Biology subjects

Zheng, J.

Publications and source records attributed to Zheng, J..

At least 37 records · Page 2Linked to original sources

bioRxiv2018

Whole genome sequence analysis of 91 Salmonella Enteritidis isolates from mice caught on poultry farms in the mid 1990s

Salmonella enterica serovar Enteritidis (SE), the most commonly reported serovar of human salmonellosis, has been frequently associated with poultry farms, eggs and egg products. Mice are known vectors of SE contamination in these facilities. The objective of this study was to use whole-genome sequencing (WGS) to analyze SE from mice obtained at poultry farms in Pennsylvania. Documenting pathogen diversity can identify reliable biomarkers for rapid detection and speed up outbreak investigations. We sequenced 91 SE isolates from 83 mice (62 spleen isolates, 29 intestinal isolates) caught at 15 poultry farms between 1995-1998 using an Illumina NextSeq 500. We identified 742 single nucleotide polymorphisms (SNPs) capable of distinguishing each isolate from one another. Isolates were divided into two major clades: there were more SNPs differences within Clade B than counterparts in Clade A. All isolates containing antimicrobial resistance genes belong to Subgroup B2. Clade-defining SNPs provided biomarkers distinguishing isolates from 12 individual subgroups, which were separated by farm location or year of collection. Nonsynonymous changes from the clade-defining SNPs proffered a better understanding of possible genetic variations among these isolates. For a broader view of SE diversity, we included data from NCBI Pathogen Detection Isolates Browser, in which subgroups in Clade B formed new SNP Clusters.\n\nImportanceWGS and SNPs analyses are excellent and powerful tools for investigating SE phylogenies. Identifying the evolutionary relationships among SE isolates from mouse, poultry, environmental, and clinical isolates, along with patterns of genetic diversity, advances understanding of SE and the role mice may play in SE contamination and spread among poultry population. Our data was able to identify SE isolates from different farms or years of collection. Moreover, the annotations of clade-defining SNPs provided information about possible protein functions among these SE isolates from each subgroup. Clade-defining or farm-unique biomarkers were useful for rapid detection and outbreak investigations.

genomics↗

bioRxiv2018

Integrating Predicted Transcriptome From Multiple Tissues Improves Association Detection

Integration of genome-wide association studies (GWAS) and expression quantitative trait loci (eQTL) studies is needed to improve our understanding of the biological mechanisms underlying GWAS hits, and our ability to identify therapeutic targets. Gene-level association test methods such as PrediXcan can prioritize candidate targets. However, limited eQTL sample sizes and absence of relevant developmental and disease context restricts our ability to detect associations. Here we propose an efficient statistical method that leverages the substantial sharing of eQTLs across tissues and contexts to improve our ability to identify potential target genes: MulTiXcan. MulTiXcan integrates evidence across multiple panels while taking into account their correlation. We apply our method to a broad set of complex traits available from the UK Biobank and show that we can detect a larger set of significantly associated genes than using each panel separately. To improve applicability, we developed an extension to work on summary statistics: S-MulTiXcan, which we show yields highly concordant results with the individual level version. Results from our analysis as well as software and necessary resources to apply our method are publicly available.

genomics↗

bioRxiv2018

Preclinical Study: Sunitinib-suppressed MiR-452-5p Facilitates Renal Cancer Cell Invasion and Metastasis Through Modulating SMAD4/SMAD7/EMT Signals

Although microRNAs (miRNAs) have been revealed as crucial modulators in tumor metastasis and target therapy, our understanding of their roles in metastatic renal cell carcinoma (mRCC) and Sunitinib treatment is limited. Here, We focused on 2 published microarray data to select out our anchored miRNA which was downregulated after Sunitinib treatment while upregulated in metastasis RCC tissues. Then we discovered that treating with Sunitinib, the targeted receptor tyrosine kinase inhibitor (TKI), inhibited renal cell migration and invasion via attenuating the expression of miR-452-5p. The novel identified miR-452-5p was upregulated and associated with poor prognosis in RCC. Preclinical studies using multiple RCC cells and xenografts model illustrated that miR-452-5p could promote RCC cell migration and invasion in vitro and in vivo. Mechanistically, P65 could directly bind to the miR-452-5p promoter and thus transcriptionally induce miR-452-5p expression, which led to post-transcriptionally abrogate SMAD4 expression, thus inhibition of its downstream signals including SMAD7 and EMT (Epithelial-Mesenchymal Transition) associated genes. Our study presented a road map for targeting this newly identified miR-452-5p and its SMAD4/SMAD7/EMT signals pathway, which imparted a new potential therapeutic strategy for mRCC treatment.

cancer biology↗

bioRxiv2018

The cortical dynamics orchestrating skilled prehension

Skillful control of movement is central to our ability to sense and manipulate the world. A large body of work in nonhuman primates has demonstrated that motor cortex provides flexible, time-varying activity patterns that control the arm during reaching and grasping. Previous studies have suggested that these patterns are generated by strong local recurrent dynamics operating autonomously from inputs during movement execution. An alternative possibility is that motor cortex requires coordination with upstream brain regions throughout the entire movement in order to yield these patterns. Here, we developed an experimental preparation in the mouse to directly test these possibilities using optogenetics and electrophysiology during a skilled reach-to-grab-to-eat task. To validate this preparation, we first established that a specific, time-varying pattern of motor cortical activity was required to produce coordinated movement. Next, in order to disentangle the contribution of local recurrent motor cortical dynamics from external input, we optogenetically held the recurrent contribution constant, then observed how motor cortical activity recovered following the end of this perturbation. Both the neural responses and hand trajectory varied from trial to trial, and this variability reflected variability in external inputs. To directly probe the role of these inputs, we used optogenetics to perturb activity in the thalamus. Thalamic perturbation at the start of the trial prevented movement initiation, and perturbation at any stage of the movement prevented progression of the hand to the target; this demonstrates that input is required throughout the movement. By comparing motor cortical activity with and without thalamic perturbation, we were able to estimate the effects of external inputs on motor cortical population activity. Thus, unlike pattern-generating circuits that are local and autonomous, such as those in the spinal cord that generate left-right alternation during locomotion, the pattern generator for reaching and grasping is distributed across multiple, strongly-interacting brain regions.

neuroscience↗

bioRxiv2018

Combining high-throughput micro-CT-RGB phenotyping and genome-wide association study to dissect the genetic architecture of tiller growth in rice

Traditional phenotyping of rice tillers is time consuming and labor intensive and lags behind the rapid development of rice functional genomics. Thus, dynamic phenotyping of rice tiller traits at a high spatial resolution and high-throughput for large-scale rice accessions is urgently needed. In this study, we developed a high-throughput micro-CT-RGB (HCR) imaging system to non-destructively extract 730 traits from 234 rice accessions at 9 time points. We used these traits to predict the grain yield in the early growth stage, and 30% of the grain yield variance was explained by 2 tiller traits in the early growth stage. A total of 402 significantly associated loci were identified by GWAS, and dynamic and static genetic components were found across the nine time points. A major locus associated with tiller angle was detected at nine time points, which contained a major gene TAC1. Significant variants associated with tiller angle were enriched in the 3'-UTR of TAC1. Three haplotypes for the gene were found and tiller angles of rice accessions containing haplotype H3 were much smaller. Further, we found two loci contained associations with both vigor-related HCR traits and yield. The superior alleles would be beneficial for breeding of high yield and dense planting.\n\nHighlightCombining high-throughput micro-CT-RGB phenotyping facility and genome-wide association study to dissect the genetic architecture of rice tiller development by using the indica subpopulation.

genetics↗

bioRxiv2017

Pyk2 suppresses contextual fear memory in a kinase-independent manner

Post-traumatic stress disorder (PTSD) is a psychological illness characterized by recalling a feeling of distress when re-experiencing the original trauma-related cues. This associative fear response plays an important role in some psychiatric disorders and elucidation of the underlying mechanisms is of great importance. Here, we constructed Pyk2 null mice and found that these mutant mice showed enhancement in contextual-fear memory, but no changes in auditory-cued and spatial-referenced learning and memory. Moreover, using kinase mutant mice, we observed that Pyk2 suppressed contextual fear memory in a kinase-independent pathway. Using high-throughput RNA sequencing, we found that immediate early genes (IEGs), such as Npas4, cFos, Zif268/Egr1, Arc, and Nr4a1, were enhanced in Pyk2 null mice. We further demonstrated that Pyk2 disruption affected pyramidal neuronal complexity and spine dynamics. Thus, we demonstrated that Pyk2 is a novel fear memory suppressor molecule and Pyk2 null mice provides a model for understanding fear-related disorders.

genetics↗

bioRxiv2017

Deep-RBPPred: Predicting RNA binding proteins in the proteome scale based on deep learning

RNA binding protein (RBP) plays an important role in cell processes. Identifying RBPs by computation and experiment are both essential. Recently, RBPPred is proposed in our group to predict RBP with a high performance. However, RBPPred is too slow for that it will generate PSSM matrix as its feature. Herein, we develop a deep learning model called Deep-RBPPred. The model has three advantages comparing to previous models. 1. Deep-RBPPred only needs few physicochemical properties. 2. Deep-RBPPred runs much faster. 3. Deep-RBPPred has a good generalization ability. In the meantime, the performance is still as good as the stats-of-the-art method. In the testing in A. thaliana, S. cerevisiae and H. sapiens proteomics, MCC (AUC) are 0.6077 (0.9421), 0.573 (0.9034) and 0.8141(0.9515) respectively when the score cutoff is set to 0.5. In the verifying in Gerstberger-1538, the SN of our model is 90.38%. The running times are 9s, 7s, 8s and 10s, respectively, for H.sapiens, A.thaliana, S.cerevisiae and Gerstberger-1538 when it is tested in GPU. Deep-RBPPred forecasts 94.65% of 299 new RBP and about 8% higher sensitivity than RBPPred. We also apply deep-RBPPred in 19 eukaryotes proteomics and 11 bacteria proteomics downloaded from Uniprot. The result shows that rate of RBPs in eukaryotes proteome are much higher than bacteria proteome. Testing in 6 proteomics shows the many RBPs may be still undiscovered so far.

bioinformatics↗

bioRxiv2017

Systematic Mendelian randomization framework elucidates hundreds of genetic loci which may influence disease through changes in DNA methylation levels

We have undertaken an extensive Mendelian randomization (MR) study using methylation quantitative trait loci (mQTL) as genetic instruments to assess the potential causal relationship between genetic variation, DNA methylation and 139 complex traits. Using two-sample MR, we observed 1,191 effects across 62 traits where genetic variants were associated with both proximal DNA methylation (i.e. cis-mQTL) and complex trait variation (P<1.39x10-08). Joint likelihood mapping provided evidence that the causal mQTL for 364 of these effects across 58 traits was also likely the causal variant for trait variation. These effects showed a high rate of replication in the UK Biobank dataset for 14 selected traits, as 121 of the attempted 129 effects replicated. Integrating expression quantitative trait loci (eQTL) data suggested that genetic variants responsible for 319 of the 364 mQTL effects also influence gene expression, which indicates a coordinated system of effects that are consistent with causality. CpG sites were enriched for histone mark peaks in tissue types relevant to their associated trait and implicated genes were enriched across relevant biological pathways. Though we are unable to distinguish mediation from horizontal pleiotropy in these analyses, our findings should prove valuable in identifying candidate loci for further evaluation and help develop mechanistic insight into the aetiology of complex disease.

genetics↗

bioRxiv2017

MicrobiomeDB: a systems biology platform for integrating, mining and analyzing microbiome experiments.

MicrobiomeDB (http://microbiomeDB.org) is a data discovery and analysis platform that empowers researchers to fully leverage experimental variables to interrogate microbiome datasets. MicrobiomeDB was developed in collaboration with the Eukaryotic Pathogens Bioinformatics Resource Center (http://EuPathDB.org) and leverages the infrastructure and user interface of EuPathDB, which allows users to construct in silico experiments using an intuitive graphical strategy approach. The current release of the database integrates microbial census data with sample details for nearly 14,000 samples originating from human, animal and environmental sources, including over 9,000 samples from healthy human subjects in the Human Microbiome Project (http://portal.ihmpdcc.org/). Query results can be statistically analyzed and graphically visualized via interactive web applications launched directly in the browser, providing insight into microbial community diversity and allowing users to identify taxa associated with any experimental covariate.

microbiology↗

bioRxiv2017

Automating Mendelian randomization through machine learning to construct a putative causal map of the human phenome

A major application for genome-wide association studies (GWAS) has been the emerging field of causal inference using Mendelian randomization (MR), where the causal effect between a pair of traits can be estimated using only summary level data. MR depends on SNPs exhibiting vertical pleiotropy, where the SNP influences an outcome phenotype only through an exposure phenotype. Issues arise when this assumption is violated due to SNPs exhibiting horizontal pleiotropy. We demonstrate that across a range of pleiotropy models, instrument selection will be increasingly liable to selecting invalid instruments as GWAS sample sizes continue to grow. Methods have been developed in an attempt to protect MR from different patterns of horizontal pleiotropy, and here we have designed a mixture-of-experts machine learning framework (MR-MoE 1.0) that predicts the most appropriate model to use for any specific causal analysis, improving on both power and false discovery rates. Using the approach, we systematically estimated the causal effects amongst 2407 phenotypes. Almost 90% of causal estimates indicated some level of horizontal pleiotropy. The causal estimates are organised into a publicly available graph database (http://eve.mrbase.org), and we use it here to highlight the numerous challenges that remain in automated causal inference.

epidemiology↗

bioRxiv2017

Regulating the UAS/GAL4 system in adult Drosophila with Tet-off GAL80 transgenes

The UAS/GAL4 system is the most used method In Drosophila melanogaster for directing the expression of a gene of interest to a specific tissue. However, the ability to control the temporal activity of GAL4 with this system is very limited. This study constructed and characterized Tet-off GAL80 transgenes designed to allow temporal control of GAL4 activity in aging adults. By placing GAL80 under the control of a Tet-off promoter, GAL4 activity is regulated by the presence or absence of tetracycline in the diet. Almost complete inhibition of the expression of UAS transgenes during the pre-adult stages of the life cycle is obtained by using four copies and two types of Tet-off GAL80 transgenes. Upon treatment of newly emerged adults with tetracycline, induction of GAL4 activity is observed but the level of induction is influenced by the concentration of the inducer, the age, the sex and the anatomical location of the expression. The inhibition of GAL4 activity and the maintenance of induced expression is altered in old animals. This study reveals that the repressive ability of GAL80 is affected by the age and sex of the animal which is a major limitation to regulate gene expression with GAL80 in aged Drosophila.

genetics↗

bioRxiv2017

Resequencing the Escherichia coli genome by GenoCare single molecule sequencing platform

Next generation sequencing (NGS) has revolutionized life sciences research. Recently, a new class of third-generation sequencing platforms has arrived to meet increasing demands in the clinic, capable of directly measuring DNA and RNA sequences at the single-molecule level without amplification. Here, we use the new GenoCare single molecule sequencing platform from Direct Genomics to resequence the E. coli genome and show comparable performance to the Illumina MiSeq system. Our platform detects single-molecule fluorescence by total internal reflection microscopy, with sequencing-by-synthesis chemistry. With a consensus sequence of 99.71% nucleotide identity to that of the Illumina MiSeq systems, GenoCare was determined to be a reliable platform for single-molecule sequencing, with strong potential for clinical applications.

genomics↗

bioRxiv2017

A mouse model of necrotic biliary pancreatitis induced by combining gallstone formation and ligation of the biliary-pancreatic duct

ObjectiveThe aim of the present investigation is to develop a mouse model of biliary pancreatitis with characteristics of both gallstone formation and pancreatitis, mimicking the human etiology and pathphysiological character.\n\nDesignMale C57BL/6 mice were fed with chow, high fat/cholesterol and lithogenic diet for 12 weeks respectively. Laparotomy was done followed by ligation of pancreatic duct (PD), bile duct and pancreatic duct (BPD), or sham operation.\n\nResultsLittle or no evidence of pancreatitis was observed in PD group of mice fed with chow or high fat/cholesterol diet, or in the tail of pancreata removed from animals fed with lithogenic diet. In the head of pancreas, pancreas damage was dramatically more severe in the lithogenic group. When bile reflux was blocked by BPD, pancreas damage markedly reduced to level of chow diet group. The lithogenic diet group also developed significantly more severe multi organ dysfunction syndrome (MODS) in the lung, kidney and liver. The severity of pancreatitis is associated with persistent high bile level of cholesterol and bile acid after obstruction of the biliary-pancreatic duct. Cholesterol crystal aggravated injury of pancreatic acinar cells caused by taurocholate. After obstruction of the biliary-pancreatic duct, in the lithogenic diet group, liver Abcg8 and Cyp7a1 was up-regulated, compared to the control group.\n\nConclusionWe developed a mouse model of severe biliary pancreatitis in both local pancreas damage and MODS. This model provides a sound explanation for the Opie theory dilemma and a potential therapeutical direction in clinical practice as well.\n\nSummary statementA biliary pancreatitis has characters of both gallstone and pancreatitis, mimicking human etiology and pathophysiology, which gave a clear answer to the long time Opie theory dilemma.

pathology↗

bioRxiv2017

PhenoSpD: an atlas of phenotypic correlations and a multiple testing correction for the human phenome

BackgroundIdentifying phenotypic correlations between complex traits and diseases can provide useful etiological insights. Restricted access to individual-level phenotype data makes it difficult to estimate large-scale phenotypic correlation across the human phenome. State-of-the-art methods, metaCCA and LD score regression, provide an alternative approach to estimate phenotypic correlation using genome-wide association study (GWAS) summary statistics.\n\nResultsHere, we present an integrated R toolkit, PhenoSpD, to 1) apply metaCCA (or LD score regression) to estimate phenotypic correlations using GWAS summary statistics; and 2) to utilize the estimated phenotypic correlations to inform correction of multiple testing for complex human traits using the spectral decomposition of matrices (SpD). The simulations suggest it is possible to estimate phenotypic correlation using samples with only a partial overlap, but as overlap decreases correlations will attenuate towards zero and multiple testing correction will be more stringent than in perfectly overlapping samples. In a case study, PhenoSpD using GWAS results suggested 324.4 independent tests among 452 metabolites, which is close to the 296 independent tests estimated using true phenotypic correlation. We further applied PhenoSpD to estimated 7,503 pair-wise phenotypic correlations among 123 metabolites using GWAS summary statistics from Kettunen et al. and PhenoSpD suggested 44.9 number of independent tests for theses metabolites.\n\nConclusionPhenoSpD integrates existing methods and provides a simple and conservative way to reduce dimensionality for complex human traits using GWAS summary statistics, which is particularly valuable for post-GWAS analysis of complex molecular traits.\n\nAvailabilityR code and documentation for PhenoSpD V1.0.0 is available online (https://github.com/MRCIEU/PhenoSpD).

bioinformatics↗

bioRxiv2017

Changing geographic patterns and risk factors for avian influenza A(H7N9) infection in China

The 5th epidemic wave in 2016-2017 of avian influenza A(H7N9) virus in China caused more human cases than any previous waves but the factors that may explain the recent range expansion and surge in incidence remain unknown. We investigated the effect of anthropogenic, poultry and wetland information and of market closures on all epidemic waves (1-5). Poultry predictor variables recently became much more important than before, supporting the assumption of much wider H7N9 transmission in the chicken reservoir, that could be linked to increases in pathogenicity. We show that the future range expansion of H7N9 to northern China may translate into a higher risk of coinciding peaks with those of seasonal influenza, leading to a higher risk of reassortments. Live-poultry market closures are showed to be effective in reducing the local incidence rates of H7N9 human cases, but should be paired with other prevention and control measures to prevent transmission.

epidemiology↗

bioRxiv2017

Single Molecule Sequencing Of M13 Virus Genome Without Amplification

Third generation sequencing is a direct measurement of DNA/RNA sequences at the single molecule level without amplification. In this study, we report sequencing of the genome of the M13 virus by a new single molecule sequencing platform. Our platform detects single molecule fluorescence by the total internal reflection microscope technique, with sequencing-by-synthesis chemistry. We sequenced the genome of M13 to a depth of 316x and 100% coverage. The consensus sequence accuracy is 100%. We demonstrated that single molecule sequencing has no significant GC bias.

genomics↗

bioRxiv2017

Causal epigenome-wide association study identifies CpG sites that influence cardiovascular disease risk

The extent to which genetic influences on complex traits and disease are mediated by changes in DNA methylation levels has not been systematically explored. We developed an analytical framework that integrates genetic fine mapping and Mendelian randomization with epigenome-wide association studies to evaluate the causal relationships between methylation levels and 14 cardiovascular disease traits.\n\nWe identified 10 genetic loci known to influence proximal DNA methylation which were also associated with cardiovascular traits (P < 3.83x10-08). Bivariate fine mapping suggested that the individual variants responsible for the observed effects on cardiovascular traits at the ABO, ADCY3, ADIPOQ, APOA1 and IL6R loci were likely mediated through changes in DNA methylation. Causal effect estimates on cardiovascular traits ranged between 0.109-0.992 per standard deviation change in DNA methylation and were replicated using results from large-scale consortia.\n\nFunctional informatics suggests that the causal variants and CpG sites identified in this study were enriched for histone mark peaks in adipose tissue and gene promoter regions. Integrating our results with expression quantitative trait loci data we provide evidence that variation at these regulatory regions is likely to also influence gene expression at these loci.

epidemiology↗

bioRxiv2016

Genetic footprint of population fragmentation and contemporary collapse in a freshwater cetacean

Understanding demographic trends and patterns of gene flow in an endangered species is crucial for devising conservation strategies. Here, we examined the extent of population structure and recent evolution of the critically endangered Yangtze finless porpoise (Neophocaena asiaeorientalis asiaeorientalis). By analysing genetic variation at the mitochondrial and nuclear microsatellite loci for 148 individuals, we identified three populations along the Yangtze River, each one connected to a group of admixed ancestry. Each population displayed extremely low genetic diversity, consistent with extremely small effective size ([≤]92 individuals). Habitat degradation and distribution gaps correlated with highly asymmetric gene-flow that was inefficient in maintaining connectivity between populations. Genetic inferences of historical demography revealed that the populations in the Yangtze descended from a small number of founders colonizing the river from the sea during the last Ice Age. The colonization was followed by a rapid population split during the last millennium predating the Chinese Modern Economy Development. However, genetic diversity showed a clear footprint of population contraction over the last 50 years leaving only ~2% of the pre-collapsed size, consistent with the population collapses reported from field studies. This genetic perspective provides background information for devising mitigation strategies to prevent this species from extinction.

evolutionary biology↗