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.

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.

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.

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.

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.

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.

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.

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.

Regulus infers signed regulatory relations from few samples' information using discretization and likelihood constraints.

MOTIVATION: Transcriptional regulation is performed by transcription factors (TF) binding to DNA in context-dependent regulatory regions and determines the activation or inhibition of gene expression. Current methods of transcriptional regulatory circuits inference, based on one or all of TF, regions and genes activity measurements require a large number of samples for ranking the candidate TF-gene regulation relations and rarely predict whether they are activations or inhibitions. We hypothesize that transcriptional regulatory circuits can be inferred from fewer samples by (1) fully integrating information on TF binding, gene expression and regulatory regions accessibility, (2) reducing data complexity and (3) using biology-based likelihood constraints to determine the global consistency between a candidate TF-gene relation and patterns of genes expressions and region activations, as well as qualify regulations as activations or inhibitions. RESULTS: We introduce Regulus, a method which computes TF-gene relations from gene expressions, regulatory region activities and TF binding sites data, together with the genomic locations of all entities. After aggregating gene expressions and region activities into patterns, data are integrated into a RDF (Resource Description Framework) endpoint. A dedicated SPARQL (SPARQL Protocol and RDF Query Language) query retrieves all potential relations between expressed TF and genes involving active regulatory regions. These TF-region-gene relations are then filtered using biological likelihood constraints allowing to qualify them as activation or inhibition. Regulus provides signed relations consistent with public databases and, when applied to biological data, identifies both known and potential new regulators. Regulus is devoted to context-specific transcriptional circuits inference in human settings where samples are scarce and cell populations are closely related, using discretization into patterns and likelihood reasoning to decipher the most robust regulatory relations.

Gene architecture is a determinant of the transcriptional response to bulky DNA damages.

Bulky DNA damages block transcription and compromise genome integrity and function. The cellular response to these damages includes global transcription shutdown. Still, active transcription is necessary for transcription-coupled repair and for induction of damage-response genes. To uncover common features of a general bulky DNA damage response, and to identify response-related transcripts that are expressed despite damage, we performed a systematic RNA-seq study comparing the transcriptional response to three independent damage-inducing agents: UV, the chemotherapy cisplatin, and benzo[a]pyrene, a component of cigarette smoke. Reduction in gene expression after damage was associated with higher damage rates, longer gene length, and low GC content. We identified genes with relatively higher expression after all three damage treatments, including NR4A2, a potential novel damage-response transcription factor. Up-regulated genes exhibit higher exon content that is associated with preferential repair, which could enable rapid damage removal and transcription restoration. The attenuated response to BPDE highlights that not all bulky damages elicit the same response. These findings frame gene architecture as a major determinant of the transcriptional response that is hardwired into the human genome.

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.

A regulatory role for the unstructured C-terminal domain of the CtBP transcriptional corepressor.

The C-terminal binding protein (CtBP) is a transcriptional corepressor that plays critical roles in development, tumorigenesis, and cell fate. CtBP proteins are structurally similar to alpha hydroxyacid dehydrogenases and feature a prominent intrinsically disordered region in the C terminus. In the mammalian system, CtBP proteins lacking the C-terminal domain (CTD) are able to function as transcriptional regulators and oligomerize, putting into question the significance of this unstructured domain for gene regulation. Yet, the presence of an unstructured CTD of ∼100 residues, including some short motifs, is conserved across Bilateria, indicating the importance of maintaining this domain over evolutionary time. To uncover the significance of the CtBP CTD, we functionally tested naturally occurring Drosophila isoforms of CtBP that possess or lack the CTD, namely CtBP(L) and CtBP(S). We used the CRISPRi system to recruit dCas9-CtBP(L) and dCas9-CtBP(S) to endogenous promoters to directly compare their transcriptional impacts in vivo. Interestingly, CtBP(S) was able to significantly repress transcription of the Mpp6 promoter, while CtBP(L) was much weaker, suggesting that the long CTD may modulate CtBP's repression activity. In contrast, in cell culture, the isoforms behaved similarly on a transfected Mpp6 reporter gene. The context-specific differences in activity of these two developmentally regulated isoforms suggests that the CTD may help provide a spectrum of repression activity suitable for developmental programs.

Sleep deprivation reduced LPS-induced IgG2b production by up-regulating BMAL1 and CLOCK expression.

Sleep deprivation (SD) weakens the immune system and leads to increased susceptibility to infectious or inflammatory diseases. However, it is still unclear how SD affects humoral immunity. In the present study, sleep disturbance was conducted using an sleep deprivation instrument, and the bacterial endotoxin lipopolysaccharide (LPS) was used to activate the immune response. It was found that SD-pretreatment reduced LPS-induced IgG2b+ B cells and IgG2b isotype antibody production in lymphocytes of spleen. And, SD-pretreatment decreased the proportion of CD4+T cells, production of CD4+T cells derived TGF-ß1 and its contribution in helping IgG2b production. Additionally, BMAL1 and CLOCK were selectively up-regulated in lymphocytes after SD. Importantly, BMAL1 and CLOCK deficiency contributed to TGF-ß1 expression and production of IgG2b+ B cells. Thus, our results provide a novel insight to explain the involvement of BMAL1 and CLOCK under SD stress condition, and their roles in inhibiting TGF-ß1 expression and contributing to reduction of LPS induced IgG2b production.

snRNA-seq analysis in multinucleated myogenic FSHD cells identifies heterogeneous FSHD transcriptome signatures associated with embryonic-like program activation and oxidative stress-induced apoptosis.

The sporadic nature of DUX4 expression in FSHD muscle challenges comparative transcriptome analyses between FSHD and control samples. A variety of DUX4 and FSHD-associated transcriptional changes have been identified, but bulk RNA-seq strategies prohibit comprehensive analysis of their spatiotemporal relation, interdependence and role in the disease process. In this study, we used single-nucleus RNA-sequencing of nuclei isolated from patient- and control-derived multinucleated primary myotubes to investigate the cellular heterogeneity in FSHD. Taking advantage of the increased resolution in snRNA-sequencing of fully differentiated myotubes, two distinct populations of DUX4-affected nuclei could be defined by their transcriptional profiles. Our data provides insights into the differences between these two populations and suggests heterogeneity in two well-known FSHD-associated transcriptional aberrations: increased oxidative stress and inhibition of myogenic differentiation. Additionally, we provide evidence that DUX4-affected nuclei share transcriptome features with early embryonic cells beyond the well-described cleavage stage, progressing into the 8-cell and blastocyst stages. Altogether, our data suggests that the FSHD transcriptional profile is defined by a mixture of individual and sometimes mutually exclusive DUX4-induced responses and cellular state-dependent downstream effects.

Identification of constrained sequence elements across 239 primate genomes.

Noncoding DNA is central to our understanding of human gene regulation and complex diseases1,2, and measuring the evolutionary sequence constraint can establish the functional relevance of putative regulatory elements in the human genome3-9. Identifying the genomic elements that have become constrained specifically in primates has been hampered by the faster evolution of noncoding DNA compared to protein-coding DNA10, the relatively short timescales separating primate species11, and the previously limited availability of whole-genome sequences12. Here we construct a whole-genome alignment of 239 species, representing nearly half of all extant species in the primate order. Using this resource, we identified human regulatory elements that are under selective constraint across primates and other mammals at a 5% false discovery rate. We detected 111,318 DNase I hypersensitivity sites and 267,410 transcription factor binding sites that are constrained specifically in primates but not across other placental mammals and validate their cis-regulatory effects on gene expression. These regulatory elements are enriched for human genetic variants that affect gene expression and complex traits and diseases. Our results highlight the important role of recent evolution in regulatory sequence elements differentiating primates, including humans, from other placental mammals.

Epigenetic and gene regulatory functions of small RNAs.

In this review article, I summarize the intervention I made during the "Hommage à François Gros" held at the Institut Pasteur in Paris on the 25th of April, 2023. I discuss how the discovery of the existence of an RNA intermediate between genetic information and protein translation has changed our perspective on the role of RNA in gene regulation in these past years. I also discuss new emerging paradigms, highlighting the role of RNA in heritable information similar to the well-known DNA function.

Dans cet article de synthèse, je résume l'intervention que j'ai faite lors du colloque «  Hommage à François Gros  ¼ qui s'est tenu le 25 avril 2023 à l'Institut Pasteur à Paris. J'explique comment la découverte de l'existence d'un ARN intermédiaire entre l'information génétique et la traduction des protéines a changé notre perspective sur le rôle de l'ARN dans la régulation des gènes au cours de ces dernières années. Je discute également de nouveaux paradigmes émergents, en soulignant le rôle de l'ARN dans la transmission d'informations héréditaires, analogue à la fonction bien connue de l'ADN.

Sex-biased gene regulation varies across human populations as a result of adaptive evolution.

OBJECTIVES: Studies of human sexual dimorphism and gender disparities in health focus on ostensibly universal molecular sex differences, such as sex chromosomes and circulating hormone levels, while ignoring the extraordinary diversity in biology, behavior, and culture acquired by different human populations over their unique evolutionary histories. MATERIALS AND METHODS: Using RNA-Seq data and whole genome sequences from 1000G and HGDP, we investigate variation in sex-biased gene expression across 11 human populations and test whether population-level variation in sex-biased expression may have resulted from adaptive evolution in regions containing sex-specific regulatory variants. RESULTS: We find that sex-biased gene expression in humans is highly variable, mostly population-specific, and demonstrates between population reversals. Expression quantitative trait locus mapping reveals sex-specific regulatory regions with evidence of recent positive natural selection, suggesting that variation in sex-biased expression may have evolved as an adaptive response to ancestral environments experienced by human populations. DISCUSSION: These results indicate that sex-biased gene expression is more flexible than previously thought and is not generally shared among human populations. Instead, molecular phenotypes associated with sex depend on complex interactions between population-specific molecular evolution and physiological responses to contemporary socioecologies.