Fishing for Function in the Human Gene Pool

Abstract

Identification and characterization of causal non-coding variants in human genomes is challenging and requires substantial experimental resources. A new study by Tehranchi et al. describes a cost-effective approach for accurate mapping of molecular quantitative trait loci (QTLs) from pooled samples, a powerful way to link disease-associated changes to molecular functions.

Keywords: GWAS; QTL; cis-regulation; non-coding DNA.

Figure 1. Mapping bQTLs: comparing a traditional approach to a pooling-based strategy

The figure shows a hypothetical scenario of using bQTL mapping to identify functional SNPs at a disease-associated locus. Traditional bQTL mapping makes use of ChIP-seq performed on different individuals to infer allele-specific binding separately for each sample (middle panel, left side). In contrast, in the pooling-based strategy introduced by Tehranchi et al. ChIP is performed on a pool of samples (middle panel, right side). The frequency of each allele in the input material (pre-ChIP) is then compared to its frequency in the enriched material (post-ChIP). Under this scenario, the traditional mapping shows that SNP #1 is bound by the transcription factor (TF) in individuals with genotype TT, while in individuals with genotype CC the site is barely bound; consistently, heterozygotes display intermediate levels of binding. The same result is obtained with the pooling-based strategy (see SNP #1 in the scatterplot), albeit at a much lower cost and reduced experimental variation. The lower panel shows the potential results. Out of the four linked variants previously associated with disease susceptibility, only #1 strongly affects the binding of the TF in the cell.