TY - JOUR T1 - Population and individual effects of non-coding variants inform genetic risk factors JF - bioRxiv DO - 10.1101/065144 SP - 065144 AU - Pala M. AU - Z. Zappala AU - M. Marongiu AU - X. Li AU - J.R. Davis AU - R. Cusano AU - F. Crobu AU - K.R. Kukurba AU - F. Reiner AU - R. Berutti AU - M.G. Piras AU - A. Mulas AU - M. Zoledziewska AU - M. Marongiu AU - F. Busonero AU - A. Maschio AU - M. Steri AU - C. Sidore AU - S. Sanna AU - E. Fiorillo AU - A. Battle AU - J. Novembre AU - C. Jones AU - A. Angius AU - G.R. Abecasis AU - D. Schlessinger AU - F. Cucca AU - S.B. Montgomery Y1 - 2016/01/01 UR - http://biorxiv.org/content/early/2016/07/21/065144.abstract N2 - Identifying functional non-coding variants can enhance genome interpretation and inform novel genetic risk factors. We used whole genomes and peripheral white blood cell transcriptomes from 624 Sardinian individuals to identify non-coding variants that contribute to population, family, and individual differences in transcript abundance. We identified 21,183 independent expression quantitative trait loci (eQTLs) and 6,768 independent splicing quantitative trait loci (sQTLs) influencing 73 and 41% of all tested genes. When we compared Sardinian eQTLs to those previously identified in Europe, we identified differentiated eQTLs at genes involved in malarial resistance and multiple sclerosis, reflecting the long-term epidemiological history of the island’s population. Taking advantage of pedigree data for the population sample, we identify segregating patterns of outlier gene expression and allelic imbalance in 61 Sardinian trios. We identified 809 expression outliers (median z-score of 2.97) averaging 13.3 genes with outlier expression per individual. We then connected these outlier expression events to rare non-coding variants. Our results provide new insight into the effects of non-coding variants and their relationship to population history, traits and individual genetic risk. ER -