We conducted a bioinformatic characterization for the most significant SNP and all SNPs correlated with the most sigificant SNP (r2>0.5). We implemented in-house Perl scripts to query bioinformatic databases, and assigned each of the 16 SNPs to one or more of the functional annotation datasets listed in Table S3. These datasets are not mutually exclusive. For example, a SNP can be located within both a candidate regulatory element (dataset #7) and a CTCF binding site (dataset #10). Because FTO is expressed and may have functional relevance in a wide array of tissues, we defined candidate cis-regulatory elements (dataset #7) as DNaseI hypersensitive sites (open chromatin loci) that are present in at least one human cell type. For SNPs that occur within predicted transcription factor binding sites (datasets #3 and #8), we computed transcription factor binding affinity for each SNP allele using the PWM-scan algorithm [60], as described previously [61].
