Resolving systematic errors in widely used enhancer activity assays in human cells

ChromActivity: integrative epigenomic and functional characterization assay based annotation of regulatory activity across diverse human cell types

We introduce ChromActivity, a computational framework for predicting and annotating regulatory activity across the genome through integration of multiple epigenomic maps and various functional characterization datasets. ChromActivity generates genomewide predictions of regulatory activity associated with each functional characterization dataset across many cell types based on available epigenomic data. It then for each cell type produces ChromScoreHMM genome annotations based on the combinatorial and spatial patterns within these predictions and ChromScore tracks of overall predicted regulatory activity. ChromActivity provides a resource for analyzing and interpreting the human regulatory genome across diverse cell types.

Single-cell multiome and enhancer connectome of human retinal pigment epithelium and choroid nominate pathogenic variants in age-related macular degeneration

Age-related macular degeneration (AMD) is a leading cause of vision loss worldwide. Genome-wide association studies (GWAS) of AMD have identified dozens of risk loci that may house disease targets. However, variants at these loci are largely noncoding, making it difficult to assess their function and whether they are causal. Here, we present a single-cell gene expression and chromatin accessibility atlas of human retinal pigment epithelium (RPE) and choroid to systematically analyze both coding and noncoding variants implicated in AMD. We employ HiChIP and Activity-by-Contact modeling to map enhancers in these tissues and predict cell and gene targets of risk variants. We further perform allele-specific self-transcribing active regulatory region sequencing (STARR-seq) to functionally test variant activity in RPE cells, including in the context of complement activation. Our work nominates new pathogenic variants and mechanisms in AMD and offers a rich and accessible resource for studying diseases of the RPE and choroid.

Spuriously transcribed RNAs from CRISPR-sgRNA expression plasmids scaffold biomolecular condensate formation and hamper accurate genomic imaging

Clustered regularly interspaced short palindromic repeats (CRISPR)-based imaging tools that utilize fluorescently tagged single-guide RNAs (sgRNAs) have enabled versatile analysis of the dynamics of single genomic loci, but the accuracy may be hindered by nonspecific subnuclear probe accumulation, generating false-positive foci in cell nuclei. By examining the subcellular localizations of sgRNA expression plasmids, their RNA transcripts, and several RNA-binding proteins, we found that spuriously transcribed (cryptic) transcripts, produced by sgRNA expression plasmids, are the major contributors of false-positive signals, independent of sgRNA scaffold design or effector probe (i.e. RNA aptamer- or oligonucleotide-based probes) used. These transcripts interact with the paraspeckle core proteins, but not with the sgRNA expression plasmids or the paraspeckle RNA scaffold NEAT1_2, to form nuclear bodies that display liquid-like properties including sphericality, fusion competence, and sensitivity to 1,6-hexanediol. Transfecting sgRNA transcription units (i.e. sgRNA expression cassettes), lacking the plasmid backbones, reduces false-positive signals and enhances genomic imaging accuracy. Overall, this study unveils previously undescribed activities of cryptic plasmid transcripts and presents an easy-to-adapt strategy that can potentially improve the precision of CRISPR-based imaging systems that implement fluorescently tagged sgRNAs.

An evolutionarily conserved constellation of functional cis-elements programs the virus-responsive fate of the human (epi)genome

Human health depends on perplexing defensive cellular responses against microbial pathogens like Viruses. Despite the major effort undertaken, the (epi)genomic mechanisms that human cells utilize to tailor defensive gene expression programs against microbial attacks have remained inadequately understood, mainly due to a significant lack of recording of the in vivo functional cis-regulatory modules (CRMs) of the human genome. Here, we introduce the virus-responsive fate of the human (epi)genome as characterized in naïve and infected cells by functional genomics, computational biology, DNA evolution, and DNA Grammar and Syntax investigations. We discovered that multitudes of novel functional virus-responsive CRMs (vrCRMs) compose typical enhancers (tEs), super-enhancers (SEs), repetitive-DNA enhancers (rDEs), and stand-alone functional genomic stretches that grant human cells regulatory underpinnings for layering basal immunity and eliminating illogical/harmful defensive responses under homeostasis, yet stimulating virus-responsive genes and transposable elements (TEs) upon infection. Moreover, extensive epigenomic reprogramming of previously unknown SE landscapes marks the transition from naïve to antiviral human cell states and involves the functions of the antimicrobial transcription factors (TFs), including interferon response factor 3 (IRF3) and nuclear factor-κB (NF-κB), as well as coactivators and transcriptional apparatus, along with intensive modifications/alterations in histone marks and chromatin accessibility. Considering the polyphyletic evolutionary fingerprints of the composite DNA sequences of the vrCRMs assessed by TFs-STARR-seq, ranging from the animal to microbial kingdoms, the conserved features of antimicrobial TFs and chromatin complexes, and their pluripotent stimulus-induced activation, these findings shed light on how mammalian (epi)genomes evolved their functions to interpret the exogenous stress inflicted and program defensive transcriptional responses against microbial agents. Crucially, many known human short variants, e.g. single-nucleotide polymorphisms (SNPs), insertions, deletions etc., and quantitative trait loci (QTLs) linked to autoimmune diseases, such as multiple sclerosis (MS), systemic lupus erythematosus (SLE), Crohn's disease (CD) etc., were mapped within or vastly proximal (±2.5 kb) to the novel in vivo functional SEs and vrCRMs discovered, thus underscoring the impact of their (mal)functions on human physiology and disease development. Hence, we delved into the virus-responsive fate of the human (epi)genome and illuminated its architecture, function, evolutionary origins, and its significance for cellular homeostasis. These results allow us to chart the "Human hyper-Atlas of virus-infection", an integrated "molecular in silico" encyclopedia situated in the UCSC Genome Browser that benefits our mechanistic understanding of human infectious/(auto)immune diseases development and can facilitate the generation of in vivo preclinical animal models, drug design, and evolution of therapeutic applications.

Comprehensive mapping of genetic variation at Epromoters reveals pleiotropic association with multiple disease traits

There is growing evidence that a wide range of human diseases and physiological traits are influenced by genetic variation of cis-regulatory elements. We and others have shown that a subset of promoter elements, termed Epromoters, also function as enhancer regulators of distal genes. This opens a paradigm in the study of regulatory variants, as single nucleotide polymorphisms (SNPs) within Epromoters might influence the expression of several (distal) genes at the same time, which could disentangle the identification of disease-associated genes. Here, we built a comprehensive resource of human Epromoters using newly generated and publicly available high-throughput reporter assays. We showed that Epromoters display intrinsic and epigenetic features that distinguish them from typical promoters. By integrating Genome-Wide Association Studies (GWAS), expression Quantitative Trait Loci (eQTLs) and 3D chromatin interactions, we found that regulatory variants at Epromoters are concurrently associated with more disease and physiological traits, as compared with typical promoters. To dissect the regulatory impact of Epromoter variants, we evaluated their impact on regulatory activity by analyzing allelic-specific high-throughput reporter assays and provided reliable examples of pleiotropic Epromoters. In summary, our study represents a comprehensive resource of regulatory variants supporting the pleiotropic role of Epromoters.

Inference of transcriptional regulation from STARR-seq data

One of the primary regulatory processes in cells is transcription, during which RNA polymerase II (Pol-II) transcribes DNA into RNA. The binding of Pol-II to its site is regulated through interactions with transcription factors (TFs) that bind to DNA at enhancer cis-regulatory elements. Measuring the enhancer activity of large libraries of distinct DNA sequences is now possible using massively parallel reporter assays (MPRAs), and computational methods have been developed to identify the dominant statistical patterns of TF binding within these large datasets. Such methods are global in their approach and may overlook important regulatory sites that function only within the local context. Here we introduce a method for inferring functional regulatory sites (their number, location, and width) within an enhancer sequence based on measurements of its transcriptional activity from an MPRA method such as STARR-seq. The model is based on a mean-field thermodynamic description of Pol-II binding that includes interactions with bound TFs. Our method applied to simulated STARR-seq data for a variety of enhancer architectures shows how data quality impacts the inference and also how it can find local regulatory sites that may be missed in a global approach. We also apply the method to recently measured STARR-seq data on androgen receptor (AR) bound sequences, a TF that plays an important role in the regulation of prostate cancer. The method identifies key regulatory sites within these sequences, which are found to overlap with binding sites of known coregulators of AR.

Enhancer cooperativity can compensate for loss of activity over large genomic distances

Enhancers are short DNA sequences that activate their target promoter from a distance; however, increasing the genomic distance between the enhancer and the promoter decreases expression levels. Many genes are controlled by combinations of multiple enhancers, yet the interaction and cooperation of individual enhancer elements are not well understood. Here, we developed a synthetic platform in mouse embryonic stem cells that allows building complex regulatory landscapes from the bottom up. We tested the system by integrating individual enhancers at different distances and confirmed that the strength of an enhancer contributes to how strongly it is affected by increased genomic distance. Furthermore, synergy between two enhancer elements depends on the distance at which the two elements are integrated: introducing a weak enhancer between a strong enhancer and the promoter strongly increases reporter gene expression, allowing enhancers to activate from increased genomic distances.

Systematic functional characterization of non-coding regulatory SNPs associated with central obesity

Central obesity is associated with higher risk of developing a wide range of diseases independent of overall obesity. Genome-wide association studies (GWASs) have identified more than 300 susceptibility loci associated with central obesity. However, the functional understanding of these loci is limited by the fact that most loci are in non-coding regions. To address this issue, our study first prioritized 2,034 single-nucleotide polymorphisms (SNPs) based on fine-mapping and epigenomic annotation analysis. Subsequently, we employed self-transcribing active regulatory region sequencing (STARR-seq) to systematically evaluate the enhancer activity of these prioritized SNPs. The resulting data analysis identified 141 SNPs with allelic enhancer activity. Further analysis of allelic transcription factor (TF) binding prioritized 20 key TFs mediating the central-obesity-relevant genetic regulatory network. Finally, as an example, we illustrate the molecular mechanisms of how rs8079062 acts as an allele-specific enhancer to regulate the expression of its targeted RNF157. We also evaluated the role of RNF157 in the adipogenic differentiation process. In conclusion, our results provide an important resource for understanding the genetic regulatory mechanisms underlying central obesity.

High-resolution dissection of human cell type-specific enhancers in cis and trans activities

The spatiotemporal-specific gene expression is regulated by cell type-specific regulatory elements. Here we selected the H3K4me1-associated DNA sequences as candidate enhancers in two different human cell lines and performed ChIP-STARR-seq to quantify the cell-type-specific enhancer activities with high-resolution. We investigated how the activity landscape of enhancers would change when transferred from native cells (cis activity) to another cell lines (trans activity). We obtained enhancers cis activity maps and trans activity maps in two different cell lines. The cis and trans activity maps enabled us to identify cell type-specific active enhancers, with enrichment of motifs of differentially expressed TFs. Comparisons between the cis and trans activity maps revealed general consistent regulatory property with different levels of activity in two cell lines, suggesting sequence intrinsic regulatory properties remain similar in different types of cells. This study provides a new perspective on sequence intrinsic enhancer activities in different types of cells.

HDI-STARR-seq: Condition-specific enhancer discovery in mouse liver in vivo

BACKGROUND

STARR-seq and other massively-parallel reporter assays are widely used to discover functional enhancers in transfected cell models, which can be confounded by plasmid vector-induced type-I interferon immune responses and lack the multicellular environment and endogenous chromatin state of complex mammalian tissues.

RESULTS

We describe HDI-STARR-seq, which combines STARR-seq plasmid library delivery to the liver, by hydrodynamic tail vein injection (HDI), with reporter RNA transcriptional initiation driven by a minimal Albumin promoter, which we show is essential for mouse liver STARR-seq enhancer activity assayed 7 days after HDI. Importantly, little or no vector-induced innate type-I interferon responses were observed. Comparisons of HDI-STARR-seq activity between male and female mouse livers and in livers from males treated with an activating ligand of the transcription factor (TF) CAR (Nr1i3) identified many condition-dependent enhancers linked to condition-specific gene expression. Further, thousands of active liver enhancers were identified using a high complexity STARR-seq library comprised of ~ 50,000 genomic regions released by DNase-I digestion of mouse liver nuclei. When compared to stringently inactive library sequences, the active enhancer sequences identified were highly enriched for liver open chromatin regions with activating histone marks (H3K27ac, H3K4me1, H3K4me3), were significantly closer to gene transcriptional start sites, and were significantly depleted of repressive (H3K27me3, H3K9me3) and transcribed region histone marks (H3K36me3).

CONCLUSION

HDI-STARR-seq offers substantial improvements over current methodologies for large scale, functional profiling of enhancers, including condition-dependent enhancers, in liver tissue in vivo, and can be adapted to characterize enhancer activities in a variety of species and tissues by selecting suitable tissue- and species-specific promoter sequences.

Crosstalk between paralogs and isoforms influences p63-dependent regulatory element activity

The p53 family of transcription factors (p53, p63 and p73) regulate diverse organismal processes including tumor suppression, maintenance of genome integrity and the development of skin and limbs. Crosstalk between transcription factors with highly similar DNA binding profiles, like those in the p53 family, can dramatically alter gene regulation. While p53 is primarily associated with transcriptional activation, p63 mediates both activation and repression. The specific mechanisms controlling p63-dependent gene regulatory activity are not well understood. Here, we use massively parallel reporter assays (MPRA) to investigate how local DNA sequence context influences p63-dependent transcriptional activity. Most regulatory elements with a p63 response element motif (p63RE) activate transcription, although binding of the p63 paralog, p53, drives a substantial proportion of that activity. p63RE sequence content and co-enrichment with other known activating and repressing transcription factors, including lineage-specific factors, correlates with differential p63RE-mediated activities. p63 isoforms dramatically alter transcriptional behavior, primarily shifting inactive regulatory elements towards high p63-dependent activity. Our analysis provides novel insight into how local sequence and cellular context influences p63-dependent behaviors and highlights the key, yet still understudied, role of transcription factor paralogs and isoforms in controlling gene regulatory element activity.

Massively parallel reporter assays identify enhancer elements in oesophageal Adenocarcinoma

Cancer is a disease underpinned by aberrant gene expression. Enhancers are regulatory elements that play a major role in transcriptional control and changes in active enhancer function are likely critical in the pathogenesis of oesophageal adenocarcinoma (OAC). Here, we utilise STARR-seq to profile the genome-wide enhancer landscape in OAC and identify hundreds of high-confidence enhancer elements. These regions are enriched in enhancer-associated chromatin marks, are actively transcribed and exhibit high levels of associated gene activity in OAC cells. These characteristics are maintained in human patient samples, demonstrating their disease relevance. This relevance is further underlined by their responsiveness to oncogenic ERBB2 inhibition and increased activity compared to the pre-cancerous Barrett's state. Mechanistically, these enhancers are linked to the core OAC transcriptional network and in particular KLF5 binding is associated with high level activity, providing further support for a role of this transcription factor in defining the OAC transcriptome. Our results therefore uncover a set of enhancer elements with physiological significance, that widen our understanding of the molecular alterations in OAC and point to mechanisms through which response to targeted therapy may occur.

Identification, Design, and Application of Noncoding Cis-Regulatory Elements

Cis-regulatory elements (CREs) play a pivotal role in orchestrating interactions with trans-regulatory factors such as transcription factors, RNA-binding proteins, and noncoding RNAs. These interactions are fundamental to the molecular architecture underpinning complex and diverse biological functions in living organisms, facilitating a myriad of sophisticated and dynamic processes. The rapid advancement in the identification and characterization of these regulatory elements has been marked by initiatives such as the Encyclopedia of DNA Elements (ENCODE) project, which represents a significant milestone in the field. Concurrently, the development of CRE detection technologies, exemplified by massively parallel reporter assays, has progressed at an impressive pace, providing powerful tools for CRE discovery. The exponential growth of multimodal functional genomic data has necessitated the application of advanced analytical methods. Deep learning algorithms, particularly large language models, have emerged as invaluable tools for deconstructing the intricate nucleotide sequences governing CRE function. These advancements facilitate precise predictions of CRE activity and enable the de novo design of CREs. A deeper understanding of CRE operational dynamics is crucial for harnessing their versatile regulatory properties. Such insights are instrumental in refining gene therapy techniques, enhancing the efficacy of selective breeding programs, pushing the boundaries of genetic innovation, and opening new possibilities in microbial synthetic biology.

HDI-STARR-seq: Condition-specific enhancer discovery in mouse liver in vivo

Background

STARR-seq and other massively-parallel reporter assays are widely used to discover functional enhancers in transfected cell models, which can be confounded by plasmid vector-induced type-I interferon immune responses and lack the multicellular environment and endogenous chromatin state of complex mammalian tissues.

Results

Here, we describe HDI-STARR-seq, which combines STARR-seq plasmid library delivery to the liver, by hydrodynamic tail vein injection (HDI), with reporter RNA transcriptional initiation driven by a minimal Albumin promoter, which we show is essential for mouse liver STARR-seq enhancer activity assayed 7 days after HDI. Importantly, little or no vector-induced innate type-I interferon responses were observed. Comparisons of HDI-STARR-seq activity between male and female mouse livers and in livers from males treated with an activating ligand of the transcription factor CAR (Nr1i3) identified many condition-dependent enhancers linked to condition-specific gene expression. Further, thousands of active liver enhancers were identified using a high complexity STARR-seq library comprised of ~ 50,000 genomic regions released by DNase-I digestion of mouse liver nuclei. When compared to stringently inactive library sequences, the active enhancer sequences identified were highly enriched for liver open chromatin regions with activating histone marks (H3K27ac, H3K4me1, H3K4me3), were significantly closer to gene transcriptional start sites, and were significantly depleted of repressive (H3K27me3, H3K9me3) and transcribed region histone marks (H3K36me3).

Conclusions

HDI-STARR-seq offers substantial improvements over current methodologies for large scale, functional profiling of enhancers, including condition-dependent enhancers, in liver tissue in vivo, and can be adapted to characterize enhancer activities in a variety of species and tissues by selecting suitable tissue- and species-specific promoter sequences.

KSHV genome harbors both constitutive and lytically induced enhancers

Kaposi's sarcoma-associated herpesvirus (KSHV) belongs to the gamma-herpesvirus family and is a well-known human oncogenic virus. In infected cells, the viral genome of 165 kbp is circular DNA wrapped in chromatin. The tight control of gene expression is critical for latency, the transition into the lytic phase, and the development of viral-associated malignancies. Distal cis-regulatory elements, such as enhancers and silencers, can regulate gene expression in a position- and orientation-independent manner. Open chromatin is another characteristic feature of enhancers. To systematically search for enhancers, we cloned all the open chromatin regions in the KSHV genome downstream of the luciferase gene and tested their enhancer activity in infected and uninfected cells. A silencer was detected upstream of the latency-associated nuclear antigen promoter. Two constitutive enhancers were identified in the K12p-OriLyt-R and ORF29 Intron regions, where ORF29 Intron is a tissue-specific enhancer. The following promoters: OriLyt-L, PANp, ALTp, and the terminal repeats (TRs) acted as lytically induced enhancers. The expression of the replication and transcription activator (RTA), the master regulator of the lytic cycle, was sufficient to induce the activity of lytic enhancers in uninfected cells. We propose that the TRs that span about 24 kbp region serve as a "viral super-enhancer" that integrates the repressive effect of the latency-associated nuclear antigen (LANA) with the activating effect of RTA. Utilizing CRISPR activation and interference techniques, we determined the connections between these enhancers and their regulated genes. The silencer and enhancers described here provide an additional layer to the complex gene regulation of herpesviruses.IMPORTANCEIn this study, we performed a systematic functional assay to identify cis-regulatory elements within the genome of the oncogenic herpesvirus, Kaposi's sarcoma-associated herpesvirus (KSHV). Similar to other herpesviruses, KSHV presents both latent and lytic phases. Therefore, our assays were performed in uninfected cells, during latent infection, and under lytic conditions. We identified two constitutive enhancers, one of which seems to be a tissue-specific enhancer. In addition, four lytically induced enhancers, which are all responsive to the replication and transcription activator (RTA), were identified. Furthermore, a silencer was identified between the major latency promoter and the lytic gene locus. Utilizing CRISPR activation and interference techniques, we determined the connections between these enhancers and their regulated genes. The terminal repeats, spanning a region of about 24 kbp, seem like a "viral super-enhancer" that integrates the repressive effect of the latency-associated nuclear antigen (LANA) with the activating effect of RTA to regulate latency to lytic transition.

HDI-STARR-seq: Condition-specific enhancer discovery in mouse liver in vivo

STARR-seq and other massively-parallel reporter assays are widely used to discover functional enhancers in transfected cell models, which can be confounded by plasmid vector-induced type-I interferon immune responses and lack the multicellular environment and endogenous chromatin state of complex mammalian tissues. Here, we describe HDI-STARR-seq, which combines STARR-seq plasmid library delivery to the liver, by hydrodynamic tail vein injection (HDI), with reporter RNA transcriptional initiation driven by a minimal Albumin promoter, which we show is essential for mouse liver STARR-seq enhancer activity assayed 7 days after HDI. Importantly, little or no vector-induced innate type-I interferon responses were observed. Comparisons of HDI-STARR-seq activity between male and female mouse livers and in livers from males treated with an activating ligand of the transcription factor CAR (Nr1i3) identified many condition-dependent enhancers linked to condition-specific gene expression. Further, thousands of active liver enhancers were identified using a high complexity STARR-seq library comprised of ~50,000 genomic regions released by DNase-I digestion of mouse liver nuclei. When compared to stringently inactive library sequences, the active enhancer sequences identified were highly enriched for liver open chromatin regions with activating histone marks (H3K27ac, H3K4me1, H3K4me3), were significantly closer to gene transcriptional start sites, and were significantly depleted of repressive (H3K27me3, H3K9me3) and transcribed region histone marks (H3K36me3). HDI-STARR-seq offers substantial improvements over current methodologies for large scale, functional profiling of enhancers, including condition-dependent enhancers, in liver tissue in vivo, and can be adapted to characterize enhancer activities in a variety of species and tissues by selecting suitable tissue- and species-specific promoter sequences.

Multiplex profiling of developmental cis-regulatory elements with quantitative single-cell expression reporters

The inability to scalably and precisely measure the activity of developmental cis-regulatory elements (CREs) in multicellular systems is a bottleneck in genomics. Here we develop a dual RNA cassette that decouples the detection and quantification tasks inherent to multiplex single-cell reporter assays. The resulting measurement of reporter expression is accurate over multiple orders of magnitude, with a precision approaching the limit set by Poisson counting noise. Together with RNA barcode stabilization via circularization, these scalable single-cell quantitative expression reporters provide high-contrast readouts, analogous to classic in situ assays but entirely from sequencing. Screening >200 regions of accessible chromatin in a multicellular in vitro model of early mammalian development, we identify 13 (8 previously uncharacterized) autonomous and cell-type-specific developmental CREs. We further demonstrate that chimeric CRE pairs generate cognate two-cell-type activity profiles and assess gain- and loss-of-function multicellular expression phenotypes from CRE variants with perturbed transcription factor binding sites. Single-cell quantitative expression reporters can be applied in developmental and multicellular systems to quantitatively characterize native, perturbed and synthetic CREs at scale, with high sensitivity and at single-cell resolution.

Validated Negative Regions (VNRs) in the VISTA Database might be Truncated Forms of Bona Fide Enhancers

The VISTA enhancer database is a valuable resource for evaluating predicted enhancers in humans and mice. In addition to thousands of validated positive regions (VPRs) in the human and mouse genomes, the database also contains similar numbers of validated negative regions (VNRs). It is previously shown that the VPRs are on average half as long as predicted overlapping enhancers that are highly conserved and hypothesize that the VPRs may be truncated forms of long bona fide enhancers. Here, it is shown that like the VPRs, the VNRs also are under strong evolutionary constraints and overlap predicted enhancers in the genomes. The VNRs are also on average half as long as predicted overlapping enhancers that are highly conserved. Moreover, the VNRs and the VPRs display similar cell/tissue-specific modification patterns of key epigenetic marks of active enhancers. Furthermore, the VNRs and the VPRs show similar impact score spectra of in silico mutagenesis. These highly similar properties between the VPRs and the VNRs suggest that like the VPRs, the VNRs may also be truncated forms of long bona fide enhancers.

Transcriptomic and spatial dissection of human ex vivo right atrial tissue reveals proinflammatory microvascular changes in ischemic heart disease

Cardiovascular disease plays a central role in the electrical and structural remodeling of the right atrium, predisposing to arrhythmias, heart failure, and sudden death. Here, we dissect with single-nuclei RNA sequencing (snRNA-seq) and spatial transcriptomics the gene expression changes in the human ex vivo right atrial tissue and pericardial fluid in ischemic heart disease, myocardial infarction, and ischemic and non-ischemic heart failure using asymptomatic patients with valvular disease who undergo preventive surgery as the control group. We reveal substantial differences in disease-associated gene expression in all cell types, collectively suggesting inflammatory microvascular dysfunction and changes in the right atrial tissue composition as the valvular and vascular diseases progress into heart failure. The data collectively suggest that investigation of human cardiovascular disease should expand to all functionally important parts of the heart, which may help us to identify mechanisms promoting more severe types of the disease.

Estrogen receptor 1 chromatin profiling in human breast tumors reveals high inter-patient heterogeneity with enrichment of risk SNPs and enhancer activity at most-conserved regions

Estrogen Receptor 1 (ESR1; also known as ERα, encoded by ESR1 gene) is the main driver and prime drug target in luminal breast cancer. ESR1 chromatin binding is extensively studied in cell lines and a limited number of human tumors, using consensi of peaks shared among samples. However, little is known about inter-tumor heterogeneity of ESR1 chromatin action, along with its biological implications. Here, we use a large set of ESR1 ChIP-seq data from 70 ESR1+ breast cancers to explore inter-patient heterogeneity in ESR1 DNA binding to reveal a striking inter-tumor heterogeneity of ESR1 action. Of note, commonly shared ESR1 sites show the highest estrogen-driven enhancer activity and are most engaged in long-range chromatin interactions. In addition, the most commonly shared ESR1-occupied enhancers are enriched for breast cancer risk SNP loci. We experimentally confirm SNVs to impact chromatin binding potential for ESR1 and its pioneer factor FOXA1. Finally, in the TCGA breast cancer cohort, we can confirm these variations to associate with differences in expression for the target gene. Cumulatively, we reveal a natural hierarchy of ESR1-chromatin interactions in breast cancers within a highly heterogeneous inter-tumor ESR1 landscape, with the most common shared regions being most active and affected by germline functional risk SNPs for breast cancer development.

Context dependent activity of p63-bound gene regulatory elements

The p53 family of transcription factors regulate numerous organismal processes including the development of skin and limbs, ciliogenesis, and preservation of genetic integrity and tumor suppression. p53 family members control these processes and gene expression networks through engagement with DNA sequences within gene regulatory elements. Whereas p53 binding to its cognate recognition sequence is strongly associated with transcriptional activation, p63 can mediate both activation and repression. How the DNA sequence of p63-bound gene regulatory elements is linked to these varied activities is not yet understood. Here, we use massively parallel reporter assays (MPRA) in a range of cellular and genetic contexts to investigate the influence of DNA sequence on p63-mediated transcription. Most regulatory elements with a p63 response element motif (p63RE) activate transcription, with those sites bound by p63 more frequently or adhering closer to canonical p53 family response element sequences driving higher transcriptional output. The most active regulatory elements are those also capable of binding p53. Elements uniquely bound by p63 have varied activity, with p63RE-mediated repression associated with lower overall GC content in flanking sequences. Comparison of activity across cell lines suggests differential activity of elements may be regulated by a combination of p63 abundance or context-specific cofactors. Finally, changes in p63 isoform expression dramatically alters regulatory element activity, primarily shifting inactive elements towards a strong p63-dependent activity. Our analysis of p63-bound gene regulatory elements provides new insight into how sequence, cellular context, and other transcription factors influence p63-dependent transcription. These studies provide a framework for understanding how p63 genomic binding locally regulates transcription. Additionally, these results can be extended to investigate the influence of sequence content, genomic context, chromatin structure on the interplay between p63 isoforms and p53 family paralogs.

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.

Validation of Enhancer Regions in Primary Human Neural Progenitor Cells using Capture STARR-seq

Genome-wide association studies (GWAS) and expression analyses implicate noncoding regulatory regions as harboring risk factors for psychiatric disease, but functional characterization of these regions remains limited. We performed capture STARR-sequencing of over 78,000 candidate regions to identify active enhancers in primary human neural progenitor cells (phNPCs). We selected candidate regions by integrating data from NPCs, prefrontal cortex, developmental timepoints, and GWAS. Over 8,000 regions demonstrated enhancer activity in the phNPCs, and we linked these regions to over 2,200 predicted target genes. These genes are involved in neuronal and psychiatric disease-associated pathways, including dopaminergic synapse, axon guidance, and schizophrenia. We functionally validated a subset of these enhancers using mutation STARR-sequencing and CRISPR deletions, demonstrating the effects of genetic variation on enhancer activity and enhancer deletion on gene expression. Overall, we identified thousands of highly active enhancers and functionally validated a subset of these enhancers, improving our understanding of regulatory networks underlying brain function and disease.

CAG repeat expansions create splicing acceptor sites and produce aberrant repeat-containing RNAs

Expansions of CAG trinucleotide repeats cause several rare neurodegenerative diseases. The disease-causing repeats are translated in multiple reading frames and without an identifiable initiation codon. The molecular mechanism of this repeat-associated non-AUG (RAN) translation is not known. We find that expanded CAG repeats create new splice acceptor sites. Splicing of proximal donors to the repeats produces unexpected repeat-containing transcripts. Upon splicing, depending on the sequences surrounding the donor, CAG repeats may become embedded in AUG-initiated open reading frames. Canonical AUG-initiated translation of these aberrant RNAs may account for proteins that have been attributed to RAN translation. Disruption of the relevant splice donors or the in-frame AUG initiation codons is sufficient to abrogate RAN translation. Our findings provide a molecular explanation for the abnormal translation products observed in CAG trinucleotide repeat expansion disorders and add to the repertoire of mechanisms by which repeat expansion mutations disrupt cellular functions.

Mechanosensitive genomic enhancers potentiate the cellular response to matrix stiffness

Epigenetic control of cellular transcription and phenotype is influenced by changes in the cellular microenvironment, yet how mechanical cues from these microenvironments precisely influence epigenetic state to regulate transcription remains largely unmapped. Here, we combine genome-wide epigenome profiling, epigenome editing, and phenotypic and single-cell RNA-seq CRISPR screening to identify a new class of genomic enhancers that responds to the mechanical microenvironment. These 'mechanoenhancers' could be active on either soft or stiff extracellular matrix contexts, and regulated transcription to influence critical cell functions including apoptosis, mechanotransduction, proliferation, and migration. Epigenetic editing of mechanoenhancers on rigid materials tuned gene expression to levels observed on softer materials, thereby reprogramming the cellular response to the mechanical microenvironment. These editing approaches may enable the precise alteration of mechanically-driven disease states.

Hold out the genome: a roadmap to solving the cis-regulatory code

Gene expression is regulated by transcription factors that work together to read cis-regulatory DNA sequences. The 'cis-regulatory code' - how cells interpret DNA sequences to determine when, where and how much genes should be expressed - has proven to be exceedingly complex. Recently, advances in the scale and resolution of functional genomics assays and machine learning have enabled substantial progress towards deciphering this code. However, the cis-regulatory code will probably never be solved if models are trained only on genomic sequences; regions of homology can easily lead to overestimation of predictive performance, and our genome is too short and has insufficient sequence diversity to learn all relevant parameters. Fortunately, randomly synthesized DNA sequences enable testing a far larger sequence space than exists in our genomes, and designed DNA sequences enable targeted queries to maximally improve the models. As the same biochemical principles are used to interpret DNA regardless of its source, models trained on these synthetic data can predict genomic activity, often better than genome-trained models. Here we provide an outlook on the field, and propose a roadmap towards solving the cis-regulatory code by a combination of machine learning and massively parallel assays using synthetic DNA.

Methylation-directed regulatory networks determine enhancing and silencing of mutation disease driver genes and explain inter-patient expression variation

BACKGROUND

Common diseases manifest differentially between patients, but the genetic origin of this variation remains unclear. To explore possible involvement of gene transcriptional-variation, we produce a DNA methylation-oriented, driver-gene-wide dataset of regulatory elements in human glioblastomas and study their effect on inter-patient gene expression variation.

RESULTS

In 175 of 177 analyzed gene regulatory domains, transcriptional enhancers and silencers are intermixed. Under experimental conditions, DNA methylation induces enhancers to alter their enhancing effects or convert into silencers, while silencers are affected inversely. High-resolution mapping of the association between DNA methylation and gene expression in intact genomes reveals methylation-related regulatory units (average size = 915.1 base-pairs). Upon increased methylation of these units, their target-genes either increased or decreased in expression. Gene-enhancing and silencing units constitute cis-regulatory networks of genes. Mathematical modeling of the networks highlights indicative methylation sites, which signified the effect of key regulatory units, and add up to make the overall transcriptional effect of the network. Methylation variation in these sites effectively describe inter-patient expression variation and, compared with DNA sequence-alterations, appears as a major contributor of gene-expression variation among glioblastoma patients.

CONCLUSIONS

We describe complex cis-regulatory networks, which determine gene expression by summing the effects of positive and negative transcriptional inputs. In these networks, DNA methylation induces both enhancing and silencing effects, depending on the context. The revealed mechanism sheds light on the regulatory role of DNA methylation, explains inter-individual gene-expression variation, and opens the way for monitoring the driving forces behind deferential courses of cancer and other diseases.

Dual stop codon suppression in mammalian cells with genomically integrated genetic code expansion machinery

Stop codon suppression using dedicated tRNA/aminoacyl-tRNA synthetase (aaRS) pairs allows for genetically encoded, site-specific incorporation of non-canonical amino acids (ncAAs) as chemical handles for protein labeling and modification. Here, we demonstrate that piggyBac-mediated genomic integration of archaeal pyrrolysine tRNA (tRNAPyl)/pyrrolysyl-tRNA synthetase (PylRS) or bacterial tRNA/aaRS pairs, using a modular plasmid design with multi-copy tRNA arrays, allows for homogeneous and efficient genetically encoded ncAA incorporation in diverse mammalian cell lines. We assess opportunities and limitations of using ncAAs for fluorescent labeling applications in stable cell lines. We explore suppression of ochre and opal stop codons and finally incorporate two distinct ncAAs with mutually orthogonal click chemistries for site-specific, dual-fluorophore labeling of a cell surface receptor on live mammalian cells.

CAG repeat expansions create splicing acceptor sites and produce aberrant repeat-containing RNAs

Expansions of CAG trinucleotide repeats cause several rare neurodegenerative diseases. The disease-causing repeats are translated in multiple reading frames, without an identifiable initiation codon. The molecular mechanism of this repeat-associated non-AUG (RAN) translation is not known. We find that expanded CAG repeats create new splice acceptor sites. Splicing of proximal donors to the repeats produces unexpected repeat-containing transcripts. Upon splicing, depending on the sequences surrounding the donor, CAG repeats may become embedded in AUG-initiated open reading frames. Canonical AUG-initiated translation of these aberrant RNAs accounts for proteins that are attributed to RAN translation. Disruption of the relevant splice donors or the in-frame AUG initiation codons is sufficient to abrogate RAN translation. Our findings provide a molecular explanation for the abnormal translation products observed in CAG trinucleotide repeat expansion disorders and add to the repertoire of mechanisms by which repeat expansion mutations disrupt cellular functions.

Optimisation of TP53 reporters by systematic dissection of synthetic TP53 response elements

TP53 is a transcription factor that controls multiple cellular processes, including cell cycle arrest, DNA repair and apoptosis. The relation between TP53 binding site architecture and transcriptional output is still not fully understood. Here, we systematically examined in three different cell lines the effects of binding site affinity and copy number on TP53-dependent transcriptional output, and also probed the impact of spacer length and sequence between adjacent binding sites, and of core promoter identity. Paradoxically, we found that high-affinity TP53 binding sites are less potent than medium-affinity sites. TP53 achieves supra-additive transcriptional activation through optimally spaced adjacent binding sites, suggesting a cooperative mechanism. Optimally spaced adjacent binding sites have a ∼10-bp periodicity, suggesting a role for spatial orientation along the DNA double helix. We leveraged these insights to construct a log-linear model that explains activity from sequence features, and to identify new highly active and sensitive TP53 reporters.

What is an enhancer?

Tight control of the transcription process is essential for the correct spatial and temporal gene expression pattern during development and in homeostasis. Enhancers are at the core of correct transcriptional activation. The original definition of an enhancer is straightforward: a DNA sequence that activates transcription independent of orientation and direction. Dissection of numerous enhancer loci has shown that many enhancer-like elements might not conform to the original definition, suggesting that enhancers and enhancer-like elements might use multiple different mechanisms to contribute to transcriptional activation. Here, we review methodologies to identify enhancers and enhancer-like elements and discuss pitfalls and consequences for our understanding of transcriptional regulation.

Epromoters are new players in the regulatory landscape with potential pleiotropic roles

Precise spatiotemporal control of gene expression during normal development and cell differentiation is achieved by the combined action of proximal (promoters) and distal (enhancers) cis-regulatory elements. Recent studies have reported that a subset of promoters, termed Epromoters, works also as enhancers to regulate distal genes. This new paradigm opened novel questions regarding the complexity of our genome and raises the possibility that genetic variation within Epromoters has pleiotropic effects on various physiological and pathological traits by differentially impacting multiple proximal and distal genes. Here, we discuss the different observations pointing to an important role of Epromoters in the regulatory landscape and summarize the evidence supporting a pleiotropic impact of these elements in disease. We further hypothesize that Epromoter might represent a major contributor to phenotypic variation and disease.

Underlying causes for prevalent false positives and false negatives in STARR-seq data

Self-transcribing active regulatory region sequencing (STARR-seq) and its variants have been widely used to characterize enhancers. However, it has been reported that up to 87% of STARR-seq peaks are located in repressive chromatin and are not functional in the tested cells. While some of the STARR-seq peaks in repressive chromatin might be active in other cell/tissue types, some others might be false positives. Meanwhile, many active enhancers may not be identified by the current STARR-seq methods. Although methods have been proposed to mitigate systematic errors caused by the use of plasmid vectors, the artifacts due to the intrinsic limitations of current STARR-seq methods are still prevalent and the underlying causes are not fully understood. Based on predicted cis-regulatory modules (CRMs) and non-CRMs in the human genome as well as predicted active CRMs and non-active CRMs in a few human cell lines/tissues with STARR-seq data available, we reveal prevalent false positives and false negatives in STARR-seq peaks generated by major variants of STARR-seq methods and possible underlying causes. Our results will help design strategies to improve STARR-seq methods and interpret the results.

Using Synthetic DNA Libraries to Investigate Chromatin and Gene Regulation

Despite the recent explosion in genome-wide studies in chromatin and gene regulation, we are still far from extracting a set of genetic rules that can predict the function of the regulatory genome. One major reason for this deficiency is that gene regulation is a multi-layered process that involves an enormous variable space, which cannot be fully explored using native genomes. This problem can be partially solved by introducing synthetic DNA libraries into cells, a method that can test the regulatory roles of thousands to millions of sequences with limited variables. Here, we review recent applications of this method to study transcription factor (TF) binding, nucleosome positioning, and transcriptional activity. We discuss the design principles, experimental procedures, and major findings from these studies and compare the pros and cons of different approaches.

High-throughput functional dissection of noncoding SNPs with biased allelic enhancer activity for insulin resistance-relevant phenotypes

Most of the single-nucleotide polymorphisms (SNPs) associated with insulin resistance (IR)-relevant phenotypes by genome-wide association studies (GWASs) are located in noncoding regions, complicating their functional interpretation. Here, we utilized an adapted STARR-seq to evaluate the regulatory activities of 5,987 noncoding SNPs associated with IR-relevant phenotypes. We identified 876 SNPs with biased allelic enhancer activity effects (baaSNPs) across 133 loci in three IR-relevant cell lines (HepG2, preadipocyte, and A673), which showed pervasive cell specificity and significant enrichment for cell-specific open chromatin regions or enhancer-indicative markers (H3K4me1, H3K27ac). Further functional characterization suggested several transcription factors (TFs) with preferential allelic binding to baaSNPs. We also incorporated multi-omics data to prioritize 102 candidate regulatory target genes for baaSNPs and revealed prevalent long-range regulatory effects and cell-specific IR-relevant biological functional enrichment on them. Specifically, we experimentally verified the distal regulatory mechanism at IRS1 locus, in which rs952227-A reinforces IRS1 expression by long-range chromatin interaction and preferential binding to the transcription factor HOXC6 to augment the enhancer activity. Finally, based on our STARR-seq screening data, we predicted the enhancer activity of 227,343 noncoding SNPs associated with IR-relevant phenotypes (fasting insulin adjusted for BMI, HDL cholesterol, and triglycerides) from the largest available GWAS summary statistics. We further provided an open resource (http://www.bigc.online/fnSNP-IR) for better understanding genetic regulatory mechanisms of IR-relevant phenotypes.

Shared Gene Targets of the ATF4 and p53 Transcriptional Networks

The master tumor suppressor p53 regulates multiple cell fate decisions, such as cell cycle arrest and apoptosis, via transcriptional control of a broad gene network. Dysfunction in the p53 network is common in cancer, often through mutations that inactivate p53 or other members of the pathway. Induction of tumor-specific cell death by restoration of p53 activity without off-target effects has gained significant interest in the field. In this study, we explore the gene regulatory mechanisms underlying a putative anticancer strategy involving stimulation of the p53-independent integrated stress response (ISR). Our data demonstrate the p53 and ISR pathways converge to independently regulate common metabolic and proapoptotic genes. We investigated the architecture of multiple gene regulatory elements bound by p53 and the ISR effector ATF4 controlling this shared regulation. We identified additional key transcription factors that control basal and stress-induced regulation of these shared p53 and ATF4 target genes. Thus, our results provide significant new molecular and genetic insight into gene regulatory networks and transcription factors that are the target of numerous antitumor therapies.

Integrative epigenomic and functional characterization assay based annotation of regulatory activity across diverse human cell types

We introduce ChromActivity, a computational framework for predicting and annotating regulatory activity across the genome through integration of multiple epigenomic maps and various functional characterization datasets. ChromActivity generates genomewide predictions of regulatory activity associated with each functional characterization dataset across many cell types based on available epigenomic data. It then for each cell type produces (1) ChromScoreHMM genome annotations based on the combinatorial and spatial patterns within these predictions and (2) ChromScore tracks of overall predicted regulatory activity. ChromActivity provides a resource for analyzing and interpreting the human regulatory genome across diverse cell types.

Shared gene targets of the ATF4 and p53 transcriptional networks

The master tumor suppressor p53 regulates multiple cell fate decisions, like cell cycle arrest and apoptosis, via transcriptional control of a broad gene network. Dysfunction in the p53 network is common in cancer, often through mutations that inactivate p53 or other members of the pathway. Induction of tumor-specific cell death by restoration of p53 activity without off-target effects has gained significant interest in the field. In this study, we explore the gene regulatory mechanisms underlying a putative anti-cancer strategy involving stimulation of the p53-independent Integrated Stress Response (ISR). Our data demonstrate the p53 and ISR pathways converge to independently regulate common metabolic and pro-apoptotic genes. We investigated the architecture of multiple gene regulatory elements bound by p53 and the ISR effector ATF4 controlling this shared regulation. We identified additional key transcription factors that control basal and stress-induced regulation of these shared p53 and ATF4 target genes. Thus, our results provide significant new molecular and genetic insight into gene regulatory networks and transcription factors that are the target of numerous antitumor therapies.

Cis-regulatory atlas of primary human CD4+ T cells

Cis-regulatory elements (CRE) are critical for coordinating gene expression programs that dictate cell-specific differentiation and homeostasis. Recently developed self-transcribing active regulatory region sequencing (STARR-Seq) has allowed for genome-wide annotation of functional CREs. Despite this, STARR-Seq assays are only employed in cell lines, in part, due to difficulties in delivering reporter constructs. Herein, we implemented and validated a STARR-Seq-based screen in human CD4+ T cells using a non-integrating lentiviral transduction system. Lenti-STARR-Seq is the first example of a genome-wide assay of CRE function in human primary cells, identifying thousands of functional enhancers and negative regulatory elements (NREs) in human CD4+ T cells. We find an unexpected difference in nucleosome organization between enhancers and NRE: enhancers are located between nucleosomes, whereas NRE are occupied by nucleosomes in their endogenous locations. We also describe chromatin modification, eRNA production, and transcription factor binding at both enhancers and NREs. Our findings support the idea of silencer repurposing as enhancers in alternate cell types. Collectively, these data suggest that Lenti-STARR-Seq is a successful approach for CRE screening in primary human cell types, and provides an atlas of functional CREs in human CD4+ T cells.

Multiplexed long-read plasmid validation and analysis using OnRamp

Recombinant plasmid vectors are versatile tools that have facilitated discoveries in molecular biology, genetics, proteomics, and many other fields. As the enzymatic and bacterial processes used to create recombinant DNA can introduce errors, sequence validation is an essential step in plasmid assembly. Sanger sequencing is the current standard for plasmid validation; however, this method is limited by an inability to sequence through complex secondary structure and lacks scalability when applied to full-plasmid sequencing of multiple plasmids owing to read-length limits. Although high-throughput sequencing does provide full-plasmid sequencing at scale, it is impractical and costly when used outside of library-scale validation. Here, we present Oxford nanopore-based rapid analysis of multiplexed plasmids (OnRamp), an alternative method for routine plasmid validation that combines the advantages of high-throughput sequencing's full-plasmid coverage and scalability with Sanger's affordability and accessibility by leveraging nanopore's long-read sequencing technology. We include customized wet-laboratory protocols for plasmid preparation along with a pipeline designed for analysis of read data obtained using these protocols. This analysis pipeline is deployed on the OnRamp web app, which generates alignments between actual and predicted plasmid sequences, quality scores, and read-level views. OnRamp is designed to be broadly accessible regardless of programming experience to facilitate more widespread adoption of long-read sequencing for routine plasmid validation. Here we describe the OnRamp protocols and pipeline and show our ability to obtain full sequences from pooled plasmids while detecting sequence variation even in regions of high secondary structure at less than half the cost of equivalent Sanger sequencing.

An unbiased AAV-STARR-seq screen revealing the enhancer activity map of genomic regions in the mouse brain in vivo

Enhancers are important cis-regulatory elements controlling cell-type specific expression patterns of genes. Furthermore, combinations of enhancers and minimal promoters are utilized to construct small, artificial promoters for gene delivery vectors. Large-scale functional screening methodology to construct genomic maps of enhancer activities has been successfully established in cultured cell lines, however, not yet applied to terminally differentiated cells and tissues in a living animal. Here, we transposed the Self-Transcribing Active Regulatory Region Sequencing (STARR-seq) technique to the mouse brain using adeno-associated-viruses (AAV) for the delivery of a highly complex screening library tiling entire genomic regions and covering in total 3 Mb of the mouse genome. We identified 483 sequences with enhancer activity, including sequences that were not predicted by DNA accessibility or histone marks. Characterizing the expression patterns of fluorescent reporters controlled by nine candidate sequences, we observed differential expression patterns also in sparse cell types. Together, our study provides an entry point for the unbiased study of enhancer activities in organisms during health and disease.

Challenges and considerations for reproducibility of STARR-seq assays

High-throughput methods such as RNA-seq, ChIP-seq, and ATAC-seq have well-established guidelines, commercial kits, and analysis pipelines that enable consistency and wider adoption for understanding genome function and regulation. STARR-seq, a popular assay for directly quantifying the activities of thousands of enhancer sequences simultaneously, has seen limited standardization across studies. The assay is long, with more than 250 steps, and frequent customization of the protocol and variations in bioinformatics methods raise concerns for reproducibility of STARR-seq studies. Here, we assess each step of the protocol and analysis pipelines from published sources and in-house assays, and identify critical steps and quality control (QC) checkpoints necessary for reproducibility of the assay. We also provide guidelines for experimental design, protocol scaling, customization, and analysis pipelines for better adoption of the assay. These resources will allow better optimization of STARR-seq for specific research needs, enable comparisons and integration across studies, and improve the reproducibility of results.

Strategies for activity analysis of single nucleotide polymorphisms associated with human diseases

Genome-wide association studies (GWAS) have identified a large number of single nucleotide polymorphism (SNP) sites associated with human diseases. In the annotation of human diseases, especially cancers, SNPs, as an important component of genetic factors, have gained increasing attention. Given that most of the SNPs are located in non-coding regions, the functional verification of these SNPs is a great challenge. The key to functional annotation for risk SNPs is to screen SNPs with regulatory activity from thousands of disease associated-SNPs. In this review, we systematically recapitulate the characteristics and functional roles of SNP sites, discuss three parallel reporter screening strategies in detail based on barcode tag classification, and recommend the common in silico strategies to help supplement the annotation of SNP sites with epigenetic activity analysis, prediction of target genes and trans-acting factors. We hope that this review will contribute to this exuberant research field by providing robust activity analysis strategies that can facilitate the translation of GWAS results into personalized diagnosis and prevention measures for human diseases.

Enhancers display constrained sequence flexibility and context-specific modulation of motif function

The information about when and where each gene is to be expressed is mainly encoded in the DNA sequence of enhancers, sequence elements that comprise binding sites (motifs) for different transcription factors (TFs). Most of the research on enhancer sequences has been focused on TF motif presence, whereas the enhancer syntax, that is, the flexibility of important motif positions and how the sequence context modulates the activity of TF motifs, remains poorly understood. Here, we explore the rules of enhancer syntax by a two-pronged approach in Drosophila melanogaster S2 cells: we (1) replace important TF motifs by all possible 65,536 eight-nucleotide-long sequences and (2) paste eight important TF motif types into 763 positions within 496 enhancers. These complementary strategies reveal that enhancers display constrained sequence flexibility and the context-specific modulation of motif function. Important motifs can be functionally replaced by hundreds of sequences constituting several distinct motif types, but these are only a fraction of all possible sequences and motif types. Moreover, TF motifs contribute with different intrinsic strengths that are strongly modulated by the enhancer sequence context (the flanking sequence, the presence and diversity of other motif types, and the distance between motifs), such that not all motif types can work in all positions. The context-specific modulation of motif function is also a hallmark of human enhancers, as we demonstrate experimentally. Overall, these two general principles of enhancer sequences are important to understand and predict enhancer function during development, evolution, and in disease.

Leveraging massively parallel reporter assays for evolutionary questions

A long-standing goal of evolutionary biology is to decode how gene regulation contributes to organismal diversity. Doing so is challenging because it is hard to predict function from non-coding sequence and to perform molecular research with non-model taxa. Massively parallel reporter assays (MPRAs) enable the testing of thousands to millions of sequences for regulatory activity simultaneously. Here, we discuss the execution, advantages, and limitations of MPRAs, with a focus on evolutionary questions. We propose solutions for extending MPRAs to rare taxa and those with limited genomic resources, and we underscore MPRA's broad potential for driving genome-scale, functional studies across organisms.

The H2A.Z and NuRD associated protein HMG20A controls early head and heart developmental transcription programs

Specialized chromatin-binding proteins are required for DNA-based processes during development. We recently established PWWP2A as a direct histone variant H2A.Z interactor involved in mitosis and craniofacial development. Here, we identify the H2A.Z/PWWP2A-associated protein HMG20A as part of several chromatin-modifying complexes, including NuRD, and show that it localizes to distinct genomic regulatory regions. Hmg20a depletion causes severe head and heart developmental defects in Xenopus laevis. Our data indicate that craniofacial malformations are caused by defects in neural crest cell (NCC) migration and cartilage formation. These developmental failures are phenocopied in Hmg20a-depleted mESCs, which show inefficient differentiation into NCCs and cardiomyocytes (CM). Consequently, loss of HMG20A, which marks open promoters and enhancers, results in chromatin accessibility changes and a striking deregulation of transcription programs involved in epithelial-mesenchymal transition (EMT) and differentiation processes. Collectively, our findings implicate HMG20A as part of the H2A.Z/PWWP2A/NuRD-axis and reveal it as a key modulator of intricate developmental transcription programs that guide the differentiation of NCCs and CMs.

Optimized high-throughput screening of non-coding variants identified from genome-wide association studies

The vast majority of disease-associated single nucleotide polymorphisms (SNP) identified from genome-wide association studies (GWAS) are localized in non-coding regions. A significant fraction of these variants impact transcription factors binding to enhancer elements and alter gene expression. To functionally interrogate the activity of such variants we developed snpSTARRseq, a high-throughput experimental method that can interrogate the functional impact of hundreds to thousands of non-coding variants on enhancer activity. snpSTARRseq dramatically improves signal-to-noise by utilizing a novel sequencing and bioinformatic approach that increases both insert size and the number of variants tested per loci. Using this strategy, we interrogated known prostate cancer (PCa) risk-associated loci and demonstrated that 35% of them harbor SNPs that significantly altered enhancer activity. Combining these results with chromosomal looping data we could identify interacting genes and provide a mechanism of action for 20 PCa GWAS risk regions. When benchmarked to orthogonal methods, snpSTARRseq showed a strong correlation with in vivo experimental allelic-imbalance studies whereas there was no correlation with predictive in silico approaches. Overall, snpSTARRseq provides an integrated experimental and computational framework to functionally test non-coding genetic variants.

Genome-wide prediction of activating regulatory elements in rice by combining STARR-seq with FACS

Self-transcribing active regulatory region sequencing (STARR-seq) is widely used to identify enhancers at the whole-genome level. However, whether STARR-seq works as efficiently in plants as in animal systems remains unclear. Here, we determined that the traditional STARR-seq method can be directly applied to rice (Oryza sativa) protoplasts to identify enhancers, though with limited efficiency. Intriguingly, we identified not only enhancers but also constitutive promoters with this technique. To increase the performance of STARR-seq in plants, we optimized two procedures. We coupled fluorescence activating cell sorting (FACS) with STARR-seq to alleviate the effect of background noise, and we minimized PCR cycles and retained duplicates during prediction, which significantly increased the positive rate for activating regulatory elements (AREs). Using this method, we determined that AREs are associated with AT-rich regions and are enriched for a motif that the AP2/ERF family can recognize. Based on GC content preferences, AREs are clustered into two groups corresponding to promoters and enhancers. Either AT- or GC-rich regions within AREs could boost transcription. Additionally, disruption of AREs resulted in abnormal expression of both proximal and distal genes, which suggests that STARR-seq-revealed elements function as enhancers in vivo. In summary, our work provides a promising method to identify AREs in plants.

Systematic discovery and functional dissection of enhancers needed for cancer cell fitness and proliferation

A scarcity of functionally validated enhancers in the human genome presents a significant hurdle to understanding how these cis-regulatory elements contribute to human diseases. We carry out highly multiplexed CRISPR-based perturbation and sequencing to identify enhancers required for cell proliferation and fitness in 10 human cancer cell lines. Our results suggest that the cell fitness enhancers, unlike their target genes, display high cell-type specificity of chromatin features. They typically adopt a modular structure, comprised of activating elements enriched for motifs of oncogenic transcription factors, surrounded by repressive elements enriched for motifs recognized by transcription factors with tumor suppressor functions. We further identify cell fitness enhancers that are selectively accessible in clinical tumor samples, and the levels of chromatin accessibility are associated with patient survival. These results reveal functional enhancers across multiple cancer cell lines, characterize their context-dependent chromatin organization, and yield insights into altered transcription programs in cancer cells.