Genome-Wide Association Implicates Candidate Genes Conferring Resistance to Maize Rough Dwarf Disease in Maize

Genome-wide association study of maize resistance to Pythium aristosporum stalk rot

Stalk rot, a severe and widespread soil-borne disease in maize, globally reduces yield and quality. Recent documentation reveals that Pythium aristosporum has emerged as one of the dominant causal agents of maize stalk rot. However, a previous study of maize stalk rot disease resistance mechanisms and breeding had mainly focused on other pathogens, neglecting P. aristosporum. To mitigate crop loss, resistance breeding is the most economical and effective strategy against this disease. This study involved characterizing resistance in 295 inbred lines using the drilling inoculation method and genotyping them via sequencing. By combining with population structure, disease resistance phenotype, and genome-wide association study (GWAS), we identified 39 significant single-nucleotide polymorphisms (SNPs) associated with P. aristosporum stalk rot resistance by utilizing six statistical methods. Bioinformatics analysis of these SNPs revealed 69 potential resistance genes, among which Zm00001d051313 was finally evaluated for its roles in host defense response to P. aristosporum infection. Through virus-induced gene silencing (VIGS) verification and physiological index determination, we found that transient silencing of Zm00001d051313 promoted P. aristosporum infection, indicating a positive regulatory role of this gene in maize's antifungal defense mechanism. Therefore, these findings will help advance our current understanding of the underlying mechanisms of maize defense to Pythium stalk rot.

Brown midrib mutant and genome-wide association analysis uncover lignin genes for disease resistance in maize

Brown midrib (BMR) maize (Zea mays L.) harbors mutations that result in lower lignin levels and higher feed digestibility, making it a desirable silage market class for ruminant nutrition. Northern leaf blight (NLB) epidemics in upstate New York highlighted the disease susceptibility of commercially grown BMR maize hybrids. We found the bm1, bm2, bm3, and bm4 mutants in a W64A genetic background to be more susceptible to foliar fungal (NLB, gray leaf spot [GLS], and anthracnose leaf blight [ALB]) and bacterial (Stewart's wilt) diseases. The bm1, bm2, and bm3 mutants showed enhanced susceptibility to anthracnose stalk rot (ASR), and the bm1 and bm3 mutants were more susceptible to Gibberella ear rot (GER). Colocalization of quantitative trait loci (QTL) and correlations between stalk strength and disease traits in recombinant inbred line families suggest possible pleiotropies. The role of lignin in plant defense was explored using high-resolution, genome-wide association analysis for resistance to NLB in the Goodman diversity panel. Association analysis identified 100 single and clustered single-nucleotide polymorphism (SNP) associations for resistance to NLB but did not implicate natural functional variation at bm1-bm5. Strong associations implicated a suite of diverse candidate genes including lignin-related genes such as a β-glucosidase gene cluster, hct11, knox1, knox2, zim36, lbd35, CASP-like protein 8, and xat3. The candidate genes are targets for breeding quantitative resistance to NLB in maize for use in silage and nonsilage purposes.

Integrated GWAS and transcriptomic analysis reveal the candidate salt-responding genes regulating Na+/K+ balance in barley (Hordeum vulgare L.)

Salt stress is one of the main abiotic stresses affecting crop yield and quality. Barley has strong salt tolerance, however, the underlying genetic basis is not fully clear, especially in the seedling stage. This study examined the ionic changes in barley core germplasms under the control and salt conditions. Genome-wide association study (GWAS) analysis revealed 54 significant SNPs from a pool of 25,342 SNPs distributed in 7 chromosomes (Chr) of the Illumina Barley 50K SNP array. These SNPs are associated with ion homeostasis traits, sodium (Na⁺) and potassium (K⁺) content, and Na⁺/K⁺ ratio representing five genomic regions on Chr 2, 4, 5, 6, and 7 in the leaves of worldwide barley accessions. And there are 3 SNP peaks located on the Chr 4, 6, and 7, which could be the "hot spots" regions for mining and identifying candidate genes for salt tolerance. Furthermore, 616 unique candidate genes were screened surrounding the significant SNPs, which are associated with transport proteins, protein kinases, binding proteins, and other proteins of unknown function. Meanwhile, transcriptomic analysis (RNA-Seq) was carried out to compare the salt-tolerant (CM72) and salt-sensitive (Gairdner) genotypes subjected to salt stress. And there was a greater accumulation of differentially expressed genes(DEGs) in Gairdner compared to CM72, mainly enriched in metabolic pathway, biosynthesis of secondary metabolites, photosynthesis, signal transduction,emphasizing the different transcriptional response in both genotypes following salt exposure. Combined GWAS and RNA-Seq analysis revealed 5 promising salt-responding genes (PGK2, BASS3, SINAT2, AQP, and SYT3) from the hot spot regions, which were verified between the salt-tolerant and salt-sensitive varieties by qRT-PCR. In all, these results provide candidate SNPs and genes responsible for salinity responding in barley, and a new idea for studying such genetic basis in similar crops.

Comparative Proteomic Analyses of Susceptible and Resistant Maize Inbred Lines at the Stage of Enations Forming following Infection by Rice Black-Streaked Dwarf Virus

Rice black-streaked dwarf virus (RBSDV) is the main pathogen causing maize rough dwarf disease (MRDD) in China. Typical enation symptoms along the abaxial leaf veins prevail in RBSDV-infected maize inbred line B73 (susceptible to RBSDV), but not in X178 (resistant to RBSDV). Observation of the microstructures of epidermal cells and cross section of enations from RBSDV-infected maize leaves found that the increase of epidermal cell and phloem cell numbers is associated with enation formation. To identify proteins associated with enation formation and candidate proteins against RBSDV infection, comparative proteomics between B73 and X178 plants were conducted using isobaric tags for relative and absolute quantitation (iTRAQ) with leaf samples at the enation forming stage. The proteomics data showed that 260 and 316 differentially expressed proteins (DEPs) were identified in B73 and X178, respectively. We found that the majority of DEPs are located in the chloroplast and cytoplasm. Moreover, RBSDV infection resulted in dramatic changes of DEPs enriched by the metabolic process, response to stress and the biosynthetic process. Strikingly, a cell number regulator 10 was significantly down-regulated in RBSDV-infected B73 plants. Altogether, these data will provide value information for future studies to analyze molecular events during both enation formation and resistance mechanism to RBSDV infection.

Functional analysis revealed the involvement of ZmABCB15 in resistance to rice black-streaked dwarf virus infection

BACKGROUND

Maize rough dwarf disease (MRDD), caused by rice black-streaked dwarf virus (RBSDV) belonging to the Fijivirus genus, seriously threatens maize production worldwide. Three susceptible varieties (Ye478, Zheng 58, and Zhengdan 958) and two resistant varieties (P138 and Chang7-2) were used in our study.

RESULTS

A set of ATP-binding cassette subfamily B (ABCB) transporter genes were screened to evaluate their possible involvements in RBSDV resistance. In the present study, ZmABCB15, an ABCB transporter family member, was cloned and functionally identified. Expression analysis showed that ZmABCB15 was significantly induced in the resistant varieties, not in the susceptible varieties, suggesting its involvement in resistance to the RBSDV infection. ZmABCB15 gene encodes a putative polar auxin transporter containing two trans-membrane domains and two P-loop nucleotide-binding domains. Transient expression analysis indicated that ZmABCB15 is a cell membrance localized protein. Over-expression of ZmABCB15 enhanced the resistance by repressing the RBSDV replication ratio. ZmABCB15 might participate in the RBSDV resistance by affecting the homeostasis of active and inactive auxins in RBSDV infected seedlings.

CONCLUSIONS

Polar auxin transport might participate in the RBSDV resistance by affecting the distribution of endogenous auxin among tissues. Our data showed the involvement of polar auxin transport in RBSDV resistance and provided novel mechanism underlying the auxin-mediated disease control technology.

A pan-Zea genome map for enhancing maize improvement

Background

Maize (Zea mays L.) is at the vanguard facing the upcoming breeding challenges. However, both a super pan-genome for the Zea genus and a comprehensive genetic variation map for maize breeding are still lacking.

Results

Here, we construct an approximately 6.71-Gb pan-Zea genome that contains around 4.57-Gb non-B73 reference sequences from fragmented de novo assemblies of 721 pan-Zea individuals. We annotate a total of 58,944 pan-Zea genes and find around 44.34% of them are dispensable in the pan-Zea population. Moreover, 255,821 common structural variations are identified and genotyped in a maize association mapping panel. Further analyses reveal gene presence/absence variants and their potential roles during domestication of maize. Combining genetic analyses with multi-omics data, we demonstrate how structural variants are associated with complex agronomic traits.

Conclusions

Our results highlight the underexplored role of the pan-Zea genome and structural variations to further understand domestication of maize and explore their potential utilization in crop improvement.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13059-022-02742-7.

Genome-Wide Profiling of Alternative Splicing and Gene Fusion during Rice Black-Streaked Dwarf Virus Stress in Maize (Zea mays L.)

Rice black-streaked dwarf virus (RBSDV) causes maize rough dwarf disease (MRDD), which is a viral disease that significantly affects maize yields worldwide. Plants tolerate stress through transcriptional reprogramming at the alternative splicing (AS), transcriptional, and fusion gene (FG) levels. However, it is unclear whether and how AS and FG interfere with transcriptional reprogramming in MRDD. In this study, we performed global profiling of AS and FG on maize response to RBSDV and compared it with transcriptional changes. There are approximately 1.43 to 2.25 AS events per gene in maize infected with RBSDV. GRMZM2G438622 was only detected in four AS modes (A3SS, A5SS, RI, and SE), whereas GRMZM2G059392 showed downregulated expression and four AS events. A total of 106 and 176 FGs were detected at two time points, respectively, including six differentially expressed genes and five differentially spliced genes. The gene GRMZM2G076798 was the only FG that occurred at two time points and was involved in two FG events. Among these, 104 GOs were enriched, indicating that nodulin-, disease resistance-, and chloroplastic-related genes respond to RBSDV stress in maize. These results provide new insights into the mechanisms underlying post-transcriptional and transcriptional regulation of maize response to RBSDV stress.

Deciphering the Genetic Architecture of Plant Virus Resistance by GWAS, State of the Art and Potential Advances

Growing virus resistant varieties is a highly effective means to avoid yield loss due to infection by many types of virus. The challenge is to be able to detect resistance donors within plant species diversity and then quickly introduce alleles conferring resistance into elite genetic backgrounds. Until now, mainly monogenic forms of resistance with major effects have been introduced in crops. Polygenic resistance is harder to map and introduce in susceptible genetic backgrounds, but it is likely more durable. Genome wide association studies (GWAS) offer an opportunity to accelerate mapping of both monogenic and polygenic resistance, but have seldom been implemented and described in the plant-virus interaction context. Yet, all of the 48 plant-virus GWAS published so far have successfully mapped QTLs involved in plant virus resistance. In this review, we analyzed general and specific GWAS issues regarding plant virus resistance. We have identified and described several key steps throughout the GWAS pipeline, from diversity panel assembly to GWAS result analyses. Based on the 48 published articles, we analyzed the impact of each key step on the GWAS power and showcase several GWAS methods tailored to all types of viruses.

qMrdd2, a novel quantitative resistance locus for maize rough dwarf disease

BACKGROUND

Maize rough dwarf disease (MRDD), a widespread disease caused by four pathogenic viruses, severely reduces maize yield and grain quality. Resistance against MRDD is a complex trait that controlled by many quantitative trait loci (QTL) and easily influenced by environmental conditions. So far, many studies have reported numbers of resistant QTL, however, only one QTL have been cloned, so it is especially important to map and clone more genes that confer resistance to MRDD.

RESULTS

In the study, a major quantitative trait locus (QTL) qMrdd2, which confers resistance to MRDD, was identified and fine mapped. qMrdd2, located on chromosome 2, was consistently identified in a 15-Mb interval between the simple sequence repeat (SSR) markers D184 and D1600 by using a recombinant inbred line (RIL) population derived from a cross between resistant ("80007") and susceptible ("80044") inbred lines. Using a recombinant-derived progeny test strategy, qMrdd2 was delineated to an interval of 577 kb flanked by markers N31 and N42. We further demonstrated that qMrdd2 is an incompletely dominant resistance locus for MRDD that reduced the disease severity index by 20.4%.

CONCLUSIONS

A major resistance QTL (qMrdd2) have been identified and successfully refined into 577 kb region. This locus will be valuable for improving maize variety resistance to MRDD via marker-assisted selection (MAS).

Genetic dissection of maize disease resistance and its applications in molecular breeding

Disease resistance is essential for reliable maize production. In a long-term tug-of-war between maize and its pathogenic microbes, naturally occurring resistance genes gradually accumulate and play a key role in protecting maize from various destructive diseases. Recently, significant progress has been made in deciphering the genetic basis of disease resistance in maize. Enhancing disease resistance can now be explored at the molecular level, from marker-assisted selection to genomic selection, transgenesis technique, and genome editing. In view of the continuing accumulation of cloned resistance genes and in-depth understanding of their resistance mechanisms, coupled with rapid progress of biotechnology, it is expected that the large-scale commercial application of molecular breeding of resistant maize varieties will soon become a reality.

Genome-Wide Association Study of Maize Aboveground Dry Matter Accumulation at Seedling Stage

Dry matter accumulation and partitioning during the early phases of development could significantly affect crop growth and productivity. In this study, the aboveground dry matter (DM), the DM of different organs, and partition coefficients of a maize association mapping panel of 412 inbred lines were evaluated at the third and sixth leaf stages (V3 and V6). Further, the properties of these phenotypic traits were analyzed. Genome-wide association studies (GWAS) were conducted on the total aboveground biomass and the DM of different organs. Analysis of GWAS results identified a total of 1,103 unique candidate genes annotated by 678 significant SNPs (P value < 1.28e-6). A total of 224 genes annotated by SNPs at the top five of each GWAS method and detected by multiple GWAS methods were regarded as having high reliability. Pathway enrichment analysis was also performed to explore the biological significance and functions of these candidate genes. Several biological pathways related to the regulation of seed growth, gibberellin-mediated signaling pathway, and long-day photoperiodism were enriched. The results of our study could provide new perspectives on breeding high-yielding maize varieties.

Large-Scale Discovery of Non-conventional Peptides in Maize and Arabidopsis through an Integrated Peptidogenomic Pipeline

Non-conventional peptides (NCPs), which include small open reading frame-encoded peptides, play critical roles in fundamental biological processes. In this study, we developed an integrated peptidogenomic pipeline using high-throughput mass spectra to probe a customized six-frame translation database and applied it to large-scale identification of NCPs in plants.A total of 1993 and 1860 NCPs were unambiguously identified in maize and Arabidopsis, respectively. These NCPs showed distinct characteristics compared with conventional peptides and were derived from introns, 3' UTRs, 5' UTRs, junctions, and intergenic regions. Furthermore, our results showed that translation events in unannotated transcripts occur more broadly than previously thought. In addition, we found that dozens of maize NCPs are enriched within regions associated with phenotypic variations and domestication selection, indicating that they potentially are involved in genetic regulation of complex traits and domestication in maize. Taken together, our study developed an integrated peptidogenomic pipeline for large-scale identification of NCPs in plants, which would facilitate global characterization of NCPs from other plants. The identification of large-scale NCPs in both monocot (maize) and dicot (Arabidopsis) plants indicates that a large portion of plant genome can be translated into biologically functional molecules, which has important implications for functional genomic studies.

Genome-wide association and epistatic interactions of flowering time in soybean cultivar

Genome-wide association studies (GWAS) have enabled the discovery of candidate markers that play significant roles in various complex traits in plants. Recently, with increased interest in the search for candidate markers, studies on epistatic interactions between single nucleotide polymorphism (SNP) markers have also increased, thus enabling the identification of more candidate markers along with GWAS on single-variant-additive-effect. Here, we focused on the identification of candidate markers associated with flowering time in soybean (Glycine max). A large population of 2,662 cultivated soybean accessions was genotyped using the 180k Axiom® SoyaSNP array, and the genomic architecture of these accessions was investigated to confirm the population structure. Then, GWAS was conducted to evaluate the association between SNP markers and flowering time. A total of 93 significant SNP markers were detected within 59 significant genes, including E1 and E3, which are the main determinants of flowering time. Based on the GWAS results, multilocus epistatic interactions were examined between the significant and non-significant SNP markers. Two significant and 16 non-significant SNP markers were discovered as candidate markers affecting flowering time via interactions with each other. These 18 candidate SNP markers mapped to 18 candidate genes including E1 and E3, and the 18 candidate genes were involved in six major flowering pathways. Although further biological validation is needed, our results provide additional information on the existing flowering time markers and present another option to marker-assisted breeding programs for regulating flowering time of soybean.

The Past, Present, and Future of Maize Improvement: Domestication, Genomics, and Functional Genomic Routes toward Crop Enhancement

After being domesticated from teosinte, cultivated maize (Zea mays ssp. mays) spread worldwide and now is one of the most important staple crops. Due to its tremendous phenotypic and genotypic diversity, maize also becomes to be one of the most widely used model plant species for fundamental research, with many important discoveries reported by maize researchers. Here, we provide an overview of the history of maize domestication and key genes controlling major domestication-related traits, review the currently available resources for functional genomics studies in maize, and discuss the functions of most of the maize genes that have been positionally cloned and can be used for crop improvement. Finally, we provide some perspectives on future directions regarding functional genomics research and the breeding of maize and other crops.

Identification of QTLs for resistance to maize rough dwarf disease using two connected RIL populations in maize

Maize rough dwarf disease (MRDD) is a significant viral disease caused by rice black-streaked dwarf virus (RBSDV) in China, which results in 30% yield losses in affected summer maize-growing areas. In this study, two connected recombinant inbred line (RIL) populations were constructed to elucidate the genetic basis of resistance during two crop seasons. Ten quantitative trait loci (QTLs) for resistance to MRDD were detected in the two RILs. Individual QTLs accounted for 4.97-23.37% of the phenotypic variance explained (PVE). The resistance QTL (qZD-MRDD8-1) with the largest effect was located in chromosome bin 8.03, representing 16.27-23.37% of the PVE across two environments. Interestingly, one pair of common significant QTLs was located in the similar region on chromosome 4 in both populations, accounting for 7.11-9.01% of the PVE in Zheng58×D863F (RIL-ZD) and 9.43-13.06% in Zheng58×ZS301 (RIL-ZZ). A total of five QTLs for MRDD resistance trait showed significant QTL-by-Environment interactions (QEI). Two candidate genes associated with resistance (GDSL-lipase and RPP13-like gene) which were higher expressed in resistant inbred line D863F than in susceptible inbred line Zheng58, were located in the physical intervals of the major QTLs on chromosomes 4 and 8, respectively. The identified QTLs will be studied further for application in marker-assisted breeding in maize genetic improvement of MRDD resistance.

Genetic architecture of maize chlorotic mottle virus and maize lethal necrosis through GWAS, linkage analysis and genomic prediction in tropical maize germplasm

KEY MESSAGE

Analysis of the genetic architecture of MCMV and MLN resistance in maize doubled-haploid populations revealed QTLs with major effects on chromosomes 3 and 6 that were consistent across genetic backgrounds and environments. Two major-effect QTLs, qMCMV3-108/qMLN3-108 and qMCMV6-17/qMLN6-17, were identified as conferring resistance to both MCMV and MLN. Maize lethal necrosis (MLN) is a serious threat to the food security of maize-growing smallholders in sub-Saharan Africa. The ability of the maize chlorotic mottle virus (MCMV) to interact with other members of the Potyviridae causes severe yield losses in the form of MLN. The objective of the present study was to gain insights and validate the genetic architecture of resistance to MCMV and MLN in maize. We applied linkage mapping to three doubled-haploid populations and a genome-wide association study (GWAS) on 380 diverse maize lines. For all the populations, phenotypic variation for MCMV and MLN was significant, and heritability was moderate to high. Linkage mapping revealed 13 quantitative trait loci (QTLs) for MCMV resistance and 12 QTLs conferring MLN resistance. One major-effect QTL, qMCMV3-108/qMLN3-108, was consistent across populations for both MCMV and MLN resistance. Joint linkage association mapping (JLAM) revealed 18 and 21 main-effect QTLs for MCMV and MLN resistance, respectively. Another major-effect QTL, qMCMV6-17/qMLN6-17, was detected for both MCMV and MLN resistance. The GWAS revealed a total of 54 SNPs (MCMV-13 and MLN-41) significantly associated (P ≤ 5.60 × 10-05) with MCMV and MLN resistance. Most of the GWAS-identified SNPs were within or adjacent to the QTLs detected through linkage mapping. The prediction accuracy for within populations as well as the combined populations is promising; however, the accuracy was low across populations. Overall, MCMV resistance is controlled by a few major and many minor-effect loci and seems more complex than the genetic architecture for MLN resistance.

Identification of a locus conferring dominant resistance to maize rough dwarf disease in maize

Maize rough dwarf disease (MRDD) is a severe viral disease of maize that occurs worldwide, particularly in the summer maize-growing areas in China, resulting in yield losses and quality deterioration in susceptible maize varieties. An effective solution to control MRDD is to use resistance genes to improve the behavior of susceptible genotypes. Here, we employed maize F₂ populations derived from a cross between susceptible line S221 and resistant line K36 for the deep sequencing of the two DNA pools containing extremely resistant and susceptible F₂ individuals, and used traditional linkage analysis to locate the resistance-related genomic region. The results showed that MRDD resistance in K36 was controlled by a single dominant locus, and an associated region was identified within the genomic interval of 68,396,487 bp and 69,523,478 bp on chromosome 6. Two simple sequence repeat (SSR) markers 6F29R29 and 6F34R34 were tightly linked to the MRDD resistance locus. The findings of the present study improve our understanding of the inheritance patterns of MRDD resistance, and should inform MRDD-resistant maize breeding programs.

Genome-wide Association Studies in Maize: Praise and Stargaze

Genome-wide association study (GWAS) has become a widely accepted strategy for decoding genotype-phenotype associations in many species thanks to advances in next-generation sequencing (NGS) technologies. Maize is an ideal crop for GWAS and significant progress has been made in the last decade. This review summarizes current GWAS efforts in maize functional genomics research and discusses future prospects in the omics era. The general goal of GWAS is to link genotypic variations to corresponding differences in phenotype using the most appropriate statistical model in a given population. The current review also presents perspectives for optimizing GWAS design and analysis. GWAS analysis of data from RNA, protein, and metabolite-based omics studies is discussed, along with new models and new population designs that will identify causes of phenotypic variation that have been hidden to date. The joint and continuous efforts of the whole community will enhance our understanding of maize quantitative traits and boost crop molecular breeding designs.

MODEM: multi-omics data envelopment and mining in maize

MODEM is a comprehensive database of maize multidimensional omics data, including genomic, transcriptomic, metabolic and phenotypic information from the cellular to individual plant level. This initial release contains approximately 1.06 M high quality SNPs for 508 diverse inbred lines obtained by combining variations from RNA sequencing on whole kernels (15 days after pollination) of 368 lines and a 50 K array for all 508 individuals. As all of these data were derived from the same diverse panel of lines, the database also allows various types of genetic mapping (including characterization of phenotypic QTLs, pQTLs; expression QTLs, eQTLs and metabolic QTLs, mQTLs). MODEM is thus designed to promote a better understanding of maize genetic architecture and deep functional annotation of the complex maize genome (and potentially those of other crop plants) and to explore the genotype-phenotype relationships and regulation of maize kernel development at multiple scales, which is also comprehensive for developing novel methods. MODEM is additionally designed to link with other databases to make full use of current resources, and it provides visualization tools for easy browsing. All of the original data and the related mapping results are freely available for easy query and download. This platform also provides helpful tools for general analyses and will be continually updated with additional materials, features and public data related to maize genetics or regulation as they become available.Database URL: (http://modem.hzau.edu.cn).

MODEM: multi-omics data envelopment and mining in maize

MODEM is a comprehensive database of maize multidimensional omics data, including genomic, transcriptomic, metabolic and phenotypic information from the cellular to individual plant level. This initial release contains approximately 1.06 M high quality SNPs for 508 diverse inbred lines obtained by combining variations from RNA sequencing on whole kernels (15 days after pollination) of 368 lines and a 50 K array for all 508 individuals. As all of these data were derived from the same diverse panel of lines, the database also allows various types of genetic mapping (including characterization of phenotypic QTLs, pQTLs; expression QTLs, eQTLs and metabolic QTLs, mQTLs). MODEM is thus designed to promote a better understanding of maize genetic architecture and deep functional annotation of the complex maize genome (and potentially those of other crop plants) and to explore the genotype-phenotype relationships and regulation of maize kernel development at multiple scales, which is also comprehensive for developing novel methods. MODEM is additionally designed to link with other databases to make full use of current resources, and it provides visualization tools for easy browsing. All of the original data and the related mapping results are freely available for easy query and download. This platform also provides helpful tools for general analyses and will be continually updated with additional materials, features and public data related to maize genetics or regulation as they become available.Database URL: (http://modem.hzau.edu.cn).