https://orcid.org/0000-0003-3665-544X
Figures
Abstract
In plants, age-related resistance (ARR) refers to a gain of disease resistance during shoot or organ maturation. ARR associated with vegetative phase change, a transition from juvenile to adult stage, is a widespread agronomic trait affecting resistance against multiple pathogens. How innate immunity in a plant is differentially regulated during successive stages of shoot maturation is unclear. In this work, we found that Arabidopsis thaliana showed ARR against its bacterial pathogen Pseudomonas syringae pv. tomato DC3000 during vegetative phase change. The timing of the ARR activation was associated with a temporal drop of miR156 level. The microRNA miR156 maintains juvenile phase by inhibiting the accumulation and translation of SPL transcripts. A systematic inspection of the loss- and gain-of-function mutants of 11 SPL genes revealed that a subset of SPL genes, notably SPL2, SPL10, and SPL11, activated ARR in adult stage. The immune function of SPL10 was independent of its role in morphogenesis. Furthermore, the SPL10 mediated an age-dependent augmentation of the salicylic acid (SA) pathway partially by direct activation of PAD4. Disrupting SA biosynthesis or signaling abolished the ARR against Pto DC3000. Our work demonstrated that the miR156-SPL10 module in Arabidopsis is deployed to operate immune outputs over developmental timing.
Author summary
Age-associated change of immunity is a widespread phenomenon in animals and plants. How organisms integrate immune maturation into a developmental clock is a fundamental question. Heterochronic microRNAs are key regulators of developmental timing. We found that a conserved heterochronic microRNA (miRNA) in Arabidopsis, microRNA156, regulates the timing of age-related resistance associated with a transition from the juvenile to the adult vegetative phase. The coordination between developmental maturation and gain of disease resistance is achieved through miR156-controlled SPL transcription factors with distinct functions. A subset of SPL transcription factors promoted resistance by directly activating key genes in defense signaling. This work bridges the knowledge gap between vegetative development and age-related resistance. Pinpointing mechanisms of the developmental regulation on immunity may pave a way for unlocking the age limit on plant immunity and lay a foundation to applications in the precision agriculture.
Citation: Hu L, Qi P, Peper A, Kong F, Yao Y, Yang L (2023) Distinct function of SPL genes in age-related resistance in Arabidopsis. PLoS Pathog 19(3): e1011218. https://doi.org/10.1371/journal.ppat.1011218
Editor: Libo Shan, Texas A & M University, UNITED STATES
Received: January 6, 2023; Accepted: February 19, 2023; Published: March 22, 2023
Copyright: © 2023 Hu et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: The data that support the findings of this study are publicly available from NCBI with access No. GSE208657.
Funding: Funding for the Agilent UPLC-QTOF was provided by the U.S. Department of Agriculture, National Institute of Food and Agriculture, Equipment Grant Program award no. 2021-70410-35297 to C.J.T and L.Y. This project is supported by NIH R35GM143067 to L.Y. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: The authors have declared that no competing interests exist.
Introduction
Both animals and plants suffer from infectious diseases, particularly at a young age [1,2]. The function of their immune systems can be enhanced with the progression of organismal maturation. In many plant species, a gain of disease resistance against certain pathogens during shoot maturation is termed age-related resistance (ARR). Plant ARR can launch robust and wide spectrum resistance against a variety of pathogens, and such trait is often selected in breeding [3].
Age-associated disease resistance is often coupled with successive developmental transitions, such as germination [4] and vegetative phase change [5] and flowering [6,7]. The heterogeneity of host age, maturing stage of infected organs and virulence of causal pathogens suggest that multiple layers of signaling are intertwined between aging and immunity [3,8]. ARR-associated juvenile-to-adult vegetative phase change (hereafter ARRVPC) has been observed among economically important vegetables, crops and fruits, such as tomato, rice and grapevine [9]. The juvenile and adult phases refer to vegetative development prior to floral induction, and predicable changes of morphological and physiological traits are associated with this transition [10–12]. Several factors were speculated to impact ARRVPC. Compared to juveniles, adult plants are exposed to environmental conditions that are not optimal for disease development (such as high UV) [2]; adult tissues may carry tough physical barriers (e.g., cell wall components, cuticle), [13]; and leaves of adult stage are primed by previous exposure to pathogens [2]. Such factors complicate the investigation of intrinsic molecular mechanisms governing the onset of ARRVPC. Nevertheless, accumulating evidence suggests that intrinsic signaling pathways govern ARR [3,14].
MicroRNA156s (miR156), a conserved microRNA family [10], regulates the onset of vegetative phase change [10,15]. MiR156 targets genes encoding SPLs (SQUAMOSA PROMOTER BINDING PROTEIN-LIKE) transcription factors, which contains a SQUAMOSA promoter binding protein (SBP) box for nuclear import and DNA binding [16–18]. In Arabidopsis, leaves generated in the juvenile shoot, e.g., juvenile leaves (usually leaves 1–7 under a short-day condition) accumulate high level of miR156 [19,20]. Throughout the expansion of juvenile leaves, they maintain the morphological (e.g., no abaxial trichome) and molecular identities (e.g., high miR156 level) of the juvenile fate. A temporal decline of miR156 level, followed by the high expression of SPLs, initiates the vegetative phase change [18–21]. SPLs have overlapping yet distinct functions to promote adult traits such as adult leaf morphogenesis, floral induction, and reduced rooting [22–24]. A total of 11 SPL genes encoded in Arabidopsis Columbia-0 (Col-0) ecotype are suppressed by miR156 via mRNA cleavage and/or translational repression [18,25]. Recent studies showed that the miR156-SPL pathway involved in plant immunity. Disrupting miR156 function in Arabidopsis by mutating SQUINT (SQN), an Arabidopsis orthologue of cyclophilin 40, compromised jasmonic acid signaling and disease resistance against necrotrophic pathogen Botrytis cinerea [26]. Furthermore, overexpressing miR156-targeted SPL9 in juvenile plants enhanced accumulation of reactive oxygen species and induced salicylic acid (SA) signaling, leading to enhanced resistance of Arabidopsis against bacterial pathogen Pseudomonas syringae [27]. Yet, a systematic dissection of the link between ARR and miR156-SPL signaling pathway is still lacking.
Here, we systemically analyzed the miR156-SPLs module in ARRVPC. We demonstrated that the ARR to Pseudomonas syringae pv. tomato DC3000 (Pto DC3000) in Arabidopsis is associated with vegetative phase change. Altering the temporal expression of miR156-SPL pathway was sufficient to change the timing of ARRVPC onset. A sub-class of SPL transcription factors (SPL2/10/11) promoted disease resistance in adult stage, and such function was independent of their roles in leaf morphology. Transcriptomic analysis unveiled multiple mechanisms that collectively contribute to ARRVPC, including priming, activating adult-specific defense programs, and strengthening juvenile defense after infection. Finally, we found SPL10 strengthened SA signaling in the adult stage by directly enhancing the transcription of PAD4. Our work provides molecular insights into the intrinsic clock that coordinates disease resistance outcomes with developmental timing.
Results
The age-related resistance to Pto DC3000 is associated with a reduction of miR156 level
To assess the ARRVPC, we measured the multiplication of Pto DC3000 in juvenile (without abaxial trichomes) and adult (with abaxial trichomes) leaves of Arabidopsis thaliana Col-0 ecotype. During the expansion of an individual leaf, defense genes are differentially expressed (S1A and S1B Fig), which is known as ontogenic resistance [4,28–31]. Ontogenic resistance occurs during the maturation of both juvenile and adult leaves (S1B and S1C Fig). Because juvenile leaves are produced in early shoot development, juvenile and adult leaves on a same plant are always at different ontogenic age (Figs 1, S1C and S1E). To avoid the impact of ontogenic resistance, we sampled fully expanded juvenile leaves (leaves 1–4) from 4- or 5-week-old plants and adult leaves (leaves 8) from 7-week-old plants, respectively (S1D Fig). To avoid the influence of flowering-associated ARR [32,33], plants were grown in a short-day condition and bolting was not observed before 10 weeks after planting. Bacterial multiplication in leaves 8 was lower than that in leaves 1, 2, 3 and 4 (Fig 1A, 1B and S2 Table). No significant differences were observed between leaves 1–2 and 3–4 (Fig 1B). We concluded that the increased resistance to Pto DC3000 was associated with vegetative phase change in Col-0.
A, developmental phenotype of a 4-week (left) and 7-week (right) Col-0 plant grown under short-day conditions. Arrows point to leaves 1,2,3,4 and leaf 8 in the left and right plants, respectively. B, Pto DC3000 bacterial growth in juvenile and adult leaves of Col-0. C, developmental phenotype of a 7-week Col-0 and 35S::MIR156A plant. Arrows indicate an adult leaf of Col-0 or a leaf from a similar position in 35S::MIR156A. D, bacterial growth in adult leaves of Col-0 and 35S::MIR156A. E, developmental phenotype of a 4-week Col-0 and 35S::MIM156 plant. Arrows indicate leaves 1 and 2 on each plant. F, Pto DC3000 bacterial growth in juvenile Col-0 and MIM156 leaves 1–2 on Day 0 and Day 2. Scale bar = 1 cm. Day 0, the day of Pto infection. Day 2, two days post-infection. CFU/cm2, bacterial colony forming unit per square centimeter of a leaf. Juv, juvenile leaves, Adu, adult leaves. The student t-test was used for statistical analysis. Each genotype was compared with Col-0, ns, not significant, *, p < 0.05, **, p < 0.01. The same annotation is used for bacterial growth dot-box plots shown in Figs 2 and 7. Repeats of bacterial growth are presented in S2 Table.
Since miR156 level in fully expanded leaves drops from the juvenile to adult transition [34], we hypothesized that a high level of miR156 suppresses immunity in juvenile stage. We compared bacterial growth in adult leaves (leaves ≥ 8) from Col-0 and leaves at the same position from transgenic plants overexpressing MIR156A under a constitutive 35S promoter from TMV (35S::MIR156A). Expressing MIR156A in adult leaves led to accelerated production of juvenile leaves, marking the prolonged juvenile phase as previously reported [19,20] (Fig 1C). Interestingly, it also led to an increase in bacterial growth when compared with leaves at the same position in Col-0 (Fig 1D). Consistently, knocking down miR156 activity by a target mimicry, 35S::MIMICRY156 [35] (MIM156) displayed enhanced disease resistance (Fig 1E and 1F). These evidences suggests that high accumulation of miR156 suppresses resistance to Pto DC3000 in the juvenile phase.
miR156-regulated SPL10 promotes ARR in adult phase
To test which miR156-targeted SPL contributes to ARRVPC, we first screened disease phenotype in the gain-of-function mutants carrying miR156-resistant SPL genes (rSPLs, Fig 2A and S2 Table). We examined the disease phenotype in juvenile leaves expressing individual rSPL gene from 9 out of 11 members under its own native promoter [23]. Low levels of endogenous SPL transcripts in juvenile leaves provided a sensitized background to test the function of rSPLs. We found that leaves 1–2 from rSPL2, 10, 9 and 13 showed increasing resistance compared to wild type, but rSPL3, 4, 6, 11 and 15 did not change resistance to Pto DC3000 (Figs 2A, S2 and S2 Table). Thus, a subset of miR156-regulated SPLs was sufficient to enhance immunity in juveniles.
A, disease phenotype of Pto DC3000 in SPL gain and loss-of function mutants. NA, not available. B, bacterial growth in leaves 1–2 and leaves 11 from Col-0 and rSPL10. C, developmental phenotype of Col-0, and early phase change phenotypes of transgenic plants expressing stable MIM156, rSPL10 and rSPL3 on ½ MS plate (top panel); developmental phenotype of Col-0, estradiol-inducible(in)MIM156, inrSPL10 and inrSPL3 at 3 days after estradiol treatment (bottom panel). D, bacterial growth in leaves 1–2 from 4 -week-old Col-0, inMIM156, inrSPL10 and inrSPL3 on Day 0 and Day 3. Emmeans package in R was used for statistical analysis in 2 A and 2 B. The student t test was used for statistical analysis in 2 A and 2 C, and each genotype was compared with Col-0 wild type, ns, not significant, *, p < 0.05, **, p < 0.01. Repeats for the experiments here are shown in S2 Table.
To check the necessity of SPLs in adult conferred immunity, we tested disease phenotypes in adult leaves with loss of function spl combinatorial mutants based on amino acid sequence similarity (Figs 2A, S2 and S2 Table). There are 5 phylogenic clades for miR156-targeted SPL genes, SPL3/4/5, SPL6, SPL2/10/11, SPL9/15, and SPL13A/13B (Fig 2A) [25,36]. In Col-0 background, SPL10 and SPL11 (78% amino acid identity) reside in a 1.6 kb tandem duplication [25]. Spl2/10/11 showed enhanced susceptibility to Pto DC3000 (Fig 2A). While the phenotypes of spl2 and spl10 single mutants were wild type-like, spl10/11 mildly reduced disease resistance (S2 Table), indicating that SPL2, 10 and 11 redundantly contributed to immunity in adult leaves. Importantly, although rSPL10 carried a higher resistance than wild type in juvenile leaves (Fig 2A and 2B), the difference between the two genotypes was much smaller in the adult stage (Fig 2B), supporting that SPL10 enhanced resistance is age dependent. Spl3/4/5 triple or spl6 single mutations did not alter resistance to Pto DC3000 (Fig 2A and S2 Table). The lack of disease phenotypes against Pto DC3000 in the gain- and loss-of-function mutants of SPL6 is consistent with a previous report [37]. rSPL9 enhanced resistance, but the spl9/15 double mutant displayed unstable phenotypes, which may be resulted from redundancy among other SPL members (Fig 2A and S2 Table). Altogether, the data confirmed the specialized function of SPLs in ARRVPC.
To further determine whether the disease phenotypes of SPL10 mutants were pleiotropic effects caused by SPL10-mediated leaf morphogenesis, we assayed bacteria multiplication in transgenic plants expressing either estradiol inducible rSPL3, rSPL10 or MIM156 (Fig 2C). Transgenic plants growing on ½ MS medium supplemented with estradiol showed typically early phase change phenotypes, indicating that the transgenes were functional [23,38]. In line with the data above (Fig 2A), applying estradiol 12 hrs before inoculation suppressed bacterial multiplication in juvenile leaves of inducible rSPL10 and inducible MIM156 lines, but not for that from inducible rSPL3 plants (Fig 2D). Notably, the leaf morphology was comparable between wild type and estradiol induced plants (Fig 2C), indicating that miR156-SPL10 controlled disease resistance and leaf morphology can be decoupled.
The basal expression of defense genes is high in the adult stage
To explore the transcriptional signature of ARRVPC, we performed RNA sequencing to compare juvenile (leaves 1–2) and adult (leaves ≥ 8) transcriptomes at 3 hours after mock treatment or Pto DC3000 infection (Fig 3A). An early time point was chosen because change of chromatin accessibility could be detected at 3 hrs post Pto infection [39]. Under mock treatment, we identified 2002 and 2320 genes that were respectively up- or down-regulated in adult leaves compared with juvenile leaves, hereafter Aduno infection (nof) (LFC = 0.58, padj < 0.05) (Figs 3B, S3C, S3D and S3 Table). As expected, SPL3/4/5 were up-regulated in adult samples (S3 Table). In addition, the Gene Ontology (GO) enrichment analysis revealed that vegetative phase change related GOs, such as adaxial/abaxial axis specification [40] were enriched in the Adunof DEGs (Fig 3D and S6A Table), confirming that our juvenile and adult samples represented two distinct developmental phases (Figs 3, S3A, S3B and S3 Table). Intriguingly, we observed that immunity related GOs were also enriched in the up-regulated Adunof DEGs, including defense response to bacterium/fungus and response to SA (Fig 3D). Here, jasmonic acid (JA) signaling-mediated defense was downregulated, coinciding with the antagonistic interaction between JA and SA in plant immunity [41]. The enrichment of pro-defense genes in up-regulated Adunof indicated that adult plants had primed defense signaling.
A, experimental settings of RNA-seq. Non-infected state and challenged (3 hours after Pto inoculation) transcriptomes from leaf 1–2 (Col-0 and rSPL10) and leaf 11 (Col-0) were compared. * indicates examples of leaf samples that were collected for RNA-seq. Green: juvenile leaves; brown: adult leaves. B, an expression profiling of DEGs identified in mock-treated adults against mock-treated juvenile leaves. DEGs, differently expressed genes with LFC ≥ ±0.58 and padj ≤ 0.05. LFC, log2 fold change of gene expression. Padj, adjusted p value. Color-codes in the heatmap, blue is for down-regulated DEGs and red is for up-regulated DEGs. Euclidean distance was used for calculating distance. Complete linkage was applied to structure the hierarchical clustering. Expressing profiles of DEGs derived from Adu-M/Juv-M are mapped in the first column of the map. The expressing profiles of those DEGs in Adu-P/Juv-P are shown in the second column of the map. Genes that were DEGs in both Adu-M/Juv-M and Adu-P/Juv-P are marked by the black bar on the right. 38% indicates the percentage of those overlapping DEGs in Adupto. C, a profile of Pto-triggered DEGs came from Juv-P/Juv-M and Adu-P/Adu-M. Adult-specifically Pto-triggered DEGs (dark red), Juvenile-specifically triggered (light brown), adult preferentially triggered (deep blue), and commonly triggered in both adults and juveniles, i.e., shared (light grey) are marked by the first column of bars on the right. The percentages (20.6%, 3.4%, 5.3%, 12.6%) and corresponding black bars indicate the proportion of each DEG category that overlaps with Adupto. D, representative GO terms enriched in DEGs of Adunof, DEGs triggered by Pto DC3000 in both adult and juvenile leaves (the Shared) and DEGs specifically triggered by Pto in adult phase within the total Adupto (20.6%). Red and blue color blocks refer to GOs enriched in up- and down-regulated DEGs, respectively. Only GO terms with FDR < 0.05 were deemed as enriched here. Fold enrichment was based on hypergeometric tests within the range of the DEG set used for each GO analysis relative to Arabidopsis genome. The analysis was done using the TAIR Gene ontology website (geneontology.org). The same GO analysis and color-coding are used for Fig 4C.
For defense induction state, we investigated genes that were differentially induced/suppressed by infection in juvenile and adult stages. Pto treatment triggered 3027 and 4728 DEGs in juvenile and adult leaves, respectively (Pto/Mock, S3 and S4 Tables, S3C and S3D Fig). Among the 2163 Pto-triggered DEGs shared between juvenile and adult leaves (2163 = 239+1924 in Figs 3C, S3C and S3D, S3 and S4 Tables), the shared up-regulated DEGs were enriched with well-characterized defense responses such as respiratory burst, defense response to bacterium and response to salicylic acid (Fig 3D). Meanwhile, photosynthesis and light harvesting signaling pathways were enriched in down-regulated DEGs, indicating that a pathogen-induced transcriptomic reprogramming switched from development to defense regardless of plant age (Fig 3D and S6A Table). A total of 864 DEGs were only induced/repressed by Pto in the juvenile stage, and there are 2565 DEGs were adult-specific (Fig 3C). Cutin biosynthetic and wax biosynthetic processes were enriched in adult-specific Pto-induced DEGs, consistent with a previously suggested consolidation of constitutive defense in ARR [42] (S6B Table).
Among genes that were specifically induced by Pto in the adult stage but not the juvenile stage, a portion of them did not eventually have higher transcription level when we compared infected adult and juvenile leaves (red bar only, Fig 3C, S3C and S3D Table). It is arguable whether inducibility of a gene alone contributes to ARR. So, we further searched for genes whose absolute expression levels were different between juvenile and adult leaves after Pto DC3000 treatment (hereafter Adupto). Genes that were specifically induced/repressed by infection in the adult stage count for 20.6% (934 out of 4528, S3 Table) of the Adupto (red bar/black bar, Fig 3C). There, cellular response to hypoxia, defense response to bacterium and response to heat were over-represented, indicating an age-dependent Pto response that may cope with abiotic stresses (Fig 3D). A 5.3% (239 out of 4528, S3G and S3H Table) of Adupto were also triggered by Pto in the juvenile stage, but the amplitude of change was preferentially higher in the adult stage (Fig 3C). Thus, ARRVPC strengthened a sector of juvenile-defense regulon as well as activated adult-specific defense genes. In addition, 38% (1722 out of 4528) of Adupto were not Pto-triggered but already had differential expression between juvenile and adult leaves before infection (Fig 3B and S3 Table). Of the 38%, GOs pertaining to defense, such as SA signaling, together with adult-related developmental pathways were enriched (Fig 3D and S6A Table). Finally, 20.1% AduPto (910 out of 4528) was not induced either by infection or age alone. These DEGs could be resulted from a synergistic interaction between age and infection (Figs 3, S3C, S3D and S3E and S3F Table). Taken together, we discovered that ARR transcriptome changes could contribute to the elevation of defense signaling at non-infected state, the adult-specific inducible defense as well as the strengthened juvenile defense.
Overexpressing SPL10 recapitulates the ARR transcriptomic landscape in juvenile leaves
To delineate the contribution of SPL10 to ARR at the transcriptomic level, we investigated the rSPL10 (r10) induced DEGs at non-infected and Pto-infected states (Fig 3A). A total of 3211 genes (1859 up-regulated and 1352 down-regulated, S5A and S5B Table) were differentially expressed in leaves 1–2 between Col-0 and r10 at non-infected state (r10nof). Out of 3211 genes, 1316 of them overlapped with Adunof (Fig 4A). A 936 of the 1316 r10nof were co-regulated in adult leaves in the same trend, attributing to 21.7% (936/4322) of the Adunof, being consistent with the function of SPL10 in specifying adult fate (Fig 4A and S5G and S5H Table). GO terms associated with immune signaling including systemic acquired resistance were enriched in the 936 co-upregulated DEGs between r10nof and Adunof (Adu/r10nof) (Fig 4C and S6C Table). After bacterial infection, we identified 2621 DEGs between leaves 1&2 from r10 and Col-0 (S5E and S5F Table). Out of 2621 DEGs, 1006 of them overlapped to Adupto (Fig 4B), with 604 out of the 1006 were co-regulated in the same trend, occupying 13.3% (604/4528) of total Adupto (Fig 4B and S5I and S5J Table). Defense-related GOs were enriched in those co-regulated DEGs (Fig 4C and S6C Table). The observations support that SPL10 activated a sector of adult immune response to Pto DC3000.
A, an expression profiling of co-regulated DEGs by adult and rSPL10 leaves at non-infected state compared with juvenile leaves. EDS1 and PAD4 were identified as Adu/r10 co-upregulated DEGs under non-infected state, which are indicated in the heatmap with arrows. B, expressing profiles of co-regulated DEGs by adult and rSPL10 from Adu-P or r10-P against Juv-P. For the clustered heatmaps in 4 A and B, blue represents down-regulated DEGs and red is for up-regulated DEGs. Euclidean distance was used for calculating distance in the partition around medoids (PAM) clustering (k = 4). C, GO enrichment of co-regulated adult and r10 vs juvenile DEGs in non-infected and Pto-infection states.
Disrupting SA signaling compromised the SPL10-mediated ARR
Since SA-related GO terms were enriched in the co-upregulated Adu/r10nof (Fig 4C), we first measured the age- and SPL10- effects on SA signaling. We assembled a core SA regulon by overlapping DEGs induced by SA and its synthetic inducer benzothiadiazole (BTH) [43,44] (Fig 5A). 81.3% of the core SA regulon (527 activated and 239 repressed genes) were detected in the gene count matrix generated from a combination of all our RNA sequencing samples. SA-activated (199/527) and -repressed (50/239) markers were enriched in Adunof (Fig 5B and S1 Information). SA-activated genes were also enriched in r10nof (Fig 5B and S1 Information), denoting that SPL10 contributed to enhancing SA signaling in the adult phase. Consistently, accumulation of Salicylic acid beta-glucoside (SAG) (an inactive SA form, stored in vacuole) was higher in adult than that in juvenile leaves (Fig 5C and S2 Table). The accumulation of free SA showed a similar trend (Fig 5C and S2 Table). Next, we sought to validate whether elevated SA response in adult phase depended on the temporal expression of SPL10. We selected four age-dependent SA-activated genes, AT3G60470, BG3, ATLTP4.4 and PR5 (Fig 5B). Their expressions were compromised in the adult leaves of spl2/10/11 (Fig 5D). Noticeably, the upregulation of the four SA responsive genes were also observed in adult or r10 leaves when plants were grown on sterile plates (Fig 5E). In conclusion, the age-related increase of SA response in leaves required SPL10 and was not primed by pre-exposure to microbes. The EDS1-PAD4 protein complex is essential for SA-mediated defense signaling [45]. We found that both genes were upregulated in adults and r10 (Fig 4A). Furthermore, a significant overlap was found between the EDS1-PAD4 core regulon (EP-core, [45] and genes co-upregulated by adults and r10 (Fig 5F), implying that the EDS1-PAD4 mediated SA signaling pathway could be differentially activated in juvenile and adult stage due to the temporal expression of SPL10.
A, 672 up-regulated core SA markers were defined via overlapping DEGs pools from Ding Y et al., 2018 (dark circle) [44] and Yang L et al., 2017 (light circle) [43]. B, expression patterns of 527 detected (out of 672) up-regulated core SA markers in adult and r10 leaves, under non-infected and Pto infection states. Four random pools of detected genes (450 genes per set) derived from each pair-wise comparison exhibits here were chosen as negative controls. Up, upregulated. No, no change. Down, downregulated. Y axis shows the negative logarithm transformed adjusted p value, -log10(padj). X axis displays the value of Log2 fold change (LFC) of gene expressions. M, mock. P, Pto DC3000. P < 0.0001 (Hypergeometric test, done by GeneOverlap R package) was reproducibly output from each overlap between core upregulated SA markers and Adunof, Adupto, r10nof and r10pto (S1 Information). The P values for 3 out of 4 random controls were not significant (S1 Information). C, endogenous SAG and free SA accumulation in juvenile, r10 and adult leaves at non-infected state. DW, dry weight. Repeats for the experiment are shown in S2 Table. D, age-associated expression of four SA markers in adult leaves from Col-0 and in comparable leaves of spl2/10/11. Similar results were seen two times. E, the qPCR of the four SA marker genes in juvenile, r10 and adult leaves on sterile 1/2 MS plates. Similar results were seen three times. F, overrepresentation of EDS1-PAD4 core regulon (EP core) in Adu/r10nof and Adu/r10pto. The EP core markers were defined in Cui et al., 2017 [45]. 127/155 of the EP core markers were detected in this work. Randomly selected 127 genes from our RNA-seq dataset were used as controls.
Out of the 936 DEGs co-regulated by adult stage and rSPL10 (Fig 4A), 400 of them were associated with SPL10-binding sites identified in a ChIP-seq experiment of SPL10 by Ye et al (Fig 6A) [24], indicating that these genes are likely direct targets of SPL10. A de novo motif discovery algorism identified potential SPL-binding sites in 203 of the co-up-regulated DEGs (Fig 6A), but not in the 197 down-regulated genes. In addition, experimentally validated SPL TF binding sites [46] were enriched in the promoter of the 203 genes (Figs 6 and S4A). Interestingly, the promoter region and gene body of PAD4 contains two potential SPL10-binding GTAC-containing motifs (Fig 6B) [24]. We generated a genomic reporter line of SPL10 (proSPL10::rSPL10-YFP). The transgenic line showed similar early phase change phenotypes observed in the proSPL10::rSPL10-GUS line, indicating that the fusion had a normal SPL10 function (Figs 6 and S4B). Using ChIP-qPCR, we validated that the motif 1 (M1, 186–182 bp away from the TSS), but not motif 2 was associated with SPL10 at uninfected state (Fig 6B). Furthermore, the transcript level of PAD4 was reduced only in the spl2/10/11 adult leaves but not in the juvenile leaves (Fig 6C), indicating that the temporal expression of PAD4 depends on SPL10. Taken together, these observations suggest that SPL10 directly promotes PAD4 expression in the adult stage.
A, overlap between Adu/r10nof co-regulated genes and potential SPL10 targets defined according to ChIP-seq data from Ye et al. (upper panel) [24]. A motif discovery and enrichment analysis of the 203 Adu/r10nof co-upregulated DEGs (lower panel). B, SPL10 bound to a GTAC-containing motif upstream of PAD4. qPCR following chromatin immunoprecipitation of rSPL10-YFP for motifs (M1 and M2) and negative control sites (nc1 and nc2), the latter of which are at least 600 bp away from M1 and M2 at the PAD4 genomic region. Three primer sets (p1-p3) were used to amplify the M1 site. Relative locations of ChIP peaks (dark grey) derived from Ye et al, primers (arrow pairs) and the tested sites (color blocks) were indicated in the schematic diagram. The student t test was performed to compare and indicate the significance of difference between the sites. C, qPCR of PAD4 transcripts level in juvenile (Juv) and adult (Adu) leaves of Col-0 and spl2/10/11. The student t test, ns, not significant, *, p < 0.05, **, p < 0.01.
To probe the genetic interactions of SA signaling and the miR156-SPL10 mediated ARR, we first tested the ARRVPC phenotype in the mutant of SALICYLIC ACID INDUCTION DEFICIENT 2 (sid2-1, defective in pathogen-induced SA biosynthesis) and NONEXPRESSER OF PR GENES 1 (npr1-1, defective in SA perception) mutants. Neither of those mutants altered the timing of vegetative phase change. As expected, both mutants in adult stage were more susceptible than Col-0 (Fig 7A). The difference of bacterial growth between wild type and the mutants in juvenile stage was less pronounced (Fig 7A), in agreement with the age-dependency of SA-mediated disease resistance. We then introduced sid2-1 mutation into MIM156 background (Figs 7 and S5A). Although precocious morphological traits were shared between MIM156 and MIM156/sid2-1, the bacteria level in MIM156/sid2-1 phenocopied that of sid2-1 (Fig 7B and S2 Table), suggesting that SID2 acts downstream of miR156. Similarly, loss of function mutation of EDS1 reversed the enhanced disease resistance phenotype in r10 plants (Figs 7C, S5B and S2 Table). The leaf morphology phenotype of r10 plants was not changed by eds1.2, which further confirmed that age-associated leaf morphology and disease resistance can be decoupled (Fig 7C). Consistent with the molecular evidence that SPL10 binds to the promoter of PAD4, the ARRVPC phenotype was compromised in pad4-1 and eds1.2 mutant (Fig 7D). In essence, miR156-SPL10 promoted resistance through SID2 and EDS1-PAD4-dependent SA signaling.
A, a comparison of Pto DC3000 growth between the juvenile and adult leaves (ARR phenotype) of Col-0, sid2-1 and npr1-1. B, developmental phenotype (top) and the bacterial growth (bottom) in 4-week-old leaves 1 and 2 from Col-0, sid2-1, MIM156 and MIM156/sid2-1. C, developmental phenotype of 4-week-old Col-0, eds1.2, r10 and r10 /eds1.2. Note the similar leaf shape between r10 and r10/eds1.2; (bottom panel) bacterial multiplication in leaves 1 and 2 derived from Col-0, eds1.2, r10 and rSPL10/eds1.2. Arrows indicate leaves 1–2. D, the ARR phenotyping of eds1.2 and pad4-1 infected with Pto DC3000. Emmeans package in R was used for statistical analysis in 7 A and D. The student t test was used for statistical analysis in 7 B-C, and each genotype was compared with Col-0 wild type, ns, not significant, *, p < 0.05, **, p < 0.01.
Discussion
In this research, we uncovered an ARR mechanism regulated by the miR156-SPL pathway, linking immune maturation to an intrinsic aging mechanism (S6 Fig). In plants, ARR occurs during predicable developmental transitions that are often accompanied by morphological changes. Our research provides a potential mechanism for the temporally coordinated change of immunity and morphogenesis, where the same molecular clock, miR156, controls different SPL genes to specify immune and developmental traits. For instance, SPL2/10/11, but not SPL3/4/5/6, are required for resistance against Pto DC3000 (Fig 2A). Interestingly, NbSPL6 is required in the N-mediated TMV resistance in tobacco [37]. The homologue of NbSPL6 in Arabidopsis, AtSPL6, is necessary to the full ETI response triggered by Pseudomonas syringae effector AvrRps4, but not basal resistance to Pto DC3000 [37] (Fig 2A). It is possible that the broad spectrum of resistance associated with ARR requires multiple SPL family members to activate different defense pathways. As rSPL10 only influenced 21.7% of Adunof and 13.3% of Adupto, other SPLs may contribute to the rest of adult defense to Pto and/or to other pathogens (Fig 4A and 4B). Alternatively, the coordinated maturation of development and immune system may be achieved by functional switch of the same SPL protein. In rice plants, Ideal plant architecture 1 (IPA1)/OsSPL14 increases panicle size [47]. IPA1 binds to an alternative cis-regulatory element to activate defense when challenged by the bacterial pathogen Xanthomonas oryzae pv. Oryzae (Xoo) [48]. In Nicotiana benthamiana and tomato plants, temporal reduction of miR6019/6020 allows its target, N gene, to mediate age-dependent resistance to tobacco mosaic virus (TMV) [49]. The temporal expression pattern of miR6019/6020 mimics that of miR156 in tobacco. It would be interesting to explore the genetic relationship between those two miRNAs in regulating ARR.
We showed that defense GO terms were enriched in up-regulated rSPL10nof and Adunof. Among those, components of SA pathway, such as SID2 and NPR1 were required for ARRVPC (Fig 6). We observed the up-regulation of SA response accompanied by a reduction of JA response in both Col-0 adults and the rSPL10 line (Figs 3 and 4). JA and SA often act antagonistically to fine-tune immune response to multiple pathogens. Our ARR transcriptome results showed that the antagonism also occurred in an age-dependent manner (Fig 3C). Upregulation of SA production and response have also been observed during vegetative-floral transition in both tomato and tobacco plants [50]. In Arabidopsis, SVP and SOC1 genes regulating floral induction also transcriptionally promote age-dependent increase of SA, independent from flowering traits [32,51]. We did not observe differential expression of SVP or SOC1 in juvenile vs adult transcriptome, suggesting the SVP-SOC1 module may not act in the ARRVPC of Arabidopsis. On the other hand, we found that ARRVPC was NPR1-dependent (Fig 6A), which is different from an age- and SA-associated but NPR1-independent gain of resistance observed before [52]. It is likely that there are parallel aging pathways strengthen SA signaling during plant maturation.
In co-upregulated Adu/r10pto DEGs, we noticed that cellular response to hypoxia was enriched (Fig 4D). Response to hypoxia of plants has been reported for counteracting submergence and waterlogging stress [53]. Respiratory burst, as part of immune responses, is oxygen dependent. At the site of Botrytis cinerea infection, hypoxic response was induced, leading to the stabilization of subgroup VII of ETHYLENE RESPONSE FACTOR (ERF-VII) [54]. Members in the ERF-VII can activate defense gene as well as hypoxic response [54]. SPL10 may upregulate genes that react to low-oxygen environment when reactive oxygen species accumulates or respiration increases. How hypoxia response contributes to ARR against biotrophs and necrotrophs remains to be seen.
Plant innate immunity shares similarities to human innate immunity, ranging from structures and functionality of innate immune receptors and their downstream signaling cascades [55,56]. Our discovery of miR156-SPL signaling in ARRVPC provides further evidence that heterochronic miRNAs coordinate aging and immunity in planta. In Caenorhabditis elegans, let-7 family microRNAs are well-characterized regulators of developmental timing by specifying stage-specific cell fates in the hypodermal seam cell lineages [57,58]. Interestingly, let-7-fam miRNAs also repress the worm’s resistance to Pseudomonas aeruginosa, an opportunistic human pathogen [59]. The dual function of let-7-fam in developmental timing and immunity is fulfilled through integrating downstream heterochronic genes and the p38 MAPK pathway [59]. Thus, deploying heterochronic microRNAs pathway can be a cross-kingdom strategy to integrate immunity and developmental timing. It will be exciting to further dissect the genetic components and regulatory architecture of coordinated maturation of immunity and development.
Material and methods
Plant material and growth conditions
Arabidopsis wild type, transgenic lines and mutants used in this study were in a Columbia-0 (Col-0) genetic background unless mentioned otherwise. The genetic cross of MIM156/sid2-1 and r10/eds1.2 were generated from this research and progenies from F3 or F4 generation were used for phenotypic test. Information for mutants and transgenic lines can be found in S1 Table. Juvenile leaves were fully expanded leaves 1–2, or 3–4 from soil-grown 4- or 5-week-old plants. Adult leaves were fully expanded leaves that derived from 7-week-old plants. The adult phase of a leaf was confirmed by appearance of abaxial trichomes [40]. Plants were sown on Fafard #3 Mix propagation soil. The planted seeds were then placed under 4°C for 2 days and transferred to a growth room under 23°C/19°C day/night and with 45% humidity. Nine hours light and 15 hours dark photoperiod with 180 μmol m-2s-1 was used as short-day condition. Lighting was made through a 5:3 combination of white (USHIO F32T8/741) and red-enriched (interlectric F32/T8/WS Gro-Lite) fluorescent lights. Plant age was counted from the first day when seeds transferred to the growth room. Only plants used for Fig 5E were grown on ½ MS plates in 24h with continuous light.
Sampling strategy for studying ARRVPC
In our short-day growth condition, plants produced 50–60 leaves before bolting. The ontogenic age of a leaf influenced defense gene expression (Figs 1 and S1A). To minimize the influence of ontogenic age of individual leaves (Figs 1 and S1B), we measured the expansion rate of juvenile and adult leaves and harvested fully expanded juvenile and adult leaves from plants of different ages (Figs 1 and S1C and S1D). Fully expanded leaves 1–4 derived from a 4- or 5-weeks old plants were sampled as juvenile leaves; fully expanded leaves (range from 8–13 depending on variations in plants) from 7-weeks old plants were sampled as adult leaves. Adult leaves showed characteristic abaxial trichome(s), blade serration and elongated petiole [20]. Plants for adult samples were planted 2–3 weeks earlier than those for juvenile leaves. Juvenile and adult samples were collected at the same time for disease assay and transcriptome analysis.
Bacterial growth assay
Pto DC3000 strain was grown under 28°C on King’s B solid medium (40 g/L proteose, 20 g/L glycerol and 15 g/L agar). The medium contained rifamycin for selection and cycloheximide to inhibit fungi growth. Glycerol stock of the bacterial strains stored under -80°C. Bacterial stock was streaked on plate for a 2-day growth and was re-streaked one day before inoculation. For infiltration, bacteria were collected from the plate and suspended in 10 mM MgCl2 solution. Bacterial suspension with concentration of 1 x 105 CFU/mL was infiltrated in Arabidopsis leaves with a needless syringe. After inoculation, plants were covered by transparent lids for one hour. Day 0 samples were collected immediately after removing lids. Each sample contained four leaf discs that were derived from four individual leaves. Leaf samples were collected using the corer (the same size for all plants) and ground with homogenizer (OMNI International) and diluted serially. KB plates with 10 μL of bacteria suspension per sample were placed under room temperature for 2 days. Colony forming units were counted manually and normalized according to inside area of the corer. Day 2 samples were collected as described above two days post-infiltration (dpi). The method was modified from Holt et al. [60].
RNA sequencing and analysis
Pto DC3000 (1 x 108 CFU/mL suspended in 10mM MgCl2) was infiltrated into juvenile and adult wild type (Col-0) leaves and leaves 1–2 from rSPL10 plants, as described above in the bacterial growth assay. 10 mM MgCl2 was used as the mock treatment. Three hours after inoculation, 20 leaf discs with comparable size from 5–10 individual plants were cored and collected as one biological repeat per genotype per treatment. Three biological repeats were prepared for each genotype/treatment. For RNA isolation, plant tissues were flash-frozen in liquid nitrogen and then ground to fine powders using homogenizer (OMNI International). Total RNAs were extracted using E.Z.N.A. Total RNA kit (Omega BIO-TEK). RNA quality was assessed with a 2100 Bioanalyzer instrument (Agilent, RIN score ≥ 7, 28S/18S ≥ 1). RNA concentration was measured using a Nanodrop spectrophotometer (Thermo Scientific, RNA concentration ≥ 50 ng/μL, 260/280 ~2.0). RNA samples were sequenced at BGI San Jose lab. Oligo dT based mRNA enrichment was followed by random N6 primer based reverse transcription. The synthesized DNA nanoballs were then sent for strand-specific mRNA sequencing (PE100) on a DNA Nanoball Sequencing (DNBseq) platform. The data was filtered using SOAPnuke software in BGI. ~48 M clean reads with average Q30 ≥ 88.81% per sample were obtained.
Files of RNA-seq raw reads together with processed data were uploaded to NCBI with access No. GSE208657. The clean RNA-seq data were aligned against the TAIR10 reference genome using HiSAT2 (v.2.1.0, [61]) with following parameters, hisat2 -p 4 -x TAIR10indexed -1 sample_strand1.fq.gz -2 sample_strand2.fq.gz -S aligned_sample.sam. The aligned reads were assembled into transcripts according to the TAIR10 annotation [62,63] using Stringtie [64]. ~ 99% overall alignment rate was reached for each sample. Differential expression analysis was done by comparing transcript levels between pairwise normalized samples using DEseq2 package in R (LFC ≥ ±0.58, padj ≤ 0.05) [65]. Gene ontology was analyzed first against the whole Arabidopsis genome at TAIR Gene Ontology terms website, http://geneontology.org/ [66], and which was then confirmed using total detected 22,622 (covers 88.7% of known genes in Arabidopsis genome) genes of the RNA-seq results on agriGO website http://systemsbiology.cau.edu.cn/agriGOv2/# [67]. Figures were generated in R, with ComplexHeatmap package that was specifically used for Figs 3B–3D and 4 [68]. Complete R scripts are available at S1 Information.
Motif discovery and enrichment analysis
The de novo motif discovery analysis was carried on the website (https://www.arabidopsis.org/tools/bulk/motiffinder/index.jsp). Frequencies of 6-mer motifs were compared between 1000 bp upstream sequences of each input gene and the current Arabidopsis genomic sequence set (33518 sequences). A total of 15 motifs containing the consensus SPL binding site, GTAC, were identified. A frequency-based sequence logo was generated through the weblogo, (https://weblogo.berkeley.edu/logo.cgi). To assess the enrichment of experimentally validated TF binding sites, we used the SEA (https://meme-suite.org/meme/tools/sea). 1000 bp upstream sequences of the 203 Adu/r10 co-upregulated DEGs (Fig 6A) were extracted from TAIR. Shuffled input sequences were chosen as control sequences. The DAP motif database [46] were selected to identify the enriched motifs.
qRT-PCR
Bacterial suspension with 1 x 108 CFU/mL was infiltrated in Arabidopsis leaves. Leaf samples were harvested at 3 hours hpi. Each sample had 16–20 leaf discs derived from 6–10 individual plants. The leaf age of plants in soil was measured following the same standard as the above. For plants on ½ MS plates, 15–20 leaves were harvested per genotype per treatment as one biological rep. leaves 8–13 from 45-day-old of Col-0 with abaxial trichomes were used as adult leaves, leaves 1–2 from 18-day-old Col-0 were used as juvenile leaves. In comparison, leaves 1–2 from 21-day-old of rSPL10 were used. For each bio-rep, three to six technical replicates were used in one qPCR run. RNA extraction was performed using Omega biotek EZNA plant RNA kit. The qPCR was performed in the Applied Biosystems QuantStudio 1 Real-Time PCR system with SYBR Green master mix (Applied Biosystems). PCR conditions were set as follows: 95°C for 5 mins, 40 cycles of 95°C for 15s, 56°C for 30s and 72°C for 20-30s. SAND (AT2G28390) or TUB2 (AT5G62690) was used as reference genes. The relative expression was calculated using relative standard curve methods. Delta-delta CT was also used for calculation when knowing that the PCR efficiency for the primers was at least more than 95% in previous standard curve results. The oligonucleotides used here can be found in S1 Table.
Estradiol-induced gene expression
The estradiol-inducible MIM156 and rSPL3 was constructed using a Gateway compatible version of the XVE system, as described by Brand et al., [69]. The MIM156 and rSPL3 sequence were cloned into pMDC160. Transgenic plants were crossed to plants containing pMDC150-35S [69] and generated homozygous. The estradiol-inducible rSPL10 was generated by cloning rSPL10 into a modified pMDC7 vector tagged with Citrine and HA.
HPLC-MS
Ten to sixty leaves 1–2 of Col-0 and r10 each and three adult Col-0 leaves (plants sawn in soil) were collected as one biological repeat for each genotype or a developmental stage. 3 to 6 biological replicates from five (for adult tissues) to thirty (for juvenile tissues) individual plants were collected in total. The leaves were then lyophilized, powdered, and weighted for getting a comparable dry weight for all samples (weighting error ≤ 0.1 mg). Metabolites from 1.5 mg or 8.5 mg (in separate experimental repeats) of dry tissue of each biological replicate were extracted and were detected under Liquid chromatography-mass spectrometry (HPLC-MS). Samples were added into 200 μL of prechilled metabolite extraction buffer, which consist of 1:1 methanol:chloroform (v/v) supplemented with 13C6-cinnamic acid, D5-benzoic acid, and resorcinol as internal standards [70]. Sonication of the samples took 30 min within an ice-chilled water bath. Then, adding 100 μL of high-performance (HPLC)-grade water, vortexing for 30 sec and centrifuging for 5 min to extract the aqueous phase of each sample, which was transferred to a new tube and stored at -80°C until analysis. Reverse-phase high-performance liquid chromatography-mass spectrometry (HPLC-MS) was used to detect Free SA and SA-conjugates [70]. Amount of salicylic acid beta-glucoside (SAG) and salicylic acid (SA) were measured and calculated in the unit of nmole metabolite per gram of dry weight (nmole/g DW).
ChIP-qPCR assay
The procedure and the preparation of reagents were modified from protocols [71–73]. In brief, 1 gram of non-treated fully expanded adult leaf tissues were collected from the proSPL10::rSPL10-YFP line. Leaves from 2–3 plants were harvested as one biological sample. Three biological replicates in total from two independent experiments were used. The tissue was crosslinked, and the chromatin was extracted and sonicated using nuclei extraction buffers and a bioruptor UCD-200 with chilling pump. 15 μL of post-sonicating chromatin solution was saved as the input. The remaining chromatin solution was immunoprecipitated by using GFP-trap Magnetic Agarose (ChromoTek, cat no. gtma). Diluted input and DNA eluted after IP were used for qPCR using primers at the indicated positions (Fig 6B and S1 Table). We used the following formula to calculate the estimated CT value for adjusting CT values of input and IP samples, DCt [normalized ChIP] = (Ct [Input]–Log2 (dilution factor for Input))–((Ct [ChIP]–Log2 (dilution factor for ChIP)), and the final output % input = 100 * 2 ^ (DCt [normalized ChIP] [73].
GUS staining assay
Plants carrying proPR2::GUS were harvested at six week after planting. The GUS solution was prepared as following and was vacuum infiltrated into plants, 0.1 M NaPO4, pH 7.0, 10 mM EDTA. 0.1% Triton X-100, 1 mM K3Fe(CN)6, 2 mM X-Gluc (X-Gluc was dissolved in N, N-DMF and made fresh). After 24 h incubation at 37°C, the staining solution was replaced with 70% ethanol. Tissues were washed several times with 70% ethanol until the chlorophyll in leaves was cleared. The GUS-stained leaves were imaged using a dissecting microscope (VWR).
Supporting information
S1 Fig. Ontogenic change of SA response and sampling approach for examining ARRvpc.
A, ontogenic-associated promoter activities of proPR2::GUS in an uninfected plant. Note the high activity in fully expanded juvenile leaves (1–7) and low in young adult leaves (12–13). The indicated leaf numbers were based on the order of the leaves on shoot. B, the incremental expression of PR2 gene spanning the expansion of juvenile and adult leaves. I, premature leaves. II, intermediate premature leaves. III, mature leaves. C, an outline of the ontogenic maturation of a juvenile leaf and an adult leaf. The boxed region indicates distinct ontogenic age of juvenile and adult leaves from the same plant; asteroids indicate juvenile and adult leaves of the same ontogenic age. D, the quantified leaf expansion rate in juvenile and adult leaves. Leaf areas were quantified and normalized through Fiji software. E, a cartoon depiction of shoot development and leaf maturation that are concurrent during the vegetative phase change.
https://doi.org/10.1371/journal.ppat.1011218.s001
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S2 Fig. Developmental phenotypes of rSPLs and spl mutants.
A and D, arrows indicate leaf 1–2 of juvenile Col-0 and rSPLs. B-C, arrows indicate representative adult leaves of Col-0 and spl mutants.
https://doi.org/10.1371/journal.ppat.1011218.s002
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S3 Fig. Quality control of RNA-seq datasets and Venn diagrams of adult vs juvenile DEGs.
A, principal component analysis showed that the effect of age and genotype likely explained 52% variance of the samples, and Pto infection effect likely explained 17% variance of the samples. B, the sample-to-sample distance matrix showed that biological replicates (Mock1-3 and Pto1-3) were well correlated (in close distance) within per genotype per treatment. The column names of the matrix are in the same order as the row names—from the “Adu-Mock1” (the first on the left) to the “r10-Pto3” (the first on the right). C, venn diagrams of Adu-DEGs generated from the indicated pair-wise comparisons. Color-coding of numbers, adult-specifically Pto-triggered DEGs (red), Juvenile-specifically triggered (brown), commonly triggered in both adults and juveniles, i.e., shared (grey), and overlap DEGs between Adunof and Adupto (black). Green numbers indicate the 20.1% synergistic DEGs that mentioned in the main text. Blue numbers refer to DEGs that were Adunof but not Adupto. Adult preferentially Pto-triggered DEGs are listed in S3 Table.
https://doi.org/10.1371/journal.ppat.1011218.s003
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S4 Fig. A, a table of enriched SPL-binding motifs within the upregulated 203 and plant phenotype of proSPL10::rSPL10-YFP.
A. Frequency-based DNA logos are shown for each enriched motif. The analysis was performed in the simple enrichment analysis-MEME Suite. Details were described in the method section. B, plant phenotype of proSPL10::rSPL10-YFP. Note the elongated leaves 1 and 2 in the transgenic plant.
https://doi.org/10.1371/journal.ppat.1011218.s004
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S5 Fig. Expression of SPL3 and SPL10 in MIM156/sid2-1 and r10/eds1.2.
A, SPL3 was used as an indicator of MIM156 function. No difference was observed in MIM156 and MIM156/sid2-1. B, SPL10 was expressed at comparable level in rSPL10 and rSPL10/eds1.2. Student t test, ns, not significant, *, p < 0.05, **, p < 0.01.
https://doi.org/10.1371/journal.ppat.1011218.s005
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S6 Fig. A model of miR156-SPL10 regulated age-related resistance during the vegetative phase change.
In brief, miR156 suppressed the resistance in juvenile phase through inhibiting SPL10. The increased expression of SPL10 followed by the decline of miR156 level gives rise to a high immune output in adult phase. That is achieved via promoting the expression of PAD4 as well as enhancing expressions of other components in SA biosynthesis and signaling pathways.
https://doi.org/10.1371/journal.ppat.1011218.s006
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S6 Table. Lists of Gene Ontology terms in Figs 3 and 4.
https://doi.org/10.1371/journal.ppat.1011218.s012
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Acknowledgments
We thank Scott Poethig from University of Pennsylvania to provide rSPL and spl mutants. We thank Khadijeh Mozaffari, Scott Harding and Chung-Jui Tsai of the Plant Metabolomics Laboratory at the University of Georgia for analytical assistance. We thank Jovana Mijatovic for providing feedback on the manuscript.
References
- 1. Solana R, Pawelec G, Tarazona R.(2006). Aging and innate immunity. Immunity.24(5):491–4. pmid:16713963.
- 2. Develey-Rivière MP, Galiana E.(2007). Resistance to pathogens and host developmental stage: a multifaceted relationship within the plant kingdom. New Phytologist.175(3):405–16. pmid:17635216
- 3. Hu L, Yang L.(2019). Time to fight: Molecular mechanisms of age-related resistance. Phytopathology.109(9):1500–8. pmid:31192748
- 4. Zou Y, Wang S, Zhou Y, Bai J, Huang G, Liu X, et al.(2018). Transcriptional regulation of the immune receptor FLS2 controls the ontogeny of plant innate immunity. The Plant Cell.30(11):2779–94. pmid:30337428
- 5. Chandler M, Tracy W.(2007). Vegetative phase change among sweet corn (Zea mays L.) hybrids varying for reaction to common rust (Puccinia sorghi Schw.). Plant breeding.126(6):569–73.
- 6. Rusterucci C, Zhao Z, Haines K, Mellersh D, Neumann M, Cameron R.(2005). Age-related resistance to Pseudomonas syringae pv. tomato is associated with the transition to flowering in Arabidopsis and is effective against Peronospora parasitica. Physiological and molecular plant pathology.66(6):222–31.
- 7. Glander S, He F, Schmitz G, Witten A, Telschow A, de Meaux J.(2018). Assortment of flowering time and immunity alleles in natural Arabidopsis thaliana populations suggests immunity and vegetative lifespan strategies coevolve. Genome biology and evolution.10(9):2278–91. pmid:30215800
- 8. Paludan SR, Pradeu T, Masters SL, Mogensen TH.(2021). Constitutive immune mechanisms: mediators of host defence and immune regulation. Nat Rev Immunol.21(3):137–50. pmid:32782357.
- 9. Panter S, Jones DA.(2002). Age-related resistance to plant pathogens.
- 10.
Poethig RS. Vegetative phase change and shoot maturation in plants. Current topics in developmental biology. 105: Elsevier; 2013. p. 125–52. https://doi.org/10.1016/B978-0-12-396968-2.00005-1
- 11. Brink RA.(1962). Phase change in higher plants and somatic cell heredity. The Quarterly Review of Biology.37(1):1–22.
- 12. Poethig RS.(1990). Phase change and the regulation of shoot morphogenesis in plants. Science.250(4983):923–30. pmid:17746915.
- 13. Alzohairy SA, Hammerschmidt R, Hausbeck MK.(2020). Changes in winter squash fruit exocarp structure associated with age-related resistance to Phytophthora capsici. Phytopathology.110(2):447–55. pmid:31454304
- 14. Carella P, Wilson DC, Cameron RK.(2015). Some things get better with age: differences in salicylic acid accumulation and defense signaling in young and mature Arabidopsis. Frontiers in plant science.5:775. pmid:25620972
- 15. Wang J-W, Park MY, Wang L-J, Koo Y, Chen X-Y, Weigel D, et al.(2011). miRNA control of vegetative phase change in trees. PLoS Genet.7(2):e1002012. Epub 2011/03/09. pmid:21383862.
- 16. Birkenbihl RP, Jach G, Saedler H, Huijser P.(2005). Functional dissection of the plant-specific SBP-domain: overlap of the DNA-binding and nuclear localization domains. Journal of molecular biology.352(3):585–96. pmid:16095614
- 17. Liang X, Nazarenus TJ, Stone JM.(2008). Identification of a consensus DNA-binding site for the Arabidopsis thaliana SBP domain transcription factor, AtSPL14, and binding kinetics by surface plasmon resonance. Biochemistry.47(12):3645–53. pmid:18302343
- 18. Rhoades MW, Reinhart BJ, Lim LP, Burge CB, Bartel B, Bartel DP.(2002). Prediction of plant microRNA targets. Cell.110(4):513–20. Epub 2002/08/31. pmid:12202040.
- 19. Wu G, Poethig RS.(2006). Temporal regulation of shoot development in Arabidopsis thaliana by miR156 and its target SPL3. Development.133(18):3539–47. pmid:16914499.
- 20. Wu G, Park MY, Conway SR, Wang J-W, Weigel D, Poethig RS.(2009). The sequential action of miR156 and miR172 regulates developmental timing in Arabidopsis. Cell.138(4):750–9. pmid:19703400
- 21. Gandikota M, Birkenbihl RP, Höhmann S, Cardon GH, Saedler H, Huijser P.(2007). The miRNA156/157 recognition element in the 3′ UTR of the Arabidopsis SBP box gene SPL3 prevents early flowering by translational inhibition in seedlings. The Plant Journal.49(4):683–93. pmid:17217458
- 22. Wang H, Wang H.(2015). The miR156/SPL module, a regulatory hub and versatile toolbox, gears up crops for enhanced agronomic traits. Molecular plant.8(5):677–88. pmid:25617719
- 23. Xu M, Hu T, Zhao J, Park M-Y, Earley KW, Wu G, et al.(2016). Developmental functions of miR156-regulated SQUAMOSA PROMOTER BINDING PROTEIN-LIKE (SPL) genes in Arabidopsis thaliana. PLoS genetics.12(8):e1006263. pmid:27541584
- 24. Ye B-B, Shang G-D, Pan Y, Xu Z-G, Zhou C-M, Mao Y-B, et al.(2020). AP2/ERF transcription factors integrate age and wound signals for root regeneration. The Plant Cell.32(1):226–41. pmid:31649122
- 25. Cardon G, Höhmann S, Klein J, Nettesheim K, Saedler H, Huijser P.(1999). Molecular characterisation of the Arabidopsis SBP-box genes. Gene.237(1):91–104. pmid:10524240
- 26. Sun T, Zhou Q, Zhou Z, Song Y, Li Y, Wang H-B, et al.(2022). SQUINT Positively Regulates Resistance to the Pathogen Botrytis cinerea via miR156–SPL9 Module in Arabidopsis. Plant and Cell Physiology.
- 27. Yin H, Hong G, Li L, Zhang X, Kong Y, Sun Z, et al.(2019). miR156/SPL9 Regulates Reactive Oxygen Species Accumulation and Immune Response in Arabidopsis thaliana. Phytopathology.PHYTO-08-18-0306-R. pmid:30526361
- 28. Berens ML, Wolinska KW, Spaepen S, Ziegler J, Nobori T, Nair A, et al.(2019). Balancing trade-offs between biotic and abiotic stress responses through leaf age-dependent variation in stress hormone cross-talk. Proc Natl Acad Sci U S A.116(6):2364–73. Epub 20190123. pmid:30674663.
- 29. Kanojia A, Gupta S, Benina M, Fernie AR, Mueller-Roeber B, Gechev T, et al.(2020). Developmentally controlled changes during Arabidopsis leaf development indicate causes for loss of stress tolerance with age. Journal of experimental botany.71(20):6340–54. pmid:32720687
- 30. Mansfeld BN, Colle M, Kang Y, Jones AD, Grumet R.(2017). Transcriptomic and metabolomic analyses of cucumber fruit peels reveal a developmental increase in terpenoid glycosides associated with age-related resistance to Phytophthora capsici. Hortic Res.4:17022. pmid:28580151.
- 31. Mansfeld BN, Colle M, Zhang C, Lin Y-C, Grumet R.(2020). Developmentally regulated activation of defense allows for rapid inhibition of infection in age-related resistance to Phytophthora capsici in cucumber fruit. BMC genomics.21(1):1–25. pmid:32917129
- 32. Wilson DC, Carella P, Isaacs M, Cameron RK.(2013). The floral transition is not the developmental switch that confers competence for the Arabidopsis age-related resistance response to Pseudomonas syringae pv. tomato. Plant Mol Biol.83(3):235–46. pmid:23722504.
- 33. Carviel JL, Al-Daoud F, Neumann M, Mohammad A, Provart NJ, Moeder W, et al.(2009). Forward and reverse genetics to identify genes involved in the age-related resistance response in Arabidopsis thaliana. Mol Plant Pathol.10(5):621–34. pmid:19694953.
- 34. He J, Xu M, Willmann MR, McCormick K, Hu T, Yang L, et al.(2018). Threshold-dependent repression of SPL gene expression by miR156/miR157 controls vegetative phase change in Arabidopsis thaliana. PLoS Genet.14(4):e1007337. pmid:29672610.
- 35. Franco-Zorrilla JM, Valli A, Todesco M, Mateos I, Puga MI, Rubio-Somoza I, et al.(2007). Target mimicry provides a new mechanism for regulation of microRNA activity. Nature genetics.39(8):1033. pmid:17643101
- 36. Guo A-Y, Zhu Q-H, Gu X, Ge S, Yang J, Luo J.(2008). Genome-wide identification and evolutionary analysis of the plant specific SBP-box transcription factor family. Gene.418(1–2):1–8. pmid:18495384
- 37. Padmanabhan MS, Ma S, Burch-Smith TM, Czymmek K, Huijser P, Dinesh-Kumar SP.(2013). Novel positive regulatory role for the SPL6 transcription factor in the N TIR-NB-LRR receptor-mediated plant innate immunity. PLoS pathogens.9(3):e1003235. pmid:23516366
- 38. Yamaguchi A, Wu M-F, Yang L, Wu G, Poethig RS, Wagner D.(2009). The microRNA-regulated SBP-Box transcription factor SPL3 is a direct upstream activator of LEAFY, FRUITFULL, and APETALA1. Developmental cell.17(2):268–78. pmid:19686687
- 39. Ding P, Sakai T, Krishna Shrestha R, Manosalva Perez N, Guo W, Ngou BPM, et al.(2021). Chromatin accessibility landscapes activated by cell-surface and intracellular immune receptors. Journal of Experimental Botany.72(22):7927–41. pmid:34387350
- 40. Telfer A, Bollman KM, Poethig RS.(1997). Phase change and the regulation of trichome distribution in Arabidopsis thaliana. Development.124(3):645–54. Epub 1997/02/01. pmid:9043079.
- 41. Thaler JS, Humphrey PT, Whiteman NK.(2012). Evolution of jasmonate and salicylate signal crosstalk. Trends in plant science.17(5):260–70. pmid:22498450
- 42. Ando K, Carr KM, Colle M, Mansfeld BN, Grumet R.(2015). Exocarp Properties and Transcriptomic Analysis of Cucumber (Cucumis sativus) Fruit Expressing Age-Related Resistance to Phytophthora capsici. PLoS One.10(11):e0142133. pmid:26528543.
- 43. Yang L, Teixeira PJPL, Biswas S, Finkel OM, He Y, Salas-Gonzalez I, et al.(2017). Pseudomonas syringae Type III Effector HopBB1 Promotes Host Transcriptional Repressor Degradation to Regulate Phytohormone Responses and Virulence. Cell Host Microbe.21(2):156–68. pmid:28132837.
- 44. Ding Y, Sun T, Ao K, Peng Y, Zhang Y, Li X, et al.(2018). Opposite roles of salicylic acid receptors NPR1 and NPR3/NPR4 in transcriptional regulation of plant immunity. Cell.173(6):1454–67. e15. pmid:29656896
- 45. Cui H, Gobbato E, Kracher B, Qiu J, Bautor J, Parker JE.(2017). A core function of EDS1 with PAD4 is to protect the salicylic acid defense sector in Arabidopsis immunity. New Phytologist.213(4):1802–17. pmid:27861989
- 46. O’Malley RC, Huang S-sC, Song L, Lewsey MG, Bartlett A, Nery JR, et al.(2016). Cistrome and epicistrome features shape the regulatory DNA landscape. Cell.165(5):1280–92. pmid:27203113
- 47. Liu M, Shi Z, Zhang X, Wang M, Zhang L, Zheng K, et al.(2019). Inducible overexpression of Ideal Plant Architecture1 improves both yield and disease resistance in rice. Nature plants.1.
- 48. Wang J, Zhou L, Shi H, Chern M, Yu H, Yi H, et al.(2018). A single transcription factor promotes both yield and immunity in rice. Science.361(6406):1026–8. pmid:30190406
- 49. Deng Y, Wang J, Tung J, Liu D, Zhou Y, He S, et al.(2018). A role for small RNA in regulating innate immunity during plant growth. PLoS pathogens.14(1):e1006756. pmid:29293695
- 50. Yalpani N, Shulaev V, Raskin I.(1993). Endogenous salicylic acid levels correlate with accumulation of pathogenesis-related proteins and virus resistance in tobacco. Phytopathology.83(7):702–8.
- 51. Wilson DC, Kempthorne CJ, Carella P, Liscombe DK, Cameron RK.(2017). Age-Related Resistance in Arabidopsis thaliana Involves the MADS-Domain Transcription Factor SHORT VEGETATIVE PHASE and Direct Action of Salicylic Acid on Pseudomonas syringae. Mol Plant Microbe Interact.30(11):919–29. pmid:28812948.
- 52. Kus JV, Zaton K, Sarkar R, Cameron RK.(2002). Age-related resistance in Arabidopsis is a developmentally regulated defense response to Pseudomonas syringae. The Plant Cell.14(2):479–90. pmid:11884688
- 53. Fukao T, Barrera-Figueroa BE, Juntawong P, Pena-Castro JM.(2019). Submergence and Waterlogging Stress in Plants: A Review Highlighting Research Opportunities and Understudied Aspects. Front Plant Sci.10:340. Epub 20190322. pmid:30967888.
- 54. Valeri MC, Novi G, Weits DA, Mensuali A, Perata P, Loreti E.(2021). Botrytis cinerea induces local hypoxia in Arabidopsis leaves. New Phytol.229(1):173–85. pmid:32124454.
- 55. Jones JD, Vance RE, Dangl JL.(2016). Intracellular innate immune surveillance devices in plants and animals. Science.354(6316):aaf6395. pmid:27934708
- 56. Rossez Y, Wolfson EB, Holmes A, Gally DL, Holden NJ.(2015). Bacterial flagella: twist and stick, or dodge across the kingdoms. PLoS pathogens.11(1):e1004483. pmid:25590430
- 57. Reinhart BJ, Slack FJ, Basson M, Pasquinelli AE, Bettinger JC, Rougvie AE, et al.(2000). The 21-nucleotide let-7 RNA regulates developmental timing in Caenorhabditis elegans. nature.403(6772):901–6. pmid:10706289
- 58. Abbott AL, Alvarez-Saavedra E, Miska EA, Lau NC, Bartel DP, Horvitz HR, et al.(2005). The let-7 MicroRNA family members mir-48, mir-84, and mir-241 function together to regulate developmental timing in Caenorhabditis elegans. Developmental cell.9(3):403–14. pmid:16139228
- 59. Ren Z, Ambros VR.(2015). Caenorhabditis elegans microRNAs of the let-7 family act in innate immune response circuits and confer robust developmental timing against pathogen stress. Proceedings of the National Academy of Sciences.112(18):E2366–E75. pmid:25897023
- 60. Holt BF 3rd, Belkhadir Y, Dangl JL.(2005). Antagonistic control of disease resistance protein stability in the plant immune system. Science.309(5736):929–32. pmid:15976272.
- 61. Kim D, Paggi JM, Park C, Bennett C, Salzberg SL.(2019). Graph-based genome alignment and genotyping with HISAT2 and HISAT-genotype. Nat Biotechnol.37(8):907–15. pmid:31375807.
- 62. Lamesch P, Berardini TZ, Li D, Swarbreck D, Wilks C, Sasidharan R, et al.(2012). The Arabidopsis Information Resource (TAIR): improved gene annotation and new tools. Nucleic Acids Res.40(Database issue):D1202-10. pmid:22140109.
- 63. Swarbreck D, Wilks C, Lamesch P, Berardini TZ, Garcia-Hernandez M, Foerster H, et al.(2008). The Arabidopsis Information Resource (TAIR): gene structure and function annotation. Nucleic Acids Res.36(Database issue):D1009–14. pmid:17986450.
- 64. Pertea M, Kim D, Pertea GM, Leek JT, Salzberg SL.(2016). Transcript-level expression analysis of RNA-seq experiments with HISAT, StringTie and Ballgown. Nat Protoc.11(9):1650–67. pmid:27560171.
- 65. Love MI, Huber W, Anders S.(2014). Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol.15(12):550. pmid:25516281.
- 66. Dolinski K, Dwight S, Eppig J, Harris M, Hill D, Issel-Tarver L, et al.(2000). Gene ontology: tool for the unification of biology. The Gene Ontology Consortium. Nat Genet.25(1):2529Attri. pmid:10802651
- 67. Tian T, Liu Y, Yan H, You Q, Yi X, Du Z, et al.(2017). agriGO v2.0: a GO analysis toolkit for the agricultural community, 2017 update. Nucleic Acids Res.45(W1):W122–W9. pmid:28472432.
- 68. Gu Z, Eils R, Schlesner M.(2016). Complex heatmaps reveal patterns and correlations in multidimensional genomic data. Bioinformatics.32(18):2847–9. pmid:27207943
- 69. Brand L, Horler M, Nuesch E, Vassalli S, Barrell P, Yang W, et al.(2006). A versatile and reliable two-component system for tissue-specific gene induction in Arabidopsis. Plant Physiol.141(4):1194–204. pmid:16896232.
- 70. Xue LJ, Guo W, Yuan Y, Anino EO, Nyamdari B, Wilson MC, et al.(2013). Constitutively elevated salicylic acid levels alter photosynthesis and oxidative state but not growth in transgenic populus. Plant Cell.25(7):2714–30. Epub 20130731. pmid:23903318.
- 71.
Ricci WA, Levin L, Zhang X. Genome-Wide Profiling of Histone Modifications with ChIP-Seq. Cereal Genomics: Springer; 2020. p. 101–17. https://doi.org/10.1007/978-1-4939-9865-4_9
- 72. Yamaguchi N, Winter CM, Wu M-F, Kwon CS, William DA, Wagner D.(2014). PROTOCOLS: Chromatin immunoprecipitation from Arabidopsis tissues. The Arabidopsis book/American Society of Plant Biologists.12. pmid:24653666
- 73. Lin X, Tirichine L, Bowler C.(2012). Protocol: Chromatin immunoprecipitation (ChIP) methodology to investigate histone modifications in two model diatom species. Plant methods.8(1):1–9.