Identifying single nucleotide polymorphisms associated with beef cattle terrain-use in the western United States

2019 Spring.Includes bibliographical references.Beef cattle are drawn to areas with gentle terrain, which may result in heavy grazing near riparian zones and minimal grazing on rugged terrain. Traditional management tools to improve grazing distribution can be costly; therefore, genomic selection has been proposed as a means of improving beef cattle grazing patterns. The objective of this thesis was to identify single nucleotide polymorphisms (SNP) associated with beef cattle terrain-use in the western U.S. Variant detection using RNA-sequencing data obtained from Angus cardiovascular tissues and Brangus reproductive tissues revealed 48 potential causative mutations in five genes that were previously associated with terrain-use indices: SDHAF3, RUSC2, SUPT20H, MAML3, and GRM5. In an additional study, Bayesian multiple-regression was performed using BovineHD genotypes and global positioning system (GPS) data collected from 80 beef cows managed in Arizona, Montana, and New Mexico. Results of this analysis suggested that beef cattle terrain-use was polygenic; however, additional observations were needed to validate the quantitative trait loci (QTL) identified. Subsequent genome-wide association studies (GWAS) were performed for six terrain-use traits using BovineSNP50 genotypes and distribution data collected from a multi-breed population of cattle (n = 330) managed in the western U.S. These analyses identified 32 QTL and 29 putative candidate genes with diverse functions related to hypoxia, heat stress, feed efficiency, weight traits, energy metabolism, and lactation. In conclusion, results presented in this thesis suggested that terrain-use is polygenic and may be improved with genetic selection; however, additional studies are needed to further elucidate the genetic mechanisms underlying terrain-use of beef cattle

Rooting Out Genetic Structure of Invasive Wild Pigs in Texas

Invasive wild pigs (Sus scrofa), also called feral swine or wild hogs, are recognized as among the most destructive invasive species in the world. Throughout the United States, invasive wild pigs have expanded rapidly over the past 40 years with populations now established in 38 states. Of the estimated 6.9 million wild pigs distributed throughout the United States, Texas supports approximately 40% of the population and similarly bears disproportionate ecological and economic costs. Genetic analyses are an effective tool for understanding invasion pathways and tracking dispersal of invasive species such as wild pigs and have been used recently in California and Florida, USA, which have similarly long-established populations and high densities of wild pigs. Our goals were to use molecular approaches to elucidate invasion and migration processes shaping wild pig populations throughout Texas, compare our results with patterns of genetic structure observed in California and Florida, and provide insights for effective management of this invasive species. We used a high-density single nucleotide polymorphism (SNP) array to evaluate population genetic structure. Genetic clusters of wild pigs throughout Texas demonstrate 2 distinct patterns: weakly resolved, spatially dispersed clusters and well-resolved, spatially localized clusters. The disparity in patterns of genetic structure suggests disparate processes are differentially shaping wild pig populations in various localities throughout the state. Our results differed from the patterns of genetic structure observed in California and Florida, which were characterized by localized genetic clusters. These differences suggest distinct biological and perhaps anthropogenic processes are shaping genetic structure in Texas. Further, these disparities demonstrate the need for location-specific management strategies for controlling wild pig populations and mitigating associated ecological and economic costs

Potential Use for Serosurveillance of Feral Swine to Map Risk for Anthrax Exposure, Texas, USA

Anthrax is a disease of concern in many mammals, including humans. Management primarily consists of prevention through vaccination and tracking clinical-level observations because environmental isolation is laborious and bacterial distribution across large geographic areas diffi cult to confi rm. Feral swine (Sus scrofa) are an invasive species with an extensive range in the southern United States that rarely succumbs to anthrax. We present evidence that feral swine might serve as biosentinels based on comparative seroprevalence in swine from historically defi ned anthrax-endemic and non–anthraxendemic regions of Texas. Overall seropositivity was 43.7% (n = 478), and logistic regression revealed county endemicity status, age-class, sex, latitude, and longitude were informative for predicting antibody status. However, of these covariates, only latitude was statistically signifi cant (β = –0.153, p = 0.047). These results suggests anthrax exposure in swine, when paired with continuous location data, could serve as a proxy for bacterial presence in specifi c areas

Overexpression of AtAHL20 causes delayed flowering in Arabidopsis via repression of FT expression

The 29-member Arabidopsis AHL gene family is classified into three main classes based on nucleotide and protein sequence evolutionary differences. These differences include the presence or absence of introns, type and/or number of conserved AT-hook and PPC domains. AHL gene family members are divided into two phylogenetic clades, Clade-A and Clade-B. A majority of the 29 members remain functionally uncharacterized. Furthermore, the biological significance of the DNA and peptide sequence diversity, observed in the conserved motifs and domains found in the different AHL types, is a subject area that remains largely unexplored. Transgenic plants overexpressing AtAHL20 flowered later than the wild type under both short and long days. Transcript accumulation analyses showed that 35S:AtAHL20 plants contained reduced FT, TSF, AGL8 and SPL3 mRNA levels. Similarly, overexpression of AtAHL20’s orthologue in Camelina sativa, Arabidopsis’ closely related Brassicaceae family member species, conferred a late-flowering phenotype via suppression of CsFT expression. However, overexpression of an aberrant AtAHL20 gene harboring a missense mutation in the AT-hook domain’s highly conserved R-G-R core motif abolished the late-flowering phenotype. Data from targeted yeast-two-hybrid assays showed that AtAHL20 interacted with itself and several other Clade-A Type-I AHLs which have been previously implicated in flowering-time regulation: AtAHL19, AtAHL22 and AtAHL29. We showed via gain-of-function analysis that AtAHL20 is a negative regulator of FT expression, as well as other downstream flowering time regulating genes. A similar outcome in Camelina sativa transgenic plants overexpressing CsAHL20 suggest that this is a conserved function. Our results demonstrate that AtAHL20 acts as a photoperiod-independent negative regulator of transition to flowering.https://doi.org/10.1186/s12870-020-02733-

Heterogenous Lung Inflammation CT Patterns Distinguish Pneumonia and Immune Checkpoint Inhibitor Pneumonitis and Complement Blood Biomarkers in Acute Myeloid Leukemia: Proof of Concept

BACKGROUND: Immune checkpoint inhibitors (ICI) may cause pneumonitis, resulting in potentially fatal lung inflammation. However, distinguishing pneumonitis from pneumonia is time-consuming and challenging. To fill this gap, we build an image-based tool, and further evaluate it clinically alongside relevant blood biomarkers. MATERIALS AND METHODS: We studied CT images from 97 patients with pneumonia and 29 patients with pneumonitis from acute myeloid leukemia treated with ICIs. We developed a CT-derived signature using a habitat imaging algorithm, whereby infected lungs are segregated into clusters ( habitats ). We validated the model and compared it with a clinical-blood model to determine whether imaging can add diagnostic value. RESULTS: Habitat imaging revealed intrinsic lung inflammation patterns by identifying 5 distinct subregions, correlating to lung parenchyma, consolidation, heterogenous ground-glass opacity (GGO), and GGO-consolidation transition. Consequently, our proposed habitat model (accuracy of 79%, sensitivity of 48%, and specificity of 88%) outperformed the clinical-blood model (accuracy of 68%, sensitivity of 14%, and specificity of 85%) for classifying pneumonia versus pneumonitis. Integrating imaging and blood achieved the optimal performance (accuracy of 81%, sensitivity of 52% and specificity of 90%). Using this imaging-blood composite model, the post-test probability for detecting pneumonitis increased from 23% to 61%, significantly ( CONCLUSION: Habitat imaging represents a step forward in the image-based detection of pneumonia and pneumonitis, which can complement known blood biomarkers. Further work is needed to validate and fine tune this imaging-blood composite model and further improve its sensitivity to detect pneumonitis

Condensation of zinc vapor in a supersonic carrier gas

A study of the condensation of a metal vapor in an inert carrier gas is made. Superheated zinc vapor is generated in a hot shot wind tunnel in a helium carrier gas and expanded in a converging-diverging nozzle. Static pressure measurements along the length of the nozzle are made to determine the location of the onset of condensation. A conical nominal Mach 5 (helium) nozzle is employed. The amount of supercooling before the onset of condensation is found to be approximately 430 K, measured along the isentrope over a range of initial zinc mass fractions of .35 to .70 for saturation partial pressures of zinc between 10 psia and 70 psia. The measurements are compared with results of an analysis based on the classical liquid drop model of nucleation. The computed results agree reasonably well with the measurements.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/41794/1/10494_2004_Article_BF00382286.pd

Type 2 Diabetes Variants Disrupt Function of SLC16A11 through Two Distinct Mechanisms

Type 2 diabetes (T2D) affects Latinos at twice the rate seen in populations of European descent. We recently identified a risk haplotype spanning SLC16A11 that explains ∼20% of the increased T2D prevalence in Mexico. Here, through genetic fine-mapping, we define a set of tightly linked variants likely to contain the causal allele(s). We show that variants on the T2D-associated haplotype have two distinct effects: (1) decreasing SLC16A11 expression in liver and (2) disrupting a key interaction with basigin, thereby reducing cell-surface localization. Both independent mechanisms reduce SLC16A11 function and suggest SLC16A11 is the causal gene at this locus. To gain insight into how SLC16A11 disruption impacts T2D risk, we demonstrate that SLC16A11 is a proton-coupled monocarboxylate transporter and that genetic perturbation of SLC16A11 induces changes in fatty acid and lipid metabolism that are associated with increased T2D risk. Our findings suggest that increasing SLC16A11 function could be therapeutically beneficial for T2D. Video Abstract [Figure presented] Keywords: type 2 diabetes (T2D); genetics; disease mechanism; SLC16A11; MCT11; solute carrier (SLC); monocarboxylates; fatty acid metabolism; lipid metabolism; precision medicin

TRY plant trait database – enhanced coverage and open access

Plant traits - the morphological, anatomical, physiological, biochemical and phenological characteristics of plants - determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits - almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

The genetic architecture of the human cerebral cortex

The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect cortical structure, we conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. We analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. We identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson's disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder

Proceedings of the 3rd Biennial Conference of the Society for Implementation Research Collaboration (SIRC) 2015: advancing efficient methodologies through community partnerships and team science

It is well documented that the majority of adults, children and families in need of evidence-based behavioral health interventionsi do not receive them [1, 2] and that few robust empirically supported methods for implementing evidence-based practices (EBPs) exist. The Society for Implementation Research Collaboration (SIRC) represents a burgeoning effort to advance the innovation and rigor of implementation research and is uniquely focused on bringing together researchers and stakeholders committed to evaluating the implementation of complex evidence-based behavioral health interventions. Through its diverse activities and membership, SIRC aims to foster the promise of implementation research to better serve the behavioral health needs of the population by identifying rigorous, relevant, and efficient strategies that successfully transfer scientific evidence to clinical knowledge for use in real world settings [3]. SIRC began as a National Institute of Mental Health (NIMH)-funded conference series in 2010 (previously titled the “Seattle Implementation Research Conference”; $150,000 USD for 3 conferences in 2011, 2013, and 2015) with the recognition that there were multiple researchers and stakeholdersi working in parallel on innovative implementation science projects in behavioral health, but that formal channels for communicating and collaborating with one another were relatively unavailable. There was a significant need for a forum within which implementation researchers and stakeholders could learn from one another, refine approaches to science and practice, and develop an implementation research agenda using common measures, methods, and research principles to improve both the frequency and quality with which behavioral health treatment implementation is evaluated. SIRC’s membership growth is a testament to this identified need with more than 1000 members from 2011 to the present.ii SIRC’s primary objectives are to: (1) foster communication and collaboration across diverse groups, including implementation researchers, intermediariesi, as well as community stakeholders (SIRC uses the term “EBP champions” for these groups) – and to do so across multiple career levels (e.g., students, early career faculty, established investigators); and (2) enhance and disseminate rigorous measures and methodologies for implementing EBPs and evaluating EBP implementation efforts. These objectives are well aligned with Glasgow and colleagues’ [4] five core tenets deemed critical for advancing implementation science: collaboration, efficiency and speed, rigor and relevance, improved capacity, and cumulative knowledge. SIRC advances these objectives and tenets through in-person conferences, which bring together multidisciplinary implementation researchers and those implementing evidence-based behavioral health interventions in the community to share their work and create professional connections and collaborations