Project description:Most of the millions of single-nucleotide polymorphisms (SNPs) in the human genome are non-coding, and many overlap with putative regulatory elements. Genome-wide association studies have linked many of these SNPs to human traits or to gene expression levels, but rarely with sufficient resolution to identify the causal SNPs. Functional screens based on reporter assays have previously been of insufficient throughput to test the vast space of SNPs for possible effects on enhancer and promoter activity. Here, we have leveraged the throughput of the SuRE reporter technology to survey a total of 5.9 million SNPs, including 57% of the known common SNPs world-wide. We identified more than 30 thousand SNPs that alter the activity of putative regulatory elements, often in a cell-type specific manner. These data indicate that a large proportion of human non-coding SNPs may affect gene regulation. Integration of these SuRE data with genome-wide association studies may help to identify causal SNPs.
Project description:Genome-wide association studies implicate multiple loci in risk for systemic lupus erythematosus (SLE), but few contain exonic variants, rendering systematic identification of non-coding variants essential to decoding SLE genetics. We utilized SNP-seq and bioinformatic enrichment to interrogate 2180 single-nucleotide polymorphisms (SNPs) from 87 SLE risk loci for potential binding of transcription factors and related proteins from B cells. 52 SNPs that passed initial screening were tested by electrophoretic mobility shift (EMSA) and luciferase reporter assays. To identify binding of transcription factors and/or other nuclear proteins in an allele-determined manner, we employed pulldown using nuclear extract from Daudi cells and silver staining in SNPs that had exhibited allele-specific differential binding by EMSA. Each pulldown product for each allele of the five high-probability SNPs (rs2297550 C/G, rs13213604 C/G, rs276461 T/C, rs9907955 C/T, rs7302634 T/C) was evaluated by mass spectrometry (MS) to identify binding nuclear proteins, yielding a set of candidate proteins for each.
Project description:We tested >13,000 sequences containing each allele of 6,628 SNPs associated with altered in vivo chromatin accessibility in human islets and/or type 2 diabetes risk (T2D GWAS SNPs) for transcriptional activity in ß cell under steady state and endoplasmic reticulum (ER) stress conditions using the massively parallel reporter assay (MPRA).
Project description:Genome-wide association studies (GWAS) have identified thousands of single nucleotide polymorphisms (SNPs) associated with different human phenotypes. Most SNPs are located in non-coding regions of the genome, where a small subset of causal SNPs is thought to contribute to risk by regulating transcription. However, identification of such causal variants remains challenging due to linkage disequilibrium, where blocks of SNPs are inherited together. Here, we performed a massively parallel reporter assay called survey of regulatory elements (SuRE) in human neural stem cells to assess the transcription regulatory potential of 7.1 million SNPs. We identified 7,002 SNPs with regulatory potential (reporter assay quantitative trait loci, raQTLs), thereby increasing the number of putative regulatory variants in neural cell types by one order of magnitude. raQTLs were enriched for enhancers and often coincide with binding sites for transcription factors, such as ZBTB33, YY1, and ETS factors. Overlapping SuRE data with eQTL data pinpointed likely gene-regulatory variants. Overlap with GWAS for seven neuropsychiatric phenotypes identified 187 raQTLs in risk loci containing 183,186 SNPs assessed by SuRE. In conclusion, our SuRE dataset provides a rich source to prioritize genetic variants that may be relevant for disease.
Project description:We adapted the DiR barcode-based parallel reporter assay systems strategy to systematically identify the SNPs that affect gene expression by modulating activities of regulatory elements. Among 293 SNPs linked with GWAS-identified prostate cancer-risk SNPs, we found 32, 9, and 11 regulatory SNPs in 22Rv1, PC-3, and LNCaP cells. Further mechanism study indicates that one SNP regulates gene expression in prostate cancer malignancy. The DiR system has great potential to advance the functional study of risk SNPs that have associations with polygenic diseases. Our findings hold great promise in benefiting prostate cancer patients with prognostic prediction.