Structural variants contribute to phenotypic variation in maize.

Comprehensively identifying the loci shaping trait variation has been challenging, in part because standard approaches often miss many types of genetic variants. Structural variants (SVs), especially transposable elements (TEs), are likely to affect phenotypic variation but we lack methods that can detect polymorphic structural variants and TEs using short-read sequencing data. Here, we used a whole genome alignment between two maize genotypes to identify polymorphic structural variants and then genotyped a large maize diversity panel for these variants using short-read sequencing data. After characterizing SV variation in the panel, we identified SV polymorphisms that are associated with life history traits and genotype-by-environment (GxE) interactions. While most of the SVs associated with traits contained TEs, only two of the SVs had boundaries that clearly matched TE breakpoints indicative of a TE insertion, while the other polymorphisms were likely caused by deletions. One of the SVs that appeared to be caused by a TE insertion had the most associations with gene expression compared to other trait-associated SVs. All of the SVs associated with traits were in linkage disequilibrium with nearby single nucleotide polymorphisms (SNPs), suggesting that the approach used here did not identify unique associations that would have been missed in a SNP association study. Overall, we have created a technique to genotype SV polymorphisms across a large diversity panel using support from genomic short-read sequencing alignments and connecting this presence/absence SV variation to diverse traits and GxE interactions.