Defining and cataloging variants in pangenome graphs

Structural variation causes some human haplotypes toalign poorly with the linear reference genome, leading to 'reference bias'. Apangenome reference graph could ameliorate this bias by relating a sample to multiplereference assemblies. However, this approach requires a new definition of a 'genetic variant.' We introduce a definition of pangenome variants and amethod, pantree, to identify them. Our approach involves a pangenome reference tree which includes all nodes(sequences) of the pangenome graph, but only a subset of its edges;non-reference edges are variant edges.Our variants are biallelic and have well-defined positions. Analyzing theMinigraph-Cactus draft human pangenome reference graph, we identified 29.6million genetic variants. Most variants (99.2%) are small, and most smallvariants (73.9%) are SNPs. 3.5 million variants (11.7%) have a reference allele which is not on GRCh38;these variants are difficult to detect without a pangenome reference, or withexisting pangenome-based approaches. They tend to be embedded within tangled,multiallelic regions. We analyze two medically relevant regions, around theHLA-A and RHD genes, identifying thousands of small variants embedded within severallarge insertions, deletions, and inversions. We release an open-source softwaretool together with a VCF variant catalogue.