Characterizing the Regulatory Impact of Rare Variants and Mapping eQTL in Zea Mays Using Nearly 2000 3' Mrnaseq Samples

The phenotypic consequences of rare alleles pose a unique problem in quantitative genetics because rare SNP effects cannot be quantified without near infinite sample sizes. However, because selection acts to keep alleles with severe deleterious consequences at low frequencies, these rare alleles are predicted to have an outsize impact on expression and observable field-based phenotypes that are relevant in breeding contexts. To profile expression for this study we sampled 7 tissue types in approximately 290 maize lines for which we have whole genome sequence data. RNAseq Libraries were produced robotically using a low cost and highly multiplexable 3' RNAseq method called QuantSeq by Lexogen. The expression values were then used to map expression quantitative trait loci, or eQTL. Using a burden test which ties rare cis regulatory variants to aberrant expression (pioneered by Zhao et al 2016) we show that the abundance of rare alleles in putative regulatory regions leads to extreme expression values which we further tie to significantly lower fitness. This result links the abundance of rare deleterious variants (genetic load) to performance in an artificially selected agronomic species. Thus, despite intensive breeding efforts, rare alleles with severe deleterious effects remain ubiquitous and continue to impact highly selected agricultural species.