Drought tolerance is derived from complex quantitative traits that are associated with different shoot and root morphological characters. This study assessed the genetic and phenotypic variation of 12 maize inbred lines and performed association analysis of 11 drought-related traits using 360 simple sequence repeats (SSRs), detecting 1,604 alleles, with an average of 4.4 alleles per locus. The average values of gene diversity (GD) and polymorphism information content (PIC) were 0.648 and 0.598, respectively. In principal component analysis (PCA), shoot fresh weight (SFW), shoot dry weight (SDW), stem weight (SW), leaf weight (LW), root fresh weight (RFW), root dry weight (RDW), and leaf area (LA) traits contributed greatly to the PCA. Association analysis was performed using a general linear model with a Q-matrix (Q GLM) and a mixed linear model with Q and K-matrices (Q + K MLM). Twelve SSR markers for drought tolerance trait were detected by Q GLM, and all maize inbred lines were clearly divided into two groups in accordance with their drought tolerance. Duplicated significant marker-trait associations (SMTAs) between Q GLM and Q + K MLM identified eight marker-trait associations involving four SSR markers that were associated with the traits of SW, SFW, RFW, and RDW with a significant level of P < 0.05. The umc1175 and umc2092 were associated with SW and SFW; umc1503 was associated with RFW, SFW, and SW; and umc2341 was associated with RDW. The detection of loci associated with drought-related traits in this study may provide better opportunities to improve maize drought tolerance by marker-assisted selection (MAS).

This study assessed the genetic and phenotypic variation of 12 flint maize inbred lines and performed association analysis of 11 drought-related traits using 360 simple sequence repeats (SSRs), detecting 1,604 alleles, with an average of 4.4 alleles per locus. The average values of gene diversity (GD) and polymorphism information content (PIC) were 0.648 and 0.598, respectively. In principal component analysis (PCA), shoot fresh weight (SFW), shoot dry weight (SDW), stem weight (SW), leaf weight (LW), root fresh weight (RFW), root dry weight (RDW), and leaf area (LA) traits contributed greatly to the PIC. Association analysis was performed using a general linear model with a Q-matrix (Q GLM) and a mixed linear model with Q and K-matrices (Q + K MLM). Twelve SSR markers for drought tolerance trait were detected by Q GLM, and all maize inbred lines were clearly divided into two groups in accordance with their drought tolerance. Duplicated significant marker-trait associations (SMTAs) between Q GLM and Q + K MLM identified eight marker-trait associations involving four SSR markers that were associated with the traits of SW, SFW, RFW, and RDW with a significant level of P < 0.05. The umc1175 and umc2092 were associated with SW and SFW; umc1503 was associated with RFW, SFW, and SW; and umc2341 was associated with RDW. The detection of loci associated with drought-related traits in this study may provide better opportunities to improve maize drought tolerance by marker-assisted selection (MAS). These results will be useful for breeders in producing tolerant varieties as well as markers for using MAS in maize breeding programs.