Related Experiment Video
Updated: May 9, 2025
Untargeted Liquid Chromatography-Mass Spectrometry-Based Metabolomics Analysis of Wheat Grain
Published on: March 13, 2020
Genomic prediction and QTL analysis for grain Zn content and yield in Aus-derived rice populations
Tapas Kumer Hore1,2,3, C H Balachiranjeevi1, Mary Ann Inabangan-Asilo1
1International Rice Research Institute (IRRI), DAPO Box 4031, Los Banos, Laguna Philippines.
Abstract:
Zinc (Zn) biofortification of rice can address Zn malnutrition in Asia. Identification and introgression of QTLs for grain Zn content and yield (YLD) can improve the efficiency of rice Zn biofortification. In four rice populations we detected 56 QTLs for seven traits by inclusive composite interval mapping (ICIM), and 16 QTLs for two traits (YLD and Zn) by association mapping. The phenotypic variance (PV) varied from 4.5% (qPN ) to 31.7% (qPH ). qDF , qDF , qDF , qPH , qPH , qPL , qPL qZn , qZn , qZn and qZn were identified in both dry and wet seasons; qZn , qZn , qZn qZn qZn and qYLD were detected by both ICIM and association mapping. qZn had the highest PV (17.8%) and additive effect (2.5 ppm). Epistasis and QTL co-locations were also observed for different traits. The multi-trait genomic prediction values were 0.24 and 0.16 for YLD and Zn respectively. qZn was co-located with a gene (OsHMA2) involved in Zn transport. These results are useful for Zn biofortificatiton of rice.
Supplementary Information:
The online version contains supplementary material available at 10.1007/s13562-024-00886-0.
