Biology subjects

Ren, B.

Publications and source records attributed to Ren, B..

At least 127 records · Page 7Linked to original sources

bioRxiv2020

Exploring the Pharmacological Mechanism of Bezoar on Cerebral Ischemic Stroke using a Network Pharmacology Approach

BackgroundIschemic stroke is a common clinical disease limited by its time window for treatment. In addition to its high mortality rate, only one treatment currently exists for ischemic stroke. Nonetheless, traditional Chinese medicine is often used as a reatment for the disease. Bezoar is a multi-functional drug that has been demonstrated to be effective for the treatment of ischemic stroke. However, its mechanism of action is yet to be fully elucidated. Based on network pharmacology, we explored the potential mechanism of action of bezoar. Symmap and literature data mining methods were used to obtain the target of bezoar. The mechanism of bezoar for the treatment of ischemic stroke was identified and ischemic stroke-related targets were retrieved using DrugBank, Online Mendelian Inheritance in Man, and Therapeutic Target Database. Protein-protein interaction networks were constructed using the Cytoscape plugin, BisoGenet, and analysed by topological methods. Gene Ontology and Kyoto Encyclopaedia of Genes and Genomes pathway enrichment were carried out via the Database for Annotation, Visualization, and Integrated Discovery server. We obtained 48 potential targets and 3 signalling pathways, including mitogen-activated protein kinase, hypoxia-inducible factor-1, and tumour necrosis factor signalling pathways. The mechanism of action of bezoar on ischemic stroke involves multiple targets and signalling pathways. Our research provides a network pharmacology framework for future Chinese medicinal research.

neuroscience↗

bioRxiv2019

Single nucleus multi-omics links human cortical cell regulatory genome diversity to disease risk variants

Single-cell technologies enable measure of unique cellular signatures, but are typically limited to a single modality. Computational approaches allow integration of diverse single-cell datasets, but their efficacy is difficult to validate in the absence of authentic multi-omic measurements. To comprehensively assess the molecular phenotypes of single cells in tissues, we devised single-nucleus methylCytosine, Chromatin accessibility and Transcriptome sequencing (snmC2T-seq) and applied it to post-mortem human frontal cortex tissue. We developed a computational framework to validate fine-grained cell types using multi-modal information and assessed the effectiveness of computational integration methods. Correlation analysis in individual cells revealed distinct relations between methylation and gene expression. Our integrative approach enabled joint analyses of the methylome, transcriptome, chromatin accessibility and conformation for 63 human cortical cell types. We reconstructed regulatory lineages for cortical cell populations and found specific enrichment of genetic risk for neuropsychiatric traits, enabling prediction of cell types with causal roles in disease.

genomics↗

bioRxiv2019

Cell type-specific enhancer-promoter connectivity maps in the human brain and disease risk association

Unique cell type-specific patterns of activated enhancers can be leveraged to interpret non-coding genetic variation associated with complex traits and diseases such as neurological and psychiatric disorders. Here, we have defined active promoters and enhancers for major cell types of the human brain. Whereas psychiatric disorders were primarily associated with regulatory regions in neurons, idiopathic Alzheimers disease (AD) variants were largely confined to microglia enhancers. Interactome maps connecting GWAS variants in cell type-specific enhancers to gene promoters revealed an extended microglia gene network in AD. Deletion of a microglia-specific enhancer harboring AD-risk variants ablated BIN1 expression in microglia but not in neurons or astrocytes. These findings revise and expand the genes likely to be influenced by non-coding variants in AD and suggest the probable brain cell types in which they function.\n\nOne Sentence SummaryIdentification of cell type-specific regulatory elements in the human brain enables interpretation of non-coding GWAS risk variants.

neuroscience↗

bioRxiv2019

Single-cell chromatin accessibility analysis of mammary gland development reveals cell state transcriptional regulators and cellular lineage relationships

It has only recently become possible to obtain single-cell level resolution of the epigenetic changes that occur during organ development. We reasoned that precision single-cell chromatin accessibility mapping of mammary gland development could provide needed insight into the epigenetic reprogramming and transcriptional regulators involved in normal mammary gland development. Here, we provide the first single-cell resource of chromatin accessibility for murine mammary development from the peak of fetal mammary stem cell (fMaSC) functional activity in late embryogenesis to the differentiation of adult basal and luminal cells. We find that the chromatin landscape within individual cells predicts both gene accessibility and transcription factor activity, and we present a web application as a scientific resource for facilitating future analyses. Strikingly, these single-cell chromatin profiling data reveal that fMaSCs can be separated into basal-like and luminal-like lineages, providing evidence of early lineage segregation prior to birth. Such distinctions were not evident in analyses of single-cell transcriptomic data.

genomics↗

bioRxiv2019

FIREcaller: an R package for detecting frequently interacting regions from Hi-C data

Hi-C experiments have been widely adopted to study chromatin spatial organization, which plays an essential role in genome function. We have recently identified frequently interacting regions (FIREs) and found that they are closely associated with cell-type-specific gene regulation. However, computational tools for detecting FIREs from Hi-C data are still lacking. In this work, we present FIREcaller, a stand-alone, user-friendly R package for detecting FIREs from Hi-C data. FIREcaller takes raw Hi-C contact matrices as input, performs within-sample and cross-sample normalization, and outputs continuous FIRE scores, dichotomous FIREs, and super-FIREs. Applying FIREcaller to Hi-C data from various human tissues, we demonstrate that FIREs and super-FIREs identified, in a tissue-specific manner, are closely related to gene regulation, are enriched for enhancer-promoter (E-P) interactions, tend to overlap with regions exhibiting epigenomic signatures of cis-regulatory roles, and aid the interpretation or GWAS variants. The FIREcaller package is implemented in R and freely available at https://yunliweb.its.unc.edu/FIREcaller. Highlights- Frequently Interacting Regions (FIREs) can be used to identify tissue and cell-type-specific cis-regulatory regions. - An R software, FIREcaller, has been developed to identify FIREs and clustered FIREs into super-FIREs.

bioinformatics↗

bioRxiv2019

Fast and Accurate Clustering of Single Cell Epigenomes Reveals Cis-Regulatory Elements in Rare Cell Types

Identification of the cis-regulatory elements controlling cell-type specific gene expression patterns is essential for understanding the origin of cellular diversity. Conventional assays to map regulatory elements via open chromatin analysis of primary tissues is hindered by heterogeneity of the samples. Single cell analysis of transposase-accessible chromatin (scATAC-seq) can overcome this limitation. However, the high-level noise of each single cell profile and the large volumes of data could pose unique computational challenges. Here, we introduce SnapATAC, a software package for analyzing scATAC-seq datasets. SnapATAC can efficiently dissect cellular heterogeneity in an unbiased manner and map the trajectories of cellular states. Using the Nystrom method, a sampling technique that generates the low rank embedding for large-scale dataset, SnapATAC can process data from up to a million cells. Furthermore, SnapATAC incorporates existing tools into a comprehensive package for analyzing single cell ATAC-seq dataset. As demonstration of its utility, SnapATAC was applied to 55,592 single-nucleus ATAC-seq profiles from the mouse secondary motor cortex. The analysis revealed [~]370,000 candidate regulatory elements in 31 distinct cell populations in this brain region and inferred candidate transcriptional regulators in each of the cell types.

bioinformatics↗

bioRxiv2019

Common DNA sequence variation influences 3-dimensional conformation of the human genome

The 3-dimensional (3D) conformation of chromatin inside the nucleus is integral to a variety of nuclear processes including transcriptional regulation, DNA replication, and DNA damage repair. Aberrations in 3D chromatin conformation have been implicated in developmental abnormalities and cancer. Despite the importance of 3D chromatin conformation to cellular function and human health, little is known about how 3D chromatin conformation varies in the human population, or whether DNA sequence variation between individuals influences 3D chromatin conformation. To address these questions, we performed Hi-C on Lymphoblastoid Cell Lines (LCLs) from 20 individuals. We identified thousands of regions across the genome where 3D chromatin conformation varies between individuals and found that this conformational variation is often accompanied by variation in gene expression, histone modifications, and transcription factor (TF) binding. Moreover, we found that DNA sequence variation influences several features of 3D chromatin conformation including loop strength, contact insulation, contact directionality and density of local cis contacts. We mapped hundreds of Quantitative Trait Loci (QTLs) associated with 3D chromatin features and found evidence that some of these same variants are associated at modest levels with other molecular phenotypes as well as complex disease risk. Our results demonstrate that common DNA sequence variants can influence 3D chromatin conformation, pointing to a more pervasive role for 3D chromatin conformation in human phenotypic variation than previously recognized.

genomics↗

bioRxiv2019

Comparing 3D genome organization in multiple species using Phylo-HMRF

Recent developments in whole-genome mapping approaches for the chromatin interactome (such as Hi-C) have offered new insights into 3D genome organization. However, our knowledge of the evolutionary patterns of 3D genome structures in mammalian species remains surprisingly limited. In particular, there are no existing phylogenetic-model based methods to analyze chromatin interactions as continuous features across different species. Here we develop a new probabilistic model, named phylogenetic hidden Markov random field (Phylo-HMRF), to identify evolutionary patterns of 3D genome structures based on multi-species Hi-C data by jointly utilizing spatial constraints among genomic loci and continuous-trait evolutionary models. The effectiveness of Phylo-HMRF is demonstrated in both simulation evaluation and application to real Hi-C data. We used Phylo-HMRF to uncover cross-species 3D genome patterns based on Hi-C data from the same cell type in four primate species (human, chimpanzee, bonobo, and gorilla). The identified evolutionary patterns of 3D genome organization correlate with features of genome structure and function, including long-range interactions, topologically-associating domains (TADs), and replication timing patterns. This work provides a new framework that utilizes general types of spatial constraints to identify evolutionary patterns of continuous genomic features and has the potential to reveal the evolutionary principles of 3D genome organization.

bioinformatics↗

bioRxiv2019

An Array of 60,000 Antibodies for Proteome-Scale Antibody Generation and Target Discovery

Antibodies are essential for elucidating the roles of genes decoded by genome sequencing. However, affordable technology for proteome-scale antibody generation does not exist. To address this, we developed the Proteome Epitope Tag Antibody Library (PETAL) and its array. PETAL consists of 62,208 mAbs against 15,199 peptides from diverse proteomes. PETAL harbors binders for a great multitude of proteins in nature due to antibody multispecificity, an intrinsic feature of an antibody. Distinctive combinations of 10,000-20,000 mAbs were found to target specific proteomes by array screening. Phenotype-specific mAb-target pairs were discovered for maize and zebrafish samples. Immunofluorescence and flow cytometry mAbs for human membrane proteins and ChIP-seq mAbs for transcription factors were identified from respective proteome-binding PETAL mAbs. Differential screening of cell surface proteomes of tumor and normal tissues discovered internalizing tumor antigens for antibody-drug conjugates. By discovering high affinity mAbs at a fraction of current time and cost, PETAL enables proteome-scale antibody generation and target discovery.

systems biology↗

bioRxiv2018

3D Chromatin Architecture Remodeling during Human Cardiomyocyte Differentiation Reveals A Novel Role of HERV-H In Demarcating Chromatin Domains

Dynamic restructuring of chromatin architecture has been implicated in cell-type specific gene regulatory programs; yet, how chromatin remodels during lineage specification remains to be elucidated. Through interrogating chromatin reorganization during human cardiomyocyte differentiation, we uncover dynamic chromatin interactions between genes and distal regulatory elements harboring noncoding variants associated with adult and congenital heart diseases. Unexpectedly, we also discover a new class of human pluripotent stem cell (PSC)-specific topologically associating domains (TAD) that are created by the actively transcribed endogenous retrotransposon HERV-H. Deletion or silencing of specific HERV-H elements eliminates corresponding TAD boundaries, while de novo insertion of HERV-H can introduce new chromatin domain boundaries in human PSCs. Furthermore, comparative analysis of chromatin architecture in other species that lack HERV-H sequences supports a role for actively transcribed HERV-H in demarcating human PSC-specific TADs. The biological role of HERV-H is further underscored by the observation that deletion of a specific HERV-H reduces transcription of genes upstream and facilitates cell differentiation. Overall, our results highlight a previously unrecognized role for retrotransposons in restructuring genome architecture in the human genome and delineate dynamic gene regulatory networks during cardiomyocyte development that inform how non-coding genetic variants contribute to human heart diseases.

genomics↗

bioRxiv2018

Simultaneous profiling of DNA methylation and chromatin architecture in mixed populations and in single cells

Dynamic DNA methylation and three-dimensional chromatin architecture compose a major portion of a cells epigenome and play an essential role in tissue specific gene expression programs. Currently, DNA methylation and chromatin organization are generally profiled in separate assays. Here, we report Methyl-HiC, a method combining in situ Hi-C and whole genome bisulfite sequencing (WGBS) to simultaneously capture chromosome conformation and DNA methylome in a single assay. Methyl-HiC analysis of mouse embryonic stem cells reveals coordinated DNA methylation between distant yet spatially proximal genomic regions. Extension of Methyl-HiC to single cells further enables delineation of the heterogeneity of both chromosomal conformation and DNA methylation in a mixed cell population, and uncovers increased dynamics of chromatin contacts and decreased stochasticity in DNA methylation in genomic regions that replicate early during cell cycle.

genomics↗

bioRxiv2018

Identification of essential regulatory elements in the human genome

The identification of essential regulatory elements is central to the understanding of the consequences of genetic variation. Here we use novel genomic data and machine learning techniques to map essential regulatory elements and to guide functional validation. We train an XGBoost model using 38 functional and structural features, including genome essentiality metrics, 3D genome organization and enhancer reporter STARR-seq data to differentiate between pathogenic and control non-coding genetic variants. We validate the accuracy of prediction by using data from tiling-deletion-based and CRISPR interference screens of activity of cis-regulatory elements. In neurodevelopmental disorders, the model (ncER, non-coding Essential Regulation) maps essential genomic segments within deletions and rearranged topologically associated domains linked to human disease. We show that the approach successfully identifies essential regulatory elements in the human genome.

genomics↗

bioRxiv2018

DNA replication-mediated error correction of ectopic CENP-A deposition maintains centromere identity

Chromatin assembled with the histone H3 variant CENP-A is the heritable epigenetic determinant of human centromere identity. Using genome-wide mapping and reference models for 23 human centromeres, CENP-A is shown in early G1 to be assembled into nucleosomes within megabase, repetitive -satellite DNAs at each centromere and onto 11,390 transcriptionally active sites on the chromosome arms. Here we identify that DNA replication acts as an error correction mechanism to sustain centromere identity through the removal of the sites of CENP-A loading on the chromosome arms, while maintaining centromere-bound CENP-A with the same DNA sequence preferences as in its initial loading.

cell biology↗

bioRxiv2018

MAPS: model-based analysis of long-range chromatin interactions from PLAC-seq and HiChIP experiments

Hi-C and chromatin immunoprecipitation (ChIP) have been combined to identify long-range chromatin interactions genome-wide at reduced cost and enhanced resolution, but extracting the information from the resulting datasets has been challenging. Here we describe a computational method, MAPS, Model-based Analysis of PLAC-seq and HiChIP, to process the data from such experiments and identify long-range chromatin interactions. MAPS adopts a zero-truncated Poisson regression framework to explicitly remove systematic biases in the PLAC-seq and HiChIP datasets, and then uses the normalized chromatin contact frequencies to identify significant chromatin interactions anchored at genomic regions bound by the protein of interest. MAPS shows superior performance over existing software tools in analysis of chromatin interactions centered on cohesin, CTCF and H3K4me3 associated regions in multiple cell types. MAPS is freely available at https://github.com/ijuric/MAPS.

bioinformatics↗

bioRxiv2018

MITA couples with PI3K to regulate actin reorganization during BCR activation

As an adaptor protein, MITA has been extensively studied in innate immunity. However, its role in adaptive immunity as well as its underlying mechanism are not completely understood. We used MITA KO mice to study the effect of MITA deficiency on B cell development and differentiation, BCR signaling during BCR activation and humoral immune response. We found that MITA deficiency promotes the differentiation of marginal zone B cells, which is linked to the lupus-like autoimmune disease that develops in MITA KO mice. MITA is involved in BCR activation and negatively regulates the activation of CD19 and Btk and positively regulates the activation of SHIP. Interestingly, we found that the activation of WASP and accumulation of F-actin is enhanced in MITA KO B cells upon stimulation. Mechanistically, we found that MITA uses PI3K mediated by the CD19-Btk axis as a central hub to control the actin remodeling that, in turn, offers feedback to BCR signaling. Overall, our study has provided a new mechanism on how MITA regulates BCR signaling via feedback from actin reorganization, which may contribute to the effects of MITA on the humoral immune response.

immunology↗

bioRxiv2018

Pancreatic islet chromatin accessibility and conformation defines distal enhancer networks of type 2 diabetes risk

The gene targets of enhancer activity in pancreatic islets are largely unknown, impeding discovery of islet regulatory networks involved in type 2 diabetes (T2D) risk. We mapped chromatin state, accessibility and conformation using ChIP-seq, ATAC-seq and Hi-C in human pancreatic islets, which we integrated with T2D genetic fine-mapping and islet expression QTL data. Active islet regulatory elements preferentially interacted with other active elements, often at distances over 1MB, and we identified target genes for thousands of distal islet enhancers. A third of T2D risk signals mapped in islet enhancers, and target genes regulated by these signals were specifically involved in processes related to protein transport and secretion. Among implicated target genes of T2D islet enhancer signals with no prior known role in islet function, we demonstrated that reduced IGF2BP2 activity in mouse islets leads to impaired glucose-stimulated insulin secretion. These results link distal islet enhancer regulation of protein secretion and transport to genetic risk of T2D, and highlight the utility of high-throughput chromatin conformation maps to uncover the gene regulatory networks of complex disease.

genomics↗

bioRxiv2017

Systematic mapping of chromatin state landscapes during mouse development

Embryogenesis requires epigenetic information that allows each cell to respond appropriately to developmental cues. Histone modifications are core components of a cells epigenome, giving rise to chromatin states that modulate genome function. Here, we systematically profile histone modifications in a diverse panel of mouse tissues at 8 developmental stages from 10.5 days post conception until birth, performing a total of 1,128 ChIP-seq assays across 72 distinct tissue-stages. We combine these histone modification profiles into a unified set of chromatin state annotations, and track their activity across developmental time and space. Through integrative analysis we identify dynamic enhancers, reveal key transcriptional regulators, and characterize the role of chromatin-based repression in developmental gene regulation. We also leverage these data to link enhancers to putative target genes, revealing connections between coding and non-coding sequence variation in disease etiology. Our study provides a compendium of resources for biomedical researchers, and achieves the most comprehensive view of embryonic chromatin states to date.

genomics↗

bioRxiv2017

Spatiotemporal DNA Methylome Dynamics of the Developing Mammalian Fetus

Genetic studies have revealed an essential role for cytosine DNA methylation in mammalian development. However, its spatiotemporal distribution in the developing embryo remains obscure. Here, we profiled the methylome landscapes of 12 mouse tissues/organs at 8 developmental stages spanning from early embryogenesis to birth. Indepth analysis of these spatiotemporal epigenome maps systematically delineated ~2 million methylation variant regions and uncovered widespread methylation dynamics at nearly one-half million tissue-specific enhancers, whose human counterparts were enriched for variants involved in genetic diseases. Strikingly, these predicted regulatory elements predominantly lose CG methylation during fetal development, whereas the trend is reversed after birth. Accumulation of non-CG methylation within gene bodies of key developmental transcription factors coincided with their transcriptional repression during later stages of fetal development. These spatiotemporal epigenomic maps provide a valuable resource for studying gene regulation during mammalian tissue/organ progression and for pinpointing regulatory elements involved in human developmental diseases.

genomics↗