Biology subjects

Wu, F.

Publications and source records attributed to Wu, F..

At least 181 records · Page 10Linked to original sources

bioRxiv2020

RNA-seq and scRNA-seq reveal trajectory progression of the retinal ganglion cell lineage in wild-type and Atoh7-null retinas

Past studies concluded that Atoh7 is critical for the emergence of the retinal ganglion cell (RGC) lineage in the developing retina, whereas Pou4f2 and Isl1 function in RGC differentiation. Atoh7 is expressed in a subset of retinal progenitor cells (RPCs) and is considered a competence factor for the RGC fate, but the molecular properties of these RPCs have not been well characterized. In this study, we first used conventional RNA-seq to investigate transcriptomic changes in Atoh7-, Pou4f2-, and Isl1-null retinas at embryonic (E) day 14.5 and identified the differentially expressed genes (DEGs), which expanded our understanding of the scope of downstream events. We then performed single cell RNA-seq (scRNA-seq) on E13.5 and E17.5 wild-type and Atoh7-null retinal cells. Clustering analysis not only correctly identified known cell types at these developmental stages but also revealed a transitional cell state which was marked by Atoh7 and genes for other lineages in a highly overlapping fashion and shared by all early developmental trajectories. Further, analysis of the Atoh7-null retina revealed that, unlike previously believed, the RGC lineage still progressed considerably and a substantial amount of RGC-specific gene expression still occurred. Thus, Atoh7 likely collaborates with other factors to shepherd the transitional RPCs to the RGC lineage by competing with other lineage factors and activating RGC-specific genes. This study thus provides significant insights into the nature of RPC competence for different retinal cell fates and revises our current view on the emergence of the RGC lineage.

developmental biology↗

bioRxiv2020

A Heat Stress Responsive NAC Transcription Factor Heterodimer Plays Key Roles in Rice Caryopsis Filling

High temperature often leads to the failure of grain filling in rice (Oryza sativa) to cause yield loss, while the mechanism is not well elucidated yet. Here, we report that two seed-specific NAM/ATAF/CUC domain transcription factors, ONAC127 and ONAC129, are responsive to heat stress and involved in the grain filling process of rice. ONAC127 and ONAC129 are dominantly expressed in the pericarp and can form a heterodimer during rice grain filling. CRISPR/Cas9 induced mutants and overexpression lines were then generated to investigate the functions of these two transcription factors. Interestingly, both knock-out and overexpression plants showed incomplete grain filling and shrunken grains, which became more severe under heat stress. Transcriptome analysis revealed that ONAC127 and ONAC129 mainly regulate stimulus response and nutrient transport. ChIP-seq analysis identified that the direct targets of ONAC127 and ONAC129 in developing rice seeds include monosaccharide transporter OsMST6, sugar transporter OsSWEET4, calmodulin-like protein OsMSR2 and AP2/ERF factor OsEATB. These results suggest that ONAC127 and ONAC129 may regulate grain filling through affecting sugar transportation and abiotic stress responses. Overall, this study demonstrates a transcriptional regulatory network involving ONAC127 and ONAC129 and coordinating multiple pathways to modulate seed development and heat stress response at rice reproductive stage.Highlight A NAC transcription factor heterodimer plays vital roles in heat stress response and sugar transportation at rice grain filling stage.Competing Interest StatementThe authors have declared no competing interest.AbbreviationsDAPDay after pollinationNAM, ATAF1/2, CUC2NACNARDNAC repression domainPTGsPotential target genesTFTranscription factorZH11Zhonghua11View Full Text

plant biology↗

bioRxiv2020

Complete genome characterisation of a novel coronavirus associated with severe human respiratory disease in Wuhan, China

Emerging and re-emerging infectious diseases, such as SARS, MERS, Zika and highly pathogenic influenza present a major threat to public health1-3. Despite intense research effort, how, when and where novel diseases appear are still the source of considerable uncertainly. A severe respiratory disease was recently reported in the city of Wuhan, Hubei province, China. At the time of writing, at least 62 suspected cases have been reported since the first patient was hospitalized on December 12nd 2019. Epidemiological investigation by the local Center for Disease Control and Prevention (CDC) suggested that the outbreak was associated with a sea food market in Wuhan. We studied seven patients who were workers at the market, and collected bronchoalveolar lavage fluid (BALF) from one patient who exhibited a severe respiratory syndrome including fever, dizziness and cough, and who was admitted to Wuhan Central Hospital on December 26th 2019. Next generation metagenomic RNA sequencing4 identified a novel RNA virus from the family Coronaviridae designed WH-Human-1 coronavirus (WHCV). Phylogenetic analysis of the complete viral genome (29,903 nucleotides) revealed that WHCV was most closely related (89.1% nucleotide similarity similarity) to a group of Severe Acute Respiratory Syndrome (SARS)-like coronaviruses (genus Betacoronavirus, subgenus Sarbecovirus) previously sampled from bats in China and that have a history of genomic recombination. This outbreak highlights the ongoing capacity of viral spill-over from animals to cause severe disease in humans.

pathology↗

bioRxiv2020

Chinese Glioma Genome Atlas (CGGA): A Comprehensive Resource with Functional Genomic Data for Chinese Glioma Patients

Gliomas are the most common and malignant intracranial tumours in adults. Recent studies have shown that functional genomics greatly aids in the understanding of the pathophysiology and therapy of glioma. However, comprehensive genomic data and analysis platforms are relatively limited. In this study, we developed the Chinese Glioma Genome Atlas (CGGA, http://www.cgga.org.cn), a user-friendly data portal for storage and interactive exploration of multi-dimensional functional genomic data that includes nearly 2,000 primary and recurrent glioma samples from Chinese cohorts. CGGA currently provides access to whole-exome sequencing (286 samples), messenger RNA sequencing (1,018 samples) and microarray (301 samples), DNA methylation microarray (159 samples), and microRNA microarray (198 samples) data, as well as detailed clinical data (e.g., WHO grade, histological type, critical molecular genetic information, age, sex, chemoradiotherapy status and survival data). In addition, we developed an analysis tool to allow users to browse mutational, mRNA/microRNA expression, and DNA methylation profiles and perform survival and correlation analyses of specific glioma subtypes. CGGA greatly reduces the barriers between complex functional genomic data and glioma researchers who seek rapid, intuitive, and high-quality access to data resources and enables researchers to use these immeasurable data sources for biological research and clinical application. Importantly, the free provision of data will allow researchers to quickly generate and provide data to the research community.

genomics↗

bioRxiv2020

Surveying Brain Tumor Heterogeneity by Single-Cell RNA Sequencing of Multi-sector Biopsies

Brain tumors are among the most challenging human tumors for which the mechanisms driving progression and heterogeneity remain poorly understood. We combined single-cell RNA-seq with multisector biopsies to sample and analyze single-cell expression profiles of gliomas from 13 Chinese patients. After classifying individual cells, we generated a spatial and temporal landscape of glioma that revealed the patterns of invasion between the different sub-regions of gliomas. We also used single-cell inferred CNVs and pseudotime trajectories to inform on the crucial branches that dominate tumor progression. The dynamic cell components of the multi-region biopsy analysis allowed us to spatially deconvolute with unprecedented accuracy the transcriptomic features of the core and those of the periphery of glioma at single cell level. Through this rich and geographically detailed dataset, we were also able to characterize and construct the chemokine and chemokine receptor interactions that exist among different tumor and non-tumor cells. This study provides the first spatial-level analysis of the cellular states that characterize human gliomas. It also presents an initial molecular map of the crosstalks between glioma cells and the surrounding microenvironment with single cell resolution.

genomics↗

bioRxiv2019

Sequestration of Methane by Symbiotic Deep-Sea Annelids: Ancient and Future Implications of Redefining the Seep Influence

Deep-sea methane seeps are dynamic sources of greenhouse gas production and unique habitats supporting ocean biodiversity and productivity. Here, we demonstrate new animal-bacterial symbioses fueled by methane, between two undescribed species of annelid (a serpulid Laminatubus and sabellid Bispira) and distinct methane-oxidizing Methylococcales bacteria. Worm tissue {delta}13C of -44{per thousand} to -58{per thousand} suggested methane-fueled nutrition for both species and shipboard experiments revealed active assimilation of 13C-labelled CH4 into animal biomass, occurring via engulfment of methanotrophic bacteria across the host epidermal surface. These worms represent a new addition to the few animals known to intimately associate with methane-oxidizing bacteria, and further explain their enigmatic mass occurrence at 150-million-year-old fossil seeps. High-resolution seafloor surveys document significant coverage by these symbioses, beyond typical obligate seep fauna. These findings uncover novel consumers of methane in the deep-sea, and by expanding the known spatial extent of methane seeps, may have important implications for deep-sea conservation.

microbiology↗

bioRxiv2019

α1A-adrenoceptor inverse agonists and agonists modulate receptor signalling through a conformational selection mechanism

G-Protein Coupled Receptors (GPCRs) transmit signals across the cell membrane via an allosteric network from the ligand-binding site to the G-protein binding site via a series of conserved microswitches. Crystal structures of GPCRs provide snapshots of inactive and active states, but poorly describe the conformational dynamics of the allosteric network that underlies GPCR activation. Here we analyse the correlation between ligand binding and receptor conformation of the 1A-adrenoceptor, known for stimulating smooth muscle contraction in response to binding noradrenaline. NMR of 13C{varepsilon}H3-methionine labelled 1A-adrenoreceptor mutants, each exhibiting differing signalling capacities, revealed how different classes of ligands modulate receptor conformational equilibria. 13C{varepsilon}H3-methionine residues near the microswitches revealed distinct states that correlated with ligand efficacies, supporting a conformational selection mechanism. We propose that allosteric coupling between the microswitches controls receptor conformation and underlies the mechanism of ligand modulation of GPCR signalling in cells.

biochemistry↗

bioRxiv2019

Lateral mechanical impedance rather than frontal, promotes cortical expansion of roots

It has long been considered that mechanical impedance on root will restrict root elongation and consequently promote radial growth. However, we did observe radial expansion but not elongation restriction in maize seedlings after short growth in sands. Mechanical impedance of soil can be classified into frontal- and lateral-type based on the interaction site of root. Therefore, we suspected that radial expansion might be mainly stimulated by lateral rather than frontal impedance. To verify our speculation, frontal and lateral impedance was provided separately. Small plastic caps were used to provide unique frontal impedance on root tip and cylindrical plastic containers were used to provide lateral impedance. Plastic caps could reduce root length remarkably. However, the radial expansion of plastic-cap-fitted roots was significantly inferior to that of the sand-cultured roots. Microstructural analysis revealed that sand-condition thickened root largely dependents on cortical expansion, whereas plastic cap did it mainly by thickening stele. In cylindrical plastic containers, mechanical impedance came only from the lateral direction and promoted the expansion of cortex just as sand-condition. Thus, we proposed that the expansion of the cortex and the consequent radial growth is mainly due to lateral impedance when growing in sands.

plant biology↗

bioRxiv2019

ER stress drives ER-to-Golgi trafficking of ATF6 by blocking its membrane insertion

Regulated ER-to-Golgi trafficking is a fundamental cellular process that enables ER-resident transcription factors to sense perturbations in the ER environment and activates transcriptional programs that restore ER and cellular homeostasis. Current models suggest sensor activation is initiated by dissociation from its ER-resident binding partners. Here we challenge this model by demonstrating that the unfolded protein sensor ATF6 is sorted to the Golgi as a newly synthesized peripheral membrane protein beyond the reach of its ER retainer, and translocon inhibition alone is sufficient to drive ATF6 activation. We identify ATF6 transmembrane domain and its C-terminus as the intrinsic factors that control membrane insertion efficiency and stress sensing capacity, and the BAG6 complex as the receptor that triages ATF6 between membrane insertion and Golgi sorting. Besides ATF6, we show that translocon inhibition expedites the activation of the cholesterol sensor SREBP2, and the catalytic domain of Golgi-bound S1P that processes both ATF6 and SREBP2 resides in the cytosol. Therefore, we propose an alternative, sensing-by-synthesis model, in which transcription factors are continuously synthesized, and perturbations to the ER environment are quantitatively sensed by the fraction of sensors that fail to be properly incorporated into ER membrane and sorted to Golgi for activation.

cell biology↗

bioRxiv2019

A Synthetic Biology Approach to Sequential Stripe Patterning and Somitogenesis

Reaction-diffusion (RD) based clock and wavefront model has long been proposed as the mechanism underlying biological pattern formation of repeated and segmented structures including somitogenesis. However, systematic molecular level understanding of the mechanism remains elusive, largely due to the lack of suitable experimental systems to probe RD quantitatively in vivo. Here we design a synthetic gene circuit that couples gene expression regulation (reaction) with quorum sensing (diffusion) to guide bacterial cells self-organizing into stripe patterns at both microscopic and colony scales. An experimentally verified mathematical model confirms that these periodic spatial structures are emerged from the integration of oscillatory gene expression as the molecular clock and the outward expanding diffusions as the propagating wavefront. Furthermore, our paired model-experiment data illustrate that the RD-based patterning is sensitive to initial conditions and can be modulated by external inducers to generate diverse patterns, including multiple-stripe pattern, target-like pattern and ring patterns with reversed fluorescence. Powered by our synthetic biology setup, we also test different topologies of gene networks and show that network motifs enabling robust oscillations are foundations of sequential stripe pattern formation. These results verified close connections between gene network topology and resulting RD driven pattern formation, offering an engineering approach to help understand biological development.

synthetic biology↗

bioRxiv2019

Polyadenylation of Histone H3.1 mRNA Promotes Cell Transformation by Displacing H3.3 from Gene Regulatory Elements

Replication-dependent canonical histone messenger RNAs (mRNAs) do not terminate with a poly(A) tail at the 3 end. We previously demonstrated that exposure to arsenic, an environmental carcinogen, induces polyadenylation of canonical histone H3.1 mRNA. The addition of a poly(A) tail to the H3.1 mRNA caused transformation of human cells in vitro, but the underlying mechanisms are unknown. Here we report that polyadenylation of H3.1 mRNA increases H3.1 protein level, resulting in depletion of histone variant H3.3 at active promoters, enhancers, and insulator regions through its displacement. Cells underwent transcriptional deregulation, G2/M cell cycle arrest, chromosome aneuploidy and aberrations. Furthermore, knocking down the expression of H3.3 induced cell transformation, whereas ectopic expression of H3.3 attenuated arsenic-induced cell transformation, suggesting that H3.3 displacement might be central to tumorigenic effects of polyadenylated H3.1 mRNA. Our study provides novel insights into the importance of proper histone stoichiometry in maintaining genome integrity.\n\nHighlightsO_LIPolyadenylation of canonical histone H3.1 mRNA promotes tumor formation in nude mice\nC_LIO_LIHistone variant H3.3 is displaced from critical gene regulatory elements by overexpression of polyadenylated H3.1 mRNA\nC_LIO_LIIncreased polyadenylated H3.1 mRNA causes abnormal transcription, cell cycle arrest, and chromosomal instability\nC_LIO_LIArsenic induces polyadenylation of H3.1 mRNA in vivo\nC_LI

molecular biology↗

bioRxiv2019

Transposable elements contribute to regulatory hubs stress-related long noncoding RNAs in Maize

Several studies have mined short-read RNA sequencing datasets to identify lncRNAs, and others have focused on the function of individual lncRNA in abiotic stress response. However, our understanding of the complement, function and origin of long-non-coding RNA (lncRNAs) response to abiotic stress, especially transposon derived lncRNA (TE-lncRNA), is still in its infancy. To discover and study lncRNAs in maize (Zea mays ssp. mays), we utilized a dataset of 127 RNA sequencing samples that included PacBio fl-cDNA and total RNA-Seq datasets. Overall, we identified 23,309 candidate lncRNAs, 60% of which were identified in polyadenylated (polyA+) samples. The majority (65%) of the 23,309 lncRNAs had sequence similarity to transposable elements (TEs). Most had similarity to long-terminal-repeat retrotransposons from the Copia and Gypsy superfamilies, representing the high proportion of these elements in the genome, but class II, DNA transposons were enriched for lncRNAs relative to their genomic representation by 2-fold. By assessing the fraction of lncRNAs that respond to abiotic stresses like heat, cold, salt and drought, we identified 1,077 differentially expressed lncRNA transcripts. Their expression was correlated (r2=0.48) with their nearest gene, suggesting that lncRNAs are subject to some of the cis regulatory features as neighboring genes. By inferring co-expression networks across our large dataset, we found that 39 lncRNAs act as major hubs in co-expression networks, of which 18 appeared to be derived from TEs. These results suggest that lncRNAs, especially TE-lncRNAs, may play key regulatory roles in moderating abiotic responses.

plant biology↗

bioRxiv2019

Field decomposition of Bt-506 corn leaf and its effect on Collembola in the black soil region of China

The litters of Bt corn would go into the soil through straw returning and field ploughing after cultivation. To clarify whether the leaf litter decomposition rate and the non-target soil Collembola were influenced by the Bt protein or other litter properties in leaf litters of Bt corn in Northeast China, leaf litterbags of Bt-506, its near isoline Zheng 58 and a local type Zhengdan 958 were used in the field in Northeast China. The leaf decomposition rate, the leaf properties and the collembolan community in litterbags were investigated later. After seven months, only 43.5 ng/g Bt protein in Bt-506 leaf litter was left. All the investigated indices were not significantly different between Bt-506 and its near isoline Zheng 58. But when compared with local type Zhengdan 958, Bt-506 and its near isoline Zheng 58 contained lower non-structural carbohydrate content but higher total nitrogen content, and had lower litter decomposition rate and less abundance of Collembola. Collembolan abundance and litter decomposition rate were both significantly correlated with the non-structural carbohydrate and total nitrogen contents of the leaf litters. Field study results revealed Bt protein did not affect the leaf litter decomposition rate and the collembolan community in leaf litterbags in short term. The significant differences of these investigated indices among corn types were caused by the different non-structural carbohydrate and total nitrogen contents in leaf litter.

ecology↗

bioRxiv2019

Genome-wide development of miRNA-based SSR markers in Cleistogenes songorica with their transferability analysis to gramineae and non- gramineae species

SSR markers are commonly used for many genetic applications, such as map construction, fingerprinting and genetic diversity analysis due to their high reproducibility, levels of polymorphism and abundance. As endogenous, small RNAs, miRNAs have essential roles in plant development and gene expression under diverse stress conditions, including various biotic and abiotic stress conditions. In the present study, we predicted 110 pre-miRNAs sequences from 287 precursor miRNAs and used them as queries for SSR marker development. Among 110 primer pairs, 85 were successfully amplified and examined for transferability to other gramineae and non-gramineae species. The results showed that all 82 primer pairs yielded unambiguous and strong amplification, and across the 23 studied Cleistogenes accessions, a total of 385 alleles were polymorphic. The number of alleles produced per primer varied from 3 to 11, with an average of 4.69 per locus. The expected heterozygosity (He) ranged from 0.44 to 0.88, with an average of 0.74 per locus, and the PIC (Polymorphism Information Content) values ranged from 0.34 to 0.87, with an average of 0.69 per locus. In this study, 1422 miRNA target genes were predicted and analyzed using the GO (Gene Ontology) and KEGG (Kyoto Encyclopedia of Genes and Genomes) databases. The results showed that this miRNA-based microsatellite marker system can be very useful for genetic diversity and marker-assisted breeding studies.

genomics↗

bioRxiv2019

The anti-apoptotic proteins Bcl-2 and Bcl-xL suppress Beclin1/Atg6-mediated lethal autophagy in polyploid cells

Inhibition of Aurora-B kinase is a synthetic lethal therapy for tumors that overexpress the MYC oncoprotein. It is currently unclear whether co-occurring oncogenic alterations might influence this synthetic lethality by confering more or less potency in the killing of tumor cells. To identify such modifers, we utilized isogenic cell lines to test a variety of cancer genes that have been previously demonstrated to promote survival under conditions of cellular stress, contribute to chemoresistance and/or suppress MYC-primed apoposis. We found that Bcl-2 and Bcl-xL, two antiapoptotic members of the Bcl-2 family, can partially suppress the synthetic lethality, but not multinucleation, elicited by a panaurora kinase inhibitor, VX-680. We demonstrate that this suppression stems from the rescue of autophagic cell death, specifically of multinucleated cells, rather than a general inhibition of apoptosis. Bcl-2 inhibits VX-680-induced death of polyploid cells by interacting with the autophagy protein Beclin1/Atg6 and rescue requires localization of Bcl-2 to the endoplasmic reticulum. These findings expand on previous conclusions that autophagic death of polyploid cells is mediated by Atg6. Bcl-2 and Bcl-xL negatively modulate MYC-VX-680 synthetic lethality and it is the anti-autophagic activity of these two Bcl-2 family proteins, specifically in multinucleate cells, that contributes to resistance to Aurora kinase-targeting drugs.

cancer biology↗

bioRxiv2019

Massive computational acceleration by using neural networks to emulate mechanism-based biological models

Mechanism-based mathematical models are the foundation for diverse applications. It is often critical to explore the massive parametric space for each model. However, for many applications, such as agent-based models, partial differential equations, and stochastic differential equations, this practice can impose a prohibitive computational demand. To overcome this limitation, we present a fundamentally new framework to improve computational efficiency by orders of magnitude. The key concept is to train an artificial neural network using a limited number of simulations generated by a mechanistic model. This number is small enough such that the simulations can be completed in a short time frame but large enough to enable reliable training of the neural network. The trained neural network can then be used to explore the system dynamics of a much larger parametric space. We demonstrate this notion by training neural networks to predict self-organized pattern formation and stochastic gene expression. With this framework, we can predict not only the 1-D distribution in space (for partial differential equation models) and probability density function (for stochastic differential equation models) of variables of interest with high accuracy, but also novel system dynamics not present in the training sets. We further demonstrate that using an ensemble of neural networks enables the self-contained evaluation of the quality of each prediction. Our work can potentially be a platform for faster parametric space screening of biological models with user defined objectives.

systems biology↗

bioRxiv2019

Time Series Experiment Design Under One-Shot Sampling: The Importance of Condition Diversity

Many biological data sets are prepared using one-shot sampling, in which each individual organism provides only one sample. Time series therefore do not follow trajectories of individuals over time. However, samples collected at different times from individuals grown/raised under the same conditions share the same perturbations of the biological processes, and hence behave as surrogates for multiple samples from a single individual at different times. This implies the importance of growing/raising individuals under multiple conditions if one-shot sampling is used. This paper models the condition effect explicitly by correlated perturbations in the variations driving the expression dynamics, quantifies the performance of the generalized likelihood-ratio test for network structure, and illustrates the difficulty in network reconstruction under one-shot sampling when the condition effect is absent.

systems biology↗

bioRxiv2018

Molecular profiles and mutation burden analysis in Chinese patients with gastric carcinoma

The goal of this work was to investigate the molecular profiles and mutation burden in Chinese patients with gastric carcinoma (GC). In total, we performed whole exome sequencing (WES) on 74 GC patients with tumor and adjacent normal formalin-fixed, paraffin-embedded (FFPE) tissue samples. The mutation spectrum of these samples showed a high concordance with TCGA and other studies on GC. We found the alterations of 17 DNA repair genes (including BRCA2, POLE and MSH3, etc.) were strongly correlated with the tumor mutation burden (TMB) and tumor neoantigen burden (TNB) of GC patients. Patients with mutations of these genes tend to have high TMB (median of TMB = 12.77, p=2.3e-6) and TNB (median of TNB = 5.97, p= 2.8e-3). In addition, younger GC patients (age < 60) have lower TMB (p = 0.0021) and TNB (p = 0.034) than older patients (age >= 60). Furthermore, we found a list of 18 genes and two genomic regions (1p36.21 and Xq26.3) were associated with peritoneal metastasis (PM) of GC, and patients with amplification of 1p36.21 and Xq26.3 have a worse prognosis (p=0.002, 0.01, respectively). Our analysis provides GC patients with potential markers for single and combination therapies.

cancer biology↗