Biology subjects

Hui, T.-Y. J.

Publications and source records attributed to Hui, T.-Y. J..

8 recordsLinked to original sources

bioRxiv2026

Accounting for pseudo-replication of Linkage Disequilibrium for contemporary Ne estimation

The Linkage Disequilibrium (LD) of unlinked loci can be used to estimate contemporary effective population size (Ne) of one to a few generations ago. In genomic datasets loci on different chromosomes are considered unlinked, but there are many more pairs of unlinked loci than there are independent pairs of chromosomes, resulting to confidence intervals (C.I.) being too narrow if the non-independence is not taken into account. Simulations were run to investigate the correlation structure among LD of unlinked loci, which can be expressed by the LD of loci along the same chromosomes, based on a discovery of a novel Random Probe LD estimator. We classify the correlation into two categories: overlapping of loci and disjoint pairs. The former is induced from the same locus being considered twice and is the stronger form of correlation. These correlations feed into {rho}, a parameter to quantify the degree of pseudo-replication in a dataset, and further a correction formula from which C.I. can be properly inferred. We demonstrate the use of our method via an analysis of genomic data from the malaria-transmitting Anopheles gambiae s.s mosquitoes. Apart from the point and C.I. estimates, we find that Var((r^2 ) ) is inflated by about 550 times due to pseudo-replication, highlighting the danger of not handling genetic correlation properly.

bioinformatics↗

bioRxiv2026

A novel unbiased Linkage Disequilibrium estimator through Random Probing

The linkage disequilibrium (LD) or correlation of alleles at different loci is a fundamental statistic in population genetics. This work presents a new estimator for the standardised LD measure r^2 between a pair of loci. The Random Probe (RP) estimator involves generating a set of random dummy loci, before calculating the r^2 between each synthetic locus and the two focal loci using one of the existing estimators (even it is known to be biased). The correlation between the two vectors of r^2 is the LD estimate. Computer simulations show promising results, with the RP estimator at least as unbiased as the current Ragsdale and Gravel estimator in most common scenarios. In the more challenging scenarios with skewed allele frequencies and small sample size, RP is preferred by having notably reduced bias, and that the bias is less sensitive to sample size and underlying LD, while maintaining mean squared error comparable to existing methods. The new estimator will most benefit applications relying on accurate measures of LD. Beyond LD, this study stimulates further discussions on whether RP estimator can be generalised to other genetic summary statistics or measures of relatedness.

bioinformatics↗

bioRxiv2026

Estimation of adult census size from close-kin dyads in the malaria mosquito Anopheles gambiae

Accurate estimates of adult mosquito abundance are central to the design and evaluation of vector control strategies, yet they are difficult to obtain from natural populations. Conventional mark-recapture methods for estimating adult mosquito census size pose logistical and other challenges. A recently developed close-kin mark-recapture (CKMR) approach is a promising alternative. However, application of CKMR has been largely confined to long-lived vertebrates. Validation on empirical data from short-lived, highly fecund insects is lacking. Here, we apply CKMR to a natural population of Anopheles gambiae, the primary African malaria mosquito, sampled from a small island in Lake Victoria, Uganda. Using a high-diversity amplicon panel of genome-wide markers, we genotyped 714 adult mosquitoes collected over a 20-day period. We classified pairs to close-kin categories by implementing probabilistic latent-kinship estimation rather than using a deterministic threshold-based framework. We observe numerous full-sibling pairs but no parent-offspring pairs, a pattern indicative of extreme variance in reproductive success owing to frequent failure of mosquito egg clutches to produce adults. To adapt the CKMR framework to mosquito life history, we explicitly modeled the mosquito life cycle including the possibility of clutch failure. By incorporating probabilities of both parent-offspring and full-sibling relationships, we estimate an adult female census size of 26,887 (95% credible interval: 6,979 - 146,011), and a clutch failure probability of 97.6% (CrI: 91.3 - 99.6%). We use these estimates to calculate the predicted variance in reproductive success and effective population size. Through individual-based simulations we confirm our estimates and the necessity of modeling reproductive variance to explain observed kinship patterns. Our results demonstrate that CKMR can be applied successfully to mosquitoes, provided that appropriate adjustments are made to account for their natural history.

ecology↗

bioRxiv2026

Assessing alternative methods of using population genomic data to measure changes in population size

Malaria remains a major global health burden, with traditional control methods facing challenges such as insecticide resistance and high operational costs. Genetic biocontrol offers a promising alternative for mosquito population suppression, but its field efficacy would require assessment. This study evaluates the role that population genomic statistics can play in detecting decreases in population size in the context of a cluster randomized control trial (cRCT), investigating the response of nucleotide diversity ({pi}), Tajimas D, segregating sites, and linkage disequilibrium (LD) under both constant and seasonal demographic scenarios. We simulated 90% and 99% population declines with various degrees of between-cluster heterogeneity, and assessed the detection power of each statistic over time and number of clusters per arm. Results show that Tajimas D is highly sensitive and robust across crash severity, seasonality and heterogeneity scenarios. Segregating sites has similar power to Tajimas D when baseline data are available. We further estimated that cRCTs require approximately 3 to 5 villages per treatment arm to achieve adequate statistical power. These findings provide recommendations for genetic monitoring of vector control interventions in wild populations.

evolutionary biology↗

bioRxiv2025

Variance partition reveals contrasting random effect contributions on the density and species composition of malaria-transmitting mosquitoes

Spatial-temporal variations exist in the density and species composition of malaria-carrying mosquitoes, which will in turn influence the transmission of the disease. While there has been extensive research on the seasonality and other main drivers of the vector populations, the heterogeneity induced by random effects is just as important but did not quite attract the same attention. To investigate the relative contributions of the between-house, between-village, and between-year variations, as well as other house-level covariates such as inhabitant number and bed net usage, intensive Pyrethroid Spray Catches (PSC) sampling was conducted across a 60-month period between 2012-2019 from four villages in the Sudano-Sahelian region of Burkina Faso. For mosquito density, measured by counts of female Anopheles gambiae s.l., our modelling showed that the between-house variation was the largest component, followed by the between-year then between-village variation, after accounting for seasonality and other covariates. Density increased with the number of inhabitants within a household but was uncorrelated with bed net usage. A subset of female mosquitoes was genotyped for species identification, and the composition of An. coluzzii and An. gambiae, the two dominant vectors in the region, varied hugely across villages without a clear seasonal trend. The between-village variance contributed up to 76% of the total random variation, followed by the between-year variance. The between-house variation was estimated to be statistically insignificant. Neither household size nor bed net usage had any impact on species composition. In short, the relative importance of the random components in mosquito density was in the reverse order from species composition. The estimates and relative strengths help parameterise potential field trials for novel vector control programmes and monitoring.

ecology↗

bioRxiv2025

Assessing the population genetic structure and demographic history of Anopheles gambiae and Anopheles arabiensis at island and mainland populations in Uganda: Implications for testing novel malaria vector control approaches.

Despite substantial investments in malaria control, the disease remains a major burden in sub-Saharan Africa, particularly Uganda. Novel tools such as gene drive systems are being developed to suppress malaria vector populations, but their deployment requires detailed knowledge of mosquito population genetics. We assessed the genetic structure, diversity, and demographic history of Anopheles gambiae and Anopheles arabiensis from six sites in Uganda: three islands in Lake Victoria and three mainland sites. A total of 2918 Anopheles gambiae and 173 Anopheles arabiensis were genotyped using targeted amplicon sequencing of 62 loci across coding and non-coding regions of the genome. Population structure analyses revealed clear separation between the two species but little differentiation within each species across sites. Pairwise FST values among An. gambiae populations were low (0.00054-0.028) but often significant, with mainland populations showing higher connectivity and island populations exhibiting greater isolation. Anopheles arabiensis mainland populations showed no statistically significant differentiation, suggesting panmixia. Principal Component Analysis and Bayesian clustering similarly distinguished species-level structure but no obvious substructure within sites. Mainland An. gambiae populations displayed higher nucleotide diversity than island populations, while An. arabiensis showed the lowest diversity overall. Tajimas D values were negative across sites, consistent with recent population expansions. Effective population size estimates indicated small populations at the islands (146 to 249) compared to large mainland populations (4,054 to 8,190). These findings demonstrate strong genetic differentiation between Anopheles gambiae and Anopheles arabiensis, and subtle but meaningful structure between island and mainland Anopheles gambiae populations. The reduced diversity and small effective population sizes at island sites suggest stronger genetic drift and limited gene flow, in contrast to the highly connected mainland populations. For malaria control, this contrast has direct implications. High connectivity among mainland populations may facilitate the spread of insecticide resistance alleles, while island populations, with their relative isolation and smaller sizes, may serve as suitable sites for contained field trials of gene drive strategies. This study highlights how geographic and ecological factors shape mosquito population structure and provides critical evidence for the design and monitoring of genetic-based vector control interventions.

evolutionary biology↗

bioRxiv2023

Whole-genome sequencing of major malaria vectors reveals the evolution of new insecticide resistance variants in a longitudinal study in Burkina Faso

Intensive deployment of insecticide based malaria vector control tools results in the rapid evolution of phenotypes resistant to these chemicals. Understanding this process on the genomic level is essential for the deployment of successful interventions. Using whole genome sequencing data of 1409 individual An. Gambiae s.l. collected from 2012 to 2017, we investigated the change in genetic structure and the evolution of the insecticide resistance variants in natural populations over time and space. The results showed similar and constant nucleotide diversity and negative Tajimas D between An. gambiae s.s. and An. coluzzii. PCA and FST showed a clear genetic structure in the An. gambiae s.l. species. Genome-wide FST and H12 scans identified genomic regions under divergent selection and also having an implication in the adaptations to ecological changes. Novel voltage-gated sodium channel pyrethroid resistance target-site alleles (V402L, I1527T) were identified at increasing frequencies alongside the established kdr alleles (Vgsc-L995F, Vgsc-L995S and N1570Y) within the An. gambiae s.l. populations. Organophosphate metabolic resistance markers were also identified, at increasing frequencies, within the An. gambiae s.s. populations from 2012 to 2017, including the SNP Ace1-G280S and its associated duplication. Variants simultaneously identified in the same vector populations raise concerns about the long-term efficacy of new-generation bednets and the recently introduced organophosphate pirimiphos-methyl indoor residual spraying. These findings highlighted the benefit of genomic malaria vector surveillance for the detection of new insecticide resistance variants, the monitoring of the existing resistance variants, and also to get insights into the evolutionary processes driving insecticide resistance. Author SummaryGenomic surveillance of malaria vectors is crucial for understanding the genetic variation in natural vector populations and also guiding the implementation of novel and innovative vector control tools. Application of sequencing technologies in vector studies provide insights on the genetic and evolutionary phenomena of vectors that could have impact on vector control strategies. By analyzing the whole genome data of 1409 wild An. gambiae s.l. mosquito collected between 2012 and 2017, we showed an emergence of novel insecticide resistance markers alongside increasing frequencies of existing insecticide resistance variants over time in Burkina Faso. We showed the benefit of genomic surveillance of malaria vectors for the monitoring of the insecticide resistance variants and also providing insights into the evolutionary processes driving insecticide resistance.

evolutionary biology↗

bioRxiv2021

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 gene drive 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. Author summaryGene drives have the potential to be applied as novel control strategy of disease-transmitting mosquitoes, by spreading genetic traits that suppress or modify the target population. Many gene drive elements work by recognising and cutting a specific target sequence in the mosquito genome and copying themselves into that target sequence allowing the gene drive to increase in frequency in the population. Like other mosquito control interventions, efficacy will greatly depend on minimising the development of resistance to the gene drive mechanism - most likely via a change in the target sequence that prevents further cutting. One strategy to reduce resistance is to target sequences that are highly conserved, which implies that changes cannot easily be tolerated. We developed a strategy that simulates high selection pressure, under which resistance is most likely to emerge, and therefore provides a stringent test of its propensity to arise. Unlike previous results with another gene drive, we recovered a resistant allele within a few generations of gene drive exposure and at high frequency. Our results show that conserved sequences can vary hugely in ability to tolerate mutations and highlights the need to functionally validate future candidate gene drive target sites for their robustness to resistance.

genetics↗