Identification of anther thermotolerance genes by the integration of linkage and association analysis in maize.

Maize is one of the world's most important staple crops, yet its production is increasingly threatened by the rising frequency of high-temperature stress (HTS). To investigate the genetic basis of anther thermotolerance under field conditions, we performed linkage and association analysis to identify HTS response quantitative trait loci (QTL) using three recombinant inbred line (RIL) populations and an association panel containing 375 diverse maize inbred lines. These analyses resulted in the identification of 16 co-located large QTL intervals. Among the 37 candidate genes identified in these QTL intervals, five have rice or Arabidopsis homologs known to influence pollen and filament development. Notably, one of the candidate genes, ZmDUP707, has been subject to selection pressure during breeding. Its expression is suppressed by HTS, leading to pollen abortion and barren seeds. We also identified several additional candidate genes potentially underly QTL previously reported by other researchers. Taken together, our results provide a pool of valuable candidate genes that could be employed by future breeding programs aiming at enhancing maize HTS tolerance.

Advancements and Prospects of Genome-Wide Association Studies (GWAS) in Maize.

Genome-wide association studies (GWAS) have emerged as a powerful tool for unraveling intricate genotype-phenotype association across various species. Maize (Zea mays L.), renowned for its extensive genetic diversity and rapid linkage disequilibrium (LD), stands as an exemplary candidate for GWAS. In maize, GWAS has made significant advancements by pinpointing numerous genetic loci and potential genes associated with complex traits, including responses to both abiotic and biotic stress. These discoveries hold the promise of enhancing adaptability and yield through effective breeding strategies. Nevertheless, the impact of environmental stress on crop growth and yield is evident in various agronomic traits. Therefore, understanding the complex genetic basis of these traits becomes paramount. This review delves into current and future prospectives aimed at yield, quality, and environmental stress resilience in maize and also addresses the challenges encountered during genomic selection and molecular breeding, all facilitated by the utilization of GWAS. Furthermore, the integration of omics, including genomics, transcriptomics, proteomics, metabolomics, epigenomics, and phenomics has enriched our understanding of intricate traits in maize, thereby enhancing environmental stress tolerance and boosting maize production. Collectively, these insights not only advance our understanding of the genetic mechanism regulating complex traits but also propel the utilization of marker-assisted selection in maize molecular breeding programs, where GWAS plays a pivotal role. Therefore, GWAS provides robust support for delving into the genetic mechanism underlying complex traits in maize and enhancing breeding strategies.

Genetic dissection of maize (Zea mays L.) chlorophyll content using multi-locus genome-wide association studies.

BACKGROUND: The chlorophyll content (CC) is a key factor affecting maize photosynthetic efficiency and the final yield. However, its genetic basis remains unclear. The development of statistical methods has enabled researchers to design and apply various GWAS models, including MLM, MLMM, SUPER, FarmCPU, BLINK and 3VmrMLM. Comparative analysis of their results can lead to more effective mining of key genes. RESULTS: The heritability of CC was 0.86. Six statistical models (MLM, BLINK, MLMM, FarmCPU, SUPER, and 3VmrMLM) and 1.25 million SNPs were used for the GWAS. A total of 140 quantitative trait nucleotides (QTNs) were detected, with 3VmrMLM and MLM detecting the most (118) and fewest (3) QTNs, respectively. The QTNs were associated with 481 genes and explained 0.29-10.28% of the phenotypic variation. Additionally, 10 co-located QTNs were detected by at least two different models or methods, three co-located QTNs were identified in at least two different environments, and six co-located QTNs were detected by different models or methods in different environments. Moreover, 69 candidate genes within or near these stable QTNs were screened based on the B73 (RefGen_v2) genome. GRMZM2G110408 (ZmCCS3) was identified by multiple models and in multiple environments. The functional characterization of this gene indicated the encoded protein likely contributes to chlorophyll biosynthesis. In addition, the CC differed significantly between the haplotypes of the significant QTN in this gene, and CC was higher for haplotype 1. CONCLUSION: This study's results broaden our understanding of the genetic basis of CC, mining key genes related to CC and may be relevant for the ideotype-based breeding of new maize varieties with high photosynthetic efficiency.

Multi-omic characterization of the maize GPI synthesis mutant gwt1 with defects in kernel development.

BACKGROUND: Glycosylphosphatidylinositol (GPI) and GPI-anchored proteins (GAPs) are important for cell wall formation and reproductive development in Arabidopsis. However, monocot counterparts that function in kernel endosperm development have yet to be discovered. Here, we performed a multi-omic analysis to explore the function of GPI related genes on kernel development in maize. RESULTS: In maize, 48 counterparts of human GPI synthesis and lipid remodeling genes were identified, in which null mutation of the glucosaminyl-phosphatidylinositol O-acyltransferase1 gene, ZmGWT1, caused a kernel mutant (named gwt1) with defects in the basal endosperm transport layer (BETL). We performed plasma membrane (PM) proteomics to characterize the potential GAPs involved in kernel development. In total, 4,981 proteins were successfully identified in 10-DAP gwt1 kernels of mutant and wild-type (WT), including 1,638 membrane-anchored proteins with different posttranslational modifications. Forty-seven of the 256 predicted GAPs were differentially accumulated between gwt1 and WT. Two predicted BETL-specific GAPs (Zm00001d018837 and Zm00001d049834), which kept similar abundance at general proteome but with significantly decreased abundance at membrane proteome in gwt1 were highlighted. CONCLUSIONS: Our results show the importance of GPI and GAPs for endosperm development and provide candidate genes for further investigation of the regulatory network in which ZmGWT1 participates.

The genetic architecture of prolificacy in maize revealed by association mapping and bulk segregant analysis.

KEY MESSAGE: Here, we revealed maize prolificacy highly correlated with domestication and identified a causal gene ZmEN1 located in one novel QTL qGEN261 that regulating maize prolificacy by using multiple-mapping methods. The development of maize prolificacy (EN) is crucial for enhancing yield and breeding specialty varieties. To achieve this goal, we employed a genome-wide association study (GWAS) to analyze the genetic architecture of EN in maize. Using 492 inbred lines with a wide range of EN variability, our results demonstrated significant differences in genetic, environmental, and interaction effects. The broad-sense heritability (H2) of EN was 0.60. Through GWAS, we identified 527 significant single nucleotide polymorphisms (SNPs), involved 290 quantitative trait loci (QTL) and 806 genes. Of these SNPs, 18 and 509 were classified as major effect loci and minor loci, respectively. In addition, we performed a bulk segregant analysis (BSA) in an F2 population constructed by a few-ears line Zheng58 and a multi-ears line 647. Our BSA results identified one significant QTL, qBEN1. Importantly, combining the GWAS and BSA, four co-located QTL, involving six genes, were identified. Three of them were expressed in vegetative meristem, shoot tip, internode and tip of ear primordium, with ZmEN1, encodes an unknown auxin-like protein, having the highest expression level in these tissues. It suggested that ZmEN1 plays a crucial role in promoting axillary bud and tillering to encourage the formation of prolificacy. Haplotype analysis of ZmEN1 revealed significant differences between different haplotypes, with inbred lines carrying hap6 having more EN. Overall, this is the first report about using GWAS and BSA to dissect the genetic architecture of EN in maize, which can be valuable for breeding specialty maize varieties and improving maize yield.

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

Starch is a major component of cereals, comprising over 70% of dry weight. It serves as a primary carbon source for humans and animals. In addition, starch is an indispensable industrial raw material. While maize (Zea mays) is a key crop and the primary source of starch, the genetic basis for starch content in maize kernels remains poorly understood. In this study, using an enlarged panel, we conducted a genome-wide association study (GWAS) based on best linear unbiased prediction (BLUP) value for starch content of 261 inbred lines across three environments. Compared with previous study, we identified 14 additional significant quantitative trait loci (QTL), encompassed a total of 42 genes, and indicated that increased marker density contributes to improved statistical power. By integrating gene expression profiling, Gene Ontology (GO) enrichment and haplotype analysis, several potential target genes that may play a role in regulating starch content in maize kernels have been identified. Notably, we found that ZmAPC4, associated with the significant SNP chr4.S_175584318, which encodes a WD40 repeat-like superfamily protein and is highly expressed in maize endosperm, might be a crucial regulator of maize kernel starch synthesis. Out of the 261 inbred lines analyzed, they were categorized into four haplotypes. Remarkably, it was observed that the inbred lines harboring hap4 demonstrated the highest starch content compared to the other haplotypes. Additionally, as a significant achievement, we have developed molecular markers that effectively differentiate maize inbred lines based on their starch content. Overall, our study provides valuable insights into the genetic basis of starch content and the molecular markers can be useful in breeding programs aimed at developing maize varieties with high starch content, thereby improving breeding efficiency. Supplementary Information: The online version contains supplementary material available at 10.1007/s11032-023-01437-6.

Mapping the gene of a maize leaf senescence mutant and understanding the senescence pathways by expression analysis.

KEY MESSAGES: Narrowing down to a single putative target gene behind a leaf senescence mutant and constructing the regulation network by proteomic method. Leaf senescence mutant is an important resource for exploring molecular mechanism of aging. To dig for potential modulation networks during maize leaf aging process, we delimited the gene responsible for a premature leaf senescence mutant els5 to a 1.1 Mb interval in the B73 reference genome using a BC1F1 population with 40,000 plants, and analyzed the leaf proteomics of the mutant and its near-isogenic wild type line. A total of 1355 differentially accumulated proteins (DAP) were mainly enriched in regulation pathways such as "photosynthesis", "ribosome", and "porphyrin and chlorophyll metabolism" by the KEGG pathway analysis. The interaction networks constructed by incorporation of transcriptome data showed that ZmELS5 likely repaired several key factors in the photosynthesis system. The putative candidate proteins for els5 were proposed based on DAPs in the fined QTL mapping interval. These results provide fundamental basis for cloning and functional research of the els5 gene, and new insights into the molecular mechanism of leaf senescence in maize.

Gene expression variation explains maize seed germination heterosis.

BACKGROUND: Heterosis has been extensively utilized in plant breeding, however, the underlying molecular mechanism remains largely elusive. Maize (Zea mays), which exhibits strong heterosis, is an ideal material for studying heterosis. RESULTS: In this study, there is faster imbibition and development in reciprocal crossing Zhengdan958 hybrids than in their parent lines during seed germination. To investigate the mechanism of heterosis of maize germination, comparative transcriptomic analyses were conducted. The gene expression patterns showed that 1324 (47.27%) and 1592 (66.44%) of the differential expression genes between hybrids and either parental line display parental dominance up or higher levels in the reciprocal cross of Zhengdan958, respectively. Notably, these genes were mainly enriched in metabolic pathways, including carbon metabolism, glycolysis/gluconeogenesis, protein processing in endoplasmic reticulum, etc. CONCLUSION: Our results provide evidence for the higher expression level genes in hybrid involved in metabolic pathways acting as main contributors to maize seed germinating heterosis. These findings provide new insights into the gene expression variation of maize embryos and improve the understanding of maize seed germination heterosis.

Dissection of the genetic architecture of peduncle vascular bundle-related traits in maize by a genome-wide association study.

The peduncle vascular system of maize is critical for the transport of photosynthetic products, nutrients, and water from the roots and leaves to the ear. Accordingly, it positively affects the grain yield. However, the genetic basis of peduncle vascular bundle (PVB)-related traits in maize remains unknown. Thus, 15 PVB-related traits of 386 maize inbred lines were investigated at three locations (Yongcheng, 17YC; Kaifeng, 20KF; and Yuanyang, 20YY). The repeatability for the 15 traits ranged from 35.53% to 92.13%. A genome-wide association study was performed and 69 non-redundant quantitative trait loci (QTL) were detected, including 9, 41, and 27 QTL identified at 17YC, 20KF, and 20YY, respectively. These QTL jointly explained 4.72% (SLL) to 37.30% (NSVB) of the phenotypic variation. Eight QTL were associated with the same trait at two locations. Furthermore, four pleiotropic QTL were identified. Moreover, one QTL (qPVB44), associated with NSVB_20KF, was co-localized with a previously reported locus related to kernel width, implying qPVB44 may affect the kernel width by modulating the number of small vascular bundles. Examinations of the 69 QTL identified 348 candidate genes that were classified in five groups. Additionally, 26 known VB-related homologous genes (e.g. VLN2, KNOX1, and UGT72B3) were detected in 20 of the 69 QTL. A comparison of the NSVB between a Zmvln2 EMS mutant and its wild type elucidated the function of the candidate gene ZmVLN2. These results are important for clarifying the genetic basis of PVB-related traits and may be useful for breeding new high-yielding maize cultivars.

Metabolomics analysis reveals differences in evolution between maize and rice.

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.

Global transcriptional profiling between inbred parents and hybrids provides comprehensive insights into ear-length heterosis of maize (Zea mays).

BACKGROUND: Maize (Zea mays) ear length, which is an important yield component, exhibits strong heterosis. Understanding the potential molecular mechanisms of ear-length heterosis is critical for efficient yield-related breeding. RESULTS: Here, a joint netted pattern, including six parent-hybrid triplets, was designed on the basis of two maize lines harboring long (T121 line) and short (T126 line) ears. Global transcriptional profiling of young ears (containing meristem) was performed. Multiple comparative analyses revealed that 874 differentially expressed genes are mainly responsible for the ear-length variation between T121 and T126 lines. Among them, four key genes, Zm00001d049958, Zm00001d027359, Zm00001d048502 and Zm00001d052138, were identified as being related to meristem development, which corroborated their roles in the superior additive genetic effects on ear length in T121 line. Non-additive expression patterns were used to identify candidate genes related to ear-length heterosis. A non-additively expressed gene (Zm00001d050649) was associated with the timing of meristematic phase transition and was determined to be the homolog of tomato SELF PRUNING, which assists SINGLE FLOWER TRUSS in driving yield-related heterosis, indicating that Zm00001d050649 is a potential contributor to drive heterotic effect on ear length. CONCLUSION: Our results suggest that inbred parents provide genetic and heterotic effects on the ear lengths of their corresponding F1 hybrids through two independent pathways. These findings provide comprehensive insights into the transcriptional regulation of ear length and improve the understanding of ear-length heterosis in maize.

A high-throughput and low-cost maize ear traits scorer.

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. Supplementary Information: The online version contains supplementary material available at 10.1007/s11032-021-01205-4.

Cytosolic malate dehydrogenase 4 modulates cellular energetics and storage reserve accumulation in maize endosperm.

Cytosolic malate dehydrogenase (MDH) is a key enzyme that regulates the interconversion between malate and oxaloacetate (OAA). However, its role in modulating storage compound accumulation in maize endosperm is largely unknown. Here, we characterized a novel naturally occurring maize mdh4-1 mutant, which produces small, opaque kernels and exhibits reduced starch but enhanced lysine content. Map-based cloning, functional complementation and allelism analyses identified ZmMdh4 as the causal gene. Enzymatic assays demonstrated that ZmMDH4 predominantly catalyses the conversion from OAA to malate. In comparison, the activity of the mutant enzyme, which lacks one glutamic acid (Glu), was completed abolished, demonstrating that the Glu residue was essential for ZmMDH4 function. Knocking down ZmMdh4 in vivo led to a substantial metabolic shift towards glycolysis and a dramatic disruption in the activity of the mitochondrial complex I, which was correlated with transcriptomic alterations. Taken together, these results demonstrate that ZmMdh4 regulates the balance between mitochondrial respiration and glycolysis, ATP production and endosperm development, through a yet unknown feedback regulatory mechanism in mitochondria.

ECOGEMS: efficient compression and retrieve of SNP data of 2058 rice accessions with integer sparse matrices.

SUMMARY: We proposed to store large-scale genotype data as integer sparse matrices, which consumed much fewer computing resources for storage and analysis than traditional approaches. In addition, the raw genotype data could be readily recovered from integer sparse matrices. Utilizing this approach, we stored the genotype data of 1612 Asian cultivated rice accessions and 446 Asian wild rice accessions across 8 584 244 SNP sites in the ECOGEMS database with 310 MB of disk usage. Graphical interface for visualization, analysis and download of SNP data were implemented in ECOGEMS, which made it a valuable resource for rice functional genomic studies. AVAILABILITY AND IMPLEMENTATION: The code and data of ECOGEMS are freely available at https://github.com/venyao/ECOGEMS. ECOGEMS is deployed at http://ecogems.ncpgr.cn and http://150.109.59.144: 3838/ECOGEMS/ for online use. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Linear depolarization ratios of nitrate-coated mineral dust particles in haze episodes.

This study reports an internal mixed particle model of dust and nitrate aerosols using the actual haze condition. We performed accurate calculations of linear depolarization ratios (LDR) of nitrate-coated mineral dust particles at three wavelengths (0.35, 0.53, and 1.06 µm) using the T-matrix method. The LDRs of the mono-disperse aerosol particles evolve differently as expressions in the Rayleigh and Mie domains. In the Rayleigh domain, the LDRs increase with the core-shell ratio and the aspect ratio and decrease when the wavelength increases. The forward and backward LDRs depend more on aspect ratio than on the core-shell ratio. In the Mie domain, the LDRs overall increase with the core-shell ratio and the aspect ratio, but there is no significant regular change. When the wavelength increases, the gradual change can be explained by the size parameter of the particles in the vicinity of the Rayleigh domain. For poly-disperse particles, the core-shell ratio mainly affects the position of the side-scattering peak, whereas aspect ratio affects the LDRs. The backscattering LDRs depend more on the variation of aspect ratio, and the core-shell ratio only affects LDRs in a small range. Furthermore, our results on the LDRs are highly promising for remote sensing of the non-spherical and inhomogeneous properties of fine aerosols compared with AERONET measurements. Our results provide a comprehensive understanding of the LDR evolution for coated non-spherical particles in a haze atmosphere. The LDRs can be used as an empirical reference for remote sensing to distinguish coated non-spherical particles.

Genetic-based dissection of arsenic accumulation in maize using a genome-wide association analysis method.

Understanding the mechanism of arsenic (As) accumulation in plants is important in reducing As's toxicity to plants and its potential risks to human health. Here, we performed a genome-wide association study to dissect the genetic basis of the As contents of different maize tissues in Xixian, which was irrigated with As-rich surface water, and Changge using an association population consisting of 230 representative maize inbred lines. Phenotypic data revealed a wide normal distribution and high repeatability for the As contents in maize tissues. The As concentrations in maize tissues followed the same trend in the two locations: kernels < axes < stems < bracts < leaves. In total, 15, 16 and 15 non-redundant quantitative trait loci (QTLs) associated with As concentrations were identified (P ≤ 2.04 × 10-6 ) in five tissues from Xixian, Changge, and the combination of the locations, respectively, explaining 9.70%-24.65% of the phenotypic variation for each QTL, on average. Additionally, four QTLs [involving 15 single nucleotide polymorphisms (SNPs)] were detected in the single and the combined locations, indicating that these loci/SNPs might be stable across different environments. The candidate genes associated with these four loci were predicted. In addition, four non-redundant QTLs (6 SNPs), including a QTL that was detected in multiple locations according to the genome-wide association study, were found to co-localize with four previously reported QTL intervals. These results are valuable to understand the genetic architecture of As mechanism in maize and facilitate the genetic improvement of varieties without As toxicity.

High-Throughput Phenotyping and QTL Mapping Reveals the Genetic Architecture of Maize Plant Growth.

With increasing demand for novel traits in crop breeding, the plant research community faces the challenge of quantitatively analyzing the structure and function of large numbers of plants. A clear goal of high-throughput phenotyping is to bridge the gap between genomics and phenomics. In this study, we quantified 106 traits from a maize (Zea mays) recombinant inbred line population (n = 167) across 16 developmental stages using the automatic phenotyping platform. Quantitative trait locus (QTL) mapping with a high-density genetic linkage map, including 2,496 recombinant bins, was used to uncover the genetic basis of these complex agronomic traits, and 988 QTLs have been identified for all investigated traits, including three QTL hotspots. Biomass accumulation and final yield were predicted using a combination of dissected traits in the early growth stage. These results reveal the dynamic genetic architecture of maize plant growth and enhance ideotype-based maize breeding and prediction.

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.

Dissecting the genetic architecture of waterlogging stress-related traits uncovers a key waterlogging tolerance gene in maize.

KEY MESSAGE: A key candidate gene, GRMZM2G110141, which could be used in marker-assisted selection in maize breeding programs, was detected among the 16 genetic loci associated with waterlogging tolerance identified through genome-wide association study. Waterlogging stress seriously affects the growth and development of upland crops such as maize (Zea mays L.). However, the genetic basis of waterlogging tolerance in crop plants is largely unknown. Here, we identified genetic loci for waterlogging tolerance-related traits by conducting a genome-wide association study using maize phenotypes evaluated in the greenhouse under waterlogging stress and normal conditions. A total of 110 trait-single nucleotide polymorphism associations spanning 16 genomic regions were identified; single associations explained 2.88-10.67% of the phenotypic variance. Among the genomic regions identified, 14 co-localized with previously detected waterlogging tolerance-related quantitative trail loci. Furthermore, 33 candidate genes involved in a wide range of stress-response pathways were predicted. We resequenced a key candidate gene (GRMZM2G110141) in 138 randomly selected inbred lines and found that variations in the 5'-UTR and in the mRNA abundance of this gene under waterlogging conditions were significantly associated with leaf injury. Furthermore, we detected favorable alleles of this gene and validated the favorable alleles in two different recombinant inbred line populations. These alleles enhanced waterlogging tolerance in segregating populations, strongly suggesting that GRMZM2G110141 is a key waterlogging tolerance gene. The set of waterlogging tolerance-related genomic regions and associated markers identified here could be valuable for isolating waterlogging tolerance genes and improving this trait in maize.

ZmCOL3, a CCT gene represses flowering in maize by interfering with the circadian clock and activating expression of ZmCCT.

Flowering time is a trait vital to the adaptation of flowering plants to different environments. Here, we report that CCT domain genes play an important role in flowering in maize (Zea mays L.). Among the 53 CCT family genes we identified in maize, 28 were located in flowering time quantitative trait locus regions and 15 were significantly associated with flowering time, based on candidate-gene association mapping analysis. Furthermore, a CCT gene named ZmCOL3 was shown to be a repressor of flowering. Overexpressing ZmCOL3 delayed flowering time by approximately 4 d, in either long-day or short-day conditions. The absence of one cytosine in the ZmCOL3 3'UTR and the presence of a 551 bp fragment in the promoter region are likely the causal polymorphisms contributing to the maize adaptation from tropical to temperate regions. We propose a modified model of the maize photoperiod pathway, wherein ZmCOL3 acts as an inhibitor of flowering either by transactivating transcription of ZmCCT, one of the key genes regulating maize flowering, or by interfering with the circadian clock.