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

Enhancing quality traits in staple crops: current advances and future perspectives

Staple crops such as rice, wheat and maize are crucial for global food security; however, improving their quality remains a significant challenge. This review summarizes recent advances in enhancing crop quality, focusing on key areas such as the molecular mechanisms underlying endosperm filling initiation, starch granule synthesis, protein body formation, and the interactions between carbon and nitrogen metabolism. It also highlights ten unresolved questions related to starch-protein spatial distribution, epigenetic regulation, and the environmental impacts on quality traits. The integration of multi-omics approaches, and rational design strategies presents opportunities to develop high-yield "super-crop" varieties with enhanced nutritional value, better processing characteristics, and attributes preferred by consumers. Addressing these challenges is crucial to promote sustainable agriculture and achieve the dual objectives of food security and environmental conservation.

Genome-wide association study to identify the genomic loci associated with wheat heading date variation under autumn-sowing conditions

The present study aimed to identify genetic loci associated with days to heading (DTH) in wheat under autumn-sowing conditions in Korea, where early heading is critical owing to the overlap between the wheat harvest and the rainy season. We evaluated 530 wheat core collections over five years, focusing on known heading date genes VRN-1 and PPD-1, and conducted a genome-wide association study (GWAS) to identify new genetic loci related to DTH. The results revealed that Korean accessions exhibited the earliest DTH, with modern Korean varieties heading even earlier, reflecting a strong breeding focus on early heading. Among the existing heading date genes, VRN-1 and PPD-D1 were significantly associated with DTH in the wheat core collection. However, all Korean varieties carried the same alleles for each of VRN-A1, PPD-A1, and PPD-D1, resulting in low genetic diversity, which rendered the existing heading date genes insufficient to fully account for the variation in DTH within the Korean varieties. GWAS identified nine single nucleotide polymorphisms (SNPs) associated with DTH in Group A (entire collection filtered, n=518) and six in Group B (accessions with genotypes identical to Korean varieties filtered, n=231). Four key SNPs (AX-95222044 and AX-94685526 in Group A, and AX-94550996 and AX-94970315 in Group B) were selected based on their effect sizes on DTH. In both groups, accessions with alleles for early heading at both of the selected SNPs exhibited the earliest DTH, advancing by 7.7 to 8.9 days. These findings suggest that the selected SNPs, particularly those reflecting the genotypes of Korean varieties, effectively explain the variations in DTH among Korean varieties and could enhance wheat breeding efficiency in Korea. Further research is needed to validate the four selected SNPs and identify the underlying genes, which could serve as valuable markers for developing early-heading wheat varieties suited to Korean autumn-sowing conditions.

Discovery and validation of SSR marker-based QTL governing fresh pod yield in dolichos bean (Lablab purpureus L. Sweet)

Identification and validation of quantitative trait loci (QTL) governing desired phenotype of target trait is a prerequisite to implement marker-assisted selection in any crop including dolichos bean. Under this premise, we used two mapping populations (MPs) to detect and cross population validate QTL controlling fresh pod yield. One of the MPs consisted of F2 individuals (MP1) derived from crossing two elite genotypes, the second MP consisted of random RILs (MP2) derived from a different pair of elite genotypes. The MP1 and MP2 were genotyped using polymorphic 86 and 91 SSR markers, respectively and linkage maps were constructed using QTL IciM mapping software. The MP1 and MP2 were phenotyped during 2021 and 2017 rainy and post rainy seasons, respectively for fresh pod yield plant-1 following two-replicated simple lattice design. QTL maps were developed in MP1 and MP2 using genotype and phenotype data. Our results indicated that the estimates of total map length, average map length per linkage group (LG) and average inter-marker distance in MP2 were greater (by at least 1.5 times) than those in MP1. While seven QTLs were detected in MP1, six were detected in MP2 with three QTL exhibiting positive and additive minor effects for fresh pod yield plant-1. We also detected one common minor positive effect QTL across two seasons in MP2 and significant epistatic QTL, whose main effects were non-significant. One each of the seven and six QTL-linked SSR markers detected in MP1 and MP2, respectively were cross-population validated. The implications of these results are discussed in relation to strategies to breed dolichos bean.

Maize kernel nutritional quality-an old challenge for modern breeders

MAIN CONCLUSION

This article offers a comprehensive overview of the starch, protein, oil, and carotenoids content in maize kernels, while also outlining future directions for research in this area. Maize is one of the most important cereal crops globally. Maize kernels serve as a vital source of feed and food, and their nutritional quality directly impacts the dietary intake of both animals and humans. Maize kernels contain starch, protein, oil, carotenoids, and a variety of vitamins and minerals, all of which are important for maintaining life and promoting health. This review presents the current understanding of the content of starch, protein, amino acids, oil, and carotenoids in maize kernels, while also highlighting knowledge gaps that need to be addressed.

Novel candidate genes and genetic basis analysis of kernel starch content in tropical maize

BACKGROUND

Starch is the most abundant carbohydrate in maize grains, serving as a primary energy source for both humans and animals, and playing a crucial role in various industrial applications. Increasing the starch content of maize grains is beneficial for improving the grain yield and quality. To gain insight into the genetic basis of starch content in maize kernels, a multiparent population (MPP) was constructed and evaluated for starch content in three different environments.

RESULTS

The integration of QTL mapping and genome-wide association analysis (GWAS) identified two SNPs, 8_166371888 and 8_178656036, which overlapped the QTL interval of qSC8-1, identified in the tropical maize line YML46. The phenotypic variance explained (PVE) by the QTL qSC8-1 was12.17%, while the SNPs 8_166371888 and 8_178656036 explained 10.19% and 5.72% of the phenotypic variance. Combined GWAS and QTL analyses led to the identification of two candidate genes, Zm00001d012005 and Zm00001d012687 located on chromosome 8.

CONCLUSIONS

The candidate gene Zm00001d012005 encodes histidine kinase, which is known to play a role in starch accumulation in rice spikes. Related histidine kinases, such as AHK1, are involved in endosperm transfer cell development in barley, which affects grain quality. Zm00001d012687 encodes triacylglycerol lipase, which reduces seed oil content. Since oil content in cereal kernels is negatively correlated with starch content, this gene is likely involved in regulating the starch content in maize kernels. These findings provide insights into the genetic mechanisms underlying kernel starch content and establish a theoretical basis for breeding maize varieties with high starch content.

Calcium and Magnesium Regulation of Kernel Sugar Content in Maize: Role of Endogenous Hormones and Antioxidant Enzymes

Ca and Mg are essential micronutrients for plant growth, and they play a crucial role in plant development and responses to adversity by influencing the activities of endogenous hormones and antioxidant enzymes. However, the specific mechanisms through which calcium (Ca) and magnesium (Mg) regulate the kernel sugar content through endogenous hormones and antioxidant enzymes remain unclear. In this study, we analyzed the impact of Ca and Mg on the physiology of maize leaves and kernel quality by determining the activities of antioxidant enzymes and endogenous hormones, and the kernel sugar content in maize leaves when supplemented with different levels of Ca and Mg. Our main findings were as follows: (1) Elevated Mg levels augmented superoxide dismutase (SOD) activity, bolstering antioxidant defenses, whereas low Ca and Mg levels diminished SOD activity. High Ca levels enhanced catalase (CAT) activity during kernel development. Low-Ca conditions stimulated gibberellin (GA) synthesis, while high-Ca and high-Mg conditions suppressed it. High Mg levels also elevated abscisic acid (ABA) levels, potentially improving stress tolerance. (2) High Ca levels increased the reducing sugar content in kernels, augmenting the energy supply, while both low and high Mg levels increased soluble sugars, with low Mg levels specifically enhancing the sucrose content, which is a critical energy reserve in plants. (3) CAT exerted a pivotal regulatory role in the sugar accumulation in maize kernels. GA, under the influence of Ca, modulated the sucrose and soluble sugar contents by inhibiting CAT, whereas ABA, under the influence of Mg, promoted CAT activity, thereby affecting the kernel sugar content. This study reveals a new mechanism through which the addition of Ca and Mg regulate the sugar content in maize kernels by affecting endogenous hormones and antioxidant enzyme activities. These findings not only enhance our understanding of the role of micronutrients in plant growth and development but also provide new strategies for improving crop yield and stress tolerance.

GWAS and Meta-QTL Analysis of Kernel Quality-Related Traits in Maize

The quality of corn kernels is crucial for their nutritional value, making the enhancement of kernel quality a primary objective of contemporary corn breeding efforts. This study utilized 260 corn inbred lines as research materials and assessed three traits associated with grain quality. A genome-wide association study (GWAS) was conducted using the best linear unbiased estimator (BLUE) for quality traits, resulting in the identification of 23 significant single nucleotide polymorphisms (SNPs). Additionally, nine genes associated with grain quality traits were identified through gene function annotation and prediction. Furthermore, a total of 697 quantitative trait loci (QTL) related to quality traits were compiled from 27 documents, followed by a meta-QTL analysis that revealed 40 meta-QTL associated with these traits. Among these, 19 functional genes and reported candidate genes related to quality traits were detected. Three significant SNPs identified by GWAS were located within the intervals of these QTL, while the remaining eight significant SNPs were situated within 2 Mb of the QTL. In summary, the findings of this study provide a theoretical framework for analyzing the genetic basis of corn grain quality-related traits and for enhancing corn quality.

Deciphering the Genetic Basis of Kernel Composition in a Maize Association Panel

The primary objective in contemporary maize breeding is to pursue high quality alongside high yield. Deciphering the genetic basis of natural variation in starch, protein, oil, and fiber contents is essential for manipulating kernel composition, thereby enhancing the kernel quality and meeting growing demands. Here, we identified 12 to 88 statistically significant loci associated with kernel composition traits through a genome-wide association study (GWAS) using a panel of 212 diverse inbred lines. A regional association study pinpointed numerous causal candidate genes at these loci. Coexpression and protein-protein interaction network analyses of candidate genes revealed several causal genes directly or indirectly involved in the metabolic processes related to kernel composition traits. Subsequent mutant experiment revealed that nonsense mutations in ZmTIFY12 affect starch, protein, and fiber content, whereas nonsense mutations in ZmTT12 affect starch, protein, and oil content. These findings provide valuable guidance for improving kernel quality in maize breeding efforts.

QTL Mapping and Candidate Gene Analysis for Starch-Related Traits in Tartary Buckwheat (Fagopyrum tataricum (L.) Gaertn)

Starch is the main component that determines the yield and quality of Tartary buckwheat. As a quantitative trait, using quantitative trait locus (QTL) mapping to excavate genes associated with starch-related traits is crucial for understanding the genetic mechanisms involved in starch synthesis and molecular breeding of Tartary buckwheat varieties with high-quality starch. Employing a recombinant inbred line population as research material, this study used QTL mapping to investigate the amylose, amylopectin, and total starch contents across four distinct environments. The results identified a total of 20 QTLs spanning six chromosomes, which explained 4.07% to 14.41% of the phenotypic variation. One major QTL cluster containing three stable QTLs governing both amylose and amylopectin content, qClu-4-1, was identified and located in the physical interval of 39.85-43.34 Mbp on chromosome Ft4. Within this cluster, we predicted 239 candidate genes and analyzed their SNP/InDel mutations, expression patterns, and enriched KEGG pathways. Ultimately, five key candidate genes, namely FtPinG0004897100.01, FtPinG0002636200.01, FtPinG0009329200.01, FtPinG0007371600.01, and FtPinG0005109900.01, were highlighted, which are potentially involved in starch synthesis and regulation, paving the way for further investigative studies. This study, for the first time, utilized QTL mapping to detect major QTLs controlling amylose, amylopectin, and total starch contents in Tartary buckwheat. The QTLs and candidate genes would provide valuable insights into the genetic mechanisms underlying starch synthesis and improving starch-related traits of Tartary buckwheat.

Multi-layer molecular analysis reveals distinctive metabolomic and transcriptomic profiles of different sweet corn varieties

In plants, sugar metabolism involves a complex interplay of genetic, molecular and environmental factors. To better understand the molecular mechanisms underlying these processes, we utilized a multi-layered approach that integrated transcriptomic and metabolomic datasets generated from multiple different varieties of sweet corn. Through this analysis, we found 2533 genes that were differentially expressed in the immature kernel tissues of sweet corn, including genes involved in transcriptional regulation, sugar metabolism, primary metabolism, and other processes associated with adaptability of sweet corn. We also detected 31 differential metabolites among the three types of sweet corn. Utilizing an integrated approach encompassing transcriptomics and eGWAS, we elucidated the transcriptional regulatory patterns governing these differential metabolites. Specifically, we delved into the transcriptional modulation of malate- and ubiquitin-associated genes across a range of sweet corn varieties, shedding new light on the molecular mechanisms underlying their regulation. This study provides a framework for future research aimed at improving the current understanding of sugar metabolism and regulatory gene networks in sweet corn, which could ultimately lead to the development of novel strategies for crop improvement.

Linkage and association mapping in multi-parental populations reveal the genetic basis of carotenoid variation in maize kernels

Carotenoids are indispensable to plants and critical components of the human diet. The carotenoid metabolic pathway is conserved across plant species, but our understanding of the genetic basis of carotenoid variation remains limited for the seeds of most cereal crops. To address this issue, we systematically performed linkage and association mapping for eight carotenoid traits using six recombinant inbred line (RIL) populations. Single linkage mapping (SLM) and joint linkage mapping (JLM) identified 77 unique additive QTLs and 104 pairs of epistatic QTLs. Among these QTLs, we identified 22 overlapping hotspots of additive and epistatic loci, highlighting the important contributions of some QTLs to carotenoid levels through additive or epistatic mechanisms. A genome-wide association study based on all RILs detected 244 candidate genes significantly associated with carotenoid traits, 23 of which were annotated as carotenoid pathway genes. Effect comparisons suggested that a small number of loci linked to pathway genes have substantial effects on carotenoid variation in our tested populations, but many loci not associated with pathway genes also make important contributions to carotenoid variation. We identified ZmPTOX as the causal gene for a QTL hotspot (Q10/JLM10/GWAS019); this gene encodes a putative plastid terminal oxidase that produces plastoquinone-9 used by two enzymes in the carotenoid pathway. Natural variants in the promoter and second exon of ZmPTOX were found to alter carotenoid levels. This comprehensive assessment of the genetic mechanisms underlying carotenoid variation establishes a foundation for rewiring carotenoid metabolism and accumulation for efficient carotenoid biofortification.

Understanding grain development in the Poaceae family by comparing conserved and distinctive pathways through omics studies in wheat and maize

The Poaceae family, commonly known as the grass family, encompasses a diverse group of crops that play an essential role in providing food, fodder, biofuels, environmental conservation, and cultural value for both human and environmental well-being. Crops in Poaceae family are deeply intertwined with human societies, economies, and ecosystems, making it one of the most significant plant families in the world. As the major reservoirs of essential nutrients, seed grain of these crops has garnered substantial attention from researchers. Understanding the molecular and genetic processes that controls seed formation, development and maturation can provide insights for improving crop yield, nutritional quality, and stress tolerance. The diversity in photosynthetic pathways between C3 and C4 plants introduces intriguing variations in their physiological and biochemical processes, potentially affecting seed development. In this review, we explore recent studies performed with omics technologies, such as genomics, transcriptomics, proteomics and metabolomics that shed light on the mechanisms underlying seed development in wheat and maize, as representatives of C3 and C4 plants respectively, providing insights into their unique adaptations and strategies for reproductive success.

Combining genome-wide association study and linkage mapping in the genetic dissection of amylose content in maize (Zea mays L.)

KEY MESSAGE

Integrated linkage and association analysis revealed genetic basis across multiple environments. The genes Zm00001d003102 and Zm00001d015905 were further verified to influence amylose content using gene-based association study. Maize kernel amylose is an important source of human food and industrial raw material. However, the genetic basis underlying maize amylose content is still obscure. Herein, we used an intermated B73 × Mo17 (IBM) Syn10 doubled haploid population composed of 222 lines and a germplasm set including 305 inbred lines to uncover the genetic control for amylose content under four environments. Linkage mapping detected 16 unique QTL, among which four were individually repeatedly identified across multiple environments. Genome-wide association study revealed 17 significant (P = 2.24E-06) single-nucleotide polymorphisms, of which two (SYN19568 and PZE-105090500) were located in the intervals of the mapped QTL (qAC2 and qAC5-3), respectively. According to the two population co-localized loci, 20 genes were confirmed as the candidate genes for amylose content. Gene-based association analysis indicated that the variants in Zm00001d003102 (Beta-16-galactosyltransferase GALT29A) and Zm00001d015905 (Sugar transporter 4a) affected amylose content across multi-environment. Tissue expression analysis showed that the two genes were specifically highly expressed in the ear and stem, respectively, suggesting that they might participate in sugar transport from source to sink organs. Our study provides valuable genetic information for breeding maize varieties with high amylose.

Exploring the phosphorus-starch content balance mechanisms in maize grains using GWAS population and transcriptome data

Examining the connection between P and starch-related signals can help elucidate the balance between nutrients and yield. This study utilized 307 diverse maize inbred lines to conduct multi-year and multi-plot trials, aiming to explore the relationship among P content, starch content, and 100-kernel weight (HKW) of mature grains. A significant negative correlation was found between P content and both starch content and HKW, while starch content showed a positive correlation with HKW. The starch granules in grains with high-P and low-starch content (HPLS) were significantly smaller compared to grains with low-P high-starch content (LPHS). Additionally, mian04185-4 (HPLS) exhibited irregular and loosely packed starch granules. A significant decrease in ZmPHOs genes expression was detected in the HPLS line ZNC442 as compared to the LPHS line SCML0849, while no expression difference was observed in AGPase encoding genes between these two lines. The down-regulated genes in ZNC442 grains were enriched in nucleotide sugar and fatty acid anabolic pathways, while up-regulated genes were enriched in the ABC transporters pathway. An accelerated breakdown of fat as the P content increased was also observed. This implied that HPLS was resulted from elevated lipid decomposition and inadequate carbon sources. The GWAS analysis identified 514 significantly associated genes, out of which 248 were differentially expressed. Zm00001d052392 was found to be significantly associated with P content/HKW, exhibiting high expression in SCML0849 but almost no expression in ZNC442. Overall, these findings suggested new approaches for achieving a P-yield balance through the manipulation of lipid metabolic pathways in grains.

Sweet corn association panel and genome-wide association analysis reveal loci for chilling-tolerant germination

Sweet corn is highly susceptible to the deleterious effects of low temperatures during the initial stages of growth and development. Employing a 56K chip, high-throughput single-nucleotide polymorphism (SNP) sequencing was conducted on 100 sweet corn inbred lines. Subsequently, six germination indicators-germination rate, germination index, germination time, relative germination rate, relative germination index, and relative germination time-were utilized for genome-wide association analysis. Candidate genes were identified via comparative analysis of homologous genes in Arabidopsis and rice, and their functions were validated using quantitative real-time polymerase chain reaction (qRT-PCR). The results revealed 35,430 high-quality SNPs, 16 of which were significantly correlated. Within 50 kb upstream and downstream of the identified SNPs, 46 associated genes were identified, of which six were confirmed as candidate genes. Their expression patterns indicated that Zm11ΒHSDL5 and Zm2OGO likely play negative and positive regulatory roles, respectively, in the low-temperature germination of sweet corn. Thus, we determined that these two genes are responsible for regulating the low-temperature germination of sweet corn. This study contributes valuable theoretical support for improving sweet corn breeding and may aid in the creation of specific germplasm resources geared toward enhancing low-temperature tolerance in sweet corn.

Genetic basis of maize stalk strength decoded via linkage and association mapping

Stalk lodging is a severe problem that limits maize production worldwide, although little attention has been given to its genetic basis. Here we measured rind penetrometer resistance (RPR), an effective index for stalk lodging, in a multi-parent population of 1948 recombinant inbred lines (RILs) and an association population of 508 inbred lines (AMP508). Linkage and association mapping identified 53 and 29 single quantitative trait loci (QTLs) and 50 and 19 pairs of epistatic interactions for RPR in the multi-parent population and AMP508 population, respectively. Phenotypic variation explained by all identified epistatic QTLs (up to ~5%) was much less than that explained by all single additive QTLs (up to ~33% in the multi-parent population and ~ 60% in the AMP508 population). Among all detected QTLs, only eight single QTLs explained >10% of phenotypic variation in single RIL populations. Alleles that increased RPR were enriched in tropical/subtropical (TST) groups from the AMP508 population. Based on genome-wide association studies in both populations, we identified 137 candidate genes affecting RPR, which were assigned to multiple biological processes, such as the biosynthesis of cell wall components. Sixty-six candidate genes were cross-validated by multiple methods or populations. Most importantly, 23 candidate genes were upregulated or downregulated in high-RPR lines relative to low-RPR lines, supporting the associations between candidate genes and RPR. These findings reveal the complex nature of the genetic basis underlying RPR and provide loci or candidate genes for developing elite varieties that are resistant to stalk lodging via molecular breeding.

Orchestrating seed storage protein and starch accumulation toward overcoming yield-quality trade-off in cereal crops

Achieving high yield and good quality in crops is essential for human food security and health. However, there is usually disharmony between yield and quality. Seed storage protein (SSP) and starch, the predominant components in cereal grains, determine yield and quality, and their coupled synthesis causes a yield-quality trade-off. Therefore, dissection of the underlying regulatory mechanism facilitates simultaneous improvement of yield and quality. Here, we summarize current findings about the synergistic molecular machinery underpinning SSP and starch synthesis in the leading staple cereal crops, including maize, rice and wheat. We further evaluate the functional conservation and differentiation of key regulators and specify feasible research approaches to identify additional regulators and expand insights. We also present major strategies to leverage resultant information for simultaneous improvement of yield and quality by molecular breeding. Finally, future perspectives on major challenges are proposed.

Linkage mapping and genomic prediction of grain quality traits in tropical maize (Zea mays L.)

The suboptimal productivity of maize systems in sub-Saharan Africa (SSA) is a pressing issue, with far-reaching implications for food security, nutrition, and livelihood sustainability within the affected smallholder farming communities. Dissecting the genetic basis of grain protein, starch and oil content can increase our understanding of the governing genetic systems, improve the efficacy of future breeding schemes and optimize the end-use quality of tropical maize. Here, four bi-parental maize populations were evaluated in field trials in Kenya and genotyped with mid-density single nucleotide polymorphism (SNP) markers. Genotypic (G), environmental (E) and G×E variations were found to be significant for all grain quality traits. Broad sense heritabilities exhibited substantial variation (0.18-0.68). Linkage mapping identified multiple quantitative trait loci (QTLs) for the studied grain quality traits: 13, 7, 33, 8 and 2 QTLs for oil content, protein content, starch content, grain texture and kernel weight, respectively. The co-localization of QTLs identified in our research suggests the presence of shared genetic factors or pleiotropic effects, implying that specific genomic regions influence the expression of multiple grain quality traits simultaneously. Genomic prediction accuracies were moderate to high for the studied traits. Our findings highlight the polygenic nature of grain quality traits and demonstrate the potential of genomic selection to enhance genetic gains in maize breeding. Furthermore, the identified genomic regions and single nucleotide polymorphism markers can serve as the groundwork for investigating candidate genes that regulate grain quality traits in tropical maize. This, in turn, can facilitate the implementation of marker-assisted selection (MAS) in breeding programs focused on improving grain nutrient levels.

Coordinated Transcriptome and Metabolome Analyses of a Barley hvhggt Mutant Reveal a Critical Role of Tocotrienols in Endosperm Starch Accumulation

Tocotrienols and tocopherols (vitamin E) are potent antioxidants that are synthesized in green plants. Unlike ubiquitous tocopherols, tocotrienols predominantly accumulate in the endosperm of monocot grains, catalyzed by homogentiate geranylgeranyl transferase (HGGT). Previously, we generated a tocotrienol-deficient hvhggt mutant with shrunken barley grains. However, the relationship between tocotrienols and grain development remains unclear. Here, we found that the hvhggt lines displayed hollow endosperms with defective transfer cells and reduced aleurone layers. The carbohydrate and starch contents of the hvhggt endosperm decreased by approximately 20 and 23%, respectively. Weighted gene coexpression network analyses identified a critical gene module containing HvHGGT, which was strongly associated with the hvhggt mutation and enriched with gene functions in starch and sucrose metabolism. Metabolome measurements revealed an elevated soluble sugar content in the hvhggt endosperm, which was significantly associated with the identified gene modules. The hvhggt endosperm had significantly higher NAD(H) and NADP(H) contents and lower levels of ADPGlc (regulated by redox balance) than the wild-type, consistent with the absence of tocotrienols. Interestingly, exogenous α-tocotrienol spraying on developing hvhggt spikes partially rescued starch accumulation and endosperm defects. Our study supports a potential novel function of tocotrienols in grain starch accumulation and endosperm development in monocot crops.

Identification of novel loci associated with starch content in maize kernels by a genome-wide association study using an enlarged SNP panel

Starch is a major component of cereals, comprising over 70% of dry weight. It serves as a primary carbon source for humans and animals. In addition, starch is an indispensable industrial raw material. While maize (Zea mays) is a key crop and the primary source of starch, the genetic basis for starch content in maize kernels remains poorly understood. In this study, using an enlarged panel, we conducted a genome-wide association study (GWAS) based on best linear unbiased prediction (BLUP) value for starch content of 261 inbred lines across three environments. Compared with previous study, we identified 14 additional significant quantitative trait loci (QTL), encompassed a total of 42 genes, and indicated that increased marker density contributes to improved statistical power. By integrating gene expression profiling, Gene Ontology (GO) enrichment and haplotype analysis, several potential target genes that may play a role in regulating starch content in maize kernels have been identified. Notably, we found that ZmAPC4, associated with the significant SNP chr4.S_175584318, which encodes a WD40 repeat-like superfamily protein and is highly expressed in maize endosperm, might be a crucial regulator of maize kernel starch synthesis. Out of the 261 inbred lines analyzed, they were categorized into four haplotypes. Remarkably, it was observed that the inbred lines harboring hap4 demonstrated the highest starch content compared to the other haplotypes. Additionally, as a significant achievement, we have developed molecular markers that effectively differentiate maize inbred lines based on their starch content. Overall, our study provides valuable insights into the genetic basis of starch content and the molecular markers can be useful in breeding programs aimed at developing maize varieties with high starch content, thereby improving breeding efficiency.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-023-01437-6.

Evaluating the potential of Bacillus licheniformis YZCUO202005 isolated from lichens in maize growth promotion and biocontrol

Lichens exist in an organismal organization of mycobiont, photobiont, and non-photoautotrophic bacteria. These organisms contribute to the growth of lichens even in poor nutrition substrates. However, studies on the isolation and application of non-photoautotrophic bacteria in plant growth and biocontrol are scanty. Therefore, a study was conducted to isolate and evaluate the potential of non-photoautotrophic bacteria from lichen tissues in maize plant growth promotion and biocontrol of plant pathogens (fungi and bacteria). Five bacterial strains were isolated and tested for their ability to produce indole-3-Acetic Acid (IAA). One bacterium named YZCUO202005 produced IAA, siderophores and biofilms, solubilized phosphate and potassium and exhibited extracellular enzymes (cellulases, proteases, amylase, and β -1,3-Glucanase). Based on the 16S rRNA sequence analysis results, YZCUO202005 was identified as Bacillus licheniformis. The strain inhibited the growth of five pathogenic fungi with an inhibition percent of between 58.7% and 71.7% and two pathogenic bacteria. Under greenhouse conditions, YZCUO202005 was tested for its abilities to enhance maize seed germination, and vegetative growth. Compared with the control treatment, the strain significantly enhanced the growth of stem length (i.e. 18 ± 0.64 cm, 78 ± 0.92 cm), leaf length (i.e. 10 ± 0.36 cm, 57 ± 1.42 cm), leaf chlorophyll levels (i.e., 13 ± 0.40, 40 ± 0.43 SPAD), and root length (i.e, 9.8 ± 2.25 cm, 22.5 ± 6.59 cm). Our results demonstrated that B. licheniformis YZCUO202005 from lichens has the potential to promote plant growth and reduce fungal and bacterial pathogens' growth. Furthermore, the results suggest that lichens are naturally rich sources of plant growth promotion and biocontrol agents that would be used in agriculture.

Coordination of carbon assimilation, allocation, and utilization for systemic improvement of cereal yield

The growth of yield outputs is dwindling after the first green revolution, which cannot meet the demand for the projected population increase by the mid-century, especially with the constant threat from extreme climates. Cereal yield requires carbon (C) assimilation in the source for subsequent allocation and utilization in the sink. However, whether the source or sink limits yield improvement, a crucial question for strategic orientation in future breeding and cultivation, is still under debate. To narrow the knowledge gap and capture the progress, we focus on maize, rice, and wheat by briefly reviewing recent advances in yield improvement by modulation of i) leaf photosynthesis; ii) primary C allocation, phloem loading, and unloading; iii) C utilization and grain storage; and iv) systemic sugar signals (e.g., trehalose 6-phosphate). We highlight strategies for optimizing C allocation and utilization to coordinate the source-sink relationships and promote yields. Finally, based on the understanding of these physiological mechanisms, we envisage a future scenery of "smart crop" consisting of flexible coordination of plant C economy, with the goal of yield improvement and resilience in the field population of cereals crops.

Efficiency of mapping epistatic quantitative trait loci

Most theoretical studies on epistatic QTL mapping have shown that this procedure is powerful, efficient to control the false positive rate (FPR), and precise to localize QTLs. The objective of this simulation-based study was to show that mapping epistatic QTLs is not an almost-perfect process. We simulated 50 samples of 400 F2 plants/recombinant inbred lines, genotyped for 975 SNPs distributed in 10 chromosomes of 100 cM. The plants were phenotyped for grain yield, assuming 10 epistatic QTLs and 90 minor genes. Adopting basic procedures of r/qtl package, we maximized the power of detection for QTLs (56-74%, on average) but associated with a very high FPR (65%) and a low detection power for the epistatic pairs (7%). Increasing the average detection power for epistatic pairs (14%) highly increased the related FPR. Adopting a procedure to find the best balance between power and FPR, there was a significant decrease in the power of QTL detection (17-31%, on average), associated with a low average detection power for epistatic pairs (8%) and an average FPR of 31% for QTLs and 16% for epistatic pairs. The main reasons for these negative results are a simplified specification of the coefficients of epistatic effects, as theoretically proved, and the effects of minor genes since 2/3 of the FPR for QTLs were due to them. We hope that this study, including the partial derivation of the coefficients of epistatic effects, motivates investigations on how to increase the power of detection for epistatic pairs, effectively controlling the FPR.

Identification of QTLs and Putative Candidate Genes for Plant Architecture of Lotus Revealed by Regional Association Mapping

The lotus (Nelumbo Adans.) is one of the most economically relevant ornamental aquatic plants. Plant architecture (PA) is an important trait for lotus classification, cultivation, breeding, and applications. However, the underlying genetic and molecular basis controlling PA remains poorly understood. In this study, an association study for PA-related traits was performed with 93 genome-wide microsatellite markers (simple sequence repeat, SSR) and 51 insertion-deletion (InDel) markers derived from the candidate regions using a panel of 293 lotus accessions. Phenotypic data analysis of the five PA-related traits revealed a wide normal distribution and high heritability from 2013 to 2016, which indicated that lotus PA-related traits are highly polygenic traits. The population structure (Q-matrix) and the relative kinships (K-matrix) of the association panels were analyzed using 93 SSR markers. The mixed linear model (MLM) taking Q-matrix and K-matrix into account was used to estimate the association between markers and the traits. A total of 26 markers and 65 marker-trait associations were identified by considering associations with p < 0.001 and Q < 0.05. Based on the significant markers, two QTLs on Chromosome 1 were identified, and two candidate genes were preliminarily determined. The results of our study provided useful information for the lotus breeding aiming at different PA phenotypes using a molecular-assisted selection (MAS) method and also laid the foundation for the illustration of the molecular mechanism underlying the major QTL and key markers associated with lotus PA.

Genome-wide association analysis of kernel nutritional quality in two natural maize populations

As one of the three staple crops, nutritional traits in maize are important for human and animal nutrition. Grain quality-related traits are closely related to grain commercial value. Understanding the genetic basis of quality-related traits in maize would be helpful for breeding high-quality maize varieties. In this study, two association panels (AM122 and AM180) were subjected to genome-wide association analysis of grain quality-related traits, including protein content, oil content, starch content, and fiber content. In total, 98 SNPs (P < 1 × 10-4) were identified to be significantly associated with these four grain quality-related traits. By integrating two sets of public transcriptome data, 31 genes located in 200 kb regions flanking the associated SNP showed high expression during kernel development and were differentially expressed in two maize inbred lines, KA225 and KB035, with significantly different quality. These genes might regulate maize grain quality by participating in plant hormone processes, autophagy processes, and others. All these results could provide important reference information for breeding high‑quality maize varieties.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-023-01360-w.

Genetic basis of resistance to southern corn leaf blight in the maize multi-parent population and diversity panel

Southern corn leaf blight (SLB), caused by the necrotrophic pathogen Cochliobolus heterostrophus, is one of the maize foliar diseases and poses a great threat to corn production around the world. Identification of genetic variations underlying resistance to SLB is of paramount importance to maize yield and quality. Here, we used a random-open-parent association mapping population containing eight recombinant inbred line populations and one association mapping panel consisting of 513 diversity maize inbred lines with high-density genetic markers to dissect the genetic basis of SLB resistance. Overall, 109 quantitative trait loci (QTLs) with predominantly small or moderate additive effects, and little epistatic effects were identified. We found 35 (32.1%) novel loci in comparison with the reported QTLs. We revealed that resistant alleles were significantly enriched in tropical accessions and the frequency of about half of resistant alleles decreased during the adaptation process owing to the selection of agronomic traits. A large number of annotated genes located in the SLB-resistant QTLs were shown to be involved in plant defence pathways. Integrating genome-wide association study, transcriptomic profiling, resequencing and gene editing, we identified ZmFUT1 and MYBR92 as the putative genes responsible for the major QTLs for resistance to C. heterostrophus. Our results present a comprehensive insight into the genetic basis of SLB resistance and provide resistant loci or genes as direct targets for crop genetic improvement.

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.

Association Mapping of Amylose Content in Maize RIL Population Using SSR and SNP Markers

The ratio of amylose to amylopectin in maize kernel starch is important for the appearance, structure, and quality of food products and processing. This study aimed to identify quantitative trait loci (QTLs) controlling amylose content in maize through association mapping with simple sequence repeat (SSR) and single-nucleotide polymorphism (SNP) markers. The average value of amylose content for an 80-recombinant-inbred-line (RIL) population was 8.8 ± 0.7%, ranging from 2.1 to 15.9%. We used two different analyses-Q + K and PCA + K mixed linear models (MLMs)-and found 38 (35 SNP and 3 SSR) and 32 (29 SNP and 3 SSR) marker-trait associations (MTAs) associated with amylose content. A total of 34 (31 SNP and 3 SSR) and 28 (25 SNP and 3 SSR) MTAs were confirmed in the Q + K and PCA + K MLMs, respectively. This study detected some candidate genes for amylose content, such as GRMZM2G118690-encoding BBR/BPC transcription factor, which is used for the control of seed development and is associated with the amylose content of rice. GRMZM5G830776-encoding SNARE-interacting protein (KEULE) and the uncharacterized marker PUT-163a-18172151-1376 were significant with higher R2 value in two difference methods. GRMZM2G092296 were also significantly associated with amylose content in this study. This study focused on amylose content using a RIL population derived from dent and waxy inbred lines using molecular markers. Future studies would be of benefit for investigating the physical linkage between starch synthesis genes using SNP and SSR markers, which would help to build a more detailed genetic map and provide new insights into gene regulation of agriculturally important traits.

Association mapping across a multitude of traits collected in diverse environments in maize

Classical genetic studies have identified many cases of pleiotropy where mutations in individual genes alter many different phenotypes. Quantitative genetic studies of natural genetic variants frequently examine one or a few traits, limiting their potential to identify pleiotropic effects of natural genetic variants. Widely adopted community association panels have been employed by plant genetics communities to study the genetic basis of naturally occurring phenotypic variation in a wide range of traits. High-density genetic marker data-18M markers-from 2 partially overlapping maize association panels comprising 1,014 unique genotypes grown in field trials across at least 7 US states and scored for 162 distinct trait data sets enabled the identification of of 2,154 suggestive marker-trait associations and 697 confident associations in the maize genome using a resampling-based genome-wide association strategy. The precision of individual marker-trait associations was estimated to be 3 genes based on a reference set of genes with known phenotypes. Examples were observed of both genetic loci associated with variation in diverse traits (e.g., above-ground and below-ground traits), as well as individual loci associated with the same or similar traits across diverse environments. Many significant signals are located near genes whose functions were previously entirely unknown or estimated purely via functional data on homologs. This study demonstrates the potential of mining community association panel data using new higher-density genetic marker sets combined with resampling-based genome-wide association tests to develop testable hypotheses about gene functions, identify potential pleiotropic effects of natural genetic variants, and study genotype-by-environment interaction.

Identifying loci controlling total starch content of leaf in Nicotiana tabacum through genome-wide association study

Starch is an important primary metabolite in plants, which can provide bioenergy for fuel ethanol production. There are many studies focusing on starch metabolism in Arabidopsis, maize, and rice, but few reports have been made on the starch content of tobacco leaves. Hence, to identify the marker-trait associations and isolate the candidate genes related to starch content of tobacco leaf, the genome-wide association study (GWAS) was performed using a multiparent advanced generation intercross (MAGIC) population consisting of 276 accessions genotyped by a 430 K SNP array. In this study, we detected the leaf starch content of tobacco plants cultivated in two places (Zhucheng and Chenzhou), which showed a wide variation of starch content in the population. A total of 28 and 45 significant single-nucleotide polymorphism (SNP) loci associated with leaf starch content were identified by single-locus and multi-locus GWAS models, respectively, and the phenotypic variance explained by these loci varied from 1.80 to - 14.73%. Furthermore, among these quantitative trait loci (QTLs), one SNP, AX-106011713 located on chromosome 19, was detected repeatedly in multiple models and two environments, which was selected for linkage disequilibrium (LD) analysis to obtain the target candidate region. Through gene annotation, haplotype, and gene expression analysis, two candidate genes encoding E3 ubiquitin-protein ligase (Ntab0823160) and fructose-bisphosphate aldolase (Ntab0375050) were obtained. Results showed that the variety carrying the beneficial alleles of the two candidate genes had higher gene expression level and leaf starch content, suggesting the potential role of candidate genes in enhancing the level of tobacco leaf starch content. Furthermore, silencing of Ntab0823160 in tobacco leaves reduced the content of total starch to 39.41-69.75% of that in the wide type plants. Taken together, our results provide useful resources for further investigation of the starch metabolic pathway and are also beneficial for the creation of eco-friendly cultivars with increased accumulation of leaf starch content.

Genetic Perturbation of the Starch Biosynthesis in Maize Endosperm Reveals Sugar-Responsive Gene Networks

In maize, starch mutants have facilitated characterization of key genes involved in endosperm starch biosynthesis such as large subunit of AGPase Shrunken2 (Sh2) and isoamylase type DBE Sugary1 (Su1). While many starch biosynthesis enzymes have been characterized, the mechanisms of certain genes (including Sugary enhancer1) are yet undefined, and very little is understood about the regulation of starch biosynthesis. As a model, we utilize commercially important sweet corn mutations, sh2 and su1, to genetically perturb starch production in the endosperm. To characterize the transcriptomic response to starch mutations and identify potential regulators of this pathway, differential expression and coexpression network analysis was performed on near-isogenic lines (NILs) (wildtype, sh2, and su1) in six genetic backgrounds. Lines were grown in field conditions and kernels were sampled in consecutive developmental stages (blister stage at 14 days after pollination (DAP), milk stage at 21 DAP, and dent stage at 28 DAP). Kernels were dissected to separate embryo and pericarp from the endosperm tissue and 3' RNA-seq libraries were prepared. Mutation of the Su1 gene led to minimal changes in the endosperm transcriptome. Responses to loss of sh2 function include increased expression of sugar (SWEET) transporters and of genes for ABA signaling. Key regulators of starch biosynthesis and grain filling were identified. Notably, this includes Class II trehalose 6-phosphate synthases, Hexokinase1, and Apetala2 transcription factor-like (AP2/ERF) transcription factors. Additionally, our results provide insight into the mechanism of Sugary enhancer1, suggesting a potential role in regulating GA signaling via GRAS transcription factor Scarecrow-like1.

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.

What are the regulatory targets for intervention in assimilate partitioning to improve crop yield and resilience?

Sucrose utilisation for the synthesis of cellular components involved in growth and development and the accumulation of biomass determines diversity in the plant kingdom; sucrose utilisation and partitioning also underpin crop yields. As a complex process the use of sucrose for the partitioning of plant products for yield is decided by the interaction of several regulatory hubs and the integration of metabolism and development. Understanding the regulation of assimilate partitioning has been a grand challenge in plant and crop science. There are emerging examples of genes and processes that appear important for assimilate partitioning that underpin yield in crops and which are amenable to intervention. Enzymes of carbon metabolism were some of the first targets in attempts to modify assimilate partitioning at the beginning (source) and end (sink) of the whole plant assimilate partitioning process. Metabolic enzymes are subject to regulatory and homeostatic mechanisms, a key factor to consider in modifying assimilate partitioning. Trehalose 6-phosphate, as a sucrose signal, may represent a special case in its ability to regulate and coordinate source and sink processes. This review summarises recent progress in understanding the underlying regulators of assimilate partitioning and the current and potentially most promising routes to crop yield enhancement with a main focus on cereals. A framework for how source-sink may regulate whole plant assimilate partitioning involving a few key elements and the central importance of reproductive development is presented.