Genome-wide association study and genome prediction of tallness trait in spinach phenotyping.

Abstract

Plant height is a critical agronomic trait in spinach (Spinacia oleracea L.), influencing both mechanical harvesting efficiency and overall yield. In this study, plant height variation was evaluated in 307 United States Department of Agriculture (USDA) germplasm accessions, which were phenotyped and genotyped using 15,058 single-nucleotide polymorphisms (SNPs) obtained from whole-genome resequencing. A genome-wide association study (GWAS) was conducted using the General Linear Model (GLM), Mixed Linear Model (MLM), Multiple Loci Mixed Model (MLMM), Fixed and Random Model Circulating Probability Unification (FarmCPU), and Bayesian-information and Linkage-disequilibrium Iteratively Nested Keyway (BLINK) models implemented in the Genomic Association and Prediction Integrated Tool version 3 (GAPIT3). Ten SNPs were significantly associated with plant height: (i) SOVchr1_10780051 (10,780,051 bp) on chromosome (chr) 1; (ii) SOVchr2_68062488 (68,062,488 bp) on chr 2; (iii) SOVchr4_38323167 (38,323,167 bp), SOVchr4_188084317 (188,084,317 bp), and SOVchr4_188084338 (188,084,338 bp) on chr 4; (iv) SOVchr5_70192260 (70,192,260 bp) and SOVchr5_105368320 (105,368,320 bp) on chr 5; and (v) SOVchr6_8139833 (8,139,833 bp), SOVchr6_90951127 (90,951,127 bp), and SOVchr6_91175684 (91,175,684 bp) on chr 6. Genomic prediction (GP) models were applied to estimate genomic estimated breeding values (GEBV) for plant height, achieving an r-value of 0.55 using GWAS-derived SNP markers in cross-population prediction. The integration of GWAS and GP provides insights into the genetic architecture of plant height in spinach and supports marker-assisted breeding strategies to enhance crop management and economic returns.