Mapping human regulatory variation using haplotype-resolved data
Mapping regulatory variants is a powerful approach for identifying the underlying biological mechanisms that define heritable phenotypes. Although each individual carries two copies of a gene, most studies of regulatory variants, such as those defining expression quantitative trait loci (eQTL), traditionally sum the expression of genes over both chromosomes. This is despite each chromosome carrying different regulatory haplotypes and studies of allele specific expression (ASE) highlighting that the two copies of each gene can be expressed at very different levels. In this study I defined allele-specific expression (ASE) across a European cohort, and using matching genomic data tested for variants that are associated with haplotype-resolved expression levels across individuals, hence potentially providing greater precision in mapping regulatory variants. This approach was generalised into the first R package available for this type of analysis, so that it can be used and expanded upon by the wider community. I illustrate how novel regulatory variants can be identified using this approach relative to standard eQTL analyses and show how it can be expanded to investigate how non-additive interactions between alleles on the two copies of each chromosome potentially shape a gene’s expression. I consequently present a novel approach for defining regulatory variants, a new easy-to-use R package implementing this approach and how it can be used to provide new insights into the complexity of genetic regulation of gene expression.