Biology subjects

Shan, Y.

Publications and source records attributed to Shan, Y..

51 records · Page 3Linked to original sources

bioRxiv2020

Characterization of the first cultured free-living representative of Candidatus Izimaplasma uncovers its unique biology

Candidatus Izimaplasma, an intermediate in the reductive evolution from Firmicutes to Mollicutes, was proposed to represent a novel class of free-living wall-less bacteria within the phylum Tenericutes found in deep-sea methane seeps. Unfortunately, the paucity of marine isolates currently available has limited further insights into their physiological and metabolic features as well as ecological roles. Here, we present a detailed description of the phenotypic traits, genomic data and central metabolisms tested in both laboratorial and deep-sea environments of the novel strain zrk13, which allows for the first time the reconstruction of the metabolic potential and lifestyle of a member of the tentatively defined Candidatus Izimaplasma. On the basis of the description of strain zrk13, the novel species and genus Xianfuyuplasma coldseepsis is proposed. Notably, DNA degradation driven by X. coldseepsis zrk13 was detected in both laboratorial and in situ conditions, strongly indicating it is indeed a key DNA degrader. Moreover, the putative genes determining degradation broadly distribute in the genomes of other Izimaplasma members. Given extracellular DNA is a particularly crucial phosphorus as well as nitrogen and carbon source for microorganisms in the seafloor, Izimaplasma bacteria are thought to be important contributors to the biogeochemical cycling in the deep ocean.

microbiology↗

bioRxiv2020

The structural mechanism underlying the antithetic effect of homologous RND1 and RhoD GTPases in plexin regulation

Plexins are semaphorin receptors that play essential roles in neuronal axon guidance and in many other important biological processes. Plexin signaling depends on a semaphorin-induced dimerization mechanism, and is modulated by small signaling GTPases of the Rho family, of which RND1 serves as a plexin activator yet its close homolog RhoD an inhibitor. Using molecular dynamics (MD) simulations we showed that RND1 reinforces plexin dimerization interface whereas RhoD destabilizes it due to their differential interaction with cell membrane. Upon binding plexin dimers at the Rho-GTPase binding (RBD) domains, RND1 and RhoD interact differently with the inner leaflet of cell membrane, and exert opposite effects on the dimerization interface via an allosteric network involving the RBD domain, RBD linkers, and a buttress segment adjacent to the dimerization interface. The differential membrane interaction is attributed to the fact that, unlike RND1, RhoD features a short C-terminal tail and a positively-charged membrane interface.

biophysics↗

bioRxiv2020

Common variants contribute to intrinsic functional architecture of human brain

The human brain remains active in the absence of explicit tasks and forms networks of correlated activity. Resting-state functional magnetic resonance imaging (rsfMRI) measures brain activity at rest, which has been linked with both cognitive and clinical outcomes. The genetic variants influencing human brain function are largely unknown. Here we utilized rsfMRI from 44,190 individuals of multiple ancestries (37,339 in the UK Biobank) to discover and validate the common genetic variants influencing intrinsic brain activity. We identified hundreds of novel genetic loci associated with intrinsic functional signatures (P < 2.8 x 10-11), including associations to the central executive, default mode, and salience networks involved in the triple network model of psychopathology. A number of intrinsic brain activity associated loci colocalized with brain disorder GWAS (e.g., Alzheimers disease, Parkinsons disease, schizophrenia) and cognition, such as 19q13.32, 17q21.31, and 2p16.1. Particularly, we detected a colocalization between one (rs429358) of the two variants in the APOE {varepsilon}4 locus and function of the default mode, central executive, attention, and visual networks. Genetic correlation analysis demonstrated shared genetic influences between brain function and brain structure in the same regions. We also detected significant genetic correlations with 26 other complex traits, such as ADHD, major depressive disorder, schizophrenia, intelligence, education, sleep, subjective well-being, and neuroticism. Common variants associated with intrinsic brain activity were enriched within regulatory element in brain tissues.

genetics↗

bioRxiv2020

A structural model of a Ras-Raf signalosome

The protein K-Ras functions as a molecular switch in signaling pathways regulating cell growth. In the MAPK pathway, which is implicated in many cancers, multiple K-Ras proteins are thought to assemble at the cell membrane with Ras-effector proteins from the Raf family. Here we propose an atomistic structural model for such an assembly. Our starting point was an asymmetric, GTP-mediated K-Ras dimer model, which we generated using unbiased molecular dynamics simulations and verified with mutagenesis experiments. Adding further K-Ras monomers in a head-to-tail fashion led to a compact helical assembly, a model we validated using electron microscopy and cell-based experiments. This assembly stabilizes K-Ras in its active state and presents composite interfaces to facilitate Raf binding. Guided by existing experimental data, we then positioned C-Raf, the downstream kinase MEK1, and accessory proteins (Galectin-3 and 14-3-3{sigma}) on the helical assembly. The resulting Ras-Raf signalosome model offers an explanation for a large body of data on MAPK signaling.

molecular biology↗

bioRxiv2020

The comprehensive genetic architecture of brain white matter

Brain regions communicate with each other via tracts of myelinated axons, commonly referred to as white matter. White matter microstructure can be measured in the living human brain using diffusion based magnetic resonance imaging (dMRI), and has been found to be altered in patients with neuropsychiatric disorders. Although under strong genetic control, few genetic variants influencing white matter microstructure have ever been identified. Here we identified common genetic variants influencing white matter microstructure using dMRI in 42,919 individuals (35,741 in the UK Biobank). The dMRIs were summarized into 215 white matter microstructure traits, including 105 measures from tract-specific functional principal component analysis. Genome-wide association analysis identified many novel white matter microstructure associated loci (P < 2.3 x 10-10). We identified shared genetic influences through genetic correlations between white matter tracts and 62 other complex traits, including stroke, neuropsychiatric disorders (e.g., ADHD, bipolar disorder, major depressive disorder, schizophrenia), cognition, neuroticism, chronotype, as well as non-brain traits. Common variants associated with white matter microstructure alter the function of regulatory elements in glial cells, particularly oligodendrocytes. White matter associated genes were enriched in pathways involved in brain disease pathogenesis, neurodevelopment process, and repair of white matter damage (P < 1.5 x 10-8). In summary, this large-scale tract-specific study provides a big step forward in understanding the genetic architecture of white matter and its genetic links to a wide spectrum of clinical outcomes.

genetics↗

bioRxiv2020

Early-life microbial intervention reduces colitis risk promoted by antibiotic-induced gut dysbiosis

Perturbations in the early life gut microbiome are associated with increased risk to complex immune disorder like inflammatory bowel diseases. We previously showed maternal antibiotic-induced gut dysbiosis vertically passed to offspring increases experimental colitis risk in IL-10 gene deficient (IL-10-/-) mice. While this could arise from emergence of pathobionts or loss/lack of essential microbes needed for appropriate immunological education, our findings suggest the latter. A dominant Bacteroides strain absent following antibiotic-induced perturbation was cultivated from murine fecal samples. Addition of this strain into mice with antibiotic-induced dysbiosis significantly promoted immune tolerance and reduced incidence of colitis in IL-10-/- mice, but only if engrafted early in life, and not during adulthood. Thus, key members of the gut microbiome are essential for development of immune tolerance to commensal microbes in early life and their addition in presence of gut dysbiosis during this period can reduce colitis risk in genetically prone hosts. HighlightsO_LISpecific gut microbes promote early life immune tolerance to key commensal microbes C_LIO_LILoss of early life keystone microbes increases colitis risk in genetically prone hosts C_LIO_LIEmergence of absent commensal microbes late in life worsened colitis outcome C_LIO_LIEarly life exposure to a missing keystone Bacteroides strain reduced colitis risk C_LI

microbiology↗

bioRxiv2020

Expanding the Coverage of the Metabolic Landscape in Cultivated Rice with Integrated Computational Approaches

Genome-scale metabolomics analysis is increasingly used for pathway and function discovery in post-genomics era. The great potential offered by developed mass spectrometry (MS)-based technology has been hindered by the obstacle that only a small portion of detected metabolites were identifiable so far. To address the critical issue of low identification coverage in metabolomics, we adopted a deep metabolomics analysis strategy by integrating advanced algorithms and expanded reference databases. The experimental reference spectra, and in silico reference spectra were adopted to facilitate the structural annotation. To further characterize the structure of metabolites, two approaches, structural motif search combined with neutral loss scanning, and metabolite association network were incorporated into our strategy. An untargeted metabolomics analysis was performed on 150 rice cultivars using Ultra Performance Liquid Chromatography (UPLC)-Quadrupole (Q)-Orbitrap mass spectrometer. 1939 of 4491 metabolite features in MS/MS spectral tag (MS2T) library were annotated, representing an extension of annotation coverage by an order of magnitude on rice. The differential accumulation patterns of flavonoids between indica and japonica cultivars were revealed, especially O-sulfated flavonoids. A series of closely-related flavonolignans were characterized, adding further evidence for the crucial role of tricin-oligolignols in lignification. Our study provides a great template in the exploration of phytochemical diversity for more plant species.

bioinformatics↗

bioRxiv2020

Beware of asymptomatic transmission: Study on 2019-nCoV prevention and control measures based on extended SEIR model

BackgroundThe 2019 new coronavirus, "2019-nCoV", was discovered from Wuhan Viral Pneumonia cases in December 2019, and was named by the World Health Organization on January 12, 2020. In the early stage, people knows little about the 2019-nCoV virus was not clear, and the spread period was encountering Chinas annual spring migration, which made the epidemic spread rapidly from Wuhan to almost all provinces in China. MethodsThis study builds a SEIRD model that considers the movement of people across regions, revealing the effects of three measures on controlling the spread of the epidemic.Based on MATLAB R2017a, computational experiments were performed to simulate the epidemic prevention and control measures. FindingsThe research results show that current prevention and control measures in China are very necessary. This study further validates the concerns of international and domestic experts regarding asymptomatic transmission (E-status). InterpretationThe results of this study are applicable to explore the impact of the implementation of relevant measures on the prevention and control of epidemic spread, and to identify key individuals that may exist during the spread of the epidemic.

microbiology↗

bioRxiv2019

Transcriptome-wide association analysis of 211 neuroimaging traits identifies new genes for brain structures and yields insights into the gene-level pleiotropy with other complex traits

Structural and microstructural variations of human brain are heritable and highly polygenic traits, with hundreds of associated genes founded in recent genome-wide association studies (GWAS). Using gene expression data, transcriptome-wide association studies (TWAS) can prioritize these GWAS findings and also identify novel gene-trait associations. Here we performed TWAS analysis of 211 structural neuroimaging phenotypes in a discovery-validation analysis of six datasets. Using a cross-tissue approach, TWAS discovered 204 associated genes (86 new) exceeding Bonferroni significance threshold of 1.37*10-8 (adjusted for testing multiple phenotypes) in the UK Biobank (UKB) cohort, and validated 18 TWAS or previous GWAS-detected genes. The TWAS-significant genes of brain structures had been linked to a wide range of complex traits in different domains. Additional TWAS analysis of 11 cognitive and mental health traits detected 69 overlapping significant genes with brain structures, further characterizing the genetic overlaps among these brain-related traits. Through TWAS gene-based polygenic risk scores (PRS) prediction, we found that TWAS PRS gained substantial power in association analysis compared to conventional variant-based PRS, and up to 6.97% of phenotypic variance (p-value=7.56*10-31) in testing datasets can be explained by UKB TWAS-derived PRS. In conclusion, our study illustrates that TWAS can be a powerful supplement to traditional GWAS in imaging genetics studies for gene discovery-validation, genetic co-architecture analysis, and polygenic risk prediction.

genetics↗

bioRxiv2019

scCancer: a package for automated processing of single cell RNA-seq data in cancer

SummaryMolecular heterogeneities bring great challenges for cancer diagnosis and treatment. Recent advance in single cell RNA-sequencing (scRNA-seq) technology make it possible to study cancer transcriptomic heterogeneities at single cell level. Here, we develop an R package named scCancer which focuses on processing and analyzing scRNA-seq data for cancer research. Except basic data processing steps, this package takes several special considerations for cancer-specific features. Firstly, the package introduced comprehensive quality control metrics. Secondly, it used a data-driven machine learning algorithm to accurately identify major cancer microenvironment cell populations. Thirdly, it estimated a malignancy score to classify malignant (cancerous) and non-malignant cells. Then, it analyzed intra-tumor heterogeneities by key cellular phenotypes (such as cell cycle and stemness) and gene signatures. Finally, a user-friendly graphic report was generated for all the analyses.\n\nAvailabilityhttp://lifeome.net/software/sccancer/.\n\nContactjgu@tsinghua.edu.cn

bioinformatics↗

bioRxiv2019

High-throughput isolation and sorting of gut microbes reduce biases of traditional cultivation strategies

Traditional cultivation approaches in microbiology are labor-intensive, low-throughput, and often yield biased sampling of taxa due to ecological and evolutionary factors. New strategies are needed to enable ample representation of rare taxa and slow-growers that are outcompeted by fast-growing organisms. We developed a microfluidic platform that anaerobically isolates and cultivates microbial cells in millions of picoliter droplets and automatically sorts droplets based on colony density. We applied our strategy to mouse and human gut microbiomes and used 16S ribosomal RNA gene amplicons to characterize taxonomic composition of cells grown using different media. We found up to 4-fold increase in richness and larger representation of rare taxa among cells grown in droplets compared to conventional culture plates. Automated sorting of droplets for slow-growing colonies further enhanced the relative abundance of rare populations. Our method improves the cultivation and analysis of diverse microbiomes to gain deeper insights into microbial functioning and lifestyles.

microbiology↗

bioRxiv2019

Structural models of full-length JAK2 kinase

The protein JAK2 is a prototypical member of the Janus kinase family, and mediates signals from numerous cytokine receptors. The constitutively active V617F mutant of JAK2 is prevalent in many bone marrow disorders, blood cancers, and autoimmune diseases, and is an important drug target. Structures have been determined for each of the four individual domains making up JAK2, and for certain pairs of these domains, but no structure of full-length JAK2 is available, and thus the mechanisms underlying JAK2 regulation and the aberrant activity of the V617F mutant have been incompletely understood. Here we propose structural models of full-length JAK2 in both its active and inactive forms. Construction of these models was informed by long-timescale molecular dynamics simulations. Subsequent mutagenesis experiments showed that mutations at the putative interdomain interfaces modulated JAK2 activity. The models provide a structural basis for understanding JAK2 autoinhibition and activation, and suggest that the constitutive activity of the V617F mutant may arise from a dual effect of destabilizing the inactive conformation and stabilizing the active conformation.

biochemistry↗

bioRxiv2019

GWAS of 19,629 individuals identifies novel genetic variants for regional brain volumes and refines their genetic co-architecture with cognitive and mental health traits

Volumetric variations of human brain are heritable and are associated with many brain-related complex traits. Here we performed genome-wide association studies (GWAS) and post-GWAS analyses of 101 brain volumetric phenotypes using the UK Biobank (UKB) sample including 19,629 participants. GWAS identified 287 independent SNPs exceeding genome-wide significance threshold of 4.9*10-10, adjusted for testing multiple phenotypes. Gene-based association study found 142 associated genes (113 new) and functional gene mapping analysis linked 122 more genes. Many of the discovered genetic variants have previously been implicated with cognitive and mental health traits (such as cognitive performance, education, mental disease/disorders), and significant genetic correlations were detected for 29 pairs of traits. The significant SNPs discovered in the UKB sample were supported by a joint analysis with other four independent studies (total sample size 2,192), and we performed a meta-analysis of five samples to provide GWAS summary statistics with sample size larger than 20,000. Using genome-wide polygenic risk scores prediction, up to 4.36% of phenotypic variance (p-value=2.97*10-22) in the four independent studies can be explained by the UKB GWAS results. In conclusion, our study identifies many new genetic variants at SNP, locus and gene levels and advances our understanding of the pleiotropy and genetic co-architecture between brain volumes and other traits.

genetics↗

bioRxiv2018

Large-scale neuroimaging and genetic study reveals genetic architecture of brain white matter microstructure

Microstructural changes of white matter (WM) tracts are known to be associated with various neuropsychiatric disorders/diseases. Heritability of structural changes of WM tracts has been examined using diffusion tensor imaging (DTI) in family-based studies for different age groups. The availability of genetic and DTI data from recent large population-based studies offers opportunity to further improve our understanding of genetic contributions. Here, we analyzed the genetic architecture of WM tracts using DTI and single-nucleotide polymorphism (SNP) data of unrelated individuals in the UK Biobank (n [~] 8000). The DTI parameters were generated using the ENIGMA-DTI pipeline. We found that DTI parameters are substantially heritable on most WM tracts. We observed a highly polygenic or omnigenic architecture of genetic influence across the genome as well as the enrichment of SNPs in active chromatin regions. Our bivariate analyses showed strong genetic correlations for several pairs of WM tracts as well as pairs of DTI parameters. We performed voxel-based analysis to illustrate the pattern of genetic effects on selected parts of the tract-based spatial statistics skeleton. Comparing the estimates from the UK Biobank to those from small population-based studies, we illustrated that sufficiently large sample size is essential for genetic architecture discovery in imaging genetics. We confirmed this finding with a simulation study.

genetics↗

bioRxiv2017

Heritability of regional brain volumes in large-scale neuroimaging and genetic studies

Brain genetics is an active research area. The degree to which genetic variants impact variations in brain structure and function remains largely unknown. We examined the heritability of regional brain volumes (p ~ 100) captured by single-nucleotide polymorphisms (SNPs) in UK Biobank (n ~ 9000). We found that regional brain volumes are highly heritable in this study population. We observed omni-genic impact across the genome as well as enrichment of SNPs in active chromatin regions. Principal components derived from regional volume data are also highly heritable, but the amount of variance in brain volume explained by the component did not seem to be related to its heritability. Heritability estimates vary substantially across large-scale functional networks and brain regions. The variation in heritability across regions was not related to measurement reliability. Heritability estimates exhibit a symmetric pattern across left and right hemispheres and are consistent in females and males. Our main findings in UK Biobank are consistent with those in Alzheimers Disease Neuroimaging Initiative (n ~ 1100), Philadelphia Neurodevelopmental Cohort (n ~ 600), and Pediatric Imaging, Neurocognition, and Genetics (n ~ 500) datasets, with more stable estimates in UK Biobank.

genetics↗