A common gene drive language eases regulatory process and eco-evolutionary extensions

Abstract

3Synthetic gene drive technologies aim to spread transgenic constructs into wild 4 populations even when they impose organismal fitness disadvantages. The prop-5 erties of gene drive constructs are diverse and depend on their molecular con-6 struction, and differential selection pressure they impose in the varied ecological 7 situations they encounter. The extraordinary diversity of conceivable drive mech-8 anisms and the range of selective parameters they may encounter makes it very 9 difficult to convey their relative predicted properties. The sheer number of pub-10 lished manuscripts in this field, experimental and theoretical, is a testament to the 11 possibilities presented by this technology. We evaluate and condense the essen-12 tial synthetic drive mechanisms from a variety of studies and present a unified 13 mathematical paradigm (and a user-friendly tool DrMxR Drive Mixer) describing 14 the properties of a wide variety of single construct gene drives (non-suppression). 15 Within this common framework, we have been able to recapitulate key published 16 results derived using bespoke modelling frameworks. Because a unified frame-17 work is employed, it is also possible to seamlessly explore the consequences 18 of combining multiple drive approaches within a single construct. We provide a 19 1 method for analytically assessing the measure of invasiveness of a drive con-20 struct. As opposed to typical studies of synthetic drives, we explore the resilience 21 of such drives in a spatially explicit manner advancing the connection between 22 realistic spatial dynamics and typical well-mixed populations. Besides a scientific 23 advance, our results and the tools provided an intuitive and objective way for regu-24 lators, scientists and NGOs to evaluate the properties and robustness of proposed 25 and future gene drive approaches. 30Drosophila melanogaster imposes an enormous organismal fitness cost, in that it is 31 homozygous lethal (and only viable as heterozygotes) [Sandler et al., 1959, Sandler 32 and Golic, 1985, Crow, 1991. Consequently, in most circumstances, natural selec-33 tion, at the organismal level would act to eliminate the SD allele. However, because 34 of its capacity to bias the production of SD functional sperm in +/SD heterozygotes, 35 the allele has rapidly increased to an equilibrium frequency of 1-5% in most natural 36 populations around the globe [Hartl, 1975, Hiraizumi and Thomas, 1984, Brand et al., 37 2015]. This natural drive element illustrates how drive elements can increase in fre-38 quency even where there is a substantial cost to (overall) organismal fitness. Since 39 the development of molecular biological techniques, there has been an interest in de-40 veloping synthetic drive elements used to push linked genes into wild populations in a 41 self-perpetuating manner. This is generally termed replacement drive, to distinguish 42 from suppression drive that aims to reduce or completely eradicate the size of target 43 populations upon release. 44 As in ...

The effect of mating complexity on gene drive dynamics

“… The above constraints on frequencies allow us to represent the dynamics of equation (2) on a de Finetti diagram. The frequency of the three genotypes (WW, WD and DD) without mate-choice ( h = 0) converge to Hardy Weinberg equilibrium (Gokhale et al, 2014; Verma et al, 2021). When we introduce the mate-choice parameter into the rate equations (1), the dynamics deviate from Hardy Weinberg equilibrium and is governed by the fixed points that appear in the interior of the de Finetti diagram.…”

“…Hence, an individual can be either of the three genotypes: WW, DD and WD. Previous work has shown that the gene drive can arise if a drive carrying genotype undergoes distortion, viability or fertility selection that acts during the different life stages of an organism (Verma et al, 2021). Hence, one can categorize various gene drive systems based on pre-existing standard population-genetic terminology (distortion, fertility selection and viability selection).…”

“…Hence, one can categorize various gene drive systems based on pre-existing standard population-genetic terminology (distortion, fertility selection and viability selection). Manipulating the strength of these forces via the engineered construct influences the probability of inheritance, giving rise to gene drive (Verma et al, 2021). Gene drives can also be classified into two types based on the purpose of the release: modification and suppression drives.…”

“…Although we use different modelling frameworks for different mating complexities, the underlying gene drive model extends from a standard population genetic perspective. Gene drive systems have previously been categorized based on standard terminology; distortion in gamete proportions, fertility selection and viability selection (Verma et al, 2021). The need for such a common language across gene drive literature has been extolled by experts and regulators alike (Alphey et al, 2020).…”

Rescue by gene swamping as a gene drive deployment strategy

“…In terms of the underlying population structure and selection pressures, two main modeling approaches have been developed: (i) discrete populations connected by migration, in which the gene drive allele frequency is tracked disregarding demographic changes, implying soft selection [6]; (ii) continuous space, where gene drive spread is modeled through spatial-demographic effects [5, 16, 19, 20]. These two approaches emphasize different aspects of selection affecting the gene drive allele frequency: in the initial stage of deployment, spread of the gene drive will depend mainly on direct competition between the gene drive and wild type alleles (i.e., soft selection) whereas at high frequencies the reduced fitness is expected to reduce the size of the population (i.e., hard selection).…”