Biology subjects

Zhang, C.

Publications and source records attributed to Zhang, C..

At least 1,009 records · Page 56Linked to original sources

bioRxiv2018

Unraveling the genetic architecture of grain size in einkorn wheat through linkage and homology mapping, and transcriptomic profiling

HighlightGenome-wide linkage and homology mapping revealed 17 genomic regions through a high-density einkorn wheat genetic map constructed using RAD-seq, and transcription levels of 20 candidate genes were explored using RNA-seq.\n\nAbstractUnderstanding the genetic architecture of grain size is a prerequisite to manipulate the grain development and improve the yield potential in crops. In this study, we conducted a whole genome-wide QTL mapping of grain size related traits in einkorn wheat by constructing a high-density genetic map, and explored the candidate genes underlying QTL through homologous analysis and RNA sequencing. The high-density genetic map spanned 1873 cM and contained 9937 SNP markers assigned to 1551 bins in seven chromosomes. Strong collinearity and high genome coverage of this map were revealed with the physical maps of wheat and barley. Six grain size related traits were surveyed in five agro-climatic environments with 80% or more broad-sense heritability. In total, 42 QTL were identified and assigned to 17 genomic regions on six chromosomes and accounted for 52.3-66.7% of the phenotypic variations. Thirty homologous genes involved in grain development were located in 12 regions. RNA sequencing provided 4959 genes differentially expressed between the two parents. Twenty differentially expressed genes involved in grain size development and starch biosynthesis were mapped to nine regions that contained 26 QTL, indicating that the starch biosynthesis pathway played a vital role on grain development in einkorn wheat. This study provides new insights into the genetic architecture of grain size in einkorn wheat, the underlying genes enables the understanding of grain development and wheat genetic improvement, and the map facilitates the mapping of quantitative traits, map-based cloning, genome assembling and comparative genomics in wheat taxa.

genetics↗

bioRxiv2018

Analysis of Local Variability and Allostery in Macromolecular Assemblies using Cryo-EM and Focused Classification

Single-particle electron cryo-microscopy and computational image classification can be used to analyze structural variability in macromolecules and their assemblies. In some cases, a particle may contain different regions that each display a range of distinct conformations. We have developed strategies, implemented within the Frealign and cisTEM image processing packages, to focus classify on specific regions of a particle and detect potential covariance. The strategies are based on masking the region of interest using either a 2-D mask applied to reference projections and particle images, or a 3-D mask applied to the 3-D volume. We show that focused classification approaches can be used to study structural allostery, a concept that is likely to gain more importance as datasets grow in size, allowing the distinction of more structural states and smaller differences between states. Finally, we apply the approaches to an experimental dataset containing the HIV-1 Transactivation Response (TAR) element RNA fused into the large bacterial ribosomal subunit, to deconvolve structural mobility within localized regions of interest.\n\nHighlightsO_LIDescription of different image classification strategies in single-particle cryo-EM\nC_LIO_LIQuantitative evaluation of two classification methods using simulated data\nC_LIO_LIApplication of the two classification methods to an experimental dataset\nC_LI

biophysics↗

bioRxiv2018

Quantitative Real-Time Imaging of Glutathione with Sub-Cellular Resolution

Quantitative imaging of glutathione with high spatial and temporal resolution is essential for studying the roles of glutathione in redox biology. We developed a fluorescent glutathione probe--HaloRT--that targets organelles of interest through expressing organelle-specific HaloTag proteins. Using HaloRT, we quantitatively measure the glutathione concentrations in the nucleus and the cytosol and find no appreciable concentration gradient between these two organelles, challenging the view of nuclear compartmentalization of glutathione.

cell biology↗

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

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

Bayesian tip dating reveals heterogeneous morphological clocks in Mesozoic birds

Recently, comprehensive morphological datasets including nearly all the well-recognized Mesozoic birds become available, making it feasible for statistically rigorous methods to unveil finer evolutionary patterns during early avian evolution. However, few quantitative and statistical studies have yet been performed. Here, we exploited the advantage of Bayesian tip dating under relaxed morphological clocks to infer both the divergence times and evolutionary rates while accounting for their uncertainties. We further subdivided the characters into six body regions (i.e., skull, axial skeleton, pectoral girdle and sternum, forelimb, pelvic girdle, and hindlimb) to assess evolutionary rate heterogeneity both along the lineages and across partitions. We observed extremely high rates of morphological character changes during early avian evolution and the clock rates are quite heterogeneous among the six regions. The branch subtending Pygostylia shows extremely high rate in the axial skeleton, while the branches subtending Ornithothoraces and Enantiornithes show very high rates in the pectoral girdle and sternum, and moderately high rates in the forelimb. The extensive modifications in these body regions largely correspond to refinement of the flight capability. The rest of the relatively slow and even rates suggest that there is no dominant selective pressure in favoring of modifications in the skull and pelvis. This study reveals the power and flexibility of Bayesian tip dating implemented in MrBayes to investigate evolutionary dynamics in deep time.

evolutionary biology↗

bioRxiv2018

Inference of species histories in the presence of gene flow

When populations become isolated, members of these populations can diverge genetically over time. This leads to genetic differences between these populations that increase over time if the isolation persists. This process can be counteracted by gene flow, i.e. when genes are exchanged between populations. In order to study the speciation processes when gene flow is present, isolation-with-migration methods have been developed. These methods typically assume that the ranked topology of the species history is already known. However, this is often not the case and the species tree is therefore of interest itself. For the inference of species trees, it is in turn often necessary to assume that there is no gene flow between co-existing species. This assumption, however, can lead to wrongly inferred speciation times and species tree topologies. We here introduce a new method that allows inference of the species tree while explicitly modelling the flow of genes between coexisting species. By using Markov chain Monte Carlo sampling, we co-infer the species tree alongside evolutionary parameters of interest. By using simulations, we show that our newly introduced approach is able to reliably infer the species trees and parameters of the isolation-with-migration model from genetic sequence data. We then use this approach to infer the species history of the mosquitoes from the Anopheles gambiae species complex. Accounting for gene flow when inferring the species history suggests a slightly different speciation order and gene flow than previously suggested.

evolutionary biology↗

bioRxiv2018

Identification of genes affecting saturated fat acid content in Elaeis guineensis by genome-wide association analysis

Oil palm is the highest yielding oil crop per unit area worldwide. Unfortunately, palm oil is often considered unhealthy. In particular, palmic acid (C16:0) is a major component of palm oil. In this study a total of 1 261 501 SNP markers were produced in a diversity panel of 200 oil palm individuals. Oil content in this population varied from 29.8% to 70.3%, palmic acid varied from 31.3% to 48.8%, and oleic acid varied from 31.3% to 50.1%. We identified 274 SNP markers significantly associated with fatty acid compositions; 44 candidate genes in the flanking regions of these SNPs were involved in fatty acid biosynthesis and metabolism. Among them, two acyl-ACP thioesterase B genes had differential expression patterns between the mesocarp and kernel, tissues which show different oil profiles in oil palm (high palmic acid and high lauric acid respectively). Overexpression of both genes caused a significant increase in palmic acid content, while overexpression of the EgFatB2 gene also caused an accumulation of lauric acid and myristic acid. Our research provides genome-wide SNPs, a set of markers significantly associated with fatty acid content, and validated candidate genes for future targeted breeding of lower saturated fat content in palm oil.

plant biology↗

bioRxiv2018

Trio deep-sequencing does not reveal unexpected mutations in Cas9-edited monkeys

CRISPR-Cas9 is a widely-used genome editing tool, but its off-target effect remains a concern, especially in view of future clinical applications. Non-human primates (NHPs) share close genetic and physiological similarities with humans, making them an ideal preclinical model for developing Cas9-based therapies. However, no comprehensive in vivo off-target assessment has been conducted in NHPs. Here we performed whole genome trio sequencing of Cas9-treated monkeys. We found they only carried a small number of de novo mutations that can be explained by expected spontaneous mutations, and no unexpected mutations were detected.

bioengineering↗

bioRxiv2018

Using molecular ecological network analysis to explore the effects of chemotherapy on intestinal microbial communities of colorectal cancer patients

Intestinal microbiota is now widely known to be key roles in the nutrition uptake, metabolism, and the regulation of human immune responses. However, we do not know how changes the intestinal microbiota in response to the chemotherapy. In this study, we used network-based analytical approaches to explore the effects of five stages of chemotherapy on the intestinal microbiota of colorectal cancer patients. The results showed that chemotherapy greatly reduced the alpha diversity and changed the specie-specie interaction networks of intestinal microbiota, proved by the network size, network connectivity and modularity. The OTU167 and OTU8 from the genus Fusobacterium and Bacteroides were identified as keystone taxa by molecular ecological networks in the first two stages of chemotherapy, and were significantly correlated with tumor makers (P < 0.05). Five stages of chemotherapy did not make the intestinal micro-ecosystem regain a steady state, because of the lower alpha diversity and more complicated ecological networks compared to the healthy individuals. Furthermore, combing the changes of ecological networks with the tumor markers, the intestinal microbiota was closely linked with clinical chemotherapeutic effects.\n\nImportanceA deeply understanding of the role of intestinal microbiota contributes to help us find path forward for improving the prognosis of colorectal cancer patients. In addition, diet or probiotics interventions will be a possible attempt to improve the clinical chemotherapeutic effects for colorectal cancer patients.

microbiology↗

bioRxiv2018

Characterization of novel inhibition of indoleamine 2,3-dioxygenase by targeting its apo form.

Indoleamine-2,3-dioxygenase 1 (IDO1) is a heme-containing enzyme that catalyzes the rate-limiting step in the kynurenine pathway of tryptophan (TRP) metabolism. As an inflammation-induced immunoregulatory enzyme, pharmacological inhibition of IDO1 activity is currently being pursued as a potential therapeutic tool for the treatment of cancer and other disease states. As such, a detailed understanding of the mechanism of action of established and novel IDO1 inhibitors remains of great interest. Comparison of a newly-developed IDO1 inhibitor (GSK5628) to the existing best-in-class compound, epacadostat (Incyte), allows us to report on a unique inhibition mechanism for IDO1. Here, we demonstrate that GSK5628 inhibits IDO1 by competing with heme for binding to a heme-free conformation of the enzyme (apo-IDO1) while epacadostat coordinates its binding with the iron atom of the IDO1 heme cofactor. Comparison of these two compounds in cellular systems reveals a long-lasting inhibitory effect of GSK5628, undescribed for other known IDO1 inhibitors. Detailed characterization of this apo-binding mechanism for IDO1 inhibition may help design superior inhibitors or may confer a unique competitive advantage over other IDO1 inhibitors vis-a-vis specificity and pharmacokinetic parameters.

biochemistry↗

bioRxiv2018

Robust associative learning is sufficient to explain structural and dynamical properties of local cortical circuits

The ability of neural networks to associate successive states of network activity lies at the basis of many cognitive functions. Hence, we hypothesized that many ubiquitous structural and dynamical properties of local cortical networks result from associative learning. To test this hypothesis, we trained recurrent networks of excitatory and inhibitory neurons on memory sequences of varying lengths and compared network properties to those observed experimentally. We show that when the network is robustly loaded with near-maximum amount of associations it can support, it develops properties that are consistent with the observed probabilities of excitatory and inhibitory connections, shapes of connection weight distributions, overrepresentations of specific 3-neuron motifs, distributions of connection numbers in clusters of 3-8 neurons, sustained, irregular, and asynchronous firing activity, and balance of excitation and inhibition. What is more, memories loaded into the network can be retrieved even in the presence of noise comparable to the baseline variations in the postsynaptic potential. Confluence of these results suggests that many structural and dynamical properties of local cortical networks are simply a byproduct of associative learning.

neuroscience↗

bioRxiv2018

Structural basis for the RNA-guided ribonuclease activity of CRISPR-Cas13d

CRISPR-Cas endonucleases directed against foreign nucleic acids mediate prokaryotic adaptive immunity and have been tailored for broad genetic engineering applications. Type VI-D CRISPR systems contain the smallest known family of single effector Cas enzymes, and their signature Cas13d ribonuclease employs guide RNAs to cleave matching target RNAs. To understand the molecular basis for Cas13d function, we resolved cryo-electron microscopy structures of Cas13d-guide RNA binary complex and Cas13d-guide-target RNA ternary complex to 3.4 and 3.3 [A] resolution, respectively. Furthermore, a 6.5 [A] reconstruction of apo Cas13d combined with hydrogen-deuterium exchange revealed conformational dynamics that have implications for RNA scanning. These structures, together with biochemical and cellular characterization, explain the compact molecular architecture of Cas13d and provide insights into the structural transitions required for enzyme activation. Our comprehensive analysis of Cas13d in diverse enzymatic states facilitated site-specific truncations for minimal size and delineates a blueprint for improving biomolecular applications of RNA targeting.

biochemistry↗

bioRxiv2018

Germline genetics encode the resistance, risk, and lymphatic metastasis of triple-negative breast cancer in the southern Chinese population

Early identification of the risk for triple-negative breast cancer (TNBC) at the asymptomatic phase could lead to better prognosis. Here we developed a machine learning method to quantify systematic impact of all rare germline mutations on each pathway. We collected 106 TNBC patients and 287 elder healthy women controls. The spectra of activity profiles in multiple pathways were mapped and most pathway activities exhibited globally suppressed by the portfolio of individual germline mutations in TNBC patients. Accordingly, all individuals were delineated into two types: A and B. Type A patients could be differentiated from controls (AUC = 0.89) and sensitive to BRCA1/2 damages; Type B patients can be also differentiated from controls (AUC = 0.69) but probably being protected from BRCA1/2 damages. Further we found that Individuals with the lowest activity of selected pathways had extreme high relative risk (up to 21.67 in type A) and increased lymph node metastasis in these patients. Our study showed that genomic DNA contains information of unimaginable pathogenic factors. And this information is in a distributed form that could be applied to risk assessment for more cancer types. SignificanceWe identified individuals who are more susceptible to triple negative breast cancer. Our method performs much better than previous assessments based on BRCA1/2 damages, even polygenic risk scores. We disclosed previously unimaginable pathogens in a distributed form on genome and extended risk prediction to scenarios for other cancers.

cancer biology↗

bioRxiv2018

Pharmacological modulation of AMPA receptor surface diffusion restores hippocampal synaptic plasticity and memory in Huntington’s disease

Impaired hippocampal synaptic plasticity is increasingly considered to play an important role in cognitive impairment in Huntingtons disease (HD). However, the molecular basis of synaptic plasticity defects is not fully understood. Combining live-cell nanoparticle tracking and super-resolution imaging, we show that dysregulation of AMPA receptors (AMPARs) surface diffusion represents a molecular basis underlying the aberrant hippocampal synaptic plasticity during HD. AMPARs surface diffusion is increased in various HD neuronal models, which results in the failure of AMPARs surface stabilization after long-term potentiation (LTP) stimuli. This appears to result from a defective brain-derived neurotrophic factor (BDNF) - tyrosine receptor kinase B (TrkB) - Ca2+/calmodulin-dependent protein kinase II (CaMKII) signaling pathway that impacts the interaction between the AMPAR auxiliary subunit stargazin and postsynaptic density protein 95 (PSD-95). Notably, the disturbed AMPAR surface diffusion is rescued, via BDNF signaling pathway and by the antidepressant tianeptine. Tianeptine also restores the impaired LTP and hippocampus-dependent memory as well as anxiety/depression-like behavior in different HD mouse models. We thus unveil a mechanistic framework underlying hippocampal synaptic and memory dysfunction and propose a new perspective in HD treatment by targeting AMPAR surface diffusion.

neuroscience↗

bioRxiv2018

Linear-double-stranded DNA (ldsDNA) based AND logic computation in mammalian cells

Synthetic biology employs engineering principles to redesign biological system for clinical or industrial purposes. The development and application of novel genetic devices for genetic circuits construction will facilitate the rapid development of synthetic biology. Here we demonstrate that mammalian cells could perform two- and three-input linear-double-stranded DNA (ldsDNA) based Boolean AND logic computation. Through hydrodynamic ldsDNA delivery, two-input ldsDNA-base AND-gate computation could be achieved in vivo. Inhibition of DNA-PKcs expression, a key enzyme in non-homologous end joining (NHEJ), could significantly downregulate the intensity of output signals from ldsDNA-based AND-gate. We further reveal that in mammalian cells ldsDNAs could undergo end processing and then perform AND-gate calculation to generate in-frame output proteins. Moreover, we show that ldsDNAs or plasmids with identical overlapping sequences could also serve as inputs of AND-gate computation. Our work establishes novel genetic devices and principles for genetic circuits construction, thus may open a new gate for the development of new disease targeting strategies and new protein genesis methodologies.

synthetic biology↗

bioRxiv2018

Characterisation of carried and invasive Neisseria meningitidis isolates in Shanghai, China from 1950 to 2016: implications for serogroup B vaccine implementation

BackgroundSerogroup B invasive meningococcal disease (IMD) is increasing in China, little is known however, about these meningococci. This study characterises a collection of isolates associated with IMD and carriage in Shanghai and assesses current vaccine strategies.\n\nMethodsIMD epidemiological data in Shanghai from 1950-2016 were obtained from the National Notifiable Diseases Registry System, with 460 isolates collected for analysis including, 169 from IMD and 291 from carriage. Serogroup B meningococcal (MenB) vaccine coverage was evaluated using Bexsero(R) Antigen Sequence Type (BAST).\n\nResultsSeven IMD epidemic periods have been observed in Shanghai since 1950, with incidence peaking from February to April. Analyses were divided according to the period of meningococcal polysaccharide vaccine (MPV) introduction: (i) pre-MPV-A, 1965-1980; (ii) post-MPV-A, 1981-2008; and (iii) post-MPV-A+C, 2009-2016. IMD incidence decreased from 55.4/100,000 to 0.71 then to 0.02, and corresponded with shifts from serogroup A ST-5 complex (MenA:cc5) to MenC:cc4821 then MenB:cc4821. MenB IMD became predominant (63.2%) in the post-MPV-A+C period, of which 50% were caused by cc4821, with the highest incidence in infants (0.45/100,000) and a case-fatality rate of 9.5%. IMD was positively correlated with carriage rates. Data indicate that fewer than 25% of MenB isolates in the post-MPV-A+C period may be covered by the vaccines Bexsero(R), Trumenba(R), or a PorA-based vaccine, NonaMen.\n\nConclusionsA unique IMD epidemiology is found in China, changing periodically from hyperepidemic to low-level endemic disease. MenB IMD now dominates in Shanghai, with isolates harbouring diverse antigenic variants potentially beyond coverage with licenced OMV- and protein-based MenB vaccines.\n\nSummaryMeningococcal disease in Shanghai, China is described and current vaccine approaches evaluated. Since 1950, MenA:cc5 shifted to MenC:cc4821 then MenB:cc4821, with MenB dominating since 2009. Distinct antigens potentially beyond coverage with licensed OMV- and protein-based MenB vaccines were found.

epidemiology↗

bioRxiv2018

Acidic microenvironment shaped by lactate accumulation promotes pluripotency through multiple mechanisms

Enhanced glycolysis is a distinct feature associated with numerous stem cells and cancer cells. However, little is known about its regulatory roles in gene expression and cell fate determination. Here we show that acidic environment shaped by lactate accumulation promotes the self-renewal and pluripotency of both mouse and human embryonic stem cells (ESCs). Mechanistically, acidic pH reduces the tri-methylation of H3K27 globally at transcriptional start sites to partially prevent ESC differentiation. In addition, acidic pH stabilizes a large number of mRNAs including pluripotency genes. Furthermore, we found that AGO1 protein is downregulated at acidic conditions, leading to the de-repression of a subset of microRNA targets in low-pH treated ESCs. Altogether, our study provides insights into mechanisms whereby acidic microenvironment produced by enhanced glycolysis regulates gene expression to determine cell fate and has broad implications in the fields of regenerative medicine and cancer biology.

developmental biology↗