Genome-wide association study for kernel composition and flour pasting behavior in wholemeal maize flour

Abstract

Background Maize is a crop in high demand for food purposes and consumers worldwide are increasingly concerned with food quality. However, breeding for improved quality is a complex task and therefore developing tools to select for better quality products is of great importance. Kernel composition, flour pasting behavior, and flour particle size have been previously identified as crucial for maize-based food quality. In this work we carried out a genome-wide association study to identify genomic regions controlling compositional and pasting properties of maize wholemeal flour. Results A collection of 132 diverse inbred lines, with a considerable representation of the food used Portuguese unique germplasm, was trialed during two seasons, and harvested samples characterized for main compositional traits, flour pasting parameters and mean particle size. The collection was genotyped with the MaizeSNP50 array. SNP-trait associations were tested using a mixed linear model accounting for genetic relatedness. Fifty-seven genomic regions were identified, associated with the 11 different quality-related traits evaluated. Regions controlling multiple traits were detected and potential candidate genes identified. As an example, for two viscosity parameters that reflect the capacity of the starch to absorb water and swell, the strongest common associated region was located near the dull endosperm 1 gene that encodes a starch synthase and is determinant on the starch endosperm structure in maize. Conclusions This study allowed for identifying relevant regions on the maize genome affecting maize kernel composition and flour pasting behavior, candidate genes for the majority of the quality-associated genomic regions, or the most promising target regions to develop molecular tools to increase efficacy and efficiency of quality traits selection (such as “breadability”) within maize breeding programs. Electronic supplementary material The online version of this article (10.1186/s12870-019-1729-7) contains supplementary material, which is available to authorized users.

Toward Mass Spectrometry Imaging in the Metabolomics Scale: Increasing Metabolic Coverage Through Multiple On-Tissue Chemical Modifications

“…Inbred B73 is derived from the Stiff Stalk Synthetic population generated at Iowa State University, and Mo17 was selected from Lancaster Sure Crop material (Troyer, 2004). These inbreds differ significantly in their genomic structure and this genetic diversity has been translated into metabolic, physiological, and phenotypic differences (Munamava et al, 2004). This approach was used to explore the metabolic differences arising from the genetic and tissue-type differences between these two inbred.…”

Genome-wide association study and its applications in the non-model crop Sesamum indicum

“…GWAS has been successfully applied to identify associations at a high resolution, detect candidate genes and dissect the quantitative traits in human, animals, and plants [ 16 , 17 ]. GWAS in various economically valuable crops has been used to gain insight into the genetic architecture of important traits, including days to heading, days to flowering panicle architecture, resistance to rice yellow mottle virus, fertility restoration, and agronomic traits in rice [ 18 – 21 ]; pattern of genetic change and evolution [ 22 , 23 ], compositional and pasting properties [ 24 ], stalk biomass [ 25 ] and leaf cuticular conductance [ 26 ] in maize; plant height components and inflorescence architecture [ 27 ], grain size [ 28 ] and grain quality [ 29 ] in sorghum; harvest index in maize [ 30 ], flowering time in canola [ 31 ], stress tolerance, oil content and seed quality [ 32 ] in brassica; oil yield and quality [ 15 ], yield related traits [ 33 , 34 ], drought tolerance [ 35 ], vitamin E [ 36 ] in sesame.…”

The utility of metabolomics as a tool to inform maize biology

“…(2018a) Primary metabolism in leaves and kernels GC-MS multiple candidate genes GWAS Wen et al. (2018) Kernel composition and flour pasting behavior NIRS multiple candidate genes GWAS Alves et al. (2019) Tocochromanols in kernels LC vte1 , vte4 , hggt1 , sh2 , su1 GWAS Baseggio et al.…”