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Long-range gene regulation involves physical proximity between enhancers and promoters to generate precise patterns of gene expression in space and time. However, in some cases, proximity coincides with gene activation, whereas, in others, preformed topologies already exist before activation. In this study, we investigate the preformed configuration underlying the regulation of the Shh gene by its unique limb enhancer, the ZRS, in vivo during mouse development. Abrogating the constitutive transcription covering the ZRS region led to a shift within the Shh-ZRS contacts and a moderate reduction in Shh transcription. Deletion of the CTCF binding sites around the ZRS resulted in the loss of the Shh-ZRS preformed interaction and a 50% decrease in Shh expression but no phenotype, suggesting an additional, CTCF-independent mechanism of promoter-enhancer communication. This residual activity, however, was diminished by combining the loss of CTCF binding with a hypomorphic ZRS allele, resulting in severe Shh loss of function and digit agenesis. Our results indicate that the preformed chromatin structure of the Shh locus is sustained by multiple components and acts to reinforce enhancer-promoter communication for robust transcription. genetics | 3D genome | gene regulation | development | limb

Genome-wide association studies have now identified tens of thousands of noncoding loci associated with human diseases and complex traits, each of which could reveal insights into biological mechanisms of disease. Many of the underlying causal variants are thought to affect enhancers, but we have lacked genome-wide maps of enhancer-gene regulation to interpret such variants. We previously developed the Activity-by-Contact (ABC) Model to predict enhancer-gene connections and demonstrated that it can accurately predict the results of CRISPR perturbations across several cell types. Here, we apply this ABC Model to create enhancer-gene maps in 131 cell types and tissues, and use these maps to interpret the functions of fine-mapped GWAS variants. For inflammatory bowel disease (IBD), causal variants are >20-fold enriched in enhancers in particular cell types, and ABC outperforms other regulatory methods at connecting noncoding variants to target genes. Across 72 diseases and complex traits, ABC links 5,036 GWAS signals to 2,249 unique genes, including a class of 577 genes that appear to influence multiple phenotypes via variants in enhancers that act in different cell types. Guided by these variant-to-function maps, we show that an enhancer containing an IBD risk variant regulates the expression of PPIF to tune mitochondrial membrane potential. Together, our study reveals insights into principles of genome regulation, illuminates mechanisms that influence IBD, and demonstrates a generalizable strategy to connect common disease risk variants to their molecular and cellular functions.

Single-cell quantification of RNAs is important for understanding cellular heterogeneity and gene regulation, yet current approaches suffer from low sensitivity for individual transcripts, limiting their utility for many applications. Here we present Hybridization of Probes to RNA for sequencing (HyPR-seq), a method to sensitively quantify the expression of hundreds of chosen genes in single cells. HyPR-seq involves hybridizing DNA probes to RNA, distributing cells into nanoliter droplets, amplifying the probes with PCR, and sequencing the amplicons to quantify the expression of chosen genes. HyPR-seq achieves high sensitivity for individual transcripts, detects nonpolyadenylated and low-abundance transcripts, and can profile more than 100,000 single cells. We demonstrate how HyPR-seq can profile the effects of CRISPR perturbations in pooled screens, detect time-resolved changes in gene expression via measurements of gene introns, and detect rare transcripts and quantify cell-type frequencies in tissue using low-abundance marker genes. By directing sequencing power to genes of interest and sensitively quantifying individual transcripts, HyPR-seq reduces costs by up to 100-fold compared to whole-transcriptome single-cell RNA-sequencing, making HyPR-seq a powerful method for targeted RNA profiling in single cells.

Genome-wide association studies (GWAS) have discovered thousands of risk loci for common, complex diseases, each of which could point to genes and gene programs that influence disease. For some diseases, it has been observed that GWAS signals converge on a smaller number of biological programs, and that this convergence can help to identify causal genes. However, identifying such convergence remains challenging: each GWAS locus can have many candidate genes, each gene might act in one or more possible programs, and it remains unclear which programs might influence disease risk. Here, we developed a new approach to address this challenge, by creating unbiased maps to link disease variants to genes to programs (V2G2P) in a given cell type. We applied this approach to study the role of endothelial cells in the genetics of coronary artery disease (CAD). To link variants to genes, we constructed enhancer-gene maps using the Activity-by-Contact model. To link genes to programs, we applied CRISPRi-Perturb-seq to knock down all expressed genes within +/-500 Kb of 306 CAD GWAS signals and identify their effects on gene expression programs using single-cell RNA-sequencing. By combining these variant-to-gene and gene-to-program maps, we find that 43 of 306 CAD GWAS signals converge onto 5 gene programs linked to the cerebral cavernous malformations (CCM) pathway, which is known to coordinate transcriptional responses in endothelial cells, but has not been previously linked to CAD risk. The strongest regulator of these programs is TLNRD1, which we show is a new CAD gene and novel regulator of the CCM pathway. TLNRD1 loss-of-function alters actin organization and barrier function in endothelial cells in vitro, and heart development in zebrafish in vivo. Together, our study identifies convergence of CAD risk loci into prioritized gene programs in endothelial cells, nominates new genes of potential therapeutic relevance for CAD, and demonstrates a generalizable strategy to connect disease variants to functions.

Long-range gene regulation involves physical proximity between enhancers and promoters to generate precise patterns of gene expression in space and time. However, in some cases proximity coincides with gene activation, whereas in others preformed topologies already exist before activation. In this study, we investigate the preformed configuration underlying the regulation of the Shh gene by its unique limb enhancer, the ZRS, in vivo during mouse development. Abrogating the constitutive transcription covering the ZRS region led to a shift within the Shh-ZRS contacts and a moderate reduction in Shh transcription. Deletion of the CTCF binding sites around the ZRS resulted in a loss of the Shh-ZRS preformed interaction and a 50% decrease in Shh expression but no phenotype, suggesting an additional, CTCFindependent mechanism of promoter-enhancer communication. This residual activity, however, was diminished by combining the loss of CTCF binding with a hypomorphic ZRS allele resulting in severe Shh loss-of-function and digit agenesis. Our results indicate that the preformed chromatin structure of the Shh locus is sustained by multiple components and acts to reinforce enhancer-promoter communication for robust transcription.

Single-cell quantification of RNAs is important for understanding cellular heterogeneity and gene regulation, yet current approaches suffer from low sensitivity for individual transcripts, limiting their utility for many applications. Here we present Hybridization of Probes to RNA for sequencing (HyPR-seq), a method to sensitively quantify the expression of up to 100 chosen genes in single cells. HyPR-seq involves hybridizing DNA probes to RNA, distributing cells into nanoliter droplets, amplifying the probes with PCR, and sequencing the amplicons to quantify the expression of chosen genes. HyPR-seq achieves high sensitivity for individual transcripts, detects nonpolyadenylated and low-abundance transcripts, and can profile more than 100,000 single cells. We demonstrate how HyPR-seq can profile the effects of CRISPR perturbations in pooled screens, detect time-resolved changes in gene expression via measurements of gene introns, and detect rare transcripts and quantify cell type frequencies in tissue using low-abundance marker genes. By directing sequencing power to genes of interest and sensitively quantifying individual transcripts, HyPR-seq reduces costs by up to 100-fold compared to whole-transcriptome scRNA-seq, making HyPR-seq a powerful method for targeted RNA profiling in single cells.