Comparing genomic techniques for developing diagnostic SNP markers

For hard-to-distinguish species and strains, genome-wide single nucleotide polymorphism (SNP) data sets have revolutionized diagnostic identification. The sheer size of these data sets, often ranging from hundreds to hundreds of thousands of markers, increases the genomic resolution for finding unique, population/species-specific alleles. Although numerous studies have used whole-genome data to develop diagnostic panels (typically dozens to hundreds of SNPs), less is known about how to reduce these panels to a minimum set of highly informative markers. Marker selection is based on a variety of criteria, but it is unlikely that the selected markers are equally informative. Here, using both wild and mass-reared individuals of the agricultural pest Anastrepha ludens (Mexican fruit fly), we developed diagnostic panels from two different types of genome-wide SNP data sets (double digest restriction-site associated DNA sequencing (ddRAD) and whole genome sequencing (WGS)). The ultimate goal of these panels is to facilitate geographic source determination of invasive flies and to delimit strains used for Sterile Insect Technique. For each type of SNP dataset, we identified highly informative markers and compared their individual and combined efficacy for identifying field-caught A. ludens samples. This information has the potential to reduce per-sample analysis costs, first, when creating the genome-wide SNP datasets, second, by reducing the quantity of markers to genotype, and thus will be informative for research in many systems where diagnostic SNP markers are used.