365 research outputs found
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Divergent sensory and immune gene evolution in sea turtles with contrasting demographic and life histories
Sea turtles represent an ancient lineage of marine vertebrates that evolved from terrestrial ancestors over 100 Mya. The genomic basis of the unique physiological and ecological traits enabling these species to thrive in diverse marine habitats remains largely unknown. Additionally, many populations have drastically declined due to anthropogenic activities over the past two centuries, and their recovery is a high global conservation priority. We generated and analyzed high-quality reference genomes for the leatherback (Dermochelys coriacea) and green (Chelonia mydas) turtles, representing the two extant sea turtle families. These genomes are highly syntenic and homologous, but localized regions of noncollinearity were associated with higher copy numbers of immune, zinc-finger, and olfactory receptor (OR) genes in green turtles, with ORs related to waterborne odorants greatly expanded in green turtles. Our findings suggest that divergent evolution of these key gene families may underlie immunological and sensory adaptations assisting navigation, occupancy of neritic versus pelagic environments, and diet specialization. Reduced collinearity was especially prevalent in microchromosomes, with greater gene content, heterozygosity, and genetic distances between species, supporting their critical role in vertebrate evolutionary adaptation. Finally, diversity and demographic histories starkly contrasted between species, indicating that leatherback turtles have had a low yet stable effective population size, exhibit extremely low diversity compared with other reptiles, and harbor a higher genetic load compared with green turtles, reinforcing concern over their persistence under future climate scenarios. These genomes provide invaluable resources for advancing our understanding of evolution and conservation best practices in an imperiled vertebrate lineage
Individual-Based Modeling of Amazon Forests Suggests That Climate Controls Productivity While Traits Control Demography
Climate, species composition, and soils are thought to control carbon cycling and forest structure in Amazonian forests. Here, we add a demographics scheme (tree recruitment, growth, and mortality) to a recently developed non-demographic model—the Trait-based Forest Simulator (TFS)—to explore the roles of climate and plant traits in controlling forest productivity and structure. We compared two sites with differing climates (seasonal vs. aseasonal precipitation) and plant traits. Through an initial validation simulation, we assessed whether the model converges on observed forest properties (productivity, demographic and structural variables) using datasets of functional traits, structure, and climate to model the carbon cycle at the two sites. In a second set of simulations, we tested the relative importance of climate and plant traits for forest properties within the TFS framework using the climate from the two sites with hypothetical trait distributions representing two axes of functional variation (“fast” vs. “slow” leaf traits, and high vs. low wood density). The adapted model with demographics reproduced observed variation in gross (GPP) and net (NPP) primary production, and respiration. However, NPP and respiration at the level of plant organs (leaf, stem, and root) were poorly simulated. Mortality and recruitment rates were underestimated. The equilibrium forest structure differed from observations of stem numbers suggesting either that the forests are not currently at equilibrium or that mechanisms are missing from the model. Findings from the second set of simulations demonstrated that differences in productivity were driven by climate, rather than plant traits. Contrary to expectation, varying leaf traits had no influence on GPP. Drivers of simulated forest structure were complex, with a key role for wood density mediated by its link to tree mortality. Modeled mortality and recruitment rates were linked to plant traits alone, drought-related mortality was not accounted for. In future, model development should focus on improving allocation, mortality, organ respiration, simulation of understory trees and adding hydraulic traits. This type of model that incorporates diverse tree strategies, detailed forest structure and realistic physiology is necessary if we are to be able to simulate tropical forest responses to global change scenarios
Assessment of infant feeding styles among low-income African-American mothers: Comparing reported and observed behaviors
This study’s goal was to provide a detailed description of feeding styles adopted by a sample of African-American women in feeding their infants in North Carolina, and to examine the correspondence between reported and observed feeding styles. Cross-sectional semi-structured interview and videotaped data were gathered in the homes of 20 participating low-income mothers of infants aged 3-20 months. Feeding styles were characterized through a tailored coding scheme (the Infant Feeding Styles Video Coding Scheme, IFSVCS) applied to both interview and video-taped data. We found that the most frequent feeding styles identified for both interviews and videotaped observations was restrictive, but that mothers were roughly equally divided among predominantly controlling (pressuring or restrictive) and less controlling (laissez-faire or indulgent) styles across methods. However, for over 2/3 of the sample, there was a lack of correspondence between interview and video-taped feeding styles. This unique characterization and comparison of observed and reported infant feeding styles provides additional insights into parental feeding approaches among mothers of infants at high risk of obesity, and highlights the need for further study of feeding style assessment and potential impact on infant weight outcomes
Informing trait-based ecology by assessing remotely sensed functional diversity across a broad tropical temperature gradient
Spatially continuous data on functional diversity will improve our ability to predict global change impacts on ecosystem properties. We applied methods that combine imaging spectroscopy and foliar traits to estimate remotelysensed functional diversity in tropical forests across an Amazon-to-Andes elevation gradient (215 to 3537 m). We evaluated the scale dependency of community assembly processes and examined whether tropical forest productivitycould be predicted by remotely sensed functional diversity. Functional richness of the community decreased withincreasing elevation. Scale-dependent signals of trait convergence, consistent with environmental filtering, play animportant role in explaining the range of trait variation within each site and along elevation. Single- and multitraitremotely sensed measures of functional diversity were important predictors of variation in rates of net and grossprimary productivity. Our findings highlight the potential of remotely sensed functional diversity to inform trait-based ecology and trait diversity-ecosystem function linkages in hyperdiverse tropical forests.Fil: Durán, Sandra M.. University of Arizona; Estados UnidosFil: Martin, Roberta E.. Arizona State University; Estados UnidosFil: Díaz, Sandra Myrna. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto Multidisciplinario de Biología Vegetal. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas Físicas y Naturales. Instituto Multidisciplinario de Biología Vegetal; ArgentinaFil: Maitner, Brian S.. Arizona State University; Estados UnidosFil: Malhi, Yadvinder. University of Oxford; Reino UnidoFil: Salinas, Norma. University of Oxford; Reino Unido. Pontificia Universidad Católica de Perú; PerúFil: Shenkin, Alexander. University of Oxford; Reino UnidoFil: Silman, Miles R.. Wake Forest University; Estados UnidosFil: Wieczynski, Daniel J.. University of Oxford; Reino UnidoFil: Asner, Gregory P.. Arizona State University; Estados UnidosFil: Bentley, Lisa Patrick. Sonoma State University; Estados UnidosFil: Savage, Van M.. University of California; Estados UnidosFil: Enquist, Brian J.. Arizona State University; Estados Unido
TLS2trees: A scalable tree segmentation pipeline for TLS data
1. Above-ground biomass (AGB) is an important metric used to quantify the mass of carbon stored in terrestrial ecosystems. For forests, this is routinely estimated at the plot scale (typically 1 ha) using inventory measurements and allometry. In recent years, terrestrial laser scanning (TLS) has appeared as a disruptive technology that can generate a more accurate assessment of tree and plot scale AGB; however, operationalising TLS methods has had to overcome a number of challenges. One such challenge is the segmentation of individual trees from plot level point clouds that are required to estimate woody volume, this is often done manually (e.g. with interactive point cloud editing software) and can be very time consuming. /
2. Here we present TLS2trees, an automated processing pipeline and set of Python command line tools that aims to redress this processing bottleneck. TLS2trees consists of existing and new methods and is specifically designed to be horizontally scalable. The processing pipeline is demonstrated on 7.5 ha of TLS data captured across 10 plots of seven forest types; from open savanna to dense tropical rainforest. /
3. A total of 10,557 trees are segmented with TLS2trees: these are compared to 1281 manually segmented trees. Results indicate that TLS2trees performs well, particularly for larger trees (i.e. the cohort of largest trees that comprise 50% of total plot volume), where plot-wise tree volume bias is ±0.4 m3 and %RMSE is 60%. Segmentation performance decreases for smaller trees, for example where DBH ≤10 cm; a number of reasons are suggested including performance of semantic segmentation step. /
4. The volume and scale of TLS data captured in forest plots is increasing. It is suggested that to fully utilise this data for activities such as monitoring, reporting and verification or as reference data for satellite missions an automated processing pipeline, such as TLS2trees, is required. To facilitate improvements to TLS2trees, as well as modification for other laser scanning modes (e.g. mobile and UAV laser scanning), TLS2trees is a free and open-source software
Treg depletion potentiates checkpoint inhibition in claudin-low breast cancer
Claudin-low breast cancer is an aggressive subtype that confers poor prognosis and is found largely within the clinical triple-negative group of breast cancer patients. Here, we have shown that intrinsic and immune cell gene signatures distinguish the claudin-low subtype clinically as well as in mouse models of other breast cancer subtypes. Despite adaptive immune cell infiltration in claudin-low tumors, treatment with immune checkpoint inhibitory antibodies against cytotoxic T lymphocyte–associated protein 4 (CTLA-4) and programmed death receptor 1 (PD-1) were ineffective in controlling tumor growth. CD4+FoxP3+ Tregs represented a large proportion of the tumor-infiltrating lymphocytes (TILs) in claudin-low tumors, and Tregs isolated from tumor-bearing mice were able to suppress effector T cell responses. Tregs in the tumor microenvironment highly expressed PD-1 and were recruited partly through tumor generation of the chemokine CXCL12. Antitumor efficacy required stringent Treg depletion combined with checkpoint inhibition; delays in tumor growth were not observed using therapies that modestly diminished the number of Tregs in the tumor microenvironment. This study provides evidence that the recruitment of Tregs to the tumor microenvironment inhibits an effective antitumor immune response and highlights early Treg recruitment as a possible mechanism for the lack of response to immune checkpoint blockade antibodies in specific subtypes of cancer that are heavily infiltrated with adaptive immune cells
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Selective and Genetic Constraints on Pneumococcal Serotype Switching
Streptococcus pneumoniae isolates typically express one of over 90 immunologically distinguishable polysaccharide capsules (serotypes), which can be classified into “serogroups” based on cross-reactivity with certain antibodies. Pneumococci can alter their serotype through recombinations affecting the capsule polysaccharide synthesis (cps) locus. Twenty such “serotype switching” events were fully characterised using a collection of 616 whole genome sequences from systematic surveys of pneumococcal carriage. Eleven of these were within-serogroup switches, representing a highly significant (p < 0.0001) enrichment based on the observed serotype distribution. Whereas the recombinations resulting in between-serogroup switches all spanned the entire cps locus, some of those that caused within-serogroup switches did not. However, higher rates of within-serogroup switching could not be fully explained by either more frequent, shorter recombinations, nor by genetic linkage to genes involved in β–lactam resistance. This suggested the observed pattern was a consequence of selection for preserving serogroup. Phenotyping of strains constructed to express different serotypes in common genetic backgrounds was used to test whether genotypes were physiologically adapted to particular serogroups. These data were consistent with epistatic interactions between the cps locus and the rest of the genome that were specific to serotype, but not serogroup, meaning they were unlikely to account for the observed distribution of capsule types. Exclusion of these genetic and physiological hypotheses suggested future work should focus on alternative mechanisms, such as host immunity spanning multiple serotypes within the same serogroup, which might explain the observed pattern
The influence of taxonomy and environment on leaf trait variation along tropical abiotic gradients
Deconstructing functional trait variation and co-variation across a wide range of environmental conditions is necessary to increase the mechanistic understanding of community assembly processes and improve current parameterization of dynamic vegetation models. Here, we present a study that deconstructs leaf trait variation and co-variation into within-species, taxonomic-, and plot-environment components along three tropical environmental gradients in Peru, Brazil, and Ghana. To do so, we measured photosynthetic, chemical, and structural leaf traits using a standardized sampling protocol for more than 1,000 individuals belonging to 367 species. Variation associated with the taxonomic component (species + genus + family) for most traits was relatively consistent across environmental gradients, but within-species variation and plot-environment variation was strongly dependent on the environmental gradient. Trait-trait co-variation was strongly linked to the environmental gradient where traits were measured, although some traits had consistent co-variation components irrespective of gradient. Our results demonstrate that filtering along these tropical gradients is mostly expressed through trait taxonomic variation, but that trait co-variation is strongly dependent on the local environment, and thus global trait co-variation relationships might not always apply at smaller scales and may quickly change under future climate scenarios.Fil: Oliveras, Imma. University of Oxford; Reino UnidoFil: Bentley, Lisa. Sonoma State University; Estados UnidosFil: Fyllas, Nikolaos M.. University Of The Aegean; GreciaFil: Gvozdevaite, Agne. University of Oxford; Reino UnidoFil: Shenkin, Alexander Frederick. University of Oxford; Reino UnidoFil: Peprah, Theresa. Forestry Research Institute Of Ghana; GhanaFil: Morandi, Paulo. Universidade Federal do Mato Grosso do Sul; BrasilFil: Peixoto, Karine Silva. Universidade Federal do Mato Grosso do Sul; BrasilFil: Boakye, Mickey. Forestry Research Institute Of Ghana; GhanaFil: Adu-Bredu, Stephen. Csir - Forestry Research Institute Of Ghana; GhanaFil: Schwantes Marimon, Beatriz. Universidade Do Estado de Mato Grosso; BrasilFil: Marimon Junior, Ben Hur. Universidade Do Estado de Mato Grosso; BrasilFil: Salinas, Norma. Pontificia Universidad Católica de Perú; PerúFil: Martin, Roberta. Arizona State University; Estados UnidosFil: Asner, Gregory. Arizona State University; Estados UnidosFil: Díaz, Sandra Myrna. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto Multidisciplinario de Biología Vegetal. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas Físicas y Naturales. Instituto Multidisciplinario de Biología Vegetal; ArgentinaFil: Enquist, Brian J.. University of Arizona; Estados UnidosFil: Malhi, Yadvinder. University of Oxford; Reino Unid
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Multi-ancestry study of blood lipid levels identifies four loci interacting with physical activity.
Many genetic loci affect circulating lipid levels, but it remains unknown whether lifestyle factors, such as physical activity, modify these genetic effects. To identify lipid loci interacting with physical activity, we performed genome-wide analyses of circulating HDL cholesterol, LDL cholesterol, and triglyceride levels in up to 120,979 individuals of European, African, Asian, Hispanic, and Brazilian ancestry, with follow-up of suggestive associations in an additional 131,012 individuals. We find four loci, in/near CLASP1, LHX1, SNTA1, and CNTNAP2, that are associated with circulating lipid levels through interaction with physical activity; higher levels of physical activity enhance the HDL cholesterol-increasing effects of the CLASP1, LHX1, and SNTA1 loci and attenuate the LDL cholesterol-increasing effect of the CNTNAP2 locus. The CLASP1, LHX1, and SNTA1 regions harbor genes linked to muscle function and lipid metabolism. Our results elucidate the role of physical activity interactions in the genetic contribution to blood lipid levels
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