Comparative QTL analysis for yield components and morphological traits in maize (Zea mays L.) under water-stressed and well-watered conditions.

Abstract

Drought significantly influences maize morphology and yield potential. The elucidation of the genetic mechanisms of yield components and morphological traits, and tightly linked molecular markers under drought stress are thus of great importance in marker assisted selection (MAS) breeding. Here, we identified 32 QTLs for grain weight per ear, kernel ratio, and ear height-to-plant height ratio across two F2:3 populations under both drought and non-drought conditions by single-environment mapping with composite interval mapping (CIM), of which 21 QTLs were mapped under water-stressed conditions. We identified 29 QTLs by joint analysis of all environments with mixed-linear-model-based composite interval mapping (MCIM), 14 QTLs involved in QTL-by-environment interactions, and 11 epistatic interactions. Further analysis simultaneously identified 20 stable QTLs (sQTLs) by CIM and MCIM could be useful for genetic improvement of these traits via QTL pyramiding. Remarkably, bin 1.07-1.10/6.05/8.03/8.06 exhibited four pleiotropic sQTLs that were consistent with phenotypic correlations among traits, supporting the pleiotropy of QTLs and playing important roles in conferring growth and yield advantages under contrasting watering conditions. These findings provide information on the genetic mechanisms responsible for yield components and morphological traits that are affected by different watering conditions. Furthermore, these alleles provide useful targets for MAS.