Systems genetics analysis of human body fat distribution genes identifies adipocyte processes.

Excess abdominal fat is a sexually dimorphic risk factor for cardio-metabolic disease and is approximated by the waist-to-hip ratio adjusted for body mass index (WHRadjBMI). Whereas this trait is highly heritable, few causal genes are known. We aimed to identify novel drivers of WHRadjBMI using systems genetics. We used two independent cohorts of adipose tissue gene expression and constructed sex- and depot-specific Bayesian networks to model gene-gene interactions from 8,492 genes. Using key driver analysis, we identified genes that, in silico and putatively in vitro, regulate many others. 51-119 key drivers in each network were replicated in both cohorts. In other cell types, 23 of these genes are found in crucial adipocyte pathways: Wnt signaling or mitochondrial function. We overexpressed or down-regulated seven key driver genes in human subcutaneous pre-adipocytes. Key driver genes ANAPC2 and RSPO1 inhibited adipogenesis, whereas PSME3 increased adipogenesis. RSPO1 increased Wnt signaling activity. In differentiated adipocytes, MIGA1 and UBR1 down-regulation led to mitochondrial dysfunction. These five genes regulate adipocyte function, and we hypothesize that they regulate fat distribution.

Human gene regulatory evolution is driven by the divergence of regulatory element function in both cis and trans.

Gene regulatory divergence between species can result from cis-acting local changes to regulatory element DNA sequences or global trans-acting changes to the regulatory environment. Understanding how these mechanisms drive regulatory evolution has been limited by challenges in identifying trans-acting changes. We present a comprehensive approach to directly identify cis- and trans-divergent regulatory elements between human and rhesus macaque lymphoblastoid cells using assay for transposase-accessible chromatin coupled to self-transcribing active regulatory region (ATAC-STARR) sequencing. In addition to thousands of cis changes, we discover an unexpected number (∼10,000) of trans changes and show that cis and trans elements exhibit distinct patterns of sequence divergence and function. We further identify differentially expressed transcription factors that underlie ∼37% of trans differences and trace how cis changes can produce cascades of trans changes. Overall, we find that most divergent elements (67%) experienced changes in both cis and trans, revealing a substantial role for trans divergence-alone and together with cis changes-in regulatory differences between species.

Trans-eQTL mapping in gene sets identifies network effects of genetic variants.

Nearly all trait-associated variants identified in genome-wide association studies (GWASs) are noncoding. The cis regulatory effects of these variants have been extensively characterized, but how they affect gene regulation in trans has been the subject of fewer studies because of the difficulty in detecting trans-expression quantitative loci (eQTLs). We developed trans-PCO for detecting trans effects of genetic variants on gene networks. Our simulations demonstrate that trans-PCO substantially outperforms existing trans-eQTL mapping methods. We applied trans-PCO to two gene expression datasets from whole blood, DGN (N = 913) and eQTLGen (N = 31,684), and identified 14,985 high-quality trans-eSNP-module pairs associated with 197 co-expression gene modules and biological processes. We performed colocalization analyses between GWAS loci of 46 complex traits and the trans-eQTLs. We demonstrated that the identified trans effects can help us understand how trait-associated variants affect gene regulatory networks and biological pathways.

Allele-Specific Regulation of the Candidate Autism Liability Gene RAI1 by the Enhancer Variant rs4925102 (C/G).

Retinoic acid-induced 1 (RAI1) is a dosage-sensitive gene that causes autistic phenotypes when deleted or duplicated. Observations from clinical cases and animal models also suggest that changes of RAI1 expression levels contribute to autism. Previously, we used a bioinformatic approach to identify several single nucleotide polymorphisms (SNPs) located within the 5'-region of RAI1 that correlate with RAI1 mRNA expression in the human brain. In particular, the SNP rs4925102 was identified as a candidate cis-acting regulatory variant, the genotype of which may affect the binding of transcription factors that influence RAI1 mRNA expression. In this study, we provide experimental evidence based on reporter gene, chromatin immunoprecipitation (ChIP), and chromatin conformation capture (3C) assays that rs4925102 regulates RAI1 mRNA expression in an allele-specific manner in human cell lines, including the neuroblastoma-derived cell line SH-SY5Y. We also describe a statistically significant association between rs4925102 genotype and autism spectrum disorder (ASD) diagnosis in a case-control study and near-statistically significant association in an Autism Genome Project (AGP) transmission disequilibrium (TDT) study using Caucasian subjects.

CoVar: A generalizable machine learning approach to identify the coordinated regulators driving variational gene expression.

Network inference is used to model transcriptional, signaling, and metabolic interactions among genes, proteins, and metabolites that identify biological pathways influencing disease pathogenesis. Advances in machine learning (ML)-based inference models exhibit the predictive capabilities of capturing latent patterns in genomic data. Such models are emerging as an alternative to the statistical models identifying causative factors driving complex diseases. We present CoVar, an ML-based framework that builds upon the properties of existing inference models, to find the central genes driving perturbed gene expression across biological states. Unlike differentially expressed genes (DEGs) that capture changes in individual gene expression across conditions, CoVar focuses on identifying variational genes that undergo changes in their expression network interaction profiles, providing insights into changes in the regulatory dynamics, such as in disease pathogenesis. Subsequently, it finds core genes from among the nearest neighbors of these variational genes, which are central to the variational activity and influence the coordinated regulatory processes underlying the observed changes in gene expression. Through the analysis of simulated as well as yeast expression data perturbed by the deletion of the mitochondrial genome, we show that CoVar captures the intrinsic variationality and modularity in the expression data, identifying key driver genes not found through existing differential analysis methodologies.

Genome-wide CRISPR activation screen identifies JADE3 as an antiviral activator of NF-kB-dependent IFITM3 expression.

The innate immune system features a web of interacting pathways that require exquisite regulation. To identify novel nodes in this immune landscape, we conducted a gain-of-function, genome-wide CRISPR activation screen with influenza A virus. We identified both appreciated and novel antiviral genes, including Jade family PHD zinc finger 3 (JADE3) a protein involved in directing the histone acetyltransferase histone acetyltransferase binding to ORC1 complex to modify chromatin and regulate transcription. JADE3 is both necessary and sufficient to restrict influenza A virus infection. Our results suggest a distinct function for JADE3 as expression of the closely related paralogs JADE1 and JADE2 does not confer resistance to influenza A virus infection. JADE3 is required for both constitutive and inducible expression of the well-characterized antiviral gene interferon-induced transmembrane protein 3 (IFITM3). Furthermore, we find JADE3 activates the NF-kB signaling pathway, which is required for the promotion of IFITM3 expression by JADE3. Therefore, we propose JADE3 activates an antiviral genetic program involving NF-kB-dependent IFITM3 expression to restrict influenza A virus infection.

Cell-type-specific and disease-associated expression quantitative trait loci in the human lung.

Common genetic variants confer substantial risk for chronic lung diseases, including pulmonary fibrosis. Defining the genetic control of gene expression in a cell-type-specific and context-dependent manner is critical for understanding the mechanisms through which genetic variation influences complex traits and disease pathobiology. To this end, we performed single-cell RNA sequencing of lung tissue from 66 individuals with pulmonary fibrosis and 48 unaffected donors. Using a pseudobulk approach, we mapped expression quantitative trait loci (eQTLs) across 38 cell types, observing both shared and cell-type-specific regulatory effects. Furthermore, we identified disease interaction eQTLs and demonstrated that this class of associations is more likely to be cell-type-specific and linked to cellular dysregulation in pulmonary fibrosis. Finally, we connected lung disease risk variants to their regulatory targets in disease-relevant cell types. These results indicate that cellular context determines the impact of genetic variation on gene expression and implicates context-specific eQTLs as key regulators of lung homeostasis and disease.

Analysis of ceRNA Network and Identification of Potential Treatment Target and Biomarkers of Endothelial Cell Injury in Sepsis.

Background: Sepsis is a complex clinical syndrome caused by a dysregulated host immune response to infection. This study aimed to identify a competing endogenous RNA (ceRNA) network that can greatly contribute to understanding the pathophysiological process of sepsis and determining sepsis biomarkers. Methods: The GSE100159, GSE65682, GSE167363, and GSE94717 datasets were obtained from the Gene Expression Omnibus (GEO) database. Weighted gene coexpression network analysis was performed to find modules possibly involved in sepsis. A long noncoding RNA-microRNA-messenger RNA (lncRNA-miRNA-mRNA) network was constructed based on the findings. Single-cell analysis was performed. Human umbilical vein endothelial cells were treated with lipopolysaccharide (LPS) to create an in vitro model of sepsis for network verification. Reverse transcription-polymerase chain reaction, fluorescence in situ hybridization, and luciferase reporter genes were used to verify the bioinformatic analysis. Result: By integrating data from three GEO datasets, we successfully constructed a ceRNA network containing 18 lncRNAs, 7 miRNAs, and 94 mRNAs based on the ceRNA hypothesis. The lncRNA ZFAS1 was found to be highly expressed in LPS-stimulated endothelial cells and may thus play a role in endothelial cell injury. Univariate and multivariate Cox analyses showed that only SLC26A6 was an independent predictor of prognosis in sepsis. Overall, our findings indicated that the ZFAS1/hsa-miR-449c-5p/SLC26A6 ceRNA regulatory axis may play a role in the progression of sepsis. Conclusion: The sepsis ceRNA network, especially the ZFAS1/hsa-miR-449c-5p/SLC26A6 regulatory axis, is expected to reveal potential biomarkers and therapeutic targets for sepsis management.

Decoding Non-coding Variants: Recent Approaches to Studying Their Role in Gene Regulation and Human Diseases.

Genome-wide association studies (GWAS) have mapped over 90% of disease- and quantitative-trait-associated variants within the non-coding genome. Non-coding regulatory DNA (e.g., promoters and enhancers) and RNA (e.g., 5' and 3' UTRs and splice sites) are essential in regulating temporal and tissue-specific gene expressions. Non-coding variants can potentially impact the phenotype of an organism by altering the molecular recognition of the cis-regulatory elements, leading to gene dysregulation. However, determining causality between non-coding variants, gene regulation, and human disease has remained challenging. Experimental and computational methods have been developed to understand the molecular mechanism involved in non-coding variant interference at the transcriptional and post-transcriptional levels. This review discusses recent approaches to evaluating disease-associated single-nucleotide variants (SNVs) and determines their impact on transcription factor (TF) binding, gene expression, chromatin conformation, post-transcriptional regulation, and translation.

Genetic variation drives differences in obesity-related gene regulation.

Heikkinen and colleagues recently demonstrated that genetic variation, rather than dietary changes, governs gene regulation in liver. This finding highlights the impact of noncoding variants on chromatin accessibility, histone modifications, transcription factor binding, and gene expression and has implications for future research directions in understanding the genetic basis of disease.

Cross-Omic Transcription Factor Analysis: An Insight on Transcription Factor Accessibility and Expression Correlation.

It is well known how sequencing technologies propelled cellular biology research in recent years, providing incredible insight into the basic mechanisms of cells. Single-cell RNA sequencing is at the front in this field, with single-cell ATAC sequencing supporting it and becoming more popular. In this regard, multi-modal technologies play a crucial role, allowing the possibility to simultaneously perform the mentioned sequencing modalities on the same cells. Yet, there still needs to be a clear and dedicated way to analyze these multi-modal data. One of the current methods is to calculate the Gene Activity Matrix (GAM), which summarizes the accessibility of the genes at the genomic level, to have a more direct link with the transcriptomic data. However, this concept is not well defined, and it is unclear how various accessible regions impact the expression of the genes. Moreover, the transcription process is highly regulated by the transcription factors that bind to the different DNA regions. Therefore, this work presents a continuation of the meta-analysis of Genomic-Annotated Gene Activity Matrix (GAGAM) contributions, aiming to investigate the correlation between the TF expression and motif information in the different functional genomic regions to understand the different Transcription Factors (TFs) dynamics involved in different cell types.

Formaldehyde regulates one-carbon metabolism and epigenetics.

Recently, Pham et al. used an array of model systems to uncover a role for the enzyme methionine adenosyltransferase (MAT)-1A, which is mainly expressed in liver, in both sensing formaldehyde and regulating transcriptional responses that protect against it. This provides a new lens for understanding the effects of formaldehyde on gene regulation.

Non-transcriptional IRF7 interacts with NF-κB to inhibit viral inflammation.

Interferon (IFN) regulatory factors (IRF) are key transcription factors in cellular antiviral responses. IRF7, a virus-inducible IRF, expressed primarily in myeloid cells, is required for transcriptional induction of interferon α and antiviral genes. IRF7 is activated by virus-induced phosphorylation in the cytoplasm, leading to its translocation to the nucleus for transcriptional activity. Here, we revealed a nontranscriptional activity of IRF7 contributing to its antiviral functions. IRF7 interacted with the pro-inflammatory transcription factor NF-κB-p65 and inhibited the induction of inflammatory target genes. Using knockdown, knockout, and overexpression strategies, we demonstrated that IRF7 inhibited NF-κB-dependent inflammatory target genes, induced by virus infection or toll-like receptor stimulation. A mutant IRF7, defective in transcriptional activity, interacted with NF-κB-p65 and suppressed NF-κB-induced gene expression. A single-action IRF7 mutant, active in anti-inflammatory function, but defective in transcriptional activity, efficiently suppressed Sendai virus and murine hepatitis virus replication. We, therefore, uncovered an anti-inflammatory function for IRF7, independent of transcriptional activity, contributing to the antiviral response of IRF7.

Differential expression of follicular fluid exosomal microRNA in women with diminished ovarian reserve.

PURPOSE: Decreased ovarian reserve function is mainly characterized by female endocrine disorders and fertility decline. Follicular fluid (FF) exosomal microRNAs (miRNAs) have been shown to regulate the function of granulosa cells (GCs). The present study explored differentially expressed miRNAs (DEmiRNAs) in patients with diminished ovarian reserve (DOR). METHODS: FF was collected from 12 DOR patients and 12 healthy controls. DEmiRNAs between the two groups were identified and analyzed using high-throughput sequencing technology and validated by real-time quantitative PCR (RT-qPCR). RESULTS: A total of 592 DEmiRNAs were identified using high-throughput miRNA sequencing, of which 213 were significantly upregulated and 379 were significantly downregulated. The sequencing results were further validated by RT-qPCR. These DEmiRNA target genes were mainly involved in the cancer pathway, phosphoinositide 3-kinase (PI3K)/protein kinase B (AKT) signaling pathway, regulation of actin cytoskeleton signaling pathway, and biological processes related to protein binding, nucleoplasm, cytoplasm, and cell membrane. CONCLUSION: FF exosomal miRNAs are significantly differentially expressed in DOR patients versus non-DOR patients, underscoring their crucial role in regulating the pathogenesis of DOR.

Accounting for isoform expression increases power to identify genetic regulation of gene expression.

A core problem in genetics is molecular quantitative trait locus (QTL) mapping, in which genetic variants associated with changes in the molecular phenotypes are identified. One of the most-studied molecular QTL mapping problems is expression QTL (eQTL) mapping, in which the molecular phenotype is gene expression. It is common in eQTL mapping to compute gene expression by aggregating the expression levels of individual isoforms from the same gene and then performing linear regression between SNPs and this aggregated gene expression level. However, SNPs may regulate isoforms from the same gene in different directions due to alternative splicing, or only regulate the expression level of one isoform, causing this approach to lose power. Here, we examine a broader question: which genes have at least one isoform whose expression level is regulated by genetic variants? In this study, we propose and evaluate several approaches to answering this question, demonstrating that "isoform-aware" methods-those that account for the expression levels of individual isoforms-have substantially greater power to answer this question than standard "gene-level" eQTL mapping methods. We identify settings in which different approaches yield an inflated number of false discoveries or lose power. In particular, we show that calling an eGene if there is a significant association between a SNP and any isoform fails to control False Discovery Rate, even when applying standard False Discovery Rate correction. We show that similar trends are observed in real data from the GEUVADIS and GTEx studies, suggesting the possibility that similar effects are present in these consortia.

Protein kinase C signaling "in" and "to" the nucleus: Master kinases in transcriptional regulation.

PKC is a multifunctional family of Ser-Thr kinases widely implicated in the regulation of fundamental cellular functions, including proliferation, polarity, motility, and differentiation. Notwithstanding their primary cytoplasmic localization and stringent activation by cell surface receptors, PKC isozymes impel prominent nuclear signaling ultimately impacting gene expression. While transcriptional regulation may be wielded by nuclear PKCs, it most often relies on cytoplasmic phosphorylation events that result in nuclear shuttling of PKC downstream effectors, including transcription factors. As expected from the unique coupling of PKC isozymes to signaling effector pathways, glaring disparities in gene activation/repression are observed upon targeting individual PKC family members. Notably, specific PKCs control the expression and activation of transcription factors implicated in cell cycle/mitogenesis, epithelial-to-mesenchymal transition and immune function. Additionally, PKCs isozymes tightly regulate transcription factors involved in stepwise differentiation of pluripotent stem cells toward specific epithelial, mesenchymal, and hematopoietic cell lineages. Aberrant PKC expression and/or activation in pathological conditions, such as in cancer, leads to profound alterations in gene expression, leading to an extensive rewiring of transcriptional networks associated with mitogenesis, invasiveness, stemness, and tumor microenvironment dysregulation. In this review, we outline the current understanding of PKC signaling "in" and "to" the nucleus, with significant focus on established paradigms of PKC-mediated transcriptional control. Dissecting these complexities would allow the identification of relevant molecular targets implicated in a wide spectrum of diseases.

Tissue-specific and cis-regulatory changes underlie parallel, adaptive gene expression evolution in house mice.

Changes in gene regulation have long been appreciated as a driving force of adaptive evolution, however the relative contributions of cis- and trans-acting changes to gene regulation over short evolutionary timescales remain unclear. Instances of recent, parallel phenotypic evolution provide an opportunity to assess whether parallel patterns are seen at the level of gene expression, and to assess the relative contribution of cis- and trans- changes to gene regulation in the early stages of divergence. Here, we studied gene expression in liver and brown adipose tissue in two wild-derived strains of house mice that independently adapted to cold, northern environments, and we compared them to a strain of house mice from a warm, tropical environment. To investigate gene regulatory evolution, we studied expression in parents and allele-specific expression in F1 hybrids of crosses between warm-adapted and cold-adapted strains. First, we found that the different cold-adapted mice showed both unique and shared changes in expression, but that the proportion of shared changes (i.e. parallelism) was greater than expected by chance. Second, we discovered that expression evolution occurred largely at tissue-specific and cis-regulated genes, and that these genes were over-represented in parallel cases of evolution. Finally, we integrated the expression data with scans for selection in natural populations and found substantial parallelism in the two northern populations for genes under selection. Furthermore, selection outliers were associated with cis-regulated genes more than expected by chance; cis-regulated genes under selection influenced phenotypes such as body size, immune functioning, and activity level. These results demonstrate that parallel patterns of gene expression in mice that have independently adapted to cold environments are driven largely by tissue-specific and cis-regulatory changes, providing insight into the mechanisms of adaptive gene regulatory evolution at the earliest stages of divergence.

Economy of Effort or Sophisticated Programming? The Prevalence of Bidirectional Promoter Complexes in the Human Genome.

An abundance of antisense promoters in the vicinity of the transcriptional start site of coding genes suggests that they play an important role in gene regulation. The divergent transcription of housekeeping genes by a common central promoter region allows for coordinated regulation of genes in related pathways and is also linked to higher promoter activity. However, closely positioned transcription start sites can also result in competition between overlapping promoter elements and generate a binary switch element. Furthermore, the direct competition resulting from the presence of an antisense promoter immediately downstream of the transcription start site of the gene produces an element that can exist in only one of two stable transcriptional states: sense or antisense. In this review, we summarize analyses of the prevalence of antisense transcription in higher eukaryotes and viruses, with a focus on the antisense promoters competing with the promoters of coding genes. The structures of bidirectional promoters driving the simultaneous expression of housekeeping genes are compared with examples of human bidirectional elements that have been shown to act as switches. Since many bidirectional elements contain a noncoding RNA as the divergent transcript, we describe examples of functional noncoding antisense transcripts that affect the epigenetic landscape and alter the expression of their host gene. Finally, we discuss opportunities for additional research on competing sense/antisense promoters, uncovering their potential role in programming cell differentiation.

Transcription regulation by long non-coding RNAs: mechanisms and disease relevance.

Long non-coding RNAs (lncRNAs) outnumber protein-coding transcripts, but their functions remain largely unknown. In this Review, we discuss the emerging roles of lncRNAs in the control of gene transcription. Some of the best characterized lncRNAs have essential transcription cis-regulatory functions that cannot be easily accomplished by DNA-interacting transcription factors, such as XIST, which controls X-chromosome inactivation, or imprinted lncRNAs that direct allele-specific repression. A growing number of lncRNA transcription units, including CHASERR, PVT1 and HASTER (also known as HNF1A-AS1) act as transcription-stabilizing elements that fine-tune the activity of dosage-sensitive genes that encode transcription factors. Genetic experiments have shown that defects in such transcription stabilizers often cause severe phenotypes. Other lncRNAs, such as lincRNA-p21 (also known as Trp53cor1) and Maenli (Gm29348) contribute to local activation of gene transcription, whereas distinct lncRNAs influence gene transcription in trans. We discuss findings of lncRNAs that elicit a function through either activation of their transcription, transcript elongation and processing or the lncRNA molecule itself. We also discuss emerging evidence of lncRNA involvement in human diseases, and their potential as therapeutic targets.

Role of H3K4 monomethylation in gene regulation.

Methylation of histone H3 on the lysine-4 residue (H3K4me) is found throughout the eukaryotic domain, and its initial discovery as a conserved epigenetic mark of active transcription from yeast to mammalian cells has contributed to the histone code hypothesis. However, recent studies have raised questions on whether the different forms of H3K4me play a direct role in gene regulation or are simply by-products of the transcription process. Here, we review the often-conflicting experimental evidence, focusing on the monomethylation of lysine 4 on histone H3 that has been linked to the transcriptional state of enhancers in metazoans. We suggest that this epigenetic mark acts in a context-dependent manner to directly facilitate the transcriptional output of the genome and the establishment of cellular identity.