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

Abstract

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 PH1.1 and Zn7.1 were consistently identified in all the four environments, ten QTLs qDF3.1, qDF6.2 qDF9.1 qPH5.1 qGL3.1, qGW3.1, qGW11.1, and qZn6.2 were detected in two environments, while two major loci qBLB11.1 and qBLB5.1 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.

Analysis of QTL responsible for grain iron and zinc content in doubled haploid lines of rice (Oryza sativa) derived from an intra‐japonica cross

“…Most traits showed limited variation as indicated by their low variances, narrow ranges and low coefficients of variation (CV). In reference to Descalsota et al (), CV that ranged from 10% to 20% were considered moderate and those that exceeded 20% were considered high. GL, GT, GW and RLW had low CV, variances close to 0 and narrow ranges.…”

“…Grain iron and zinc contents are positively correlated (Anandan, Rajiv, Eswaran, & Prakash, ; Descalsota et al, ; Descalsota‐Empleo, Amparado, et al, ; Dixit et al, ; Inabangan‐Asilo et al, ; Stangoulis et al, ; Swamy, Descalsota, et al, ; Xu et al, ). Similarly, in this work, grain iron and zinc contents were positively correlated and presented similar correlations with other traits.…”

“…The development of genotypes with high mean iron and zinc contents and yield is a major target of biofortification breeding. However, grain iron and zinc contents are negatively correlated with grain yield (Dixit et al, ; Inabangan‐Asilo et al, ; Norton et al, ), which has a diluting effect on zinc content (Descalsota et al, ). In the present work, SPP, TGW and PN were considered as proxies for grain yield because PN, a direct regulator of grain number (Ikeda et al, ), and grain weight are major components of grain yield (Huo et al, ).…”

“…Nevertheless, a previous work failed to find significant correlations between seed dimensions and iron and zinc contents (Anuradha et al, ). Descalsota et al () reported that in a coloured rice panel, iron and zinc contents are negatively correlated with GW and TGW but are positively correlated with GL. Descalsota‐Empleo, Amparado, et al () observed that in a Multiparent Advanced Generation Intercross (MAGIC) Plus population grown during the 2015 dry season, zinc content is weakly and negatively correlated with PL, GL, GW and TGW and iron content is weakly and negatively correlated with GL, GW and TGW.…”

“…The chromosomal locations of qFe2.1, qFe3.1, qFe8.2 and qZn12.1 are consistent in the two populations. Descalsota et al () mapped QTL related to iron and zinc contents in a MAGIC Plus population evaluated over two seasons and two locations. They found that two QTL for iron and zinc contents, namely qFe7.1 and qZn7.1, colocated on chromosome 7.…”