# Identification of QTLs associated with opaque2 modifiers influencing kernel opacity, kernel hardness, and tryptophan content in quality protein maize

## TL;DR

Researchers identified genetic regions linked to kernel traits in Quality Protein Maize to improve nutrition and yield.

## Contribution

The study identifies QTLs associated with kernel opacity, hardness, and tryptophan content in Quality Protein Maize.

## Key findings

- Eleven QTLs across six chromosomes were detected for kernel traits in Quality Protein Maize.
- Candidate genes like opaque1 and floury1 co-localize with these QTLs.
- QTLs qHRD9.1 and qTRP9.1 are key targets for improving hardness and tryptophan content.

## Abstract

Lysine and tryptophan, two essential amino acids, are generally deficient in normal maize but enriched in opaque2 (o2) mutants. However, these o2 mutants are linked to undesirable effects like soft endosperm and yield loss. To circumvent this, researchers introgressed o2 modifiers (Mo2s) into mutant maize and developed Quality Protein Maize (QPM). This study identifies genomic regions linked to Mo2 governing kernel hardness, opacity, and tryptophan content. Two QPM lines (DQL 2104–1 and DQL 2034), contrasting for these traits, were crossed to develop a 138 F2 and 109 F2:3 mapping population. Genotyping with 141 informative SSR markers resulted in 2417.01 cM genetic map with an average marker distance of 20.66 cM between markers. Inclusive composite interval mapping (ICIM) detected 11 QTLs across six different chromosomes: seven QTLs for kernel opacity (chromosomes 1, 2, 4, 7), three for hardness (chromosomes 7, 8, 9), and one for tryptophan (chromosome 9). These QTLs co-localized with candidate genes (opaque1, opaque11, floury1, floury2, floury4, mucronate1, and waxy1). The identified QTLs provide foundational targets for marker-assisted breeding. Few QTLs like qHRD9.1 (PVE = 14.18%) and qTRP9.1 (PVE = 10.69%) are prime candidates for improving hardness and tryptophan. These loci can be pyramided into elite lines using SSR markers; genomic selection could be used to optimize trait stacking. Future fine-mapping and functional studies will refine these regions, accelerating the development of high-yielding QPM with vitreous kernels and enhanced nutritional quality.