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KAKU4 regulates leaf senescence through modulation of H3K27me3 deposition in the Arabidopsis genome

BMC Plant Biology volume 24, Article number: 177 (2024) Cite this article

Abstract

Lamins are the major components of the nuclear lamina, which regulate chromatin structure and gene expression. KAKU4 is a unique nuclear lamina component in the nuclear periphery, modulates nuclear shape and size in Arabidopsis. The knowledge about the regulatory role of KAKU4 in leaf development remains limited. Here we found that knockdown of KAKU4 resulted in an accelerated leaf senescence phenotype, with elevated levels of H2O2 and hormones, particularly SA, JA, and ABA. Our results demonstrated the importance of KAKU4 as a potential negative regulator in age-triggered leaf senescence in Arabidopsis. Furthermore, we conducted combination analyses of transcriptomic and epigenomic data for the kaku4 mutant and WT leaves. The knockdown of KAKU4 lowered H3K27me3 deposition in the up-regulated genes associated with hormone pathways, programmed cell death, and leaf senescence, including SARD1, SAG113/HAI1, PR2, and so forth. In addition, we found the functional crosstalks between KAKU4 and its associated proteins (CRWN1/4, PNET2, GBPL3, etc.) through comparing multiple transcriptome datasets. Overall, our results indicated that KAKU4 may inhibit the expression of a series of genes related to hormone signals and H2O2 metabolism by affecting the deposition of H3K27me3, thereby suppressing leaf senescence.

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FormalPara Running title

Knockdown of KAKU4 speeds leaf senescence.

Summary Statement:

In summary, our results demonstrated the importance of KAKU4 as a potential negative regulator in age-triggered leaf senescence through modulating H3K27me3 deposition in Arabidopsis. This work may advance the knowledge about the regulatory role of plant nuclear lamina proteins or the regulation of leaf senescence.

Introduction

The nuclear lamina (NL) is an important structural determinant for the nuclear envelope, covering the inner surface of the inner nuclear membrane (INM). Lamina consists of a thin meshwork of lamins, which are structural components of the nuclear lamina that regulate genome organization and gene expression [1,2,3,4,5]. A point mutation in the eleventh exon of the lamin encoding gene LMNA can cause Hutchinson-Gilford progeria syndrome (HGPS), a rare premature-aging disease in children. This mutation affects the process of alternative splicing, resulting in the accumulation of the truncated abnormal protein, which leads to a series of changes in the nucleus, including in nuclear morphology, DNA repair, chromatin remodeling, and nuclear transport [6,7,8]. Lamin A buffers Casein kinase 2 (CK2) activity to modulate aging in a progeria mouse model [9]. Declining lamin B1 expression mediates age-dependent decreases of hippocampal stem cell activity [10]. Thus, the defects in the components of the nuclear lamina can affect the morphology of the nucleus, leading to human diseases and aging.

Although no lamin-homologous proteins have been found in plants, the putative lamina-like structures have been discovered in the carrot, and a nuclear matrix constituent protein (NMCP1) has been identified as a peripheral framework component of its nuclei [11]. In Arabidopsis, multiple lamin-like proteins are identified, including CRWNs [12, 13], KAKU4 [14], NEAPs [15], and PNET2 [16]. Especially, the proteomics technologies speed up to identify the complex components among the interaction partners of CRWN1, KAKU4, PNET2_A/B, NEAP1, the nuclear basket protein GBPL3, and some other lamina related components [16,17,18,19].

Four CRWNs, named CRWN1, CRWN2, CRWN3, and CRWN4, are NMCP homologs in Arabidopsis [13, 20]. The mutants crwn1 and crwn4 show aberrantly small and spherical nuclei in the epidermal cells of the leaf and root [12]. In addition to nuclear morphology and size, CRWNs are involved in the regulation of a series of biological processes. The double mutant crwn1crwn2 and crwn1crwn4 exhibit ectopic defense responses and spontaneous cell death against the virulent bacterial pathogens, which is related to the upregulation of salicylic acid (SA)-biosynthesis gene SID2 and increase SA content [21]. CRWNs play an important role in diminishing ROS accumulation and protecting genomic DNA against excessive oxidative damage induced by the genotoxic agent methyl methanesulfonate. Under normal growth conditions, crwn1crwn3, crwn2crwn3, and crwn2crwn4 show enhanced leaf cell death, over-accumulation of ROS, and slightly earlier leaf senescence [22].

Meanwhile, CRWN1 is involved in maintaining chromatin compartmentalization [23]. The loss of CRWN1 results in the loss of specific chromatin distribution at the nuclear periphery. Furthermore, CRWN1, CRWN4, and non-CG DNA methylation have recently been discovered to be involved in regulating chromatin tethering at the nuclear periphery [24]. CRWN1 interacts with the copper-associated gene locus, localized to the nuclear lamina under excess copper conditions [25]. In addition, PWWP-domain interactor of polycombs (PWO1) has been reported to physically interact with CRWN1 protein, functioning in the same pathway to affect nuclear morphology. Further, it regulates the expression of a similar set of targets, which have significant overlap with H3K27me3 targets [26]. PWO1 is involved in polycomb group (PcG) silencing by repressing H3K27me3 accumulation in a subset of PcG targets [27]. Polycomb repressive complex 2 (PRC2) can trimethylate lysine 27 on histone H3 (H3K27me3) [28]. H3K27me3 accumulation levels near genes involved in salicylic acid biosynthesis are decreased in crwn mutants [29]. Recently, AtGBPL3/CRWN1&4/KAKU4 complex has been identified to play an essential role during interphase in H3K27me3-associated transcriptional repression at the nuclear periphery [30].

KAKU4 protein has been identified as a nuclear inner envelope protein and a unique nuclear lamina component in the nuclear periphery, physically interacts with CRWN1 and CRWN4, and modulates nuclear shape and size [14]. Similar to crwn1 and crwn4, the nuclei of the kaku4 mutant in epidermal cells of cotyledons, hypocotyls, and roots, are smaller and less elongated than those of wild-type (WT) plants. KAKU4 is mediated by the deformation of the vegetative nucleus of pollen grains and controls its migration over sperm cells in pollen tubes [31]. However, the knowledge of the biological functions and gene regulation network of KAKU4 protein remains limited. In this study, we found that the knockdown of the KAKU4 gene resulted in significant early leaf senescence. In the kaku4 mutant, H2O2 was obviously accumulated, and the plant hormones salicylic acid (SA), jasmonic acid (JA), and abscisic acid (ABA) were also increased. To elucidate the possible molecular mechanisms underlying the KAKU4 protein regulating plant leaf senescence, we conducted high-throughput sequencing technology, including RNA-seq and ChIP-seq data analyses. Our results suggested that KAKU4 may modulate H3K27me3 deposition to regulate leaf senescence in Arabidopsis.

Results

Knockdown of KAKU4 results in an accelerated leaf-senescence phenotype

To investigate the possible role of the KAKU4 gene in leaf development, we performed a genetic analysis of the age-triggered leaf-senescence phenotype for the SALK T-DNA insertion line kaku4 mutant (SALK_076754) (Supplementary Figure S1A) and wide-type (WT) plants. Compared to WT, kaku4 mutant plants exhibited a significantly accelerated leaf-senescence phenotype. In 4-week-old plants, the cotyledons of the kaku4 mutant had begun to turn yellow (Supplementary Figure S1D). In the sixth week, some rosette leaves of kaku4 mutant turned yellow, while most leaves of WT plants remained green (Fig. 1A and B, Supplementary Figure S1E). Additionally, whole plant and leaves of the kaku4 mutant were smaller than those of WT plants (Fig. 1A and B). We also examined some senescence-related parameters to validate the early-senescence phenotype of the kaku4 mutant. Consistent with the accelerated leaf-senescence phenotype, the chlorophyll content in rosette leaves of the kaku4 mutant was significantly lower than that in the WT (Fig. 1C), and membrane-ion leakage was higher in the kaku4 mutant than in the WT (Fig. 1D).

Fig. 1
figure 1

Phenotypic analysis of the kaku4 mutant and WT in leaf senescence. (A) Age-dependent senescence phenotype of the sixth-week kaku4 mutant and WT. The length of the white bar represents 1 cm. (B) Rosettes leaves of the sixth-week kaku4 mutant and WT. Bar = 1 cm. (C) Chlorophyll content in the sixth-week rosette leaves of the kaku4 mutant and WT. (D) Relative ion leakage in the sixth-week rosette leaves of the kaku4 mutant and WT. (E) H2O2 content in the sixth-week rosettes leaves of the kaku4 mutant and WT. (F-H) Content of the plant hormone: SA (F), JA (G), and ABA (H) in the sixth-week rosettes leaves of kaku4 mutant and WT. Significant difference between the kaku4 mutant and WT were determined according to Student’s t-test. *P-value ≤ 0.05, **P-value ≤ 0.01, ***P-value ≤ 0.001. The pair-wise ANOVA test for the genotypic variation between kaku4 mutant and WT (C-H) were showed in Supplementary Table S11

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To study the possible signaling pathways of KAKU4-mediated leaf senescence, we measured several aspects related to leaf senescence, such as H2O2 and hormones. H2O2 is an important regulator of leaf senescence [32]. Many aging-triggered leaf senescence processes are mediated by the H2O2-signaling pathway [33, 34]. Using a quantitative assay, we assessed H2O2 content in sixth-week rosette leaves of the kaku4 mutant and WT plants, and found that the kaku4 mutant produced much more H2O2 than the WT (Fig. 1E). The measurement result for H2O2 indicated that knockdown of KAKU4 gene could accelerate leaf senescence by inducing H2O2 levels. Phytohormones also function as important regulators in leaf senescence, and SA, ABA, and JA accelerate leaf senescence [33, 35, 36]. Thus, we measured the levels of several hormones in the sixth-week rosette leaves of the kaku4 mutant and WT plants (Fig. 1F-H). The contents of SA, JA, and ABA in kaku4 mutant were 4-fold, 9-fold, and 3-fold higher than those in WT, respectively. In the meanwhile, we used one-way ANOVA with Bonferroni correction for the statistical analysis, the results showed that the difference of the phenotypes between kaku4 mutant and WT were significant (Supplemental Table S11).

In addition, we applied a transgenic strategy to complement the kaku4 mutant phenotype. We generated several KAKU4-complemented lines (35S::KAKU4/kaku4-1 and 35S::KAKU4/kaku4-2) and KAKU4-overexpression lines (35S::KAKU4/WT-1 and 35S::KAKU4/WT-2) under the control of the 35S promoter (Supplementary Figure S1B) against the background of the kaku4 mutant and WT, respectively. The gene expression levels of both types of transformation lines together with the kaku4 mutant and WT were validated with qRT-PCR (Supplementary Figure S1C). The results of phenotypic analysis showed that the accelerated leaf-senescence phenotype was rescued in KAKU4-complemented lines, and chlorophyll content was higher than that of the kaku4 mutant. In the meantime, KAKU4-overexpression lines exhibited a slightly delayed leaf-senescence phenotype with relatively higher chlorophyll content than that in WT plants (Supplementary Figure S1E and F).

To further confirm that the mutation of KAKU4 accelerates leaf senescence, we employed CRISPR/Cas9 gene editing approach to knock down the KAKU4 gene and generated specific and heritable targeted mutations in Arabidopsis. We designed one editing site and successfully obtained three CRISPR/Cas9 mutants, including kaku4-03Cas9, kaku4-04Cas9, and kaku4-05Cas9 (Supplementary Figure S2A). Compared to WT, kaku4 CRISPR/Cas9 mutants showed accelerated leaf-senescence phenotype as well as the T-DNA insertion line, no matter for the cotyledons of kaku4 mutants in the young plants (Supplementary Figure S2B) or for the rosette leaves of kaku4 mutants in the mature plants (Supplementary Figure S2C and S2D). In the meanwhile, we examined the chlorophyll content in rosette leaves of both T-DNA insertion line and CRISPR/Cas9 mutants, and the result validated the early-senescence phenotype of the kaku4 mutants (Supplementary Figure S2E).

Overall, our results demonstrated the importance of KAKU4 as a potential negative regulator in age-triggered leaf senescence in Arabidopsis.

KAKU4 mediates some key biological processes

Transcriptomic data analysis was conducted to explore the possible downstream genes regulated by KAKU4 during leaf senescence. Rosette leaves of the sixth-week kaku4 mutant and WT plants were sampled for RNA-seq with three independent biological replicates for each sample (Supplementary Table S1). We performed differential expression analyses on RNA-seq data using DESeq2 [37] with the cutoff: |log2(fold change)| ≥ 1 and P-value ≤ 0.05. Compared to the WT, 3,281 genes were upregulated and 2,073 genes were downregulated in kaku4 mutant (Supplementary Table S2). Among these differentially expressed genes, we found that some iron homeostasis related BHLH genes such as BHLH038, BHLH039, and BHLH100 [38] were significantly downregulated with large fold changes (log2(fold change) ≤ -3) (Fig. 2A). Likewise, some upregulated genes showing the large fold changes (log2(fold change) ≥ 3), are mainly related to leaf senescence, programmed cell death (PCD), and plant hormone pathways, including SRG2, AtGSTU3, KTI1, JOX3, JAO4, NATA1, and NCED2. The SRG2 gene encodes a protein similar to beta-glucosidase that is expressed in the senescing organs of Arabidopsis plants [39]. We found that SRG2 was significantly upregulated in the 6-week-old rosette leaves of the kaku4 mutant, as well as the senescence-associated reference gene AtGSTU3, which participates in PCD and the toxin catabolic process [40]. In addition, the genes with large fold change between the WT and kaku4 mutant also included some hormone biosynthesis and signaling pathways related genes, such as the ABA synthesis gene NCED2, SA-related genes (KTI1), and JA-related genes (NATA1, JOX3, and JAO4) [41,42,43,44]. This result indicated that the mutation of KAKU4 significantly affected the expression of senescence- and hormone-related genes. We further performed Gene Ontology (GO) enrichment analysis for differentially expressed genes (DEGs) to infer related biological processes in KAKU4-mediated leaf senescence (Fig. 2B and C). For genes that are upregulated in kaku4 mutant, the enriched GO terms were mainly related to chromatin organization and histone modification, phytohormones (SA, JA, ABA, ethylene, and so forth), programmed cell death, hydrogen peroxide metabolic process, leaf senescence, and so forth (Fig. 2B, Supplementary Table S3). The results of GO enrichment analysis suggested that phytohormone signaling, H2O2-mediated signaling, and leaf senescence were activated in the kaku4 mutant, which was coincident with the results of phenotype analysis between the kaku4 mutant and WT (Fig. 1). Additionally, many other biological processes were also activated in the kaku4 mutant, and the related GO terms include nitrate transport, cellular response to nitrogen starvation, cellular response to phosphate starvation, regulation of cell cycle, and regulation of programmed cell death (Fig. 2B, Supplementary Table S3). Meanwhile, the genes downregulated in the kaku4 mutant were mainly associated with ribosome biogenesis, RNA methylation, “photosynthesis, light reaction”, phospholipid biosynthetic process, and cytokinin-activated signaling pathway (Fig. 2C, Supplementary Table S3). Taken together, genome-wide transcriptome analysis revealed that KAKU4 acts as a regulator for many biological processes including chromatin remodeling, hormone signaling, and leaf senescence.

Fig. 2
figure 2

RNA-seq based transcriptome data analysis of the kaku4 mutant and WT. (A) mRNA-seq analyses of gene expression in the kaku4 mutant using stringent cutoff criteria (|log2(fold change)| ≥ 1 and P-value ≤ 0.05). Dashed lines indicate a log2(fold change) of ± 1. Red dots indicate the 3281 upregulated genes in the kaku4 mutant. The green dots indicate the 2073 downregulated genes in the kaku4 mutant. (B) and (C) GO enrichment analyses for genes that were upregulated (B) and downregulated (C) in the kaku4 mutant by agriGOv2 and REVIGO. The scatter plot shows the cluster representatives in two-dimensional space derived by applying multidimensional scaling to a matrix of the significant GO terms with semantic similarities. The color and size of the bubble indicate the log10FDR (legend in bottom right-hand corner). The colors from red to green represent the significance level of the GO terms from high to low. Fisher’s exact test was conducted, and the P-value was adjusted using the Benjamini-Yekutieli method, FDR ≤ 0.05. (D) Real-time RT-PCR for selected genes among WT, kaku4 mutant, KAKU4-complementation, and KAKU4-overexpression lines; the error bars represent the standard deviations of three replicates. The transcripts are as follows: SAG113/HAI1 - AT5G59220; SAG12 - AT5G45890; NAP - AT1G69490; EIN2 - AT5G03280; SARD1 - AT1G73805; PR1 - AT2G14610; PR2/BGL2 - AT3G57260; ALD1 - AT2G13810; LOX1 - AT1G55020; LOX4 - AT1G72520; BAP2 - AT2G45760; WRKY33 - AT2G38470; REF6/JMJ12 - AT3G48430; CYP94B3 - AT3G48520; NCED2 - AT4G18350; and RD29B - AT5G52300. The primers for each gene are listed in Supplementary Table S4. (E) Comparative analysis of the differential expressed genes (DEGs) of kaku4 mutant and crwn1, crwn4, crwn1crwn4, pnet2abc, gbpl3, and ref6 mutants, and comparative analysis of the upregulated DEGs of kaku4 mutant and the target genes of SARD1. Significance level of the overlap using the custom SEA tool in the plantGSAD database. (F) SEA compare analysis of GESA enrichment analysis results for the upregulated DEGs in kaku4 mutant, the overlap DEGs in kaku4 mutant and crwn1, crwn4, crwn1crwn4, pnet2abc, gbpl3, and ref6 mutants, and overlapping genes between upregulated DEGs in kaku4 mutant and SARD1 target genes

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We further used additional biological replicate samples and carried out qRT-PCR analyses for some selected marker genes (Supplementary Table S4). We added the leaf samples from the mutant complementation and overexpression lines. As shown in Fig. 2D and 16 genes were upregulated in the kaku4 mutant, while the mRNA levels for most of them were rescued nearly to the WT level in the complementation lines, and much lower levels in the overexpression lines. The expression levels of most selected genes validated the RNA-seq results very well. Besides several key senescence marker genes such as SAG113/HAI1 and SAG12, some hormone pathways and cell death related genes were also validated. For example, SARD1, PR1, PR2, and BAP2 were both involved in the SA pathway and in regulating plant immunity [45,46,47]. CYP94B3, LOX1, and LOX4 were involved in JA synthesis, and have been reported to be related to leaf senescence [48,49,50]. In addition, ABA biosynthesis (NCED2) and signal pathway genes (RD29B, SAG113/HAI1) were included, as was the ethylene signal transduction gene (EIN2) [44, 51,52,53].

The results of transcriptome analysis matched our phenotypes well, and the mutation of KAKU4 gene resulted in upregulation of multiple genes, possibly promoting leaf senescence.

Functional crosstalks between KAKU4 and CRWNs/PNET2/GBPL3/REF6/SARD1 through comparing of the transcriptome data

KAKU4 protein interacts with lamin-like proteins CRWNs, PNET2_A/B, and nuclear basket protein GBPL3, and these proteins are required to balance plant growth and stress responses [16, 18, 21]. In order to investigate whether there are some functional crosstalks between KAKU4 and CRWNs, PNET2, GBPL3, we compared the transcriptome data related to kaku4 mutant and crwn1, crwn4, crwn1crwn4, pnet2abc, gbpl3 mutants (Supplementary Table S6). We reanalyzed the transcriptome data of crwn1, crwn4, and crwn1crwn4 mutants [21], and obtained the DEGs of crwn mutants (crwn1, crwn4, crwn1crwn4). The DEGs of the pnet2abc and gbpl3 mutants were obtained from literatures [16, 18]. Between the kaku4 mutant and the mutants of these associated genes, we found that there were significant overlaps of their upregulated DEGs (Fig. 2E).

In the meanwhile, we considered the fact that SARD1 is a key regulator of the expression of SID2 and can promote SA synthesis [54]. We obtained a list of the target genes of SARD1 from literature [55] and found that there existed significant overlap between the upregulated DEGs of kaku4 mutant and the target genes of SARD1 (Fig. 2E). Furthermore, the loss of function of H3K27me3 demethylase REF6 increased H3K27me3 levels at all of the target senescence associated genes (SAGs) [56]. REF6 promotes leaf senescence by directly activating major senescence regulatory and functional genes in Arabidopsis. We carried out real-time qRT-PCR analyses for the JMJ12/REF6 gene, and the result showed that JMJ12/REF6 gene was upregulated in the kaku4 mutant, while in the KAKU4 complementation lines, the mRNA level of the JMJ12/REF6 gene was partially rescued, and the JMJ12/REF6 gene showed a much lower level of mRNA in the KAKU4 overexpression lines (Fig. 2D). We obtained the transcription profiles of the mutant of JMJ12/REF6 from literature [56]. The significant overlap was found between the upregulated DEGs in kaku4 mutant and downregulated DEGs in ref6 mutant (Fig. 2E).

We further applied the SEA compare tool in the PlantGSAD database [57] to study the biological processes of the overlap gene between these genes and upregulated DEGs in kaku4 mutant. We found that these overlapping genes enriched biological process terms such as “defense response”, “immune response”, “cell death” and “regulation of hydrogen peroxide metabolic process”. We also found many biological process terms related to hormones such as “salicylic acid mediated signaling pathway”, “jasmonic acid mediated signaling pathway”, “response to ethylene stimulus”, “response to abscisic acid stimulus”, etc. (Fig. 2F).

Overall, we compared the multiple transcriptome datasets and the results indicate that there were some functional crosstalks between KAKU4 and its associated proteins (CRWN1/4, PNET2, GBPL3, SARD1, REF6), in some important biological processes such as defense response, cell death, and response to SA, JA, ABA, and forth.

Distinct H3K27me3 profiles in the kaku4 mutant and WT plants

KAKU4 can physically interact with CRWN1 and CRWN4 [14], which are in the same complex with a PWWP-containing protein PWO1 [26]. PWO1 interacts with several subunits of PRC2 (i.e., CLF, SWN, and MEA) [27]. We performed immunoblotting with specific antibody to detect trimethylate lysine 27 on histone H3 (H3K27me3) in the leaves of kaku4 mutant and WT. As shown in Supplementary Figure S3, the H3K27me3 level in kaku4 mutant was significantly lower than that in WT. We further performed H3K27me3 ChIP-seq using the sixth-week rosette leaves of the kaku4 mutant and the WT. A total of 3,748 and 4,695 enriched regions of H3K27me3 were identified in the kaku4 mutant and the WT, which were associated with 4,560 and 5,797 genes, respectively (Supplementary Table S7 and S8). More H3K27me3 deposited regions were found in WT than in the mutant. Further, we characterized the H3K27me3 distribution in different functional regions. The Arabidopsis genome was categorized into six genomic subregions: promoter, 5’ untranslated region (5’UTR), 3’UTR, exon, intron, and intergenic region, based on the physical positions of the genes. The distribution of H3K27me3 was similar in the kaku4 mutant and the WT, mainly distributed in the exon region, with the exception of slight differences in the coding exon, intergenic and other regions (Fig. 3A).

Fig. 3
figure 3

ChIP-seq analysis of H3K27me3 in the kaku4 mutant and WT. (A) The distribution of H3K27me3 within different regions (Promoter, 5’UTR, Coding exon, Intron, 3’UTR and Intergenic) of Arabidopsis genome in the kaku4 mutant and WT. (B) Distribution of H3K27me3 among the Arabidopsis genes. A meta-gene profile was generated using the normalized sequencing density of H3K27me3 in the kaku4 mutant and WT. The gene body was converted into a percentage to standardize genes of different lengths. The 1 kb upstream and downstream regions of the gene are included. (C) The heatmaps display H3K27me3 signal around TSSs in the kaku4 mutant and WT for genes upregulated and with decreased H3K27me3 accumulation in the kaku4 mutant. For each gene, the H3K27me3 signals are displayed along − 1 kb to 1 kb regions around the TSSs. (D) The gene expression values in the kaku4 mutant and WT are shown for genes upregulated and with decreased H3K27me3 accumulation in the kaku4 mutant. (E) GO enrichment analyses for genes upregulated and with decreased H3K27me3 accumulation in the kaku4 mutant by agriGO and REVIGO. The scatterplot shows the cluster representatives in a two-dimensional space derived by applying multidimensional scaling to a matrix of significant GO terms with semantic similarities. Bubble color and size indicates the log10(FDR) (legend in bottom right). (F) Genes with decreased H3K27me3 accumulation in the kaku4 mutant are shown in the UCSC genome browser. The locations of ChIP–qPCR primers for H3K27me3 validation are marked in red lines. (G) ChIP–qPCR validation of H3K27me3 deposition for genes with decreased H3K27me3 in kaku4 mutant. Significant difference between the kaku4 mutant and WT were determined according to Student’s t-test. *P-value ≤ 0.05, **P-value ≤ 0.01, ***P-value ≤ 0.001

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We performed metagene analyses to compare the level of normalized H3K27me3 signal along the genetic region. It was found that H3K27me3 reached a higher level in WT than in the kaku4 mutant in the gene body, but the deposition upstream of the TSS was slightly lower than that in the mutant (Fig. 3B). Then, we identified genes with these differential H3K27me3 regions located within 2 kb upstream of TSS and the gene bodies as differential H3K27me3-deposited genes. A total of 820 genes with higher H3K27me3 deposition were identified in the WT and 16 genes in the kaku4 mutant (Supplementary Table S9). In the kaku4 mutant, significantly more genes were associated with decreased H3K27me3 deposition than with increased deposition. The presence of H3K27me3 is usually correlated with gene silencing in animals and plants [58].

We conducted combination analyses of transcriptomic and epigenomic data. We compared H3K27me3-changed genes and differentially expressed genes between the kaku4 mutant and the WT, and identified 104 genes with decreased H3K27me3 deposition (Fig. 3C) and higher expression levels in the mutant (Fig. 3D and Supplementary Table S10). Their upregulated expression might be affected by KAKU4-involved H3K27me3 deposition. GO enrichment showed that GO terms associated with SA response, SA biosynthesis, JA response, defense response, aging, and organ senescence were enriched (Fig. 3E). Some processes closely related to aging, such as H2O2 metabolism and programmed cell death, were also significantly enriched (Fig. 3E). In addition, many genes related to ABA metabolism and signal transduction pathway were identified with lower H3K27me3 deposition and were upregulated in the kaku4 mutant, including the ABA synthesis gene NCED2, the ABA 8’-hydroxylase gene CYP707A2, and ABA signal pathway genes such as SAG113/HAI1, HAI2, and RD29B.

We selected several genes (PR2, SARD1, MC2, SAG113, and PHT3;2) for ChIP-qPCR validation. PR2 is the marker gene activated in response to pathogens. SARD1 is a key regulator of the expression of SID2 and can promote SA synthesis [54]. PHT3;2 encodes a mitochondrial phosphate transporter that is highly expressed in senescent leaves [59]. SAG113/HAI1 functions as a negative regulator of osmotic stress and ABA signaling. The metacaspases MC2 and MC1 antagonistically control programmed cell death in Arabidopsis [60]. The ChIP-qPCR results of the selected genes showed a decrease in H3K27me3 in the kaku4 mutant than in the WT, which confirmed the ChIP-seq results (Fig. 3F and G).

In summary, these results indicated that KAKU4 might regulate SA signaling, JA signaling, ABA signaling, and senescence by affecting H3K27me3 deposition.

Discussion

In this study, we found that the mutation of KAKU4 gene resulted in an accelerated leaf senescence phenotype, with higher levels of H2O2 and some hormone contents. RNA-seq analysis showed that multiple genes were differentially expressed between the kaku4 mutant and the WT plants in 6-week-old rosette leaves. In particular, the upregulated genes in the mutant were significantly enriched in some hormone pathways (SA, JA, ABA, and ethylene), H2O2 metabolism, programmed cell death, leaf senescence, and flowering, among others. In addition, we also concerned that knockdown of KAKU4 may affect the biological processes regulated by other lamin-like proteins such as CRWNs, PNET2, and nuclear basket protein GBPL3, etc. We conducted data-mining analysis and the results showed that there are some functional crosstalks between KAKU4 and its associated proteins (CRWN1/4, PNET2, GBPL3), including defense response, cell death, and response to SA and JA, etc. Further ChIP-seq and ChIP-qPCR analyses showed that KAKU4 was involved in H3K27me3 deposition in a series of genes associated with hormone pathways, H2O2 metabolism, leaf senescence, and so on.

KAKU4 physically interacts with two lamin-like proteins: CRWN1 and CRWN4 [14]. CRWN1 is reported to be involved in SA-mediated plant immune responses [61]. CRWN1 interacts with NTL9 and SNI1, forming a complex to repress the expression of PR1. In addition, it inhibits the function of NPR1, which promotes PR1 expression mediated by TGA1. CRWNs may also participate in the regulation of SA biosynthesis [21]. In Arabidopsis, the double-mutants crwn1crwn3, crwn2crwn3, and crwn2crwn4 exhibit accelerated cell death and increased ROS accumulation [23]. In particular, CRWNs were reported to specifically localize and build a meshwork structure at the nuclear periphery, regulating chromatin distribution and gene expression through fluorescence in situ hybridization and RNA-seq analyses [25]. In addition, CRWNs physically interact with a PWWP domain containing protein PWO1 [26]. Through the mediation of PWO1, CRWN1 and CRWN4 may be associated with PRC2 and H3K27me3 accumulation. The expression of a substantial number of H3K27me3 targets is affected by either loss of PWO1 or CRWN1/CRWN2 [26]. The H3K27me3 accumulation levels near the genes involved in SA biosynthesis are decreased in crwn mutants [29]. Our epigenomic data analysis results presented here showed that knockdown of KAKU4 significantly modulated the H3K27me3 modification in Arabidopsis genome. The combination analyses of epigenomic and transcriptomic data showed that, the genes with higher H3K27me3 deposition in WT and up-regulated in kaku4 mutant, were significantly associated with some hormone pathways (such as SA signaling and biosynthesis pathways), program cell death and leaf senescence, etc. A key SA biosynthesis regulator, SARD1, shows decreased H3K27me3 accumulation in crwn1crwn2 [29], while the expression of SARD1 increases markedly in crwn1crwn2 [21]. Interestingly, we found that SARD1 was upregulated in the kaku4 mutant with lower deposition of H3K27me3, as well as many genes related to defense and cell death. These results indicated that KAKU4 plays a key role in regulating senescence-associated hormone pathways in the leaves with the mediation of H3K27me3 deposition.

Taken together, we proposed a model for the role of KAKU4 in leaf senescence (Fig. 4). KAKU4 interacts with CRWN1 and CRWN4, which physically interact with PWO1, possibly promoting the deposition of H3K27me3 on a series of genes. This in turn inhibits the expression of some key genes (such as SARD1, PR2, LOX4, NCED2, SAG113/HAI1, PHT3;2, and others), leading to the inhibition of some biological processes, such as hormone-signaling pathways, PCD, and leaf senescence. The knockdown of the KAKU4 gene causes a series of phenotypic changes, such as SA, JA, ABA and H2O2 accumulation, increased ion leakage at the membranes, and reduced chlorophyll content, resulting in leaf senescence. Our findings expand the knowledge for the role of KAKU4 in regulating key genes related to hormone pathways, PCD, and leaf senescence.

Fig. 4
figure 4

Model for the role of KAKU4 during leaf senescence. KAKU4, CRWN1, CRWN4, PWO1, and PRC2 might form complexes through protein-protein interaction that promote H3K27me3 deposition on a series of genes, and inhibit the expression of these genes. These genes were involved in the regulation of some biological processes, such as hormone-mediated signaling pathways (SA, JA, ABA, and so forth), PCD, and H2O2 metabolism, which suppress the production of related hormones and H2O2, while maintaining chlorophyll content to ultimately prevent the senescence of plant leaves

Full size image

Materials and methods

Plant materials and growth conditions

Surface-sterilized Arabidopsis thaliana (Col-0, kaku4 mutant lines, KAKU4-complementation lines, and KAKU4-overexpression lines) seeds were placed on half-strength MS (Murashige and Skoog) medium (pH 5.7 to 5.8, 1% [w/v] sucrose, and 0.7% agar). Following a three-day stratification period at 4 °C, the seeds were transferred to a conditioning chamber that had a 16-hour light (22 °C)/8-hour dark (19 °C) cycle. The seedlings were planted in soil after germination for ten days.

Identification of the kaku4 T-DNA insertion mutant

From the Arabidopsis Biological Resource Center (ABRC), the kaku4 (SALK_076754) seeds were acquired. Using two sequential PCR experiments, homozygous T-DNA insertion mutant plants were verified. Two gene-specific primers were used in one assay: RP (SALK_076754-RP) and LP (SALK_076754-LP). One gene-specific primer (SALK076754-RP) and one T-DNA-specific primer (LB) were utilized in the other test. Supplementary Table S4 contains a list of all primers utilized in this investigation.

Construction of transgenic KAKU4-complementation lines and KAKU4-overexpression lines

Amplification of the cDNA region of KAKU4 was achieved by PCR using specific primers (Supplementary Table S4) to produce the genetic complementation and overexpression lines of the protein. For the control of the 35 S promoter, the acquired DNA sequence was ligated into the XbaI and KpnI sites of the super-1300 vector (pCambia1300). After the DNA construct was confirmed through sequencing, it was electroporated into Agrobacterium tumefaciens GV3101, which underwent floral infiltration to produce the KAKU4-complementation lines and KAKU4-overexpression lines [62]. Hygromycin resistance was used to screen the transformed plants, and PCR was used to confirm the results. For further investigation, homozygous T2 seeds of transgenic plants were utilized.

Construction and identification of the kaku4 CRISPR/Cas9 mutant

The coding sequences of KAKU4 were chosen as the target and cloned into the plasmid (pCBSG12B) to generate kaku4 mutant by the clustered regularly interspaced short palindromic repeats (CRISPR)/associated protein9 (Cas9) gene editing approach. The kaku4-03Cas9, kaku4-04Cas9, and kaku4-05Cas9 were generated in Columbia background and confirmed by PCR assay, using the gene-specific primers: ka-ex1_cas_F2 and ka-ex1_cas_R2 (listed in Supplementary Table S4).

Chlorophyll content, ion leakage, H2O2 content measurement

The 6-week-old rosette leaves were homogenized in liquid nitrogen and then incubated in 80% acetone (v/v) for an entire night at 4 °C in order to determine the chlorophyll content. Next, centrifuge at 2700 g for 3 min. Following measurements of absorbance at 646 and 663 nm, the chlorophyll concentration was computed as follows: Chlorophyll a (mg/mL) is equal to 12.21×A663 − 2.81×A646, while Chlorophyll b (mg/mL) is equal to 20.13×A646 − 5.03×A663. Chlorophyll a + Chlorophyll b equals the chlorophyll content (mg/mL).

Electrolytes that had leaked from leaves were measured in order to determine membrane ion leakage. The initial conductivity was measured after the third and fourth rosette leaves from the plants were submerged for three hours at 23 °C in three milliliters of 400 mM mannitol with light shaking. The total conductivity was measured following a 10-minute boil. The percentage of initial conductivity compared to total conductivity was used to calculate conductivity [63].

Using an Amples Red H2O2/peroxidase assay kit (Molecular Probes) and following the manufacturer’s instructions, the H2O2 production was quantified [64].

Plant hormone content measurement

To determine the hormone content, 6-week-old rosette leaves from Arabidopsis plants cultivated in soil were harvested. After homogenizing the rosette leaves in liquid nitrogen, 500 µl of the extract solution and 50 µl of the internal standard working solution were added. The mixture was vortexed and shaken for 30 min at 4 °C. 1 ml of the extract CHCl3 was then added, and the mixture was vortexed and shaken for 30 min at 4 °C again. Gather the bottom layer of liquid after centrifugation, then use helium to dry it at room temperature. Following their dissolution in 0.1 ml of MeOH, the samples were filtered through a 0.1 µM filter.

An UPLC-HRMS system with a heated electrospray ionization (HESI) source (UPLC, Waters ACQUITY UPLC i-Class, Milford, MA, USA; MS, Thermo Fisher Q-Exactive, Bremen, Germany) was used to analyze the samples. Chromatographic separation with a Poroshell 120 EC-C18 column (3.0 × 75 mm, 2.7 μm, Agilent, USA) at a flow rate of 0.4 ml min− 1. For the analysis of SA, ABA, and JA, the mobile phases were 0.05% AA in water (phase A) and 0.05% AA in ACN (phase B). Use 0.1% FA in MeOH (phase B) and 0.1% FA in water (phase A) for ZT and OPDA detection. The gradient program was configured to start at 90% A at 0 min, go from 60% A at 6.25 min, then 10% A at 7.5 min, hold for 3 min, and back to the starting condition. The temperature in the column was 35 °C.

In MS analysis, both positive and negative ion modes were employed. The spray voltage (+) at 3.5 kV, spray voltage (-) at 3 kV, aux gas flow rate at 10 units, sheath gas flow rate at 30 arbitrary units, sweep gas flow rate at 5 units, gas heater temperature at 350 °C, capillary temperature at 320 °C, and S-lens RF level at 55% were the parameters set for the HESI source. For data acquisition, two scans were used: the full MS scan (resolution: 70,000, AGC target: 3E6, maximum IT: 100 ms, scan range: 50–750 m/z) and the targeted MS2 scan (resolution: 17,500, AGC target: 2E5, isolation window: 2.0 m/z).

RNA extraction and RNA-seq analysis

For the purpose of creating independent biological samples, 150 mg of the 6-week-old Arabidopsis plants’ rosette leaves (WT or kaku4 mutant) were collected and frozen in liquid nitrogen. Using the TRIZOL® reagent (Invitrogen, CA, USA) and Qiagen RNeasy columns (Qiagen, Hilden, Germany), total RNA was isolated and purified in accordance with the manufacturer’s instructions.

The Beijing Genomics Institute constructed the sequencing libraries, and 150-bp pair-end reads were sequenced using an IlluminaHiSeq™ 2000. Three biological replicates of the RNA-seq data were produced. TopHat2 v2.0.9 software was used to align the paired-end clean reads of RNA-seq to the reference genome (TAIR10) [65] and Cufflinks were used to calculate FPKM values [66]. TopHat2 and Cufflinks were both run with default parameters. The cutoff: |log2FoldChange| ≥ 1 and P-value ≤ 0.05, were used to identify the differential expressed genes (DEGs) between WT and kaku4 mutant (Supplementary Table S2).

Chromatin immunoprecipitation and ChIP-seq analysis

With a few minor adjustments, a native chromatin immunoprecipitation (ChIP) was carried out essentially as former publications [67]. Approximately 20 g of the rosette leaves from the plants at week six were ground into a fine powder using liquid nitrogen and then resuspended in TBS (10 mM Tris, pH 7.5, 3 mM CaCl2, 2 mM MgCl2, 0.1 mM PMSF, 2/5 tab of complete mini (Roche Applied Science, Indianapolis) with 0.5% Tween 40). Subsequently, the nuclei were purified using a sucrose gradient and digested for five minutes at 37 °C using ten units of micrococcal nuclease (Sigma, St Louis). The nucleosome samples were centrifuged after being incubated for 4 h with 4% protein A Sepharose (GH healthcare Bio-Sciences AB, Uppsala) and pre-immune rabbit serum (1:100 dilution). Anti-trimethyl-histone H3 (Lys 27) antibodies (Millipore, 07-449) were incubated with the supernatant for an overnight period at 4 °C. The control experiments employed an identical volume of pre-immune rabbit serum, which functioned as a nonspecific binding control in every ChIP experiment. Following that, the samples were incubated for four hours at 4 °C with 25% protein A Sepharose. Using an elution buffer (20 mM Tris-HCl at pH 7.5, 5 mM EDTA, 50 mM NaCl, 1% SDS) the immune complexes were extracted from the washed beads following centrifugation of the pellet (bound) fractions. Following phenol/chloroform extraction, ethanol precipitation was used to extract immunoprecipitated DNA. In 100 µl of TE buffer (pH 8.0), the ChIPed DNA was once again suspended, and used for library construction by the Beijing Genomics Institute, then sequenced using the Illumina system Novaseq 6000 with a 150-bp read length.

Using BOWTIE2 software [68] with default parameters, all clean ChIP-seq reads were mapped to the Arabidopsis genome TAIR10. To identify peaks, the reads were organized using the MACS program (bandwidth, 300 bp; model fold, 10, 30; P = 1.00e-5) [69]. The UCSC genome browser was used to visualize the ChIP-seq data [70]. Using CEAS software, the distribution of peaks found in the ChIP-seq along the Arabidopsis genome were characterized [71]. Genes that overlapped the peaks, including the 2-kb upstream and gene body regions, were thought to carry the epigenetic marks. Supplementary Table S7 displayed the related peak numbers and gene numbers. Supplementary Table S9 included a list of all differential H3K27me3-related genes, which were utilized for further analysis.

Gene ontology analysis

Using agriGOv2 [72] and REVIGO [73], GO enrichment analysis of RNA-seq and ChIP-seq data was carried out. The custom analysis in PlantGSEA platform [74]was used to perform the gene set enrichment analysis of KEGG, Caf, transcript factor target, and MapMan. P-values of less than 0.05 as the cutoff indicated that a term was significantly enriched.

Quantitative real-time PCR

Utilizing the Moloney Murine Leukaemia Virus (M-MLV; Invitrogen), reverse transcription was carried out. After being heated to 70 °C for two minutes, 10 µl samples containing 2 µg of total RNA and 20 pmol of random hexamers (Invitrogen) were cooled on ice for an additional two minutes. Next, incorporate the reaction buffer and M-MLV into a 20 µl total volume that includes 20 pmol random hexamers, 500 µM dNTPs, 200 units of M-MLV, 50 mM Tris-HCl (pH 8.3), 75 mM KCl, 3 mM MgCl2 and 5 mM dithiothreitol. After that, the samples were incubated for 1.5 h at 37 °C [75]. The cDNA samples were diluted to 8 ng/µL for real-time RT-PCR analysis.

Using gene-specific primers (Supplementary Table S4) and an ECO Real-Time PCR system (Illumina) in accordance with the manufacturer’s instructions, real-time PCR experiments were carried out. SYBR Green was used to perform three biological repeats with 8 ng of cDNA. To standardize all of the data for the real-time RT-PCR experiments, each sample’s internal control was Arabidopsis 18 S rRNA (Supplementary Table S4). The quantitative variation between replicates was assessed using the relative quantitation method (ΔΔCT) to evaluate the gene-expression levels in wild-type, kaku4 mutant, KAKU4-complementation and KAKU4-overexpression lines.

ChIP-qPCR

The prepared DNA in ChIP was subjected to quantitative PCR analysis using an ECO Real-Time PCR system (Illumina). The ChIP-qRCR gene-specific primers were displayed in Supplementary Table S4. Three independent repetitions of the experiments were conducted. 25 S was utilized as a negative control to calculate the relative fold enrichment (RFE) of modified histone-associated sequences in the bound fractions. 2−ΔΔCT± standard deviation (SD) was used to compute RFE, where ΔΔCT is equal to ΔCT (positive control) - ΔCT (negative control).

Immunoblots

After being ground in liquid nitrogen, harvested leaves from both the kaku4 mutant and WT were extracted using 2×SDS-PAGE loading buffer (P1040; Solarbio) at 100 °C for 10 min. The mixture was centrifuged at 12,000 rpm for 10 min. Proteins that were extracted underwent separation on 10% SDS-PAGE gels before being transferred to PVDF membranes (Millipore, 0.22 μm). At room temperature (24 °C), membranes were blocked in blocking buffer (5% milk dissolved in 1×TBST (Tris Buffered Saline with Tween 20) for one hour. Then the membranes were incubated in blocking buffer with antibodies against H3 (BE3015; EASYBIO) and H3K27me3 (07-449; Millipore) for 1.5 h at room temperature. Membranes were incubated for one hour at room temperature with TBST after being washed five times for three minutes each. Membranes were incubated for 1 h at room temperature with diluted 1/2,000 Goat Anti-Mouse IgG, HRP Conjugated (CW0102S; CWBIO) and Anti-Rabbit VHH HRP (KTSM1322; AlpalifeBio) following five rounds of washing in TBST for three minutes each. Membranes were incubated in electrochemiluminescence (ECL) buffer (BE6706; EASYBIO) for one minute after being rinsed five times in TBST.

Data availability

The RNA-seq and ChIP-seq raw data were deposited in the NCBI Gene Expression Omnibus with the accession number GSE250299.

References

  1. van Steensel B, Belmont AS. Lamina-Associated domains: links with chromosome Architecture, Heterochromatin, and Gene Repression. Cell. 2017;169(5):780–91.

    Article  PubMed  PubMed Central  Google Scholar 

  2. Bi X, Cheng YJ, Hu B, Ma X, Wu R, Wang JW, Liu C. Nonrandom domain organization of the Arabidopsis genome at the nuclear periphery. Genome Res. 2017;27(7):1162–73.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Zheng X, Hu J, Yue S, Kristiani L, Kim M, Sauria M, Taylor J, Kim Y, Zheng Y. Lamins organize the Global Three-Dimensional Genome from the Nuclear periphery. Mol Cell. 2018;71(5):802–815e807.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Karoutas A, Akhtar A. Functional mechanisms and abnormalities of the nuclear lamina. Nat Cell Biol. 2021;23(2):116–26.

    Article  CAS  PubMed  Google Scholar 

  5. Shevelyov YY, Ulianov SV. The Nuclear Lamina as an organizer of chromosome Architecture. Cells-Basel 2019, 8(2).

  6. Gonzalo S, Kreienkamp R, Askjaer P. Hutchinson-Gilford Progeria Syndrome: a premature aging disease caused by LMNA gene mutations. Ageing Res Rev. 2017;33:18–29.

    Article  CAS  PubMed  Google Scholar 

  7. Scaffidi P, Misteli T. Lamin A-dependent nuclear defects in human aging. Science. 2006;312(5776):1059–63.

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  8. Tran JR, Chen H, Zheng X, Zheng Y. Lamin in inflammation and aging. Curr Opin Cell Biol. 2016;40:124–30.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Ao Y, Zhang J, Liu ZJ, Qian MX, Li Y, Wu ZP, Sun PF, Wu J, Bei WX, Wen JQ et al. Lamin a buffers CK2 kinase activity to modulate aging in a progeria mouse model. Sci Adv 2019, 5(3).

  10. bin Imtiaz MK, Jaeger BN, Bottes S, Machado RAC, Vidmar M, Moore DL, et al. Declining lamin B1 expression mediates age-dependent decreases of hippocampal stem cell activity. Cell Stem Cell. 2021;28(5):967–77.

    Article  Google Scholar 

  11. Masuda K, Takahashi S, Nomura K, Arimoto M, Inoue M. Residual structure and constituent proteins of the peripheral framework of the cell nucleus in somatic embryos from Daucus carota L. Planta. 1993;191(4):532–40.

    Article  CAS  Google Scholar 

  12. Sakamoto Y, Takagi S. LITTLE NUCLEI 1 and 4 regulate nuclear morphology in Arabidopsis thaliana. Plant Cell Physiol. 2013;54(4):622–33.

    Article  CAS  PubMed  Google Scholar 

  13. Dittmer TA, Stacey NJ, Sugimoto-Shirasu K, Richards EJ. LITTLE NUCLEI genes affecting nuclear morphology in Arabidopsis thaliana. Plant Cell. 2007;19(9):2793–803.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Goto C, Tamura K, Fukao Y, Shimada T, Hara-Nishimura I. The Novel Nuclear envelope protein KAKU4 modulates nuclear morphology in Arabidopsis. Plant Cell. 2014;26(5):2143–55.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Pawar V, Poulet A, Détourné G, Tatout C, Vanrobays E, Evans DE, Graumann K. A novel family of plant nuclear envelope-associated proteins. J Exp Bot. 2016;67(19):5699–710.

    Article  CAS  PubMed  Google Scholar 

  16. Tang Y, Dong QL, Wang TY, Gong L, Gu YN. PNET2 is a component of the plant nuclear lamina and is required for proper genome organization and activity. Dev Cell. 2022;57(1):19–31.

    Article  CAS  PubMed  Google Scholar 

  17. Huang AB, Tang Y, Shi XT, Jia M, Zhu JH, Yan XH, Chen HQ, Gu YN. Proximity labeling proteomics reveals critical regulators for inner nuclear membrane protein degradation in plants. Nat Commun 2020, 11(1).

  18. Tang Y, Ho MI, Kang BH, Gu YN. GBPL3 localizes to the nuclear pore complex and functionally connects the nuclear basket with the nucleoskeleton in plants. Plos Biol 2022, 20(10).

  19. Tang Y, Huang AB, Gu YN. Global profiling of plant nuclear membrane proteome in Arabidopsis. Nat Plants. 2020;6(7):838–47.

    Article  CAS  PubMed  Google Scholar 

  20. Dittmer TA, Misteli T. The lamin protein family. Genome Biol. 2011;12(5):222.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Choi J, Strickler SR, Richards EJ. Loss of CRWN Nuclear proteins induces cell death and salicylic acid Defense Signaling. Plant Physiol. 2019;179(4):1315–29.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Wang Q, Liu S, Lu C, La Y, Dai J, Ma H, Zhou S, Tan F, Wang X, Wu Y, et al. Roles of CRWN-family proteins in protecting genomic DNA against oxidative damage. J Plant Physiol. 2019;233:20–30.

    Article  CAS  PubMed  Google Scholar 

  23. Hu B, Wang N, Bi X, Karaaslan ES, Weber AL, Zhu W, Berendzen KW, Liu C. Plant lamin-like proteins mediate chromatin tethering at the nuclear periphery. Genome Biol. 2019;20(1):87.

    Article  PubMed  PubMed Central  Google Scholar 

  24. Sequeira-Mendes J, Araguez I, Peiro R, Mendez-Giraldez R, Zhang X, Jacobsen SE, Bastolla U, Gutierrez C. The functional topography of the Arabidopsis Genome is Organized in a reduced number of Linear motifs of Chromatin States. Plant Cell. 2014;26(6):2351–66.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Sakamoto Y, Sato M, Sato Y, Harada A, Suzuki T, Goto C, Tamura K, Toyooka K, Kimura H, Ohkawa Y et al. Subnuclear gene positioning through lamina association affects copper tolerance. Nat Commun 2020, 11(1).

  26. Mikulski P, Hohenstatt ML, Farrona S, Smaczniak C, Stahl Y, Kalyanikrishna, Kaufmann K, Angenent G, Schubert D. The chromatin-Associated protein PWO1 interacts with Plant Nuclear Lamin-Like Components to Regulate Nuclear size. Plant Cell. 2019;31(5):1141–54.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Hohenstatt ML, Mikulski P, Komarynets O, Klose C, Kycia I, Jeltsch A, Farrona S, Schubert D. PWWP-DOMAIN INTERACTOR OF POLYCOMBS1 interacts with polycomb-group proteins and histones and regulates Arabidopsis Flowering and Development. Plant Cell. 2018;30(1):117–33.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Pu L, Sung ZR. PcG and trxG in plants - friends or foes. Trends Genet. 2015;31(5):252–62.

    Article  CAS  PubMed  Google Scholar 

  29. Choi J, Richards EJ. The role of CRWN nuclear proteins in chromatin-based regulation of stress response genes. Plant Signal Behav. 2020;15(1):1694224.

    Article  PubMed  Google Scholar 

  30. Reimann TM, Müdsam C, Schachtler C, Ince S, Sticht H, Herrmann C, et al. The large GTPase AtGBPL3 links nuclear envelope formation and morphogenesis to transcriptional repression. Nat Plants. 2023;9(5):766–84.

    Article  CAS  PubMed  Google Scholar 

  31. Goto C, Tamura K, Nishimaki S, Maruyama D, Hara-Nishimura I. The nuclear envelope protein KAKU4 determines the migration order of the vegetative nucleus and sperm cells in pollen tubes. J Exp Bot. 2020;71(20):6273–81.

    Article  CAS  PubMed  Google Scholar 

  32. Jajic I, Sarna T, Strzalka K. Senescence, stress, and reactive oxygen species. Plants. 2015;4(3):393–411.

    Article  PubMed  PubMed Central  Google Scholar 

  33. Guo P, Li Z, Huang P, Li B, Fang S, Chu J, Guo H. A tripartite amplification Loop Involving the transcription factor WRKY75, salicylic acid, and reactive oxygen species accelerates Leaf Senescence. Plant Cell. 2017;29(11):2854–70.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Wu A, Allu AD, Garapati P, Siddiqui H, Dortay H, Zanor MI, Asensi-Fabado MA, Munne-Bosch S, Antonio C, Tohge T, et al. JUNGBRUNNEN1, a reactive oxygen species-responsive NAC transcription factor, regulates longevity in Arabidopsis. Plant Cell. 2012;24(2):482–506.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. He Y, Fukushige H, Hildebrand DF, Gan S. Evidence supporting a role of jasmonic acid in Arabidopsis leaf senescence. Plant Physiol. 2002;128(3):876–84.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Asad MAU, Zakari SA, Zhao Q, Zhou L, Ye Y, Cheng F. Abiotic stresses intervene with ABA signaling to induce destructive metabolic pathways leading to death: premature Leaf Senescence in plants. Int J Mol Sci 2019, 20(2).

  37. Love MI, Huber W, Anders S. Moderated estimation of Fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 2014;15(12):550.

    Article  PubMed  PubMed Central  Google Scholar 

  38. Wang HY, Klatte M, Jakoby M, Baumlein H, Weisshaar B, Bauer P. Iron deficiency-mediated stress regulation of four subgroup ib BHLH genes in Arabidopsis thaliana. Planta. 2007;226(4):897–908.

    Article  CAS  PubMed  Google Scholar 

  39. Callard D, Axelos M, Mazzolini L. Novel molecular markers for late phases of the growth cycle of Arabidopsis thaliana cell-suspension cultures are expressed during organ senescence. Plant Physiol. 1996;112(2):705–15.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Buchanan-Wollaston V, Page T, Harrison E, Breeze E, Lim PO, Nam HG, Lin JF, Wu SH, Swidzinski J, Ishizaki K, et al. Comparative transcriptome analysis reveals significant differences in gene expression and signalling pathways between developmental and dark/starvation-induced senescence in Arabidopsis. Plant J. 2005;42(4):567–85.

    Article  CAS  PubMed  Google Scholar 

  41. Gepstein S, Sabehi G, Carp MJ, Hajouj T, Nesher MFO, Yariv I, Dor C, Bassani M. Large-scale identification of leaf senescence-associated genes. Plant J. 2003;36(5):629–42.

    Article  CAS  PubMed  Google Scholar 

  42. Smirnova E, Marquis V, Poirier L, Aubert Y, Zumsteg J, Menard R, Miesch L, Heitz T. Jasmonic Acid Oxidase 2 Hydroxylates Jasmonic Acid and represses basal defense and resistance responses against Botrytis cinerea infection. Mol Plant. 2017;10(9):1159–73.

    Article  CAS  PubMed  Google Scholar 

  43. Lou YR, Bor M, Yan J, Preuss AS, Jander G. Arabidopsis NATA1 Acetylates Putrescine and decreases Defense-Related Hydrogen Peroxide Accumulation. Plant Physiol. 2016;171(2):1443–55.

    CAS  PubMed  PubMed Central  Google Scholar 

  44. Qin XQ, Zeevaart JAD. The 9-cis-epoxycarotenoid cleavage reaction is the key regulatory step of abscisic acid biosynthesis in water-stressed bean. P Natl Acad Sci USA. 1999;96(26):15354–61.

    Article  ADS  CAS  Google Scholar 

  45. Sun TJ, Zhang YX, Li Y, Zhang Q, Ding YL, Zhang YL. ChIP-seq reveals broad roles of SARD1 and CBP60g in regulating plant immunity. Nat Commun 2015, 6.

  46. Betsuyaku S, Katou S, Takebayashi Y, Sakakibara H, Nomura N, Fukuda H. Salicylic acid and Jasmonic Acid pathways are activated in spatially different domains around the infection site during effector-triggered immunity in Arabidopsis thaliana. Plant Cell Physiol. 2018;59(1):8–16.

    Article  CAS  PubMed  Google Scholar 

  47. Yang HJ, Yang SH, Li YQ, Hua J. The Arabidopsis BAP1 and BAP2 genes are general inhibitors of programmed cell death. Plant Physiol. 2007;145(1):135–46.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Kim J, Park SJ, Lee IH, Chu H, Penfold CA, Kim JH, Buchanan-Wollaston V, Nam HG, Woo HR, Lim PO. Comparative transcriptome analysis in Arabidopsis ein2/ore3 and ahk3/ore12 mutants during dark-induced leaf senescence. J Exp Bot. 2018;69(12):3023–36.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Lopez MA, Vicente J, Kulasekaran S, Vellosillo T, Martinez M, Irigoyen ML, Cascon T, Bannenberg G, Hamberg M, Castresana C. Antagonistic role of 9-lipoxygenase-derived oxylipins and ethylene in the control of oxidative stress, lipid peroxidation and plant defence. Plant J. 2011;67(3):447–58.

    Article  CAS  PubMed  Google Scholar 

  50. Kitaoka N, Matsubara T, Sato M, Takahashi K, Wakuta S, Kawaide H, Matsui H, Nabeta K, Matsuura H. Arabidopsis CYP94B3 encodes Jasmonyl-l-Isoleucine 12-Hydroxylase, a key enzyme in the oxidative catabolism of Jasmonate. Plant Cell Physiol. 2011;52(10):1757–65.

    Article  CAS  PubMed  Google Scholar 

  51. Yamaguchi-Shinozaki K, Shinozaki K. Arabidopsis DNA encoding two desiccation-responsive rd29 genes. Plant Physiol. 1993;101(3):1119–20.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Bhaskara GB, Nguyen TT, Verslues PE. Unique Drought Resistance functions of the highly ABA-Induced Clade A protein phosphatase 2Cs. Plant Physiol. 2012;160(1):379–95.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Yoshida T, Nishimura N, Kitahata N, Kuromori T, Ito T, Asami T, Shinozaki K, Hirayama T. ABA-Hypersensitive germination3 encodes a protein phosphatase 2 C (AtPP2CA) that strongly regulates abscisic acid signaling during germination among Arabidopsis protein phosphatase 2Cs. Plant Physiol. 2006;140(1):115–26.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Wang L, Tsuda K, Truman W, Sato M, Nguyen le V, Katagiri F, Glazebrook J. CBP60g and SARD1 play partially redundant critical roles in salicylic acid signaling. Plant J. 2011;67(6):1029–41.

    Article  CAS  PubMed  Google Scholar 

  55. Sun T, Zhang Y, Li Y, Zhang Q, Ding Y, Zhang Y. ChIP-seq reveals broad roles of SARD1 and CBP60g in regulating plant immunity. Nat Commun. 2015;6:10159.

    Article  ADS  CAS  PubMed  Google Scholar 

  56. Wang X, Gao J, Gao S, Song Y, Yang Z, Kuai B. The H3K27me3 demethylase REF6 promotes leaf senescence through directly activating major senescence regulatory and functional genes in Arabidopsis. PLoS Genet. 2019;15(4):e1008068.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  57. Ma X, Yan H, Yang J, Liu Y, Li Z, Sheng M, Cao Y, Yu X, Yi X, Xu W, et al. PlantGSAD: a comprehensive gene set annotation database for plant species. Nucleic Acids Res. 2022;50(D1):D1456–67.

    Article  CAS  PubMed  Google Scholar 

  58. Lafos M, Kroll P, Hohenstatt ML, Thorpe FL, Clarenz O, Schubert D. Dynamic regulation of H3K27 trimethylation during Arabidopsis differentiation. PLoS Genet. 2011;7(4):e1002040.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  59. Waese J, Fan J, Pasha A, Yu H, Fucile G, Shi R, Cumming M, Kelley LA, Sternberg MJ, Krishnakumar V, et al. ePlant: visualizing and exploring multiple levels of data for Hypothesis Generation in Plant Biology. Plant Cell. 2017;29(8):1806–21.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  60. Coll NS, Vercammen D, Smidler A, Clover C, Van Breusegem F, Dangl JL, Epple P. Arabidopsis type I metacaspases control cell death. Science. 2010;330(6009):1393–7.

    Article  ADS  CAS  PubMed  Google Scholar 

  61. Guo T, Mao X, Zhang H, Zhang Y, Fu M, Sun Z, Kuai P, Lou Y, Fang Y. Lamin-like proteins negatively regulate Plant Immunity through NAC WITH TRANSMEMBRANE MOTIF1-LIKE9 and NONEXPRESSOR OF PR GENES1 in Arabidopsis thaliana. Mol Plant. 2017;10(10):1334–48.

    Article  CAS  PubMed  Google Scholar 

  62. Clough SJ, Bent AF. Floral dip: a simplified method for Agrobacterium-mediated transformation of Arabidopsis thaliana. Plant J. 1998;16(6):735–43.

    Article  CAS  PubMed  Google Scholar 

  63. Woo HR, Chung KM, Park JH, Oh SA, Ahn T, Hong SH, Jang SK, Nam HG. ORE9, an F-box protein that regulates leaf senescence in Arabidopsis. Plant Cell. 2001;13(8):1779–90.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  64. Yu J, Zhang YX, Di C, Zhang QL, Zhang K, Wang CC, You Q, Yan H, Dai SY, Yuan JS, et al. JAZ7 negatively regulates dark-induced leaf senescence in Arabidopsis. J Exp Bot. 2016;67(3):751–62.

    Article  CAS  PubMed  Google Scholar 

  65. Kim D, Pertea G, Trapnell C, Pimentel H, Kelley R, Salzberg SL. TopHat2: accurate alignment of transcriptomes in the presence of insertions, deletions and gene fusions. Genome Biol. 2013;14(4):R36.

    Article  PubMed  PubMed Central  Google Scholar 

  66. Trapnell C, Roberts A, Goff L, Pertea G, Kim D, Kelley DR, Pimentel H, Salzberg SL, Rinn JL, Pachter L. Differential gene and transcript expression analysis of RNA-seq experiments with TopHat and Cufflinks. Nat Protoc. 2012;7(3):562–78.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  67. Nagaki K, Talbert PB, Zhong CX, Dawe RK, Henikoff S, Jiang J. Chromatin immunoprecipitation reveals that the 180-bp satellite repeat is the key functional DNA element of Arabidopsis thaliana centromeres. Genetics. 2003;163(3):1221–5.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  68. Langmead B, Salzberg SL. Fast gapped-read alignment with Bowtie 2. Nat Methods. 2012;9(4):357–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  69. Zhang Y, Liu T, Meyer CA, Eeckhoute J, Johnson DS, Bernstein BE, Nusbaum C, Myers RM, Brown M, Li W, et al. Model-based analysis of ChIP-Seq (MACS). Genome Biol. 2008;9(9):R137.

    Article  PubMed  PubMed Central  Google Scholar 

  70. Kent WJ, Sugnet CW, Furey TS, Roskin KM, Pringle TH, Zahler AM, Haussler D. The human genome browser at UCSC. Genome Res. 2002;12(6):996–1006.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  71. Shin H, Liu T, Manrai AK, Liu XS. CEAS: cis-regulatory element annotation system. Bioinformatics. 2009;25(19):2605–6.

    Article  CAS  PubMed  Google Scholar 

  72. Tian T, Liu Y, Yan H, You Q, Yi X, Du Z, Xu W, Su Z. agriGO v2.0: a GO analysis toolkit for the agricultural community, 2017 update. Nucleic Acids Res. 2017;45(W1):W122–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  73. Supek F, Bosnjak M, Skunca N, Smuc T. REVIGO summarizes and visualizes long lists of gene ontology terms. PLoS ONE. 2011;6(7):e21800.

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  74. Yi X, Du Z, Su Z. PlantGSEA: a gene set enrichment analysis toolkit for plant community. Nucleic Acids Res. 2013;41(Web Server issue):W98–103.

    Article  PubMed  PubMed Central  Google Scholar 

  75. Wang C, Wei Q, Zhang K, Wang L, Liu F, Zhao L, Tan Y, Di C, Yan H, Yu J, et al. Down-regulation of OsSPX1 causes high sensitivity to cold and oxidative stresses in rice seedlings. PLoS ONE. 2013;8(12):e81849.

    Article  ADS  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

We thank Ms. Qunlian Zhang for technical support. We also thank Xinxin Yang and Lifan Zhou in Yongliang Zhang’s lab for helping Western blot experiment.

Funding

This work was supported by grants from the National Natural Science Foundation of China (31970629 and 32170673).

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Author notes

  1. Yaxin Cao, Hengyu Yan, and Minghao Sheng these authors contributed equally to this work.

Authors and Affiliations

  1. State Key Laboratory of Plant Environmental Resilience, College of Biological Sciences, China Agricultural University, Beijing, 100193, China

    Yaxin Cao, Hengyu Yan, Minghao Sheng, Yue Liu, Xinyue Yu, Zhongqiu Li, Wenying Xu & Zhen Su

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  1. Yaxin Cao
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  2. Hengyu Yan
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  3. Minghao Sheng
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  8. Zhen Su
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Contributions

W.X. and S.Z. conceived and designed the research. Y.C., H.Y., and M.S. performed most of the experiments. Y.C. and M.S. generated the mutants and overexpression lines. Y.C., H.Y., Y.L., X.Y., Z.L.,W.X., and S.Z. were involved in data analysis. Y.C., H.Y., M.S., W.X. and S.Z. wrote the manuscript. All authors reviewed the manuscript.

Corresponding author

Correspondence to Zhen Su.

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The seeds of Arabidopsis thaliana (Col-0 and kaku4 mutant) were obtained from the Arabidopsis Biological Resource Center (ABRC), eliminating the need for field permissions to collect samples.

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The authors declare no competing interests.

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Cao, Y., Yan, H., Sheng, M. et al. KAKU4 regulates leaf senescence through modulation of H3K27me3 deposition in the Arabidopsis genome. BMC Plant Biol 24, 177 (2024). https://doi.org/10.1186/s12870-024-04860-9

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Keywords

BMC Plant Biology

ISSN: 1471-2229

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