Biology subjects

Wang, C.

Publications and source records attributed to Wang, C..

At least 1,081 records · Page 60Linked to original sources

bioRxiv2018

Cell-to-cell variation in defective virus expression and effects on host responses during influenza virus infection

Virus and host factors contribute to cell-to-cell variation in viral infections and determine the outcome of the overall infection. However, the extent of the variability at the single cell level and how it impacts virus-host interactions at a systems level are not well understood. To characterize the dynamics of viral transcription and host responses, we used single-cell RNA sequencing to quantify at multiple time points the host and viral transcriptomes of human A549 cells and primary bronchial epithelial cells infected with influenza A virus. We observed substantial variability of viral transcription between cells, including the accumulation of defective viral genomes (DVGs) that impact viral replication. We show a correlation between DVGs and viral-induced variation of the host transcriptional program and an association between differential induction of innate immune response genes and attenuated viral transcription in subpopulations of cells. These observations at the single cell level improve our understanding of the complex virus-host interplay during influenza infection.\n\nIMPORTANCEDefective influenza virus particles generated during viral replication carry incomplete viral genomes and can interfere with the replication of competent viruses. These defective genomes are thought to modulate disease severity and pathogenicity of the influenza infection. Different defective viral genomes also introduce another source of variation across a heterogeneous cell population. Evaluating the impact of defective virus genomes on host cell responses cannot be fully resolved at the population level, requiring single cell transcriptional profiling. Here we characterized virus and host transcriptomes in individual influenza-infected cells, including that of defective viruses that arise during influenza A virus infection. We established an association between defective virus transcription and host responses and validated interfering and immunostimulatory functions of identified dominant defective virus genome species in vitro. This study demonstrates the intricate effects of defective viral genomes on host transcriptional responses and highlights the importance of capturing host-virus interactions at the single-cell level.

microbiology↗

bioRxiv2018

Alternative hydrogen uptake pathways suppress methane production in ruminants

Farmed ruminants are the largest source of anthropogenic methane emissions globally. The methanogenic archaea responsible for these emissions use molecular hydrogen (H2), produced during bacterial and eukaryotic carbohydrate fermentation, as their primary energy source. In this work, we used comparative genomic, metatranscriptomic, and co-culture-based approaches to gain a system-wide understanding of the organisms and pathways responsible for ruminal H2 metabolism. Two thirds of sequenced rumen bacterial and archaeal genomes encode enzymes that catalyze H2 production or consumption, including 26 distinct hydrogenase subgroups. Metatranscriptomic analysis confirmed that these hydrogenases are differentially expressed in sheep rumen. Electron-bifurcating [FeFe]-hydrogenases from carbohydrate-fermenting Clostridia (e.g. Ruminococcus) accounted for half of all hydrogenase transcripts. Various H2 uptake pathways were also expressed, including methanogenesis (Methanobrevibacter), fumarate reduction and nitrate ammonification (Selenomonas), and acetogenesis (Blautia). Whereas methanogenesis predominated in high methane yield sheep, alternative uptake pathways were significantly upregulated in low methane yield sheep. Complementing these findings, we observed significant differential expression and activity of the hydrogenases of the hydrogenogenic cellulose fermenter Ruminococcus albus and the hydrogenotrophic fumarate reducer Wolinella succinogenes in co-culture compared to pure culture. We conclude that H2 metabolism is a more complex and widespread trait among rumen microorganisms than previously recognized. There is evidence that alternative hydrogenotrophs, including acetogens and selenomonads, can prosper in the rumen and effectively compete with methanogens for H2 in low methane yield ruminants. Strategies to increase flux through alternative H2 uptake pathways, including animal selection, dietary supplementation, and methanogenesis inhibitors, may lead to sustained methane mitigation.

microbiology↗

bioRxiv2018

Effects of Biogas Slurry on Fruit Economic Traits and Soil Nutrient of Camellia oleifera Abel

Soil nutrients play a principal role in Camellia oleifera Abel (oil-seed camellia) production. Camellia oleifera absorbs nutrients from surrounding soils and its production is highly influenced by nutrients or fertilization. In this study, we investigated the effects of biogas slurry applications on soil nutrients and economic traits of C. oleifera fruits. Five different amounts of fertilizing biogas slurry (0, 10, 20, 30, or 40 kg/plant/year from three applications per year) were applied to C. oleifera plants in 2015 and 2016. Rhizosphere soil nutrients and C. oleifera fruit economic traits (yield, seed rate, and oil yield)were measured. Fertilization with biogas slurryincreasedsoil organic matter, available nitrogen (N), phosphorus (P), and potassium (K) in both 2015 and 2016. Increases in soil available N, P, and Kwere largest at the highest slurry application rate and second largest at the second highest application rate. Fruit economic traits were maximized at the two highest application rates. Oil yield was correlated withsoil available P in 2015 and 2016, and soil organic matter in 2015. Fertilization with biogas slurry decreased saturated fatty acid content in fruit but had no effect on unsaturated fatty acid content. In conclusion, fertilization with biogas slurry increases rhizosphere soil nutrients and fruit economic traits of C. oleifera with the rates of at least 30 kg/plant/year having the most positive effects.

plant biology↗

bioRxiv2018

Comparative analysis of sequencing technologies platforms for single-cell transcriptomics

All single-cell RNA-seq protocols and technologies require library preparation prior to sequencing on a platform such as Illumina. Here, we present the first report to utilize the BGISEQ-500 platform for scRNA-seq, and compare the sensitivity and accuracy to Illumina sequencing. We generate a scRNA-seq resource of 468 unique single-cells and 1,297 matched single cDNA samples, performing SMARTer and Smart-seq2 protocols on mESCs and K562 cells with RNA spike-ins. We sequence these libraries on both BGISEQ-500 and Illumina HiSeq platforms using single- and paired-end reads. The two platforms have comparable sensitivity and accuracy in terms of quantification of gene expression, and low technical variability. Our study provides a standardised scRNA-seq resource to benchmark new scRNA-seq library preparation protocols and sequencing platforms.

genomics↗

bioRxiv2018

CSTDB: A Crop Stress-tolerance Gene and Protein Database Integrated by Convolutional Neural Networks

Numerous studies have shown that many genes and proteins in plants are involved in the regulation of plant resistance to abiotic and biotic stresses. The researches on the stress tolerance of crops are also the focus of many researchers. To provides a reliable platform for collecting and retrieving genetic and protein information related to stress tolerance found in crops, we constructed CSTDB(Crops Stress-tolerance Database), an integrated database that includes stress-tolerance genes and proteins for many crop species. The database was developed based on convolutional neural network technology. It is a web-accessible database that contains detailed information on the stress-tolerance genes and proteins of major crop species. Currently, the database records four major crops containing 1,371 abiotic stress-tolerance genes or proteins, and 207 genes or proteins associated with biotic stress. Each gene and protein has detailed functional information and sequence information, such as stress types, Genbank ID, Pubmed ID, Protein ID, 3D model picture and FASTA files. As a user-friendly browsing tool, this database provides search functions, BALST functions and file download functions. CSTDB can be a valuable resource, which is designed to meet the broad needs of researchers working on crops stress-tolerance experiments. Database URL: http://pcsb.ahau.edu.cn:8080/CSTDB

bioinformatics↗

bioRxiv2018

Efficient Proximal Gradient Algorithm for Inference of Differential Gene Networks

BackgroundGene networks in living cells can change depending on various conditions such as caused by different environments, tissue types, disease states, and development stages. Identifying the differential changes in gene networks is very important to understand molecular basis of various biological process. While existing algorithms can be used to infer two gene networks separately from gene expression data under two different conditions, and then to identify network changes, such an approach does not exploit the data jointly, and it is thus suboptimal. A desirable approach would be clearly to infer two gene networks jointly, which can yield improved estimates of network changes.\n\nResultsIn this paper, we developed a proximal gradient algorithm for differential network (ProGAdNet) inference, that jointly infers two gene networks under different conditions and then identifies changes in the network structure. Computer simulations demonstrated that our ProGAdNet outperformed existing algorithms in terms of inference accuracy, and was much faster than a similar approach for joint inference of gene networks. Gene expression data of breast tumors and normal tissues in the TCGA database were analyzed with our ProGAdNet, and revealed that 268 genes were involved in the changed network edges. Gene set enrichment analysis of this set of 268 genes identified a number of gene sets related to breast cancer or other types of cancer, which corroborated the gene set identified by ProGAdNet was very informative about the cancer disease status. A software package implementing the ProGAdNet and computer simulations is available upon request.\n\nConclusionWith its superior performance over existing algorithms, ProGAdNet provides a valuable tool for finding changes in gene networks, which may aid the discovery of gene-gene interactions changed under different conditions.

bioinformatics↗

bioRxiv2018

Quantitative Analysis of Interactive Behavior of Mitochondria and Lysosomes Using Structured Illumination Microscopy

Super-resolution optical microscopy has extended the spatial resolution of cell biology from the cellular level to the nanoscale, enabling the observation of the interactive behavior of single mitochondria and lysosomes. Quantitative parametrization of interaction between mitochondria and lysosomes under super-resolution optical microscopy, however, is currently unavailable, which has severely limited our understanding of the molecular machinery underlying mitochondrial functionality. Here, we introduce an M-value to quantitatively investigate mitochondria and lysosome contact (MLC) and mitophagy under structured illumination microscopy. We found that the M-value for an MLC is typically less than 0.4, whereas in mitophagy it ranges from 0.5 to 1.0. This system permits further investigation of the detailed molecular mechanism governing the interactive behavior of mitochondria and lysosomes.

cell biology↗

bioRxiv2018

Root Anatomy based on Root Cross-Section Image Analysis with Deep Learning

Aboveground plant efficiency has improved significantly in recent years, and the improvement has led to a steady increase in global food production. The improvement of belowground plant efficiency has potential to further increase food production. However, belowground plant roots are harder to study, due to inherent challenges presented by root phenotyping. Several tools for identifying root anatomical features in root cross-section images have been proposed. However, the existing tools are not fully automated and require significant human effort to produce accurate results. To address this limitation, we use a fully automated approach, specifically, the Faster Region-based Convolutional Neural Network (Faster R-CNN), to identify anatomical traits in root cross-section images. By training Faster R-CNN models on root cross-section images, we can detect objects such as root, stele and late metaxylem, and predict rectangular bounding boxes around such objects. Subsequently, the bounding boxes can be used to estimate the root diameter, stele diameter, late metaxylem number, and average diameter. Experimental evaluation using standard object detection metrics, such as intersection-over-union and mean average precision, has shown that the Faster R-CNN models trained on rice root cross-section images can accurately detect root, stele and late metaxylem objects. Furthermore, the results have shown that the measurements estimated based on predicted bounding boxes have small root mean square error when compared with the corresponding ground truth values, suggesting that Faster R-CNN can be used to accurately detect anatomical features. A webserver for performing root anatomy using the Faster R-CNN models trained on rice images is available at https://rootanatomy.org, together with a link to a GitHub repository that contains a copy of the Faster R-CNN code. The labeled images used for training and evaluating the Faster R-CNN models are also available from the GitHub repository.

bioinformatics↗

bioRxiv2018

Managing the Spatial Covariance of Genetic Diversity in Niemann-Pick C1 Through Modulation of the Hsp70 Chaperone System

Genetic diversity provides a rich repository for understanding the role of proteostasis in the management of the protein fold to allow biology to evolve through variation in the population and in response to the environment. Failure in proteostasis can trigger multiple disease states affecting both human health and lifespan. Niemann-Pick C (NPC) disease is a genetic disorder mainly caused by mutations in NPC1, a multi-spanning transmembrane protein that is trafficked through the exocytic pathway to late endosomes and lysosomes (LE/Ly) to manage cholesterol homeostasis. Proteostatic defects triggered by >600 NPC1 variants found in the human population inhibit export of NPC1 protein from ER or function in downstream LE/Ly, leading to accumulation of cholesterol and rapid onset neurodegeneration in childhood for most patients. We now show that chemical allosteric inhibitors, such as JG98, targeting the cytosolic Hsp70 chaperone/co-chaperone complex improves the trafficking and stability of NPC1 variants with diverse NPC1 genotypes. By exploiting the knowledge-base of NPC1 variants found in the world-wide patient population using Variation Spatial Profiling (VSP), a Gaussian-process based machine learning (ML) approach, we show how the Hsp70 chaperone system alters the spatial covariance (SCV) tolerance of the ER and the SCV set-points for each residue of the NPC1 polypeptide chain differentially to improve trafficking efficiency and post-ER stability for variants distributed across the entire NPC1 polypeptide. The impact of JG98 is supported by the observation that silencing of Hsp70 specific nucleotide exchange factors (NEF) (BCL-anthogene (BAG) family) co-chaperones significantly improve the folding status of NPC1 variants. Together, these studies suggest that targeting the cytosolic Hsp70 system to adjust the SCV tolerance of the proteostasis network can improve recognition of the plasticity of the NPC1 fold found in the disease population for trafficking to the LE/Ly compartments.

genomics↗

bioRxiv2018

Analysis of contributory gut microbiota and lauric acid against necrotic enteritis in Clostridium perfringens and Eimeria side-by-side challenge model

Gut microbiota has been demonstrated to be involved in intestinal nutrition, defense, and immunity, as well as participating in disease progression. This study was to investigate gut microbiota changes in chickens challenged with netB-positive Clostridium perfringens strain 1 (CP1) and/or the predisposing Eimeria species (Eimeria). In addition, the effects of lauric acid, a medium-chain fatty acid (MCFA), on NE reduction and modulation of microbiota were evaluated. The results demonstrated that microbial communities in the jejunum were distinct from those in the cecum, and the microbial community change was more significant in jejunum. Challenge of CP1 in conjunction with Eimeria significantly reduced species diversity in jejunal microbiota, but cecal microbiota remained stable. In the jejunum, CP1 challenge increased the abundance of the genera of Clostridium sensu stricto 1, Escherichia Shigella, and Weissella, but significantly decreased the population of Lactobacillus. Eimeria infection on its own was unable to promote NE, demonstrating decrements of Clostridium sensu stricto 1 and Lactobacillus. Co-infection with CP1 and Eimeria reproduced the majority of NE lesions with significant increment of Clostridium sensu stricto 1 and reduction in Lactobacillus. The changes of these two taxa increased the severity of NE lesions. Further analyses of metagenomeSeq, STAMP, and LEfSe showed significant overgrowth of Clostridium sensu stricto 1 was associated with NE and Eimeria infection than C. perfringens challenge alone. The supplementation of lauric acid did not reduce NE incidence and severity but decreased the relative abundance of Escherichia Shigella. In conclusion, significant overgrowth of Clostridium sensu stricto 1 in the jejunm is the major microbiota contributory to NE. Controlling proliferation of this taxon in the jejunum should be the niche for developing effective strategies against NE.

microbiology↗

bioRxiv2018

Tissue-expression profiles unveils the gene interaction of hepatopancreas, eyestalk, and ovary in precocious female Chinese mitten crab, Eriocheir sinensis

Sexual precocity is a serious and common biological phenomenon in animal species. Large amount of precocity individuals was identified in Chinese mitten crab, Eriocheir sinensis, which caused huge economical loss every year. However, the underlying genetic basis of precocity in E. sinensis is still lack. In this study, histology observation, comparative transcriptome was conducted among different stages of precocious one-year old and normal two-year old E. sinensis, tissue-expression profiles of ovary, hepatopancreas, and eyestalk tissues were presented and compared. Genes associated with lipid metabolic process, lipid transport, vitelline membrane formation, vitelline synthesis and neuropeptide hormone related genes were upregulated in the ovary, hepatopancreas and eyestalk of precocious E. sinensis. Our results indicated eyestalk involved in neuroendocrine system providing neuropeptide hormone that may induce vitellogenesis in hepatopancreas and further stimulate ovary development. Hepatopancreas is a site for energy storage, vitellogenin synthesis and may assist to induce oogenesis through lipid transport in precocious E. sinensis. The genetic basis of precocity in E. sinensis is an integrated gene regulatory network of eyestalk, hepatopancreas, and ovary tissues. Our study provides effective convenient phenotype measurement method for identification of potential precocious E. sinensis detection, and valuable genetic resources and novel insights into the research of molecular mechanism of precocity in E. sinensis.

bioinformatics↗

bioRxiv2018

SuperCT: A supervised-learning-framework to enhance the characterization of single-cell transcriptomic profiles

Characterization of individual cell types is fundamental to the study of multicellular samples such as tumor tissues. Single-cell RNAseq techniques, which allow high-throughput expression profiling of individual cells, have significantly advanced our ability of this task. Currently, most of the scRNA-seq data analyses are commenced with unsupervised clustering of cells followed by visualization of clusters in a low-dimensional space. Clusters are often assigned to different cell types based on canonical markers. However, the efficiency of characterizing the known cell types in this way is low and limited by the investigator[s] knowledge. In this study, we present a technical framework of training the expandable supervised-classifier in order to reveal the single-cell identities based on their RNA expression profiles. Using multiple scRNA-seq datasets we demonstrate the superior accuracy, robustness, compatibility and expandability of this new solution compared to the traditional methods. We use two examples of model upgrade to demonstrate how the projected evolution of the cell-type classifier is realized.

bioinformatics↗

bioRxiv2018

Tau Secretion and Propagation Is Regulated by p300/CBP via Autophagy-Lysosomal Pathway in Tauopathy

The trans-neuronal propagation of tau has been implicated in the progression of tau-mediated neurodegeneration. Tau secretion from neurons is the first step in tau transmission, but little is known about the cellular mechanism. Here, we report that p300/CBP, the lysine acetyltransferase that acetylates tau and regulates its homeostasis and toxicity, serves as a key regulator of tau secretion by inhibiting the autophagy-lysosomal pathway (ALP). Increased p300/CBP activity was associated with impaired function of this pathway in a tau transgenic mouse model. p300/CBP hyperactivation increased tau secretion by blocking autophagic flux. Conversely, inhibiting p300/CBP genetically or pharmacologically promoted autophagic flux, and reduced tau accumulation, tau secretion, and tau propagation in fibril-induced tau spreading models in vitro and in vivo. Our findings show that p300/CBP-induced impairment in the ALP underlies excessive unconventional secretion and pathogenic spread of tau.

neuroscience↗

bioRxiv2018

Timing mechanism of sexually dimorphic nervous system differentiation

In all animals, sexual differentiation of somatic tissue is precisely timed, yet the molecular mechanisms that control the timing of sexual differentiation, particularly in the brain, are poorly understood. We have used sexually dimorphic molecular, anatomical and behavioral features of the C. elegans nervous system to decipher a regulatory pathway that controls the precise timing of sexual differentiation. We find that the sexually dimorphic differentiation of postmitotic neurons in the male nervous system is abrogated in animals that carry a mutation in the miRNA let-7 and prematurely executed in animals either lacking the let-7 inhibitor lin-28, or the direct let-7 target lin-41, an RNA-binding, posttranscriptional regulator. We show that an isoform of a phylogenetically conserved transcription factor, lin-29a, is a critical target of LIN-41 in controlling sexual maturation of sex-shared neurons. lin-29a is expressed in a male-specific manner in a subset of sex-shared neurons at the onset of sexual maturation. lin-29a acts cell-autonomously in these neurons to control the expression of sexually dimorphic neurotransmitter switches, sensory receptor expression, neurite anatomy and connectivity, and locomotor behavior. lin-29a is not only required but also sufficient to impose male-specific features at earlier stages of development and in the opposite sex. The temporal, sexual and spatial specificity of lin-29a expression is controlled intersectionally through the lin-28/let-7/lin-41 heterochronic pathway, sex chromosome configuration and neuron type-specific terminal selector transcription factors. Two Doublesex-like transcription factors represent additional neuron-type specific targets of LIN-41 and are regulated in a similar intersectional manner, indicating the existence of modular outputs downstream of the heterochronic pathway. In conclusion, we have provided insights into the molecular logic of the timing of sexual differentiation in the C. elegans nervous system. Remarkably, the lin28/let7 axis also controls the timing of sexual differentiation in mice and humans thereby hinting toward a striking universality of the control mechanisms of sexual differentiation.

neuroscience↗

bioRxiv2018

Carbohydrate activity regulation of floral quantity during the juvenile phase in black pepper (Piper nigrum L.)

Black pepper plants maintain synchronous vegetative growth and flowering during their lifetimes, even in the juvenile phase. How to limit the duration of flowering, facilitate a return to vegetative development should be studied. Light intensity has been reported to affect the levels of stored carbohydrates in some horticultural trees. However, it is unclear whether increased flowering intensity in adaptable light intensity is due to the regulation of carbohydrates in black pepper. Here, we report the characterization of carbohydrates and enzyme turnover in major source leaves under shading treatments during the juvenile phase of pepper. In addition to the previous finding that carbohydrate levels are correlated with flowering time, we report the novel finding that carbohydrate contents in the leaves control floral quantity. To gain insights into the underlying physiological mechanisms, we analyzed the effect of shading on sugar contents and floral transition, which revealed that shading regulated carbohydrate levels, an increase in starch accumulation improved floral quantity, and sucrose-starch ratio played a negative role in inflorescence quantity. Based on this analysis, we characterized the changes in enzyme activities in the leaves that affect carbohydrate dynamics and identified the key indicator enzymes and optimal shading intensity for the five developmental periods.\n\nHighlightWe identified the key carbohydrates, indicator enzymes and optimal shading intensity to control inflorescence quantity during the juvenile phase in black pepper for labor-saving.

biophysics↗

bioRxiv2018

QUBIC2: A novel biclustering algorithm for large-scale bulk RNA-sequencing and single-cell RNA-sequencing data analysis

The combination of biclustering and large-scale gene expression data holds a promising potential for inference of the condition specific functional pathways/networks. However, existing biclustering tools do not have satisfied performance on high-resolution RNA-sequencing (RNA-Seq) data, majorly due to the lack of (i) a consideration of high sparsity of RNA-Seq data, e.g., the massive zeros or lowly expressed genes in the data, especially for single-cell RNA-Seq (scRNA-Seq) data, and (ii) an understanding of the underlying transcriptional regulation signals of the observed gene expression values. Here we presented a novel biclustering algorithm namely QUBIC2, for the analysis of large-scale bulk RNA-Seq and scRNA-Seq data. Key novelties of the algorithm include (i) used a truncated model to handle the unreliable quantification of genes with low or moderate expression, (ii) adopted the mixture Gaussian distribution and an information-divergency objective function to capture shared transcriptional regulation signals among a set of genes, (iii) utilized a Core-Dual strategy to identify biclusters and optimize relevant parameters, and (iv) developed a size-based P-value framework to evaluate the statistical significances of all the identified biclusters. Our method validation on comprehensive data sets of bulk and single cell RNA-seq data suggests that QUBIC2 had superior performance in functional modules detection and cell type classification compared with the other five widely-used biclustering tools. In addition, the applications of temporal and spatial data demonstrated that QUBIC2 can derive meaningful biological information from scRNA-Seq data. The source code for QUBIC2 can be freely accessed at https://github.com/maqin2001/qubic2.

bioinformatics↗

bioRxiv2018

A simian-adenovirus-vectored rabies vaccine suitable for thermostabilisation and clinical development for low-cost single-dose pre-exposure prophylaxis

BackgroundEstimates of current global rabies mortality range from 26,000 to 59,000 deaths per annum. Although pre-exposure prophylaxis using inactivated rabies virus vaccines (IRVs) is effective, it requires two to three doses and is regarded as being too expensive and impractical for inclusion in routine childhood immunization programmes.\n\nMethodology/ Principal FindingsHere we report the development of a simian-adenovirus-vectored rabies vaccine intended to enable cost-effective population-wide pre-exposure prophylaxis against rabies. ChAdOx2 RabG uses the chimpanzee adenovirus serotype 68 (AdC68) backbone previously shown to achieve pre-exposure protection against rabies in non-human primates. ChAdOx2 differs from AdC68 in that it contains the human adenovirus serotype 5 (AdHu5) E4 orf6/7 region in place of the AdC68 equivalents, enhancing ease of manufacturing in cell lines which provide AdHu5 E1 proteins in trans.\n\nWe show that immunogenicity of ChAdOx2 RabG in mice is comparable to that of AdC68 RabG and other adenovirus serotypes expressing rabies virus glycoprotein. High titers of rabies virus neutralizing antibody (VNA) are elicited after a single dose. The relationship between levels of VNA activity and rabies glycoprotein monomer-binding antibody differs after immunization with adenovirus-vectored vaccines and IRV vaccines, suggesting routes to further enhancement of the efficacy of the adenovirus-vectored candidates. We also demonstrate that ChAdOx2 RabG can be thermostabilised using a low-cost method suitable for clinical bio-manufacture and ambient-temperature distribution in tropical climates. Finally, we show that a dose-sparing effect can be achieved by formulating ChAdOx2 RabG with a simple chemical adjuvant. This approach could lower the cost of ChAdOx2 RabG and other adenovirus-vectored vaccines.\n\nConclusions/ SignificanceChAdOx2 RabG may prove to be a useful tool to reduce the human rabies death toll. We have secured funding for Good Manufacturing Practice-compliant bio-manufacture and Phase I clinical trial of this candidate.\n\nAuthor summaryRabies was, after smallpox, the second human disease for which an efficacious vaccine was developed, by Pasteur in 1885. Although it is eminently preventable, with highly efficacious vaccines available for both humans and animals, it still causes considerable mortality in low and middle-income countries. It is a particular problem in areas with the weakest healthcare and veterinary infrastructure, where achieving prompt post-exposure vaccination or high-coverage dog vaccination are challenging.\n\nHere, we report the development of a new candidate rabies vaccine, designed to enable low-cost single-dose pre-exposure human rabies prophylaxis in such settings. ChAdOx2 RabG is based upon a simian adenovirus-vectored candidate previously shown to achieve protection after a single dose in non-human primates, now modified to allow clinical-grade bio-manufacture. We show that it induces a potent immune response in mice, that this response can be further enhanced by clinically-relevant adjuvant, and that we can stabilise it such that it can withstand temperatures of up to 45 {degrees}C for a month. We will be performing a clinical trial of this candidate in the near future.

immunology↗

bioRxiv2018

Efficient variant set mixed model association tests for continuous and binary traits in large-scale whole genome sequencing studies

With advances in Whole Genome Sequencing (WGS) technology, more advanced statistical methods for testing genetic association with rare variants are being developed. Methods in which variants are grouped for analysis are also known as variant-set, gene-based, and aggregate unit tests. The burden test and Sequence Kernel Association Test (SKAT) are two widely used variant-set tests, which were originally developed for samples of unrelated individuals and later have been extended to family data with known pedigree structures. However, computationally-efficient and powerful variant-set tests are needed to make analyses tractable in large-scale WGS studies with complex study samples. In this paper, we propose the variant-Set Mixed Model Association Tests (SMMAT) for continuous and binary traits using the generalized linear mixed model framework. These tests can be applied to large-scale WGS studies involving samples with population structure and relatedness, such as in the National Heart, Lung, and Blood Institutes Trans-Omics for Precision Medicine (TOPMed) program. SMMAT tests share the same null model for different variant sets, and a virtue of this null model, which includes covariates only, is that it needs to be only fit once for all tests in each genome-wide analysis. Simulation studies show that all the proposed SMMAT tests correctly control type I error rates for both continuous and binary traits in the presence of population structure and relatedness. We also illustrate our tests in a real data example of analysis of plasma fibrinogen levels in the TOPMed program (n = 23,763), using the Analysis Commons, a cloud-based computing platform.

genetics↗