Biology subjects

Duan, J.

Publications and source records attributed to Duan, J..

8 recordsLinked to original sources

bioRxiv2018

Transcriptional Network Analysis on Brains Reveals a Potential Regulatory Role of PPP1R3F in Autism Spectrum Disorders

ObjectiveThis study aims at identifying master regulators of transcriptional networks in autism spectrum disorders (ASDs).\n\nResultsWith two sets of independent RNA-Seq data generated on cerebellum from patients with ASDs and control subjects (N=39 and 45 for set 1, N=24 and 38 for set 2, respectively), we carried out a network deconvolution of transcriptomic data, followed by virtual protein activity analysis. We identified PPP1R3F (Protein Phosphatase 1 Regulatory Subunit 3F) as a master regulator affecting a large body of downstream genes that are associated with the disease phenotype. Pathway enrichment analysis on the identified targets of PPP1R3F in both datasets indicated alteration of endocytosis pathway. This exploratory analysis is limited by sample size, but it illustrates a successful application of network deconvolution approaches in the analysis of brain gene expression data and generates a hypotheses that may be further validated by large-scale studies in the future.

bioinformatics↗

bioRxiv2018

Reduced but not Enhanced Default Mode Network Functional Connectivity in Major Depressive Disorder: Evidence from 25 Cohorts in the REST-meta-MDD Project

Major Depressive Disorder (MDD) is common and disabling, but its neural pathophysiology remains unclear. Functional brain network studies in MDD have largely had limited statistical power and data analysis approaches have varied widely. The REST-meta-MDD Project of resting-state fMRI (R-fMRI) addresses these issues. The 25 research groups in China composing the REST-meta-MDD Project contributed R-fMRI data of 1,300 patients with MDD and 1,128 normal controls (NCs). The data were preprocessed locally with a standardized protocol prior to aggregated group analyses. We focused on functional connectivity (FC) within the default mode network (DMN), frequently reported to show increased FC in MDD. We found decreased instead of increased DMN FC when comparing 848 MDDs with 794 NCs from 17 sites after data exclusion. We found FC reduction only in recurrent MDD, not in first-episode drug-naive MDD. Decreased DMN FC was associated with medication usage but not with MDD duration. DMN FC was also positively related to symptom severity but only in recurrent MDDs. Exploratory analyses also revealed alterations of local intrinsic activity in MDD. We confirmed the key role of DMN in MDD but found reduced rather than increased FC within the DMN. Future studies should test whether decreased DMN FC mediates treatment response. This manuscript announces the publicly available resting-state fMRI indices of the REST-meta-MDD consortium shared via the R-fMRI Maps Project.\n\nSIGNIFICANCE STATEMENTFunctional connectivity within the default mode network in major depressive disorder patients has been frequently reported abnormal but with contradicting directions in previous small sample size studies. By creating the REST-meta-MDD consortium containing neuroimaging data of 1,300 depressed patients and 1,128 normal controls from 25 research groups in China, we found decreased default mode network functional connectivity in depressed patients, driven by patients with recurrent depression, and associated with current medication treatment but not with disease duration. These findings suggest that default mode network functional connectivity remains a prime target for understanding the pathophysiology of depression, with particular relevance to revealing mechanisms of effective treatments.

neuroscience↗

bioRxiv2018

Cytokinin treatment of rice induces minimal effect on differential splicing compared to splicing between tissues

Alternatively spliced genes produce multiple spliced isoforms, called transcript variants. In differential alternative splicing, the relative abundance of transcript variants differs across sample types. Differential alternative splicing is common in animal systems and influences cellular development in many processes, but its extent and significance is not as well known in plants. To investigate alternative splicing in plants, we examined rice seedling RNA-Seq data that included approximately 40 million sequence alignments per library, three libraries per sample type, and four sample types: roots and shoots, each treated with exogenous cytokinin delivered hydroponically, plus mock-treated controls. Cytokinin treatment triggered expression changes in thousands of genes, but had minimal effect on alternative splicing. However, there were many splicing differences between roots and shoots. Analysis of a similar (but less deeply sequenced) mRNA-Seq data set from Arabidopsis showed the same pattern. Quantitative fragment analysis of reverse transcriptase-PCR products made from newly prepared rice samples confirmed nine of ten differential splicing events between rice roots and shoots. In both the Arabidopsis and rice mRNA-Seq data sets, most genes annotated as alternatively spliced had small minor variant frequencies, i.e., the less frequently observed forms were supported by fewer than 20% of informative mRNA-Seq sequences. Of splicing choices where there was more abundant support for minor forms, most alternative splicing events were located within the protein-coding sequence and also maintained the annotated reading frame. A tool for visualizing protein annotations in the context of genomic sequence (ProtAnnot) together with a genome browser (Integrated Genome Browser) were used to visualize and assess effects of differential splicing on gene function. In general, differentially spliced regions coincided with conserved regions in the encoded proteins, indicating that differential alternative splicing is likely to affect protein function between root and shoot tissue in rice.

molecular biology↗

bioRxiv2018

Structure of the mouse TRPC4 ion channel

Members of the transient receptor potential (TRP) ion channels conduct cations into cells. They mediate functions ranging from neuronally-mediated hot and cold sensation to intracellular organellar and primary ciliary signaling. Structures belonging to the TRPV, TRPM, TRPP, TRPA and TRPML subfamilies have been solved, but to date, none of the founding canonical (TRPC) structures. Here we report an electron cryo-microscopy (cryo-EM) structure of TRPC4 in its apo state to an overall resolution of 3.3 [A]. The structure reveals an unusually complex architecture with a long pore loop stabilized by a disulfide bond. Beyond the shared tetrameric six-transmembrane fold, the TRPC4 structure deviates from other TRP channels with a unique cytosolic domain, this unique cytosolic N-terminal domain forms extensive aromatic contacts with the TRP and the C-terminal domains. The comparison of our structure with other known TRP structures provides molecular insights into TRPC4 ion selectivity and extends our knowledge of the diversity and evolution of the TRP channels.

biophysics↗

bioRxiv2017

PKD2 is an essential ion channel subunit in the primary cilium of the renal collecting duct epithelium

Mutations in either Pkd1 or Pkd2 result in Autosomal Dominant Polycystic Kidney Disease (ADPKD). Although PKD2 is proposed to be an ion channel subunit, recordings of PKD2 ion channels conflict in their properties. Using a new ADPKD mouse model, we observe primary cilia are abnormally long in cells associated with cysts. Using primary cultures of collecting duct epithelial cells, we show that PKD2, but not PKD1, is a required subunit for primary cilia ion channel. The ciliary PKD2 channel conducts potassium and sodium ions, but little calcium. We also demonstrate that PKD2 is not constitutively active in the plasma membrane, but PKD2 channels are functional in primary cilia and are sensitized by high cilioplasmic [Ca2+]. We introduce a novel method for measuring PKD2 channels heterologously expressed in primary cilia of HEK-293 cells, which will have utility characterizing Pkd2 variants that cause ADPKD in their native ciliary membrane.

biophysics↗

bioRxiv2017

Reverse Engineering of Trascriptional Networks Uncovers Candidate Master Regulators Governing Neuropathology of Schizophrenia

Tissue-specific reverse engineering of transcriptional networks has uncovered master regulators (MRs) of cellular networks in various cancers, yet the application of this method to neuropsychiatric disorders is largely unexplored. Here, using RNA-Seq data on postmortem dorsolateral prefrontal cortex (DLPFC) from schizophrenia (SCZ) patients and control subjects, we deconvolved the transcriptional network to identify MRs that mediate expression of a large body of target genes. Together with an independent RNA-Seq data on cultured cells derived from olfactory neuroepithelium, we identified TCF4, a leading SCZ risk locus implicated by genome-wide association studies, as one of the top candidate MRs that may be potentially dysregulated in SCZ. We validated the dysregulated TCF4-related transcriptional network through examining the transcription factor binding footprints inferred from human induced pluripotent stem cell (hiPSC)-derived neuronal ATAC-Seq data, as well as direct binding sites obtained from ChIP-seq data in SH-SY5Y cells. The predicted TCF4 transcriptional targets were enriched for genes showing transcriptomic changes upon knockdown of TCF4 in hiPSC-derived neural progenitor cells (NPC) and glutamatergic neurons (Glut_N), based on observations from three separate cell lines. The altered TCF4 gene network perturbations in NPC, as compared to that in Glut_N, was more similar to the expression differences in the TCF4 gene network observed in the DLPFC of individuals with SCZ. Moreover, TCF4-associated gene expression changes in NPC were more enriched than Glut_N for pathways involved in neuronal activity, genome-wide significant SCZ risk genes, and SCZ-associated de novo mutations. Our results suggest that TCF4 may potentially serve as a MR of a gene network that confers susceptibility to SCZ at early stage of neurodevelopment, highlighting the importance of network dysregulation involving core genes and many hundreds of peripheral genes in conferring susceptibility to neuropsychiatric diseases.

neuroscience↗

bioRxiv2017

Gut Microbiota Composition Related With Clostridium difficile-Positive Diarrhea And C. Difficile Type (A+B+, A-B+, And A-B-) In ICU Hospitalized Patients

BackgroundGut microbiota composition of intensive care unit (ICU) patients suffering from Clostridium difficile-positive diarrhea (CDpD) is still poorly understood. This study aims to use 16S rDNA (and metagenome) sequencing to compare the microbiota composition of 58 (and 5) ICU patients with CDpD (CDpD group), 33 (and 4) ICU patients with C. difficile negative diarrhea (CDnD group), and 21 (and 5) healthy control subjects (control group), as well as CDpD patients in A+B+ (N=34; A/B: C. difficile TcdA/B), A-B+ (N=7), and A-B- (N=17) subgroups. For 16S rDNA data, OTU clustering (tool: UPARSE), taxonomic assignment (tool: RDP classifier), -diversity and {beta}-diversity analyses (tool: QIIME) were conducted. For metagenome data, metagenome assembly (tool: SOAP), gene calling (tools: MetaGeneMark, CD-HIT, and SoapAligner), unigene alignment (tool: DIAMOND), taxon difference analysis (tool: Metastats), and gene annotation (tool: DIAMOND) were performed.\n\nResultsThe microbial diversity of CDpD group was lower than that of CDnD and control groups. The abundances of 10 taxa (e.g. Deferribacteres, Cryptomycota, Acetothermia) in CDpD group were significantly higher than that in CDnD group. The abundances of Saccharomycetes and Clostridia were significantly lower in CDpD in comparison with control. A+B+, A-B+ and A-B- subgroups couldnt be separated in principal component analysis, while some taxa are significantly different between A+B+ and A-B- subgroups.\n\nConclusionCDpD might relate to the decrease of beneficial taxa (i.e. Saccharomycetes and Clostridia) and the increase of harmful taxa (e.g. Deferribacteres, Cryptomycota, Acetothermia) in gut microbiota in ICU patients. C. difficile type might be slightly associated with gut microbiota composition.

molecular biology↗

bioRxiv2017

Drug Target Ontology to Classify and Integrate Drug Discovery Data

BackgroundOne of the most successful approaches to develop new small molecule therapeutics has been to start from a validated druggable protein target. However, only a small subset of potentially druggable targets has attracted significant research and development resources. The Illuminating the Druggable Genome (IDG) project develops resources to catalyze the development of likely targetable, yet currently understudied prospective drug targets. A central component of the IDG program is a comprehensive knowledge resource of the druggable genome.\n\nResultsAs part of that effort, we have been developing a framework to integrate, navigate, and analyze drug discovery data based on formalized and standardized classifications and annotations of druggable protein targets, the Drug Target Ontology (DTO). DTO was constructed by extensive curation and consolidation of various resources. DTO classifies the four major drug target protein families, GPCRs, kinases, ion channels and nuclear receptors, based on phylogenecity, function, target development level, disease association, tissue expression, chemical ligand and substrate characteristics, and target-family specific characteristics. The formal ontology was built using a new software tool to auto-generate most axioms from a database while also supporting manual knowledge acquisition. A modular, hierarchical implementation facilitates development and maintenance and makes use of various external ontologies, thus integrating the DTO into the ecosystem of biomedical ontologies. As a formal OWL-DL ontology, DTO contains asserted and inferred axioms. Modeling data from the Library of Integrated Network-based Cellular Signatures (LINCS) program illustrates the potential of DTO for contextual data integration and nuanced definition of important drug target characteristics. DTO has been implemented in the IDG user interface Portal, Pharos and the TIN-X explorer of protein target disease relationships.\n\nConclusionsDTO was built based on the need for a formal semantic model for druggable targets including various related information such as protein, gene, protein domain, protein structure, binding site, small molecule drug, mechanism of action, protein tissue localization, disease association, and many other types of information. DTO will further facilitate the otherwise challenging integration and formal linking to biological assays, phenotypes, disease models, drug poly-pharmacology, binding kinetics and many other processes, functions and qualities that are at the core of drug discovery. The first version of DTO is publically available via the website http://drugtargetontology.org/, Github (https://github.com/DrugTargetOntology/DTO), and the NCBO Bioportal (https://bioportal.bioontology.org/ontologies/DTO). The long-term goal of DTO is to provide such an integrative framework and to populate the ontology with this information as a community resource.

bioinformatics↗