Near Real-Time Use of Optical Remote Sensing and Synthetic Aperture Radar for Response to Central U.S. Flooding in Late April-Early May 2017

No abstract availabl

Model Sensitivity to Topographic Uncertainty in Meso- and Microtidal Marshes

Light detection and ranging (Lidar) derived digital elevation models are widely used in modeling coastal marsh systems. However, the topographic error in these models can affect simulations of marsh coverage and characteristics. We investigated the relevance and impact of this error in micro- and mesotidal systems. Lidar-derived and RTK-adjusted topography were each used in a dynamic marsh model, and the resulting marsh coverages were examined. For two microtidal sites (Apalachicola, FL, USA, and Grand Bay, MS, USA) using solely lidar-derived topography, the model produced Cohen Kappa values of 0.1 for both estuaries when compared with National Wetland Inventory data indicating “very poor agreement.” Applying the RTK-adjusted topography improved the model marsh coverage results to “substantial agreement” with the values to 0.6 and 0.77, respectively. The mesotidal site in Plum Island, MA, USA, contained similar topographic errors, but the model produced a Cohen Kappa value of 0.73, which categorized it as “very good agreement” with no need for a further topographic adjustment given its present robust biomass productivity. The results demonstrate that marsh models are sensitive to topographic errors when the errors are comparable to the tidal range. The particular sensitivity of the modeling results to topographic error in microtidal systems highlights the need for close scrutiny of lidar-derived topography

Using Optical Remote Sensing and Synthetic Aperture Radar for Near-Real-Time Response to the Central U.S. Flooding in April-May 2017

No abstract availabl

Host Plants and Climate Structure Habitat Associations of the Western Monarch Butterfly

The monarch butterfly is one of the most easily recognized and frequently studied insects in the world, and has recently come into the spotlight of public attention and conservation concern because of declining numbers of individuals associated with both the eastern and western migrations. Historically, the larger eastern migration has received the most scientific attention, but this has been changing in recent years, and here we report the largest-ever attempt to map and characterize non-overwintering habitat for the western monarch butterfly. Across the environmentally and topographically complex western landscape, we include 8,427 observations of adults and juvenile monarchs, as well as 20,696 records from 13 milkweed host plant species. We find high heterogeneity of suitable habitats across the geographic range, with extensive concentrations in the California floristic province in particular. We also find habitat suitability for the butterfly to be structured primarily by host plant habitat associations, which are in turn structured by a diverse suite of climatic variables. These results add to our knowledge of range and occupancy determinants for migratory species and provide a tool that can be used by conservation biologists and researchers interested in interactions among climate, hosts and host-specific animals, and by managers for prioritizing future conservation actions at regional to watershed scales

Alliance of Genome Resources Portal: unified model organism research platform

The Alliance of Genome Resources (Alliance) is a consortium of the major model organism databases and the Gene Ontology that is guided by the vision of facilitating exploration of related genes in human and well-studied model organisms by providing a highly integrated and comprehensive platform that enables researchers to leverage the extensive body of genetic and genomic studies in these organisms. Initiated in 2016, the Alliance is building a central portal (www.alliancegenome.org) for access to data for the primary model organisms along with gene ontology data and human data. All data types represented in the Alliance portal (e.g. genomic data and phenotype descriptions) have common data models and workflows for curation. All data are open and freely available via a variety of mechanisms. Long-term plans for the Alliance project include a focus on coverage of additional model organisms including those without dedicated curation communities, and the inclusion of new data types with a particular focus on providing data and tools for the non-model-organism researcher that support enhanced discovery about human health and disease. Here we review current progress and present immediate plans for this new bioinformatics resource

Alliance of Genome Resources Portal: unified model organism research platform

The Alliance of Genome Resources (Alliance) is a consortium of the major model organism databases and the Gene Ontology that is guided by the vision of facilitating exploration of related genes in human and well-studied model organisms by providing a highly integrated and comprehensive platform that enables researchers to leverage the extensive body of genetic and genomic studies in these organisms. Initiated in 2016, the Alliance is building a central portal (www.alliancegenome.org) for access to data for the primary model organisms along with gene ontology data and human data. All data types represented in the Alliance portal (e.g. genomic data and phenotype descriptions) have common data models and workflows for curation. All data are open and freely available via a variety of mechanisms. Long-term plans for the Alliance project include a focus on coverage of additional model organisms including those without dedicated curation communities, and the inclusion of new data types with a particular focus on providing data and tools for the non-model-organism researcher that support enhanced discovery about human health and disease. Here we review current progress and present immediate plans for this new bioinformatics resource

Preterm neonatal morbidity and mortality by gestational age: a contemporary cohort

Although preterm birth less than 37 weeks gestation is the leading cause of neonatal morbidity and mortality in the United States, the majority of data regarding preterm neonatal outcomes come from older studies, and many reports have been limited to only very preterm neonates. Delineation of neonatal outcomes by delivery gestational age is needed to further clarify the continuum of mortality and morbidity frequencies among preterm neonates

No Reliable Association between Runs of Homozygosity and Schizophrenia in a Well-Powered Replication Study

It is well known that inbreeding increases the risk of recessive monogenic diseases, but it is less certain whether it contributes to the etiology of complex diseases such as schizophrenia. One way to estimate the effects of inbreeding is to examine the association between disease diagnosis and genome-wide autozygosity estimated using runs of homozygosity (ROH) in genome-wide single nucleotide polymorphism arrays. Using data for schizophrenia from the Psychiatric Genomics Consortium (n = 21,868), Keller et al. (2012) estimated that the odds of developing schizophrenia increased by approximately 17% for every additional percent of the genome that is autozygous (β = 16.1, CI(β) = [6.93, 25.7], Z = 3.44, p = 0.0006). Here we describe replication results from 22 independent schizophrenia case-control datasets from the Psychiatric Genomics Consortium (n = 39,830). Using the same ROH calling thresholds and procedures as Keller et al. (2012), we were unable to replicate the significant association between ROH burden and schizophrenia in the independent PGC phase II data, although the effect was in the predicted direction, and the combined (original + replication) dataset yielded an attenuated but significant relationship between Froh and schizophrenia (β = 4.86,CI(β) = [0.90,8.83],Z = 2.40,p = 0.02). Since Keller et al. (2012), several studies reported inconsistent association of ROH burden with complex traits, particularly in case-control data. These conflicting results might suggest that the effects of autozygosity are confounded by various factors, such as socioeconomic status, education, urbanicity, and religiosity, which may be associated with both real inbreeding and the outcome measures of interest

Contribution of copy number variants to schizophrenia from a genome-wide study of 41,321 subjects

Copy number variants (CNVs) have been strongly implicated in the genetic etiology of schizophrenia (SCZ). However, genome-wide investigation of the contribution of CNV to risk has been hampered by limited sample sizes. We sought to address this obstacle by applying a centralized analysis pipeline to a SCZ cohort of 21,094 cases and 20,227 controls. A global enrichment of CNV burden was observed in cases (OR=1.11, P=5.7×10−15), which persisted after excluding loci implicated in previous studies (OR=1.07, P=1.7 ×10−6). CNV burden was enriched for genes associated with synaptic function (OR = 1.68, P = 2.8 ×10−11) and neurobehavioral phenotypes in mouse (OR = 1.18, P= 7.3 ×10−5). Genome-wide significant evidence was obtained for eight loci, including 1q21.1, 2p16.3 (NRXN1), 3q29, 7q11.2, 15q13.3, distal 16p11.2, proximal 16p11.2 and 22q11.2. Suggestive support was found for eight additional candidate susceptibility and protective loci, which consisted predominantly of CNVs mediated by non-allelic homologous recombination

Genetic correlation between amyotrophic lateral sclerosis and schizophrenia

A. Palotie on työryhmän Schizophrenia Working Grp Psychiat jäsen.We have previously shown higher-than-expected rates of schizophrenia in relatives of patients with amyotrophic lateral sclerosis (ALS), suggesting an aetiological relationship between the diseases. Here, we investigate the genetic relationship between ALS and schizophrenia using genome-wide association study data from over 100,000 unique individuals. Using linkage disequilibrium score regression, we estimate the genetic correlation between ALS and schizophrenia to be 14.3% (7.05-21.6; P = 1 x 10(-4)) with schizophrenia polygenic risk scores explaining up to 0.12% of the variance in ALS (P = 8.4 x 10(-7)). A modest increase in comorbidity of ALS and schizophrenia is expected given these findings (odds ratio 1.08-1.26) but this would require very large studies to observe epidemiologically. We identify five potential novel ALS-associated loci using conditional false discovery rate analysis. It is likely that shared neurobiological mechanisms between these two disorders will engender novel hypotheses in future preclinical and clinical studies.Peer reviewe