A main challenge in genome-wide association studies (GWAS) is to pinpoint possible causal variants. Results from GWAS typically do not directly translate into causal variants because the majority of ...hits are in non-coding or intergenic regions, and the presence of linkage disequilibrium leads to effects being statistically spread out across multiple variants. Post-GWAS annotation facilitates the selection of most likely causal variant(s). Multiple resources are available for post-GWAS annotation, yet these can be time consuming and do not provide integrated visual aids for data interpretation. We, therefore, develop FUMA: an integrative web-based platform using information from multiple biological resources to facilitate functional annotation of GWAS results, gene prioritization and interactive visualization. FUMA accommodates positional, expression quantitative trait loci (eQTL) and chromatin interaction mappings, and provides gene-based, pathway and tissue enrichment results. FUMA results directly aid in generating hypotheses that are testable in functional experiments aimed at proving causal relations.
Genome-wide association studies (GWAS) of psychological traits are generally conducted on (dichotomized) sums of items or symptoms (e.g., case-control status), and not on the individual items or ...symptoms themselves. We conduct large-scale GWAS on 12 neuroticism items and observe notable and replicable variation in genetic signal between items. Within samples, genetic correlations among the items range between 0.38 and 0.91 (mean r
= .63), indicating genetic heterogeneity in the full item set. Meta-analyzing the two samples, we identify 255 genome-wide significant independent genomic regions, of which 138 are item-specific. Genetic analyses and genetic correlations with 33 external traits support genetic differences between the items. Hierarchical clustering analysis identifies two genetically homogeneous item clusters denoted depressed affect and worry. We conclude that the items used to measure neuroticism are genetically heterogeneous, and that biological understanding can be gained by studying them in genetically more homogeneous clusters.
On 2012 October 23, a strong white-light emission, associated with an X1.8-class flare, was observed by the Solar Optical Telescope on board the Hinode satellite. White-light kernels were clearly ...observed along the Ca ii H ribbons. RHESSI also observed hard X-ray emissions that were almost located on the white-light kernels. The total energy of the white-light emission was and the total energy of the accelerated electrons was almost of the same order when we used 40 keV as the lower energy cutoff. The white-light emission appears to have originated from nonthermal electrons in these energies. Moreover, the EUV imaging spectrometer on board the Hinode satellite performed a raster scan over this flaring active region and the flare occurred during the scan. Over the white-light kernels, we observed redshifts of a few tens of km s−1 in Fe xii. It appears that these EUV responses originated from some accelerated electrons due to the solar flare and they are considered to be the source of the white-light emission. In fact, the electron density of the white-light kernels was less than , which is sufficiently low for nonthermal electrons to penetrate into the photosphere.
Single-cell RNA sequencing (scRNA-seq) data allows to create cell type specific transcriptome profiles. Such profiles can be aligned with genome-wide association studies (GWASs) to implicate cell ...type specificity of the traits. Current methods typically rely only on a small subset of available scRNA-seq datasets, and integrating multiple datasets is hampered by complex batch effects. Here we collated 43 publicly available scRNA-seq datasets. We propose a 3-step workflow with conditional analyses within and between datasets, circumventing batch effects, to uncover associations of traits with cell types. Applying this method to 26 traits, we identify independent associations of multiple cell types. These results lead to starting points for follow-up functional studies aimed at gaining a mechanistic understanding of these traits. The proposed framework as well as the curated scRNA-seq datasets are made available via an online platform, FUMA, to facilitate rapid evaluation of cell type specificity by other researchers.
Abstract
Thermal microwave emissions detected from stellar atmospheres contain information on stellar activity. However, even for the Sun, the relationship between multifrequency microwave data and ...other activity indices remains unclear. We investigated the relationships among the thermal microwave fluxes with 1, 2, 3.75, and 9.4 GHz, their circular polarizations, and several activity indices recorded during recent solar cycles and observed that these relationships can be categorized into two groups. In the first group, the relationship between the microwave fluxes and solar indices, which are strongly related to the active regions, can be well-fitted by using a linear function. In the second group, the fitting function is dependent on frequency. Specifically, the microwave fluxes at 1 and 2 GHz can be well-fitted to the total unsigned magnetic and extreme ultraviolet fluxes by employing a power-law function. The trend changes around 3.75 GHz, and the trend for the 9.4 GHz fluxes can be fitted by using a linear function. For the first time, we present the relationship between circular polarization and solar indices. Moreover, we extrapolated these relationships of the solar microwave fluxes to higher values and compared them with the solar-type stars. We found that
ϵ
Eri, whose microwave emission originates from thermal plasma, follows the extrapolated relationship. However, to date, only one star’s emission at 1–10 GHz has been confirmed as thermal emission. More solar-type stars should be observed with future radio interferometers to confirm that relationships based on solar data can be applied to stellar microwave data.
An X1.6 flare occurred in active region AR 12192 on 2014 October 22 at 14:02 UT and was observed by Hinode, IRIS, SDO, and RHESSI. We analyze a bright kernel that produces a white light (WL) flare ...with continuum enhancement and a hard X-ray (HXR) peak. Taking advantage of the spectroscopic observations of IRIS and Hinode/EIS, we measure the temporal variation of the plasma properties in the bright kernel in the chromosphere and corona. We find that explosive evaporation was observed when the WL emission occurred, even though the intensity enhancement in hotter lines is quite weak. The temporal correlation of the WL emission, HXR peak, and evaporation flows indicates that the WL emission was produced by accelerated electrons. To understand the WL emission process, we calculated the energy flux deposited by non-thermal electrons (observed by RHESSI) and compared it to the dissipated energy estimated from a chromospheric line (Mg ii triplet) observed by IRIS. The deposited energy flux from the non-thermal electrons is about (3-7.7) × 1010 erg cm−2 s−1 for a given low-energy cutoff of 30-40 keV, assuming the thick-target model. The energy flux estimated from the changes in temperature in the chromosphere measured using the Mg ii subordinate line is about (4.6-6.7) × 109 erg cm−2 s−1: ∼6%-22% of the deposited energy. This comparison of estimated energy fluxes implies that the continuum enhancement was directly produced by the non-thermal electrons.
Pestalopezia brunneopruinosa, the type species of Pestalopezia in Leotiomycetes, produces typical cup-shaped ascomata. Because its asexual morph has conidia comprised of five cells including apical ...and basal appendages and three pigmented median cells, it was first described as Pestalotia gibbosa, which belongs to Sordariomycetes. This contradiction has not been resolved due to the difficulty in isolating this fungus in culture. In this study, we isolated separate strains from the sexual morph and the asexual morph for molecular analysis. Phylogenetic trees of Sporocadaceae based on internal transcribed spacer, partial β-tubulin, and partial translation elongation factor 1-alpha sequence datasets revealed that both strains fall into the same taxon, in a clade in Pestalotiopsis sensu stricto alongside P. gaultheriae and P. spathulata. We provide the first evidence that fungi producing cup-shaped ascomata in Pestalotiopsis belong to Sordariomycetes, and we have proposed the transfer of Pestalopezia brunneopruinosa to Pestalotiopsis gibbosa.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Cognitive brain networks such as the default-mode network (DMN), frontoparietal network, and salience network, are key functional networks of the human brain. Here we show that the rapid evolutionary ...cortical expansion of cognitive networks in the human brain, and most pronounced the DMN, runs parallel with high expression of human-accelerated genes (HAR genes). Using comparative transcriptomics analysis, we present that HAR genes are differentially more expressed in higher-order cognitive networks in humans compared to chimpanzees and macaques and that genes with high expression in the DMN are involved in synapse and dendrite formation. Moreover, HAR and DMN genes show significant associations with individual variations in DMN functional activity, intelligence, sociability, and mental conditions such as schizophrenia and autism. Our results suggest that the expansion of higher-order functional networks subserving increasing cognitive properties has been an important locus of genetic changes in recent human brain evolution.
Abstract The Kepler space telescope and Transiting Exoplanet Survey Satellite unveiled that Sun-like stars frequently host exoplanets. These exoplanets are subject to fluxes of ionizing radiation in ...the form of X-ray and extreme-ultraviolet (EUV) radiation that may cause changes in their atmospheric dynamics and chemistry. While X-ray fluxes can be observed directly, EUV fluxes cannot be observed because of severe interstellar medium absorption. Here we present a new empirical method to estimate the whole stellar X-ray plus EUV (XUV) and far-UV (FUV) spectra as a function of total unsigned magnetic fluxes of stars. The response of the solar XUV and FUV spectrum (0.1–180 nm) to the solar total unsigned magnetic flux is investigated by using the long-term Sun-as-a-star data set over 10 yr, and the power-law relation is obtained for each wavelength with a spectral resolution of 0.1–1 nm. We applied the scaling relations to active young Sun-like stars (G dwarfs), EK Dra (G1.5V), π 1 Uma (G1.5V), and κ 1 Ceti (G5V) and found that the observed spectra (except for the unobservable longward EUV wavelength) are roughly consistent with the extension of the derived power-law relations with errors of an order of magnitude. This suggests that our model is a valuable method to derive the XUV/FUV fluxes of Sun-like stars, including the EUV band mostly absorbed at wavelengths longward of 36 nm. We also discuss differences between the solar extensions and stellar observations at wavelengths in the 2–30 nm band and conclude that simultaneous observations of magnetic and XUV/FUV fluxes are necessary for further validations.
The phenotypic correlation between human intelligence and brain volume (BV) is considerable (r ≈ 0.40), and has been shown to be due to shared genetic factors. To further examine specific genetic ...factors driving this correlation, we present genomic analyses of the genetic overlap between intelligence and BV using genome-wide association study (GWAS) results. First, we conduct a large BV GWAS meta-analysis (N = 47,316 individuals), followed by functional annotation and gene-mapping. We identify 18 genomic loci (14 not previously associated), implicating 343 genes (270 not previously associated) and 18 biological pathways for BV. Second, we use an existing GWAS for intelligence (N = 269,867 individuals), and estimate the genetic correlation (r
) between BV and intelligence to be 0.24. We show that the r
is partly attributable to physical overlap of GWAS hits in 5 genomic loci. We identify 92 shared genes between BV and intelligence, which are mainly involved in signaling pathways regulating cell growth. Out of these 92, we prioritize 32 that are most likely to have functional impact. These results provide information on the genetics of BV and provide biological insight into BV's shared genetic etiology with intelligence.
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