Aligning functional network constraint to evolutionary outcomes

Background. Functional constraint through genomic architecture is suggested to be an important dimension of genome evolution, but quantitative evidence for this idea is rare. In this contribution, existing evidence and discussions on genomic architecture as constraint for convergent evolution, rapid adaptation, and genic adaptation are summarized into alternative, testable hypotheses. Network architecture statistics from protein-protein interaction networks are then used to calculate differences in evolutionary outcomes on the example of genomic evolution among yeast, and the results are used to evaluate statistical support for these longstanding hypotheses. Results.A discriminant function analysis lent statistical support to classifying the yeast interactome into hub, intermediate and peripheral nodes based on network neighborhood connectivity, betweenness centrality, and average shortest path length. Quantitative support for the existence of genomic architecture as mechanistic basis for evolutionary constraint is then revealed through utilizing these statistical parameters of the protein-protein interaction network in combination with estimators of protein evolution. Conclusions.As functional genetic networks are becoming increasingly available, it will now be possible to evaluate functional genetic network constraint against variables describing complex phenotypes and environments, for better understanding of commonly observed deterministic patterns of evolution in non-model organisms. The hypothesis framework and methodological approach outlined herein may help to quantify the extrinsic versus intrinsic dimensions of evolutionary constraint, and result in a better understanding of how fast, effectively, or deterministically organisms adapt

Clinical relevance of circulating tumour cells in the bone marrow of patients with SCCHN

Background: Clinical outcome of patients with head and neck squamous cell carcinoma (SCCHN) depends on several risk factors like the presence of locoregional lymph node or distant metastases, stage, localisation and histologic differentiation of the tumour. Circulating tumour cells in the bone marrow indicate a poor prognosis for patients with various kinds of malignoma. The present study examines the clinical relevance of occult tumour cells in patients suffering from SCCHN. Patients and Methods: Bone marrow aspirates of 176 patients suffering from SCCHN were obtained prior to surgery and stained for the presence of disseminated tumour cells. Antibodies for cytokeratin 19 were used for immunohistochemical detection with APAAP on cytospin slides. Within a clinical follow-up protocol over a period of 60 months, the prognostic relevance of several clinicopathological parameters and occult tumour cells was evaluated. Results: Single CK19-expressing tumour cells could be detected in the bone marrow of 30.7% of the patients. There is a significant correlation between occult tumour cells in the bone marrow and relapse. Uni- and multivariate analysis of all clinical data showed the metastases in the locoregional lymph system and detection of disseminated tumour cells in the bone marrow to be statistically highly significant for clinical prognosis. Conclusion: The detection of minimal residual disease underlines the understanding of SCCHN as a systemic disease. Further examination of such cells will lead to a better understanding of the tumour biology, as well as to improvement of diagnostic and therapeutic strategies

Ecomorphological Variation in Three Species of Cybotoid Anoles

© 2018 by The Herpetologists' League, Inc. Caribbean Anolis lizards exhibit a complex suite of ecological, morphological, and behavioral traits that allow their specialization to particular microhabitats. These microhabitat specialists, called ecomorphs, have independently evolved on the four islands of the Greater Antilles, and diversification among anole ecomorphs has been the focus of many studies. Yet, habitat specialization has also occurred among species within the same ecomorph group. Here, we examined ecological, morphological, and behavioral divergence in three Hispaniolan trunk-ground species, the cybotoid anoles: Anolis cybotes, A. marcanoi, and A. longitibialis. We found differences in limb morphology, locomotor behavior, and perch use among the three cybotoid species that mirror differences across the ecomorphs. Among these species of cybotoids, those that have longer limbs tend to move less frequently, occupy broader perches, and have smaller fourth toes with fewer lamellae. We also observed that the species with greater male-biased size dimorphism had larger heads, smaller dewlaps, and smaller testes. These results are consistent with the predictions of sexual selection theory, in that species with large male body size may have larger heads because of increased male-male combat, and smaller testes potentially attributable to a trade-off between pre- and postcopulatory selection. Overall, our study suggests that a combination of local adaptation to different structural habitats and sexual selection might produce ecomorphological diversification within cybotoid anoles of the same ecomorph group

Genomic and phenotypic signatures of climate adaptation in an Anolis lizard

Integrated knowledge on phenotype, physiology and genomic adaptations is required to understand the effects of climate on evolution. The functional genomic basis of organismal adaptation to changes in the abiotic environment, its phenotypic consequences, and its possible convergence across vertebrates, are still understudied. In this study, we use a comparative approach to verify predicted gene functions for vertebrate thermal adaptation with observed functions underlying repeated genomic adaptations in response to elevation in the lizard Anolis cybotes. We establish a direct link between recurrently evolved phenotypes and functional genomics of altitude-related climate adaptation in three highland and lowland populations in the Dominican Republic. We show that across vertebrates, genes contained in this interactome are expressed within the brain and during development. These results are relevant to elucidate the effect of global climate change across vertebrates, and might aid in furthering insight into gene-environment relationships under disturbances to external homeostasis

How the First Stars Regulated Star Formation. II. Enrichment by Nearby Supernovae

Metals from Population III (Pop III) supernovae led to the formation of less massive Pop II stars in the early universe, altering the course of evolution of primeval galaxies and cosmological reionization. There are a variety of scenarios in which heavy elements from the first supernovae were taken up into second-generation stars, but cosmological simulations only model them on the largest scales. We present small-scale, high-resolution simulations of the chemical enrichment of a primordial halo by a nearby supernova after partial evaporation by the progenitor star. We find that ejecta from the explosion crash into and mix violently with ablative flows driven off the halo by the star, creating dense, enriched clumps capable of collapsing into Pop II stars. Metals may mix less efficiently with the partially exposed core of the halo, so it might form either Pop III or Pop II stars. Both Pop II and III stars may thus form after the collision if the ejecta do not strip all the gas from the halo. The partial evaporation of the halo prior to the explosion is crucial to its later enrichment by the supernova.Comment: Accepted to Ap

Correlates of eye colour and pattern in mantellid frogs

With more than 250 species, the Mantellidae is the most species-rich family of frogs in Madagascar. These frogs are highly diversified in morphology, ecology and natural history. Based on a molecular phylogeny of 248 mantellids, we here examine the distribution of three characters reflecting the diversity of eye colouration and two characters of head colouration along the mantellid tree, and their correlation with the general ecology and habitat use of these frogs. We use Bayesian stochastic character mapping, character association tests and concentrated changes tests of correlated evolution of these variables. We confirm previously formulated hypotheses of eye colour pattern being significantly correlated with ecology and habits, with three main character associations: many tree frogs of the genus Boophis have a bright coloured iris, often with annular elements and a blue-coloured iris periphery (sclera); terrestrial leaf-litter dwellers have an iris horizontally divided into an upper light and lower dark part; and diurnal, terrestrial and aposematic Mantella frogs have a uniformly black iris. Furthermore, the presence of a frenal streak and a dark tympanic patch were associated with each other, with horizontally divided iris colour, and with terrestrial habits. Our study is restricted to the mantellid radiation, and the performed tests detect the simultaneous distribution of independent character states in a tree, rather than providing a measure for phylogenetic independent correlation of these character states. The concentrated changes tests suggest that the evolutionary origin of a bright iris might indeed be correlated to arboreal habits. Yet, rather than testing hypotheses of adaptive evolution of eye colour in anurans, our study serves to formulate hypotheses of convergence more precisely and thus to open perspectives for their further testing in a comparative framework along the anuran tree of life. For instance, a brightly coloured iris and sclera might serve mate recognition or as aposematic defensive strategy especially in tree frogs, and a horizontally divided iris colour might constitute a disruptive defensive strategy in frogs inhabiting the leaf litter stratum

Plant phenology supports the multi-emergence hypothesis for ebola spillover events

Ebola virus disease outbreaks in animals (including humans and great apes) start with sporadic host switches from unknown reservoir species. The factors leading to such spillover events are little explored. Filoviridae viruses have a wide range of natural hosts and are unstable once outside hosts. Spillover events, which involve the physical transfer of viral particles across species, could therefore be directly promoted by conditions of host ecology and environment. In this report we outline a proof of concept that temporal fluctuations of a set of ecological and environmental variables describing the dynamics of the host ecosystem are able to predict such events of Ebola virus spillover to humans and animals. We compiled a dataset of climate and plant phenology variables and Ebola virus disease spillovers in humans and animals. We identified critical biotic and abiotic conditions for spillovers via multiple regression and neural networks based time series regression. Phenology variables proved to be overall better predictors than climate variables. African phenology variables are not yet available as a comprehensive online resource. Given the likely importance of phenology for forecasting the likelihood of future Ebola spillover events, our results highlight the need for cost-effective transect surveys to supply phenology data for predictive modelling efforts

Evidence for an intrinsic factor promoting landscape genetic divergence in Madagascan leaf-litter frogs

The endemic Malagasy frog radiations are an ideal model system to study patterns and processes of speciation in amphibians. Large-scale diversity patterns of these frogs, together with other endemic animal radiations, led to the postulation of new and the application of known hypotheses of species diversification causing diversity patterns in this biodiversity hotspot. Both extrinsic and intrinsic factors have been studied in a comparative framework, with extrinsic factors usually being related to the physical environment (landscape, climate, river catchments, mountain chains), and intrinsic factors being clade-specific traits or constraints (reproduction, ecology, morphology, physiology). Despite some general patterns emerging from such large-scale comparative analyses, it became clear that the mechanism of diversification in Madagascar may vary among clades, and may be a multifactorial process. In this contribution, I test for intrinsic factors promoting population-level divergence within a clade of terrestrial, diurnal leaf-litter frogs (genus Gephyromantis) that has previously been shown to diversify according to extrinsic factors. Landscape genetic analyses of the microendemic species Gephyromantis enki and its widely distributed, larger sister species Gephyromantis boulengeri over a rugged landscape in the Ranomafana area shows that genetic variance of the smaller species cannot be explained by landscape resistance alone. Both topographic and riverine barriers are found to be important in generating this divergence. This case study yields additional evidence for the probable importance of body size in lineage diversification

Methods for identifying low emissions development options for agriculture

Low emissions development strategies (LEDS) are national economic and social development plans that promote sustainable development while reducing GHG emissions. While LEDS programs have helped to mainstream economy-wide planning for low emissions, planning for low emissions agriculture has remained nascent. Low-emissions development (LED) in agriculture acknowledges that the primary purpose of agriculture is to produce food and other goods for human needs, and that climate change mitigation is a secondary goal that should not compromise production. This paper describes a research process and protocol to identify high potential LED options in agriculture at the United States Agency for International Development (USAID). The case study illustrates the steps for the identification and prioritization of LED options including: idea generation, concept development, and evidence building. Each stage is designed to gather and analyze data that specifically enable managers and stakeholders to make informed evaluations. The method gathers not only emission and mitigation information but also food security and income generation data, lending process legitimacy to the research. The incorporation of institutional factors and local contextual systems in the LED concept development stage improves the output credibility and salience. In the final process phase, stakeholders are given an active role in determining the criteria for prioritization and building evidence. The LED option identification and prioritization process illustrates how careful evidence-building can increase the credibility and salience of outputs and legitimacy of the overall results

Toward a protocol for quantifying the greenhouse gas balance and identifying mitigation options in smallholder farming systems

Globally, agriculture is directly responsible for 14% of annual greenhouse gas (GHG) emissions and induces an additional 17% through land use change, mostly in developing countries (Vermeulen et al 2012). Agricultural intensification and expansion in these regions is expected to catalyze the most significant relative increases in agricultural GHG emissions over the next decade (Smith et al 2008, Tilman et al 2011). Farms in the developing countries of sub-Saharan Africa and Asia are predominately managed by smallholders, with 80% of land holdings smaller than ten hectares (FAO 2012). One can therefore posit that smallholder farming significantly impacts the GHG balance of these regions today and will continue to do so in the near future. However, our understanding of the effect smallholder farming has on the Earth's climate system is remarkably limited. Data quantifying existing and reduced GHG emissions and removals of smallholder production systems are available for only a handful of crops, livestock, and agroecosystems (Herrero et al 2008, Verchot et al 2008, Palm et al 2010). For example, fewer than fifteen studies of nitrous oxide emissions from soils have taken place in sub-Saharan Africa, leaving the rate of emissions virtually undocumented. Due to a scarcity of data on GHG sources and sinks, most developing countries currently quantify agricultural emissions and reductions using IPCC Tier 1 emissions factors. However, current Tier 1 emissions factors are either calibrated to data primarily derived from developed countries, where agricultural production conditions are dissimilar to that in which the majority of smallholders operate, or from data that are sparse or of mixed quality in developing countries (IPCC 2006). For the most part, there are insufficient emissions data characterizing smallholder agriculture to evaluate the level of accuracy or inaccuracy of current emissions estimates. Consequentially, there is no reliable information on the agricultural GHG budgets for developing economies. This dearth of information constrains the capacity to transition to low-carbon agricultural development, opportunities for smallholders to capitalize on carbon markets, and the negotiating position of developing countries in global climate policy discourse. Concerns over the poor state of information, in terms of data availability and representation, have fueled appeals for new approaches to quantifying GHG emissions and removals from smallholder agriculture, for both existing conditions and mitigation interventions (Berry and Ryan 2013, Olander et al 2013). Considering the dependence of quantification approaches on data and the current data deficit for smallholder systems, it is clear that in situ measurements must be a core part of initial and future strategies to improve GHG inventories and develop mitigation measures for smallholder agriculture. Once more data are available, especially for farming systems of high priority (e.g., those identified through global and regional rankings of emission hotspots or mitigation leverage points), better cumulative estimates and targeted actions will become possible. Greenhouse gas measurements in agriculture are expensive, time consuming, and error prone. These challenges are exacerbated by the heterogeneity of smallholder systems and landscapes and the diversity of methods used. Concerns over methodological rigor, measurement costs, and the diversity of approaches, coupled with the demand for robust information suggest it is germane for the scientific community to establish standards of measurements—'a protocol'—for quantifying GHG emissions from smallholder agriculture. A standard protocol for use by scientists and development organizations will help generate consistent, comparable, and reliable data on emissions baselines and allow rigorous comparisons of mitigation options. Besides enhancing data utility, a protocol serves as a benchmark for non-experts to easily assess data quality. Obviously many such protocols already exist (e.g., GraceNet, Parkin and Venterea 2010). None, however, account for the diversity and complexity of smallholder agriculture, quantify emissions and removals from crops, livestock, and biomass together to calculate the net balance, or are adapted for the research environment of developing countries; conditions that warrant developing specific methods. Here we summarize an approach being developed by the Consultative Group on International Agricultural Research's (CGIAR) Climate Change, Agriculture, and Food Security Program (CCAFS) and partners. The CGIAR-CCAFS smallholder GHG quantification protocol aims to improve quantification of baseline emission levels and support mitigation decisions. The protocol introduces five novel quantification elements relevant for smallholder agriculture (figure 1). First, it stresses the systematic collection of 'activity data' to describe the type, distribution, and extent of land management activities in landscapes cultivated by smallholder. Second, it advocates an informed sampling approach that concentrates measurement activities on emission hotspots and leverage points to capture heterogeneity and account for the diversity and complexity of farming activities. Third, it quantifies emissions at multiple spatial scales, whole-farm and landscape, to provide information targeted to household and communities decisions. Fourth, it encourages GHG research to document farm productivity and economics in addition to emissions, in recognition of the importance of agriculture to livelihoods. Fifth, it develops cost-differentiated measurement solutions that optimize the relationships among scale, cost, and accuracy. Each of the five innovations is further described in the main article