Genomic insights of leafminer resistance in spinach through GWAS approach and genomic prediction

The Leafminers, representing a diverse group of insects from various genera within the Agromyzidae family, pose a significant threat to spinach ( Spinacia oleracea L.) production. This study aimed to identify single nucleotide polymorphism (SNP) markers associated with leafminer resistance through a genome-wide association study (GWAS) and to evaluate the prediction accuracy (PA) for selecting resistant spinach using genomic prediction (GP). Using a dataset of 84 301 SNPs obtained from whole-genome resequencing, seven GWAS models, including BLINK, FarmCPU, MLM, and MLMM in GAPIT 3, as well as MLM, GLM, and SMR in TASSEL 5, were employed to perform GWAS on a panel of 286 USDA spinach germplasm accessions. Three SNP markers, namely 1_115279256_C_T, 3_157082529_C_T, and 4_168510908_T_G on chromosomes 1, 3, and 4, respectively, were identified as associated with leafminer resistance. In the 30 kb flanking regions of these markers, four candidate genes ( SOV1g031330 , SOV1g031340 , SOV4g047270 , and SOV4g047280 ), encoding LOB domain-containing protein, KH domain-containing protein, were discovered. Nodulin-like domain-containing protein, and SAM domain-containing protein, were discovered. The PA for leafminer resistance selection was estimated using ten different SNP sets, including two GWAS-derived marker sets (three and 51 SNPs) and eight random marker sets (ranging from 51 to 10 K SNPs) analyzed by seven GP models. The findings emphasized the superior performance of GWAS-derived SNP sets, reaching a PA of up to 0.79 using the cBLUP model. Notably, this research marks the pioneering application of GP in the context of insect resistance, providing a significant advancement in the understanding and management of leafminer resistance in spinach cultivation.