For most eukaryotes, sexual reproduction is a fundamental process that requires meiosis. In turn, meiosis typically depends on a reciprocal exchange of DNA between each pair of homologous chromosomes, known as a crossover (CO), to ensure proper chromosome segregation. The frequency and distribution of COs are regulated by intrinsic and extrinsic environmental factors, but much more is known about the molecular mechanisms governing the former compared to the latter. Here we show that elevated temperature induces meiotic hyper-recombination in Arabidopsis thaliana and we use genetic analysis with mutants in different recombination pathways to demonstrate that the extra COs are derived from the major Type I interference sensitive pathway. We also show that heat-induced COs are not the result of an increase in DNA double-strand breaks and that the hyper-recombinant phenotype is likely specific to thermal stress rather than a more generalized stress response. Taken together, these findings provide initial mechanistic insight into how environmental cues modulate plant meiotic recombination and may also offer practical applications.
BackgroundMental health issues among farmers are identified population health concerns. While one systematic review focused on suicide in farming populations in the United States, there have been no scoping studies examining mental health in farming communities worldwide. The objectives of this scoping review were to: provide a descriptive analysis of the literature pertaining to mental health outcomes in farming populations; describe the international scope of the research; and highlight published mental health services and interventions that have been evaluated.MethodsFollowing Arksey and O’Malley’s scoping review framework, five major health and science platforms were used to identify studies examining mental health outcomes in farming populations, worldwide. Studies that met a priori inclusion criteria that were published prior to December 31, 2017 were included in this review. Data synthesis and descriptive statistics were conducted using STATA 15® software; proportions were calculated by country.ResultsThe initial literature search yielded 9,906 records. After title and abstract screening, 676 articles were reviewed in-full. Of these, 341 met a priori inclusion criteria. Studies included were conducted between 1979 and 2017; the majority (265; 77.7%) were published between 2002–2017. The most frequently measured outcomes were stress (41.9%), suicide (33.1%), and depression (32.6%). Over 70% of studies that examined stress described using quantitative research methods, most predominantly, cross-sectional designs (42.7%). Approximately 64% of studies that measured suicide reported using a quantitative approach; the largest proportion of included suicide studies (33.6%) described using cohort designs. Approximately 84% of studies that measured depression described using quantitative approaches; sixty percent of these studies reported using a cross-sectional study design. Twenty included studies described a mental health service or intervention (5.9%).ConclusionsThis scoping review provides a critical overview of the literature examining mental health outcomes in farming populations worldwide. Given the importance of farming and agriculture, this review can be used to ensure future research complements existing work, avoids unnecessary overlap, and begins to tackle the less-studied mental health outcomes amongst farmers. These results can guide researchers to identified gaps in research and services, leading to a more informed approach to future work, and ultimately, a more comprehensive understanding of mental health among farmers worldwide.
Fluctuating environmental pressures can challenge organisms by repeatedly shifting the optimum phenotype. Two contrasting evolutionary strategies to cope with these fluctuations are 1) evolution of the mean phenotype to follow the optimum (adaptive tracking) or 2) diversifying phenotypes so that at least some individuals have high fitness in the current fluctuation (bet-hedging). Bet-hedging could underlie stable differences in the behavior of individuals that are present even when genotype and environment are held constant. Instead of being simply ‘noise,’ behavioral variation across individuals may reflect an evolutionary strategy of phenotype diversification. Using geographically diverse wild-derived fly strains and high-throughput assays of individual preference, we tested whether thermal preference variation in Drosophila melanogaster could reflect a bet-hedging strategy. We also looked for evidence that populations from different regions differentially adopt bet-hedging or adaptive-tracking strategies. Computational modeling predicted regional differences in the relative advantage of bet-hedging, and we found patterns consistent with that in regional variation in thermal preference heritability. In addition, we found that temporal patterns in mean preference support bet-hedging predictions and that there is a genetic basis for thermal preference variability. Our empirical results point to bet-hedging in thermal preference as a potentially important evolutionary strategy in wild populations.
Our current understanding of the regulation of gene expression in the early Drosophila melanogaster embryo comes from observations of a few genes at a time, as with in situ hybridizations, or observation of gene expression levels without regards to patterning, as with RNA-sequencing. Single-nucleus RNA-sequencing however, has the potential to provide new insights into the regulation of gene expression for many genes at once while simultaneously retaining information regarding the position of each nucleus prior to dissociation based on patterned gene expression. In order to establish the use of single-nucleus RNA sequencing in Drosophila embryos prior to cellularization, here we look at gene expression in control and insulator protein, dCTCF, maternal null embryos during zygotic genome activation at nuclear cycle 14. We find that early embryonic nuclei can be grouped into distinct clusters according to gene expression. From both virtual and published in situ hybridizations, we also find that these clusters correspond to spatial regions of the embryo. Lastly, we provide a resource of candidate differentially expressed genes that might show local changes in gene expression between control and maternal dCTCF null nuclei with no detectable differential expression in bulk. These results highlight the potential for single-nucleus RNA-sequencing to reveal new insights into the regulation of gene expression in the early Drosophila melanogaster embryo.
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