Genotyping by sequencing reveals the genetic diversity and population structure of Peruvian highland maize races

Peruvian maize exhibits abundant morphological diversity, with landraces cultivated from sea level (sl) up to 3,500 m above sl. Previous research based on morphological descriptors, defined at least 52 Peruvian maize races, but its genetic diversity and population structure remains largely unknown. Here, we used genotyping-by-sequencing (GBS) to obtain single nucleotide polymorphisms (SNPs) that allow inferring the genetic structure and diversity of 423 maize accessions from the genebank of Universidad Nacional Agraria la Molina (UNALM) and Universidad Nacional Autónoma de Tayacaja (UNAT). These accessions represent nine races and one sub-race, along with 15 open-pollinated lines (purple corn) and two yellow maize hybrids. It was possible to obtain 14,235 high-quality SNPs distributed along the 10 maize chromosomes of maize. Gene diversity ranged from 0.33 (sub-race Pachia) to 0.362 (race Ancashino), with race Cusco showing the lowest inbreeding coefficient (0.205) and Ancashino the highest (0.274) for the landraces. Population divergence (F_ST) was very low (mean = 0.017), thus depicting extensive interbreeding among Peruvian maize. A cluster containing maize landraces from Ancash, Apurímac, and Ayacucho exhibited the highest genetic variability. Population structure analysis indicated that these 423 distinct genotypes can be included in 10 groups, with some maize races clustering together. Peruvian maize races failed to be recovered as monophyletic; instead, our phylogenetic tree identified two clades corresponding to the groups of the classification of the races of Peruvian maize based on their chronological origin, that is, anciently derived or primary races and lately derived or secondary races. Additionally, these two clades are also congruent with the geographic origin of these maize races, reflecting their mixed evolutionary backgrounds and constant evolution. Peruvian maize germplasm needs further investigation with modern technologies to better use them massively in breeding programs that favor agriculture mainly in the South American highlands. We also expect this work will pave a path for establishing more accurate conservation strategies for this precious crop genetic resource.