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Population- and individual-specific regulatory variation in Sardinia. | LitMetric

AI Article Synopsis

  • Genetic studies often link complex traits to noncoding variants, so researchers analyzed data from 624 Sardinians to uncover how regulatory variations affect gene expression and splicing.
  • They discovered 21,183 expression quantitative trait loci (eQTLs) and 6,768 splicing quantitative trait loci (sQTLs), including 619 new loci, along with high-frequency QTLs related to malarial resistance and multiple sclerosis.
  • Additionally, they found 809 expression outliers related to rare variants, giving insights into significant regulatory variants and their implications for genetic traits and population history.

Article Abstract

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.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5411016PMC
http://dx.doi.org/10.1038/ng.3840DOI Listing

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