3D genomic features across >50 diverse cell types reveal insights into the genomic architecture of childhood obesity.

The prevalence of childhood obesity is increasing worldwide, along with the associated common comorbidities of type 2 diabetes and cardiovascular disease in later life. Motivated by evidence for a strong genetic component, our prior genome-wide association study (GWAS) efforts for childhood obesity revealed 19 independent signals for the trait; however, the mechanism of action of these loci remains to be elucidated. To molecularly characterize these childhood obesity loci we sought to determine the underlying causal variants and the corresponding effector genes within diverse cellular contexts. Integrating childhood obesity GWAS summary statistics with our existing 3D genomic datasets for 57 human cell types, consisting of high-resolution promoter-focused Capture-C/Hi-C, ATAC-seq, and RNA-seq, we applied stratified LD score regression and calculated the proportion of genome-wide SNP heritability attributable to cell type-specific features, revealing pancreatic alpha cell enrichment as the most statistically significant. Subsequent chromatin contact-based fine-mapping was carried out for genome-wide significant childhood obesity loci and their linkage disequilibrium proxies to implicate effector genes, yielded the most abundant number of candidate variants and target genes at the BDNF, ADCY3, TMEM18 and FTO loci in skeletal muscle myotubes and the pancreatic beta-cell line, EndoC-BH1. One novel implicated effector gene, ALKAL2 - an inflammation-responsive gene in nerve nociceptors - was observed at the key TMEM18 locus across multiple immune cell types. Interestingly, this observation was also supported through colocalization analysis using expression quantitative trait loci (eQTL) derived from the Genotype-Tissue Expression (GTEx) dataset, supporting an inflammatory and neurologic component to the pathogenesis of childhood obesity. Our comprehensive appraisal of 3D genomic datasets generated in a myriad of different cell types provides genomic insights into pediatric obesity pathogenesis.

A 584 bp deletion in CTRB2 inhibits chymotrypsin B2 activity and secretion and confers risk of pancreatic cancer.

Genome-wide association studies (GWASs) have discovered 20 risk loci in the human genome where germline variants associate with risk of pancreatic ductal adenocarcinoma (PDAC) in populations of European ancestry. Here, we fine-mapped one such locus on chr16q23.1 (rs72802365, p = 2.51 × 10-17, OR = 1.36, 95% CI = 1.31-1.40) and identified colocalization (PP = 0.87) with aberrant exon 5-7 CTRB2 splicing in pancreatic tissues (pGTEx = 1.40 × 10-69, ßGTEx = 1.99; pLTG = 1.02 × 10-30, ßLTG = 1.99). Imputation of a 584 bp structural variant overlapping exon 6 of CTRB2 into the GWAS datasets resulted in a highly significant association with pancreatic cancer risk (p = 2.83 × 10-16, OR = 1.36, 95% CI = 1.31-1.42), indicating that it may underlie this signal. Exon skipping attributable to the deletion (risk) allele introduces a premature stop codon in exon 7 of CTRB2, yielding a truncated chymotrypsinogen B2 protein that lacks chymotrypsin activity, is poorly secreted, and accumulates intracellularly in the endoplasmic reticulum (ER). We propose that intracellular accumulation of a nonfunctional chymotrypsinogen B2 protein leads to ER stress and pancreatic inflammation, which may explain the increased pancreatic cancer risk in carriers of CTRB2 exon 6 deletion alleles.

A UVB-responsive common variant at chromosome band 7p21.1 confers tanning response and melanoma risk via regulation of the aryl hydrocarbon receptor, AHR.

Genome-wide association studies (GWASs) have identified a melanoma-associated locus on chromosome band 7p21.1 with rs117132860 as the lead SNP and a secondary independent signal marked by rs73069846. rs117132860 is also associated with tanning ability and cutaneous squamous cell carcinoma (cSCC). Because ultraviolet radiation (UVR) is a key environmental exposure for all three traits, we investigated the mechanisms by which this locus contributes to melanoma risk, focusing on cellular response to UVR. Fine-mapping of melanoma GWASs identified four independent sets of candidate causal variants. A GWAS region-focused Capture-C study of primary melanocytes identified physical interactions between two causal sets and the promoter of the aryl hydrocarbon receptor (AHR). Subsequent chromatin state annotation, eQTL, and luciferase assays identified rs117132860 as a functional variant and reinforced AHR as a likely causal gene. Because AHR plays critical roles in cellular response to dioxin and UVR, we explored links between this SNP and AHR expression after both 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) and ultraviolet B (UVB) exposure. Allele-specific AHR binding to rs117132860-G was enhanced following both, consistent with predicted weakened AHR binding to the risk/poor-tanning rs117132860-A allele, and allele-preferential AHR expression driven from the protective rs117132860-G allele was observed following UVB exposure. Small deletions surrounding rs117132860 introduced via CRISPR abrogates AHR binding, reduces melanocyte cell growth, and prolongs growth arrest following UVB exposure. These data suggest AHR is a melanoma susceptibility gene at the 7p21.1 risk locus and rs117132860 is a functional variant within a UVB-responsive element, leading to allelic AHR expression and altering melanocyte growth phenotypes upon exposure.

Tunable self-cleaving ribozymes for modulating gene expression in eukaryotic systems.

Advancements in the field of synthetic biology have been possible due to the development of genetic tools that are able to regulate gene expression. However, the current toolbox of gene regulatory tools for eukaryotic systems have been outpaced by those developed for simple, single-celled systems. Here, we engineered a set of gene regulatory tools by combining self-cleaving ribozymes with various upstream competing sequences that were designed to disrupt ribozyme self-cleavage. As a proof-of-concept, we were able to modulate GFP expression in mammalian cells, and then showed the feasibility of these tools in Drosophila embryos. For each system, the fold-reduction of gene expression was influenced by the location of the self-cleaving ribozyme/upstream competing sequence (i.e. 5' vs. 3' untranslated region) and the competing sequence used. Together, this work provides a set of genetic tools that can be used to tune gene expression across various eukaryotic systems.

A Transcriptome-Wide Association Study Identifies Novel Candidate Susceptibility Genes for Pancreatic Cancer.

BACKGROUND: Although 20 pancreatic cancer susceptibility loci have been identified through genome-wide association studies in individuals of European ancestry, much of its heritability remains unexplained and the genes responsible largely unknown. METHODS: To discover novel pancreatic cancer risk loci and possible causal genes, we performed a pancreatic cancer transcriptome-wide association study in Europeans using three approaches: FUSION, MetaXcan, and Summary-MulTiXcan. We integrated genome-wide association studies summary statistics from 9040 pancreatic cancer cases and 12 496 controls, with gene expression prediction models built using transcriptome data from histologically normal pancreatic tissue samples (NCI Laboratory of Translational Genomics [n = 95] and Genotype-Tissue Expression v7 [n = 174] datasets) and data from 48 different tissues (Genotype-Tissue Expression v7, n = 74-421 samples). RESULTS: We identified 25 genes whose genetically predicted expression was statistically significantly associated with pancreatic cancer risk (false discovery rate < .05), including 14 candidate genes at 11 novel loci (1p36.12: CELA3B; 9q31.1: SMC2, SMC2-AS1; 10q23.31: RP11-80H5.9; 12q13.13: SMUG1; 14q32.33: BTBD6; 15q23: HEXA; 15q26.1: RCCD1; 17q12: PNMT, CDK12, PGAP3; 17q22: SUPT4H1; 18q11.22: RP11-888D10.3; and 19p13.11: PGPEP1) and 11 at six known risk loci (5p15.33: TERT, CLPTM1L, ZDHHC11B; 7p14.1: INHBA; 9q34.2: ABO; 13q12.2: PDX1; 13q22.1: KLF5; and 16q23.1: WDR59, CFDP1, BCAR1, TMEM170A). The association for 12 of these genes (CELA3B, SMC2, and PNMT at novel risk loci and TERT, CLPTM1L, INHBA, ABO, PDX1, KLF5, WDR59, CFDP1, and BCAR1 at known loci) remained statistically significant after Bonferroni correction. CONCLUSIONS: By integrating gene expression and genotype data, we identified novel pancreatic cancer risk loci and candidate functional genes that warrant further investigation.

Genome-wide meta-analysis identifies five new susceptibility loci for pancreatic cancer.

In 2020, 146,063 deaths due to pancreatic cancer are estimated to occur in Europe and the United States combined. To identify common susceptibility alleles, we performed the largest pancreatic cancer GWAS to date, including 9040 patients and 12,496 controls of European ancestry from the Pancreatic Cancer Cohort Consortium (PanScan) and the Pancreatic Cancer Case-Control Consortium (PanC4). Here, we find significant evidence of a novel association at rs78417682 (7p12/TNS3, P = 4.35 × 10-8). Replication of 10 promising signals in up to 2737 patients and 4752 controls from the PANcreatic Disease ReseArch (PANDoRA) consortium yields new genome-wide significant loci: rs13303010 at 1p36.33 (NOC2L, P = 8.36 × 10-14), rs2941471 at 8q21.11 (HNF4G, P = 6.60 × 10-10), rs4795218 at 17q12 (HNF1B, P = 1.32 × 10-8), and rs1517037 at 18q21.32 (GRP, P = 3.28 × 10-8). rs78417682 is not statistically significantly associated with pancreatic cancer in PANDoRA. Expression quantitative trait locus analysis in three independent pancreatic data sets provides molecular support of NOC2L as a pancreatic cancer susceptibility gene.

Characterising cis-regulatory variation in the transcriptome of histologically normal and tumour-derived pancreatic tissues.

OBJECTIVE: To elucidate the genetic architecture of gene expression in pancreatic tissues. DESIGN: We performed expression quantitative trait locus (eQTL) analysis in histologically normal pancreatic tissue samples (n=95) using RNA sequencing and the corresponding 1000 genomes imputed germline genotypes. Data from pancreatic tumour-derived tissue samples (n=115) from The Cancer Genome Atlas were included for comparison. RESULTS: We identified 38 615 cis-eQTLs (in 484 genes) in histologically normal tissues and 39 713 cis-eQTL (in 237 genes) in tumour-derived tissues (false discovery rate <0.1), with the strongest effects seen near transcriptional start sites. Approximately 23% and 42% of genes with significant cis-eQTLs appeared to be specific for tumour-derived and normal-derived tissues, respectively. Significant enrichment of cis-eQTL variants was noted in non-coding regulatory regions, in particular for pancreatic tissues (1.53-fold to 3.12-fold, p≤0.0001), indicating tissue-specific functional relevance. A common pancreatic cancer risk locus on 9q34.2 (rs687289) was associated with ABO expression in histologically normal (p=5.8×10-8) and tumour-derived (p=8.3×10-5) tissues. The high linkage disequilibrium between this variant and the O blood group generating deletion variant in ABO (exon 6) suggested that nonsense-mediated decay (NMD) of the 'O' mRNA might explain this finding. However, knockdown of crucial NMD regulators did not influence decay of the ABO 'O' mRNA, indicating that a gene regulatory element influenced by pancreatic cancer risk alleles may underlie the eQTL. CONCLUSIONS: We have identified cis-eQTLs representing potential functional regulatory variants in the pancreas and generated a rich data set for further studies on gene expression and its regulation in pancreatic tissues.

Analyzing negative feedback using a synthetic gene network expressed in the Drosophila melanogaster embryo.

BACKGROUND: A complex network of gene interactions controls gene regulation throughout development and the life of the organisms. Insights can be made into these processes by studying the functional interactions (or "motifs") which make up these networks. RESULTS: We sought to understand the functionality of one of these network motifs, negative feedback, in a multi-cellular system. This was accomplished using a synthetic network expressed in the Drosophila melanogaster embryo using the yeast proteins Gal4 (a transcriptional activator) and Gal80 (an inhibitor of Gal4 activity). This network is able to produce an attenuation or shuttling phenotype depending on the Gal80/Gal4 ratio. This shuttling behavior was validated by expressing Gal3, which inhibits Gal80, to produce a localized increase in free Gal4 and therefore signaling. Mathematical modeling was used to demonstrate the capacity for negative feedback to produce these varying outputs. CONCLUSIONS: The capacity of a network motif to exhibit different phenotypes due to minor changes to the network in multi-cellular systems was shown. This work demonstrates the importance of studying network motifs in multi-cellular systems.