ABSTRACT
Deciphering the fine-scale molecular mechanisms that shape the genetic effects at disease-associated loci from genome-wide association studies (GWAS) remains challenging. The key avenue is to identify the essential molecular phenotypes that mediate the causal variant and disease under particular biological conditions. Therefore, integrating GWAS signals with context-specific quantitative trait loci (QTLs) (such as different tissue/cell types, disease states, and perturbations) from extensive molecular phenotypes would present important strategies for full understanding of disease genetics. Via persistent curation and systematic data processing of large-scale human molecular trait QTLs (xQTLs), we updated our previous QTLbase database (now QTLbase2, http://mulinlab.org/qtlbase) to comprehensively analyze and visualize context-specific QTLs across 22 molecular phenotypes and over 95 tissue/cell types. Overall, the resource features the following major updates and novel functions: (i) 960 more genome-wide QTL summary statistics from 146 independent studies; (ii) new data for 10 previously uncompiled QTL types; (iii) variant query scope expanded to fit 195 QTL datasets based on whole-genome sequencing; (iv) supports filtering and comparison of QTLs for different biological conditions, such as stimulation types and disease states; (v) a new linkage disequilibrium viewer to facilitate variant prioritization across tissue/cell types and QTL types.
Subject(s)
Genome-Wide Association Study , Quantitative Trait Loci , Humans , Chromosome Mapping , Linkage Disequilibrium , Phenotype , Polymorphism, Single Nucleotide , Quantitative Trait Loci/genetics , Catalogs as TopicABSTRACT
Interpreting the molecular mechanism of genomic variations and their causal relationship with diseases/traits are important and challenging problems in the human genetic study. To provide comprehensive and context-specific variant annotations for biologists and clinicians, here, by systematically integrating over 4TB genomic/epigenomic profiles and frequently-used annotation databases from various biological domains, we develop a variant annotation database, called VannoPortal. In general, the database has following major features: (i) systematically integrates 40 genome-wide variant annotations and prediction scores regarding allele frequency, linkage disequilibrium, evolutionary signature, disease/trait association, tissue/cell type-specific epigenome, base-wise functional prediction, allelic imbalance and pathogenicity; (ii) equips with our recent novel index system and parallel random-sweep searching algorithms for efficient management of backend databases and information extraction; (iii) greatly expands context-dependent variant annotation to incorporate large-scale epigenomic maps and regulatory profiles (such as EpiMap) across over 33 tissue/cell types; (iv) compiles many genome-scale base-wise prediction scores for regulatory/pathogenic variant classification beyond protein-coding region; (v) enables fast retrieval and direct comparison of functional evidence among linked variants using highly interactive web panel in addition to plain table; (vi) introduces many visualization functions for more efficient identification and interpretation of functional variants in single web page. VannoPortal is freely available at http://mulinlab.org/vportal.
Subject(s)
Databases, Genetic , Genetic Diseases, Inborn/genetics , Genetic Variation/genetics , Molecular Sequence Annotation , Algorithms , Epigenome/genetics , Genetic Diseases, Inborn/classification , Genome, Human/genetics , Genome-Wide Association Study , Genotype , Humans , Polymorphism, Single Nucleotide/genetics , Quantitative Trait Loci/genetics , SoftwareABSTRACT
BACKGROUND & AIMS: Copy number alterations (CNAs), elicited by genome instability, are a major source of intratumor heterogeneity. How CNAs evolve in hepatocellular carcinoma (HCC) remains unknown. METHODS: We performed single-cell DNA sequencing (scDNA-seq) on 1275 cells isolated from 10 patients with HCC, ploidy-resolved scDNA-seq on 356 cells from 1 additional patient, and single-cell RNA sequencing on 27,344 cells from 3 additional patients. Three statistical fitting models were compared to investigate the CNA accumulation pattern. RESULTS: Cells in the tumor were categorized into the following 3 subpopulations: euploid, pseudoeuploid, and aneuploid. Our scDNA-seq analysis revealed that CNA accumulation followed a dual-phase copy number evolution model, that is, a punctuated phase followed by a gradual phase. Patients who exhibited prolonged gradual phase showed higher intratumor heterogeneity and worse disease-free survival. Integrating bulk RNA sequencing of 17 patients with HCC, published datasets of 1196 liver tumors, and immunohistochemical staining of 202 HCC tumors, we found that high expression of CAD, a gene involved in pyrimidine synthesis, was correlated with rapid tumorigenesis and reduced survival. The dual-phase copy number evolution model was validated by our single-cell RNA sequencing data and published scDNA-seq datasets of other cancer types. Furthermore, ploidy-resolved scDNA-seq revealed the common clonal origin of diploid- and polyploid-aneuploid cells, suggesting that polyploid tumor cells were generated by whole genome doubling of diploid tumor cells. CONCLUSIONS: Our work revealed a novel dual-phase copy number evolution model, showed HCC with longer gradual phase was more severe, identified CAD as a promising biomarker for early recurrence of HCC, and supported the diploid origin of polyploid HCC.
Subject(s)
Biomarkers, Tumor/genetics , Carcinoma, Hepatocellular/genetics , Clonal Evolution , Genetic Heterogeneity , Liver Neoplasms/genetics , Sequence Analysis, DNA , Single-Cell Analysis , Adult , Aged , Carcinoma, Hepatocellular/metabolism , DNA Copy Number Variations , Disease Progression , Disease-Free Survival , Female , Gene Dosage , Gene Expression Regulation, Neoplastic , Genomic Instability , Humans , Liver Neoplasms/mortality , Liver Neoplasms/pathology , Liver Neoplasms/therapy , Male , Middle Aged , Models, Genetic , Neoplasm Recurrence, Local , Ploidies , Time FactorsABSTRACT
The advances of large-scale genomics studies have enabled compilation of cell type-specific, genome-wide DNA functional elements at high resolution. With the growing volume of functional annotation data and sequencing variants, existing variant annotation algorithms lack the efficiency and scalability to process big genomic data, particularly when annotating whole-genome sequencing variants against a huge database with billions of genomic features. Here, we develop VarNote to rapidly annotate genome-scale variants in large and complex functional annotation resources. Equipped with a novel index system and a parallel random-sweep searching algorithm, VarNote shows substantial performance improvements (two to three orders of magnitude) over existing algorithms at different scales. It supports both region-based and allele-specific annotations and introduces advanced functions for the flexible extraction of annotations. By integrating massive base-wise and context-dependent annotations in the VarNote framework, we introduce three efficient and accurate pipelines to prioritize the causal regulatory variants for common diseases, Mendelian disorders, and cancers.
Subject(s)
Computational Biology/methods , Genetic Predisposition to Disease/genetics , Algorithms , Databases, Genetic , Genetic Variation , Genome, Human , Humans , Molecular Sequence Annotation , Whole Genome SequencingABSTRACT
BACKGROUND: Constipation was associated with incidence of dementia and cognitive decline. Laxatives are the mainstay of constipation management and are commonly used among older populations for both treatment and prevention of constipation. However, the association between use of laxatives and incident dementia, and whether laxatives use may modify the effect of genetic predisposition on dementia remains unclear. METHODS: We applied 1:3 propensity score matching to balance the baseline characteristics of the laxative users versus non-users and to reduce potential confounders using multi-variates adjusted Cox hazards regression models. We categorized genetic risk into three groups (low, middle, and high) through a genetic risk score of common genetic variants. Information on laxatives use was assessed at baseline and categories into four varieties, including bulk forming laxatives, softeners and emollients, osmotic laxatives, and stimulant laxatives. RESULTS: Of 486,994 participants, there were 14,422 laxatives users in UK Biobank. After propensity score matching, participants with use of laxatives (n = 14,422) and matched non-laxative (n = 43,266) exposed individuals were enrolled. Over follow-up to 15 years, there were 1377 participants developed dementia (539 for Alzheimer's disease, and 343 for vascular dementia). The use of laxatives had greater risk of dementia (HR, 1.72; 95% CI:1.54-1.92), Alzheimer's disease (HR, 1.36; 95% CI: 1.13-1.63), and vascular dementia (HR, 1.53; 95% CI: 1.23-1.92). Compared to non-laxative exposed participants, those with use of softeners and emollients drugs, stimulant laxatives, and osmotic laxatives were associated with 96% (HR, 1.96; 95 CI: 1.23-3.12; P = 0.005), 80% (HR, 1.80; 95% CI: 1.37-2.37; P < 0.001), and 107% (HR, 2.07; 95% CI: 1.47-2.92; P < 0.001) higher risk of developed incident dementia, respectively. In joint effect analysis, compared to participants with low/middle genetic susceptibility and non-laxatives use, the HR (95% CIs) of dementia was 4.10 (3.49-4.81) for those with high genetic susceptibility plus use of laxatives. There was an additive interaction between laxatives use and genetic susceptibility on dementia (RERI: 0.736, 95% CI: 0.127 to 1.246; AP: 0.180, 95% CI: 0.047 to 0.312). CONCLUSIONS: Use of laxatives was associated with higher risk of dementia and modify the effect of genetic susceptibility on dementia. Our findings suggested that attention should be paid to the relationship between laxatives use and dementia, especially in people at high genetic susceptibility.
Subject(s)
Alzheimer Disease , Dementia, Vascular , Humans , Laxatives , Genetic Predisposition to Disease , Cohort Studies , Emollients , Propensity Score , ConstipationABSTRACT
Although overexpression of EZH2, a catalytic subunit of the polycomb repressive complex 2 (PRC2), is an eminent feature of various cancers, the regulation of its abundance and function remains insufficiently understood. We report here that the PRC2 complex is physically associated with ubiquitin-specific protease USP7 in cancer cells where USP7 acts to deubiquitinate and stabilize EZH2. Interestingly, we found that USP7-catalyzed H2BK120ub1 deubiquitination is a prerequisite for chromatin loading of PRC2 thus H3K27 trimethylation, and this process is not affected by H2AK119 ubiquitination catalyzed by PRC1. Genome-wide analysis of the transcriptional targets of the USP7/PRC2 complex identified a cohort of genes including FOXO1 that are involved in cell growth and proliferation. We demonstrated that the USP7/PRC2 complex drives cancer cell proliferation and tumorigenesis in vitro and in vivo. We showed that the expression of both USP7 and EZH2 elevates during tumor progression, corresponding to a diminished FOXO1 expression, and the level of the expression of USP7 and EZH2 strongly correlates with histological grades and prognosis of tumor patients. These results reveal a dual role for USP7 in the regulation of the abundance and function of EZH2, supporting the pursuit of USP7 as a therapeutic target for cancer intervention.
Subject(s)
Carcinogenesis , Enhancer of Zeste Homolog 2 Protein/metabolism , Polycomb Repressive Complex 2/metabolism , Ubiquitin-Specific Peptidase 7/metabolism , Animals , Female , Forkhead Box Protein O1/metabolism , HEK293 Cells , Humans , Mice , Mice, Inbred BALB C , Sf9 Cells , Ubiquitination , Xenograft Model Antitumor AssaysABSTRACT
Functional crosstalk between histone modifications and chromatin remodeling has emerged as a key regulatory mode of transcriptional control during cell fate decisions, but the underlying mechanisms are not fully understood. Here we discover an HRP2-DPF3a-BAF epigenetic pathway that coordinates methylated histone H3 lysine 36 (H3K36me) and ATP-dependent chromatin remodeling to regulate chromatin dynamics and gene transcription during myogenic differentiation. Using siRNA screening targeting epigenetic modifiers, we identify hepatoma-derived growth factor-related protein 2 (HRP2) as a key regulator of myogenesis. Knockout of HRP2 in mice leads to impaired muscle regeneration. Mechanistically, through its HIV integrase binding domain (IBD), HRP2 associates with the BRG1/BRM-associated factor (BAF) chromatin remodeling complex by interacting directly with the BAF45c (DPF3a) subunit. Through its Pro-Trp-Trp-Pro (PWWP) domain, HRP2 preferentially binds to H3K36me2. Consistent with the biochemical studies, ChIP-seq analyses show that HRP2 colocalizes with DPF3a across the genome and that the recruitment of HRP2/DPF3a to chromatin is dependent on H3K36me2. Integrative transcriptomic and cistromic analyses, coupled with ATAC-seq, reveal that HRP2 and DPF3a activate myogenic genes by increasing chromatin accessibility through recruitment of BRG1, the ATPase subunit of the BAF complex. Taken together, these results illuminate a key role for the HRP2-DPF3a-BAF complex in the epigenetic coordination of gene transcription during myogenic differentiation.
Subject(s)
Cell Cycle Proteins/metabolism , Chromatin Assembly and Disassembly , DNA-Binding Proteins/metabolism , Histone Code , Myoblasts/metabolism , Transcription Factors/metabolism , Animals , Binding Sites , Cell Cycle Proteins/genetics , Cell Differentiation , DNA-Binding Proteins/genetics , HEK293 Cells , Humans , Male , Mice , Muscle Development , Myoblasts/cytology , Protein Binding , Transcription Factors/geneticsABSTRACT
Recent advances in genome sequencing and functional genomic profiling have promoted many large-scale quantitative trait locus (QTL) studies, which connect genotypes with tissue/cell type-specific cellular functions from transcriptional to post-translational level. However, no comprehensive resource can perform QTL lookup across multiple molecular phenotypes and investigate the potential cascade effect of functional variants. We developed a versatile resource, named QTLbase, for interpreting the possible molecular functions of genetic variants, as well as their tissue/cell-type specificity. Overall, QTLbase has five key functions: (i) curating and compiling genome-wide QTL summary statistics for 13 human molecular traits from 233 independent studies; (ii) mapping QTL-relevant tissue/cell types to 78 unified terms according to a standard anatomogram; (iii) normalizing variant and trait information uniformly, yielding >170 million significant QTLs; (iv) providing a rich web client that enables phenome- and tissue-wise visualization; and (v) integrating the most comprehensive genomic features and functional predictions to annotate the potential QTL mechanisms. QTLbase provides a one-stop shop for QTL retrieval and comparison across multiple tissues and multiple layers of molecular complexity, and will greatly help researchers interrogate the biological mechanism of causal variants and guide the direction of functional validation. QTLbase is freely available at http://mulinlab.org/qtlbase.
Subject(s)
Databases, Genetic , Genome-Wide Association Study , Genomics , Genotype , Phenotype , Quantitative Trait Loci , Quantitative Trait, Heritable , Computational Biology/methods , Genomics/methods , Humans , Software , Web BrowserABSTRACT
Genome-wide association studies (GWASs) have revolutionized the field of complex trait genetics over the past decade, yet for most of the significant genotype-phenotype associations the true causal variants remain unknown. Identifying and interpreting how causal genetic variants confer disease susceptibility is still a big challenge. Herein we introduce a new database, CAUSALdb, to integrate the most comprehensive GWAS summary statistics to date and identify credible sets of potential causal variants using uniformly processed fine-mapping. The database has six major features: it (i) curates 3052 high-quality, fine-mappable GWAS summary statistics across five human super-populations and 2629 unique traits; (ii) estimates causal probabilities of all genetic variants in GWAS significant loci using three state-of-the-art fine-mapping tools; (iii) maps the reported traits to a powerful ontology MeSH, making it simple for users to browse studies on the trait tree; (iv) incorporates highly interactive Manhattan and LocusZoom-like plots to allow visualization of credible sets in a single web page more efficiently; (v) enables online comparison of causal relations on variant-, gene- and trait-levels among studies with different sample sizes or populations and (vi) offers comprehensive variant annotations by integrating massive base-wise and allele-specific functional annotations. CAUSALdb is freely available at http://mulinlab.org/causaldb.
Subject(s)
Chromosome Mapping , Databases, Genetic , Disease/genetics , Genome, Human , Genome-Wide Association Study , Genotype , Humans , Linkage Disequilibrium , Quantitative Trait LociABSTRACT
The need to distribute therapy evenly systemically throughout the large muscle volume within the body makes Duchenne muscular dystrophy (DMD) therapy a challenge. Cell and exon-skipping therapies are promising but have limited effects, and thus enhancing their therapeutic potency is of paramount importance to increase the accessibility of these therapies to DMD patients. In this study, we demonstrate that co-administered glycine improves phosphorodiamidate morpholino oligomer (PMO) potency in mdx mice with marked functional improvement and an up to 50-fold increase of dystrophin in abdominal muscles compared to PMO in saline. Glycine boosts satellite cell proliferation and muscle regeneration by increasing activation of mammalian target of rapamycin complex 1 (mTORC1) and replenishing the one-carbon unit pool. The expanded regenerating myofiber population then results in increased PMO uptake. Glycine also augments the transplantation efficiency of exogenous satellite cells and primary myoblasts in mdx mice. Our data provide evidence that glycine enhances satellite cell proliferation, cell transplantation, and oligonucleotide efficacy in mdx mice, and thus it has therapeutic utility for cell therapy and drug delivery in muscle-wasting diseases.
Subject(s)
Cell Proliferation/drug effects , Cell Transplantation/methods , Glycine Agents/administration & dosage , Glycine/administration & dosage , Morpholinos/administration & dosage , Muscular Dystrophy, Duchenne/drug therapy , Myoblasts/transplantation , Satellite Cells, Skeletal Muscle/metabolism , Satellite Cells, Skeletal Muscle/transplantation , Animals , Disease Models, Animal , Drug Synergism , HEK293 Cells , Humans , Mechanistic Target of Rapamycin Complex 1/metabolism , Mice , Mice, Inbred C57BL , Mice, Inbred mdx , Muscle, Skeletal/physiology , Regeneration/drug effects , Signal Transduction/drug effects , Treatment OutcomeABSTRACT
Predicting the functional or pathogenic regulatory variants in the human non-coding genome facilitates the interpretation of disease causation. While numerous prediction methods are available, their performance is inconsistent or restricted to specific tasks, which raises the demand of developing comprehensive integration for those methods. Here, we compile whole genome base-wise aggregations, regBase, that incorporate largest prediction scores. Building on different assumptions of causality, we train three composite models to score functional, pathogenic and cancer driver non-coding regulatory variants respectively. We demonstrate the superior and stable performance of our models using independent benchmarks and show great success to fine-map causal regulatory variants on specific locus or at base-wise resolution. We believe that regBase database together with three composite models will be useful in different areas of human genetic studies, such as annotation-based casual variant fine-mapping, pathogenic variant discovery as well as cancer driver mutation identification. regBase is freely available at https://github.com/mulinlab/regBase.
Subject(s)
Databases, Genetic , Genome, Human , Genome-Wide Association Study/methods , Software , Datasets as Topic , Humans , Neoplasms/genetics , Polymorphism, Single Nucleotide/geneticsABSTRACT
The systematic investigation of gene mutation and expression is important to discover novel biomarkers and therapeutic targets in cancers. Here, we integrated genomics, transcriptomics, proteomics, and metabolomics to analyze three hepatocellular carcinoma (HCC) cell lines with differential metastatic potentials. The results revealed the profile of the prometastasis metabolism potentially associated with HCC metastasis. The multiomic analysis identified 12 genes with variations at multiple levels from three metabolic pathways, including glycolysis, starch, and sucrose metabolism, and glutathione metabolism. Furthermore, uridine diphosphate (UDP)-glucose pyrophosphorylase 2 (UGP2), was observed to be persistently up-regulated with increased metastatic potential. UGP2 overexpression promoted cell migration and invasion and enhanced glycogenesis in vitro The role of UGP2 in metastasis was further confirmed using a tumor xenograft mouse model. Taken together, the compendium of multiomic data provides valuable insights in understanding the roles of shifted cellular metabolism in HCC metastasis.
Subject(s)
Carcinoma, Hepatocellular , Liver Neoplasms , Carcinoma, Hepatocellular/genetics , Carcinoma, Hepatocellular/metabolism , Carcinoma, Hepatocellular/pathology , Cell Line, Tumor , Gene Expression Regulation, Neoplastic , Genomics , Glucose/metabolism , Glycolysis , Humans , Liver Neoplasms/genetics , Liver Neoplasms/metabolism , Liver Neoplasms/pathology , Metabolomics , Neoplasm Invasiveness/genetics , Nucleotidyltransferases/physiology , Proteomics , Starch/metabolismABSTRACT
Genome-wide association studies have generated over thousands of susceptibility loci for many human complex traits, and yet for most of these associations the true causal variants remain unknown. Tissue/cell type-specific prediction and prioritization of non-coding regulatory variants will facilitate the identification of causal variants and underlying pathogenic mechanisms for particular complex diseases and traits. By leveraging recent large-scale functional genomics/epigenomics data, we develop an intuitive web server, GWAS4D (http://mulinlab.tmu.edu.cn/gwas4d or http://mulinlab.org/gwas4d), that systematically evaluates GWAS signals and identifies context-specific regulatory variants. The updated web server includes six major features: (i) updates the regulatory variant prioritization method with our new algorithm; (ii) incorporates 127 tissue/cell type-specific epigenomes data; (iii) integrates motifs of 1480 transcriptional regulators from 13 public resources; (iv) uniformly processes Hi-C data and generates significant interactions at 5 kb resolution across 60 tissues/cell types; (v) adds comprehensive non-coding variant functional annotations; (vi) equips a highly interactive visualization function for SNP-target interaction. Using a GWAS fine-mapped set for 161 coronary artery disease risk loci, we demonstrate that GWAS4D is able to efficiently prioritize disease-causal regulatory variants.
Subject(s)
Genetic Diseases, Inborn , Genome-Wide Association Study , Quantitative Trait Loci/genetics , Software , Computational Biology/trends , Genomics/methods , Humans , Polymorphism, Single Nucleotide/geneticsABSTRACT
Mitotic chromosomes are one of the most commonly recognized sub-cellular structures in eukaryotic cells. Yet basic information necessary to understand their structure and assembly, such as their composition, is still lacking. Recent proteomic studies have begun to fill this void, identifying hundreds of RNA-binding proteins bound to mitotic chromosomes. However, by contrast, there are only two RNA species (U3 snRNA and rRNA) that are known to be associated with the mitotic chromosome, suggesting that there are many mitotic chromosome-associated RNAs (mCARs) not yet identified. Here, using a targeted protocol based on 5'-tag sequencing to profile the mammalian mCAR population, we report the identification of 1279 mCARs, the majority of which are ncRNAs, including lncRNAs that exhibit greater conservation across 60 vertebrate species than the entire population of lncRNAs. There is also a significant enrichment of snoRNAs and specific SINE RNAs. Finally, â¼40% of the mCARs are presently unannotated, many of which are as abundant as the annotated mCARs, suggesting that there are also many novel ncRNAs in the mCARs. Overall, the mCARs identified here, together with the previous proteomic and genomic data, constitute the first comprehensive catalogue of the molecular composition of the eukaryotic mitotic chromosomes.
Subject(s)
Chromosomes, Mammalian/chemistry , Mitosis/genetics , RNA, Untranslated/analysis , 3T3 Cells , Animals , High-Throughput Nucleotide Sequencing , Metaphase/genetics , Mice , RNA, Untranslated/chemistry , RNA, Untranslated/isolation & purification , Sequence Analysis, RNA , Sequence Tagged SitesABSTRACT
Glioblastoma multiforme (GBM) is one of the most lethal brain tumors, characterized by profound heterogeneity. While single-cell transcriptomic studies have revealed extensive intra-tumor heterogeneity, shed light on intra-tumor diversity, spatial intricacies remain largely unexplored. Leveraging clinical GBM specimens, this study employs spatial transcriptomics technology to delve into gene expression heterogeneity. Our investigation unveils a significant enrichment of tissue stem cell signature in regions bordering necrosis and the peritumoral area, positively correlated with the mesenchymal subtype signature. Moreover, upregulated genes in these regions are linked with extracellular matrix (ECM)-receptor interaction, proteoglycans, as well as vascular endothelial growth factor (VEGF) and angiopoietin-Tie (ANGPT) signaling pathways. In contrast, signatures related to glycogen metabolism and oxidative phosphorylation show no relevance to pathological zoning, whereas creatine metabolism signature is notably exclusive to vascular-enriched areas. These spatial profiles not only offer valuable references but also pave the way for future in-depth functional and mechanistic investigations into GBM progression.
ABSTRACT
Disruption of circadian rhythm during pregnancy produces adverse health outcomes in offspring; however, the role of maternal circadian rhythms in the immune system of infants and their susceptibility to inflammation remains poorly understood. Here we show that disruption of circadian rhythms in pregnant mice profoundly aggravates the severity of neonatal inflammatory disorders in both male and female offspring, such as necrotizing enterocolitis and sepsis. The diminished maternal production of docosahexaenoic acid (DHA) and the impaired immunosuppressive function of neonatal myeloid-derived suppressor cells (MDSCs) contribute to this phenomenon. Mechanistically, DHA enhances the immunosuppressive function of MDSCs via PPARγ-mediated mitochondrial oxidative phosphorylation. Transfer of MDSCs or perinatal supplementation of DHA relieves neonatal inflammation induced by maternal rhythm disruption. These observations collectively demonstrate a previously unrecognized role of maternal circadian rhythms in the control of neonatal inflammation via metabolic reprograming of myeloid cells.
Subject(s)
Animals, Newborn , Circadian Rhythm , Inflammation , Myeloid Cells , Animals , Female , Mice , Inflammation/metabolism , Pregnancy , Myeloid Cells/metabolism , Male , Docosahexaenoic Acids/metabolism , Docosahexaenoic Acids/pharmacology , Myeloid-Derived Suppressor Cells/metabolism , Mice, Inbred C57BLABSTRACT
Cerebral ischaemiaâreperfusion injury (IRI), during which neurons undergo oxygen-glucose deprivation/reoxygenation (OGD/R), is a notable pathological process in many neurological diseases. N1-methyladenosine (m1A) is an RNA modification that can affect gene expression and RNA stability. The m1A landscape and potential functions of m1A modification in neurons remain poorly understood. We explored RNA (mRNA, lncRNA, and circRNA) m1A modification in normal and OGD/R-treated mouse neurons and the effect of m1A on diverse RNAs. We investigated the m1A landscape in primary neurons, identified m1A-modified RNAs, and found that OGD/R increased the number of m1A RNAs. m1A modification might also affect the regulatory mechanisms of noncoding RNAs, e.g., lncRNA-RNA binding proteins (RBPs) interactions and circRNA translation. We showed that m1A modification mediates the circRNA/lncRNAâmiRNA-mRNA competing endogenous RNA (ceRNA) mechanism and that 3' untranslated region (3'UTR) modification of mRNAs can hinder miRNA-mRNA binding. Three modification patterns were identified, and genes with different patterns had intrinsic mechanisms with potential m1A-regulatory specificity. Systematic analysis of the m1A landscape in normal and OGD/R neurons lays a critical foundation for understanding RNA modification and provides new perspectives and a theoretical basis for treating and developing drugs for OGD/R pathology-related diseases.
Subject(s)
MicroRNAs , RNA, Long Noncoding , Animals , Mice , RNA, Circular/genetics , RNA, Long Noncoding/genetics , RNA, Messenger/genetics , 3' Untranslated Regions , Glucose , Neurons , OxygenABSTRACT
Microbiota have an important function in shaping and priming neonatal immunity, although the cellular and molecular mechanisms underlying these effects remain obscure. Here we report that prenatal antibiotic exposure causes significant elevation of group 2 innate lymphoid cells (ILC2s) in neonatal lungs, in both cell numbers and functionality. Downregulation of type 1 interferon signaling in ILC2s due to diminished production of microbiota-derived butyrate represents the underlying mechanism. Mice lacking butyrate receptor GPR41 (Gpr41-/-) or type 1 interferon receptor IFNAR1 (Ifnar1-/-) recapitulate the phenotype of neonatal ILC2s upon maternal antibiotic exposure. Furthermore, prenatal antibiotic exposure induces epigenetic changes in ILC2s and has a long-lasting deteriorative effect on allergic airway inflammation in adult offspring. Prenatal supplementation of butyrate ameliorates airway inflammation in adult mice born to antibiotic-exposed dams. These observations demonstrate an essential role for the microbiota in the control of type 2 innate immunity at the neonatal stage, which suggests a therapeutic window for treating asthma in early life.
Subject(s)
Anti-Bacterial Agents , Immunity, Innate , Interferon Type I , Lymphocytes , Animals , Mice , Butyrates , Cytokines , Down-Regulation , Inflammation , Lung , Anti-Bacterial Agents/adverse effects , Anti-Bacterial Agents/pharmacology , Maternal Exposure , Interferon Type I/drug effects , Interferon Type I/metabolismABSTRACT
Genetic sharing is extensively observed for autoimmune diseases, but the causal variants and their underlying molecular mechanisms remain largely unknown. Through systematic investigation of autoimmune disease pleiotropic loci, we found most of these shared genetic effects are transmitted from regulatory code. We used an evidence-based strategy to functionally prioritize causal pleiotropic variants and identify their target genes. A top-ranked pleiotropic variant, rs4728142, yielded many lines of evidence as being causal. Mechanistically, the rs4728142-containing region interacts with the IRF5 alternative promoter in an allele-specific manner and orchestrates its upstream enhancer to regulate IRF5 alternative promoter usage through chromatin looping. A putative structural regulator, ZBTB3, mediates the allele-specific loop to promote IRF5-short transcript expression at the rs4728142 risk allele, resulting in IRF5 overactivation and M1 macrophage polarization. Together, our findings establish a causal mechanism between the regulatory variant and fine-scale molecular phenotype underlying the dysfunction of pleiotropic genes in human autoimmunity.
Subject(s)
Autoimmune Diseases , DNA-Binding Proteins , Interferon Regulatory Factors , Humans , Alleles , Autoimmunity , Chromatin , Polymorphism, Single Nucleotide , Promoter Regions, GeneticABSTRACT
CCCTC-binding factor (CTCF) is a transcription regulator with a complex role in gene regulation. The recognition and effects of CTCF on DNA sequences, chromosome barriers, and enhancer blocking are not well understood. Existing computational tools struggle to assess the regulatory potential of CTCF-binding sites and their impact on chromatin loop formation. Here we have developed a deep-learning model, DeepAnchor, to accurately characterize CTCF binding using high-resolution genomic/epigenomic features. This has revealed distinct chromatin and sequence patterns for CTCF-mediated insulation and looping. An optimized implementation of a previous loop model based on DeepAnchor score excels in predicting CTCF-anchored loops. We have established a compendium of CTCF-anchored loops across 52 human tissue/cell types, and this suggests that genomic disruption of these loops could be a general mechanism of disease pathogenesis. These computational models and resources can help investigate how CTCF-mediated cis-regulatory elements shape context-specific gene regulation in cell development and disease progression.