes that are not revealed by lower-resolution analyses. IMPORTANCE Pseudomonas aeruginosa is a bacterial opportunistic pathogen responsible for significant morbidity and mortality in cystic fibrosis (CF) patients. Once it has colonized the lung in CF, it is highly resilient and rarely eradicated. This study presents a deep sampling examination of the fine-scale evolutionary dynamics of P. aeruginosa in the lungs of a chronically infected CF patient. We show that diversity of P. aeruginosa is driven by recurrent clonal emergence and expansion within this patient and identify potential adaptive variants associated with these events. This high-resolution sequencing strategy thus reveals important intraspecies dynamics that explain a clinically important phenomenon not evident at a lower-resolution analysis of community structure.

scholarly journals Impacts of Recurrent Hitchhiking on Divergence and Demographic Inference in Drosophila

2017 ◽  
Author(s):  
Jeremy D. Lange ◽  
John E. Pool
Keyword(s):  
Natural Selection ◽  
Population Genetic ◽  
Large Population ◽  
Selective Sweeps ◽  
Demographic Parameter ◽  
Genome Wide ◽  
Standard Population ◽  
Population Sizes ◽  
The Common ◽  
Demographic Inference

AbstractIn species with large population sizes such as Drosophila, natural selection may have substantial effects on genetic diversity and divergence. However, the implications of this widespread nonneutrality for standard population genetic assumptions and practices remain poorly resolved. Here, we assess the consequences of recurrent hitchhiking (RHH), in which selective sweeps occur at a given rate randomly across the genome. We use forward simulations to examine two published RHH models for D. melanogaster, reflecting relatively common/weak and rare/strong selection. We find that unlike the rare/strong RHH model, the common/weak model entails a slight degree of Hill-Robertson interference in high recombination regions. We also find that the common/weak RHH model is more consistent with our genome-wide estimate of the proportion of substitutions fixed by natural selection between D. melanogaster and D. simulans (19%). Finally, we examine how these models of RHH might bias demographic inference. We find that these RHH scenarios can bias demographic parameter estimation, but such biases are weaker for parameters relating recently-diverged populations, and for the common/weak RHH model in general. Thus, even for species with important genome-wide impacts of selective sweeps, neutralist demographic inference can have some utility in understanding the histories of recently-diverged populations.

scholarly journals On the unfounded enthusiasm for soft selective sweeps II: examining recent evidence from humans, flies, and viruses

2018 ◽  
Author(s):  
Rebecca B. Harris ◽  
Andrew Sackman ◽  
Jeffrey D. Jensen
Keyword(s):  
Positive Selection ◽  
Large Scale ◽  
Natural Populations ◽  
Population Data ◽  
Population Level ◽  
Selective Sweeps ◽  
Effective Population ◽  
Initial Description ◽  
Neutral Models ◽  
Soft Selective Sweeps

ABSTRACTSince the initial description of the genomic patterns expected under models of positive selection acting on standing genetic variation and on multiple beneficial mutations—so-called soft selective sweeps—researchers have sought to identify these patterns in natural population data. Indeed, over the past two years, large-scale data analyses have argued that soft sweeps are pervasive across organisms of very different effective population size and mutation rate—humans, Drosophila, and HIV. Yet, others have evaluated the relevance of these models to natural populations, as well as the identifiability of the models relative to other known population-level processes, arguing that soft sweeps are likely to be rare. Here, we look to reconcile these opposing results by carefully evaluating three recent studies and their underlying methodologies. Using population genetic theory, as well as extensive simulation, we find that all three examples are prone to extremely high false-positive rates, incorrectly identifying soft sweeps under both hard sweep and neutral models. Furthermore, we demonstrate that well-fit demographic histories combined with rare hard sweeps serve as the more parsimonious explanation. These findings represent a necessary response to the growing tendency of invoking parameter-heavy, assumption-laden models of pervasive positive selection, and neglecting best practices regarding the construction of proper demographic null models.

scholarly journals The Evolution of Mutator Genes in Bacterial Populations: The Roles of Environmental Change and Timing

Genetics ◽  
2003 ◽  
Vol 164 (3) ◽  
pp. 843-854 ◽  
Author(s):  
Mark M Tanaka ◽  
Carl T Bergstrom ◽  
Bruce R Levin
Keyword(s):  
Selective Sweeps ◽  
Deleterious Mutations ◽  
Beneficial Mutation ◽  
Beneficial Mutations ◽  
Bacterial Populations ◽  
High Frequencies ◽  
Laboratory Populations ◽  
Experimental And Theoretical Studies ◽  
Theoretical Results ◽  
Mutator Genes

Abstract Recent studies have found high frequencies of bacteria with increased genomic rates of mutation in both clinical and laboratory populations. These observations may seem surprising in light of earlier experimental and theoretical studies. Mutator genes (genes that elevate the genomic mutation rate) are likely to induce deleterious mutations and thus suffer an indirect selective disadvantage; at the same time, bacteria carrying them can increase in frequency only by generating beneficial mutations at other loci. When clones carrying mutator genes are rare, however, these beneficial mutations are far more likely to arise in members of the much larger nonmutator population. How then can mutators become prevalent? To address this question, we develop a model of the population dynamics of bacteria confronted with ever-changing environments. Using analytical and simulation procedures, we explore the process by which initially rare mutator alleles can rise in frequency. We demonstrate that subsequent to a shift in environmental conditions, there will be relatively long periods of time during which the mutator subpopulation can produce a beneficial mutation before the ancestral subpopulations are eliminated. If the beneficial mutation arises early enough, the overall frequency of mutators will climb to a point higher than when the process began. The probability of producing a subsequent beneficial mutation will then also increase. In this manner, mutators can increase in frequency over successive selective sweeps. We discuss the implications and predictions of these theoretical results in relation to antibiotic resistance and the evolution of mutation rates.

scholarly journals Detection of hard and soft selective sweeps from Drosophila melanogaster population genomic data

2020 ◽  
Author(s):  
Nandita Garud ◽  
Philipp W. Messer ◽  
Dmitri Petrov
Keyword(s):  
Drosophila Melanogaster ◽  
Natural Population ◽  
Genomic Data ◽  
Selective Sweeps ◽  
Demographic Models ◽  
Population Genomic ◽  
Free Parameters ◽  
Candidate Loci ◽  
Soft Selective Sweeps ◽  
Positive Controls

AbstractWhether hard sweeps or soft sweeps dominate adaptation has been a matter of much debate. Recently, we developed haplotype homozygosity statistics that (i) can detect both hard and soft sweeps with similar power and (ii) can classify the detected sweeps as hard or soft. The application of our method to population genomic data from a natural population of Drosophila melanogaster (DGRP) allowed us to rediscover three known cases of adaptation at the loci Ace, Cyp6g1, and CHKov1 known to be driven by soft sweeps, and detected additional candidate loci for recent and strong sweeps. Surprisingly, all of the top 50 candidates showed patterns much more consistent with soft rather than hard sweeps. Recently, Harris et al. 2018 criticized this work, suggesting that all the candidate loci detected by our haplotype statistics, including the positive controls, are unlikely to be sweeps at all and instead these haplotype patterns can be more easily explained by complex neutral demographic models. They also claim, confusingly, that these neutral non-sweeps are likely to be hard instead of soft sweeps. Here, we reanalyze the DGRP data using a range of complex admixture demographic models and reconfirm our original published results suggesting that the majority of recent and strong sweeps in D. melanogaster are first likely to be true sweeps, and second, that they do appear to be soft. Furthermore, we discuss ways to take this work forward given that the demographic models employed in such analyses are generally necessarily too simple to capture the full demographic complexity, while more realistic models are unlikely to be inferred correctly because they require fitting a very large number of free parameters.

scholarly journals Detection of hard and soft selective sweeps from Drosophila melanogaster population genomic data

PLoS Genetics ◽  
2021 ◽  
Vol 17 (2) ◽  
pp. e1009373 ◽  
Author(s):  
Nandita R. Garud ◽  
Philipp W. Messer ◽  
Dmitri A. Petrov
Keyword(s):  
Drosophila Melanogaster ◽  
Natural Population ◽  
Genomic Data ◽  
Selective Sweeps ◽  
Demographic Models ◽  
Population Genomic ◽  
Free Parameters ◽  
Candidate Loci ◽  
Soft Selective Sweeps ◽  
Positive Controls

Whether hard sweeps or soft sweeps dominate adaptation has been a matter of much debate. Recently, we developed haplotype homozygosity statistics that (i) can detect both hard and soft sweeps with similar power and (ii) can classify the detected sweeps as hard or soft. The application of our method to population genomic data from a natural population ofDrosophila melanogaster(DGRP) allowed us to rediscover three known cases of adaptation at the lociAce,Cyp6g1, andCHKov1known to be driven by soft sweeps, and detected additional candidate loci for recent and strong sweeps. Surprisingly, all of the top 50 candidates showed patterns much more consistent with soft rather than hard sweeps. Recently, Harriset al. 2018 criticized this work, suggesting that all the candidate loci detected by our haplotype statistics, including the positive controls, are unlikely to be sweeps at all and that instead these haplotype patterns can be more easily explained by complex neutral demographic models. They also claim that these neutral non-sweeps are likely to be hard instead of soft sweeps. Here, we reanalyze the DGRP data using a range of complex admixture demographic models and reconfirm our original published results suggesting that the majority of recent and strong sweeps inD.melanogasterare first likely to be true sweeps, and second, that they do appear to be soft. Furthermore, we discuss ways to take this work forward given that most demographic models employed in such analyses are necessarily too simple to capture the full demographic complexity, while more realistic models are unlikely to be inferred correctly because they require a large number of free parameters.

scholarly journals Experimental Evolution of Magnetite Nanoparticle Resistance in Escherichia coli

2021 ◽  
Author(s):  
Akamu Ewunkem ◽  
LaShunta Rodgers ◽  
Daisha Campbell ◽  
Constance Staley ◽  
Kiran Subedi ◽  
...  
Keyword(s):  
Escherichia Coli ◽  
Magnetite Nanoparticles ◽  
Experimental Evolution ◽  
Genomic Analysis ◽  
Whole Genome ◽  
Selective Sweeps ◽  
Magnetite Nanoparticle ◽  
Genomic Changes ◽  
E Coli ◽  
Scanning Electron

Experimental evolution was utilized to produce 5 magnetite nanoparticle-resistant (FeNP1-5) populations of Escherichia coli. The control populations were not exposed to magnetite nanoparticles. The 24-hour growth of these replicates was evaluated in the presence of increasing concentrations magnetite NPs as well as other ionic metals (gallium III, iron II, iron III, silver I) and antibiotics (ampicillin, chloramphenicol, rifampicin, sulfanilamide, tetracycline). Scanning electron microscope was utilized to determine cell size and shape in response to magnetite nanoparticle selection. Whole genome sequencing was carried out to determine if any genomic changes that resulted from magnetite nanoparticle resistance. After 25 days of selection magnetite resistance was evident in the FeNP treatment. The FeNP populations also showed a highly significantly (p < 0.0001) greater 24-growth as measured by optical density in metals (Fe (II), Fe (III), Ga (III), Ag and Cu II); as well as antibiotics (ampicillin, chloramphenicol, rifampicin, sulfanilamide, and tetracycline). The FeNP resistant populations also showed a significantly greater cell length compared to controls (p < 0.001). Genomic analysis of FeNP identified both polymorphisms and hard selective sweeps in the RNA polymerase genes rpoA, rpoB, and rpoC. Collectively, our results show that E. coli can rapidly evolve resistance to magnetite nanoparticles and that this result is correlated resistances to other metals and antibiotics. There were also changes in cell morphology resulting from adaptation to magnetite NPs. Thus, the various applications of magnetite nanoparticles could result in unanticipated changes in resistance to both metal and antibiotics.

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