High-throughput Reporter Assay Research Articles

Quantitative, titratable and high-throughput reporter assays to measure DNA double strand break repair activity in cells.

Repair of DNA damage is essential for the maintenance of genome stability and cell viability. DNA double strand breaks (DSBs) constitute a toxic class of DNA lesion and multiple cellular pathways exist to mediate their repair. Robust and titratable assays of cellular DSB repair (DSBR) are important to functionally interrogate the integrity and efficiency of these mechanisms in disease models as well as in response to genetic or pharmacological perturbations. Several variants of DSBR reporters are available, however these are often limited by throughput or restricted to specific cellular models. Here, we describe the generation and validation of a suite of extrachromosomal reporter assays that can efficiently measure the major DSBR pathways of homologous recombination (HR), classical nonhomologous end joining (cNHEJ), microhomology-mediated end joining (MMEJ) and single strand annealing (SSA). We demonstrate that these assays can be adapted to a high-throughput screening format and that they are sensitive to pharmacological modulation, thus providing mechanistic and quantitative insights into compound potency, selectivity, and on-target specificity. We propose that these reporter assays can serve as tools to dissect the interplay of DSBR pathway networks in cells and will have broad implications for studies of DSBR mechanisms in basic research and drug discovery.

Single-cell multiomics of the human retina reveals hierarchical transcription factor collaboration in mediating cell type-specific effects of genetic variants on gene regulation

BackgroundSystematic characterization of how genetic variation modulates gene regulation in a cell type-specific context is essential for understanding complex traits. To address this question, we profile gene expression and chromatin accessibility in cells from healthy retinae of 20 human donors through single-cell multiomics and genomic sequencing.ResultsWe map eQTL, caQTL, allelic-specific expression, and allelic-specific chromatin accessibility in major retinal cell types. By integrating these results, we identify and characterize regulatory elements and genetic variants effective on gene regulation in individual cell types. The majority of identified sc-eQTLs and sc-caQTLs display cell type-specific effects, while the cis-elements containing genetic variants with cell type-specific effects are often accessible in multiple cell types. Furthermore, the transcription factors whose binding sites are perturbed by genetic variants tend to have higher expression levels in the cell types where the variants exert their effects, compared to the cell types where the variants have no impact. We further validate our findings with high-throughput reporter assays. Lastly, we identify the enriched cell types, candidate causal variants and genes, and cell type-specific regulatory mechanism underlying GWAS loci.ConclusionsOverall, genetic effects on gene regulation are highly context dependent. Our results suggest that cell type-dependent genetic effect is driven by precise modulation of both trans-factor expression and chromatin accessibility of cis-elements. Our findings indicate hierarchical collaboration among transcription factors plays a crucial role in mediating cell type-specific effects of genetic variants on gene regulation.

FRI455 Polycystic Ovary Syndrome-Associated DENND1A Non-Coding Risk Loci Alter Gene Expression

Abstract Disclosure: L. Sankaranarayanan: None. G. Johnson: None. A. Barrera: None. A.E. Dunaif: None. T. Reddy: None. Polycystic ovary syndrome (PCOS) is a leading cause of infertility and type 2 diabetes affecting 10-15% of menstruating people worldwide. PCOS is characterized by increased circulating testosterone levels, ovulatory dysfunction and insulin resistance. Genome wide association studies (GWAS) have identified ∼20 replicated common PCOS susceptibility loci in European and Han Chinese cohorts. The associated variants are predominantly non-coding and implicate neuroendocrine, reproductive, and metabolic causal pathways. Rare non-coding variants in DENND1A, a GWAS candidate gene that regulates androgen biosynthesis, were present in ∼50% of PCOS families by whole genome sequencing. These associations suggest non-coding genetic contributions to the development of PCOS. We tested the hypothesis that PCOS GWAS risk loci contribute to PCOS pathogenesis by altering gene regulation. We first identified ∼1500 functioning regulatory elements across the GWAS associated regions using a high throughput reporter assay, STARR-seq, in two different cell lines. We used H295R, an adrenal cell line model for testosterone production and COV434, an ovarian granulosa cell line. We identified cell-line specific and overlapping regulatory regions suggesting that there is context specific gene regulation. Sixty percent of the identified regions are in previously documented open chromatin regions from DNase-seq and ATAC-seq studies supporting our hypothesis that these regulatory regions are functional. We additionally experimentally tested the regulatory effect of five of the regulatory regions identified in the DENND1A locus in H295R cells using CRISPR-based epigenetic editing tools. This endogenous perturbation increases DENND1A gene levels (measured by qPCR) and also increased testosterone produced by the H295R cells (measured by ELISA), suggesting that these regions are biologically relevant to PCOS pathogenesis.We investigated allele-specific regulatory activity in a multi-ethnic pool of five genomes from healthy individuals. We identified 21 common genetic variants (minor allele frequency in the population >0.05) that alter regulatory activity in the DENND1A locus, including two that are ancestry-specific. Further, rs12237685 and rs28441318 are also eQTLS for DENND1A from the GTEX project and reside within open chromatin regions in ovarian cells. The functional consequences of non-coding genetic variants associated with complex traits has been exceptionally difficult to elucidate. Our findings suggest that both the common genetic variants and rare PCOS patient-associated DENND1A variants and altered gene expression. Further, some of those variants may contribute to allele-specific genetic risk for PCOS. Presentation Date: Friday, June 16, 2023

5. Collaborative Study on the Genetics of Alcoholism: Functional genomics.

Alcohol Use Disorder is a complex genetic disorder, involving genetic, neural, and environmental factors, and their interactions. The Collaborative Study on the Genetics of Alcoholism (COGA) has been investigating these factors and identified putative alcohol use disorder risk genes through genome-wide association studies. In this review, we describe advances made by COGA in elucidating the functional changes induced by alcohol use disorder risk genes using multimodal approaches with human cell lines and brain tissue. These studies involve investigating gene regulation in lymphoblastoid cells from COGA participants and in post-mortem brain tissues. High throughput reporter assays are being used to identify single nucleotide polymorphisms in which alternate alleles differ in driving gene expression. Specific single nucleotide polymorphisms (both coding or noncoding) have been modeled using induced pluripotent stem cells derived from COGA participants to evaluate the effects of genetic variants on transcriptomics, neuronal excitability, synaptic physiology, and the response to ethanol in human neurons from individuals with and without alcohol use disorder. We provide a perspective on future studies, such as using polygenic risk scores and populations of induced pluripotent stem cell-derived neurons to identify signaling pathways related with responses to alcohol. Starting with genes or loci associated with alcohol use disorder, COGA has demonstrated that integration of multimodal data within COGA participants and functional studies can reveal mechanisms linking genomic variants with alcohol use disorder, and potential targets for future treatments.

Practical application of massively parallel reporter assay in biotechnology and medicine

The development and viability of an organism relies on tissue-specific gene programs. The genome regulatory elements play a key role in the regulation of such programs, whereas its disfunction can lead to the establishment of various pathologies, including cancer, congenital disorders, and autoimmune diseases. The development of high-throughput approaches in genomics has led to the emergence of massively parallel reporter assays (MPRA), which enable genome-wide screening and functional verification of regulatory elements. Although MPRA was originally used for investigation of fundamental aspects of epigenetics, it also has a great potential for clinical and practical biotechnology. Currently, MPRA is used for validation of clinically significant mutations, identification of tissue-specific regulatory elements, identification of the favorable loci for transgene integration, as well as represents an essential tool for creating highly efficient expression systems, with a wide range of applications from protein production and design of novel therapeutic antibody super-producers to gene therapy. In this review, the basic principles and areas of practical application of high-throughput reporter assays will be discussed.

Translational enhancement by base editing of the Kozak sequence rescues haploinsufficiency.

A variety of single-gene human diseases are caused by haploinsufficiency, a genetic condition by which mutational inactivation of one allele leads to reduced protein levels and functional impairment. Translational enhancement of the spare allele could exert a therapeutic effect. Here we developed BOOST, a novel gene-editing approach to rescue haploinsufficiency loci by the change of specific single nucleotides in the Kozak sequence, which controls translation by regulating start codon recognition. We evaluated for translational strength 230 Kozak sequences of annotated human haploinsufficient genes and 4621 derived variants, which can be installed by base editing, by a high-throughput reporter assay. Of these variants, 149 increased the translation of 47 Kozak sequences, demonstrating that a substantial proportion of haploinsufficient genes are controlled by suboptimal Kozak sequences. Validation of 18 variants for 8 genes produced an average enhancement in an expression window compatible with the rescue of the genetic imbalance. Base editing of the NCF1 gene, whose monoallelic loss causes chronic granulomatous disease, resulted in the desired increase of NCF1 (p47phox) protein levels in a relevant cell model. We propose BOOST as a fine-tuned approach to modulate translation, applicable to the correction of dozens of haploinsufficient monogenic disorders independently of the causing mutation.

Epigenomic profiling of glucocorticoid responses identifies cis-regulatory disruptions impacting steroid resistance in childhood acute lymphoblastic leukemia

Glucocorticoids (GCs) are a mainstay of contemporary, multidrug chemotherapy in the treatment of childhood acute lymphoblastic leukemia (ALL), and resistance to GCs remains a major clinical concern. Resistance to GCs is predictive of ALL relapse and poor clinical outcome, and therefore represents a major hurdle limiting further improvements in survival rates. While advances have been made in identifying genes implicated in GC resistance, there remains an insufficient understanding of the impact of cis-regulatory disruptions in resistance. To address this, we mapped the gene regulatory response to GCs in two ALL cell lines using functional genomics and high-throughput reporter assays and identified thousands of GC-responsive changes to chromatin state, including the formation of over 250 GC-responsive super-enhancers and a depletion of AP-1 bound cis-regulatory elements implicated in cell proliferation and anti-apoptotic processes. By integrating our GC response maps with genetic and epigenetic datasets in primary ALL cells from patients, we further uncovered cis-regulatory disruptions at GC-responsive genes that impact GC resistance in childhood ALL. Overall, these data indicate that GCs initiate pervasive effects on the leukemia epigenome, and that alterations to the GC gene regulatory network contribute to GC resistance.

Compatibility rules of human enhancer and promoter sequences.

Gene regulation in the human genome is controlled by distal enhancers that activate specific nearby promoters1. A proposed model for this specificity is that promoters have sequence-encoded preferences for certain enhancers, for example, mediated by interacting sets of transcription factors or cofactors2. This 'biochemical compatibility' model has been supported by observations at individual human promoters and by genome-wide measurements in Drosophila3-9. However, the degree to which human enhancers and promoters are intrinsically compatible has not yet been systematically measured, and how their activities combine to control RNA expression remains unclear. Here we design a high-throughput reporter assay called enhancer × promoter self-transcribing active regulatory region sequencing (ExP STARR-seq) and applied it to examine the combinatorial compatibilities of 1,000 enhancer and 1,000 promoter sequences in human K562 cells. We identify simple rules for enhancer-promoter compatibility, whereby most enhancers activate all promoters by similar amounts, and intrinsic enhancer and promoter activities multiplicatively combine to determine RNA output (R2 = 0.82). In addition, two classes of enhancers and promoters show subtle preferential effects. Promoters of housekeeping genes contain built-in activating motifs for factors such as GABPA and YY1, which decrease the responsiveness of promoters to distal enhancers. Promoters of variably expressed genes lack these motifs and show stronger responsiveness to enhancers. Together, this systematic assessment of enhancer-promoter compatibility suggests a multiplicative model tuned by enhancer and promoter class to control gene transcription in the human genome.

Host-Dependent Producibility of Recombinant Cypridina noctiluca Luciferase With Glycosylation Defects.

Cypridina noctiluca luciferase (CLuc) is a secreted luminescent protein that reacts with its substrate (Cypridina luciferin) to emit light. CLuc is known to be a thermostable protein and has been used for various research applications, including in vivo imaging and high-throughput reporter assays. Previously, we produced a large amount of recombinant CLuc for crystallographic analysis. However, this recombinant protein did not crystallize, probably due to heterogeneous N-glycan modifications. In this study, we produced recombinant CLuc without glycan modifications by introducing mutations at the N-glycan modification residues using mammalian Expi293F cells, silkworms, and tobacco Bright Yellow-2 cells. Interestingly, recombinant CLuc production depended heavily on the expression hosts. Among these selected hosts, we found that Expi293F cells efficiently produced the recombinant mutant CLuc without significant effects on its luciferase activity. We confirmed the lack of N-glycan modifications for this mutant protein by mass spectrometry analysis but found slight O-glycan modifications that we estimated were about 2% of the ion chromatogram peak area for the detected peptide fragments. Moreover, by using CLuc deletion mutants during the investigation of O-glycan modifications, we identified amino acid residues important to the luciferase activity of CLuc. Our results provide invaluable information related to CLuc function and pave the way for its crystallographic analysis.

Epromoters function as a hub to recruit key transcription factors required for the inflammatory response

Gene expression is controlled by the involvement of gene-proximal (promoters) and distal (enhancers) regulatory elements. Our previous results demonstrated that a subset of gene promoters, termed Epromoters, work as bona fide enhancers and regulate distal gene expression. Here, we hypothesized that Epromoters play a key role in the coordination of rapid gene induction during the inflammatory response. Using a high-throughput reporter assay we explored the function of Epromoters in response to type I interferon. We find that clusters of IFNa-induced genes are frequently associated with Epromoters and that these regulatory elements preferentially recruit the STAT1/2 and IRF transcription factors and distally regulate the activation of interferon-response genes. Consistently, we identified and validated the involvement of Epromoter-containing clusters in the regulation of LPS-stimulated macrophages. Our findings suggest that Epromoters function as a local hub recruiting the key TFs required for coordinated regulation of gene clusters during the inflammatory response.

PARROT is a flexible recurrent neural network framework for analysis of large protein datasets.

The rise of high-throughput experiments has transformed how scientists approach biological questions. The ubiquity of large-scale assays that can test thousands of samples in a day has necessitated the development of new computational approaches to interpret this data. Among these tools, machine learning approaches are increasingly being utilized due to their ability to infer complex nonlinear patterns from high-dimensional data. Despite their effectiveness, machine learning (and in particular deep learning) approaches are not always accessible or easy to implement for those with limited computational expertise. Here we present PARROT, a general framework for training and applying deep learning-based predictors on large protein datasets. Using an internal recurrent neural network architecture, PARROT is capable of tackling both classification and regression tasks while only requiring raw protein sequences as input. We showcase the potential uses of PARROT on three diverse machine learning tasks: predicting phosphorylation sites, predicting transcriptional activation function of peptides generated by high-throughput reporter assays, and predicting the fibrillization propensity of amyloid beta with data generated by deep mutational scanning. Through these examples, we demonstrate that PARROT is easy to use, performs comparably to state-of-the-art computational tools, and is applicable for a wide array of biological problems.

Cis-regulatory variants affect gene expression dynamics in yeast.

Evolution of cis-regulatory sequences depends on how they affect gene expression and motivates both the identification and prediction of cis-regulatory variants responsible for expression differences within and between species. While much progress has been made in relating cis-regulatory variants to expression levels, the timing of gene activation and repression may also be important to the evolution of cis-regulatory sequences. We investigated allele-specific expression (ASE) dynamics within and between Saccharomyces species during the diauxic shift and found appreciable cis-acting variation in gene expression dynamics. Within-species ASE is associated with intergenic variants, and ASE dynamics are more strongly associated with insertions and deletions than ASE levels. To refine these associations, we used a high-throughput reporter assay to test promoter regions and individual variants. Within the subset of regions that recapitulated endogenous expression, we identified and characterized cis-regulatory variants that affect expression dynamics. Between species, chimeric promoter regions generate novel patterns and indicate constraints on the evolution of gene expression dynamics. We conclude that changes in cis-regulatory sequences can tune gene expression dynamics and that the interplay between expression dynamics and other aspects of expression is relevant to the evolution of cis-regulatory sequences.

A high-throughput cell-based gaussia luciferase reporter assay for measurement of CYP1A1, CYP2B6, and CYP3A4 induction

The induction of cytochrome P450s can result in reduced drug efficacy and lead to potential drug–drug interactions. The xenoreceptors—aryl hydrocarbon receptor (AhR), constitutive androstane receptor (CAR), and pregnane X receptor (PXR)—play key roles in CYP induction by xenobiotics. In order to be able to rapidly screen for the induction of three enzymes (CYP1A1, CYP2B6, and CYP3A4), we generated a stable AhR-responsive HepG2 cell line, a stable CAR-responsive HepG2 cell line, and a stable PXR-responsive HepG2 cell line. To validate these stable xenoreceptor-responsive HepG2 cell lines, we evaluated the induction of the different Gaussia reporter activities, as well as the mRNA and protein expression levels of endogenous CYPs in response to different inducers. The induction of luciferase activity in the stable xenoreceptor-responsive HepG2 cell lines by specific inducers occurred in a concentration dependent manner. There was a positive correlation between the induction of luciferase activities and the induction endogenous CYP mRNA expression levels. These xenoreceptor-responsive HepG2 cell lines were further validated with known CYP1A1, CYP2B6, and CYP3A4 inducers. These stable xenoreceptor-responsive HepG2 cell lines may be used in preclinical research for the rapid and sensitive detection of AhR, CAR, and PXR ligands that induce CYP450 isoforms.

Correcting signal biases and detecting regulatory elements in STARR-seq data.

High-throughput reporter assays such as self-transcribing active regulatory region sequencing (STARR-seq) have made it possible to measure regulatory element activity across the entire human genome at once. The resulting data, however, present substantial analytical challenges. Here, we identify technical biases that explain most of the variance in STARR-seq data. We then develop a statistical model to correct those biases and to improve detection of regulatory elements. This approach substantially improves precision and recall over current methods, improves detection of both activating and repressive regulatory elements, and controls for false discoveries despite strong local correlations in signal.

A systematic evaluation of the design and context dependencies of massively parallel reporter assays.

Massively parallel reporter assays (MPRAs) functionally screen thousands of sequences for regulatory activity in parallel. To date, there has been no systematic comparison of differences in MPRA design. Here, we screen a library of 2,440 candidate liver enhancers and controls for regulatory activity in HepG2 cells using nine different MPRA designs. We identify subtle but significant differences that correlate with epigenetic and sequence-level features, as well as differences in dynamic range and reproducibility. We also validate en masse that enhancer activity is robustly independent of orientation, at least for our library and designs. Finally, with a new method, we assemble and test the same enhancers as 192-mers, 354-mers, and 678-mers, and observe surprisingly large differences. This work provides a framework for the experimental design of high-throughput reporter assays, suggesting that the extended sequence context of tested elements, and to a lesser degree the precise assay, influence MPRA results.

Correction: Integration of high-throughput reporter assays identify a critical enhancer of the Ikzf1 gene.

[This corrects the article DOI: 10.1371/journal.pone.0233191.].

Integration of high-throughput reporter assays identify a critical enhancer of the Ikzf1 gene.

The Ikzf1 locus encodes the lymphoid specific transcription factor Ikaros, which plays an essential role in both T and B cell differentiation, while deregulation or mutation of IKZF1/Ikzf1 is involved in leukemia. Tissue-specific and cell identity genes are usually associated with clusters of enhancers, also called super-enhancers, which are believed to ensure proper regulation of gene expression throughout cell development and differentiation. Several potential regulatory regions have been identified in close proximity of Ikzf1, however, the full extent of the regulatory landscape of the Ikzf1 locus is not yet established. In this study, we combined epigenomics and transcription factor binding along with high-throughput enhancer assay and 4C-seq to prioritize an enhancer element located 120 kb upstream of the Ikzf1 gene. We found that deletion of the E120 enhancer resulted in a significant reduction of Ikzf1 mRNA. However, the epigenetic landscape and 3D topology of the locus were only slightly affected, highlighting the complexity of the regulatory landscape regulating the Ikzf1 locus.

Allele-specific expression and high-throughput reporter assay reveal functional genetic variants associated with alcohol use disorders

Genome-wide association studies (GWAS) of complex traits, such as alcohol use disorders (AUD), usually identify variants in non-coding regions and cannot by themselves distinguish whether the associated variants are functional or in linkage disequilibrium with the functional variants. Transcriptome studies can identify genes whose expression differs between alcoholics and controls. To test which variants associated with AUD may cause expression differences, we integrated data from deep RNA-seq and GWAS of four postmortem brain regions from 30 subjects with AUD and 30 controls to analyze allele-specific expression (ASE). We identified 88 genes with differential ASE in subjects with AUD compared to controls. Next, to test one potential mechanism contributing to the differential ASE, we analyzed single nucleotide polymorphisms (SNPs) in the 3′ untranslated regions (3′UTR) of these genes. Of the 88 genes with differential ASE, 61 genes contained 437 SNPs in the 3′UTR with at least one heterozygote among the subjects studied. Using a modified PASSPORT-seq (parallel assessment of polymorphisms in miRNA target-sites by sequencing) assay, we identified 25 SNPs that affected RNA levels in a consistent manner in two neuroblastoma cell lines, SH-SY5Y and SK-N-BE(2). Many of these SNPs are in binding sites of miRNAs and RNA-binding proteins, indicating that these SNPs are likely causal variants of AUD-associated differential ASE. In sum, we demonstrate that a combination of computational and experimental approaches provides a powerful strategy to uncover functionally relevant variants associated with the risk for AUD.

Bayesian estimation of genetic regulatory effects in high-throughput reporter assays.

High-throughput reporter assays dramatically improve our ability to assign function to noncoding genetic variants, by measuring allelic effects on gene expression in the controlled setting of a reporter gene. Unlike genetic association tests, such assays are not confounded by linkage disequilibrium when loci are independently assayed. These methods can thus improve the identification of causal disease mutations. While work continues on improving experimental aspects of these assays, less effort has gone into developing methods for assessing the statistical significance of assay results, particularly in the case of rare variants captured from patient DNA. We describe a Bayesian hierarchical model, called Bayesian Inference of Regulatory Differences, which integrates prior information and explicitly accounts for variability between experimental replicates. The model produces substantially more accurate predictions than existing methods when allele frequencies are low, which is of clear advantage in the search for disease-causing variants in DNA captured from patient cohorts. Using the model, we demonstrate a clear tradeoff between variant sequencing coverage and numbers of biological replicates, and we show that the use of additional biological replicates decreases variance in estimates of effect size, due to the properties of the Poisson-binomial distribution. We also provide a power and sample size calculator, which facilitates decision making in experimental design parameters. The software is freely available from www.geneprediction.org/bird. The experimental design web tool can be accessed at http://67.159.92.22:8080. Supplementary data are available at Bioinformatics online.

Genomic annotation of disease-associated variants reveals shared functional contexts.

Variation in non-coding DNA, encompassing gene regulatory regions such as enhancers and promoters, contributes to risk for complex disorders, including type 2 diabetes. While genome-wide association studies have successfully identified hundreds of type 2 diabetes loci throughout the genome, the vast majority of these reside in non-coding DNA, which complicates the process of determining their functional significance and level of priority for further study. Here we review the methods used to experimentally annotate these non-coding variants, to nominate causal variants and to link them to diabetes pathophysiology. In recent years, chromatin profiling, massively parallel sequencing, high-throughput reporter assays and CRISPR gene editing technologies have rapidly become indispensable tools. Rather than treating individual variants in isolation, we discuss the importance of accounting for context, both genetic (such as flanking DNA sequence) and environmental (such as cellular state or environmental exposure). Incorporating these features shows promise in terms of revealing biologically convergent molecular signatures across distant and seemingly unrelated loci. Studying regulatory elements in the proper context will be crucial for interpreting the functional significance of disease-associated variants and applying the resulting knowledge to improve patient care.