Bilkent University

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. Results for the final phase of the 1000 Genomes Project are presented including whole-genome sequencing, targeted exome sequencing, and genotyping on high-density SNP arrays for 2,504 individuals across 26 populations, providing a global reference data set to support biomedical genetics. The 1000 Genomes Project has sought to comprehensively catalogue human genetic variation across populations, providing a valuable public genomic resource. The data obtained so far have found applications ranging from association studies and fine mapping studies to the filtering of likely neutral variants in rare-disease cohorts. The authors now report on the final phase of the project, phase 3, which covers previously uncharacterized areas of human genetic diversity in terms of the populations sampled and categories of characterized variation. The sample now includes more than 2,500 individuals from 26 global populations, with low coverage whole-genome and deep exome sequencing, as well as dense microarray genotyping. They find that while most common variants are shared across populations, rarer variants are often restricted to closely related populations. The authors also demonstrate the use of the phase 3 dataset as a reference panel for imputation to improve the resolution in genetic association studies.

The cBio Cancer Genomics Portal (http://cbioportal.org) is an open-access resource for interactive exploration of multidimensional cancer genomics data sets, currently providing access to data from more than 5,000 tumor samples from 20 cancer studies. The cBio Cancer Genomics Portal significantly lowers the barriers between complex genomic data and cancer researchers who want rapid, intuitive, and high-quality access to molecular profiles and clinical attributes from large-scale cancer genomics projects and empowers researchers to translate these rich data sets into biologic insights and clinical applications.

The cBioPortal for Cancer Genomics (http://cbioportal.org) provides a Web resource for exploring, visualizing, and analyzing multidimensional cancer genomics data. The portal reduces molecular profiling data from cancer tissues and cell lines into readily understandable genetic, epigenetic, gene expression, and proteomic events. The query interface combined with customized data storage enables researchers to interactively explore genetic alterations across samples, genes, and pathways and, when available in the underlying data, to link these to clinical outcomes. The portal provides graphical summaries of gene-level data from multiple platforms, network visualization and analysis, survival analysis, patient-centric queries, and software programmatic access. The intuitive Web interface of the portal makes complex cancer genomics profiles accessible to researchers and clinicians without requiring bioinformatics expertise, thus facilitating biological discoveries. Here, we provide a practical guide to the analysis and visualization features of the cBioPortal for Cancer Genomics.

By characterizing the geographic and functional spectrum of human genetic variation, the 1000 Genomes Project aims to build a resource to help to understand the genetic contribution to disease. Here we describe the genomes of 1,092 individuals from 14 populations, constructed using a combination of low-coverage whole-genome and exome sequencing. By developing methods to integrate information across several algorithms and diverse data sources, we provide a validated haplotype map of 38 million single nucleotide polymorphisms, 1.4 million short insertions and deletions, and more than 14,000 larger deletions. We show that individuals from different populations carry different profiles of rare and common variants, and that low-frequency variants show substantial geographic differentiation, which is further increased by the action of purifying selection. We show that evolutionary conservation and coding consequence are key determinants of the strength of purifying selection, that rare-variant load varies substantially across biological pathways, and that each individual contains hundreds of rare non-coding variants at conserved sites, such as motif-disrupting changes in transcription-factor-binding sites. This resource, which captures up to 98% of accessible single nucleotide polymorphisms at a frequency of 1% in related populations, enables analysis of common and low-frequency variants in individuals from diverse, including admixed, populations. This report from the 1000 Genomes Project describes the genomes of 1,092 individuals from 14 human populations, providing a resource for common and low-frequency variant analysis in individuals from diverse populations; hundreds of rare non-coding variants at conserved sites, such as motif-disrupting changes in transcription-factor-binding sites, can be found in each individual. This report by the 1000 Genomes Project describes the genomes of 1,092 individuals from 14 human populations, providing a resource for common and low-frequency variant analysis in individuals from diverse populations. Integrative analyses reveal profiles of rare and common variants in different populations. The frequencies of rare variants vary across biological pathways, and hundreds of rare, non-coding variants at conserved sites — such as changes disrupting transcription-factor motifs — can be established for each individual.

In the past decade, extracellular vesicles (EVs) have been recognized as potent vehicles of intercellular communication, both in prokaryotes and eukaryotes. This is due to their capacity to transfer proteins, lipids and nucleic acids, thereby influencing various physiological and pathological functions of both recipient and parent cells. While intensive investigation has targeted the role of EVs in different pathological processes, for example, in cancer and autoimmune diseases, the EV‐mediated maintenance of homeostasis and the regulation of physiological functions have remained less explored. Here, we provide a comprehensive overview of the current understanding of the physiological roles of EVs, which has been written by crowd‐sourcing, drawing on the unique EV expertise of academia‐based scientists, clinicians and industry based in 27 European countries, the United States and Australia. This review is intended to be of relevance to both researchers already working on EV biology and to newcomers who will encounter this universal cell biological system. Therefore, here we address the molecular contents and functions of EVs in various tissues and body fluids from cell systems to organs. We also review the physiological mechanisms of EVs in bacteria, lower eukaryotes and plants to highlight the functional uniformity of this emerging communication system.

Electronic circuits provide us with the ability to control the transport and storage of electrons. However, the performance of electronic circuits is now becoming rather limited when digital information needs to be sent from one point to another. Photonics offers an effective solution to this problem by implementing optical communication systems based on optical fibers and photonic circuits. Unfortunately, the micrometer-scale bulky components of photonics have limited the integration of these components into electronic chips, which are now measured in nanometers. Surface plasmon-based circuits, which merge electronics and photonics at the nanoscale, may offer a solution to this size-compatibility problem. Here we review the current status and future prospects of plasmonics in various applications including plasmonic chips, light generation, and nanolithography.

<para xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> A method is proposed, called channel polarization, to construct code sequences that achieve the symmetric capacity <emphasis emphasistype="italic"><formula formulatype="inline"><tex Notation="TeX">$I(W)$</tex></formula></emphasis> of any given binary-input discrete memoryless channel (B-DMC) <emphasis emphasistype="italic"><formula formulatype="inline"><tex Notation="TeX">$W$</tex></formula></emphasis>. The symmetric capacity is the highest rate achievable subject to using the input letters of the channel with equal probability. Channel polarization refers to the fact that it is possible to synthesize, out of <emphasis emphasistype="italic"><formula formulatype="inline"><tex Notation="TeX">$N$</tex></formula></emphasis> independent copies of a given B-DMC <emphasis emphasistype="italic"><formula formulatype="inline"> <tex Notation="TeX">$W$</tex></formula></emphasis>, a second set of <emphasis emphasistype="italic"><formula formulatype="inline"><tex Notation="TeX">$N$</tex> </formula></emphasis> binary-input channels <emphasis emphasistype="italic"><formula formulatype="inline"><tex Notation="TeX">$\{W_N^{(i)}:1\le i\le N\}$</tex> </formula></emphasis> such that, as <emphasis emphasistype="italic"><formula formulatype="inline"><tex Notation="TeX">$N$</tex></formula></emphasis> becomes large, the fraction of indices <emphasis emphasistype="italic"><formula formulatype="inline"> <tex Notation="TeX">$i$</tex></formula></emphasis> for which <emphasis emphasistype="italic"><formula formulatype="inline"><tex Notation="TeX">$I(W_N^{(i)})$</tex></formula></emphasis> is near <emphasis emphasistype="italic"><formula formulatype="inline"><tex Notation="TeX">$1$</tex> </formula></emphasis> approaches <emphasis emphasistype="italic"><formula formulatype="inline"><tex Notation="TeX">$I(W)$</tex></formula></emphasis> and the fraction for which <emphasis emphasistype="italic"><formula formulatype="inline"> <tex Notation="TeX">$I(W_N^{(i)})$</tex></formula></emphasis> is near <emphasis emphasistype="italic"><formula formulatype="inline"><tex Notation="TeX">$0$</tex> </formula></emphasis> approaches <emphasis emphasistype="italic"><formula formulatype="inline"><tex Notation="TeX">$1-I(W)$</tex></formula></emphasis>. The polarized channels <emphasis emphasistype="italic"><formula formulatype="inline"> <tex Notation="TeX">$\{W_N^{(i)}\}$</tex></formula></emphasis> are well-conditioned for channel coding: one need only send data at rate <emphasis emphasistype="italic"><formula formulatype="inline"><tex Notation="TeX">$1$</tex></formula></emphasis> through those with capacity near <emphasis emphasistype="italic"><formula formulatype="inline"> <tex Notation="TeX">$1$</tex></formula></emphasis> and at rate <emphasis emphasistype="italic"><formula formulatype="inline"><tex Notation="TeX">$0$</tex></formula></emphasis> through the remaining. Codes constructed on the basis of this idea are called polar codes. The paper proves that, given any B-DMC <emphasis emphasistype="italic"><formula formulatype="inline"><tex Notation="TeX">$W$</tex></formula></emphasis> with <emphasis emphasistype="italic"><formula formulatype="inline"><tex Notation="TeX">$I(W)&gt; 0$</tex></formula></emphasis> and any target rate <emphasis emphasistype="italic"><formula formulatype="inline"><tex Notation="TeX">$R ≪ I(W)$</tex></formula></emphasis>, there exists a sequence of polar codes <emphasis emphasistype="italic"><formula formulatype="inline"><tex Notation="TeX">$\{{\Fraktur {C}}_n;n\ge 1\}$</tex> </formula></emphasis> such that <emphasis emphasistype="italic"><formula formulatype="inline"> <tex Notation="TeX">${\Fraktur {C}}_n$</tex></formula></emphasis> has block-length <emphasis emphasistype="italic"><formula formulatype="inline"><tex Notation="TeX">$N=2^n$</tex> </formula></emphasis>, rate <emphasis emphasistype="italic"><formula formulatype="inline"> <tex Notation="TeX">$\ge R$</tex></formula></emphasis>, and probability of block error under successive cancellation decoding bounded as <emphasis emphasistype="italic"><formula formulatype="inline"><tex Notation="TeX">$P_{e}(N,R) \le O(N^{-{1\over 4}})$</tex> </formula></emphasis> independently of the code rate. This performance is achievable by encoders and decoders with complexity <emphasis emphasistype="italic"><formula formulatype="inline"><tex Notation="TeX">$O(N\log N)$</tex></formula></emphasis> for each. </para>

First-principles calculations of structure optimization, phonon modes, and finite temperature molecular dynamics predict that silicon and germanium can have stable, two-dimensional, low-buckled, honeycomb structures. Similar to graphene, these puckered structures are ambipolar and their charge carriers can behave like a massless Dirac fermion due to their pi and pi(*) bands which are crossed linearly at the Fermi level. In addition to these fundamental properties, bare and hydrogen passivated nanoribbons of Si and Ge show remarkable electronic and magnetic properties, which are size and orientation dependent. These properties offer interesting alternatives for the engineering of diverse nanodevices.

Structural variants are implicated in numerous diseases and make up the majority of varying nucleotides among human genomes. Here we describe an integrated set of eight structural variant classes comprising both balanced and unbalanced variants, which we constructed using short-read DNA sequencing data and statistically phased onto haplotype blocks in 26 human populations. Analysing this set, we identify numerous gene-intersecting structural variants exhibiting population stratification and describe naturally occurring homozygous gene knockouts that suggest the dispensability of a variety of human genes. We demonstrate that structural variants are enriched on haplotypes identified by genome-wide association studies and exhibit enrichment for expression quantitative trait loci. Additionally, we uncover appreciable levels of structural variant complexity at different scales, including genic loci subject to clusters of repeated rearrangement and complex structural variants with multiple breakpoints likely to have formed through individual mutational events. Our catalogue will enhance future studies into structural variant demography, functional impact and disease association. The Structural Variation Analysis Group of The 1000 Genomes Project reports an integrated structural variation map based on discovery and genotyping of eight major structural variation classes in 2,504 unrelated individuals from across 26 populations; structural variation is compared within and between populations and its functional impact is quantified. The Structural Variation Analysis Group of The 1000 Genomes Project reports an integrated structural variation map based on discovery and genotyping of eight major structural variation classes in genomes for 2,504 unrelated individuals from across 26 populations. They characterize structural variation within and between populations and quantify its functional effect. The authors further create a phased reference panel that will be valuable for population genetic and disease association studies.

We present the largest exome sequencing study of autism spectrum disorder (ASD) to date (n = 35,584 total samples, 11,986 with ASD). Using an enhanced analytical framework to integrate de novo and case-control rare variation, we identify 102 risk genes at a false discovery rate of 0.1 or less. Of these genes, 49 show higher frequencies of disruptive de novo variants in individuals ascertained to have severe neurodevelopmental delay, whereas 53 show higher frequencies in individuals ascertained to have ASD; comparing ASD cases with mutations in these groups reveals phenotypic differences. Expressed early in brain development, most risk genes have roles in regulation of gene expression or neuronal communication (i.e., mutations effect neurodevelopmental and neurophysiological changes), and 13 fall within loci recurrently hit by copy number variants. In cells from the human cortex, expression of risk genes is enriched in excitatory and inhibitory neuronal lineages, consistent with multiple paths to an excitatory-inhibitory imbalance underlying ASD.

The genetics underlying severe COVID-19 The immune system is complex and involves many genes, including those that encode cytokines known as interferons (IFNs). Individuals that lack specific IFNs can be more susceptible to infectious diseases. Furthermore, the autoantibody system dampens IFN response to prevent damage from pathogen-induced inflammation. Two studies now examine the likelihood that genetics affects the risk of severe coronavirus disease 2019 (COVID-19) through components of this system (see the Perspective by Beck and Aksentijevich). Q. Zhang et al. used a candidate gene approach and identified patients with severe COVID-19 who have mutations in genes involved in the regulation of type I and III IFN immunity. They found enrichment of these genes in patients and conclude that genetics may determine the clinical course of the infection. Bastard et al. identified individuals with high titers of neutralizing autoantibodies against type I IFN-α2 and IFN-ω in about 10% of patients with severe COVID-19 pneumonia. These autoantibodies were not found either in infected people who were asymptomatic or had milder phenotype or in healthy individuals. Together, these studies identify a means by which individuals at highest risk of life-threatening COVID-19 can be identified. Science , this issue p. eabd4570 , p. eabd4585 ; see also p. 404

Using first-principles plane-wave calculations, we investigate two-dimensional (2D) honeycomb structure of group-IV elements and their binary compounds as well as the compounds of group III-V elements. Based on structure optimization and phonon-mode calculations, we determine that 22 different honeycomb materials are stable and correspond to local minima on the Born-Oppenheimer surface. We also find that all the binary compounds containing one of the first row elements, B, C, or N have planar stable structures. On the other hand, in the honeycomb structures of Si, Ge, and other binary compounds the alternating atoms of hexagons are buckled since the stability is maintained by puckering. For those honeycomb materials which were found stable, we calculated optimized structures, cohesive energies, phonon modes, electronic-band structures, effective cation and anion charges, and some elastic constants. The band gaps calculated within density functional theory using local density approximation are corrected by $G{W}_{0}$ method. Si and Ge in honeycomb structure are semimetal and have linear band crossing at the Fermi level which attributes massless Fermion character to charge carriers as in graphene. However, all binary compounds are found to be semiconductor with band gaps depending on the constituent atoms. We present a method to reveal elastic constants of 2D honeycomb structures from the strain energy and calculate the Poisson's ratio as well as in-plane stiffness values. Preliminary results show that the nearly lattice matched heterostructures of these compounds can offer alternatives for nanoscale electronic devices. Similar to those of the three-dimensional group-IV and group III-V compound semiconductors, one deduces interesting correlations among the calculated properties of present honeycomb structures.

We present a DNA library preparation method that has allowed us to reconstruct a high-coverage (30×) genome sequence of a Denisovan, an extinct relative of Neandertals. The quality of this genome allows a direct estimation of Denisovan heterozygosity indicating that genetic diversity in these archaic hominins was extremely low. It also allows tentative dating of the specimen on the basis of "missing evolution" in its genome, detailed measurements of Denisovan and Neandertal admixture into present-day human populations, and the generation of a near-complete catalog of genetic changes that swept to high frequency in modern humans since their divergence from Denisovans.

Fluorescent chemosensors for ions and neutral analytes have been widely applied in many diverse fields such as biology, physiology, pharmacology, and environmental sciences. The field of fluorescent chemosensors has been in existence for about 150 years. In this time, a large range of fluorescent chemosensors have been established for the detection of biologically and/or environmentally important species. Despite the progress made in this field, several problems and challenges still exist. This tutorial review introduces the history and provides a general overview of the development in the research of fluorescent sensors, often referred to as chemosensors. This will be achieved by highlighting some pioneering and representative works from about 40 groups in the world that have made substantial contributions to this field. The basic principles involved in the design of chemosensors for specific analytes, problems and challenges in the field as well as possible future research directions are covered. The application of chemosensors in various established and emerging biotechnologies, is very bright.

Metal-halide perovskites have rapidly emerged as one of the most promising materials of the 21st century, with many exciting properties and great potential for a broad range of applications, from photovoltaics to optoelectronics and photocatalysis. The ease with which metal-halide perovskites can be synthesized in the form of brightly luminescent colloidal nanocrystals, as well as their tunable and intriguing optical and electronic properties, has attracted researchers from different disciplines of science and technology. In the last few years, there has been a significant progress in the shape-controlled synthesis of perovskite nanocrystals and understanding of their properties and applications. In this comprehensive review, researchers having expertise in different fields (chemistry, physics, and device engineering) of metal-halide perovskite nanocrystals have joined together to provide a state of the art overview and future prospects of metal-halide perovskite nanocrystal research.

Recent studies have revealed that single-layer transition-metal oxides and dichalcogenides (MX 2) might offer properties superior to those of graphene. So far, only very few MX 2 compounds have been synthesized as suspended single layers, and some of them have been exfoliated as thin sheets. Using first-principles structure optimization and phonon calculations based on density functional theory, we predict that, out of 88 different combinations of MX 2 compounds, several of them can be stable in free-standing, single-layer honeycomb-like structures. These materials have two-dimensional hexagonal lattices and have top-view appearances as if they consisted of either honeycombs or centered honeycombs. However, their bonding is different from that of graphene; they can be viewed as a positively charged plane of transition-metal atoms sandwiched between two planes of negatively charged oxygen or chalcogen atoms. Electron correlation in transition-metal oxides was treated by including Coulomb repulsion through LDA + U calculations. Our analysis of stability was extended to include in-plane stiffness, as well as ab initio, finite-temperature molecular dynamics calculations. Some of these single-layer structures are direct- or indirect-band-gap semiconductors, only one compound is half-metal, and the rest are either ferromagnetic or nonmagnetic metals. Because of their surface polarity, band gap, high in-plane stiffness, and suitability for functionalization by adatoms or vacancies, these single-layer structures can be utilized in a wide range of technological applications, especially as nanoscale coatings for surfaces contributing crucial functionalities. In particular, the manifold WX 2 heralds exceptional properties promising future nanoscale applications. © 2012 American Chemical Society.

An algorithm for efficient and accurate computation of the fractional Fourier transform is given. For signals with time-bandwidth product N, the presented algorithm computes the fractional transform in O(NlogN) time. A definition for the discrete fractional Fourier transform that emerges from our analysis is also discussed.

The Sensitivity of Long-Term Interest Rates to Economic News: Evidence and Implications for Macroeconomic Models by Refet S. Gürkaynak, Brian Sack and Eric Swanson. Published in volume 95, issue 1, pages 425-436 of American Economic Review, March 2005

We investigate the effects of U.S. monetary policy on asset prices using a high-frequency event-study analysis. We test whether these effects are adequately captured by a single factor--changes in the federal funds rate target-and find that they are not. Instead, we find that two factors are required. These factors have a structural interpretation as a "current federal funds rate target" factor and a "future path of policy" factor, with the latter closely associated with FOMC statements. We measure the effects of these two factors on bond yields and stock prices using a new intraday dataset going back to 1990. According to our estimates, both monetary policy actions and statements have important but differing effects on asset prices, with statements having a much greater impact on longer-term Treasury yields.

We report a first-principles study, which demonstrates that a single Ti atom coated on a single-walled nanotube (SWNT) binds up to four hydrogen molecules. The first H2 adsorption is dissociative with no energy barrier while the other three adsorptions are molecular with significantly elongated H-H bonds. At high Ti coverage we show that a SWNT can strongly adsorb up to 8 wt % hydrogen. These results advance our fundamental understanding of dissociative adsorption of hydrogen in nanostructures and suggest new routes to better storage and catalyst materials.