A genome-wide association study uncovers a ZmRap2.7-ZCN9/ZCN10 module to regulate ABA signalling and seed vigour in maize.

Seed vigour, including rapid, uniform germination and robust seedling establishment under various field conditions, is becoming an increasingly essential agronomic trait for achieving high yield in crops. However, little is known about this important seed quality trait. In this study, we performed a genome-wide association study to identify a key transcription factor ZmRap2.7, which regulates seed vigour through transcriptionally repressing expressions of three ABA signalling genes ZmPYL3, ZmPP2C and ZmABI5 and two phosphatidylethanolamine-binding genes ZCN9 and ZCN10. In addition, ZCN9 and ZCN10 proteins could interact with ZmPYL3, ZmPP2C and ZmABI5 proteins, and loss-of-function of ZmRap2.7 and overexpression of ZCN9 and ZCN10 reduced ABA sensitivity and seed vigour, suggesting a complex regulatory network for regulation of ABA signalling mediated seed vigour. Finally, we showed that four SNPs in ZmRap2.7 coding region influenced its transcriptionally binding activity to the downstream gene promoters. Together with previously identified functional variants within and surrounding ZmRap2.7, we concluded that the distinct allelic variations of ZmRap2.7 were obtained independently during maize domestication and improvement, and responded separately for the diversities of seed vigour, flowering time and brace root development. These results provide novel genes, a new regulatory network and an evolutional mechanism for understanding the molecular mechanism of seed vigour.

Genomic basis determining root system architecture in maize.

KEY MESSAGE: A total of 389 and 344 QTLs were identified by GWAS and QTL mapping explaining accumulatively 32.2-65.0% and 23.7-63.4% of phenotypic variation for 14 shoot-borne root traits using more than 1300 individuals across multiple field trails. Efficient nutrient and water acquisition from soils depends on the root system architecture (RSA). However, the genetic determinants underlying RSA in maize remain largely unexplored. In this study, we conducted a comprehensive genetic analysis for 14 shoot-borne root traits using 513 inbred lines and 800 individuals from four recombinant inbred line (RIL) populations at the mature stage across multiple field trails. Our analysis revealed substantial phenotypic variation for these 14 root traits, with a total of 389 and 344 QTLs identified through genome-wide association analysis (GWAS) and linkage analysis, respectively. These QTLs collectively explained 32.2-65.0% and 23.7-63.4% of the trait variation within each population. Several a priori candidate genes involved in auxin and cytokinin signaling pathways, such as IAA26, ARF2, LBD37 and CKX3, were found to co-localize with these loci. In addition, a total of 69 transcription factors (TFs) from 27 TF families (MYB, NAC, bZIP, bHLH and WRKY) were found for shoot-borne root traits. A total of 19 genes including PIN3, LBD15, IAA32, IAA38 and ARR12 and 19 GWAS signals were overlapped with selective sweeps. Further, significant additive effects were found for root traits, and pyramiding the favorable alleles could enhance maize root development. These findings could contribute to understand the genetic basis of root development and evolution, and provided an important genetic resource for the genetic improvement of root traits in maize.

Hybrid performance evaluation and genome-wide association analysis of root system architecture in a maize association population.

KEY MESSAGE: The genetic architecture of RSA traits was dissected by GWAS and coexpression networks analysis in a maize association population. Root system architecture (RSA) is a crucial determinant of water and nutrient uptake efficiency in crops. However, the maize genetic architecture of RSA is still poorly understood due to the challenges in quantifying root traits and the lack of dense molecular markers. Here, an association mapping panel including 356 inbred lines were crossed with a common tester, Zheng58, and the test crosses were phenotyped for 12 RSA traits in three locations. We observed a 1.3 ~ sixfold phenotypic variation for measured RSA in the association panel. The association panel consisted of four subpopulations, non-stiff stalk (NSS) lines, stiff stalk (SS), tropical/subtropical (TST), and mixed. Zheng58 × TST has a 2.1% higher crown root number (CRN) and 8.6% less brace root number (BRN) than Zheng58 × NSS and Zheng58 × SS, respectively. Using a genome-wide association study (GWAS) with 1.25 million SNPs and correction for population structure, 191 significant SNPs were identified for root traits. Ninety (47%) of the significant SNPs showed positive allelic effects, and 101 (53%) showed negative effects. Each locus could explain 0.39% to 11.8% of phenotypic variation. By integrating GWAS results and comparing coexpression networks, 26 high-priority candidate genes were identified. Gene GRMZM2G377215, which belongs to the COBRA-like gene family, affected root growth and development. Gene GRMZM2G468657 encodes the aspartic proteinase nepenthesin-1, related to root development and N-deficient response. Collectively, our research provides progress in the genetic dissection of root system architecture. These findings present the further possibility for the genetic improvement of root traits in maize.

Mining genes regulating root system architecture in maize based on data integration analysis.

KEY MESSAGE: A new strategy that integrated multiple public data resources was established to construct root gene co-expression network and mine genes regulating root system architecture in maize. A root gene co-expression network, containing 13,874 genes, was constructed. A total of 53 root hub genes and 16 priority root candidate genes were identified. One priority root candidate was further functionally verified using overexpression transgenic maize lines. Root system architecture (RSA) is crucial for crops productivity and stress tolerance. In maize, few RSA genes are functionally cloned, and effective discovery of RSA genes remains a great of challenge. In this work, we established a strategy to mine maize RSA genes by integrating functionally characterized root genes, root transcriptome, weighted gene co-expression network analysis (WGCNA) and genome-wide association analysis (GWAS) of RSA traits based on public data resources. A total of 589 maize root genes were collected by searching well-characterized root genes in maize or homologous genes of other species. We performed WGCNA to construct a maize root gene co-expression network containing 13874 genes based on public available root transcriptome data, and further discovered the 53 hub genes related to root traits. In addition, by the prediction function of obtained root gene co-expression network, a total of 1082 new root candidate genes were explored. By further overlapping the obtained new root candidate gene with the root-related GWAS of RSA candidate genes, 16 priority root candidate genes were identified. Finally, a priority root candidate gene, Zm00001d023379 (encodes pyruvate kinase 2), was validated to modulate root open angle and shoot-borne roots number using its overexpression transgenic lines. Our results develop an integration analysis method for effectively exploring regulatory genes of RSA in maize and open a new avenue to mine the candidate genes underlying complex traits.

Plasticity of root anatomy during domestication of a maize-teosinte derived population.

Maize (Zea mays L.) has undergone profound changes in root anatomy for environmental adaptation during domestication. However, the genetic mechanism of plasticity of maize root anatomy during the domestication process remains unclear. In this study, high-resolution mapping was performed for nine root anatomical traits using a maize-teosinte population (mexicana × Mo17) across three environments. Large genetic variations were detected for different root anatomical traits. The cortex, stele, aerenchyma areas, xylem vessel number, and cortical cell number had large variations across three environments, indicating high plasticity. Sixteen quantitative trait loci (QTL) were identified, including seven QTL with QTL × environment interaction (EIQTL) for high plasticity traits and nine QTL without QTL × environment interaction (SQTL). Most of the root loci were consistent with shoot QTL depicting domestication signals. Combining transcriptome and genome-wide association studies revealed that AUXIN EFFLUX CARRIER PIN-FORMED LIKE 4 (ZmPILS4) serves as a candidate gene underlying a major QTL of xylem traits. The near-isogenic lines (NILs) with lower expression of ZmPILS4 had 18-24% more auxin concentration in the root tips and 8-15% more xylem vessels. Nucleotide diversity values analysis in the promoter region suggested that ZmPILS4 was involved in maize domestication and adaptation. These results revealed the potential genetic basis of root anatomical plasticity during domestication.

An allele of ZmPORB2 encoding a protochlorophyllide oxidoreductase promotes tocopherol accumulation in both leaves and kernels of maize.

Phytol is one of the key precursors for tocopherol synthesis in plants, however, the underlying mechanisms concerning the accumulation of tocopherol remain poorly understood. In this study, qVE5, a major QTL affecting tocopherol accumulation in maize kernels was identified via a positional cloning approach. qVE5 encodes a protochlorophyllide oxidoreductase (ZmPORB2), which localizes to the chloroplast. Overexpression of ZmPORB2 increased tocopherol content in both leaves and kernels. Candidate gene association analysis identified a 5/8-bp insertion/deletion (InDel058) in the 5' untranslated region (UTR) as the causal polymorphism in affecting ZmPORB2 expression and being highly associated with tocopherol content. We showed that higher expression of ZmPORB2 correlated with more chlorophyll metabolites in the leaf following pollination. RNA-sequencing and metabolic analysis in near isogenic lines (NILs) support that ZmPORB2 participates in chlorophyll metabolism enabling the production of phytol, an important precursor of tocopherol. We also found that the tocopherol content in the kernel is mainly determined by the maternal genotype, a fact that was further confirmed by in vitro culture experiments. Finally, a PCR-based marker based on Indel058 was developed in order to facilitate the high tocopherol (vitamin E) maize breeding.

Large-scale metabolite quantitative trait locus analysis provides new insights for high-quality maize improvement.

It is generally recognized that many favorable genes which were lost during domestication, including those related to both nutritional value and stress resistance, remain hidden in wild relatives. To uncover such genes in teosinte, an ancestor of maize, we conducted metabolite profiling in a BC2 F7 population generated from a cross between the maize wild relative (Zea mays ssp. mexicana) and maize inbred line Mo17. In total, 65 primary metabolites were quantified in four tissues (seedling-stage leaf, grouting-stage leaf, young kernel and mature kernel) with clear tissue-specific patterns emerging. Three hundred and fifty quantitative trait loci (QTLs) for these metabolites were obtained, which were distributed unevenly across the genome and included two QTL hotspots. Metabolite concentrations frequently increased in the presence of alleles from the teosinte genome while the opposite was observed for grain yield and shape trait QTLs. Combination of the multi-tissue transcriptome and metabolome data provided considerable insight into the metabolic variations between maize and its wild relatives. This study thus identifies favorable genes hidden in the wild relative which should allow us to balance high yield and quality in future modern crop breeding programs.

Combined physiological, transcriptome, and genetic analysis reveals a molecular network of nitrogen remobilization in maize.

In plants, nitrogen remobilization from source to sink organs is an important process regulated by complex transcriptional regulatory networks. However, the relationship between nitrogen remobilization and leaf senescence and the molecular regulatory network that controls them are unknown in maize. Here, using 15N labeling and a transcriptome approach, a dynamic analysis of the nitrogen remobilization process was conducted in two elite maize inbred lines (PH4CV and PH6WC) with contrasting leaf senescence. PH4CV showed higher nitrogen remobilization efficiency (NRE) than PH6WC, mainly in the middle and lower leaves from 15 d to 35 d after silking. The co-expression network analysis revealed that ethylene and cytokinin metabolism-related genes triggered the onset of nitrogen remobilization, while abscisic acid and jasmonic acid biosynthesis-related genes controlled the progression of nitrogen remobilization. By integrating genetic analysis, functional annotation, and gene expression, two candidate genes underlying a major quantitative trait locus of NRE were identified, namely an early senescence acting gene (ZmASR6) and an ATP-dependent Clp protease gene (GRMZM2G172230). Hormone-coupled transcription factors and downstream target genes reveal a gene regulatory network for the nitrogen remobilization process after silking in maize. These results uncovered a sophisticated regulatory mechanism for nitrogen remobilization, and further provided characterization of valuable genes for genetic improvement of nitrogen use efficiency in maize.

Recombination Pattern Characterization via Simulation Using Different Maize Populations.

Efficient recombination is critical to both plant breeding and gene cloning. However, almost all traditional recombination studies and genetic improvements require the slow and labor-intensive population construction process, and little is known about the recombination characteristics of populations of different types, generations, and origins. Here, we provide a simple and efficient simulation method for population construction based on doubled haploid (DH) and intermated B73 × Mo17 maize (IBM) populations to predict the recombination pattern. We found that the chromosomes had 0, 1, 2, and 3 recombination events that occurred at rates of 0.16, 0.30, 0.23, and 0.15, respectively, in the DH and the recombination rate of each chromosome in the IBM population ranged from 0 to 12.1 cM per 125 kb. Based on the observed recombination parameters, we estimated the number of recombination events and constructed the linkage maps of the simulated DH and recombination inbred line (RIL) populations. These simulated populations exhibited similar recombination patterns compared with the real populations, suggesting the feasibility of this simulation approach. We then compared the recombination rates of the simulated populations of different types (DH induced or self-crossed), generations, and origins (using the 8, 16, and 32 multiparent advanced generation intercross (MAGIC) populations), and suggested a rapid and cost-effective population construction procedure for breeders and geneticists, while maintaining an optimal recombination rate. This study offers a convenient method for optimizing the population construction process and has broader implications for other crop species, thereby facilitating future population studies and genetic improvement strategies.

Trait ontology analysis based on association mapping studies bridges the gap between crop genomics and Phenomics.

BACKGROUND: Trait ontology (TO) analysis is a powerful system for functional annotation and enrichment analysis of genes. However, given the complexity of the molecular mechanisms underlying phenomes, only a few hundred gene-to-TO relationships in plants have been elucidated to date, limiting the pace of research in this "big data" era. RESULTS: Here, we curated all the available trait associated sites (TAS) information from 79 association mapping studies of maize (Zea mays L.) and rice (Oryza sativa L.) lines with diverse genetic backgrounds and built a large-scale TAS-derived TO system for functional annotation of genes in various crops. Our TO system contains information for up to 18,042 genes (6345 in maize at the 25 k level and 11,697 in rice at the 50 k level), including gene-to-TO relationships, which covers over one fifth of the annotated gene sets for maize and rice. A comparison of Gene Ontology (GO) vs. TO analysis demonstrated that the TAS-derived TO system is an efficient alternative tool for gene functional annotation and enrichment analysis. We therefore combined information from the TO, GO, metabolic pathway, and co-expression network databases and constructed the TAS system, which is publicly available at http://tas.hzau.edu.cn . TAS provides a user-friendly interface for functional annotation of genes, enrichment analysis, genome-wide extraction of trait-associated genes, and crosschecking of different functional annotation databases. CONCLUSIONS: TAS bridges the gap between genomic and phenomic information in crops. This easy-to-use tool will be useful for geneticists, biologists, and breeders in the agricultural community, as it facilitates the dissection of molecular mechanisms conferring agronomic traits in an easy, genome-wide manner.

Increased biomass accumulation in maize grown in mixed nitrogen supply is mediated by auxin synthesis.

The use of mixed nitrate and ammonium as a nitrogen source can improve plant growth. Here, we used metabolomics and transcriptomics to study the underlying mechanisms. Maize plants were grown hydroponically in the presence of three forms of nitrogen (nitrate alone, 75%/25% nitrate/ammonium, and ammonium alone). Plants grown with mixed nitrogen had a higher photosynthetic rate than those supplied only with nitrate, and had the highest leaf area and shoot and root biomass among the three nitrogen treatments. In shoot and root, the concentration of nitrogenous compounds (ammonium, glutamine, and asparagine) and carbohydrates (sucrose, glucose, and fructose) in plants with a mixed nitrogen supply was higher than that with nitrate supply, but lower than that with ammonium supply. The activity of the related enzymes (glutamate synthase, asparagine synthase, phosphoenolpyruvate carboxylase, invertase, and ADP-glucose pyrophosphorylase) changed accordingly. Specifically, the mixed nitrogen source enhanced auxin synthesis via the shikimic acid pathway, as indicated by the higher levels of phosphoenolpyruvate and tryptophan compared with the other two treatments. The expression of corresponding genes involving auxin synthesis and response was up-regulated. Supply of only ammonium resulted in high levels of glutamine and asparagine, starch, and trehalose hexaphosphate. We conclude that, in addition to increased photosynthesis, mixed nitrogen supply enhances leaf growth via increasing auxin synthesis to build a large sink for carbon and nitrogen utilization, which, in turn, facilitates further carbon assimilation and nitrogen uptake.

Efficacy of Sublingual Administration of Dermatophagoides Farinae Drops for Treatment of Pediatric Allergic Rhinitis Accompanied by Adenoid Hypertrophy and Improvement of Immune Function.

BACKGROUND The aim of this study was to determine the efficacy of sublingual administration of Dermatophagoides farinae drops for the treatment of allergic rhinitis (AR) accompanied by adenoid hypertrophy and the effect on immune function in children. MATERIAL AND METHODS Eosinophil counts in peripheral blood before and after treatment were determined; serum levels of immunoglobulin E (IgE), total IgE (T-IgE), immunoglobulin G4 (IgG4), interleukin-2 (IL-2), and interleukin-6 (IL-6) before and after treatment were detected by enzyme-linked immunosorbent assay. RESULTS The total effective rate in the study group was significantly higher than that in the control group (P<0.05). In both the study and control groups, symptom scores, medication scores, eosinophil counts in the peripheral blood, and serum levels of IgE, T-IgE, and IL-6 were significantly lower than those before treatment (P<0.05), while the serum levels of IgG4 and IL-2 were significantly higher than those before treatment (P<0.05). After treatment, symptom scores, medication scores, eosinophil counts in the peripheral blood, and serum levels of IgE, T-IgE, and IL-6 in the study group were significantly lower than those in the control group (P<0.05), while the serum levels of IgG4 and IL-2 were significantly higher in the study group than those in the control group (P<0.05). CONCLUSIONS Sublingual administration of D. farinae drops improved the clinical symptoms of pediatric AR caused by Dermatophagoides mites and improved the immune functions in children.

New lncRNA annotation reveals extensive functional divergence of the transcriptome in maize.

Long non-coding RNAs (lncRNAs), whose sequences are approximately 200 bp or longer and unlikely to encode proteins, may play an important role in eukaryotic gene regulation. Although the latest maize (Zea mays L.) reference genome provides an essential genomic resource, genome-wide annotations of maize lncRNAs have not been updated. Here, we report on a large transcriptomic dataset collected from 749 RNA sequencing experiments across different tissues and stages of the maize reference inbred B73 line and 60 from its wild relative teosinte. We identified 18,165 high-confidence lncRNAs in maize, of which 6,873 are conserved between maize and teosinte. We uncovered distinct genomic characteristics of conserved lncRNAs, non-conserved lncRNAs, and protein-coding transcripts. Intriguingly, Shannon entropy analysis showed that conserved lncRNAs are likely to be expressed similarly to protein-coding transcripts. Co-expression network analysis revealed significant variation in the degree of co-expression. Furthermore, selection analysis indicated that conserved lncRNAs are more likely than non-conserved lncRNAs to be located in regions subject to recent selection, indicating evolutionary differentiation. Our results provide the latest genome-wide annotation and analysis of maize lncRNAs and uncover potential functional divergence between protein-coding, conserved lncRNA, and non-conserved lncRNA genes, demonstrating the high complexity of the maize transcriptome.

Intraspecific variation of residual heterozygosity and its utility for quantitative genetic studies in maize.

BACKGROUND: Residual heterozygosity (RH) in advanced inbred lines of plants benefits quantitative trait locus (QTL) mapping studies. However, knowledge of factors affecting the genome-wide distribution of RH remains limited. RESULTS: A set of 2196 heterogeneous inbred family (HIF) maize lines derived from 12 recombinant inbred line (RIL) populations was genotyped using the Maize50K SNP chip. A total of 18,615 unique RH intervals were identified, ranging from 505 to 2095 intervals per population, with average maize genome coverage of 94.8%. Across all populations, there were 8.6 RH intervals per HIF line on average, ranging from 1.8 to 14 intervals; the average size of an RH interval was approximately 58.7 Mb, ranging from 7.2 to 74.1 Mb. A given RH region was present in an average of 5 different individuals within a population. Seven RH hotspots, where RH segments were enriched in the genome, were found to be subject to selection during population development. The RH patterns varied significantly across populations, presumably reflecting differences in the genetic background of each population, and 8 QTLs were found to affect heterozygosity levels in the RH hotspots. The potential use of this HIF library for the fine mapping of QTLs was assessed based on publicly available QTL information, achieving a ≤ 1 Mb resolution on average. CONCLUSION: The examined library of HIF lines offers insight into the RH landscape and its intraspecific variation and provides a useful resource for the QTL cloning of important agronomic traits in maize.

Beyond pathways: genetic dissection of tocopherol content in maize kernels by combining linkage and association analyses.

Although tocopherols play an important role in plants and animals, the genetic architecture of tocopherol content in maize kernels has remained largely unknown. In this study, linkage and association analyses were conducted to examine the genetic architecture of tocopherol content in maize kernels. Forty-one unique quantitative trait loci (QTLs) were identified by linkage mapping in six populations of recombinant inbred lines (RILs). In addition, 32 significant loci were detected via genome-wide association study (GWAS), 18 of which colocalized with the QTLs identified by linkage mapping. Fine mapping of a major QTL validated the accuracy of GWAS and QTL mapping results and suggested a role for nontocopherol pathway genes in the modulation of natural tocopherol variation. We provided genome-wide evidence that genes involved in fatty acid metabolism, chlorophyll metabolism and chloroplast function may affect natural variation in tocopherols. These findings were confirmed through mutant analysis of a particular gene from the fatty acid pathway. In addition, the favourable alleles for many of the significant SNPs/QTLs represented rare alleles in natural populations. Together, our results revealed many novel genes that are potentially involved in the variation of tocopherol content in maize kernels. Pyramiding of the favourable alleles of the newly elucidated genes and the well-known tocopherol pathway genes would greatly improve tocopherol content in maize.

The Genetic Basis of Plant Architecture in 10 Maize Recombinant Inbred Line Populations.

Plant architecture is a key factor affecting planting density and grain yield in maize (Zea mays). However, the genetic mechanisms underlying plant architecture in diverse genetic backgrounds have not been fully addressed. Here, we performed a large-scale phenotyping of 10 plant architecture-related traits and dissected the genetic loci controlling these traits in 10 recombinant inbred line populations derived from 14 diverse genetic backgrounds. Nearly 800 quantitative trait loci (QTLs) with major and minor effects were identified as contributing to the phenotypic variation of plant architecture-related traits. Ninety-two percent of these QTLs were detected in only one population, confirming the diverse genetic backgrounds of the mapping populations and the prevalence of rare alleles in maize. The numbers and effects of QTLs are positively associated with the phenotypic variation in the population, which, in turn, correlates positively with parental phenotypic and genetic variations. A large proportion (38.5%) of QTLs was associated with at least two traits, suggestive of the frequent occurrence of pleiotropic loci or closely linked loci. Key developmental genes, which previously were shown to affect plant architecture in mutant studies, were found to colocalize with many QTLs. Five QTLs were further validated using the segregating populations developed from residual heterozygous lines present in the recombinant inbred line populations. Additionally, one new plant height QTL, qPH3, has been fine-mapped to a 600-kb genomic region where three candidate genes are located. These results provide insights into the genetic mechanisms controlling plant architecture and will benefit the selection of ideal plant architecture in maize breeding.

The Conserved and Unique Genetic Architecture of Kernel Size and Weight in Maize and Rice.

Maize (Zea mays) is a major staple crop. Maize kernel size and weight are important contributors to its yield. Here, we measured kernel length, kernel width, kernel thickness, hundred kernel weight, and kernel test weight in 10 recombinant inbred line populations and dissected their genetic architecture using three statistical models. In total, 729 quantitative trait loci (QTLs) were identified, many of which were identified in all three models, including 22 major QTLs that each can explain more than 10% of phenotypic variation. To provide candidate genes for these QTLs, we identified 30 maize genes that are orthologs of 18 rice (Oryza sativa) genes reported to affect rice seed size or weight. Interestingly, 24 of these 30 genes are located in the identified QTLs or within 1 Mb of the significant single-nucleotide polymorphisms. We further confirmed the effects of five genes on maize kernel size/weight in an independent association mapping panel with 540 lines by candidate gene association analysis. Lastly, the function of ZmINCW1, a homolog of rice GRAIN INCOMPLETE FILLING1 that affects seed size and weight, was characterized in detail. ZmINCW1 is close to QTL peaks for kernel size/weight (less than 1 Mb) and contains significant single-nucleotide polymorphisms affecting kernel size/weight in the association panel. Overexpression of this gene can rescue the reduced weight of the Arabidopsis (Arabidopsis thaliana) homozygous mutant line in the AtcwINV2 gene (Arabidopsis ortholog of ZmINCW1). These results indicate that the molecular mechanisms affecting seed development are conserved in maize, rice, and possibly Arabidopsis.

Genetic Determinants of the Network of Primary Metabolism and Their Relationships to Plant Performance in a Maize Recombinant Inbred Line Population.

Deciphering the influence of genetics on primary metabolism in plants will provide insights useful for genetic improvement and enhance our fundamental understanding of plant growth and development. Although maize (Zea mays) is a major crop for food and feed worldwide, the genetic architecture of its primary metabolism is largely unknown. Here, we use high-density linkage mapping to dissect large-scale metabolic traits measured in three different tissues (leaf at seedling stage, leaf at reproductive stage, and kernel at 15 d after pollination [DAP]) of a maize recombinant inbred line population. We identify 297 quantitative trait loci (QTLs) with moderate (86.2% of the mapped QTL, R(2) = 2.4 to 15%) to major effects (13.8% of the mapped QTL, R(2) >15%) for 79 primary metabolites across three tissues. Pairwise epistatic interactions between these identified loci are detected for more than 25.9% metabolites explaining 6.6% of the phenotypic variance on average (ranging between 1.7 and 16.6%), which implies that epistasis may play an important role for some metabolites. Key candidate genes are highlighted and mapped to carbohydrate metabolism, the tricarboxylic acid cycle, and several important amino acid biosynthetic and catabolic pathways, with two of them being further validated using candidate gene association and expression profiling analysis. Our results reveal a metabolite-metabolite-agronomic trait network that, together with the genetic determinants of maize primary metabolism identified herein, promotes efficient utilization of metabolites in maize improvement.

The genetic architecture of amino acids dissection by association and linkage analysis in maize.

Amino acids are both constituents of proteins, providing the essential nutrition for humans and animals, and signalling molecules regulating the growth and development of plants. Most cultivars of maize are deficient in essential amino acids such as lysine and tryptophan. Here, we measured the levels of 17 different total amino acids, and created 48 derived traits in mature kernels from a maize diversity inbred collection and three recombinant inbred line (RIL) populations. By GWAS, 247 and 281 significant loci were identified in two different environments, 5.1 and 4.4 loci for each trait, explaining 7.44% and 7.90% phenotypic variation for each locus in average, respectively. By linkage mapping, 89, 150 and 165 QTLs were identified in B73/By804, Kui3/B77 and Zong3/Yu87-1 RIL populations, 2.0, 2.7 and 2.8 QTLs for each trait, explaining 13.6%, 16.4% and 21.4% phenotypic variation for each QTL in average, respectively. It implies that the genetic architecture of amino acids is relative simple and controlled by limited loci. About 43.2% of the loci identified by GWAS were verified by expression QTL, and 17 loci overlapped with mapped QTLs in the three RIL populations. GRMZM2G015534, GRMZM2G143008 and one QTL were further validated using molecular approaches. The amino acid biosynthetic and catabolic pathways were reconstructed on the basis of candidate genes proposed in this study. Our results provide insights into the genetic basis of amino acid biosynthesis in maize kernels and may facilitate marker-based breeding for quality protein maize.

Combining Quantitative Genetics Approaches with Regulatory Network Analysis to Dissect the Complex Metabolism of the Maize Kernel.

Metabolic quantitative trait locus (QTL) studies have allowed us to better understand the genetic architecture underlying naturally occurring plant metabolic variance. Here, we use two recombinant inbred line (RIL) populations to dissect the genetic architecture of natural variation of 155 metabolites measured in the mature maize (Zea mays) kernel. Overall, linkage mapping identified 882 metabolic QTLs in both RIL populations across two environments, with an average of 2.1 QTLs per metabolite. A large number of metabolic QTLs (more than 65%) were identified with moderate effects (r(2) = 2.1%-10%), while a small portion (less than 35%) showed major effects (r(2) > 10%). Epistatic interactions between these identified loci were detected for more than 30% of metabolites (with the proportion of phenotypic variance ranging from 1.6% to 37.8%), implying that genetic epistasis is not negligible in determining metabolic variation. In total, 57 QTLs were validated by our previous genome-wide association study on the same metabolites that provided clues for exploring the underlying genes. A gene regulatory network associated with the flavonoid metabolic pathway was constructed based on the transcriptional variations of 28,769 genes in kernels (15 d after pollination) of 368 maize inbred lines. A large number of genes (34 of 58) in this network overlapped with previously defined genes controlled by maize PERICARP COLOR1, while three of them were identified here within QTL intervals for multiple flavonoids. The deeply characterized RIL populations, elucidation of metabolic phenotypes, and identification of candidate genes lay the foundation for maize quality improvement.