Mapping and Validation of QTLs for the Amino Acid and Total Protein Content in Brown Rice

Abstract

Highly nutritious rice production will be benefited with the improvement of amino acid content (AAC) and protein content (PC). The identification of quantitative trait loci (QTLs) associated with the PC and AAC of rice grains could provide a basis for improving the nutritional value of rice grains. Here, we conducted QTL analyses using recombinant inbred lines from the cross between indica (Milyang 23 or M23) and japonica (Tong 88-7 or T887) rice varieties, afterward employing genotyping-by-sequencing to obtain a high-density genetic map. A total of 17 and 3 QTLs were detected for AAC and PC, respectively. Among them, two QTLs associated with more than 10 AACs, qAAC6.1 and qAAC7.1, were identified for the first time in this study. Each favorable allele that increased the AAC of the two QTLs was derived from M23 and T887, respectively. Allelic combination of qAAC6.1 M23 and qAAC7.1 T887 showed significantly higher content of associated amino acids (AAs) than other allelic combinations. Near-isogenic line (NIL) possessing qAAC7.1 T887 with M23 genetic background had significantly higher AACs than both parents. These results indicate that the pyramiding of QTLs would be useful in developing brown rice with a high AA and protein content.

Contrasting Water Withholding Responses of Young Maize Plants Reveal Link Between Lipid Peroxidation and Osmotic Regulation Corroborated by Genetic Analysis

“…For example, in the study on sunflower hybrids by Khalil et al ( 2016 ), higher broad-sense heritabilities were reported compared to repeatabilities detected in our study, which could be explained by the different crops, different stages and using hybrids compared to inbred lines. Several studies reported loci associated with proline accumulation in barley (Fan et al, 2015 ; Jang et al, 2020 ) and rice (Sayed et al, 2012 ), hydrogen peroxide build-up (Gill et al, 2019 ; Kumar and Nadarajah, 2020 ), and TBARS in rice (Jiang et al, 2009 ), wheat (Ma et al, 2015 ), and cotton (Yasir et al, 2019 ); however, there are no available results for these important physiological processes in maize up to this date. Non-zero genetic variances in variance component analysis ( Table 1 ) imply feasibility of breeding directly for these traits, although the fold change compared to control might be more useful in screening of maize accessions due to the functional diversity of analyzed traits even in non-stressful conditions.…”

QTL Analysis of Rice Grain Size Using Segregating Populations Derived from the Large Grain Line

“…The Fluidigm SNP genotyping system has automated polymerase chain reaction (PCR) and integrated fluidic circuit (IFC) technology, which automatically mixes PCR reagents through microfluidic channel networks. The indica-japonica SNP assays, based on the Fluidigm system developed in the previous study [16], have been applied to various genetic analyses and molecular breeding, such as bulked segregant analysis (BSA) [17], genetic diversity analysis [18,19], QTL analysis [20][21][22][23], and background profiling [24][25][26]. This Fluidigm SNP marker set has provided a faster and more cost-effective tool than other high-throughput SNP genotyping systems for primary analysis during molecular breeding using inter-subspecific populations, to date.…”

Enhancing the Nutritional Quality of Major Food Crops Through Conventional and Genomics-Assisted Breeding

“…Among cereals, rice and wheat are also sources of protein in daily diets, though in limited quantity. The major effect of QTLs for grain protein content has been mapped in rice ( 28 , 33 , 39 , 43 ) and Wheat ( 15 , 17 , 22 ) ( Table 1 ).…”