We introduce multi-trait analysis of GWAS (MTAG), a method for joint analysis of summary statistics from genome-wide association studies (GWAS) of different traits, possibly from overlapping samples. ...We apply MTAG to summary statistics for depressive symptoms (N
= 354,862), neuroticism (N = 168,105), and subjective well-being (N = 388,538). As compared to the 32, 9, and 13 genome-wide significant loci identified in the single-trait GWAS (most of which are themselves novel), MTAG increases the number of associated loci to 64, 37, and 49, respectively. Moreover, association statistics from MTAG yield more informative bioinformatics analyses and increase the variance explained by polygenic scores by approximately 25%, matching theoretical expectations.
The collection of Earth system models available in the archive of phase 5 of CMIP (CMIP5) represents, at least to some degree, a sample of uncertainty of future climate evolution. The presence of ...duplicated code as well as shared forcing and validation data in the multiple models in the archive raises at least three potential problems: biases in the mean and variance, the overestimation of sample size, and the potential for spurious correlations to emerge in the archive because of model replication. Analytical evidence is presented to demonstrate that the distribution of models in the CMIP5 archive is not consistent with a random sample, and a weighting scheme is proposed to reduce some aspects of model codependency in the ensemble. A method is proposed for selecting diverse and skillful subsets of models in the archive, which could be used for impact studies in cases where physically consistent joint projections of multiple variables (and their temporal and spatial characteristics) are required.
Abstract
Here we present 1701 light curves of 1550 unique, spectroscopically confirmed Type Ia supernovae (SNe Ia) that will be used to infer cosmological parameters as part of the Pantheon+ SN ...analysis and the Supernovae and
H
0
for the Equation of State of dark energy distance-ladder analysis. This effort is one part of a series of works that perform an extensive review of redshifts, peculiar velocities, photometric calibration, and intrinsic-scatter models of SNe Ia. The total number of light curves, which are compiled across 18 different surveys, is a significant increase from the first Pantheon analysis (1048 SNe), particularly at low redshift (
z
). Furthermore, unlike in the Pantheon analysis, we include light curves for SNe with
z
< 0.01 such that SN systematic covariance can be included in a joint measurement of the Hubble constant (
H
0
) and the dark energy equation-of-state parameter (
w
). We use the large sample to compare properties of 151 SNe Ia observed by multiple surveys and 12 pairs/triplets of “SN siblings”—SNe found in the same host galaxy. Distance measurements, application of bias corrections, and inference of cosmological parameters are discussed in the companion paper by Brout et al., and the determination of
H
0
is discussed by Riess et al. These analyses will measure
w
with ∼3% precision and
H
0
with ∼1 km s
−1
Mpc
−1
precision.
S-adenosylmethionine (SAM) is the methyl donor for biological methylation modifications that regulate protein and nucleic acid functions. Here, we show that methylation of a phospholipid, ...phosphatidylethanolamine (PE), is a major consumer of SAM. The induction of phospholipid biosynthetic genes is accompanied by induction of the enzyme that hydrolyzes S-adenosylhomocysteine (SAH), a product and inhibitor of methyltransferases. Beyond its function for the synthesis of phosphatidylcholine (PC), the methylation of PE facilitates the turnover of SAM for the synthesis of cysteine and glutathione through transsulfuration. Strikingly, cells that lack PE methylation accumulate SAM, which leads to hypermethylation of histones and the major phosphatase PP2A, dependency on cysteine, and sensitivity to oxidative stress. Without PE methylation, particular sites on histones then become methyl sinks to enable the conversion of SAM to SAH. These findings reveal an unforeseen metabolic function for phospholipid and histone methylation intrinsic to the life of a cell.
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•Phospholipid methylation is the major consumer of SAM•Phospholipid methylation enables conversion of SAM to other sulfur metabolites•Lack of phospholipid methylation causes hypermethylation of histones and PP2A•Histones are methyl sinks in the absence of phospholipid methylation
Ye et al. show that methylation of phosphatidylethanolamine for the synthesis of phosphatidylcholine is the major consumer of SAM and is required for the efficient synthesis of cysteine and glutathione. Cells lacking phospholipid methylation accumulate SAM and exhibit hypermethylation of histones, revealing a role for phospholipids and histones as methyl group sinks, which is required for optimal cellular metabolism, signaling, and transcriptional regulation.
Conspectus The discovery of materials capable of storing magnetic information at the level of single molecules and even single atoms has fueled renewed interest in the slow magnetic relaxation ...properties of single-molecule magnets (SMMs). The lanthanide elements, especially dysprosium, continue to play a pivotal role in the development of potential nanoscale applications of SMMs, including, for example, in molecular spintronics and quantum computing. Aside from their fundamentally fascinating physics, the realization of functional materials based on SMMs requires significant scientific and technical challenges to be overcome. In particular, extremely low temperatures are needed to observe slow magnetic relaxation, and while many SMMs possess a measurable energy barrier to reversal of the magnetization (U eff), very few such materials display the important properties of magnetic hysteresis with remanence and coercivity. Werner-type coordination chemistry has been the dominant method used in the synthesis of lanthanide SMMs, and most of our knowledge and understanding of these materials is built on the many important contributions based on this approach. In contrast, lanthanide organometallic chemistry and lanthanide magnetochemistry have effectively evolved along separate lines, hence our goal was to promote a new direction in single-molecule magnetism by uniting the nonclassical organometallic synthetic approach with the traditionally distinct field of molecular magnetism. Over the last several years, our work on SMMs has focused on obtaining a detailed understanding of why magnetic materials based on the dysprosium metallocene cation building block {Cp2Dy}+ display slow magnetic relaxation. Specifically, we aspired to control the SMM properties using novel coordination chemistry in a way that hinges on key considerations, such as the strength and the symmetry of the crystal field. In establishing that the two cyclopentadienyl ligands combine to provide a strongly axial crystal field, we were able to propose a robust magneto-structural correlation for understanding the properties of dysprosium metallocene SMMs. In doing so, a blueprint was established that allows U eff and the magnetic blocking temperature (T B) to be improved in a well-defined way. Although experimental discoveries with SMMs occur more rapidly than quantitative theory can (currently) process and explain, a clear message emanating from the literature is that a combination of the two approaches is most effective. In this Account, we summarize the main findings from our own work on dysprosium metallocene SMMs, and consider them in the light of related experimental studies and theoretical interpretations of related materials reported by other protagonists. In doing so, we aim to contribute to the nascent and healthy debate on the nature of spin dynamics in SMMs and allied molecular nanomagnets, which will be crucial for the further advancement of this vibrant research field.
Hybridization, genetic mixture of distinct populations, gives rise to myriad recombinant genotypes. Characterizing the genomic composition of hybrids is critical for studies of hybrid zone dynamics, ...inheritance of traits, and consequences of hybridization for evolution and conservation. Hybrid genomes are often summarized either by an estimate of the proportion of alleles coming from each ancestral population or classification into discrete categories like F1, F2, backcross, or merely "hybrid" vs. "pure". In most cases, it is not realistic to classify individuals into the restricted set of classes produced in the first two generations of admixture. However, the continuous ancestry index misses an important dimension of the genotype. Joint consideration of ancestry together with interclass heterozygosity (proportion of loci with alleles from both ancestral populations) captures all of the information in the discrete classification without the unrealistic assumption that only two generations of admixture have transpired.
I describe a maximum likelihood method for joint estimation of ancestry and interclass heterozygosity. I present two worked examples illustrating the value of the approach for describing variation among hybrid populations and evaluating the validity of the assumption underlying discrete classification.
Naively classifying natural hybrids into the standard six line cross categories can be misleading, and false classification can be a serious problem for datasets with few molecular markers. My analysis underscores previous work showing that many (50 or more) ancestry informative markers are needed to avoid erroneous classification.
Although classification of hybrids might often be misleading, valuable inferences can be obtained by focusing directly on distributions of ancestry and heterozygosity. Estimating and visualizing the joint distribution of ancestry and interclass heterozygosity is an effective way to compare the genetic structure of hybrid populations and these estimates can be used in classic quantitative genetic methods for assessing additive, dominant, and epistatic genetic effects on hybrid phenotypes and fitness. The methods are implemented in a freely available package "HIest" for the R statistical software ( http://cran.r-project.org/web/packages/HIest/index.html).
Few innovations in the money markets have brought more attention by regulators and policy makers than the digital currency Bitcoin. However, few studies in the literature have examined the price ...dynamics of Bitcoin. Besides providing an exploratory glace at the value and volatility of the Bitcoin across time, we also test whether the unusual level of Bitcoin’s volatility is attributable to speculative trading. Results in this study do not find that, during 2013, speculative trading contributed to the unprecedented rise and subsequent crash in Bitcoin’s value nor do we find that speculative trading is directly associated with Bitcoin’s unusual level of volatility.
Arginine methylation is a ubiquitous post-translational modification. Three predominant types of arginine-guanidino methylation occur in Eukarya: mono (Rme1/MMA), symmetric (Rme2s/SDMA), and ...asymmetric (Rme2a/ADMA). Arginine methylation frequently occurs at sites of protein–protein and protein–nucleic acid interactions, providing specificity for binding partners and stabilization of important biological interactions in diverse cellular processes. Each methylarginine isoform—catalyzed by members of the protein arginine methyltransferase family, Type I (PRMT1-4,6,8) and Type II (PRMT5,9)—has unique downstream consequences. Methylarginines are found in ordered domains, domains of low complexity, and in intrinsically disordered regions of proteins—the latter two of which are intimately connected with biological liquid–liquid phase separation. This review highlights discoveries illuminating how arginine methylation affects genome integrity, gene transcription, mRNA splicing and mRNP biology, protein translation and stability, and phase separation. As more proteins and processes are found to be regulated by arginine methylation, its importance for understanding cellular physiology will continue to grow.
Chemical fuels for molecular machinery Borsley, Stefan; Leigh, David A.; Roberts, Benjamin M. W.
Nature chemistry,
07/2022, Letnik:
14, Številka:
7
Journal Article
Recenzirano
Odprti dostop
Chemical reaction networks that transform out-of-equilibrium ‘fuel’ to ‘waste’ are the engines that power the biomolecular machinery of the cell. Inspired by such systems, autonomous artificial ...molecular machinery is being developed that functions by catalysing the decomposition of chemical fuels, exploiting kinetic asymmetry to harness energy released from the fuel-to-waste reaction to drive non-equilibrium structures and dynamics. Different aspects of chemical fuels profoundly influence their ability to power molecular machines. Here we consider the structure and properties of the fuels that biology has evolved and compare their features with those of the rudimentary synthetic chemical fuels that have so far been used to drive autonomous non-equilibrium molecular-level dynamics. We identify desirable, but context-specific, traits for chemical fuels together with challenges and opportunities for the design and invention of new chemical fuels to power synthetic molecular machinery and other dissipative nanoscale processes.Chemically fuelled synthetic molecular machines are capable of driving and sustaining non-equilibrium motion, analogous to the biomachinery that underpins life. This Review discusses the chemical and physical features of biological and synthetic chemical fuels and highlights potential challenges and opportunities for the development of synthetic chemically fuelled machinery.
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