Biology subjects

Zhang, Q.

Publications and source records attributed to Zhang, Q..

At least 757 records · Page 42Linked to original sources

bioRxiv2018

An Empirical Bayes Approach for the Identification of Long-range Chromosomal Interaction from Hi-C Data

Hi-C experiments have become very popular for studying the 3D genome structure in recent years. Identification of long-range chromosomal interaction, i.e., peak detection, is crucial for Hi-C data analysis. But it remains a challenging task due to the inherent high dimensionality, sparsity and the over-dispersion of the Hi-C count data matrix. We propose EBHiC, an empirical Bayes approach for peak detection from Hi-C data. The proposed framework provides flexible over-dispersion modeling by explicitly including the 'true' interaction intensities as latent variables. To implement the proposed peak identification method (via the empirical Bayes test), we estimate the overall distributions of the observed counts semiparametrically using a smoothed EM algorithm, and the empirical null by discrete curve fitting. We conducted extensive simulations to validate and evaluate the performance of our proposed approach and applied it to real datasets. Our results suggest that EBHiC can better identify peaks than Fit-Hi-C in terms of accuracy, biological interpretability, and the consistency across biological replicates.

bioinformatics↗

bioRxiv2018

High Dimensional Mediation Analysis with Applications to Causal Gene Identification

Mediation analysis has been a popular framework for elucidating the mediating mechanism of the exposure effect on the outcome. Previous literature in causal mediation primarily focused on the classical settings with univariate exposure and univariate mediator, with recent growing interests in high dimensional mediator. In this paper, we study the mediation model with high dimensional exposure and high dimensional mediator, and introduce two procedures for mediator selection, MedFix and MedMix. MedFix is our new application of adaptive lasso with one additional tuning parameter. MedMix is a novel mediation model based on high dimensional linear mixed model, for which we also develop a new variable selection algorithm. Our study is motivated by the causal gene identification problem, where causal genes are defined as the genes that mediate the genetic effect. For this problem, the genetic variants are the high dimensional exposure, the gene expressions the high dimensional mediator, and the phenotype of interest the outcome. We evaluate the proposed methods using a mouse f2 dataset for diabetes study, and extensive real data driven simulations. We show that the mixed model based approach leads to higher accuracy in mediator selection and mediation effect size estimation, and is more reproducible across independent measurements of the response and more robust against model misspecification. The source R code will be made available on Github https://github.com/QiZhangStat/highMed upon the publication of this paper.

bioinformatics↗

bioRxiv2018

Reference genes for RT-qPCR normalisation in different tissues, developmental stages and stress conditions of Hypericum perforatum

AbstactHypericum perforatum is a widely known medicinal herb used mostly as a remedy for depression because of its abundant secondary metabolites. Quantitative real-time PCR (qRT-PCR) is an optimized method for the efficient and reliable quantification of gene expression studies. In general, reference genes are used in qRT-PCR analysis because of their known or suspected housekeeping roles. However, their expression level cannot be assumed to remain stable under all possible experimental conditions. Thus, the identification of high quality reference genes is very necessary for the interpretation of qRT-PCR data. In this study, we investigated the expression of fourteen candidate genes, including nine housekeeping genes and five potential candidate genes. Additionally, the HpHYP1 gene, belonging to the PR-10 family associated with stress control, was used for validation of the candidate reference genes. Three programs were applied to evaluate the gene expression stability across four different plant tissues, three developmental stages and a set of abiotic stress and hormonal treatments. The candidate genes showed a wide range of Ct values in all samples, indicating that they are differentially expressed. Integrating all of the algorithms and evaluations, ACT2 and TUB-{beta} were the most stable combination overall and for different developmental stages samples. Moreover, ACT2 and EF1- were considered to be the two most applicable reference genes for different tissues and for stress samples. Majority of the conventional housekeeping genes exhibited better than the potential reference genes. The obtained results will contribute to improving credibility of standardization and quantification of transcription levels in future expression research of H. perforatum.

plant biology↗

bioRxiv2018

Anatomical basis and physiological role of cerebrospinal fluid transport through the murine cribriform plate

Cerebrospinal fluid (CSF) flows through the brain, transporting chemical signals and removing waste. CSF production in the brain is balanced by a constant outflow of CSF, the anatomical basis of which is poorly understood. Here we characterized the anatomy and physiological function of the CSF outflow pathway along the olfactory sensory nerves through the cribriform plate, and into the nasal epithelia. Chemical ablation of olfactory sensory nerves greatly reduced outflow of CSF through the cribriform plate. The reduction in CSF outflow did not cause an increase in intracranial pressure (ICP), consistent with an alteration in the pattern of CSF drainage or production. Our results suggest that damage to olfactory sensory neurons (such as from air pollution) could contribute to altered CSF turnover and flow, providing a potential mechanism for neurological diseases.

neuroscience↗

bioRxiv2018

ReQTL - an allele-level measure of variation-expression genomic relationships

MotivationBy testing for association of DNA genotypes with gene expression levels, expression quantitative trait locus (eQTL) analyses have been instrumental in understanding how thousands of single nucleotide variants (SNVs) may affect gene expression. As compared to DNA genotypes, RNA genetic variation represents a phenotypic trait that reflects the actual allele content of the studied system. RNA genetic variation can be measured at expressed genome regions, and differs from the DNA genotype in sites subjected to regulatory forces. Therefore, assessment of correlation between RNA genetic variation and gene expression can reveal regulatory genomic relationships in addition to eQTLs.\n\nResultsWe introduce ReQTL, an eQTL modification which substitutes the DNA allele count for the variant allele frequency (VAF) at expressed SNV loci in the transcriptome. We exemplify the method on sets of RNA-sequencing data from human tissues obtained though the Genotype-Tissue Expression Project (GTEx) and demonstrate that ReQTL analyses show consistently high performance and sufficient power to identify both previously known and novel molecular associations. The majority of the SNVs implicated in significant cis-ReQTLs identified by our analysis were previously reported as significant cis-eQTL loci. Notably, trans ReQTL loci in our data were substantially enriched in RNA-editing sites. In summary, ReQTL analyses are computationally feasible and do not require matched DNA data, hence they have a high potential to facilitate the discovery of novel molecular interactions through exploration of the increasingly accessible RNA-sequencing datasets.\n\nAvailability and implementationSample scripts used in our ReQTL analyses are available with the Supplementary Material (ReQTL_sample_code).\n\nContacthorvatha@gwu.edu or lfspurr@gwmail.gwu.edu\n\nSupplementary InformationRe_QTL_Supplementary_Data.zip

genomics↗

bioRxiv2018

Bayesian reassessment of the epigenetic architecture of complex traits

1Epigenetic DNA modification is partly under genetic control, and occurs in response to a wide range of environmental exposures. Linking epigenetic marks to clinical outcomes may provide greater insight into underlying molecular processes of disease, assist in the identification of therapeutic targets, and improve risk prediction. Here, we present a statistical approach, based on Bayesian inference, that estimates associations between disease risk and all measured epigenetic probes jointly, automatically controlling for both data structure (including cell-count effects, relatedness, and experimental batch effects) and correlations among probes. We benchmark our approach in simulation study, finding improved estimation of probe associations across a wide range of scenarios over existing approaches. Our method estimates the total proportion of disease risk captured by epigenetic probe variation, and when we applied it to measures of body mass index (BMI) and cigarette consumption behaviour in 5,101 individuals, we find that 66.7% (95% CI 60.0-72.8) of the variation in BMI and 67.7% (95% CI 58.4-76.9) of the variation in cigarette consumption can be captured by methylation array data from whole blood, independent of the variation explained by single nucleotide polymorphism markers. We find novel associations, with smoking behaviour associated with a methylation probe at the MNDA gene with >95% posterior inclusion probability, which is a myeloid cell nuclear differentiation antigen gene previously implicated as a biomarker for inflammation and non-Hodgkin lymphoma risk. We conduct unique genome-wide enrichment analyses, identifying blood cholesterol, lipid transport and sterol metabolism pathways for BMI, and response to xenobiotic stimulus and negative regulation of RNA polymerase II promoter transcription for smoking, all with >95% posterior inclusion probability of having methylation probes with associations >1.5 times larger than the average. Finally, we improve phenotypic prediction in two independent cohorts by 28.7% and 10.2% for BMI and smoking respectively over a LASSO model. These results imply that probe measures may capture large amounts of variance because they are likely a consequence of the phenotype rather than a cause. As a result, 'omics' data may enable accurate characterization of disease progression and identification of individuals who are on a path to disease. Our approach facilitates better understanding of the underlying epigenetic architecture of complex common disease and is applicable to any kind of genomics data.

genomics↗

bioRxiv2018

OSCA: a tool for omic-data-based complex trait analysis

The rapid increase of omic data in the past decades has greatly facilitated the investigation of associations between omic profiles such as DNA methylation (DNAm) and complex traits in large cohorts. Here, we proposed a mixed-linear-model-based method (called MOMENT) that tests for association between a DNAm probe and trait with all other distal probes fitted in multiple random-effect components to account for the effects of unobserved confounders as well as the correlations between distal probes induced by the confounders. We demonstrated by simulations that MOMENT showed a lower false positive rate and more robustness than existing methods. MOMENT has been implemented in a versatile software package (called OSCA) together with a number of other implementations for omic-data-based analysis including the estimation of variance in a trait captured by all measures of multiple omic profiles, omic-data-based quantitative trait locus (xQTL) analysis, and meta-analysis of xQTL data.

bioinformatics↗

bioRxiv2018

Bacteroides fragilis defense against Cronobacter sakazakii -induced pathogenicity by regulating the intestinal epithelial barrier function and attenuating both apoptotic and pyroptotic cell death

Cronobacter sakazakii (CS), an important pathogen, is associated with the development of necrotizing enterocolitis (NEC), infant sepsis, and meningitis. Several randomized prospective clinical trials demonstrated that oral probiotics could decrease the incidence of NEC. Previously, we isolated and characterized a novel probiotic, B. fragilis strain ZY-312. However, it remains unclear how ZY-312 protects the host from the effects of CS infection. To understand the underlying mechanisms triggering the probiotic effects, we tested the hypothesis that there was a cross-talk between probiotics/probiotics-modulated microbiota and the local immune system, governed by the permeability of the intestinal mucosa using in vitro and in vivo models for the intestinal permeability. The probiotic effects of ZY-312 on intestinal epithelial cells were first examined, which revealed that ZY-312 inhibited CS invasion, CS-induced dual cell death (pyroptosis and apoptosis), and epithelial barrier dysfunction in vitro and in vivo. ZY-312 also decreased the expression of an inflammasome (NOD-like receptor family member pyrin domain-containing protein 3 (NLRP3), caspase-3, and serine protease caspase-1 in a neonatal rat model. Furthermore, ZY-312 significantly modulated the compositions of the intestinal bacterial communities, and decreased the relative abundances of Proteobacteria, Gamma proteobacteria, but increased the relative abundance of Bacteroides and Bacillus in neonatal rats. In conclusion, our findings have shown for the first time that the probiotic, B. fragilis ZY-312, suppresses CS-induced NEC by modulating the pro-inflammatory response and dual cell death (apoptosis and pyroptosis).\n\nAuthor summaryCronobacter sakazakii, a major necrotizing enterocolitis pathogen, is used as a model microorganism for the study of opportunistic bacteria in the pathogenesis of necrotizing enterocolitis. Here, we have now unequivocally demonstrated that both apoptotic and pyroptotic stimuli contribute to the pathogenesis of Cronobacter sakazakii -induced necrotizing enterocolitis. Previously, we isolated and characterized a novel probiotic, B. fragilis strain ZY-312. We found that the ZY-312 defense against Cronobacter sakazakii-induced necrotizing enterocolitis by inhibiting Cronobacter sakazakii invasion, epithelial barrier dysfunction, the expression of inflammatory cytokines and dual cell death (pyroptosis and apoptosis). This study demonstrates the utility of ZY-312 as a promising probiotic agent for the prevention and treatment of various intestinal diseases, including NEC.

microbiology↗

bioRxiv2018

Genomic Bayesian confirmatory factor analysis and Bayesian network to characterize a wide spectrum of rice phenotypes

Drawing biological inferences from large data generated to dissect the genetic basis of complex traits remains a challenge. Since multiple phenotypes likely share mutual relationships, elucidating the interdependencies among economically important traits can accelerate the genetic improvement of plants and animals. A Bayesian network depicts a probabilistic directed acyclic graph representing conditional dependencies among variables. This study aims to characterize various phenotypes in rice (Oryza sativa) via confirmatory factor analysis and Bayesian network. Confirmatory factor analysis under the Bayesian treatment hypothesized that 48 observed phenotypes resulted from six latent variables including grain morphology, morphology, flowering time, physiology (e.g., ion content), yield, and morphological salt response. This was followed by studying the genetics of each latent variable. Bayesian network structures involving the genomic component of six latent variables were established by fitting four different algorithms. Negative genomic correlations were obtained between salt response and yield, salt response and grain morphology, salt response and physiology, and morphology and yield, whereas a positive correlation was obtained between yield and grain morphology. There were four common directed edges across the different Bayesian networks. Physiological components influenced the flowering time and grain morphology, and morphology and 4 grain morphology influenced yield. This work suggests that the Bayesian network coupled with factor analysis can provide an effective approach to understand the interdependence patterns among phenotypes and to predict the potential influence of external interventions or selection related to target traits in the high-dimensional interrelated complex traits systems.

genetics↗

bioRxiv2018

Oxytocin amplifies sex differences in human mate choice

Infidelity is the major cause of breakups and individuals with a history of infidelity are more likely to repeat it, but may also present a greater opportunity for short-term sexual relationships. Here in a pre-registered, double-blind study involving 160 subjects we report that while both sexes valued faithful individuals most for long-term relationships, both single men and those in a relationship were more interested in having short-term relationships with previously unfaithful individuals than women. Oxytocin administration resulted in men rating the faces of unfaithful women as more attractive but in women rating those of unfaithful men as less attractive and also finding them less memorable. Oxytocin also increased mens interest in having short-term relationships with previously unfaithful women whereas it increased womens interest in having long-term relationships with faithful men. Thus, oxytocin release during courtship may first act to amplify sex-dependent priorities in attraction and mate choice before subsequently promoting romantic bonds.

neuroscience↗

bioRxiv2018

Trajectories of inflammatory biomarkers over the eighth decade and their associations with immune cell counts and epigenetic ageing

BACKGROUNDEpigenetic age acceleration (an older methylation age compared to chronological age) correlates strongly with various age-related morbidities and mortality. Chronic systemic inflammation is thought to be a hallmark of ageing but the relationship between an increased epigenetic age and this likely key phenotype of ageing has not yet been extensively investigated.\n\nMETHODSWe modelled the trajectories of the inflammatory biomarkers C-reactive protein (CRP; measured using both a high- and low-sensitivity assay), and interleukin-6 (IL-6) over the 8th decade in the Lothian Birth Cohort 1936. We additionally investigated the association between CRP and imputed leukocyte counts. Using linear mixed models we examined the cross-sectional and longitudinal association between the inflammatory biomarkers and two measures of epigenetic age acceleration, derived from the Horvath and Hannum epigenetic clocks.\n\nRESULTSLow-sensitivity CRP declined, high-sensitivity CRP did not change, and IL-6 increased over time. CRP levels inversely associated with total counts of CD8+T cells and CD4+T cells, and positively associated with senescent CD8+T cells, plasmablasts and granulocytes. Cross-sectionally, the Hannum, but not the Horvath, measure of age acceleration was positively associated with low-sensitivity CRP, high-sensitivity CRP, IL-6 and a restricted measure of CRP ([≤]10mg/L) likely reflecting levels relevant to chronic inflammation.\n\nCONCLUSIONSWe found a divergent relationship between inflammation and immune system parameters in older age. We additionally report the Hannum measure of epigenetic age acceleration associated with an elevated inflammatory profile cross-sectionally, but not longitudinally.

epidemiology↗

bioRxiv2018

Regulation by HSP70/90 in the different tissues and testis development of male cattle (Cattle-yak and Yak)

HSP70/90 play important role in testis develop and spermatozoa regulation, but the contact of HSP70/90 with infertility in cattle is unclear. Here, we focus on male cattle-yak and yak, which to investigate the expression and localization of HSP70/90 in different tissues, and explore the influence of HSP70/90 to infertility. In our study, a total of 54 cattle (24 cattle-yak and 30 yak) were examined. The HSP90 mRNA of cattle-yak was cloned first and found amino acid variation in HSP90, which led to difference at protein spatial structure compare with yak. To investigate whether the expression of HSP70/90 mRNA and protein are different in cattle-yak and yak, we used real-time quantitative PCR (qRT-PCR) and Western blot (WB) to examine them. We found that the expression level of HSP70/90 mRNA and protein are disparity in different tissues and testis development stages, and obviously high expression was observed in testicle during juvenile and adult, Moreover, it s interestingly in which the HSP70 expression is significant high in yak whereas HSP90 in cattle-yak (P<0.01). On this bases, we detect the location of HSP70/90 in testis by immunohistochemical (IHC) and immunofluorescence (IF), the results demonstrate that HSP70/90 were located in the epithelial cells, spermatogenic cells and mesenchymal cells. In summary, our study proved the expression of HSP70/90 are different in tissues, and the expression of HSP90 is obviously high in testis of cattle-yak, which propose that the infertility of cattle-yak may cause from up-regulating of HSP90.

biochemistry↗

bioRxiv2018

TP promotes malignant progression in hepatocellular carcinoma through pentose Warburg effect

Tumor progression is dependent on metabolic reprogramming. Metastasis and vasculogenic mimicry (VM) are typical tumor progression. The relationship of metastasis, VM and metabolic reprogramming is not clear. In this study, we identified the novel role of Twist1, a VM regulator, in the transcriptional regulation of the expression of thymidine phosphorylase (TP). We demonstrated that TP promoted extracellular thymidine metabolization into ATP and amino acids through pentose Warburg effect by coupling the pentose phosphate pathway and glycolysis. Moreover, Twist1 relied on TP-induced metabolic reprogramming to promote hepatocellular carcinoma (HCC) metastasis and VM formation mediated by VE-Cad, VEGFR1, and VEGFR2 in vitro and in vivo. TP inhibitor tipiracil reduced promotion effect of TP enzyme activity on HCC VM formation and metastasis. Our findings demonstrate that TP, transcriptionally activated by Twist1, promotes HCC VM formation and metastasis through pentose Warburg effect, contributing to tumor progression.

cell biology↗

bioRxiv2018

ROCK1/Drp1-mediated aberrant mitochondrial fission is crucial for dopaminergic nerve cell apoptosis

Dopamine deficiency caused by apoptosis of the dopaminergic nerve cells in the midbrain substantia nigra is the main pathological basis of Parkinson's disease (PD). Recent research has shown that dynamin-related protein 1 (Drp1)-mediated aberrant mitochondrial fission plays an important role in dopaminergic nerve cell apoptosis. However, the upstream regulatory mechanism remains unclear. Our study shows that knockdown of Drp1 blocked aberrant mitochondrial fission and dopaminergic nerve cell apoptosis. Importantly, we found that ROCK1 was activated in an MPP+-induced PD cell model and that ROCK1 knockdown and the specific ROCK1 activation inhibitor Y-27632 blocked Drp1-mediated aberrant mitochondrial fission and apoptosis of dopaminergic nerve cell through suppression of Drp1 dephosphorylation/activation. Our in vivo study confirmed that Y-27632 significantly improved symptoms of a PD mouse model through inhibition of Drp1-mediated aberrant mitochondrial fission and apoptosis of dopaminergic nerve cell. Collectively, Our study suggests an important molecular mechanism of PD pathogenesis involving ROCK1-regulated dopaminergic nerve cell apoptosis via activation of Drp1-induced aberrant mitochondrial fission.

neuroscience↗

bioRxiv2018

Temporal Gene Coexpression Network Analysis Using A Low-rank plus Sparse Framework

Various gene network models with distinct physical nature have been widely used in biological studies. For temporal transcriptomic studies, the current dynamic models either ignore the temporal variation in the network structure or fail to scale up to a large number of genes due to severe computational bottlenecks and sample size limitation. On the other hand, correlation-based gene networks are more computationally more affordable, but have not been properly extended to gene expression time-course data.\n\nWe propose Temporal Gene Coexpression Network (TGCN) for the transcriptomic time-course data. The mathematical nature of TGCN is the joint modeling of multiple covariance matrices across time points using a \"low-rank plus sparse\" framework, in which the network similarity across time points is explicitly modeled in the low-rank component. Using both simulations and a real data application, we showed that TGCN improved the covariance estimation loss and identified more robust and interpretable gene modules.

bioinformatics↗

bioRxiv2018

A computational protocol to characterize elusive Candidate Phyla Radiation bacteria in oral environments using metagenomic data

Several studies have documented the diversity and potential pathogenic associations of organisms in the human oral cavity. Although much progress has been made in understanding the complex bacterial community inhabiting the human oral cavity, our understanding of some microorganisms is less resolved due to a variety of reasons. One such little-understood group is the candidate phyla radiation (CPR), which is a recently identified, but highly abundant group of ultrasmall bacteria with reduced genomes and unusual ribosomes. Here, we present a computational protocol for the detection of CPR organisms from metagenomic data. Our approach relies on a self-constructed dataset comprising published CPR genomic sequences as a filter to identify CPR sequences from metagenomic sequencing data. After assembly and functional prediction, the taxonomic affiliation of CPR contigs can be identified through phylogenetic analysis with publically available 16S rRNA gene and ribosomal proteins, in addition to sequence similarity analyses (e.g., average nucleotide identity calculations and contig mapping). Using this protocol, we reconstructed two draft genomes of organisms within the TM7 superphylum, that had genome sizes of 0.594 Mb and 0.678 Mb. Among the predicted functional genes of the constructed genomes, a high percentage were related to signal transduction, cell motility, and cell envelope biogenesis, which could contribute to cellular morphological changes in response to environmental cues.\n\nImportanceCandidate phyla radiation (CPR) bacterial group is a recently identified, but highly diverse and abundant group of ultrasmall bacteria exhibiting reduced genomes and limited metabolic capacities. A number of studies have reported their potential pathogenic associations in multiple mucosal diseases including periodontitis, halitosis, and inflammatory bowel disease. However, CPR organisms are difficult to cultivate and are difficult to detect with PCR-based methods due to divergent genetic sequences. Thus, our understanding of CPR has lagged behind that of other bacterial component. Here, we used metagenomic approaches to overcome these previous barriers to CPR identification, and established a computational protocol for detection of CPR organisms from metagenomic samples. The protocol describe herein holds great promise for better understanding the potential biological functioning of CPR. Moreover, the pipeline could be applied to other organisms that are difficult to cultivate.

bioinformatics↗

bioRxiv2018

Using LASSO in gene co-expression network for genome-wide identification of gene interactions responding to salt stress in rice

In many applications, such as gene co-expression network analyses, data arises with a huge number of covariates while the size of sample is comparatively small. To improve the accuracy of prediction, variable selection is often used to get a sparse solution by forcing coefficients of variables contributing less to the observed response variable to zero. Various algorithms were developed for variable selection, but LASSO is well known for its statistical accuracy, computational feasibility and broad applicability to adaptation. In this project, we applied LASSO to the gene co-expression network of rice with salt stress to discover key gene interactions for salt-tolerance related phenotypes. The dataset we have is a high-dimensional one, having 50K genes from 100 samples, with the issue of multicollinearity for fitting linear regression - the expression level of genes in the same pathway tends to be highly correlated. The property of LASSO with sparse parameters is naturally suitable to identify gene interactions of interest in this dataset. After biologically functional modules in the co-expression network was identified, the major changed expression patterns were further selected by LASSO regression to establish a linear relationship between gene expression profiles and physiological responses, such as sodium/potassium condenses, with salt stress. Five modules of intensively co-expressed genes, from 45 to 291 genes, were identified by our method with significant P-values, which indicate these modules are significantly associated with physiological responses to stress. Genes in these modules have functions related to ion transport, osmotic adjustment, and oxidative tolerance. For example, LOC_Os7g47350 and LOC_Os07g37320 are co-expressed gene in the same module 15. Both are ion transporter genes and have higher gene expression levels for rice with low sodium levels with salt stress.

bioinformatics↗

bioRxiv2018

An Organometallic Ir(III) Molecular Probe for Imaging Microtubules in Fluorescence and Electron Microscopy

We report a versatile cyclometalated Iridium (III) complex probe that achieves synchronous fluorescence-electron microscopy correlation to reveal microtubule ultrastructure in cells. The selective insertion of probe between repeated and {beta} units of microtubule triggers remarkable fluorescent enhancement, and high TEM contrast due to the presence of heavy Ir ions. The highly photostable probe allows live cell imaging of tubulin localization and motion during cell division with an resolution of 20 nm, and under TEM imaging reveals the {beta} unit interspace of 45[A] of microtubule in cells.

cell biology↗