scholarly journals Dominance shifts increase the likelihood of soft selective sweeps

2021 ◽  
Author(s):  
Pavitra Muralidhar ◽  
Carl Veller
Keyword(s):  
Selective Sweep ◽  
Primary Source ◽  
Pesticide Use ◽  
Selective Sweeps ◽  
Multiple Alleles ◽  
Standing Variation ◽  
Haplotypic Diversity ◽  
Evolutionary Rescue ◽  
Genetics Of Adaptation ◽  
Soft Selective Sweeps

AbstractGenetic models of adaptation to a new environment have typically assumed that the alleles involved maintain a constant fitness dominance across the old and new environments. However, theories of dominance suggest that this should often not be the case. Instead, the alleles involved should frequently shift from recessive deleterious in the old environment to dominant beneficial in the new environment. Here, we study the consequences of these expected dominance shifts for the genetics of adaptation to a new environment. We find that dominance shifts increase the likelihood that adaptation occurs from the standing variation, and that multiple alleles from the standing variation are involved (a soft selective sweep). Furthermore, we find that expected dominance shifts increase the haplotypic diversity of selective sweeps, rendering soft sweeps more detectable in small genomic samples. In cases where an environmental change threatens the viability of the population, we show that expected dominance shifts of newly beneficial alleles increase the likelihood of evolutionary rescue and the number of alleles involved. Finally, we apply our results to a well-studied case of adaptation to a new environment: the evolution of pesticide resistance at the Ace locus in Drosophila melanogaster. We show that, under reasonable demographic assumptions, the expected dominance shift of resistant alleles causes soft sweeps to be the most frequent outcome in this case, with the primary source of these soft sweeps being the standing variation at the onset of pesticide use, rather than recurrent mutation thereafter.

scholarly journals Soft selective sweeps in evolutionary rescue

2016 ◽  
Author(s):  
Benjamin A. Wilson ◽  
Pleuni S. Pennings ◽  
Dmitri A. Petrov
Keyword(s):  
Drug Resistance ◽  
Population Genetics ◽  
Population Genetic ◽  
Genetic Adaptation ◽  
Selective Sweeps ◽  
Adaptive Mutations ◽  
Evolutionary Rescue ◽  
Large Populations ◽  
Genetic Signatures ◽  
Soft Selective Sweeps

AbstractEvolutionary rescue occurs when a population that is declining in size because of an environmental change is rescued by genetic adaptation. Evolutionary rescue is an important phenomenon at the intersection of ecology and population genetics. While most population genetic models of evolutionary rescue focus on estimating the probability of rescue, we focus on whether one or more adaptive lineages contribute to evolutionary rescue. We find that when evolutionary rescue is likely, it is often driven by soft selective sweeps where multiple adaptive mutations spread through the population simultaneously. We give full analytic results for the probability of evolutionary rescue and the probability that evolutionary rescue occurs via soft selective sweeps in our model. We expect that these results will find utility in understanding the genetic signatures associated with various evolutionary rescue scenarios in large populations, such as the evolution of drug resistance in viral, bacterial, or eukaryotic pathogens.

scholarly journals Allele Surfing Promotes Microbial Adaptation from Standing Variation

2016 ◽  
Author(s):  
Matti Gralka ◽  
Fabian Stiewe ◽  
Fred Farrell ◽  
Wolfram Möebius ◽  
Bartek Waclaw ◽  
...  
Keyword(s):  
Genetic Drift ◽  
Selective Sweeps ◽  
High Frequencies ◽  
Microbial Adaptation ◽  
Standing Variation ◽  
Resource Limited ◽  
Variation Range ◽  
Mean Fitness ◽  
Soft Selective Sweeps ◽  
Uniform Population

AbstractThe coupling of ecology and evolution during range expansions enables mutations to establish at expanding range margins and reach high frequencies. This phenomenon, called allele surfing, is thought to have caused revolutions in the gene pool of many species, most evidently in microbial communities. It has remained unclear, however, under which conditions allele surfing promotes or hinders adaptation. Here, using microbial experiments and simulations, we show that, starting with standing adaptive variation, range expansions generate a larger increase in mean fitness than spatially uniform population expansions. The adaptation gain results from ‘soft’ selective sweeps emerging from surfing beneficial mutations. The rate of these surfing events is shown to sensitively depend on the strength of genetic drift, which varies among strains and environmental conditions. More generally, allele surfing promotes the rate of adaptation per biomass produced, which could help developing biofilms and other resource-limited populations to cope with environmental challenges.

scholarly journals A Likelihood Approach for Uncovering Selective Sweep Signatures from Haplotype Data

2020 ◽  
Vol 37 (10) ◽  
pp. 3023-3046
Author(s):  
Alexandre M Harris ◽  
Michael DeGiorgio
Keyword(s):  
Selective Sweep ◽  
Natural Populations ◽  
Haplotype Frequency ◽  
Human Populations ◽  
Ratio Test ◽  
Whole Genome ◽  
Selective Sweeps ◽  
Test Statistic ◽  
Haplotypic Diversity ◽  
Haplotype Data

Abstract Selective sweeps are frequent and varied signatures in the genomes of natural populations, and detecting them is consequently important in understanding mechanisms of adaptation by natural selection. Following a selective sweep, haplotypic diversity surrounding the site under selection decreases, and this deviation from the background pattern of variation can be applied to identify sweeps. Multiple methods exist to locate selective sweeps in the genome from haplotype data, but none leverages the power of a model-based approach to make their inference. Here, we propose a likelihood ratio test statistic T to probe whole-genome polymorphism data sets for selective sweep signatures. Our framework uses a simple but powerful model of haplotype frequency spectrum distortion to find sweeps and additionally make an inference on the number of presently sweeping haplotypes in a population. We found that the T statistic is suitable for detecting both hard and soft sweeps across a variety of demographic models, selection strengths, and ages of the beneficial allele. Accordingly, we applied the T statistic to variant calls from European and sub-Saharan African human populations, yielding primarily literature-supported candidates, including LCT, RSPH3, and ZNF211 in CEU, SYT1, RGS18, and NNT in YRI, and HLA genes in both populations. We also searched for sweep signatures in Drosophila melanogaster, finding expected candidates at Ace, Uhg1, and Pimet. Finally, we provide open-source software to compute the T statistic and the inferred number of presently sweeping haplotypes from whole-genome data.

scholarly journals Soft Selective Sweeps in Evolutionary Rescue

Genetics ◽  
2017 ◽  
Vol 205 (4) ◽  
pp. 1573-1586 ◽  
Author(s):  
Benjamin A. Wilson ◽  
Pleuni S. Pennings ◽  
Dmitri A. Petrov
Keyword(s):  
Selective Sweeps ◽  
Evolutionary Rescue ◽  
Soft Selective Sweeps

scholarly journals A likelihood approach for uncovering selective sweep signatures from haplotype data

2019 ◽  
Author(s):  
Alexandre M. Harris ◽  
Michael DeGiorgio
Keyword(s):  
Selective Sweep ◽  
Natural Populations ◽  
Haplotype Frequency ◽  
Human Populations ◽  
Ratio Test ◽  
Whole Genome ◽  
Selective Sweeps ◽  
Test Statistic ◽  
Haplotypic Diversity ◽  
Haplotype Data

AbstractSelective sweeps are frequent and varied signatures in the genomes of natural populations, and detecting them is consequently important in understanding mechanisms of adaptation by natural selection. Following a selective sweep, haplotypic diversity surrounding the site under selection decreases, and this deviation from the background pattern of variation can be applied to identify sweeps. Multiple methods exist to locate selective sweeps in the genome from haplotype data, but none leverage the power of a model-based approach to make their inference. Here, we propose a likelihood ratio test statistic T to probe whole genome polymorphism datasets for selective sweep signatures. Our framework uses a simple but powerful model of haplotype frequency spectrum distortion to find sweeps and additionally make an inference on the number of presently sweeping haplotypes in a population. We found that the T statistic is suitable for detecting both hard and soft sweeps across a variety of demographic models, selection strengths, and ages of the beneficial allele. Accordingly, we applied the T statistic to variant calls from European and sub-Saharan African human populations, yielding primarily literature-supported candidates, including LCT, RSPH3, and ZNF211 in CEU, SYT1, RGS18, and NNT in YRI, and HLA genes in both populations. We also searched for sweep signatures in Drosophila melanogaster, finding expected candidates at Ace, Uhg1, and Pimet. Finally, we provide open-source software to compute the T statistic and the inferred number of presently sweeping haplotypes from whole-genome data.

scholarly journals Genetic Diversity, Structure, and Selective Sweeps in Spinacia turkestanica Associated With the Domestication of Cultivated Spinach

2021 ◽  
Vol 12 ◽  
Author(s):  
Sanjaya Gyawali ◽  
Gehendra Bhattarai ◽  
Ainong Shi ◽  
Chris Kik ◽  
Lindsey J. du Toit
Keyword(s):  
Genetic Diversity ◽  
Central Asia ◽  
Selective Sweep ◽  
Spinacia Oleracea ◽  
Genomic Region ◽  
Day Length ◽  
Mountain Range ◽  
Nucleotide Polymorphisms ◽  
Selective Sweeps ◽  
Genetic Diversity And Structure

Genotype-by-sequencing (GBS) was used to explore the genetic diversity and structure of Spinacia turkestanica, and the selective sweeps involved in domestication of cultivated spinach, S. oleracea, from S. turkestanica. A total 7,065 single nucleotide polymorphisms (SNPs) generated for 16 Spinacia oleracea and 76 S. turkestanica accessions placed the S. oleracea accessions in one group, Q1, and the 76 S. turkestanica accessions, which originated from Central Asia, in two distinct groups, Q2 and Q3. The Q2 group shared greater genetic identity with the S. oleracea accessions, Q1, than the Q3 S. turkestanica group. Likewise, the S. oleracea Q1 group had a smaller Fst (0.008) with the Q2 group than with the Q3 group (Fst = 0.012), and a greater gene flow (Nm = 30.13) with the Q2 group than with the Q3 group (Nm = 21.83). The Q2 accessions originated primarily from Uzbekistan while the Q3 accessions originated mostly from Tajikistan. The Zarafshan Mountain Range appears to have served as a physical barrier that largely separated members of the Q2 and Q3 groups of S. turkestanica. Accessions with admixtures of Q2 and Q3 were collected primarily from lower elevations at the southern end of the Zarafshan Mountain Range in Uzbekistan. Selective sweep regions identified at 32, 49, and 52 Mb on chromosomes 1, 2, and 3, respectively, appear to have played a vital role in the domestication of S. oleracea as they are correlated with important domestication traits, including day length sensitivity for bolting (flowering). High XP-CLR scores at the 52 Mb genomic region of chromosome three suggest that a selective sweep at this region was responsible for early differentiation of S. turkestanica into two groups in Central Asia.

scholarly journals Diversity patterns and selective sweeps in a Southeast European panel of maize inbred lines as combined with two West European panels

2020 ◽  
Author(s):  
Vlatko Galić ◽  
Violeta Anđelković ◽  
Natalija Kravić ◽  
Nikola Grčić ◽  
Tatjana Ledenčan ◽  
...  
Keyword(s):  
Selective Sweep ◽  
Genetic Material ◽  
Plant Morphology ◽  
Inbred Lines ◽  
Chromosome 2 ◽  
Selective Sweeps ◽  
Phenotypic Analysis ◽  
Maize Breeding ◽  
Favorable Alleles ◽  
Diversity Patterns

AbstractMore than one third of European grain maize is produced in South Eastearn Europe (SEE) and utilization of historical maize material developed in SEE for its favorable alleles and diversity has long been speculated. However, molecular diversity of the SEE maize genetic material is scarce. The objectives of this study were i) to analyze diversity patterns in a large panel of densely genotyped historical accessions from SEE, ii) to compare the data with those obtained from other two European panels, and iii) to identify genomic regions that have undergone selection (selective sweeps) in response to adaptation to SEE conditions. 572 accessions of the historical inbred lines from Maize Research Institute Zemun Polje representing the SEE material were genotyped using the 600k maize genotyping Axiom array. The genotyping results were merged with two European panels DROPS and TUM. Genetic structure and diversity were analyzed using neighbor-joining cladogram, PcoA, Admixture, Structure and sNMF. To detect the selective sweep signals, Tajima’s D statistic and RAiSD were employed. The best number of ancestral populations was K=7, whereby one of them is a subpopulation containing inbreds belong exclusively to the SEE panel. The prevalence of inbreds linked to historical US inbred lines Wf9, Oh43, Pa91 and A374 was detected in SEE. Possible soft selective sweep was detected in chromosome 2 in region harboring a gene linked to promotion of flowering FPF1. Additional scan for selective sweeps using the RAiSD methodology yielded four signals in chromosomes 5 and 6, all in gene-rich regions. Several candidates of selection were identified, influencing the plant morphology and adaptation. Our study provides the first step towards the utilization of the SEE genetic materials for use in maize breeding. Phenotypic analysis is needed for assessment of SEE accessions for favorable alleles, and identification of breeding targets.

scholarly journals Evaluating the performance of selection scans to detect selective sweeps in domestic dogs

2015 ◽  
Author(s):  
Florencia Schlamp ◽  
Julian van der Made ◽  
Rebecca Stambler ◽  
Lewis Chesebrough ◽  
Adam R Boyko ◽  
...  
Keyword(s):  
Artificial Selection ◽  
Population Sample ◽  
Population Bottlenecks ◽  
Selective Sweeps ◽  
Nucleotide Polymorphism ◽  
Genomic Signatures ◽  
Population Genomic ◽  
Dog Domestication ◽  
Soft Selective Sweeps ◽  
Positive Controls

Selective breeding of dogs has resulted in repeated artificial selection on breed-specific morphological phenotypes. A number of quantitative trait loci associated with these phenotypes have been identified in genetic mapping studies. We analyzed the population genomic signatures observed around the causal mutations for 12 of these loci in 25 dog breeds, for which we genotyped 25 individuals in each breed. By measuring the population frequencies of the causal mutations in each breed, we identified those breeds in which specific mutations most likely experienced positive selection. These instances were then used as positive controls for assessing the performance of popular statistics to detect selection from population genomic data. We found that artificial selection during dog domestication has left characteristic signatures in the haplotype and nucleotide polymorphism patterns around selected loci that can be detected in the genotype data from a single population sample. However, the sensitivity and accuracy at which such signatures were detected varied widely between loci, the particular statistic used, and the choice of analysis parameters. We observed examples of both hard and soft selective sweeps and detected strong selective events that removed genetic diversity almost entirely over regions >10 Mbp. Our study demonstrates the power and limitations of selection scans in populations with high levels of linkage disequilibrium due to severe founder effects and recent population bottlenecks.

scholarly journals The complex genomic basis of rapid convergent adaptation to pesticides across continents in a fungal plant pathogen

2020 ◽  
Author(s):  
Fanny E. Hartmann ◽  
Tiziana Vonlanthen ◽  
Nikhil Kumar Singh ◽  
Megan McDonald ◽  
Andrew Milgate ◽  
...  
Keyword(s):  
Selective Sweep ◽  
De Novo ◽  
Association Studies ◽  
Strong Support ◽  
Phenotypic Trait ◽  
Phenotypic Traits ◽  
Genome Wide Association Studies ◽  
Zymoseptoria Tritici ◽  
Standing Variation ◽  
Genome Wide

AbstractConvergent evolution leads to identical phenotypic traits in different species or populations. Convergence can be driven by standing variation allowing selection to favor identical alleles in parallel or the same mutations can arise independently. However, the molecular basis of such convergent adaptation remains often poorly resolved. Pesticide resistance in agricultural ecosystems is a hallmark of convergence in phenotypic traits. Here, we analyze the major fungal pathogen Zymoseptoria tritici causing serious losses on wheat and with parallel fungicide resistance emergence across continents. We sampled three population pairs each from a different continent spanning periods early and late in the application of fungicides. To identify causal loci for resistance, we combined knowledge from molecular genetics work and performed genome-wide association studies (GWAS) on a global set of isolates. We discovered yet unknown factors in azole resistance including membrane stability functions. We found strong support for the ‘hotspot’ model of resistance evolution with parallel changes in a small set of loci but additional loci showed more population-specific allele frequency changes. Genome-wide scans of selection showed that half of all known resistance loci were overlapping a selective sweep region. Hence, the application of fungicides was one of the major selective agents acting on the pathogen over the past decades. Furthermore, loci identified through GWAS showed the highest overlap with selective sweep regions underlining the importance to map phenotypic trait variation in evolving populations. Our population genomic analyses showed that both de novo mutations and gene flow likely contributed to the parallel emergence of resistance.

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