On any good pirate map, ‘X’ marks the spot for buried treasure. It turns out the same is true in epigenetics: xQTL analysis marks the spot for buried GWAS associations. Genome-wide association studies (GWAS) have been instrumental in identifying single nucleotide polymorphisms (SNPs) associated with human disease. However, finding the biological relevance of such SNPs is challenging. Quantitative trait locus experiments link SNPs with expression (eQTL), DNA methylation (mQTL), and histone acetylation (haQTL) levels, and have informed SNP relevance. SNPs associated with molecular phenotypes (xQTL) studies have been primarily used to understand disease states; very few studies have looked at normally aging subject. Further, few have used brain tissue, or integrated multiple molecular marks.
The labs of Philip De Jager at Columbia University (New York) and Sara Mostafavi at the University of British Columbia (Canada) sought to examine xQTLs in brain tissue from an aging cohort. They sough to develop a neuroscience resource using xQTL analysis from RNA-seq, DNA methylation, and histone acetylation (H3K9ac) data. They used dorsolateral prefrontal cortex (DLPFC) from autopsies of about 500 individuals enrolled in two longitudinal aging studies. The xQTL Serve portal presents a list of SNPs associated with cortical gene expression, DNA methylation, and/or histone modification levels that reflect the impact of genetic variation on the transcriptome and epigenome of aging brains. Here are the details of what they found:
- Many xQTL SNPs influence multiple molecular features
- A large fraction of xQTL SNPs directly affect gene expression
- A small fraction (9%) of eQTLs are fully mediated by epigenetic features
- By including the fraction of each cell type relevant to each SNPs proposed molecular feature, the cell type specific of each eQTL was found to be ambiguous for most, a minority had clear cell types
- By applying xQTL serve, they found enrichment of xQTLs SNPs in 19 public GWAS datasets, identifying 20 new disease-specific loci
The xQTL Serve tool is intended to for the neuroscience community to examine epigenetic, genetic, and transcriptional interplay. Users will be able to functionally annotate their results, add to their analyses, or guide functional studies; for example, choosing a cell type for follow up.
Dig for you own buried GWAS treasure, check out the article in Nature Neuroscience, September 2017 and the xQTL Serve resource.