Genetic structure of Anopheles gambiae populations on islands in northwestern Lake Victoria, Uganda

BACKGROUND: Alternative means of malaria control are urgently needed. Evaluating the effectiveness of measures that involve genetic manipulation of vector populations will be facilitated by identifying small, genetically isolated vector populations. The study was designed to use variation in microsatellite markers to look at genetic structure across four Lake Victoria islands and two surrounding mainland populations and for evidence of any restriction to free gene flow. METHODS: Four Islands (from 20–50 km apart) and two surrounding mainland populations (96 km apart) were studied. Samples of indoor resting adult mosquitoes, collected over two consecutive years, were genotyped at microsatellite loci distributed broadly throughout the genome and analysed for genetic structure, effective migration (Nem) and effective population size (Ne). RESULTS: Ne estimates showed island populations to consist of smaller demes compared to the mainland ones. Most populations were significantly differentiated geographically, and from one year to the other. Average geographic pair-wise FST ranged from 0.014–0.105 and several pairs of populations had Ne m < 3. The loci showed broad heterogeneity at capturing or estimating population differences. CONCLUSION: These island populations are significantly genetically differentiated. Differences reoccurred over the study period, between the two mainland populations and between each other. This appears to be the product of their separation by water, dynamics of small populations and local adaptation. With further characterisation these islands could become possible sites for applying measures evaluating effectiveness of control by genetic manipulation

Risks of adverse perinatal and maternal outcomes among women with hypertensive disorders of pregnancy in southwestern Uganda.

INTRODUCTION: Hypertensive disorders of pregnancy (HDP) are a leading cause of global perinatal (fetal and neonatal) and maternal morbidity and mortality. We sought to describe HDP and determine the magnitude and risk factors for adverse perinatal and maternal outcomes among women with HDP in southwestern Uganda. METHODS: We prospectively enrolled pregnant women admitted for delivery and diagnosed with HDP at a tertiary referral hospital in southwestern Uganda from January 2019 to November 2019, excluding women with pre-existing hypertension. The participants were observed and adverse perinatal and maternal outcomes were documented. We used multivariable logistic regression models to determine independent risk factors associated with adverse perinatal and maternal outcomes. RESULTS: A total of 103 pregnant women with a new-onset HDP were enrolled. Almost all women, 93.2% (n = 96) had either pre-eclampsia with severe features or eclampsia. The majority, 58% (n = 60) of the participants had an adverse perinatal outcome (36.9% admitted to the neonatal intensive care unit (ICU), 20.3% stillbirths, and 1.1% neonatal deaths). Fewer participants, 19.4% (n = 20) had an adverse maternal outcome HELLP syndrome (7.8%), ICU admission (3%), and postpartum hemorrhage (3%). In adjusted analyses, gestational age of < 34 weeks at delivery and birth weight <2.5kg were independent risk factors for adverse perinatal outcomes while referral from another health facility and eclampsia were independent risk factors for adverse maternal outcomes. CONCLUSION: Among women with HDP at our institution, majority had preeclampsia with severe symptoms or eclampsia and an unacceptably high rate of adverse perinatal and maternal outcomes; over a fifth of the mothers experiencing stillbirth. This calls for improved antenatal surveillance of women with HDP and in particular improved neonatal and maternal critical care expertise at delivering facilities. Earlier detection and referral, as well as improvement in initial management at lower level health units and on arrival at the referral site is imperative

Detection of a reduced susceptibility to chlorfenapyr in the malaria vector Anopheles gambiae contrasts with full susceptibility in Anopheles funestus across Africa

New insecticides have recently been produced to help control pyrethroid-resistant malaria vectors including the pyrrole, chlorfenapyr. Monitoring the susceptibility of mosquito populations against this new product and potential cross-resistance with current insecticides is vital for better resistance management. In this study, we assessed the resistance status of the major malaria vectors Anopheles gambiae and Anopheles funestus to chlorfenapyr across Africa and explored potential cross-resistance with known pyrethroid resistance markers. Efficacy of chlorfenapyr 100 µg/ml against An. gambiae and An. funestus from five Cameroonian locations, the Democratic Republic of Congo, Ghana, Uganda, and Malawi was assessed using CDC bottle assays. Synergist assays were performed with PBO (4%), DEM (8%) and DEF (0.25%) and several pyrethroid-resistant markers were genotyped in both species to assess potential cross-resistance between pyrethroids and chlorfenapyr. Resistance to chlorfenapyr was detected in An. gambiae populations from DRC (Kinshasa) (mortality rate: 64.3 ± 7.1%) Ghana (Obuasi) (65.9 ± 7.4%), Cameroon (Mangoum; 75.2 ± 7.7% and Nkolondom; 86.1 ± 7.4). In contrast, all An. funestus populations were fully susceptible. A negative association was observed between the L1014F-kdr mutation and chlorfenapyr resistance with a greater frequency of homozygote resistant mosquitoes among the dead mosquitoes after exposure compared to alive (OR 0.5; P = 0.02) whereas no association was found between GSTe2 (I114T in An. gambiae; L119F in An. funestus) and resistance to chlorfenapyr. A significant increase of mortality to chlorfenapyr 10 µg/ml was observed in An. funestus after to PBO, DEM and DEF whereas a trend for a decreased mortality was observed in An. gambiae after PBO pre-exposure. This study reveals a greater risk of chlorfenapyr resistance in An. gambiae populations than in An. funestus. However, the higher susceptibility in kdr-resistant mosquitoes points to higher efficacy of chlorfenapyr against the widespread kdr-based pyrethroid resistance

Genome-wide diversity and structure variation among lablab [Lablab purpureus (L.) Sweet] accessions and their implication in a forage breeding program

Open Access Article; Published online: 19 Mar 2021Most orphan crops have not been fully sequenced, hence we rely on genome sequences of related species to align markers to different chromosomes. This hinders their utilisation in plant population improvement programs. Utilising the advances in the science of sequencing technologies, the population structure, relatedness, and genetic diversity among accessions can be assessed quickly for better exploitation in forage breeding programs. Using DArTseq technology, we studied the genetic and structural variation in 65 Lablab purpureus (L.) Sweet conserved gene-bank accessions using 9320 DArTseq-based SNPs and 15,719 SilicoDart markers. These markers had a low discriminating ability with mean polymorphic information content (P.I.C.) of 0.14 with DArTseq-based SNPs and 0.13 with SilicoDart markers. However, the markers had a high mean call rate of 73% with DArTseq-based SNPs and 97% with SilicoDart markers. Analysis of molecular variance revealed a high within populations variance (99.4%), indicating a high gene exchange or low genetic differentiation (PhiPT = 0.0057) among the populations. Structure analysis showed three allelic pools in variable clusters of ΔK = 3 and 6. Phylogenetic tree of lablab accessions showed three main groups with variable membership coefficients. Most pairs of accessions (40.3%) had genetic distances between 0.10 and 0.15 for SilicoDart markers, while for DArTseq-based SNPs, (46.5%) had genetic distances between 0.20 and 0.25. Phylogenetic clustering and minimum spanning analysis divided the 65 accessions into three groups, irrespective of their origin. For the first time, this study produced high-density markers with good genom coverage. The utilisation of these accessions in a forage program will base on the information from molecular-based grouping. The outcomes uncovered the presence of noteworthy measure of variety in Uganda, CIAT and ILRI accessions, thus demonstrating an opportunity for further marker-trait-association studies

Employing phylogenetic tree shape statistics to resolve the underlying host population structure

BACKGROUND: Host population structure is a key determinant of pathogen and infectious disease transmission patterns. Pathogen phylogenetic trees are useful tools to reveal the population structure underlying an epidemic. Determining whether a population is structured or not is useful in informing the type of phylogenetic methods to be used in a given study. We employ tree statistics derived from phylogenetic trees and machine learning classification techniques to reveal an underlying population structure. RESULTS: In this paper, we simulate phylogenetic trees from both structured and non-structured host populations. We compute eight statistics for the simulated trees, which are: the number of cherries; Sackin, Colless and total cophenetic indices; ladder length; maximum depth; maximum width, and width-to-depth ratio. Based on the estimated tree statistics, we classify the simulated trees as from either a non-structured or a structured population using the decision tree (DT), K-nearest neighbor (KNN) and support vector machine (SVM). We incorporate the basic reproductive number ([Formula: see text]) in our tree simulation procedure. Sensitivity analysis is done to investigate whether the classifiers are robust to different choice of model parameters and to size of trees. Cross-validated results for area under the curve (AUC) for receiver operating characteristic (ROC) curves yield mean values of over 0.9 for most of the classification models. CONCLUSIONS: Our classification procedure distinguishes well between trees from structured and non-structured populations using the classifiers, the two-sample Kolmogorov-Smirnov, Cucconi and Podgor-Gastwirth tests and the box plots. SVM models were more robust to changes in model parameters and tree size compared to KNN and DT classifiers. Our classification procedure was applied to real -world data and the structured population was revealed with high accuracy of [Formula: see text] using SVM-polynomial classifier

Parsimonious genotype by environment interaction covariance models for cassava (Manihot esculenta)

Open Access Journal; Published online: 21 Sep 2022The assessment of cassava clones across multiple environments is often carried out at the uniform yield trial, a late evaluation stage, before variety release. This is to assess the differential response of the varieties across the testing environments, a phenomenon referred to as genotype-by-environment interaction (GEI). This phenomenon is considered a critical challenge confronted by plant breeders in developing crop varieties. This study used the data from variety trials established as randomized complete block design (RCBD) in three replicates across 11 locations in different agro-ecological zones in Nigeria over four cropping seasons (2016–2017, 2017–2018, 2018–2019, and 2019–2020). We evaluated a total of 96 varieties, including five checks, across 48 trials. We exploited the intricate pattern of GEI by fitting variance–covariance structure models on fresh root yield. The goodness-of-fit statistics revealed that the factor analytic model of order 3 (FA3) is the most parsimonious model based on Akaike Information Criterion (AIC). The three-factor loadings from the FA3 model explained, on average across the 27 environments, 53.5% [FA (1)], 14.0% [FA (2)], and 11.5% [FA (3)] of the genetic effect, and altogether accounted for 79.0% of total genetic variability. The association of factor loadings with weather covariates using partial least squares regression (PLSR) revealed that minimum temperature, precipitation and relative humidity are weather conditions influencing the genotypic response across the testing environments in the southern region and maximum temperature, wind speed, and temperature range for those in the northern region of Nigeria. We conclude that the FA3 model identified the common latent factors to dissect and account for complex interaction in multi-environment field trials, and the PLSR is an effective approach for describing GEI variability in the context of multi-environment trials where external environmental covariables are included in modeling

Exploring genotype by environment interaction on cassava yield and yield related traits using classical statistical methods

Open Access Journal; Published online: 18 Jul 2022Variety advancement decisions for root quality and yield-related traits in cassava are complex due to the variable patterns of genotype-by-environment interactions (GEI). Therefore, studies focused on the dissection of the existing patterns of GEI using linear-bilinear models such as Finlay-Wilkinson (FW), additive main effect and multiplicative interaction (AMMI), and genotype and genotype-by-environment (GGE) interaction models are critical in defining the target population of environments (TPEs) for future testing, selection, and advancement. This study assessed 36 elite cassava clones in 11 locations over three cropping seasons in the cassava breeding program of IITA based in Nigeria to quantify the GEI effects for root quality and yield-related traits. Genetic correlation coefficients and heritability estimates among environments found mostly intermediate to high values indicating high correlations with the major TPE. There was a differential clonal ranking among the environments indicating the existence of GEI as also revealed by the likelihood ratio test (LRT), which further confirmed the statistical model with the heterogeneity of error variances across the environments fit better. For all fitted models, we found the main effects of environment, genotype, and interaction significant for all observed traits except for dry matter content whose GEI sensitivity was marginally significant as found using the FW model. We identified TMS14F1297P0019 and TMEB419 as two topmost stable clones with a sensitivity values of 0.63 and 0.66 respectively using the FW model. However, GGE and AMMI stability value in conjunction with genotype selection index revealed that IITA-TMS-IBA000070 and TMS14F1036P0007 were the top-ranking clones combining both stability and yield performance measures. The AMMI-2 model clustered the testing environments into 6 mega-environments based on winning genotypes for fresh root yield. Alternatively, we identified 3 clusters of testing environments based on genotypic BLUPs derived from the random GEI component

Transmission of HIV-1 infection in sub-Saharan Africa and effect of elimination of unsafe injections

During the past year, a group has argued that unsafe injections are a major if not the main mode of HIV-1 transmission\ud in sub-Saharan Africa. We review the main arguments used to question the epidemiological interpretations on the lead\ud role of unsafe sex in HIV-1 transmission, and conclude there is no compelling evidence that unsafe injections are a\ud predominant mode of HIV-1 transmission in sub-Saharan Africa. Conversely, though there is a clear need to eliminate\ud all unsafe injections, epidemiological evidence indicates that sexual transmission continues to be by far the major\ud mode of spread of HIV-1 in the region. Increased efforts are needed to reduce sexual transmission of HIV-1

Studies of transgenic mosquitoes in disease-endemic countries: preparation of containment facilities

Novel approaches to area-wide control of vector species offer promise as additional tools in the fight against vectored diseases. Evaluation of transgenic insect strains aimed at field population control in disease-endemic countries may involve international partnerships and should be done in a stepwise approach, starting with studies in containment facilities. The preparations of both new-build and renovated facilities are described, including working with local and national regulations regarding land use, construction, and biosafety requirements, as well as international guidance to fill any gaps in regulation. The examples given are for containment categorization at Arthropod Containment Level 2 for initial facility design, classification of wastes, and precautions during shipping. Specific lessons were derived from preparations to evaluate transgenic (non-gene drive) mosquitoes in West and East African countries. Documented procedures and the use of a non-transgenic training strain for trial shipments and culturing were used to develop competence and confidence among the African facility staff, and along the chain of custody for transport. This practical description is offered to support other research consortia or institutions preparing containment facilities and operating procedures in conditions where research on transgenic insects is at an early stage