The 1000 Genomes Project set out to provide a comprehensive description of common human genetic variation by applying whole-genome sequencing to a diverse set of individuals from multiple populations. Here we report completion of the project, having reconstructed the genomes of 2,504 individuals from 26 populations using a combination of low-coverage whole-genome sequencing, deep exome sequencing, and dense microarray genotyping. We characterized a broad spectrum of genetic variation, in total over 88 million variants (84.7 million single nucleotide polymorphisms (SNPs), 3.6 million short insertions/deletions (indels), and 60,000 structural variants), all phased onto high-quality haplotypes. This resource includes >99% of SNP variants with a frequency of >1% for a variety of ancestries. We describe the distribution of genetic variation across the global sample, and discuss the implications for common disease studies.
Summary Genomic structural variants (SVs) are abundant in humans, differing from other variation classes in extent, origin, and functional impact. Despite progress in SV characterization, the nucleotide resolution architecture of most SVs remains unknown. We constructed a map of unbalanced SVs (i.e., copy number variants) based on whole genome DNA sequencing data from 185 human genomes, integrating evidence from complementary SV discovery approaches with extensive experimental validations. Our map encompassed 22,025 deletions and 6,000 additional SVs, including insertions and tandem duplications. Most SVs (53%) were mapped to nucleotide resolution, which facilitated analyzing their origin and functional impact. We examined numerous whole and partial gene deletions with a genotyping approach and observed a depletion of gene disruptions amongst high frequency deletions. Furthermore, we observed differences in the size spectra of SVs originating from distinct formation mechanisms, and constructed a map constructed a map of SV hotspots formed by common mechanisms. Our analytical framework and SV map serves as a resource for sequencing-based association studies.
Amyloid-beta peptide (Abeta) interacts with the vasculature to influence Abeta levels in the brain and cerebral blood flow, providing a means of amplifying the Abeta-induced cellular stress underlying neuronal dysfunction and dementia. Systemic Abeta infusion and studies in genetically manipulated mice show that Abeta interaction with receptor for advanced glycation end products (RAGE)-bearing cells in the vessel wall results in transport of Abeta across the blood-brain barrier (BBB) and expression of proinflammatory cytokines and endothelin-1 (ET-1), the latter mediating Abeta-induced vasoconstriction. Inhibition of RAGE-ligand interaction suppresses accumulation of Abeta in brain parenchyma in a mouse transgenic model. These findings suggest that vascular RAGE is a target for inhibiting pathogenic consequences of Abeta-vascular interactions, including development of cerebral amyloidosis.
Intelligence is highly heritable and a major determinant of human health and well-being. Recent genome-wide meta-analyses have identified 24 genomic loci linked to variation in intelligence, but much about its genetic underpinnings remains to be discovered. Here, we present a large-scale genetic association study of intelligence (n = 269,867), identifying 205 associated genomic loci (190 new) and 1,016 genes (939 new) via positional mapping, expression quantitative trait locus (eQTL) mapping, chromatin interaction mapping, and gene-based association analysis. We find enrichment of genetic effects in conserved and coding regions and associations with 146 nonsynonymous exonic variants. Associated genes are strongly expressed in the brain, specifically in striatal medium spiny neurons and hippocampal pyramidal neurons. Gene set analyses implicate pathways related to nervous system development and synaptic structure. We confirm previous strong genetic correlations with multiple health-related outcomes, and Mendelian randomization analysis results suggest protective effects of intelligence for Alzheimer's disease and ADHD and bidirectional causation with pleiotropic effects for schizophrenia. These results are a major step forward in understanding the neurobiology of cognitive function as well as genetically related neurological and psychiatric disorders.
With the advent of atomically thin and flat layers of conducting materials such as graphene, new designs for thin film energy storage devices with good performance have become possible. Here, we report an "in-plane" fabrication approach for ultrathin supercapacitors based on electrodes comprised of pristine graphene and multilayer reduced graphene oxide. The in-plane design is straightforward to implement and exploits efficiently the surface of each graphene layer for energy storage. The open architecture and the effect of graphene edges enable even the thinnest of devices, made from as grown 1-2 graphene layers, to reach specific capacities up to 80 μFcm(-2), while much higher (394 μFcm(-2)) specific capacities are observed multilayer reduced graphene oxide electrodes. The performances of devices with pristine as well as thicker graphene-based structures are examined using a combination of experiments and model calculations. The demonstrated all solid-state supercapacitors provide a prototype for a broad range of thin-film based energy storage devices.
International audienceEl Niño–Southern Oscillation (ENSO) is a naturally occurring mode of tropical Pacific variability, with global impacts on society and natural ecosystems. While it has long been known that El Niño events display a diverse range of amplitudes, triggers, spatial patterns, and life cycles, the realization that ENSO’s impacts can be highly sensitive to this event-to-event diversity is driving a renewed interest in the subject. This paper surveys our current state of knowledge of ENSO diversity, identifies key gaps in understanding, and outlines some promising future research directions
Water evaporation is a ubiquitous natural process that harvests thermal energy from the ambient environment. It has previously been utilized in a number of applications including the synthesis of nanostructures and the creation of energy-harvesting devices. Here, we show that water evaporation from the surface of a variety of nanostructured carbon materials can be used to generate electricity. We find that evaporation from centimetre-sized carbon black sheets can reliably generate sustained voltages of up to 1 V under ambient conditions. The interaction between the water molecules and the carbon layers and moreover evaporation-induced water flow within the porous carbon sheets are thought to be key to the voltage generation. This approach to electricity generation is related to the traditional streaming potential, which relies on driving ionic solutions through narrow gaps, and the recently reported method of moving ionic solutions across graphene surfaces, but as it exploits the natural process of evaporation and uses cheap carbon black it could offer advantages in the development of practical devices.
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