As a global pollution problem, heavy metal contamination poses a serious hazard to soil microorganisms which play an extremely important role in soil chemical cycling and ecological persistence. ...However, the effects that different levels of heavy metal contamination in soils have on microorganisms and the interactions between them are still unclear. The purpose of this research is to analyze the microbial structure under different levels of heavy metal contamination, find out heavy metal tolerant species under different environmental conditions, then provide useful reference for the bioremediation of contaminated farmland. In this study, 16s rRNA high-throughput sequencing technology was used to investigate the microbial communities in severe level (SL), moderate level (ML), light level (LL) and clean level (CL) of heavy metal contaminated soils, and the relationships between environment variables and microorganisms were analyzed. The results showed that the concentrations of heavy metals and soil physicochemical properties had various impacts on microbial community composition under different heavy metal contamination levels. Most dominant bacteria were in significant negative correlation with Cd in ML region, and significantly correlated with TN and OM in LL region. However, there was no significant correlation between dominant fungi and the physicochemical properties in LL region. And most of the dominant fungi were significantly correlated with the heavy metal concentrations in SL region. The bacterial phyla such as Proteobacteria, Acidobacteria and Bacteroidetes showed more tolerance with heavy metal contamination in SL, ML and LL regions, respectively. Meanwhile, the dominant fungi of Ascomycota, Basidiomycota, Chytridiomycota, Glomeromycota, Zygomycota and Rozellomycota showed stronger correlations with heavy metal contamination in SL and LL regions. These results indicated that some microorganisms had strong tolerance to heavy metal contamination and had certain heavy metals digestion ability, which can create an appropriate soil environment for the growth of food crops.
•Most dominant bacteria were in significant negative correlation with Cd in ML region.•There was no significant correlation between dominant fungi and the physicochemical properties in LL region.•Most of the dominant fungi were significantly correlated with the heavy metal concentrations in SL region.•Some microorganisms had strong tolerance to heavy metal contamination and certain heavy metals digestion ability.
Genetic risk prediction is an important goal in human genetics research and precision medicine. Accurate prediction models will have great impacts on both disease prevention and early treatment ...strategies. Despite the identification of thousands of disease-associated genetic variants through genome wide association studies (GWAS), genetic risk prediction accuracy remains moderate for most diseases, which is largely due to the challenges in both identifying all the functionally relevant variants and accurately estimating their effect sizes in the presence of linkage disequilibrium. In this paper, we introduce AnnoPred, a principled framework that leverages diverse types of genomic and epigenomic functional annotations in genetic risk prediction for complex diseases. AnnoPred is trained using GWAS summary statistics in a Bayesian framework in which we explicitly model various functional annotations and allow for linkage disequilibrium estimated from reference genotype data. Compared with state-of-the-art risk prediction methods, AnnoPred achieves consistently improved prediction accuracy in both extensive simulations and real data.
Abstract
With the detection of a binary neutron star system and its corresponding electromagnetic counterparts, a new window of transient astronomy has opened. Due to the size of the sky localization ...regions, which can span hundreds to thousands of square degrees, there are significant benefits to optimizing tilings for these large sky areas. The rich science promised by gravitational wave astronomy has led to the proposal for a variety of proposed tiling and time allocation schemes, and for the first time, we make a systematic comparison of some of these methods. We find that differences of a factor of 2 or more in efficiency are possible, depending on the algorithm employed. For this reason, with future surveys searching for electromagnetic counterparts, care should be taken when selecting tiling, time allocation, and scheduling algorithms to optimize counterpart detection.
Accurate prediction of disease risk based on genetic factors is an important goal in human genetics research and precision medicine. Advanced prediction models will lead to more effective disease ...prevention and treatment strategies. Despite the identification of thousands of disease-associated genetic variants through genome-wide association studies (GWAS) in the past decade, accuracy of genetic risk prediction remains moderate for most diseases, which is largely due to the challenges in both identifying all the functionally relevant variants and accurately estimating their effect sizes. In this work, we introduce PleioPred, a principled framework that leverages pleiotropy and functional annotations in genetic risk prediction for complex diseases. PleioPred uses GWAS summary statistics as its input, and jointly models multiple genetically correlated diseases and a variety of external information including linkage disequilibrium and diverse functional annotations to increase the accuracy of risk prediction. Through comprehensive simulations and real data analyses on Crohn's disease, celiac disease and type-II diabetes, we demonstrate that our approach can substantially increase the accuracy of polygenic risk prediction and risk population stratification, i.e. PleioPred can significantly better separate type-II diabetes patients with early and late onset ages, illustrating its potential clinical application. Furthermore, we show that the increment in prediction accuracy is significantly correlated with the genetic correlation between the predicted and jointly modeled diseases.
Identifying functional regions in the human genome is a major goal in human genetics. Great efforts have been made to functionally annotate the human genome either through computational predictions, ...such as genomic conservation, or high-throughput experiments, such as the ENCODE project. These efforts have resulted in a rich collection of functional annotation data of diverse types that need to be jointly analyzed for integrated interpretation and annotation. Here we present GenoCanyon, a whole-genome annotation method that performs unsupervised statistical learning using 22 computational and experimental annotations thereby inferring the functional potential of each position in the human genome. With GenoCanyon, we are able to predict many of the known functional regions. The ability of predicting functional regions as well as its generalizable statistical framework makes GenoCanyon a unique and powerful tool for whole-genome annotation. The GenoCanyon web server is available at http://genocanyon.med.yale.edu.
The chemical constituents of two root samples of
DC. collected in Yunnan Province, China, were investigated. Five new oligomeric benzofurans (
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), nine new benzofuran/dihydrobenzofuran derivatives, ...and a new thymol analog were isolated, and their structures were determined using extensive spectroscopic techniques, such as 1D and 2D NMR spectroscopy and DFT calculations of the CD spectra. Most of the new compounds, including oligomeric benzofurans (
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), were obtained from only one of the root samples. Furthermore, this is the first example that produces oligomeric benzofurans in this plant. These results imply that diversification of secondary metabolites in
is ongoing. Plausible biosynthetic pathways for
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are also proposed.
Despite the success of large-scale genome-wide association studies (GWASs) on complex traits, our understanding of their genetic architecture is far from complete. Jointly modeling multiple traits’ ...genetic profiles has provided insights into the shared genetic basis of many complex traits. However, large-scale inference sets a high bar for both statistical power and biological interpretability. Here we introduce a principled framework to estimate annotation-stratified genetic covariance between traits using GWAS summary statistics. Through theoretical and numerical analyses, we demonstrate that our method provides accurate covariance estimates, thereby enabling researchers to dissect both the shared and distinct genetic architecture across traits to better understand their etiologies. Among 50 complex traits with publicly accessible GWAS summary statistics (Ntotal≈ 4.5 million), we identified more than 170 pairs with statistically significant genetic covariance. In particular, we found strong genetic covariance between late-onset Alzheimer disease (LOAD) and amyotrophic lateral sclerosis (ALS), two major neurodegenerative diseases, in single-nucleotide polymorphisms (SNPs) with high minor allele frequencies and in SNPs located in the predicted functional genome. Joint analysis of LOAD, ALS, and other traits highlights LOAD’s correlation with cognitive traits and hints at an autoimmune component for ALS.
Alkyne metathesis represents a rapidly emerging synthetic method that has shown great potential in small molecule and polymer synthesis. However, its practical use has been impeded by the limited ...availability of user-friendly catalysts and their generally high moisture/air sensitivity. Herein, we report an alkyne metathesis catalyst system that can operate under open-air conditions with a broad substrate scope and excellent yields. These catalysts are composed of simple multidentate tris(2-hydroxyphenyl)methane ligands, which can be easily prepared in multi-gram scale. The catalyst substituted with electron withdrawing cyano groups exhibits the highest activity at room temperature with excellent functional group tolerance (-OH, -CHO, -NO
, pyridyl). More importantly, the catalyst provides excellent yields (typically >90%) in open air, comparable to those operating under argon. When dispersed in paraffin wax, the active catalyst can be stored on a benchtop under ambient conditions without any decrease in activity for one day (retain 88% after 3 days). This work opens many possibilities for developing highly active user-friendly alkyne metathesis catalysts that can function in open air.
Ferroptosis, a new form of regulated cell death, results from the iron-dependent accumulation of lipid peroxides that are associated with reactive oxygen species. However, it remains unclear how ...hydroxyl radical (•OH) and cellular microenvironments such as viscosity alter in this process. Herein, we characterize for the first time the changing behavior of •OH and cytoplasmic viscosity during ferroptosis using a dual-functional fluorescence probe (H–V) that is designed via the molecular rotor strategy and the unique aromatic hydroxylation of •OH. Probe H–V shows completely separate spectral responses to •OH and viscosity with high sensitivity and selectivity, thereby achieving the detection of •OH and viscosity in two independent channels without spectral cross-interference. With the probe we find that ferroptosis is accompanied by significant •OH generation and cytoplasmic viscosity increase. Most notably, the raised •OH comprises the majority of the total reactive oxygen species in ferroptosis. H–V is biocompatible, ready to prepare, and may be expected to be used in the study of viscosity and •OH detection in more biosystems.
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