Skip to main content
  • Research article
  • Open access
  • Published:

Comparative analysis of cytokinin response factors in Brassica diploids and amphidiploids and insights into the evolution of Brassica species

Abstract

Background

Cytokinin is a classical phytohormone that plays important roles in numerous plant growth and development processes. In plants, cytokinin signals are transduced by a two-component system, which involves many genes, including cytokinin response factors (CRFs). Although CRFs take vital part in the growth of Arabidopsis thaliana and Solanum lycopersicum, little information of the CRFs in the Brassica U-triangle species has been known yet.

Results

We identified and compared 141 CRFs in the diploids and amphidiploids of Brassica species, including B. rapa, B. oleracea, B. nigra, B. napus, and B. juncea. For all the 141 CRFs, the sequence and structure analysis, physiological and biochemical characteristics analysis were performed. Meanwhile, the Ka/Ks ratios of orthologous and paralogous gene pairs were calculated, which indicated the natural selective pressure upon the overall length or a certain part of the CRFs. The expression profiles of CRFs in different tissues and under various stresses were analyzed in B. oleracea, B. nigra, and B. napus. The similarities and differences in gene sequences and expression profiles among the homologous genes of these species were discussed. In addition, AtCRF11 and its ortholog BrCRF11a were identified to be related to primary root growth in Arabidopsis.

Conclusion

This study performed a genome-wide comparative analysis of the CRFs in the diploids and amphidiploids of the Brassica U-triangle species. Many similarities and differences in gene sequences and expression profiles existed among the CRF homologous genes of these species. In the bioinformatics analysis, we found the close relativity of the CRF homologous genes in the Brassica A and C genomes and the distinctiveness of those in the B genome, and the CRF homologous genes in B subgenome were considerably influenced by the A subgenome of B. juncea. In addition, we identified a new function of the Clade V CRFs related to root growth, which also clarified the functional conservation between Arabidopsis and B. rapa. These results not only offer useful information on the functional analysis of CRFs but also provide new insights into the evolution of Brassica species.

Background

Cytokinin is a major phytohormone that plays a key role in plant growth and development processes, such as leaf senescence [1, 2], root and shoot development [1, 3], and chloroplast development [4], as well as in biotic and abiotic stress responses [5,6,7]. In plants, cytokinin is perceived and responded through a multistep phosphorelay pathway, which is similar to the two-component system in bacteria [8, 9]. In Arabidopsis thaliana, cytokinin is recognized by sensor histidine kinases, which autophosphorylate the conserved His residue located at the kinase domain. Then, His-containing phosphotransfer proteins (HPs) transduce a signal. After a multistep His→Asp→His→Asp phosphorelay, the signal is transferred to Arabidopsis response regulators (ARRs), which comprise type-A ARRs, type-B ARRs, and type-C ARRs [9, 10]. Type-A ARRs are rapidly upregulated by cytokinin treatment, whereas type-B ARRs contain transactivating domains that regulate the transcription of cytokinin-activated targets, such as type-A ARRs [11, 12]. Cytokinin response factors (CRFs), a subset of AP2 transcription factors (TFs), are newly identified components in the cytokinin signaling pathway. They likely operate downstream of the HPs and include common or specific targets with type-B ARRs [13].

Thus far, 12 CRFs have been identified in A. thaliana [13, 14], 11 CRFs in Solanum lycopersicum [15], and 21 CRFs in Brassica rapa [16]. As components involved in cytokinin signal transduction, numbers of CRFs are closely related to plant development and stress responses [17]. For example, CRF6 negatively regulates leaf senescence [18], whereas the overexpression lines of CRF1, CRF3, or CRF5 display leaf senescence in early stages in A. thaliana [19]. AtCRF3 and AtCRF5 can promote the growth of lateral roots [19]. CRFs, such as AtCRF2, AtCRF3, and AtCRF6, affect female reproductive organ development by interfering with the development of the placenta and ovules [20]. In addition, numbers of CRF genes in several species are related to abiotic stress responses. In A. thaliana, AtCRF4 can be induced by cold stress [21], and AtCRF6 is related to oxidative stress and salt stress [18, 22]. In S. lycopersicum, SlCRF1 can be induced by cold and drought stresses, SlCRF2 and SlCRF3 are involved in drought and oxidative stresses, and SlCRF5 is related to flooding, drought, oxidative, and cold stresses [23, 24]. In B. rapa, BrCRF1, BrCRF2, and BrCRF19 are upregulated by drought stress, whereas BrCRF5 and BrCRF21 are induced by salt stress [16]. Notably, AtCRF2 can positively regulate salicylic acid-mediated plant immunity in A. thaliana, and plants overexpressing AtCRF5 exhibit pathogen resistance. All these phenomena suggest that CRFs play a role in biotic stress responses [25, 26].

Brassica consists of numerous species with a remarkable morphological diversity [27], which is a result of the long-term evolution. There are three diploids, namely, B. rapa (AA, 2n = 20), B. nigra (BB, 2n = 16), and B. oleracea (CC, 2n = 18). As a result of natrual hybridization between the diploids, there are three amphidiploids, namely, B. napus (AACC, 2n = 38), B. juncea (AABB, 2n = 36), and B. carinata (BBCC, 2n = 34). The relationship between these six species have been illustrated through the Brassica U-triangle [28]. This group of species provides an excellent model for studies on species evolution by homologous recombination and polyploidization. The relationship among Brassica species has been characterized by many methods [29], such as genomic in situ hybridization (GISH) with fluorescence in situ hybridization (FISH) [30, 31], ribosomal DNA probes [32, 33], sequence-characterized amplified region markers [34] or repetitive sequence elements [35, 36], and simple-sequence repeat (SSR) markers [37, 38]. Meanwhile, relevant analysis of certain genes or gene families were also performed in order to elucidate the evolution of Brassica species [39]. Many genomes of the Brassica species have been sequenced [40,41,42,43], thereby providing a basis for evolutionary analysis and smoothening the process of functional gene mining.

In this study, we identified all of the CRF genes in B. rapa, B. nigra, B. oleracea, B. napus, and B. juncea and analyzed their phylogeny, sequence properties, and selective pressure to reveal the evolution among these species. We also examined the expression patterns of these genes in different tissues and organs or under various treatments and obtained some useful information for future functional analysis of CRFs. The functions of CRFs are substantially determined by the similarities and differences among their sequences [44, 45]. The similarities and differences among the sequences of CRFs in these species also provided some clues of their functions. This research not only analyzed the functions of CRFs but also offered insights into the evolution of Brassica species, which would make significant impact on functional genomics and breeding improvement in Brassica crops.

Methods

Identification of CRFs in Brassica diploid species and their amphidiploids

The protein sequences of known CRFs in A. thaliana were downloaded from TAIR and then used as seed sequences to search NCBI (https://www.ncbi.nlm.nih.gov/) for B. rapa, B. oleracea, and B. napus and the Brassica Database [46] for B. rapa, B. oleracea, B. nigra, B. juncea, and B. napus. BlastP search with an expected value of 100 was applied. The protein sequences of the identified CRFs were examined with SMART (http://smart.embl-heidelberg.de/smart/ set_mode.cgi?GENOMIC = 1) [47] and ClustalX [48]. Protein sequences that did not contain the AP2 domain or CRF domain were excluded from the further analysis. These protein sequences, CDS, and genome sequences of the CRFs were downloaded from the Brassica Database [46].

Nomenclature and characterization analysis of CRFs

We identified orthologous genes by phylogenetic approach, and did blast to confirm their relations. All of the newly identified CRFs and BrCRFs were named on the basis of their orthologous genes in A. thaliana [14, 16], and the paralogous genes in each species were distinguished by English letters. CRF-related information, such as locus, chromosome position, ORF length, and deduced polypeptide length, was searched from B. rapa version 1.5 genome [42], B. oleracea version 1.1 genome [41], B. napus version 4.1 genome [40], B. nigra version 1.1 genome, and B. juncea version 1.5 genome [43]. The isoelectric point (pI) and molecular weight of the CRFs were predicted using Compute pI/Mw (http://web.expasy.org/compute_pi/) [49,50,51].

Motif recognition, gene structure, and phylogenetic analysis

The motifs of CRFs were identified with MEME (http://meme-suite.org/tools/meme) [52]. The protein sequences of the identified CRFs were used for multiple-sequence alignment by ClustalW [53] with a gap open penalty of 10 and a gap extension penalty of 0.2, and unrooted phylogenetic trees were generated with the neighbor-joining method with a 1000-replicate bootstrap and other default parameters in MEGA version 6 [54]. The sequence logoes were created by WedLogo 3 (http://weblogo.threeplusone.com/). Finally, the phylogenetic tree of all CRFs was decorated in Itol (http://itol.embl.de/) [55]. The gene structures of CRFs were analyzed and drawn with Gene Structure Display Server (http://gsds.cbi.pku.edu.cn/) [56].

Chromosome mapping and synteny analysis

Chromosomal location maps were drawn with MapChart in accordance with the positions of initiation codons and decorated in PhotoShop CS5 for the transcriptional orientation marks and bars. Synteny analysis was performed on GEvo (https://genomevolution.org/CoGe/GEvo.pl) [57] by using 100 kb sequence before and after each gene respectively, and non-CDS sequences were masked. Figures were decorated in PhotoShop CS5 to mark the gene names.

Analysis of evolutionary selection pressure

The synonymous (Ks) and nonsynonymous substitution (Ka) rates of orthologous and paralogous genes were calculated with MEGA version 6 [54] by using a Compute Pairway Distance plate. Ka/Ks ratios were calculated and subtotaled in Microsoft Excel 2007, and box plots were drawn in E Chart (http://www.ehbio.com/ImageGP/index.php/Home/Index/ Boxplot.html). Ka/Ks values of orthologous genes between Brassica species and A. thaliana with a sliding window of 20 codons were calculated and drafted in MATLAB R2017b [58].

Analysis of the putative promoter regions of CRFs

The upstream sequences (1500 bp) of the initiation codons of BrCRFs, BolCRFs, BniCRFs, BnaCRFs, and BjuCRFs were chosen as the putative promoter regions of CRFs and used to identify the cis-elements related to hormones and stresses. The cis-regulatory elements along the putative promoter sequences were identified by using PLACE (https://sogo.dna.affrc.go.jp/cgi-bin/sogo.cgi?lang=en&pj=640&action=page&page=newplace) [59] and PlantCARE (http://bioinformatics.psb.ugent.be/webtools/plantcare/html/) [60].

Plant growth and treatments

B. oleracea cv. Sanxiong was grown in the experimental farm of the Zhejiang Academy of Agricultural Sciences, whereas B. napus line 166–13 and B. nigra line 1611–01 were cultivated in the experimental farm of Zhejiang University. Roots, floral stems, leaves, flowers, siliques, sepals, petals, stamens, and pistils were sampled to analyze tissue- and organ-specific expression.

The three materials were also cultivated under a 14 h light/10 h dark photoperiod at 24 °C/22 °C for about 3 weeks before treatments. For the exogenous hormone treatments, 100 μM 6-BA, NAA, and abscisic acid (ABA) were sprayed onto the three materials, and controls were sprayed with double distilled water only. All of the materials were sampled at 0, 0.5, and 1 h after treatment. In the salt treatment, a nutrient solution with 200 mM NaCl was used as a treatment, and a normal nutrient solution was utilized as control. The materials were sampled at 0, 4, 8, and 16 h after treatment. The second true leaves in all of the treatment groups were sampled to minimize differences. All of the samples were frozen in liquid nitrogen immediately and then stored at − 75 °C.

RNA extraction and qRT-PCR analysis

For B. napus and B. nigra samples, TRIzol reagent (Invitrogen, Germany) was used to extract total RNA in accordance with the manufacturer’s instructions, and the first cDNA strand was synthesized using a TaKaRa reverse transcription system (Japan) in accordance with the manufacturer’s protocol. For B. oleracea samples, RNA extraction kits (Omega, USA) were utilized in accordance with the manufacturer’s instructions. qRT-PCR was performed with Primers for qRT-PCR (Additional file 1: Table S1) were designed by Primer version 5.0. A qRT-PCR mixture was 15 μL in volume and composed of 7.5 μL of SYBR Green Master Mix reagent (Toyobo, Japan), 0.6 μL of specific primer, 2 μL of cDNA, and 5.9 μL of ddH2O. qRT-PCR was run using a StepOne real-time PCR machine (BioRAD, USA) programmed to heat for 30 s at 95 °C, followed by 40 cycles of 5 s at 95 °C and 45 s at 55 °C–58 °C. The specificity of the reactions was verified through melting curve analysis. GAPDH [61] and 25S [62] were used as internal controls. Comparative ΔΔCT method was applied to analyze the relative expression levels of CRFs. Hierarchical clustering and heatmap representation of the expression pattern of CRFs were drawn in HemI [63]. Three biological replicates were included for each sample.

Arabidopsis mutant and transformation

Atcrf11 (AT3G25890) mutant was purchased from ABRC (SALK205786C). The full-length coding sequence of BrCRF11a was inserted into the pCAMBIA1301 vector and driven by the CaMV 35S promoter. The constructed vector was transformed into Arabidopsis plants by the floral-dip method with Agrobacterium strain GV3101 to obtain BrCRF11a-overexpressing transgenic Arabidopsis. The relative expressions of BrCRF11a and AtCRF11 in the three types of Arabidopsis seedlings were analyzed by qRT-PCR. AtTUB4 (TUBULIN BETA CHAIN 4, AT5G44340) was used as internal reference. The primers used here can be found in the Additional file 1: Table S1. All of the Arabidopsis plants (wild-type Col-0, Atcrf11 mutant and BrCRF11a-overexpressing transgenic Arabidopsis p35S::BrCRF11a) were grown on Murashige and Skoog (MS) medium for 5 days before the root lengths of the seedlings were measured.

Results

Identification, classification, and phylogenetic analysis of CRFs in the Brassica genomes

A total of 120 new CRFs, which simultaneously contain the AP2 domain and the CRF domain, were identified in Brassica species: 18 CRFs in B. oleracea, 24 CRFs in B. nigra, 38 CRFs in B. juncea, and 40 CRFs in B. napus (Table 1). The results searched from B. rapa version 1.5 genome were consistent with those from former research [16]. All of the 120 genes were named, and the 21 CRFs in B. rapa were renamed on the basis of their orthologs in A. thaliana. The paralogs were distinguished by English letters (Additional file 2: Table S2). In addition, the basic information of the genes was searched. The length of the gene sequences ranged from 441 bp to 1151 bp. In all of the species, the shortest gene sequence was that of CRF7, and the longest gene sequence was that of CRF3, except B. juncea in which the longest was CRF12. For the protein length (147–364 amino acids) and molecular weight (16.1–41.4 kDa), the shortest was found in CRF7, and the longest was observed in CRF3 in all of the species herein. The pI of the proteins ranged from 4.56 to 10.00. The protein with the lowest pI was detected in CRF3 in all of the species except B. juncea, whose CRF10 was the protein with the lowest pI. The protein with the highest pI was identified in CRF7 in all of the species except B. nigra, whose CRF8 was the protein with the highest pI.

Table 1 Numbers of CRFs in Brassica species

A phylogenetic tree was constructed using the protein sequences of the genes (Fig. 1). This result showed that the orthologs among genomes and the paralogs in one species were closely related. The genes can be divided into five clades: Clade I (CRF1s and CRF2s), Clade II (CRF3s and CRF4s), Clade III (CRF5s and CRF6s), Clade IV (CRF7s and CRF8s), and Clade V (CRF9–12 s). We found that Clades I, II, III, and V were closely related with one another, whereas Clade IV was distantly related with them.

Fig. 1
figure 1

Phylogenetic tree based on CRF homologous protein sequences in Brassica plants. The CRFs are divided into five clades and marked by different colors. The equidistant rings indicate the scale of relative divergence. The bootstrap values were calculated from 1000 replicates and the values less than 50% were hided. The figure was obtained by MEGA version 6 and Itol (http://itol.embl.de/)

Gene structure and conserved motif analysis of CRFs in Brassica species

The phylogenetic trees of CRFs in B. nigra (Fig. 2a), B. oleracea (Fig. 2b), B. napus (Fig. 2c), and B. juncea (Fig. 2d) were constructed separately. Five clades remained in each species, and this finding was consistent with the previous phylogenetic analysis (Fig. 1). Notably, all of the species here did not possess any other orthologs of AtCRF9. Gene structure analysis showed that most CRFs had only one exon except BnaCRF1a, BnaCRF1b, BnaCRF2a, BnaCRF3a, and BjuCRF12a, which contained two exons and one intron (Fig. 2). Conserved motif analysis and multiple alignment were performed using the CRFs’ protein sequences. The sequences could be divided into three types based on sequence similarity: Type A included proteins in Clades I, II, and III (CRF1–6 s), Type B comprised the proteins in Clade IV (CRF7s and CRF8s), and Type C consisted of proteins in Clade V (CRF9–12 s). All of the proteins had one AP2 domain (Motif 1, 2) and one CRF domain (Motif 3, 4). The TEH region (Motif 6) only existed in the N-terminal region of Type A proteins, and all of the Type A proteins contained a putative mitogen-activated protein kinase (MAPK) phosphorylation site (Motif 5) on the C-terminal region. Type B proteins were shorter and did not have motifs other than the AP2 and CRF domains. The length of the Type C proteins was similar to that of the Type A proteins. However, the former did not contain a TEH region and an MAPK motif. Instead, they possessed motifs with consensus sequences [FNF × ×L × IPD] and [GPSxLPD×DF × DV] (Fig. 2 and Additional file 3: Figure S1).

Fig. 2
figure 2

Phylogenetic relationships, gene structures, and motif analysis of CRFs in Brassica species. The CRFs in B. nigra (a), B. oleracea (b), B. napus (c), and B. juncea (d) are shown. In every figure, the phylogenetic relationship is shown on the left, the gene structure in middle, and the motifs on the right. The genes belonging to different clades were marked by red Latin numbers. Motif 1 and Motif 2 formed the AP2 domain. The CRF domain was comprised of Motif 3 and Motif 4. Motif 5 was a putative mitogen-activated protein kinase (MAPK) phosphorylation site. Motif 6 represented the TEH region

Chromosomal distribution comparison and synteny analysis of CRFs among Brassica species

A refined analysis of synteny blocks was performed by GEvo website (Additional file 4: Figure S2) and provided some clear hints to the origin of genes in allotetraploids (Table 2 and Additional file 5: Table S3). The gene origins of most of the genes in the allotetraploids could be found in the diploids, whereas few of them were newly generated. Moreover, some genes in the diploids did not have corresponding genes in the allotetraploids. In addition, some genes (BnaCRF2d, BnaCRF6c, BjuCRF6c and BjuCRF12b) were highly similar to their paralogous genes (Additional file 4: Figure S2).

Table 2 List of origin genes in B. oleracea and amphidiploid genes in B. napus

Chromosomal mapping of CRFs in B. rapa, B. oleracea, B. nigra, B. juncea, and B. napus was performed separately on basis of genomic information (Fig. 3 and Additional file 6: Figure S3). Results showed that the CRFs were distributed throughout almost all the chromosomes in every genome, except A04 in B. rapa; B05 in B. nigra; C04 and C05 in B. oleracea; A04, A10, and C09 in B. napus; and A04 and B01 in B. juncea.

Fig. 3
figure 3

Chromosomal mapping of CRFs in B. rapa, B. oleracea, and B. napus.. The CRFs in B. rapa (a), B. oleracea (b), and B. napus (c) are shown except those located on the scaffolds. The locations were shown on the left of the chromosomes, whereas the gene names were on the right. The arrows next to gene names show the direction of transcription. The bar indicates the size of 5 Mb

By comparing the B. oleracea genome with the C subgenome of B. napus (Fig. 3b and c), the chromosomal location of most allotetraploid genes are similar to their origin genes. Although some genes, such as BolCRF5, BolCRF7a, BolCRF8a, BolCRF10a, and BnaCRF8c, possess incomplete location information, their corresponding genes offer hints. However, gene rearrangements are also present. For example, BolCRF3c is located in chromosome C07 in B. oleracea, and its corresponding gene BnaCRF3d is in chromosome C02 in B. napus. Moreover, no origin gene of BnaCRF2d is present on the corresponding site in the B. oleracea genome. On one hand, the origin gene may have degenerated after hybridization. On the other hand, the chromosomal sequence around BnaCRF2d is highly similar to that of BnaCRF2b and may be a copy of BnaCRF2b derived from segmental duplication or another mechanism. Indeed, BolCRF3b and BolCRF4c possess no corresponding gene in the other genome. The relationship of the corresponding genes between B. rapa and the A subgenomes of B. napus and B. juncea is similar to that between B. oleracea and the C subgenome of B. napus (Fig. 3a, c and Additional file 6: Figure S3B). In the A subgenome of B. napus, BnaCRF4a, BnaCRF6a, and BnaCRF8d are rearranged after hybridization, and the corresponding genes of BrCRF3a, BrCRF4c, BrCRF7a, and BrCRF11b were not found. Especially, BnaCRF12, the corresponding gene of BrCRF12, is located in chromosome C05, which belongs to the C subgenome of B. napus. Similarly, BnaCRF6c is also significantly similar to BnaCRF6b in chromosome C08. In the A subgenome of B. juncea, only the corresponding genes of BrCRF4a, BrCRF4b, and BrCRF4c were not observed. Although the information was incomplete for BjuCRF4, the number of CRF4 genes decreased significantly in B. juncea. By contrast, no origin gene of BjuCRF5b was found in B. rapa; the gene possibly degenerated after hybridization. BjuCRF8a, the corresponding gene of BrCRF8a, was rearranged from the A subgenome to C subgenome. At the same time, BjuCRF6c was highly similar to BjuCRF6b, which was coincident with BnaCRF6c in B. napus. This situation was also noted between BjuCRF12a and BjuCRF12b.

These findings were much more complicated for B. nigra and B. juncea (Additional file 6: Figure S3). All the corresponding genes were rearranged, and no significant regularity was found among these genes. A total of 7 of 24 CRFs in B. nigra have no corresponding genes in B. juncea, and this proportion was higher than that in B. rapa (1 of 21) and in B. oleracea (2 of 18).

Gene retention ratio and evolutionary selection pressure analysis of CRFs in the Brassica species

The numbers of CRFs counted by genome (subgenome) and gene name separately are displayed in Table 1. Genome triplication occurred in the Brassica species since their divergence from the A. thaliana lineage at about 13–17 million years ago (MYA) [42]. Thus, the diploids and their amphidiploids reasonably possess 3 and 6 paralogs, respectively, for every corresponding CRF gene in A. thaliana. On this basis, gene retention ratios were calculated by genome (subgenome) and gene name separately (Additional file 7: Figure S4). Although the gene retention ratios in the genomes or subgenomes were almost the same, the gene retention ratios for B. nigra and B. rapa were higher, but lower for the B subgenome in B. juncea, than that in the other species. For the gene retention ratios of different genes, more CRF10 genes and less CRF12 genes were maintained. Furthermore, no CRF9 gene existed in the Brassica species. In addition, the gene retention ratios of CRFs in the three sub-genomes of B. rapa, B. oleracea, and B. napus were analyzed (Additional file 8: Figure S5.). The result showed that the gene retention ratios of CRFs in the three sub-genomes were the same in B. oleracea. In B. rapa, B. napus A, and B. napus C, the gene retention ratios of CRFs were higher in LF and MF1 and lower in MF2. Furthermore, the gene retention ratios of CRFs in the three sub-genomes in B. rapa and B. oleracea were higher (0.5 or 0.58) than that in B. napus A and B. napus C (0.33 or 0.42).

The Ks (synonymous substitution rates) and Ka (non-synonymous substitution rates) were determined to explore the gene divergence after duplication. The Ka/Ks value indicates the selection pressure on a gene pair. Ka/Ks < 1 means negative selection, Ka/Ks = 1 means neutral selection, and Ka/Ks > 1 means positive selection [64]. We obtained the Ka/Ks ratios from duplicated CRF orthologous gene pairs (Fig. 4a and b) between the Brassica species and A. thaliana and duplicated CRF paralogous gene pairs (Fig. 4c and d) in every Brassica genome. All the gene pairs underwent negative selection, and the Ka/Ks values ranged from 0 to 0.5. In different Brassica species, the Ka/Ks values of CRF gene pairs seemed to be similar. The results indicate that the Brassica species have encountered the similar selection pressure during the processes of domestication (Fig. 4a and c). For different CRF genes, in the evolution between Brassica species and A. thaliana, the Ka/Ks values of CRF7s were the lowest, whereas those of the CRF11s were the highest. However, in the Brassica species, the Ka/Ks values of the CRF1s and CRF8s were the lower, whereas those of CRF6s, CRF7s, CRF10s, and CRF11s were relatively higher (Fig. 4b and d).

Fig. 4
figure 4

Box-plots of the Ka/Ks values of homologous gene pairs in Brassica species and Arabidopsis thaliana. Orthologous gene pairs between Brassica species and Arabidopsis thaliana (a and b) and paralogous gene pairs among each Brassica species (C and D) were shown. The statistics by species (a and c) and by gene name (b and d) are displayed. The values of CRF9 and CRF12 are not shown because of the exceedingly low numbers

Furthermore, we calculated the Ka/Ks values of the CRF orthologous gene pairs of Br-At, Bol-At, and Bna-At with a sliding window of 20 codons. Thus, we observed whether the Ka/Ks ratios changed in different parts of the protein (Additional file 9: Figure S6). We found that the Ka/Ks values of different protein parts were extremely distinct. Almost every protein contained at least one part with a Ka/Ks value more than 1. This result indicates that the mutations in these parts underwent positive selection. However, most of these parts avoided but were close to the conserved motifs. In addition, the C-termination parts of the proteins usually possessed relatively high Ka/Ks values of more than 1. Meanwhile, the orthologous genes manifested a similar variation trend.

Analysis of the putative promoter regions of CRFs in Brassica species

Gene expression variation among species is believed to be responsible for much of the phenotypic diversity [65], and many genes, with tissue-specific or stress-responsive expression patterns, are closely related to the cis-regulatory elements located upstream of these genes [66]. To thoroughly understand the function of the CRF genes and determine the presence of functional diversity among Brassica species, the putative promoter regions of CRFs in Brassica species were analyzed using PLACE website. The cis-regulatory elements related to hormones and stresses were counted, such as ARR1AT, CPBCSPOR, NTBBF1ARROLB, MYBATRD22, CBFHV and so forth. These results showed that all the CRFs contained several cis-regulatory elements related to hormones and stresses in their promoters (Additional file 10: Table S4). In particular, elements related to cytokinin, auxin, ABA, and GA were much more than other hormones. Similarly, more cold-stress elements were present than those related to other stresses. Meanwhile, we found that for many paralogous genes, there always existed a gene containing much more elements than its paralogous genes. Meanwhile, the PlantCARE website was also utilized to analyze the promoters. Although the dataset was restricted, the result coincided with the prediction of PLACE website (Additional file 11: Table S5).

Expression pattern of CRFs in different tissues and organs of the Brassica species

The temporal and spatial expression of genes is the foundation of their function [67]. To obtain some clues about the functions of BolCRFs, BniCRFs, and BnaCRFs, qRT-PCR was used to analyze the transcription levels of these genes in the roots, stems, leaves, flowers, and siliques (Fig. 5). This result showed that the relative expressions of 4 BniCRFs (BniCRF3a, 3b, 5b, and 6a) and 11 BnaCRFs (BnaCRF1b, 2b, 2c, 3a, 3b, 3e, 4e, 4f, 5a, 5b, and 6a) among different tissues were much more different than those of BolCRFs and other BniCRFs or BnaCRFs. Meanwhile, we found that almost all the CRFs exhibited higher relative expression levels in flowers and siliques. A total of 42, 59, and 48 out of 81 analyzed CRFs also showed more transcripts in the roots, stems, and leaves, respectively. For paralogous genes in one species, some genes showed similar expression patterns in different tissues (BolCRF3b with BolCRF3c, BniCRF8a with BniCRF8b, BnaCRF4a with BnaCRF4d, and so on), while some genes expressed complementarily (BolCRF4a with BolCRF4b, BolCRF7a with BolCRF7b, BnaCRF6a with BnaCRF6c, and so on). As regards the relationship between original genes and their corresponding genes, BolCRF1, BolCRF2, BolCRF3a, BolCRF3c, BolCRF4b, BolCRF5, BolCRF6a, BolCRF7a, and BolCRF8a exhibited similar expression patterns to their corresponding genes, but BolCRF4a, BolCRF6b, BolCRF7b, BolCRF8b, BolCRF10a, BolCRF10b, and BolCRF11 displayed complementary expression profiles. Furthermore, by comparing the collinearity genes between B. oleracea and B. nigra, we noted the lacking orderliness that may have been derived from the distant relationship between such species.

Fig. 5
figure 5

Hierarchical clustering and heatmap representation for the expression pattern of CRFs in different tissues and organs of Brassica species. CRFs in different species are marked by different colors: B. oleracea (red), B. nigra (blue), and B. napus (black). R: root, L: leaf, F: flower, Sl: silique, Se: sepal, Pe: petal, St: stamen, and Pi: pistil. The relative expression levels of genes are presented using fold-change values transformed to Log2 format

Because CRFs belong to the AP2 super family [13] and AP2 is considered to be important for flower development [68], we further analyzed the transcriptional levels of the CRFs in sepals, petals, stamens, and pistils (Fig. 5). We found that most of the BolCRFs and BniCRFs showed smaller changes of relative expression levels in the four floral organs, whereas the relative expression levels of most BnaCRFs changed a lot among the four floral organs. Furthermore, some genes showed pistil-preferential expression among the four floral organs. These genes were BolCRF2, BolCRF3b, BolCRF3c, BolCRF4c, BniCRF11b, BnaCRF4e, and BnaCRF10b. Meanwhile, BolCRF1, BolCRF4a, BniCRF6c, BnaCRF1b, BnaCRF2b, BnaCRF2c, BnaCRF3a, BnaCRF3b, BnaCRF3e, BnaCRF4f, BnaCRF5a, BnaCRF5b, and BnaCRF6a also revealed higher relative expression levels in pistil. On the contrary, genes such as BolCRF7b, BniCRF5a, BniCRF5b, BniCRF6a, BnaCRF7a, BnaCRF7b, and BnaCRF7d exhibited lower relative expression levels in the pistil but higher relative expression levels in other floral organs.

Effects of exogenous 6-BA, NAA, and ABA on the expression of CRFs in Brassica species

CRF genes were firstly discovered to respond to exogenous cytokinin, which explains their designation as CRFs [13]. To confirm whether the CRFs respond to cytokinin, qRT-PCR was applied to test the relative expression levels of the CRFs at 0.5 and 1 h after 6-BA treatment. Results showed most of the CRFs tested responded to exogenous cytokinin in various degrees (Fig. 6a). BolCRF3b, BolCRF6a, BolCRF6b, BolCRF10a, BniCRF1, BniCRF2b, BniCRF3a, BniCRF8a, BniCRF8b, BniCRF10a, BniCRF10c, BnaCRF1b, BnaCRF2a, BnaCRF2b, BnaCRF2d, BnaCRF3c, BnaCRF3d, BnaCRF3e, BnaCRF4b, BnaCRF4e, BnaCRF5a, BnaCRF5b, BnaCRF6b, BnaCRF6c, BnaCRF6d, BnaCRF7a, BnaCRF10c, BnaCRF10f, and BnaCRF11b were up-regulated significantly, whereas BolCRF3c, BolCRF4a, BolCRF4b, BolCRF5, BniCRF3b, BniCRF3c, BniCRF4a, BniCRF4b, BniCRF6c, and BnaCRF4c were obviously down-regulated. The genes initially up-regulated then down-regulated were BniCRF2a, BniCRF5a, BniCRF5b, BniCRF10b, and BniCRF11b, whereas those initially down-regulated then up-regulated were BniCRF6b, BnaCRF1a, BnaCRF2c, and BnaCRF6a. Three pairs of genes in B. oleracea and B. napus (BolCRF6a with BnaCRF6d, BolCRF6b with BnaCRF6b, and BolCRF10a with BnaCRF10f) showed the same response profiles. No significant regularity was recognized between B. oleracea and B. nigra.

Fig. 6
figure 6

Hierarchical clustering and heatmap representation for the expression pattern of CRFs in Brassica species with exogenous 6-BA, NAA, and ABA. The genes’ relative expression levels at 0, 0.5, and 1 h after treatment with 6-BA (a), NAA (b), and ABA(c). The CRFs in different species are marked by different colors: B. oleracea (red), B. nigra (blue), and B. napus (black). The relative expression levels of genes are presented using fold-change values transformed to Log2 format

In addition, more than 20 auxin-related genes can also be regulated by cytokinin, this observation suggests that auxin–cytokinin crosstalk may result from some genes co-regulated by the two hormones [69]. We analyzed the relative expression levels of the CRFs at 0.5 and 1 h after NAA treatment; the results revealed that numbers of genes can be regulated by NAA (Fig. 6b). On one hand, some genes were significantly up-regulated and included BolCRF3a, BolCRF4b, BniCRF4a, BniCRF5a, BniCRF6a, BniCRF7a, BniCRF10c, BnaCRF1a, BnaCRF1b, BnaCRF2a, BnaCRF3b, BnaCRF3c, BnaCRF3e, and BnaCRF10a. On the other hand, several genes were down-regulated obviously, namely, BolCRF3b, BolCRF4a, BolCRF4c, BolCRF6a, BniCRF1, BniCRF2a, BniCRF4c, BniCRF6c, BnaCRF2c, BnaCRF3a, BnaCRF3d, BnaCRF4a, BnaCRF4d, BnaCRF4e, BnaCRF4f, BnaCRF5a, BnaCRF5b, BnaCRF6b, BnaCRF6d, BnaCRF10b, BnaCRF10d, and BnaCRF10e. Meanwhile, BolCRF3c, BnaCRF2b, BnaCRF4b, BnaCRF4c, BnaCRF6a, BnaCRF7a, BnaCRF7b, BnaCRF7c, BnaCRF7d, BnaCRF8a, BnaCRF8b, BnaCRF8c, BnaCRF8d, BnaCRF10c, BnaCRF10f, BnaCRF11a, BnaCRF11b, and BnaCRF12 were initially down-regulated and then up-regulated. Conversely, BniCRF4b and BniCRF8b were initially up-regulated then down-regulated. Significantly, the paralogous genes of BnaCRF1, BnaCRF5, BnaCRF7, BnaCRF8, and BnaCRF11 displayed similar response profiles. The response profiles to NAA of two genes, namely, BolCRF4a and BolCRF6a, were similar to those of their corresponding genes in B. napus (BnaCRF4f and BnaCRF6d, respectively).

Analysis of the promoter regions of the CRFs showed the existence of several elements related to ABA. Therefore, ABA treatment was performed to test whether the CRFs can response to exogenous ABA. qRT-PCR was performed to analyze the relative expression levels of the CRFs at 0.5 and 1 h after ABA treatment. In fact, many CRFs responded to ABA (Fig. 6c). BolCRF4b, BniCRF1, BniCRF2a, BniCRF3a, BniCRF3b, BniCRF3c, BniCRF4a, BniCRF4b, BniCRF4c, BniCRF6c, BniCRF7a, BniCRF8b, BniCRF10a, BniCRF10b, BniCRF10c, BniCRF11a, BniCRF11b, BnaCRF1b, BnaCRF2c, BnaCRF5a, BnaCRF5b, BnaCRF7a, BnaCRF10a, BnaCRF10c, and BnaCRF10d were up-regulated by ABA. On the contrary, ABA can significantly down-regulate BolCRF3a, BolCRF3b, BolCRF4a, BolCRF6a, BolCRF8a, BolCRF8b, BolCRF10a, BnaCRF2a, BnaCRF6a, BnaCRF6d, BnaCRF7b, BnaCRF8c, BnaCRF8d, BnaCRF10e, BnaCRF10f, BnaCRF11a, BnaCRF11b, and BnaCRF12. Meanwhile, BnaCRF2d, BnaCRF4c, and BnaCRF4e are down-regulated initially and subsequently up-regulated. Especially, paralogous genes of BniCRF3, BniCRF4, BniCRF10, BniCRF11, BolCRF8, and BnaCRF5 show similar response profiles, and the response profiles of BolCRF6a, BolCRF8a, and BolCRF10a are consistent with those of their corresponding genes in B. napus (BnaCRF6d, BnaCRF8c, and BnaCRF10f).

Expression profiles of BolCRFs, BniCRFs, and BnaCRFs under salt stress

To date, many genes belonging to the AP2/ERF gene family from various plant species have been shown to be involved in abiotic stress responses [70, 71], especially in the drought and salt stress response [72]. The expression profiles of CRFs under salt stress for 4, 8, and 16 h were analyzed by qRT-PCR (Fig. 7). In B. oleracea, BolCRF3b and BolCRF11 were up-regulated, while BolCRF1, BolCRF2, BolCRF3a, BolCRF3c, and BolCRF4b were down-regulated continuously after salt treatment. The expressions of other BolCRFs were not changed. In B. nigra, 5 genes (BniCRF1, BniCRF2a, BniCRF10a, BniCRF11a, and BniCRF11b) were up-regulated, while 4 genes (BniCRF3a, BniCRF3b, BniCRF4c, and BniCRF5b) were down-regulated sustainedly, and the expression changes of the other BniCRFs were zigzag. In B. napus, 8 genes were up-regulated persistently, namely BnaCRF3e, BnaCRF4b, BnaCRF4e, BnaCRF5b, BnaCR10b, BnaCR10e, BnaCRF10f, and BnaCRF12. Five genes, consist of BnaCRF2a, BnaCRF3b, BnaCRF10c, BnaCRF10d, and BnaCRF11a, were down-regulated continuously. However, the expression changes of the other BnaCRFs were fluctuant under salt stress.

Fig. 7
figure 7

Hierarchical clustering and heatmap representation for the expression patterns of CRFs in Brassica species under salt stress. The genes’ relative expression levels at 0, 4, 8, and 16 h after salt treatment. The CRFs of different species are marked by different colors: B. oleracea (red), B. nigra (blue), and B. napus (black). The relative expression levels of genes are presented using fold-change values transformed to Log2 format

Functional analysis of AtCRF11 and BrCRF11a in the root growth of Arabidopsis

Many CRFs were found to be highly expressed in the root, and some can even modulate root growth in Arabidopsis [19, 22]. However, most studies focused on the CRFs in Clades I, II, III, and IV; studies on the CRFs of Clade V are limited. Interestingly, in our previous study, we found that some CRFs in Clade V, such as CRF11, exhibited preferential expression in the root of B. rapa. To examine whether AtCRF11 and its orthologous gene BrCRF11a play a role in the root growth of Arabidopsis, we grew three types of Arabidopsis (wild type Col-0, Atcrf11 mutant and BrCRF11a-overexpressing transgenic Arabidopsis p35S:: BrCRF11a) on MS medium. Relative expressions of BrCRF11a and AtCRF11 in the three types of Arabidopsis seedlings were analyzed (Fig. 8b). BrCRF11a and AtCRF11 are orthologous genes, and the similarity of their nucleotide sequences is 81%. It is difficult to design primers for qRT-PCR to distinguish them perfectly. They might affect each other in the expression analysis, but we could find the up-expression and down-expression of the two genes to some extent. After 5 days, an obvious difference was noted in the root lengths of the three types of Arabidopsis (Fig. 8a). In the Atcrf11 mutant, the root length was shorter than that of the wild type, whereas that of p35S::BrCRF11a was much longer than that of the wild type. The statistical analysis of the changing root lengths among the three types of Arabidopsis showed that the differences were fairly significant (Fig. 8c).

Fig. 8
figure 8

Functional analysis of AtCRF11 and BrCRF11a in the root growth of Arabidopsis. a Five-day-old seedlings growing on MS medium. The length of a square slide is about 1.2 cm. b Relative expression analysis of BrCRF11a and AtCRF11 in the three types of Arabidopsis. c Statistical analysis of the changing root length among the three types of Arabidopsis.t” test was applied, and P < 0.01 is marked by “**”

Discussion

In this study, we identified the CRFs (Additional file 2: Table S2) in diploids (B. rapa, B. nigra, and B. oleracea) and amphidiploids (B. napus and B. juncea) of Brassica. Although no new member was found in B. rapa [16], we updated some of the species’ information, which is essential to subsequent investigations. In general, most of the new CRFs, except for BnaCRF1a, BnaCRF1b, BnaCRF2a, BnaCRF3a, and BjuCRF12a, do not contain introns (Fig. 2). Among these genes, BnaCRF1a and BjuCRF12a, are consistent with their original genes BrCRF1 and BrCRF12, respectively, whereas the introns of BnaCRF1b, BnaCRF2a, and BnaCRF3a might emerge after the hybridization of the A and C genomes. In terms of CDS and protein lengths, as well as the molecular weights and pI of the CRFs in the same clade, similar characters were found among the Brassica species. In addition, the protein sequences of all the CRFs were aligned by ClustalX [48], and similar domains and motifs were identified (Additional file 3: Figure S1) [16, 45]. These results suggest that CRFs possess conserved functions among these species, which coincide with the previous result [14].

The Brassica diploids underwent an extra whole-genome triplication (WGT) event after diverging from A. thaliana [73, 74]. Thus, we calculated the gene retention of every gene and classified them by genome/subgenome and gene name (Additional file 7: Figure S4). This result showed that the gene retentions were similar among genomes but ranged from genes with no ortholog of AtCRF9 to those with almost no loss of AtCRF10 ortholog. This biased gene loss following whole-genome duplication is considered to indicate the gene functions [75].

To analyze the selective pressure suffered by the orthologous and paralogous gene pairs, the Ka/Ks ratios were calculated. Ka/Ks < 1 reveals a negative selection, whereas Ka/Ks > 1 indicates a positive selection. Generally speaking, the Ka/Ks ratios of all the CRFs ranged from 0 to 0.5, which suggests a stringent negative selection applied on these genes. Meanwhile, in different Brassica species, the Ka/Ks values of orthologs or paralogs were almost the same (Fig. 4a and c). However, the Ka/Ks values of the orthologs or paralogs showed an extraordinary difference when classified by gene name. For the orthologous gene pairs between Brassica species and A. thaliana, the selection pressures on the CRF7s were the severest, and the selection pressures on the CRF11s were the mildest along the evolution from A. thaliana to Brassica species (Fig. 4b). For the paralogs within each of the Brassica species, the selective pressures on the paralogous genes of CRF1s and CRF8s were likely stronger, and the paralogs of CRF6s, CRF7s, CRF10s, and CRF11s have encountered a milder natural selection within a Brassica genome. Meanwhile, the Ka/Ks values of orthologous gene pairs were around 0.3, which was higher than those of paralogous gene pairs at about 0.2. This result suggests a weaker natural selection between the Brassica species and A. thaliana than that in the Brassica species alone. Furthermore, meticulous works were carried out to analyze the Ka/Ks values of the different regions in one gene compared with its ortholog in A. thaliana with a sliding window (Additional file 9: Figure S6). We found that most of the CRFs in B. rapa, B. oleracea, and B. napus achieved a peak of Ka/Ks value of more than 1 in the last 100 codons of the C-terminal region. This result implies that the mutations in this region are positively selected, which highly likely embodies their functional differentiation. This opinion is supported by previous research; for instance, the transcriptional activity of AtCRF5 was found to be governed by the C-terminal domain [44], and the C-terminal sequence divergence was correlated with vascular expression [45]. Besides, some Ka/Ks peaks exceeding 1 were located in the N-termination and in regions close to the AP2 domain; the functions of these regions remain to be elucidated.

Given the wide application of synteny analysis in genome comparison and evolutionary analyses [76, 77], we performed a meticulous synteny analysis for the CRFs between the amphidiploids and their parental diploids to ascertain where the CRFs in the amphidiploids originate (Additional file 4: Figure S2). As a result, we obtained the original genes in the diploids and their corresponding genes in the amphidiploids (Table 2 and Additional file 5: Table S3). On this basis, the gene rearrangements that occurred after hybridization were discovered, such as BolCRF3c with BnaCRF3d, BnaCRF4a with BrCRF4a, BjuCRF8a with BrCRF8a and so on. Moreover, many genes, such as BrCRF11b, BnaCRF3e, BnaCRF4c, and BjuCRF5b, do not possess an original gene or corresponding amphidiploid gene probably because of incomplete genome information or the degeneration of corresponding genes during evolution after hybridization. The CRF distribution in the B. nigra genome differed from those in B. rapa and B. oleracea; this result is consistent with a previous conclusion on the close relativity of the Brassica A and C genomes and the distinctiveness of the B genome [78, 79]. However, the CRF distribution significantly differed between the genome of B. nigra and the B subgenome of B. juncea. This result implies that the CRFs in the B subgenome were considerably influenced by the A subgenome of B. juncea. Otherwise, this result was derived from the low sequencing proportion (68%) of the B. nigra genome [43]. Notably, four gene pairs (BnaCRF2b with BnaCRF2d, BnaCRF6b with BnaCRF6c, BjuCRF6b with BjuCRF6c, and BjuCRF12a with BjuCRF12b) were extraordinarily similar to each other and located in different subgenomes of an amphidiploid. On one hand, one gene in the pair may be a copy of the other, which was rearranged [80, 81]. On the other hand, a similar gene may existed in their parental genomes but degenerated after hybridization.

To find clues to the functions of the CRFs in B. nigra, B. oleracea, and B. napus, we analyzed the expression patterns of these genes in different organs. All the CRFs were constitutively expressed genes, but different relative expression levels were noted in different organs (Fig. 5). The relative expression levels of almost all of the CRFs were higer in the flowers and siliques; this observation suggests the genes’ important roles in reproductive development, which was coincident with previous research [20]. Among the four floral organs, many CRFs presented higher relative expression levels in the pistils; this finding indicates the link between CRFs and pistil development. The crosstalk of cytokinin with other phytohormones is well known to be involved in many plant growth processes [3, 82]. In this present research, numerous cis-elements related to hormones were found in the putative promoter region of the CRFs (Additional file 10: Table S4 and Additional file 11: Table S5). Additionally, most CRFs were found to respond to cytokinin (6-BA), auxin (NAA), and ABA treatments, although the response patterns are dissimilar (Fig. 6). Such result agrees with those of the CRFs that highly participate in the crosstalk between cytokinin and other hormones, such as auxin, ABA, and salicylic acid [20, 25, 83]. To date, numbers of AP2/ERF TFs have been identified to be related to abiotic stress responses in various plant species [70, 71]. Since a subfamily of the AP2/ERF family consist of ERF TFs, some members of the ERF subfamily have been proven to respond to many abiotic stresses, such as high salinity and drought [84]. Thus, CRFs, as Group VI and VI-L members of the ERF subfamily, also share the capability to respond to abiotic stresses [16, 23]. A similar result was obtained in this study (Fig. 7), and cis-elements related to stresses in the putative promoter region of the CRFs (Additional file 10: Table S4 and Additional file 11: Table S5) also supported our results.

B. napus and B. juncea are known to be formed ~ 7500 years or 0.038–0.055 MYA by the hybridization between B. rapa and B. oleracea/B. nigra [40, 43]; such event is far behind the divergence time of B. rapa (13–17 MYA) [42]. Although the evolution time is relatively shorter for the amphidiploid B. napus, the CRFs in this genome considerably differ from those of its parental genomes. For example, only 3 of 16 CRF gene pairs between B. napus and B. oleracea exhibited metastable expression patterns in at least two situations in this research. The orthologous gene pairs among the three diploids also shared low similarities in expression profiles [16]. All these results indicate that CRFs likely serve species-specific functions despite their numerous common functions.

In our previous study [16], we found that the relative expression level of BrCRF11a in the root of B. rapa was higher. In this present study, we found that the relative expression levels of BolCRF11, BniCRF11a, and BniCRF11b in the root were also higher (Fig. 5). These results indicate that the CRF11s may be related to the root growth. We analyzed the functions of AtCRF11 and BrCRF11a in the Arabidopsis root. Knocking out AtCRF11 inhibited primary root growth, whereas overexpressing BrCRF11a in Arabidopsis resulted in primary root growth promotion. These findings confirmed our hypothesis and agreed with those of previous works, which indicated the expression or function of the CRF genes in the root in many species, such as A. thaliana [19], S. lycopersicum [24], and B. rapa [16]. However, the relative expression levels of BnaCRF11a and BnaCRF11b in the root were lower. It needs further study to analyze the functions of CRF11s in B. rapa, B. oleracea, and B. napus, to find whether the fuctional differentiation exists and to explore their precise biological roles.

Conclusion

In this study, we characterized 141 CRF genes in three diploids and two amphidiploids of Brassica U-triangle species. On the basis of the comparisons among their sequences and expression patterns, we analyzed the functional inheritance and differentiation of CRFs among the species during the evolution. Our results showed the close relativity of the Brassica A and C genomes and the distinctiveness of the B genome, and the B subgenome was considerably influenced by the A subgenome of B. juncea.. Furthermore, we firstly discovered the function of a Clade V CRF, CRF11, related to root growth. This study provided insights into the functional genomics and evolutionary biology of plants and obtained useful information for fine farming and improved breeding.

Abbreviations

6-BA:

6-Benzylaminopurine

A. :

Arabidopsis

ABA:

Abscisic acid

ARRs:

Arabidopsis response regulators

B. :

Brassica

CRF :

Cytokinin Response Factor

HPs:

His-containing phosphotransfer proteins

Ka :

Non-synonymous substitution rates

Ks :

Synonymous substitution rates

MS:

Murashige and Skoog

MYA:

Million years ago

NAA:

1-naphthylacetic acid

qRT-PCR:

Quantitative reverse-transcription PCR

S. :

Solanum

TFs:

Transcriptional factors

WGT:

Whole-genome triplication

References

  1. Riefler M, Novak O, Strnad M, Schmulling T. Arabidopsis cytokinin receptor mutants reveal functions in shoot growth, leaf senescence, seed size, germination, root development, and cytokinin metabolism. Plant Cell. 2006;18(1):40–54.

    Article  CAS  Google Scholar 

  2. Ma XQ, Zhang J, Burgess P, Rossi S, Huang BR. Interactive effects of melatonin and cytokinin on alleviating drought-induced leaf senescence in creeping bentgrass (Agrostis stolonifera). Environ Exp Bot. 2018;145:1–11.

    Article  CAS  Google Scholar 

  3. Liu JL, Moore S, Chen CL, Lindsey K. Crosstalk complexities between auxin, cytokinin, and ethylene in Arabidopsis root development: from experiments to systems modeling, and back again. Mol Plant. 2017;10(12):1480–96.

    Article  CAS  Google Scholar 

  4. Cortleven A, Marg I, Yamburenko MV, Schlicke H, Hill K, Grimm B, Schaller GE, Schmulling T. Cytokinin regulates the etioplast-chloroplast transition through the two-component signaling system and activation of chloroplast-related genes. Plant Physiol. 2016;172(1):464–78.

    Article  CAS  Google Scholar 

  5. O'Brien JA, Benkova E. Cytokinin cross-talking during biotic and abiotic stress responses. Front Plant Sci. 2013;4:451.

    PubMed  PubMed Central  Google Scholar 

  6. Wang FF, Cheng ST, Wu Y, Ren BZ, Qian W. A bacterial receptor PcrK senses the plant hormone cytokinin to promote adaptation to oxidative stress. Cell Rep. 2017;21(10):2940–51.

    Article  CAS  Google Scholar 

  7. Zwack PJ, Rashotte AM. Interactions between cytokinin signalling and abiotic stress responses. J of Exp Bot. 2015;66(16):4863–71.

    Article  CAS  Google Scholar 

  8. Kakimoto T. Perception and signal transduction of cytokinins. Annu Rev Plant Biol. 2003;54:605–27.

    Article  CAS  Google Scholar 

  9. To JPC, Kieber JJ. Cytokinin signaling: two-components and more. Trends Plant Sci. 2008;13(2):85–92.

    Article  Google Scholar 

  10. Zdarska M, Dobisova T, Gelova Z, Pernisova M, Dabravolski S, Hejatko J. Illuminating light, cytokinin, and ethylene signalling crosstalk in plant development. J Exp Bot. 2015;66(16):4913–31.

    Article  CAS  Google Scholar 

  11. Mason MG, Mathews DE, Argyros DA, Maxwell BB, Kieber JJ, Alonso JM, Ecker JR, Schaller GE. Multiple type-B response regulators mediate cytokinin signal transduction in Arabidopsis. Plant Cell. 2005;17(11):3007–18.

    Article  CAS  Google Scholar 

  12. Ferreira FJ, Kieber JJ. Cytokinin signaling. Curr Opin Plant Biol. 2005;8(5):518–25.

    Article  CAS  Google Scholar 

  13. Rashotte AM, Mason MG, Hutchison CE, Ferreira FJ, Schaller GE, Kieber JJ. A subset of Arabidopsis AP2 transcription factors mediates cytokinin responses in concert with a two-component pathway. PNAS. 2006;103(29):11081–5.

    Article  CAS  Google Scholar 

  14. Rashotte AM, Goertzen LR. The CRF domain defines Cytokinin response factor proteins in plants. BMC Plant Biol. 2010;10:74.

    Article  Google Scholar 

  15. Shi X, Gupta S, Rashotte AM. Solanum lycopersicum cytokinin response factor (SlCRF) genes: characterization of CRF domain-containing ERF genes in tomato. J Exp Bot. 2012;63(2):973–82.

    Article  CAS  Google Scholar 

  16. Liu Z, Kong L, Zhang M, Lv Y, Liu Y, Zou M, Lu G, Cao J, Yu X. Genome-wide identification, phylogeny, evolution and expression patterns of AP2/ERF genes and cytokinin response factors in Brassica rapa ssp. pekinensis. PLoS One. 2013;8(12):e83444.

    Article  Google Scholar 

  17. Kim J. CYTOKININ RESPONSE FACTORs gating environmental signals and hormones. Trends Plant Sci. 2016;21(12):993–6.

    Article  CAS  Google Scholar 

  18. Zwack PJ, Robinson BR, Risley MG, Rashotte AM. Cytokinin response factor 6 negatively regulates leaf senescence and is induced in response to cytokinin and numerous abiotic stresses. Plant Cell Physiol. 2013;54(6):971–81.

    Article  CAS  Google Scholar 

  19. Raines T, Shanks C, Cheng CY, McPherson D, Argueso CT, Kim HJ, Franco-Zorrilla JM, Lopez-Vidriero I, Solano R, Vankova R, et al. The cytokinin response factors modulate root and shoot growth and promote leaf senescence in Arabidopsis. Plant J. 2016;85(1):134–47.

    Article  CAS  Google Scholar 

  20. Cucinotta M, Manrique S, Guazzotti A, Quadrelli NE, Mendes MA, Benkova E, Colombo L. Cytokinin response factors integrate auxin and cytokinin pathways for female reproductive organ development. Development. 2016;143(23):4419–24.

    Article  CAS  Google Scholar 

  21. Zwack PJ, Compton MA, Adams CI, Rashotte AM. Cytokinin response factor 4 (CRF4) is induced by cold and involved in freezing tolerance. Plant Cell Rep. 2016;35(3):573–84.

    Article  CAS  Google Scholar 

  22. Zwack PJ, De Clercq I, Howton TC, Hallmark HT, Hurny A, Keshishian EA, Parish AM, Benkova E, Mukhtar MS, Van Breusegem F, et al. Cytokinin response factor 6 represses cytokinin-associated genes during oxidative stress. Plant Physiol. 2016;172(2):1249–58.

    CAS  PubMed  PubMed Central  Google Scholar 

  23. Gupta S, Rashotte AM. Expression patterns and regulation of SlCRF3 and SlCRF5 in response to cytokinin and abiotic stresses in tomato (Solanum lycopersicum). J Plant Physiol. 2014;171(3–4):349–58.

    Article  CAS  Google Scholar 

  24. Shi X, Gupta S, Rashotte AM. Characterization of two tomato AP2/ERF genes, SlCRF1 and SlCRF2 in hormone and stress responses. Plant Cell Rep. 2014;33(1):35–45.

    Article  CAS  Google Scholar 

  25. Kwon T. Cytokinin response factor 2 positively regulates salicylic acid-mediated plant immunity in Arabidopsis thaliana. Plant Biotechnol. 2016;33(3):207–10.

    Article  Google Scholar 

  26. Liang YS, Ermawati N, Cha JY, Jung MH, Su'udi M, Kim MG, Ha SH, Park CG, Son D. Overexpression of an AP2/ERF-type transcription factor CRF5 confers pathogen resistance to Arabidopsis plants. J Korean Soc Appl Bi. 2010;53(2):142–8.

    Article  CAS  Google Scholar 

  27. Kanwal M, Rabbani MA, Iqbal S, Fayyaz L, Afzal M. Genetic diversity in Brassica species and Eruca sativa for yield associated parameters. Genetika-Belg. 2014;46(2):537–43.

    Article  Google Scholar 

  28. N U. Genomic analysis of Brassica with special reference to the experimental formation of B. napus and peculiar mode of fertilization. Jpn J Bot. 1935;7:389–452.

    Google Scholar 

  29. Chen S, Nelson MN, Chevre AM, Jenczewski E, Li ZY, Mason AS, Meng JL, Plummer JA, Pradhan A, Siddique KHM, et al. Trigenomic bridges for Brassica improvement. Crit Rev Plant Sci. 2011;30(6):524–47.

    Article  CAS  Google Scholar 

  30. Snowdon RJ, Kohler W, Friedt W, Kohler A. Genomic in situ hybridization in Brassica amphidiploids and interspecific hybrids. Theor Appl Genet. 1997;95(8):1320–4.

    Article  CAS  Google Scholar 

  31. Maluszynska J, Hasterok R. Identification of individual chromosomes and parental genomes in Brassica juncea using GISH and FISH. Cytogenet Genome Res. 2005;109(1–3):310–4.

    Article  CAS  Google Scholar 

  32. Snowdon RJ, Friedrich T, Friedt W, Kohler W. Identifying the chromosomes of the A- and C-genome diploid Brassica species B. rapa (syn. campestris) and B. oleracea in their amphidiploid B. napus. Theor Appl Genet. 2002;104(4):533–8.

    Article  CAS  Google Scholar 

  33. Tonosaki K, Nishio T. Identification of species in tribe Brassiceae by dot-blot hybridization using species-specific ITS1 probes. Plant Cell Rep. 2010;29(10):1179–86.

    Article  CAS  Google Scholar 

  34. Pankin AA, Khavkin EE. Genome-specific scar markers help solve taxonomy issues: a case study with Sinapis arvensis (Brassiceae, Brassicaceae). Am J Bot. 2011;98(3):E54–7.

    Article  Google Scholar 

  35. Alix K, Heslop-Harrison JS. The diversity of retroelements in diploid and allotetraploid Brassica species. Plant Mol Biol. 2004;54(6):895–909.

    Article  CAS  Google Scholar 

  36. Alix K, Ryder CD, Moore J, King GJ, Heslop-Harrison JS. The genomic organization of retrotransposons in Brassica oleracea. Plant Mol Biol. 2005;59(6):839–51.

    Article  CAS  Google Scholar 

  37. Mason AS, Nelson MN, Castello MC, Yan GJ, Cowling WA. Genotypic effects on the frequency of homoeologous and homologous recombination in Brassica napus × B. carinata hybrids. Theor Appl Genet. 2011;122(3):543–53.

    Article  Google Scholar 

  38. Thakur AK, Singh KH, Singh L, Nanjundan J, Khan YJ, Singh D. SSR marker variations in Brassica species provide insight into the origin and evolution of Brassica amphidiploids. Hereditas. 2017;155:6.

    Article  Google Scholar 

  39. Yu JY, Tehrim S, Zhang FQ, Tong CB, Huang JY, Cheng XH, Dong CH, Zhou YQ, Qin R, Hua W, Liu SY. Genome-wide comparative analysis of NBS-encoding genes between Brassica species and Arabidopsis thaliana. BMC Genomics. 2014;15:3.

    Article  Google Scholar 

  40. Chalhoub B, Denoeud F, Liu S, Parkin IA, Tang H, Wang X, Chiquet J, Belcram H, Tong C, Samans B, et al. Plant genetics. Early allopolyploid evolution in the post-Neolithic Brassica napus oilseed genome. Science. 2014;345(6199):950–3.

    Article  CAS  Google Scholar 

  41. Liu S, Liu Y, Yang X, Tong C, Edwards D, Parkin IA, Zhao M, Ma J, Yu J, Huang S, et al. The Brassica oleracea genome reveals the asymmetrical evolution of polyploid genomes. Nat Commun. 2014;5:3930.

    Article  CAS  Google Scholar 

  42. Wang X, Wang H, Wang J, Sun R, Wu J, Liu S, Bai Y, Mun JH, Bancroft I, Cheng F, et al. The genome of the mesopolyploid crop species Brassica rapa. Nat Genet. 2011;43(10):1035–9.

    Article  CAS  Google Scholar 

  43. Yang J, Liu D, Wang X, Ji C, Cheng F, Liu B, Hu Z, Chen S, Pental D, Ju Y, et al. The genome sequence of allopolyploid Brassica juncea and analysis of differential homoeolog gene expression influencing selection. Nat Genet. 2016;48(10):1225–32.

    Article  CAS  Google Scholar 

  44. Striberny B, Melton AE, Schwacke R, Krause K, Fischer K, Goertzen LR, Rashotte AM. Cytokinin response factor 5 has transcriptional activity governed by its C-terminal domain. Plant Signal Behav. 2017;12(2):e1276684.

    Article  Google Scholar 

  45. Zwack PJ, Shi X, Robinson BR, Gupta S, Compton MA, Gerken DM, Goertzen LR, Rashotte AM. Vascular expression and C-terminal sequence divergence of cytokinin response factors in flowering plants. Plant Cell Physiol. 2012;53(10):1683–95.

    Article  CAS  Google Scholar 

  46. Cheng F, Liu SY, Wu J, Fang L, Sun SL, Liu B, Li PX, Hua W, Wang XW. BRAD, the genetics and genomics database for Brassica plants. BMC Plant Biol. 2011;11:1–6.

    Article  Google Scholar 

  47. Letunic I, Doerks T, Bork P. SMART 7: recent updates to the protein domain annotation resource. Nucleic Acids Res. 2012;40(D1):D302–5.

    Article  CAS  Google Scholar 

  48. Kohli DK, Bachhawat AK. CLOURE: Clustal output Reformatter, a program for reformatting ClustalX/ClustalW outputs for SNP analysis and molecular systematics. Nucleic Acids Res. 2003;31(13):3501–2.

    Article  CAS  Google Scholar 

  49. Bjellqvist B, Hughes GJ, Pasquali C, Paquet N, Ravier F, Sanchez JC, Frutiger S, Hochstrasser D. The focusing positions of polypeptides in immobilized pH gradients can be predicted from their amino-acid-sequences. Electrophoresis. 1993;14(10):1023–31.

    Article  CAS  Google Scholar 

  50. Bjellqvist B, Basse B, Olsen E, Celis JE. Reference points for comparisons of 2-dimensional maps of proteins from different human cell-types defined in a pH scale where isoelectric points correlate with polypeptide compositions. Electrophoresis. 1994;15(3–4):529–39.

    Article  CAS  Google Scholar 

  51. Gasteiger E, Gattiker A, Hoogland C, Ivanyi I, Appel RD, Bairoch A. ExPASy: the proteomics server for in-depth protein knowledge and analysis. Nucleic Acids Res. 2003;31(13):3784–8.

    Article  CAS  Google Scholar 

  52. Bailey TL, Boden M, Buske FA, Frith M, Grant CE, Clementi L, Ren JY, Li WW, Noble WS. MEME SUITE: tools for motif discovery and searching. Nucleic Acids Res. 2009;37:W202–8.

    Article  CAS  Google Scholar 

  53. 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.

    Article  CAS  Google Scholar 

  54. Tamura K, Stecher G, Peterson D, Filipski A, Kumar S. MEGA6: molecular evolutionary genetics analysis version 6.0. Mol Biol Evol. 2013;30(12):2725–9.

    Article  CAS  Google Scholar 

  55. Letunic I, Bork P. Interactive tree of life (iTOL) v3: an online tool for the display and annotation of phylogenetic and other trees. Nucleic Acids Res. 2016;44(W1):W242–5.

    Article  CAS  Google Scholar 

  56. Hu B, Jin JP, Guo AY, Zhang H, Luo JC, Gao G. GSDS 2.0: an upgraded gene feature visualization server. Bioinformatics. 2015;31(8):1296–7.

    Article  Google Scholar 

  57. Lyons E, Freeling M. How to usefully compare homologous plant genes and chromosomes as DNA sequences. Plant J. 2008;53(4):661–73.

    Article  CAS  Google Scholar 

  58. Cristianini N, Hahn MW. Introduction to computational genomics: a case studies approach. Cambridge, UK: Cambridge University Press; 2007.

  59. Higo K, Ugawa Y, Iwamoto M, Korenaga T. Plant cis-acting regulatory DNA elements (PLACE) database: 1999. Nucleic Acids Res. 1999;27(1):297–300.

    Article  CAS  Google Scholar 

  60. Rombauts S, Dehais P, van Montagu M, Rouze P. PlantCARE, a plant cis-acting regulatory element database. Nucleic Acids Res. 1999;27(1):295–6.

    Article  CAS  Google Scholar 

  61. Broekgaarden C, Poelman EH, Steenhuis G, Voorrips RE, Dicke M, Vosman B. Responses of Brassica oleracea cultivars to infestation by the aphid Brevicoryne brassicae: an ecological and molecular approach. Plant Cell Environ. 2008;31(11):1592–605.

    Article  CAS  Google Scholar 

  62. Shopan J, Mou HP, Zhang LL, Zhang CT, Ma WW, Walsh JA, Hu ZY, Yang JH, Zhang MF. Eukaryotic translation initiation factor 2B-beta (eIF2Bβ), a new class of plant virus resistance gene. Plant J. 2017;90(5):929–40.

    Article  CAS  Google Scholar 

  63. Deng WK, Wang YB, Liu ZX, Cheng H, Xue Y. HemI: a toolkit for illustrating heatmaps. PLoS One. 2014;9(11):e111988.

    Article  Google Scholar 

  64. Lynch M, Conery J. The evolutionary fate and consequences of duplicate genes. Science. 2000;290(5494):5.

    Article  Google Scholar 

  65. Glaser-Schmitt A, Parsch J. Functional characterization of adaptive variation within a cis-regulatory element influencing Drosophila melanogaster growth. PLoS Biol. 2018;16(1):e2004538.

    Article  Google Scholar 

  66. Le DT, Nishiyama R, Watanabe Y, Vankova R, Tanaka M, Seki M, Ham LH, Yamaguchi-Shinozaki K, Shinozaki K, Tran LSP. Identification and expression analysis of cytokinin metabolic genes in soybean under normal and drought conditions in relation to cytokinin levels. PLoS One. 2012;7(8):e42411.

    Article  CAS  Google Scholar 

  67. Zhang K, Wang R, Zi H, Li Y, Cao X, Li D, Guo L, Tong J, Pan Y, Jiao Y, et al. AUXIN RESPONSE FACTOR3 regulates floral meristem determinacy by repressing cytokinin biosynthesis and signaling. Plant Cell. 2018;30:324–46.

    Article  CAS  Google Scholar 

  68. Kunst L, Klenz JE, Martinezzapater J, Haughn GW. AP2 gene determines the identity of perianth organs in flowers of Arabidopsis thaliana. Plant Cell. 1989;1(12):1195–208.

    Article  Google Scholar 

  69. Brenner WG, Ramireddy E, Heyl A, Schmulling T. Gene regulation by cytokinin in Arabidopsis. Front Plant Sci. 2012;3:8.

    Article  CAS  Google Scholar 

  70. Mizoi J, Shinozaki K, Yamaguchi-Shinozaki K. AP2/ERF family transcription factors in plant abiotic stress responses. BBA-Gene Regul Mech. 2012;1819(2):86–96.

    CAS  Google Scholar 

  71. Shu YJ, Liu Y, Zhang J, Song LL, Guo CH. Genome-wide analysis of the AP2/ERF superfamily genes and their responses to abiotic stress in Medicago truncatula. Front Plant Sci. 2016;6:1247.

    Article  Google Scholar 

  72. Li H, Wang Y, Wu M, Li LH, Li C, Han ZP, Yuan JY, Chen CB, Song WQ, Wang CG. Genome-wide identification of AP2/ERF transcription factors in Cauliflower and expression profiling of the ERF family under salt and drought stresses. Front Plant Sci. 2017;8:946.

    Article  Google Scholar 

  73. Cheng F, Mandakova T, Wu J, Xie Q, Lysak MA, Wang XW. Deciphering the diploid ancestral genome of the mesohexaploid Brassica rapa. Plant Cell. 2013;25(5):1541–54.

    Article  CAS  Google Scholar 

  74. Lysak MA, Koch MA, Pecinka A, Schubert I. Chromosome triplication found across the tribe Brassiceae. Genome Res. 2005;15(4):516–25.

    Article  CAS  Google Scholar 

  75. Liang Z, Schnable JC. Functional divergence between subgenomes and gene pairs after whole genome duplications. Mol Plant. 2018;11:388–97.

    Article  CAS  Google Scholar 

  76. Shirasawa K, Isuzugawa K, Ikenaga M, Saito Y, Yamamoto T, Hirakawa H, Isobe S. The genome sequence of sweet cherry (Prunus avium) for use in genomics-assisted breeding. DNA Res. 2017;24(5):499–508.

    Article  CAS  Google Scholar 

  77. Ye Z, Pan Y, Zhang Y, Cui H, Jin G, McHardy AC, Fan L, Yu X. Comparative whole-genome analysis reveals artificial selection effects on Ustilago esculenta genome. DNA Res. 2017;24(6):635–48.

    Article  CAS  Google Scholar 

  78. Inaba R, Nishio T. Phylogenetic analysis of Brassiceae based on the nucleotide sequences of the S-locus related gene, SLR1. Theor Appl Genet. 2002;105(8):1159–65.

    Article  CAS  Google Scholar 

  79. Warwick SI, Sauder CA. Phylogeny of tribe Brassiceae (Brassicaceae) based on chloroplast restriction site polymorphisms and nuclear ribosomal internal transcribed spacer and chloroplast trnL intron sequences. Can J Bot. 2005;83(5):467–83.

    Article  CAS  Google Scholar 

  80. Zhang R, Xue C, Liu GQ, Liu XY, Zhang ML, Wang X, Zhang T, Gong ZY. Segmental duplication of chromosome 11 and its implications for cell division and genome-wide expression in rice. Sci Rep. 2017;7:2689.

    Article  CAS  Google Scholar 

  81. Sun L, Fan ZQ, Weng XJ, Ye XH, Long J, Fu KP, Yan SH, Wang B, Zhuo YG, Liu XX, et al. Rapid detection of Down's syndrome using quantitative real-time PCR (qPCR) targeting segmental duplications on chromosomes 21 and 11. Gene. 2014;552(2):272–6.

    Article  CAS  Google Scholar 

  82. Muller CJ, Larsson E, Spichal L, Sundberg E. Cytokinin-auxin crosstalk in the gynoecial primordium ensures correct domain patterning. Plant Physiol. 2017;175(3):1144–57.

    Article  CAS  Google Scholar 

  83. Simaskova M, O'Brien JA, Khan M, van Noorden G, Otvos K, Vieten A, De Clercq I, van Haperen JM, Cuesta C, Hoyerova K, et al. Cytokinin response factors regulate PIN-FORMED auxin transporters. Nat Commun. 2015;6:8717.

  84. Fujita M, Fujita Y, Noutoshi Y, Takahashi F, Narusaka Y, Yamaguchi-Shinozaki K, Shinozaki K. Crosstalk between abiotic and biotic stress responses: a current view from the points of convergence in the stress signaling networks. Curr Opin Plant Biol. 2006;9(4):436–42.

    Article  Google Scholar 

Download references

Acknowledgements

The authors gratefully acknowledge Dr. Longjiang Fan and Dr. Enhui Shen for their technological guidance, and thank Dr. Gang Lu, in particular, for the stimulating discussions and critical reading of the manuscript.

Funding

This work was partially supported by the National Key Research and Development Program of China (2016YFD0100204–31), the 948 Project of Agricultural Ministry of China (2014-Z28), National Natural Science Foundation of China (31460521, 31700272 and 31872110), the Breeding Project of the Sci-tech Foundation of Zhejiang Province (2016C02051–6-1), the Project of the Sci-tech Foundation of Ningbo City (2015C110008), the Development Project of Wuxi City (CLE02N1603), and the Project of Application on Public Welfare Technology in Zhejiang Province (LGN18C150003). The funding body had not involved in the design of the study and collection, analysis, and interpretation of the data or in writing the manuscript.

Availability of data and materials

Plant materials are available under request to the respective owner institutions. The datasets supporting the results of this article are included within the article and its additional files. The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

Author information

Authors and Affiliations

Authors

Contributions

XY and LK proposed and designed the research. LK and KZ performed the experiment under abiotic and biotic stresses. YG, KZ, and LK performed the qRT-PCR analysis. LM, HD, CC, and LK performed the statistical analyses, interpretation of experimental results. LK, XY and ZL wrote and revised the manuscript. All the authors read and approved the final manuscript.

Corresponding author

Correspondence to Xiaolin Yu.

Ethics declarations

Ethics approval and consent to participate

Not applicable. This study has not directly involved humans and animals. The plant materials have not been directly used. The seeds of Brassica oleracea were obtained from Zhejiang Academy of Agricultural Sciences. The seeds of B. nigra, B. juncea and Arabidopsis thaliana were obtained from our laboratory. All transgenic plants were die out. We comply with the Convention on the Trade in Endangered Species of Wild Fauna and Flora.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Additional files

Additional file 1:

Table S1. Primers used for qRT-PCR. (XLS 47 kb)

Additional file 2:

Table S2. Characterization of CRFs in Brassica species. (DOC 255 kb)

Additional file 3:

Figure S1. Conserve motif alignment of three types CRFs. The figure was obtained by ClustalX and WedLogo 3 (http://weblogo.threeplusone.com/). (DOC 3169 kb)

Additional file 4:

Figure S2. Synteny analysis of CRFs among Brassica species. (A) Alignment between genes in diploid and in allotetraploid. (B) Alignment between similar genes in allotetraploid. Gene models are colored in grey (gene) and green (CDS). Red blocks indicate the high-scoring segment pair (HSP), and pink links show the connectors between HSP.The figure was formed on GEvo (https://genomevolution.org/CoGe/GEvo.pl). (TIF 8633 kb)

Additional file 5:

Table S3. List of origin genes in B. rapa, B. nigra and amphidiploid genes in B. napus, B. juncea. High-similarity genes are marked in bold. (DOC 58 kb)

Additional file 6:

Figure S3. Chromosomal mapping of CRFs in B. nigra and B. juncea. The CRFs in B. nigra (A) and B. juncea (B) are shown except those located on the scaffolds. The locations were shown on the left of the chromosomes, whereas the gene names were on the right. The arrows next to gene names show the direction of transcription. The bar indicates the size of 5 Mb. (TIF 9375 kb)

Additional file 7:

Figure S4. Box-plots of gene retention ratio. Statistics by genomes (A) and by gene names (B) are shown. The Violin plots indicate the number of the same value. (TIF 3464 kb)

Additional file 8:

Figure S5. Gene retention ratios of CRFs in the three sub-genomes of B. rapa, B. oleracea, and B. napus. (TIF 1003 kb)

Additional file 9:

Figure S6. Ka/Ks values of CRF orthologous gene pairs of Br-At, Bol-At and Bna-At over a sliding window of 20 codons. The x-axis indicates the starting codon of sliding window. The y-axis shows the Ka/Ks values. (DOC 1218 kb)

Additional file 10:

Table S4. Elements relate to hormone and stress in the promotor of CRFs predicted by PLACE.Table S5. Elements relate to hormone and stress in the promotor of CRFs predicted by PlantCARE. (XLS 39 kb)

Additional file 11:

Table S5. Elements relate to hormone and stress in the promotor of CRFs predicted by PlantCARE. (XLS 37 kb)

Rights and permissions

Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Kong, L., Zhao, K., Gao, Y. et al. Comparative analysis of cytokinin response factors in Brassica diploids and amphidiploids and insights into the evolution of Brassica species. BMC Genomics 19, 728 (2018). https://doi.org/10.1186/s12864-018-5114-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s12864-018-5114-y

Keywords