The Pandora multi-algorithm approach to automated pattern recognition of cosmic-ray muon and neutrino events in the MicroBooNE detector.

The development and operation of liquid-argon time-projection chambers for neutrino physics has created a need for new approaches to pattern recognition in order to fully exploit the imaging capabilities offered by this technology. Whereas the human brain can excel at identifying features in the recorded events, it is a significant challenge to develop an automated, algorithmic solution. The Pandora Software Development Kit provides functionality to aid the design and implementation of pattern-recognition algorithms. It promotes the use of a multi-algorithm approach to pattern recognition, in which individual algorithms each address a specific task in a particular topology. Many tens of algorithms then carefully build up a picture of the event and, together, provide a robust automated pattern-recognition solution. This paper describes details of the chain of over one hundred Pandora algorithms and tools used to reconstruct cosmic-ray muon and neutrino events in the MicroBooNE detector. Metrics that assess the current pattern-recognition performance are presented for simulated MicroBooNE events, using a selection of final-state event topologies

Gene–Environment Interactions at Nucleotide Resolution

Interactions among genes and the environment are a common source of phenotypic variation. To characterize the interplay between genetics and the environment at single nucleotide resolution, we quantified the genetic and environmental interactions of four quantitative trait nucleotides (QTN) that govern yeast sporulation efficiency. We first constructed a panel of strains that together carry all 32 possible combinations of the 4 QTN genotypes in 2 distinct genetic backgrounds. We then measured the sporulation efficiencies of these 32 strains across 8 controlled environments. This dataset shows that variation in sporulation efficiency is shaped largely by genetic and environmental interactions. We find clear examples of QTN:environment, QTN: background, and environment:background interactions. However, we find no QTN:QTN interactions that occur consistently across the entire dataset. Instead, interactions between QTN only occur under specific combinations of environment and genetic background. Thus, what might appear to be a QTN:QTN interaction in one background and environment becomes a more complex QTN:QTN:environment:background interaction when we consider the entire dataset as a whole. As a result, the phenotypic impact of a set of QTN alleles cannot be predicted from genotype alone. Our results instead demonstrate that the effects of QTN and their interactions are inextricably linked both to genetic background and to environmental variation

Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990-2015: a systematic analysis for the Global Burden of Disease Study 2015

SummaryBackground The Global Burden of Diseases, Injuries, and Risk Factors Study 2015 provides an up-to-date synthesis of the evidence for risk factor exposure and the attributable burden of disease. By providing national and subnational assessments spanning the past 25 years, this study can inform debates on the importance of addressing risks in context. Methods We used the comparative risk assessment framework developed for previous iterations of the Global Burden of Disease Study to estimate attributable deaths, disability-adjusted life-years (DALYs), and trends in exposure by age group, sex, year, and geography for 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks from 1990 to 2015. This study included 388 risk-outcome pairs that met World Cancer Research Fund-defined criteria for convincing or probable evidence. We extracted relative risk and exposure estimates from randomised controlled trials, cohorts, pooled cohorts, household surveys, census data, satellite data, and other sources. We used statistical models to pool data, adjust for bias, and incorporate covariates. We developed a metric that allows comparisons of exposure across risk factors—the summary exposure value. Using the counterfactual scenario of theoretical minimum risk level, we estimated the portion of deaths and DALYs that could be attributed to a given risk. We decomposed trends in attributable burden into contributions from population growth, population age structure, risk exposure, and risk-deleted cause-specific DALY rates. We characterised risk exposure in relation to a Socio-demographic Index (SDI). Findings Between 1990 and 2015, global exposure to unsafe sanitation, household air pollution, childhood underweight, childhood stunting, and smoking each decreased by more than 25%. Global exposure for several occupational risks, high body-mass index (BMI), and drug use increased by more than 25% over the same period. All risks jointly evaluated in 2015 accounted for 57·8% (95% CI 56·6–58·8) of global deaths and 41·2% (39·8–42·8) of DALYs. In 2015, the ten largest contributors to global DALYs among Level 3 risks were high systolic blood pressure (211·8 million [192·7 million to 231·1 million] global DALYs), smoking (148·6 million [134·2 million to 163·1 million]), high fasting plasma glucose (143·1 million [125·1 million to 163·5 million]), high BMI (120·1 million [83·8 million to 158·4 million]), childhood undernutrition (113·3 million [103·9 million to 123·4 million]), ambient particulate matter (103·1 million [90·8 million to 115·1 million]), high total cholesterol (88·7 million [74·6 million to 105·7 million]), household air pollution (85·6 million [66·7 million to 106·1 million]), alcohol use (85·0 million [77·2 million to 93·0 million]), and diets high in sodium (83·0 million [49·3 million to 127·5 million]). From 1990 to 2015, attributable DALYs declined for micronutrient deficiencies, childhood undernutrition, unsafe sanitation and water, and household air pollution; reductions in risk-deleted DALY rates rather than reductions in exposure drove these declines. Rising exposure contributed to notable increases in attributable DALYs from high BMI, high fasting plasma glucose, occupational carcinogens, and drug use. Environmental risks and childhood undernutrition declined steadily with SDI; low physical activity, high BMI, and high fasting plasma glucose increased with SDI. In 119 countries, metabolic risks, such as high BMI and fasting plasma glucose, contributed the most attributable DALYs in 2015. Regionally, smoking still ranked among the leading five risk factors for attributable DALYs in 109 countries; childhood underweight and unsafe sex remained primary drivers of early death and disability in much of sub-Saharan Africa. Interpretation Declines in some key environmental risks have contributed to declines in critical infectious diseases. Some risks appear to be invariant to SDI. Increasing risks, including high BMI, high fasting plasma glucose, drug use, and some occupational exposures, contribute to rising burden from some conditions, but also provide opportunities for intervention. Some highly preventable risks, such as smoking, remain major causes of attributable DALYs, even as exposure is declining. Public policy makers need to pay attention to the risks that are increasingly major contributors to global burden. Funding Bill & Melinda Gates Foundation

Inferring the joint demographic history of multiple populations from multidimensional SNP frequency data

Demographic models built from genetic data play important roles in illuminating prehistorical events and serving as null models in genome scans for selection. We introduce an inference method based on the joint frequency spectrum of genetic variants within and between populations. For candidate models we numerically compute the expected spectrum using a diffusion approximation to the one-locus two-allele Wright-Fisher process, involving up to three simultaneous populations. Our approach is a composite likelihood scheme, since linkage between neutral loci alters the variance but not the expectation of the frequency spectrum. We thus use bootstraps incorporating linkage to estimate uncertainties for parameters and significance values for hypothesis tests. Our method can also incorporate selection on single sites, predicting the joint distribution of selected alleles among populations experiencing a bevy of evolutionary forces, including expansions, contractions, migrations, and admixture. As applications, we model human expansion out of Africa and the settlement of the New World, using 5 Mb of noncoding DNA resequenced in 68 individuals from 4 populations (YRI, CHB, CEU, and MXL) by the Environmental Genome Project. We also combine our demographic model with a previously estimated distribution of selective effects among newly arising amino acid mutations to accurately predict the frequency spectrum of nonsynonymous variants across three continental populations (YRI, CHB, CEU).Comment: 17 pages, 4 figures, supporting information included with sourc

Diversity and selective sweep in the OsAMT1;1 genomic region of rice

<p>Abstract</p> <p>Background</p> <p>Ammonium is one of the major forms in which nitrogen is available for plant growth. <it>OsAMT1;1 </it>is a high-affinity ammonium transporter in rice (<it>Oryza sativa </it>L.), responsible for ammonium uptake at low nitrogen concentration. The expression pattern of the gene has been reported. However, variations in its nucleotides and the evolutionary pathway of its descent from wild progenitors are yet to be elucidated. In this study, nucleotide diversity of the gene <it>OsAMT1;1 </it>and the diversity pattern of seven gene fragments spanning a genomic region approximately 150 kb long surrounding the gene were surveyed by sequencing a panel of 216 rice accessions including both cultivated rice and wild relatives.</p> <p>Results</p> <p>Nucleotide polymorphism (Pi) of <it>OsAMT1;1 </it>was as low as 0.00004 in cultivated rice (<it>Oryza sativa</it>), only 2.3% of that in the common wild rice (<it>O. rufipogon</it>). A single dominant haplotype was fixed at the locus in <it>O. sativa</it>. The test values for neutrality were significantly negative in the entire region stretching 5' upstream and 3' downstream of the gene in all accessions. The value of linkage disequilibrium remained high across a 100 kb genomic region around <it>OsAMT1;1 </it>in <it>O. sativa</it>, but fell rapidly in <it>O. rufipogon </it>on either side of the promoter of <it>OsAMT1;1</it>, demonstrating a strong natural selection within or nearby the ammonium transporter.</p> <p>Conclusions</p> <p>The severe reduction in nucleotide variation at <it>OsAMT1;1 </it>in rice was caused by a selective sweep around <it>OsAMT1;1</it>, which may reflect the nitrogen uptake system under strong selection by the paddy soil during the domestication of rice. Purifying selection also occurred before the wild rice diverged into its two subspecies, namely <it>indica </it>and <it>japonica</it>. These findings would provide useful insights into the processes of evolution and domestication of nitrogen uptake genes in rice.</p

Suppression and Regression of Choroidal Neovascularization in Mice by a Novel CCR2 Antagonist, INCB3344

PURPOSE: To investigate the effect of an intravitreally administered CCR2 antagonist, INCB3344, on a mouse model of choroidal neovascularization (CNV). METHODS: CNV was induced by laser photocoagulation on Day 0 in wild type mice. INCB3344 or vehicle was administered intravitreally immediately after laser application. On Day 14, CNV areas were measured on retinal pigment epithelium (RPE)-choroid flat mounts and histopathologic examination was performed on 7 µm-thick sections. Macrophage infiltration was evaluated by immunohistochemistry on RPE-choroid flat mounts and quantified by flow cytometry on Day 3. Expression of vascular endothelial growth factor (VEGF) protein in RPE-choroid tissue was examined by immunohistochemistry and ELISA, VEGF mRNA in sorted macrophages in RPE-choroid tissue was examine by real-time PCR and expression of phosphorylated extracellular signal-regulated kinase (p-ERK 1/2) in RPE-choroid tissue was measured by Western blot analysis on Day 3. We also evaluated the efficacy of intravitreal INCB3344 to spontaneous CNV detected in Cu, Zn-superoxide dismutase (SOD1) deficient mice. Changes in CNV size were assessed between pre- and 1week post-INCB3344 or vehicle administration in fundus photography and fluorescence angiography (FA). RESULTS: The mean CNV area in INCB3344-treated mice decreased by 42.4% compared with the vehicle-treated control mice (p<0.001). INCB3344 treatment significantly inhibited macrophage infiltration into the laser-irradiated area (p<0.001), and suppressed the expression of VEGF protein (p = 0.012), VEGF mRNA in infiltrating macrophages (p<0.001) and the phosphorylation of ERK1/2 (p<0.001). The area of spontaneous CNV in Sod1⁻/⁻ mice regressed by 70.35% in INCB3344-treated animals while no change was detected in vehicle-treated control mice (p<0.001). CONCLUSIONS: INCB3344 both inhibits newly forming CNV and regresses established CNV. Controlling inflammation by suppressing macrophage infiltration and angiogenic ability via the CCR-2/MCP-1 signal may be a useful therapeutic strategy for treating CNV associated with age-related macular degeneration

Organization and molecular evolution of a disease-resistance gene cluster in coffee trees

<p>Abstract</p> <p>Background</p> <p>Most disease-resistance (R) genes in plants encode NBS-LRR proteins and belong to one of the largest and most variable gene families among plant genomes. However, the specific evolutionary routes of NBS-LRR encoding genes remain elusive. Recently in coffee tree (<it>Coffea arabica</it>), a region spanning the <it>S</it>_<it>H</it><it>3 </it>locus that confers resistance to coffee leaf rust, one of the most serious coffee diseases, was identified and characterized. Using comparative sequence analysis, the purpose of the present study was to gain insight into the genomic organization and evolution of the <it>S</it>_<it>H</it><it>3 </it>locus.</p> <p>Results</p> <p>Sequence analysis of the <it>S</it>_<it>H</it><it>3 </it>region in three coffee genomes, E^aand C^asubgenomes from the allotetraploid <it>C. arabica </it>and C^cgenome from the diploid <it>C. canephora</it>, revealed the presence of 5, 3 and 4 R genes in E^a, C^a, and C^cgenomes, respectively. All these R-gene sequences appeared to be members of a CC-NBS-LRR (CNL) gene family that was only found at the <it>S</it>_<it>H</it><it>3 </it>locus in <it>C. arabica</it>. Furthermore, while homologs were found in several dicot species, comparative genomic analysis failed to find any CNL R-gene in the orthologous regions of other eudicot species. The orthology relationship among the <it>S</it>_<it>H</it><it>3</it>-CNL copies in the three analyzed genomes was determined and the duplication/deletion events that shaped the <it>S</it>_<it>H</it><it>3 </it>locus were traced back. Gene conversion events were detected between paralogs in all three genomes and also between the two sub-genomes of <it>C. arabica</it>. Significant positive selection was detected in the solvent-exposed residues of the <it>S</it>_<it>H</it><it>3</it>-CNL copies.</p> <p>Conclusion</p> <p>The ancestral <it>S</it>_<it>H</it><it>3</it>-CNL copy was inserted in the <it>S</it>_<it>H</it><it>3 </it>locus after the divergence between Solanales and Rubiales lineages. Moreover, the origin of most of the <it>S</it>_<it>H</it><it>3</it>-CNL copies predates the divergence between <it>Coffea </it>species. The <it>S</it>_<it>H</it><it>3</it>-CNL family appeared to evolve following the birth-and-death model, since duplications and deletions were inferred in the evolution of the <it>S</it>_<it>H</it><it>3 </it>locus. Gene conversion between paralog members, inter-subgenome sequence exchanges and positive selection appear to be the major forces acting on the evolution of <it>S</it>_<it>H</it><it>3</it>-CNL in coffee trees.</p

Domestication history and geographical adaptation inferred from a SNP map of African rice

African rice (Oryza glaberrima Steud.) is a cereal crop species closely related to Asian rice (Oryza sativa L.) but was independently domesticated in West Africa-3,000 years ago. African rice is rarely grown outside sub-Saharan Africa but is of global interest because of its tolerance to abiotic stresses. Here we describe a map of 2.32 million SNPs of African rice from whole-genome resequencing of 93 landraces. Population genomic analysis shows a population bottleneck in this species that began-13,000-15,000 years ago with effective population size reaching its minimum value-3,500 years ago, suggesting a protracted period of population size reduction likely commencing with predomestication management and/or cultivation. Genome-wide association studies (GWAS) for six salt tolerance traits identify 11 significant loci, 4 of which are within-300 kb of genomic regions that possess signatures of positive selection, suggesting adaptive geographical divergence for salt tolerance in this species

Genomic Analysis of QTLs and Genes Altering Natural Variation in Stochastic Noise

Quantitative genetic analysis has long been used to study how natural variation of genotype can influence an organism's phenotype. While most studies have focused on genetic determinants of phenotypic average, it is rapidly becoming understood that stochastic noise is genetically determined. However, it is not known how many traits display genetic control of stochastic noise nor how broadly these stochastic loci are distributed within the genome. Understanding these questions is critical to our understanding of quantitative traits and how they relate to the underlying causal loci, especially since stochastic noise may be directly influenced by underlying changes in the wiring of regulatory networks. We identified QTLs controlling natural variation in stochastic noise of glucosinolates, plant defense metabolites, as well as QTLs for stochastic noise of related transcripts. These loci included stochastic noise QTLs unique for either transcript or metabolite variation. Validation of these loci showed that genetic polymorphism within the regulatory network alters stochastic noise independent of effects on corresponding average levels. We examined this phenomenon more globally, using transcriptomic datasets, and found that the Arabidopsis transcriptome exhibits significant, heritable differences in stochastic noise. Further analysis allowed us to identify QTLs that control genomic stochastic noise. Some genomic QTL were in common with those altering average transcript abundance, while others were unique to stochastic noise. Using a single isogenic population, we confirmed that natural variation at ELF3 alters stochastic noise in the circadian clock and metabolism. Since polymorphisms controlling stochastic noise in genomic phenotypes exist within wild germplasm for naturally selected phenotypes, this suggests that analysis of Arabidopsis evolution should account for genetic control of stochastic variance and average phenotypes. It remains to be determined if natural genetic variation controlling stochasticity is equally distributed across the genomes of other multi-cellular eukaryotes