12 research outputs found

    Conserved transcriptomic profiles underpin monogamy across vertebrates

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    Social monogamy, typically characterized by the formation of a pair bond, increased territorial defense, and often biparental care, has independently evolved multiple times in animals. Despite the independent evolutionary origins of monogamous mating systems, several homologous brain regions and neuropeptides and their receptors have been shown to play a conserved role in regulating social affiliation and parental care, but little is known about the neuromolecular mechanisms underlying monogamy on a genomic scale. Here, we compare neural transcriptomes of reproductive males in monogamous and nonmonogamous species pairs of Peromyscus mice, Microtus voles, parid songbirds, dendrobatid frogs, and Xenotilapia species of cichlid fishes. We find that, while evolutionary divergence time between species or clades did not explain gene expression similarity, characteristics of the mating system correlated with neural gene expression patterns, and neural gene expression varied concordantly across vertebrates when species transition to monogamy. Our study provides evidence of a universal transcriptomic mechanism underlying the evolution of monogamy in vertebrates

    Correction for “Conserved transcriptomic profiles underpin monogamy across vertebrates,”Proceedings of the National Academy of Sciences of the United States of America(2019)116 (1331–1336)Doi:10.1073/pnas.1813775116)

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    which was first published January 22, 2019; 10.1073/pnas.1813775116 (Proc Natl Acad Sci USA 116:1331–1336). The authors wish to note the following: “When conducting the DESeq2 analyses on the orthologous gene groups (OGGs), the wrong data frame was called in R due to a naming error. Because of how different data frames were generated throughout the analysis pipeline, this error was reproduced consistently, introducing a systematic error. The numbers of concordantly regulated OGGs as shown in the various panels of Fig. 3 in the main paper have now been updated. Instead of the original 123 genes, there are now 121 genes, with 50 genes maintained in the corrected analysis. “In addition, the heatmap of candidate genes shown in the original Fig. 5 is incomplete: In the corrected analysis, there are 42 candidate genes that fit our candidate gene criteria [i.e., significant in DESeq2 analysis of all clades, greater than ±1 log2 fold-difference between the species pairs, and above threshold in 6 of 10 Rank-Rank Hypergeometric Overlap (RRHO) pairwise analyses]. This list contains all but 4 of the 24 genes previously reported in Fig. 5.” The corrected Fig. 3 and Fig. 5 appear below, along with their respective legends; the legend for Fig. 3 has been corrected. For the supporting information, the SI Appendix has been updated online to correct Fig. S5, its legend, and Table S7; and Datasets S1 and S2 have also been corrected online

    Addressing Climate Change Impacts on Health

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    Key messages• Climate change is a global health emergency that presents diverse risks to human lives including but not limited to heat exposure and heat stress; water scarcity, flooding and droughts; changing distribution of vector-borne and other infectious diseases; and food insecurity and malnutrition. Impacts are felt most intensely by vulnerable populations and communities, including those with pre-existing health conditions.• Effective adaptation and resilience-building to the health risks posed by climate change will need to be tailored to local circumstances and capacities; integrated into wider plans for sustainable development, disaster risk reduction and health sector reform, and should involve collaboration between national and local governmental bodies, public health professionals, health-care providers and local households and communities • Aligning climate change adaptation and mitigation actions is more likely to be effective than addressing these actions separately in reducing the health impacts of climate change. Emphasising the co-benefits to health from climate change mitigation can incentivise decision-makers to undertake climate action that directly benefits a country’s own population in the near term whilst also contributing to global efforts to combat climate change.• Addressing the complex interactions between health and climate change requires multi-sectoral and whole systems approaches and policies to assess health challenges, support the development and implementation of effective policy solutions, minimise trade-offs and identify actions that achieve objectives for health and climate change at the same time.• Coordinated and multidisciplinary monitoring, surveillance and reporting of disease in crops, livestock, and human populations are important to reduce health risks, and require long-term investment and cross-border collaborations and partnerships. Effective surveillance can support early warning systems, recognising that people and animals will move across borders in new ways due to climate change.• Sustainable management of agriculture and water is essential to reduce health risks from spread of disease in animals and crops, as well as risks to food security, water scarcity and nutrition that can cause harm to population health and economic sustainability. Promoting healthy dietary choices, including increased consumption of plant-based foods, can also reduce emissions from food systems alongside non-communicable disease risks.• Mobilisation of public and private finance is vital to closing climate and health financing gaps, through delivery of the committed US$100 billion in international climate finance to low and middle-income countries, combined with a doubling of adaptation finance by 2025

    A schematic summarising some key differences in metabolism at 37°C compared to 28°C, centred on glutamate/asparagine metabolism and the TCA cycle.

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    <p>This model is predicted by integrating data from the RNA-seq, proteomics and phenotype microarray studies. Intermediates (boxes) and pathways (arrows) predicted to be down regulated at 37°C are in red while those up regulated are in green. Data suggests TCA cycle intermediates (back boxes) would be relatively isolated from glutamate/asparagine metabolism and could be maintained via the conversion of L-serine into citrate via pyruvate. Black arrows indicate certain potential enzyme pathways that are present and predicted to be unchanged at 37°C. The data suggests a central role for imported peptides and amino acids in metabolism at 37°C. Opp/Dpp represent oligo- and di-peptide importers, TCT represents tricarboxylic acid and PEP is Phosphoenolpyruvate.</p

    The genus <i>Photorhabdus</i> contains three predominant species.

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    <p>A stylized representation of a previous six gene MLST phylogeny (<i>adk</i>, <i>ghd</i>, <i>mdk</i>, <i>ndh</i>, <i>pgm</i> and <i>recA</i>) of <i>Photorhabdus</i> (adapted from [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0144937#pone.0144937.ref005" target="_blank">5</a>]) is shown. The grey areas indicate species that consist of multiple strains, the majority of which are unable to grow above 34°C, with only a few <i>P</i>. <i>luminescens</i> strains capable of growth at temperatures up to 37°C. Example strains are <i>P</i>. <i>luminescens</i><sup>TT01</sup> and <i>P</i>. <i>temperata</i><sup>K122</sup>. The clinical strains adapted to 37°C are boxed. The stars and circles indicate the potential historical timing of temperature adaptation, which could have occurred ancestrally (star) or independently (circles) in different geographical isolates.</p

    Clinical <i>Photorhabdus</i> isolates are able to survive exposure to higher temperatures than most non-clinical isolates.

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    <p>The optical density achieved by representative strains after overnight growth in static conditions (at 28°C in LB medium) after prior 18 h exposure to a range of temperatures. A range of clinical (N. American and Australian) and non-clinical (European) strains of <i>P</i>. <i>asymbiotica (Pa)</i> were tested, and the well-studied <i>P</i>. <i>luminescens</i> strain (<i>Pl</i><sup>TT01</sup>) was included for comparison. Green stars and red diamonds indicate thermal tolerance and intolerance respectively. <i>Pa</i> strain designations are indicated as superscripts.</p
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