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Genome-wide identification and expressional analysis of carotenoid cleavage oxygenase (CCO) gene family in Betula platyphylla under abiotic stress

BMC Genomics volume 25, Article number: 872 (2024) Cite this article

Abstract

Background

Carotenoid cleavage oxygenases (CCOs) are a group of enzymes that catalyze the oxidative cleavage of carotenoid molecules. These enzymes widely exist in plants, fungi, and certain bacteria, and are involved in various biological processes. It would be of great importance and necessity to identify CCO members in birch and characterize their responses upon abiotic stresses.

Results

A total of 16 BpCCOs, including 8 BpCCDs and 8 BpNCEDs were identified in birch, and phylogenetic tree analysis showed that they could be classified into six subgroups. Collinearity analysis revealed that BpCCOs have the largest number of homologous genes in Gossypium hirsutum and also have more homologous genes in other dicotyledons. In addition, promoter analysis revealed that the promoter regions of BpCCOs contained many abiotic stress-related and hormone-responsive elements. The results of qRT-PCR showed that most of the BpCCOs were able to respond significantly to ABA, PEG, salt and cold stresses. Finally, the prediction of the interacting proteins of BpCCOs by STRING revealed several proteins that may interact with BpCCOs and be involved in plant growth and development/abiotic stress processes, such as HEC1 (bHLH), ATABA1, ATVAMP714, etc.

Conclusion

In this study, the CCO members were identified in birch in a genome-wide scale. These results indicate that BpCCO genes may play important roles in the abiotic stress responses of birch plants.

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Background

Carotenoids are a class of isoprenoid compounds found in a wide range of photosynthetic and non-photosynthetic organisms (e.g. bacteria and fungi) and play an important role in the growth and development process [1, 2]. For example, xanthophylls and violaxanthin function as components of plant light-harvesting protein complexes [3]. In addition, carotenoids in chloroplasts are responsible for light absorption, electron transfer, and the elimination of triplet oxygen and superoxide anion during plant photosynthesis [4, 5]. On the other hand, the carotenoid-derived product zeaxanthin aldehyde can be converted to the phytohormone abscisic acid (ABA), which plays an important role in a number of biological processes such as plant abiotic stress response and seed development [6, 7]. In the carotenoid metabolic pathway, carotenoid cleavage oxygenases (CCOs) specifically catalyze the cleavage of conjugated double bonds in the polyene chain of the carotenoid molecule, resulting in the formation of a variety of deacylated carotenoids and their derivatives [6, 8]. In higher plants, based on the epoxy structure of substrate, CCOs can be further classified into carotenoid cleavage dioxygenases (CCDs) and nine-cis-epoxycarotenoid dioxygenases (NCEDs) [9]. CCDs are mainly responsible for the oxidative cleavage of carotenoids in higher plants, leading to the biosynthesis of biologically smaller apocarotenoids [5]. NCEDs can catalyze the cleavage of the 11,12 double bond of violaxanthin (C40) or neoxanthin (C40) to form xanthoxin (C15), and this catalytic reaction carried out by NCEDs is considered to be the rate-limiting step in ABA biosynthesis [10, 11].

In recent years, with the accumulation of the studies on plant CCO family, CCOs have been found in several species. For instance, nine known CCO members have been found in Arabidopsis [12,13,14], 13 in poplar [14], 19 in Nicotiana tabacum [15], 16 in Forsythia suspensa [16], etc [17,18,19]. Meanwhile, CCO family members were found to be actively involved in growth and developmental regulation and stress response processes in plants. For example, AtCCD7 and AtCCD8 are capable of sequentially oxidizing β-carotene to produce monocerolactone hormone synthesis precursors, which play important roles in biological processes such as meristem formation, lateral root formation, seed germination, and response to drought and salt stresses [20,21,22,23]. In plants, the first carotenoid-cleaving enzyme involved in precursor flavin biosynthesis, NCED, was derived from an abscisic acid hormone-deficient maize (Zea mays) mutant. The mutant embryos were found to have normal sensitivity to ABA, and the detached leaves from mutant seedlings showed significantly higher rates of water loss than wild-type leaves [24]. In Glycine max, the expression levels of CCOs were found to change significantly upon salt, drought, low and high temperature stress, suggesting that CCOs may be involved in multiple abiotic stress response processes [25]. The overexpression of sweet potato carotenoid cleavage dioxygenase 4 (IbCCD4) reduced the salt tolerance of the transgenic Arabidopsis [26]. In cotton, virus-induced gene silencing of GaNCED3a, the ortholog of GhNCED3a_A/D, reduced the resistance of the transgenic plants not only to drought but also to salt treatment, and also led to significantly reduced proline content, high malondialdehyde content and high-water loss rate [27]. Arabidopsis overexpressing Crocus sativus CCD4b had longer roots and more lateral roots, as well as increased tolerance to salt, dehydration and oxidative stress compared to wild type [28]. Furthermore, Brassica oleracea CCD1 and CCD4 are highly responsive to both drought and salt stress [29]. In Malus domestica, the expression level of an CCO gene changed significantly under both salt and drought stress, suggesting that MdCCO is involved in the abiotic stress response process in apple [30]. The above results indicate that CCO family genes have important biological functions in plant growth and development and in response to abiotic stress. However, there has been no study to date to identify the CCO family genes in birch (Betula platyphylla) at the genome-wide level.

In this study, Betula platyphylla was selected as the research material. It is a widespread tree species in eastern Asia, born on mountain slopes or in forests at altitudes of 400–4100 m, with strong adaptability. Birch especially preferring moist soils, and is a pioneer tree species in secondary forests. Therefore, birch is used as an ideal plant material for researches on plant responses to abiotic stresses. Hu et al. found that the transgenic birch plants showed better tolerance to salt and osmotic stress upon the overexpression of BpNAC012 gene [31]. Guo et al. identified the BpIMYB46 gene from birch and found it to be involved in the salt and osmotic tolerance [32]. In Wang et. al.’s research, the expression of an BpNAC gene, BpNAC90, was responsive to drought stress. The overexpression of this gene conferred improved drought tolerance to the transgenic birch plants [33]. With the development of genome sequencing technology, the whole genome sequencing has been accomplished for birch in recent years [34]. Based on a current clear genomic background, a total of 16 members of the Betula platyphylla CCO (BpCCO) gene family have been identified with bioinformatics methods. Then, the analyses on gene structure, chromosomal localization, collinearity, and promoter activity were also performed. Additionally, we analyzed the expression patterns of BpCCOs under abiotic stresses using qRT-PCR. The protein interaction network of BpCCOs was also proposed. This study provides new insights into the evolutionary relationships of the BpCCO family, serving as a valuable reference for investigating the biological functions of CCOs and the abiotic stress response of forest tree.

Methods

Identification of the CCOs in Betula platyphylla

To obtain the genome information of Betula platyphylla, the genome, coding sequences (CDS) and protein data of Betula platyphylla were searched and downloaded from the Phytozome v13.1 database (https://phytozome.jgi.doe.gov/pz/portal.html). A BLASTP search was performed and the Hidden Markov Model (HMM) [35] file (PF03055) was retrieved from the Pfam protein family database (http://pfam.xfam.org). The putative members of the carotenoid cleavage oxygenase family in birch were identified using HMMER v3.1. The sequences of these putative members were then further checked using InterPro (http://www.ebi.ac.uk/interpro).

After obtaining the BpCCO family members, their amino acid sequence characteristics such as molecular weight, isoelectric point, amino acid number, aliphatic index and hydrophilic average (GRAVY) score were analyzed using ExPASy (http://www.expasy.org/).

Phylogenetic relationships and genestructures of BpCCOs

The conserved motifs of BpCCOs were identified by using online tool MEME 5.0 (http://meme-suite.org). After the alignment of the protein sequences of BpCCOs by using Clustal X [36], the phylogenetic tree was constructed via MEGA 11 software [37, 38] (number of bootstrap replicates = 1000) with the Maximum likelihood (ML) method. Online software GSDS2.0 (Gene Structure Display Server: http://gsds.cbi.pku.edu.cn/) was used to analyze the exon and intron distribution patterns of BpCCOs, which were visualized by using Tbtools-II (v1.120) [39].

Chromosomal localization and collinearity visualization

The location information of the BpCCOs was retrieved from Phytozome database and mapped onto the chromosome using Tbtools-II (v1.120). To analyze the syntenic relationships between the CCOs from birch and other plant species, the CCO gene sequences from four dicots (Salix purpurea, Populus trichocarpa, Arabidopsis thaliana, Gossypium hirsutum) and one monocot (Oryza sativa) were retrieved from phytozome database. Gene duplication events were investigated using the MCScanX (Multicollinearity Scanning Toolkit) software [40] with default parameters, and were visualized using TBtools [39]. Tbtools-II (v1.120) was used to calculate the non-synonymous (Ka) and synonymous (Ks) ratio for duplicated gene pairs.

Cis-acting element analysis

The sequence 2000 bp upstream of the transcription start site (TSS) of each BpCCO was extracted from the Phytozome database. Cis-elements were predicted with PLACE [41] and visualized with TBtools.

GO (gene ontology) annotation of BpCCOs

GO annotation of BpCCOs was conducted using Tbtools-II (v1.120) software. The protein sequences were uploaded to Tbtools-II (v1.120), and then through BLAST in Phytozome database. The results were visualized and downloaded. All parameters were set as default.

Collection of miRNA targeting BpCCOs

The coding sequences of BpCCOs were uploaded to the psRNATarget database (http://plantgrn.noble.org/psRNATarget) to search for the miRNAs that target the BpCCOs. The targeting relationships were further predicted by graphical illustration. The results were visualized by Cytoscape (v3.0) software.

Construction of protein-protein interaction network

Interacting proteins of BpCCOs were predicted using STRING online software [42] and linear relationships in the predicted results were visualised using Cytoscape [43].

Yeast transformation and transcriptional activation activity verification

Yeast transformation assay was conducted to identify the transcriptional activation activity of BpCCD4 and BpNCED5. The coding sequences of BpCCD4 and BpNCED5 were cloned and then combined with pGBKT7 vector, respectively, by using two enzyme digestion. The recombinant vector (pGBKT7-BpCCD4, pGBKT7-BpNCED5), positive control (pGBKT7-53/pGADT7-T) and negative control (pGBKT7) were transformed into yeast competent cells (Y2H), respectively. The transformed yeast fluids were cultured on the nutrition-deprived media (SD/-Trp, SD/-Trp/-His/-Ade) for the test of growing state.

Yeast two hybrid assay

According to the results of protein-protein interaction network, two combinations (BpCCD4/BpABA1, BpNCED5/BpVAMP714) were selected for further verification. The coding sequences of BpABA1 and BpVAMP714 were cloned and then combined with pGADT7 vector, respectively. The vector combinations pGBKT7-BpCCD4/pGADT7-BpABA1, pGBKT7-BpNCED5/ pGADT7-BpVAMP714, pGBKT7-53/pGADT7-T (positive control) and pGBKT7-LAM/pGADT7-T (negative control) were transformed into yeast competent cells (Y2H), respectively. The transformed yeast fluids were cultured on the nutrition-deprived media (SD/-Trp/-Leu, SD/-Trp/-Leu/-His/-Ade) for the test of growing state.

Salt-resistant yeast transformation

Salt-resistant yeast transformation assay to explore the function of BpCCOs in salt tolerance. The coding sequences of BpCCD7, BpNCED2.5 and BpNCED5 were cloned and combined with pYES2-NTB vector, respectively, with seamless cloning method. The recombinant vectors, pYES2-NTB-BpCCD7, pYES2-NTB-BpNCED2.5 and pYES2-NTB-BpNCED5, as well as negative control (pYES2-NTB) were transformed into salt-resistant yeast (INVSc1). The transformed yeast fluids were cultuerd on nutrition-deprived yeast media (SD/-Ura) with different concentration of salt (NaCl). The concentration gradient of salt was set 0, 0.3, 0.6, 1.0, 1.3, 1.6 and 2.0 M. The growth state of yeast indicates salt tolerance.

Plant materials and treatments

The plant materials (not in a publicly available herbarium) used in this study were white birch (Betula platytphylla) preserved by the State Key Laboratory of Tree Genetics and Breeding, Northeast Forestry University (Harbin, China). This plant species was firstly identified by Chen et al. via transcriptomic analysis in 2021 [44]. The deposition numbers of the genomic data of white birch are 679 for phytozome database and 78630 for NCBI database. They were cultivated with vegetative reproduction method and grown in a greenhouse with a 16-h light/8-h dark photoperiod at 25℃. For tissue-specific analysis, seedlings were grown in hydroponic culture (1/2 MS medium containing 25 g/L sucrose, 0.02 mg/L NAA and 0.4 mg IBA) for 60 d. After homogenization, plant samples including root, stem and leaf were collected, immediately frozen in liquid nitrogen and kept in a refrigerator at -80℃ for further experimental use.

The seedlings for ABA, PEG6000 or NaCl treatment were also grown in hydroponic culture for 60 d. For ABA treatment, we adjusted the concentration of ABA in hydroponic culture to 100 µM. For the PEG6000 treatment, we adjusted the concentration of PEG6000 in the hydroponic culture to 20% (W/V). For salt treatment, we adjusted the concentration of NaCl in the hydroponic culture to 200 mM. Plant samples (leaf) were collected at 0 h, 3 h, 6 h, 12 h, 24 h and 48 h of each treatment according to the result of tissue-specific analysis. For cold treatment, the treatment conditions were 4℃ for 3 h, seedlings were first grown in hydroponic culture for 60 d and then transplanted to soil for further growth for 30 days. After cold treatment, plant leaves were collected. Prior to sample preservation, all collected roots were rinsed with deionized water to remove the nutrient solution and then the excess water was absorbed with absorbent tissue. All these samples had three biological replicates.

qRT-PCR validation

Total RNA of the plant samples was extracted using the Mega Pure Plant RNA Kit (Msunflowers Biotech Co.,Ltd, Beijing, China). The quality of RNA was examined by gel electrophoresis and concentration measurement. The cDNA was then synthesised using a reverse transcription kit (PrimeScriptTM RT Reagent Kit, Takara Bio, Kusatsu, Japan). Primers used in qRT-PCR were designed according to the downloaded full-length cDNA sequences of BpCCOs, and 18 S ribosomal RNA was selected as the internal reference gene. qRT-PCR was performed using THUNDERBIRD Next SYBR qPCR Mix (TOYOBO, Osaka, Japan). The reaction system was 20 µL and the conditions were as follows: predenaturation at 94℃ for 30 s, denaturation at 94℃ for 5 s, renaturation at 58℃ for 15 s, extension at 72℃ for 10 s, step 2 to 4 for 45 cycles, melting curve for 6 s. The reaction was performed on an Applied Biosystems 7500 Fast Real-Time PCR System. Each reaction had 3 biological replicates. The relative expression levels of BpCCOs were calculated using the 2-∆∆Ct method [45].

Statistical analysis

Regular calculations were carried out with the assistance of Excel software. Significant differences were analyzed by one-way ANOVA followed by Duncan’s multiple range test.

Result

Phylogenetic and structural analysis of CCO family members

A total of 16, 23, and 9 CCOs were obtained from Betula platyphylla, Populus trichocarpa and Arabidopsis thaliana, respectively, and a phylogenetic tree was generated based on their sequences. CCOs can be classified into two subfamilies, namely CCDs (II-VI) and NCEDs (I). Based on the previous studies on the Arabidopsis CCO family [46], CCDs were further classified into five subgroups (I-VI) (Fig. 1). Among them, subgroups II, III, IV and V corresponded to CCD4, CCD1, CCD7 and CCD8 in Arabidopsis, while members of subgroup VI appeared only in poplar and birch, suggesting that members of this subgroup may have appeared after the differentiation of herbaceous and woody plants. Among all the subgroups, subgroup I contained the highest number of genes (17 genes) and IV contained the lowest number of genes (3 genes).

Fig. 1
figure 1

Phylogenetic analysis of CCOs in Betula platyphylla (Bp), Arabidopsis thaliana (At), and Populus trichocarpa (Ptr). Maximum likelihood (ML) method with 1,000 bootstrap replicates was applied to draw the phylogenetic tree via MEGA11 software. The tree was divided into two subfamilies or six subgroups; each color represents one subgroup. Black stars indicate BpCCOs

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Table 1 Basic information of CCO genes in birch, Arabidopsis and Poplar
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The analysis revealed that the length of these proteins varied between 97 (BpNCED2.3) and 657 (AtNCED9) amino acids in all three species (Table 1). The molecular weights ranged from 10866.49 (BpNCED2.3) to 73107.61 Da (BpCCD1.1). The pI of the CCO protein ranged from 4.67 (BpNCED2.4) to 9.73 (PtrCCD4.1), with 34 out of 48 CCO proteins being acidic (pI < 7). The aliphatic index of the CCO protein ranged from 65.84 (BpNCED2.4) to 90.48 (PtrCCD4.1), which indicates that most CCO proteins were stable. The grand average of hydropathicity (GRAVY) value ranged from − 0.725 (BpNCED2.1) to -0.112 (BpNCED6). The GRAVY value of all CCO proteins from the three species is less than 0, which indicates that all these proteins exhibit hydrophilicity.

Exon-intron and motif patterns of BpCCOs

Based on the sequence information of BpCCOs, the gene structure and motif pattern of each member were analyzed using TBtools and MEME software, respectively (Fig. 2). Generally, genes within the same evolutionary branch exhibited structural resemblances. The results showed that the number of exons in members of the NCED subfamily ranged from 1 to 5, with an average of 2.1. The number of exons in members of the CCD subfamily ranged from 1 to 13, with an average of 7.5. Except few genes, the number of exons was relatively conserved in most genes of the different subfamilies.

Fig. 2
figure 2

Exon-intron and protein motif of the BpCCO gene family members. In the left part, boxes symbolize exon. Thin lines symbolize. In the right part, colored boxes symbolize different motifs. The clustering was performed according to the phylogenetic analysis. Scale bar indicates the length of gene (bp)

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Chromosomal distribution and collinearity analysis of BpCCOs

By searching the latest version of Betula platyphylla v1.1 database, the position information of BpCCOs on chromosomes was obtained and visualized as shown in Fig. 3 and Supplementary Table 1. The results showed that BpCCOs were unevenly distributed on eight chromosomes. Among them, three BpCCOs were distributed on Chr01, Chr06 and Chr13 each, two BpCCOs were distributed on Chr02 and Chr04 each, and one BpCCO was distributed on Chr03, Chr07 and Chr08 each. To probe the gene duplication events of the BpCCO family members, we calculated the homology ratios and the total length of homologous fragments among the members. A total of five pairs that evolved into homologous genes due to gene duplication events were identified, of which four were segmental duplications and one was a tandem duplication (BpCCD1.1/BpCCD1.2) (Fig. 3). We also found that the Ka/Ks values of these gene pairs were less than 1, indicating a strong purifying selection (Table 2).

Fig. 3
figure 3

Chromosomal localization and collinearity analysis of the BpCCO family. Blue rectangles symbolize chromosomes. Red lines indicate duplication gene pairs of BpCCOs

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Table 2 The Ka/Ks ratios of duplication for BpCCOs
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The syntenic relationships between CCOs from birch and other four plant species (Salix purpurea, Populus trichocarpa, Arabidopsis thaliana, Gossypium hirsutum) were investigated. It is shown in Fig. 4 and Supplementary Table 2 that there were 9, 10, 6, 11, and 4 homologous pairs between B. platyphylla with S. purpurea, P. trichocarpa, A. thaliana, G. hirsutum, and O. sativa, respectively. BpNCED2.5 had the highest number of homologous genes (nine) in the other species. BpCCD8, BpCCD1.1, BpCCD10.1 and BpCCD7 also had more than four homologous genes.

Fig. 4
figure 4

Collinearity analysis of the CCO genes from Betula platyphylla and five other species. The CCO collinear genes are connected with a red line, while other collinear genes are connected with gray line

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Expression patterns of BpCCOs in different birch tissues

The expression patterns of BpCCOs in different birch tissues were investigated by using qRT-PCR. As shown in Fig. 5 and Supplementary Table 3, a total of nine BpCCOs were highly expressed in leaves, namely BpCCD4, BpNCED2.2, BpCCD1.2, BpNCED2.3, BpCCD10.1, BpNCED2.5, BpNCED2.1, BpCCD10.3 and BpNCED3. Two BpCCOs were highly expressed in roots, BpCCD8 and BpNCED2.4. Five BpCCOs were highly expressed in stems, BpCCD7, BpCCD1.1, BpCCD10.2, BpNCED5 and BpNCED6. Overall, individual members of the BpCCOs were expressed in roots, stems and leaves, and most members were the highest expressed in leaves.

Fig. 5
figure 5

Tissue-specific expression analysis of BpCCOs. The analysis was performed using roots, stems and leaves of birch as plant materials. Relative expression levels were calculated using the 2-ΔΔCt method with root expression of BpCCD10.3 as a control. Primers are shown in Supplementary Table 8. The 18 S rRNA gene was used as an internal reference

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Cis-elements analysis of BpCCOs promoters

The cis-elements in the promoter regions of BpCCOs were analyzed to explore the biological processes in which BpCCOs may be involved. It is shown in Fig. 6 that the different family members contain a number of elements associated with stress and hormonal responses. A large number of cis-elements associated with abiotic stresses were found in the promoter regions of most BpCCOs, such as the response to dehydration (CBFHV, MYBCORE, DRECRTCOREAT, MYCATRD22, etc.), ammonium (AMMORESIIUDCRNIA1 and AMMORESIVDCRNIA1), anaerobic-related (ANAERO1/2/3CONSENSUS), water stress (MYCATERD1 and MYBATRD22), drought (ABREZMRAB28, DRECRTCOREAT, and DRE1COREZMRAB17, etc.), low temperature (LTRECOREATCOR15), hypoxic (CURECORECR), etc. Similarly, a large number of cis-elements associated with biotic stress were found in the promoter regions of most members, for example, pathogen-response (SEBFCONSSTPR10A and GCCCORE) and pathogenesis-Related (MYB1LEPR). Furthermore, a large number of phytohormone-responsive elements have been identified in the promoter regions of BpCCOs, for instance, abscisic acid response elements (SBOXATRBCS, MYB1AT, 2SSEEDPROTBANAPA, etc.), auxin response elements (CATATGGMSAUR, ARFAT, AUXREPSIAA4, etc.), gibberellin response element (GADOWNAT, CAREOSREP1, GAREAT, etc.), jasmonic acid response elements (T/GBOXATPIN2 and GCCCORE), and ethylene response elements (ERELEE4 and LECPLEACS2), suggesting that BpCCOs may be involved in multiple biological processes.

Quantitatively, the most frequently abiotic stress response elements were ABA response elements, with a total of 593. It was followed by anaerobic-related elements (400) and JA-responsive elements (354). It suggests that BpCCOs are likely to show strong responses to these three stresses. On the other hand, BpCCOs also contain a large number of biotic stress response elements, 502 in total, which suggests that BpCCOs may also play important roles in the biotic stress response.

Fig. 6
figure 6

Cis-elements analysis of birch CCO genes promoters. The PLACE software was used to analyze the 2000 bp DNA sequence upstream the transcription starts site (TSS) of BpCCOs. The heat map represents the number of elements, and the bar graph represents the total number of elements

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GO enrichment of BpCCOs

The results of the enrichment analysis showed BpCCOs were classified into three main categories: biological process, cellular component, and molecular function (Fig. 7). In the biological process category, the most abundant GO term was carotene catabolic process, which included the genes BpCCD1.1, BpNCED5.1, BpCCD8.1, BpCCD10.1 and BpCCD7.1. In the Molecular Function category, oxidoreductase activity, acting on single donors with incorporation of molecular oxygen, incorporation of two oxygen atoms, metal ion binding, and carotenoid dioxygenase activity were the top three GO terms in terms of abundance. In the Cellular Component category, the GO term chloroplast was enriched with the highest abundance.

Fig. 7
figure 7

GO enrichment analysis of BpCCOs. The enrichment results were classified into three categories, Biological Process, Cellular Component, and Molecular Function

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miRNAs that target BpCCOs

A total of 114 miRNA-BpCCO target pairs were obtained, and subsequently a network of miRNA-BpCCOs was generated (Fig. 8). It was found that among all the predicted pairs, miR156-related pairs took the largest proportion (number is 11). The related genes were BpNCED3 and BpCCD10.1. The prediction results showed that the binding sites of these miR156s for BpCCD10.1 were the same (Supplementary Table 9), suggesting that the miR156s were able to specifically recognize specific region in the sequence, which implies that this prediction model is of high confidence level.

Fig. 8
figure 8

miRNAs potentially targeting BpCCOs. Purple dots represent BpCCOs. Green dots represent miRNAs. The targeting relationships were predicted using psRNATarget online software

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Responses of BpCCOs upon abiotic stresses

The results of cis-element analysis indicated that the promoters of BpCCOs were enriched with a variety of stress-responsive cis-acting elements, and these genes may respond to a wide range of abiotic stresses. Therefore, we subjected birch to ABA, PEG, salt and cold treatments and determined the relative expression levels of each member at different treatment times using qRT-PCR (Supplementary Tables 4, 5, 6, 7).

Upon ABA treatment (Fig. 9), the expression levels of all BpCCOs were significantly changed except BpCCD8. A total of five BpCCOs were consistently up-regulated with the ABA treatment, namely BpCCD1.1, BpCCD10.3, BpNCED2.2, BpNCED5 and BpNCED6. Six BpCCOs were consistently down-regulated in expression, namely BpCCD1.2, BpCCD4, BpCCD10.1, BpCCD10.2, BpNCED2.3 and BpNCED2.5. In addition, three BpCCOs (BpCCD7, BpNCED2.1 and BpNCED3) showed up-regulation from 0 to 24 h and down-regulation at 48 h. BpNCED2.4, on the other hand, showed down-regulation from 0 to 12 h followed by increased expression. Overall, most of the BpCCOs showed significant response to ABA, however, the response pattern was different for different members.

Fig. 9
figure 9

Expression patterns of BpCCOs in response to 100 µM ABA treatment. X-axis shows treatment time point, Y-axis represents relative expression level. The data was processed using the 2−ΔΔCt method. Gene expression at 0 h was set to 1 and expression in the other time points was relative to it. (t test, * p < 0.05, ** p < 0.01)

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Upon PEG treatment (Figs. 10), 12 BpCCOs showed significantly up-regulated expression at one time point, except BpCCD8, BpCCD10.3, BpNCED2.4 and BpNCED6, which showed a tendency to first significantly up-regulate and then significantly down-regulate their expression, which suggests that PEG treatment activates most BpCCOs.

The results of salt treatment assay (Fig. 11) showed that a total of eight BpCCOs were activated and consistently up-regulated in expression by salt treatment, namely BpCCD7, BpCCD10.3, BpNCED2.1, BpNCED2.3, BpNCED2.4, BpNCED2.5, BpNCED3 and BpNCED5. Six BpCCOs firstly showed significant activation and then significant decrease in expression, namely BpCCD1.1, BpCCD8, BpCCD10.1, BpCCD10.2, BpNCED2.2 and BpNCED6. In addition, two BpCCDs (BpCCD1.2 and BpCCD4) were significantly down-regulated after salt treatment. Overall, most of the BpCCOs were activated in expression 0–6 h after salt stress.

The results of cold treatment (Fig. 12) showed that a total of eight BpCCOs were significantly up-regulated 3 h after cold treatment, namely BpCCD1.2, BpCCD4, BpCCD10.3, BpNCED2.1, BpNCED2.2, BpNCED2.4, BpNCED5 and BpNCED6. Four BpCCOs were significantly down-regulated, namely BpCCD7, BpNCED2.3, BpNCED2.5 and BpNCED3. The expression levels of other genes showed no significant changes. Collectively, it indicates that cold stress can cause significant changes in the expression of most BpCCOs.

Fig. 10
figure 10

Expression patterns of BpCCOs upon PEG6000 treatment. X-axis shows treatment time point, Y-axis represents relative expression level. The data was processed using the 2−ΔΔCt method. Gene expression at 0 h was set to 1 and expression in the other time points was relative to it. (t test, * p < 0.05, ** p < 0.01)

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Fig. 11
figure 11

Expression patterns of BpCCOs in response to salt treatment. X-axis shows treatment time point, Y-axis represents relative expression level. The data was processed using the 2−ΔΔCt method. Gene expression in 0 h was set to 1 and expression in the other time points was relative to it. (t test, * p < 0.05, ** p < 0.01)

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Fig. 12
figure 12

Expression patterns of BpCCOs in response to cold treatment. X-axis shows treatment time point, Y-axis represents relative expression level. The data was processed using the 2−ΔΔCt method. Gene expression in 0 h was set to 1 and expression in the other time points was relative to it. (t test, * p < 0.05, ** p < 0.01)

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Protein-protein interaction network of BpCCOs

To better understand the putative functions and interactions of BpCCOs, we first constructed an interaction network model of BpCCO proteins using STRING (Fig. 13). Subsequent functional annotation of all genes in the network was performed using the homologous gene identification method, which showed that only a few genes could be annotated, including HEC1 (bHLH), BPChr06G29579 (bHLH), ATABA1 (BPChr06G16528), ATRPB15.9 (BPChr03G15114), ATTBP2 (BPChr07G24868), ATVAMP714 (BPChr10G15896), CYP90D1 (BPChr06G19200), MAX2 (BPChr11G15589), RACK1A (BPChr12G02842) and ZDS (BPChr05G31567). The proteins encoded by these genes may interact with CCOs and jointly play important roles in certain biological processes.

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Fig. 13
figure 13

Protein interaction network analysis of BpCCOs. Interaction networks were constructed by using STRING database (https://string-db.org/, accessed on 9 Sep. 2023). The purple node represents BpCCOs and the blue-green node represents proteins that can interact with BpCCOs. Node size represents the connectivity of the protein

Full size image

Transcriptional activation activity of BpCCD4 and BpNCED5

The transcription activation activity of BpCCD4 and BpNCED5 was investigated by yeast transformation. As shown in Fig. 14, the yeast transformed with positive control can grow both on the SD/-Trp and SD/-Trp/-His/-Ade medium. The yeast transformed with BpCCD4, BpNCED5, respectively, can grow on the SD/-Trp medium while cannot grow on SD/-Trp/-His/-Ade medium, which indicates the successful transformation and no transcription activation activity.

Fig. 14
figure 14

Transcriptional activation activity of BpCCD4 and BpNCED5. Positive control is pGBKT7-53/pGADT7-T. Negative control is pGBKT7. SD means nutrition-deprived yeast medium

Full size image

Interaction between BpCCD4 and BpABA1, BpNCED5 and BpVAMP714

To further verify the protein-protein interaction network, yeast two hybrid assay was conducted with two protein combinations, BpCCD4/BpABA1 and BpNCED5/BpVAMP714. As shown in Fig. 15, the results showed that the yeast transformed with two vector combinations as well as positive control and negative control, respectively, can grow on SD/-Trp/-Leu medium, which indicates successful co-transformation. The yeast transformed with the two vector combinations, respectively and positive control, can grow on the SD/-Trp/-Leu/-His/-Ade medium, while negative control cannot. It proved the protein-protein interaction between BpCCD4 and BpABA1, as well as BpNCED5 and BpVAMP714.

Fig. 15
figure 15

Protein-protein interaction between BpCCD4 and BpABA1, as well as BpNCED5 and BpVAMP714. Positive control is pGBKT7-53/pGADT7-T. Negative control is pGBKT7-LAM/pGBKT7-T. SD means nutrition-deprived yeast medium

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Function of BpCCD7, BpNCED2.5 and BpNCED5 in salt tolerance

According to the expressional responses of BpCCOs upon salt treatment, BpCCD7, BpNCED2.5 and BpNCED5 were selected for further verification of their function in salt tolerance. As shown in Fig. 16, the growth traces of all experimental groups and control weakened with increasing salt concentration. The yeast transformed with pYES2-NTB-BpCCD7, pYES2-NTB-BpNCED2.5 and pYES2-NTB-BpNCED5 can grow on SD/-Ura media with 2.0 M Nacl while negative control cannot. It proved the positive effects of BpCCD7, BpNCED2.5 and BpNCED7 in salt tolerance.

Fig. 16
figure 16

Functions of BpCCD7, BpNCED2.5 and BpNCED5 in salt tolerance. Negative control is pYES2-NTB. SD means nutrition-deprived yeast medium. 1, 10− 1, 10− 2 indicates different dilution of yeast fluids

Full size image

Discussion

To date, CCO gene family members have been identified in a genome-wide range in several plant species, with 13 in banana [47], 10 in Liriodendron chinese [48], 10 in cucumber [49], 11 in pepper [50] and 47 in Saccharum spontaneum [18]. Here, the BpCCO gene family members were identified from a genome-wide range, and their expressional responses upon different abiotic stresses were explored.

In this study, a total of 16 BpCCO genes were identified from birch genome, including 8 BpCCDs and 8 BpNCEDs. BpCCOs can be classified into two subfamilies, namely BpCCDs (II-VI) and BpNCEDs (I). The phylogenetic analysis showed that the CCO family members from birch, poplar and Arabidopsis can be classified into six subgroups. It was found that all the subgroups, except subgroup VI, contained CCOs from all the three species, suggesting possible similarity in the evolutionary patterns of CCOs in herbaceous and woody plants. Furthermore, the phylogenetic tree also showed that all BpCCOs except BpCCD1.1 and BpCCD1.2 were on the same branch with PtrCCOs, suggesting that the CCOs in birch and poplar may share closer evolutionary relationships. Consequently, it can be inferred that CCOs have diverged with the evolution of the herbaceous and woody plant. In addition, the exon-intron patterns of BpCCOs exhibited similarity within the same subfamily. The motif analysis showed that only few genes in the adjacent branches had similar motifs, such as BpNCED2.5, BpNCED3 and BpNCED5; and BpCCD1.1 and BpCCD1.2. The other genes differed greatly in the type of motifs, suggesting that there are large functional differences between CCO members which may have emerged during evolution. BpCCOs had multiple colinear genes across species, which reached the most in Gossypium hirsutum (Gh), suggesting that BpCCOs have evolved to be more closely related to GhCCOs. In addition, BpCCOs had the lowest number of colinear genes in O. sativa (4 pairs), which was similar to the results of the previously reported study on poplar CCOs (1 pair) [14], probably due to the fact that rice is a monocotyledon and distantly related to other dicotyledons. According to the results of GO enrichment analysis, BpCCOs can be enriched in three categories, biological process, cellular component, and molecular function, in which carotenoid is an importantpart. Carotenoid is known to be one of the most important antioxidants in living organisms [14, 51]. These BpCCOs were enriched in relevant GO terms involved in carotenoid synthesis or metabolism, suggesting that these genes have potential ROS scavenging functions, implying that they may play an important role in plants under biotic/abiotic stress. miRNAs play important roles in plant growth and development and are involved in the post-transcriptional regulation of genes by binding to specific sequences. In recent years, miRNA has been proved to be involved in plant abiotic stress response [52, 53]. The results showed that miR156 participates the most in the miRNA-gene regulation. miR156 is one of the largest gene families in plants and plays important roles in plant defense against biotic/abiotic stresses. For example, MicroRNA156 is able to improve drought tolerance in Medicago sativa [54]. miR156 is able to influence salt tolerance in apple by regulating downstream gene expression [55]. It is therefore hypothesized that miR156s are likely to be involved in plant stress tolerance processes through the regulation of BpNCED3 and BpCCD10.1, and thus in plant stress tolerance. In addition, five miR169 family members were predicted to potentially regulate the expression of BpNCED2.5, BpNCED2.4 and BpNCED6. miR169s also possess important functions in plant stress tolerance, such as most of the poplar miR169s can respond to ABA and salt stress. In Arabidopsis, it was found that plants were more sensitive to drought stress after overexpression of miR169a [56]. zma-miR169 was reported to respond positively to salt stress in maize leaves [57]. In this study, miR169s targets were found to be BpNCED2.5, BpNCED2.4 and BpNCED6, suggesting that these genes may be regulated by miR169s and thus involved in abiotic stresses such as drought and salt. In addition, there are a number of miRNAs predicted to bind BpCCOs, such as miR159s, miR393s and so on, all of which may be involved in plant stress tolerance processes by regulating the expression of BpCCOs.

The expression patterns of BpCCDs and BpNCEDs in different plant tissues, including root, stem and leaf, were investigated by using qRT-PCR. The results indicated a clear divergence between the expression levels of these genes, even those with closer evolutionary relationships. For instance, BpCCD1.1 and BpCCD1.2 shared close evolutionary relationship. However, BpCCD1.2 had high expression levels over all tissues, especially leaf, while BpCCD1.1 was not so abundantly expressed over all tissues and the highest in stem. According to Auldridge et al. and Simkin et al. [58, 59], AtCCD1 and PhCCD1 were both expressed in high levels over all tissues. BpCCD1.2 shared a similar expression pattern with these two genes, which indicates BpCCD1.2 may play an important role in certain metabolisms. CCD1 gene in poplar was also the most expressed in leaf [14], which implies the similar function between BpCCD1 and PtCCD1. BpCCD4 and BpCCD1.2 shared similar expression patterns with approximately half of BpNCEDs. These genes were the highest expressed in leaf, which indicated the important functions of them in plant leaf. Previous evidence has proven that AtCCD7 had the highest expression level in root, and the expression levels of PtCCD7 were low over all tissues [14]. As showed in Fig. 1, BpCCD7 had close evolutionary relationship with PtCCD7. BpCCD7 was also expressed at low levels over all tissues, which may indicate certain functional similarity between these two genes. It may also imply the different functions of CCD7 in herbaceous and woody plants. NCEDs are the rate limiting enzymes for the biosynthesis of ABA, a key signal molecule in the growth and development and stress response of plants [60, 61]. NCEDs participate in the regulation of endogenous ABA and thereby function in stress response. In Arabidopsis, AtNCED3 was induced by drought stress and regulated the drought stress response of plants by altering the transpiration rate of leaf and controlling the level of endogenous ABA [62]. In this study, BpNCED3 was also induced by ABA and drought treatment, as well as salt and cold stress, which can also cause osmotic harm. These evidences indicate the potential important roles this gene may play in the stress response of plants. AtNCED6 and AtNCED9 participated in the biosynthesis of ABA in seed germination [63]. Upon abiotic stress, NCEDs in Crocus sativus were closely related to the content of ABA [64]. In this study, BpNCED3, -5, -6 and AtNCED3, -6, -9 had similar motif and gene structures, which indicates that BpNCED3, -5, -6 may function in the accumulation of ABA and abiotic stress response of plants. BpCCD4 shared similar tissue-specific expression pattern with most of BpNCEDs. However, their expression patterns upon abiotic stress were different. It indicates that the genes with similar tissue-specific expression patterns probably do not response to abiotic stress synchronously. BpNCEDs seem to play more significant roles in the abiotic stress of plants than BpCCDs according to the expression analysis under abiotic stresses. Although CCD4 had high expression levels in various plant species, the evidence of its functions in stress response remains insufficient. More studies on CCD4 focused mainly on fruit and floral organ. For instance, the Arabidopsis plant overexpressing AtCCD4 exhibited lower contents of β-carotene and lutein and more β-violone accumulation [65]. Function loss of CCD4 changed the petal color of azalea from yellow to white [66], as well as that of Eustoma grandiflorum from light yellow to white [67]. These evidences indicate that BpCCD4 may function in the biological process of fruit and floral organ. Previous studies proved that CCDs play a major role in the biosynthesis and signal transduction of ABA upon stress condition [68, 69]. The functions of CCD and NCED genes in birch remain unclear. In this case, the cis-acting elements in the promoters of BpCCDs and BpNCEDs were analyzed. The expression patterns of BpCCDs and BpNCEDs upon abiotic stress were determined by using qRT-PCR. The results that these genes were responsive to different abiotic stresses to different degrees indicate their important functions in the abiotic stress response of birch. To further investigate their function in abiotic stress response, BpCCD7, BpNCED2.5 and BpNCED5 was subjected to salt-resistant yeast transformation. The boosted salt tolerance of the yeast transformed with these genes indicates their positive roles in salt response, which provides an insight into the important functions of BpCCOs in abiotic stress response.

Protein-protein interaction is an important way of molecular signal transduction. In this case, the protein interaction networks of BpCCOs were constructed. The results of yeast two hybrid assay proved the interaction between BpCCD4 and BpABA1, BpNCED5 and BpVAMP714, which validates the reliability of the prediction result. ATABA1 has the highest connectivity in the network and its function has been reported. The aba1 mutant has a defect in the biosynthesis of ABA. The aba1 mutation results in a reduced pool of ABA precursors, such as violaxanthin and neoxanthin, and affects the oxidative cleavage of epoxy-carotenoids, resulting in reduced ABA synthesis [70, 71]. In our constructed network, the ATABA1 protein may interact with five CCDs (BpCCD1.1, BpCCD1.2, BpCCD4, BpCCD7 and BpCCD8), which may act synergistically with ATABA1 to affect the process of oxidative cleavage of epoxy-carotenoids. ATVAMP714 is predicted to interact with seven CCO proteins (BpCCD4, BpNCED2.2, BpNCED2.3, BpNCED2.4, BpNCED2. 5, BpNCED3 and BpNCED5), and previous studies have shown that ATVAMP71 and ATVAMP712 [72, 73], members of the ATVAMP71 family, are able to participate in the ABA-mediated drought response process in plants, while ATVAMP714 [74], which is structurally related to ATVAMP71 and ATVAMP712, is likely to have a similar function, and this process is likely to involve CCO proteins. Two members of the basic helix-loop-helix (bHLH) transcription factor (TF) gene family, BPChr06G29579 (bHLH) and HEC1 (bHLH), are predicted to potentially interact with CCOs. bHLH is one of the largest TF families in plants, with several members in different species involved in abiotic stress response and phytohormone (ABA, JA, IAA, etc.) signaling pathways [75, 76], biological processes in which CCOs are also likely to be indirectly involved. In addition to the above proteins, CYP90D1 (BPChr06G19200) [77], ZDS (BPChr05G31567) [78, 79], RACK1A (BPChr12G02842) [80], MAX2 (BPChr11G15589) [81, 82], and ATTBP2 (BPChr07G24868) [83, 84] have also been reported in other species to be involved in a variety of growth and developmental processes as well as in the stress response of plants, all of which also have the possibility of indirect involvement of CCOs.

The functions of most of BpCCOs still await further verification. With the development of molecular biology, bioinformatics and botany, the specific functions of these genes are expected to be determined. Overall, these results provide a reference for the future study on BpCCO genes and the exploration of gene resources on stress response of plants.

Conclusions

A total of 16 CCO genes were identified from birch genome, and phylogenetic analysis showed that these genes could be classified into two subfamilies or six subgroups. Structural analysis and motif analysis showed that members of the subgroups had similar gene structures, but the motifs were highly variable. Chromosomal localisation results showed that the 16 BpCCOs genes were unevenly distributed on eight chromosomes. Colinearity analysis showed that BpCCOs had more colinear genes in the dicotyledonous plant Gossypium hirsutum. Promoter cis-element analysis showed that the promoters of BpCCOs contained a large number of abiotic stress response elements. Most of the BpCCOs were able to respond to ABA, salt, PEG and cold treatment. In addition, the protein interaction networks were constructed. Several proteins that may interact with BpCCO proteins were identified, which may function together with BpCCOs during plant resistance. Overall, this study provides an important reference for the study of the CCOs family and enriches the information related to the birch gene family.

Data availability

All data generated/analyzed are included in this manuscript (and supplementary files).

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Funding

This study was supported by the Local Post-doctoral Funding in 2023 (520415482), Full-time Post-doctoral Support Program (520415898), and the Fundamental Research Funds for the Central Universities (2572018AA32).

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  1. Jiajie Yu and Yiran Wang contributed equally to this work.

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  1. State Key Laboratory of Tree Genetics and Breeding, Northeast Forestry University, Heilongjiang Harbin, 150040, China

    Jiajie Yu, Yiran Wang, Heming Bai, Xiang Zhang & Ruiqi Wang

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  1. Jiajie Yu
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Contributions

R.W. designed the research, acquired the funding, and revised the manuscript. J.Y., Y.W. and X.Z. conducted the experiments, analyzed the data. H.B., R.W. and X.Z. drafted the manuscript and provided the plant materials.

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Correspondence to Ruiqi Wang.

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Yu, J., Wang, Y., Bai, H. et al. Genome-wide identification and expressional analysis of carotenoid cleavage oxygenase (CCO) gene family in Betula platyphylla under abiotic stress. BMC Genomics 25, 872 (2024). https://doi.org/10.1186/s12864-024-10777-2

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Keywords

BMC Genomics

ISSN: 1471-2164

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