Faculty Bibliography

Genomic context critically modulates regulatory function but is difficult to manipulate systematically. The murine insulin-like growth factor 2 (Igf2)/H19 locus is a paradigmatic model of enhancer selectivity, whereby CTCF occupancy at an imprinting control region directs downstream enhancers to activate either H19 or Igf2. We used synthetic regulatory genomics to repeatedly replace the native locus with 157-kb payloads, and we systematically dissected its architecture. Enhancer deletion and ectopic delivery revealed previously uncharacterized long-range regulatory dependencies at the native locus. Exchanging the H19 enhancer cluster with the Sox2 locus control region (LCR) showed that the H19 enhancers relied on their native surroundings while the Sox2 LCR functioned autonomously. Analysis of regulatory DNA actuation across cell types revealed that these enhancer clusters typify broader classes of context sensitivity genome wide. These results show that unexpected dependencies influence even well-studied loci, and our approach permits large-scale manipulation of complete loci to investigate the relationship between regulatory architecture and function.

Sox2 expression in mouse embryonic stem cells (mESCs) depends on a distal cluster of DNase I hypersensitive sites (DHSs), but their individual contributions and degree of interdependence remain a mystery. We analyzed the endogenous Sox2 locus using Big-IN to scarlessly integrate large DNA payloads incorporating deletions, rearrangements, and inversions affecting single or multiple DHSs, as well as surgical alterations to transcription factor (TF) recognition sequences. Multiple mESC clones were derived for each payload, sequence-verified, and analyzed for Sox2 expression. We found that two DHSs comprising a handful of key TF recognition sequences were each sufficient for long-range activation of Sox2 expression. By contrast, three nearby DHSs were entirely context dependent, showing no activity alone but dramatically augmenting the activity of the autonomous DHSs. Our results highlight the role of context in modulating genomic regulatory element function, and our synthetic regulatory genomics approach provides a roadmap for the dissection of other genomic loci.

The specificity of interactions between genomic regulatory elements and potential target genes is influenced by the binding of insulator proteins such as CTCF, which can act as potent enhancer blockers when interposed between an enhancer and a promoter in a reporter assay. But not all CTCF sites genome-wide function as insulator elements, depending on cellular and genomic context. To dissect the influence of genomic context on enhancer blocker activity, we integrated reporter constructs with promoter-only, promoter and enhancer, and enhancer blocker configurations at hundreds of thousands of genomic sites using the Sleeping Beauty transposase. Deconvolution of reporter activity by genomic position reveals distinct expression patterns subject to genomic context, including a compartment of enhancer blocker reporter integrations with robust expression. The high density of integration sites permits quantitative delineation of characteristic genomic context sensitivity profiles, and their decomposition into sensitivity to both local and distant DNase I hypersensitive sites. Furthermore, using a single-cell expression approach to test the effect of integrated reporters for differential expression of nearby endogenous genes reveals that CTCF insulator elements do not completely abrogate reporter effects on endogenous gene expression. Collectively, our results lend new insight to genomic regulatory compartmentalization and its influence on the determinants of promoter-enhancer specificity.

Functional assessment of disease-associated sequence variation at non-coding regulatory elements is complicated by their high degree of context sensitivity to both the local chromatin and nuclear environments. Allelic profiling of DNA accessibility across individuals has shown that only a select minority of sequence variation affects transcription factor (TF) occupancy, yet low sequence diversity in human populations means that no experimental assessment is available for the majority of disease-associated variants. Here we describe high-resolution in vivo maps of allelic DNA accessibility in liver, kidney, lung and B cells from 5 increasingly diverged strains of F1 hybrid mice. The high density of heterozygous sites in these hybrids enables precise quantification of effect size and cell-type specificity for hundreds of thousands of variants throughout the mouse genome. We show that chromatin-altering variants delineate characteristic sensitivity profiles for hundreds of TF motifs. We develop a compendium of TF-specific sensitivity profiles accounting for genomic context effects. Finally, we link maps of allelic accessibility to allelic transcript levels in the same samples. This work provides a foundation for quantitative prediction of cell-type specific effects of non-coding variation on TF activity, which will facilitate both fine-mapping and systems-level analyses of common disease-associated variation in human genomes.

Effective public response to a pandemic relies upon accurate measurement of the extent and dynamics of an outbreak. Viral genome sequencing has emerged as a powerful approach to link seemingly unrelated cases, and large-scale sequencing surveillance can inform on critical epi-demiological parameters. Here, we report the analysis of 864 SARS-CoV-2 sequences from cases in the New York City metropolitan area during the COVID-19 outbreak in Spring 2020. The majority of cases had no recent travel history or known exposure, and genetically linked cases were spread throughout the region. Comparison to global viral sequences showed that early transmission was most linked to cases from Europe. Our data are consistent with numerous seeds from multiple sources and a prolonged period of unrecognized community spreading. This work highlights the complementary role of genomic surveillance in addition to traditional epidemiological indicators.

Genome-wide association studies have identified many noncoding variants associated with common diseases and traits. We show that these variants are concentrated in regulatory DNA marked by deoxyribonuclease I (DNase I) hypersensitive sites (DHSs). Eighty-eight percent of such DHSs are active during fetal development and are enriched in variants associated with gestational exposure-related phenotypes. We identified distant gene targets for hundreds of variant-containing DHSs that may explain phenotype associations. Disease-associated variants systematically perturb transcription factor recognition sequences, frequently alter allelic chromatin states, and form regulatory networks. We also demonstrated tissue-selective enrichment of more weakly disease-associated variants within DHSs and the de novo identification of pathogenic cell types for Crohn's disease, multiple sclerosis, and an electrocardiogram trait, without prior knowledge of physiological mechanisms. Our results suggest pervasive involvement of regulatory DNA variation in common human disease and provide pathogenic insights into diverse disorders.

Genetic variation within intron 3 of the CACNA1C calcium channel gene is associated with schizophrenia and bipolar disorder, but analysis of the causal variants and their effect is complicated by a nearby variable-number tandem repeat (VNTR). Here, we used 155 long-read genome assemblies from 78 diverse individuals to delineate the structure and population variability of the CACNA1C intron 3 VNTR. We categorized VNTR sequences into 7 Types of structural alleles using sequence differences among repeat units. Only 12 repeat units at the 5' end of the VNTR were shared across most Types, but several Types were related through a series of large and small duplications. The most diverged Types were rare and present only in individuals with African ancestry, but the multiallelic structural polymorphism Variable Region 2 was present across populations at different frequencies, consistent with expansion of the VNTR preceding the emergence of early hominins. VR2 was in complete linkage disequilibrium with fine-mapped schizophrenia variants (SNPs) from genome-wide association studies (GWAS). This risk haplotype was associated with decreased CACNA1C gene expression in brain tissues profiled by the GTEx project. Our work suggests that sequence variation within a human-specific VNTR affects gene expression, and provides a detailed characterization of new alleles at a flagship neuropsychiatric locus.

Pervasive transcriptional activity is observed across diverse species. The genomes of extant organisms have undergone billions of years of evolution, making it unclear whether these genomic activities represent effects of selection or 'noise'^1-4. Characterizing default genome states could help understand whether pervasive transcriptional activity has biological meaning. Here we addressed this question by introducing a synthetic 101-kb locus into the genomes of Saccharomyces cerevisiae and Mus musculus and characterizing genomic activity. The locus was designed by reversing but not complementing human HPRT1, including its flanking regions, thus retaining basic features of the natural sequence but ablating evolved coding or regulatory information. We observed widespread activity of both reversed and native HPRT1 loci in yeast, despite the lack of evolved yeast promoters. By contrast, the reversed locus displayed no activity at all in mouse embryonic stem cells, and instead exhibited repressive chromatin signatures. The repressive signature was alleviated in a locus variant lacking CpG dinucleotides; nevertheless, this variant was also transcriptionally inactive. These results show that synthetic genomic sequences that lack coding information are active in yeast, but inactive in mouse embryonic stem cells, consistent with a major difference in 'default genomic states' between these two divergent eukaryotic cell types, with implications for understanding pervasive transcription, horizontal transfer of genetic information and the birth of new genes.

The loss of the tail is among the most notable anatomical changes to have occurred along the evolutionary lineage leading to humans and to the 'anthropomorphous apes'^1-3, with a proposed role in contributing to human bipedalism^4-6. Yet, the genetic mechanism that facilitated tail-loss evolution in hominoids remains unknown. Here we present evidence that an individual insertion of an Alu element in the genome of the hominoid ancestor may have contributed to tail-loss evolution. We demonstrate that this Alu element-inserted into an intron of the TBXT gene^7-9-pairs with a neighbouring ancestral Alu element encoded in the reverse genomic orientation and leads to a hominoid-specific alternative splicing event. To study the effect of this splicing event, we generated multiple mouse models that express both full-length and exon-skipped isoforms of Tbxt, mimicking the expression pattern of its hominoid orthologue TBXT. Mice expressing both Tbxt isoforms exhibit a complete absence of the tail or a shortened tail depending on the relative abundance of Tbxt isoforms expressed at the embryonic tail bud. These results support the notion that the exon-skipped transcript is sufficient to induce a tail-loss phenotype. Moreover, mice expressing the exon-skipped Tbxt isoform develop neural tube defects, a condition that affects approximately 1 in 1,000 neonates in humans¹⁰. Thus, tail-loss evolution may have been associated with an adaptive cost of the potential for neural tube defects, which continue to affect human health today.

Genetically engineered mouse models (GEMMs) help us to understand human pathologies and develop new therapies, yet faithfully recapitulating human diseases in mice is challenging. Advances in genomics have highlighted the importance of non-coding regulatory genome sequences, which control spatiotemporal gene expression patterns and splicing in many human diseases^1,2. Including regulatory extensive genomic regions, which requires large-scale genome engineering, should enhance the quality of disease modelling. Existing methods set limits on the size and efficiency of DNA delivery, hampering the routine creation of highly informative models that we call genomically rewritten and tailored GEMMs (GREAT-GEMMs). Here we describe 'mammalian switching antibiotic resistance markers progressively for integration' (mSwAP-In), a method for efficient genome rewriting in mouse embryonic stem cells. We demonstrate the use of mSwAP-In for iterative genome rewriting of up to 115 kb of a tailored Trp53 locus, as well as for humanization of mice using 116 kb and 180 kb human ACE2 loci. The ACE2 model recapitulated human ACE2 expression patterns and splicing, and notably, presented milder symptoms when challenged with SARS-CoV-2 compared with the existing K18-hACE2 model, thus representing a more human-like model of infection. Finally, we demonstrated serial genome writing by humanizing mouse Tmprss2 biallelically in the ACE2 GREAT-GEMM, highlighting the versatility of mSwAP-In in genome writing.