Biology subjects

Messer, P. W.

Publications and source records attributed to Messer, P. W..

10 recordsLinked to original sources

bioRxiv2018

Population dynamics of underdominance gene drive systems in continuous space

Underdominance gene drive systems promise a mechanism for rapidly spreading payload alleles through a local population while otherwise remaining confined, unable to spread into neighboring populations due to their frequency-dependent dynamics. Such systems could provide a new tool in the fight against vector-borne diseases by disseminating transgenic payloads through vector populations. If local confinement can indeed be achieved, the decision-making process for the release of such constructs would likely be considerably simpler compared to other gene drive mechanisms such as CRISPR homing drives. So far, the confinement ability of underdominance systems has only been demonstrated in models of panmictic populations linked by migration. How such systems would behave in realistic populations where individuals move over continuous space remains largely unknown. Here, we study several underdominance systems in continuous-space population models and show that their dynamics are drastically altered from those in panmictic populations. Specifically, we find that all underdominance systems we studied can fail to persist in such environments, even after successful local establishment. At the same time, we find that a two-locus two-toxin-antitoxin system can still successfully invade neighboring populations in many scenarios even under weak migration. This suggests that the parameter space for underdominance systems to both establish in a given region and remain confined to that region would likely be highly limited. Overall, these results indicate that spatial context must be considered when assessing strategies for the deployment of underdominance systems.

genetics↗

bioRxiv2018

Multiple loci of small effect confer wide variability in efficiency and resistance rate of CRISPR gene drive

Gene drives could allow for control of vector-borne diseases by directly suppressing vector populations or spreading genetic payloads designed to reduce pathogen transmission. CRISPR homing gene drives work by cleaving wild-type alleles, which are then converted to drive alleles by homology-directed repair, increasing the frequency of the drive in a population. However, resistance alleles can form when end-joining repair takes place in lieu of homology-directed repair. Such alleles cannot be converted to drive alleles, which would halt the spread of a drive through a population. To investigate the effects of natural genetic variation on resistance formation, we developed a CRISPR homing gene drive in Drosophila melanogaster and crossed it into the genetically diverse Drosophila Genetic Reference Panel (DGRP) lines, measuring several performance parameters. Most strikingly, resistance allele formation post-fertilization in the early embryo ranged from 7% to 79% among lines and averaged 42{+/-}18%. We performed a Genome-Wide Association Study (GWAS) using our results in the DGRP lines and found that the resistance and conversion rates were polygenic, with several genetic polymorphisms showing relatively weak association. RNAi knockdown of several of these genes confirmed their effect, but their small effect sizes implies that their manipulation will yield only modest improvements to the efficacy of gene drives.

genetics↗

bioRxiv2018

SLiM 3: Forward genetic simulations beyond the Wright-Fisher model

With the desire to model population genetic processes under increasingly realistic scenarios, forward genetic simulations have become a critical part of the toolbox of modern evolutionary biology. The SLiM forward genetic simulation framework is one of the most powerful and widely used tools in this area. However, its foundation in the Wright-Fisher model has been found to pose an obstacle to implementing many types of models; it is difficult to adapt the Wright-Fisher model, with its many assumptions, to modeling ecologically realistic scenarios such as explicit space, overlapping generations, individual variation in reproduction, density-dependent population regulation, individual variation in dispersal or migration, local extinction and recolonization, mating between subpopulations, age structure, fitness-based survival and hard selection, emergent sex ratios, and so forth. In response to this need, we here introduce SLiM 3, which contains two key advancements aimed at abolishing these limitations. First, the new non-Wright-Fisher or \"nonWF\" model type provides a much more flexible foundation that allows the easy implementation of all of the above scenarios and many more. Second, SLiM 3 adds support for continuous space, including spatial interactions and spatial maps of environmental variables. We provide a conceptual overview of these new features, and present several example models to illustrate their use. These two key features allow SLiM 3 models to go beyond the Wright-Fisher model, opening up new horizons for forward genetic modeling.

evolutionary biology↗

bioRxiv2018

Molecular safeguarding of CRISPR gene drive experiments

CRISPR-based gene drives have sparked both enthusiasm and deep concerns due to their potential for genetically altering entire species. This raises the question about our ability to prevent the unintended spread of such drives from the laboratory into a natural population. Here, we experimentally demonstrate the suitability of synthetic target sites and split drives as flexible safeguarding strategies for gene drive experiments.

genetics↗

bioRxiv2018

Tree-sequence recording in SLiM opens new horizons for forward-time simulation of whole genomes

There is an increasing demand for evolutionary models to incorporate relatively realistic dynamics, ranging from selection at many genomic sites to complex demography, population structure, and ecological interactions. Such models can generally be implemented as individual-based forward simulations, but the large computational overhead of these models often makes simulation of whole chromosome sequences in large populations infeasible. This situation presents an important obstacle to the field that requires conceptual advances to overcome. The recently developed tree-sequence recording method (Kelleher et al., 2018), which stores the genealogical history of all genomes in the simulated population, could provide such an advance. This method has several benefits: (1) it allows neutral mutations to be omitted entirely from forward-time simulations and added later, thereby dramatically improving computational efficiency; (2) it allows neutral burn-in to be constructed extremely efficiently after the fact, using \"recapitation\"; (3) it allows direct examination and analysis of the genealogical trees along the genome; and (4) it provides a compact representation of a populations genealogy that can be analyzed in Python using the msprime package. We have implemented the tree-sequence recording method in SLiM 3 (a free, open-source evolutionary simulation software package) and extended it to allow the recording of non-neutral mutations, greatly broadening the utility of this method. To demonstrate the versatility and performance of this approach, we showcase several practical applications that would have been beyond the reach of previously existing methods, opening up new horizons for the modeling and exploration of evolutionary processes.

evolutionary biology↗

bioRxiv2018

Maximum likelihood estimation of fitness components in experimental evolution

Estimating fitness differences between allelic variants is a central goal of experimental evolution. Current methods for inferring selection from allele frequency time series typically assume that evolutionary dynamics at the locus of interest can be described by a fixed selection coefficient. However, fitness is an aggregate of several components including mating success, fecundity, and viability, and distinguishing between these components could be critical in many scenarios. Here we develop a flexible maximum likelihood framework that can disentangle different components of fitness and estimate them individually in males and females from genotype frequency data. As a proof-of-principle, we apply our method to experimentally-evolved cage populations of Drosophila melanogaster, in which we tracked the relative frequencies of a loss-of-function and wild-type allele of yellow. This X-linked gene produces a recessive yellow phenotype when disrupted and is involved in male courtship ability. We find that the fitness costs of the yellow phenotype take the form of substantially reduced mating preference of wild-type females for yellow males, together with a modest reduction in the viability of yellow males and females. Our framework should be generally applicable to situations where it is important to quantify fitness components of specific genetic variants, including quantitative characterization of the population dynamics of CRISPR gene drives.

evolutionary biology↗

bioRxiv2018

Signatures of insecticide selection in the genome of Drosophila melanogaster.

Resistance to insecticides has evolved in multiple insect species, leading to increased application rates and even control failures. Understanding the genetic basis of insecticide resistance is fundamental for mitigating its impact on crop production and disease control. We performed a GWAS approach with the Drosophila Genetic Reference Panel (DGRP) to identify the mutations involved in resistance to two widely used classes of insecticides: organophosphates (OPs, parathion) and pyrethroids (deltamethrin). Most variation in parathion resistance was associated with mutations in the target gene Ace, while most variation in deltamethrin resistance was associated with mutations in Cyp6a23, a gene encoding a detoxification enzyme never previously associated with resistance. A \"nested GWAS\" further revealed the contribution of other loci: Dscam1 and trpl were implicated in resistance to parathion, but only in lines lacking Wolbachia. Cyp6a17, the paralogous gene of Cyp6a23, and CG7627, an ATP-binding cassette transporter, were implicated in deltamethrin resistance. We observed signatures of recent selective sweeps at all of these resistance loci and confirmed that the soft sweep at Ace is indeed driven by the identified resistance mutations. Analysis of allele frequencies in additional population samples revealed that most resistance mutations are segregating across the globe, but that frequencies can vary substantially among populations. Altogether, our data reveal that the widely used OP and pyrethroid insecticides imposed a strong selection pressure on natural insect populations. However, it remains unclear why, in Drosophila, resistance evolved due to changes in the target site for OPs, but due to a detoxification enzyme for pyrethroids.\n\nArticle summaryInsecticides are widely used to control pests and insect vectors of disease. In response to the strong selection pressure exerted by insecticides, resistance has evolved in most insect species. We identified few genes present in several Drosophila melanogaster natural populations implicated in the evolution of resistance against two insecticides widely used today. We identified primary and secondary genes involved in the resistance. Surprisingly, resistance evolved in the target site for one insecticide, but was associated to changes in a novel detoxification enzyme for the other insecticide.

evolutionary biology↗

bioRxiv2017

Reducing resistance allele formation in CRISPR gene drives

CRISPR gene drives can efficiently convert heterozygous cells with one copy of the drive allele into homozygotes, thereby enabling super-Mendelian inheritance. This mechanism could be used, for example, to rapidly disseminate a genetic payload through a population, promising novel strategies for the control of vector-borne diseases. However, all CRISPR gene drives tested have produced significant quantities of resistance alleles that cannot be converted to drive alleles and would likely prevent these drives from spreading in a natural population. In this study, we assessed three strategies for reducing resistance allele formation. First, we directly compared drives with the nanos and vasa promoters, which showed that the vasa drive produced high levels of resistance alleles in somatic cells. This was not observed in the nanos drive. Another strategy was the addition of a second gRNA to the drive, which both significantly increased the drive conversion efficiency and reduced the formation rate of resistance alleles. Finally, to minimize maternal carryover of Cas9, we assessed the performance of an autosomal drive acting in the male germline, and found no subsequent formation of resistance alleles in embryos. Our results mark a step toward developing effective gene drives capable of functioning in natural populations and provide several possible avenues for further reduction of resistance rates.

genetics↗

bioRxiv2017

Novel CRISPR/Cas9 gene drive constructs in Drosophila reveal insights into mechanisms of resistance allele formation and drive efficiency in genetically diverse populations

A functioning gene drive system could fundamentally change our strategies for the control of vector-borne diseases by facilitating rapid dissemination of transgenes that prevent pathogen transmission or reduce vector capacity. CRISPR/Cas9 gene drive promises such a mechanism, which works by converting cells that are heterozygous for the drive construct into homozygotes, thereby enabling super-Mendelian inheritance. Though CRISPR gene drive activity has already been demonstrated, a key obstacle for current systems is their propensity to generate resistance alleles. In this study, we developed two CRISPR gene drive constructs based on the nanos and vasa promoters that allowed us to illuminate the different mechanisms by which resistance alleles are formed in the model organism Drosophila melanogaster. We observed resistance allele formation at high rates both prior to fertilization in the germline and post-fertilization in the embryo due to maternally deposited Cas9. Assessment of drive activity in genetically diverse backgrounds further revealed substantial differences in conversion efficiency and resistance rates. Our results demonstrate that the evolution of resistance will likely impose a severe limitation to the effectiveness of current CRISPR gene drive approaches, especially when applied to diverse natural populations.

genetics↗

bioRxiv2017

asymptoticMK: A web-based tool for the asymptotic McDonald-Kreitman test

The McDonald-Kreitman (MK) test is a widely used method for quantifying the role of positive selection in molecular evolution. One key shortcoming of this test lies in its sensitivity to the presence of slightly deleterious mutations, which can severely bias its estimates. An asymptotic version of the MK test was recently introduced that addresses this problem by evaluating polymorphism levels for different mutation frequencies separately, and then extrapolating a function fitted to that data. Here we present asymptoticMK, a web-based implementation of this asymptotic McDonald-Kreitman test. Our web service provides a simple R-based interface into which the user can upload the required data (polymorphism and divergence data for the genomic test region and a neutrally evolving reference region). The web service then analyzes the data and provides plots of the test results. This service is free to use, open-source, and available at http://benhaller.com/messerlab/asymptoticMK.html.

evolutionary biology↗