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. 2022 Nov 23;191(2):1305–1323. doi: 10.1093/plphys/kiac519

Multi-omics analysis reveals the mechanism of bHLH130 responding to low-nitrogen stress of apple rootstock

Xiaona Wang 1,2, Xiaofen Chai 3,4, Beibei Gao 5,6, Cecilia Deng 7, Catrin S Günther 8, Ting Wu 9,10, Xinzhong Zhang 11,12, Xuefeng Xu 13,14, Zhenhai Han 15,16,b, Yi Wang 17,18,✉,c,b
PMCID: PMC9922409  PMID: 36417197

Abstract

Nitrogen is critical for plant growth and development. With the increase of nitrogen fertilizer application, nitrogen use efficiency decreases, resulting in wasted resources. In apple (Malus domestica) rootstocks, the potential molecular mechanism for improving nitrogen uptake efficiency to alleviate low-nitrogen stress remains unclear. We utilized multi-omics approaches to investigate the mechanism of nitrogen uptake in two apple rootstocks with different responses to nitrogen stress, Malus hupehensis and Malus sieversii. Under low-nitrogen stress, Malus sieversii showed higher efficiency in nitrogen uptake. Multi-omics analysis revealed substantial differences in the expression of genes involved in flavonoid and lignin synthesis pathways between the two materials, which were related to the corresponding metabolites. We discovered that basic helix–loop–helix 130 (bHLH130) transcription factor was highly negatively associated with the flavonoid biosynthetic pathway. bHLH130 may directly bind to the chalcone synthase gene (CHS) promoter and inhibit its expression. Overexpressing CHS increased flavonoid accumulation and nitrogen uptake. Inhibiting bHLH130 increased flavonoid biosynthesis while decreasing lignin accumulation, thus improving nitrogen uptake efficiency. These findings revealed the molecular mechanism by which bHLH130 regulates flavonoid and lignin biosyntheses in apple rootstocks under low-nitrogen stress.

Under low-nitrogen stress, multi-omics analysis revealed that transcription factor bHLH130 affects apple rootstock nitrogen uptake by regulating the flavonoid pathway.

Introduction

Nitrogen is an essential macronutrient for all life and central to plant primary metabolism, directly affecting plant growth and development. Plants predominantly acquire nitrogen through their roots in the form of ammonium and nitrate or incorporated into small organic compounds, such as urea (Kiba and Krapp, 2016). In order to improve yield and increase the application of nitrogen fertilizer, it has caused serious environmental problems (Sun et al., 2018). Thus, understanding the molecular mechanism of plant response to low-nitrogen stress is essential for selecting good rootstocks and increasing yield.

In response to nitrogen deficiency, plants will produce a series of stress responses, such as reduced photosynthesis, which is accompanied by leaf chlorosis and anthocyanin accumulation. To overcome low-nitrogen stress, however, plants display elaborate responses to enhance nitrogen uptake efficiency by changing root physiology and architecture (Chun et al., 2005; Nacry et al., 2013). It is well evidenced that nitrogen-use-efficient genotypes develop more root tips and larger root surface areas, than nitrogen-use-inefficient genotypes, resulting in improved nitrogen uptake capacity and utilization efficiency.

The aromatic amino acid phenylalanine (Phe) is the primary substrate for phenylpropanoid biosynthesis, providing precursors for both lignin and flavonoid biosyntheses. Using multi-omics analyses, Phe metabolism was recently highlighted to partake in regulating root architecture and physiological characteristics under both high- and low-nitrogen conditions (Xin et al., 2019). The same study showed that the plant hormone signal transduction pathway was substantially enriched under low-nitrogen conditions, increasing the concentrations of stress-related hormones such as abscisic acid (ABA), jasmonic acid (JA), and salicylic acid (SA). Metabolic cross-talk between increased flavonoid production and auxin transportation is known to influence plant leaf pigmentation and scavenging of free radicals under stress (Santelia et al., 2008).

The expression of genes related to flavonoid biosynthesis pathway is regulated by different transcription factor (TF) families including MYB, basic helix–loop–helix (bHLH), WD40, and WRKY families (Tohge et al., 2005; Li et al., 2020). However, certain MYBs can also directly bind to the promotors of structural genes and regulate their expression. In apple (Malus domestica) fruit, the repressor MdMYB16 can suppress the expression of anthocyanidin synthase gene (ANS) and anthocyanin 3-O-glycosyltransferase gene (A3GT) directly (Xu et al., 2017) and also activate the expression of cinnamoyl-coenzyme A reductase gene (CCR), which catalyzes the final step of monolignol biosynthesis, as part of a MdMYB16/MDMYB1-miR7125-MdCCR module, thus regulating the homeostasis between anthocyanin and lignin biosyntheses (Hu et al., 2021). The bHLH protein is central to the MBW complex by binding to both MYB and WD40 proteins, which cannot directly interact with each other. In Arabidopsis (Arabidopsis thaliana), the bHLH TF family is subdivided into 12 subgroups, and members of subgroup III are predominantly associated with the gene regulation of the flavonoid pathway (Heim et al., 2003), in particular activation of anthocyanin biosynthesis. MYB-repressors and activators share the same region that binds bHLH proteins, and research on bHLH-mediated repression of the flavonoid pathway has predominantly focused on the role of the MYB partner (Chen et al., 2019a). In fact, less than a handful of studies report bHLH-mediated repression of anthocyanins (Burr et al., 1996; Zhao et al., 2019, 2020), and the molecular mechanisms remain to be elucidated.

Developmental anthocyanin biosynthesis is common in angiosperms and particularly enriched in reproductive organs, such as flowers and fruits (Winkel-Shirley, 2001), often promoting mutualistic interactions. However, most if not all higher land plants also produce anthocyanins in vegetative organs and in particular as response to biotic and abiotic stresses, such as high-ultraviolet B (UVB) (Davies et al., 2020). In Populus trichocarpa, UVB treatment induced the expression of B-box 23 (BBX23) transcription factor, which activated the expression of MYB TFs and structural genes of the flavonoid metabolic pathway, and promoted the accumulation of procyanidins and anthocyanins (Li et al., 2021). That stress-anthocyanins accumulate in leaves as an adaptive response to nitrogen limitation is well established (Peng et al., 2008) and suggested to aid in the protection of the photosynthetic apparatus from excess light. However, recent studies have shown that nitrogen limitation also induced anthocyanin accumulation in apple roots and that this played an important role in plant tolerance to low-nitrogen stress (Sun et al., 2018).

Plant stress tolerance to nitrogen deficiency is a multidimensional trait, and we used two apple rootstock species with contrasting tolerance to low-nitrogen stress as a model to elucidate the underlying molecular mechanisms. To identify regulatory metabolic pathways and associated candidate TFs, an untargeted metabolomics and transcriptomics approach was chosen, based on differential analyses. We further studied the regulatory function of candidate TFs using in vitro and in vivo experiments. Finally, we used the apple rootstock with low-nitrogen uptake efficiency to study the mechanism underlying nitrogen uptake changes by overexpression or silencing of bHLH130. This study introduces the molecular regulatory mechanism mediating the stress response to low nitrogen in plant roots. Moreover, our data suggest a molecular marker as a potential target for the breeding of low-nitrogen stress-resilient cultivars.

Results

Differences in nitrogen uptake efficiency of different apple rootstocks in response to low nitrogen

Two apple rootstock species, Malus hupehensis (Mh) and Malus sieversii (Ms), which have contrasting responses to nitrogen limitation (Wang et al., 2012), were selected to investigate the physiological mechanisms in response to low-nitrogen stress. Plant stress in response to low nitrogen supply was most apparent for Mh and indicated by leaf chlorosis, lower shoot biomass, total nitrogen accumulation, and NO3− concentration (Figure 1 , A–C; Supplemental Figure S1, A and B). Compared with Mh, low nitrogen treatment significantly increased root/shoot ratio, root activity, root biomass, and nitrogen uptake efficiency of Ms (Figure 1, D–F; Supplemental Figure S1C). In addition, compared with normal nitrogen (CK), root system architecture (RSA) was significantly increased under low nitrogen conditions: the root tip number, root volume, root surface area, and root forks of Ms were significantly higher than those of Mh, which might give Ms a more developed RSA (Supplemental Figure S2, A–F). These results indicated that nitrogen uptake was more efficient in Ms under low-nitrogen conditions and likely mitigating low-nitrogen stress in this rootstock species.

Figure 1.

Figure 1

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Comparison of nitrogen uptake efficiency of two different apple rootstocks Malus hupehensis (Mh) and Malus sieversii (Ms) treated with normal nitrogen (3.3 mM KNO3, CK) and low-nitrogen (0.3 mM KNO3, LN) conditions for 15 days. (A) Phenotype of leaves. Scale bar: 1 cm. Total nitrogen accumulation (B), root NO3− concentration (C), root/shoot ratio (D), root activity (E), and nitrogen uptake efficiency (F) in the roots of Mh and Ms. DW, dry weight; FW, fresh weight; RDW, root dry weight. The bar graphs represent the means ± SE from six biological replicates. Asterisks indicate significant differences between the test group and the control group (based on the Student's t test: *P < 0.05; **P < 0.01).

Transcriptome analysis revealed that low-nitrogen stress tolerance is associated with differential gene expression of the flavonoid and lignin pathways

In order to understand the gene regulatory network of both apple rootstock species in detail, RNA-sequencing (RNA-Seq) was performed on roots of Mh and Ms treated with low nitrogen for 0, 24, and 96 h, respectively. The base quality Q30 (the number of bases with sequencing error rate ≤0.1%) was above 93% for all the RNA-Seq libraries, and the overall mapping rate ranged from 78.97% to 89.81% against the apple reference genome (GDDH13; Supplemental Table S1; Daccord et al., 2017). The correlation coefficient heat map and principal component analysis (PCA) validated that the three biological replicates clustered well for each treatment, and there was a substantial separation between the two apple rootstock species (Figure 2A; Supplemental Figure S3). Using samples at 0 h as control, in Mh, 3,094 (1,032 up and 2,062 down) and 4,618 (1,864 up, 2,754 down) differentially expressed genes (DEGs) were detected after 24 and 96 h of low-nitrogen treatment, respectively. In Ms, the total number of DEGs was approximately three-fold higher compared with Mh at 24 h (11,449 total, 4,772 up, 6,677 down) as well as 96 h (11,170 total, 4,505 up, 6,665 down) of low-nitrogen treatment (Figure 2B).

Figure 2.

Figure 2

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Transcriptome analysis of Malus hupehensis (Mh) and Malus sieversii (Ms) under different times of low-nitrogen treatment. (A) Principal component analysis (PCA). (B) Numbers of differentially expressed genes (DEGs) detected between Mh and Ms after low-nitrogen treatment (control: 0 h). (C) GO enrichment cycle diagram of Mh and (D) Ms treated with low nitrogen for 24 and 96 h. From outside to inside, the first circle represents the GO ID number corresponding to different grouping colors, and the length of the bar in the second circle is the gene enriched in the pathway. The color intensity represents the P-value. The third circle represents the number of DEGs enriched in the pathway, including upregulated genes and downregulated genes. The fourth circle (polar bar graph) represents the enrichment factor of the 20 most highly significantly enriched pathways. (E) The DEGs Venn diagram for different treatments of each comparison group and the unique and common pathways of DEGs enrichment between apple rootstock species and treatment time.

GO functional annotation results showed that these DEGs were mainly associated with “biological processes,” “molecular functions,” and “cellular components”. DEG metabolic categories within these groups, however, differed for both apple rootstock species (Figure 2, C and D; Supplemental Tables S2 and S3) in response to low nitrogen, indicating that not only the number but also the biological function of DEGs in response to low nitrogen was different between the two rootstock species.

DEGs that were rootstock specific and time-independent were further analyzed, and this identified 1,885 common DEGs in Mh and 8,863 common DEGs in Ms across low-nitrogen treatment time. Cross-comparison of these time-independent DEGs between apple rootstock species identified that 433 and 7,411 DEGs were unique to Mh and Ms, respectively (Figure 2E; Supplemental Figure S4). KEGG enrichment analysis illustrated that these species-specific DEGs were mainly genes related to the flavonoid and lignin biosynthesis pathways (Figure 2E; Supplemental Figure S5, A and B; Supplemental Table S4). The remaining time-independent DEGs (1,452) were common for both apple rootstock species and mainly identified as genes related to plant hormone signal transduction and MAPK signaling pathways (Figure 2E; Supplemental Figure S5C; Supplemental Table S4).

We further compared the species-independent effect of low-nitrogen treatment time on gene expression (Figure 2E; Supplemental Table S4) and identified 2,344 common DEGs after 24 h, and 3,168 common DEGs after 96 h. Cross-comparison between 24 and 96 h revealed 892 time-dependent DEGs unique for 24 h of low-nitrogen treatment. KEGG enrichment analysis showed that these DEGs were mainly related to lignin biosynthesis (Figure 2E; Supplemental Figures S6 and S7A; Supplemental Table S5). The time-dependent DEGs (1,716) unique to 96 h were mainly genes related to carbon metabolism and flavonoid biosynthesis pathway (Figure 2E; Supplemental Figures S6 and S7B; Supplemental Table S5). In both apple rootstock species, low-nitrogen treatment induced lignin- and flavonoid pathway-related genes in a time-dependent and plant hormone-related genes in a time-independent manner. Overall gene expression was more strongly altered in Ms compared with that in Mh, and Ms-specific DEGs were predominantly enriched in the flavonoid pathway.

Upregulation of CHS and downregulation of HCT corresponded with low-nitrogen stress tolerance in apple rootstock

Based on the transcriptome analysis, we found that plant hormone signal transduction, flavonoid, and lignin biosynthesis pathways played a positive role in apple rootstocks in response to low-nitrogen stress and further explored the key regulatory mechanisms.

In the plant hormone signal transduction pathway, low-nitrogen treatment affected genes related to ethylene, auxin, ABA, SA, JA, brassinosteroid, cytokine, and gibberellin pathways (Figure 3A). Most of these DEGs were downregulated in both apple rootstock species, except for DELLA protein (MD17G1260700) and a soluble gibberellin receptor GID1 (MD12G1227200), which are both enriched in the gibberellin pathway and upregulated in both species. In addition, the SA-related TF TGA (MD16G1046000) and auxin response protein SAUR (MD08G1015100) genes were also increased in response to low nitrogen (Supplemental Table S6).

Figure 3.

Figure 3

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Analysis of DEGs related to plant hormone signal transduction and flavonoid and lignin biosynthesis pathways. Heat map of DEGs involved in (A) plant hormone signal transduction and (B) lignin and flavonoid biosynthesis as represented by the pathway map. PAL, Phenylalanine ammonia-lyase; C4′H, cinnamic acid 4-hydroxylase; 4CL, 4-coumarate-CoA ligase; HCT, hydroxycinnamoyl-CoA transferase; C3H, coumaroylshikimate 3′-monooxygenase; CCoAOMT, caffeoyl-CoA O-methyl transferase; F5H, ferulate-5-hydroxylase; CCR, cinnamoyl-CoA reductase; CAD, cinnamyl alcohol dehydrogenase; COMT, caffeic acid 3-O-methyltransferase; CHS, chalcone synthase; CHI, chalcone isomerase; F3H, flavanone 3-hydroxylase; F3′H, flavonoid-3′-hydroxylase; DFR, dihydroflavonol 4-reductase; ANS, anthocyanidin synthase; FLS, flavonol synthase; A3GT, UDP-glucose: anthocyanidin 3-O-glucosyltransferase; LAR, leucocyanidin reductase; ANR, anthocyanidin reductase; FNS, flavonoid synthase. C, the relative expression levels of flavonoid pathway-related and HCT genes at 0, 24, and 96 h after low-nitrogen treatment. Malus hupehensis (Mh), Malus sieversii (Ms). Data are presented as means ± SE from three biological replicates. Significant differences compared with the 0 h were determined using One-way ANOVA: *P < 0.05; **P < 0.01; ***P < 0.001.

The phenylpropanoid pathway links plant primary with secondary metabolism, and PAL, C4′H, and 4CL work in concert to convert Phe to p-coumaroyl-CoA. A total of 18 DEGs were detected from the flavonoid pathway (chalcone synthase, CHS; chalcone isomerase, CHI; flavanone 3-hydroxylase, F3H; flavonoid-3′-hydroxylase, F3′H; dihydroflavonol 4-reductase, DFR; leucocyanidin reductase, LAR; anthocyanidin synthase, ANS; anthocyanidin reductase, ANR; flavonoid synthase, FNS; and anthocyanin 3-O-glycosyltransferase, A3GT), including multiple isoforms for some of these structural genes, and all of these were upregulated in response to low-nitrogen treatment in both apple rootstock species (Figure 3B; Supplemental Table S7). RT-qPCR confirmed that the transcript abundances of specific flavonoid pathway genes, i.e. CHS (MD04G1003400), F3H (MD02G1132200), and LAR (MD13G1046900), were significantly increased in response to low nitrogen, and their expression levels in Ms were substantially higher compared with those of Mh (Figure 3C). In the lignin biosynthesis pathway, most structural genes were differentially expressed and generally downregulated in response to low nitrogen except for CAD (cinnamyl alcohol dehydrogenase) isoform MD05G1089900 in both rootstock species (Figure 3B; Supplemental Table S8).

Both chalcone synthase (CHS) and hydroxycinnamoyl-CoA transferase (HCT) use coumaroyl-CoA as substrate and catalyze the first committed step for flavonoid and lignin biosyntheses, respectively. While transcript abundances of all identified CHS isoforms increased in response to low nitrogen, the gene expression of two HCT isoforms, which were common to Ms and Mh was downregulated in both rootstock species. Especially the transcript abundance of HCT (MD14G1155800) was highly significantly lower in Ms in response to low nitrogen (Figure 3C). Based on the RT-qPCR and DEGs analyses, we concluded that upregulation of CHS and downregulation of HCT might be associated with observed tolerance for low-nitrogen stress in Ms rootstock.

Flavonoids and phenolic acids increased in response to low nitrogen

In order to investigate the metabolic response of apple rootstocks to low-nitrogen stress, UPLC-MS/MS was used for widely targeted metabolome analysis of Mh and Ms roots after 0, 24, and 96 h of low-nitrogen treatment. A total of 586 metabolites from 12 chemical classes were identified, including 134 flavonoids, 102 phenolic acids, 66 lipids, and 58 amino acids and their derivatives (Figure 4A; Supplemental Table S9). After 24 h of low-nitrogen treatment, concentrations of 42 (24 increased and 18 decreased) metabolites changed significantly in Mh but only 27 (17 increased and 10 decreased) in Ms when compared with 0-h treatment as control (Figure 4B). After 96 h of low-nitrogen treatment, the number of significantly altered metabolites increased in both apple rootstock species, to 75 (57 increased and 18 decreased) and 66 (45 increased and 21 decreased) in Mh and Ms, respectively (Supplemental Tables S10 and S11). Thus, the number of significantly increased metabolites was greater compared with decreased ones in both rootstock species.

Figure 4.

Figure 4

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Metabolome analysis under low-nitrogen stress: (A) Pie chart of detected metabolite composition distribution. (B) Numbers of differentially accumulated metabolites (DAMs) under different treatments. (C) UpSet Venn diagram between each comparison group, the horizontal bar chart on the left shows the element statistics for each comparison group (i.e. statistics on the number of differential metabolites), a single black dot in the middle matrix represents a grouping specific element, the lines between points represent the intersection specific to different groupings, the vertical bar chart represents the number of corresponding intersection elements. (D) Heat map of different metabolites unique to Malus hupehensis (Mh) and Malus sieversi (Ms). (E) Differential metabolites in a common response to low-nitrogen stress and specific heat maps of differential metabolites at 24 and 96 h of low-nitrogen treatment, respectively.

Subsequently, we analyzed the differentially accumulated metabolites (DAMs) of each comparison group. By comparing the DAMs of the two apple rootstocks across time, we found that 25 DAMs were unique to Mh (phenolic acids: 8, flavonoids: 6, amino acids and their derivatives: 6, and others: 5), while 10 DAMs were unique to Ms, which were primarily classified as flavonoids (Figure 4, C and D; Supplemental Figure S8; Supplemental Table S12). When comparing time-dependent changes in metabolites across rootstock species, we identified only 7 DAMs (4 common and 3 unique) after 24 h of low-nitrogen treatment but 33 DAMs after 96 h (4 common, 29 unique). The majority of DAMs unique to 96 h of low-nitrogen treatment were classified as flavonoids and phenolic acids (Figure 4, C and E; Supplemental Figure S9; Supplemental Table S13). Collectively, these results indicated that pro-longed low-nitrogen treatment generally increased the accumulation of flavonoids and phenolic acids in both apple rootstock species but that the diversity of phenolic acids was greater in Mh.

Combined transcriptomic and metabolomics analyses revealed contrasting patterns of flavonoid and lignin biosyntheses in response to low nitrogen

The phenylpropanoid pathway, converting phenylalanine to coumaryl-CoA, is the shared upstream pathway for flavonoid as well as lignin biosynthesis. Under low nitrogen, phenylalanine and p-coumaric acid concentrations accumulated in both apple rootstock species, providing sufficient substrates for downstream branches (Figure 5).

Figure 5.

Figure 5

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Metabolite and transcript abundances of flavonoid and lignin biosynthesis pathways in apple rootstock under low-nitrogen treatment: Malus hupehensis (Mh) and Malus sieversii (Ms).

In both apple rootstock species, genes as well as metabolites of the lignin pathway generally decreased in response to low-nitrogen treatment and were more pronounced in Ms, especially the accumulation of a smaller amount of lignin monomer. HCT is catalyzing the first step of this pathway and the expression of the key gene HCT decreased in parallel with p-coumaroyl quinic acid and caffeoyl quinic acid concentrations. CAD catalyzes the final step of monolignol biosynthesis and is a key enzyme for lignin synthesis. In Ms, CAD gene expression also decreased with the length of low-nitrogen treatment, and the concentrations of CAD-products coniferyl alcohol and sinapyl alcohol were lower when compared with those of Mh (Figure 5; Supplemental Tables S8 and S14).

Furthermore, transcript abundance of key genes of the flavonoid biosynthesis pathway, in particular, CHS and CHI together with the respective products naringenin chalcone and naringenin were increased. F3H, F3′H, and FLS gene expressions were also upregulated under low nitrogen and the concentrations of dihydroflavonols and most flavonol-3-O-glycosides increased in parallel. DFR and ANS are important genes for both, anthocyanin and proanthocyanin biosyntheses. Proanthocyanidins are oligomers or polymers of catechin and epicatechin, synthesized by LAR and ANR, respectively. In this study, the expression of both LAR and ANR genes was upregulated in response to low nitrogen, but LAR expression was substantially higher in Ms, which corresponded well with increased catechin concentrations in Ms, compared with that in Mh (Figure 5; Supplemental Tables S7 and S15). A3GT catalyzes the final step of anthocyanin biosynthesis, and A3GT expression together with anthocyanin accumulation was higher in Ms than in Mh. Collectively, low-nitrogen stress increased the concentrations of monolignols in Mh, while the differences in flavonoid composition between rootstock species were likely attributed to increased expression of LAR and A3GT in Ms.

Transcription factor bHLH130 is likely negatively regulating flavonoid biosynthesis

We annotated 1,452 transcripts that were differentially expressed after low-nitrogen treatment in both apple rootstock species and found that these DEGs were mainly downregulated and predominantly associated with the following TF families: ERF, MYB, WRKY, bHLH, and NAC (Figure 6A). Among these, the transcript abundances of TFs, such as bZIP25 (MD05G1206400), MYB4 (MD10G1124100), MYBR10 (MD17G1184100), ATAF2 (MD15G1136600), WRKY72 (MD14G1196100), ERF25 (MD10G1286300), and WRKY17 (MD15G1106600) were significantly different between the two rootstock species and at least four-fold lower in Ms compared with those in Mh (Supplemental Table S16). The expression of bHLH130 (MD02G1315600), WRKY17, and ERF25 was significantly downregulated under low-nitrogen treatment, while MYB4 was upregulated in Ms but downregulated in Mh, which were validated using RT-qPCR (Figure 6B).

Figure 6.

Figure 6

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To screen transcription factors (TFs) that may regulate flavonoid biosynthesis and lignin biosynthesis under low-nitrogen stress. (A) Heat map of differentially expressed TFs after low-nitrogen treatment. (B) RT-qPCR validation. The relative expression levels of TFs at 0, 24, and 96 h after low-nitrogen treatment. Malus hupehensis (Mh) and Malus sieversii (Ms). Transcriptional regulatory network diagram of lignin biosynthesis pathway (C) and flavonoid biosynthesis pathway (D). The network graph was drawn if the correlation coefficient was greater than 0.8. Solid line is a positive correlation, dotted line is a negative correlation. Data are presented as means ± SE from three biological replicates. Significant differences compared with the 0 h were determined using one-way ANOVA: *P < 0.05; **P < 0.01; ***P < 0.001.

Then, we constructed the correlation network of structural genes related to lignin and flavonoid biosyntheses and differential expression TFs. In the lignin pathway, we identified four TFs families including ERF, WRKY, MYB, and bHLH whose expression was highly correlated with the structural genes HCT (MD17G1225100, MD14G1155800) and CAD (MD05G1089900), and formed a correlation network. In this correlation network, 15 TFs corresponded to ERF-type transcription factors, suggesting an important role for the ERF family in regulating lignin biosynthesis. Concurrently, bHLH130 was substantially positively correlated with HCT (MD14G1155800) expression (Figure 6C; Supplemental Table S17). To further characterize TFs that may regulate the flavonoid pathway, we identified 29 TFs which were strongly correlated (R > 0.8) with structural genes and classified these as members of the MYB, ERF, NAC, bHLH, and WRKY TF families (Figure 6D; Supplemental Table S18). The correlation network analysis indicated that the transcription factor bHLH130 was highly negatively correlated with the transcript abundance of all structural genes of the flavonoid pathway (Figure 6D). These results indicated that bHLH130 was possibly negatively regulating flavonoid biosynthesis and positively regulating lignin biosynthesis.

MhbHLH130 directly negatively regulates MhCHS by binding to its promoter

To explore the role of the four candidate TFs, WRKY17, ERF25, MYB4, and bHLH130 in regulating flavonoid and lignin biosyntheses, we first performed cis-acting element analysis on the promoter sequences of the key genes MhCHS (MD04G1003400) and MhHCT (MD14G1155800), as entry points to the respective pathways. We found that both structural genes contained binding elements for all four TFs (Supplemental Figure S10A). Subsequently, the yeast one-hybrid assay results showed that only MhbHLH130 directly bound to the MhCHS promoter, while other proteins did not (Figure 7A; Supplemental Figures S10B and S11A). The results of the double luciferase assay showed that co-expression of MhbHLH130 or MhMYB4 with pro-MhHCT led to a significant increase in luminescence intensity compared with the control (Supplemental Figures S10, C-E and S11, C and D). However, only when co-expressed with MhbHLH130, the fused MhCHS promoter significantly decreased LUC-activity. When the MhCHS promoter was mutated at the bHLH recognition site, LUC-activity remained unchanged (Figure 7, B–D). Consistently, electrophoretic mobility shift assay (EMSA) indicated that MhbHLH130 directly bound to the DNA probe containing the G-box present in the promoter region of MhCHS, but not to the MhHCT promoter (Figure 7E; Supplemental Figure S11B). It further indicated that MhbHLH130 directly binds to the promoter regions of MhCHS to regulate flavonoid biosynthesis.

Figure 7.

Figure 7

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Transcriptional regulation of MhCHS gene promoter by MhbHLH130. MhbHLH130 binds to the MhCHS promoter (A) as indicated by yeast one-hybrid assay. AD/BD, AD-TF/BD, and AD/BD-promoter were used as the negative controls. pB42AD vector: AD; pLaczi vector: BD. (B) Schematic diagrams of effector and reporter constructs used for the dual-luciferase (LUC) assay. (C) Luciferase imaging analysis. (D) Determination of luciferase-enzyme activity, The LUC/REN of empty SK vector (EV) plus promoter vector was set as 1. The symbols − and + represent absence or presence. (E) Electrophoretic mobility shift assay (EMSA). The core sequence (Wild) and mutation sequence (Mutant) on the promoter are on the top panels. The wild probe containing the bHLH binding site was biotin-labeled. Competition for MhbHLH130 binding was performed with cold probes. The symbols − and + represent absence or presence of the probe and GST-tagged MhbHLH130 protein. The data are presented as means ± SE from three biological replicates. Asterisks indicate significant differences between the test group and the control group (based on the Student's t test: *P < 0.05).

Inhibition of MhbHLH130 promotes nitrogen uptake, which may be associated with increased flavonoid accumulation and decreased lignin content

MhCHS is the target gene of MhbHLH130. CHS is the first key enzyme gene in the flavonoid biosynthesis pathway in plants (Koes et al., 1989). We generated transient MhCHS overexpression (pRI-MhCHS) and silenced (TRV-MhCHS) roots and quantified gene expression by RT-qPCR (Supplemental Figure S12A). After low-nitrogen treatment, leaves of MhCHS silenced plants showed obvious chlorosis (Supplemental Figure S12, B and C).

Overexpressing MhCHS significantly increased, while silencing MhCHS decreased the flavonoid content in roots compared with the control (Supplemental Figure S12D). Furthermore, overexpressing MhCHS showed higher nitrate reductase (NR) activity, NO3− concentration, and nitrate uptake activity than the control, which contrasted with observations for silencing MhCHS in roots (Supplemental Figure S12, E–G). Concurrently, the overexpression of MhCHS increased nitrate absorption by upregulating some genes responsible for nitrate uptake and assimilation (Supplemental Figure S12H). These results are indicative of the proposed role in root flavonoid accumulation that MhCHS plays for enhanced nitrogen uptake.

To verify the regulatory function of MhbHLH130, phylogenetic analysis was performed with bHLH genes that have previously been reported to regulate flavonoid biosynthesis in other species. This showed that MhbHLH130 was most closely related to Pyrus × bretschneideri bHLH130 (Supplemental Figure S13A). When the eGFP-fused protein was transiently transfected into N. benthamiana, the GFP fluorescence of MhbHLH130 was exclusively found in the nucleus (Supplemental Figure S13B), when compared with the 35S::eGFP, which was distributed throughout the cell.

We generated transient MhbHLH130 overexpression (pRI-MhbHLH130) and silenced (TRV-MhbHLH130) roots in Mh (Supplemental Figure S14A). Compared with the control, overexpression of MhbHLH130 inhibited and silencing of MhbHLH130 promoted the accumulation of anthocyanins, whereas a contrasting pattern was observed for lignin content (Supplemental Figure S14, B and C). Concurrently, overexpression of MhbHLH130 downregulated genes related to flavonoid biosynthesis (CHS, LAR, F3H, and DFR) and upregulated genes related to lignin biosynthesis (HCT, F5H), whereas silencing MhbHLH130 gave a contrasting response (Supplemental Figure S14, D and E). Furthermore, we found that the expression of nitrate uptake and assimilation-related genes, as well as NO3− concentration and nitrate uptake activity, decreased in roots following overexpression of MhbHLH130 and increased in MhbHLH130-silenced roots (Supplemental Figure S14, F–H), compared with the control.

We also generated six transgenic MhbHLH130-silenced (RNAi-MhbHLH130) lines and tested residual MhbHLH130 expression using RT-qPCR analysis (Supplemental Figure S15, A and B). Three lines with the lowest bHLH130 expression levels were chosen for further analysis. Under low-nitrogen conditions (0.3 mM KNO3, LN), leaf chlorosis was obvious in the empty-vector control (RNAi-control) plant compared with the RNAi-MhbHLH130 lines (Figure 8, A and B). In addition, we found that the flavonoid content in the roots of RNAi-MhbHLH130 lines was higher than that of the RNAi-control, while the lignin content was significantly reduced (Figure 8, C and D). Furthermore, shoot biomass, root/shoot ratio, and nitrogen-uptake-related indicators, such as NO3− influx rate, NO3− concentration, NR activity, and total nitrogen accumulation, were significantly higher in RNAi-MhbHLH130 lines compared with the RNAi-control (Figure 8, E–H; Supplemental Figure S16, A and B). In comparison to normal nitrogen conditions (3.3 mM KNO3, CK), RSA was affected under low-nitrogen conditions (Supplemental Figure S17A). Compared with the RNAi-control, there was no difference in root tip number and root surface area of RNAi-MhbHLH130 lines under normal nitrogen conditions. After low-nitrogen treatment, however, these parameters were significantly increased (Supplemental Figure S17, B and C). Collectively, these data demonstrated that both the repression of MhbHLH130 and overexpression of MhCHS increased root flavonoid content and decreased lignin content and promoted root nitrogen uptake. The opposite was observed in response to the overexpression of MhbHLH130 and silencing of MhCHS. Thus, both genes were shown to have contrasting effects on root flavonoid and lignin content and consequently low MhbHLH130 associated with high MhCHS expression likely providing favorable conditions for root growth under low-nitrogen stress.

Figure 8.

Figure 8

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RNAi-MhbHLH130 transgenic apple plants promoted flavonoid synthesis and improved nitrogen uptake efficiency. The phenotypes (A), SPAD (Soil and plant analyzer development) (B), flavonoid content (C), lignin content determination (D), NO3− flux rate (E), root NO3− concentration (F), nitrate reductase (NR) activity (G), and total nitrogen accumulation (H) of RNAi-MhbHLH130 lines and RNAi treated for 15 days under normal nitrogen (3.3 mM KNO3, CK) and low-nitrogen (0.3 mM KNO3, LN) conditions. The empty vector RNAi was used as a control. Scale bar: 1 cm; DW, dry weight; FW, fresh weight; and RDW, root dry weight. The data are presented as means ± SE from three biological replicates. Asterisks indicate significant differences between the transgenic lines and the control group (based on the Student's t test: *P < 0.05; **P < 0.01; ***P < 0.001).

Discussion

Soil nitrogen is essential for plant growth and development and is often a limiting factor for crop yield. For example, nitrogen deficiency has been identified as a key factor limiting apple tree growth and productivity (Kucukyumuk and Erdal, 2011; Fazio et al., 2013). Most commercial apple trees are grafted on rootstocks, which influences tree height and vigor but also resilience to climate and soil conditions. Thus, the nutrient absorption capacity of the rootstock roots plays a key role in the growth and development of the tree and crop yield (Kucukyumuk and Erdal, 2011; Fazio et al., 2013). While diverging nitrogen tolerance has been reported in apple rootstock species, the molecular mechanisms underlying low-nitrogen stress tolerance have not been described. In this study, we used two widely used rootstocks, Ms and Mh, with contrasting responses to low nitrogen supply to explore the physiological and molecular mechanisms that cause differences in nitrogen uptake efficiency.

Possible physiological processes involved in low-nitrogen enhancement of nitrogen uptake efficiency

The root system is the main organ for plants to absorb nutrients from the soil. Under low-nitrogen treatment, the root activity, nitrogen uptake efficiency, and RSA were significantly increased in Ms compared with those in Mh (Figure 1; Supplemental Figure S2). This is consistent with other studies reporting that root architecture was closely related to nutrient uptake efficiency. In response to low phosphorous, the number of lateral roots and root hairs was increased (Zheng et al., 2019), whereas elongation of lateral roots was observed in response to low nitrate (Liu et al., 2020). Under drought stress, the root surface area, root/shoot ratio, total root length, and root water conductivity of Ms increased, which improved drought resistance (Geng et al., 2019). This suggested that Ms could absorb nutrients and alleviate stress better Mh.

Substrate diversion from the lignin to the flavonoid pathway may act as adaptive response

Plants adapt to environmental stress by a complex network of molecular cross-talk, regulating gene transcription and metabolite biosynthesis. The rise of multi-omics has made the transcriptional, protein, and metabolic networks of plants clearer, and responses to nutrient deficiency, such as low nitrogen, have been well studied in the model plant Arabidopsis thaliana (Luo et al., 2020), but are less researched in arable and horticultural crops. Under low-nitrogen stress, transcriptomics and metabolomics of the apple rootstocks Ms and Mh revealed differential expressions of structural genes and concomitant accumulation of metabolites related to flavonoid and lignin biosyntheses. The flavonoid and the lignin biosynthetic pathways are two important branches of the phenylpropanoid pathway, and substrate competition is likely. In this study, low-nitrogen treatment induced gene expression of the flavonoid pathway and downregulated genes critical for lignin biosynthesis, which likely increased the metabolite flow to the flavonoid pathway. In Ms, however, gene transcription and metabolite abundance of flavonoids was increased, and biosynthesis of lignin, i.e. sinapyl alcohol and coniferyl alcohol, was lower when compared with that of Mh (Figure 5).

Previous studies have shown that under high nitrogen conditions, genes, proteins, and metabolites involved in the biosynthesis of phenylpropanoid and flavonoid are downregulated together, which is not conducive to the carbon and nitrogen balance of apple fruits, leading to reduced fruit production (Wang et al., 2021). The accumulation of flavonoids such as anthocyanin plays a positive role in improving plant tolerance to low nitrogen (Liang and He, 2018). In the study by Sun et al. (2018), overexpression of MdATG18a in both Arabidopsis and apple improved tolerance to N-depletion and caused a greater accumulation of anthocyanin content. Moreover, MdATG18a functioned in nitrate uptake and assimilation by upregulating nitrate reductase MdNIA2 and three high-affinity nitrate transporters MdNRT2.1/2.4/2.5. However, the underlying molecular mechanisms elucidating the relationship between low nitrogen and flavonoid synthesis remain to be determined. Masclaux-Daubresse (2014) has proposed a role for the C/N balance because anthocyanin biosynthesis requires carbon resources. Lignin is an abundant component of plant cell walls, providing mechanical support and aiding water transport and stress resistance (Liu et al., 2018). Studies have shown that the overexpression of MdMYB46 in apple plants increased root lignin content, which improved salt and osmotic stress tolerance (Chen et al., 2019b). However, increased root lignin accumulation also reduced the elongation of root cell walls in soybean (Yamaguchi et al., 2010), likely decreasing nutrient absorption. Thus, substrate diversion from the lignin to the flavonoid pathway is likely a more widely adopted strategy by plants to mitigate low-nitrogen stress.

Inhibition of bHLH130 might be central to low-nitrogen adaptation in plants

In addition to nitrate signaling, the biosynthesis of flavonoid is affected by a variety of developmental and environmental factors (An et al., 2020; Ren et al., 2021). The MYB-bHLH-WD40 protein complex plays a central role in the transcriptional regulation of flavonoid biosynthesis in plants, and nitrogen starvation was previously shown to release inhibition of MdMYB1, the main activator of anthocyanin biosynthesis in apples (Ren et al., 2021). In our study, we identified that the transcription factor bHLH130 was negatively correlated with flavonoid pathway genes and significantly downregulated in response to low nitrogen (Figure 6, B and D). However, the biological function of bHLH130 has not been previously characterized in detail. Recently, a subgroup III bHLH from wintersweet (Chimonanthus praecox), CpbHLH1, was shown to inhibit anthocyanin production, leading to a strong reduction in nitrogen-stress-induced anthocyanin accumulation (Zhao et al., 2020), but the molecular mechanism was not resolved. Phylogenetic tree analysis showed that MhbHLH130 was closely related to Pyrus × bretschneideri bHLH130, which was reported to regulate flavonoid biosynthesis (Supplemental Figure S13A).

CHS and HCT are the first key enzymes in the biosynthesis of flavonoid and lignin, respectively. In this study, MhbHLH130 directly binds to the MhCHS promoter and inhibited its expression (Figure 7). Overexpression of MhCHS increased root nitrogen uptake by accumulating higher levels of flavonoids compared with control (Supplemental Figure S12). MYB4 is known to act as a repressor of the phenylpropanoid pathway, inhibiting C4′H in particular, which produces coumaric acid as the main substrate for coumaroyl-CoA formation a precursor for both flavonoid and lignin biosyntheses (Jin et al., 2000). Although MYB4 expression was significantly upregulated in Ms in response to low nitrogen, this did not seem to affect coumaric acid concentrations. In contrast to bHLH130, promoter binding of MYB4 protein to the CHS promoter was not observed, suggesting that MYB4 is unlikely to transcriptionally regulate the flavonoid pathway (Supplemental Figure S10, B–D). Interestingly, both MYB4 and bHLH130 cannot directly bind to the HCT promoter, but activated it indirectly, increasing LUC-activity significantly (Supplemental Figures S10, B, C and E and S11). MYB as well bHLH proteins usually function as part of a complex (Wang et al., 2022), suggesting that they might potentially be indirectly involved in HCT promoter activation. Nevertheless, bHLH130 but not MYB4 gene expression was associated with HCT in apple rootstock species and significantly lower in Ms than Mh. Inhibition of bHLH130 promoted the accumulation of flavonoids, including anthocyanins, reduced lignin content, and improved nitrogen uptake efficiency (Figure 8; Supplemental Figure S14). In addition, under normal nitrogen conditions, compared with RNAi, RSA of RNAi-MhbHLH130 lines did not change, suggesting that MhbHLH130 regulates nitrogen uptake by regulating flavonoid synthesis rather than affecting RSA (Supplemental Figure S17). These results suggest that bHLH130 is likely to play a central role in plant tolerance to low-nitrogen stress, which is promoted by bHLH130 downregulation and subsequent increase in flavonoids and decreased root lignification, which improves tolerance to low-nitrogen stress.

On the basis of multi-omics analysis, we propose a working model for bHLH130-mediated response of the apple rootstocks to low-nitrogen stress (Figure 9): bHLH130 directly binds to and inhibits the CHS promoter, a regulatory gene for flavonoid biosynthesis. “bHLH130-CHS” module may regulate flavonoid biosynthesis and nitrate uptake in response to low-nitrogen stress. In addition, bHLH130 can indirectly promote the transcription of HCT and reduce lignin content. However, more evidence is needed to verify the “bHLH130-HCT” module. The transcription factor bHLH130 seems to be able to adjust the two complementary pathways of lignin and flavonoid biosyntheses, mediating the metabolic fluxes between them to improve nitrogen uptake efficiency of the apple rootstocks. These findings help elucidate the molecular mechanism and regulatory network of apple rootstocks under low-nitrogen stress and provide a biological basis for the selection of rootstocks with high nitrogen uptake efficiency.

Figure 9.

Figure 9

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Hypothesis model of the role of bHLH130 in mediating apple rootstock response to low-nitrogen stress. The transcription factor bHLH130 can directly inhibit the transcription of CHS. Low-nitrogen stress inhibits the expression of bHLH130 and consequently the transcription of CHS increases, which promotes the accumulation of flavonoids and improves root nitrogen uptake. In addition, bHLH130 can indirectly promote the transcription of HCT and reduce lignin content. Inhibition of bHLH130 enhances root nitrogen uptake either by changing the metabolic fluxes between flavonoid and lignin biosynthesis. The dashed line on the right indicates the potential mechanism of bHLH130 in regulating the lignin biosynthesis pathway, which needs further evidence.

Materials and methods

Plant materials and treatment

In this experiment, Malus hupehensis (Mh) and Malus sieversii (Ms) plants were used as experimental materials. After seed stratification (4°C, 1 month) and germination, seedlings were transferred to the substrate (peat: vermiculite = 1:1). After growing to five true leaves, the roots of the seedlings were cleaned carefully and cultured in Hoagland nutrient solution, which was changed once a week. For phenotypic observation and physiological indexes determination, 6-week-old seedlings of similar size and status were treated with low nitrate (0.3 mM KNO3 and 3 mM KCl) and normal nitrate (3.3 mM KNO3) concentration as control (0.8 mM MgSO4 .7H2O, 0.5 mM KH2PO4, 18.7 μM H3BO3, 3 μM MnCl2 .4H2O, 3 μM ZnSO4 .7H2O, 0.3 μM H4N·1/6Mo7O24, 0.1 μM CuSO4 .5H2O, 1.6 mM CaCl2, and EDTA-FeNa) for 15 days. The growth conditions were set at a temperature of 25°C with a 16-h day/8-h night photoperiod. Each experiment was repeated at least six times.

Transcriptome analysis

The roots treated with low nitrate for 0, 24, and 96 h were collected. Each treatment had three biological replicates, and each biological replicate contained four seedlings. Total RNA extraction, library construction, and sequencing were performed by Wuhan Metware Biotechnology Co., Ltd. (Wuhan, China). The HISAT2 software was used to quickly and accurately map cleaned reads to the apple reference genome (GDDH13; Daccord et al., 2017). Fragments per kilobase of transcript per million mapped reads (FPKM) values were used to estimate gene expression levels (Trapnell et al., 2010). DEGs were performed using the DEGSeq R package (1.20.0). Using the standard | log2(fold-change) | > 1 and adjusted P-value < 0.05 screening of DEGs (Benjamini and Hochberg, 1995). According to the FPKM value of all genes in each sample, Pearson correlation coefficients of samples within and between groups were calculated, and a heat map and PCA were drawn.

Pearson correlation coefficient was used to calculate the correlation between DEGs, and the differential genes whose correlation coefficient R was greater than 0.8 were screened to draw the correlation network diagram.

GO and KEGG enrichment analysis

Gene Ontology (GO) enrichment analysis was implemented by the GOseq R package. According to the KEGG database (http://www.genome.jp/kegg/), and KOBAS software was used to test the statistical enrichment of DEGs in KEGG pathways (Mao et al., 2005). P-value <0.05 was used as the threshold value of significant enrichment.

RT-qPCR analysis

Reverse transcription quantitative PCR (RT-qPCR) was performed to target and validate the transcript abundance of candidate genes (primer sequences are listed in Supplemental Table S19) and used the ABI QuantStudio™ 6 Flex system (Applied Biosystems Inc., Foster City, CA, USA). Three technical replicates were used for each biological replicate. The relative expression level was calculated as previously described (Livak and Schmittgen, 2001).

Widely targeted metabolome analysis

Aliquots of the same root material used for transcriptome analysis were freeze-dried and ground to a fine powder. Sample processing, sequencing, and data analysis were performed by Wuhan Metware Biotechnology Co., Ltd. (Wuhan, China). Ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) was used for data acquisition and analysis (Chen et al., 2013). Based on the metware database (MWDB), the qualitative and quantitative analysis of metabolites was carried out. The differential metabolites were screened by combining the fold change and the Variable Importance in Projection (VIP) value of the OPLS-DA model. The screening conditions were VIP ≥ 1, fold change ≥ 2, and fold change ≤ 0.5.

Yeast one-hybrid assay (Y1H)

The Y1H analysis was performed as previously described (Zhang et al., 2020). The CDS of TF genes were constructed onto the pB42AD vector (AD-TF vector, Clontech, CA, USA), and the promoter sequences of MhCHS and MhHCT (about 2000 bp upstream of ATG) were cloned into pLaczi (BD-promoter vector). Using empty vectors (pB42AD and pLacZi) as negative controls, all constructs were transformed into Saccharomyces cerevisiae strain EGY48. Details of related primer sequences are listed in Supplemental Table S19. Each assay was performed in triplicate.

Subcellular localization of MhbHLH130

The CDS of MhbHLH130, without the stop codon, was cloned into the pRI101-eGFP vector. All constructs were transformed into A. tumefaciens strain GV3101, following which positive strains were injected into the N. benthamiana leaves. Three days later, fluorescence images were taken with a laser scanning confocal microscope (Olympus, FV3000 microscope) at 488 nm excitation wavelength and 500 nm emission wavelength. The related primers are shown in Supplemental Table S19.

Dual-luciferase reporter gene assay

The pGreenII 0029 62-SK vector containing the respective candidate TF CDS was used as the effector vector, and the pGreenII 0800-LUC vector containing the MhCHS or MhHCT promoter sequence was used as the reporter vector. All constructs and empty-vector control were transformed into A. tumefaciens strain GV3101 harboring the pSoup plasmids. Cells were collected by centrifugation at 5000 g for 8 min and resuspended in infiltration buffer (10 mM MES pH 5.7, 10 mM MgCl2, and 200 μM acetosyringone) to obtain an optical density of 0.6–0.8 at 600 nm. The infection and activity assay were performed as described previously (Wei et al., 2017). Details of related primer sequences are listed in Supplemental Table S19. Each experiment was repeated at least three times.

Electrophoretic mobility shift assay

The full-length CDS of MhbHLH130 was fused into the pGEX4T-1 vector to generate GST fusion proteins. The resulting plasmids were transformed into E. coli strain BL21 (DE3), and protein was induced by 0.5 mM IPTG and incubated with a biotin-labeled probe at the 5′-end or competitors which were not labeled probes. EMSA assay was conducted according to the manufacturer's protocol of Chemiluminescent EMSA Kit (Beyotime Biotechnology, China). The probes used are listed in Supplemental Table S19.

Transient expression in apple plants

The overexpressing vector pRI101-eGFP-MhbHLH130 or MhCHS and specific primers were designed to amplify a partial fragment of MhbHLH130 or MhCHS (about 400 bp), which was then linked to the silencing vector pTRV2 to obtain pTRV2-MhbHLH130 or MhCHS. All constructs were transformed into A. tumefaciens strain GV3101 by electroporation and transfected into apple plant seedlings by vacuum infiltration (Tian et al., 2015). The specific primers are listed in Supplemental Table S19.

Hairy root transgenic system

Interference vector RNAi-MhbHLH130 was constructed, and empty vector RNAi and RNAi-MhbHLH130 were transformed into A. rhizogenes strain K599, respectively. Healthy seedlings aged 7–10 days were selected for A. tumefaciens injection. The injection procedure was performed as previously described (Meng et al., 2019).

DNA extraction

DNA extraction was based on the CTAB method. The extraction steps were performed as previously described (Tel-Zur et al., 1999).

Determination of total nitrogen accumulation, nitrogen uptake efficiency, and 15NO3− uptake

Plant dry matter was recorded after drying plant samples in an oven to a constant weight. The nitrogen concentration was determined by Kjeldahl method (He et al., 2015). Total nitrogen accumulation was calculated by multiplying the nitrogen concentration by the total plant dry weight (mg N). Nitrogen uptake efficiency was calculated as total nitrogen accumulation divided by root dry weight (mg N g−1 RDW) (Abenavoli et al., 2016).

Plants were placed in 3.3 mM K15NO3 (atom %15N: 99%) solution for 30 min, and then the roots were dried and ground fully. The samples were analyzed for total nitrogen and atom percentage 15N using stable isotope-mass spectrometry (Finnigan DELTAplus XP by Thermo Fisher Scientific). The methods were performed as previously described (Ho et al., 2009; Hu et al., 2009). Each experiment was repeated at least three times.

Determination of nitrate concentration

Nitrate concentration was determined using the SA method as previously described (Patterson et al., 2010). In brief, about 10 mg of dried root samples was taken, and 2 mL deionized water was added. The suspension was taken for subsequent reaction. The NO3− concentration was determined spectrophotometrically at 410 nm using a KNO3 standard curve in the concentration range of 10–120 mg L−1. Each experiment was repeated at least three times.

Root architecture measurement

The WinRHIZO Pro (2007 edition) root analysis system was used to analyze scanned root sample images.

Determination of anthocyanin and flavonoid content, lignin content

The anthocyanin content was determined with a Plant Anthocyanin Kit (HSG-2-Y), the flavonoid content with a Plant Flavonoid Kit (LHT-2-G), and the lignin content with a Plant Lignin Kit (MZS-2-G; Suzhou Keming Biotechnology Co., Ltd, Suzhou, China) following the manufacturer's instructions. In brief, the anthocyanin concentration was determined by spectrophotometry at 530 and 700 nm, respectively, and calculated as fresh weight equivalent. About 0.02 g of dry sample was weighed and extracted with oscillation at 60°C for 2 h. The supernatant was taken, and the absorbance value at 510 nm was measured to calculate the flavonoid content. The lignin content was determined using spectrophotometry at 280 nm with 5 mg per sample in triplicate. Each experiment was repeated at least three times.

Nitrate reductase (NR) activity

Nitrate reductase (NR) activity was determined with an NR Assay Kit (NR-2-W) following the manufacturer's instructions. In brief, fresh roots (0.1 g) were taken and homogenized in a cold mortar with a pestle in 1-ml extraction solution. The homogenate was centrifuged at 8,000 g for 10 min at 4°C. The supernatant was used for the determination of NR activity. Three replicates were performed for every treatment.

Root activity

Root activity was measured by the triphenyl tetrazolium chloride (TTC) method. The extraction steps were performed as previously described (Aibibu et al., 2010). Six replicates were used for measurements. Each experiment was repeated six three times.

Net NO3− flux measurement with non-invasive micro-test technology (NMT)

Net NO3− flux was measured in the YoungerUSA (Xuyue Beijing) NMT Service Center using NMT [NMT100 Series, YoungerUSA LLC, Amherst, MA, USA; Xuyue (Beijing) Sci. & Tech. Co., Ltd., Beijing, China] and iFluxes/imFluxes 2.0 (Younger USA) software (Sa et al., 2019). NO3− fluxes were measured for an average of 5 min at the position of 3 mm (±1 mm) from the root tip. Three replicates were performed for every treatment.

Statistical analysis

Data processing and mapping related to omics validation testing were performed using GraphPad Prism 8.00 software. One-way Analysis of Variance (ANOVA) and Student's t test were used for univariate analysis between treatments at α 0.05. Each treatment was represented by at least three biological replicates.

Accession numbers

The RNA-Seq data in this study have been uploaded to NCBI under BioProject ID: PRJNA708147 and the URL is https://www.ncbi.nlm.nih.gov/sra/PRJNA708147. The login numbers of all sequences used in this study are listed in Supplemental Table S19.

Supplemental data

Supplemental Figure S1 . Measurement of physiological and morphological parameters of Malus hupehensis (Mh) and Malus sieversii (Ms) plants treated with normal nitrogen (3.3 mM KNO3, CK) and low nitrogen (0.3 mM KNO3, LN) conditions for 15 days.

Supplemental Figure S2 . Root architecture of Mh and Ms treated for 15 days under normal nitrogen (3.3 mM KNO3, CK) and low nitrogen (0.3 mM KNO3, LN) conditions.

Supplemental Figure S3 . Intersample correlation heat map.

Supplemental Figure S4 . Venn diagram of differentially expressed genes between different materials: Malus hupehensis (Mh) and Malus sieversii (Ms).

Supplemental Figure S5 . KEGG enrichment analysis of differentially expressed genes in different materials.

Supplemental Figure S6 . Venn diagram of differentially expressed genes at different time points under low-nitrogen treatment: Malus hupehensis (Mh) and Malus sieversii (Ms).

Supplemental Figure S7 . KEGG-rich distribution plots corresponding to unique DEGs at different time points under low-nitrogen treatment.

Supplemental Figure S8 . Venn diagram of different metabolites between different materials: Malus hupehensis (Mh) and Malus sieversii (Ms).

Supplemental Figure S9 . Venn diagram of different metabolites at different time points of low-nitrogen treatment: Malus hupehensis (Mh) and Malus sieversii (Ms).

Supplemental Figure S10 . Transcriptional regulation of MhCHS and MhHCT gene promoters by TFs MhMYB4, MhERF25, and MhWRKY17, respectively.

Supplemental Figure S11 . Transcriptional regulation of MhHCT gene promoter by MhbHLH130.

Supplemental Figure S12 . MhCHS promotes flavonoid synthesis and improves nitrogen uptake in roots.

Supplemental Figure S13 . Phylogenetic tree and subcellular localization of MhbHLH130.

Supplemental Figure S14 . Characterization of the transient transformation of pRI-MhbHLH130 and TRV-MhbHLH130.

Supplemental Figure S15 . Hairy root transgenic system in apple rootstock and identification of RNAi-MhbHLH130 lines.

Supplemental Figure S16 . Measurement of physiological and morphological parameters of RNAi-MhbHLH130 lines and RNAi treated for 15 days under normal nitrogen (3.3 mM KNO3, CK) and low-nitrogen (0.3 mM KNO3, LN) conditions.

Supplemental Figure S17 . Root architecture of RNAi-MhbHLH130 lines and RNAi treated with normal nitrogen (3.3 mM KNO3, CK) and low nitrogen (0.3 mM KNO3, LN) for 15 days.

Supplemental Table S1 . Quality statistics of RNA-sequencing data.

Supplemental Table S2 . GO enrichment of differentially expressed genes in Malus hupehensis treated with low nitrogen for 24 and 96 h.

Supplemental Table S3 . GO enrichment of differentially expressed genes in Malus sieversii treated with low nitrogen for 24 and 96 h.

Supplemental Table S4 . KEGG pathway of differentially expressed genes between the two materials.

Supplemental Table S5 . KEGG pathway of unique differentially expressed genes at 24 and 96 h after low-nitrogen treatment.

Supplemental Table S6 . Differentially expressed genes related to plant hormone signal transduction.

Supplemental Table S7 . Differentially expressed genes related to flavonoid biosynthesis.

Supplemental Table S8 . Differentially expressed genes related to lignin biosynthesis.

Supplemental Table S9 . A total of 586 detected metabolites in this study, and they responded to low-nitrogen stress in apple rootstocks.

Supplemental Table S10 . Difference of metabolite accumulation between 24 and 96 h after low-nitrogen treatment in Malus hupehensis.

Supplemental Table S11 . Difference of metabolite accumulation between 24 and 96 h after low-nitrogen treatment in Malus sieversii.

Supplemental Table S12 . Different unique metabolites of the two materials under low-nitrogen treatment.

Supplemental Table S13 . Differential metabolites in response to low N stress and unique metabolites in response to low N treatment at 24 and 96 h, respectively.

Supplemental Table S14 . Metabolites associated with lignin biosynthesis pathway.

Supplemental Table S15 . Metabolites associated with flavonoid biosynthesis pathway.

Supplemental Table S16 . Transcription factors under low-nitrogen stress.

Supplemental Table S17 . Correlation coefficient between transcription factors and genes related to lignin biosynthesis.

Supplemental Table S18 . Correlation coefficient between transcription factors and genes related to flavonoid biosynthesis.

Supplemental Table S19 . Sequence of primer pairs used in this study.

Supplementary Material

kiac519_Supplementary_Data
Click here for additional data file. (1.8MB, pdf)

Acknowledgments

We would like to thank Dr. Zhaoyu Gu from China Agricultural University, Prof. Andrew Allan from the University of Auckland/PFR, and Dr. Simon Deroles from PFR for their expertise and for reviewing our manuscript.

Contributor Information

Xiaona Wang, College of Horticulture, China Agricultural University, Beijing 100193, P.R. China; Key Laboratory of Biology and Genetic Improvement of Horticultural (Nutrition and Physiology), the Ministry of Agriculture and Rural Affairs, Beijing 100193, P.R. China.

Xiaofen Chai, College of Horticulture, China Agricultural University, Beijing 100193, P.R. China; Key Laboratory of Biology and Genetic Improvement of Horticultural (Nutrition and Physiology), the Ministry of Agriculture and Rural Affairs, Beijing 100193, P.R. China.

Beibei Gao, College of Horticulture, China Agricultural University, Beijing 100193, P.R. China; Key Laboratory of Biology and Genetic Improvement of Horticultural (Nutrition and Physiology), the Ministry of Agriculture and Rural Affairs, Beijing 100193, P.R. China.

Cecilia Deng, The New Zealand Institute for Plant and Food Research Ltd, 120 Mt Albert Road, 1025 Auckland, New Zealand.

Catrin S Günther, The New Zealand Institute for Plant and Food Research Ltd, Ruakura Research Campus, Bisley Road, 3216 Hamilton, New Zealand.

Ting Wu, College of Horticulture, China Agricultural University, Beijing 100193, P.R. China; Key Laboratory of Biology and Genetic Improvement of Horticultural (Nutrition and Physiology), the Ministry of Agriculture and Rural Affairs, Beijing 100193, P.R. China.

Xinzhong Zhang, College of Horticulture, China Agricultural University, Beijing 100193, P.R. China; Key Laboratory of Biology and Genetic Improvement of Horticultural (Nutrition and Physiology), the Ministry of Agriculture and Rural Affairs, Beijing 100193, P.R. China.

Xuefeng Xu, College of Horticulture, China Agricultural University, Beijing 100193, P.R. China; Key Laboratory of Biology and Genetic Improvement of Horticultural (Nutrition and Physiology), the Ministry of Agriculture and Rural Affairs, Beijing 100193, P.R. China.

Zhenhai Han, College of Horticulture, China Agricultural University, Beijing 100193, P.R. China; Key Laboratory of Biology and Genetic Improvement of Horticultural (Nutrition and Physiology), the Ministry of Agriculture and Rural Affairs, Beijing 100193, P.R. China.

Yi Wang, College of Horticulture, China Agricultural University, Beijing 100193, P.R. China; Key Laboratory of Biology and Genetic Improvement of Horticultural (Nutrition and Physiology), the Ministry of Agriculture and Rural Affairs, Beijing 100193, P.R. China.

Funding

This work was supported by the National Key Research and Development Program of China (2016YFD0201103), the earmarked fund for China Agriculture Research System (CARS-27), the 111 Project (B17043) and the 2115 Talent Development Program of China Agricultural University, and the Key Laboratory of Beijing Municipality of Stress Physiology and Molecular Biology for Fruit Trees.

Author contributions

Z.H. and Y.W. conceived and designed the research. X.W., X.C., and B.G. performed the experiments and analyzed the data. T.W., X.Z., and X.X. provided suggestions on experiments. X.W. and Y.W. wrote the manuscript, C.D. and C.S.G. gave advice, reviewed, and edited the manuscript.

The authors responsible for distribution of materials integral to the findings presented in this article in accordance with the policy described in the Instructions for Authors (https://academic.oup.com/plphys/pages/General-Instructions) are Yi Wang (wangyi@cau.edu.cn) and Zhenhai Han (rschan@cau.edu.cn).

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