Flavonoid metabolism plays an important role in response to lead stress in maize at seedling stage.

BACKGROUND: Pb stress, a toxic abiotic stress, critically affects maize production and food security. Although some progress has been made in understanding the damage caused by Pb stress and plant response strategies, the regulatory mechanisms and resistance genes involved in the response to lead stress in crops are largely unknown. RESULTS: In this study, to uncover the response mechanism of maize to Pb stress phenotype, physiological and biochemical indexes, the transcriptome, and the metabolome under different concentrations of Pb stress were combined for comprehensive analysis. As a result, the development of seedlings and antioxidant system were significantly inhibited under Pb stress, especially under relatively high Pb concentrations. Transcriptome analysis revealed 3559 co-differentially expressed genes(co-DEG) under the four Pb concentration treatments (500 mg/L, 1000 mg/L, 2000 mg/L, and 3000 mg/L Pb(NO3)2), which were enriched mainly in the GO terms related to DNA-binding transcription factor activity, response to stress, response to reactive oxygen species, cell death, the plasma membrane and root epidermal cell differentiation. Metabolome analysis revealed 72 and 107 differentially expressed metabolites (DEMs) under T500 and T2000, respectively, and 36 co-DEMs. KEGG analysis of the DEMs and DEGs revealed a common metabolic pathway, namely, flavonoid biosynthesis. An association study between the flavonoid biosynthesis-related DEMs and DEGs revealed 20 genes associated with flavonoid-related metabolites, including 3 for genistin and 17 for calycosin. CONCLUSION: In summary, the study reveals that flavonoid metabolism plays an important role in response to Pb stress in maize, which not only provides genetic resources for the genetic improvement of maize Pb tolerance in the future but also enriches the theoretical basis of the maize Pb stress response.

Combined GWAS and QTL analysis for dissecting the genetic architecture of kernel test weight in maize.

Kernel weight in a unit volume is referred to as kernel test weight (KTW) that directly reflects maize (Zea mays L.) grain quality. In this study, an inter-mated B73 × Mo17 (IBM) Syn10 doubled haploid (DH) population and an association panel were used to identify loci responsible for KTW of maize across multiple environments. A total of 18 significant KTW-related single-nucleotide polymorphisms (SNPs) were identified using genome-wide association study (GWAS); they were closely linked to 12 candidate genes. In the IBM Syn10 DH population, linkage analysis detected 19 common quantitative trait loci (QTL), five of which were repeatedly detected among multiple environments. Several verified genes that regulate maize seed development were found in the confidence intervals of the mapped QTL and the LD regions of GWAS, such as ZmYUC1, BAP2, ZmTCRR-1, dek36 and ZmSWEET4c. Combined QTL mapping and GWAS identified one significant SNP that was co-identified in the both populations. Based on the co-localized SNP across the both populations, 17 candidate genes were identified. Of them, Zm00001d044075, Zm00001d044086, and Zm00001d044081 were further identified by candidate gene association study for KTW. Zm00001d044081 encodes homeobox-leucine zipper protein ATHB-4, which has been demonstrated to control apical embryo development in Arabidopsis. Our findings provided insights into the mechanism underlying maize KTW and contributed to the application of molecular-assisted selection of high KTW breeding in maize.

A combination of linkage mapping and GWAS brings new elements on the genetic basis of yield-related traits in maize across multiple environments.

KEY MESSAGE: Using GWAS and QTL mapping identified 100 QTL and 138 SNPs, which control yield-related traits in maize. The candidate gene GRMZM2G098557 was further validated to regulate ear row number by using a segregation population. Understanding the genetic basis of yield-related traits contributes to the improvement of grain yield in maize. This study used an inter-mated B73 × Mo17 (IBM) Syn10 doubled-haploid (DH) population and an association panel to identify the genetic loci responsible for nine yield-related traits in maize. Using quantitative trait loci (QTL) mapping, 100 QTL influencing these traits were detected across different environments in the IBM Syn10 DH population, with 25 co-detected in multiple environments. Using a genome-wide association study (GWAS), 138 single-nucleotide polymorphisms (SNPs) were identified as correlated with these traits (P < 2.04E-06) in the association panel. Twenty-one pleiotropic QTL/SNPs were identified to control different traits in both populations. A combination of QTL mapping and GWAS uncovered eight significant SNPs (PZE-101097575, PZE-103169263, ZM011204-0763, PZE-104044017, PZE-104123110, SYN8062, PZE-108060911, and PZE-102043341) that were co-located within seven QTL confidence intervals. According to the eight co-localized SNPs by the two populations, 52 candidate genes were identified, among which the ear row number (ERN)-associated SNP SYN8062 was closely linked to SBP-transcription factor 7 (GRMZM2G098557). Several SBP-transcription factors were previously demonstrated to modulate maize ERN. We then validated the phenotypic effects of SYN8062 in the IBM Syn10 DH population, indicating that the ERN of the lines with the A-allele in SYN8062 was significantly (P < 0.05) larger than that of the lines with the G-allele in SYN8062 in each environment. These findings provide valuable information for understanding the genetic mechanisms of maize grain yield formation and for improving molecular marker-assisted selection for the high-yield breeding of maize.

Genome-wide association studies and QTL mapping uncover the genetic architecture of ear tip-barrenness in maize.

Ear tip-barrenness (ETB) phenotype threatens crop yield, because it reduces the kernel number per ear. The genetic basis of ETB in maize remains largely unknown. Herein, a genome-wide association study (GWAS) and quantitative trait loci (QTL) mapping were jointly applied to identify the significant genetic loci interrelated with ETB. Six significant SNPs were detected at a stringent P-value threshold (1.95 × 10-6 ). Additionally, four environment-stable SNPs were co-detected across a single environment and best linear unbiased prediction (BLUP) model at a less stringent P-value threshold (1 × 10-4 ). The above 10 SNPs were closely linked to 6 candidate genes, which mainly involved seed development, photosynthesis and ethylene response. Moreover, the ratio of superior allele at each significant SNP ranged from 0 to 83.33% in 30 investigated maize elite lines. QTL mapping identified 14 QTL with phenotypic variation explained (PVE) ranging from 3.64 to 7.09%, of which one QTL (qETB2-1) was repeatedly identified in two environments. Combined analysis of GWAS and QTL mapping showed that one SNP (PZE-102175229, chromosome 2: 217 66 Mb) was located in the QTL (qETB2-2, chromosome 2: 215 90-217 82 Mb). Eighteen gene models situated in the linkage disequilibrium (LD) region of the co-localized SNP were further used to evaluate their correlation with ETB by candidate gene association analysis. Two superior haplotypes and two superior alleles were detected among 74 lines for Zm00001d007195, Zm00001d007197 and Zm00001d007201. These results provide more information for clarifying the molecular mechanism of ETB and for speeding up the genetic improvement of maize varieties.

Combined linkage mapping and association analysis reveals genetic control of maize kernel moisture content.

The free moisture in crop kernels after being naturally dried is referred to as kernel moisture content (KMC). Maize KMC reflects grain quality and influences transportation and storage of seeds. We used an IBM Syn10 DH maize population consisting of 249 lines and an association panel comprising 310 maize inbred lines to identify the genetic loci affecting maize KMC in three environments. Using the IBM population detected 13 QTL on seven chromosomes, which were clustered into nine common QTL. Genome-wide association analysis (GWAS) identified 16 significant SNPs across the 3 environments, which were linked to 158 genes across the three environments. Combined QTL mapping and GWAS found two SNPs that were located in two of the mapped QTL, respectively. Twenty-three genes were linked with the loci co-localized in both populations. Of these 181 genes, five have previously been reported to be associated with KMC or to regulate seed development. These associations were verified by candidate gene association analysis. Two superior alleles and one favorable haplotype for Zm00001d007774 and Zm00001d047868 were found to influence KMC. These findings provide insights into molecular mechanisms underlying maize KMC and contribute to the use of marker-assisted selection for breeding low-KMC maize.

Combination of multi-locus genome-wide association study and QTL mapping reveals genetic basis of tassel architecture in maize.

Maize tassel architecture is a complex quantitative trait that is significantly correlated with biomass yield and grain yield. The present study evaluated the major trait of maize tassel architecture, namely, tassel branch number (TBN), in an association population of 359 inbred lines and an IBM Syn 10 population of 273 doubled haploid lines across three environments. Approximately 43,958 high-quality single nucleotide polymorphisms were utilized to detect significant QTNs associated with TBN based on new multi-locus genome-wide association study methods. There were 30, 38, 73, 40, 47, and 53 QTNs associated with tassel architecture that were detected using the FastmrEMMA, FastmrMLM, EM-BLASSO, mrMLM, pkWMEB, and pLARmEB models, respectively. Among these QTNs, 51 were co-identified by at least two of these methods. In addition, 12 QTNs were consistently detected across multiple environments. Furthermore, 19 QTLs distributed on chromosomes 1, 2, 3, 4, 6, and 7 were detected in 3 environments and the BLUP model based on 6618 bin markers, which explained 3.64-10.96% of the observed phenotypic variations in TBN. Of these, three QTLs were co-detected in two environments. One QTN associated with TBN was localized to one QTL. Approximately 55 candidate genes were detected by common QTNs and LD criteria. One candidate gene, Zm00001d016615, was identified as a putative target of the RA1 gene. Meanwhile, RA1 was previously validated to plays an important role in tassel development. In addition, the newly identified candidate genes Zm00001d003939, Zm00001d030212, Zm00001d011189, and Zm00001d042794 have been reported to involve in a spikelet meristem identity module. The findings of the present study improve our understanding of the genetic basis of tassel architecture in maize.

A genetic study of the regeneration capacity of embryonic callus from the maize immature embryo culture.

We carried out a study of regeneration capacities of embryonic callus from maize immature embryo culture with 144 different inbred lines of natural groups from different countries, and found that the regeneration capacity was affected by three factors: environment, genotype and the interaction between the environment and genotype. We found that green embryonic callus rate (GCR), embryonic callus differentiating rate (CDR) and the plantlet number of embryonic callus regeneration (CPN) have significant positive correlations with each other, and they all have significant negative correlations with embryonic callus browning rate (CBR). Moreover, embryonic callus cloning index for the first subculture (CCI1) and embryonic callus cloning index for the second subculture (CCI2) have a significant positive correlation with each other, and CCI2 is positively correlated with green GCR, and is negatively correlated with CBR. Embryonic callus rooting rate (CRR) is positively correlated with GCR, CDR and CPN to some degree. Furthermore, we calculated Broad-Sense Heritability of each trait, and uncovered that the heritability index of CCI1, CCI2 and CRR was lower, and the heritability index of others was higher. In addition, by using the Ward method for two-way cluster analysis, we found eleven inbred lines with high regenerating abilities, and the rooting situation of regenerating plantlet was excellent by rooting culture, which could be used as the elite inbred lines of the maize transgenic receptor.

Multi-Locus Genome-Wide Association Study Reveals the Genetic Architecture of Stalk Lodging Resistance-Related Traits in Maize.

Stalk lodging resistance, which is mainly measured by stem diameter (SD), stalk bending strength (SBS), and rind penetrometer resistance (RPR) in maize, seriously affects the yield and quality of maize (Zea mays L.). To dissect its genetic architecture, in this study multi-locus genome-wide association studies for stalk lodging resistance-related traits were conducted in a population of 257 inbred lines, with tropical, subtropical, and temperate backgrounds, genotyped with 48,193 high-quality single nucleotide polymorphisms. The analyses of phenotypic variations for the above traits in three environments showed high broad-sense heritability (0.679, 0.720, and 0.854, respectively). In total, 423 significant Quantitative Trait Nucleotides (QTNs) were identified by mrMLM, FASTmrEMMA, ISIS EM-BLASSO, and pLARmEB methods to be associated with the above traits. Among these QTNs, 29, 34, and 48 were commonly detected by multiple methods or across multiple environments to be related to SD, SBS, and RPR, respectively. The superior allele analyses in 30 elite lines showed that only eight lines contained more than 50% of the superior alleles, indicating that stalk lodging resistance can be improved by the integration of more superior alleles. Among sixty-three candidate genes of the consistently expressed QTNs, GRMZM5G856734 and GRMZM2G116885, encoding membrane steroid-binding protein 1 and cyclin-dependent kinase inhibitor 1, respectively, possibly inhibit cell elongation and division, which regulates lodging resistance. Our results provide the further understanding of the genetic foundation of maize lodging resistance.