Genetic variation in DNMT3B and increased global DNA methylation is associated with suicide attempts in psychiatric patients

Recently, a significant epigenetic component in the pathology of suicide has been realized. Here we investigate candidate functional SNPs in epigenetic‐regulatory genes, DNMT1 and DNMT3B, for association with suicide attempt (SA) among patients with co‐existing psychiatric illness. In addition, global DNA methylation levels [5‐methyl cytosine (5‐mC%)] between SA and psychiatric controls were quantified using the Methylflash Methylated DNA Quantification Kit. DNA was obtained from blood of 79 suicide attempters and 80 non‐attempters, assessed for DSM‐IV Axis I disorders. Functional SNPs were selected for each gene (DNMT1; n = 7, DNMT3B; n = 10), and genotyped. A SNP (rs2424932) residing in the 3′ UTR of the DNMT3B gene was associated with SA compared with a non‐attempter control group (P = 0.001; Chi‐squared test, Bonferroni adjusted P value = 0.02). Moreover, haplotype analysis identified a DNMT3B haplotype which differed between cases and controls, however this association did not hold after Bonferroni correction (P = 0.01, Bonferroni adjusted P value = 0.56). Global methylation analysis showed that psychiatric patients with a history of SA had significantly higher levels of global DNA methylation compared with controls (P = 0.018, Student's t‐test). In conclusion, this is the first report investigating polymorphisms in DNMT genes and global DNA methylation quantification in SA risk. Preliminary findings suggest that allelic variability in DNMT3B may be relevant to the underlying diathesis for suicidal acts and our findings support the hypothesis that aberrant DNA methylation profiles may contribute to the biology of suicidal acts. Thus, analysis of global DNA hypermethylation in blood may represent a biomarker for increased SA risk in psychiatric patients.     

Are Sage-Grouse Fine-Scale Specialists or Shrub-Steppe Generalists?

Sage-grouse (Centrocercus spp.) are influencing rapidly evolving land management policy in the western United States. Management objectives for fine-scale vegetation characteristics (e.g., grass height >18 cm) have been adopted by land management agencies based on resource selection or relationships with fitness proxies reported among numerous habitat studies. Some managers, however, have questioned the appropriateness of these objectives. Moreover, it remains untested whether habitat–fitness relationships documented at fine scales (i.e., among individual nests within a study area) also apply at scales of management units (e.g., pastures or grazing allotments), which are many orders of magnitude larger. We employed meta-analyses of studies published from 1991 to 2019 to help resolve the role of fine-scale vegetation structure in nest site selection and nest success across the geographic range of greater sage-grouse (C. urophasianus) and evaluate the validity of established habitat management objectives. Specifically, we incorporated effects of study design and functional responses to resource availability in meta-regression models linking vegetation structure to nest site selection, and used a novel meta-analytic approach to simultaneously model vegetation structure and its relationship to nest success. Our approach tested habitat relationships at a range-wide extent and a grain size closely matching scales at which agencies make management decisions. We found moderate, but context-dependent, effects of shrub characteristics and weak effects of herbaceous vegetation on nest site selection. None of the tested vegetation characteristics were related to variation in nest success, suggesting nesting habitat–fitness relationships have been inappropriately extrapolated in developing range-wide habitat management objectives. Our findings reveal surprising flexibility in habitat use for a species often depicted as having very particular fine-scale habitat requirements, and cast doubt on the practice of adopting precise management objectives for vegetation structure based on findings of individual small-scale field studies. © 2020 The Authors. The Journal of Wildlife Management published by Wiley Periodicals, Inc. on behalf of The Wildlife Society.     

Predictive Models for Escherichia coli Concentrations at Inland Lake Beaches and Relationship of Model Variables to Pathogen Detection

Predictive models, based on environmental and water quality variables, have been used to improve the timeliness and accuracy of recreational water quality assessments, but their effectiveness has not been studied in inland waters. Sampling at eight inland recreational lakes in Ohio was done in order to investigate using predictive models for Escherichia coli and to understand the links between E. coli concentrations, predictive variables, and pathogens. Based upon results from 21 beach sites, models were developed for 13 sites, and the most predictive variables were rainfall, wind direction and speed, turbidity, and water temperature. Models were not developed at sites where the E. coli standard was seldom exceeded. Models were validated at nine sites during an independent year. At three sites, the model resulted in increased correct responses, sensitivities, and specificities compared to use of the previous day''s E. coli concentration (the current method). Drought conditions during the validation year precluded being able to adequately assess model performance at most of the other sites. Cryptosporidium, adenovirus, eaeA (E. coli), ipaH (Shigella), and spvC (Salmonella) were found in at least 20% of samples collected for pathogens at five sites. The presence or absence of the three bacterial genes was related to some of the model variables but was not consistently related to E. coli concentrations. Predictive models were not effective at all inland lake sites; however, their use at two lakes with high swimmer densities will provide better estimates of public health risk than current methods and will be a valuable resource for beach managers and the public.     

Genomic evidence of genetic variation with pleiotropic effects on caterpillar fitness and plant traits in a model legume

Plant–insect interactions are ubiquitous, and have been studied intensely because of their relevance to damage and pollination in agricultural plants, and to the ecology and evolution of biodiversity. Variation within species can affect the outcome of these interactions. Specific genes and chemicals that mediate these interactions have been identified, but genome‐ or metabolome‐scale studies might be necessary to better understand the ecological and evolutionary consequences of intraspecific variation for plant–insect interactions. Here, we present such a study. Specifically, we assess the consequences of genome‐wide genetic variation in the model plant Medicago truncatula for Lycaeides melissa caterpillar growth and survival (larval performance). Using a rearing experiment and a whole‐genome SNP data set (>5 million SNPs), we found that polygenic variation in M. truncatula explains 9%–41% of the observed variation in caterpillar growth and survival. Genetic correlations among caterpillar performance and other plant traits, including structural defences and some anonymous chemical features, suggest that multiple M. truncatula alleles have pleiotropic effects on plant traits and caterpillar performance (or that substantial linkage disequilibrium exists among distinct loci affecting subsets of these traits). A moderate proportion of the genetic effect of M. truncatula alleles on L. melissa performance can be explained by the effect of these alleles on the plant traits we measured, especially leaf toughness. Taken together, our results show that intraspecific genetic variation in M. truncatula has a substantial effect on the successful development of L. melissa caterpillars (i.e., on a plant–insect interaction), and further point toward traits potentially mediating this genetic effect.     

Low‐tech riparian and wet meadow restoration increases vegetation productivity and resilience across semiarid rangelands

Restoration of riparian and wet meadow ecosystems in semiarid rangelands of the western United States is a high priority given their ecological and hydrological importance in the region. However, traditional restoration approaches are often intensive and costly, limiting the extent over which they can be applied. Practitioners are increasingly trying new restoration techniques that are more cost‐effective, less intensive, and can more practically scale up to the scope of degradation. Unfortunately, practitioners typically lack resources to undertake outcome‐based evaluations necessary to judge the efficacy of these techniques. In this study, we use freely available, satellite remote sensing to explore changes in vegetation productivity (normalized difference vegetation index) of three distinct, low‐tech, riparian and wet meadow restoration projects. Case studies are presented that range in geographic location (Colorado, Oregon, and Nevada), restoration practice (Zeedyk structures, beaver dam analogs, and grazing management), and time since implementation. Restoration practices resulted in increased vegetation productivity of up to 25% and increased annual persistence of productive vegetation. Improvements in productivity with time since restoration suggest that elevated resilience may further enhance wildlife habitat and increase forage production. Long‐term, documented outcomes of conservation are rare; we hope our findings empower practitioners to further monitor and explore the use of low‐tech methods for restoration of ecohydrologic processes at meaningful spatial scales.     

Estimating differential reproductive success from nests of related individuals, with application to a study of the mottled sculpin, Cottus bairdi

Understanding how variation in reproductive success is related to demography is a critical component in understanding the life history of an organism. Parentage analysis using molecular markers can be used to estimate the reproductive success of different groups of individuals in natural populations. Previous models have been developed for cases where offspring are random samples from the population but these models do not account for the presence of full- and half-sibs commonly found in large clutches of many organisms. Here we develop a model for comparing reproductive success among different groups of individuals that explicitly incorporates within-nest relatedness. Inference for the parameters of the model is done in a Bayesian framework, where we sample from the joint posterior of parental assignments and fertility parameters. We use computer simulations to determine how well our model recovers known parameters and investigate how various data collection scenarios (varying the number of nests or the number of offspring) affect the estimates. We then apply our model to compare reproductive success among different age groups of mottled sculpin, Cottus bairdi, from a natural population. We demonstrate that older adults are more likely to contribute to a nest and that females in the older age groups contribute more eggs to a nest than younger individuals.     

Differential modulation of 3T3-L1 adipogenesis mediated by 11beta-hydroxysteroid dehydrogenase-1 levels

The localized activation of circulating glucocorticoids in vivo by the enzyme 11beta-hydroxysteroid dehydrogenase type 1 (11beta-HSD1) plays a critical role in the development of the metabolic syndrome. However, the precise contribution of 11beta-HSD1 in the initiation of adipogenesis by inactive glucocorticoids is not fully understood. 3T3-L1 fibroblasts can be terminally differentiated to mature adipocytes in a glucocorticoid-dependent manner. Both inactive rodent dehydrocorticosterone and human cortisone were able to substitute for the synthetic glucocorticoid dexamethasone in 3T3-L1 adipogenesis, suggesting a potential role for 11beta-HSD1 in these effects. Differentiation of 3T3-L1 cells caused a strong increase in 11beta-HSD1 protein levels, which occurred late in the differentiation protocol. Reduction of 11beta-HSD1 activity in 3T3-L1 fibroblasts, achieved by pharmacological inhibition or adenovirally mediated delivery of short hairpin RNA constructs, specifically blocked the ability of inactive glucocorticoids to drive 3T3-L1 differentiation. However, even modest increases in exogenous 11beta-HSD1 expression in 3T3-L1 fibroblasts, to levels comparable with endogenous 11beta-HSD1 in differentiated 3T3-L1 adipocytes, were sufficient to block adipogenesis. Luciferase reporter assays indicated that overexpressed 11beta-HSD1 was catalyzing the inactivating dehydrogenase reaction, because the ability of both active and inactive glucocorticoids to activate the glucocorticoid receptor were largely suppressed. These results suggest that the temporal regulation of 11beta-HSD1 expression is tightly controlled in 3T3-L1 cells, so as to mediate the initiation of differentiation by inactive glucocorticoids and also to prevent the inhibitory activity of prematurely expressed 11beta-HSD1 during adipogenesis.