A medium‐density genotyping platform for cultivated strawberry using DArTag technology

Genomic prediction in breeding populations containing hundreds to thousands of parents and seedlings is prohibitively expensive with current high‐density genetic marker platforms designed for strawberry. We developed mid‐density panels of molecular inversion probes (MIPs) to be deployed with the “DArTag” marker platform to provide a low‐cost, high‐throughput genotyping solution for strawberry genomic prediction. In total, 7742 target single nucleotide polymorphism (SNP) regions were used to generate MIP assays that were tested with a screening panel of 376 octoploid Fragaria accessions. We evaluated the performance of DArTag assays based on genotype segregation, amplicon coverage, and their ability to produce subgenome‐specific amplicon alignments to the FaRR1 assembly and subsequent alignment‐based variant calls with strong concordance to DArT's alignment‐free, count‐based genotype reports. We used a combination of marker performance metrics and physical distribution in the FaRR1 assembly to select 3K and 5K production panels for genotyping of large strawberry populations. We show that the 3K and 5K DArTag panels are able to target and amplify homologous alleles within subgenomic sequences with low‐amplification bias between reference and alternate alleles, supporting accurate genotype calling while producing marker genotypes that can be treated as functionally diploid for quantitative genetic analysis. The 3K and 5K target SNPs show high levels of polymorphism in diverse F. × ananassa germplasm and UC Davis cultivars, with mean pairwise diversity (π) estimates of 0.40 and 0.32 and mean heterozygous genotype frequencies of 0.35 and 0.33, respectively. Core Ideas Routine deployment of genomic selection (GS) requires access to cost‐effective genotyping tools and technologies. We present a medium‐density genotyping platform with 3k and 5k subgenome‐specific sites for octoploid strawberry. The core sites cover the FARR1 octoploid reference genome and accurately captures genomic relatedness for GS.