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Article

Genome-Wide Characterization and Expression Profile of the Jumonji-C Family Genes in Populus alba × Populus glandulosa Reveal Their Potential Roles in Wood Formation

by
Zhenghao Geng
†,
Rui Liu
† and
Xiaojing Yan
*
State Key Laboratory of Tree Genetics and Breeding, Chinese Academy of Forestry, Beijing 100091, China
*
Author to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Int. J. Mol. Sci. 2025, 26(12), 5666; https://doi.org/10.3390/ijms26125666
Submission received: 30 April 2025 / Revised: 6 June 2025 / Accepted: 10 June 2025 / Published: 13 June 2025
(This article belongs to the Section Molecular Plant Sciences)
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Abstract

The Jumonji C (JMJ-C) domain-containing gene family regulates epigenetic and developmental processes in plants. We identified 55 JMJ-C genes in Populus alba × Populus glandulosa using HMM and BLASTp analyses. Chromosomal mapping revealed an asymmetric distribution with conserved synteny. Phylogenetic reconstruction revealed that PagJMJ genes segregate into five evolutionarily conserved subfamilies, exhibiting classification patterns identical to those of Arabidopsis thaliana and Populus trichocarpa. Synteny analysis indicated a closer relationship with P. trichocarpa than with A. thaliana. Motif and promoter analyses highlighted subfamily-specific features and diverse cis-elements, particularly light-responsive motifs. Expression profiling revealed tissue-specific patterns, with key genes enriched in roots, vascular tissues, and leaves. Developmental analysis in cambium and xylem identified four expression clusters related to wood formation. Co-expression analysis identified six key PagJMJ genes (PagJMJ6, 29, 34, 39, 53, and 55) strongly associated with wood formation-related transcription factors. ChIP-qPCR analysis revealed that key genes co-expressed with PagJMJ genes were marked by H3K4me3 and H3K9me2 modifications. These findings provide insights into the evolutionary and functional roles of PagJMJ genes in poplar vascular development and wood formation.

1. Introduction

Epigenetics refers to reversible, enzyme-mediated modifications that regulate gene expression without altering the DNA sequence, with these changes often being heritable across generations [1,2,3]. Key epigenetic modifications include DNA methylation, histone methylation/acetylation, nucleosome remodeling, and noncoding RNA-mediated regulation [4,5]. Among these, histone methylation is an important and conserved epigenetic modification that regulates transcription by modulating chromatin states or directly recruiting specific effector proteins to activate or repress gene expression [6,7]. The balance of histone methylation is maintained by the opposing actions of histone methyltransferases (HMTs) and histone demethylases (HDMs), which add or remove methyl groups from specific lysine and arginine residues [8,9]. The Jumonji-C (JMJ-C) family proteins are crucial histone demethylases with broad substrate specificity, which remove methyl marks via Fe(II)- and α-ketoglutarate (α-KG)-dependent hydroxylation reactions [10,11]. JMJ-C family proteins can be divided into four categories based on their catalytic domains and substrate specificity: KDM3, KDM4, KDM5, and KDM6 [12]. These proteins are mainly involved in the demethylation process of histone methylation modifications such as H3K4me3, H3K9me2/3, and H3K27me3 [13]. JMJ-C proteins play critical roles in plant developmental processes, including seed germination and dormancy [14,15,16], root patterning [17,18,19], shoot architecture [20,21,22], leaf morphogenesis and senescence [23,24], floral transition [25,26,27,28]. JMJ-C family proteins also play important regulatory roles in plant responses to biotic and abiotic stresses [29,30,31]. JMJ-C-encoding genes have been identified in multiple plant species, such as Arabidopsis thaliana [12], Zea mays [32], Oryza sativa [29], Solanum lycopersicum [33], Citrus sinensis [34], Gossypium hirsutum [31], and Cucumis melo L. [35]. Although studies have shown that members of the plant JMJ-C protein family are widely involved in multiple processes such as growth and development, hormone signaling, and environmental stress response, the JMJ-C gene family has not been systematically studied in woody plants.
Wood is a key product of plant secondary growth, playing a crucial role in forestry, biomass energy development, carbon sequestration, and ecosystem balance [36]. Its formation is a complex process involving multiple stages, including cell division, differentiation, secondary wall synthesis, and programmed cell death [37,38]. These stages are intricately regulated by genetic, developmental, and environmental factors [39]. To date, most research on the molecular mechanism of wood formation has focused on transcription factors and hormone regulation [40,41,42]. Only a few studies have highlighted the significant role of epigenetic modifications in regulating key genes involved in this process. For example, during secondary wall synthesis, the lignin monomer synthase genes PtrCCoAOMT2 and PtrCCR2 are regulated by histone deacetylation [43]. Additionally, in the development of the poplar vascular cambium, the transcription factor PtrVCS2/WOX4a collaborates with a histone acetyltransferase complex to regulate this process [44]. Most existing research focuses on histone acetylation, while the specific regulatory mechanisms of histone methylation in wood formation remain largely unexplored. Therefore, this study focused on the histone demethylase JMJ-C, systematically analyzing its gene family composition, phylogenetic relationships, and expression patterns in P. alba × P. glandulosa and further explored the potential functional mechanisms in the wood formation.

2. Results

2.1. Chromosomal Location and Homologous Gene Analysis of JMJ-C Genes in P. alba × P. glandulosa

Members of the JMJ-C gene family were systematically identified in the P. alba × P. glandulosa genome (v3.1) using a dual approach combining Hidden Markov Models (HMMs) and BLASTp analyses (version 2.16.0). The HMM algorithm was first applied using the conserved JMJ-C domain model (PF02373) as a query, followed by cross-validation against A. thaliana JMJ-C protein sequences. This screening identified 55 putative PagJMJ genes, designated PagJMJ1 through PagJMJ55, based on their chromosomal positions and linear arrangement. Chromosomal mapping revealed an asymmetric distribution pattern, with genes dispersed across 12 chromosomes in both the A and B chromosome sets (Figure 1A,B). Comparative analysis of homologous chromosome pairs indicated conserved syntenic relationships, with PagJMJ genes maintaining corresponding positions in both genome sets. Comprehensive molecular characteristics of PagJMJ proteins—including gene nomenclature, genomic identifiers, chromosomal coordinates, amino acid composition, molecular weight, and theoretical pI values—are detailed in Table S1. The 55 identified proteins exhibited substantial size variation, reflected in diverse molecular weights and isoelectric points. Chromosomal distribution analysis showed no significant correlation between chromosome size and PagJMJ gene density.
Homologous gene pairs were systematically identified using MCScanX (Figure 1C), revealing 56 paralogous relationships. Evolutionary pressure analysis showed that all gene pairs had Ka/Ks ratios < 1 (Table S2), indicating predominant purifying selection. Notably, the KDM5 subfamily members PagJMJ34 and PagJMJ23 exhibited the highest Ka values, while PagJMJ34 and PagJMJ50 had the highest Ks values. The KDM3 subfamily pair—PagJMJ12 and PagJMJ41—displayed the highest Ka/Ks ratios, suggesting relatively relaxed selective constraints within this lineage.

2.2. Phylogenetic Analysis of PagJMJ Genes

To explore the evolutionary dynamics of PagJMJ genes, we conducted a comparative phylogenetic analysis using 102 JMJ-C protein sequences from A. thaliana [12], P. trichocarpa [45], and P. alba × P. glandulosa (Figure 2). The phylogenetic tree was divided into five evolutionary clades-KDM4/JHDM3, KDM5/JARID1, JMJD6, KDM3/JHDM2, and JMJ-C domain-only-based on the Arabidopsis subfamily classification, supported by sequence conservation patterns and domain architecture. Similar to Arabidopsis thaliana and Populus trichocarpa, we also identified five subfamilies of JMJ-C proteins in P. alba × P. glandulosa. Among these clades, KDM4/JHDM3, KDM5/JARID1, and KDM3/JHDM2 formed the three largest groups, while JMJD6 had the fewest members (Figure 2).

2.3. Collinearity Analysis of the PagJMJ Genes Family Across Species

To explore the evolutionary origins of PagJMJ genes, we conducted a synteny analysis to identify interspecies collinearity between P. alba × P. glandulosa and two other species (Figure 3). Gray lines indicate collinear blocks across different chromosomes, while red, blue, and green lines highlight specific collinear JMJ-C gene pairs (red lines: P. trichocarpa between P. alba × P. glandulosa, blue lines: P. trichocarpa between A. thaliana, green lines: P. alba × P. glandulosa between Arabidopsis thaliana). Evolutionary pressure analysis across these species showed that all gene pairs had Ka/Ks ratios < 1 (Tables S3 and S4), indicating predominant purifying selection. Our analysis identified 13 collinear JMJ-C gene pairs between P. alba × P. glandulosa and A. thaliana, with chromosomes 1, 4, and 5 of A. thaliana exhibiting collinearity with PagJMJ genes. Additionally, 59 collinear JMJ-C gene pairs were found between P. trichocarpa and P. alba × P. glandulosa, reflecting their closer evolutionary relationship compared to A. thaliana. Notably, several PagJMJ genes (PagJMJ5, 7, 8, 9, 18, 28, 31, 35, 36, 37, and 52) showed collinear relationships with eight JMJ-C genes in A. thaliana, suggesting their potential significance in the evolutionary dynamics of these gene families.

2.4. Gene Structure and Conserved Motif Analysis of PagJMJ Genes

In P. alba × P. glandulosa, the KDM3/JHDM2, KDM4/JHDM3, KDM5/JARID1, JMJD6, and JMJC domain-only subfamilies consist of 16, 13, 12, 4, and 10 gene members, respectively (Figure 4A). To further characterize the 55 PagJMJ genes, we conducted gene structure and motif distribution analyses using the MEME suite (Figure 4B). Ten conserved motifs (1–10) were identified, with the three most conserved motifs overlapping the JMJ-C domain sequence (Figure S1). Subfamily-specific analysis revealed that members of the same group shared similar motif types and arrangements. Notably, motif 9 was present in members of KDM3, KDM4, and KDM5 subfamilies, highlighting the structural conservation of the JMJ-C domain. The KDM3 subfamily, the largest group, consistently retained six motifs (6, 5, 7, 9, 4, and 8). However, variations in motif composition and arrangement within subfamilies suggested potential functional divergence despite shared phylogenetic classification.
Conserved domain analysis confirmed that all P. alba × P. glandulosa JMJ-C proteins contained the JMJ-C domain (Figure 4C). In the KDM5/JARID1 and KDM4/JHDM3 subfamilies, the JMJ-N domain was consistently present alongside the JMJ-C domain. Additionally, FYRC and FYRN domains were found in PagJMJ23, 50, 29, 55, 4, 33, 20, and 47, while PagJMJ7 and 37 contained the most domains, including JmjN, JmjC, PHD_RSF1, BRIGHT, zf-C5HC2 and PHD_SF (Figure 4C).
To assess functional diversification, we systematically analyzed exon–intron architectures in PagJMJ genes (Figure 4D). Structural analysis revealed considerable variation, with exon counts ranging from 2 to 33 and intron numbers varying between 1 and 32. Phylogenetic clustering indicated that genes within the same clade exhibited conserved structural architectures, suggesting shared evolutionary trajectories.

2.5. Cis-Element Analysis of PagJMJ Genes Promoter Regions

Promoter analysis of PagJMJ genes revealed diverse cis-acting elements categorized into two functional groups (Figure 5). The first group consists of hormone-responsive elements, including those involved in responses to abscisic acid, methyl jasmonate (MeJA), gibberellin, salicylic acid, and auxin. The second group comprises stress-related elements associated with environmental stimuli such as light, low temperature, drought, and defense responses.
Among these elements, light-responsive motifs were the most abundant, present in all PagJMJ family members. Other frequently occurring elements included those associated with anaerobic induction (122 occurrences), abscisic acid responsiveness (68 occurrences), gibberellin responsiveness (68 occurrences), drought inducibility (37 occurrences), and MeJA responsiveness (47 occurrences). Notably, abscisic acid-responsive elements and gibberellin-responsive elements were scarce present in the KDM4 subfamily.

2.6. Expression Patterns of PagJMJ Genes in Different Tissues

To investigate the tissue-specific expression patterns of the PagJMJ gene family, we analyzed the JMJ-C gene expression levels with reference to the published RNA-seq results of axillary bud, young leaf, functional leaf, cambium, xylem, and root in P. alba × P. glandulosa [46]. Cluster analysis revealed that these genes formed six distinct expression groups (Figure 6A). These results showed tissue-specific expression profiles across different organs. In root tissues, four genes (PagJMJ52, 35, 5, 50, 29, and 55) exhibited particularly high expression levels. In the vascular system, PagJMJ18, 20, and 9 were predominantly expressed in the xylem, while PagJMJ34, 26, 1, 30, 14, 16, and 45 were specifically enriched in the cambium. Leaf tissues displayed diverse expression patterns: twelve genes (PagJMJ39, 37, 7, 47, 11, 24, 49, 33, 4, 2, 36, and 8) were mainly expressed in functional leaves, whereas another set of ten genes (PagJMJ28, 54, 21, 22, 48, 15, 44, 25, 51, and 10) showed high expression in young leaves. Axillary buds exhibited a unique expression profile, with ten genes (PagJMJ13, 41, 42, 3, 27, 53, 17, 32, 46, and 19) showing particularly high transcript levels, suggesting their specialized regulatory roles in bud development and maintenance.
To further investigate the relationship between PagJMJ genes and wood formation, we selected 37 PagJMJ genes with high expression levels in cambium and xylem (key tissues involved in wood development) as targets for follow-up research. Based on the published transcriptome sequencing data from the phloem (including cambium) and xylem of 20-day [46], 6-month [47], and 10-year-old [48] trees, we analyzed the expression patterns of these key genes across different developmental stages. This analysis identified four distinct groups, providing insights into their potential roles in wood formation (Figure 6B). Group I genes (PagJMJ26, 1, 30, 38, 9, 55, 6, and 34) were preferentially expressed in the cambium and xylem of 20-day-old trees. Group II genes (PagJMJ47, 28, 13, 42, 41, and 12) maintained high expression levels in these vascular tissues at both the 20-day-old and 6-month-old stages. Group III genes (PagJMJ43, 52, 32, 39, 10, and 14) were consistently expressed in cambium throughout development. Group IV genes (PagJMJ33, 4, 23, 50, 20, 36, 8, 31, and 2) were consistently expressed in the xylem among different stages. Group V genes (PagJMJ27, 53, 35, 5, 18, 16, and 45) were consistently expressed in the vascular tissue at 10-year-old stages. These findings suggest that PagJMJ genes may play distinct roles in tissue differentiation and vascular development in poplar.

2.7. Co-Expression Analysis of PagJMJ Genes and Wood Formation-Related Genes

Gene co-expression analysis is a powerful approach for identifying functionally related genes with similar expression patterns, revealing potential coregulatory relationships, shared biological functions, or participation in common signaling pathways. To explore the involvement of the 37 PagJMJ genes in wood formation, we performed Weighted Correlation Network Analysis (WGCNA) using RNA-Seq data from six tissue types (20-day-old cambium and xylem, 6-month-old phloem and xylem, 10-year-old phloem and xylem). This analysis constructed a tissue-specific co-expression network based on differentially expressed genes.
Our results identified 15 distinct co-expression modules (Figure 7A), with strong correlation patterns among genes within each module (Figure 7B). Modules with correlation coefficients greater than 0.7—specifically, the red, brown, magenta, black, blue, and green modules—show significant associations with tissues at different developmental stages. Within the brown and blue modules, we identified eight and two PagJMJ genes, respectively. After further selection, we retained four PagJMJ genes highly expressed in the xylem and cambium: PagJMJ6, 29, 34, and 55 in the brown module (Figure 7C) and PagJMJ39 and 53 in the blue module (Figure 7D). To further investigate the roles of PagJMJ genes in wood formation, we identified four and twelve wood formation-related transcription factors (TFs) in the brown and blue modules, respectively. Using a weight threshold of 0.2 for potential interactions, we visualized the regulatory relationships using Cytoscape (3.8.2). The brown module contained key TFs, including PagbHLH186, ARF5a, and STMa/c, while the blue module harbored PagARF3/4/6a/6b/8, KNAT6b/c, RR13a, SHN2b, BES1c, NAC071 and APL (Figure 7C,D).
We further validated the co-expression relationship of the PagJMJ genes and their predicted coregulatory transcription factors in xylem and phloem tissues at three developmental stages: 20 days, 6 months, and 10 years. RT-qPCR analysis revealed that PagJMJ6, JMJ29, JMJ55, ARF5a, STMa, and STMc were highly expressed in both xylem and phloem tissues of younger trees (20-day-old and 6-month-old), suggesting their potential roles in the early stages of wood formation. PagJMJ34 exhibited elevated expression in the xylem of both 20-day-old and 10-year-old trees, while PagbHLH186 showed peak expression specifically in the xylem of 20-day-old trees (Figure 8A). In contrast, PagJMJ39, ARF4, ARF6a, KNAT6b, KNAT6c, and APL consistently showed higher transcript levels in phloem compared to xylem across all developmental stages (20 days, 6 months, and 10 years). PagNAC71 displayed a similar expression pattern to these genes in younger trees, but in 10-year-old trees, its expression was higher in the xylem than in the phloem. PagJMJ53 mirrored this expression trend with PagNAC71 in the 20-day-old and 10-year-old trees but showed lower expression in 6-month-old trees. Similarly, PagARF8, BES1c, RR13a, and ARF3 were more strongly expressed in phloem than in xylem at 20 days and 6 months, although their expression levels did not differ significantly between tissues in 10-year-old trees. PagARF6b displayed a phloem-preferential expression pattern only at the 6-month stage, with no significant difference observed at 20 days or 10 years. PagSHN2b showed the opposite trend, with higher expression in the xylem at 20 days and 6 months but elevated expression in the phloem in 10-year-old trees (Figure 8B). These findings suggest the following: PagJMJ6, 29, 34, and 55 may functionally interact with PagbHLH186, ARF5a, and STMa/c; PagJMJ39 and 53 may functionally interact with PagARF3/4/6a/6b/8, KNAT6b/c, APL, NAC71, BES1c, RR13a, and SHN2b. These interactions potentially form regulatory complexes to modulate downstream genes involved in wood formation.

2.8. Analysis of Histone Modification Levels in Wood Formation-Related Genes

Evolutionary analysis revealed that PagJMJ6/29/34/55 are homologous to AtJMJ16, which specifically regulates the demethylation of H3K4me3, a histone modification associated with active transcription [49]. Meanwhile, PagJMJ39 is homologous to AtJMJ28, and PagJMJ53 shares homology with AtJMJ27, while AtJMJ27 and AtJMJ28 are responsible for H3K9me2 demethylation, which is typically linked to gene silencing [50]. To further elucidate the functional roles of PagJMJ genes, we analyzed H3K4me3 and H3K9me2 modification levels of wood-formation-related genes co-expressed with them. ChIP-qPCR analysis in the phloem and xylem of 10-year-old trees revealed that the PagbHLH186, STMa, and ARF5a, which are co-expressed with PagJMJ6/29/34/55, were marked by H3K4me3 modifications, with higher enrichment observed in the phloem compared to the xylem (Figure 9A). Similarly, the PagARF6b, ARF8, BES1c, APL, KNAT6b, KNAT6c, and SHN2, which are co-expressed with PagJMJ39/53, were enriched for H3K9me2 modifications. Except for PagAPL, all of these genes showed higher levels of H3K9me2 in the phloem than in the xylem (Figure 9B).

3. Discussion

We identified a total of 55 JMJ-C proteins in P. alba × P. glandulosa, a number that exceeds those reported in other plant species. All 55 PagJMJ genes contained intact coding sequences without premature stop codons, indicating that they encode functional proteins. Specifically, the JMJ-C protein family comprises 21 members in the model A. thaliana [12], 22 in Phyllostachys edulis [51], 20 in Oryza sativa [29], 20 in Solanum lycopersicum [33], and 17 in Cucumis melo L. [35]. This expansion in P. alba × P. glandulosa is likely due to its hybrid origin, which results in two sets of chromosomes, as well as an increased number of gene duplication events during evolution. It has been reported in the literature that in species such as A. thaliana [12], rice [29], tomato [33], and lemon [35], JMJ-C genes can be divided into five subfamilies. However, there is also a report indicating that in maize [32], the JMJD6 and JMJ-C domain-only subfamilies are lacking. Based on sequence similarity and domain composition, the PagJMJ gene family was classified into five subfamilies: KDM4/JHDM3, KDM5/JARID1, KDM3/JHDM2, JMJD6 and JMJ-C domain-only, exhibiting classification patterns identical to those of A. thaliana and P. trichocarpa. Our findings notably revealed an overlap between the JMJ-C domain and Cupin_8 superfamily in both JMJ-C domain-only and JMJD6 subfamilies (Figure 4C), which aligns with previous reports that JMJ-C proteins belong to the Cupin superfamily due to their characteristic double-stranded β-helix motif structure [52].
Several PagJMJ genes exhibited syntenic relationships, suggesting that the expansion of this gene family was primarily driven by segmental duplication rather than tandem duplication. Collinearity analyses further revealed that P. alba × P. glandulosa shares a higher degree of genomic collinearity with P. trichocarpa than with Arabidopsis, consistent with the closer evolutionary relationship among Populus species. The distribution of PagJMJ family genes across the two chromosomal sets (A and B) was generally balanced. However, some notable exceptions were observed: chromosomes 11A and 12A each habored three and two PagJMJ genes, respectively, whereas their homologous counterparts (11B and 12B) contained only one gene each. These findings suggest potential structural or functional differences between homologous chromosomes that may have influenced the retention or loss of specific JMJ-C genes during evolution. Interestingly, light-responsive cis-elements were the most abundant among the identified promoter motifs (Figure 5). Although the direct role of light in wood formation remains underexplored in trees, emerging evidence suggests that light signaling pathways can influence vascular differentiation and cambial activity, often through crosstalk with phytohormones such as auxin and cytokinin. Therefore, the enrichment of these elements may indicate a potential mechanism by which PagJMJ genes integrate environmental light into the regulation of secondary growth.
Tissue-specific expression analysis provides valuable insights into the functional diversification of PagJMJ gene families. Notably, 37 PagJMJ genes exhibited preferential expression in the cambium and xylem tissues, suggesting their potential involvement in wood formation. The classification of 37 PagJMJ genes into five distinct temporal expression groups suggests a dynamic regulatory network governing vascular tissue differentiation and secondary growth. Histone methylation modification often interacts with transcription factors to exert synergistic regulatory functions and plays an important role in the growth and development of plants. Gene co-expression and qPCR analysis revealed that PagJMJ genes (PagJMJ6, 29, 34, 39, 53, and 55) exhibit strong associations with key transcription factors involved in vascular development, secondary growth, and hormone signaling pathways.
JMJ proteins, as histone demethylases, play essential roles in epigenetic regulation by modulating histone methylation status. ChIP-qPCR results in phloem and xylem tissues showed that PagbHLH186, STMa, and ARF5a are associated with H3K4me3 enrichment, whereas PagARF6b, ARF8, BES1c, APL, KNAT6b, KNAT6c, and SHN2 is enriched for H3K9me2. These patterns are consistent with the histone modification targets of their respective co-expression PagJMJ genes, supporting their potential regulatory roles in wood development. Given these co-expression and ChIP-qPCR analysis results, we speculate that PagJMJ6, PagJMJ29, PagJMJ34, and PagJMJ55 may regulate wood formation by modifying the H3K4me3 methylation status of key gene loci. Meanwhile, PagJMJ39 and PagJMJ53 may influence wood formation through H3K9me2 modification, potentially altering chromatin accessibility and gene expression patterns. Further experimental validation, such as protein-DNA interaction profiling and genetic modification studies, will be necessary to elucidate their precise regulatory roles and molecular mechanisms in secondary growth and wood development.

4. Materials and Methods

4.1. Plant Materials

Poplar (P. alba × P. glandulosa) plants were planted in the greenhouse located at the State Key Laboratory of Tree Genetics and Breeding, Beijing, China. The xylem and phloem of 20-day-old and 6-month-old plants were extracted and stored in liquid nitrogen for RNA extraction. The xylem and phloem samples of 10-year-old plants were collected from P. alba × P. glandulosa trees in the Beiwu garden (39°59′ N, 116°15′ E; Beijing, China).

4.2. Identification and Physicochemical Analysis of PagJMJ Proteins

Genomic resources for this study were obtained from publicly available databases. Genome sequences and annotation files for P. trichocarpa (v3.1) and A. thaliana (TAIR10) were retrieved from the Phytozome database (https://phytozome-next.jgi.doe.gov/ (accessed on 3 March 2025)), while genome data for P. alba × P. glandulosa (v3.1) were acquired from Figshare (https://doi.org/10.6084/m9.figshare.12369209 (accessed on 3 March 2025)). To identify JMJ-C proteins, we employed a dual-approach strategy. First, BLASTp searches were conducted using Arabidopsis JMJ-C protein sequences as queries against both Populus genomes, applying a stringent E-value cutoff of 1 × 10−10. Second, the conserved JMJ-C domain HMM profile (PF02373) was downloaded from the InterPro database (https://www.ebi.ac.uk/interpro/ (accessed on 3 March 2025)) and used for HMMER 3.4 searches with an E-value threshold of 1 × 10−5. The results from both methods were cross-validated and integrated with existing literature to ensure comprehensive identification without redundancy. For the 55 genes obtained above, we resubmitted their protein sequences to the InterPro database for verification and found that each gene contained the JMJ-C domain.
For phylogenetic analysis, JMJ-C protein sequences were aligned and trimmed using ClustalW, and a phylogenetic tree was conducted using MEGA12 with the Neighbor-Joining method. The analysis included 26 JMJ-C proteins from P. trichocarpa, 55 from P. alba × P. glandulosa, and 21 from A. thaliana, employing the p-distance model with 1000 bootstrap replicates. The phylogenetic tree was visualized using iTOL (https://itol.embl.de/ (accessed on 5 March 2025)). Additionally, physicochemical properties of the identified PagJMJ proteins, including molecular weight and isoelectric point, were characterized using the ExPASy ProtParam tool (http://web.expasy.org/protparam/ (accessed on 5 March 2025)).

4.3. Chromosomal Localization and Collinearity Analysis of PagJMJ Genes

The chromosomal positions of PagJMJ genes in the P. alba × P. glandulosa genome were determined using GFF annotations and visualized with the Gene Location Visualize module in TBtools (version 2.210) [53]. Using MCScanX (version 2019), collinearity analysis was performed to identify conserved syntenic relationships among PagJMJ genes. The results were visualized using the circlize and ComplexHeatmap packages in R. We calculated the ratio of non-synonymous to synonymous substitution (Ka/Ks) for duplicated gene pairs using the YN method in KaKs_Calculator (version 3.0) to assess evolutionary constraints [54].

4.4. Analysis of Conserved Domains, Motifs, Gene Structures and Cis-Acting Elements

Conserved domains and motifs in PagJMJ proteins were identified using MEME (http://meme-suite.org/tools/meme (accessed on 10 March 2025)). Gene structures, including intron–exon organization and untranslated regions (UTRs), were annotated based on GFF3 data from the P. alba × P. glandulosa genome database. For cis-acting regulatory element analysis, 2000 bp upstream promoter sequences of all PagJMJ genes were extracted and analyzed using the PlantCARE database (http://bioinformatics.psb.ugent.be/webtools/plantcare/html/ (accessed on 10 March 2025)) [55]. All results were visualized using TBtools (version 2.210) [53].

4.5. Collinearity Analyses of JMJ-C Genes Across Different Species

The protein sequences files and GFF annotations of P. trichocarpa, P. alba × P. glandulosa, and A. thaliana were aligned and analyzed using the jcvi.compara.catalog module of JCVI software (v1.4.16, Tanghaibao; Fuzhou, China). Collinearity relationships were then visualized using the jcvi.graphics.karyotype module.

4.6. Transcriptomic Resources

To investigate the expression patterns of PagJMJ genes, we utilized transcriptomic data from different tissues (axillary bud, young leaf, functional leaf, cambium, xylem, and root), available in the NCBI Sequence Read Archive (SRA) under accession number PRJNA916663. Additionally, RNA-seq data from different development stages (6-month-old and 10-year-old) were retrieved from the SRA with accession numbers PRJNA723483 and PRJNA703312, respectively. Gene expression levels were visualized in heatmaps, with normalization performed using Z-score transformation.

4.7. Weighted Gene Co-Expression Network Analysis (WGCNA)

Gene co-expression networks were constructed and analyzed using the WGCNA package in R. Only genes with expression levels >1 in at least 90% of samples were included. The weighted gene co-expression network was constructed with the following parameters: a soft-thresholding power (β) of 11 to enforce scale-free topology, a signed hybrid network type, module detection sensitivity set to DeepSplit = 4, a minimum module size of 30 genes, and module merging at a cut height of 0.35. Then, we exported the network files for Cytoscape visualization using WGCNA’s exportNetworkToCytoscape function with an edge weight threshold of 0.2. The resulting networks, including PagJMJ genes, were visualized using Cytoscape (v3.8.2).

4.8. RNA Extraction and Quantitative RT-PCR

Total RNA was extracted from the xylem and phloem tissues of P. alba × P. glandulosa at three developmental stages (20-day-old, 6-month-old, and 10-year-old) using the CTAB method. cDNA was synthesized from 1 µg of total RNA using the HiFiScript gDNA Removal RT MasterMix (CWBIO, CW2020M, Nanjing, China). RT-qPCR was performed using the UltraSYBR Mixture (CWBIO, Nanjing, China) with 50× diluted cDNA as the template. The 18S rRNA gene served as the internal reference.
The RT-qPCR conditions consisted of an initial denaturation at 95 °C for 10 min, followed by 45 cycles of 95 °C for 15 s and 60 °C for 1 min. Relative gene expression levels were calculated using the 2−ΔΔCt method. Three independent biological replicates and three technical replicates were analyzed for each sample. Data were expressed as mean ± standard deviation (SD) and visualized using GraphPad Prism 8. Gene-specific primers were listed in Table S5.

4.9. Chromatin Immunoprecipitation and Quantitative PCR

Chromatin immunoprecipitation (ChIP) assays were performed according to established protocols [56]. Briefly, 5 g of xylem and phloem tissues from 10-year-old poplar trees were ground in liquid nitrogen and suspended in precooled lysis buffer. Crosslinking was carried out by vacuum infiltration with 1% (w/v) formaldehyde for 20 min and subsequently quenched with 0.125 M glycine. Chromatin was then extracted and sonicated using a Bioruptor Plus (Diagenode, Basel, Switzerland) to generate DNA fragments of 200–500 bp. Immunoprecipitation was performed overnight at 4 °C using antibodies specific to H3K4me3 and H3K9me2. After reverse crosslinking, DNA was purified and subjected to quantitative PCR (qPCR) analysis. Gene-specific primers were listed in Table S5.

5. Conclusions

Based on phylogenetic, genomic distribution, gene structure and conserved motif, promoter binding site, and expression profiles analysis, this study comprehensively and systematically identified 55 PagJMJ genes in P. alba × P. glandulosa. Tissue-specific expression and gene co-expression analysis revealed that PagJMJ genes (PagJMJ6, 29, 34, 39, 53, and 55) may play a role in modulating TF expression (PagbHLH186, ARF5a, STMa/c, ARF3/4/6a/6b/8, KNAT6b/c, RR13a, SHN2b, BES1c, NAC071, and APL) during wood formation. Overall, these findings highlight the potential regulatory roles of PagJMJ genes in wood formation and provide new insights into the epigenetic and transcriptional control of secondary growth in poplar.

Supplementary Materials

The following supporting information can be downloaded at https://www.mdpi.com/article/10.3390/ijms26125666/s1.

Author Contributions

X.Y. conceived the research plan; Z.G. and R.L. performed the experiments; X.Y., Z.G. and R.L. analyzed the data; Z.G. and X.Y. wrote the manuscript. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by the National Key Research and Development Program of China (2021YFD2200900 to X.Y.) and Fundamental Research Funds of the Chinese Academy of Forestry (CAFYBB2023QB010 to X.Y.).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The original contributions presented in this study are included in the article. Further inquiries can be directed to the corresponding author.

Conflicts of Interest

The authors declare no conflicts of interest.

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Figure 1. Chromosome distribution and synteny analysis of PagJMJ genes in P. alba × P. glandulosa. (A) Chromosomal localization of PagJMJ genes across the 12 chromosomes of the A genome in P. alba × P. glandulosa. (B) Chromosomal localization of PagJMJ genes across the 12 chromosomes of the B genome in P. alba × P. glandulosa. (C) Comparative analysis of the distribution and syntenic relationships within the PagJMJ gene family, with syntenic gene pairs illustrated by blue connecting lines.
Figure 1. Chromosome distribution and synteny analysis of PagJMJ genes in P. alba × P. glandulosa. (A) Chromosomal localization of PagJMJ genes across the 12 chromosomes of the A genome in P. alba × P. glandulosa. (B) Chromosomal localization of PagJMJ genes across the 12 chromosomes of the B genome in P. alba × P. glandulosa. (C) Comparative analysis of the distribution and syntenic relationships within the PagJMJ gene family, with syntenic gene pairs illustrated by blue connecting lines.
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Figure 2. Phylogenetic analysis of JMJ-C family proteins in three plant species. A phylogenetic tree of JMJ-C proteins from P. alba × P. glandulosa, P. trichocarpa, and Arabidopsis thaliana. The tree was constructed using the ClustalW and Neighbor-Joining (NJ) method, with 1000 bootstrap replicates in MEGA 12.0. Based on sequence homology, JMJ-C proteins were classified into five distinct subfamilies: KDM4/JHDM3, KDM5/JARID1, JMJD6, KDM3/JHDM2, and JMJ-C domain-only. These subfamilies are represented by different colored blocks, as illustrated in the lower left corner of the figure.
Figure 2. Phylogenetic analysis of JMJ-C family proteins in three plant species. A phylogenetic tree of JMJ-C proteins from P. alba × P. glandulosa, P. trichocarpa, and Arabidopsis thaliana. The tree was constructed using the ClustalW and Neighbor-Joining (NJ) method, with 1000 bootstrap replicates in MEGA 12.0. Based on sequence homology, JMJ-C proteins were classified into five distinct subfamilies: KDM4/JHDM3, KDM5/JARID1, JMJD6, KDM3/JHDM2, and JMJ-C domain-only. These subfamilies are represented by different colored blocks, as illustrated in the lower left corner of the figure.
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Figure 3. Collinear analysis of PagJMJ genes in P. alba × P. glandulosa with P. trichocarpa and A. thaliana. Collinear analysis of PagJMJ genes from P. alba × P. glandulosa was performed with two related species, P. trichocarpa and A. thaliana. Red boxes indicate chromosomes of P. trichocarpa, blue boxes indicate chromosomes of A. thaliana, green boxes indicate chromosomes of P. alba × P. glandulosa. Red lines highlight the collinear JMJ-C gene pairs between P. trichocarpa and P. alba × P. glandulosa. Blue lines represent the collinear JMJ-C gene pairs between P. trichocarpa and A. thaliana. Green lines denote the collinear JMJ-C gene pairs between P. alba × P. glandulosa and A. thaliana.
Figure 3. Collinear analysis of PagJMJ genes in P. alba × P. glandulosa with P. trichocarpa and A. thaliana. Collinear analysis of PagJMJ genes from P. alba × P. glandulosa was performed with two related species, P. trichocarpa and A. thaliana. Red boxes indicate chromosomes of P. trichocarpa, blue boxes indicate chromosomes of A. thaliana, green boxes indicate chromosomes of P. alba × P. glandulosa. Red lines highlight the collinear JMJ-C gene pairs between P. trichocarpa and P. alba × P. glandulosa. Blue lines represent the collinear JMJ-C gene pairs between P. trichocarpa and A. thaliana. Green lines denote the collinear JMJ-C gene pairs between P. alba × P. glandulosa and A. thaliana.
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Figure 4. Comprehensive sequence analyses of PagJMJ genes. (A) Phylogenetic relationships of PagJMJ proteins were reconstructed using the NJ method, revealing that these proteins cluster into three distinct groups. (B) Conserved motifs within PagJMJ proteins were identified using the MEME tool (version 5.5.7), resulting in the identification of 10 unique motifs, designated as Motif 1 through Motif 10. (C) The schematic representation of conserved domains illustrates their positions and sizes, with each domain depicted as a colored square. (D) Gene structure analysis of PagJMJ genes highlighted the organization of UTRs, introns, and exons, where UTRs are shown in green, exons in yellow, and introns in grey. A scale bar of 2 kb is provided for reference.
Figure 4. Comprehensive sequence analyses of PagJMJ genes. (A) Phylogenetic relationships of PagJMJ proteins were reconstructed using the NJ method, revealing that these proteins cluster into three distinct groups. (B) Conserved motifs within PagJMJ proteins were identified using the MEME tool (version 5.5.7), resulting in the identification of 10 unique motifs, designated as Motif 1 through Motif 10. (C) The schematic representation of conserved domains illustrates their positions and sizes, with each domain depicted as a colored square. (D) Gene structure analysis of PagJMJ genes highlighted the organization of UTRs, introns, and exons, where UTRs are shown in green, exons in yellow, and introns in grey. A scale bar of 2 kb is provided for reference.
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Figure 5. Cis-acting elements of the PagJMJ genes. The distribution of cis-acting elements within the 2000 bp upstream promoter regions of PagJMJ genes is illustrated. Different colored circles represent distinct types of regulatory elements, highlighting their positions and abundance across the gene family.
Figure 5. Cis-acting elements of the PagJMJ genes. The distribution of cis-acting elements within the 2000 bp upstream promoter regions of PagJMJ genes is illustrated. Different colored circles represent distinct types of regulatory elements, highlighting their positions and abundance across the gene family.
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Figure 6. Expression profiles of PagJMJ genes in P. alba × P. glandulosa in 20-day-old cambium (C-20 D) and xylem (X-20 D), 6-month-old phloem (P-6 M) and xylem (X-6 M), and 10-year-old phloem (P-10 Y) and xylem (X-10 Y). (A) Heatmap displaying the transcript abundance of PagJMJ genes across different tissues, including axillary buds, young leaves, functional leaves, cambium, xylem, and roots. (B) Expression patterns of PagJMJ genes with high expression levels in cambium and xylem at different developmental stages. K-means clustering analysis categorizes PagJMJ genes into five distinct clusters (I–V) based on their expression profiles. The color scale (blue to red) represents low to high expression levels.
Figure 6. Expression profiles of PagJMJ genes in P. alba × P. glandulosa in 20-day-old cambium (C-20 D) and xylem (X-20 D), 6-month-old phloem (P-6 M) and xylem (X-6 M), and 10-year-old phloem (P-10 Y) and xylem (X-10 Y). (A) Heatmap displaying the transcript abundance of PagJMJ genes across different tissues, including axillary buds, young leaves, functional leaves, cambium, xylem, and roots. (B) Expression patterns of PagJMJ genes with high expression levels in cambium and xylem at different developmental stages. K-means clustering analysis categorizes PagJMJ genes into five distinct clusters (I–V) based on their expression profiles. The color scale (blue to red) represents low to high expression levels.
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Figure 7. Relationship between PagJMJ genes and potential transcription factors predicted by WGCNA. (A) Hierarchical cluster tree of gene co-expression modules, with color bands indicating 13 distinct modules. (B) Heatmap displaying the correlation between co-expression modules and tissue types. The color intensity represents the correlation coefficient, while values within the cells indicate p-values. (C,D) Co-expression networks of the brown and blue modules, showing interactions between PagJMJ genes and potential transcription factors. Red circles represent PagJMJ genes, while blue circles indicate transcription factors.
Figure 7. Relationship between PagJMJ genes and potential transcription factors predicted by WGCNA. (A) Hierarchical cluster tree of gene co-expression modules, with color bands indicating 13 distinct modules. (B) Heatmap displaying the correlation between co-expression modules and tissue types. The color intensity represents the correlation coefficient, while values within the cells indicate p-values. (C,D) Co-expression networks of the brown and blue modules, showing interactions between PagJMJ genes and potential transcription factors. Red circles represent PagJMJ genes, while blue circles indicate transcription factors.
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Figure 8. RT-qPCR analysis of PagJMJ genes and WGCNA-predicted transcription factors in xylem and phloem tissues of P. alba × P. glandulosa at different developmental stages. (A) Relative expression levels of genes from the brown module were determined by RT-qPCR. (B) Relative expression levels of genes from the blue module were determined by RT-qPCR.Expression was analyzed in phloem and xylem tissues collected from 20-day-old (P-20 D, X-20 D), 6-month-old (P-6 M, X-6 M), and 10-year-old (P-10 Y, X-10 Y) trees. Data are presented as means ± standard deviation (SD) of three biological replicates. Statistical significance was determined by one-way analysis of variance (ANOVA), and different lowercase letters indicate significant differences among samples (p < 0.05).
Figure 8. RT-qPCR analysis of PagJMJ genes and WGCNA-predicted transcription factors in xylem and phloem tissues of P. alba × P. glandulosa at different developmental stages. (A) Relative expression levels of genes from the brown module were determined by RT-qPCR. (B) Relative expression levels of genes from the blue module were determined by RT-qPCR.Expression was analyzed in phloem and xylem tissues collected from 20-day-old (P-20 D, X-20 D), 6-month-old (P-6 M, X-6 M), and 10-year-old (P-10 Y, X-10 Y) trees. Data are presented as means ± standard deviation (SD) of three biological replicates. Statistical significance was determined by one-way analysis of variance (ANOVA), and different lowercase letters indicate significant differences among samples (p < 0.05).
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Figure 9. Detection of H3K4me3 (A) and H3K9me2 (B) levels at specific genes. Phloem and xylem tissues collected from 10-year-old (P-10 Y, X-10 Y) trees were used for the ChIP-qPCR assays with anti-H3K4me3 and anti-H3K9me3 antibodies. Data are presented as means ± standard deviation (SD) of three biological replicates. Statistical significance was determined by one-way analysis of variance (ANOVA), and different lowercase letters indicate significant differences among samples (p < 0.05).
Figure 9. Detection of H3K4me3 (A) and H3K9me2 (B) levels at specific genes. Phloem and xylem tissues collected from 10-year-old (P-10 Y, X-10 Y) trees were used for the ChIP-qPCR assays with anti-H3K4me3 and anti-H3K9me3 antibodies. Data are presented as means ± standard deviation (SD) of three biological replicates. Statistical significance was determined by one-way analysis of variance (ANOVA), and different lowercase letters indicate significant differences among samples (p < 0.05).
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Geng, Z.; Liu, R.; Yan, X. Genome-Wide Characterization and Expression Profile of the Jumonji-C Family Genes in Populus alba × Populus glandulosa Reveal Their Potential Roles in Wood Formation. Int. J. Mol. Sci. 2025, 26, 5666. https://doi.org/10.3390/ijms26125666

AMA Style

Geng Z, Liu R, Yan X. Genome-Wide Characterization and Expression Profile of the Jumonji-C Family Genes in Populus alba × Populus glandulosa Reveal Their Potential Roles in Wood Formation. International Journal of Molecular Sciences. 2025; 26(12):5666. https://doi.org/10.3390/ijms26125666

Chicago/Turabian Style

Geng, Zhenghao, Rui Liu, and Xiaojing Yan. 2025. "Genome-Wide Characterization and Expression Profile of the Jumonji-C Family Genes in Populus alba × Populus glandulosa Reveal Their Potential Roles in Wood Formation" International Journal of Molecular Sciences 26, no. 12: 5666. https://doi.org/10.3390/ijms26125666

APA Style

Geng, Z., Liu, R., & Yan, X. (2025). Genome-Wide Characterization and Expression Profile of the Jumonji-C Family Genes in Populus alba × Populus glandulosa Reveal Their Potential Roles in Wood Formation. International Journal of Molecular Sciences, 26(12), 5666. https://doi.org/10.3390/ijms26125666

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