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

A comparison of the physicochemical properties, digestibility, and expression patterns of starch-related genes of two supersweet corn hybrids (F1) and their parents

The quality difference of corn largely depends on parental selection. Herein, the structure, digestive characteristics, and expression patterns of starch-related genes of two supersweet maize hybrids and their parents were studied. The structural analysis revealed that the starch of supersweet corn is round or oval, and the particles are smaller compared to those of normal corn. Hybridization changed the grain morphology, crystal, and helical structure of starch. Parents had a significantly different influence on supersweet corn. Notably, hybridization improved the setback value and digestibility of Shantian1500F1 and Shantian2000F1 compared to that of the parents. ZmBEI, ZmPHOH, and ZmAGPL2 genes had a consistent high expression throughout the whole grain formation phase. The results of this study expand our understanding of the breeding of supersweet corn hybrids and the effect of parents on the new strand. These results provide a useful reference for further breeding and studies of supersweet corn for starch production in corn.

Comparison of the physicochemical properties of starches from maize reciprocal F1 hybrids and their parental lines

Heterosis on maize yield and quality is highly variable and depends on parental selection. This study investigated and compared the starch structure and physicochemical properties among four sweet-waxy maize lines, four waxy maize lines, and their eight reciprocal F1 hybrids. Compared with the sweet-waxy maize, waxy maize and F1 hybrids had lower extent of branching of amylopectin and relative crystallinity, and larger starch granule size. Waxy maize starch had higher breakdown viscosity and retrogradation percentage, and lower setback viscosity and gelatinization enthalpy than the sweet-waxy maize starch. Meanwhile, the peak and setback viscosities, and retrogradation enthalpy of most F1 hybrid starches were higher than those of their female parent, while gelatinization enthalpy was the opposite. The F1 hybrid starches had higher onset temperature and retrogradation percentage and lower gelatinization enthalpy than their male parent in general. In conclusion, this study provides a framework for the production of new hybrids.

Genome-wide association study of quality traits and starch pasting properties of maize kernels

BACKGROUND

Starch are the main nutritional components of maize (Zea mays L.), and starch pasting properties are widely used as essential indicators for quality estimation. Based on the previous studies, various genes related to pasting properties have been identified in maize. However, the loci underlying variations in starch pasting properties in maize inbred lines remain to be identified.

RESULTS

To investigate the genetic architecture of these traits, the starch pasting properties were examined based on 292 maize inbred lines, which were genotyped with the MaizeSNP50 BeadChip composed of 55,126 evenly spaced, random SNPs. A genome-wide association study (GWAS) implemented in the software package FarmCPU was employed to identify genomic loci for the starch pasting properties. 48 SNPs were found to be associated with pasting properties. Moreover, 37 candidate genes were correlated with pasting properties. Among the candidate genes, GRMZM2G143646 and GRMZM2G166407 were associated with breakdown and final viscosity significantly, and both genes encode PPR (Pentatricopeptide repeat) protein. We used GWAS to explore candidate genes of maize starch pasting properties in this study. The identified candidate genes will be useful for further understanding of the genetic architecture of starch pasting properties in maize.

CONCLUSION

This study showed a complex regulation network about maize quality trait and starch pasting properties. It may provide some useful markers for marker assisted selection and a basis for cloning the genes behind these SNPs.

Genome-wide association studies of grain yield and quality traits under optimum and low-nitrogen stress in tropical maize (Zea mays L.)

KEY MESSAGE

Genome-wide association study (GWAS) demonstrated that multiple genomic regions influence grain quality traits under nitrogen-starved soils. Using genomic prediction, genetic gains can be improved through selection for grain quality traits. Soils in sub-Saharan Africa are nitrogen deficient due to low fertilizer use and inadequate soil fertility management practices. This has resulted in a significant yield gap for the major staple crop maize, which is undermining nutritional security and livelihood sustainability across the region. Dissecting the genetic basis of grain protein, starch and oil content under nitrogen-starved soils can increase our understanding of the governing genetic systems and improve the efficacy of future breeding schemes. An association mapping panel of 410 inbred lines and four bi-parental populations were evaluated in field trials in Kenya and South Africa under optimum and low nitrogen conditions and genotyped with 259,798 SNP markers. Genetic correlations demonstrated that these populations may be utilized to select higher performing lines under low nitrogen stress. Furthermore, genotypic, environmental and GxE variations in nitrogen-starved soils were found to be significant for oil content. Broad sense heritabilities ranged from moderate (0.18) to high (0.86). Under low nitrogen stress, GWAS identified 42 SNPs linked to grain quality traits. These significant SNPs were associated with 51 putative candidate genes. Linkage mapping identified multiple QTLs for the grain quality traits. Under low nitrogen conditions, average prediction accuracies across the studied genotypes were higher for oil content (0.78) and lower for grain yield (0.08). Our findings indicate that grain quality traits are polygenic and that using genomic selection in maize breeding can improve genetic gain. Furthermore, the identified genomic regions and SNP markers can be utilized for selection to improve maize grain quality traits.

Traditional Foods From Maize (Zea mays L.) in Europe

Maize (Zea mays L.) is one of the major crops of the world for feed, food, and industrial uses. It was originated in Central America and introduced into Europe and other continents after Columbus trips at the end of the 15th century. Due to the large adaptability of maize, farmers have originated a wide variability of genetic resources with wide diversity of adaptation, characteristics, and uses. Nowadays, in Europe, maize is mainly used for feed, but several food specialties were originated during these five centuries of maize history and became traditional food specialties. This review summarizes the state of the art of traditional foodstuffs made with maize in Southern, South-Western and South-Eastern Europe, from an historic evolution to the last research activities that focus on improving sustainability, quality and safety of food production.

Genetic dissection of QTLs for starch content in four maize DH populations

Starch is the principal carbohydrate source in maize kernels. Understanding the genetic basis of starch content (SC) benefits greatly in improving maize yield and optimizing end-use quality. Here, four double haploid (DH) populations were generated and were used to identify quantitative trait loci (QTLs) associated with SC. The phenotype of SC exhibited continuous and approximate normal distribution in each population. A total of 13 QTLs for SC in maize kernels was detected in a range of 3.65-16.18% of phenotypic variation explained (PVE). Among those, only some partly overlapped with QTLs previously known to be related to SC. Meanwhile, 12 genes involved in starch synthesis and metabolism located within QTLs were identified in this study. These QTLs will lay the foundation to explore candidate genes regulating SC in maize kernel and facilitate the application of molecular marker-assisted selection for a breeding program to cultivate maize varieties with a deal of grain quality.

Portuguese Common Bean Natural Variation Helps to Clarify the Genetic Architecture of the Legume's Nutritional Composition and Protein Quality

Common bean is a nutritious food legume widely appreciated by consumers worldwide. It is a staple food in Latin America, and a component of the Mediterranean diet, being an affordable source of protein with high potential as a gourmet food. Breeding for nutritional quality, including both macro and micronutrients, and meeting organoleptic consumers' preferences is a difficult task which is facilitated by uncovering the genetic basis of related traits. This study explored the diversity of 106 Portuguese common bean accessions, under two contrasting environments, to gain insight into the genetic basis of nutritional composition (ash, carbohydrates, fat, fiber, moisture, protein, and resistant starch contents) and protein quality (amino acid contents and trypsin inhibitor activity) traits through a genome-wide association study. Single-nucleotide polymorphism-trait associations were tested using linear mixed models accounting for the accessions' genetic relatedness. Mapping resolution to the gene level was achieved in 56% of the cases, with 102 candidate genes proposed for 136 genomic regions associated with trait variation. Only one marker-trait association was stable across environments, highlighting the associations' environment-specific nature and the importance of genotype × environment interaction for crops' local adaptation and quality. This study provides novel information to better understand the molecular mechanisms regulating the nutritional quality in common bean and promising molecular tools to aid future breeding efforts to answer consumers' concerns.

Genetic basis of kernel starch content decoded in a maize multi-parent population

Starch is the most abundant storage carbohydrate in maize kernels and provides calories for humans and other animals as well as raw materials for various industrial applications. Decoding the genetic basis of natural variation in kernel starch content is needed to manipulate starch quantity and quality via molecular breeding to meet future needs. Here, we identified 50 unique single quantitative trait loci (QTLs) for starch content with 18 novel QTLs via single linkage mapping, joint linkage mapping and a genome-wide association study in a multi-parent population containing six recombinant inbred line populations. Only five QTLs explained over 10% of phenotypic variation in single populations. In addition to a few large-effect and many small-effect additive QTLs, limited pairs of epistatic QTLs also contributed to the genetic basis of the variation in kernel starch content. A regional association study identified five non-starch-pathway genes that were the causal candidate genes underlying the identified QTLs for starch content. The pathway-driven analysis identified ZmTPS9, which encodes a trehalose-6-phosphate synthase in the trehalose pathway, as the causal gene for the QTL qSTA4-2, which was detected by all three statistical analyses. Knockout of ZmTPS9 increased kernel starch content and, in turn, kernel weight in maize, suggesting potential applications for ZmTPS9 in maize starch and yield improvement. These findings extend our knowledge about the genetic basis of starch content in maize kernels and provide valuable information for maize genetic improvement of starch quantity and quality.

Grass pea natural variation reveals oligogenic resistance to Fusarium oxysporum f. sp. pisi

Grass pea (Lathyrus sativus L.) is an annual legume species, phylogenetically close to pea (Pisum sativum L.), that may be infected by Fusarium oxysporum f. sp. pisi (Fop), the causal agent of fusarium wilt in peas with vast worldwide yield losses. A range of responses varying from high resistance to susceptibility to this pathogen has been reported in grass pea germplasm. Nevertheless, the genetic basis of that diversity of responses is still unknown, hampering its breeding exploitation. To identify genomic regions controlling grass pea resistance to fusarium wilt, a genome-wide association study approach was applied on a grass pea worldwide collection of accessions inoculated with Fop race 2. Disease responses were scored in this collection that was also subjected to high-throughput based single nucleotide polymorphisms (SNP) screening through genotyping-by-sequencing. A total of 5,651 high-quality SNPs were considered for association mapping analysis, performed using mixed linear models accounting for population structure. Because of the absence of a fully assembled grass pea reference genome, SNP markers' genomic positions were retrieved from the pea's reference genome v1a. In total, 17 genomic regions were associated with three fusarium wilt response traits in grass pea, anticipating an oligogenic control. Seven of these regions were located on pea chromosomes 1, 6, and 7. The candidate genes underlying these regions were putatively involved in secondary and amino acid metabolism, RNA (regulation of transcription), transport, and development. This study revealed important fusarium wilt resistance favorable grass pea SNP alleles, allowing the development of molecular tools for precision disease resistance breeding.

The utility of metabolomics as a tool to inform maize biology

With the rise of high-throughput omics tools and the importance of maize and its products as food and bioethanol, maize metabolism has been extensively explored. Modern maize is still rich in genetic and phenotypic variation, yielding a wide range of structurally and functionally diverse metabolites. The maize metabolome is also incredibly dynamic in terms of topology and subcellular compartmentalization. In this review, we examine a broad range of studies that cover recent developments in maize metabolism. Particular attention is given to current methodologies and to the use of metabolomics as a tool to define biosynthetic pathways and address biological questions. We also touch upon the use of metabolomics to understand maize natural variation and evolution, with a special focus on research that has used metabolite-based genome-wide association studies (mGWASs).

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

BACKGROUND

Sesame is a rare example of non-model and minor crop for which numerous genetic loci and candidate genes underlying features of interest have been disclosed at relatively high resolution. These progresses have been achieved thanks to the applications of the genome-wide association study (GWAS) approach. GWAS has benefited from the availability of high-quality genomes, re-sequencing data from thousands of genotypes, extensive transcriptome sequencing, development of haplotype map and web-based functional databases in sesame.

RESULTS

In this paper, we reviewed the GWAS methods, the underlying statistical models and the applications for genetic discovery of important traits in sesame. A novel online database SiGeDiD ( http://sigedid.ucad.sn/ ) has been developed to provide access to all genetic and genomic discoveries through GWAS in sesame. We also tested for the first time, applications of various new GWAS multi-locus models in sesame.

CONCLUSIONS

Collectively, this work portrays steps and provides guidelines for efficient GWAS implementation in sesame, a non-model crop.

Volatilome-Genome-Wide Association Study on Wholemeal Maize Flour

Odor and aroma, resulting from the perception of volatiles by the olfactory receptors, are important in consumer food acceptance. To develop more efficient molecular breeding tools to improve the odor/aroma on maize (Zea mays L.), a staple food crop, increasing the knowledge on the genetic basis of maize volatilome is needed. In this work, we conducted a genome-wide association study on a unique germplasm collection to identify genomic regions controlling maize wholemeal flour's volatilome. We identified 64 regions on the maize genome and candidate genes controlling the levels of 15 volatiles, mainly aldehydes. As an example, the Zm00001d033623 gene was within a region associated with 2-octenal (E) and 2-nonenal (E), two byproducts of linoleic acid oxidation. This gene codes for linoleate 9S-lipoxygenase, an enzyme responsible for oxidizing linoleic acid. This knowledge can now support the development of molecular tools to increase the selection efficacy/efficiency of these volatiles within maize breeding programs.

Alleles to Enhance Antioxidant Content in Maize-A Genome-Wide Association Approach

The interest in antioxidant compound breeding in maize (Zea mays L.), a major food crop, has increased in recent years. However, breeding of antioxidant compounds in maize can be hampered, given the complex genetic nature of these compounds. In this work, we followed a genome-wide association approach, using a unique germplasm collection (containing Portuguese germplasm), to study the genetic basis of several antioxidants in maize. Sixty-seven genomic regions associated with seven antioxidant compounds and two color-related traits were identified. Several significant associations were located within or near genes involved in the carotenoid (Zm00001d036345) and tocopherol biosynthetic pathways (Zm00001d017746). Some indications of a negative selection against α-tocopherol levels were detected in the Portuguese maize germplasm. The strongest single nucleotide polymorphism (SNP)-trait associations and the SNP alleles with larger effect sizes were pinpointed and set as priority for future validation studies; these associations detected now constitute a benchmark for developing molecular selection tools for antioxidant compound selection in maize.

Maize Open-Pollinated Populations Physiological Improvement: Validating Tools for Drought Response Participatory Selection

Participatory selection—exploiting specific adaptation traits to target environments—helps to guarantees yield stability in a changing climate, in particular under low-input or organic production. The purpose of the present study was to identify reliable, low-cost, fast and easy-to-use tools to complement traditional selection for an effective participatory improvement of maize populations for drought resistance/tolerance. The morphological and eco-physiological responses to progressive water deprivation of four maize open-pollinated populations were assessed in both controlled and field conditions. Thermography and Chl a fluorescence, validated by gas exchange indicated that the best performing populations under water-deficit conditions were ‘Fandango’ and to a less extent ‘Pigarro’ (both from participatory breeding). These populations showed high yield potential under optimal and reduced watering. Under moderate water stress, ‘Bilhó’, originating from an altitude of 800 m, is one of the most resilient populations. The experiments under chamber conditions confirmed the existence of genetic variability within ‘Pigarro’ and ‘Fandango’ for drought response relevant for future populations breeding. Based on the easiness to score and population discriminatory power, the performance index (PIABS) emerges as an integrative phenotyping tool to use as a refinement of the common participatory maize selection especially under moderate water deprivation.

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

Exploring the metabolic differences directly on tissues is essential for the comprehensive understanding of how multicellular organisms function. Mass spectrometry imaging (MSI) is an attractive technique toward this goal; however, MSI in metabolomics scale has been hindered by multiple limitations. This is most notable for single cell level high-spatial resolution imaging because of the limited number of molecules in small sampling size and the low ionization yields of many metabolites. Several on-tissue chemical derivatization approaches have been reported to increase MSI signals of targeted compounds, especially in matrix-assisted laser desorption/ionization (MALDI)-MSI. Herein, we adopt a combination of chemical derivatization reactions, to selectively enhance metabolite signals of a specific functional group for each consecutive tissue section. Three well-known on-tissue derivatization methods were used as a proof of concept experiment: coniferyl aldehyde for primary amines, Girard's reagent T for carbonyl groups, and 2-picolylamine for carboxylic acids. This strategy was applied to the cross-sections of leaves and roots from two different maize genotypes (B73 and Mo17), and enabled the detection of over six hundred new unique metabolite features compared to without modification. Statistical analysis indicated quantitative variation between metabolites in the tissue sections, while MS images revealed differences in localization of these metabolites. Combined, this untargeted approach facilitated the visualization of various classes of compounds, demonstrating the potential for untargeted MSI in the metabolomics scale.