Single-step genome-wide association study for susceptibility toTeratosphaeria nubilosaand precocity of vegetative phase change inEucalyptus globulus

Mycosphaerella leaf disease (MLD) is one of the most prevalent foliar diseases of E. globulus plantations around the world. Since resistance management strategies have not been effective in commercial plantations, breeding to develop more resistant genotypes is the most promising strategy. Available genomic information can be used to detect genomic regions associated with resistance to MLD, which could significantly speed up the process of genetic improvement. In this study, we investigated the genetic basis of MLD resistance in a breeding population of E. globulus which was genotyped with the EUChip60K SNP array. Resistance to MLD was evaluated for resistance of the juvenile foliage, as defoliation and leaf spot severity, and for precocity of change to resistant adult foliage. Genome-wide association studies (GWAS) were carried out applying four Single-SNP models, a Genomic Best Linear Unbiased Prediction (GBLUP-GWAS) approach, and a Single-step genome-wide association study (ssGWAS). The Single-SNP and GBLUP-GWAS models detected 13 and 16 SNP-trait associations in chromosomes 2, 3 y 11; whereas the ssGWAS detected 66 SNP-trait associations in the same chromosomes, and additional significant SNP-trait associations in chromosomes 5 to 9 for the precocity of phase change (proportion of adult foliage). For this trait, the two main regions in chromosomes 3 and 11 were identified for the three approaches. The SNPs identified in these regions were positioned near the key miRNA genes, miR156.5 and miR157.4 , which have a main role in the regulation of the timing of vegetative change, and also in the response to environmental stresses in plants. Our results outlined that ssG-WAS was more powerful in detecting regions that affect resistance than conventional GWAS approaches. Additionally, suggest a polygenic genetic architecture for the heteroblastic transition in E. globulus and identified useful SNP markers for the development of marker-assisted selection strategies for resistance.