RT Journal Article
SR Electronic
T1 Population and individual effects of non-coding variants inform genetic risk factors
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 065144
DO 10.1101/065144
A1 Pala M.
A1 Z. Zappala
A1 M. Marongiu
A1 X. Li
A1 J.R. Davis
A1 R. Cusano
A1 F. Crobu
A1 K.R. Kukurba
A1 F. Reiner
A1 R. Berutti
A1 M.G. Piras
A1 A. Mulas
A1 M. Zoledziewska
A1 M. Marongiu
A1 F. Busonero
A1 A. Maschio
A1 M. Steri
A1 C. Sidore
A1 S. Sanna
A1 E. Fiorillo
A1 A. Battle
A1 J. Novembre
A1 C. Jones
A1 A. Angius
A1 G.R. Abecasis
A1 D. Schlessinger
A1 F. Cucca
A1 S.B. Montgomery
YR 2016
UL http://biorxiv.org/content/early/2016/07/21/065144.abstract
AB 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.