Biology subjects

Kanitz, R.

Publications and source records attributed to Kanitz, R..

6 recordsLinked to original sources

bioRxiv2026

Evaluating pesticide mixtures for resistance management in asexual insect pests

Many economically important insect pests reproduce through asexual or partially asexual life cycles, yet how reproductive mode influences insecticide resistance management remains unclear. The choice of resistance management strategy has been suggested to differ for sexual and asexual pests. For instance, current IRAC guidance suggests that pesticide mixtures are less effective in non-mating pests than in sexually reproducing populations. Here, stochastic evolutionary simulations are used to compare resistance evolution under sequences and mixtures across four reproductive modes observed in pests of economic importance: sexual reproduction, obligate parthenogenesis, cyclical parthenogenesis and haplodiploidy. Contrary to current expectations, mixtures are not disadvantaged in asexual populations and, in some cases, lead to delayed resistance evolution compared to sexually reproducing populations. These differences arise as the result of reduced genetic recombination which constrained the assembly and spread of multi-resistant genotypes. Overall, these findings suggest that mixtures remain a viable resistance management strategy for pests with asexual reproduction.

evolutionary biology↗

bioRxiv2026

Constraining pesticide resistance using evolution-informed selection regimes

The rapid evolution of pesticide resistance in sexually reproducing pests threatens global food security, yet the evolutionary principles needed to design durable resistance management strategies remain poorly tested experimentally. Theory predicts that deploying multiple pesticide compounds simultaneously should suppress resistance more effectively than sequential rotations, but empirical support in sexual pest populations has remained inconclusive. Here, we directly test how selection regime shapes resistance evolution using a genetically defined, obligately mating Caenorhabditis elegans system. We evolved large dioecious populations from a near-isogenic ancestor carrying two major-effect resistance alleles under contrasting pesticide deployment regimes. We show that compound mixtures combined with a substantial refuge consistently produced the strongest constraint on resistance evolution, markedly slowing the spread of resistance even when resistance alleles were neither recessive nor rare. Species-agnostic computational simulations reproduced the overall evolutionary dynamics, suggesting broad applicability. Overall, our results provide direct experimental evidence that pesticide resistance evolution can be predictably constrained by manipulating selection regimes.

evolutionary biology↗

bioRxiv2025

A synoptic solution to a Wright-Fisher model with recurrent mutation, drift and selection

The time to fixation (conditional upon fixation) and probability of fixation are key summary statistics of classical population genetics. Here, they are integrated to solve the time to fixation unconditional on fixation in a Wright-Fisher model with recurrent mutation, drift and selection. In its derivation, minor improvements to the probability of fixation and the probability distributions of emergence and spread (or passage) are made. The solution is an exponentially modified Gaussian (ex-Gaussian) distribution with a mean and variance that is the sum of the mean and variance of the underlying exponential and normal (i.e. Gaussian) distributions. To demonstrate its value as a synoptic solution to the Wright-Fisher model, the ex-Gaussian distribution is used to partition the effects of the evolutionary forces of mutation, drift, selection and (to some extent) migration on chosen points of the probability distribution of fixation times. Further, the solution is used to derive (and show the quantitative meaning of) the stochastic drift barrier to nearly neutral mutations with very low selection coefficients, and its consequences on the probability distribution of phenotypic and/or fitness effects that contribute to adaptation. In this way, the probability distribution of the time to fixation unconditional on fixation provides an elegant summary of some key results from classical population genetics, and is also likely to have many other theoretical and applied uses.

evolutionary biology↗

bioRxiv2024

Tuning Spatial Distributions of Selection Pressure to Suppress Emergence of Resistance

Control measures such as insecticides or antimicrobials are used to contain biological agents such as pathogenic bacteria and vectors of human and plant diseases, respectively. Following control measure application, a resistant subpopulation may eventually rise to such frequency that the control measure will be rendered ineffective: The timescale over which this occurs is the effective lifetime of the control measure. Prolonging this timescale relaxes urgency at which novel control measure needs to be developed. Spatial heterogeneity in control measure application can influence the rate at which resistance to the control measure evolves; in the agricultural context, this fact is exploited by distributing insecticides in mosaics across cropping regions in order to slow the rate of resistance evolution. Contemporary and historical modeling practices, which aim to inform agricultural practices, often employ assumptions which squeeze out the impact of the spatio-temporal heterogeneity endemic to nature. In this paper, we present a minimal model of continuous dispersal and spatio-temporal heterogeneity in selection pressure distribution which exhibits a novel dynamic: The spatial distribution of selection pressure may be tuned in order to minimize the initial rate at which resistance evolves, thus increasing the effective lifetime of a pesticide. Author summaryThere are many contexts in which humans apply control measures to biological agents: pesticides are applied in fields to kill the pests that damage crops, mosquito nests are distributed to prevent the spread of malaria, and cancer drugs are applied to kill off tumors in humans. These control measures are examples of selection pressures, which select against strains which are susceptible to them. If a mutation occurs which confers resistance, the control agent will select for the resistant strain, thus reducing the efficacy of the control agent as the frequency of resistance increases in the population. This necessitates more of the control agent to be applied, or for a novel control agent to be developed. The former may have unintended consequences on the local environment, and the latter is expensive and time-intensive. It is preferable to carefully tune how the control agent is applied - perhaps instead of one massive compact region of control measure application, it is better to apply the control measure over multiple smaller regions? Here, we use a toy model of motile organisms to demonstrate that an optimal distribution exists for a variety of scenarios.

evolutionary biology↗

bioRxiv2018

Assessing natural selection during range expansions: Insights from a spatially explicit ABC study

For at least 40 years now, evolutionary biologists have discussed the relative roles of natural selection and genetic drift in shaping the genetic composition of populations. Range expansions are of particular interest in this discussion: They normally occur over environmental gradients allowing local adaptation to take place, but the demographic properties of these expansions also potentiate genetic-drift effects, which may in turn randomly generate extreme changes in allele frequencies as populations expand in territory and numbers (i.e. allele surfing). Here, we address the detection and measurement of selection in such scenario using simulations. We mimic a range expansion over a variable selective gradient where individuals have in their genomes both loci that are neutral and loci determining a quantitative trait subject to selection. The responsiveness of summary statistics to the selective pressure is then assessed, and estimates of the selective pressure are made - based on these statistics - with approximate Bayesian computation (ABC). We observe that statistics related to isolation-by-distance patterns present a strong response to selection. This response can be used in ABC to estimate the strength of selection acting on the simulated populations with very reliable measures of estimability, regardless of the genetic architecture underlying the selected trait. Furthermore, these estimates are robust to noise produced by other genetic and demographic parameters such as heritability, mutation, migration and population-growth rates. This approach of taking into account the spatial dimension of differentiation in quantitative traits offers a promising avenue of investigation about the role of natural selection in range-expansion scenarios, with possible implementations in the study of natural cases, as well.

evolutionary biology↗

bioRxiv2017

Complex genetic patterns in human arise from a simple range-expansion model over continental landmasses

Although it is generally accepted that geography is a major factor shaping human genetic differentiation, it is still disputed how much of this differentiation is a result of a simple process of isolation-by-distance, and if there are factors generating distinct clusters of genetic similarity. We address this question using a geographically explicit simulation framework coupled with an Approximate Bayesian Computation approach. Based on six simple summary statistics only, we estimated the most probable demographic parameters that shaped modern human evolution under an isolation by distance scenario, and found these were the following: an initial population in East Africa spread and grew from 4000 individuals to 5.7 million in about 132 000 years. Subsequent simulations with these estimates followed by cluster analyses produced results nearly identical to those obtained in real data. Thus, a simple diffusion model from East Africa explains a large portion of the genetic diversity patterns observed in modern humans. We argue that a model of isolation by distance along the continental landmasses might be the relevant null model to use when investigating selective effects in humans and probably many other species.

genetics↗