beta-Arrestin1 modulates lymphoid enhancer factor transcriptional activity through interaction with phosphorylated dishevelled proteins.

One aspect of the function of the beta-arrestins is to serve as scaffold or adapter molecules coupling G-protein coupled receptors (GPCRs) to signal transduction pathways distinct from traditional second messenger pathways. Here we report the identification of Dishevelled 1 and Dishevelled 2 (Dvl1 and Dvl2) as beta-arrestin1 (betaarr1) interacting proteins. Dvl proteins participate as key intermediates in signal transmission from the seven membrane-spanning Frizzled receptors leading to inhibition of glycogen synthase kinase-3beta (GSK-3beta), stabilization of beta-catenin, and activation of the lymphoid enhancer factor (LEF) transcription factor. We find that phosphorylation of Dvl strongly enhances its interaction with betaarr1, suggesting that regulation of Dvl phosphorylation and subsequent interaction with betaarr1 may play a key role in the activation of the LEF transcription pathway. Because coexpression of the Dvl kinases, CK1epsilon and PAR-1, with Dvl synergistically activates LEF reporter gene activity, we reasoned that coexpression of betaarr1 with Dvl might also affect LEF-dependent gene activation. Interestingly, whereas betaarr1 or Dvl alone leads to low-level stimulation of LEF (2- to 5-fold), coexpression of betaarr1 with either Dvl1 or Dvl2 leads to a synergistic activation of LEF (up to 16-fold). Additional experiments with LiCl as an inhibitor of GSK-3beta kinase activity indicate that the step affected by betaarr1 is upstream of GSK-3beta and most likely at the level of Dvl. These results identify betaarr1 as a regulator of Dvl-dependent LEF transcription and suggest that betaarr1 might serve as an adapter molecule that can couple Frizzled receptors and perhaps other GPCRs to these important transcription pathways.

Dissecting the Functional Impacts of Non-Coding Genetic Variation

A large proportion of the variation in traits between individuals can be attributed to variation in the nucleotide sequence of the genome. The most commonly studied traits in human genetics are related to disease and disease susceptibility. Although scientists have identified genetic causes for over 4,000 monogenic diseases, the underlying mechanisms of many highly prevalent multifactorial inheritance disorders such as diabetes, obesity, and cardiovascular disease remain largely unknown. Identifying genetic mechanisms for complex traits has been challenging because most of the variants are located outside of protein-coding regions, and determining the effects of such non-coding variants remains difficult. In this dissertation, I evaluate the hypothesis that such non-coding variants contribute to human traits and diseases by altering the regulation of genes rather than the sequence of those genes. I will specifically focus on studies to determine the functional impacts of genetic variation associated with two related complex traits: gestational hyperglycemia and fetal adiposity. At the genomic locus associated with maternal hyperglycemia, we found that genetic variation in regulatory elements altered the expression of the HKDC1 gene. Furthermore, we demonstrated that HKDC1 phosphorylates glucose in vitro and in vivo, thus demonstrating that HKDC1 is a fifth human hexokinase gene. At the fetal-adiposity associated locus, we identified variants that likely alter VEPH1 expression in preadipocytes during differentiation. To make such studies of regulatory variation high-throughput and routine, we developed POP-STARR, a novel high throughput reporter assay that can empirically measure the effects of regulatory variants directly from patient DNA. By combining targeted genome capture technologies with STARR-seq, we assayed thousands of haplotypes from 760 individuals in a single experiment. We subsequently used POP-STARR to identify three key features of regulatory variants: that regulatory variants typically have weak effects on gene expression; that the effects of regulatory variants are often coordinated with respect to disease-risk, suggesting a general mechanism by which the weak effects can together have phenotypic impact; and that nucleotide transversions have larger impacts on enhancer activity than transitions. Together, the findings presented here demonstrate successful strategies for determining the regulatory mechanisms underlying genetic associations with human traits and diseases, and value of doing so for driving novel biological discovery.

Quantifying Eukaryotic Gene Regulation in Hormone Response and Disease.

Quantifying the function of mammalian enhancers at the genome or population scale has been longstanding challenge in the field of gene regulation. Studies of individual enhancers have provided anecdotal evidence on which many foundational assumptions in the field are based. Genome-scale studies have revealed that the number of sites bound by a given transcription factor far outnumber the genes that the factor regulates. In this dissertation we describe a new method, chromatin immune-enriched reporter assays (ChIP-reporters), and use that approach to comprehensively test the enhancer activity of genomic loci bound by the glucocorticoid receptor (GR). Integrative genomics analyses of our ChIP-reporter data revealed an unexpected mechanism of glucocorticoid (GC)-induced gene regulation. In that mechanism, only the minority of GR bound sites acts as GC-inducible enhancers. Many non-GC-inducible GR binding sites interact with GC-induced sites via chromatin looping. These interactions can increase the activity of GC-induced enhancers. Finally, we describe a method that enables the detection and characterization of the functional effects of non-coding genetic variation on enhancer activity at the population scale. Taken together, these studies yield both mechanistic and genetic evidence that provides context that informs the understanding of the effects of multiple enhancer variants on gene expression.