lentiMPRA and MPRAflow for high-throughput functional characterization of gene regulatory elements

Proximity analysis of native proteomes reveals phenotypic modifiers in a mouse model of autism and related neurodevelopmental conditions

One of the main drivers of autism spectrum disorder is risk alleles within hundreds of genes, which may interact within shared but unknown protein complexes. Here we develop a scalable genome-editing-mediated approach to target 14 high-confidence autism risk genes within the mouse brain for proximity-based endogenous proteomics, achieving the identification of high-specificity spatial proteomes. The resulting native proximity proteomes are enriched for human genes dysregulated in the brain of autistic individuals, and reveal proximity interactions between proteins from high-confidence risk genes with those of lower-confidence that may provide new avenues to prioritize genetic risk. Importantly, the datasets are enriched for shared cellular functions and genetic interactions that may underlie the condition. We test this notion by spatial proteomics and CRISPR-based regulation of expression in two autism models, demonstrating functional interactions that modulate mechanisms of their dysregulation. Together, these results reveal native proteome networks in vivo relevant to autism, providing new inroads for understanding and manipulating the cellular drivers underpinning its etiology.

Deciphering the genetics and mechanisms of predisposition to multiple myeloma

Multiple myeloma (MM) is an incurable malignancy of plasma cells. Epidemiological studies indicate a substantial heritable component, but the underlying mechanisms remain unclear. Here, in a genome-wide association study totaling 10,906 cases and 366,221 controls, we identify 35 MM risk loci, 12 of which are novel. Through functional fine-mapping and Mendelian randomization, we uncover two causal mechanisms for inherited MM risk: longer telomeres; and elevated levels of B-cell maturation antigen (BCMA) and interleukin-5 receptor alpha (IL5RA) in plasma. The largest increase in BCMA and IL5RA levels is mediated by the risk variant rs34562254-A at TNFRSF13B. While individuals with loss-of-function variants in TNFRSF13B develop B-cell immunodeficiency, rs34562254-A exerts a gain-of-function effect, increasing MM risk through amplified B-cell responses. Our results represent an analysis of genetic MM predisposition, highlighting causal mechanisms contributing to MM development.

Dynamic stress- and inflammatory-based regulation of psychiatric risk loci in human neurons

The prenatal environment can alter neurodevelopmental and clinical trajectories, markedly increasing risk for psychiatric disorders in childhood and adolescence. To understand if and how fetal exposures to stress and inflammation exacerbate manifestation of genetic risk for complex brain disorders, we report a large-scale context-dependent massively parallel reporter assay (MPRA) in human neurons designed to catalogue genotype x environment (GxE) interactions. Across 240 genome-wide association study (GWAS) loci linked to ten brain traits/disorders, the impact of hydrocortisone, interleukin 6, and interferon alpha on transcriptional activity is empirically evaluated in human induced pluripotent stem cell (hiPSC)-derived glutamatergic neurons. Of ~3,500 candidate regulatory risk elements (CREs), 11% of variants are active at baseline, whereas cue-specific CRE regulatory activity range from a high of 23% (hydrocortisone) to a low of 6% (IL-6). Cue-specific regulatory activity is driven, at least in part, by differences in transcription factor binding activity, the gene targets of which show unique enrichments for brain disorders as well as co-morbid metabolic and immune syndromes. The dynamic nature of genetic regulation informs the influence of environmental factors, reveals a mechanism underlying pleiotropy and variable penetrance, and identifies specific risk variants that confer greater disorder susceptibility after exposure to stress or inflammation. Understanding neurodevelopmental GxE interactions will inform mental health trajectories and uncover novel targets for therapeutic intervention.

GET: a foundation model of transcription across human cell types

Transcriptional regulation, involving the complex interplay between regulatory sequences and proteins, directs all biological processes. Computational models of transcription lack generalizability to accurately extrapolate in unseen cell types and conditions. Here, we introduce GET, an interpretable foundation model designed to uncover regulatory grammars across 213 human fetal and adult cell types. Relying exclusively on chromatin accessibility data and sequence information, GET achieves experimental-level accuracy in predicting gene expression even in previously unseen cell types. GET showcases remarkable adaptability across new sequencing platforms and assays, enabling regulatory inference across a broad range of cell types and conditions, and uncovering universal and cell type specific transcription factor interaction networks. We evaluated its performance on prediction of regulatory activity, inference of regulatory elements and regulators, and identification of physical interactions between transcription factors. Specifically, we show GET outperforms current models in predicting lentivirus-based massive parallel reporter assay readout with reduced input data. In fetal erythroblasts, we identify distal (>1Mbp) regulatory regions that were missed by previous models. In B cells, we identified a lymphocyte-specific transcription factor-transcription factor interaction that explains the functional significance of a leukemia-risk predisposing germline mutation. In sum, we provide a generalizable and accurate model for transcription together with catalogs of gene regulation and transcription factor interactions, all with cell type specificity.

Iterative deep learning-design of human enhancers exploits condensed sequence grammar to achieve cell type-specificity

An important and largely unsolved problem in synthetic biology is how to target gene expression to specific cell types. Here, we apply iterative deep learning to design synthetic enhancers with strong differential activity between two human cell lines. We initially train models on published datasets of enhancer activity and chromatin accessibility and use them to guide the design of synthetic enhancers that maximize predicted specificity. We experimentally validate these sequences, use the measurements to re-optimize the predictor, and design a second generation of enhancers with improved specificity. Our design methods embed relevant transcription factor binding site (TFBS) motifs with higher frequencies than comparable endogenous enhancers while using a more selective motif vocabulary, and we show that enhancer activity is correlated with transcription factor expression at the single cell level. Finally, we characterize causal features of top enhancers via perturbation experiments and show enhancers as short as 50bp can maintain specificity.

Decoding polygenic diseases: advances in noncoding variant prioritization and validation

Genome-wide association studies (GWASs) provide a key foundation for elucidating the genetic underpinnings of common polygenic diseases. However, these studies have limitations in their ability to assign causality to particular genetic variants, especially those residing in the noncoding genome. Over the past decade, technological and methodological advances in both analytical and empirical prioritization of noncoding variants have enabled the identification of causative variants by leveraging orthogonal functional evidence at increasing scale. In this review, we present an overview of these approaches and describe how this workflow provides the groundwork necessary to move beyond associations toward genetically informed studies on the molecular and cellular mechanisms of polygenic disease.

Methods for Functional Characterization of Genetic Polymorphisms of Non-Coding Regulatory Regions of the Human Genome

Currently, numerous associations between genetic polymorphisms and various diseases have been characterized through the Genome-Wide Association Studies. Majority of the clinically significant polymorphisms are localized in non-coding regions of the genome. While modern bioinformatic resources make it possible to predict molecular mechanisms that explain influence of the non-coding polymorphisms on gene expression, such hypotheses require experimental verification. This review discusses the methods for elucidating molecular mechanisms underlying dependence of the disease pathogenesis on specific genetic variants within the non-coding sequences. A particular focus is on the methods for identification of transcription factors with binding efficiency dependent on polymorphic variations. Despite remarkable progress in bioinformatic resources enabling prediction of the impact of polymorphisms on the disease pathogenesis, there is still the need for experimental approaches to investigate this issue.

Area postrema neurons mediate interleukin-6 function in cancer cachexia

Interleukin-6 (IL-6) has been long considered a key player in cancer cachexia. It is believed that sustained elevation of IL-6 production during cancer progression causes brain dysfunctions, which ultimately result in cachexia. However, how peripheral IL-6 influences the brain remains poorly understood. Here we show that neurons in the area postrema (AP), a circumventricular structure in the hindbrain, is a critical mediator of IL-6 function in cancer cachexia in male mice. We find that circulating IL-6 can rapidly enter the AP and activate neurons in the AP and its associated network. Peripheral tumor, known to increase circulating IL-6, leads to elevated IL-6 in the AP, and causes potentiated excitatory synaptic transmission onto AP neurons and AP network hyperactivity. Remarkably, neutralization of IL-6 in the brain of tumor-bearing mice with an anti-IL-6 antibody attenuates cachexia and the hyperactivity in the AP network, and markedly prolongs lifespan. Furthermore, suppression of Il6ra, the gene encoding IL-6 receptor, specifically in AP neurons with CRISPR/dCas9 interference achieves similar effects. Silencing Gfral-expressing AP neurons also attenuates cancer cachectic phenotypes and AP network hyperactivity. Our study identifies a central mechanism underlying the function of peripheral IL-6, which may serve as a target for treating cancer cachexia.

Massively parallel characterization of regulatory elements in the developing human cortex

Nucleotide changes in gene regulatory elements are important determinants of neuronal development and diseases. Using massively parallel reporter assays in primary human cells from mid-gestation cortex and cerebral organoids, we interrogated the cis-regulatory activity of 102,767 open chromatin regions, including thousands of sequences with cell type-specific accessibility and variants associated with brain gene regulation. In primary cells, we identified 46,802 active enhancer sequences and 164 variants that alter enhancer activity. Activity was comparable in organoids and primary cells, suggesting that organoids provide an adequate model for the developing cortex. Using deep learning we decoded the sequence basis and upstream regulators of enhancer activity. This work establishes a comprehensive catalog of functional gene regulatory elements and variants in human neuronal development.

Genetic regulation of cell type-specific chromatin accessibility shapes brain disease etiology

Nucleotide variants in cell type-specific gene regulatory elements in the human brain are risk factors for human disease. We measured chromatin accessibility in 1932 aliquots of sorted neurons and non-neurons from 616 human postmortem brains and identified 34,539 open chromatin regions with chromatin accessibility quantitative trait loci (caQTLs). Only 10.4% of caQTLs are shared between neurons and non-neurons, which supports cell type-specific genetic regulation of the brain regulome. Incorporating allele-specific chromatin accessibility improves statistical fine-mapping and refines molecular mechanisms that underlie disease risk. Using massively parallel reporter assays in induced excitatory neurons, we screened 19,893 brain QTLs and identified the functional impact of 476 regulatory variants. Combined, this comprehensive resource captures variation in the human brain regulome and provides insights into disease etiology.

Massively parallel reporter assays and mouse transgenic assays provide complementary information about neuronal enhancer activity

Genetic studies find hundreds of thousands of noncoding variants associated with psychiatric disorders. Massively parallel reporter assays (MPRAs) and in vivo transgenic mouse assays can be used to assay the impact of these variants. However, the relevance of MPRAs to in vivo function is unknown and transgenic assays suffer from low throughput. Here, we studied the utility of combining the two assays to study the impact of non-coding variants. We carried out an MPRA on over 50,000 sequences derived from enhancers validated in transgenic mouse assays and from multiple fetal neuronal ATAC-seq datasets. We also tested over 20,000 variants, including synthetic mutations in highly active neuronal enhancers and 177 common variants associated with psychiatric disorders. Variants with a high impact on MPRA activity were further tested in mice. We found a strong and specific correlation between MPRA and mouse neuronal enhancer activity including changes in neuronal enhancer activity in mouse embryos for variants with strong MPRA effects. Mouse assays also revealed pleiotropic variant effects that could not be observed in MPRA. Our work provides a large catalog of functional neuronal enhancers and variant effects and highlights the effectiveness of combining MPRAs and mouse transgenic assays.

Dissecting the biology of feeding and eating disorders

Feeding and eating disorders (FEDs) are heterogenous and characterized by varying patterns of dysregulated eating and weight. Genome-wide association studies (GWASs) are clarifying their underlying biology and their genetic relationship to other psychiatric and metabolic/anthropometric traits. Genetic research on anorexia nervosa (AN) has identified eight significant loci and uncovered genetic correlations implicating both psychiatric and metabolic/anthropometric risk factors. Careful explication of these metabolic contributors may be key to developing effective and enduring treatments for devastating, life-altering, and frequently lethal illnesses. We discuss clinical phenomenology, genomics, phenomics, intestinal microbiota, and functional genomics and propose a path that translates variants to genes, genes to pathways, and pathways to metabolic outcomes to advance the science and eventually treatment of FEDs.

Optimizing sequence design strategies for perturbation MPRAs: a computational evaluation framework

The advent of perturbation-based massively parallel reporter assays (MPRAs) technique has facilitated the delineation of the roles of non-coding regulatory elements in orchestrating gene expression. However, computational efforts remain scant to evaluate and establish guidelines for sequence design strategies for perturbation MPRAs. In this study, we propose a framework for evaluating and comparing various perturbation strategies for MPRA experiments. Within this framework, we benchmark three different perturbation approaches from the perspectives of alteration in motif-based profiles, consistency of MPRA outputs, and robustness of models that predict the activities of putative regulatory motifs. While our analyses show very similar results across multiple benchmarking metrics, the predictive modeling for the approach involving random nucleotide shuffling shows significant robustness compared with the other two approaches. Thus, we recommend designing sequences by randomly shuffling the nucleotides of the perturbed site in perturbation-MPRA, followed by a coherence check to prevent the introduction of other variations of the target motifs. In summary, our evaluation framework and the benchmarking findings create a resource of computational pipelines and highlight the potential of perturbation-MPRA in predicting non-coding regulatory activities.

Characterization of enhancer activity in early human neurodevelopment using Massively Parallel Reporter Assay (MPRA) and forebrain organoids

Regulation of gene expression through enhancers is one of the major processes shaping the structure and function of the human brain during development. High-throughput assays have predicted thousands of enhancers involved in neurodevelopment, and confirming their activity through orthogonal functional assays is crucial. Here, we utilized Massively Parallel Reporter Assays (MPRAs) in stem cells and forebrain organoids to evaluate the activity of ~ 7000 gene-linked enhancers previously identified in human fetal tissues and brain organoids. We used a Gaussian mixture model to evaluate the contribution of background noise in the measured activity signal to confirm the activity of ~ 35% of the tested enhancers, with most showing temporal-specific activity, suggesting their evolving role in neurodevelopment. The temporal specificity was further supported by the correlation of activity with gene expression. Our findings provide a valuable gene regulatory resource to the scientific community.

Characterization of caffeine response regulatory variants in vascular endothelial cells

Genetic variants in gene regulatory sequences can modify gene expression and mediate the molecular response to environmental stimuli. In addition, genotype-environment interactions (GxE) contribute to complex traits such as cardiovascular disease. Caffeine is the most widely consumed stimulant and is known to produce a vascular response. To investigate GxE for caffeine, we treated vascular endothelial cells with caffeine and used a massively parallel reporter assay to measure allelic effects on gene regulation for over 43,000 genetic variants. We identified 665 variants with allelic effects on gene regulation and 6 variants that regulate the gene expression response to caffeine (GxE, false discovery rate [FDR] < 5%). When overlapping our GxE results with expression quantitative trait loci colocalized with coronary artery disease and hypertension, we dissected their regulatory mechanisms and showed a modulatory role for caffeine. Our results demonstrate that massively parallel reporter assay is a powerful approach to identify and molecularly characterize GxE in the specific context of caffeine consumption.

Integrative functional genomic analyses identify genetic variants influencing skin pigmentation in Africans

Skin color is highly variable in Africans, yet little is known about the underlying molecular mechanism. Here we applied massively parallel reporter assays to screen 1,157 candidate variants influencing skin pigmentation in Africans and identified 165 single-nucleotide polymorphisms showing differential regulatory activities between alleles. We combine Hi-C, genome editing and melanin assays to identify regulatory elements for MFSD12, HMG20B, OCA2, MITF, LEF1, TRPS1, BLOC1S6 and CYB561A3 that impact melanin levels in vitro and modulate human skin color. We found that independent mutations in an OCA2 enhancer contribute to the evolution of human skin color diversity and detect signals of local adaptation at enhancers of MITF, LEF1 and TRPS1, which may contribute to the light skin color of Khoesan-speaking populations from Southern Africa. Additionally, we identified CYB561A3 as a novel pigmentation regulator that impacts genes involved in oxidative phosphorylation and melanogenesis. These results provide insights into the mechanisms underlying human skin color diversity and adaptive evolution.

Strategies for dissecting the complexity of neurodevelopmental disorders

Neurodevelopmental disorders (NDDs) are associated with a wide range of clinical features, affecting multiple pathways involved in brain development and function. Recent advances in high-throughput sequencing have unveiled numerous genetic variants associated with NDDs, which further contribute to disease complexity and make it challenging to infer disease causation and underlying mechanisms. Herein, we review current strategies for dissecting the complexity of NDDs using model organisms, induced pluripotent stem cells, single-cell sequencing technologies, and massively parallel reporter assays. We further highlight single-cell CRISPR-based screening techniques that allow genomic investigation of cellular transcriptomes with high efficiency, accuracy, and throughput. Overall, we provide an integrated review of experimental approaches that can be applicable for investigating a broad range of complex disorders.

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.

Quantifying orthogonal barcodes for sequence census assays

Summary

Barcode-based sequence census assays utilize custom or random oligonucloetide sequences to label various biological features, such as cell-surface proteins or CRISPR perturbations. These assays all rely on barcode quantification, a task that is complicated by barcode design and technical noise. We introduce a modular approach to quantifying barcodes that achieves speed and memory improvements over existing tools. We also introduce a set of quality control metrics, and accompanying tool, for validating barcode designs.

Availability and implementation

https://github.com/pachterlab/kb_python, https://github.com/pachterlab/qcbc.

Joint epigenome profiling reveals cell-type-specific gene regulatory programmes in human cortical organoids

Gene expression is regulated by multiple epigenetic mechanisms, which are coordinated in development and disease. However, current multiomics methods are frequently limited to one or two modalities at a time, making it challenging to obtain a comprehensive gene regulatory signature. Here, we describe a method-3D genome, RNA, accessibility and methylation sequencing (3DRAM-seq)-that simultaneously interrogates spatial genome organization, chromatin accessibility and DNA methylation genome-wide and at high resolution. We combine 3DRAM-seq with immunoFACS and RNA sequencing in cortical organoids to map the cell-type-specific regulatory landscape of human neural development across multiple epigenetic layers. Finally, we apply a massively parallel reporter assay to profile cell-type-specific enhancer activity in organoids and to functionally assess the role of key transcription factors for human enhancer activation and function. More broadly, 3DRAM-seq can be used to profile the multimodal epigenetic landscape in rare cell types and different tissues.

Characterization of human transcription factor function and patterns of gene regulation in HepG2 cells

Transcription factors (TFs) are trans-acting proteins that bind cis-regulatory elements (CREs) in DNA to control gene expression. Here, we analyzed the genomic localization profiles of 529 sequence-specific TFs and 151 cofactors and chromatin regulators in the human cancer cell line HepG2, for a total of 680 broadly termed DNA-associated proteins (DAPs). We used this deep collection to model each TF's impact on gene expression, and identified a cohort of 26 candidate transcriptional repressors. We examine high occupancy target (HOT) sites in the context of three-dimensional genome organization and show biased motif placement in distal-promoter connections involving HOT sites. We also found a substantial number of closed chromatin regions with multiple DAPs bound, and explored their properties, finding that a MAFF/MAFK TF pair correlates with transcriptional repression. Altogether, these analyses provide novel insights into the regulatory logic of the human cell line HepG2 genome and show the usefulness of large genomic analyses for elucidation of individual TF functions.

Design and deep learning of synthetic B-cell-specific promoters

Synthetic biology and deep learning synergistically revolutionize our ability for decoding and recoding DNA regulatory grammar. The B-cell-specific transcriptional regulation is intricate, and unlock the potential of B-cell-specific promoters as synthetic elements is important for B-cell engineering. Here, we designed and pooled synthesized 23 640 B-cell-specific promoters that exhibit larger sequence space, B-cell-specific expression, and enable diverse transcriptional patterns in B-cells. By MPRA (Massively parallel reporter assays), we deciphered the sequence features that regulate promoter transcriptional, including motifs and motif syntax (their combination and distance). Finally, we built and trained a deep learning model capable of predicting the transcriptional strength of the immunoglobulin V gene promoter directly from sequence. Prediction of thousands of promoter variants identified in the global human population shows that polymorphisms in promoters influence the transcription of immunoglobulin V genes, which may contribute to individual differences in adaptive humoral immune responses. Our work helps to decipher the transcription mechanism in immunoglobulin genes and offers thousands of non-similar promoters for B-cell engineering.

MPRAbase: A Massively Parallel Reporter Assay Database

Massively parallel reporter assays (MPRAs) represent a set of high-throughput technologies that measure the functional effects of thousands of sequences/variants on gene regulatory activity. There are several different variations of MPRA technology and they are used for numerous applications, including regulatory element discovery, variant effect measurement, saturation mutagenesis, synthetic regulatory element generation or characterization of evolutionary gene regulatory differences. Despite their many designs and uses, there is no comprehensive database that incorporates the results of these experiments. To address this, we developed MPRAbase, a manually curated database that currently harbors 129 experiments, encompassing 17,718,677 elements tested across 35 cell types and 4 organisms. The MPRAbase web interface ( http://www.mprabase.com ) serves as a centralized user-friendly repository to download existing MPRA data for independent analysis and is designed with the ability to allow researchers to share their published data for rapid dissemination to the community.

A Cre-dependent massively parallel reporter assay allows for cell-type specific assessment of the functional effects of non-coding elements in vivo

The function of regulatory elements is highly dependent on the cellular context, and thus for understanding the function of elements associated with psychiatric diseases these would ideally be studied in neurons in a living brain. Massively Parallel Reporter Assays (MPRAs) are molecular genetic tools that enable functional screening of hundreds of predefined sequences in a single experiment. These assays have not yet been adapted to query specific cell types in vivo in a complex tissue like the mouse brain. Here, using a test-case 3'UTR MPRA library with genomic elements containing variants from autism patients, we developed a method to achieve reproducible measurements of element effects in vivo in a cell type-specific manner, using excitatory cortical neurons and striatal medium spiny neurons as test cases. This targeted technique should enable robust, functional annotation of genetic elements in the cellular contexts most relevant to psychiatric disease.

Using a modular massively parallel reporter assay to discover context-specific regulatory grammars in type 2 diabetes

Recent genome-wide association studies have established that most complex disease-associated loci are found in noncoding regions where defining their function is nontrivial. In this study, we leverage a modular massively parallel reporter assay (MPRA) to uncover sequence features linked to context-specific regulatory activity. We screened enhancer activity across a panel of 198-bp fragments spanning over 10k type 2 diabetes- and metabolic trait-associated variants in the 832/13 rat insulinoma cell line, a relevant model of pancreatic beta cells. We explored these fragments' context sensitivity by comparing their activities when placed up-or downstream of a reporter gene, and in combination with either a synthetic housekeeping promoter (SCP1) or a more biologically relevant promoter corresponding to the human insulin gene ( INS ). We identified clear effects of MPRA construct design on measured fragment enhancer activity. Specifically, a subset of fragments (n = 702/11,656) displayed positional bias, evenly distributed across up- and downstream preference. A separate set of fragments exhibited promoter bias (n = 698/11,656), mostly towards the cell-specific INS promoter (73.4%). To identify sequence features associated with promoter preference, we used Lasso regression with 562 genomic annotations and discovered that fragments with INS promoter-biased activity are enriched for HNF1 motifs. HNF1 family transcription factors are key regulators of glucose metabolism disrupted in maturity onset diabetes of the young (MODY), suggesting genetic convergence between rare coding variants that cause MODY and common T2D-associated regulatory variants. We designed a follow-up MPRA containing HNF1 motif-enriched fragments and observed several instances where deletion or mutation of HNF1 motifs disrupted the INS promoter-biased enhancer activity, specifically in the beta cell model but not in a skeletal muscle cell line, another diabetes-relevant cell type. Together, our study suggests that cell-specific regulatory activity is partially influenced by enhancer-promoter compatibility and indicates that careful attention should be paid when designing MPRA libraries to capture context-specific regulatory processes at disease-associated genetic signals.

Combining TSS-MPRA and sensitive TSS profile dissimilarity scoring to study the sequence determinants of transcription initiation

Cis-regulatory elements (CREs) can be classified by the shapes of their transcription start site (TSS) profiles, which are indicative of distinct regulatory mechanisms. Massively parallel reporter assays (MPRAs) are increasingly being used to study CRE regulatory mechanisms, yet the degree to which MPRAs replicate individual endogenous TSS profiles has not been determined. Here, we present a new low-input MPRA protocol (TSS-MPRA) that enables measuring TSS profiles of episomal reporters as well as after lentiviral reporter chromatinization. To sensitively compare MPRA and endogenous TSS profiles, we developed a novel dissimilarity scoring algorithm (WIP score) that outperforms the frequently used earth mover's distance on experimental data. Using TSS-MPRA and WIP scoring on 500 unique reporter inserts, we found that short (153 bp) MPRA promoter inserts replicate the endogenous TSS patterns of ∼60% of promoters. Lentiviral reporter chromatinization did not improve fidelity of TSS-MPRA initiation patterns, and increasing insert size frequently led to activation of extraneous TSS in the MPRA that are not active in vivo. We discuss the implications of our findings, which highlight important caveats when using MPRAs to study transcription mechanisms. Finally, we illustrate how TSS-MPRA and WIP scoring can provide novel insights into the impact of transcription factor motif mutations and genetic variants on TSS patterns and transcription levels.

Characterization of enhancer activity in early human neurodevelopment using Massively parallel reporter assay (MPRA) and forebrain organoids

Regulation of gene expression through enhancers is one of the major processes shaping the structure and function of the human brain during development. High-throughput assays have predicted thousands of enhancers involved in neurodevelopment, and confirming their activity through orthogonal functional assays is crucial. Here, we utilized Massively Parallel Reporter Assays (MPRAs) in stem cells and forebrain organoids to evaluate the activity of ~7,000 gene-linked enhancers previously identified in human fetal tissues and brain organoids. We used a Gaussian mixture model to evaluate the contribution of background noise in the measured activity signal to confirm the activity of ~35% of the tested enhancers, with most showing temporal-specific activity, suggesting their evolving role in neurodevelopment. The temporal specificity was further supported by the correlation of activity with gene expression. Our findings provide a valuable gene regulatory resource to the scientific community.

Extreme Sensitivity of Fitness to Environmental Conditions: Lessons from #1BigBatch

The phrase "survival of the fittest" has become an iconic descriptor of how natural selection works. And yet, precisely measuring fitness, even for single-celled microbial populations growing in controlled laboratory conditions, remains a challenge. While numerous methods exist to perform these measurements, including recently developed methods utilizing DNA barcodes, all methods are limited in their precision to differentiate strains with small fitness differences. In this study, we rule out some major sources of imprecision, but still find that fitness measurements vary substantially from replicate to replicate. Our data suggest that very subtle and difficult to avoid environmental differences between replicates create systematic variation across fitness measurements. We conclude by discussing how fitness measurements should be interpreted given their extreme environment dependence. This work was inspired by the scientific community who followed us and gave us tips as we live tweeted a high-replicate fitness measurement experiment at #1BigBatch.

Transcription factor binding site orientation and order are major drivers of gene regulatory activity

The gene regulatory code and grammar remain largely unknown, precluding our ability to link phenotype to genotype in regulatory sequences. Here, using a massively parallel reporter assay (MPRA) of 209,440 sequences, we examine all possible pair and triplet combinations, permutations and orientations of eighteen liver-associated transcription factor binding sites (TFBS). We find that TFBS orientation and order have a major effect on gene regulatory activity. Corroborating these results with genomic analyses, we find clear human promoter TFBS orientation biases and similar TFBS orientation and order transcriptional effects in an MPRA that tested 164,307 liver candidate regulatory elements. Additionally, by adding TFBS orientation to a model that predicts expression from sequence we improve performance by 7.7%. Collectively, our results show that TFBS orientation and order have a significant effect on gene regulatory activity and need to be considered when analyzing the functional effect of variants on the activity of these sequences.

Widespread RNA hypoediting in schizophrenia and its relevance to mitochondrial function

RNA editing, the endogenous modification of nucleic acids, is known to be altered in genes with important neurological function in schizophrenia (SCZ). However, the global profile and molecular functions of disease-associated RNA editing remain unclear. Here, we analyzed RNA editing in postmortem brains of four SCZ cohorts and uncovered a significant and reproducible trend of hypoediting in patients of European descent. We report a set of SCZ-associated editing sites via WGCNA analysis, shared across cohorts. Using massively parallel reporter assays and bioinformatic analyses, we observed that differential 3' untranslated region (3'UTR) editing sites affecting host gene expression were enriched for mitochondrial processes. Furthermore, we characterized the impact of two recoding sites in the mitofusin 1 (MFN1) gene and showed their functional relevance to mitochondrial fusion and cellular apoptosis. Our study reveals a global reduction of editing in SCZ and a compelling link between editing and mitochondrial function in the disease.

Massively parallel characterization of transcriptional regulatory elements in three diverse human cell types

The human genome contains millions of candidate cis-regulatory elements (CREs) with cell-type-specific activities that shape both health and myriad disease states. However, we lack a functional understanding of the sequence features that control the activity and cell-type-specific features of these CREs. Here, we used lentivirus-based massively parallel reporter assays (lentiMPRAs) to test the regulatory activity of over 680,000 sequences, representing a nearly comprehensive set of all annotated CREs among three cell types (HepG2, K562, and WTC11), finding 41.7% to be functional. By testing sequences in both orientations, we find promoters to have significant strand orientation effects. We also observe that their 200 nucleotide cores function as non-cell-type-specific 'on switches' providing similar expression levels to their associated gene. In contrast, enhancers have weaker orientation effects, but increased tissue-specific characteristics. Utilizing our lentiMPRA data, we develop sequence-based models to predict CRE function with high accuracy and delineate regulatory motifs. Testing an additional lentiMPRA library encompassing 60,000 CREs in all three cell types, we further identified factors that determine cell-type specificity. Collectively, our work provides an exhaustive catalog of functional CREs in three widely used cell lines, and showcases how large-scale functional measurements can be used to dissect regulatory grammar.

Genetic regulation of cell-type specific chromatin accessibility shapes the etiology of brain diseases

Nucleotide variants in cell type-specific gene regulatory elements in the human brain are major risk factors of human disease. We measured chromatin accessibility in sorted neurons and glia from 1,932 samples of human postmortem brain and identified 34,539 open chromatin regions with chromatin accessibility quantitative trait loci (caQTL). Only 10.4% of caQTL are shared between neurons and glia, supporting the cell type specificity of genetic regulation of the brain regulome. Incorporating allele specific chromatin accessibility improves statistical fine-mapping and refines molecular mechanisms underlying disease risk. Using massively parallel reporter assays in induced excitatory neurons, we screened 19,893 brain QTLs, identifying the functional impact of 476 regulatory variants. Combined, this comprehensive resource captures variation in the human brain regulome and provides novel insights into brain disease etiology.

Whole-genome sequencing reveals a complex African population demographic history and signatures of local adaptation

We conduct high coverage (>30×) whole-genome sequencing of 180 individuals from 12 indigenous African populations. We identify millions of unreported variants, many predicted to be functionally important. We observe that the ancestors of southern African San and central African rainforest hunter-gatherers (RHG) diverged from other populations >200 kya and maintained a large effective population size. We observe evidence for ancient population structure in Africa and for multiple introgression events from "ghost" populations with highly diverged genetic lineages. Although currently geographically isolated, we observe evidence for gene flow between eastern and southern Khoesan-speaking hunter-gatherer populations lasting until ∼12 kya. We identify signatures of local adaptation for traits related to skin color, immune response, height, and metabolic processes. We identify a positively selected variant in the lightly pigmented San that influences pigmentation in vitro by regulating the enhancer activity and gene expression of PDPK1.

Massively parallel characterization of psychiatric disorder-associated and cell-type-specific regulatory elements in the developing human cortex

Nucleotide changes in gene regulatory elements are important determinants of neuronal development and disease. Using massively parallel reporter assays in primary human cells from mid-gestation cortex and cerebral organoids, we interrogated the cis-regulatory activity of 102,767 sequences, including differentially accessible cell-type specific regions in the developing cortex and single-nucleotide variants associated with psychiatric disorders. In primary cells, we identified 46,802 active enhancer sequences and 164 disorder-associated variants that significantly alter enhancer activity. Activity was comparable in organoids and primary cells, suggesting that organoids provide an adequate model for the developing cortex. Using deep learning, we decoded the sequence basis and upstream regulators of enhancer activity. This work establishes a comprehensive catalog of functional gene regulatory elements and variants in human neuronal development.

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.

Characterization of De Novo Promoter Variants in Autism Spectrum Disorder with Massively Parallel Reporter Assays

Autism spectrum disorder (ASD) is a common, complex, and highly heritable condition with contributions from both common and rare genetic variations. While disruptive, rare variants in protein-coding regions clearly contribute to symptoms, the role of rare non-coding remains unclear. Variants in these regions, including promoters, can alter downstream RNA and protein quantity; however, the functional impacts of specific variants observed in ASD cohorts remain largely uncharacterized. Here, we analyzed 3600 de novo mutations in promoter regions previously identified by whole-genome sequencing of autistic probands and neurotypical siblings to test the hypothesis that mutations in cases have a greater functional impact than those in controls. We leveraged massively parallel reporter assays (MPRAs) to detect transcriptional consequences of these variants in neural progenitor cells and identified 165 functionally high confidence de novo variants (HcDNVs). While these HcDNVs are enriched for markers of active transcription, disruption to transcription factor binding sites, and open chromatin, we did not identify differences in functional impact based on ASD diagnostic status.

Area postrema neurons mediate interleukin-6 function in cancer-associated cachexia

Interleukin-6 (IL-6) has been long considered a key player in cancer-associated cachexia 1-15 . It is believed that sustained elevation of IL-6 production during cancer progression causes brain dysfunctions, which ultimately result in cachexia 16-20 . However, how peripheral IL-6 influences the brain remains poorly understood. Here we show that neurons in the area postrema (AP), a circumventricular structure in the hindbrain, mediate the function of IL-6 in cancer-associated cachexia in mice. We found that circulating IL-6 can rapidly enter the AP and activate AP neurons. Peripheral tumor, known to increase circulating IL-6 1-5,15,18,21-23 , leads to elevated IL-6 and neuronal hyperactivity in the AP, and causes potentiated excitatory synaptic transmission onto AP neurons. Remarkably, neutralization of IL-6 in the brain of tumor-bearing mice with an IL-6 antibody prevents cachexia, reduces the hyperactivity in an AP network, and markedly prolongs lifespan. Furthermore, suppression of Il6ra , the gene encoding IL-6 receptor, specifically in AP neurons with CRISPR/dCas9 interference achieves similar effects. Silencing of Gfral-expressing AP neurons also ameliorates the cancer-associated cachectic phenotypes and AP network hyperactivity. Our study identifies a central mechanism underlying the function of peripheral IL-6, which may serve as a target for treating cancer-associated cachexia.

Genomic characterization and therapeutic utilization of IL-13-responsive sequences in asthma

Epithelial responses to the cytokine interleukin-13 (IL-13) cause airway obstruction in asthma. Here we utilized multiple genomic techniques to identify IL-13-responsive regulatory elements in bronchial epithelial cells and used these data to develop a CRISPR interference (CRISPRi)-based therapeutic approach to downregulate airway obstruction-inducing genes in a cell type- and IL-13-specific manner. Using single-cell RNA sequencing (scRNA-seq) and acetylated lysine 27 on histone 3 (H3K27ac) chromatin immunoprecipitation sequencing (ChIP-seq) in primary human bronchial epithelial cells, we identified IL-13-responsive genes and regulatory elements. These sequences were functionally validated and optimized via massively parallel reporter assays (MPRAs) for IL-13-inducible activity. The top secretory cell-selective sequence from the MPRA, a novel, distal enhancer of the sterile alpha motif pointed domain containing E-26 transformation-specific transcription factor (SPDEF) gene, was utilized to drive CRISPRi and knock down SPDEF or mucin 5AC (MUC5AC), both involved in pathologic mucus production in asthma. Our work provides a catalog of cell type-specific genes and regulatory elements involved in IL-13 bronchial epithelial response and showcases their use for therapeutic purposes.

Efficient Selection of Enhancers and Promoters from MIA PaCa-2 Pancreatic Cancer Cells by ChIP-lentiMPRA

A library of active genome regulatory elements (putative promoters and enhancers) from MIA PaCa-2 pancreatic adenocarcinoma cells was constructed using a specially designed lentiviral vector and a massive parallel reporter assay (ChIP-lentiMPRA). Chromatin immunoprecipitation of the cell genomic DNA by H3K27ac antibodies was used for primary enrichment of the library for regulatory elements. Totally, 11,264 unique genome regions, many of which are capable of enhancing the expression of the CopGFP reporter gene from the minimal CMV promoter, were identified. The regions tend to be located near promoters. Based on the proximity assay, we found an enrichment of highly expressed genes among those associated with three or more mapped distal regions (2 kb distant from the 5'-ends of genes). It was shown significant enrichment of genes related to carcinogenesis or Mia PaCa-2 cell identity genes in this group. In contrast, genes associated with 1-2 distal regions or only with proximal regions (within 2 kbp of the 5'-ends of genes) are more often related to housekeeping functions. Thus, ChIP-lentiMPRA is a useful strategy for creating libraries of regulatory elements for the study of tumor-specific gene transcription.

Scalable Functional Assays for the Interpretation of Human Genetic Variation

Scalable sequence-function studies have enabled the systematic analysis and cataloging of hundreds of thousands of coding and noncoding genetic variants in the human genome. This has improved clinical variant interpretation and provided insights into the molecular, biophysical, and cellular effects of genetic variants at an astonishing scale and resolution across the spectrum of allele frequencies. In this review, we explore current applications and prospects for the field and outline the principles underlying scalable functional assay design, with a focus on the study of single-nucleotide coding and noncoding variants.

Focus on your locus with a massively parallel reporter assay

A growing number of variants associated with risk for neurodevelopmental disorders have been identified by genome-wide association and whole genome sequencing studies. As common risk variants often fall within large haplotype blocks covering long stretches of the noncoding genome, the causal variants within an associated locus are often unknown. Similarly, the effect of rare noncoding risk variants identified by whole genome sequencing on molecular traits is seldom known without functional assays. A massively parallel reporter assay (MPRA) is an assay that can functionally validate thousands of regulatory elements simultaneously using high-throughput sequencing and barcode technology. MPRA has been adapted to various experimental designs that measure gene regulatory effects of genetic variants within cis- and trans-regulatory elements as well as posttranscriptional processes. This review discusses different MPRA designs that have been or could be used in the future to experimentally validate genetic variants associated with neurodevelopmental disorders. Though MPRA has limitations such as it does not model genomic context, this assay can help narrow down the underlying genetic causes of neurodevelopmental disorders by screening thousands of sequences in one experiment. We conclude by describing future directions of this technique such as applications of MPRA for gene-by-environment interactions and pharmacogenetics.

Secondary structures in RNA synthesis, splicing and translation

Even though the functional role of mRNA molecules is primarily decided by the nucleotide sequence, several properties are determined by secondary structure conformations. Examples of secondary structures include long range interactions, hairpins, R-loops and G-quadruplexes and they are formed through interactions of non-adjacent nucleotides. Here, we discuss advances in our understanding of how secondary structures can impact RNA synthesis, splicing, translation and mRNA half-life. During RNA synthesis, secondary structures determine RNA polymerase II (RNAPII) speed, thereby influencing splicing. Splicing is also determined by RNA binding proteins and their binding rates are modulated by secondary structures. For the initiation of translation, secondary structures can control the choice of translation start site. Here, we highlight the mechanisms by which secondary structures modulate these processes, discuss advances in technologies to detect and study them systematically, and consider the roles of RNA secondary structures in disease.

Modeling common and rare genetic risk factors of neuropsychiatric disorders in human induced pluripotent stem cells

Recent genome-wide association studies (GWAS) and whole-exome sequencing of neuropsychiatric disorders, especially schizophrenia, have identified a plethora of common and rare disease risk variants/genes. Translating the mounting human genetic discoveries into novel disease biology and more tailored clinical treatments is tied to our ability to causally connect genetic risk variants to molecular and cellular phenotypes. When combined with the Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)/CRISPR-associated (Cas) nuclease-mediated genome editing system, human induced pluripotent stem cell (hiPSC)-derived neural cultures (both 2D and 3D organoids) provide a promising tractable cellular model for bridging the gap between genetic findings and disease biology. In this review, we first conceptualize the advances in understanding the disease polygenicity and convergence from the past decade of iPSC modeling of different types of genetic risk factors of neuropsychiatric disorders. We then discuss the major cell types and cellular phenotypes that are most relevant to neuropsychiatric disorders in iPSC modeling. Finally, we critically review the limitations of iPSC modeling of neuropsychiatric disorders and outline the need for implementing and developing novel methods to scale up the number of iPSC lines and disease risk variants in a systematic manner. Sufficiently scaled-up iPSC modeling and a better functional interpretation of genetic risk variants, in combination with cutting-edge CRISPR/Cas9 gene editing and single-cell multi-omics methods, will enable the field to identify the specific and convergent molecular and cellular phenotypes in precision for neuropsychiatric disorders.

High-throughput characterization of the role of non-B DNA motifs on promoter function

lternative DNA conformations, termed non-B DNA structures, can affect transcription, but the underlying mechanisms and their functional impact have not been systematically characterized. Here, we used computational genomic analyses coupled with massively parallel reporter assays (MPRAs) to show that certain non-B DNA structures have a substantial effect on gene expression. Genomic analyses found that non-B DNA structures at promoters harbor an excess of germline variants. Analysis of multiple MPRAs, including a promoter library specifically designed to perturb non-B DNA structures, functionally validated that Z-DNA can significantly affect promoter activity. We also observed that biophysical properties of non-B DNA motifs, such as the length of Z-DNA motifs and the orientation of G-quadruplex structures relative to transcriptional direction, have a significant effect on promoter activity. Combined, their higher mutation rate and functional effect on transcription implicate a subset of non-B DNA motifs as major drivers of human gene-expression-associated phenotypes.

Computational and experimental methods for classifying variants of unknown clinical significance

The increase in sequencing capacity, reduction in costs, and national and international coordinated efforts have led to the widespread introduction of next-generation sequencing (NGS) technologies in patient care. More generally, human genetics and genomic medicine are gaining importance for more and more patients. Some communities are already discussing the prospect of sequencing each individual's genome at time of birth. Together with digital health records, this shall enable individualized treatments and preventive measures, so-called precision medicine. A central step in this process is the identification of disease causal mutations or variant combinations that make us more susceptible for diseases. Although various technological advances have improved the identification of genetic alterations, the interpretation and ranking of the identified variants remains a major challenge. Based on our knowledge of molecular processes or previously identified disease variants, we can identify potentially functional genetic variants and, using different lines of evidence, we are sometimes able to demonstrate their pathogenicity directly. However, the vast majority of variants are classified as variants of uncertain clinical significance (VUSs) with not enough experimental evidence to determine their pathogenicity. In these cases, computational methods may be used to improve the prioritization and an increasing toolbox of experimental methods is emerging that can be used to assay the molecular effects of VUSs. Here, we discuss how computational and experimental methods can be used to create catalogs of variant effects for a variety of molecular and cellular phenotypes. We discuss the prospects of integrating large-scale functional data with machine learning and clinical knowledge for the development of accurate pathogenicity predictions for clinical applications.

Functional annotation of breast cancer risk loci: current progress and future directions

Genome-wide association studies coupled with large-scale replication and fine-scale mapping studies have identified more than 150 genomic regions that are associated with breast cancer risk. Here, we review efforts to translate these findings into a greater understanding of disease mechanism. Our review comes in the context of a recently published fine-scale mapping analysis of these regions, which reported 352 independent signals and a total of 13,367 credible causal variants. The vast majority of credible causal variants map to noncoding DNA, implicating regulation of gene expression as the mechanism by which functional variants influence risk. Accordingly, we review methods for defining candidate-regulatory sequences, methods for identifying putative target genes and methods for linking candidate-regulatory sequences to putative target genes. We provide a summary of available data resources and identify gaps in these resources. We conclude that while much work has been done, there is still much to do. There are, however, grounds for optimism; combining statistical data from fine-scale mapping with functional data that are more representative of the normal "at risk" breast, generated using new technologies, should lead to a greater understanding of the mechanisms that influence an individual woman's risk of breast cancer.

AAV Deployment of Enhancer-Based Expression Constructs In Vivo in Mouse Brain

Enhancers are binding platforms for a diverse array of transcription factors that drive specific expression patterns of tissue- and cell-type-specific genes. Multiple means of assessing non-coding DNA and various chromatin states have proven useful in predicting the presence of enhancer sequences in the genome, but validating the activity of these sequences and finding the organs and developmental stages they are active in is a labor-intensive process. Recent advances in adeno-associated virus (AAV) vectors have enabled the widespread delivery of transgenes to mouse tissues, enabling in vivo enhancer testing without necessitating a transgenic animal. This protocol shows how a reporter construct that expresses EGFP under the control of a minimal promoter, which does not drive significant expression on its own, can be used to study the activity patterns of candidate enhancer sequences in the mouse brain. An AAV-packaged reporter construct is delivered to the mouse brain and incubated for 1-4 weeks, after which the animal is sacrificed, and brain sections are observed under a microscope. EGFP appears in cells in which the tested enhancer is sufficient to initiate gene expression, pinpointing the location and developmental stage in which the enhancer is active in the brain. Standard cloning methods, low-cost AAV packaging, and expanding AAV serotypes and methods for in vivo delivery and standard imaging readout make this an accessible approach for the study of how gene expression is regulated in the brain.

Massively parallel reporter perturbation assays uncover temporal regulatory architecture during neural differentiation

Gene regulatory elements play a key role in orchestrating gene expression during cellular differentiation, but what determines their function over time remains largely unknown. Here, we perform perturbation-based massively parallel reporter assays at seven early time points of neural differentiation to systematically characterize how regulatory elements and motifs within them guide cellular differentiation. By perturbing over 2,000 putative DNA binding motifs in active regulatory regions, we delineate four categories of functional elements, and observe that activity direction is mostly determined by the sequence itself, while the magnitude of effect depends on the cellular environment. We also find that fine-tuning transcription rates is often achieved by a combined activity of adjacent activating and repressing elements. Our work provides a blueprint for the sequence components needed to induce different transcriptional patterns in general and specifically during neural differentiation.

How gene regulatory elements regulate gene expression during cellular differentiation remains largely unknown. Here the authors use perturbation-based massively parallel reporter assays at early time points of neural differentiation to systematically characterize how regulatory elements and motifs within them guide different transcriptional patterns.

Multimodal profiling of the transcriptional regulatory landscape of the developing mouse cortex identifies Neurog2 as a key epigenome remodeler

How multiple epigenetic layers and transcription factors (TFs) interact to facilitate brain development is largely unknown. Here, to systematically map the regulatory landscape of neural differentiation in the mouse neocortex, we profiled gene expression and chromatin accessibility in single cells and integrated these data with measurements of enhancer activity, DNA methylation and three-dimensional genome architecture in purified cell populations. This allowed us to identify thousands of new enhancers, their predicted target genes and the temporal relationships between enhancer activation, epigenome remodeling and gene expression. We characterize specific neuronal transcription factors associated with extensive and frequently coordinated changes across multiple epigenetic modalities. In addition, we functionally demonstrate a new role for Neurog2 in directly mediating enhancer activity, DNA demethylation, increasing chromatin accessibility and facilitating chromatin looping in vivo. Our work provides a global view of the gene regulatory logic of lineage specification in the cerebral cortex.

By profiling multiple epigenetic layers and enhancer activity in vivo, the authors show a widespread remodeling of the regulatory landscape during mouse cortical development and identify Neurog2 as a key transcription factor driving this process.

Advances in profiling chromatin architecture shed light on the regulatory dynamics underlying brain disorders

Understanding the exquisitely complex nature of the three-dimensional organization of the genome and how it affects gene regulation remains a central question in biology. Recent advances in sequencing- and imaging-based approaches in decoding the three-dimensional chromatin landscape have enabled a systematic characterization of gene regulatory architecture. In this review, we outline how chromatin architecture provides a reference atlas to predict the functional consequences of non-coding variants associated with human traits and disease. High-throughput perturbation assays such as massively parallel reporter assays (MPRA) and CRISPR-based genome engineering in combination with a reference atlas opened an avenue for going beyond observational studies to experimentally validating the regulatory principles of the genome. We conclude by providing a suggested path forward by calling attention to barriers that can be addressed for a more complete understanding of the regulatory landscape of the human brain.