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Research data keyboard_double_arrow_right Dataset 2018Embargo end date: 08 Jun 2018 EnglishDryad NSERC, NWO | Adaptation to environment..., EC | SHENSERC ,NWO| Adaptation to environmental change in blue tits, what do insights from the past tell us about the future? ,EC| SHEDubuc-Messier, Gabrielle; Caro, Samuel P.; Perrier, Charles; Van Oers, Kees; Reale, Denis; Charmantier, Anne;Understanding the causes and consequences of population phenotypic divergence is a central goal in ecology and evolution. Phenotypic divergence among populations can result from genetic divergence, phenotypic plasticity or a combination of the two. However, few studies have deciphered these mechanisms for populations geographically close and connected by gene flow, especially in the case of personality traits. In this study, we used a common garden experiment to explore the genetic basis of the phenotypic divergence observed between two blue tit (Cyanistes caeruleus) populations inhabiting contrasting habitats separated by 25 km, for two personality traits (exploration speed and handling aggression), one physiological trait (heart rate during restraint) and two morphological traits (tarsus length and body mass). Blue tit nestlings were removed from their population and raised in a common garden for up to five years. We then compared adult phenotypes between the two populations, as well as trait-specific Qst and Fst . Our results revealed differences between populations similar to those found in the wild, suggesting a genetic divergence for all traits. Qst - Fst comparisons revealed that the traits divergences likely result from dissimilar selection patterns rather than from genetic drift. Our study is one of the first to report a Qst - Fst comparison for personality traits and adds to the growing body of evidence that population genetic divergence is possible at a small scale for a variety of traits including behavioural traits. Data filesArchive.zip
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visibility 5visibility views 5 download downloads 1 Powered bymore_vert DRYAD; NARCIS; DANS-... arrow_drop_down DRYAD; NARCIS; DANS-EASYDataset . 2018add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2019Embargo end date: 07 May 2019 EnglishDryad UKRI | Deciphering dog domestica..., WT, EC | UNDEAD +7 projectsUKRI| Deciphering dog domestication through a combined ancient DNA and geometric morphometric approach ,WT ,EC| UNDEAD ,EC| TURKEY ,EC| Extinction Genomics ,SSHRC ,WT| Genome diversity and evolution in transmissible cancers in dogs and tasmanian devils ,NSF| Doctoral Dissertation Research: Human Population Inferences Via Canine Genetics ,NIH| Comprehensive Characterization of Canine Genomic Structural Diversity ,WT| Domestic animals as a model to understand the relationship between deleterious mutations, demography and diseaseAuthors: Leathlobhair, Máire Ní; Perri, Angela R.; Irving-Pease, Evan K.; Witt, Kelsey E.; +46 AuthorsLeathlobhair, Máire Ní; Perri, Angela R.; Irving-Pease, Evan K.; Witt, Kelsey E.; Linderholm, Anna; Haile, James; Lebrasseur, Ophelie; Ameen, Carly; Blick, Jeffrey; Boyko, Adam R.; Brace, Selina; Nunes Cortes, Yahaira; Crockford, Susan J.; Devault, Alison; Dimopoulos, Evangelos A.; Eldridge, Morley; Enk, Jacob; Gopalakrishnan, Shyam; Gori, Kevin; Grimes, Vaughan; Guiry, Eric; Hansen, Anders J.; Hulme-Beaman, Ardern; Johnson, John; Kitchen, Andrew; Kasparov, Aleksei K.; Kwon, Young-Mi; Nikolskiy, Pavel A.; Peraza Lope, Carlos; Manin, Aurélie; Martin, Terrance; Meyer, Michael; Noack Myers, Kelsey; Omura, Mark; Rouillard, Jean-Marie; Pavlova, Elena Y.; Sciulli, Paul; Mikkel-Holger, Sinding S.; Strakova, Andrea; Ivanova, Varvara V.; Widga, Christopher; Willerslev, Eske; Pitulko, Vladimir V.; Barnes, Ian; Gilbert, M. Thomas P.; Dobney, Keith M.; Malhi, Ripan S.; Murchison, Elizabeth P.; Larson, Greger; Frantz, Laurent A. F.;Dogs were present in the Americas prior to the arrival of European colonists, but the origin and fate of these pre-contact dogs are largely unknown. We sequenced 71 mitochondrial and seven nuclear genomes from ancient North American and Siberian dogs spanning ~9,000 years. Our analysis indicates that American dogs were not domesticated from North American wolves. Instead, American dogs form a monophyletic lineage that likely originated in Siberia and dispersed into the Americas alongside people. After the arrival of Europeans, native American dogs almost completely disappeared, leaving a minimal genetic legacy in modern dog populations. Remarkably, the closest detectable extant lineage to pre-contact American dogs is the canine transmissible venereal tumor, a contagious cancer clone derived from an individual dog that lived up to 8,000 years ago. Mitochondrial DNA FASTA fileFASTA file containing 1166 dog mtDNA genomes used in this studyfull_mtDNA_alignment.fastaNEXUS treeMaximum likelihood tree (RAxML) of 1166 dogs mtDNA genomes used in this studyfull_mtDNA_alignment.treExcel sheetPublication source of the 1166 mtDNA genomes used in this studyfull_mtDNA_alignment.xlsxPlink (bed) fileContains genotype for dogs 54 dogsfull_data.bedPlink file (bim)Contains genotype for 54 dogsfull_data.bimPlink file (fam)Contains genotype for 54 dogsfull_data.famNJ tree in Figure 2bNJ tree in Figure 2b (see Table S2 for more info)Figure_b.treNexus fileNexus file used for producing Figure S12 (MKV model in MrBayes)Binary_char_MKV.nexNEXUS treeBayesian tree in Figure S12 (see Table S2 for more info)Figure_S12.tre
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For further information contact us at helpdesk@openaire.euapps Other research product2018 English NSERC, EC | NORSNSERC ,EC| NORSAdams, C.; Strong, K.; Batchelor, R. L.; Bernath, P. F.; Brohede, S.; Boone, C.; Degenstein, D.; Daffer, W. H.; Drummond, J. R.; Fogal, P. F.; Farahani, E.; Fayt, C.; Fraser, A.; Goutail, F.; Hendrick, F.; Kolonjari, F.; Lindenmaier, R.; Manney, G.; McElroy, C. T.; McLinden, C. A.; Mendonca, J.; Park, J.-H.; Pavlovic, B.; Pazmino, A.; Roth, C.; Savastiouk, V.; Walker, K. A.; Weaver, D.; Zhao, X.;The Optical Spectrograph and Infra-Red Imager System (OSIRIS) and the Atmospheric Chemistry Experiment (ACE) have been taking measurements from space since 2001 and 2003, respectively. This paper presents intercomparisons between ozone and NO2 measured by the ACE and OSIRIS satellite instruments and by ground-based instruments at the Polar Environment Atmospheric Research Laboratory (PEARL), which is located at Eureka, Canada (80° N, 86° W) and is operated by the Canadian Network for the Detection of Atmospheric Change (CANDAC). The ground-based instruments included in this study are four zenith-sky differential optical absorption spectroscopy (DOAS) instruments, one Bruker Fourier transform infrared spectrometer (FTIR) and four Brewer spectrophotometers. Ozone total columns measured by the DOAS instruments were retrieved using new Network for the Detection of Atmospheric Composition Change (NDACC) guidelines and agree to within 3.2%. The DOAS ozone columns agree with the Brewer spectrophotometers with mean relative differences that are smaller than 1.5%. This suggests that for these instruments the new NDACC data guidelines were successful in producing a homogenous and accurate ozone dataset at 80° N. Satellite 14–52 km ozone and 17–40 km NO2 partial columns within 500 km of PEARL were calculated for ACE-FTS Version 2.2 (v2.2) plus updates, ACE-FTS v3.0, ACE-MAESTRO (Measurements of Aerosol Extinction in the Stratosphere and Troposphere Retrieved by Occultation) v1.2 and OSIRIS SaskMART v5.0x ozone and Optimal Estimation v3.0 NO2 data products. The new ACE-FTS v3.0 and the validated ACE-FTS v2.2 partial columns are nearly identical, with mean relative differences of 0.0 ± 0.2% and −0.2 ± 0.1% for v2.2 minus v3.0 ozone and NO2, respectively. Ozone columns were constructed from 14–52 km satellite and 0–14 km ozonesonde partial columns and compared with the ground-based total column measurements. The satellite-plus-sonde measurements agree with the ground-based ozone total columns with mean relative differences of 0.1–7.3%. For NO2, partial columns from 17 km upward were scaled to noon using a photochemical model. Mean relative differences between OSIRIS, ACE-FTS and ground-based NO2 measurements do not exceed 20%. ACE-MAESTRO measures more NO2 than the other instruments, with mean relative differences of 25–52%. Seasonal variation in the differences between NO2 partial columns is observed, suggesting that there are systematic errors in the measurements and/or the photochemical model corrections. For ozone spring-time measurements, additional coincidence criteria based on stratospheric temperature and the location of the polar vortex were found to improve agreement between some of the instruments. For ACE-FTS v2.2 minus Bruker FTIR, the 2007–2009 spring-time mean relative difference improved from −5.0 ± 0.4% to −3.1 ± 0.8% with the dynamical selection criteria. This was the largest improvement, likely because both instruments measure direct sunlight and therefore have well-characterized lines-of-sight compared with scattered sunlight measurements. For NO2, the addition of a ±1° latitude coincidence criterion improved spring-time intercomparison results, likely due to the sharp latitudinal gradient of NO2 during polar sunrise. The differences between satellite and ground-based measurements do not show any obvious trends over the missions, indicating that both the ACE and OSIRIS instruments continue to perform well.
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For further information contact us at helpdesk@openaire.euapps Other research productkeyboard_double_arrow_right Other ORP type 2020 EnglishmedRxiv NIH | The Electronic Medical Re..., NIH | Modifier Genes that Influ..., NIH | Consequences of Self-Negl... +108 projectsNIH| The Electronic Medical Records and Genomics (eMERGE) Network, Phase III ,NIH| Modifier Genes that Influence Age at Onset or Protect Against Development of Alzheimer's Disease (AD) ,NIH| Consequences of Self-Neglect in a Biracial Population of Older People ,NIH| Sequence-based Discovery of AD Risk & Protective Alleles ,NIH| Clinical Core ,NIH| Large Scale Genome Sequencing ,NIH| ROLE FOR FIBROBLAST GROWTH FACTOR IN ALZHEIMERS DISEASE ,NIH| Multi-ethnic genome-wide Alzheimer association study ,NIH| ARIC Neurocognitive Study (ARIC-NCS) ,NIH| ALZHEIMERS DISEASE RESEARCH CENTER ,NIH| A Proteogenomic Approach to Understanding AD GWAS Results ,NIH| CORONARY HEART DISEASE AND STROKE ,NIH| CORONARY HEART DISEASE &STROKE IN PEOPLE AGED 65-84 ,NIH| Role of LRP &its ligand tPA in LTP &aging ,ANR| GENMED ,NIH| Statistical Methods for Next-Gen Sequencing in Disease Association Studies ,NWO| 100-plus ,NWO| 100-plus ,NIH| Building Research Infrastructure &Network in Chicago Chinatown ,CIHR ,NIH| Genetic Studies of Alzheimer's Disease in Caribbean Hispanics ,NIH| UCLA Alzheimers Disease Research Center ,NIH| Genetic Studies of Alzheimer Disease in Koreans ,NIH| Alzheimers Disease in Mild Cognitive Impairment ,NIH| CHS-Transition Phase -268055222 ,NIH| Administrative Core ,NIH| GENETIC DIFFERENCES IN ALZHEIMERS CASES AND CONTROLS ,NIH| CHARGE consortium: gene discovery for CVD and aging phenotypes ,NIH| Alzheimers Disease and Gene Discovery on Chromosome 9 ,NIH| GENETIC EPIDEMIOLOGICAL STUDIES OF ALZHEIMERS DISEASE ,NWO| NCHA Subsidiebesluit 2008-2012 ,NIH| GENES, AGING, LEARNING AND DEMENTIA ,NIH| CORONARY HEART DISEASE &STROKE IN PEOPLE AGED 65-84 ,NIH| Gene discovery in PSP by transcriptome, neuropathology and sequence analysis ,NIH| Genomes and Genetics at the BCM-HGSC ,NIH| Mayo Alzheimers Disease Research Center ,NIH| CORE--CLINICAL ,NIH| Genetic Epidemiology of Alzheimers Disease in African Americans ,NIH| Genetic Epidemiology of Early-Onset Alzheimers disease in Caribbean Hispanics and non-Hispanic Whites ,NIH| Risk Factors, Pathology, and Clinical Expressions of AD ,NIH| ARIC Neurocognitive Study (ARIC-NCS) ,NIH| Genome wide association study of gene expression levels in Alzheimers disease ,NIH| Consortium for Alzheimers Sequence Analysis (CASA) ,NIH| Metabolic Factors in AD ,FWF| Genetics of Cerebral Small Vessel Disease ,NIH| Genomic Convergence in Alzheimer Disease ,NIH| DATA MANAGEMENT AND BIOSTATISTICS ,NIH| Epidemiologic Study of Neural Reserve and Neurobiology of Aging ,NIH| Replication and Extension of ADSP Discoveries in African-Americans ,NIH| AMYLOID DEPOSTION, VASCULAR DISEASE AND CLINICAL PROGRESSION OF AD ,NIH| CORONARY HEART DISEASE AND STROKE ,NIH| ALZHEIMERS DISEASE AND ANIMAL MODELS ,FWF| MRI white matter abnormalities in the elderly: Genetic risk factors, rate of progression and neuropsychologic consequences ,NIH| Large Scale Sequencing and Analysis of Genomes ,NIH| THE FRAMINGHAM HEART STUDY-268025195 ,NIH| Stanford Alzheimer's Disease Research Center ,NIH| Next Generation gene discovery in neurogenetics ,NIH| CENTRAL BLOOD ANALYSIS LABORATORY FOR CHS ,NIH| Alzheimers Disease Center Core ,NIH| Genetic Studies of Dementia in the Amish ,NIH| A system approach to targeting innate immunity in AD ,NIH| RISK FACTORS FOR INCIDENT AD IN A BIRACIAL COMMUNITY ,NIH| Collaborative GWAS of Dementia, AD and related MRI and Cognitive Endophenotypes ,NIH| Boston University Alzheimer's Disease Center ,NIH| CHS research resources for the cardiovascular health of older adults ,NIH| Exceptional aging: 12 year trajectories to function ,NIH| Coordinating Center for Genetics and Genomics of Alzheimer's Disease (CGAD) ,NIH| CORE--CLINICAL ,NIH| QUANTITATIVE INDICES OF NEURON VULNERABILITY IN DEMENTIA ,NIH| THE NIA GENETICS OF ALZHEIMER'S DISEASE DATA STORAGE SITE ,NIH| ALZHEIMERS DISEASE DATA COORDINATING CENTER ,NIH| SHORT-TERM STABILITY OF CLINICAL TESTS ,NIH| CORE-- EDUCATION AND INFORMATION TRANSFER ,NIH| CHS Events Follow-up Study ,NIH| ARIC Neurocognitive Study (ARIC-NCS) ,NWO| Dissecting genetic complexity of Alzheimer's disease and cognitive function ,WT| BRAINEACv2: a resource for the interpretation of genetic variation in multiple regions of the adult human brain ,NIH| CORE--CLINICAL ,NIH| CHARGE: Identifying Risk & Protective SNV for AD in ADSP Case-control Sample ,NIH| The ARIC and Neurocognitive Longitudinal Study ,NIH| MRI, Cognitive, Genetic and Biomarker Precursors of AD & Dementia in Young Adults ,NIH| Building on GWAS for NHLBI-disease: the CHARGE consortium ,NIH| Integrative translational discovery of vascular risk factors in aging and dementia ,NIH| The National Institute on Aging (NIA) Late Onset of Alzheimer's Disease (LOAD) Family-Based Study (FBS) ,NIH| EDUCATION AND INFORMATION CORE ,EC| ENGAGE ,NIH| ADSP Follow-up in Multi-Ethnic Cohorts via Endophenotypes, Omics & Model Systems ,NIH| Temporal Trends, Novel Imaging and Molecular Characterization of Preclinical and Clinical Alzheimer's Disease in the Framingham Cohorts ,NIH| COGNITIVE TESTS, APOE, BRAIN MRI AND RISKS OF DEMENTIA ,NIH| Clinical Core ,NIH| Epidemiology of Familial Late-Onset Alzheimer's Disease ,NIH| Pleiotropy GWAS of Alzheimer's Disease ,NIH| Whole Genome Sequencing in Ethnically Diverse Cohorts for the ADSP Follow-Up Study (FUS) ,FWF| Mechanisms of Small Vessel Related Brain Damage and Cognitive Impairment ,NIH| INDIANAPOLIS/IBADAN DEMENTIA PROJECT ,NIH| Admin Supplement for University of Florida -Mt. Sinai Medical Center AD Research Center ,NIH| Clinical Core ,NIH| Sequence-based Discovery of AD Risk & Protective Alleles ,NIH| Alzheimer Disease Genetic Architecture in African Americans ,NIH| UC Davis Alzheimer's Core Center ,NIH| Identification and characterization of AD risk networks using multi-dimensional 'omics' data ,NIH| Alzheimer's Disease Genetics Consortium ,NIH| CORE--NEUROPATHOLOGY CORE ,NIH| GENETIC LINKAGE STUDIES IN NEUROGENETIC DISORDERS ,NIH| An Integrated Genomic Approach to Alzheimer Disease ,NIH| PRECURSORS OF STROKE INCIDENCE AND PROGNOSIS ,NIH| Genomic and Biological Studies of APOE ?2 in Alzheimer Disease ,NIH| National Cell Repository for Alzheimer's Disease (NCRAD) ,NIH| ALZHEIMERS DISEASE RESEARCH CENTER ,NIH| Genetic Epidemiology and Multi-Omics Analyses in Familial and Sporadic Alzheimer's Disease Among Secular Caribbean Hispanics and Religious Order ,NIH| Education and Information Transfer CoreHolstege, Henne; Grozeva, Detelina; Sims, Rebecca; Luckcuck, Lauren; Denning, Nicola; Marshall, Rachel; Saad, Salha; Williams, Julie; Meggy, Alun; Lambert, Jean-Charles; Hulsman, M.; Charbonnier, C.; Grenier-Boley, B.; Quenez, O.; van Rooij, J.; Ahmad, S.; Amin, N.; Norsworthy, P.; Dols, O.; Hummerich, H.; Kawalia, A.; Amouyel, P.; Beecham, G.; Berr, C.; Bis, J.; Boland, A.; Bossu, P.; Bouwman, F.; Campion, D.; Daniele, A.; Dartigues, J. F.; Debette, S.; Deleuze, J. F.; Destefano, A.; Farrer, L.; Fox, N.; Glimberti, D.; Genin, E.; Haines, J.; Holmes, C.; Arfan Ikram, M.; Ikram, M.; Jansen, I.; Kraaij, R.; Lathrop, M.; Lemstra, A.; Lleo, A.; Luckcuck, L.; Marschall, R.; Martin, E.; Masullo, C.; Mayeux, R.; Mecocci, P.; Mol, M.; Morgan, K.; Nacmia, B.; Naj, A.; Pastor, P.; Pericak-Vance, M.; Redon, R; Richard, A. C.; Riedel-Heller, S.; Rivadeneira, F.; Rousseau, S.; Ryan, N.; Sanchez-Juan, P.; Schellenberg, G.; Scheltens, P.; Scott, J.; Seripa, D.; Spalletta, G.; Tijms, B.; Uitterlinden, A.; van der Lee, S.; Wagner, M.; Wallon, D.; Wang, L. S.; Zarea, A.; Reinders, M.; Clarimon, J.; van Swieten, J.; Hardy, J.; Ramirez, A.; Mead, S. H.; van der Flier, W.; van Duijn, C.; Nicolas, G.; Bellenguez, C.; Lambert, J. C.;The genetic component of Alzheimer’s disease (AD) has been mainly assessed using Genome Wide Association Studies (GWAS), which do not capture the risk contributed by rare variants. Here, we compared the gene-based burden of rare damaging variants in exome sequencing data from 32,558 individuals —16,036 AD cases and 16,522 controls— in a two-stage analysis. Next to known genes TREM2, SORL1 and ABCA7, we observed a significant association of rare, predicted damaging variants in ATP8B4 and ABCA1 with AD risk, and a suggestive signal in ADAM10. Next to these genes, the rare variant burden in RIN3, CLU, ZCWPW1 and ACE highlighted these genes as potential driver genes in AD-GWAS loci. Rare damaging variants in these genes, and in particular loss-of-function variants, have a large effect on AD-risk, and they are enriched in early onset AD cases. The newly identified AD-associated genes provide additional evidence for a major role for APP-processing, Aβ-aggregation, lipid metabolism and microglial function in AD.
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For further information contact us at helpdesk@openaire.euapps Other research product2018 English EC | HELIXEC| HELIXAuthors: Grillakis, Manolis G.; Koutroulis, Aristeidis G.; Daliakopoulos, Ioannis N.; Tsanis, Ioannis K.;Grillakis, Manolis G.; Koutroulis, Aristeidis G.; Daliakopoulos, Ioannis N.; Tsanis, Ioannis K.;Bias correction of climate variables is a standard practice in climate change impact (CCI) studies. Various methodologies have been developed within the framework of quantile mapping. However, it is well known that quantile mapping may significantly modify the long-term statistics due to the time dependency of the temperature bias. Here, a method to overcome this issue without compromising the day-to-day correction statistics is presented. The methodology separates the modeled temperature signal into a normalized and a residual component relative to the modeled reference period climatology, in order to adjust the biases only for the former and preserve the signal of the later. The results show that this method allows for the preservation of the originally modeled long-term signal in the mean, the standard deviation and higher and lower percentiles of temperature. To illustrate the improvements, the methodology is tested on daily time series obtained from five Euro CORDEX regional climate models (RCMs).
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2018Embargo end date: 19 Nov 2018 EnglishDryad EC | EVOCULTURE, NSERCEC| EVOCULTURE ,NSERCAuthors: Street, Sally E.; Navarrete, Ana F.; Reader, Simon M.; Laland, Kevin N.;Street, Sally E.; Navarrete, Ana F.; Reader, Simon M.; Laland, Kevin N.;Explanations for primate brain expansion and the evolution of human cognition and culture remain contentious despite extensive research. While multiple comparative analyses have investigated variation in brain size across primate species, very few have addressed why primates vary in how much they use social learning. Here, we evaluate the hypothesis that the enhanced reliance on socially transmitted behavior observed in some primates has coevolved with enlarged brains, complex sociality, and extended lifespans. Using recently developed phylogenetic comparative methods we show that, across primate species, a measure of social learning proclivity increases with absolute and relative brain volume, longevity (specifically reproductive lifespan), and social group size, correcting for research effort. We also confirm relationships of absolute and relative brain volume with longevity (both juvenile period and reproductive lifespan) and social group size, although longevity is generally the stronger predictor. Relationships between social learning, brain volume, and longevity remain when controlling for maternal investment and are therefore not simply explained as a by-product of the generally slower life history expected for larger brained species. Our findings suggest that both brain expansion and high reliance on culturally transmitted behavior coevolved with sociality and extended lifespan in primates. This coevolution is consistent with the hypothesis that the evolution of large brains, sociality, and long lifespans has promoted reliance on culture, with reliance on culture in turn driving further increases in brain volume, cognitive abilities, and lifespans in some primate lineages. Primate_data_Street_Navarrete_Reader_Laland_2017
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visibility 15visibility views 15 download downloads 4 Powered bymore_vert DRYAD; NARCIS; DANS-... arrow_drop_down DRYAD; NARCIS; DANS-EASYDataset . 2018add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2018Embargo end date: 12 Jun 2018 EnglishDryad CIHR, NSF | Graduate Research Fellows..., NSERC +1 projectsCIHR ,NSF| Graduate Research Fellowship Program (GRFP) ,NSERC ,EC| ApeAttachmentMielke, Alexander; Preis, Anna; Samuni, Liran; Gogarten, Jan F.; Wittig, Roman M.; Crockford, Catherine;Living in permanent social groups forces animals to make decisions about when, how and with whom to interact, requiring decisions to be made that integrate multiple sources of information. Changing social environments can influence this decision-making process by constraining choice or altering the likelihood of a positive outcome. Here, we conceptualised grooming as a choice situation where an individual chooses one of a number of potential partners. Studying two wild populations of sympatric primate species, sooty mangabeys (Cercocebus atys atys) and Western chimpanzees (Pan troglodytes verus), we tested what properties of potential partners influenced grooming decisions, including their relative value based on available alternatives and the social relationships of potential partners with bystanders who could observe the outcome of the decision. Across 1,529 decision events, multiple partner attributes (e.g. dominance ranks, social relationship quality, reproductive state, partner sex) influenced choice. Individuals preferred to initiate grooming with partners of similar global rank, but this effect was driven by a bias towards partners with a high rank compared to other locally available options. Individuals also avoided grooming partners who had strong social relationships with at least one bystander. Results indicated flexible decision-making in grooming interactions in both species, based on a partner’s value given the local social environment. Viewing partner choice as a value-based decision-making process allows researchers to compare how different species solve similar social problems. Data Model1Data for Models 1-1 and 1-2Data Model2Data for Models 2-1 and 2-2Script Model 1 and 2Scripts necessary to analyse Models 1 and 2
DRYAD; NARCIS; DANS-... arrow_drop_down DRYAD; NARCIS; DANS-EASYDataset . 2018add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2020 EnglishZenodo EC | FLATLAND, EC | MaX, NSERC +2 projectsEC| FLATLAND ,EC| MaX ,NSERC ,EC| MaX ,EC| NFFA-EuropeDendzik, Maciej; R. Patrick Xian; Perfetto, Enrico; Sangalli, Davide; Kutnyakhov, Dmytro; Dong, Shuo; Beaulieu, Samuel; Pincelli, Tommaso; Pressacco, Federico; Curcio, Davide; Agustsson, Steinn Ymir; Heber, Michael; Hauer, Jasper; Wurth, Wilfried; Brenner, Günter; Acremann, Yves; Hofmann, Philip; Wolf, Martin; Marini, Andrea; Stefanucci, Gianluca; Rettig, Laurenz; Ernstorfer, Ralph;Pump-probe core-level photoemission spectroscopy data of tungsten diselenide (WSe2) measured using an electron momentum microscope at the FLASH Free-electron laser.
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For further information contact us at helpdesk@openaire.euapps Other research product2019 English NWO | Response of the Iron Biog..., EC | PHOXYNWO| Response of the Iron Biogeochemical Cycle on Continental Shelves to Seawater Deoxygenation ,EC| PHOXYGustafsson, Erik; Hagens, Mathilde; Sun, Xiaole; Reed, Daniel C.; Humborg, Christoph; Slomp, Caroline P.; Gustafsson, Bo G.;Enhanced release of alkalinity from the seafloor, principally driven by anaerobic degradation of organic matter under low-oxygen conditions and associated secondary redox reactions, can increase the carbon dioxide (CO2) buffering capacity of seawater and therefore oceanic CO2 uptake. The Baltic Sea has undergone severe changes in oxygenation state and total alkalinity (TA) over the past decades. The link between these concurrent changes has not yet been investigated in detail. A recent system-wide TA budget constructed for the past 50 years using BALTSEM, a coupled physical–biogeochemical model for the whole Baltic Sea area revealed an unknown TA source. Here we use BALTSEM in combination with observational data and one-dimensional reactive-transport modeling of sedimentary processes in the Fårö Deep, a deep Baltic Sea basin, to test whether sulfate (SO42-) reduction coupled to iron (Fe) sulfide burial can explain the missing TA source in the Baltic Proper. We calculated that this burial can account for up to 26 % of the missing source in this basin, with the remaining TA possibly originating from unknown river inputs or submarine groundwater discharge. We also show that temporal variability in the input of Fe to the sediments since the 1970s drives changes in sulfur (S) burial in the Fårö Deep, suggesting that Fe availability is the ultimate limiting factor for TA generation under anoxic conditions. The implementation of projected climate change and two nutrient load scenarios for the 21st century in BALTSEM shows that reducing nutrient loads will improve deep water oxygen conditions, but at the expense of lower surface water TA concentrations, CO2 buffering capacities and faster acidification. When these changes additionally lead to a decrease in Fe inputs to the sediment of the deep basins, anaerobic TA generation will be reduced even further, thus exacerbating acidification. This work highlights that Fe dynamics plays a key role in the release of TA from sediments where Fe sulfide formation is limited by Fe availability, as exemplified by the Baltic Sea. Moreover, it demonstrates that burial of Fe sulfides should be included in TA budgets of low-oxygen basins.
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For further information contact us at helpdesk@openaire.euapps Other research product2019 English NSF | Collaborative Research: A..., NSERC, NWO | Perturbations of System E... +1 projectsNSF| Collaborative Research: Arctic Temperature Amplification during the Middle Pliocene (ArcAMP): Assessing the Interaction Among Feedback Mechanisms ,NSERC ,NWO| Perturbations of System Earth: Reading the Past to Project the Future - A proposal to create the Netherlands Earth System Science Centre (ESSC) ,EC| PACEMAKERAuthors: Fletcher, Tamara L.; Warden, Lisa; Sinninghe Damsté, Jaap S.; Brown, Kendrick J.; +3 AuthorsFletcher, Tamara L.; Warden, Lisa; Sinninghe Damsté, Jaap S.; Brown, Kendrick J.; Rybczynski, Natalia; Gosse, John C.; Ballantyne, Ashley P.;The mid-Pliocene is a valuable time interval for investigating equilibrium climate at current atmospheric CO2 concentrations because atmospheric CO2 concentrations are thought to have been comparable to the current day and yet the climate and distribution of ecosystems were quite different. One intriguing, but not fully understood, feature of the early to mid-Pliocene climate is the amplified Arctic temperature response and its impact on Arctic ecosystems. Only the most recent models appear to correctly estimate the degree of warming in the Pliocene Arctic and validation of the currently proposed feedbacks is limited by scarce terrestrial records of climate and environment. Here we reconstruct the summer temperature and fire regime from a subfossil fen-peat deposit on west–central Ellesmere Island, Canada, that has been chronologically constrained using cosmogenic nuclide burial dating to 3.9+1.5/-0.5 Ma. The estimate for average mean summer temperature is 15.4±0.8 ∘C using specific bacterial membrane lipids, i.e., branched glycerol dialkyl glycerol tetraethers. This is above the proposed threshold that predicts a substantial increase in wildfire in the modern high latitudes. Macro-charcoal was present in all samples from this Pliocene section with notably higher charcoal concentration in the upper part of the sequence. This change in charcoal was synchronous with a change in vegetation that included an increase in abundance of fire-promoting Pinus and Picea. Paleo-vegetation reconstructions are consistent with warm summer temperatures, relatively low summer precipitation and an incidence of fire comparable to fire-adapted boreal forests of North America and central Siberia. To our knowledge, this site provides the northernmost evidence of fire during the Pliocene. It suggests that ecosystem productivity was greater than in the present day, providing fuel for wildfires, and that the climate was conducive to the ignition of fire during this period. The results reveal that interactions between paleo-vegetation and paleoclimate were mediated by fire in the High Arctic during the Pliocene, even though CO2 concentrations were similar to modern values.
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Research data keyboard_double_arrow_right Dataset 2018Embargo end date: 08 Jun 2018 EnglishDryad NSERC, NWO | Adaptation to environment..., EC | SHENSERC ,NWO| Adaptation to environmental change in blue tits, what do insights from the past tell us about the future? ,EC| SHEDubuc-Messier, Gabrielle; Caro, Samuel P.; Perrier, Charles; Van Oers, Kees; Reale, Denis; Charmantier, Anne;Understanding the causes and consequences of population phenotypic divergence is a central goal in ecology and evolution. Phenotypic divergence among populations can result from genetic divergence, phenotypic plasticity or a combination of the two. However, few studies have deciphered these mechanisms for populations geographically close and connected by gene flow, especially in the case of personality traits. In this study, we used a common garden experiment to explore the genetic basis of the phenotypic divergence observed between two blue tit (Cyanistes caeruleus) populations inhabiting contrasting habitats separated by 25 km, for two personality traits (exploration speed and handling aggression), one physiological trait (heart rate during restraint) and two morphological traits (tarsus length and body mass). Blue tit nestlings were removed from their population and raised in a common garden for up to five years. We then compared adult phenotypes between the two populations, as well as trait-specific Qst and Fst . Our results revealed differences between populations similar to those found in the wild, suggesting a genetic divergence for all traits. Qst - Fst comparisons revealed that the traits divergences likely result from dissimilar selection patterns rather than from genetic drift. Our study is one of the first to report a Qst - Fst comparison for personality traits and adds to the growing body of evidence that population genetic divergence is possible at a small scale for a variety of traits including behavioural traits. Data filesArchive.zip
DRYAD; NARCIS; DANS-... arrow_drop_down DRYAD; NARCIS; DANS-EASYDataset . 2018add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
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visibility 5visibility views 5 download downloads 1 Powered bymore_vert DRYAD; NARCIS; DANS-... arrow_drop_down DRYAD; NARCIS; DANS-EASYDataset . 2018add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2019Embargo end date: 07 May 2019 EnglishDryad UKRI | Deciphering dog domestica..., WT, EC | UNDEAD +7 projectsUKRI| Deciphering dog domestication through a combined ancient DNA and geometric morphometric approach ,WT ,EC| UNDEAD ,EC| TURKEY ,EC| Extinction Genomics ,SSHRC ,WT| Genome diversity and evolution in transmissible cancers in dogs and tasmanian devils ,NSF| Doctoral Dissertation Research: Human Population Inferences Via Canine Genetics ,NIH| Comprehensive Characterization of Canine Genomic Structural Diversity ,WT| Domestic animals as a model to understand the relationship between deleterious mutations, demography and diseaseAuthors: Leathlobhair, Máire Ní; Perri, Angela R.; Irving-Pease, Evan K.; Witt, Kelsey E.; +46 AuthorsLeathlobhair, Máire Ní; Perri, Angela R.; Irving-Pease, Evan K.; Witt, Kelsey E.; Linderholm, Anna; Haile, James; Lebrasseur, Ophelie; Ameen, Carly; Blick, Jeffrey; Boyko, Adam R.; Brace, Selina; Nunes Cortes, Yahaira; Crockford, Susan J.; Devault, Alison; Dimopoulos, Evangelos A.; Eldridge, Morley; Enk, Jacob; Gopalakrishnan, Shyam; Gori, Kevin; Grimes, Vaughan; Guiry, Eric; Hansen, Anders J.; Hulme-Beaman, Ardern; Johnson, John; Kitchen, Andrew; Kasparov, Aleksei K.; Kwon, Young-Mi; Nikolskiy, Pavel A.; Peraza Lope, Carlos; Manin, Aurélie; Martin, Terrance; Meyer, Michael; Noack Myers, Kelsey; Omura, Mark; Rouillard, Jean-Marie; Pavlova, Elena Y.; Sciulli, Paul; Mikkel-Holger, Sinding S.; Strakova, Andrea; Ivanova, Varvara V.; Widga, Christopher; Willerslev, Eske; Pitulko, Vladimir V.; Barnes, Ian; Gilbert, M. Thomas P.; Dobney, Keith M.; Malhi, Ripan S.; Murchison, Elizabeth P.; Larson, Greger; Frantz, Laurent A. F.;Dogs were present in the Americas prior to the arrival of European colonists, but the origin and fate of these pre-contact dogs are largely unknown. We sequenced 71 mitochondrial and seven nuclear genomes from ancient North American and Siberian dogs spanning ~9,000 years. Our analysis indicates that American dogs were not domesticated from North American wolves. Instead, American dogs form a monophyletic lineage that likely originated in Siberia and dispersed into the Americas alongside people. After the arrival of Europeans, native American dogs almost completely disappeared, leaving a minimal genetic legacy in modern dog populations. Remarkably, the closest detectable extant lineage to pre-contact American dogs is the canine transmissible venereal tumor, a contagious cancer clone derived from an individual dog that lived up to 8,000 years ago. Mitochondrial DNA FASTA fileFASTA file containing 1166 dog mtDNA genomes used in this studyfull_mtDNA_alignment.fastaNEXUS treeMaximum likelihood tree (RAxML) of 1166 dogs mtDNA genomes used in this studyfull_mtDNA_alignment.treExcel sheetPublication source of the 1166 mtDNA genomes used in this studyfull_mtDNA_alignment.xlsxPlink (bed) fileContains genotype for dogs 54 dogsfull_data.bedPlink file (bim)Contains genotype for 54 dogsfull_data.bimPlink file (fam)Contains genotype for 54 dogsfull_data.famNJ tree in Figure 2bNJ tree in Figure 2b (see Table S2 for more info)Figure_b.treNexus fileNexus file used for producing Figure S12 (MKV model in MrBayes)Binary_char_MKV.nexNEXUS treeBayesian tree in Figure S12 (see Table S2 for more info)Figure_S12.tre
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visibility 16visibility views 16 download downloads 1 Powered bymore_vert DRYAD; NARCIS; DANS-... arrow_drop_down add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euapps Other research product2018 English NSERC, EC | NORSNSERC ,EC| NORSAdams, C.; Strong, K.; Batchelor, R. L.; Bernath, P. F.; Brohede, S.; Boone, C.; Degenstein, D.; Daffer, W. H.; Drummond, J. R.; Fogal, P. F.; Farahani, E.; Fayt, C.; Fraser, A.; Goutail, F.; Hendrick, F.; Kolonjari, F.; Lindenmaier, R.; Manney, G.; McElroy, C. T.; McLinden, C. A.; Mendonca, J.; Park, J.-H.; Pavlovic, B.; Pazmino, A.; Roth, C.; Savastiouk, V.; Walker, K. A.; Weaver, D.; Zhao, X.;The Optical Spectrograph and Infra-Red Imager System (OSIRIS) and the Atmospheric Chemistry Experiment (ACE) have been taking measurements from space since 2001 and 2003, respectively. This paper presents intercomparisons between ozone and NO2 measured by the ACE and OSIRIS satellite instruments and by ground-based instruments at the Polar Environment Atmospheric Research Laboratory (PEARL), which is located at Eureka, Canada (80° N, 86° W) and is operated by the Canadian Network for the Detection of Atmospheric Change (CANDAC). The ground-based instruments included in this study are four zenith-sky differential optical absorption spectroscopy (DOAS) instruments, one Bruker Fourier transform infrared spectrometer (FTIR) and four Brewer spectrophotometers. Ozone total columns measured by the DOAS instruments were retrieved using new Network for the Detection of Atmospheric Composition Change (NDACC) guidelines and agree to within 3.2%. The DOAS ozone columns agree with the Brewer spectrophotometers with mean relative differences that are smaller than 1.5%. This suggests that for these instruments the new NDACC data guidelines were successful in producing a homogenous and accurate ozone dataset at 80° N. Satellite 14–52 km ozone and 17–40 km NO2 partial columns within 500 km of PEARL were calculated for ACE-FTS Version 2.2 (v2.2) plus updates, ACE-FTS v3.0, ACE-MAESTRO (Measurements of Aerosol Extinction in the Stratosphere and Troposphere Retrieved by Occultation) v1.2 and OSIRIS SaskMART v5.0x ozone and Optimal Estimation v3.0 NO2 data products. The new ACE-FTS v3.0 and the validated ACE-FTS v2.2 partial columns are nearly identical, with mean relative differences of 0.0 ± 0.2% and −0.2 ± 0.1% for v2.2 minus v3.0 ozone and NO2, respectively. Ozone columns were constructed from 14–52 km satellite and 0–14 km ozonesonde partial columns and compared with the ground-based total column measurements. The satellite-plus-sonde measurements agree with the ground-based ozone total columns with mean relative differences of 0.1–7.3%. For NO2, partial columns from 17 km upward were scaled to noon using a photochemical model. Mean relative differences between OSIRIS, ACE-FTS and ground-based NO2 measurements do not exceed 20%. ACE-MAESTRO measures more NO2 than the other instruments, with mean relative differences of 25–52%. Seasonal variation in the differences between NO2 partial columns is observed, suggesting that there are systematic errors in the measurements and/or the photochemical model corrections. For ozone spring-time measurements, additional coincidence criteria based on stratospheric temperature and the location of the polar vortex were found to improve agreement between some of the instruments. For ACE-FTS v2.2 minus Bruker FTIR, the 2007–2009 spring-time mean relative difference improved from −5.0 ± 0.4% to −3.1 ± 0.8% with the dynamical selection criteria. This was the largest improvement, likely because both instruments measure direct sunlight and therefore have well-characterized lines-of-sight compared with scattered sunlight measurements. For NO2, the addition of a ±1° latitude coincidence criterion improved spring-time intercomparison results, likely due to the sharp latitudinal gradient of NO2 during polar sunrise. The differences between satellite and ground-based measurements do not show any obvious trends over the missions, indicating that both the ACE and OSIRIS instruments continue to perform well.
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For further information contact us at helpdesk@openaire.euapps Other research productkeyboard_double_arrow_right Other ORP type 2020 EnglishmedRxiv NIH | The Electronic Medical Re..., NIH | Modifier Genes that Influ..., NIH | Consequences of Self-Negl... +108 projectsNIH| The Electronic Medical Records and Genomics (eMERGE) Network, Phase III ,NIH| Modifier Genes that Influence Age at Onset or Protect Against Development of Alzheimer's Disease (AD) ,NIH| Consequences of Self-Neglect in a Biracial Population of Older People ,NIH| Sequence-based Discovery of AD Risk & Protective Alleles ,NIH| Clinical Core ,NIH| Large Scale Genome Sequencing ,NIH| ROLE FOR FIBROBLAST GROWTH FACTOR IN ALZHEIMERS DISEASE ,NIH| Multi-ethnic genome-wide Alzheimer association study ,NIH| ARIC Neurocognitive Study (ARIC-NCS) ,NIH| ALZHEIMERS DISEASE RESEARCH CENTER ,NIH| A Proteogenomic Approach to Understanding AD GWAS Results ,NIH| CORONARY HEART DISEASE AND STROKE ,NIH| CORONARY HEART DISEASE &STROKE IN PEOPLE AGED 65-84 ,NIH| Role of LRP &its ligand tPA in LTP &aging ,ANR| GENMED ,NIH| Statistical Methods for Next-Gen Sequencing in Disease Association Studies ,NWO| 100-plus ,NWO| 100-plus ,NIH| Building Research Infrastructure &Network in Chicago Chinatown ,CIHR ,NIH| Genetic Studies of Alzheimer's Disease in Caribbean Hispanics ,NIH| UCLA Alzheimers Disease Research Center ,NIH| Genetic Studies of Alzheimer Disease in Koreans ,NIH| Alzheimers Disease in Mild Cognitive Impairment ,NIH| CHS-Transition Phase -268055222 ,NIH| Administrative Core ,NIH| GENETIC DIFFERENCES IN ALZHEIMERS CASES AND CONTROLS ,NIH| CHARGE consortium: gene discovery for CVD and aging phenotypes ,NIH| Alzheimers Disease and Gene Discovery on Chromosome 9 ,NIH| GENETIC EPIDEMIOLOGICAL STUDIES OF ALZHEIMERS DISEASE ,NWO| NCHA Subsidiebesluit 2008-2012 ,NIH| GENES, AGING, LEARNING AND DEMENTIA ,NIH| CORONARY HEART DISEASE &STROKE IN PEOPLE AGED 65-84 ,NIH| Gene discovery in PSP by transcriptome, neuropathology and sequence analysis ,NIH| Genomes and Genetics at the BCM-HGSC ,NIH| Mayo Alzheimers Disease Research Center ,NIH| CORE--CLINICAL ,NIH| Genetic Epidemiology of Alzheimers Disease in African Americans ,NIH| Genetic Epidemiology of Early-Onset Alzheimers disease in Caribbean Hispanics and non-Hispanic Whites ,NIH| Risk Factors, Pathology, and Clinical Expressions of AD ,NIH| ARIC Neurocognitive Study (ARIC-NCS) ,NIH| Genome wide association study of gene expression levels in Alzheimers disease ,NIH| Consortium for Alzheimers Sequence Analysis (CASA) ,NIH| Metabolic Factors in AD ,FWF| Genetics of Cerebral Small Vessel Disease ,NIH| Genomic Convergence in Alzheimer Disease ,NIH| DATA MANAGEMENT AND BIOSTATISTICS ,NIH| Epidemiologic Study of Neural Reserve and Neurobiology of Aging ,NIH| Replication and Extension of ADSP Discoveries in African-Americans ,NIH| AMYLOID DEPOSTION, VASCULAR DISEASE AND CLINICAL PROGRESSION OF AD ,NIH| CORONARY HEART DISEASE AND STROKE ,NIH| ALZHEIMERS DISEASE AND ANIMAL MODELS ,FWF| MRI white matter abnormalities in the elderly: Genetic risk factors, rate of progression and neuropsychologic consequences ,NIH| Large Scale Sequencing and Analysis of Genomes ,NIH| THE FRAMINGHAM HEART STUDY-268025195 ,NIH| Stanford Alzheimer's Disease Research Center ,NIH| Next Generation gene discovery in neurogenetics ,NIH| CENTRAL BLOOD ANALYSIS LABORATORY FOR CHS ,NIH| Alzheimers Disease Center Core ,NIH| Genetic Studies of Dementia in the Amish ,NIH| A system approach to targeting innate immunity in AD ,NIH| RISK FACTORS FOR INCIDENT AD IN A BIRACIAL COMMUNITY ,NIH| Collaborative GWAS of Dementia, AD and related MRI and Cognitive Endophenotypes ,NIH| Boston University Alzheimer's Disease Center ,NIH| CHS research resources for the cardiovascular health of older adults ,NIH| Exceptional aging: 12 year trajectories to function ,NIH| Coordinating Center for Genetics and Genomics of Alzheimer's Disease (CGAD) ,NIH| CORE--CLINICAL ,NIH| QUANTITATIVE INDICES OF NEURON VULNERABILITY IN DEMENTIA ,NIH| THE NIA GENETICS OF ALZHEIMER'S DISEASE DATA STORAGE SITE ,NIH| ALZHEIMERS DISEASE DATA COORDINATING CENTER ,NIH| SHORT-TERM STABILITY OF CLINICAL TESTS ,NIH| CORE-- EDUCATION AND INFORMATION TRANSFER ,NIH| CHS Events Follow-up Study ,NIH| ARIC Neurocognitive Study (ARIC-NCS) ,NWO| Dissecting genetic complexity of Alzheimer's disease and cognitive function ,WT| BRAINEACv2: a resource for the interpretation of genetic variation in multiple regions of the adult human brain ,NIH| CORE--CLINICAL ,NIH| CHARGE: Identifying Risk & Protective SNV for AD in ADSP Case-control Sample ,NIH| The ARIC and Neurocognitive Longitudinal Study ,NIH| MRI, Cognitive, Genetic and Biomarker Precursors of AD & Dementia in Young Adults ,NIH| Building on GWAS for NHLBI-disease: the CHARGE consortium ,NIH| Integrative translational discovery of vascular risk factors in aging and dementia ,NIH| The National Institute on Aging (NIA) Late Onset of Alzheimer's Disease (LOAD) Family-Based Study (FBS) ,NIH| EDUCATION AND INFORMATION CORE ,EC| ENGAGE ,NIH| ADSP Follow-up in Multi-Ethnic Cohorts via Endophenotypes, Omics & Model Systems ,NIH| Temporal Trends, Novel Imaging and Molecular Characterization of Preclinical and Clinical Alzheimer's Disease in the Framingham Cohorts ,NIH| COGNITIVE TESTS, APOE, BRAIN MRI AND RISKS OF DEMENTIA ,NIH| Clinical Core ,NIH| Epidemiology of Familial Late-Onset Alzheimer's Disease ,NIH| Pleiotropy GWAS of Alzheimer's Disease ,NIH| Whole Genome Sequencing in Ethnically Diverse Cohorts for the ADSP Follow-Up Study (FUS) ,FWF| Mechanisms of Small Vessel Related Brain Damage and Cognitive Impairment ,NIH| INDIANAPOLIS/IBADAN DEMENTIA PROJECT ,NIH| Admin Supplement for University of Florida -Mt. Sinai Medical Center AD Research Center ,NIH| Clinical Core ,NIH| Sequence-based Discovery of AD Risk & Protective Alleles ,NIH| Alzheimer Disease Genetic Architecture in African Americans ,NIH| UC Davis Alzheimer's Core Center ,NIH| Identification and characterization of AD risk networks using multi-dimensional 'omics' data ,NIH| Alzheimer's Disease Genetics Consortium ,NIH| CORE--NEUROPATHOLOGY CORE ,NIH| GENETIC LINKAGE STUDIES IN NEUROGENETIC DISORDERS ,NIH| An Integrated Genomic Approach to Alzheimer Disease ,NIH| PRECURSORS OF STROKE INCIDENCE AND PROGNOSIS ,NIH| Genomic and Biological Studies of APOE ?2 in Alzheimer Disease ,NIH| National Cell Repository for Alzheimer's Disease (NCRAD) ,NIH| ALZHEIMERS DISEASE RESEARCH CENTER ,NIH| Genetic Epidemiology and Multi-Omics Analyses in Familial and Sporadic Alzheimer's Disease Among Secular Caribbean Hispanics and Religious Order ,NIH| Education and Information Transfer CoreHolstege, Henne; Grozeva, Detelina; Sims, Rebecca; Luckcuck, Lauren; Denning, Nicola; Marshall, Rachel; Saad, Salha; Williams, Julie; Meggy, Alun; Lambert, Jean-Charles; Hulsman, M.; Charbonnier, C.; Grenier-Boley, B.; Quenez, O.; van Rooij, J.; Ahmad, S.; Amin, N.; Norsworthy, P.; Dols, O.; Hummerich, H.; Kawalia, A.; Amouyel, P.; Beecham, G.; Berr, C.; Bis, J.; Boland, A.; Bossu, P.; Bouwman, F.; Campion, D.; Daniele, A.; Dartigues, J. F.; Debette, S.; Deleuze, J. F.; Destefano, A.; Farrer, L.; Fox, N.; Glimberti, D.; Genin, E.; Haines, J.; Holmes, C.; Arfan Ikram, M.; Ikram, M.; Jansen, I.; Kraaij, R.; Lathrop, M.; Lemstra, A.; Lleo, A.; Luckcuck, L.; Marschall, R.; Martin, E.; Masullo, C.; Mayeux, R.; Mecocci, P.; Mol, M.; Morgan, K.; Nacmia, B.; Naj, A.; Pastor, P.; Pericak-Vance, M.; Redon, R; Richard, A. C.; Riedel-Heller, S.; Rivadeneira, F.; Rousseau, S.; Ryan, N.; Sanchez-Juan, P.; Schellenberg, G.; Scheltens, P.; Scott, J.; Seripa, D.; Spalletta, G.; Tijms, B.; Uitterlinden, A.; van der Lee, S.; Wagner, M.; Wallon, D.; Wang, L. S.; Zarea, A.; Reinders, M.; Clarimon, J.; van Swieten, J.; Hardy, J.; Ramirez, A.; Mead, S. H.; van der Flier, W.; van Duijn, C.; Nicolas, G.; Bellenguez, C.; Lambert, J. C.;The genetic component of Alzheimer’s disease (AD) has been mainly assessed using Genome Wide Association Studies (GWAS), which do not capture the risk contributed by rare variants. Here, we compared the gene-based burden of rare damaging variants in exome sequencing data from 32,558 individuals —16,036 AD cases and 16,522 controls— in a two-stage analysis. Next to known genes TREM2, SORL1 and ABCA7, we observed a significant association of rare, predicted damaging variants in ATP8B4 and ABCA1 with AD risk, and a suggestive signal in ADAM10. Next to these genes, the rare variant burden in RIN3, CLU, ZCWPW1 and ACE highlighted these genes as potential driver genes in AD-GWAS loci. Rare damaging variants in these genes, and in particular loss-of-function variants, have a large effect on AD-risk, and they are enriched in early onset AD cases. The newly identified AD-associated genes provide additional evidence for a major role for APP-processing, Aβ-aggregation, lipid metabolism and microglial function in AD.
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For further information contact us at helpdesk@openaire.euapps Other research product2018 English EC | HELIXEC| HELIXAuthors: Grillakis, Manolis G.; Koutroulis, Aristeidis G.; Daliakopoulos, Ioannis N.; Tsanis, Ioannis K.;Grillakis, Manolis G.; Koutroulis, Aristeidis G.; Daliakopoulos, Ioannis N.; Tsanis, Ioannis K.;Bias correction of climate variables is a standard practice in climate change impact (CCI) studies. Various methodologies have been developed within the framework of quantile mapping. However, it is well known that quantile mapping may significantly modify the long-term statistics due to the time dependency of the temperature bias. Here, a method to overcome this issue without compromising the day-to-day correction statistics is presented. The methodology separates the modeled temperature signal into a normalized and a residual component relative to the modeled reference period climatology, in order to adjust the biases only for the former and preserve the signal of the later. The results show that this method allows for the preservation of the originally modeled long-term signal in the mean, the standard deviation and higher and lower percentiles of temperature. To illustrate the improvements, the methodology is tested on daily time series obtained from five Euro CORDEX regional climate models (RCMs).