Deciphering molecular circuits from genetic variation underlying transcriptional responsiveness to stimuli

Insights into the genomic homogeneity of Moroccan indigenous sheep breeds though the lens of runs of homozygosity

Numerous studies have indicated that Morocco's indigenous sheep breeds are genetically homogenous, posing a risk to their survival in the challenging harsh climate conditions where they predominantly inhabit. To understand the genetic behind genetic homogeneity through the lens of runs of homozygosity (ROH), we analyzed the whole genome sequences of five indigenous sheep breeds (Beni Guil, Ouled Djellal, D'man, Sardi, Timahdite and Admixed).The results from principal component, admixture, Fst, and neighbour joining tree analyses consistently showed a homogenous genetic structure. This structure was characterized by an average length of 1.83 Mb for runs of homozygosity (ROH) segments, with a limited number of long ROH segments (24-48 Mb and > 48 Mb). The most common ROH segments were those ranging from 1-6 Mb. The most significant regions of homozygosity (ROH Islands) were mostly observed in two chromosomes, namely Chr1 and Chr5. Specifically, ROH Islands were exclusively discovered in the Ouled Djellal breed on Chr1, whereas Chr5 exhibited ROH Islands in all breeds. The analysis of ROH Island and iHS technique was employed to detect signatures of selection on Chr1 and Chr5. The results indicate that Chr5 had a high level of homogeneity, with the same genes being discovered across all breeds. In contrast, Chr1 displays some genetic variances between breeds. Genes identified on Chr5 included SLC39A1, IL23A, CAST, IL5, IL13, and IL4 which are responsible for immune response while genes identified on Chr1 include SOD1, SLAMF9, RTP4, CLDN1, and PRKAA2. ROH segment profile and effective population sizes patterns suggests that the genetic uniformity of studied breeds is the outcome of events that transpired between 250 and 300 generations ago. This research not only contributes to the understanding of ROH distribution across breeds but helps design and implement native sheep breeding and conservation strategies in Morocco. Future research, incorporating a broader sample size and utilizing the pangenome for reference, is recommended to further elucidate these breeds' genomic landscapes and adaptive mechanisms.

Status and trends of RGS16 based on data visualization analysis: A review

G-protein signaling regulator 16 (RGS16) has been confirmed that RGS16 is associated with cancer, neurodegenerative diseases, and cardiovascular diseases. Moreover, many studies have shown that RGS16 can be used as a biomarker for cancer diagnosis and prognosis. We used CiteSpace and VOS viewer software to perform a bibliometric analysis of 290 publications in the core collection of Web of Science. All the articles come from 399 institutions, including 618 authors, 179 journals, 40 countries, 115 keywords, 1 language, two types of papers, and reviews. The United States has the largest number of publications. The Research Center of Allergy and Infectious Diseases (NIAID) publishes the most papers, Emory University is the most recent of all institutions with the most recent results in the RGS16 study. Cell biology is the most studied discipline, and the most studied topic is migration. Drury published RGS16-related articles with the most citations (n = 15), and Berman published articles with the most citations (n = 106). The biological applications of RGS16 are currently a hot area of RGS16 research, including inflammation, cancer, ulcerative colitis, metabolic acidosis, platelet activation, and thrombosis. The current scientometrics study provides an overview of RGS16 research from 1995 to 2022. This study provides an overview of current and potential future research hotspots in the field of RGS16 and can be used as a resource for interested researchers.

Single-cell RNA-sequencing of peripheral blood mononuclear cells reveals widespread, context-specific gene expression regulation upon pathogenic exposure

The host's gene expression and gene regulatory response to pathogen exposure can be influenced by a combination of the host's genetic background, the type of and exposure time to pathogens. Here we provide a detailed dissection of this using single-cell RNA-sequencing of 1.3M peripheral blood mononuclear cells from 120 individuals, longitudinally exposed to three different pathogens. These analyses indicate that cell-type-specificity is a more prominent factor than pathogen-specificity regarding contexts that affect how genetics influences gene expression (i.e., eQTL) and co-expression (i.e., co-expression QTL). In monocytes, the strongest responder to pathogen stimulations, 71.4% of the genetic variants whose effect on gene expression is influenced by pathogen exposure (i.e., response QTL) also affect the co-expression between genes. This indicates widespread, context-specific changes in gene expression level and its regulation that are driven by genetics. Pathway analysis on the CLEC12A gene that exemplifies cell-type-, exposure-time- and genetic-background-dependent co-expression interactions, shows enrichment of the interferon (IFN) pathway specifically at 3-h post-exposure in monocytes. Similar genetic background-dependent association between IFN activity and CLEC12A co-expression patterns is confirmed in systemic lupus erythematosus by in silico analysis, which implies that CLEC12A might be an IFN-regulated gene. Altogether, this study highlights the importance of context for gaining a better understanding of the mechanisms of gene regulation in health and disease.

Leveraging the cell lineage to predict cell-type specificity of regulatory variation from bulk genomics

Recent computational methods have enabled the inference of the cell-type-specificity of eQTLs based on bulk transcriptomes from highly heterogeneous tissues. However, these methods are limited in their scalability to highly heterogeneous tissues and limited in their broad applicability to any cell-type specificity of eQTLs. Here we present and demonstrate Cell Lineage Genetics (CeL-Gen), a novel computational approach that allows inference of eQTLs together with the subsets of cell types in which they have an effect, from bulk transcriptome data. To obtain improved scalability and broader applicability, CeL-Gen takes as input the known cell lineage tree and relies on the observation that dynamic changes in genetic effects occur relatively infrequently during cell differentiation. CeL-Gen can therefore be used not only to tease apart genetic effects derived from different cell types but also to infer the particular differentiation steps in which genetic effects are altered.

Combining Multiple Approaches and Models to Dissect the Genetic Architecture of Resistance to Infections in Fish

Infectious diseases represent a major threat for the sustainable development of fish farming. Efficient vaccines are not available against all diseases, and growing antibiotics resistance limits the use of antimicrobial drugs in aquaculture. It is therefore important to understand the basis of fish natural resistance to infections to help genetic selection and to develop new approaches against infectious diseases. However, the identification of the main mechanisms determining the resistance or susceptibility of a host to a pathogenic microbe is challenging, integrating the complexity of the variation of host genetics, the variability of pathogens, and their capacity of fast evolution and adaptation. Multiple approaches have been used for this purpose: (i) genetic approaches, QTL (quantitative trait loci) mapping or GWAS (genome-wide association study) analysis, to dissect the genetic architecture of disease resistance, and (ii) transcriptomics and functional assays to link the genetic constitution of a fish to the molecular mechanisms involved in its interactions with pathogens. To date, many studies in a wide range of fish species have investigated the genetic determinism of resistance to many diseases using QTL mapping or GWAS analyses. A few of these studies pointed mainly toward adaptive mechanisms of resistance/susceptibility to infections; others pointed toward innate or intrinsic mechanisms. However, in the majority of studies, underlying mechanisms remain unknown. By comparing gene expression profiles between resistant and susceptible genetic backgrounds, transcriptomics studies have contributed to build a framework of gene pathways determining fish responsiveness to a number of pathogens. Adding functional assays to expression and genetic approaches has led to a better understanding of resistance mechanisms in some cases. The development of knock-out approaches will complement these analyses and help to validate putative candidate genes critical for resistance to infections. In this review, we highlight fish isogenic lines as a unique biological material to unravel the complexity of host response to different pathogens. In the future, combining multiple approaches will lead to a better understanding of the dynamics of interaction between the pathogen and the host immune response, and contribute to the identification of potential targets of selection for improved resistance.

Cell Type- and Stimulation-Dependent Transcriptional Programs Regulated by Atg16L1 and Its Crohn's Disease Risk Variant T300A

Genome-wide association studies have identified common genetic variants impacting human diseases; however, there are indications that the functional consequences of genetic polymorphisms can be distinct depending on cell type-specific contexts, which produce divergent phenotypic outcomes. Thus, the functional impact of genetic variation and the underlying mechanisms of disease risk are modified by cell type-specific effects of genotype on pathological phenotypes. In this study, we extend these concepts to interrogate the interdependence of cell type- and stimulation-specific programs influenced by the core autophagy gene Atg16L1 and its T300A coding polymorphism identified by genome-wide association studies as linked with increased risk of Crohn's disease. We applied a stimulation-based perturbational profiling approach to define Atg16L1 T300A phenotypes in dendritic cells and T lymphocytes. Accordingly, we identified stimulus-specific transcriptional signatures revealing T300A-dependent functional phenotypes that mechanistically link inflammatory cytokines, IFN response genes, steroid biosynthesis, and lipid metabolism in dendritic cells and iron homeostasis and lysosomal biogenesis in T lymphocytes. Collectively, these studies highlight the combined effects of Atg16L1 genetic variation and stimulatory context on immune function.

Klotho: An Elephant in Aging Research

The year 2017 marked the 20th anniversary of the first publication describing Klotho. This single protein was and is remarkable in that its absence in mice conferred an accelerated aging, or progeroid, phenotype with a dramatically shortened life span. On the other hand, genetic overexpression extended both health span and life span by an impressive 30%. Not only has Klotho deficiency been linked to a number of debilitating age-related illnesses but many subsequent reports have lent credence to the idea that Klotho can compress the period of morbidity and extend the life span of both model organisms and humans. This suggests that Klotho functions as an integrator of organ systems, making it both a promising tool for advancing our understanding of the biology of aging and an intriguing target for interventional studies. In this review, we highlight advances in our understanding of Klotho as well as key challenges that have somewhat limited our view, and thus translational potential, of this potent protein.

Klotho: A Major Shareholder in Vascular Aging Enterprises

Accelerated vascular aging is a condition that occurs as a complication of several highly prevalent inflammatory conditions such as chronic kidney disease, cancer, HIV infection and diabetes. Age-associated vascular alterations underlie a continuum of expression toward clinically overt cardiovascular disease. This has contributed to the striking epidemiologic transition whereby such noncommunicable diseases have taken center stage as modern-day global epidemics and public health problems. The identification of α-Klotho, a remarkable protein that confers powerful anti-aging properties has stimulated significant interest. In fact, emerging data have provided fundamental rationale for Klotho-based therapeutic intervention for vascular diseases and multiple other potential indications. However, the application of such discoveries in Klotho research remains fragmented due to significant gaps in our molecular understanding of Klotho biology, as well as hurdles in clinical research and experimental barriers that must first be overcome. These advances will be critical to establish the scientific platform from which future Klotho-based interventional trials and therapeutic enterprises can be successfully launched.

Dynamics of Dual Specificity Phosphatases and Their Interplay with Protein Kinases in Immune Signaling

Dual specificity phosphatases (DUSPs) have a well-known role as regulators of the immune response through the modulation of mitogen-activated protein kinases (MAPKs). Yet the precise interplay between the various members of the DUSP family with protein kinases is not well understood. Recent multi-omics studies characterizing the transcriptomes and proteomes of immune cells have provided snapshots of molecular mechanisms underlying innate immune response in unprecedented detail. In this study, we focus on deciphering the interplay between members of the DUSP family with protein kinases in immune cells using publicly available omics datasets. Our analysis resulted in the identification of potential DUSP-mediated hub proteins including MAPK7, MAPK8, AURKA, and IGF1R. Furthermore, we analyzed the association of DUSP expression with TLR4 signaling and identified VEGF, FGFR, and SCF-KIT pathway modules to be regulated by the activation of TLR4 signaling. Finally, we identified several important kinases including LRRK2, MAPK8, and cyclin-dependent kinases as potential DUSP-mediated hubs in TLR4 signaling. The findings from this study have the potential to aid in the understanding of DUSP signaling in the context of innate immunity. Further, this will promote the development of therapeutic modalities for disorders with aberrant DUSP signaling.

Porcine circovirus type 2 ORF3 protein induces apoptosis in melanoma cells

BACKGROUND

The current treatment of malignant melanoma is limited by the lack of effective therapeutic approaches, and alternative treatments are needed. Proliferative diseases such as melanoma and other cancers may be treatable by virally-encoded apoptotic proteins that are targeted to rapidly multiplying cells. Caspase-dependent apoptosis, that is frequently used in chemotherapy, can boost the cell proliferation that caspase-independent cell death does not.

METHODS

In the current study, the porcine circovirus type 2 (PCV2), proapoptotic protein ORF3 was expressed in mouse and human cancer cell lines, and its apoptotic activity was assessed.

RESULTS

Quantitative assessment of the apoptotic cells by flow cytometry showed that apoptotic cell death was significantly increased in ORF3-expressing malignant cells, compared to ORF3 non-expressing cells. Our data show that PCV2 ORF3 induces apoptosis in a caspase-3 and -8 independent manner. ORF3 expression seems to cause an increase in abnormal mitosis in B16F10 melanoma cells by interacting with centrosomes and thereby disrupting the formation of the mitotic spindle. In addition, we show that ORF3 of PCV2 also exhibits significant anti-tumor effects in vivo. Although the expression of Regulator of G protein Signaling (RGS)-16 by recipient mice inhibited the development of grafted melanoma in vivo, it was not required for the antitumoral activity of ORF3.

CONCLUSION

PCV2 ORF3 causes abnormal mitosis in rapidly dividing cells and increases the apoptosis of cancer cells. Apoptin might, therefore, be considered to develop future antitumoral strategies.

Waveband specific transcriptional control of select genetic pathways in vertebrate skin (Xiphophorus maculatus)

Background

Evolution occurred exclusively under the full spectrum of sunlight. Conscription of narrow regions of the solar spectrum by specific photoreceptors suggests a common strategy for regulation of genetic pathways. Fluorescent light (FL) does not possess the complexity of the solar spectrum and has only been in service for about 60 years. If vertebrates evolved specific genetic responses regulated by light wavelengths representing the entire solar spectrum, there may be genetic consequences to reducing the spectral complexity of light.

Results

We utilized RNA-Seq to assess changes in the transcriptional profiles of Xiphophorus maculatus skin after exposure to FL (“cool white”), or narrow wavelength regions of light between 350 and 600 nm (i.e., 50 nm or 10 nm regions, herein termed “wavebands”). Exposure to each 50 nm waveband identified sets of genes representing discrete pathways that showed waveband specific transcriptional modulation. For example, 350–400 or 450–500 nm waveband exposures resulted in opposite regulation of gene sets marking necrosis and apoptosis (i.e., 350–400 nm; necrosis suppression, apoptosis activation, while 450–500 nm; apoptosis suppression, necrosis activation).

Further investigation of specific transcriptional modulation employing successive 10 nm waveband exposures between 500 and 550 nm showed; (a) greater numbers of genes may be transcriptionally modulated after 10 nm exposures, than observed for 50 nm or FL exposures, (b) the 10 nm wavebands induced gene sets showing greater functional specificity than 50 nm or FL exposures, and (c) the genetic effects of FL are primarily due to 30 nm between 500 and 530 nm.

Interestingly, many genetic pathways exhibited completely opposite transcriptional effects after different waveband exposures. For example, the epidermal growth factor (EGF) pathway exhibits transcriptional suppression after FL exposure, becomes highly active after 450–500 nm waveband exposure, and again, exhibits strong transcriptional suppression after exposure to the 520–530 nm waveband.

Conclusions

Collectively, these results suggest one may manipulate transcription of specific genetic pathways in skin by exposure of the intact animal to specific wavebands of light. In addition, we identify genes transcriptionally modulated in a predictable manner by specific waveband exposures. Such genes, and their regulatory elements, may represent valuable tools for genetic engineering and gene therapy protocols.

Electronic supplementary material

The online version of this article (10.1186/s12864-018-4735-5) contains supplementary material, which is available to authorized users.

Reconstructing the Molecular Function of Genetic Variation in Regulatory Networks

Over the past decade, genetic studies have recognized hundreds of polymorphic DNA loci called response QTLs (reQTLs) as potential contributors to interindividual variation in transcriptional responses to stimulations. Such reQTLs commonly affect the transduction of signals along the regulatory network that controls gene transcription. Identifying the pathways through which reQTLs perturb the underlying network has been a major challenge. Here, we present GEVIN ("Genome-wide Embedding of Variation In Networks"), a methodology that simultaneously identifies a reQTL and the particular pathway in which the reQTL affects downstream signal transduction along the network. Using synthetic data, we show that this algorithm outperforms existing pathway identification and reQTL identification methods. We applied GEVIN to the analysis of murine and human dendritic cells in response to pathogenic components. These analyses revealed significant reQTLs together with their perturbed Toll-like receptor signaling pathways. GEVIN thus offers a powerful framework that renders a comprehensive picture of disease-related DNA loci and their molecular functions within regulatory networks.

Identifying novel transcription factors involved in the inflammatory response by using binding site motif scanning in genomic regions defined by histone acetylation

The innate immune response to pathogenic challenge is a complex, multi-staged process involving thousands of genes. While numerous transcription factors that act as master regulators of this response have been identified, the temporal complexity of gene expression changes in response to pathogen-associated molecular pattern receptor stimulation strongly suggest that additional layers of regulation remain to be uncovered. The evolved pathogen response program in mammalian innate immune cells is understood to reflect a compromise between the probability of clearing the infection and the extent of tissue damage and inflammatory sequelae it causes. Because of that, a key challenge to delineating the regulators that control the temporal inflammatory response is that an innate immune regulator that may confer a selective advantage in the wild may be dispensable in the lab setting. In order to better understand the complete transcriptional response of primary macrophages to the bacterial endotoxin lipopolysaccharide (LPS), we designed a method that integrates temporally resolved gene expression and chromatin-accessibility measurements from mouse macrophages. By correlating changes in transcription factor binding site motif enrichment scores, calculated within regions of accessible chromatin, with the average temporal expression profile of a gene cluster, we screened for transcriptional factors that regulate the cluster. We have validated our predictions of LPS-stimulated transcriptional regulators using ChIP-seq data for three transcription factors with experimentally confirmed functions in innate immunity. In addition, we predict a role in the macrophage LPS response for several novel transcription factors that have not previously been implicated in immune responses. This method is applicable to any experimental situation where temporal gene expression and chromatin-accessibility data are available.

Genetic regulatory effects modified by immune activation contribute to autoimmune disease associations

The immune system plays a major role in human health and disease, and understanding genetic causes of interindividual variability of immune responses is vital. Here, we isolate monocytes from 134 genotyped individuals, stimulate these cells with three defined microbe-associated molecular patterns (LPS, MDP, and 5'-ppp-dsRNA), and profile the transcriptomes at three time points. Mapping expression quantitative trait loci (eQTL), we identify 417 response eQTLs (reQTLs) with varying effects between conditions. We characterize the dynamics of genetic regulation on early and late immune response and observe an enrichment of reQTLs in distal cis-regulatory elements. In addition, reQTLs are enriched for recent positive selection with an evolutionary trend towards enhanced immune response. Finally, we uncover reQTL effects in multiple GWAS loci and show a stronger enrichment for response than constant eQTLs in GWAS signals of several autoimmune diseases. This demonstrates the importance of infectious stimuli in modifying genetic predisposition to disease.Insight into the genetic influence on the immune response is important for the understanding of interindividual variability in human pathologies. Here, the authors generate transcriptome data from human blood monocytes stimulated with various immune stimuli and provide a time-resolved response eQTL map.

Writ large: Genomic dissection of the effect of cellular environment on immune response

Cells of the immune system routinely respond to cues from their local environment and feed back to their surroundings through transient responses, choice of differentiation trajectories, plastic changes in cell state, and malleable adaptation to their tissue of residence. Genomic approaches have opened the way for comprehensive interrogation of such orchestrated responses. Focusing on genomic profiling of transcriptional and epigenetic cell states, we discuss how they are applied to investigate immune cells faced with various environmental cues. We highlight some of the emerging principles on the role of dense regulatory circuitry, epigenetic memory, cell type fluidity, and reuse of regulatory modules in achieving and maintaining appropriate responses to a changing environment. These provide a first step toward a systematic understanding of molecular circuits in complex tissues.

Local Adaptation of Sun-Exposure-Dependent Gene Expression Regulation in Human Skin

Sun-exposure is a key environmental variable in the study of human evolution. Several skin-pigmentation genes serve as classical examples of positive selection, suggesting that sun-exposure has significantly shaped worldwide genomic variation. Here we investigate the interaction between genetic variation and sun-exposure, and how this impacts gene expression regulation. Using RNA-Seq data from 607 human skin samples, we identified thousands of transcripts that are differentially expressed between sun-exposed skin and non-sun-exposed skin. We then tested whether genetic variants may influence each individual’s gene expression response to sun-exposure. Our analysis revealed 10 sun-exposure-dependent gene expression quantitative trait loci (se-eQTLs), including genes involved in skin pigmentation (SLC45A2) and epidermal differentiation (RASSF9). The allele frequencies of the RASSF9 se-eQTL across diverse populations correlate with the magnitude of solar radiation experienced by these populations, suggesting local adaptation to varying levels of sunlight. These results provide the first examples of sun-exposure-dependent regulatory variation and suggest that this variation has contributed to recent human adaptation.

Varying levels of sun-exposure across the world have significantly shaped human evolution. Previous analyses have found several skin pigmentation genes with evidence of strong evolutionary pressures throughout human history, manifesting as large differences in the frequency of genomic variants across populations. But even within populations, individuals respond differently to sun-exposure, suggesting variation in addition to the major differences in skin pigmentation across populations. Here we investigated whether genetic variants associate with response to sun-exposure within Europeans. To measure the response we analyzed gene expression in sun-exposed and non-sun-exposed skin, and identified ten genetic variants that associated with the sun-exposure response of nearby genes. One of these genetic variants, which associated with the sun-exposure response of the gene RASSF9, showed evidence of adaptation in humans in response to solar radiation. Together this evidence suggests that the regulation of gene expression is influenced by sun-exposure and that the sun-exposure dependent effect on RASSF9 expression may have had an effect on human fitness. To our knowledge, this is the first example of an environment-dependent regulatory variant with evidence of adaptation in humans.

POEM: Identifying Joint Additive Effects on Regulatory Circuits

MOTIVATION

Expression Quantitative Trait Locus (eQTL) mapping tackles the problem of identifying variation in DNA sequence that have an effect on the transcriptional regulatory network. Major computational efforts are aimed at characterizing the joint effects of several eQTLs acting in concert to govern the expression of the same genes. Yet, progress toward a comprehensive prediction of such joint effects is limited. For example, existing eQTL methods commonly discover interacting loci affecting the expression levels of a module of co-regulated genes. Such "modularization" approaches, however, are focused on epistatic relations and thus have limited utility for the case of additive (non-epistatic) effects.

RESULTS

Here we present POEM (Pairwise effect On Expression Modules), a methodology for identifying pairwise eQTL effects on gene modules. POEM is specifically designed to achieve high performance in the case of additive joint effects. We applied POEM to transcription profiles measured in bone marrow-derived dendritic cells across a population of genotyped mice. Our study reveals widespread additive, trans-acting pairwise effects on gene modules, characterizes their organizational principles, and highlights high-order interconnections between modules within the immune signaling network. These analyses elucidate the central role of additive pairwise effect in regulatory circuits, and provide computational tools for future investigations into the interplay between eQTLs.

AVAILABILITY

The software described in this article is available at csgi.tau.ac.il/POEM/.

Integrated Genomics of Crohn's Disease Risk Variant Identifies a Role for CLEC12A in Antibacterial Autophagy

The polymorphism ATG16L1 T300A, associated with increased risk of Crohn’s disease, impairs pathogen defense mechanisms including selective autophagy, but specific pathway interactions altered by the risk allele remain unknown. Here, we use perturbational profiling of human peripheral blood cells to reveal that CLEC12A is regulated in an ATG16L1-T300A-dependent manner. Antibacterial autophagy is impaired in CLEC12A-deficient cells, and this effect is exacerbated in the presence of the ATG16L1^∗300A risk allele. Clec12a^−/− mice are more susceptible to Salmonella infection, supporting a role for CLEC12A in antibacterial defense pathways in vivo. CLEC12A is recruited to sites of bacterial entry, bacteria-autophagosome complexes, and sites of sterile membrane damage. Integrated genomics identified a functional interaction between CLEC12A and an E3-ubiquitin ligase complex that functions in antibacterial autophagy. These data identify CLEC12A as early adaptor molecule for antibacterial autophagy and highlight perturbational profiling as a method to elucidate defense pathways in complex genetic disease.

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Integrated genomics reveals risk-allele-specific autophagy pathway interactions

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CLEC12A is important for antibacterial autophagy in epithelial and immune cells

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CLEC12A knockdown amplifies antibacterial autophagy defects in ATG16L1^∗300A cells

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Clec12a^−/− mice are more susceptible to Salmonella infection in vivo

Genetic basis of autoimmunity

Autoimmune diseases affect up to approximately 10% of the population. While rare Mendelian autoimmunity syndromes can result from monogenic mutations disrupting essential mechanisms of central and peripheral tolerance, more common human autoimmune diseases are complex disorders that arise from the interaction between polygenic risk factors and environmental factors. Although the risk attributable to most individual nucleotide variants is modest, genome-wide association studies (GWAS) have the potential to provide an unbiased view of biological pathways that drive human autoimmune diseases. Interpretation of GWAS requires integration of multiple genomic datasets including dense genotyping, cis-regulatory maps of primary immune cells, and genotyped studies of gene expression in relevant cell types and cellular conditions. Improved understanding of the genetic basis of autoimmunity may lead to a more sophisticated understanding of underlying cellular phenotypes and, eventually, novel diagnostics and targeted therapies.

bacterial infection drives the expression dynamics of microRNAs and their isomiRs

The optimal coordination of the transcriptional response of host cells to infection is essential for establishing appropriate immunological outcomes. In this context, the role of microRNAs (miRNAs) – important epigenetic regulators of gene expression – in regulating mammalian immune systems is increasingly well recognised. However, the expression dynamics of miRNAs, and that of their isoforms, in response to infection remains largely unexplored. Here, we characterized the genome-wide miRNA transcriptional responses of human dendritic cells, over time, to various mycobacteria differing in their virulence as well as to other bacteria outside the genus Mycobacterium, using small RNA-sequencing. We detected the presence of a core temporal response to infection, shared across bacteria, comprising 49 miRNAs, highlighting a set of miRNAs that may play an essential role in the regulation of basic cellular responses to stress. Despite such broadly shared expression dynamics, we identified specific elements of variation in the miRNA response to infection across bacteria, including a virulence-dependent induction of the miR-132/212 family in response to mycobacterial infections. We also found that infection has a strong impact on both the relative abundance of the miRNA hairpin arms and the expression dynamics of miRNA isoforms. That we observed broadly consistent changes in relative arm expression and isomiR distribution across bacteria suggests that this additional, internal layer of variability in miRNA responses represents an additional source of subtle miRNA-mediated regulation upon infection. Collectively, this study increases our understanding of the dynamism and role of miRNAs in response to bacterial infection, revealing novel features of their internal variability and identifying candidate miRNAs that may contribute to differences in the pathogenicity of mycobacterial infections.

MicroRNAs (miRNAs) are small, non-coding RNAs that regulate important cellular processes by inhibiting the expression of gene targets. In recent years, it has become clear that miRNAs play a critical role in the regulation of the immune response to infection, a highly complex phenotype involving the activation of both generic and infection-specific responses. However, it remains unclear to what extent miRNAs are involved in the regulation of these two types of response. Here, focusing on the miRNA response to mycobacteria, pathogens of major public health importance, we present the first comparative, deep sequencing-based analysis of the miRNA response to a panel of bacterial infections. We define a set of miRNAs that play an essential role in basic cellular responses to stress and identify pathogen-specific miRNA responses that reflect mechanisms by which certain pathogens interfere with the host response to infection. In addition, we show that infection can alter the expression level and proportions of miRNA isoforms, transcripts originating from the same miRNA but with slight differences in their nucleotide sequences. This study highlights a novel aspect of miRNA expression dynamics upon infection and increases our understanding of miRNA-mediated mechanisms involved in host cellular responses to infection.

Linking traits based on their shared molecular mechanisms

There is growing recognition that co-morbidity and co-occurrence of disease traits are often determined by shared genetic and molecular mechanisms. In most cases, however, the specific mechanisms that lead to such trait-trait relationships are yet unknown. Here we present an analysis of a broad spectrum of behavioral and physiological traits together with gene-expression measurements across genetically diverse mouse strains. We develop an unbiased methodology that constructs potentially overlapping groups of traits and resolves their underlying combination of genetic loci and molecular mechanisms. For example, our method predicts that genetic variation in the Klf7 gene may influence gene transcripts in bone marrow-derived myeloid cells, which in turn affect 17 behavioral traits following morphine injection; this predicted effect of Klf7 is consistent with an in vitro perturbation of Klf7 in bone marrow cells. Our analysis demonstrates the utility of studying hidden causative mechanisms that lead to relationships between complex traits.

A statistical framework for revealing signaling pathways perturbed by DNA variants

Much of the inter-individual variation in gene expression is triggered via perturbations of signaling networks by DNA variants. We present a novel probabilistic approach for identifying the particular pathways by which DNA variants perturb the signaling network. Our procedure, called PINE, relies on a systematic integration of established biological knowledge of signaling networks with data on transcriptional responses to various experimental conditions. Unlike previous approaches, PINE provides statistical aspects that are critical for prioritizing hypotheses for followup experiments. Using simulated data, we show that higher accuracy is attained with PINE than with existing methods. We used PINE to analyze transcriptional responses of immune dendritic cells to several pathogenic stimulations. PINE identified statistically significant genetic perturbations in the pathogen-sensing signaling network, suggesting previously uncharacterized regulatory mechanisms for functional DNA variants.

Dissecting dynamic genetic variation that controls temporal gene response in yeast

Inter-individual variation in regulatory circuits controlling gene expression is a powerful source of functional information. The study of associations among genetic variants and gene expression provides important insights about cell circuitry but cannot specify whether and when potential variants dynamically alter their genetic effect during the course of response. Here we develop a computational procedure that captures temporal changes in genetic effects, and apply it to analyze transcription during inhibition of the TOR signaling pathway in segregating yeast cells. We found a high-order coordination of gene modules: sets of genes co-associated with the same genetic variant and sharing a common temporal genetic effect pattern. The temporal genetic effects of some modules represented a single state-transitioning pattern; for example, at 10-30 minutes following stimulation, genetic effects in the phosphate utilization module attained a characteristic transition to a new steady state. In contrast, another module showed an impulse pattern of genetic effects; for example, in the poor nitrogen sources utilization module, a spike up of a genetic effect at 10-20 minutes following stimulation reflected inter-individual variation in the timing (rather than magnitude) of response. Our analysis suggests that the same mechanism typically leads to both inter-individual variation and the temporal genetic effect pattern in a module. Our methodology provides a quantitative genetic approach to studying the molecular mechanisms that shape dynamic changes in transcriptional responses.

Extensive remodeling of DC function by rapid maturation-induced transcriptional silencing

The activation, or maturation, of dendritic cells (DCs) is crucial for the initiation of adaptive T-cell mediated immune responses. Research on the molecular mechanisms implicated in DC maturation has focused primarily on inducible gene-expression events promoting the acquisition of new functions, such as cytokine production and enhanced T-cell-stimulatory capacity. In contrast, mechanisms that modulate DC function by inducing widespread gene-silencing remain poorly understood. Yet the termination of key functions is known to be critical for the function of activated DCs. Genome-wide analysis of activation-induced histone deacetylation, combined with genome-wide quantification of activation-induced silencing of nascent transcription, led us to identify a novel inducible transcriptional-repression pathway that makes major contributions to the DC-maturation process. This silencing response is a rapid primary event distinct from repression mechanisms known to operate at later stages of DC maturation. The repressed genes function in pivotal processes--including antigen-presentation, extracellular signal detection, intracellular signal transduction and lipid-mediator biosynthesis--underscoring the central contribution of the silencing mechanism to rapid reshaping of DC function. Interestingly, promoters of the repressed genes exhibit a surprisingly high frequency of PU.1-occupied sites, suggesting a novel role for this lineage-specific transcription factor in marking genes poised for inducible repression.

Genetic architecture of ethanol-responsive transcriptome variation in Saccharomyces cerevisiae strains

Natural variation in gene expression is pervasive within and between species, and it likely explains a significant fraction of phenotypic variation between individuals. Phenotypic variation in acute systemic responses can also be leveraged to reveal physiological differences in how individuals perceive and respond to environmental perturbations. We previously found extensive variation in the transcriptomic response to acute ethanol exposure in two wild isolates and a common laboratory strain of Saccharomyces cerevisiae. Many expression differences persisted across several modules of coregulated genes, implicating trans-acting systemic differences in ethanol sensing and/or response. Here, we conducted expression QTL mapping of the ethanol response in two strain crosses to identify the genetic basis for these differences. To understand systemic differences, we focused on "hotspot" loci that affect many transcripts in trans. Candidate causal regulators contained within hotspots implicate upstream regulators as well as downstream effectors of the ethanol response. Overlap in hotspot targets revealed additive genetic effects of trans-acting loci as well as "epi-hotspots," in which epistatic interactions between two loci affected the same suites of downstream targets. One epi-hotspot implicated interactions between Mkt1p and proteins linked to translational regulation, prompting us to show that Mkt1p localizes to P bodies upon ethanol stress in a strain-specific manner. Our results provide a glimpse into the genetic architecture underlying natural variation in a stress response and present new details on how yeast respond to ethanol stress.

Common genetic variants modulate pathogen-sensing responses in human dendritic cells

Little is known about how human genetic variation affects the responses to environmental stimuli in the context of complex diseases. Experimental and computational approaches were applied to determine the effects of genetic variation on the induction of pathogen-responsive genes in human dendritic cells. We identified 121 common genetic variants associated in cis with variation in expression responses to Escherichia coli lipopolysaccharide, influenza, or interferon-β (IFN-β). We localized and validated causal variants to binding sites of pathogen-activated STAT (signal transducer and activator of transcription) and IRF (IFN-regulatory factor) transcription factors. We also identified a common variant in IRF7 that is associated in trans with type I IFN induction in response to influenza infection. Our results reveal common alleles that explain interindividual variation in pathogen sensing and provide functional annotation for genetic variants that alter susceptibility to inflammatory diseases.

Digital cell quantification identifies global immune cell dynamics during influenza infection

Hundreds of immune cell types work in coordination to maintain tissue homeostasis. Upon infection, dramatic changes occur with the localization, migration, and proliferation of the immune cells to first alert the body of the danger, confine it to limit spreading, and finally extinguish the threat and bring the tissue back to homeostasis. Since current technologies can follow the dynamics of only a limited number of cell types, we have yet to grasp the full complexity of global in vivo cell dynamics in normal developmental processes and disease. Here, we devise a computational method, digital cell quantification (DCQ), which combines genome‐wide gene expression data with an immune cell compendium to infer in vivo changes in the quantities of 213 immune cell subpopulations. DCQ was applied to study global immune cell dynamics in mice lungs at ten time points during 7 days of flu infection. We find dramatic changes in quantities of 70 immune cell types, including various innate, adaptive, and progenitor immune cells. We focus on the previously unreported dynamics of four immune dendritic cell subtypes and suggest a specific role for CD103⁺CD11b⁻DCs in early stages of disease and CD8⁺pDC in late stages of flu infection.

A genomic portrait of the genetic architecture and regulatory impact of microRNA expression in response to infection

MicroRNAs (miRNAs) are critical regulators of gene expression, and their role in a wide variety of biological processes, including host antimicrobial defense, is increasingly well described. Consistent with their diverse functional effects, miRNA expression is highly context dependent and shows marked changes upon cellular activation. However, the genetic control of miRNA expression in response to external stimuli and the impact of such perturbations on miRNA-mediated regulatory networks at the population level remain to be determined. Here we assessed changes in miRNA expression upon Mycobacterium tuberculosis infection and mapped expression quantitative trait loci (eQTL) in dendritic cells from a panel of healthy individuals. Genome-wide expression profiling revealed that ∼40% of miRNAs are differentially expressed upon infection. We find that the expression of 3% of miRNAs is controlled by proximate genetic factors, which are enriched in a promoter-specific histone modification associated with active transcription. Notably, we identify two infection-specific response eQTLs, for miR-326 and miR-1260, providing an initial assessment of the impact of genotype-environment interactions on miRNA molecular phenotypes. Furthermore, we show that infection coincides with a marked remodeling of the genome-wide relationships between miRNA and mRNA expression levels. This observation, supplemented by experimental data using the model of miR-29a, sheds light on the role of a set of miRNAs in cellular responses to infection. Collectively, this study increases our understanding of the genetic architecture of miRNA expression in response to infection, and highlights the wide-reaching impact of altering miRNA expression on the transcriptional landscape of a cell.

Systems approaches to human autoimmune diseases

Systemic autoimmune diseases result from interactions between genes and environmental triggers that lead to dysregulation of both innate and adaptive immunity. Systems biology approaches enable the global characterization of complex systems at the DNA, RNA and protein levels. Recent technological breakthroughs such as deep sequencing or high-throughput proteomics are revealing novel inflammatory pathways involved in autoimmunity. Herein, we review recent developments, challenges and promising avenues in the use of systems approaches to understand human systemic autoimmune and autoinflammatory diseases.