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Environmental and Genetic Contributions to Imperfect wMel-Like Wolbachia Transmission and Frequency Variation.

ABSTRACT: Maternally transmitted Wolbachia bacteria infect about half of all insect species. They usually show imperfect maternal transmission and often produce cytoplasmic incompatibility (CI). Irrespective of CI, Wolbachia frequencies tend to increase when rare only if they benefit host fitness. Several Wolbachia, including wMel that infects Drosophila melanogaster, cause weak or no CI and persist at intermediate frequencies. On the island of São Tomé off West Africa, the frequencies of wMel-like Wolbachia infecting Drosophila yakuba (wYak) and Drosophila santomea (wSan) fluctuate, and the contributions of imperfect maternal transmission, fitness effects, and CI to these fluctuations are unknown. We demonstrate spatial variation in wYak frequency and transmission on São Tomé. Concurrent field estimates of imperfect maternal transmission do not predict spatial variation in wYak frequencies, which are highest at high altitudes where maternal transmission is the most imperfect. Genomic and genetic analyses provide little support for D. yakuba effects on wYak transmission. Instead, rearing at cool temperatures reduces wYak titer and increases imperfect transmission to levels observed on São Tomé. Using mathematical models of Wolbachia frequency dynamics and equilibria, we infer that temporally variable imperfect transmission or spatially variable effects on host fitness and reproduction are required to explain wYak frequencies. In contrast, spatially stable wSan frequencies are plausibly explained by imperfect transmission, modest fitness effects, and weak CI. Our results provide insight into causes of wMel-like frequency variation in divergent hosts. Understanding this variation is crucial to explain Wolbachia spread and to improve wMel biocontrol of human disease in transinfected mosquito systems.

SUBMITTER: Hague MTJ

PROVIDER: S-EPMC7404227 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Background: Twin studies indicate that genetic and environmental factors contribute to both psychological resilience and coping style, but estimates of their relative molecular and shared environmental contributions are limited. The degree of overlap in the genetic architectures of these traits is also unclear. Methods: Using data from a large population- and family-based cohort Generation Scotland (N = 8,734), we estimated the genetic and shared environmental variance components for resilience, task-, emotion-, and avoidance-oriented coping style in a linear mixed model (LMM). Bivariate LMM analyses were used to estimate the genetic correlations between these traits. Resilience and coping style were measured using the Brief Resilience Scale and Coping Inventory for Stressful Situations, respectively. Results: The greatest proportion of the phenotypic variance in resilience remained unexplained, although significant contributions from common genetic variants and family-shared environment were found. Both task- and avoidance-oriented coping had significant contributions from common genetic variants, sibling- and couple-shared environments, variance in emotion-oriented coping was attributable to common genetic variants, family- and couple-shared environments. The estimated correlation between resilience and emotion-oriented coping was high for both common-variant-associated genetic effects (r G = -0.79, se = 0.19), and for the additional genetic effects from the pedigree (r K = -0.94, se = 0.30). Genetic correlations between resilience and task- and avoidance-oriented coping did not meet statistical significance. Conclusions: Both genetics and shared environmental effects were major contributing factors to coping style, whilst the variance in resilience remains largely unexplained. Strong genetic overlap between resilience and emotion-oriented coping suggests a relationship whereby genetic factors that increase negative emotionality also lead to decreased resilience. We suggest that genome-wide family-based studies of resilience and coping may help to elucidate tractable methodologies to identify genetic architectures and modifiable environmental risk factors to protect against psychiatric illness, although further work with larger sample sizes is needed.

Project description:BACKGROUND:The variation and covariation for many cardiometabolic traits have been decomposed into genetic and environmental fractions, by using twin or single-nucleotide polymorphism (SNP) models. However, differences in population, age, sex, and other factors hamper the comparison between twin- and SNP-based estimates. METHODS AND RESULTS:Twenty-four cardiometabolic traits and 700,000 genotyped SNPs were available in the study base of 10 682 twins from TwinGene cohort. For the 27 highly correlated pairs (absolute phenotypic correlation coefficient ?0.40), twin-based bivariate structural equation models were performed in 3870 complete twin pairs, and SNP-based bivariate genomic relatedness matrix restricted maximum likelihood methods were performed in 5779 unrelated individuals. In twin models, the model including additive genetic variance and unique/nonshared environmental variance was the best-fitted model for 7 pairs (5 of them were between blood pressure traits); the model including additive genetic variance, common/shared environmental variance, and unique/nonshared environmental variance components was best fitted for 4 pairs, but estimates of shared environment were close to zero; and the model including additive genetic variance, dominant genetic variance, and unique/nonshared environmental variance was best fitted for 16 pairs, in which significant dominant genetic effects were identified for 13 pairs (including all 9 obesity-related pairs). However, SNP models did not identify significant estimates of dominant genetic effects for any pairs. In the paired t test, twin- and SNP-based estimates of additive genetic correlation were not significantly different (both were 0.67 on average), whereas the nonshared environmental correlations from these 2 models differed slightly from each other (on average, twin-based estimate=0.64 and SNP-based estimate=0.68). CONCLUSIONS:Beside additive genetic effects and nonshared environment, nonadditive genetic effects (dominance) also contribute to the covariation between certain cardiometabolic traits (especially for obesity-related pairs); contributions from the shared environment seem to be weak for their covariation in TwinGene samples.

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Environmental and Genetic Contributions to Imperfect wMel-Like Wolbachia Transmission and Frequency Variation.

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