Spatial, Roadway, and Biotic Factors Associated with Barn Owl (\u3cem\u3eTyto alba\u3c/em\u3e) Mortality and Characteristics of Mortality Hotspots Along Interstates 84 and 86 in Idaho

One of the world’s highest roadway mortality rates for barn owls (Tyto alba) occurs along Interstate 84/86 (I-84/86) in southern Idaho. Although mortality occurs in numerous portions of the I-84/86 corridor, there are segments where relatively much higher numbers of owls are killed (in total comprising \u3e20% of the corridor total, hereafter “hotspots”). My objectives were to 1) identify areas of greatest mortality (hotspots), 2) understand the spatial, roadway, and biotic factors potentially contributing to barn owl-vehicle collisions and 3) assess how mortality hotspots have changed over time. If factors contributing to barn owl mortality along highways can be identified, it may be possible to find ways to reduce barn owl-vehicle collisions in this region. To do so, I conducted road surveys to identify locations of barn owl-vehicle collisions, and quantified spatial, roadway, and biotic factors along the focal highway to examine how they related to patterns of barn owl roadway mortality. I also quantified mortality hotspots to examine temporal and spatial changes between a previous survey in 2004-2006 and this study in 2013-2015. Standardized road kill surveys conducted by Than Boves from 2004 to 2006 located 812 dead barn owls. Between 2013 and 2015, I located another 550 dead barn owls. I characterized nine spatial, 19 roadway, and nine biotic variables that may potentially affect barn owl roadway mortality using squares of 1-, 3-, and 5-km lengths centered on 120 randomly selected sites along the I-84/86 corridor. I evaluated variables at each of the three scales in relation to the number of dead barn owls counted along 1- and 5-km highway segments to determine their respective best scales (either 1-, 3-, or 5-km) using Akaike Information Criterion (AICC). This approach produced two sets of models: the 1-km highway segment model set and the 5-km highway segment model set. The final variable set included 14 variables for both the 1- and 5-km model sets. I assessed the potential effects of all possible combinations of these variables within each set (spatial, roadway, and biotic) on number of dead barn owls in 1- and 5-km highway segments using Generalized Linear Models within an AICC information theoretic model selection framework and combined the variables from the top models in each variable set into a final set in which I assessed all possible combinations (a total of eight variables for the 1-km set and seven variables for the 5-km set). I averaged the variables into a final model for the 1-km set, whereas model averaging was not necessary for the 5-km set. One of the variables in the final 1-km model (width of the median) was further analyzed to determine its potential correlation with percent land cover type. In the final 1-km model set, percentage human structures, cumulative length of secondary roads (length of all roads other than I-84/86), and width of median had an inverse relationship with the number of dead barn owls/1-km segment/survey. Percent land cover type varied with the width of the median in that the median was generally wider when the highway was surrounded by shrubs (rs = 0.30, p = 0.0008) and narrower when surrounded by crops (rs= -0.24, p = 0.009). The number of dead barn owls/1-km segment/survey increased with commercial average annual daily traffic (CAADT), small mammal abundance index, and when the plant cover type in the roadside verge was grass. The final model for the 5-km model set included percentage of crops in which the number of dead barn owls/5-km segment/survey increased as the percentage of crops increased. Barn owls are associated with agricultural lands and thus less likely to occur in areas with high percentages of human structures, secondary roads, and when the median is wide in shrublands. Barn owl carcasses increased with higher small mammal abundance index values as well as when there was grass in the verges. Furthermore, the small mammal abundance index was greater in grass versus mixed shrub verges (Wilcoxon rank sum test: eastbound verge, W = 1507, p = 0.01; westbound verge, W = 2255, p I evaluated temporal and spatial changes in hotspots between survey periods using point density estimation and KDE+. Additionally, of the 120 randomly selected sites, I calculated which fell within an area delineated as a hotspot and which did not as defined by the point density estimation analysis. I compared characteristics of the two types of sites (hotspot and non-hotspot) for the 14 spatial, roadway, and biotic variables selected for final modeling. The area between Bliss and Hazelton was the section of I-84/86 with the highest rates of barn owl-vehicle collisions in both surveys, although particular hotspots did exhibit some expansions and contractions between 2004-2006 and 2013-2015. Two of the historical hotspots no longer appeared as hotspots in the recent surveys indicating they perhaps have shifted or were so fatal they reduced the local barn owl population and thus no longer appear as hotspots. Therefore, these historical hotspots may still be important mortality zones and important for future mitigation consideration as the hotspots potentially have reduced the barn owl population in these areas. The most important difference between hotspots and other sites was the higher number of secondary roads (Wilcoxon rank sum test: W = 613, p = 0.001) and higher traffic volume (W = 600, p = 0.002) in hotspots. However, hotspots were also generally situated close to the Snake River Canyon and other water features which should have more prey, provide nesting and/or roosting sites, and attract owls; had low slopes (level terrain) which would allow owls to fly low to the pavement; narrow medians (correlated with cropland); and flexible rather than rigid pavement type (potentially related to noise level), and did not contain the highest number of dairies (which should attract owls to their higher rodent populations). The hotspots were also in regions of I-84/86 with moderate to high small mammal abundance and features that should correlate with higher rodent abundance: low percentages of human structures near the highway, grass cover types in the median and verges, high percentages of crops, and few obstructions to low flight. Mortality hotspots along I-84/86 were generally devoid of low flying obstructions, so establishing barriers to low flight may be an effective technique to reduce barn owl-vehicle collisions. Reducing small mammals in verges and median vegetation could also potentially reduce barn owl mortality. Because I found fewer small mammals in areas with shrubs, establishing taller shrub vegetation may reduce small mammal habitat and reduce hunting success, encouraging owls to hunt elsewhere. Reducing wildlife-collisions involving barn owls in Idaho is important for motorist safety and would be an important step in ensuring the persistence of this avian species

Author Correction: Convalescent plasma for hospitalized patients with COVID-19: an open-label, randomized controlled trial (Nature Medicine, (2021), 27, 11, (2012-2024), 10.1038/s41591-021-01488-2)

In the version of this Article initially published, there was an omission in the member list for the CONCOR-1 Study Group. Valérie Arsenault (Héma-Québec, Montreal, Quebec, Canada) has now been included in the CONCOR-1 Study Group in the online version of the article

Phenotypic spectrum and transcriptomic profile associated with germline variants in TRAF7

PURPOSE: Somatic variants in tumor necrosis factor receptor-associated factor 7 (TRAF7) cause meningioma, while germline variants have recently been identified in seven patients with developmental delay and cardiac, facial, and digital anomalies. We aimed to define the clinical and mutational spectrum associated with TRAF7 germline variants in a large series of patients, and to determine the molecular effects of the variants through transcriptomic analysis of patient fibroblasts. METHODS: We performed exome, targeted capture, and Sanger sequencing of patients with undiagnosed developmental disorders, in multiple independent diagnostic or research centers. Phenotypic and mutational comparisons were facilitated through data exchange platforms. Whole-transcriptome sequencing was performed on RNA from patient- and control-derived fibroblasts. RESULTS: We identified heterozygous missense variants in TRAF7 as the cause of a developmental delay-malformation syndrome in 45 patients. Major features include a recognizable facial gestalt (characterized in particular by blepharophimosis), short neck, pectus carinatum, digital deviations, and patent ductus arteriosus. Almost all variants occur in the WD40 repeats and most are recurrent. Several differentially expressed genes were identified in patient fibroblasts. CONCLUSION: We provide the first large-scale analysis of the clinical and mutational spectrum associated with the TRAF7 developmental syndrome, and we shed light on its molecular etiology through transcriptome studies

Shared heritability and functional enrichment across six solid cancers

Correction: Nature Communications 10 (2019): art. 4386 DOI: 10.1038/s41467-019-12095-8Quantifying the genetic correlation between cancers can provide important insights into the mechanisms driving cancer etiology. Using genome-wide association study summary statistics across six cancer types based on a total of 296,215 cases and 301,319 controls of European ancestry, here we estimate the pair-wise genetic correlations between breast, colorectal, head/neck, lung, ovary and prostate cancer, and between cancers and 38 other diseases. We observed statistically significant genetic correlations between lung and head/neck cancer (r(g) = 0.57, p = 4.6 x 10(-8)), breast and ovarian cancer (r(g) = 0.24, p = 7 x 10(-5)), breast and lung cancer (r(g) = 0.18, p = 1.5 x 10(-6)) and breast and colorectal cancer (r(g) = 0.15, p = 1.1 x 10(-4)). We also found that multiple cancers are genetically correlated with non-cancer traits including smoking, psychiatric diseases and metabolic characteristics. Functional enrichment analysis revealed a significant excess contribution of conserved and regulatory regions to cancer heritability. Our comprehensive analysis of cross-cancer heritability suggests that solid tumors arising across tissues share in part a common germline genetic basis.Peer reviewe

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

Rare coding variants in PLCG2, ABI3, and TREM2 implicate microglial-mediated innate immunity in Alzheimer's disease

We identified rare coding variants associated with Alzheimer’s disease (AD) in a 3-stage case-control study of 85,133 subjects. In stage 1, 34,174 samples were genotyped using a whole-exome microarray. In stage 2, we tested associated variants (P<1×10-4) in 35,962 independent samples using de novo genotyping and imputed genotypes. In stage 3, an additional 14,997 samples were used to test the most significant stage 2 associations (P<5×10-8) using imputed genotypes. We observed 3 novel genome-wide significant (GWS) AD associated non-synonymous variants; a protective variant in PLCG2 (rs72824905/p.P522R, P=5.38×10-10, OR=0.68, MAFcases=0.0059, MAFcontrols=0.0093), a risk variant in ABI3 (rs616338/p.S209F, P=4.56×10-10, OR=1.43, MAFcases=0.011, MAFcontrols=0.008), and a novel GWS variant in TREM2 (rs143332484/p.R62H, P=1.55×10-14, OR=1.67, MAFcases=0.0143, MAFcontrols=0.0089), a known AD susceptibility gene. These protein-coding changes are in genes highly expressed in microglia and highlight an immune-related protein-protein interaction network enriched for previously identified AD risk genes. These genetic findings provide additional evidence that the microglia-mediated innate immune response contributes directly to AD development

Genomic Relationships, Novel Loci, and Pleiotropic Mechanisms across Eight Psychiatric Disorders

Genetic influences on psychiatric disorders transcend diagnostic boundaries, suggesting substantial pleiotropy of contributing loci. However, the nature and mechanisms of these pleiotropic effects remain unclear. We performed analyses of 232,964 cases and 494,162 controls from genome-wide studies of anorexia nervosa, attention-deficit/hyper-activity disorder, autism spectrum disorder, bipolar disorder, major depression, obsessive-compulsive disorder, schizophrenia, and Tourette syndrome. Genetic correlation analyses revealed a meaningful structure within the eight disorders, identifying three groups of inter-related disorders. Meta-analysis across these eight disorders detected 109 loci associated with at least two psychiatric disorders, including 23 loci with pleiotropic effects on four or more disorders and 11 loci with antagonistic effects on multiple disorders. The pleiotropic loci are located within genes that show heightened expression in the brain throughout the lifespan, beginning prenatally in the second trimester, and play prominent roles in neurodevelopmental processes. These findings have important implications for psychiatric nosology, drug development, and risk prediction.Peer reviewe

New genetic loci link adipose and insulin biology to body fat distribution.

Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, here we conduct genome-wide association meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals. We identify 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (BMI), and an additional 19 loci newly associated with related waist and hip circumference measures (P < 5 × 10(-8)). In total, 20 of the 49 waist-to-hip ratio adjusted for BMI loci show significant sexual dimorphism, 19 of which display a stronger effect in women. The identified loci were enriched for genes expressed in adipose tissue and for putative regulatory elements in adipocytes. Pathway analyses implicated adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead