SUMMARY Mammalian genomes are organized into megabase-scale topologically associated domains (TADs). We demonstrate that disruption of TADs can rewire long-range regulatory architecture and result in pathogenic phenotypes. We show that distinct human limb malformations are caused by deletions, inversions, or duplications altering the structure of the TAD-spanning WNT6/IHH/EPHA4/PAX3 locus. Using CRISPR/Cas genome editing, we generated mice with corresponding rearrangements. Both in mouse limb tissue and patient-derived fibroblasts, disease-relevant structural changes cause ectopic interactions between promoters and non-coding DNA, and a cluster of limb enhancers normally associated with Epha4 is misplaced relative to TAD boundaries and drives ectopic limb expression of another gene in the locus. This rewiring occurred only if the variant disrupted a CTCF-associated boundary domain. Our results demonstrate the functional importance of TADs for orchestrating gene expression via genome architecture and indicate criteria for predicting the pathogenicity of human structural variants, particularly in non-coding regions of the human genome.

Structural variations (SVs) contribute to the variability of our genome and are often associated with disease. Their study in model systems was hampered until now by labor-intensive genetic targeting procedures and multiple mouse crossing steps. Here we present the use of CRISPR/Cas for the fast (10 weeks) and efficient generation of SVs in mice. We specifically produced deletions, inversions, and also duplications at six different genomic loci ranging from 1.1 kb to 1.6 Mb with efficiencies up to 42%. After PCR-based selection, clones were successfully used to create mice via aggregation. To test the practicability of the method, we reproduced a human 500 kb disease-associated deletion and were able to recapitulate the human phenotype in mice. Furthermore, we evaluated the regulatory potential of a large genomic interval by deleting a 1.5 Mb fragment. The method presented permits rapid in vivo modeling of genomic rearrangements.

The binding of transcription factors to short recognition sequences plays a pivotal role in controlling the expression of genes. The sequence and shape characteristics of binding sites influence DNA binding specificity and have also been implicated in modulating the activity of transcription factors downstream of binding. To quantitatively assess the transcriptional activity of tens of thousands of designed synthetic sites in parallel, we developed a synthetic version of STARR-seq (synSTARR-seq). We used the approach to systematically analyze how variations in the recognition sequence of the glucocorticoid receptor (GR) affect transcriptional regulation. Our approach resulted in the identification of a novel highly active functional GR binding sequence and revealed that sequence variation both within and flanking GR’s core binding site can modulate GR activity without apparent changes in DNA binding affinity. Notably, we found that the sequence composition of variants with similar activity profiles was highly diverse. In contrast, groups of variants with similar activity profiles showed specific DNA shape characteristics indicating that DNA shape may be a better predictor of activity than DNA sequence. Finally, using single cell experiments with individual enhancer variants, we obtained clues indicating that the architecture of the response element can independently tune expression mean and cell-to cell variability in gene expression (noise). Together, our studies establish synSTARR as a powerful method to systematically study how DNA sequence and shape modulate transcriptional output and noise.

26The binding of transcription factors to short recognition sequences plays a pivotal role in 27 controlling the expression of genes. The sequence and shape characteristics of binding sites 28 influence DNA binding specificity and have also been implicated in modulating the activity 29 of transcription factors downstream of binding. To quantitatively assess the transcriptional 30 activity of dozens of thousands of designed synthetic sites in parallel, we developed a 31 synthetic version of STARR-seq (synSTARR-seq). We used the approach to systematically 32 analyze how variations in the recognition sequence of the glucocorticoid receptor (GR) 33 affect transcriptional regulation. Our approach resulted in the identification of a novel 34 highly active functional GR binding sequence and revealed that sequence variation both 35 within and flanking GR's core binding site can modulate GR activity without apparent 36 changes in DNA binding affinity. Notably, we found that the sequence composition of 37 variants with similar activity profiles was highly diverse. In contrast, groups of variants 38 with similar activity profiles showed distinct DNA shape characteristics indicating that DNA 39 shape may be a better predictor of activity than DNA sequence. Finally, using single cell 40 experiments with individual enhancer variants, we obtained clues indicating that the 41 architecture of the response element can independently tune expression mean and cell-to 42 cell variability in gene expression (noise). Together, our studies establish synSTARR as a 43 powerful method to systematically study how DNA sequence and shape modulate 44 transcriptional output and noise. 45 46 47 48 3 Keywords 49 Enhancers, transcriptional regulation, glucocorticoid receptor, transcriptional noise, DNA 50 shape 51 52 53The interplay between transcription factors (TFs) and genomically encoded cis-54 regulatory elements plays a key role in specifying where and when genes are expressed. In 55 addition, the architecture of cis-regulatory elements influences the expression level of 56 individual genes. For example, transcriptional output can be tuned by varying the number 57 of TF binding sites, either for a given TF or for distinct TFs, present at an enhancer [1, 2]. 58 Moreover, differences in its DNA-binding sites can modulate the magnitude of 59 transcriptional activation, as exemplified by the glucocorticoid receptor (GR), a hormone-60 activated TF [3][4][5]. The sequence differences can reside within the 15 base pair (bp) core GR 61 binding sequence (GBS) consisting of two imperfect 6 bp palindromic half-sites separated 62 by a 3 bp spacer. Moreover, sequences directly flanking the core also modulate GR activity 63 [3]. However, these sequence-induced changes in activity cannot be explained by affinity 64 [3]. Instead, the flanking nucleotides induce structural changes in both DNA and the DNA 65 binding domain of GR, arguing for their role in tuning GR activity [3]. 66 Notably, the expression level of a gene is typically measured for p...

The glucocorticoid receptor (GR), a hormone-activated transcription factor, binds to a myriad of genomic binding sites yet seems to regulate a much smaller number of genes. Genome-wide analysis of GR binding and gene regulation has shown that the likelihood of GR-dependent regulation increases with decreased distance of its binding to the transcriptional start site of a gene. To test if we can adopt this knowledge to expand the repertoire of GR target genes, we used CRISPR/Cas-mediated homology-directed repair to add a single GR-binding site directly upstream of the transcriptional start site of each of four genes. To our surprise, we found that the addition of a single GR-binding site can be enough to convert a gene into a GR target. The gain of GR-dependent regulation was observed for two of four genes analyzed and coincided with acquired GR binding at the introduced binding site. However, the gene-specific gain of GR-dependent regulation could not be explained by obvious differences in chromatin accessibility between converted genes and their non-converted counterparts. Furthermore, by introducing GR-binding sequences with different nucleotide compositions, we show that activation can be facilitated by distinct sequences without obvious differences in activity between the GR-binding sequence variants we tested. The approach to use genome engineering to build genomic response elements facilitates the generation of cell lines with tailored repertoires of GR-responsive genes and a framework to test and refine our understanding of the cis-regulatory logic of gene regulation by testing if engineered response elements behave as predicted.