Profiling variable-number tandem repeat variation across populations using repeat-pangenome graphs

Abstract

Variable number tandem repeats (VNTRs) are composed of consecutive repetitive DNA with hypervariable repeat count and composition. They include protein coding sequences and associations with clinical disorders. It has been difficult to incorporate VNTR analysis in disease studies that use short-read sequencing because the traditional approach of mapping to the human reference is less effective for repetitive and divergent sequences. In this work, we solve VNTR mapping for short reads with a repeat-pangenome graph (RPGG), a data structure that encodes both the population diversity and repeat structure of VNTR loci from multiple haplotype-resolved assemblies. We develop software to build a RPGG, and use the RPGG to estimate VNTR composition with short reads. We use this to discover VNTRs with length stratified by continental population, and expression quantitative trait loci, indicating that RPGG analysis of VNTRs will be critical for future studies of diversity and disease.

Variable number tandem repeats (VNTRs) are difficult to analyze by short-read sequencing in disease studies. Here, the authors describe a VNTR mapping strategy for short-read analyses using a repeat pangenome graph. This method will help elucidate the contribution of VNTRs to diversity and disease.