https://orcid.org/0009-0006-2543-5723
Figures
Abstract
The CAD (Cinnamyl Alcohol Dehydrogenase) gene family is a key determinant for lignin biosynthesis in plants. In legumes, CAD enzymes are involved in the development of vascular tissues such as xylem and Casparian strip and they contribute to the production of antimicrobial and antifungal compounds. Thereby, it offers defense against pathogens and pests. Despite their biological significance, a comparative genome-wide analysis of the CAD gene family in Medicago truncatula and Lotus japonicus has not been explored. Therefore, we conducted a comparative genome-wide study to investigate the characteristics and potential role of CAD genes in these two model legume species. A total of 51 CAD genes were identified in M. truncatula (MtCAD) and 35 in L. japonicus (LjCAD). The CAD proteins are prominently characterized by ADH_N and ADH_zinc_N domains that were distributed in 8 and 6 chromosomes of MtCAD and LjCAD, respectively. Structural organization and conserved motif analysis indicated notable similarities between MtCAD and LjCAD proteins. However, considering the ancestry and functionality and based on the evolutionary analysis, LjCAD showed more similarities with Arabidopsis than MjCAD. Gene duplication analysis identified twelve duplicated gene pairs in MtCAD and eight in LjCAD, including both tandem and segmental duplication events. Most MtCAD and LjCAD were found in the cytoplasm with some of the cis-acting regulatory elements associated with stress responses. Gene Ontology annotation suggested that most MtCAD genes were associated with biological processes whereas LjCAD genes are mainly enriched in molecular functions. Both MtCAD and LjCAD showed potential roles in secondary metabolite production. Three substantial transcription factor families such as bZIP, C2H2, and ERF and several unique microRNAs were predicted to target MtCAD and LjCAD in regulating their gene expression against certain abiotic stressors for instance cold, freezing, drought, and heat. The MtCAD and LjCAD expressed highly in stress-responsive tissues such as nodule, root, immature flower, seed, and leaf. Meanwhile, RNA-sequencing data further highlighted several potential stress-responsive genes. In M. truncatula, The MtCAD1, MtCAD3, MtCAD9, MtCAD15, MtCAD23, MtCAD27, and MtCAD47 exhibited higher expression under cold, drought, and freezing stress compared with control conditions. Whereas in L. japonicus, LjCAD6, LjCAD8, and LjCAD11 showed higher expression under cold, drought, and heat stress. Thus, these genes may serve as promising candidates for improving abiotic stress tolerance and provide molecular insights into their functional roles for future crop improvement programs and experimental validation.
Citation: Khatun MS, Zohra FT, Shing P, Islam MSU, Rahman SM, Sarkar MAR (2026) Comparative genome-wide analysis of CAD (Cinnamyl Alcohol Dehydrogenase) gene family in Medicago truncatula and Lotus japonicus and their expression profiles in response to various abiotic abiotic stresses. PLoS One 21(7): e0353726. https://doi.org/10.1371/journal.pone.0353726
Editor: Mojtaba Kordrostami, Nuclear Science and Technology Research Institute, IRAN, ISLAMIC REPUBLIC OF
Received: December 30, 2025; Accepted: June 26, 2026; Published: July 21, 2026
Copyright: © 2026 Khatun et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: All relevant data are within the manuscript and its Supporting Information files.
Funding: The author(s) received no specific funding for this work.
Competing interests: The authors have declared that no competing interests exist.
1. Introduction
The CAD (Cinnamyl Alcohol Dehydrogenase) gene family is a multigene family with tissue-specific or stress-inducible isoforms [1]. In plants, one of the most essential functions of the CAD gene is their role in lignin biosynthesis which modifies the plant’s structure, defense systems, and stress tolerance [2]. Upon pathogen recognition, signaling pathways activate defense-related gene expression, leading to the biosynthesis of phytoalexins, such as terpenoids and phenylpropanoids [3]. Phenylpropanoids are antimicrobial compounds that catalyse the final step in monolignol biosynthesis where cinnamyl aldehydes are converted into their corresponding alcohols by CAD enzymes [4]. During polymerisation, monolignols produce lignin which strengthens the secondary walls of stems and roots as well as vascular tissues [5]. The phenylpropanoid pathway produces monolignols like p-coumaryl, coniferyl, and sinapyl alcohols. The oxidative coupling of monolignols produces lignin as a complex polymer with hydroxyphenyl (H) guaiacyl (G) and syringyl (S) units [6]. The process of lignin synthesis shows variation because monolignols undergo different degrees of coupling depending on species, tissue type, and developmental stage [7]. In vascular tissues, particularly the xylem, lignin plays a crucial role in transporting water and provides structural support as well as resistance against pathogens and environmental stresses [8].
The CAD gene activity is associated with the conserved ADH_N and ADH_zinc_N domains. ADH_ N domain catalyzes cinnamyl aldehydes and maintains the overall structure and function of the enzyme [9]. Meanwhile, ADH_zinc_ N domain specifically binds two zinc ions-one for catalysis and one for structural stability and ensures proper enzyme function, substrate binding, and lignin polymerisation [10]. In response to pathogenic threats, plants strengthen their cell walls through lignification. For instance, Verticillium dahliae infection activates lignification in several plant species [11]. The roots of tomato show a rise in lignin synthesis after pathogen resistance, while the cotton plant shows V. dahliae elicitor-mediated lignin deposition through transcriptomic evidence of gene upregulation [12, 13]. Additionally, transcription factor GhMYB4 and the enzyme Gh4CL30 have been reported to regulate defense response through modification of cotton lignification processes [14].
Medicago truncatula and Lotus japonicus were selected for comparative analysis because they are well-established model legumes with complementary ecological and physiological traits. Although, both species share conserved nodulation and lignin biosynthesis pathways, they differ in stress responses and environmental adaptation. M. truncatula, a forage legume, was first introduced as a model legume in 1990 [15]. Meanwhile, L. japonicus was introduced as a model legume in 1992 [16]. Since then, both the species have contributed significantly to the advancements of legume biology. They have been widely used to study rhizobia Nod factor recognition and the signaling networks regulating nodule formation [17]. They have also been facilitated the identification of genetic mechanisms that enhance tolerance to salinity and drought conditions. For instance, the activation of CCaMK and a gain of function mutation in LHK1 can induce this process without requiring rhizobial signals [18].
Despite their shared characteristics as model legumes, M. truncatula and L. japonicus differ in their ecological adaptation and stress response mechanisms. M. truncatula is primarily adapted to Mediterranean environments and has been widely used to study drought and salinity tolerance [19]. In contrast, L. japonicas, native to temperate East Asia, thrives across varied environments and exhibits distinct symbiotic relationships and stress response mechanisms [20].
The comparative genome-wide study on MtCAD and LjCAD genes provides insights into the evolutionary, structural, and functional characteristics in of the CAD gene family in M. truncatula and L. japonicus. The evolutionary phylogenetic tree analysis revealed more genetic resemblance of LjCAD with AtCAD than MtCAD. Gene structure, conserved domain, and motif analysis further demonstrated functional and structural conformity among different CAD subgroups. Gene duplication analysis indicated that the evolution of MtCAD and LjCAD genes was primarily driven by purifying selection, with both tandem and segmental duplication events contributing to their expansion. GO and KEGG pathway analyses further clarified their biological roles and metabolic functions, while CARE analysis revealed their involvement particularly with presence of multiple the stress responsive signaling motif. Additionally, tissue-specific expression patterns and RNA-sequencing data under various abiotic stresses further supported these findings. Based on the role of CAD genes in lignin biosynthesis and plant defense system, we hypothesize that the expansion and diversification of the CAD gene family in M. truncatula and L. japonicus contribute to functional specialization in abiotic stress adaptation. We further hypothesize that specific CAD gene clades possess stress-responsive regulatory elements and display differential expression patterns under various abiotic stress conditions.
2. Methods and materials
2.1. Identification and characterization of CAD genes in legume families (Medicago and Lotus)
The CAD gene DNA binding domains from Arabidopsis were used as queries to retrieve CAD-related gene sequences, whole genome sequences, and protein sequences from Medicago truncatula and Lotus japonicas (S1–S5 Data in S1 File). These sequences were obtained from Phytozome v13 using BLASTp (Protein-Basic Local Alignment Search Tool), with an E-value threshold set to −1, a comparison matrix of BLOSUM62, and default parameters [21]. To identify conserved domain patterns across CAD protein sequences, several tools were employed, including SMART Simple Modular Architecture Research Tool (SMART) [22], NCBI CDD (Conserved Domain Database) [23], and PfamScan [24], all using default settings. The candidate were selected based on the presence of ADH_N domain.
2.2. Determination of physiochemical properties of MtCAD and LjCAD
The physicochemical properties of MtCAD and LjCAD were analyzed, including the number of amino acid residues, molecular weight (in kDa), isoelectric point (pI), instability index, aliphatic index, and Grand Average of Hydropathy (GRAVY). These properties were determined using the ProtParam online tool available at
2.3. Phylogenetic analysis among MtCAD, LjCAD, AtCAD, OsCAD, SbCAD, HvCAD, and BdCAD
Phylogenetic tree analysis was performed using MEGA11 software [25]. The tree was constructed using the Maximum Likelihood (ML) model [26] with Jones–Taylor–Thornton (JTT) as substitution model. Uniform rates among sites and Nearest-Neighbor-Interchange (NNI) heuristic search were applied. Meanwhile, a total of 1000 bootstrap replicates were conducted to evaluate branch support. The ClustalW program was utilized for sequence alignment [27]. The resulting phylogenetic tree was visualized using the ChiPlot online tool [28].
2.4. Conserved motif, domain, and gene structure analysis of MtCAD and LjCAD
Conserved motif analysis was performed using the MEME (Multiple EM for Motif Elicitation) suite [29] with default parameters except the motif parameter set to 10. Visualizations were made using the ChiPlot online program. Domain organization was identified using the Motif Search tool [30] and further visualized using DOG2.0 software [31]. Gene structure analysis, including exon-intron organization, was performed using the Gene Structure Display Server (GSDS) version 2.0 [32].
2.5. Time divergence, gene duplication, and Ka/Ks ratio calculation of MtCAD and LjCAD
The Ka/Ks ratios and divergence times of duplicated gene pairs in MtCAD and LjCAD were calculated using TBtools v2.154 [33]. The divergence time between MtCAD and LjCAD was calculated in million years ago (MYA) using T = Ks/2λ, where λ represents the neutral substitution rate (6.5 × 10−9 substitutions per site per year) [34].
2.6. Collinearity, synteny and chromosomal localization analysis of MtCAD and LjCAD
Collinearity and synteny relationships among CAD genes were analyzed using TBtools v2.154. The MCScanX algorithm was used to process the whole genome sequences and genome annotation files [35]. The MG2C web v2 server mapped and displayed the chromosomal locations of MtCAD and LjCAD [36].
2.7. Prediction of subcellular localization and cis-acting regulatory elements in MtCAD and LjCAD
The sub cellular localizations were predicted using the Wolf PSORT online program predicted protein sub cellular localization [37]. Sequences of 5′ UTR spanning 2000 base pairs were extracted for both MtCAD and LjCAD from the plant CARE database. [38]. The graphical representation was performed in RStudio version 2024.09.0 [39].
2.8. Gene ontology (GO), protein-protein interactions (PPIs), KEGG pathway (Kyoto Encyclopedia of Genes and Genomes) analysis of MtCAD and LjCAD
Gene Ontology (GO) annotation was predicted using the PlantRegMap tool with a threshold p-value of 0.01 and default parameters [40]. Protein-protein interactions and KEGG pathway analysis were performed using the STRING version 12 online tool by utilizing peptide sequences (S3 Data in S1 File) [41]. The visualization of GO functions and KEGG pathways was performed using SRPLOT [42].
2.9. Transcription factors (TFs) and regulatory network analysis of MtCAD and LjCAD
Information on transcription factors potentially regulating MtCAD and LjCAD genes was obtained from the PlantTFDB database using default parameters and a threshold p-value of 1 × 10 ⁻ ⁴. Regulatory networks between CAD genes and transcription factors were constructed and visualized using Cytoscape software version 3.10.3 [43].
2.10. Prediction of putative micro-RNAs (miRNAs) targeting MtCAD and LjCAD
Putative microRNAs (miRNAs) targeting MtCAD and LjCAD genes were predicted using the miRBase database [44] and the psRNATarget server [45]. The miRNA-gene regulatory networks were visualized using Cytoscape version 3.10.3.
2.11. Tissue-specific and various abiotic stress treatment expression pattern in MtCAD and LjCAD
The tissue-specific expression data of MtCAD genes (bio project ID: PRJNA80163) [46] were obtained from NCBI Sequence Read Archive (SRA) and the LjCAD genes tissue-specific expression data were retrieved from Lotus japonicus Expression Atlas [47]. The RNA-sequencing data of various abiotic stressors treatment were generated with bio project ID: PRJNA884427 for LjCAD [48] and bio project ID: PRJNA286829 for MtCAD from NCBI [49]. For quality control and trimming, version 0.32 of trimmomatic package was used [50]. Clean reads were aligned to the reference genomes of M. truncatula and L. japonicus using STAR v2.7.11b [51]. Samtools packages version 1.20 was used for the conversion of the sequence alignment map (SAM) to binary alignment map (BAM) files [52]. Gene expression levels were quantified as Fragments Per Kilobase of transcript per Million mapped reads (FPKM) using RSEM v1.1.17 [53]. The expression patterns were visualized using TB tools v2.154.
3. Results
3.1. Identification and determination of physiochemical properties of MtCAD and LjCAD
A comprehensive analysis identified a total of 86 cinnamyl alcohol dehydrogenase (CAD) genes, comprising 51 MtCAD in M. truncatula and 35 LjCAD in L. japonicus. The length of amino acid in M. truncatula ranged from 109 A.A. (MtCAD51) to 633 A.A. (MtCAD16 & MtCAD17) (Table 1). Meanwhile, the length of amino acid in L. japonicus ranged from 312 A.A. (LjCAD15) to 671 A.A. (LjCAD21). Accordingly, LjCAD proteins were generally heavier ranging from 33.29 kDa (LjCAD15) to 70.77 kDa (LjCAD21). In contrast, the molecular weight of MtCAD ranged from 11.43 kDa (MtCAD51) to 68.89 kDa (MtCAD17). Both MtCAD and LjCAD showed higher number of acidic proteins. For example, 29 MtCAD were acidic while 22 LjCAD were acidic. Further, 39 MtCAD had instability index lower than 40, whereas 31 LjCAD proteins had instability index below 40. Two protein groups displayed predominantly hydrophobic characteristics in their GRAVY value yet MtCAD exhibited a broader hydrophobicity scale due to MtCAD51 (0.304) being its most hydrophobic member alongside MtCAD29 (−0.242). Meanwhile, LjCAD comprised most hydrophilic LjCAD1 (0.242) and most hydrophobic LjCAD4 (−0.163).
3.2. Phylogenetic relationship analysis among MtCAD, LjCAD, AtCAD, OsCAD, SbCAD, HvCAD and BdCAD
A comparative phylogenetic tree was constructed by using a total of 134 CAD proteins, 51 from M. truncatula, 35 from L. japonicus, 9 from A. thaliana, 11 from Hordeum vulgare, 12 from Oryza sativa, 7 Brachypodium distachyon and 9 from Sorghum bicolor (Fig 1). Based on the distribution pattern of AtCAD proteins, the MtCAD and LjCAD genes were classified into nine groups (A–I). Among these, group C contained the highest number of members (33), including 17 MtCAD and 16 LjCAD genes. In contrast, groups E and F contained the fewest members (6 each). The remaining groups, A, B, D, G, H and I, contained 8, 28, 12, 16, 10, and 12 members, respectively (S1 Fig). Notably, this distribution pattern showed that LjCAD shared a closer evolutionary relationship with AtCAD.
Phylogenetic relationship among MtCAD, LjCAD, AtCAD, OsCAD, SbCAD, HvCAD and BdCAD were classified into 7 groups (A-I). Each group shows distinct colors and shapes. The candidate MtCAD and LjCAD was labeled with red and green star, respectively. Whereas AtCAD was labeled as parallelogram with orange color, SbCAD with magenta circle, OsCAD with purple plus HvCAD with green rectangle and BdCAD with blue diamond.
3.3. Conserved motif, domain, and gene structure analysis of MtCAD and LjCAD
In this study, 10 highly conserved motifs were analyzed for both MtCAD and LjCAD. The highest number of motifs (9) were found in both MtCAD and LjCAD (MtCAD1, MtCAD3, MtCAD4, MtCAD18, MtCAD19, MtCAD20, MtCAD21, MtCAD22, MtCAD23, MtCAD25, MtCAD26, MtCAD27, MtCAD28, MtCAD30, MtCAD31, MtCAD46, MtCAD47, LjCAD2, LjCAD6, LjCAD8, LjCAD9, LjCAD10, LjCAD17, LjCAD22, LjCAD29, LjCAD33, and LjCAD35). On the other hand, MtCAD51 contains the lowest number of motif (1) (S2 Fig A). Meanwhile, the minimum number of motif was present in LjCAD19 (2) (S2 Fig B). These conserved regions are critical for maintaining the catalytic of CAD proteins. Notably, the conserved domain analysis identified ADH_N domain along with ADH_zinc_ N domain (except MtCAD29 and MtCAD51) that were present in both MtCAD and LjCAD (S3 Fig A and B). Accordingly, the gene structure analysis revealed the presence of intron in 49 MtCAD genes (except MtCAD50 and MtCAD51) (Fig 2 A). Whereas, all the LjCAD genes contained intron (Fig 2 B). The highest number of introns in MtCAD and LjCAD were 18 and 17, respectively (S6 Data in S1 File).
A. MtCAD chromosome is shown in purple color. B. LjCAD chromosome is shown in light green color. The chromosome number is at the top of each chromosome bar. The millions of bases (Mb) indicate the length of each chromosome on the left.
3.4. Chromosomal localization, collinearity, and synteny analysis of MtCAD and LjCAD
The 51 MtCAD were distributed across 8 chromosomes (S4 Fig A), while the 35 LjCAD genes were distributed on 6 chromosomes (S4 Fig B). This distribution showed that the highest number of MtCAD (15) were located on chromosome 5. Meanwhile, the highest number of LjCAD (10) were present on chromosome 1. Notably, three scaffold chromosome in MtCADs (MtCAD49, MtCAD50 and MtCAD51) and 1 contig chromosome in LjCAD (LjCAD35) were found.
Additionally, 12 collinear pairs of MtCAD and 8 collinear pairs of LjCAD were identified in this analysis. In M. truncatula, chromosomes 3, 5, and 7 participated most frequently in forming collinear gene pairs with other chromosomes (S5 Fig A). Chromosome 1 and chromosome 2 also formed collinear pairings more frequently compared to the remaining chromosomes. For example, MtCAD2 on chromosome 1 paired with MtCAD42 on chromosome 7, MtCAD8 on chromosome 3 paired with MtCAD33 on chromosome 5, and MtCAD3 on chromosome 1 paired with MtCAD29 on chromosome 5. On the other hand, LjCAD10 on chromosome 1 paired with LjCAD21 on chromosome 3, LjCAD12 on chromosome 2 paired with LjCAD21 on chromosome 3, and LjCAD25 on chromosome 4 paired with LjCAD32 on chromosome 6 (S5 Fig B).
The syntenic analysis further revealed that MtCAD genes formed 15 pairs with A. thaliana, 1 pair with O. sativa, and 1 pair with Z. mays (Fig 3 A). Meanwhile, LjCAD had 16 pairs with A. thaliana, 2 pairs with O. sativa, and 2 pairs with Z. mays (Fig 3 B). The pairing concluded that LjCAD had a closer relationship with Arabidopsis.
A. The synteny of M. truncatula with A. thaliana, O. sativa, and Z. mays. The green, magenta, yellow, and orange rectangles represent M. truncatula, A. thaliana, O. sativa, and Z. mays, respectively. B. The synteny of L. japonicas with A. thaliana, O. sativa, and Z. mays. The red, green, sky blue, and purple rectangles represent L. japonicas, A. thaliana, O. sativa, and Z. mays, respectively. The blue color line indicates a syntenic relationship between the species.
3.5. Gene duplication, time divergence, and Ka/Ks ratio calculation of MtCAD and LjCAD
In this analysis, 12 pairs of duplicated genes were found in MtCAD, while 8 pairs of duplicated genes were found in LjCAD (S7 Data in S1 File). Additionally, 4 segmental and 6 tandem duplications were exhibited in MtCAD. Whereas, 5 segmental and 3 tandem duplications were found in LjCAD. In MtCAD, the evolutionary time divergence varied from 6.080145846 MYA (MtCAD43-MtCAD44) to 77.80829779 MYA (MtCAD3-MtCAD29) (S6 Fig A). In LjCAD, it ranged from 8.029178047 MYA (LjCAD5-LjCAD6) to 48.70931528 MYA (LjCAD11-LjCAD14) (S6 Fig B). The Ka/Ks ratios of all duplicated gene pairs were less than 1 in both the species. Thus, it indicated that these genes have predominantly evolved under purifying selection. This further suggested that selective pressure has acted to maintain the functional conservation of duplicated CAD genes during evolution.
3.6. Prediction of subcellular localization and cis-acting regulatory elements (CARE) in MtCAD and LjCAD
Subcellular localization prediction suggested that MtCAD proteins might distribute across several cellular compartments including the nucleus, mitochondria, cytoplasm, chloroplast, peroxisome, cytoskeleton, Golgi apparatus, vacuole, endoplasmic reticulum, plasma membrane, and extracellular space (S7 Fig A). However, the majority of MtCAD proteins (92.16%) were predicted to localize in the cytoplasm (S7 Fig B). Similarly, most LjCAD proteins (85.71%) were predicted to be cytoplasmic (S7 Fig C) while a smaller proportion showed potential localization signals for other compartments, including the chloroplast (S7 Fig D). These results suggested that cytoplasmic localization is the predominant prediction for CAD proteins in both species whereas other predicted localizations might represent secondary or lower-confidence signals.
CARE analysis included 60 motifs of MtCAD and 56 motifs of LjCAD that were classified into 4 groups, such as light responsiveness (LR), tissue-specific expression, phytohormone responsiveness (PR), and stress responsiveness (SR) (S8 Data in S1 File). The majority of MtCAD and LjCAD motifs were associated with light responsiveness. In both MtCAD and LjCAD, the Box 4 motif was present predominantly (Fig 4 A and B). Several stress and hormone responsive elements were also widely distributed including ARE and ABRE motifs which are commonly associated with anaerobic and abscisic acid-mediated stress responses. In addition, TGACG-motif and CGTCA-motif (MeJA-responsive elements) as well as GT1-motif, G-box, and WUN-motif were identified in multiple CAD promoters. This suggested potential regulatory roles in stress signaling and defense responses.
A. Color bar of MtCAD CARE (black = 0, green = 1–2, blue = 2-4, red = 4-6, and yellow = 6-8) is illustrated. B. Different colors (black = 0, green = 1–2, yellow = 2-4, red = 4-6, magenta = 6-8, blue = 8-10) of LjCAD is illustrated, Functions associated with CAREs are shown at the bottom of the heat map.
3.7. Gene Ontology (GO), Protein-Protein Interaction (PPIs), KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway analysis of MtCAD and LjCAD
In the gene ontology, 40 and 48 GO annotations were identified in MtCAD and LjCAD grouped into 3 categories: biological process (BP), cellular component (CC), and molecular function (MF) (S9 Data in S1 File). In MtCAD, most genes were associated with biological processes related to oxidation-reduction reactions and metabolic processes (Fig 5 A). In contrast, LjCAD genes were mainly enriched in molecular functions such as oxidoreductase activity and ion binding (Fig 5 B).
A. Different color bar represents different function. The higher bar, the more the MtCAD genes are present. B. Different color bar represents different function. The higher bar, the more the LjCAD genes are present.
The PPI showed that MtCAD18, MtCAD20, MtCAD21, MtCAD22, MtCAD25, MtCAD26, MtCAD27, MtCAD28, MtCAD30, and MtCAD31 exhibited higher interactions with CAD7 (S8 Fig A). Furthermore, CAD7 interacted with CAD1–2, PDC3, PER48, CAD8, PDC4, and SDH (S10 Data in S1 File). Meanwhile, LjCAD showed strong interactions with ADH1, which, in turn, interacted with F2K13.90 and PDC3 (S8 Fig B).
KEGG pathway mapping highlighted that both MtCAD and LjCAD genes were involved in several metabolic pathways, including fatty acid degradation, tyrosine metabolism, glycolysis/gluconeogenesis, phenylpropanoid biosynthesis, and the biosynthesis of secondary metabolites (S11 Data). Among these, the phenylpropanoid biosynthesis pathway is particularly relevant because it included key reactions involved in lignin production. Some pathways are species specific as MtCADs were associated with valine, leucine, and isoleucine degradation, arginine and proline metabolism, tryptophan metabolism, glycerolipid metabolism, and alpha-linolenic acid metabolism (Fig 6 A) while LjCADs participated in limonene and pinene degradation, histidine metabolism, lysine degradation, beta-alanine metabolism, pyruvate metabolism, and carbon metabolism (Fig 6 B).
A. The metabolic pathway of the MtCAD. The p-value range and number of gene count in small to large round are represented in the right side. B. The metabolic pathway of the LjCAD. The p-value range and number of gene count in small to large round are represented in the right side.
3.8. Transcription factors and regulatory network analysis of MtCAD and LjCAD
In MtCAD and LjCAD, a total of 103 and 102 unique TFs were predicted correspondingly. About 7 TFs were predominantly found in both species. In MtCAD, the major TF families included ERF, MYB, bZIP, NAC, LBD, GATA, and Nin-like (S9 Fig A), whereas ERF, NAC, MYB, bHLH, MIKC_MADS, LBD, and GATA were identified in LjCAD (S9 Fig B). The largest family found in both MtCAD and LjCAD was ERF. For example, ERF members such as Medtr5g008590, Medtr8g092460, Medtr3g072610, Medtr5g083340, and Medtr2g015050 were associated with multiple MtCAD genes, while Lj6g3v0841450, Lj6g3v2007040, Lj2g3v2113110, Lj6g3v2006220, Lj0g3v0114779, and Lj2g3v1989210 were predicted to interact with several LjCAD. The ERF family showed the highest number of predicted interactions, potentially regulating 36 MtCAD and 28 LjCAD genes (S10 Fig A and B).
3.9. Prediction of putative micro-RNAs targeting MtCAD and LjCAD
A total of 510 and 21 mature miRNAs were predicted to target 49 MtCAD and 12 LjCAD genes, respectively (S12 Data in S1 File). Among them, mtr-miR2086-5p targeted the largest number of MtCAD genes, including MtCAD9, MtCAD10, MtCAD11, MtCAD16, MtCAD19, MtCAD20, MtCAD32, MtCAD43, and MtCAD44 (S8 Fig A). Some miRNA such as mtr-miR169c targeted MtCAD21, MtCAD22, MtCAD26, MtCAD27, MtCAD28, MtCAD31, MtCAD43, and MtCAD44 and mtr-miR2592a-3p also targeted MtCAD30, MtCAD34, MtCAD35, MtCAD9, MtCAD10, and MtCAD50). Likewise, in LjCAD, lja-miR7533a targeted LjCAD15 and LjCAD16, while the rest of the miRNAs targeted one specific LjCAD (S11 Fig B). These predicted interactions suggest possible post-transcriptional regulation of CAD genes by miRNAs in both species.
3.10. Tissue-specific and various abiotic stress treatment expression in MtCAD and LjCAD
In this analysis, the expression of MtCAD in different tissues such as bud, nodule, blade, open flower, root, and seed pod, while the expression of LjCAD in immature flower, mature flower, seed pod, seed, root, and leaf had been studied (S13 Data in S1 File, Fig 7 A and B). For each gene, the tissue showing the highest observed expression was identified. In MtCAD, MtCAD25 exhibited the highest expression in buds, MtCAD27 in open flowers, and MtCAD28 in blades. Root-associated expression was observed for MtCAD3, MtCAD6, and MtCAD9, which showed their highest expression in roots and nodules. In LjCAD, the highest observed expression was detected in immature flowers for LjCAD23 and in mature flowers, seeds, and roots for several other genes, including LjCAD30 and LjCAD32. These observations indicate the tissues where CAD genes might be preferentially expressed. These results represent indicative tissue-specific expression trends.
A. A heat map representing the tissue expression pattern in MtCAD is shown. B. A heat map representing the tissue expression pattern in LjCAD is shown. Various tissues are at the bottom of the heat map. The color bar represents the intensity of the expression.
The expression in various abiotic stressors were carried out to the expression pattern in both MtCAD and LjCAD (S14 Data in S1 File, Fig 8 A and B). In MtCAD, cold stress induced higher transcript levels in MtCAD1, MtCAD3, MtCAD8, MtCAD9, MtCAD10, MtCAD11, MtCAD13, MtCAD15, MtCAD19, MtCAD20, MtCAD23, MtCAD25, MtCAD26, MtCAD27, MtCAD31, MtCAD34, MtCAD39, MtCAD46 and MtCAD47 suggested their role as cold-responsive candidate genes pending functional validation. Some genes also exhibited highly during freezing stress such as, MtCAD1, MtCAD2, MtCAD3, MtCAD4, MtCAD5, MtCAD6, MtCAD9, MtCAD10, MtCAD11, MtCAD13, MtCAD15, MtCAD19, MtCAD20, MtCAD23, MtCAD25, MtCAD26, MtCAD27, MtCAD32, MtCAD36, MtCAD41, MtCAD46, MtCAD48, and MtCAD51. During drought stress, a subset of MtCAD genes, including MtCAD1, MtCAD2, MtCAD3, MtCAD4, MtCAD5, MtCAD6, MtCAD7, MtCAD9, MtCAD10, MtCAD11, MtCAD12, MtCAD14, MtCAD15, MtCAD17, MtCAD18, MtCAD19, MtCAD23, MtCAD24, MtCAD26, MtCAD27, MtCAD28, MtCAD30, MtCAD33, MtCAD37, MtCAD42, MtCAD43, MtCAD46, MtCAD47, and MtCAD48 showed higher transcript levels compared to control. In salt stress, MtCAD1, MtCAD4, MtCAD5, MtCAD6, MtCAD7, MtCAD8, MtCAD9, MtCAD10, MtCAD11, MtCAD12, MtCAD15, MtCAD17, MtCAD18, MtCAD19, MtCAD20, MtCAD25, MtCAD26, MtCAD28, MtCAD32, MtCAD33, MtCAD37, MtCAD41, MtCAD42, MtCAD45, MtCAD47, MtCAD48, and MtCAD49 showed up regulation. Lastly, MtCAD1, MtCAD4, MtCAD6, MtCAD7, MtCAD10, MtCAD17, MtCAD19, MtCAD26, MtCAD27, MtCAD28, MtCAD32, MtCAD33, MtCAD37, MtCAD38, MtCAD42, MtCAD45, MtCAD47, and MtCAD48 showed during ABA treatment.
A. A heat map representing different stressed expression in MtCAD is shown. B. A heat map representing different stressed expression in LjCAD is shown. The bottom of the heat map contains levels of treatment and color bar represents the intensity of expression.
In LjCAD, cold stress led to treatment-induced increases in transcript levels in LjCAD2, LjCAD4, LjCAD5, LjCAD6, LjCAD8, LjCAD9, LjCAD11, LjCAD13, LjCAD16, LjCAD17, LjCAD19, LjCAD22, LjCAD23, LjCAD28, LjCAD29, LjCAD30, LjCAD31, LjCAD33, and LjCAD35. Heat stress induced higher expression in LjCAD1, LjCAD4, LjCAD6, LjCAD7, LjCAD8, LjCAD9, LjCAD11, LjCAD19, LjCAD20, LjCAD24, LjCAD29, LjCAD32, and LjCAD34. Under drought stress, LjCAD2, LjCAD4, LjCAD5, LjCAD6, LjCAD7, LjCAD8, LjCAD9, LjCAD10, LjCAD11, LjCAD13, LjCAD15, LjCAD16, LjCAD17, LjCAD19, LjCAD20, LjCAD21, LjCAD22, LjCAD23, LjCAD24, LjCAD25, LjCAD27, LjCAD28, LjCAD29, LjCAD30, LjCAD31, LjCAD32, LjCAD33, LjCAD34, and LjCAD35 showed treatment-induced increases. NaCl stress also induced higher transcript levels in LjCAD1, LjCAD2, LjCAD3, LjCAD8, LjCAD9, LjCAD11, LjCAD13, LjCAD16, LjCAD27, LjCAD28, LjCAD29, LjCAD32, LjCAD33, LjCAD34, and LjCAD35. These results indicated potential stress-responsive CAD genes but functional validation is further necessary to confirm their roles in stress tolerance.
4. Discussion
Both ADH_N domain and ADH_zinc_N domain are crucial for the overall structure and function of cinnamyl alcohol dehydrogenase [54]. The structural integrity is maintained as the ADH_N domain functions as the catalytic core, while the ADH_zinc_N domain contributes to metal ion stabilization [55]. ADH_N is a GroES-like domain and is potentially involved in structural stabilization [56]. Legumes are exposed to various abiotic stresses such as cold, heat, drought and salinity stress. Under these stress conditions, CAD genes are upregulated to maintain efficient catalytic activity [57]. The larger number of CADs in M. truncatula compared with L. japonicus suggests possible differences in environmental adaptation. The physiochemical properties of MtCAD and LjCAD proteins unveiled that the longer amino acid sequences observed in LjCAD proteins may contribute to greater structural complexity compared with MtCAD proteins. Higher number of acidic protein indicated the enzymatic activity [58]. The instability index analysis highlighted that a majority of CAD proteins in both species were stable (39 MtCAD and 31 LjCAD), with M. truncatula displaying a slightly higher proportion of stable proteins [59].
A significant expansion in CAD proteins revealed through the largest group C based on the evolutionary phylogenetic tree. This reflects adaptive evolution linked to secondary cell wall formation, stress responses, or symbiotic interactions, which are critical for legume biology [60, 61]. Meanwhile, the smaller groups E and F exhibited strong purifying selection. Notably, LjCAD had a closer evolutionary relationship with A. thaliana compared with M. truncatula due to its position in phylogenetic tree. Therefore, despite both being legumes, they had different structure, function and regulatory mechanisms [62]. The closer affinity of LjCAD with AtCAD is due to shared evolutionary pressures, gene retention patterns, or functional constraints [63, 64].
The identification of nine major conserved motifs suggested that these regions are essential for proper protein folding and functional activity. In contrast, the presence of only a single motif in MtCAD51 may indicate functional specialization or divergence [65, 66]. Further analysis of major ADH_N and ADH_zinc_N domains revealed their contribution in alcohol dehydrogenase-like catalytic activity and zinc ion binding [67, 68]. A notable finding of introns in 49 out of 51 MtCAD and 35 LjCAD indicated their role in gene regulation and alternative splicing. Ultimately, the conservation of domain and motif regulates lignin biosynthesis in legumes [69, 70].
The clustering of MtCAD mostly on chromosome 5 (15 genes) and LjCAD on chromosome 1 (10 genes) along with 3 MtCAD (MtCAD49, MtCAD50, and MtCAD51) on scaffolds and 1 LjCAD (LjCAD35) on contig showed the exact locations of CADs. Further, identification of 12 collinear pairs in MtCAD and 9 collinear pair in LjCAD provided strong evidence for the structural conservation [71, 72]. Synteny analysis between MtCAD and LjCAD genes with other species provided their evolutionary relationships. It confirmed the closer evolutionary relationship of LjCAD compared to MtCAD. Previously, comparative genomic studies have demonstrated that conserved syntenic relationships among gene families reflect shared ancestry and functional conservation during plant evolution, particularly for genes involved in lignin biosynthesis and secondary cell wall formation [73, 74].
Gene duplication plays a key role in the expansion of gene families and contributes to functional redundancy, diversification, and environmental adaptation [75]. In this study, 12 pairs of duplicated gene in MtCAD and 9 pairs in LjCAD revealed both segmental and tandem pairs. The broad divergence times (between 6.08 MYA and 77.81 MYA in MtCAD and between 8.03 MYA and 48.71 MYA in LjCAD) indicated continuous CAD duplication [76]. Selective pressure analysis based on the nonsynonymous-to-synonymous substitution ratio (Ka/Ks) found to be less than 1 indicating purifying selection [77, 78]. This pattern suggested that duplicated CAD genes may retain conserved biological functions and that deleterious mutations have been removed through evolutionary constraints.
Subcellular localization analysis suggested that most MtCAD and LjCAD proteins are predicted to localize in the cytoplasm. This observation is consistent with the known role of CAD enzymes in the final steps of monolignol biosynthesis which primarily occur in the cytosol before monolignols are transported to the cell wall for lignin polymerization [79]. A smaller proportion of proteins were predicted to localize to other cellular compartments such as the chloroplast where specialized biosynthetic processes and secondary metabolism occurred [80]. But, experimental validation would be further required to confirm the precise cellular localization of these CAD proteins.
Cis-acting regulatory elements in promoter regions play an important role in controlling gene expression under environmental and hormonal stimuli [81]. In this study, a large number of light-responsive elements were identified in both MtCAD and LjCAD, suggesting that CAD genes may be transcriptionally regulated by light signals. These are known to influence lignin biosynthesis and plant development. The presence of ABRE and ARE elements indicates possible regulation by abscisic acid signaling and anaerobic stress conditions [82]. Furthermore, the detection of MeJA-responsive motifs (TGACG-motif and CGTCA-motif) and wound-responsive elements such as WUN-motif suggests that CAD genes may participate in plant defense and stress adaptation pathways [83]. These promoter regions ensure that CAD gene expression could be modulated by multiple environmental cues and hormonal signals.
Gene Ontology annotation suggested that most CAD proteins in both species, MtCAD and LjCAD, are associated with oxidoreductase activity and metabolic processes which is consistent with the enzymatic role of CAD in catalyzing the reduction of cinnamaldehydes to their corresponding alcohols during monolignol biosynthesis [84]. This particular function is relevant with the phenylpropanoid metabolic pathway for production of lignin and other secondary metabolites in plants [85].
PPI has crucial role in species diversification and cellular activity regulation [86, 87]. It revealed interactions between MtCAD, LjCAD, and Arabidopsis proteins showing their involvement in primary and secondary metabolism. MtCAD exhibited interactions with AtCAD7, while LjCAD showed strong interactions with AtADH1.
KEGG analysis further supported the functional role by linking several CAD genes to the phenylpropanoid biosynthesis pathway as well as to broader secondary metabolic pathways [88, 89]. These pathways are known to contribute to plant structural integrity, stress tolerance, and defense responses. Based on previous study, CAD enzymes catalyze the final step of lignin monomer biosynthesis within the phenylpropanoid pathway [74]. Although additional metabolic pathways were also detected, these associations may reflect the broader metabolic context of oxidoreductase enzymes rather than direct involvement in those pathways [90, 91]. Therefore, the presence of CAD genes in phenylpropanoid and secondary metabolite biosynthesis pathways provided the most biologically relevant functional insight.
Transcriptional and post-transcriptional control mechanisms are associated with TFs [92]. Several TF families were predicted to be associated with CAD genes, including ERF, MYB, NAC, bZIP, and bHLH. These TF families have previously been reported to participate in lignin biosynthesis and secondary cell wall formation in plants. For example, MYB and NAC transcription factors are well-established regulators of lignin biosynthetic pathways, while ERF family members have also been implicated in stress-induced lignin accumulation [93, 94]. Therefore, the predicted TF-CAD regulatory network may reflect potential regulatory mechanisms controlling CAD expression.
MicroRNAs are important regulators of gene expression in plants and frequently control genes involved in development, stress responses, and secondary metabolism [95]. A larger number of miRNAs were predicted to target MtCAD genes (510 miRNAs targeting 49 genes) compared with LjCAD (21 miRNAs targeting 12 genes), suggesting potentially more complex post-transcriptional regulation in M. truncatula. Several miRNAs were predicted to regulate multiple CAD genes. This indicated that certain miRNAs may coordinate the regulation of lignin biosynthesis-related genes. Previous studies have shown that miRNAs can modulate stress-responsive pathways and secondary cell wall formation, processes closely associated with lignin metabolism [96]. However, the regulatory relationships identified require experimental validation.
Plants use tissue-specific gene expression as their fundamental biological mechanism to optimize their responses to stress through activating stress-responsive genes in particular cells or tissues [97, 98]. Tissue-specific expression patterns provided understanding the roles in plant growth, development, and organ differentiation [99]. For instance, the high expression of MtCAD25 in buds and LjCAD23 in immature flowers suggested their involvement in early reproductive development, while the highest expression of MtCAD3 and MtCAD9 in roots indicated functions related to nutrient uptake and stress adaptation. Expression analysis of PoptrCAD genes revealed that they expressed in leaves, petioles, bark, and xylem, although their expression levels varied among these tissues. For instance, PoptrCAD7 showed relatively higher expression in leaves and petioles but exhibited very low expression in bark and xylem [100]. Some genes including MtCAD42 and MtCAD47 showed relatively high expression across multiple tissues suggesting broader metabolic or structural functions.
Under cold stress, 12 MtCAD and 13 LjCAD genes exhibited increased transcript levels and suggested their potential involvement in cold-responsive metabolic pathways, cellular protection mechanisms, and regulatory networks. In pepper, CaCAD1 expression increased under low temperature and it contributed to lignin biosynthesis and cold stress response [101].
Among these, MtCAD27 and LjCAD11 showed the highest transcript accumulation, indicating particularly strong cold-responsive behavior. During drought stress, 29 MtCAD and 30 LjCAD genes showed increased expression, with MtCAD10 and LjCAD16 displaying the largest treatment-induced regulation. In melon, drought stress significantly induced the expression of CmCAD genes and promoted lignin biosynthesis in stems [102]. Increased expression of CAD genes under drought has also been associated with enhanced lignin accumulation and improved stress adaptation in several plant species [103]. Under freezing stress, among 24 increased level of expression of MtCAD genes, MtCAD10 exhibited the highest transcript levels. Similarly, under salt stress, MtCAD11 showed the most significant increase while ABA treatment induced maximal expression in MtCAD28. In LjCAD, LjCAD11 showed the highest treatment-induced expression under both heat and NaCl stress. These findings highlight stress-responsive candidates but functional validation is required to confirm their roles in stress tolerance.
5. Conclusion
The comparative genome-wide study of 51 MtCAD and 35 LjCAD provided valuable insights into their role under different abiotic stresses. All the MtCAD and LjCAD proteins contained ADH_N domain. Evolutionary analysis with A. thaliana indicated a closer association of LjCAD genes with AtCAD and thus it reflected shared evolutionary pressures. The subcellular localization indicated that majority of MtCAD and LjCAD were found in chloroplast. Furthermore, MtCAD and LjCAD genes were unevenly distributed across eight and six chromosomes, respectively, exhibiting distinct exon-intron structures and gene lengths. Purifying selection was observed across all MtCAD and LjCAD genes, consistent with their conserved evolutionary relationships. Functional annotations revealed the role of MtCAD in oxidation-reduction process along with the role of LjCAD in oxidoreductase activity. ERF was the largest TF found in both MtCAD and LjCAD. The expression revealed the increased transcript level in MtCAD1, MtCAD3, MtCAD9, MtCAD15, MtCAD23, MtCAD27, and MtCAD47 under cold, drought and freezing stress and LjCAD6, LjCAD8, and LjCAD11 under cold, drought and heat stress. These patterns indicated that these genes are potential stress-responsive candidates under multiple abiotic conditions. Such findings will provide a basis for future studies and breeding programs for developing plants with improved stress resilience.
Supporting information
S1 File. S1 Data.
Phylogenetic tree sequences of CAD proteins. S2 Data. 2000 bp sequences of MtCAD and LjCAD gene families. S3 Data. Peptide sequences of MtCAD and LjCAD. S4 Data. CDS of MtCAD and LjCAD. S5 Data. Genomic sequences of MtCAD and LjCAD. S6 Data. Exon and intron counts of MtCAD and LjCAD.S7 Data. KaKs ratio of MtCAD and LjCAD. S8 Data. CARE of MtCAD and LjCAD. S9 Data. GO of MtCAD and LjCAD. S10 Data. PPI of MtCAD and LjCAD. S11 Data. PPI of MtCAD and LjCAD. S12 Data. MicroRNA of MtCAD and LjCAD. S13 Data. Tissue specific expression of MtCAD and LjCAD. S14 Data. Abiotic stress expression of MtCAD and LjCAD.
https://doi.org/10.1371/journal.pone.0353726.s001
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S1 Fig. Phylogenetic distribution of the CAD.
https://doi.org/10.1371/journal.pone.0353726.s002
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S2 Fig. A. Different colors indicate individual motifs for MtCAD.
B. Specific-colored box aligned on the right side of the figure shows 10 different motifs. Different colors indicate individual motifs for LjCAD.
https://doi.org/10.1371/journal.pone.0353726.s003
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S3 Fig. A. The purple box illustrates the conserved domain, whereas the blue box illustrates entire protein of respective MtCAD.
B. The blue box illustrates the conserved domain, whereas the green box illustrates entire protein of respective MtCAD.
https://doi.org/10.1371/journal.pone.0353726.s004
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S4 Fig. A. The black lines represent introns, blue represents exons, and green lines represent upstream/downstream region.
B. The black lines represent introns, blue represents exons, and deep pink lines represent upstream/downstream region.
https://doi.org/10.1371/journal.pone.0353726.s005
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S5 Fig. A. Orange color rectangles represent chromosomes 1–8. Scf represents scaffold chromosome.
B. The collinear relationship of the LjCAD. Green rectangles represent chromosomes 1–6. Contig represents contiguous chromosome. The dark blue lines represent collinear relations between them.
https://doi.org/10.1371/journal.pone.0353726.s006
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S6 Fig. A. The Ka/Ks of MtCAD represents the ratio of Ka to Ks, with divergence time (measured in million years ago, MYA).
B. The Ka/Ks of LjCAD represents the ratio of Ka to Ks, with divergence time (measured in million years ago, MYA). The color bar represents the range of value.
https://doi.org/10.1371/journal.pone.0353726.s007
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S7 Fig. A. The absence and presence of the respective MtCAD genes in various organelles are shown.
B. The percentage of MtCAD gene location across various cellular organelles is represented by a deep purple bar diagram. C. The absence and presence of the respective LjCAD genes in various organelles are shown. D. The percentage of LjCAD gene location across various cellular organelles is represented by a deep blue diagram.
https://doi.org/10.1371/journal.pone.0353726.s008
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S8 Fig. A. The MtCAD protein-protein interaction displayed at network nodes with the proteins in nodes, and the line colors indicate different data sources.
B. The LjCAD protein- protein interaction displayed at network nodes with the proteins in nodes, and the line colors indicate different data sources.
https://doi.org/10.1371/journal.pone.0353726.s009
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S9 Fig. A. The heat map represents transcription factors (TFs) in MtCAD. The orange box on the right side of the heat map indicates the presence of TFs in genes.
B. The heat map represents transcription factors (TFs) in LjCAD. The green box on the right side of the heat map indicates the presence of TFs in genes.
https://doi.org/10.1371/journal.pone.0353726.s010
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S10 Fig. A. This figure shows the interactions between different TFs and MtCAD gene. On the right side of the figure, the color representation is shown. B.
This figure shows the interactions between different TFs and LjCAD gene. On the right side of the figure, the color representation is shown.
https://doi.org/10.1371/journal.pone.0353726.s011
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S11 Fig. A. The purple round rectangle represents the exons of the MtCAD gene, straight black line represents intron and red color small round rectangle represents microRNA (miRNA).
B. The blue round rectangle represents the exons of the LjCAD gene, straight black line represents intron and red color small round rectangle represents microRNA (miRNA).
https://doi.org/10.1371/journal.pone.0353726.s012
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Acknowledgments
The authors are very grateful to the Laboratory of Functional Genomics and Proteomics, Department of Genetic Engineering and Biotechnology, Faculty of Biological Science and Technology, Jashore University of Science and Technology, Jashore 7408, Bangladesh for providing the opportunity to conduct this research. The authors acknowledge and appreciate the reviewers and the members of the editorial panel for their valuable comments and critical suggestions for improving the quality of this manuscript.
References
- 1. Feuillet C, Lauvergeat V, Deswarte C, Pilate G, Boudet A, Grima-Pettenati J. Tissue- and cell-specific expression of a cinnamyl alcohol dehydrogenase promoter in transgenic poplar plants. Plant Mol Biol. 1995;27(4):651–67. pmid:7727744
- 2. Wang L, Sun G, Wang J, Zhu H, Wu Y. Systematic characterization of cinnamyl alcohol dehydrogenase members revealed classification and function divergence in Haplomitrium mnioides. J Plant Res. 2025;138(1):173–87. pmid:39609336
- 3. Yadav V, Wang Z, Wei C, Amo A, Ahmed B, Yang X, et al. Phenylpropanoid Pathway Engineering: An Emerging Approach towards Plant Defense. Pathogens. 2020;9(4):312. pmid:32340374
- 4. Zhu Z, Chen R, Zhang L. Simple phenylpropanoids: recent advances in biological activities, biosynthetic pathways, and microbial production. Nat Prod Rep. 2024;41(1):6–24. pmid:37807808
- 5. Li H, Zhang S, Zhao Y, Zhao X, Xie W, Guo Y, et al. Identification and Characterization of Cinnamyl Alcohol Dehydrogenase Encoding Genes Involved in Lignin Biosynthesis and Resistance to Verticillium dahliae in Upland Cotton (Gossypium hirsutum L.). Front Plant Sci. 2022;13:840397. pmid:35574065
- 6. Ralph J, Lundquist K, Brunow G, Lu F, Kim H, Schatz PF, et al. Lignins: Natural polymers from oxidative coupling of 4-hydroxyphenyl- propanoids. Phytochemistry Reviews. 2004;3(1–2):29–60.
- 7. Vermerris W, Sherman DM, McIntyre LM. Phenotypic plasticity in cell walls of maize brown midrib mutants is limited by lignin composition. J Exp Bot. 2010;61(9):2479–90. pmid:20410320
- 8. Yadav S, Chattopadhyay DJ. Lignin: the building block of defense responses to stress in plants. J Plant Growth Regul. 2023;42(10):6652–66.
- 9. Qi K, Song X, Yuan Y, Bao J, Gong X, Huang X, et al. CAD Genes: Genome-Wide Identification, Evolution, and Their Contribution to Lignin Biosynthesis in Pear (Pyrus bretschneideri). Plants (Basel). 2021;10(7):1444. pmid:34371647
- 10. Youn B, Camacho R, Moinuddin SGA, Lee C, Davin LB, Lewis NG, et al. Crystal structures and catalytic mechanism of the Arabidopsis cinnamyl alcohol dehydrogenases AtCAD5 and AtCAD4. Org Biomol Chem. 2006;4(9):1687–97. pmid:16633561
- 11. Zhang Y, Wu L, Wang X, Chen B, Zhao J, Cui J, et al. The cotton laccase gene GhLAC15 enhances Verticillium wilt resistance via an increase in defence-induced lignification and lignin components in the cell walls of plants. Mol Plant Pathol. 2019;20(3):309–22. pmid:30267563
- 12. Miedes E, Vanholme R, Boerjan W, Molina A. The role of the secondary cell wall in plant resistance to pathogens. Frontiers in Plant Science. 2014;5:358. pmid:25161657
- 13. Qiu P, Zheng B, Yuan H, Yang Z, Lindsey K, Wang Y, et al. The elicitor VP2 from Verticillium dahliae triggers defence response in cotton. Plant Biotechnol J. 2024;22(2):497–511. pmid:37883523
- 14. Xiao S, Hu Q, Shen J, Liu S, Yang Z, Chen K, et al. GhMYB4 downregulates lignin biosynthesis and enhances cotton resistance to Verticillium dahliae. Plant Cell Rep. 2021;40(4):735–51. pmid:33638657
- 15. Rose RJ. Medicago truncatula as a model for understanding plant interactions with other organisms, plant development and stress biology: past, present and future. Funct Plant Biol. 2008;35(4):253–64. pmid:32688781
- 16. Handberg K, Stougaard JJTPJ. Lotus japonicus, an autogamous, diploid legume species for classical and molecular genetics. Plant J. 1992;2(4):487–96.
- 17. Geurts R, Bisseling TJ. Rhizobium nod factor perception and signalling. Plant Cell. 2002;14(suppl_1):S239–49.
- 18. Popp C, Ott TJ. Regulation of signal transduction and bacterial infection during root nodule symbiosis. Curr Opin Plant Biol. 2011;14(4):458–67.
- 19. Friesen ML, von Wettberg EJB, Badri M, Moriuchi KS, Barhoumi F, Chang PL, et al. The ecological genomic basis of salinity adaptation in Tunisian Medicago truncatula. BMC Genomics. 2014;15(1):1160. pmid:25534372
- 20. Pérez-Delgado CM, García-Calderón M, Monje-Rueda MD, Márquez AJ, Betti MJA. Transcriptomic analysis of L. Japonicus symbiosis reveals new candidate genes for local and systemic regulation of nodule function. J Exp Bot. 2020;10(6):819.
- 21. Goodstein DM, Shu S, Howson R, Neupane R, Hayes RD, Fazo J, et al. Phytozome: a comparative platform for green plant genomics. Nucleic Acids Res. 2012;40(Database issue):D1178-86. pmid:22110026
- 22. Letunic I, Khedkar S, Bork PJ. SMART: recent updates, new developments and status in 2020. Nucleic Acids Res. 2021;49(D1):D458–60.
- 23. Lu S, Wang J, Chitsaz F, Derbyshire MK, Geer RC, Gonzales NR. CDD/SPARCLE: the conserved domain database in 2020. Nucleic Acids Research. 2020;48(D1):D265–8.
- 24. Bateman A, Coin L, Durbin R, Finn RD, Hollich V, Griffiths‐Jones S. The Pfam protein families database. Nucleic Acids Research. 2004;32(suppl_1):D138–41.
- 25. Tamura K, Stecher G, Kumar S. MEGA11: Molecular Evolutionary Genetics Analysis Version 11. Molecular Biology and Evolution. 2021;38(7):3022–7. pmid:33892491
- 26. Yang Z. PAML 4: phylogenetic analysis by maximum likelihood. Mol Biol Evol. 2007;24(8):1586–91. pmid:17483113
- 27. Thompson JD, Higgins DG, Gibson TJ. CLUSTAL W: improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position-specific gap penalties and weight matrix choice. Nucleic Acids Res. 1994;22(22):4673–80. pmid:7984417
- 28. Xie J, Chen Y, Cai G, Cai R, Hu Z, Wang H. Tree Visualization By One Table (tvBOT): a web application for visualizing, modifying and annotating phylogenetic trees. Nucleic Acids Res. 2023;51(W1):W587–92. pmid:37144476
- 29. Bailey TL, Johnson J, Grant CE, Noble WS. The MEME Suite. Nucleic Acids Research. 2015;43(W1):W39-49. pmid:25953851
- 30. Kanehisa M, Goto S, Kawashima S, Nakaya A. The KEGG databases at GenomeNet. Nucleic Acids Res. 2002;30(1):42–6. pmid:11752249
- 31. Ren J, Wen L, Gao X, Jin C, Xue Y, Yao X. DOG 1.0: illustrator of protein domain structures. Cell Res. 2009;19(2):271–3. pmid:19153597
- 32. Hu B, Jin J, Guo A-Y, Zhang H, Luo J, Gao G. GSDS 2.0: an upgraded gene feature visualization server. Bioinformatics. 2015;31(8):1296–7. pmid:25504850
- 33. Chen C, Chen H, Zhang Y, Thomas HR, Frank MH, He Y, et al. TBtools: An Integrative Toolkit Developed for Interactive Analyses of Big Biological Data. Mol Plant. 2020;13(8):1194–202. pmid:32585190
- 34. Lynch M, Conery JS. The evolutionary fate and consequences of duplicate genes. Science. 2000;290(5494):1151–5.
- 35. Wang Y, Tang H, Debarry JD, Tan X, Li J, Wang X, et al. MCScanX: a toolkit for detection and evolutionary analysis of gene synteny and collinearity. Nucleic Acids Res. 2012;40(7):e49. pmid:22217600
- 36. Chao J, Li Z, Sun Y, Aluko OO, Wu X, Wang Q, et al. MG2C: a user-friendly online tool for drawing genetic maps. Mol Hortic. 2021;1(1):16. pmid:37789491
- 37.
Horton P, Park K-J, Obayashi T, Nakai K. Protein subcellular localization prediction with WoLF PSORT. In: Proceedings of the 4th Asia-Pacific bioinformatics conference, 2006.
- 38. Rombauts S, Déhais P, Van Montagu M, Rouzé PJ. PlantCARE, a plant cis-acting regulatory element database. Nucleic Acids Research. 1999;27(1):295–6.
- 39.
Team RCJC. R language and environment for statistical computing. R Foundation for Statistical. 2020.
- 40. Tian F, Yang D-C, Meng Y-Q, Jin J, Gao G. PlantRegMap: charting functional regulatory maps in plants. Nucleic Acids Res. 2020;48(D1):D1104–13. pmid:31701126
- 41. Szklarczyk D, Gable AL, Lyon D, Junge A, Wyder S, Huerta-Cepas J, et al. STRING v11: protein-protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets. Nucleic Acids Res. 2019;47(D1):D607–13. pmid:30476243
- 42. Tang D, Chen M, Huang X, Zhang G, Zeng L, Zhang G, et al. SRplot: A free online platform for data visualization and graphing. PLoS One. 2023;18(11):e0294236. pmid:37943830
- 43. Shannon P, Markiel A, Ozier O, Baliga NS, Wang JT, Ramage D, et al. Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res. 2003;13(11):2498–504. pmid:14597658
- 44. Kozomara A, Birgaoanu M, Griffiths-Jones SJ. miRBase: from microRNA sequences to function. Nucleic Acids Research. 2019;47(D1):D155–62.
- 45. Dai X, Zhuang Z, Zhao PX. psRNATarget: a plant small RNA target analysis server (2017 release). Nucleic Acids Res. 2018;46(W1):W49–54. pmid:29718424
- 46. Gao C, Li Z, Zhang H, Li C, Sun H, Li S, et al. Genome-Wide Identification and Characterization of the GASA Gene Family in Medicago truncatula, and Expression Patterns under Abiotic Stress and Hormone Treatments. Plants (Basel). 2024;13(17):2364. pmid:39273848
- 47. Mun T, Bachmann A, Gupta V, Stougaard J, Andersen SU. Lotus Base: An integrated information portal for the model legume Lotus japonicus. Sci Rep. 2016;6:39447. pmid:28008948
- 48. Sun Z, Liu Z, Zhi M, Ran Q, Xue W, Tang Y, et al. Comparative Genomics of Lotus japonicus Reveals Insights into Proanthocyanidin Accumulation and Abiotic Stress Response. Plants (Basel). 2024;13(8):1151. pmid:38674560
- 49. Shu Y, Liu Y, Zhang J, Song L, Guo C. Genome-Wide Analysis of the AP2/ERF Superfamily Genes and their Responses to Abiotic Stress in Medicago truncatula. Front Plant Sci. 2016;6:1247. pmid:26834762
- 50. Bolger AM, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics. 2014;30(15):2114–20. pmid:24695404
- 51. Dobin A, Gingeras TR. Mapping RNA-seq Reads with STAR. Curr Protoc Bioinformatics. 2015;51:11.14.1-11.14.19. pmid:26334920
- 52. Li H, Handsaker B, Wysoker A, Fennell T, Ruan J, Homer N, et al. The sequence alignment/map format and SAMtools. Bioinformatics. 2009;25(16):2078–9.
- 53. Li B, Dewey CN. RSEM: Accurate transcript quantification from RNA-Seq data with or without a reference genome. BMC Bioinformatics. 2011;12:1–16.
- 54. Eom HS, Kim H, Hyun KT. The cinnamyl alcohol dehydrogenase (CAD) gene family in flax (Linum usitatissimum L.): Insight from expression profiling of cads induced by elicitors in cultured flax cells. AoB Plants. 2016;68(3):603–12.
- 55. Zhang H, Wang S, Li O, Zeng C, Liu X, Wen J, et al. Genome-wide identification of alcohol dehydrogenase (ADH) gene family in oilseed rape (Brassica napus L.) and BnADH36 functional verification under salt stress. BMC Plant Biol. 2024;24(1):1013. pmid:39465389
- 56. Wang R, Du C, Gu G, Zhang B, Lin X, Chen C, et al. Genome-wide identification and expression analysis of the ADH gene family under diverse stresses in tobacco (Nicotiana tabacum L.). BMC Genomics. 2024;25(1):13. pmid:38166535
- 57. Yadav S, Gaikwad AB, Kalwan G, Sharma L, Jain P. The emerging trends and prospects of DNA methylomics for abiotic stress tolerance in legumes. J Biotechnol. 2025;:1–17.
- 58. Frieden C. Protein-protein interaction and enzymatic activity. Annu Rev Biochem. 1971;40:653–96. pmid:4399448
- 59. Gamage DG, Gunaratne A, Periyannan GR, Russell TG. Applicability of Instability Index for In vitro Protein Stability Prediction. Protein Pept Lett. 2019;26(5):339–47. pmid:30816075
- 60. Colbert JB, Coleman HDJ. Functional diversification and the plant secondary cell wall. J Mol Evol. 2023;91(6):761–72.
- 61. Zhang J, Xie M, Tuskan GA, Muchero W, Chen J-G. Recent Advances in the Transcriptional Regulation of Secondary Cell Wall Biosynthesis in the Woody Plants. Front Plant Sci. 2018;9:1535. pmid:30405670
- 62. López M, Tejera NA, Lluch CJA. Differential strategies of the model legumes Lotus japonicus and Medicago truncatula in the adaptation to salt stress: Photosynthetic and nutritional responses. AJoPP. 2008;3(3):121–30.
- 63. Guo DM, Ran JH, Wang XQ. Evolution of the cinnamyl/sinapyl alcohol dehydrogenase (CAD/SAD) gene family: the emergence of real lignin is associated with the origin of bona fide CAD. Journal of Molecular Evolution. 2010;71:202–18.
- 64. Sun Z, Liu Z, Zhi M, Ran Q, Xue W, Tang Y, et al. Comparative Genomics of Lotus japonicus Reveals Insights into Proanthocyanidin Accumulation and Abiotic Stress Response. Plants (Basel). 2024;13(8):1151. pmid:38674560
- 65.
Horan K, Shelton CR, Girke TJ. Predicting conserved protein motifs with Sub-HMMs. 2010;11:1–15.
- 66. Mackenzie CO, Grigoryan GJ. Protein structural motifs in prediction and design. J Coisb. 2017;44:161–7.
- 67.
Wang R, Du C, Gu G, Zhang B, Lin X, Chen C. Genome-wide identification and expression analysis of the ADH gene family in tobacco (Nicotiana tabacum L.). 2023.
- 68. Li T, Luo W, Du C, Lin X, Lin G, Chen R, et al. Functional and evolutionary comparative analysis of the DIR gene family in Nicotiana tabacum L. and Solanum tuberosum L. BMC Genomics. 2024;25(1):671. pmid:38970011
- 69. Tognacca RS, Rodríguez FS, Aballay FE, Cartagena CM, Servi L, Petrillo E. Alternative splicing in plants: current knowledge and future directions for assessing the biological relevance of splice variants. J Exp Bot. 2023;74(7):2251–72. pmid:36306285
- 70. Wang J, Feng J, Jia W, Fan P, Bao H, Li S, et al. Genome-Wide Identification of Sorghum bicolor Laccases Reveals Potential Targets for Lignin Modification. Front Plant Sci. 2017;8:714. pmid:28529519
- 71. Tang H, Bowers JE, Wang X, Ming R, Alam M, Paterson AH. Synteny and collinearity in plant genomes. Science. 2008;320(5875):486–8. pmid:18436778
- 72. Dormann CF, Elith J, Bacher S, Buchmann C, Carl G, Carré G. Collinearity: a review of methods to deal with it and a simulation study evaluating their performance. Ecography. 2013;36(1):27–46.
- 73. Tobias CM, Chow EK. Structure of the cinnamyl-alcohol dehydrogenase gene family in rice and promoter activity of a member associated with lignification. Planta. 2005;220(5):678–88. pmid:15452707
- 74. Kim S-J, Kim M-R, Bedgar DL, Moinuddin SGA, Cardenas CL, Davin LB, et al. Functional reclassification of the putative cinnamyl alcohol dehydrogenase multigene family in Arabidopsis. Proc Natl Acad Sci U S A. 2004;101(6):1455–60. pmid:14745009
- 75. Wang Y, Wang X, Paterson AH. Genome and gene duplications and gene expression divergence: a view from plants. Ann N Y Acad Sci. 2012;1256:1–14. pmid:22257007
- 76.
Staggemeier VG, Diniz-Filho JAF, Forest F, Lucas EJA. Phylogenetic analysis in Myrcia section Aulomyrcia and inferences on plant diversity in the Atlantic rainforest. 2015;115(5):747–61.
- 77. Hurst LD. The Ka/Ks ratio: diagnosing the form of sequence evolution. Trends Genet. 2002;18(9):486. pmid:12175810
- 78. Li L-L, Xiao Y, Wang X, He Z-H, Lv Y-W, Hu X-S. The Ka /Ks and πa /πs Ratios under Different Models of Gametophytic and Sporophytic Selection. Genome Biol Evol. 2023;15(8):evad151. pmid:37561000
- 79. Wang Y, Chantreau M, Sibout R, Hawkins S. Plant cell wall lignification and monolignol metabolism. Front Plant Sci. 2013;4:220. pmid:23847630
- 80.
Jensen PE, Leister DJF. Chloroplast evolution, structure and functions. 2014;6:40.
- 81. Hernandez-Garcia CM, Finer JJ. Identification and validation of promoters and cis-acting regulatory elements. Plant Sci. 2014;217–218:109–19. pmid:24467902
- 82. Dar NA, Amin I, Wani W, Wani SA, Shikari AB, Wani SH, et al. Abscisic acid: A key regulator of abiotic stress tolerance in plants. Plant Gene. 2017;11:106–11.
- 83. Xi Y, Hu W, Zhou Y, Liu X, Qian Y. Genome-Wide Identification and Functional Analysis of Polyamine Oxidase Genes in Maize Reveal Essential Roles in Abiotic Stress Tolerance. Front Plant Sci. 2022;13:950064. pmid:35991458
- 84. Wang L, Sun G, Wang J, Zhu H, Wu Y. Systematic characterization of cinnamyl alcohol dehydrogenase members revealed classification and function divergence in Haplomitrium mnioides. J Plant Res. 2025;138(1):173–87. pmid:39609336
- 85. Yao T, Feng K, Xie M, Barros J, Tschaplinski TJ, Tuskan GA, et al. Phylogenetic Occurrence of the Phenylpropanoid Pathway and Lignin Biosynthesis in Plants. Front Plant Sci. 2021;12:704697. pmid:34484267
- 86. Ding Z, Kihara D. Computational identification of protein-protein interactions in model plant proteomes. Sci Rep. 2019;9(1):8740. pmid:31217453
- 87. Yang S, Li H, He H, Zhou Y, Zhang Z. Critical assessment and performance improvement of plant-pathogen protein-protein interaction prediction methods. Brief Bioinform. 2019;20(1):274–87. pmid:29028906
- 88.
Kanehisa MJPBM. KEGG bioinformatics resource for plant genomics and metabolomics. 2016.
- 89. Masoudi-Nejad A, Goto S, Endo TR, Kanehisa M. KEGG bioinformatics resource for plant genomics research. J Plant Biol Methods. 2007:437–58.
- 90. Abulfaraj AA, Shami AY, Alotaibi NM, Alomran MM, Aloufi AS, Al-Andal A, et al. Exploration of genes encoding KEGG pathway enzymes in rhizospheric microbiome of the wild plant Abutilon fruticosum. AMB Express. 2024;14(1):27. pmid:38381255
- 91. Ibrahim HMM, Hosseini P, Alkharouf NW, Hussein EHA, Gamal El-Din AEKY, Aly MAM, et al. Analysis of gene expression in soybean (Glycine max) roots in response to the root knot nematode Meloidogyne incognita using microarrays and KEGG pathways. BMC Genomics. 2011;12:220. pmid:21569240
- 92. Cai X, Zhang Y, Zhang C, Zhang T, Hu T, Ye J, et al. Genome-wide analysis of plant-specific Dof transcription factor family in tomato. J Integr Plant Biol. 2013;55(6):552–66. pmid:23462305
- 93. Schwechheimer C, Zourelidou M, Bevan MJA. Plant transcription factor studies. Aropb. 1998;49(1):127–50.
- 94. Xie M, Zhang J, Tschaplinski TJ, Tuskan GA, Chen JG, Muchero WJF. Regulation of lignin biosynthesis and its role in growth-defense tradeoffs. Fips. 2018;9:1427.
- 95. Owusu Adjei M, Zhou X, Mao M, Rafique F, Ma J. MicroRNAs Roles in Plants Secondary Metabolism. Plant Signal Behav. 2021;16(7):1915590. pmid:33938393
- 96. Yang J, Zhang Y, Jia J, Wang C, Fu YJ. Flavonoid‐lignin crosstalk: engineering metabolic flux for optimised plant growth and stress resilience. Cell Environment. 2025;48(11):8141–60.
- 97. Yaschenko AE, Fenech M, Mazzoni-Putman S, Alonso JM, Stepanova AN. Deciphering the molecular basis of tissue-specific gene expression in plants: Can synthetic biology help?. Curr Opin Plant Biol. 2022;68:102241. pmid:35700675
- 98.
Jopcik M, Bauer M, Moravcikova J, Boszoradova E, Matusikova I, Libantova JJPC, et al. Plant tissue-specific promoters can drive gene expression in Escherichia coli. 2013;113:387–96.
- 99. De Rybel B, Mähönen AP, Helariutta Y, Weijers D. Plant vascular development: from early specification to differentiation. Nat Rev Mol Cell Biol. 2016;17(1):30–40. pmid:26580717
- 100. Barakat A, Bagniewska-Zadworna A, Choi A, Plakkat U, DiLoreto DS, Yellanki P, et al. The cinnamyl alcohol dehydrogenase gene family in Populus: phylogeny, organization, and expression. BMC Plant Biol. 2009;9:26. pmid:19267902
- 101. Xiao J, Cao B, Tang W, Sui X, Tang Y, Lai Y, et al. The CaCAD1-CaPOA1 module positively regulates pepper resistance to cold stress by increasing lignin accumulation. Int J Biol Macromol. 2025;290:139979. pmid:39826724
- 102. Liu W, Jiang Y, Jin Y, Wang C, Yang J, Qi H. Drought-induced ABA, H2O2 and JA positively regulate CmCAD genes and lignin synthesis in melon stems. BMC Plant Biol. 2021;21(1).
- 103. Yang M, Wang L, Wang X, Li Y, Huang H. Transcriptomic Response to Drought Stress in Populus davidiana Dode. Forests. 2023;14(7):1465.