High-throughput mapping of regulatory DNA

Quantifying the effects of cis-regulatory DNA on gene expression is a major challenge. Here, we present the multiplexed editing regulatory assay (MERA), a high-throughput CRISPR-Cas9–based approach that analyzes the functional impact of the regulatory genome in its native context. MERA tiles thousands of mutations across ~40 kb of cis-regulatory genomic space and uses knock-in green fluorescent protein (GFP) reporters to read out gene activity. Using this approach, we obtain quantitative information on the contribution of cis-regulatory regions to gene expression. We identify proximal and distal regulatory elements necessary for expression of four embryonic stem cell–specific genes. We show a consistent contribution of neighboring gene promoters to gene expression and identify unmarked regulatory elements (UREs) that control gene expression but do not have typical enhancer epigenetic or chromatin features. We compare thousands of functional and nonfunctional genotypes at a genomic location and identify the base pair–resolution functional motifs of regulatory elements.National Institutes of Health (U.S.) (1U01HG007037

Population- and individual-specific regulatory variation in Sardinia

Genetic studies of complex traits have mainly identified associations with noncoding variants. To further determine the contribution of regulatory variation, we combined whole-genome and transcriptome data for 624 individuals from Sardinia to identify common and rare variants that influence gene expression and splicing. We identified 21,183 expression quantitative trait loci (eQTLs) and 6,768 splicing quantitative trait loci (sQTLs), including 619 new QTLs. We identified high-frequency QTLs and found evidence of selection near genes involved in malarial resistance and increased multiple sclerosis risk, reflecting the epidemiological history of Sardinia. Using family relationships, we identified 809 segregating expression outliers (median z score of 2.97), averaging 13.3 genes per individual. Outlier genes were enriched for proximal rare variants, providing a new approach to study large-effect regulatory variants and their relevance to traits. Our results provide insight into the effects of regulatory variants and their relationship to population history and individual genetic risk.M.P. is supported by the European Union’s Horizon 2020 Research and Innovation Programme under grant agreement 633964 (ImmunoAgeing). Z.Z. is supported by the National Science Foundation (NSF) GRFP (DGE- 114747) and by the Stanford Center for Computational, Evolutionary, and Human Genomics (CEHG). Z.Z., J.R.D., and G.T.H. also acknowledge support from the Stanford Genome Training Program (SGTP; NIH/NHGRI T32HG000044). J.R.D. is supported by the Stanford Graduate Fellowship. K.R.K. is supported by Department of Defense, Air Force Office of Scientific Research, National Defense Science and Engineering Graduate (NDSEQ) Fellowship 32 CFR 168a. S.J.S. is supported by the NIHR Cambridge Biomedical Research Centre. The SardiNIA project is supported in part by the intramural program of the National Institute on Aging through contract HHSN271201100005C to the Consiglio Nazionale delle Ricerche of Italy. The RNA sequencing was supported by the PB05 InterOmics MIUR Flagship grant; by the FaReBio2011 “Farmaci e Reti Biotecnologiche di Qualità” grant; and by Sardinian Autonomous Region (L.R. no. 7/2009) grant cRP3-154 to F. Cucca, who is also supported by the Italian Foundation for Multiple Sclerosis (FISM 2015/R/09) and by the Fondazione di Sardegna (ex Fondazione Banco di Sardegna, Prot. U1301.2015/AI.1157.BE Prat. 2015-1651). S.B.M. is supported by the US National Institutes of Health through R01HG008150, R01MH101814, U01HG007436, and U01HG009080. All of the authors would like to thank the CRS4 and the SCGPM for the computational infrastructure supporting this project