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H3K36 methyltransferase GhKMT3;1a and GhKMT3;2a promote flowering in upland cotton

BMC Plant Biology volume 24, Article number: 739 (2024) Cite this article

Abstract

Background

The SET domain group (SDG) genes encode histone lysine methyltransferases, which regulate gene transcription by altering chromatin structure and play pivotal roles in plant flowering determination. However, few studies have investigated their role in the regulation of flowering in upland cotton.

Results

A total of 86 SDG genes were identified through genome-wide analysis in upland cotton (Gossypium hirsutum). These genes were unevenly distributed across 25 chromosomes. Cluster analysis revealed that the 86 GhSDGs were divided into seven main branches. RNA-seq data and qRT‒PCR analysis revealed that lysine methyltransferase 3 (KMT3) genes were expressed at high levels in stamens, pistils and other floral organs. Using virus-induced gene silencing (VIGS), functional characterization of GhKMT3;1a and GhKMT3;2a revealed that, compared with those of the controls, the GhKMT3;1a- and GhKMT3;2a-silenced plants exhibited later budding and flowering and lower plant heightwere shorter. In addition, the expression of flowering-related genes (GhAP1, GhSOC1 and GhFT) significantly decreased and the expression level of GhSVP significantly increased in the GhKMT3;1a- and GhKMT3;2a-silenced plants compared with the control plants.

Conclusion

A total of 86 SDG genes were identified in upland cotton, among which GhKMT3;1a and GhKMT3;2a might regulate flowering by affecting the expression of GhAP1, GhSOC1, GhFT and GhSVP. These findings will provide genetic resources for advanced molecular breeding in the future.

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Introduction

Histone lysine methylation is one of the most important epigenetic modifications in plants, where it regulates eukaryotic gene transcription by modifying the chromatin structure [1]. In plants, histone methylation plays a key role in processes such as growth and development and in the response to environmental factors [2, 3]. The methylation of histones by lysine methyltransferases (KMTases) plays a crucial role in regulating chromatin function. Most known histone lysine methyltransferases can be categorized into two group: SDG proteins with conserved SET domains and a partial SET domain-free DOT1p and DOT1L proteins, whereas only the SDG proteins have histone methyltransferase activity in plants [4, 5]. SDG proteins transfer methyl groups from cofactors to specific histone 3 (H3) residues and histone 4 (H4) residues with the help of the SET domain [6]. On the basis of sequence homology, SDG proteins are classified into seven groups (KMT1, KMT2, KMT3, KMT6, KMT7, S-ET, and RBCMT), and different subfamilies have histone methyltransferase activities with different substrate specificities. For example, KMT1 is specific for H3K9; KMT2 and KMT7 are specific for H3K4; and KMT3 and KMT6 are specific for H3K36 and H3K27 [7]. The S-ET proteins have an interrupted SET domain and may be involved in the methylation of nonhistone proteins. RBCMT possesses H3K4 and H3K36 methyltransferase activity in animals [8]. Among the substrate specificities, di-/trimethylation of H3K4 and H3K36 are strongly correlated with active gene transcription, whereas dimethylation of H3K9 and trimethylation of H3K27 are associated with gene repression [9].

SDGs play a key role in the response to biotic and abiotic stresses [10, 11]. In Arabidopsis, the expression of cold-responsive genes is activated by a decrease in H3K27me3 methylation at low temperatures to help the plants cope with cold stress [12]. The SDG8/KMT3;1 gene plays a key role in drought stress in Arabidopsis, and plants with this gene mutated exhibit reduced drought tolerance [13, 14]. SDG721 enhances saline‒alkali stress tolerance in rice through H3K4me3 deposition in OsHKT1:5 [15]. Furthermore, SDG33 and SDG44 appear to regulate (JA) signaling pathway-related gene expression in response to pathogen infection and drought in tomato [16]. SDGs also play significant roles in the control of plant morphogenesis and development, such as floral organ development [17,18,19], leaf morphology [20], lateral root formation [21, 22], and seed germination [23, 24]. In addition to the abovementioned activities, SDGs affect flowering time by fine-tuning multiple genetic pathways, including those associated with endogenous and environmental signals. SDG1/CLF (CURLY LEAF) is the first identified plant SDG protein that controls flower morphology and flowering time by mediating trimethylation at H3K27 sites [17, 25]. SUVH5, a member of the KMT1 subfamily, promotes the flowering process by inhibiting heterochromatin formation at the FLC (FLOWERING LOCUS C) locus H3K9 methylation [26, 27]. AtATX1/SDG27 and AtATXR3/SDG2 control flowering time by depositing H3K4me3 marks at the FLC locus [28,29,30]. H3K36 methylation is predominantly conducted by KMT3 subfamily members, particularly SDG8/ASHH2/KMT3;1a, the representative gene responsible for modulating the flowering process. In Arabidopsis, Brassica napus and other cruciferous plants, KMT3;1 represses flowering by promoting FLC expression and downregulating the expression of FT (FLOWERING LOCUS T) and SOC1 (SUPPRESSOR OF OVEREXPRESSION OF CONSTANS 1) [31,32,33]. However, in rice, KMT3;1 promotes brassinolactin-related gene expression by modifying the chromatin region of genes via H3K36me2/me3 and accelerating flowering [34, 35]. Another KMT3 subfamily member, SDG26/ASHH1/KMT3;2a, also exhibits H3K36 methyltransferase activity. However, kmt3;2a loss-of-function mutants exhibit late flowering [31]. Other KMT3 genes are also involved in the regulation of flowering, SDG7/KMT3;4b is a negative regulator of vernalization [36], SDG4/ASHR3/KMT3;3 regulate anther and stamen development, and overexpression of ASHR3 causes growth arrest and anther deformities [37]. SDGs in the KMT3 subfamily affect flowering by altering the histone methylation pattern of flowering-related genes.

Upland cotton (Gossypium hirsutum L.) is a widely farmed type of cotton and the world’s primary source of natural fiber [38]. Early maturity, which is a crucial trait of cotton, helps plants effectively avoid the effects of low temperature, expands suitable planting areas, and facilitates mechanized harvesting in northwestern inland cotton-producing areas in China [39]. Flowering time is one of the most crucial elements of the early maturity trait in cotton [40] and is directly affected by histone methylation [32]. Several previous studies have analyzed the functions of SDG family members in Gossypium raimondii, focusing primarily on their roles in the response to high temperature. Additionally, research has revealed that H3K4me3 and H3K27me3 methyltransferase genes are involved in anther development under high temperatures in G. hirsutum. Recently, it was reported that GhSDG51 in upland cotton plays a role in regulating salt stress [41,42,43]. However, the GhSDGs related to growth and development in cotton remain unknown. Previous studies have shown that histone methylation regulates FLC, which is involved in flowering. Since cotton lacks an FLC homolog, our investigation focused on the significance of H3K36 methylation in regulating flowering time in upland cotton plants. A detailed examination of the SDGs of the three cotton species was performed, and the evolutionary relationships among the species were investigated. The expression patterns of GhKMT3s in different tissues were evaluated via qRT‒PCR, and the functions of GhKMT3;1a and GhKMT3;2a in controlling flowering time were investigated via VIGS technology. These findings showed that silencing these two genes reduced plant height and delayed the time of budding and flowering in upland cotton.

Methods

Identification and sequence analysis of SDG genes in two Gossypium species

The sequences of the Arabidopsis SET domain-containing proteins were retrieved from TAIR. Whole-genome data for G. hirsutum and G. arboreum were downloaded from CottonFGD (http://www.cottonfgd.org/). Pfam was used to construct a hidden Markov model profile of the SET domain (PF00856) [44], and protein databases were scanned using HMMER v3.0 (http://hmmer.org/) and an E value < e−5. The SMART database model (http://smart.embl-heidelberg.de/) was used to verify each SDG protein, and duplicate sequences were manually deleted [45]. The identified SDG genes were named according to their homology with Arabidopsis genes.

Analysis of gene phylogenetic relationships, structure and domain architecture

The ClustalW tool was used with the default settings to perform multiple sequence alignment of SDG proteins from four plant species, namely, G. raimondii, G. arboreum, G. hirsutum and A. thaliana [46]. An evolutionary tree was constructed with default parameters on the basis of the results from the comparison. The tree was visualized via iTOL (https://itol.embl.de/) [47]. Gene structures were drawn with GSDS 2.0 (http://gsds.cbi.pku.edu.cn/) on the basis of the CDS and genome data. The batch smart plugin of TBtools was used to analyze the SET domain of the SDG proteins.

Chromosome location, synteny analysis and the Ka/Ks ratio

According to the genomic annotation files in the CottonFGD, TBtools was used to obtain information on SDG chromosome positions [48]. The homology and the nonsynonymous substitution rates (Ka) and synonymous substitution rates (Ks) of the homologous SDG genes of upland cotton and other species were determined using TBtools software.

Expression pattern, interaction network, cis‑regulatory element (CRE) and Gene Ontology (GO) analyses of SDG proteins

The RNA-seq data of the G. hirsutum accession were downloaded from the Zhejiang University website (http://cotton.zju.edu.cn/) [40]. Transcriptomic data were obtained for various tissues (roots, stems, leaves, stamens, petals and plants at different flowering stages). The 2.0 kb upstream region of the GhSDG family nucleotide sequence promoter was extracted, and the PlantCARE database (http://bioinformatics.psb.ugent.be/) was used for screening. The interactions of SDG proteins were analyzed via STRING software (https://string-db.org/).

Plant material, RNA extraction, and reverse transcription-quantitative PCR

The G. hirsutum variety Zhongmian113 (ZM113) was grown in a laboratory at Gansu Agricultural University in Lanzhou, China. Samples of tissues, including roots, stems, leaves, sepals, petals, buds, stamens and pistils, were collected. The GhSDG qRT‒PCR-specific primers (Table S1) were designed with Primer-BLAST. An RT‒qPCR mixture was prepared according to the SuperReal Premix Plus (SYBR Green) kit (FP209, Tiangen, China), and the reactions were performed using a LightCycler® 96 instrument. The reaction conditions were as follows: 95 °C for 3 min, followed by 40 cycles of 95 °C for 5 s and 60 °C for 15 s. The housekeeping gene β-actin was used as an internal control, and relative expression levels were calculated via the 2−ΔΔCT method [49].

Vector construction, VIGS and expression profiling procedures for flowering-related genes in cotton

The coding sequences of the GhKMT3;1a and GhKMT3;2a genes were downloaded from CottonFGD to design specific primers. The online tool NCBI Primer-BLAST (https://blast.ncbi.nlm.nih.gov/Blast.cgi/) was used to design an appropriate silencing region in the target gene, and specific cDNA sequences of GhKMT3;1a (319) and GhKMT3;2a (366) were amplified via specific primers (Table S1) and then cloned and inserted into the pTRV2 vector. The bacterial strain GV3101 containing one of the recombinant pTRV2 vectors (pTRV:CLA, pTRV:GhKMT3;1a, pTRV:GhKMT3;2a, and pTRV:00) associated with pTRV1 was then injected into two enlarged cotyledons of eight-day-old ZM113 plants cultured at 25 °C and placed in the dark for 24 h [50]. At the four-leaf stage, RNA was extracted from the silenced cotton leaves, and the silencing efficiency was determined via qRT‒PCR. The expression of five genes that regulate flowering, namely, GhSOC1, GhFT, GhAP1, GhLFY, and GhSVP, in the control and silenced plants was assessed via qRT‒PCR.

Results

Identification, sequence analysis and phylogenetic tree of SDG proteins

A total of 86 GhSDGs in upland cotton were identified by genome-wide analysis (Table S2). The gene length ranged from 1,173 (GhS-ET;4a) to 23,402 bp (GhRBCMT;7). The CDS length varied from 1,014 to 7,440 bp, and the protein length varied from 337 to 2,479 amino acids. The isoelectric points of the proteins ranged from 4.22 to 9.89. The subcellular localization prediction results suggested that 52 of the proteins localized to the nucleus and that 8 of the proteins localized to the cytoplasm (Table S2).

A phylogenetic tree was constructed to determine the evolutionary relationships among SDG proteins in three Gossypium species and 47 matching genes from Arabidopsis (Fig. 1). The SDG genes from the four plants were classified into 7 groups with well-supported bootstrap values. A total of 30, 10, 9, 8, 2, 10, and 17 GhSDGs were found in the KMT1 clade through BRCMT. Clade VI was the largest clade, with 30 members, followed by BRCMT (17 members). The smallest clade was KMT7, which contained only two members. In most cases, one SDG gene from A. thaliana corresponded to four homologous SDG genes from Gossypium (one, one and two homologous SDG genes from G. arboreum, G. raimondii and G. hirsutum, respectively). SDG genes were found on every branch of the three Gossypium species and Arabidopsis.

Fig. 1
figure 1

Phylogenetic tree of SDG proteins. This tree includes 86, 47, 51 and 47 SET domain-containing proteins from G. hirsutum, G. arboretum, G. raimondii, and A. thaliana, respectively. Gh, G. hirsutum; Gr, G. raimondii; At, A. thaliana; Ga, G. arboreum

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Chromosome distribution and gene duplication analysis

A total of 86 GhSDGs were distributed on 25 chromosomes of G. hirsutum, except for A04 (Fig. 2). 43 genes were located in the At and Dt subgenomes. The highest number of GhSDGs (8) mapped to chromosome A05, followed by chromosomes A12 (6), D02 (6) and D12 (6) (Fig. 2). Only one GhSDG gene was located on chromosomes A01, A07, D01, and D07. The majority of the genes were located in terminal areas (Fig. 2).

Fig. 2
figure 2

Distribution of GhSDG genes on chromosomes in G. hirsutum. The length of the G. hirsutum chromosomes is indicated on the vertical axis. The chromosome numbers (A01–D13) are labeled at the top of each chromosome

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In view of the importance of gene duplication in the amplification of plant gene families, we examined probable duplication events for the 86 GhSDG genes from G. hirsutum, and 67 homologous duplicated gene pairs were discovered (Fig. 3a). All of these gene pairs were produced through segmental or whole-genome duplication. Numerous similar genes were found on various cotton chromosomes, demonstrating that the SDG gene family is extensively conserved [51]. In the G. hirsutum genome, the Ka/Ks values of most duplicates were calculated to be lower than 1, clearly indicating that these genes are evolving under purifying selection (Table S3).

Fig. 3
figure 3

a Collinearity analysis of the SDGs. The class I KMT1A, II KMT1B, III KMT2, IV KMT3, V KMT6, VI KMT7, and VII S-ET VIII RBCMT GhSDGs are represented by purple, blue, green, red, cyan, yellow, and rust, respectively. b Synteny analysis of the GhSDG genes among the three Gossypium species

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We investigated the mechanism of gene expansion and evolutionary dynamics of the SDG family during Gossypium species evolution and identified 109 homologous SDG gene pairs between G. hirsutum and G. arboretum (Fig. 3b). The homologous segments between the two polyploid species exhibited the largest percentage, with 13 SDG gene pairs on chromosome A05 of G. hirsutum. Chromosome 12 of G. arboretum contained 19 homologous gene pairs. A total of 112 homologous SDG gene pairs were found between the G. hirsutum and G. raimondii genomes. Chromosomes 8 and 5 of G. raimondii contained 18 and 15 SDG homolog pairs, respectively. Only a few KMT1B, KMT6B, RBCMT and S-ET subfamily genes did not show homology between the two closely related Gossypium species.

Analysis of the gene structure and domain architecture of the GhSDGs

Understanding the structural development of the GhSDG family is important; thus, the exons and introns of the genes were analyzed. As anticipated, the gene architectures of the GhSDG genes in the same subgroup were identical. The numbers of exons and introns in the GhSDG genes varied widely, from one exon and no introns to a maximum of 24 exons and 23 introns (Fig. 4). A total of 11 GhSDGs in KMT1A and 3 GhSDGs in S-ET did not contain introns, whereas KMT2 harbored the most exons and introns.

Fig. 4
figure 4

Domain organization (left) and gene structure (right) of GhSDGs. On the left (domain organization), the different colored boxes represent the following different conserved domains: SET (SM000317), CXC (SM001114), SANT (SM000717), PostSET (SM000508), AWS (SM000570), PHD (SM000249), PWWP (PF00855), FYRN (SM000541), FYRC (SM000542), SRA (SM000466), Pre-SET (SM000468), WIYLD (PF10440), and Rubis-subs-bind (PF09273). The gene structure (right) of the GhSDGs includes a CDS (red box) and an intron (black line)

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To understand the functions of the GhSDGs, we analyzed their protein functional domains. Each subgroup had unique domain compositions, and pre-SET, SET and post-SET domains were detected in the KMT1 class. KMT1A proteins were found to contain an SRA domain, whereas KMT1B proteins often contained another WIYLD domain. The KMT2 class included ten proteins in 4 groups. In addition to the SET domain, several highly conserved protein domains (PWWP, FYRN, and FYRC) and the PHD (plant homeodomain) were found in GhKMT2 proteins. PostSET domains, AWSs (associated with SET), and SETs were three conserved domains found in KMT3 proteins. The C-terminal region of the KMT6A protein had a conserved domain (SANT, CXC). Only the PHD and SET domains were present in GhKMT6B proteins. S-ET proteins had only a fully interrupted SET domain. The GhRBCMT proteins included SET and Rubis-subs-binding domains, except for GhRBCMT;4a/4b/6a/6b, which contained only a SET domain. This diversity of domain elements suggested that these genes may have a variety of activities.

Cis-acting regulatory elements in GhSDG promoters, gene interaction network and functional analysis

Gene expression is regulated mainly by the corresponding promoter through the direct binding of transcription factors to cis-acting regulatory regions. To explore the regulatory patterns and elucidate the probable functions of the identified genes, the upstream regulatory sequences of the 86 GhSDGs were examined. Four groups of cis-acting elements, including growth- and development-related promoters and hormone-, light-, and abiotic stress-responsive elements, were found within the GhSDG promoter (Fig. 5), and these GhSDG elements were highly enriched in those that respond to light. Box-4 was the most abundant element (280) and was found in the promoters of 83 GhSDGs; it is part of a conserved DNA module with functions in light responsiveness. The second most common element was the G-box element, which plays a key role in regulating the circadian rhythm [52]. Many types of phytohormone responsive elements are involved in the ABA response element (ABRE), MeJA-responsive element (CGTCA-motif and TGACG-motif), GA-responsive element (P-box, TATC-box and GARE-motif), and salicylic acid-responsive element (TCA-element) motifs, indicating that various phytohormones may control the expression of GhSDGs. Other cis-acting elements included plant growth- and development-related elements, including RY-elements (8) involved in seed-specific regulation, O2-sites (43) involved in metabolic regulation, CAT-boxes (23) related to meristem expression, and the GCN4_motif (18) involved in endosperm expression, suggesting that these SDG genes are crucial for plant reproduction. Additional biological and abiotic stress-related elements were subsequently detected, indicating that SDGs may also play a role in the stress response.

Fig. 5
figure 5

Cis-element analysis of the GhSDGs. Information about the promoters of the GhSDG genes is provided. The graph shows the enrichment of cis-acting elements, and different colors indicate different numbers of elements

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A SET domain-containing protein (COG2940) was found at the center of the gene interaction network (Fig. S1) and had many connections to methyltransferase-related terms, including methyltransferase activity (NOG258745), N-methyltransferase (KOG1337) and positive regulation of the red or far-red light signaling pathway (NOG255231). We performed Gene Ontology (GO) annotation analysis to predict GhSDG activity, revealing the potential involvement of GhSDG proteins in numerous biological processes, cellular components and molecular processes (Table S4). Most GhSDG proteins were found to be involved in the positive regulation of protein-lysine N-methyltransferase activity and histone lysine methylation in biological processes. According to the results of the cellular component analysis, GhSDG proteins were largely located in the nucleus.

Expression patterns of GhSDG genes in different tissues and at different developmental stages

In this study, RNA-seq data from 18 G. hirsutum tissues were examined to determine the expression profiles of the 86 GhSDGs in various tissues and organs. Some GhSDGs from the same class exhibited expression specificity among the 18 tissues and organs, whereas other GhSDGs from different classes presented similar expression patterns in various tissues and organs, suggesting potential functional divergence of the GhSDGs in upland cotton development. The expression patterns of the GhSDGs were divided into three groups on the basis of hierarchical clustering: G1 (Group 1), G2 (Group 2), and G3 (Group 3) (Fig. 6a). The G1 genes typically exhibited low expression in the majority of flowering organs and high expression throughout the flowering stage. Most G2 genes presented varying expression levels during the flowering stage, and some of these genes were highly expressed in anthers. G3 genes were generally highly expressed in most flowering organs. However, several genes, such as GhKMT2;2a, GhKMT1A;4d, GhRBCMT;8a and GhRBCMT;8b, exhibited low expression after anthesis.

Fig. 6
figure 6

Expression profiles of GhSDG genes in the organs of upland cotton. a Prediction of GhSDG expression in different tissues. The text -3 to 20 DPA indicates -3, 0, 1, 3, 5, 10 and 20 days after anthesis. b qRT‒PCR was conducted to analyze the relative expression of eight GhSDG genes in different tissues. The different letters (a, b, c, d and e) indicate significant differences based on Duncan’s honestly significant difference test.

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GhKMT3;1A, a KMT3 gene, presented the highest FPKM value in flower organs. Comparatively high FPKM values and stage-specific gene expression were observed for other KMT3 GhSDGs (KMT3;1b, KMT3;1c, KMT3;2b) in the stamen at anthesis. However, phylogenetic tree analysis revealed that GhKMT3;1a, GhKMT3;1b, GhKMT3;1c and GhKMT3;2b shared the highest homology with AtKMT3;1/ASHH2 and AtKMT3;2/ASHH1, which were clustered in the KMT3 subfamily. The abovementioned results suggest that the roles of GhKMT3;1a and GhKMT3;2a may be similar to those of KMT3;1 and KMT3;2, which participate in flower fertilization and pollination [53, 54], and these could be considered candidate genes for the control of flowering time.

To further investigate the response of GhSDGs in different tissues and organs, we selected 8 GhKMT3s and confirmed their expression in roots, stems, leaves, sepals, petals, buds, stamens and pistils via RT‒qPCR (Fig. 6b). All the genes presented distinct expression patterns. Five genes (GhKMT3;1a, GhKMT3;1b, GhKMT3;1c, GhKMT3;2a and GhKMT3;2b) were highly expressed in flower tissues, and their expression patterns varied. The leaves presented notable increases in the expression of three genes, namely, GhKMT3;3a, GhKMT3;3b, and GhKMT3;4. The tissue expression levels of 8 specific genes in G. hirsutum were investigated via qRT‒PCR analysis, and the results exhibited a high degree of concordance with the RNA-seq data.

Functional validation of GhKMT3;1a and GhKMT3;2a in upland cotton by VIGS

To further investigate the role of GhKMT3;1a and GhKMT3;2a in regulating flowering in cotton, we cloned the GhKMT3;1a and GhKMT3;2a complementary DNA (cDNA) sequence fragments from the early‐maturing cotton cultivar ZM113. We observed plant morphology after silencing two crucial GhSDG genes (GhKMT3;1a and GhKMT3;2a) via a VIGS system (Fig. 7a and b). An albino phenotype was observed approximately 8 days after the injection of TRV1 + GhCLA into the cotton plants (Fig. S2). qRT‒PCR analysis revealed that the expression levels of TRV:GhKMT3;1a and TRV:GhKMT3;2a were lower than those in TRV:00 (Fig. 7c), indicating that these two genes were successfully silenced. Under normal conditions, the growth of both silenced lines was significantly retarded, and flower bud emergence occurred 6 days later in these lines than in TRV:00 plants. Moreover, compared with that of the control plants, the height of the TRV:GhKMT3;1a cotton plants was decreased by 6 cm, and the height of the TRV:GhKMT3;2a plants was decreased by 5.8 cm (Fig. 7b). These results suggest that GhKMT3;1a and GhKMT3;2a are positive regulators of flowering and development.

Fig. 7
figure 7

Phenotypic variations in VIGS-treated plants. a Phenotypes of TRV:00, TRV:GhKMT3;1a and TRV:GhKMT3;2a. b The flowering time was measured as the budding day. c Relative expression levels of exogenous GhKMT3;1a and GhKMT3;2a in silenced plants grown to the three-leaf stage under LD conditions. c The flowering time was measured as the budding day. d Expression levels of GhKMT3;1a and GhKMT3;2a in the silenced plants

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Subsequently, we measured the expression of GhKMT3;1a and GhKMT3;2a in TRV:GhKMT3;1a, TRV:GhKMT3;2a and TRV:00 and found that the relative expression level of the GhKMT3;2a gene also decreased in TRV:GhKMT3;1a. However, the expression of the GhKMT3;1a gene in the TRV:GhKMT3;2a plants did not differ from that in the TRV:00 plants (Fig. 7d).

GhKMT3;1a and GhKMT3;2a are involved in regulating flowering-related genes

GhAP1, GhSOC1, GhFT, GhSVP (SHORT VEGETATIVE PHASE) and GhLFY (LEAFY) were found to be important regulatory factors in flower development. To determine how GhKMT3;1a and GhKMT3;2a affect flowering in cotton, we measured the expression levels of these five important genes that regulate flowering in the silenced lines and in the TRV:00 plants via RT‒qPCR (Fig. 8a). Compared with those in the TRV:00 plants, the expression levels of the GhSOC1, GhFT and GhAP1 genes were significantly lower in the silenced plants, whereas the levels of the GhSVP genes increased significantly, and the expression levels of the GhLFY genes decreased but not significantly. Taken together, these results indicate that GhKMT3;1a and GhKMT3;2a may promote flowering by affecting the transcription levels of key flowering-related genes.

Fig. 8
figure 8

a Expression analysis of genes regulating flowering time. b Interaction network of the GhKMT3;1a and GhKMT3;2a proteins with key flowering-related proteins

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On the basis of homologs in Arabidopsis, we investigated GhKMT3;1a and GhKMT3;2a and predicted protein interaction networks involving key flowering-related genes. Our findings revealed that GhKMT3;2a may play a role in the flowering process of plants by regulating SOC1, whereas GhKMT3;1a is not directly involved in this regulation; instead, GhKMT3;1a may indirectly participate in the expression of flowering-related genes through its interaction with GhKMT3;2a (Fig. 8b).

Discussion

Number and characteristics of GhSDG genes

According to the results of the phylogenetic analysis, 86 GhSDGs and 48 GaSDGs were identified in G. hirsutum and G. arboretum, respectively. A total of 47 SDG proteins have been identified in A. thaliana [45], and 52 SDG proteins have been identified in G. raimondii [41]. To date, the greatest number of SDGs has been detected in monocotyledonous 6-ploid wheat (166), followed by B. napus (122) [55, 56]. In addition, Jian et al. identified 74 SDG proteins in G. hirsutum, which might be caused by inconsistent screening conditions [43]. The seven clades of the SET family encode proteins with different physicochemical properties, functions, and regulatory mechanisms, and the physicochemical properties of these cotton SDG genes are shown in Table S2. Subcellular localization analysis revealed that a majority of the GhSDG proteins localize to the nucleus, which is consistent with the results of previous studies, suggesting that SDG proteins mainly add methyl groups to histone lysine residues [56, 57]. These results are consistent with our GO analysis (Fig. s1) and with previous studies showing that these genes are involved in regulating various developmental and response processes, such as vegetative growth, reproductive growth, the stress response and the organelle organization of chloroplasts and ribosomes [58, 59].

Exon‒intron structure analysis revealed that the number of exons in cotton SDG genes varied from 1 to 24, with substantial structural differences (Fig. 4). During the evolution of the GhSDG gene family, some introns were lost and gained, which might be related to the flexibility of gene expression and thus allows for selective gene loss [45]. The conserved structural domains of the GhSDG proteins were investigated, and consistent with the A. thaliana SDG protein domain structure, all the cotton SDG proteins exhibited one typical conserved SET domain. In addition to the SET domain, the SDGs included the pre-SET domain, WIYLD domain, SRA domain, post-SET domain, SANT domain, PWWP domain, AWS domain, PHD domain, FYRC domain, FRYN domain, and Rubis-subs-bind domain. Notably, the included gene domains differed among the seven subfamilies, suggesting that the different functions of the SDG family are attributable to these different domains [60]. For example, in the KMT3 subfamily, the SET domain and AWS domain function together to methylate histones with other proteins [61]. It is likely that the gain of these additional domains enables SET domain-containing proteins to acquire new functions [62].

Expansion of GhSDG genes

G. hirsutum is an allotetraploid plant that originated from the female parent G. arboreum (At subgenome) and the male parent G. raimondii (Dt subgenome) 1.5 million years ago [63]. We discovered that the number of SDG genes increased as a result of the cotton tetraploidization event (Fig. 1). A majority of SDGs are present as two diploid copies in tetraploids. Interestingly, the number of SDG genes in the allotetraploid G. hirsutum (86) is actually lower than the sum of SDG genes in G. arboreum (48) and G. raimondii (52), suggesting that chromosome doubling and consequent rapid genome expansion during polyploidization result in varying degrees of gene loss [64]. Phylogenetic data revealed that most of the Arabidopsis SDG members generally corresponded to two G. hirsutum homologs (Fig. 1); however, some Arabidopsis SDGs had only one or no homolog in cotton, including KMT1B;2a/2b, KMT6A;1 and BRCMT;1. Some SDG genes have no orthologous gene pairs in cotton, which might be due to chromosomal rearrangement or fusion during evolution [65]. The homology between the SDG genes of tetraploid and diploid cotton species is greater than that between the SDG genes of Arabidopsis and diploid cotton species. The GhSDGs exhibited good collinearity with the GrSDGs and GaSDGs, and during evolution, the synteny of genes between species with shorter evolutionary distances was high [66], indicating that G. hirsutum evolved from two diploid cotton species. SDG gene expansion most likely allows varied transcriptome control and adaptation to complex terrestrial environments [67].

Expression and potential functions of GhSDG genes

Analysis of the cis-regulatory elements of the GhSDG gene family revealed many regulatory regions in the promoter region, mostly related to various responses to light, plant hormones and growth and development, similar to prior findings [56, 68]. An investigation of protein interaction networks revealed that GhSDGs exhibit methyltransferase activity (NOG258745) and positive regulation of the red or far-red light signaling pathway (NOG255231), and these genes were previously shown to be involved in processes such as seed germination control, hypocotyl growth inhibition, flowering induction, and anthocyanin accumulation [69]. Hence, some cotton SDGs might assist in plant growth via methyltransferase activity. However, few studies have investigated the functions of GhSDGs in G. hirsutum. In general, by evaluating the expression profiles of these GhSDGs in diverse tissues at various developmental stages, their putative activities might be determined. The GhSDGs were more highly expressed in all floral developmental stages, with the highest expression occurring in the ovule on the 3rd day before anthesis, and a few genes exhibited high expression throughout mature inflorescences (Fig. 6). Overall, the analyses suggested that the expression of certain cotton SDGs might be stable across different stages. Considering that their orthologs in Arabidopsis, KMT3 subfamily members, are involved in reproductive organ development [31], GhKMT3s may exhibit similar functions in cotton. In particular, according to the RT‒qPCR results, GhKMT3;1a/1b/2a/2b was highly expressed in the stamens of mature inflorescences, which is consistent with findings in wheat and B. napus [55, 56].

SDGs regulate the activation of target genes in plants by methylating histone H3 and are important transduction components that integrate environmental and developmental inputs. Accumulating evidence has revealed a key role for H3K36me2 and H3K36me3 in regulating flowering time [31, 32, 34, 35]. A lack of AtKMT3;1 and AtKMT3;2 leads to abnormal flowering, and homologous genes exhibit functional similarities among different species. GhKMT3;1a and GhKMT3;2a in the KMT3 family are orthologs of AtKMT3;1 and AtKMT3;2 and are clustered in the same branch; these genes may have similar functions and are involved in controlling flowering time. Therefore, we performed qRT‒PCR analysis of KMT3 subfamily members in upland cotton and identified GhKMT3;1a and GhKMT3;2a as candidate genes for reproductive organ development. To further elucidate how H3K36 affects cotton development, we silenced two GhSDGs (GhKMT3;1a and GhKMT3;2a) via VIGS and found that silencing these two genes led to a reduced flowering time in cotton. However, further in-depth investigations are needed to elucidate the exact mechanisms by which H3K36 regulates the expression of key flowering-related genes and thus affects the development of upland cotton plants.

In Arabidopsis thaliana, the activation of FLC expression was associated with enrichment of H3K4 and H3K36 methylation of the FLC promoter. Mutation of kmt3;1 leads to a decrease in H3K36 methylation at the FLC locus and thus early flowering; in addition, the flowering of the kmt3;2 mutant was delayed, but no change in the level of covalent histone modifications was detected [11]. Therefore, we speculated that KMT3;2 might regulate flowering through other flowering-related pathways. Another study analyzing flowering-related genes revealed that KMT3;2 binds to SOC1, which is required for the deposition of H3K36 methylation at this site [54]. In addition, KMT3;1 is epistatic to KMT3;2 in Arabidopsis, and the kmt3;1 kmt3;2 double mutant presented defects similar to those of the kmt3;1 mutant and opposite those of the kmt3;2 mutant [70]. In upland cotton, delayed flowering due to the absence of the FLC gene was observed in both TRV:GhKMT3;1a and TRV:GhKMT3;2a. We predicted that, similar to KMT3;2, GhKMT3;2a might regulate flowering by regulating GhSOC1 expression. In the silenced plants, the expression levels of GhSOC1, GhAP1 and GhFT decreased, and the expression of GhSVP increased (Fig. 8a). GhSVP and GhSOC1 had antagonistic effects on the integration of flowering signals, and the increase in GhSVP expression may have been caused by the decrease in GhSOC1 expression [71], whereas the expression of the GhLFY gene did not change significantly, indicating that GhLFY may be involved in other flowering pathways. We subsequently detected redundancy between the two genes in the silenced lines and found that the expression level of GhKMT3;2a in TRV:GhKMT3;1a also decreased (Fig. 7d). TRV:GhKMT3;1a plants are equivalent to a double ghkmt3;1a and 2a mutant, exactly like the sdg8 sdg26 (kmt3;1 kmt3;2) double mutant described in Arabidopsis. In these plants, downregulation of GhKMT3;1a has little or no effect compared with downregulation of GhKMT3;2a. SDG26 and SDG8 in A. thaliana can self-interact to form homodimers, which may have the same function in cotton [72]. Owing to the absence of the FLC gene in upland cotton, we hypothesized that GhKMT3;1a indirectly participates in the regulation of flowering by regulating the expression of GhKMT3;2a.

Conclusions

Members of the SDG gene family are major histone lysine methyltransferases, and the evolution of the SDG gene family in three Gossypium species was analyzed. Analyses of the number of genes, chromosomal location, and apparent evolutionary history confirmed that the GhSDG genes were conserved during cotton evolution. Expression analysis and VIGS revealed that GhKMT3;1a and GhKMT3;2a positively regulate flower development in upland cotton. These findings also indicated that GhKMT3;1a and GhKMT3;2a might bind directly to chromatin, methylate H3K36, and activate the expression of the floral transition-related gene GhSOC1, thus affecting other flowering regulation-related genes.

Availability of data and materials

The genomic data for cotton and Arabidopsis thaliana can be downloaded from CottonFGD (https://cottonfgd.org/) and TAIR (https://www.arabidopsis.org/), respectively. The analysis software, analysis methods and datasets generated are available from the corresponding author upon reasonable request.

Abbreviations

SDG:

Set domain group

KMTase:

Histone lysine methyltransferase

RBCMT:

Ribulose-1,5-bisphosphate carboxylase/oxygenase (Rubisco) methyltransferase

FLC:

Flowering locus C

FT:

Flowering locus T

SOC1:

Suppressor of overexpression of constans 1

JA:

Jasmonic acid

qRT‒PCR:

Quantitative real-time PCR

SET:

Su (var), E(z), and Trithorax

ATX1:

Arabidopsis trithorax-like protein1

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Acknowledgements

We would like to express our sincere appreciation to all teachers, students, and instrument platform in our research group for their invaluable assistance.

Funding

This work was supported by the National Natural Science Foundation of China (32260478 and 31971986), the Gansu Province Science and Technology Program (23JRRA1402) and the Natural Science Foundation of the Xinjiang Production and Construction Corps (2024DA019).

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  1. College of Life Science and Technology, Gansu Agricultural University, Lanzhou, 730070, China

    Jisheng Ju, Ying Li, Pingjie Ling, Jin Luo, Wei Wei, Wenmin Yuan, Caixiang Wang & Junji Su

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Contributions

JSJ, JJS, CXW designed the research program; JSJ performed most of the experiments; JL, WW, WMY performed part of the experiments; JSJ, PJL, YL wrote and revised the manuscript. All authors read and approved the final manuscript.

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Correspondence to Caixiang Wang or Junji Su.

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The plant materials used in this study are common ecotypes used for plant research. The plant materials were collected at Gansu Agricultural University, Lanzhou, China. The experimental procedures used on plants, including the collection of plant material, complied with relevant institutional, national, and international guidelines and legislation. All methods used in the manuscript were performed in accordance with relevant guidelines and regulations.

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Ju, J., Li, Y., Ling, P. et al. H3K36 methyltransferase GhKMT3;1a and GhKMT3;2a promote flowering in upland cotton. BMC Plant Biol 24, 739 (2024). https://doi.org/10.1186/s12870-024-05457-y

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  • DOI: https://doi.org/10.1186/s12870-024-05457-y

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BMC Plant Biology

ISSN: 1471-2229

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