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In plant, APETALA2/ethylene‐responsive factor (AP2/ERF)‐domain transcription factors are important in regulating abiotic stress tolerance. In this study, ZmEREB57 encoding a AP2/ERF transcription factor was identified and its function was investigated in maize. ZmEREB57 is a nuclear protein with transactivation activity induced by several abiotic stress types. Furthermore, two CRISPR/Cas9 knockout lines of ZmEREB57 showed enhanced sensitivity to saline conditions, whereas the overexpression of ZmEREB57 increased salt tolerance in maize and Arabidopsis. DNA affinity purification sequencing (DAP‐Seq) analysis revealed that ZmEREB57 notably regulates target genes by binding to promoters containing an O‐box‐like motif (CCGGCC). ZmEREB57 directly binds to the promoter of ZmAOC2 involved in the synthesis of 12‐oxo‐phytodienoic acid (OPDA) and jasmonic acid (JA). Transcriptome analysis revealed that several genes involved in regulating stress and redox homeostasis showed differential expression patterns in OPDA‐ and JA‐treated maize seedlings exposed to salt stress compared to those treated with salt stress alone. Analysis of mutants deficient in the biosynthesis of OPDA and JA revealed that OPDA functions as a signalling molecule in the salt response. Our results indicate that ZmEREB57 involves in salt tolerance by regulating OPDA and JA signalling and confirm early observations that OPDA signalling functions independently of JA signalling. SUMMARY STATEMENT: As an important cereal crop worldwide, however, the yield and quality of maize are severely affected by salt stress. This study identified that ZmEREB57, a AP2/ERF transcription factor, contributes to salt tolerance in maize. The ZmEREB57‐mediated salt stress response can be achieved by binding to the ZmAOC2 promoter, which is a positive regulator of OPDA biosynthesis. Although as being a precursor for JA synthesis, OPDA functions independently of JA as a signalling molecule in the salt response. [ABSTRACT FROM AUTHOR]

Southern corn leaf blight (SCLB) seriously threatens corn production. The timely and accurate monitoring of SCLB conditions (e.g., detection during the asymptomatic stage and severity classification during the symptomatic stage) is valuable for precision agriculture, because the application of pesticides depends on disease conditions. Compared with time-consuming and laborious field surveys, spectroscopy is a promising tool for plant disease monitoring. The unique advantages of combining multiple spectral enhancement features for monitoring rice and wheat diseases have been recognized. However, physiological and biochemical differences between maize leaves and rice and wheat leaves, along with the specific spectral response of SCLB, are likely to affect the performance of combining multiple spectral enhancement features. In addition, similar previous studies have not combined spectral slope features, i.e., first-order spectral derivatives (FSDs), with spectral bands (SBs) and spectral indices (SIs) and wavelet features (WFs) to improve plant disease detection. Thus, the performance of a method that combines FSDs, WFs, SBs, and SIs for SCLB asymptomatic detection, symptomatic detection, and symptomatic severity classification should be evaluated further. Here, the utility of combining SBs, SIs, WFs, and FSDs was quantified and evaluated in the asymptomatic detection, symptomatic detection, and symptomatic severity classification of SCLB. Various forms of spectral enhancement features that were sensitive to SCLB infection from the asymptomatic stage to the severe stage were first identified and combined using the RELIEF-F and sequential floating forward selection algorithms on the basis of two independent inoculation experiments. Finally, SCLB asymptomatic detection, symptomatic detection, and symptomatic severity classification models were developed and evaluated using the support vector machine algorithm. Results showed that combining FSDs with SBs, SIs, and WFs achieved the best performance in SCLB spectroscopic monitoring. (1) SCLB asymptomatic detection and symptomatic detection were moderately improved, i.e., overall accuracy (OA) and macro F1 (MF1) improved by ~ 1% to 2%. The OA of SCLB asymptomatic detection was 87.1% with an MF1 of 0.87, and that of symptomatic detection was 93.1% with an MF1 of 0.93. (2) SCLB symptomatic severity classification was significantly improved, i.e., OA and MF1 improved by ~ 7%. The OA of severity classification was 81.8% with am MF1 of 0.82. This study demonstrated that the complementary relationships among SBs, SIs, WFs, and FSDs could effectively improve SCLB spectroscopic monitoring. The proposed method provides a novel tool for large-scale SCLB spectroscopic monitoring. It has broad implications for assisting management decisions (i.e., when and where to apply pesticides and how much to apply) in precision agriculture. [ABSTRACT FROM AUTHOR]

Summary: 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. [ABSTRACT FROM AUTHOR]

Summary: Ear length (EL), which is controlled by quantitative trait loci (QTLs), is an important component of grain yield and as such is a key target trait in maize breeding. However, very few EL QTLs have been cloned, and their molecular mechanisms are largely unknown.Here, using a genome wide association study (GWAS), we identified a QTL, YIGE1, which encodes an unknown protein that regulates EL by affecting pistillate floret number. Overexpression of YIGE1 increased female inflorescence meristem (IM) size, increased EL and kernel number per row (KNPR), and thus enhanced grain yield. By contrast, CRISPR/Cas9 knockout and Mutator insertion mutant lines of YIGE1 displayed decreased IM size and EL.A single‐nucleotide polymorphism (SNP) located in the regulatory region of YIGE1 had a large effect on its promoter strength, which positively affected EL by increasing gene expression. Further analysis shows that YIGE1 may be involved in sugar and auxin signal pathways to regulate maize ear development, thus affecting IM activity and floret production in maize inflorescence morphogenesis.These findings provide new insights into ear development and will ultimately facilitate maize molecular breeding. See also the Commentary on this article by Cowling & Kelley, 234: 337–339. [ABSTRACT FROM AUTHOR]

The employment of doubled-haploid (DH) technology in maize has vastly accelerated the efficiency of developing inbred lines. The selection of superior lines has to rely on genotypes with genomic selection (GS) model, rather than phenotypes due to the high expense of field phenotyping. In this work, we implemented 'genome optimization via virtual simulation (GOVS)' using the genotype and phenotype data of 1404 maize lines and their F1 progeny. GOVS simulates a virtual genome encompassing the most abundant 'optimal genotypes' or 'advantageous alleles' in a genetic pool. Such a virtually optimized genome, although can never be developed in reality, may help plot the optimal route to direct breeding decisions. GOVS assists in the selection of superior lines based on the genomic fragments that a line contributes to the simulated genome. The assumption is that the more fragments of optimal genotypes a line contributes to the assembly, the higher the likelihood of the line favored in the F1 phenotype, e.g. grain yield. Compared to traditional GS method, GOVS-assisted selection may avoid using an arbitrary threshold for the predicted F1 yield to assist selection. Additionally, the selected lines contributed complementary sets of advantageous alleles to the virtual genome. This feature facilitates plotting the optimal route for DH production, whereby the fewest lines and F1 combinations are needed to pyramid a maximum number of advantageous alleles in the new DH lines. In summary, incorporation of DH production, GS and genome optimization will ultimately improve genomically designed breeding in maize. Short abstract: Doubled-haploid (DH) technology has been widely applied in maize breeding industry, as it greatly shortens the period of developing homozygous inbred lines via bypassing several rounds of self-crossing. The current challenge is how to efficiently screen the large volume of inbred lines based on genotypes. We present the toolbox of genome optimization via virtual simulation (GOVS), which complements the traditional genomic selection model. GOVS simulates a virtual genome encompassing the most abundant 'optimal genotypes' in a breeding population, and then assists in selection of superior lines based on the genomic fragments that a line contributes to the simulated genome. Availability of GOVS (https://govs-pack.github.io/) to the public may ultimately facilitate genomically designed breeding in maize. [ABSTRACT FROM AUTHOR]

Summary: Low grain moisture at harvest is crucial for safe production, transport and storage, but the genetic architecture of this trait in maize (Zea mays) remains elusive. Here, we measured the dynamic changes in grain moisture content in an association‐mapping panel of 513 diverse maize inbred lines at five successive stages across five geographical environments. Genome‐wide association study (GWAS) revealed 71 quantitative trait loci (QTLs) that influence grain moisture in maize. Epistatic effects play vital roles in the variability in moisture levels, even outperforming main‐effect QTLs during the early dry‐down stages. Distinct QTL–environment interactions influence the spatio‐temporal variability of maize grain moisture, which is primarily triggered at specific times. By combining genetic population analysis, transcriptomic profiling and gene editing, we identified GRMZM5G805627 and GRMZM2G137211 as candidate genes underlying major QTLs for grain moisture in maize. Our results provide insights into the genetic architecture of dynamic changes in grain moisture, which should facilitate maize breeding. [ABSTRACT FROM AUTHOR]

Summary: Tassel branch number (TBN) is one of the important agronomic traits that directly contribute to grain yield in maize (Zea mays L.), and identification of genes precisely regulating TBN in the parental lines is important for maize hybrid breeding. In this study, a quantitative trait nucleotide (QTN), QDtbn1, related to tassel branch number was identified using a testcrossing association mapping population through association mapping with the Indels/SNPs in the 5′‐UTR (untranslated region) of Zm00001d053358, which encodes a Kelch repeat‐containing F‐box protein. QDtbn1 was further confirmed to be associated with TBN by a dominant model using an F2 population, and over‐expressing of the candidate gene resulted in a decreasing of TBN, implying that QDtbn1 was governed by the candidate gene with a negative model. This makes QDtbn1 very useful in maize hybrid breeding. QDtbn1 could interact with a maize Skp1‐like protein and a SnRK1 protein, and the SnRK1 could also interact with a SnRK2.8 protein. In addition, quantitative real‐time PCR assay showed that five substrates of SnRK2 were down‐regulated in the over‐expressed plants. These imply that the SCF (Skp1/Cul1/F‐box protein/Roc1) complex and ABA signal pathway might be involved in the modulation of TBN in maize. [ABSTRACT FROM AUTHOR]

Plant phenotypic plasticity describes altered phenotypic performance of an individual when grown in different environments. Exploring genetic architecture underlying plant plasticity variation may help mitigate the detrimental effects of a rapidly changing climate on agriculture, but little research has been done in this area to date. In the present study, we established a population of 976 maize F1 hybrids by crossing 488 diverse inbred lines with two elite testers. Genome-wide association study identified hundreds of quantitative trait loci associated with phenotypic plasticity variation across diverse F1 hybrids, the majority of which contributed very little variance, in accordance with the polygenic nature of these traits. We identified several quantitative trait locus regions that may have been selected during the tropical-temperate adaptation process. We also observed heterosis in terms of phenotypic plasticity, in addition to the traditional genetic value differences measured between hybrid and inbred lines, and the pattern of which was affected by genetic background. Our results demonstrate a landscape of phenotypic plasticity in maize, which will aid in the understanding of its genetic architecture, its contribution to adaptation and heterosis, and how it may be exploited for future maize breeding in a rapidly changing environment. [ABSTRACT FROM AUTHOR]

In this study, based on automatic control and image processing, a high-throughput and low-cost maize ear traits scorer (METS) was developed for the automatic measurement of 34 maize ear traits. In total, 813 maize ears were measured using METS, and the results showed that the square of the correlation coefficient (R2) of the manual measurements versus the automatic measurements for ear length, ear diameter, and kernel thickness were 0.96, 0.79, and 0.85, respectively. These maize ear traits could be used to classify the type, and the results showed that the classification accuracy of the support vector machine (SVM) model for the test set was better than that of the random forest (RF) model. In addition, the general applicability of the image analysis pipeline was also demonstrated on other independent maize ear phenotyping platforms. In conclusion, equipped with image processing and automatic control technologies, we have developed a high-throughput method for maize ear scoring, which could be popularized in maize functional genetics, genomics, and breeding applications. [ABSTRACT FROM AUTHOR]

SUMMARY: Metabolites are the intermediate and final products of metabolism, which play essential roles in plant growth, evolution and adaptation to changing climates. However, it is unclear how evolution contributes to metabolic variation in plants. Here, we investigated the metabolomics data from leaf and seed tissues in maize and rice. Using principal components analysis based on leaf metabolites but not seed metabolites, metabolomics data could be clearly separated for rice Indica and Japonica accessions, while two maize subgroups, temperate and tropical, showed more visible admixture. Rice and maize seed exhibited significant interspecific differences in metabolic variation, while within rice, leaf and seed displayed similar metabolic variations. Among 10 metabolic categories, flavonoids had higher variation in maize than rice, indicating flavonoids are a key constituent of interspecific metabolic divergence. Interestingly, metabolic regulation was also found to be reshaped dramatically from positive to negative correlations, indicative of the differential evolutionary processes in maize and rice. Moreover, perhaps due to this divergence significantly more metabolic interactions were identified in rice than maize. Furthermore, in rice, the leaf was found to harbor much more intense metabolic interactions than the seed. Our result suggests that metabolomes are valuable for tracking evolutionary history, thereby complementing and extending genomic insights concerning which features are responsible for interspecific differentiation in maize and rice. Significance Statement: Metabolites are the intermediate and final products of metabolism, which play essential roles in plant growth, evolution and adaptation to changing climates, but it is unclear how evolution contributes to metabolic variation in plants. We investigated the metabolomics data from leaf and seed tissues in maize and rice, and our result suggests that metabolomes are valuable for tracking evolutionary history, thereby complementing and extending genomic insights concerning which features are responsible for interspecific differentiation in maize and rice. [ABSTRACT FROM AUTHOR]

Summary: Traditional genetic studies focus on identifying genetic variants associated with the mean difference in a quantitative trait. Because genetic variants also influence phenotypic variation via heterogeneity, we conducted a variance‐heterogeneity genome‐wide association study to examine the contribution of variance heterogeneity to oil‐related quantitative traits. We identified 79 unique variance‐controlling single nucleotide polymorphisms (vSNPs) from the sequences of 77 candidate variance‐heterogeneity genes for 21 oil‐related traits using the Levene test (P < 1.0 × 10−5). About 30% of the candidate genes encode enzymes that work in lipid metabolic pathways, most of which define clear expression variance quantitative trait loci. Of the vSNPs specifically associated with the genetic variance heterogeneity of oil concentration, 89% can be explained by additional linked mean‐effects genetic variants. Furthermore, we demonstrated that gene × gene interactions play important roles in the formation of variance heterogeneity for fatty acid compositional traits. The interaction pattern was validated for one gene pair (GRMZM2G035341 and GRMZM2G152328) using yeast two‐hybrid and bimolecular fluorescent complementation analyses. Our findings have implications for uncovering the genetic basis of hidden additive genetic effects and epistatic interaction effects, and we indicate opportunities to stabilize efficient breeding and selection of high‐oil maize (Zea mays L.). Significance Statement: This work validated the additive manner in which oil concentration is inherited, and can be used to guide the selection of haplotypes for improvement of oil concentration even with low phenotypic variability. However, gene × gene interaction plays a major role in the formation of variance heterogeneity of fatty acid compositional traits, which will allow modification of breeding selection plans to achieve the most efficient means of creating maize lines with the desired fatty acids. [ABSTRACT FROM AUTHOR]

MaizeCUBIC is a free database that describes genomic variations, gene expression, phenotypes and quantitative trait locus (QTLs) for a maize CUBIC population (24 founders and 1404 inbred offspring). The database not only includes information for over 14M single nucleotide polymorphism (SNPs) and 43K indels previously identified but also contains 660K structure variations (SVs) and 600M novel sequences newly identified in the present study, which represents a comprehensive high-density variant map for a diverse population. Based on these genomic variations, the database would demonstrate the mosaic structure for each progeny, reflecting a high-resolution reshuffle across parental genomes. A total of 23 agronomic traits measured on parents and progeny in five locations, where are representative of the maize main growing regions in China, were also included in the database. To further explore the genotype–phenotype relationships, two different methods of genome-wide association studies (GWAS) were employed for dissecting the genetic architecture of 23 agronomic traits. Additionally, the Basic Local Alignment Search Tool and primer design tools are developed to promote follow-up analysis and experimental verification. All the original data and corresponding analytical results can be accessed through user-friendly online queries and web interface dynamic visualization, as well as downloadable files. These data and tools provide valuable resources on genetic and genomic studies of maize and other crops. [ABSTRACT FROM AUTHOR]

Mining novel kernel size-related genes by pQTL mapping and multi-omics integrative analysis in developing maize kernels The results reveal that the transcript level alone does not always reliably predict protein abundance at the population scale, and protein abundance variation may play an important role in orchestrating the biological functions of genes involved in the same biological pathways. Keywords: proteomics; protein quantitative trait locus; multi-omics integration; kernel-related traits; maize EN proteomics protein quantitative trait locus multi-omics integration kernel-related traits maize 1489 1491 3 08/26/21 20210801 NES 210801 As a sink organ for starch, protein, oil and essential nutrients, the maize ( I Zea mays i ) kernel is not only the main target for yield and quality improvement but also a model system for genetic and molecular biology studies. [Extracted from the article]

CRISPR/Cas9, Genome-editing, Fluorescence protein, Visualization, Zea mays Keywords: CRISPR/Cas9; Genome-editing; Fluorescence protein; Visualization; Zea mays EN CRISPR/Cas9 Genome-editing Fluorescence protein Visualization Zea mays 872 874 3 05/20/21 20210501 NES 210501 The emerging and promising biotechnology methodology of CRISPR/Cas9 gene editing is revolutionizing crop improvement. [Extracted from the article]

Summary: 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. Significance Statement: Known as vitamin E, tocopherol is a lipid‐soluble antioxidant required for plant growth and human health. In this study, characterization of ZmPORB2 involved in chlorophyll metabolism revealed that this gene affects tocopherol content in maize by the maternal genotype and has applicable potential in breeding. [ABSTRACT FROM AUTHOR]

Summary: 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 BC2F7 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. Significance Statement: A large scale QTL mapping of primary metabolite traits in a teosinte‐maize population reveals robust advantages existing in teosinte primary metabolism. [ABSTRACT FROM AUTHOR]

Summary: Maize (Zea mays mays) oil is a rich source of polyunsaturated fatty acids (FAs) and energy, making it a valuable resource for human food, animal feed, and bio‐energy. Although this trait has been studied via conventional genome‐wide association study (GWAS), the single nucleotide polymorphism (SNP)‐trait associations generated by GWAS may miss the underlying associations when traits are based on many genes, each with small effects that can be overshadowed by genetic background and environmental variation. Detecting these SNPs statistically is also limited by the levels set for false discovery rate. A complementary pathways analysis that emphasizes the cumulative aspects of SNP‐trait associations, rather than just the significance of single SNPs, was performed to understand the balance of lipid metabolism, conversion, and catabolism in this study. This pathway analysis indicated that acyl‐lipid pathways, including biosynthesis of wax esters, sphingolipids, phospholipids and flavonoids, along with FA and triacylglycerol (TAG) biosynthesis, were important for increasing oil and FA content. The allelic variation found among the genes involved in many degradation pathways, and many biosynthesis pathways leading from FAs and carbon partitioning pathways, was critical for determining final FA content, changing FA ratios and, ultimately, to final oil content. The pathways and pathway networks identified in this study, and especially the acyl‐lipid associated pathways identified beyond what had been found with GWAS alone, provide a real opportunity to precisely and efficiently manipulate high‐oil maize genetic improvement. Significance Statement: This pathway analysis provided insights into the genetic basis of lipid metabolism, beyond what could be detected via GWAS alone, and indicated specific opportunities to precisely and efficiently manipulate high‐oil maize genetic improvement. [ABSTRACT FROM AUTHOR]

Summary: Maize is the cereal crop with the highest production worldwide, and its oil is a key energy resource. Improving the quantity and quality of maize oil requires a better understanding of lipid metabolism. To predict the function of maize genes involved in lipid biosynthesis, we assembled transcriptomic and lipidomic data sets from leaves of B73 and the high‐oil line By804 in two distinct time‐series experiments. The integrative analysis based on high‐dimensional regularized regression yielded lipid–transcript associations indirectly validated by Gene Ontology and promoter motif enrichment analyses. The co‐localization of lipid‐transcript associations using the genetic mapping of lipid traits in leaves and seedlings of a B73 × By804 recombinant inbred line population uncovered 323 genes involved in the metabolism of phospholipids, galactolipids, sulfolipids and glycerolipids. The resulting association network further supported the involvement of 50 gene candidates in modulating levels of representatives from multiple acyl‐lipid classes. Therefore, the proposed approach provides high‐confidence candidates for experimental testing in maize and model plant species. [ABSTRACT FROM AUTHOR]

Genome information from model species such as rice can assist in the cloning of genes in a complex genome, such as maize. Here, we identified a maize ortholog of rice GS5 that contributes to kernel development in maize. The genome-wide association analysis of the expression levels of ZmGS5, and 15 of its 26 paralogs, identified a trans-regulator on chromosome 7, which was a BAK1-like gene. This gene that we named as ZmBAK1-7 could regulate the expression of ZmGS5 and three of the paralogs. Candidate-gene association analyses revealed that these five genes were associated with maize kernel development-related traits. Linkage analyses also detected that ZmGS5 and ZmBAK1-7 co-localized with mapped QTLs. A transgenic analysis of ZmGS5 in Arabidopsis thaliana L. showed a significant increase in seed weight and cell number, suggesting that ZmGS5 may have a conserved function among different plant species that affects seed development. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

The worldwide production of maize (Zea mays L.) is frequently impacted by water scarcity and as a result, increased drought tolerance is a priority target in maize breeding programs. While DREB transcription factors have been demonstrated to play a central role in desiccation tolerance, whether or not natural sequence variations in these genes are associated with the phenotypic variability of this trait is largely unknown. In the present study, eighteen ZmDREB genes present in the maize B73 genome were cloned and systematically analyzed to determine their phylogenetic relationship, synteny with rice, maize and sorghum genomes; pattern of drought-responsive gene expression, and protein transactivation activity. Importantly, the association between the nucleic acid variation of each ZmDREB gene with drought tolerance was evaluated using a diverse population of maize consisting of 368 varieties from tropical and temperate regions. A significant association between the genetic variation of ZmDREB2.7 and drought tolerance at seedling stage was identified. Further analysis found that the DNA polymorphisms in the promoter region of ZmDREB2.7, but not the protein coding region itself, was associated with different levels of drought tolerance among maize varieties, likely due to distinct patterns of gene expression in response to drought stress. In vitro, protein-DNA binding assay demonstrated that ZmDREB2.7 protein could specifically interact with the target DNA sequences. The transgenic Arabidopsis overexpressing ZmDREB2.7 displayed enhanced tolerance to drought stress. Moreover, a favorable allele of ZmDREB2.7, identified in the drought-tolerant maize varieties, was effective in imparting plant tolerance to drought stress. Based upon these findings, we conclude that natural variation in the promoter of ZmDREB2.7 contributes to maize drought tolerance, and that the gene and its favorable allele may be an important genetic resource for the genetic improvement of drought tolerance in maize. [ABSTRACT FROM AUTHOR]

To investigate the genetic basis of maize seedling response to waterlogging, we performed a genome-wide association study in 144 maize inbred lines, measuring length, fresh and dry weight of roots and shoots under normal and waterlogged conditions using 45,868 SNPs. This panel was divided into three subgroups based on the population structure results and the LD decay distance was 180 kb. A biparental advanced backcross (AB) population was also used to detect quantitative trait loci (QTL). In a comparison of 16 different models, principal components analysis (PCA/top PC3) + K was found to be best for reduction of false-positive associations for further analysis. A whole-genome scan detected four strong peak signals ( P < 2.18 × 10) significantly associated with the waterlogging response on chromosomes 5, 6 and 9. SNP4784, SNP200, SNP298, and SNP6314 showed significant association with corresponding traits under waterlogging and explained 14.99-19.36 %, 15.75-17.64 %, 16.08 % and 15.44 % of the phenotypic variation, respectively. The identified SNPs were located in GRMZM2G012046, GRMZM2G009808, GRMZM2G137108 and GRMZM2G369629 (AGPV1). SNP4784 (GRMZM2G012046) was colocalized with the major QTL that was identified with the same traits in the AB population. Forty-seven SNPs significantly associated ( P < 2.18 × 10) with six traits in association mapping were identified and, among these, 33 SNPs were already reported in literature as waterlogging-related traits. These results will help elucidate the genetic basis of differential responses and tolerance to waterlogging stress among maize inbred lines, and provide novel loci for improvement of waterlogging tolerance of maize inbred lines using marker-assisted selection. [ABSTRACT FROM AUTHOR]

α-carotene is one of the important components of pro-vitamin A, which is able to be converted into vitamin A in the human body. One maize ( Zea mays L.) ortholog of carotenoid hydroxylases in Arabidopsis thaliana, ZmcrtRB3, was cloned and its role in carotenoid hydrolyzations was addressed. ZmcrtRB3 was mapped in a quantitative trait locus (QTL) cluster for carotenoid-related traits on chromosome 2 (bin 2.03) in a recombinant inbred line (RIL) population derived from By804 and B73. Candidate-gene association analysis identified 18 polymorphic sites in ZmcrtRB3 significantly associated with one or more carotenoid-related traits in 126 diverse yellow maize inbred lines. These results indicate that the enzyme ZmcrtRB3 plays a role in hydrolyzing both α- and β-carotenes, while polymorphisms in ZmcrtRB3 contributed more variation in α-carotene than that in β-carotene. Two single nucleotide polymorphisms (SNPs), SNP1343 in 5′untranslated region and SNP2172 in the second intron, consistently had effects on α-carotene content and composition with explained phenotypic variations ranging from 8.7% to 34.8%. There was 1.7- to 3.7-fold change between the inferior and superior haplotype for α-carotene content and composition. Thus, SNP1343 and SNP2172 are potential polymorphic sites to develop functional markers for applying marker-assisted selection in the improvement of pro-vitamin A carotenoids in maize kernels. [ABSTRACT FROM AUTHOR]

The organization of maize ( Zea mays L.) germplasm into genetically divergent heterotic groups is the foundation of a successful hybrid maize breeding program. In this study, 94 CIMMYT maize lines (CMLs) and 54 United States germplasm enhancement of maize (GEM) lines were assembled and characterized using 1,266 single nucleotide polymorphisms (SNPs) with high quality. Based on principal component analysis (PCA), the GEM lines and CMLs were clearly separated. In the GEM lines, there were two groups classified by PCA corresponding to the heterotic groups 'stiff stalk' and 'non-stiff stalk'. CMLs did not form obvious subgroups by PCA. The allelic frequency of each SNP differed in GEM lines and CMLs. In total, 3.6% alleles (46/1,266) of CMLs are absent in GEM lines and 4.4% alleles (56/1,266) of GEM lines are absent in CMLs. The performance of F1 plants ( n = 654) produced by crossing between different groups based on pedigree information was evaluated at the breeding nurseries of two CIMMYT stations. Genomic estimated phenotypic values of plant height and days to anthesis for a testing set of 45 F1 crosses were predicted based on the training data of 600 F1 crosses using a best linear unbiased prediction method. The prediction accuracy benefitted from the adoption of the markers associated with quantitative trait loci for both traits; however, it does not necessarily increase with an increase in marker density. It is suggested that genomic selection combined with association analysis could improve prediction efficiency and reduce cost. For hybrid maize breeding in the tropics, incorporating GEM lines which have unique alleles and clear heterotic patterns into tropically adapted lines could be beneficial for enhancing heterosis in grain yields. [ABSTRACT FROM AUTHOR]

The gene encoding acyl-CoA:diacylglycerol acyltransferase ( DGAT1- 2) is a key quantitative trait locus that controls oil content and oleic acid composition in maize kernels. Here we re-sequenced the DGAT1- 2 region responsible for oil variation in a maize landrace set and in 155 inbred lines (35 high-oil and 120 normal lines). The high-oil DGAT1- 2 allele was present in most Northern Flint and Southern Dent populations but was absent in five of eight Corn Belt Dent open-pollinated populations and in most of the earlier inbred lines. Loss of the high-oil DGAT1- 2 allele possibly resulted from genetic drift in the early twentieth century when a few Corn Belt Dent populations were selected for the development of high-grain-yield inbred lines. Association analysis detected significant effects of two PCR-based functional markers (HO06 and DGAT04; developed based on DGAT1- 2 polymorphisms) on kernel oil content and oleic acid composition using the 155 inbred lines. Zheng58 and Chang7-2, the parent inbred lines of elite hybrid Zhengdan958, were used to transfer the favorable allele from the high-oil line By804 using marker-assisted backcrossing with the two functional markers. In BC5F2:3 populations, oil content of the three genotypes (−/−, +/−, and +/+) was, respectively, 3.37, 4.20, and 4.61% (Zheng58 recipient line) and 4.14, 4.67, and 5.25% (Chang7-2 recipient line). Oil content of homozygous kernels containing the high-oil DGAT1- 2 allele increased by 27-37% compared with recurrent parents. Hence, these functional markers can be used to re-introduce the high-oil DGAT1- 2 allele into modern inbred lines for increased oil content through marker-assisted backcrossing. [ABSTRACT FROM AUTHOR]

Studies plant height in maize, an important agronomic and model trait that is suitable for studying developmental biology. Use of data from locations in Wuhan and Xiangfan and a molecular linkage map covering 10 chromosomes; Analysis of QTLs affecting plant height at five different developmental stages by the combination of composite interval mapping and the conditional analysis method; Number of QTLs located at different regions of five chromosomes; Finding that there were different QTL effect values on plant height at various developmental stages; Indication that three QTLs were detected at all five stages; Suggestion that QTL expression varied at different stages; Detection of seven conditional QTLs for plant height; Indication that QTLs for plant height are expressed in different time-space; Implication for marker assistant selection when conducted for quantitative traits.

Maize (Zea mays) is one of the most widely grown crops in the world, with an annual global production of over 1147 million tons. Genomics approaches are thought to be the best solution for accelerating yield improvement to meet the challenges of a growing population and global climate change. Here, we review current approaches to the exploration of novel genetic variation in genomes, DNA modifications, and transcription levels of cultivated maize, landraces, and wild relatives. We discuss applications of genetic engineering to maize yield improvement and highlight future directions for maize genomics studies. [ABSTRACT FROM AUTHOR]

Southern Corn Rust (SCR) is one of the most destructive diseases in corn production, significantly affecting corn quality and yields globally. Field-based fast, nondestructive diagnosis of SCR is critical for smart agriculture applications to reduce pesticide use and ensure food safety. The development of spectral disease indices (SDIs), based on in situ leaf reflectance spectra, has proven to be an effective method in detecting plant diseases in the field. However, little is known about leaf spectral signatures that can assist in the accurate diagnosis of SCR, and no SDIs-based model has been reported for the field-based SCR monitoring. Here, to address those issues, we developed SDIs-based monitoring models to detect SCR-infected leaves and classify SCR damage severity. In detail, we first collected in situ leaf reflectance spectra (350–2500 nm) of healthy and infected corn plants with three severity levels (light, medium, and severe) using a portable spectrometer. Then, the RELIEF-F algorithm was performed to select the most discriminative features (wavelengths) and two band normalized differences for developing SDIs (i.e., health index and severity index) in SCR detection and severity classification, respectively. The leaf reflectance spectra, most sensitive to SCR detection and severity classification, were found in the 572 nm, 766 nm, and 1445 nm wavelength and 575 nm, 640 nm, and 1670 nm wavelength, respectively. These spectral features were associated with leaf pigment and leaf water content. Finally, by employing a support vector machine (SVM), the performances of developed SCR-SDIs were assessed and compared with 38 stress-related vegetation indices (VIs) identified in the literature. The SDIs-based models developed in this study achieved an overall accuracy of 87% and 70% in SCR detection and severity classification, 1.1% and 8.3% higher than the other best VIs-based model under study, respectively. Our results thus suggest that the SCR-SDIs is a promising tool for fast, nondestructive diagnosis of SCR in the field over large areas. To our knowledge, this study represents one of the first few efforts to provide a theoretical basis for remote sensing of SCR at field and larger scales. With the increasing use of unmanned aerial vehicles (UAVs) with hyperspectral measurement capability, more studies should be conducted to expand our developed SCR-SDIs for SCR monitoring at different study sites and growing stages in the future. [ABSTRACT FROM AUTHOR]

Alternative splicing (AS) enhances transcriptome diversity and plays important roles in regulating plant processes. Although widespread natural variation in AS has been observed in plants, how AS is regulated and contribute to phenotypic variation is poorly understood. Here, we report a population-level transcriptome assembly and genome-wide association study to identify splicing quantitative trait loci (sQTLs) in developing maize (Zea mays) kernels from 368 inbred lines. We detected 19,554 unique sQTLs for 6570 genes. Most sQTLs showed small isoform usage changes without involving major isoform switching between genotypes. The sQTL-affected isoforms tend to display distinct protein functions. We demonstrate that nonsense-mediated mRNA decay, microRNA-mediated regulation, and small interfering peptide-mediated peptide interference are frequently involved in sQTL regulation. The natural variation in AS and overall mRNA level appears to be independently regulated with different cis -sequences preferentially used. We identified 214 putative trans -acting splicing regulators, among which ZmGRP1 , encoding an hnRNP-like glycine-rich RNA binding protein, regulates the largest trans -cluster. Knockout of ZmGRP1 by CRISPR/Cas9 altered splicing of numerous downstream genes. We found that 739 sQTLs colocalized with previous marker-trait associations, most of which occurred without changes in overall mRNA level. Our findings uncover the importance of AS in diversifying gene function and regulating phenotypic variation. [ABSTRACT FROM AUTHOR]

Maize kernel traits such as kernel length, kernel width and kernel number determine kernel weight and, consequently, maize yield. Therefore, the measurement of kernel traits is important for maize breeding and the evaluation of maize yield. The conventional method for measuring kernel traits is still manual, which is time consuming, costly and subjective. In this study, a novel maize kernel traits scorer (MKTS) was developed for the automatic measurement of 12 maize kernel traits based on line-scan imaging, image processing, and automatic control techniques. Here, total of 615 samples were measured to evaluate the system performance. The results showed that the MKTS was capable of evaluating maize kernel traits with the mean absolute percentage error of the manual and automatic measurements less than 5% and the measurement efficiency of approximately 72 s for the measurement of 6 ears. In conclusion, this high-throughput scorer will provide maize scientists with a novel tool to assist in maize functional genetics and maize breeding. [ABSTRACT FROM AUTHOR]

α-carotene is one of the important components of pro-vitamin A, which is able to be converted into vitamin A in the human body. One maize ( Zea mays L.) ortholog of carotenoid hydroxylases in Arabidopsis thaliana, ZmcrtRB3, was cloned and its role in carotenoid hydrolyzations was addressed. ZmcrtRB3 was mapped in a quantitative trait locus (QTL) cluster for carotenoid-related traits on chromosome 2 (bin 2.03) in a recombinant inbred line (RIL) population derived from By804 and B73. Candidate-gene association analysis identified 18 polymorphic sites in ZmcrtRB3 significantly associated with one or more carotenoid-related traits in 126 diverse yellow maize inbred lines. These results indicate that the enzyme ZmcrtRB3 plays a role in hydrolyzing both α- and β-carotenes, while polymorphisms in ZmcrtRB3 contributed more variation in α-carotene than that in β-carotene. Two single nucleotide polymorphisms (SNPs), SNP1343 in 5′untranslated region and SNP2172 in the second intron, consistently had effects on α-carotene content and composition with explained phenotypic variations ranging from 8.7% to 34.8%. There was 1.7- to 3.7-fold change between the inferior and superior haplotype for α-carotene content and composition. Thus, SNP1343 and SNP2172 are potential polymorphic sites to develop functional markers for applying marker-assisted selection in the improvement of pro-vitamin A carotenoids in maize kernels. [ABSTRACT FROM AUTHOR]