Single-Cell Transcriptomic Profiling of Pluripotent Stem Cell-Derived SCGB3A2+ Airway Epithelium.

Lung epithelial lineages have been difficult to maintain in pure form in vitro, and lineage-specific reporters have proven invaluable for monitoring their emergence from cultured pluripotent stem cells (PSCs). However, reporter constructs for tracking proximal airway lineages generated from PSCs have not been previously available, limiting the characterization of these cells. Here, we engineer mouse and human PSC lines carrying airway secretory lineage reporters that facilitate the tracking, purification, and profiling of this lung subtype. Through bulk and single-cell-based global transcriptomic profiling, we find PSC-derived airway secretory cells are susceptible to phenotypic plasticity exemplified by the tendency to co-express both a proximal airway secretory program as well as an alveolar type 2 cell program, which can be minimized by inhibiting endogenous Wnt signaling. Our results provide global profiles of engineered lung cell fates, a guide for improving their directed differentiation, and a human model of the developing airway

SNPs in Multi-Species Conserved Sequences (MCS) as useful markers in association studies: a practical approach

<p>Abstract</p> <p>Background</p> <p>Although genes play a key role in many complex diseases, the specific genes involved in most complex diseases remain largely unidentified. Their discovery will hinge on the identification of key sequence variants that are conclusively associated with disease. While much attention has been focused on variants in protein-coding DNA, variants in noncoding regions may also play many important roles in complex disease by altering gene regulation. Since the vast majority of noncoding genomic sequence is of unknown function, this increases the challenge of identifying "functional" variants that cause disease. However, evolutionary conservation can be used as a guide to indicate regions of noncoding or coding DNA that are likely to have biological function, and thus may be more likely to harbor SNP variants with functional consequences. To help bias marker selection in favor of such variants, we devised a process that prioritizes annotated SNPs for genotyping studies based on their location within Multi-species Conserved Sequences (MCSs) and used this process to select SNPs in a region of linkage to a complex disease. This allowed us to evaluate the utility of the chosen SNPs for further association studies. Previously, a region of chromosome 1q43 was linked to Multiple Sclerosis (MS) in a genome-wide screen. We chose annotated SNPs in the region based on location within MCSs (termed MCS-SNPs). We then obtained genotypes for 478 MCS-SNPs in 989 individuals from MS families.</p> <p>Results</p> <p>Analysis of our MCS-SNP genotypes from the 1q43 region and comparison to HapMap data confirmed that annotated SNPs in MCS regions are frequently polymorphic and show subtle signatures of selective pressure, consistent with previous reports of genome-wide variation in conserved regions. We also present an online tool that allows MCS data to be directly exported to the UCSC genome browser so that MCS-SNPs can be easily identified within genomic regions of interest.</p> <p>Conclusion</p> <p>Our results showed that MCS can easily be used to prioritize markers for follow-up and candidate gene association studies. We believe that this novel approach demonstrates a paradigm for expediting the search for genes contributing to complex diseases.</p

Model organisms contribute to diagnosis and discovery in the Undiagnosed Diseases Network: Current state and a future vision

Decreased sequencing costs have led to an explosion of genetic and genomic data. These data have revealed thousands of candidate human disease variants. Establishing which variants cause phenotypes and diseases, however, has remained challenging. Significant progress has been made, including advances by the National Institutes of Health (NIH)-funded Undiagnosed Diseases Network (UDN). However, 6000-13,000 additional disease genes remain to be identified. The continued discovery of rare diseases and their genetic underpinnings provides benefits to affected patients, of whom there are more than 400 million worldwide, and also advances understanding the mechanisms of more common diseases. Platforms employing model organisms enable discovery of novel gene-disease relationships, help establish variant pathogenicity, and often lead to the exploration of underlying mechanisms of pathophysiology that suggest new therapies. The Model Organism Screening Center (MOSC) of the UDN is a unique resource dedicated to utilizing informatics and functional studies in model organisms, including worm (Caenorhabditis elegans), fly (Drosophila melanogaster), and zebrafish (Danio rerio), to aid in diagnosis. The MOSC has directly contributed to the diagnosis of challenging cases, including multiple patients with complex, multi-organ phenotypes. In addition, the MOSC provides a framework for how basic scientists and clinicians can collaborate to drive diagnoses. Customized experimental plans take into account patient presentations, specific genes and variant(s), and appropriateness of each model organism for analysis. The MOSC also generates bioinformatic and experimental tools and reagents for the wider scientific community. Two elements of the MOSC that have been instrumental in its success are (1) multidisciplinary teams with expertise in variant bioinformatics and in human and model organism genetics, and (2) mechanisms for ongoing communication with clinical teams. Here we provide a position statement regarding the central role of model organisms for continued discovery of disease genes, and we advocate for the continuation and expansion of MOSC-type research entities as a Model Organisms Network (MON) to be funded through grant applications submitted to the NIH, family groups focused on specific rare diseases, other philanthropic organizations, industry partnerships, and other sources of support

The Arctic Research of the Composition of the Troposphere from Aircraft and Satellites (ARCTAS) Mission: Design, Execution, and First Results

The NASA Arctic Research of the Composition of the Troposphere from Aircraft and Satellites (ARCTAS) mission was conducted in two 3-week deployments based in Alaska (April 2008) and western Canada (June–July 2008). Its goal was to better understand the factors driving current changes in Arctic atmospheric composition and climate, including (1) influx of mid-latitude pollution, (2) boreal forest fires, (3) aerosol radiative forcing, and (4) chemical processes. The June–July deployment was preceded by one week of flights over California (ARCTAS-CARB) focused on (1) improving state emission inventories for greenhouse gases and aerosols, (2) providing observations to test and improve models of ozone and aerosol pollution. ARCTAS involved three aircraft: a DC-8 with a detailed chemical payload, a P-3 with an extensive aerosol and radiometric payload, and a B-200 with aerosol remote sensing instrumentation. The aircraft data augmented satellite observations of Arctic atmospheric composition, in particular from the NASA A-Train. The spring phase (ARCTAS-A) revealed pervasive Asian pollution throughout the Arctic as well as significant European pollution below 2 km. Unusually large Siberian fires in April 2008 caused high concentrations of carbonaceous aerosols and also affected ozone. Satellite observations of BrO column hotspots were found not to be related to Arctic boundary layer events but instead to tropopause depressions, suggesting the presence of elevated inorganic bromine (5–10 pptv) in the lower stratosphere. Fresh fire plumes from Canada and California sampled during the summer phase (ARCTAS-B) indicated low $NO_x$ emission factors from the fires, rapid conversion of $NO_x$ to PAN, no significant secondary aerosol production, and no significant ozone enhancements except when mixed with urban pollution.Engineering and Applied Science

Search for short baseline nu(e) disappearance with the T2K near detector

8 pages, 6 figures, submitted to PRD rapid communication8 pages, 6 figures, submitted to PRD rapid communicationWe thank the J-PARC staff for superb accelerator performance and the CERN NA61 collaboration for providing valuable particle production data. We acknowledge the support of MEXT, Japan; NSERC, NRC and CFI, Canada; Commissariat `a l’Energie Atomique and Centre National de la Recherche Scientifique–Institut National de Physique Nucle´aire et de Physique des Particules, France; DFG, Germany; INFN, Italy; National Science Centre (NCN), Poland; Russian Science Foundation, RFBR and Ministry of Education and Science, Russia; MINECO and European Regional Development Fund, Spain; Swiss National Science Foundation and State Secretariat for Education, Research and Innovation, Switzerland; STFC, UK; and DOE, USA. We also thank CERN for the UA1/NOMAD magnet, DESY for the HERA-B magnet mover system, NII for SINET4, the WestGrid and SciNet consortia in Compute Canada, GridPP, UK. In addition participation of individual researchers and institutions has been further supported by funds from ERC (FP7), EU; JSPS, Japan; Royal Society, UK; DOE Early Career program, USA

Measurements of neutrino oscillation in appearance and disappearance channels by the T2K experiment with 6.6 x 10(20) protons on target

111 pages, 45 figures, submitted to Physical Review D. Minor revisions to text following referee comments111 pages, 45 figures, submitted to Physical Review D. Minor revisions to text following referee comments111 pages, 45 figures, submitted to Physical Review D. Minor revisions to text following referee commentsWe thank the J-PARC staff for superb accelerator performance and the CERN NA61/SHINE Collaboration for providing valuable particle production data. We acknowledge the support of MEXT, Japan; NSERC, NRC, and CFI, Canada; CEA and CNRS/IN2P3, France; DFG, Germany; INFN, Italy; National Science Centre (NCN), Poland; RSF, RFBR and MES, Russia; MINECO and ERDF funds, Spain; SNSF and SER, Switzerland; STFC, UK; and the U. S. Deparment of Energy, USA. We also thank CERN for the UA1/NOMAD magnet, DESY for the HERA-B magnet mover system, NII for SINET4, the WestGrid and SciNet consortia in Compute Canada, GridPP, UK, and the Emerald High Performance Computing facility in the Centre for Innovation, UK. In addition, participation of individual researchers and institutions has been further supported by funds from ERC (FP7), EU; JSPS, Japan; Royal Society, UK; and DOE Early Career program, USA

Measurement of the electron neutrino charged-current interaction rate on water with the T2K ND280 pi(0) detector

10 pages, 6 figures, Submitted to PRDhttp://journals.aps.org/prd/abstract/10.1103/PhysRevD.91.112010© 2015 American Physical Society11 pages, 6 figures, as accepted to PRD11 pages, 6 figures, as accepted to PRD11 pages, 6 figures, as accepted to PR

Genetic risk and a primary role for cell-mediated immune mechanisms in multiple sclerosis.

Multiple sclerosis is a common disease of the central nervous system in which the interplay between inflammatory and neurodegenerative processes typically results in intermittent neurological disturbance followed by progressive accumulation of disability. Epidemiological studies have shown that genetic factors are primarily responsible for the substantially increased frequency of the disease seen in the relatives of affected individuals, and systematic attempts to identify linkage in multiplex families have confirmed that variation within the major histocompatibility complex (MHC) exerts the greatest individual effect on risk. Modestly powered genome-wide association studies (GWAS) have enabled more than 20 additional risk loci to be identified and have shown that multiple variants exerting modest individual effects have a key role in disease susceptibility. Most of the genetic architecture underlying susceptibility to the disease remains to be defined and is anticipated to require the analysis of sample sizes that are beyond the numbers currently available to individual research groups. In a collaborative GWAS involving 9,772 cases of European descent collected by 23 research groups working in 15 different countries, we have replicated almost all of the previously suggested associations and identified at least a further 29 novel susceptibility loci. Within the MHC we have refined the identity of the HLA-DRB1 risk alleles and confirmed that variation in the HLA-A gene underlies the independent protective effect attributable to the class I region. Immunologically relevant genes are significantly overrepresented among those mapping close to the identified loci and particularly implicate T-helper-cell differentiation in the pathogenesis of multiple sclerosis

Genome-wide and Ordered-Subset linkage analyses provide support for autism loci on 17q and 19p with evidence of phenotypic and interlocus genetic correlates

BACKGROUND: Autism is a neurobehavioral spectrum of phenotypes characterized by deficits in the development of language and social relationships and patterns of repetitive, rigid and compulsive behaviors. Twin and family studies point to a significant genetic etiology, and several groups have performed genomic linkage screens to identify susceptibility loci. METHODS: We performed a genome-wide linkage screen in 158 combined Tufts, Vanderbilt and AGRE (Autism Genetics Research Exchange) multiplex autism families using parametric and nonparametric methods with a categorical autism diagnosis to identify loci of main effect. Hypothesizing interdependence of genetic risk factors prompted us to perform exploratory studies applying the Ordered-Subset Analysis (OSA) approach using LOD scores as the trait covariate for ranking families. We employed OSA to test for interlocus correlations between loci with LOD scores ≥1.5, and empirically determined significance of linkage in optimal OSA subsets using permutation testing. Exploring phenotypic correlates as the basis for linkage increases involved comparison of mean scores for quantitative trait-based subsets of autism between optimal subsets and the remaining families. RESULTS: A genome-wide screen for autism loci identified the best evidence for linkage to 17q11.2 and 19p13, with maximum multipoint heterogeneity LOD scores of 2.9 and 2.6, respectively. Suggestive linkage (LOD scores ≥1.5) at other loci included 3p, 6q, 7q, 12p, and 16p. OSA revealed positive correlations of linkage between the 19p locus and 17q, between 19p and 6q, and between 7q and 5p. While potential phenotypic correlates for these findings were not identified for the chromosome 7/5 combination, differences indicating more rapid achievement of "developmental milestones" was apparent in the chromosome 19 OSA-defined subsets for 17q and 6q. OSA was used to test the hypothesis that 19p linkage involved more rapid achievement of these milestones and it revealed significantly increased LOD* scores at 19p13. CONCLUSIONS: Our results further support 19p13 as harboring an autism susceptibility locus, confirm other linkage findings at 17q11.2, and demonstrate the need to analyze more discreet trait-based subsets of complex phenotypes to improve ability to detect genetic effects

Gene-Network Analysis Identifies Susceptibility Genes Related to Glycobiology in Autism

The recent identification of copy-number variation in the human genome has opened up new avenues for the discovery of positional candidate genes underlying complex genetic disorders, especially in the field of psychiatric disease. One major challenge that remains is pinpointing the susceptibility genes in the multitude of disease-associated loci. This challenge may be tackled by reconstruction of functional gene-networks from the genes residing in these loci. We applied this approach to autism spectrum disorder (ASD), and identified the copy-number changes in the DNA of 105 ASD patients and 267 healthy individuals with Illumina Humanhap300 Beadchips. Subsequently, we used a human reconstructed gene-network, Prioritizer, to rank candidate genes in the segmental gains and losses in our autism cohort. This analysis highlighted several candidate genes already known to be mutated in cognitive and neuropsychiatric disorders, including RAI1, BRD1, and LARGE. In addition, the LARGE gene was part of a sub-network of seven genes functioning in glycobiology, present in seven copy-number changes specifically identified in autism patients with limited co-morbidity. Three of these seven copy-number changes were de novo in the patients. In autism patients with a complex phenotype and healthy controls no such sub-network was identified. An independent systematic analysis of 13 published autism susceptibility loci supports the involvement of genes related to glycobiology as we also identified the same or similar genes from those loci. Our findings suggest that the occurrence of genomic gains and losses of genes associated with glycobiology are important contributors to the development of ASD