The advent of next-generation sequencing has expanded our understanding of the genotypic, pathobiological, and phenotypic spectrum of human disease, helping to inform more personalized patient care. Current clinical guidelines are prompting the generation of large volumes of clinical diagnostic genome sequencing data, but we remain unable to interpret variants found in the noncoding 98.5% of sequencing data. In this review, we discuss the known and emerging mechanisms by which noncoding variants cause human disease. Through the lens of immunity, we integrate insights from population genetics, evolutionary and functional genomics, and in silico strategies to propose a framework for identifying and characterizing potential disease-relevant noncoding variants with regulatory impact on gene expression. By tackling the assessment of this vast black box of missing genetic contributions to disease, we hope to improve diagnostic yields and clinical management for more unsolved patients.
Peng et al. (Wed,) studied this question.