Biology subjects

Xu, Z.

Publications and source records attributed to Xu, Z..

At least 433 records · Page 24Linked to original sources

bioRxiv2020

Guidelines for accurate genotyping of SARS-CoV-2 using amplicon-based sequencing of clinical samples

BackgroundSARS-CoV-2 genotyping has been instrumental to monitor virus evolution and transmission during the pandemic. The reliability of the information extracted from the genotyping efforts depends on a number of aspects, including the quality of the input material, applied technology and potential laboratory-specific biases. These variables must be monitored to ensure genotype reliability. The current lack of guidelines for SARS-CoV-2 genotyping leads to inclusion of error-containing genome sequences in studies of viral spread and evolution. ResultsWe used clinical samples and synthetic viral genomes to evaluate the impact of experimental factors, including viral load and sequencing depth, on correct sequence determination using an amplicon-based approach. We found that at least 1000 viral genomes are necessary to confidently detect variants in the genome at frequencies of 10% or higher. The broad applicability of our recommendations was validated in >200 clinical samples from six independent laboratories. The genotypes of clinical isolates with viral load above the recommended threshold cluster by sampling location and period. Our analysis also supports the rise in frequency of 20A.EU1 and 20A.EU2, two recently reported European strains whose dissemination was favoured by travelling during the summer 2020. ConclusionsWe present much-needed recommendations for reliable determination of SARS-CoV-2 genome sequence and demonstrate their broad applicability in a large cohort of clinical samples.

genomics↗

bioRxiv2020

N439K variant in spike protein may alter the infection efficiency and antigenicity of SARS-CoV-2 based on molecular dynamics simulation

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), causing an outbreak of coronavirus disease 2019 (COVID-19), has been undergoing various mutations. The analysis of the structural and energetic effects of mutations on protein-protein interactions between the receptor binding domain (RBD) of SARS-CoV-2 and angiotensin converting enzyme 2 (ACE2) or neutralizing monoclonal antibodies will be beneficial for epidemic surveillance, diagnosis, and optimization of neutralizing agents. According to the molecular dynamics simulation, a key mutation N439K in the SARS-CoV-2 RBD region created a new salt bridge which resulted in greater electrostatic complementarity. Furthermore, the N439K-mutated RBD bound hACE2 with a higher affinity than wild-type, which may lead to more infectious. In addition, the N439K-mutated RBD was markedly resistant to the SARS-CoV-2 neutralizing antibody REGN10987, which may lead to the failure of neutralization. These findings would offer guidance on the development of neutralizing antibodies and the prevention of COVID-19.

bioinformatics↗

bioRxiv2020

The female (XX) and male (YY) genomes provide insights into the sex determination mechanism in spinach

Sexual reproduction is the primary means of reproduction for the vast majority of macroscopic organisms, including almost all animals and plants. Sex chromosomes are predicted to play a central role in sexual dimorphism. Sex determination in spinach is controlled by a pair of sex chromosomes. However, the mechanisms of sex determination in spinach remain poorly understand. Here, we assembled the genomes of both a female (XX) and a male (YY) individual of spinach, and the genome sizes were 978 Mb with 28,320 predicted genes and 926 Mb with 26,537 predicted genes, respectively. Based on reported sex-linked markers, chromosomes 4 of the female and male genome were defined as the X and Y chromosomes, and a 10 Mb male-specific region of the Y chromosome (MSY) from approximately 95- 105 Mb, was identified that contains abundant transposable elements (92.32%). Importantly, a large-scale inversion of about 13 Mb in length was detected on the X chromosome, corresponding to ~9 Mb and ~4 Mb on the Y chromosome, which were located on both sides of the MSY with two distinct evolutionary strata. Almost all sex-linked/Y-specific markers were enriched on the inversions/MSY, suggesting that the flanked inversions might result in recombination suppression between the X and Y chromosomes to maintain the MSY. Forty-nine genes within the MSY had functional homologs elsewhere in the autosomal region, suggesting movement of genes onto the MSY. The X and Y chromosomes of spinach provide a valuable resource for investigating spinach sex chromosomes evolution from wild to cultivated spinach and also provide a broader understanding of the sex determination model in the Amaranthaceae family.

genomics↗

bioRxiv2020

The bone microenvironment invigorates metastatic seeds for further dissemination

Metastasis has been considered as the terminal step of tumor progression. However, recent clinical studies suggest that many metastases are seeded from other metastases, rather than primary tumors. Thus, some metastases can further spread, but the corresponding pre-clinical models are lacking. By using several approaches including parabiosis and an evolving barcode system, we demonstrated that the bone microenvironment facilitates breast and prostate cancer cells to further metastasize and establish multi-organ secondary metastases. Importantly, dissemination from the bone microenvironment appears to be more aggressive compared to that from mammary tumors and lung metastases. We further uncovered that this metastasis-promoting effect is independent from genetic selection, as single cell-derived cancer cell populations (SCPs) exhibited enhanced metastasis capacity after being extracted from the bone microenvironment. Taken together, our work revealed a previously unappreciated effect of the bone microenvironment on metastasis evolution, and suggested a stable reprogramming process that engenders cancer cells more metastatic.

cancer biology↗

bioRxiv2020

Template-independent genome editing and repairing correct frameshift disease in vivo

Frameshift mutation caused by small insertions/deletions (indels) often generate truncated and non-functional proteins, which underlies 22% inherited Mendelian disorders in humans. However, there is no efficient in vivo gene therapy strategies available to date, especially in postmitotic systems. Here, we leveraged the non-homologous end joining (NHEJ) mediated non-random editing profiles to compensate the frameshift mutation in a USH1F mouse model - av3j. After treatment by the selected gRNA, about 50% editing products showed reading-frame restoration, and more than 70% targeted hair cells recovered mechanotransduction. In vivo treatment ameliorated the hearing and balance symptoms in homozygous mutant mice. Furthermore, a scale-up analysis of 114 gRNAs targeting 40 frameshift deafness mutations reveals that 65% loci have at least one gRNA with predicted therapeutic potential. Together, our study demonstrates that the NHEJ-mediated frame restoration is a simple and highly efficient therapeutic strategy for small-indel induced frameshift mutations.

neuroscience↗

bioRxiv2020

Phenotypic plasticity of ER+ breast cancer in the bone microenvironment

ER+ breast cancer exhibits a strong bone-tropism in metastasis. How the bone microenvironment impacts the ER signaling and endocrine therapies remains poorly understood. Here, we discover that the osteogenic niche transiently reduces ER expression and activities specifically in bone micrometastases (BMMs), leading to endocrine resistance. This is mediated by gap junctions and paracrine FGF/PDGF signaling, which together generate a stable "memory": cancer cells extracted from bone remain resistant to endocrine therapies for several generations. Using single cell-derived populations (SCPs), we demonstrated that this process is independent of clonal selection, and represents an EZH2-mediated epigenomic reprogramming. EZH2 drives ER+ BMMs toward a basal and stem-like state. EZH2 inhibition reverses endocrine resistance. Our data demonstrates how epigenomic adaptation to the bone microenvironment drives phenotypic plasticity of metastatic seeds and alters their therapeutic responses together with clonal selection, and provides insights into the clinical enigma of ER+ metastatic recurrences despite endocrine therapies.

cancer biology↗

bioRxiv2020

A Markov Random Field Model for Network-based Differential Expression Analysis of Single-cell RNA-seq Data

BackgroundRecent development of single cell sequencing technologies has made it possible to identify genes with different expression (DE) levels at the cell type level between different groups of samples. In this article, we propose to borrow information through known biological networks to increase statistical power to identify differentially expressed genes (DEGs). ResultsWe develop MRFscRNAseq, which is based on a Markov Random Field (MRF) model to appropriately accommodate gene network information as well as dependencies among cell types to identify cell-type specific DEGs. We implement an Expectation-Maximization (EM) algorithm with mean field-like approximation to estimate model parameters and a Gibbs sampler to infer DE status. Simulation study shows that our method has better power to detect cell-type specific DEGs than conventional methods while appropriately controlling type I error rate. The usefulness of our method is demonstrated through its application to study the pathogenesis and biological processes of idiopathic pulmonary fibrosis (IPF) using a single-cell RNA-sequencing (scRNA-seq) data set, which contains 18,150 protein-coding genes across 38 cell types on lung tissues from 32 IPF patients and 28 normal controls. ConclusionsThe proposed MRF model is implemented in the R package MRFscRNAseq available on GitHub. By utilizing gene-gene and cell-cell networks, our method increases statistical power to detect differentially expressed genes from scRNA-seq data.

bioinformatics↗

bioRxiv2020

SECANT: a biology-guided semi-supervised method for clustering, classification, and annotation of single-cell multi-omics

The recent advance of single cell sequencing (scRNA-seq) technology such as Cellular Indexing of Transcriptomes and Epitopes by Sequencing (CITE-seq) allows researchers to quantify cell surface protein abundance and RNA expression simultaneously at single cell resolution. Although CITE-seq and other similar technologies have quickly gained enormous popularity, novel methods for analyzing this new type of single cell multi-omics data are still in urgent need. A limited number of available tools utilize data-driven approach, which may undermine the biological importance of surface protein data. In this study, we developed SECANT, a biology-guided SEmi-supervised method for Clustering, classification, and ANnoTation of single-cell multi-omics. SECANT can be used to analyze CITE-seq data, or jointly analyze CITE-seq and scRNA-seq data. The novelties of SECANT include 1) using confident cell type labels identified from surface protein data as guidance for cell clustering, 2) providing general annotation of confident cell types for each cell cluster, 3) fully utilizing cells with uncertain or missing cell type labels to increase performance, and 4) accurate prediction of confident cell types identified from surface protein data for scRNA-seq data. Besides, as a model-based approach, SECANT can quantify the uncertainty of the results, and our framework can be easily extended to handle other types of multi-omics data. We successfully demonstrated the validity and advantages of SECANT via simulation studies and analysis of public and in-house real datasets. We believe this new method will greatly help researchers characterize novel cell types and make new biological discoveries using single cell multi-omics data.

bioinformatics↗

bioRxiv2020

The effect of Basal core promoter and pre-core mutations on HBV replication and persistence in mice

The appearance of the BCP or Pre-C mutations, which reduce or abolish HBeAg production, could increase HBV replication. The remove of the HBeAg often lead to a vigorous immune response, which has an important role in HBV related fulminant outcome. In this study, BCP mutations and Pre-C mutations were separately introduced by site-directed mutagenesis in the same genetic background of an HBV infectious clone, to determine the effect of these mutations per se on replication. BCP and Pre-C mutations increased HBV replication both in vitro and in vivo. HBV could persist in mice injected with wild type HBV infectious clone for about 7 weeks. However, HBV could persist about 5 weeks in mice injected with BCP HBV infectious clone, and 3 weeks only in mice injected with Pre-C HBV infectious clone. HBV related CD8+ CTL response in BCP HBV infectious clone injected mice only slightly increased, but significantly increased in Pre-C HBV infectious clone injected mice compared with that in wild type HBV infectious clone injected mice. The population of Tregs significantly increased in liver but not in spleen of mice injected with Pre-C HBV infectious clone. In summary, we demonstrate that HBeAg plays an important role in suppressing the CTL response, which is related with increasing the frequency of Tregs in mouse. Lack of HBeAg expression leads to the partial loss of immune tolerance.

microbiology↗

bioRxiv2020

Evidence for ZAP-independent CpG reduction in SARS-CoV-2 genome, and pangolin coronavirus origin of 5'UTR

SARS-CoV-2, the causative agent of COVID-19, has an RNA genome, which is, overall, closely related to the bat coronavirus sequence RaTG13. However, the ACE2-binding domain of this virus is more similar to a coronavirus isolated from a Guangdong pangolin. In addition to this unique feature, the genome of SARS-CoV-2 (and its closely related coronaviruses) has a low CpG content. This has been postulated to be the signature of an evolutionary pressure exerted by the host antiviral protein ZAP. Here, we analyzed the sequences of a wide range of viruses using both alignment-based and alignment free approaches to investigate the origin of SARS-CoV-2 genome. Our analyses revealed a high level of similarity between the 5UTR of SARS-CoV-2 and that of the Guangdong pangolin coronavirus. This suggests bat and pangolin coronaviruses might have recombined at least twice (in the 5UTR and ACE2 binding regions) to seed the formation of SARS-CoV-2. An alternative hypothesis is that the lineage preceding SARS-CoV-2 is a yet to be sampled bat coronavirus whose ACE2 binding domain and 5UTR are distinct from other known bat coronaviruses. Additionally, we performed a detailed analysis of viral genome compositions as well as expression and RNA binding data of ZAP to show that the low CpG abundance in SARS-CoV-2 is not related to an evolutionary pressure from ZAP.

genomics↗

bioRxiv2020

Overcoming resistance to immune checkpoint therapy in PTEN-null prostate cancer by sequential intermittent anti-PI3Ka/b/δ and anti-PD-1 treatment

Prostate cancers generally lack T cell infiltration and display resistance to immune checkpoint therapies (ICT). We found that intermittent but not daily dosing of PI3K/{beta}/{delta} inhibitor BAY1082439 on a Pten-null spontaneous prostate cancer model could overcome ICT resistance and unleash CD8+ T cell-dependent anti-tumor immunity in vivo. Mechanistically, BAY1082439 converts Pten-null cancer cell-intrinsic immune-suppression to immune-stimulation by promoting IFN/{gamma} pathway activation, {beta}2-microglubin expression and CXCL10/CCL5 secretion. Together with its preferential Treg inhibition activity, BAY1082439 promotes clonal expansion of tumor-associated CD8+ T cells. Once primed, tumors remain as T cell-inflamed and become responsive to anti-PD-1 therapy. Our data suggest that intermittent PI3K inhibition can alleviate Pten-null cancer cell-intrinsic immunosuppressive activity and turn "cold" tumors into T cell-inflamed ones, paving the way for successful ICT. SignificanceThe combination of ICT and targeted therapies holds great promises for broad and long-lasting therapeutic effects for cancers. However, combining ICT with anti-PI3K inhibitors have been difficult because the multifaceted effects of PI3K on both cancer cells and immune cells within the tumor microenvironment. Here we show a carefully designed anti-PI3K treatment, both in its specificity and dosing schedule, to inhibit cancer cell growth while promoting anti-tumor immunity, is critically important for successful ICT. Since the PI3K pathway is one of the most frequently altered signaling pathways in human cancers, our work may shed light on treating those cancers with PI3K activation and overcome resistance to ICT. HighlightsO_LIIntermittent PI3K/{beta}/{delta} inhibitor BAY1082439 treatment overcomes ICT resistance C_LIO_LIBAY1082439 turns Pten-null prostate cancer from "cold" to T cell-inflamed C_LIO_LIBAY1082439 inhibits cancer cell-intrinsic immunosuppressive activity and Treg C_LIO_LIBAY1082439 promotes clonal expansion and immunity of tumor-associated CD8+ T cells C_LI

cancer biology↗

bioRxiv2020

Auxin guides germ cell specification in Arabidopsis anthers

Germ cells (GCs) transmit genetic information from one generation to the next. Unlike animal GCs, plant GCs are induced post-embryonically, forming locally from somatic cells. This induction is coordinated with organogenesis and might be guided by positional cues. In angiosperms, male GCs initiate from the internal layers at the four corners of the anther primordia and are gradually enclosed by parietal cell (PC) layers, leading to a concentric GC-PC pattern.1,2 However, the underlying mechanism of GC initiation and GC-PC pattern formation is unclear. Auxin affects pattern formation3 and anther development.4-11 However, whether GC formation involves auxin remains unknown. We report that the auxin distribution in pre-meiotic anthers parallels GC initiation, forming a centripetal gradient between the outer primordial cells and the inner GCs. The auxin biosynthesis genes TRYPTOPHAN AMINOTRANSFERASE OF ARABIDOPSIS 1 (TAA1) and TRYPTOPHAN AMINOTRANSFERASE RELATED 2 (TAR2)5,12 are responsible for this patterning and essential for GC specification. SPOROCYTELESS/NOZZLE (SPL/NZZ, a determinant for GC specification)13-15 mediates the effect of auxin on GC specification, modulates auxin homeostasis, and maintains centripetal auxin patterning. Our results reveal that auxin is a key factor guiding GC specification in Arabidopsis anthers.

plant biology↗

bioRxiv2020

Fast-Bonito: A Faster Basecaller for Nanopore Sequencing

Oxford Nanopore Technologies (ONT) is a promising sequencing technology that could generate relatively longer sequencing reads compared to the next generation sequencing (NGS) technology. The base calling process is very important for TGS. It translates the original electrical signals from the sequencer to the nucleotide sequence. By doing that, the base calling could significantly influence the accuracy of downstream analysis. Bonito is a recently developed basecaller based on deep neuron network, the neuron network architecture of which is composed of a single convolutional layer followed by three stacked bidirectional GRU layers. Although Bonito achieved the state-of-the-art accuracy, its speed is so slow that it is not likely to be used in production. We therefore implement Fast-Bonito, which introduces systematic optimization to speed up Bonito. Fast-Bonito archives 53.8% faster than the original version on NVIDIA V100 and could be further speed up by HUAWEI Ascend 910 NPU, achieving 565% faster than the original version. The accuracy of Fast-Bonito is also slightly higher than the original Bonito.

bioinformatics↗

bioRxiv2020

Algorithmic and data modeling: will algorithmic modeling improve predictions of traits evaluated on ordinal scales?

Selection of markers linked to alleles at quantitative trait loci (QTL) for tolerance to Iron Deficiency Chlorosis (IDC) has not been successful. Genomic selection has been advocated for continuous numeric traits such as yield and plant height. For ordinal data types such as IDC, genomic prediction models have not been systematically compared. The objectives of research reported in this manuscript were to evaluate the most commonly used genomic prediction method, ridge regression and its equivalent logistic ridge regression method, with algorithmic modeling methods including random forest, gradient boosting, support vector machine, K-nearest neighbors, Naive Bayes, and artificial neural network using the usual comparator metric of prediction accuracy. In addition we compared the methods using metrics of greater importance for decisions about selecting and culling lines for use in variety development and genetic improvement projects. These metrics include specificity, sensitivity, precision, decision accuracy, and area under the receiver operating characteristic curve. We found that Support Vector Machine provided the best specificity for culling IDC susceptible lines, while Random Forest GP models provided the best combined set of decision metrics for retaining IDC tolerant and culling IDC susceptible lines.

genomics↗

bioRxiv2020

SpRY greatly expands the genome editing scope in rice with highly flexible PAM recognition

Plant genome engineering mediated by various CRISPR-based tools requires specific protospacer adjacent motifs (PAMs), such as the well-performed NGG, NG, NNG, etc., to initiate the target recognition, which notably restricts the editable range of the plant genome. In this study, we thoroughly investigated the nuclease activity and the PAM preference of two structurally-engineered SpCas9 variants (SpG and SpRY) in transgenic rice. Our study shows that SpG nuclease favors NGD PAMs, albeit less efficiently than the previously described SpCas9-NG and that SpRY nuclease achieves efficient editing across a wide range of genomic loci, exhibiting a preference of NGD as well as NAN PAMs. Furthermore, SpRY-fused cytidine deaminase hAID*{Delta} and adenosine deaminase TadA8e were generated, respectively. These constructs efficiently induced C-to-T and A-to-G conversions in the target genes toward various non-canonical PAMs, including non-G PAMs. Remarkably, high-frequency self-editing events (indels and DNA fragments deletion) in the integrated T-DNA fragments as a result of the nuclease activity of SpRY were observed, whereas the self-editing of SpRY nickase-mediated base editor was quite low in transgenic rice lines. In conclusion, the broad PAM compatibility of SpRY greatly expands the targeting scope of CRISPR-based tools in plant genome engineering.

plant biology↗

bioRxiv2020

Neonicotinoids stimulate H2-limited methane emission in Periplaneta americana through the regulation of gut bacterium community

Methane emitted by insects is considered to be an important source of atmospheric methane. Here we report the stimulation of methane emission in Periplaneta americana, an insect species with abundant methanogens, by neonicotinoids, insecticides widely used to control insect pests. The application of cycloxaprid (CYC) and imidacloprid (IMI) caused foregut expansion in P. americana, and increased the methane production and emission. Antibiotics could mostly eliminate the stimulatory effects. In P. americana gut, hydrogen levels increased and pH values decreased, which could be significantly explained by the gut bacterium community change. The proportion of several bacterium genera increased in guts following CYC treatment, and four genera from five with increased proportions could generate hydrogen at anaerobic conditions. Hydrogen is a central intermediate in methanogenesis. Gut methanogens could use the increased hydrogen to produce more methane, especially at acidic conditions. Following neonicotinoid applications, all increased methanogens in both foregut and hindgut used hydrogen as electron donor to produce methane. Besides, the up-regulation of mcrA, encoding the enzyme that catalyzes the final step of methanogenesis, suggested an enhanced methane production ability in present methanogens. In the termite Coptotermes chaohuensis, another methanogen-abundant insect species, hydrogen levels in gut and methane emission significantly increased after neonicotinoid treatment, which was similar to the results in P. americana. In summary, neonicotinoids changed bacterium community in P. americana gut to generate more hydrogen, which then stimulate gut methanogens to produce and emit more methane. The finding raised a new concern over neonicotinoid applications, and might be a potential environmental risk associated with global warming.

ecology↗

bioRxiv2020

Applications of spatial models to ordinal data: Geospatial Statistics for Soybean Iron Deficiency Chlorosis

Models have been developed to account for heterogeneous spatial variation in field trials. These spatial models have been shown to successfully increase the quality of phenotypic data resulting in improved effectiveness of selection by plant breeders. The models were developed for continuous data types such as grain yield and plant height, but data for most traits, such as in iron deficiency chlorosis (IDC), are recorded on ordinal scales. Is it reasonable to make spatial adjustments to ordinal data by simply applying methods developed for continuous data? The objective of the research described herein is to evaluate methods for spatial adjustment on ordinal data, using soybean IDC as an example. Spatial adjustment models are classified into three different groups: group I, moving average grid adjustment; group II, geospatial autoregressive regression (SAR) models; and group III, tensor product penalized P-splines. Comparisons of eight models sampled from these three classes demonstrate that spatial adjustments depend on severity of field heterogeneity, the irregularity of the spatial patterns, and the model used. SAR models generally produce better performance metrics than other classes of models. However, none of the eight evaluated models fully removed spatial patterns indicating that there is a need to either adjust existing models or develop novel models for spatial adjustments of ordinal data collected in fields exhibiting discontinuous transitions between heterogeneous patches.

plant biology↗

bioRxiv2020

Improved Prediction of Smoking Status via Isoform-Aware RNA-seq Deep Learning Models

Most predictive models based on gene expression data do not leverage information related to gene splicing, despite the fact that splicing is a fundamental feature of eukaryotic gene expression. Cigarette smoking is an important environmental risk factor for many diseases, and it has profound effects on gene expression. Using smoking status as a prediction target, we developed deep neural network predictive models using gene, exon, and isoform level quantifications from RNA sequencing data in over 2,000 subjects in the COPDGene Study. We observed that models using exon and isoform quantifications clearly outperformed gene-level models when using data from 5 genes from a previously published five gene prediction model. Whereas the test set performance of the previously published model was 0.82 in the original publication, our exon-based models including an exon-to-isoform mapping layer achieved a test set AUC of 0.88 using data from the same 5 genes and an AUC of 0.94 using a larger set of exon quantifications. Isoform variability is an important source of latent information in RNA-seq data that can be used to improve clinical prediction models. Author summaryPredictive models based on gene expression are already a part of medical decision making for selected situations such as early breast cancer treatment. Most of these models are based on measures that do not capture critical aspects of gene splicing, but with RNA sequencing it is possible to capture some of these aspects of alternative splicing and use them to improve clinical predictions. Building on previous models to predict cigarette smoking status, we show that measures of alternative splicing significantly improve the accuracy of these predictive models.

genomics↗