Identifying and mapping cell-type-specific chromatin programming of gene expression

A novel multi-omics mendelian randomization method for gene set enrichment and its application to psychiatric disorders

Genome-wide association studies (GWAS) of psychiatric disorders (PD) yield numerous loci with significant signals, but often do not implicate specific genes. Because GWAS risk loci are enriched in expression/protein/methylation quantitative loci (e/p/mQTL, hereafter xQTL), transcriptome/proteome/methylome-wide association studies (T/P/MWAS, hereafter XWAS) that integrate xQTL and GWAS information, can link GWAS signals to effects on specific genes. To further increase detection power, gene signals are aggregated within relevant gene sets (GS) by performing gene set enrichment (GSE) analyses. Often GSE methods test for enrichment of "signal" genes in curated GS while overlooking their linkage disequilibrium (LD) structure, allowing for the possibility of increased false positive rates. Moreover, no GSE tool uses xQTL information to perform mendelian randomization (MR) analysis. To make causal inference on association between PD and GS, we develop a novel MR GSE (MR-GSE) procedure. First, we generate a "synthetic" GWAS for each MSigDB GS by aggregating summary statistics for x-level (mRNA, protein or DNA methylation (DNAm) levels) from the largest xQTL studies available) of genes in a GS. Second, we use synthetic GS GWAS as exposure in a generalized summary-data-based-MR analysis of complex trait outcomes. We applied MR-GSE to GWAS of nine important PD. When applied to the underpowered opioid use disorder GWAS, none of the four analyses yielded any signals, which suggests a good control of false positive rates. For other PD, MR-GSE greatly increased the detection of GO terms signals (2,594) when compared to the commonly used (non-MR) GSE method (286). Some of the findings might be easier to adapt for treatment, e.g., our analyses suggest modest positive effects for supplementation with certain vitamins and/or omega-3 for schizophrenia, bipolar and major depression disorder patients. Similar to other MR methods, when applying MR-GSE researchers should be mindful of the confounding effects of horizontal pleiotropy on statistical inference.

Iterative assay for transposase-accessible chromatin by sequencing to isolate functionally relevant neuronal subtypes

The Drosophila brain contains tens of thousands of distinct cell types. Thousands of different transgenic lines reproducibly target specific neuron subsets, yet most still express in several cell types. Furthermore, most lines were developed without a priori knowledge of where the transgenes would be expressed. To aid in the development of cell type-specific tools for neuronal identification and manipulation, we developed an iterative assay for transposase-accessible chromatin (ATAC) approach. Open chromatin regions (OCRs) enriched in neurons, compared to whole bodies, drove transgene expression preferentially in subsets of neurons. A second round of ATAC-seq from these specific neuron subsets revealed additional enriched OCR2s that further restricted transgene expression within the chosen neuron subset. This approach allows for continued refinement of transgene expression, and we used it to identify neurons relevant for sleep behavior. Furthermore, this approach is widely applicable to other cell types and to other organisms.

The complex biology of aryl hydrocarbon receptor activation in cancer and beyond

The aryl hydrocarbon receptor (AHR) signaling pathway is a complex regulatory network that plays a critical role in various biological processes, including cellular metabolism, development, and immune responses. The complexity of AHR signaling arises from multiple factors, including the diverse ligands that activate the receptor, the expression level of AHR itself, and its interaction with the AHR nuclear translocator (ARNT). Additionally, the AHR crosstalks with the AHR repressor (AHRR) or other transcription factors and signaling pathways and it can also mediate non-genomic effects. Finally, posttranslational modifications of the AHR and its interaction partners, epigenetic regulation of AHR and its target genes, as well as AHR-mediated induction of enzymes that degrade AHR-activating ligands may contribute to the context-specificity of AHR activation. Understanding the complexity of AHR signaling is crucial for deciphering its physiological and pathological roles and developing therapeutic strategies targeting this pathway. Ongoing research continues to unravel the intricacies of AHR signaling, shedding light on the regulatory mechanisms controlling its diverse functions.

Identifying potential risk genes and pathways for neuropsychiatric and substance use disorders using intermediate molecular mediator information

Neuropsychiatric and substance use disorders (NPSUDs) have a complex etiology that includes environmental and polygenic risk factors with significant cross-trait genetic correlations. Genome-wide association studies (GWAS) of NPSUDs yield numerous association signals. However, for most of these regions, we do not yet have a firm understanding of either the specific risk variants or the effects of these variants. Post-GWAS methods allow researchers to use GWAS summary statistics and molecular mediators (transcript, protein, and methylation abundances) infer the effect of these mediators on risk for disorders. One group of post-GWAS approaches is commonly referred to as transcriptome/proteome/methylome-wide association studies, which are abbreviated as T/P/MWAS (or collectively as XWAS). Since these approaches use biological mediators, the multiple testing burden is reduced to the number of genes (∼20,000) instead of millions of GWAS SNPs, which leads to increased signal detection. In this work, our aim is to uncover likely risk genes for NPSUDs by performing XWAS analyses in two tissues-blood and brain. First, to identify putative causal risk genes, we performed an XWAS using the Summary-data-based Mendelian randomization, which uses GWAS summary statistics, reference xQTL data, and a reference LD panel. Second, given the large comorbidities among NPSUDs and the shared cis-xQTLs between blood and the brain, we improved XWAS signal detection for underpowered analyses by performing joint concordance analyses between XWAS results i) across the two tissues and ii) across NPSUDs. All XWAS signals i) were adjusted for heterogeneity in dependent instruments (HEIDI) (non-causality) p-values and ii) used to test for pathway enrichment. The results suggest that there were widely shared gene/protein signals within the major histocompatibility complex region on chromosome 6 (BTN3A2 and C4A) and elsewhere in the genome (FURIN, NEK4, RERE, and ZDHHC5). The identification of putative molecular genes and pathways underlying risk may offer new targets for therapeutic development. Our study revealed an enrichment of XWAS signals in vitamin D and omega-3 gene sets. So, including vitamin D and omega-3 in treatment plans may have a modest but beneficial effect on patients with bipolar disorder.

Identifying polymorphic cis-regulatory variants as risk markers for lung carcinogenesis and chemotherapy responses in tobacco smokers from eastern India

Aberrant expression of xenobiotic metabolism and DNA repair genes is critical to lung cancer pathogenesis. This study aims to identify the cis-regulatory variants of the genes modulating lung cancer risk among tobacco smokers and altering their chemotherapy responses. From a list of 2984 SNVs, prioritization and functional annotation revealed 22 cis-eQTLs of 14 genes within the gene expression-correlated DNase I hypersensitive sites using lung tissue-specific ENCODE, GTEx, Roadmap Epigenomics, and TCGA datasets. The 22 cis-regulatory variants predictably alter the binding of 44 transcription factors (TFs) expressed in lung tissue. Interestingly, 6 reported lung cancer-associated variants were found in linkage disequilibrium (LD) with 5 prioritized cis-eQTLs from our study. A case-control study with 3 promoter cis-eQTLs (p < 0.01) on 101 lung cancer patients and 401 healthy controls from eastern India with confirmed smoking history revealed an association of rs3764821 (ALDH3B1) (OR = 2.53, 95% CI = 1.57-4.07, p = 0.00014) and rs3748523 (RAD52) (OR = 1.69, 95% CI = 1.17-2.47, p = 0.006) with lung cancer risk. The effect of different chemotherapy regimens on the overall survival of lung cancer patients to the associated variants showed that the risk alleles of both variants significantly decreased (p < 0.05) patient survival.

Transcriptomic profiling implicates PAF1 in both active and repressive immune regulatory networks

BACKGROUND

Sitting at the interface of gene expression and host-pathogen interaction, polymerase associated factor 1 complex (PAF1C) is a rising player in the innate immune response. The complex localizes to the nucleus and associates with chromatin to modulate RNA polymerase II (RNAPII) elongation of gene transcripts. Performing this function at both proximal and distal regulatory elements, PAF1C interacts with many host factors across such sites, along with several microbial proteins during infection. Therefore, translating the ubiquity of PAF1C into specific impacts on immune gene expression remains especially relevant.

RESULTS

Advancing past work, we treat PAF1 knockout cells with a slate of immune stimuli to identify key trends in PAF1-dependent gene expression with broad analytical depth. From our transcriptomic data, we confirm PAF1 is an activator of traditional immune response pathways as well as other cellular pathways correlated with pathogen defense. With this model, we employ computational approaches to refine how PAF1 may contribute to both gene activation and suppression. Specifically focusing on transcriptional motifs and regulons, we predict gene regulatory elements strongly associated with PAF1, including those implicated in an immune response. Overall, our results suggest PAF1 is involved in innate immunity at several distinct axes of regulation.

CONCLUSIONS

By identifying PAF1-dependent gene expression across several pathogenic contexts, we confirm PAF1C to be a key mediator of innate immunity. Combining these transcriptomic profiles with potential regulatory networks corroborates the previously identified functions of PAF1C. With this, we foster new avenues for its study as a regulator of innate immunity, and our results will serve as a basis for targeted study of PAF1C in future validation studies.

Normal and Pathological NRF2 Signalling in the Central Nervous System

The nuclear factor erythroid 2-related factor 2 (NRF2) was originally described as a master regulator of antioxidant cellular response, but in the time since, numerous important biological functions linked to cell survival, cellular detoxification, metabolism, autophagy, proteostasis, inflammation, immunity, and differentiation have been attributed to this pleiotropic transcription factor that regulates hundreds of genes. After 40 years of in-depth research and key discoveries, NRF2 is now at the center of a vast regulatory network, revealing NRF2 signalling as increasingly complex. It is widely recognized that reactive oxygen species (ROS) play a key role in human physiological and pathological processes such as ageing, obesity, diabetes, cancer, and neurodegenerative diseases. The high oxygen consumption associated with high levels of free iron and oxidizable unsaturated lipids make the brain particularly vulnerable to oxidative stress. A good stability of NRF2 activity is thus crucial to maintain the redox balance and therefore brain homeostasis. In this review, we have gathered recent data about the contribution of the NRF2 pathway in the healthy brain as well as during metabolic diseases, cancer, ageing, and ageing-related neurodegenerative diseases. We also discuss promising therapeutic strategies and the need for better understanding of cell-type-specific functions of NRF2 in these different fields.

Extensive evaluation of ATAC-seq protocols for native or formaldehyde-fixed nuclei

BACKGROUND

The "Assay for Transposase Accessible Chromatin sequencing" (ATAC-seq) is an efficient and easy to implement protocol to measure chromatin accessibility that has been widely used in multiple applications studying gene regulation. While several modifications or variants of the protocol have been published since it was first described, there has not yet been an extensive evaluation of the effects of specific protocol choices head-to-head in a consistent experimental setting. In this study, we tested multiple protocol options for major ATAC-seq components (including three reaction buffers, two reaction temperatures, two enzyme sources, and the use of either native or fixed nuclei) in a well-characterized cell line. With all possible combinations of components, we created 24 experimental conditions with four replicates for each (a total of 96 samples). In addition, we tested the 12 native conditions in a primary sample type (mouse lung tissue) with two different input amounts. Through these extensive comparisons, we were able to observe the effect of different ATAC-seq conditions on data quality and to examine the utility and potential redundancy of various quality metrics.

RESULTS

In general, native samples yielded more peaks (particularly at loci not overlapping transcription start sites) than fixed samples, and the temperature at which the enzymatic reaction was carried out had a major impact on data quality metrics for both fixed and native nuclei. However, the effect of various conditions tested was not always consistent between the native and fixed samples. For example, the Nextera and Omni buffers were largely interchangeable across all other conditions, while the THS buffer resulted in markedly different profiles in native samples. In-house and commercial enzymes performed similarly.

CONCLUSIONS

We found that the relationship between commonly used measures of library quality differed across temperature and fixation, and so evaluating multiple metrics in assessing the quality of a sample is recommended. Notably, we also found that these choices can bias the functional class of elements profiled and so we recommend evaluating several formulations in any new experiments. Finally, we hope the ATAC-seq workflow formulated in this study on crosslinked samples will help to profile archival clinical specimens.

Promoter/enhancer-based controllability of regulatory networks

Understanding the mechanisms of tissue-specific transcriptional regulation is crucial as mis-regulation can cause a broad range of diseases. Here, we investigated transcription factors (TF) that are indispensable for the topological control of tissue specific and cell-type specific regulatory networks as a function of their binding to regulatory elements on promoters and enhancers of corresponding target genes. In particular, we found that promoter-binding TFs that were indispensable for regulatory network control regulate genes that are tissue-specifically expressed and overexpressed in corresponding cancer types. In turn, indispensable, enhancer-binding TFs were enriched with disease and signaling genes as they control an increasing number of cell-type specific regulatory networks. Their target genes were cell-type specific for blood and immune-related cell-types and over-expressed in blood-related cancers. Notably, target genes of indispensable enhancer-binding TFs in cell-type specific regulatory networks were enriched with cancer drug targets, while target genes of indispensable promoter-binding TFs were bona-fide targets of cancer drugs in corresponding tissues. Our results emphasize the significant role control analysis of regulatory networks plays in our understanding of transcriptional regulation, demonstrating potential therapeutic implications in tissue-specific drug discovery research.

HNF4A defines tissue-specific circadian rhythms by beaconing BMAL1::CLOCK chromatin binding and shaping the rhythmic chromatin landscape

Transcription modulated by the circadian clock is diverse across cell types, underlying circadian control of peripheral metabolism and its observed perturbation in human diseases. We report that knockout of the lineage-specifying Hnf4a gene in mouse liver causes associated reductions in the genome-wide distribution of core clock component BMAL1 and accessible chromatin marks (H3K4me1 and H3K27ac). Ectopically expressing HNF4A remodels chromatin landscape and nucleates distinct tissue-specific BMAL1 chromatin binding events, predominantly in enhancer regions. Circadian rhythms are disturbed in Hnf4a knockout liver and HNF4A-MODY diabetic model cells. Additionally, the epigenetic state and accessibility of the liver genome dynamically change throughout the day, synchronized with chromatin occupancy of HNF4A and clustered expression of circadian outputs. Lastly, Bmal1 knockout attenuates HNF4A genome-wide binding in the liver, likely due to downregulated Hnf4a transcription. Our results may provide a general mechanism for establishing circadian rhythm heterogeneity during development and disease progression, governed by chromatin structure.

Genetic and epigenetic features of promoters with ubiquitous chromatin accessibility support ubiquitous transcription of cell-essential genes

Gene expression is controlled by regulatory elements within accessible chromatin. Although most regulatory elements are cell type-specific, a subset is accessible in nearly all the 517 human and 94 mouse cell and tissue types assayed by the ENCODE consortium. We systematically analyzed 9000 human and 8000 mouse ubiquitously-accessible candidate cis-regulatory elements (cCREs) with promoter-like signatures (PLSs) from ENCODE, which we denote ubi-PLSs. These are more CpG-rich than non-ubi-PLSs and correspond to genes with ubiquitously high transcription, including a majority of cell-essential genes. ubi-PLSs are enriched with motifs of ubiquitously-expressed transcription factors and preferentially bound by transcriptional cofactors regulating ubiquitously-expressed genes. They are highly conserved between human and mouse at the synteny level but exhibit frequent turnover of motif sites; accordingly, ubi-PLSs show increased variation at their centers compared with flanking regions among the ∼186 thousand human genomes sequenced by the TOPMed project. Finally, ubi-PLSs are enriched in genes implicated in Mendelian diseases, especially diseases broadly impacting most cell types, such as deficiencies in mitochondrial functions. Thus, a set of roughly 9000 mammalian promoters are actively maintained in an accessible state across cell types by a distinct set of transcription factors and cofactors to ensure the transcriptional programs of cell-essential genes.

Transcriptional and epigenetic control of hematopoietic stem cell fate decisions in vertebrates

Hematopoietic stem cells (HSCs) are the foundation of adult hematopoiesis that produce all types of mature blood lineages. In vertebrates, HSC development is a stepwise process, coordinately regulated by chromatin architectures and a group of transcriptional and epigenetic regulators. A deeper understanding of the molecular mechanisms governing the generation, expansion, and function of HSCs holds great promise in the generation and expansion of engraftable HSCs in vitro for clinical applications. This study reviewed recent advances in transcriptional and epigenetic control of hematopoietic stem cell fate decisions in vertebrates.

Heat-Triggered Remote Control of CRISPR-dCas9 for Tunable Transcriptional Modulation

CRISPR-associated proteins (Cas) are enabling powerful new approaches to control mammalian cell functions, yet the lack of spatially defined, noninvasive modalities limits their use as biological tools. Here, we integrate thermal gene switches with dCas9 complexes to confer remote control of gene activation and suppression with short pulses of heat. Using a thermal switch constructed from the heat shock protein A6 (HSPA6) locus, we show that a single heat pulse 3-5 °C above basal temperature is sufficient to trigger expression of dCas9 complexes. We demonstrate that dCas9 fused to the transcriptional activator VP64 is functional after heat activation, and, depending on the number of heat pulses, drives transcription of endogenous genes GzmB and CCL21 to levels equivalent to that achieved by a constitutive viral promoter. Across a range of input temperatures, we find that downstream protein expression of GzmB closely correlates with transcript levels (R² = 0.99). Using dCas9 fused with the transcriptional suppressor KRAB, we show that longitudinal suppression of the reporter d2GFP depends on key thermal input parameters including pulse magnitude, number of pulses, and dose fractionation. In living mice, we extend our study using photothermal heating to spatially target implanted cells to suppress d2GFP in vivo. Our study establishes a noninvasive and targeted approach to harness Cas-based proteins for modulation of gene expression to complement current methods for remote control of cell function.

A possible role for epigenetic feedback regulation in the dynamics of the epithelial-mesenchymal transition (EMT)

The epithelial-mesenchymal transition (EMT) often plays a critical role in cancer metastasis and chemoresistance, and decoding its dynamics is crucial to design effective therapeutics. EMT is regulated at multiple levels-transcriptional, translational, protein stability and epigenetics; the mechanisms by which epigenetic regulation can alter the dynamics of EMT remain elusive. Here, to identify the possible effects of epigenetic regulation in EMT, we incorporate a feedback term in our previously proposed model of EMT regulation of the miR-200/ZEB/miR-34/SNAIL circuit. This epigenetic feedback that stabilizes long-term transcriptional activity can alter the relative stability and distribution of states in a given cell population, particularly when incorporated in the inhibitory effect on miR-200 from ZEB. This feedback can stabilize the mesenchymal state, thus making transitions out of that state difficult. Conversely, epigenetic regulation of the self-activation of ZEB has only minor effects. Our model predicts that this effect could be seen in experiments, when epithelial cells are treated with an external EMT-inducing signal for a sufficiently long period of time and then allowed to recover. Our preliminary experimental data indicates that a chronic TGF-β exposure gives rise to irreveversible EMT state; i.e. unable to reverse back to the epithelial state. Thus, this integrated theoretical-experimental approach yields insights into how an epigenetic feedback may alter the dynamics of EMT.

Computational Analysis of Transcriptional Regulation Sites at the HTT Gene Locus

BACKGROUND

Huntington's disease is a late onset neurological disorder caused by a trinucleotide CAG repeat expansion mutation in the HTT gene encoding for the protein huntingtin. Despite considerable ongoing research, the wild-type function of huntingtin is not yet fully understood.

OBJECTIVE

To improve knowledge of HTT gene regulation at the transcriptional level and inform future studies aimed at uncovering the HTT gene's normal function.

METHODS

The HTT gene region was functionally characterized through an in silico analysis using publicly available data sets. ChIP-seq data sets and the online STRING database were used to identify putative transcription factor binding sites (TFBSs) and protein-protein interactions within the HTT promoter region. siRNA-mediated knockdown and ChIP-qPCR of STAT1, a TF identified from the in silico analysis, were used to validate the bioinformatics screen.

RESULTS

16 regions containing potential regulatory genomic markers were identified. TFBSs for 59 transcription factors (TFs) were detected in one or more of the 16 candidate regions. Using these TFs, 15 clusters of protein-protein interactions were identified using STRING. siRNA-mediated knockdown of STAT1 resulted in an increase in HTT expression, and ChIP-qPCR detected enrichment of STAT1 binding at one of the predicted regions. These assays confirmed the utility of the bioinformatic analysis.

CONCLUSIONS

Putative regulatory regions outside of the immediate HTT promoter region have been identified with specific protein-protein interactions. Future work will focus on in vitro and in vivo studies to examine the effect of modulating identified TFBSs and altering the levels of specific TFs of interest in regulating HTT gene expression.

Combinatorial Transcriptional Control of Plant Specialized Metabolism

Plants produce countless specialized compounds of diverse chemical nature and biological activities. Their biosynthesis often exclusively occurs either in response to environmental stresses or is limited to dedicated anatomical structures. In both scenarios, regulation of biosynthesis appears to be mainly controlled at the transcriptional level, which is generally dependent on a combined interplay of DNA-related mechanisms and the activity of transcription factors that may act in a combinatorial manner. How environmental and developmental cues are integrated into a coordinated cell type-specific stress response has only partially been unraveled so far. Building on the available examples from (metabolic) gene expression, here we propose theoretical models of how this integration of signals may occur at the level of transcriptional control.

Predicting stimulation-dependent enhancer-promoter interactions from ChIP-Seq time course data

We have developed a machine learning approach to predict stimulation-dependent enhancer-promoter interactions using evidence from changes in genomic protein occupancy over time. The occupancy of estrogen receptor alpha (ERα), RNA polymerase (Pol II) and histone marks H2AZ and H3K4me3 were measured over time using ChIP-Seq experiments in MCF7 cells stimulated with estrogen. A Bayesian classifier was developed which uses the correlation of temporal binding patterns at enhancers and promoters and genomic proximity as features to predict interactions. This method was trained using experimentally determined interactions from the same system and was shown to achieve much higher precision than predictions based on the genomic proximity of nearest ERα binding. We use the method to identify a genome-wide confident set of ERα target genes and their regulatory enhancers genome-wide. Validation with publicly available GRO-Seq data demonstrates that our predicted targets are much more likely to show early nascent transcription than predictions based on genomic ERα binding proximity alone.

Predicting gene expression in massively parallel reporter assays: A comparative study

In many human diseases, associated genetic changes tend to occur within noncoding regions, whose effect might be related to transcriptional control. A central goal in human genetics is to understand the function of such noncoding regions: given a region that is statistically associated with changes in gene expression (expression quantitative trait locus [eQTL]), does it in fact play a regulatory role? And if so, how is this role "coded" in its sequence? These questions were the subject of the Critical Assessment of Genome Interpretation eQTL challenge. Participants were given a set of sequences that flank eQTLs in humans and were asked to predict whether these are capable of regulating transcription (as evaluated by massively parallel reporter assays), and whether this capability changes between alternative alleles. Here, we report lessons learned from this community effort. By inspecting predictive properties in isolation, and conducting meta-analysis over the competing methods, we find that using chromatin accessibility and transcription factor binding as features in an ensemble of classifiers or regression models leads to the most accurate results. We then characterize the loci that are harder to predict, putting the spotlight on areas of weakness, which we expect to be the subject of future studies.

Modeling the causal regulatory network by integrating chromatin accessibility and transcriptome data

Cell packs a lot of genetic and regulatory information through a structure known as chromatin, i.e. DNA is wrapped around histone proteins and is tightly packed in a remarkable way. To express a gene in a specific coding region, the chromatin would open up and DNA loop may be formed by interacting enhancers and promoters. Furthermore, the mediator and cohesion complexes, sequence-specific transcription factors, and RNA polymerase II are recruited and work together to elaborately regulate the expression level. It is in pressing need to understand how the information, about when, where, and to what degree genes should be expressed, is embedded into chromatin structure and gene regulatory elements. Thanks to large consortia such as Encyclopedia of DNA Elements (ENCODE) and Roadmap Epigenomic projects, extensive data on chromatin accessibility and transcript abundance are available across many tissues and cell types. This rich data offer an exciting opportunity to model the causal regulatory relationship. Here, we will review the current experimental approaches, foundational data, computational problems, interpretive frameworks, and integrative models that will enable the accurate interpretation of regulatory landscape. Particularly, we will discuss the efforts to organize, analyze, model, and integrate the DNA accessibility data, transcriptional data, and functional genomic regions together. We believe that these efforts will eventually help us understand the information flow within the cell and will influence research directions across many fields.

Tissue-specific regulatory circuits reveal variable modular perturbations across complex diseases

Mapping perturbed molecular circuits that underlie complex diseases remains a great challenge. We developed a comprehensive resource of 394 cell type- and tissue-specific gene regulatory networks for human, each specifying the genome-wide connectivity among transcription factors, enhancers, promoters and genes. Integration with 37 genome-wide association studies (GWASs) showed that disease-associated genetic variants--including variants that do not reach genome-wide significance--often perturb regulatory modules that are highly specific to disease-relevant cell types or tissues. Our resource opens the door to systematic analysis of regulatory programs across hundreds of human cell types and tissues (http://regulatorycircuits.org).

Functional transcription factor target discovery via compendia of binding and expression profiles

Genome-wide experiments to map the DNA-binding locations of transcription-associated factors (TFs) have shown that the number of genes bound by a TF far exceeds the number of possible direct target genes. Distinguishing functional from non-functional binding is therefore a major challenge in the study of transcriptional regulation. We hypothesized that functional targets can be discovered by correlating binding and expression profiles across multiple experimental conditions. To test this hypothesis, we obtained ChIP-seq and RNA-seq data from matching cell types from the human ENCODE resource, considered promoter-proximal and distal cumulative regulatory models to map binding sites to genes, and used a combination of linear and non-linear measures to correlate binding and expression data. We found that a high degree of correlation between a gene’s TF-binding and expression profiles was significantly more predictive of the gene being differentially expressed upon knockdown of that TF, compared to using binding sites in the cell type of interest only. Remarkably, TF targets predicted from correlation across a compendium of cell types were also predictive of functional targets in other cell types. Finally, correlation across a time course of ChIP-seq and RNA-seq experiments was also predictive of functional TF targets in that tissue.

Incorporating chromatin accessibility data into sequence-to-expression modeling

Prediction of gene expression levels from regulatory sequences is one of the major challenges of genomic biology today. A particularly promising approach to this problem is that taken by thermodynamics-based models that interpret an enhancer sequence in a given cellular context specified by transcription factor concentration levels and predict precise expression levels driven by that enhancer. Such models have so far not accounted for the effect of chromatin accessibility on interactions between transcription factor and DNA and consequently on gene-expression levels. Here, we extend a thermodynamics-based model of gene expression, called GEMSTAT (Gene Expression Modeling Based on Statistical Thermodynamics), to incorporate chromatin accessibility data and quantify its effect on accuracy of expression prediction. In the new model, called GEMSTAT-A, accessibility at a binding site is assumed to affect the transcription factor's binding strength at the site, whereas all other aspects are identical to the GEMSTAT model. We show that this modification results in significantly better fits in a data set of over 30 enhancers regulating spatial expression patterns in the blastoderm-stage Drosophila embryo. It is important to note that the improved fits result not from an overall elevated accessibility in active enhancers but from the variation of accessibility levels within an enhancer. With whole-genome DNA accessibility measurements becoming increasingly popular, our work demonstrates how such data may be useful for sequence-to-expression models. It also calls for future advances in modeling accessibility levels from sequence and the transregulatory context, so as to predict accurately the effect of cis and trans perturbations on gene expression.

Pluripotency, Differentiation, and Reprogramming: A Gene Expression Dynamics Model with Epigenetic Feedback Regulation

Embryonic stem cells exhibit pluripotency: they can differentiate into all types of somatic cells. Pluripotent genes such as Oct4 and Nanog are activated in the pluripotent state, and their expression decreases during cell differentiation. Inversely, expression of differentiation genes such as Gata6 and Gata4 is promoted during differentiation. The gene regulatory network controlling the expression of these genes has been described, and slower-scale epigenetic modifications have been uncovered. Although the differentiation of pluripotent stem cells is normally irreversible, reprogramming of cells can be experimentally manipulated to regain pluripotency via overexpression of certain genes. Despite these experimental advances, the dynamics and mechanisms of differentiation and reprogramming are not yet fully understood. Based on recent experimental findings, we constructed a simple gene regulatory network including pluripotent and differentiation genes, and we demonstrated the existence of pluripotent and differentiated states from the resultant dynamical-systems model. Two differentiation mechanisms, interaction-induced switching from an expression oscillatory state and noise-assisted transition between bistable stationary states, were tested in the model. The former was found to be relevant to the differentiation process. We also introduced variables representing epigenetic modifications, which controlled the threshold for gene expression. By assuming positive feedback between expression levels and the epigenetic variables, we observed differentiation in expression dynamics. Additionally, with numerical reprogramming experiments for differentiated cells, we showed that pluripotency was recovered in cells by imposing overexpression of two pluripotent genes and external factors to control expression of differentiation genes. Interestingly, these factors were consistent with the four Yamanaka factors, Oct4, Sox2, Klf4, and Myc, which were necessary for the establishment of induced pluripotent stem cells. These results, based on a gene regulatory network and expression dynamics, contribute to our wider understanding of pluripotency, differentiation, and reprogramming of cells, and they provide a fresh viewpoint on robustness and control during development.

Characterization of pluripotent states, in which cells can both self-renew and differentiate, and the irreversible loss of pluripotency are important research areas in developmental biology. In particular, an understanding of these processes is essential to the reprogramming of cells for biomedical applications, i.e., the experimental recovery of pluripotency in differentiated cells. Based on recent advances in dynamical-systems theory for gene expression, we propose a gene-regulatory-network model consisting of several pluripotent and differentiation genes. Our results show that cellular-state transition to differentiated cell types occurs as the number of cells increases, beginning with the pluripotent state and oscillatory expression of pluripotent genes. Cell-cell signaling mediates the differentiation process with robustness to noise, while epigenetic modifications affecting gene expression dynamics fix the cellular state. These modifications ensure the cellular state to be protected against external perturbation, but they also work as an epigenetic barrier to recovery of pluripotency. We show that overexpression of several genes leads to the reprogramming of cells, consistent with the methods for establishing induced pluripotent stem cells. Our model, which involves the inter-relationship between gene expression dynamics and epigenetic modifications, improves our basic understanding of cell differentiation and reprogramming.