Identifying regions of risk to honey bees from Zika vector control in the USA

This is the final version. Available on open access from Taylor & Francis via the DOI in this recordData accessibility: All novel data presented in this analysis is made available in the Supporting Information. Zika suitability projections used are available in association with their original publication.Managed honey bees are a crucial component of many countries’ agricultural systems. Critically, it is now well established that honey bees are faced with multiple threats, and therefore, it is important that we determine and mitigate new threats. The emergence of Zika virus has introduced the new threat of insecticidal mosquito control leading to honey bee losses, with demand from beekeepers for a comprehensive risk assessment to help mitigate losses. Here, we present novel estimates of county-level honey bee colony densities across the USA and combine these new data with different projections of Zika virus suitability to assess the magnitude of this risk. We find that up to 13% of colonies can reasonably be expected to experience elevated risk of damaging pesticide exposure, according to interpretation of current Zika virus projections. We show a significant positive correlation between areas of Zika suitability and honey bee colony density. Increased risk of colony loss to pesticides are found in the South-East, Gulf Coast, Florida, and the California Central Valley. We highlight certain states which are better placed to mitigate threats, recommending other states look towards these schemes to protect apiculture from both government and commercial pesticide application.Natural Environment Research Council (NERC)National Science Foundation (NSF

HECTD2 Is Associated with Susceptibility to Mouse and Human Prion Disease

Prion diseases are fatal transmissible neurodegenerative disorders, which include Scrapie, Bovine Spongiform Encephalopathy (BSE), Creutzfeldt-Jakob Disease (CJD), and kuru. They are characterised by a prolonged clinically silent incubation period, variation in which is determined by many factors, including genetic background. We have used a heterogeneous stock of mice to identify Hectd2, an E3 ubiquitin ligase, as a quantitative trait gene for prion disease incubation time in mice. Further, we report an association between HECTD2 haplotypes and susceptibility to the acquired human prion diseases, vCJD and kuru. We report a genotype-associated differential expression of Hectd2 mRNA in mouse brains and human lymphocytes and a significant up-regulation of transcript in mice at the terminal stage of prion disease. Although the substrate of HECTD2 is unknown, these data highlight the importance of proteosome-directed protein degradation in neurodegeneration. This is the first demonstration of a mouse quantitative trait gene that also influences susceptibility to human prion diseases. Characterisation of such genes is key to understanding human risk and the molecular basis of incubation periods

An integrated computational pipeline and database to support whole-genome sequence annotation

We describe here our experience in annotating the Drosophila melanogaster genome sequence, in the course of which we developed several new open-source software tools and a database schema to support large-scale genome annotation. We have developed these into an integrated and reusable software system for whole-genome annotation. The key contributions to overall annotation quality are the marshalling of high-quality sequences for alignments and the design of a system with an adaptable and expandable flexible architecture

A Copine family member, Cpne8, is a candidate quantitative trait gene for prion disease incubation time in mouse

Prion disease incubation time in mice is determined by many factors including genetic background. The prion gene itself plays a major role in incubation time; however, other genes are also known to be important. Whilst quantitative trait loci (QTL) studies have identified multiple loci across the genome, these regions are often large, and with the exception of Hectd2 on Mmu19, no quantitative trait genes or nucleotides for prion disease incubation time have been demonstrated. In this study, we use the Northport heterogeneous stock of mice to reduce the size of a previously identified QTL on Mmu15 from approximately 25 to 1.2 cM. We further characterised the genes in this region and identify Cpne8, a member of the copine family, as the most promising candidate gene. We also show that Cpne8 mRNA is upregulated at the terminal stage of disease, supporting a role in prion disease. Applying these techniques to other loci will facilitate the identification of key pathways in prion disease pathogenesis

Calibrating the Performance of SNP Arrays for Whole-Genome Association Studies

To facilitate whole-genome association studies (WGAS), several high-density SNP genotyping arrays have been developed. Genetic coverage and statistical power are the primary benchmark metrics in evaluating the performance of SNP arrays. Ideally, such evaluations would be done on a SNP set and a cohort of individuals that are both independently sampled from the original SNPs and individuals used in developing the arrays. Without utilization of an independent test set, previous estimates of genetic coverage and statistical power may be subject to an overfitting bias. Additionally, the SNP arrays' statistical power in WGAS has not been systematically assessed on real traits. One robust setting for doing so is to evaluate statistical power on thousands of traits measured from a single set of individuals. In this study, 359 newly sampled Americans of European descent were genotyped using both Affymetrix 500K (Affx500K) and Illumina 650Y (Ilmn650K) SNP arrays. From these data, we were able to obtain estimates of genetic coverage, which are robust to overfitting, by constructing an independent test set from among these genotypes and individuals. Furthermore, we collected liver tissue RNA from the participants and profiled these samples on a comprehensive gene expression microarray. The RNA levels were used as a large-scale set of quantitative traits to calibrate the relative statistical power of the commercial arrays. Our genetic coverage estimates are lower than previous reports, providing evidence that previous estimates may be inflated due to overfitting. The Ilmn650K platform showed reasonable power (50% or greater) to detect SNPs associated with quantitative traits when the signal-to-noise ratio (SNR) is greater than or equal to 0.5 and the causal SNP's minor allele frequency (MAF) is greater than or equal to 20% (N = 359). In testing each of the more than 40,000 gene expression traits for association to each of the SNPs on the Ilmn650K and Affx500K arrays, we found that the Ilmn650K yielded 15% times more discoveries than the Affx500K at the same false discovery rate (FDR) level

Real-world Multicenter Analysis of Clinical Outcomes and Safety of Meropenem-Vaborbactam in Patients Treated for Serious Gram-Negative Bacterial Infections

Fourty patients were treated with meropenem-vaborbactam (MEV) for serious Gram-negative bacterial (GNB) infections. Carbapenem-resistant Enterobacteriaceae (CRE) comprised 80.0% of all GNB infections. Clinical success occurred in 70.0% of patients. Mortality and recurrence at 30 days were 7.5% and 12.5%, respectively. One patient experienced a probable rash due to MEV

Mammalian interspecies substitution of immune modulatory alleles by genome editing

We describe a fundamentally novel feat of animal genetic engineering: the precise and efficient substitution of an agronomic haplotype into a domesticated species. Zinc finger nuclease in-embryo editing of the RELA locus generated live born domestic pigs with the warthog RELA orthologue, associated with resilience to African Swine Fever. The ability to efficiently achieve interspecies allele introgression in one generation opens unprecedented opportunities for agriculture and basic research

The use of NDVI and its Derivatives for Monitoring Lake Victoria’s Water Level and Drought Conditions

Normalized Difference Vegetation Index (NDVI), which is a measure of vegetation vigour, and lake water levels respond variably to precipitation and its deficiency. For a given lake catchment, NDVI may have the ability to depict localized natural variability in water levels in response to weather patterns. This information may be used to decipher natural from unnatural variations of a given lake’s surface. This study evaluates the potential of using NDVI and its associated derivatives (VCI (vegetation condition index), SVI (standardised vegetation index), AINDVI (annually integrated NDVI), green vegetation function (F g ), and NDVIA (NDVI anomaly)) to depict Lake Victoria’s water levels. Thirty years of monthly mean water levels and a portion of the Global Inventory Modelling and Mapping Studies (GIMMS) AVHRR (Advanced Very High Resolution Radiometer) NDVI datasets were used. Their aggregate data structures and temporal co-variabilities were analysed using GIS/spatial analysis tools. Locally, NDVI was found to be more sensitive to drought (i.e., responded more strongly to reduced precipitation) than to water levels. It showed a good ability to depict water levels one-month in advance, especially in moderate to low precipitation years. SVI and SWL (standardized water levels) used in association with AINDVI and AMWLA (annual mean water levels anomaly) readily identified high precipitation years, which are also when NDVI has a low ability to depict water levels. NDVI also appears to be able to highlight unnatural variations in water levels. We propose an iterative approach for the better use of NDVI, which may be useful in developing an early warning mechanisms for the management of lake Victoria and other Lakes with similar characteristics