Background

Maize (Zea mays L.) is the world’s most widely grown crop for food, animal feed, biofuel and other industrial materials, and displays the highest global grain production [1]. By 2050, it is estimated that the human population will reach 9 billion [2]. Increasing yield while providing added nutritional value in maize is thus imperative to meet the growing nutritional demand of the huge global population [3, 40]. With the aid of high-throughput genoty** and metabolomics data, metabolic QTL were identified in a rice Zhenshan 97 and Minghui 63 recombinant inbred line (RIL) population, and some of the candidate genes for flavonoid content were further validated by examining over-expression transgenic rice lines [41]. A novel gene (BETA GLUCOSIDASE 6, BGLU6) was recently identified to be responsible for the production of flavonol 3-O-gentiobioside 7-O-rhamnoside (F3GG7R) in an Arabidopsis RIL population [42, 43]. In maize, hundreds of loci associated with metabolites from multiple pathways including flavonoid metabolism were identified, following genome wide association studies (GWAS) on a diverse maize population that revealing the genetic influences underlying metabolic variation [44]. In addition, near isogenic lines (NILs) containing P1-rr and P1-ww were used to study the co-expression and direct target genes of the R2R3-MYB transcription factor P1 [31]. Since P1 was proven to regulate some well-known genes involved in flavonoid biosynthesis, such as FLS1 and A1 through targeted molecular experiments [45], this study represented a great advance to systematically comprehend its gene regulatory circuitry. Maysin (C-glycosyl flavone) present in maize silks confers natural resistance to the corn earworm (Helicoverpa zea), which can cause severe damages on maize in the Americas [12]. Two loci that are capable of conferring salmon silks phenotypes, salmon silks 1 (sm1) and salmon silks 2 (sm2) were identified through QTL map** [30] in 2004. And previous genetic analyses predicted P1 to be epistatic to the salmon silk mutation [13]. Based on the available sm1 and sm2 map** information and knowledge of the genes regulated by P1 [13, 31], the molecular identification of the sm1 and sm2 gene products are revealed as a UDP-rhamnose synthase and a rhamnosyl transferase, respectively [12]. The molecular characterization of sm1 and sm2 therefore completes the maysin biosynthetic pathway. It can thus be anticipated that deep probing of further profiling studies will facilitate the elucidation of the genetic complexity of maize flavonoid biosynthesis. Indeed, integrative approaches are increasingly applied to enhance our understanding of metabolic pathway structure and regulation and how these affect the end-phenotypes of plants [46].

Previously, comprehensive metabolic profiling using liquid chromatography tandem mass spectrometry (LC-MS/MS) was carried out in mature maize kernels coming from several populations. Combined linkage analysis and GWAS was carried out on the resultant datasets which led to the identification of a variety of loci involved in multiple biosynthetic pathways [44,

Results

Variation of flavonoids in different maize populations

An association map** panel (AMP) and two RIL populations were planted in multiple environments (simply called AMPE1, AMPE2 for AMP, BBE1, BBE2 for BB RIL population, and ZYE1 and ZYE2 for ZY RIL population, which were described in detail in “Materials and Methods”) and the mature kernels harvested from these six field experiments were used for LC-MS/MS based metabolite profiling. In our previous metabolome-based GWAS study, 983 metabolite features were identified in the AMP [44]. 184 of these 983 metabolite features with chemical or putative annotations were analyzed in BB and ZY RIL populations subsequently [47]. In this study, we extract the profile of flavonoids from these previous datasets, which includes 29 flavonoids and five of them were chemically annotated. Briefly, these 29 flavonoids can be classified into flavones, flavanones, anthocyanins and methoxylated flavonoid. Among them, 28, 27, 23, 22, 25, 24 flavonoids were found in AMPE1, AMPE2, BBE1, BBE2, ZYE1, ZYE2, respectively, 15 flavonoids were detected in all the six environments (Table 1). The AMP and both RIL populations manifested great diversity in their flavonoid levels (Additional files 1 and 2: Tables S1 and S2), as indicated by the distribution of the log2 value of fold changes (Fig. 1a). In AMP, all flavonoids have broad-sense heritability (H2) greater than 0.3 and over 65% of flavonoids have H2 greater than 0.7. Over 45% and 60% of flavonoids have H2 greater than 0.5 in BB and ZY populations, respectively (Additional file 3: Figure S1). Correlation coefficient networks were also constructed based on flavonoid levels detected in each experiment, respectively, which demonstrated a clear separation between methoxylated flavonoids and other flavonoids, and most flavones were consistently linked to each other with R > 0.3 (Fig. 1b).

Table 1 Detailed information of 29 flavonoids detected in this study
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Fig. 1
figure 1

Distribution of log2-fold changes and correlation coefficient based network of all flavonoids measured in AMP and two RIL populations. a Box plots showing the log2 value of fold changes of 29 flavonoids among the AMP and both BB and ZY RILs. Data from different environments (experiments) for AMP and each RIL population are shown. b Correlation coefficient based network of all flavonoids in each experiment for AMP and both BB and ZY populations. R ≥ 0.3 for correlation coefficient between two flavonoids was used to construct the network

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GWAS for flavonoid levels

A total of 79 loci were identified by GWAS at significance level of P ≤ 1.8 × 10−6 in two experiments (AMPE1, AMPE2) (Table 2). Briefly, 51 loci were identified for 23 flavonoids in AMPE1, with an R2 (explained phenotypic variation) ranging from 6.84 to 19.77% and a mean of 8.93%; while 28 loci were detected for 18 flavonoids in AMPE2. Each locus could explain phenotypic variation ranging from 6.88 to 19.48%, with a mean of 10.19% (Additional file 4: Table S3). Of the 17 common flavonoids for which significant loci were detected in both experiments, a total of 42 and 27 loci were detected in AMPE1 and AMPE2, respectively, and 12 of which were conserved for the same flavonoids in both experiments (Additional file 5: Figure S2A). The detailed information for GWAS results including P value and R2 of each locus, physical position and minor allele frequency (MAF) of lead SNP and the most likely candidate gene and its annotation are provided in Additional file 4: Table S3. All potential candidate genes and their functional annotations within 100 kb (50 kb upstream and downstream of the lead SNP) of the loci identified from GWAS are listed in Additional file 6: Table S4.

Table 2 Summary of significant loci-trait associations identified by GWAS and QTL identified by linkage map**
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Linkage map** for flavonoid levels in the two RIL populations

For the BB population, 51 and 55 QTL were mapped for 22 flavonoids in BBE1 and BBE2, respectively (Table 2). A total of 99 QTL were detected for the 19 common flavonoids in both experiments (Additional file 7: Table S5), 12 QTL of which were conserved for the same flavonoid in both experiments (Additional file 5: Figure S2B). The percentage of phenotypic variation (R2) that each QTL could explain ranged from 2.94 to 76.79%, with a mean of 10.33% (Additional file 7: Table S5). Twenty-nine QTL that explained greater than 10% of the phenotypic variation (R 2 = 10.03-76.79%) were identified.

In the ZY population, a total of 123 QTL were detected in the two experiments (Table 2). Each QTL could explain between 2.85 and 23.17% of phenotypic variation, with an average variation of 9.35%. 47 QTL were identified that explained greater than 10% of the variation (R 2 = 10.02–23.17%). Specifically, 64 QTL were detected for 23 flavonoids in ZYE1 (Table 2), with an R2 range of 4.81 to 23.17% and a mean of 9.38%, while in ZYE2, 59 QTL were identified for 23 flavonoids (Table 2) and an R2 range of 2.85–18.34% with a mean of 9.31% (Additional file 7: Table S5). Of the 21 common flavonoids for which could detected QTL in both experiments, a total of 57 and 51 QTL were detected in ZYE1 and ZYE2, respectively, 27 of which were conserved for the same flavonoids in both experiments (Additional file 5: Figure S2C).

Linkage map** results from both BB and ZY populations indicated that most flavonoid QTL were identified with moderate effects (R 2 < 10%), while a relatively small portion showed major effects (27.4% QTL for BB and 38.2% QTL for ZY with an R 2 ≥ 10%). The identified QTL in both RIL populations are evenly distributed across the maize genome, and detailed information for the QTL results, including logarithm of odds (LOD) value, 2-LOD confidence interval, explained phenotypic variation (R2) of each QTL, as well as candidate genes and their annotations are provided in Additional files 7 and 8: Tables S5 and S6. Two and four flavonoids QTL hot spots were observed across the maize genome in the BB and ZY population, respectively, determined by using 500 permutations at the level of 0.05 (Additional file 5: Figure S2B-S2C; Additional file 7: Table S5). These QTLs were shared by flavonoids that are biochemically related and three known flavonoid pathway genes (p1, c2 and mrpa3) located in hot spots on chromosome 1, 4 and 9, respectively (Additional file 5: Figure S2A, S2C).

In Additional file 9: Table S7, the co-localization of QTL and/or significant loci identified across different environments or different populations is summarized. Overall, 49 trait-loci combinations that are 25 QTLs corresponding to 23 traits were detected in more than one environments or populations (AMP, BBRIL, ZYRIL) in this study (Additional file 9: Table S7). Among them, 11 combinations (six loci for 11 traits) were detected in more than two environments which including seven combinations (five loci for seven traits) identified in four environments. Detailed analyses of the candidate genes underlying these loci will almost certainly provide useful further information concerning the flavonoid biosynthetic pathway.

Candidate genes revealed by multiple evidences

In our previous study, a primary regulatory network consisted of 58 candidate genes for the flavonoid biosynthetic pathway was constructed using an eQTL and qGWAS method based on the expression level of 15 known maize flavonoid pathway genes [3).

Table 3 Candidate genes of flavonoid biosynthetic pathway revealed by multiple evidences
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In Table 3, we summarized genes for which multiple lines of evidence were provided, i.e., these are genes repeatedly identified in multiple populations or across multiple environments or overlapped genes between the result of network analysis and genetic map** (Table 3). Three of the 11 genes from the primary network and 14 of the 28 genes from the secondary network mentioned above were detected in more than two environments or for more than two flavonoids in one environment, respectively (Table 3). These genes were subsequently prioritized for further functional characterization. 40% of these 45 candidate genes revealed by multiple evidences mentioned above were annotated as enzymes, while functions of 29% of these genes remain unknown. Genes that were annotated as transcription factor and participating in cellular organization only accounted for a small proportion (Additional file 10: Figure S3).

Functional verification of candidate genes underlying the natural variation of flavonoids in the mature maize kernel

According to the map** results and multiple information regarding prior knowledge of flavonoid biosynthesis and functional annotation of candidate genes, we chose several genes that were supported by multiple evidences for further verification. A QTL on chromosome 6 was identified for the level of C-pentosyl-apigenin O-caffeoylhexoside (n1270) in the B73/BY804 RIL population (Fig. 2a). Three genes, GRMZM2G162755 (UGT1, chr6:119876153-119878032), GRMZM2G162783 (UGT3, Chr6:119,862,763-119,864,524) and GRMZM2G383404 (UGT4, chr6:120018887-120020772) which are all annotated as flavonoids 3-O-glucosyltransferase are located within this QTL. UGT1 is about 12Kb upstream of UGT3, and both genes were identified as targets of the R2R3-MYB transcript factor P1 [31]. UGT1 co-expressed with several genes involved in the flavonoid pathway, such as C2 (GRMZM2G422750, chalcone synthase), Chi1 (GRMZM2G155329, chalcone flavanone isomerase 1) and Pr1 (GRMZM2G025832, cytochrome P450) [80]

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Herein we looked into the genetic variations between the two parental lines of the BB RIL population (B73 and By804) and found seven SNPs between the parents in the coding sequence of UGT1, which could cause nonsynonymous mutations (Fig. 2d). Three pairs of KASP (LGC) primers which can successfully genotype three (i.e., SNP811, SNP1331, and SNP1415) of the seven SNPs were used to test the association panel aiming to validate the function of these three SNPs in UGT1. They all exhibited a minor allele frequency (MAF) of more than 0.05. At the sites SNP811 (a Pro to Ala variant) and SNP1331 (a Gly to Glu variant), phenotypic values of lines with the alleles from the two parents were significantly different (t test, P < 0.05; Fig. 2c). Significant phenotypic differences between the lines harboring B73 alleles and By804 alleles were also observed for several other flavonoids detected in this study. For instance, the levels of three apigenin derivatives, chrysoeriol and six chrysoeriol derivatives, four tricin derivatives and cyanidin 3-O-glucoside detected in lines with two parental alleles at SNP811 were significantly different. Similarly, the levels of cyanidin 3-O-glucoside, chrysoeriol di-C-hexoside, 3′,4′,5′-tricetin-O-hexoside and apigenin C-pentosyl-O-coumaroylhexoside in lines with two parental alleles at SNP1331 were significantly different (Additional file 11: Figure S4). In addition, we conducted candidate association analysis using these three SNPs - SNP1331 displayed the lowest P value and can therefore be considered as the most promising functional site among these three SNPs (Additional file 12: Table S8). Compared to SNP811, SNP1331 was associated with more flavonoids, which may suggest that it exhibits broader substrate specificity.

GRMZM2G383404 (UGT4) is around 142 kb away from UGT1, which is associated with the level of apigenin C-pentosyl-C-pentoside (n1201) as revealed by our previous genome wide association analysis, and an amino acid substitution (Asp to Ala) was suggested as one of the functional genetic variants [44]. In the present study, we generated over-expression lines by ectopically expressing GRMZM2G383404 under the control of the maize ubiquitin promoter in the rice cultivar Zhonghua11 (Fig. 3a). We detected the level of flavonoids in the rice leaves of the wild type and T1 individuals of two over-expression lines (L4 and L5) (Fig. 3b). The level of more than half (14/26) of the detected flavonoids were significantly decreased in the over-expression lines. The fold change of these 14 flavonoids between the over-expression lines and wild type ranged from 0.25 to 0.68 (Fig. 3c and Additional file 13: Figure S5). Among them, fold change between the over-expression lines and wild type of the level of apigenin C-pentosyl-C-pentoside was around 0.65. Along with apigenin C-pentosyl-C-pentoside, two other apigenin derivatives (i.e., apigenin 7-O-glucoside and apigenin di-C-hexoside) were also affected (Additional file 13: Figure S5). Notably, the level of all the tricin derivatives detected here (and tricin itself) was significantly decreased (Additional file 13: Figure S5). Moreover, the content of chrysoeriol, chrysoeriol O-hexoside and vitexin were also significantly decreased (Additional file 13: Figure S5). However, no significant changes were found for the content of C-pentosyl-apigenin O-caffeoylhexoside, for which UGT4 was identified in the QTL region as mentioned above. Hence, UGT1 and UGT3 but not UGT4 could be the causative genes for the variance of C-pentosyl-apigenin O-caffeoylhexoside. However, the transgenic result of UGT4 can suggest its influence in the flavonoid biosynthesis. However, further biochemical assay is needed to strongly confirm the function and activity.

Fig. 3
figure 3

Transgenic result of UGT4. a Diagram of over-expression construct. b The bar plot showing the average mRNA level of UGT4 (GRMZM2G383404) in the wild type (WT) and over-expression lines (T1) (the individual number is 9, 5, 9 for WT, L4 and L5, respectively, 3 technical replicates for each line). c The bar plot showing the relative contents of apigenin C-pentosyl-C-pentoside (n1201) in the WT and UGT4 over-expression lines (n = 9, 5, 9 for WT, L4 and L5, respectively), * and ** represent the significant level of P < 0.05 and P 0.01, respectively

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On chromosome 2, gene GRMZM5G843555 was suggested to be important in determining the level of apigenin C-pentosyl-O-coumaroyl hexoside (n1268) by both linkage map** in Zong3/Yu87-1 population (Fig. 4a) and GWAS in AMPE1 (Fig. 4c). GRMZM5G843555 is annotated as an oxoglutarate/iron-dependent oxygenase (OXY), which belongs to the oxygenase superfamily. However, GRMZM5G843555 (OXY) shows low sequence similarity with the well-known 2-ODD genes, such as FNS. OXY is one of the maize prolyl 4-hydroxylase family (P4Hs) members, which may play a role in tolerance to abiotic stresses, such as water-logging [48]. Correlations between the content of various flavonoids and the expression level of OXY revealed that the content of chrysoeriol, chrysoeriol O-rhamnosyl-O-hexoside, tricin O-rhamnosyl-O-hexoside and 3′,4′,5′-tricetin O-rhamnosyl-O-hexoside, chrysoeriol O-hexoside, chrysoeriol di-C-hexoside and chrysoeriol C-hexosyl-O-rhamnoside were negatively correlated with expression level of OXY (r = -0.19 ~ -0.1; p < 0.05) (Fig. 4d). We further profiled the rice over-expression lines and quantified the level of 26 flavonoids (Fig. 4b). The levels of 20 flavonoids were significantly decreased compared with that of the wild type (Fig. 4e-h, Additional file 14: Figure S6). Within these 20 flavonoids, the content of six flavonoids was negatively correlated with the OXY expression level. Based on the result, we speculate that the OXY may act as a competitor or inhibitor of the flux through the apigenin, chrysoeriol and tricin branches of flavonoid metabolism.

Fig. 4
figure 4

Linkage and association map** of OXY and validation by transformation. a and c Diagram of linkage map** and GWAS results for the level of Apigenin C-pentosyl-O-coumaroylhexoside in maize kernel. LOD values are shown as a function of their genetic positions. And the peak SNP is located within OXY (GRMZM5G843555). b The bar plot showing the mRNA level of OXY in wild type (WT) and over-expression lines (T1) (the individual number is 6, 10, 7, 8 for WT, L31, L35, L36 and L37, respectively, 3 technical replicates for each line individual). d Plot of correlation between the content of different flavonoids and the normalized expression level of gene OXY in association panel. e-h The bar plot for the relative contents (fold change relative to the mean level of each flavonoid) of naringenin, chrysoeriol, vitexin and tricin between the WT and OXY over-expression lines (n = 6, 10, 10, 10 respectively). * and ** represent the significant level of P < 0.05 and P < 0.01, respectively

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In addition, abundant genetic variants between Zong3 and Yu87-1 in the promoter region of OXY were observed (Additional file 15: Figure S7). Cis-element prediction using PlantCARE (http://bioinformatics.psb.ugent.be/webtools/plantcare/html/) found a variant between the sequences of the two parental lines at the MBS II (MYB binding site II, [49]). The variant at this binding site may affect the function of OXY through transcriptional regulation, as suggested by the finding in Petunia Hybrida [49]. Indeed, a strong cis-eQTL for OXY was identified in our previous study, which may suggest the potential function of this genetic variant at the upstream of this gene (Additional file 16: Figure S8).

To investigate the co-expression mode of the above mentioned genes, a qGWAS-based network was constructed (Fig. 5). GRMZM5G843555 (OXY) is not in this network for no related genes found by using the threshold of P < 3.5 × 10−7 (0.01/28369). UGT4 clustered independently from the rest. Four well-known genes involving in the flavonoids biosynthesis are present in the co-expression network, such as a1 (GRMZM2G026930), c2 (GRMZM2G422750), chi1 (GRMZM2G155329) and whp1 (GRMZM2G151227). 22 uncharacterized genes are also revealed in the network, including a gene homologous to chalcone isomerase (GRMZM2G175076) and other 21 genes with unknown function or without direct functional annotations related to flavonoid biosynthesis.

Fig. 5
figure 5

Co-expression network for UGT1, UGT2, UGT3 and UGT4 based on a qGWAS method. The red indicates these four genes. The green diamond indicates the known enzyme involved in the flavonoid pathway. The blue circle indicates the uncharacterized co-expressing genes

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