The population genetics of partial diapause, with applications to the aestivating malaria mosquito Anopheles coluzzii.

Diapause, a form of dormancy to delay or halt the reproductive development during unfavourable seasons, has evolved in many insect species. One example is aestivation, an adult-stage diapause enhancing malaria vectors' survival during the dry season (DS) and their re-establishment in the next rainy season (RS). This work develops a novel genetic approach to estimate the number or proportion of individuals undergoing diapause, as well as the breeding sizes of the two seasons, using signals from temporal allele frequency dynamics. Our modelling shows the magnitude of drift is dampened at early RS when previously aestivating individuals reappear. Aestivation severely biases the temporal effective population size ( N e $$ {N}_e $$ ), leading to overestimation of the DS breeding size by 1 / 1 - α 2 $$ 1/{\left(1-\alpha \right)}^2 $$ across 1 year, where α $$ \alpha $$ is the aestivating proportion. We find sampling breeding individuals in three consecutive seasons starting from an RS is sufficient for parameter estimation, and perform extensive simulations to verify our derivations. This method does not require sampling individuals in the dormant state, the biggest challenge in most studies. We illustrate the method by applying it to a published data set for Anopheles coluzzii mosquitoes from Thierola, Mali. Our method and the expected evolutionary implications are applicable to any species in which a fraction of the population diapauses for more than one generation, and are difficult or impossible to sample during that stage.

Potential persistence mechanisms of the major Anopheles gambiae species complex malaria vectors in sub-Saharan Africa: a narrative review.

The source of malaria vector populations that re-establish at the beginning of the rainy season is still unclear yet knowledge of mosquito behaviour is required to effectively institute control measures. Alternative hypotheses like aestivation, local refugia, migration between neighbouring sites, and long-distance migration (LDM) are stipulated to support mosquito persistence. This work assessed the malaria vector persistence dynamics and examined various studies done on vector survival  via these hypotheses; aestivation, local refugia, local or long-distance migration across sub-Saharan Africa, explored a range of methods used, ecological parameters and highlighted the knowledge trends and gaps. The results about a particular persistence mechanism that supports the re-establishment of Anopheles gambiae, Anopheles coluzzii or Anopheles arabiensis in sub-Saharan Africa were not conclusive given that each method used had its limitations. For example, the Mark-Release-Recapture (MRR) method whose challenge is a low recapture rate that affects its accuracy, and the use of time series analysis through field collections whose challenge is the uncertainty about whether not finding mosquitoes during the dry season is a weakness of the conventional sampling methods used or because of hidden shelters. This, therefore, calls for further investigations emphasizing the use of ecological experiments under controlled conditions in the laboratory or semi-field, and genetic approaches, as they are known to complement each other. This review, therefore, unveils and assesses the uncertainties that influence the different malaria vector persistence mechanisms and provides recommendations for future studies.

Resistance to a CRISPR-based gene drive at an evolutionarily conserved site is revealed by mimicking genotype fixation.

CRISPR-based homing gene drives can be designed to disrupt essential genes whilst biasing their own inheritance, leading to suppression of mosquito populations in the laboratory. This class of gene drives relies on CRISPR-Cas9 cleavage of a target sequence and copying ('homing') therein of the gene drive element from the homologous chromosome. However, target site mutations that are resistant to cleavage yet maintain the function of the essential gene are expected to be strongly selected for. Targeting functionally constrained regions where mutations are not easily tolerated should lower the probability of resistance. Evolutionary conservation at the sequence level is often a reliable indicator of functional constraint, though the actual level of underlying constraint between one conserved sequence and another can vary widely. Here we generated a novel adult lethal gene drive (ALGD) in the malaria vector Anopheles gambiae, targeting an ultra-conserved target site in a haplosufficient essential gene (AGAP029113) required during mosquito development, which fulfils many of the criteria for the target of a population suppression gene drive. We then designed a selection regime to experimentally assess the likelihood of generation and subsequent selection of gene drive resistant mutations at its target site. We simulated, in a caged population, a scenario where the gene drive was approaching fixation, where selection for resistance is expected to be strongest. Continuous sampling of the target locus revealed that a single, restorative, in-frame nucleotide substitution was selected. Our findings show that ultra-conservation alone need not be predictive of a site that is refractory to target site resistance. Our strategy to evaluate resistance in vivo could help to validate candidate gene drive targets for their resilience to resistance and help to improve predictions of the invasion dynamics of gene drives in field populations.

Contemporary Ne estimation using temporally spaced data with linked loci.

The contemporary effective population size N e is important in many disciplines including population genetics, conservation science and pest management. One of the most popular methods of estimating this quantity uses temporal changes in allele frequency due to genetic drift. A significant assumption of the existing methods is the independence among loci while constructing confidence intervals (CI), which restricts the types of species or genetic data applicable to the methods. Although genetic linkage does not bias point N e estimates, applying these methods to linked loci can yield unreliable CI that are far too narrow. We extend the current methods to enable the use of many linked loci to produce precise contemporary N e estimates, while preserving the targeted CI width and coverage. This is achieved by deriving the covariance of changes in allele frequency at linked loci in the face of recombination and sampling errors, such that the extra sampling variance due to between-locus correlation is properly handled. Extensive simulations are used to verify the new method. We apply the method to two temporally spaced genomic data sets of Anopheles mosquitoes collected from a cluster of villages in Burkina Faso between 2012 and 2014. With over 33,000 linked loci considered, the N e estimate for Anopheles coluzzii is 9,242 (95% CI 5,702-24,282), and for Anopheles gambiae it is 4,826 (95% CI 3,602-7,353).

Estimating linkage disequilibrium from genotypes under Hardy-Weinberg equilibrium.

BACKGROUND: Measures of linkage disequilibrium (LD) play a key role in a wide range of applications from disease association to demographic history estimation. The true population LD cannot be measured directly and instead can only be inferred from genetic samples, which are unavoidably subject to measurement error. Previous studies of r2 (a measure of LD), such as the bias due to finite sample size and its variance, were based on the special case that the true population-wise LD is zero. These results generally do not hold for non-zero [Formula: see text] values, which are more common in real genetic data. RESULTS: This work generalises the estimation of r2 to all levels of LD, and for both phased and unphased data. First, we provide new formulae for the effect of finite sample size on the observed r2 values. Second, we find a new empirical formula for the variance of the observed r2, equals to 2E[r2](1 - E[r2])/n, where n is the diploid sample size. Third, we propose a new routine, Constrained ML, a likelihood-based method to directly estimate haplotype frequencies and r2 from diploid genotypes under Hardy-Weinberg Equilibrium. While serving the same purpose as the pre-existing Expectation-Maximisation algorithm, the new routine can have better convergence and is simpler to use. A new likelihood-ratio test is also introduced to test for the absence of a particular haplotype. Extensive simulations are run to support these findings. CONCLUSION: Most inferences on LD will benefit from our new findings, from point and interval estimation to hypothesis testing. Genetic analyses utilising r2 information will become more accurate as a result.

Partitioning the contributions of alternative malaria vector species.

BACKGROUND: In many locations malaria is transmitted by more than one vector species. Some vector control interventions, in particular those using genetic approaches, are likely to be targeted against a single species or species complex, at least initially, and it would therefore be useful to be able to predict the epidemiological impact of controlling a single species when multiple vector species are present. METHODS: To address this issue, the classical Ross-McDonald model of malaria epidemiology is expanded to account for multiple vector species, giving expressions for the equilibrium prevalence, sporozoite rates and reproductive number. These allow one to predict when control of just one vector species will lead to elimination of the disease. Application of the model is illustrated using published data from a particularly extensive entomological and epidemiological survey before the rollout of bed nets in eastern Kenya, where Anopheles gambiae s.l. and An. funestus were vectors. RESULTS: Meta-analysis indicates that sporozoite rates were 38 % higher in An. gambiae s.l. than in An. funestus, and, according to the model, this difference could be due to An. gambiae s.l. having a higher frequency of feeding on humans, a higher human-to-mosquito transmission rate, a lower adult mortality rate, and/or a shorter incubation period. Further calculations suggest that An. gambiae s.l. would have been sufficient to maintain transmission by itself throughout the region, whereas An. funestus would not have been able to support transmission by itself in Malindi District. CONCLUSIONS: Partitioning the contributions of different vector species may allow us to predict whether malaria will persist after targeted vector control.

Estimating effective population size from temporally spaced samples with a novel, efficient maximum-likelihood algorithm.

The effective population size [Formula: see text] is a key parameter in population genetics and evolutionary biology, as it quantifies the expected distribution of changes in allele frequency due to genetic drift. Several methods of estimating [Formula: see text] have been described, the most direct of which uses allele frequencies measured at two or more time points. A new likelihood-based estimator [Formula: see text] for contemporary effective population size using temporal data is developed in this article. The existing likelihood methods are computationally intensive and unable to handle the case when the underlying [Formula: see text] is large. This article tries to work around this problem by using a hidden Markov algorithm and applying continuous approximations to allele frequencies and transition probabilities. Extensive simulations are run to evaluate the performance of the proposed estimator [Formula: see text], and the results show that it is more accurate and has lower variance than previous methods. The new estimator also reduces the computational time by at least 1000-fold and relaxes the upper bound of [Formula: see text] to several million, hence allowing the estimation of larger [Formula: see text]. Finally, we demonstrate how this algorithm can cope with nonconstant [Formula: see text] scenarios and be used as a likelihood-ratio test to test for the equality of [Formula: see text] throughout the sampling horizon. An R package "NB" is now available for download to implement the method described in this article.