Genetic Analysis of Agronomic Traits and Grain Iron and Zinc Concentrations in a Doubled Haploid Population of Rice (Oryza sativa L.).

The development of micronutrient dense rice varieties with good agronomic traits is one of the sustainable and cost-effective approaches for reducing malnutrition. Identification of QTLs for high grain Fe and Zn, yield and yield components helps in precise and faster development of high Fe and Zn rice. We carried out a three-season evaluation using IR05F102 x IR69428 derived doubled-haploid population at IRRI. Inclusive composite interval mapping was carried out using SNP markers and Best Linear Unbiased Estimates of the phenotypic traits. A total of 23 QTLs were identified for eight agronomic traits and grain Fe and Zn concentration that explained 7.2 to 22.0% PV. A QTL by environment interaction analysis confirmed the stability of nine QTLs, including two QTLs for Zn on chromosomes 5 and 12. One epistatic interaction for plant height was significant with 28.4% PVE. Moreover, five QTLs were identified for Fe and Zn that harbor several candidate genes, e.g. OsZIP6 on QTL qZn5.1. A number of QTLs were associated with a combination of greater yield and increased grain Zn levels. These results are useful for development of new rice varieties with good agronomic traits and high grain Zn using MAS, and identification of genetic resources with the novel QTLs for grain Zn.

Genome-Wide Association Mapping in a Rice MAGIC Plus Population Detects QTLs and Genes Useful for Biofortification.

The development of rice genotypes with micronutrient-dense grains and disease resistance is one of the major priorities in rice improvement programs. We conducted Genome-wide association studies (GWAS) using a Multi-parent Advanced Generation Inter-Cross (MAGIC) Plus population to identify QTLs and SNP markers that could potentially be integrated in biofortification and disease resistance breeding. We evaluated 144 MAGIC Plus lines for agronomic and biofortification traits over two locations for two seasons, while disease resistance was screened for one season in the screen house. X-ray fluorescence technology was used to measure grain Fe and Zn concentrations. Genotyping was carried out by genotype by sequencing and a total of 14,242 SNP markers were used in the association analysis. We used Mixed linear model (MLM) with kinship and detected 57 significant genomic regions with a -log10 (P-value) ≥ 3.0. The PH 1.1 and Zn 7.1 were consistently identified in all the four environments, ten QTLs qDF 3.1, qDF 6.2 qDF 9.1 qPH 5.1 qGL 3.1, qGW 3.1, qGW 11.1, and qZn 6.2 were detected in two environments, while two major loci qBLB 11.1 and qBLB 5.1 were identified for Bacterial Leaf Blight (BLB) resistance. The associated SNP markers were found to co-locate with known major genes and QTLs such as OsMADS50 for days to flowering, osGA20ox2 for plant height, and GS3 for grain length. Similarly, Xa4 and xa5 genes were identified for BLB resistance and Pi5(t), Pi28(t), and Pi30(t) genes were identified for Blast resistance. A number of metal homeostasis genes OsMTP6, OsNAS3, OsMT2D, OsVIT1, and OsNRAMP7 were co-located with QTLs for Fe and Zn. The marker-trait relationships from Bayesian network analysis showed consistency with the results of GWAS. A number of promising candidate genes reported in our study can be further validated. We identified several QTLs/genes pyramided lines with high grain Zn and acceptable yield potential, which are a good resource for further evaluation to release as varieties as well as for use in breeding programs.