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Genome-wide identification, evolutionary and functional analyses of KFB family members in potato

Abstract

Background

Kelch repeat F-box (KFB) proteins play vital roles in the regulation of multitudinous biochemical and physiological processes in plants, including growth and development, stress response and secondary metabolism. Multiple KFBs have been characterized in various plant species, but the family members and functions have not been systematically identified and analyzed in potato.

Results

Genome and transcriptome analyses of StKFB gene family were conducted to dissect the structure, evolution and function of the StKFBs in Solanum tuberosum L. Totally, 44 StKFB members were identified and were classified into 5 groups. The chromosomal localization analysis showed that the 44 StKFB genes were located on 12 chromosomes of potato. Among these genes, two pairs of genes (StKFB15/16 and StKFB40/41) were predicted to be tandemly duplicated genes, and one pair of genes (StKFB15/29) was segmentally duplicated genes. The syntenic analysis showed that the KFBs in potato were closely related to the KFBs in tomato and pepper. Expression profiles of the StKFBs in 13 different tissues and in potato plants with different treatments uncovered distinct spatial expression patterns of these genes and their potential roles in response to various stresses, respectively. Multiple StKFB genes were differentially expressed in yellow- (cultivar ‘Jin-16’), red- (cultivar ‘Red rose-2’) and purple-fleshed (cultivar ‘Xisen-8’) potato tubers, suggesting that they may play important roles in the regulation of anthocyanin biosynthesis in potato.

Conclusions

This study reports the structure, evolution and expression characteristics of the KFB family in potato. These findings pave the way for further investigation of functional mechanisms of StKFBs, and also provide candidate genes for potato genetic improvement.

Peer Review reports

Background

The F-box gene family broadly exists in plants and plays a crucial role in plant growth and development through a ubiquitin-mediated degradation of cellular proteins [1, 2]. F-box proteins are named for the presence of conserved F-box domain, which is generally located at the N-terminus of the protein and functions in coordination with other motifs at the C-terminus [3, 4]. The F-box domain consists of around 50 amino acids and binds to SKP1 (S-phase Kinase-associated Protein 1) or SKP1-like proteins in the SCF (Skp1-Cullin-F-box) complex, which is the most typical E3 (ubiquitin-ligation enzymes) in organisms [4, 5]. The C-terminus usually contains some highly variable secondary motifs that are responsible for the specific recognition and binding of their substrate proteins [1]. F-box proteins are diverse due to their different C-terminal motifs, such as Kelch repeats, leucine-rich repeats, WD-40 repeats and tetratricopeptide repeats that interact with specific proteins through the UPS (ubiquitination-26 s proteasome system) degradation pathway [4, 6, 7].

Kelch repeat F-box (KFB) subfamily is a major category of the F-box protein family and participates in ubiquitin-mediated protein degradation by selective binding of target proteins [1]. The approximately 50 residues of the F-box domain at N-terminus of KFB lack strictly conserved sequences and only a few amino acid residues are relatively invariant. By analyzing the alignment of 234 sequences used to create the F-box Pfam profile (http://pfam.wustl.edu/cgi-bin/getdesc?name=Fbox), Kipreos and Pagano found that the 8th amino acid of F-box domain was mostly leucine (L) or methionine (M); the 9th amino acids was mainly proline (P); the 16th was isoleucine (I) or valine (V); the 20th was leucine (L) or methionine (M), and the 32nd was serine (S) or cysteine (C) [3]. This domain of KFB was used to accurately recognize the core element of SCF and functions in protein degradation via ubiquitylation pathway. Another typical domain of KFB is the Kelch motif, which is a highly evolved but ancient consensus sequence [8]. Sequence alignment of Kelch repeats (supplemental Web data at http://info.med.yale.edu/cooley) showed that the sequence identity between individual Kelch motifs is low, and each Kelch motif is featured with 8 conserved amino acid residues: four hydrophobic amino acids, followed by two adjacent glycines (G), and two non-adjacent aromatic amino acids (Y or W) [9]. The crystal structure of the Kelch domain of fungal galactose oxidase revealed that multiple Kelch repeats can generate a β-propeller with blades arrayed around a funnel-like central axis [10, 11]. Different numbers of repeated Kelch motifs can generate distinct contact sites and interact with disparate partners, resulting in the diversification of KFB functions [12]. However, the key residues associated with protein contact sites in the β-propeller structures of the vast majority KFBs have not been mapped. Apart from F-box domain and Kelch repeat motifs, some KFB members possess other conserved domains. For example, the LOV (Light, Oxygen or Voltage) domain has been found to exist in N-terminus of some KFB proteins, including ZTL (ZEITLUPE), FKF1 (Flavin-binding Kelch repeat F-box 1) and LKP2 (Light, oxygen or voltage Kelch protein 2) [13]. The presence of the LOV domain in KFB proteins makes their function different from that of other KFB proteins.

With the development of deep sequencing, numerous KFBs have been identified in many plant species, like chickpea (Cicer arietinum), Arabidopsis (Arabidopsis thaliana), salvia (Salvia miltiorrhiza), wheat (Triticum aestivum) and so on, but only a few KFB members have been functionally characterized in depth [1, 14,15,16]. KFB proteins have been demonstrated to participate in plant growth and development. For example, CFK1 (COP9 interacting F-box Kelch 1) was proved to participate in hypocotyl elongation under light in Arabidopsis [17]. OsFBK12 modulated seed germination and leaf senescence by affecting ethylene levels in rice [18]. In potato, StFKF1 controlled potato tuberization and maturation by affecting the activity of StSP6A, which interacted with StCDF (Cycling Dof Factor) [19, 20]. CTG10 (Cold Temperature Germinating 10), a Kelch F-box protein in Arabidopsis, stimulated the seed germination through a negatively regulation of PIF1 (Phytochrome Interacting Factor 1) activity [21]. Furthermore, previous studies have exemplified that large numbers of KFB members played a pivotal role in circadian rhythm regulation and photomorphogenesis. In Arabidopsis, one KFB member named AFR (Attenuated Far-red Response) degraded the light signal suppressor and enabled plants to perceive light signals at dawn [22]. ZTL, FKF1, LKP2, as three KFBs with similar structure and function, controlled the photoperiod flowering activity by degrading AtCDFs in Arabidopsis [23, 24]. GmZTL3 and GmFKF1 were also demonstrated to regulate flowering process in soybean [25, 26]. Additionally, several KFB members were involved in plant hormone signaling and stress responses. The expression of SmKFB5 was inhibited in the hairy roots of Salvia miltiorrhiza treated with methyl jasmonate (MeJA) [1]. AtKFB39/KMD3 induced by Meloidogyne incognita in plant roots can degrade specific target proteins through the formation of SCFAtKFB39 complex and thereby promote the successful phagocytosis of pathogens [27]. In recent decades, an increasingly number of studies have focused on the function of KFB proteins in the biosynthesis of secondary metabolites, and great progress has been made. One of CmKFB members in muskmelon was reported to negatively regulate the production and accumulation of naringin chalcone by transferring the metabolic flux of flavonoids [28]. AtKFBPAL and AtKFBCHS, post-translationally regulated phenylpropanoid metabolism by mediating protein ubiquitination and degradation of PAL (phenylalanine ammonia-lyase) and CHS (chalcone synthase), respectively, thereby controlling development and stress response in Arabidopsis thaliana [14, 29]. The negative role of AtFKF1 in regulation of cellulose biosynthesis was also observed in Arabidopsis [30].

Potato (Solanum tuberosum L.), originally discovered in the Andes region of South America and initially domesticated in Peru, is considered as a dominant crop closely related to social and economic development [31]. The yield of edible dry matter per unit area of potato has been reported to be almost the same as that of cereal crops [32]. During long period of cultivation in the field and adaptation to extreme environment, potato has gradually accumulated abundant genes for resistance to diversified stresses, including diseases, pests, drought, cold, high salt and so on [33]. Colored potatoes, especially purple fleshed potatoes rich in anthocyanins are favored by many consumers [34, 35]. Despite the importance of potato, the functions and regulatory mechanisms of most StKFBs are still largely unknown in potatoes. KFB family members, as described above, play important roles in plant growth and development, stress responses, and biosynthesis of secondary metabolites. However, the functions and regulatory mechanism of StKFBs has not been systematically reported in potatoes.

In this research, gene members of StKFB family were firstly identified from the whole genome of potato. Their sequence characteristics, motif composition, gene structure, evolutionary relationship, duplication events and synteny prediction were comprehensively analyzed. In order to shed light into their underlying functions, the expression profiles of the identified StKFB members were examined across various tissues, different treatments, as well as tubers from cultivars containing various levels of anthocyanin content, using in-house and publicly available transcriptome sequencing data. Moreover, the expression patterns of 9 selected StKFB genes in the tubers with different colors were analyzed by quantitative real-time polymerase chain reaction (qRT-PCR). These results will enrich the knowledge of structural characteristics, evolutionary relationship and expression patterns of potato KFBs and provide a theoretical basis for further exploration of the functional mechanism of StKFB members.

Result

Identification of StKFB members in potato

The profile HMMs (Hidden Markov Models) of F-box domains and Kelch domains were downloaded from Pfam database [36] (Additional file 1: Table S1). Totally, 379 and 45 candidate proteins containing F-box domains and Kelch domains were identified, respectively, by searching the potato protein sequences using HMMER software package v3.0 [37]. Furthermore, 84 StKFB members were identified by alignment against the potato genome (DM v4.03/v4.04) [38] using AtKFB protein sequences from Arabidopsis (TAIR10). Totally, 91 StKFBs were preliminarily obtained through these two methods. After removal of redundant and non-full length sequences, 44 StKFB family members were identified (Table 1). These StKFB members were renamed as StKFB01 to StKFB44 based on their chromosomal localizations. Their CDS and protein sequences were presented in Additional file 2.

Table 1 The list of StKFB members identified in potato

The CDS length of the candidate StKFBs ranged from 405 bp (StKFB17) to 1905 bp (StKFB01), encoding 134 to 634 amino acids. Molecular weight (MW) of the deduced StKFB proteins varied from 14.5 KDa (StKFB17) to 70.39 KDa (StKFB01). Of these 44 StKFB members, most of them contained a single Kelch motif (23 members), followed by the members contained 3 Kelch motifs (8 members), 2 Kelch motifs (7 members), 4 Kelch motifs (4 members), 5 Kelch motifs (1 members) and 6 Kelch motifs (1 member). The differences in Kelch motif numbers in StKFBs revealed their structural complexity and functional diversity. The theoretical isoelectric point (pI) of the StKFBs widely ranged from 4.8 (StKFB01) to 10.02 (StKFB03), suggesting that these KFB proteins may distribute and function in different microenvironments of cells. The prediction of subcellular localization showed that the majority of StKFBs were located in nucleus, and only a few members exist in chloroplast (StKFB17, StKFB19, StKFB24 and StKFB41) and cell membrane (StKFB24). The grand average of hydropathicity (GRAVY) data indicated that most StKFBs may belong to hydrophilic proteins except StKFB18, StKFB26, StKFB36 and StKFB42.

Structural analysis of conserved domains in StKFBs

The sequences and positions of F-box and Kelch domains in 44 StKFB members were detected using PfamScan database [39] (Additional file 1: Table S2 and Table S3). Multiple sequence alignment analysis of F-box domains showed that the identity of all aligned sequences was 29.87% and these relatively conserved amino acids were discontinuous (Fig. 1a). In this figure, the amino acids labeled in pink, such as proline (P), leucine (L), valine (V) and tryptophan (W) at the 9th, 17th, 31st and 35th position respectively, were the most conserved residues with identity greater than 75%. The amino acids marked in blue and yellow were less conserved, with identity more than 50 and 33%, respectively. Other amino acids without any color shadow had great variation. Furthermore, the secondary structures prediction of F-box domains of StKFBs showed that helices and coils were the main secondary structures, while the strands and coils were dominant in F-box domains of a few StKFB members (Fig. 1b). Such structures may facilitate their interaction with other proteins like SKP1 in their network.

Fig. 1
figure 1

Multi-sequence alignment (a) and the secondary structure prediction (b) of F-box domains in the identified StKFBs. (a) The identity was automatically calculated by multiple sequence alignment of DNAMAN X software. The amino acids with identity greater than 75, 50 and 33% are highlighted in pink, blue and yellow, respectively. (b) Secondary structures prediction was performed using online tool provided by NovoPro Bioscience Inc.

The sequences of Kelch motifs of StKFBs were also variable. The most striking feature of each Kelch repeat was the conserved bi-glycine (GG) and two characteristically spaced aromatic residues (Y or W) (Additional file 1: Table S3). Four inverted β-sheets were spatially twisted into a Kelch motif (Fig. 2a). Multiple Kelch repeats were arranged as blades around a funnel-shaped central axis to form a β propeller structure (Fig. 2b-g). The intra-blade loops connected two adjacent sheets in each Kelch motif; while the inter-blade loops jointed different Kelch motifs. The diversification of spatial structures of Kelch motifs with different numbers implies difference in StKFB functions.

Fig. 2
figure 2

The tertiary structures of Kelch motifs with different numbers. a A typical Kelch motif with a four-stranded β-sheets. b-g The tertiary structures of Kelch domains with 1–6 Kelch motifs predicted by SWISS-MODEL website. The Kelch domains were extracted from StKFB07, StKFB02, StKFB03, StKFB01, StKFB09 and StKFB27, respectively

Gene duplication analyses of StKFB genes

The 44 deduced StKFBs were unevenly distributed on 12 potato chromosomes according to chromosomal localization analysis using Circos software [40] (Fig. 3). Relatively more StKFB genes were observed on Chr01, Chr04 and Chr06, containing 8, 6 and 5 StKFBs, respectively. While StKFB genes were less distributed in Chr10, Chr07, Chr12, containing 1, 2 and 2 StKFB genes, respectively. Most chromosomes contained 3 (Chr05, Chr08, Chr09 and Chr11) or 4 StKFB genes (Chr02 and Chr03).

Fig. 3
figure 3

Chromosomal distribution and gene duplication of StKFB genes. Chromosomal distribution of StKFB genes was conducted by Circos software. Gene duplication events of StKFBs were analyzed by MCScanX. Colorized lines inside represent all synteny blocks in the potato genome. The segmentally duplicated genes are linked by the bold red line. Tandem duplications are indicated in blue box

Analysis of gene duplication events in potato genome manifested that there were 7753 single copy genes, 17,021 dispersed genes, 4269 tandem duplications, 5996 segmental duplications and 2443 adjacent but discontinuous repetitive genes in the potato genome (Additional file 3: Fig. S1). Among the 44 StKFB genes, StKFB15/StKFB16 on Chr03 (location: 59850507 Mb/59.861699 Mb) and StKFB40/StKFB41 on Chr11 (location: 41.047198 Mb/41.054665 Mb) were found to be two pairs of tandem duplications (Fig. 3) according to the definition of tandemly duplicated genes [41]. Besides, StKFB15/StKFB29 was predicted to be one pair of segmental duplications, implying that they may have differentiated from the same ancestor gene.

The ratio of the number of non-synonymous substitutions per non-synonymous site (Ka) to the number of synonymous substitutions per synonymous site (Ks) is an effective indicator to test the positive selection pressure after gene duplication and to infer the potential date of duplication events [42]. The Ka/Ks ratios of StKFB15/StKFB16, StKFB40/StKFB41, StKFB15/StKFB29 were 0.21, 0.65 and 0.26 (less than 1.0), respectively (Table 2), indicating that these duplicated genes were experienced purification and elimination by natural selection during the evolutionary process. Moreover, the occurrence dates of these duplication events were also estimated according to Shen and Yuan [43]. The earliest divergence time between StKFB15 and StKFB16 was around 58.16 million years ago (Mya), while StKFB40 and StKFB41 began to diverge from 9.77 Mya. The segmental duplication StKFB15/StKFB29 was found to occur around 28.14 Mya, which was later than the divergence date of StKFB15 and StKFB16.

Table 2 Tandemly and segmentally duplicated StKFB pairs in potato and inference of duplication time

Evolutionary analysis of KFB family members in potato and other plant species

To explore the potential evolutionary relationship of KFB proteins in different plant species, a maximum-likelihood (ML) phylogenetic tree was constructed based on the multiple sequence alignment of 284 KFBs, including 44 StKFBs from potato, 115 AtKFBs from Arabidopsis, 39 OsKFBs from rice and 86 GhKFBs from upland cotton. As shown in Fig. 4, all the 284 KFB members were classified into five groups, with Group II containing the most members (117 KFBs) and Group III containing the least members (6 KFBs).

Fig. 4
figure 4

Phylogenetic tree of KFB proteins from potato and other plant species. The maximum- likelihood method of IQ-TREE software was applied to construct the phylogenetic tree with 1000 bootstrap replicates. The model VT + F + R7 was automatically evaluated as the best-fit model through ModelFinder analysis. Branch lines in different colors represent different clans. The abbreviations used for different plant KFB proteins are as follows: At-Arabidopsis thaliana, St-Solanum tuberosum, Os-Oryza sativa and Gh-Gossypium hirsutum

The StKFBs in potato were categorized into these five clades according to the classification schemes of other plant species. Group I contained 76 plant KFB members, including 71 AtKFBs, 3 GhKFBs, 1 StKFBs and 1 OsKFB. Large numbers of AtKFB members in Group I implied that KFBs from Arabidopsis may have undergone expansion [1, 41]. Group II was the largest clade with a total of 117 plant KFB proteins, containing 48 GhKFBs, 30 AtKFBs, 23 OsKFB and 16 StKFBs. Many KFB members in this group have been functionally studied, such as At1g15670 (AtKFB01) and At1g80440 (AtKFB20) which have been demonstrated to post-translationally regulate phenylpropanoid metabolism [14]. Another AtKFB protein, At2g44130 enhanced nematode susceptibility in Arabidopsis [27]. OsFBK12 (Os03g07530) has been reported to play a role in seed germination and leaf senescence of rice [18]. Group III was the smallest clade among the five groups, including 2 AtKFBs, 2 GhKFBs, 1 OsKFB and 1 StKFBs. Group IV was the second smallest group, but the members within the group had distinct characteristics. For example, At5g57360/ZTL, At2g18925/LKP2 and At1g68050/FKF1, which contained LOV motif, were involved in plant circadian rhythm and photomorphogenesis [1]. Group V was composed of 72 KFB members. Most of the potato KFBs (24 members) and 31 upland cotton KFBs were classified into Group V, while KFBs from Arabidopsis and rice were less distributed in this group (8 and 9 members respectively). This phylogenetic tree helps to predict the functions of StKFBs that are closely related to those in other plant species.

Phylogenetic analysis, conserved motifs and exon-intron organization of StKFB family members

The phylogenetic analysis of the 44 StKFB protein sequences was carried out by IQ-TREE [44, 45] to further investigate the evolution relationship of StKFB members in potato. Except for StKFB17, the classification of StKFB members is generally consistent with that in phylogenetic tree among different plant species (Fig. 5a).

Fig. 5
figure 5

Phylogenetic relationships (a), motif composition (b) and gene structures (c) of StKFB members. (a) The phylogenetic tree was constructed by IQ-TREE software using the neighbor-joining method with 1000 bootstrap replicates. The branch lines in different colors represent different KFB groups. (b) Motif composition of StKFB proteins was performed by MEME software v5.3.0. The motifs, numbered 1–20, are displayed in different colored boxes. The length of proteins can be estimated using the scale at the bottom. (c) Exon/intron distribution of corresponding StKFB genes was carried out by GSDS 2.0. The yellow boxes represent exons of genes; the blue boxes indicate untranslated region (UTR); the lines refer to introns of genes. The length of genes can be estimated using the scale at the bottom

Additionally, twenty putative conserved motifs in the 44 StKFB members were identified by MEME software v5.3.0 [46] to investigate the conservation and diversification of structures in StKFB family members (Fig. 5b). The details of the 20 motifs were shown in Additional file 1: Table S4 and Additional file 3: Fig. S2. The motif composition diagram depicted that the numbers of conserved motifs in each KFB protein sequence ranged from 2 to 11 (Fig. 5b). The majority of StKFB members contained Motif 1 (37 members), Motif 2 (23 members), Motif 3 (23 members) and Motif 6 (32 members), suggesting that these motifs are highly conserved in StKFBs. In comparison, several motifs only appeared in a specific group. For instance, Motif 17 and 18 were only distributed in some StKFB members of Group V; while Motif 3 was rarely distributed in Group V. Motif specificity was also shown in tandem and segmental duplications. Motif 11 and 15 were found only in StKFB40 and StKFB41, and Motif 16 was unique to StKFB15, StKFB16 and StKFB29. By annotating the conserved motifs with InterProScan [47, 48], five motifs (Motif 1, 4, 10, 12 and 15) were found as parts of the F-box domains, and four motifs (Motif 2, 3, 5, 13) were considered as Kelch repeats (Additional file 1: Table S4).

Furthermore, the number and length of introns and extrons in StKFB genes were analyzed to explore the structural diversity of StKFB gene sequences. As shown in Fig. 5c, 34 StKFB genes had no introns, while 8, 1 and 1 StKFBs contained 1, 2 and 3 introns, respectively. Apart from intron number differences, the length of introns also displayed certain degrees of variation. In comparison with StKFB09, StKFB14 and StKFB38, the introns within StKFB02, StKFB06, StKFB15, StKFB24, StKFB25, StKFB35 and StKFB37 were relatively large. Although the gene structures of most closely related genes exhibited high similarity and conservation, there still exist several differences in intron numbers and intron length between some of the phylogenetically related members. StKFB16 and StKFB29 had no intron, while StKFB15 had a long intron, which may result in the expression pattern and function of StKFB15 being different from that of StKFB16 and StKFB29. Gene structure diversity may have driven the evolution of the KFB gene family.

Syntenic analysis of KFB genes in different plant species

Synteny describes the similarity of gene arrangement in different genomes, and to some extent, can represent the evolutionary relationship of genes in different species [49]. To deduce the potential phylogenetic mechanism of StKFB genes, the comparative syntenic analysis of KFB genes was conducted between potato and five other plant species respectively, including four dicots (Arabidopsis, pepper, tomato and upland cotton) and one monocot (rice) (Fig. 6). In general, potato KFB genes showed a closer syntenic relationship with those in dicots than the monocot. Totally, 25 potato KFB members were found to be syntenic with KFBs in pepper, followed by upland cotton (18), tomato (16), Arabidopsis (14) and rice (2). The syntenic genes of 5 StKFB members (StKFB02, StKFB06, StKFB20, StKFB22 and StKFB30) were all discovered in the genome of these dicots (Additional file 1: Table S5). It is noteworthy that Genome A and Genome D of upland cotton contained 17 syntenic genes of StKFB genes, respectively. The syntenic gene of StKFB26 only existed in Genome A, while the syntenic gene of StKFB13 was specifically contained in Genome D of upland cotton.

Fig. 6
figure 6

Synteny analysis of KFB genes between potato and five other plant species. The syntenic relationship was analyzed by MCScanX software. Gray lines in the background indicate the collinear blocks within potato and other plant genomes, while the red lines highlight the syntenic KFB gene pairs. The abbreviations used for different plant genomes are as follows: Ath-Arabidopsis thaliana, Stu-Solanum tuberosum, Ca-Capsicum annuum, Sl-Solanum lycopersicum, Os-Oryza sativa, GhA/D-Genome A/D of Gossypium hirsutum

The orthologous KFB genes syntenic with StKFB genes in other plants were listed in Additional file 1: Table S5. We noticed that the Ka/Ks values of orthologs pairs were less than 1, suggesting that these genes had evolved under the effect of negative or purifying selection. Some StKFB genes were syntenic with more than two genes in the genome of pepper, Arabidopsis and upload cotton. For example, StKFB18 in potato was found to be syntenic with two Arabidopsis KFB genes (At4g39550.1 and At2g21950.1). Similarly, PHT79419 and PHT88782 in pepper were identified to be the syntenic genes of StKFB16. In upland cotton, two genes in Genome A (Gh_A01g1212 and Gh_A12g1407) and one gene in Genome D (Gh_D01g1375) were syntenic with StKFB01. These orthologous KFB genes in different plants may facilitate KFB family evolution. Moreover, the KFB syntenic gene pairs found between potato and other plants were anchored on conserved syntenic blocks. And potato KFBs has a larger syntenic blocks with tomato and pepper KFBs, indicating that the syntenic relationship of potato KFB gene family were closer to tomato and pepper KFBs than those in other plants.

Tissue-specific expression analysis of StKFB genes

The expression heatmap of StKFB genes in 13 different potato tissues displayed that the expression levels of individual members of this gene family varied greatly in various tissues (Fig. 7a). Some StKFB genes exhibited tissue-specific expression patterns. For example, StKFB10 and StKFB28, two closely related KFB genes on the phylogenetic tree, were both predominately expressed in flower organs, suggesting their possible involvement in potato flowering. StKFB15/16/32/38/42/44 were mainly expressed in immature fruits; while StKFB02/05/08/13/14/21/24/25 were expressed higher in mature fruits than in immature fruits, inferring that these members might participate in fruit formation and development. Other members such as StKFB07/23/29/34, showed high levels of expression in vegetative organs, such as shoots, roots, tubers and stolon, suggesting an involvement of them in plant vegetative growth. In addition, we found that some StKFBs with close phylogenetic relationship showed different expression patterns. StKFB15 and StKFB16 were predicted to be a pair of tandem duplication, but their expression patterns were not the same. StKFB15 was mainly expressed in stolon, immature fruits and tubers, while StKFB16 was highly expressed in shoot and immature fruits. StKFB29, the predicted segmentally duplicated gene of StKFB15, appeared high expression in stolon, tubers and petioles.

Fig. 7
figure 7

Expression profiles of StKFB genes in different potato tissues (a) and in potato plants with different treatments (b). The dataset was obtained from the publicly available dataset for FPKM values of all the representative transcripts across 40 DM and 16 RH libraries: DM_RH_RNA-Seq_FPKM_expression_matrix_for_DM_v4.03_13dec2013_desc.xlsx (http://spuddb.uga.edu/pgsc_download.shtml)

Furthermore, the correlation between the expression patterns of StKFBs in diverse tissues was also analyzed. The genes with positive correlation might act synergistically in similar tissues; while the genes with negative correlation might indicate that the function of these members is differentiated [50]. As shown in Additional file 3: Fig. S3a, StKFB23, StKFB29 and StKFB34, which were highly expressed in vegetative tissues, had a positive correlation with each other. StKFB20/28/35/36 with high expression in stamens also showed a high positive correlation. Similarly, StKFB02/05/18/19/21/27 were positively correlated and clustered together in the expression heatmap (Fig. 7a and Additional file 3: Fig. S3a). In contrast, StKFB15/23/29/34 were negatively correlated with StKFB03/26/39/40/41, indicating that these two groups of genes may perform functions in different potato tissues.

Expression patterns of StKFBs in potato plants with different treatments

The RNA-seq data of whole potato plants with various treatments was used to detect the response of StKFB genes to different stresses (Additional file 1: Table S6). As shown in Fig. 7b, the StKFB genes have different degrees of response to these stresses. The number of up-regulated StKFBs induced by salt (150 mM NaCl) and drought stresses (260 μM mannitol) was greater than that of down-regulated members. The expression levels of StKFB03/04/07/17/34 were increased in both salt stress and drought stress, while StKFB06 showed decreased expression under both treatments compared with the control group. Besides, StKFB13/14/15/24/25/30 were predominant StKFB transcripts during heat stress (35 °C). Additionally, StKFBs were also respond to hormone-induced stresses and StKFB23 was found to be up-regulated under abscisic acid (ABA), inidole-3-acetic acid (IAA) and gibberellic acid (GA3) treatments. Apart from StKFB23, exogenous ABA treatment increased the expression levels of StKFB01/13/24/25/26; while the expression levels of StKFB04 and StKFB15 were induced by exogenous IAA treatment. More genes were up-regulated under GA3 induction than ABA and IAA induction. For biotic stress, StKFB13/14/20/24/25/30 were down-regulated in potato plants infected with Phytophthora infestans; while the expression of other members had no significant difference. The expression levels of StKFB10/28/32/38/43/44 were too low to be detected in these treatments.

Meanwhile, we analyzed the correlations between the StKFB genes expression in potato plants with different treatments (Additional file 3: Fig. S3b). StKFB08/09/12/21/33 showed high positive correlations with each other. StKFB02/20/22, which were highly expressed under salt stress and heat stress, were positively correlated. StKFB18 was positively correlated with StKFB05/19/27/39, but negatively correlated with StKFB11/13/16/23/29/34. StKFB03/11/15/16/26/29/31/34/35/42 were positively correlated among each other and were negative correlated with StKFB36 and StKFB37. These results might suggest that potato may adaptively respond to harmful environments by mitigating the threat of adversity through coordination and compensation of StKFB family members.

Expression patterns of StKFB genes in potato tubers with different colors

KFB proteins have been demonstrated to regulate phenylpropanoid biosynthesis via degradation of PAL and CHS, the key enzymes in anthocyanin biosynthesis [14, 29]. Therefore, we speculated that StKFBs may be involved in anthocyanins biosynthesis in potato. To explore the roles of StKFB genes in anthocyanin biosynthesis, the expression levels of StKFBs in potato tubers with different colors were investigated. The skin and flesh of ‘Jin-16’ tubers were yellow in color, while those of ‘Red Rose-2’ and ‘Xisen-8’ were red and dark purple, respectively (Fig. 8a). The anthocyanin contents in the flesh of tubers were also measured. The relative anthocyanin content of tuber flesh in ‘Xisen-8’ was significantly higher than that in ‘Red Rose-2’ (~ 2.7-fold) and ‘Jin-16’ (~ 103.5-fold) (Fig. 8b), suggesting that a different regulatory mechanism related with anthocyanin biosynthesis may exist among the three potato varieties.

Fig. 8
figure 8

Expression of StKFB genes in three colored potato tubers. a The appearance, cross profile and anthocyanin extraction of ‘Jin-16’, ‘Red Rose-2’ and ‘Xisen-8’ tubers. b Relative anthocyanin content calculated as absorbance at 530 nm/fresh weight (g). c Expression profiles of StKFB genes in three colored potato tubers detected via in-house transcriptome sequencing data. Each variety had three biological replicates. d Expression patterns of 9 selected genes in three colored potato tubers detected by qRT-PCR. Values are means ± SD of three replicates in each experiment. Bars with different lowercase letters represent significant difference at p < 0.05

The tubers of these three varieties were used as materials for RNA sequencing. After eliminating the low-quality reads, Illumina adapters and reads with unidentifiable base information, the clean reads obtained from each sample accounted for more than 95% of the raw reads (Additional file 1: Table S7). The clean bases generated from transcriptome sequencing were all above 12.00 G. In each sample, the number of filtered reads that could be mapped to the reference genome (DM v4.03/v4.04) made up more than 81% of the total clean reads (Additional file 1: Table S8).

By analyzing the RNA-seq results (Additional file 1: Table S6), we found that StKFB gene members were expressed at different levels in these potato cultivars (Fig. 8c). Specifically, StKFB06/16/21/22/24/27/31/39/41 were highly expressed in ‘Xisen-8’ compared with the other two cultivars. The expression levels of StKFB20/25/29/34 were specifically highly expressed in ‘Red Rose-2’. Genes like StKFB03/05/08/32/36/40 were highly expressed in both colored potato tubers. The expression levels of StKFB07/11/12/15/35/42/44 were relatively higher in ‘Jin-16’ than that in ‘Red Rose-2’ and ‘Xisen-8’. Accordingly, these 7 genes were positively correlated with each other, but negatively correlated with most of the highly expressed genes in colored potato tubers (Additional file 3: Fig. S3c).

To further validate the expression of StKFB genes in potato tubers, the qRT-PCR technique was used to detect the transcript levels of 9 randomly selected StKFB genes in different potato cultivars. Primer sequences of these genes were shown in Additional file 1: Table S9. And the primer specificity of each gene was presented by the melting curve (Additional file 3: Fig. S4). The expression of StKFB03 in tubers of ‘Jin-16’ was set to 1 and the expression of other genes in different cultivars were compared with that (Fig. 8d). Generally, the expression trend of individual StKFB gene in different potato tubers shown in qRT-PCR was basically consistent with RNA-seq data (Additional file 3: Fig. S5). Among these selected genes, the expression levels of StKFB16 and StKFB31 were the lowest, and there was no significant difference among the three potato varieties. On the contrary, StKFB39 had the highest expression level in three colored potato tubers, followed by StKFB29, StKFB27, StKFB14 and StKFB03. Specifically, the expression levels of StKFB03, StKFB27 and StKFB39 were significantly higher in ‘Red Rose-2’ and ‘Xisen-8’ than that in ‘Jin-16”. While other genes, such as StKFB15 and StKFB44 witnessed decreased expression levels in ‘Red Rose-2’ and ‘Xisen-8’ in comparison with ‘Jin-16′. Additionally, the expression of StKFB29 in ‘Xisen-8′ tubers was significantly lower than that in ‘Jin-16′ and ‘Red Rose-2′. These genes that were differentially expressed among ‘Jin-16′, ‘Red Rose-2′ and ‘Xisen-8′ are potentially involved in anthocyanin biosynthesis.

Discussion

The diversity and complexity of KFB structures make their functions diversified

Although both the F-box proteins and the Kelch containing proteins can bind to other proteins to mediate the substrates degradation via ubiquitylation pathway in all organisms, some studies have found that proteins that co-exist with the F-box domain and Kelch motifs were only observed in eukaryotes [41, 51, 52]. Compared to KFB in human and other animals, a large number of KFB members were identified in plants [12]. More than 103, 68 and 31 KFB members were identified in Arabidopsis thaliana, Populus trichocarpa and Salvia miltiorrhiza, respectively [1]. To date, multiple KFB genes have been isolated from chickpea, Arabidopsis, wheat and so on [14,15,16], but the potato KFB members have not been systematically identified and investigated. In this study, 44 KFB genes from potato (Solanum tuberosum) were identified and analyzed in phylogenetic relationship, extron-intro organization, motif composition, syntenic relationship and expression patterns. However, these 44 members may not represent all the KFB genes in the potato genome. The main reason is the lack of strictly conserved sequences in the F-box domains and Kelch motifs [3, 9], in which only a few amino acid residues are relatively invariant (Fig. 1, Additional file 1: Table S2 and S3). Therefore, it is possible that there exist other StKFB members that have not been detected.

By analyzing the protein sequences of F-box domains of StKFBs, we found that L at the 8th and 20th positions, P at the 9th position, I at the 16th position, and C or S at the 32nd position were highly conserved residues, which is consistent with the results of existing research [3]. Besides, D (aspartic acid), L, P, V (valine) at the 11th, 17th, 21st and 31st positions, respectively, were also conserved in F-box domains of StKFBs. However, due to the discontinuity of these relatively conserved amino acids, the sequence identity of F-box domain is low, which makes it difficult to identify KFB members.

Kelch motif is the secondary domain of KFB proteins [8], and characterized by 8 highly conserved amino acids: 4 hydrophobic amino acid residues, 2 glycine (G) and 2 aromatic amino acid residues (Y or W) (Additional file 1: Table S3). Multiple Kelch motifs would be folded to form a β-propeller with a pocket that coordinates ions required for enzyme activity and is the most likely site for KFB substrate binding [9]. The motif distribution of StKFB members were further analyzed. Based on annotation of the conserved motifs, Motif 1, 4, 10, 12 and 15 were predicted as parts of the F-box domains, while Motif 2, 3, 5 and 13 were Kelch domains (Additional file 1: Table S4). These different motifs belong to the same domain, showing the variability of this domain.

F-box domains and Kelch domains have been identified as essential components for degradation of regulatory proteins via UPS [12]. The F-box domain recognizes and binds with SKP1 to form the SCF E3 ubiquitin ligase complex; while Kelch domain is responsible for selectively interacting with target proteins [53]. Therefore, the variability of the Kelch domain is important for the recognition of different substrates, which has been demonstrated in both animals and plants. For example, α-Scruin, a Kelch repeat protein in Limulus spermatozoa, has been demonstrated to bind with F-actin and participate in actin stabilization and crosslinking. While β-scruin, having 67% sequence identity with α-Scruin, was located in the actin-free acrosomal vesicle and had different binding partners from α-scruin [9]. In Arabidopsis, AtKFB50 (At3g59940) and AtKFBCHS (At1g23390) respectively recognized and bind to PAL and CHS, mediating their proteolysis [14, 29]. Besides, the number of Kelch repeats varies in different KFB family members, which may also be a vital factor that causes the difference in KFB functions [8]. In this study, most potato KFB members (30/44) contain 1–2 Kelch motifs, followed by those containing 3 Kelch motifs (8 members). StKFB members containing 4–6 Kelch motifs are the fewest, with only 6 members in total. Although it is known that β-propellers structure formed by multiple Kelch repeats can produce different contact sites and interact with different partners, the most key residues associated with substrate proteins remain unknown. Moreover, due to the low sequence similarity of the Kelch motifs, it is almost impossible to infer its function from the primary sequence of KFB. In addition, many of them have degenerated Kelch motifs, suggesting that they might be pseudogenes or their functions may be divergent [41]. Therefore, the binding substrates of these StKFB members and their functions need further experimental verification.

The evolution of the StKFB family is relatively stable, and the duplicated genes may result in functional differentiation of StKFB members

Previous studies implied that KFB family originated before the branching of animals and plants, and may have undergone a rapid evolution in some land plants [12]. Sun et al. have found that one of the KFB subfamilies (G5) included large numbers of KFB genes in Arabidopsis, but had very few members in rice, pine and poplar, suggesting that a rapid gene birth of KFBs has occurred in Arabidopsis [41]. Also, a phylogenetic analysis of KFB proteins from S. miltiorrhiza, Arabidopsis, rice, human, mice and C. reinhardtii showed that 67 of 69 KFB members in Group I belong to Arabidopsis [1]. Similarly, in our results of KFB family evolutionary relationship among potato, Arabidopsis, rice and upland cotton, we found that 71 of the 76 members of Group I were Arabidopsis KFBs and only 5 KFBs were from other plants that we analyzed (Fig. 4).

One of the main driving forces of gene expansion is the occurrence of gene duplication events [12]. Multiple KFB genes in the G5 subfamily of Arabidopsis were found to be tandemly arrayed on the same chromosome, which probably led to the gene evolution [41]. Potato KFB family did not seem to undergo a rapid gene birth event like Arabidopsis KFBs. Forty-four StKFB genes were unevenly located on 12 potato chromosomes, including 2 pairs of tandem duplications (StKFB15/StKFB16, StKFB40/StKFB41) and 1 pair of segmental duplications (StKFB16/StKFB29) (Fig. 3). The Ka/Ks ratios of three pairs of duplicated StKFB genes were all less than 1, suggesting that the duplicated StKFBs might have undergone great selection constraint during evolution. Also, the Ka/Ks values of the orthologous pairs of KFB genes between potato and other plants were all less than 1, denoting that the corresponding homologous KFBs have not experienced positive selection (Additional file 1: Table S5). Besides, the syntenic analysis of KFB genes in different plants showed that the numbers of syntenic KFB pairs between potato and other dicots (Arabidopsis, pepper, tomato and upland cotton) were more than those between potato and the monocot (rice), indicating that potato KFBs had a closer syntenic relationship with those in dicots. Furthermore, multiple KFB orthologous pairs between potato and other two solanaceae plants (tomato and pepper) were arrayed on corresponding chromosomes and in corresponding orders, speculating that the syntenic relationship of potato KFBs was closer to the KFBs in tomato and pepper. The closely related gene members in the phylogenetic tree may have similar structure and function [33]. Therefore, phylogenetic analysis can be used as a preliminary method to study the potential function of the unknown StKFBs.

The existence of duplicated KFBs may result in redundancy of their function [41, 54]. For instance, two duplicated genes in Arabidopsis, LKP1/ZTL/AtKFB98 and LKP2/FKL2/AtKFB22, were found to share redundant functions in controlling the circadian clock and flowering time [55]. Both AtKFB29 and AtKFB32 were involved in the anther development, indicating that they may participate in the similar biological processes and have redundant functions [41]. However, numerous studies have confirmed that gene evolution caused by gene duplication may also lead to the loss of original functions and the generation of new functions. Duplication events in the active and regulatory regions such as the CDS and the promoter region, may affect the function of family genes under evolution process [56, 57]. In tartary buckwheat, several duplicated FtARFs (like FtARF7 and FtARF13) were highly expressed in different organs [50]. Similarly, many tandemly duplicated AtKFB members of G5 showed preferential expression in certain organs [41]. In this study, potato duplicated KFBs showed the different expression patterns in various potato organs and under diversified stresses (Fig. 7a and b). StKFB41 was highly expressed in mannitol-treated potato plants, but StKFB40 did not show obvious expression. Besides, StKFB16 was mainly expressed in shoots and immature fruits, while its tandemly duplicated gene StKFB15 was highly expressed in immature fruits and stolon. StKFB29, the segmentally duplicated gene of StKFB15 was predominately expressed in stolon. It is possible that evolution leads to structural differences in proteins, such as the generation of degenerated Kelch motifs, and results in their divergent functions.

Expression patterns and functional prediction of the StKFB genes

KFB proteins are widely involved in multitudinous biochemical and physiological processes in plants. The accelerated evolution of the KFB family may have contributed to more complex and varied protein-degradation mechanisms to improve plant adaptation to changing environments [12]. At present, the functions of some KFB genes have been deeply studied in Arabidopsis, rice and other model plants, while only a few StKFBs have been functionally investigated in potato. Therefore, the existing research results of KFB homologous genes in other species can be used as an important basis for the functional prediction of potato KFB family members. The functional annotations of StKFB members and their corresponding homologous genes in Arabidopsis are shown in Additional file 1: Table S10. According to the annotated information, we found that almost all KFBs may be involved in the degradation of specific proteins by UPS (Additional file 1: Table S10), thus playing an important role in different plant growth stages.

Primarily, the role of KFBs in different physiological processes of plant growth and development cannot be ignored. In this study, publicly available RNA-seq data was used to investigate the expression profiles of StKFB genes in several potato tissues and in potato plants with different treatments. The results showed that StKFB10, annotated as S-haplotype-specific F-box gene (SFB) (Additional file 1: Table S10), was specifically highly expressed in flowers (Fig. 7a), indicating that this gene may play an essential role in flower development. SFB specifically degrades non-self S-RNase through the formation of SCFSFB complex with SCF, while its self S-RNase is not degraded. This inhibits the growth of self-pollen tubes by degrading ribosomal RNA (rRNA), thus presenting self-incompatibility in potato and other plants [58]. In addition, StKFB08, StKFB13, StKFB20, StKFB22, StKFB28, StKFB33, StKFB35 and StKFB36, were also highly expressed in stamen or other flower tissues, indicating that they may also regulate potato flowering development. These studies provide evidence and direction for functional prediction of these StKFB genes, but the specific functional mechanism needs to be further studied.

StKFB01 was a LOV blue light receptor gene (StFKF1) and was highly expressed in whole flowers, leaves and petioles in potato (Fig. 7a). It has been reported that StFKF1, StGI and StCDF1 would form a complex that mediates degradation of StCDF1 through ubiquitination pathway and ultimately induces the expression of StCONSTANS (StCO) [20]. StCO is essential for converting light and clock signals into flowering signals, thereby promoting flowering and inhibiting tuberization by regulating the expression of StFT and its homologous genes [59]. Therefore, StKFB01 plays an important role in photoperiodic flowering and potato tuberization. Its orthologous genes AtFKF1 (At1g68050) and OsFKF1 (Os11g34460) also serve as photoreceptors that regulates flowering in Arabidopsis and rice [60, 61]. The similar function of these three KFB proteins may be attributed to the fact that they all contain a LOV domain belonging to the Per-Arnt-Sim (PAS) superfamily (Additional file 3: Fig. S6), which is a blue light sensing module [62]. Although StKFB27 belongs to the same group as these three KFBs, it is highly expressed in shoots and mature fruits (Fig. 7a), which may show different functions due to its lack of the LOV domain (Additional file 3: Fig. S6).

KFBs not only participate in the growth and development of organs and tissues, but also mediate plant defense signaling [12]. At present, the mechanism of F-box proteins response to stresses has been well investigated, while the regulation of KFBs in stress responses is rarely studied. It has been reported that multiple F-box genes, such as ATPP2-B11 and OsMSR9, positively regulate salt tolerance in plants [63]. A nuclear KFB member in chickpea, named CarF-Box 1, was also found to have a positive response to salt stress [15]. In this study, StKFB02/03/04/17/30/34/40 had up-regulated expression levels in salt-stressed potato plants compared with control group (Fig. 7b), implying that they may participate in salt stress response. For drought stress, the expression of StKFB04/11/17/23/34/35/41 were up-regulated, while StKFB06 was down-regulated in potato treated with mannitol. These genes may play positive or negative roles in potato drought tolerance. Similar results were found in other F-box proteins, such as TaFBA1 and GmFBX176, which are positive and negative regulators of drought tolerance in plants, respectively [64, 65]. Some StKFBs were also induced by heat, ABA, IAA and GA3, but the functional mechanism remains unclear. In addition, some KFB genes were identified to be involved in plant pathogen interaction as the “susceptibility” (S) genes, contributing to the successful infection of pathogens [12]. For example, KMD3/AtKFB39 (At2g44130), a KFB from A. thaliana, could be induced in roots by Meloidogyne incognita infection [27]. The expression of BIG24.1 was induced by botrytis infection in grapevine [66]. However, in this study, we did not find any StKFBs that can be induced by P. infestans (Fig. 7b). Whether and in what way these StKFB are involved in potato response to P. infestans requires further investigation.

Additionally, some studies have clarified the involvement of KFBs in secondary metabolites production. OsFBK1 (Os01g47050) negatively regulated lignin synthesis by degrading Cinnamoyl-CoA Reductase (OsCCR), and thus affected the secondary cell wall thickenings of anther and root [67]. In Arabidopsis, Zhang et al. have elucidated that protein ubiquitination and degradation mediated by AtKFB01 (At1g15670), AtKFB20 (At1g80440), AtKFB39 (At2g44130) and AtKFB50 (At3g59940) regulated the proteolysis of PALs, thereby modulating phenylpropanoid metabolism [14]. In 2017, they also found that another KFB, named KFBCHS (At1g23390), regulate the proteolysis of CHS and control flavonoid and anthocyanin biosynthesis in Arabidopsis [29]. However, there is limited understanding of the types of KFB interacting proteins involved in the ubiquitination pathway during secondary metabolism. Anthocyanin is one of the main secondary metabolites in the biosynthesis of plant flavonoid, which makes flowers, fruits and other organs show various colors under different pH conditions in plant vacuole [34]. Due to its outstanding free radical scavenging capacity, anthocyanin was demonstrated to have healthcare effects such as antioxidation, anti-aging, anti-tumor and immune activity regulation [68,69,70]. Purple-fleshed potato, accumulating large amounts of anthocyanin content, is regarded as high-value feedstock for food and industrial processing. To investigate which StKFBs might be involved in anthocyanin biosynthesis, transcriptomic analysis was performed on potato tubers with different colors, and its accuracy was verified by qRT-PCR on 9 randomly selected StKFBs genes. The results showed that most of the StKFB genes were differentially expressed in three colored potatoes. StKFB15 and StKFB29, which were closely related with AtKFB01 and AtKFB20, were down-regulated significantly in the purple-fleshed tubers (‘Xisen-8’) compared with the yellow-fleshed tubers (‘Jin-16’) (Fig. 8d). StKFB07 and StKFB23, the homologous genes of OsFBK1 and AtKFBCHS, respectively, also showed a downward expression trend in ‘Xisen-8’ tubers. Referring to the negative regulation of OsFBK1 and AtKFBCHS in the synthesis of secondary metabolites, we hypothesized that StKFB07 and StKFB23 may also play a negative role in phenylpropanoid biosynthesis. Furthermore, other genes such as StKFB11/18/30/38/42/44 were highly expressed in ‘Jin-16’ tubers and lowly expressed in the ‘Red Rose-2’ or ‘Xisen-8’. The different expression of the StKFBs suggested their potential roles in the modulation of anthocyanin biosynthesis. Notably, no expression of StKFB43 was detected either in different potato tissues or potato plants under different treatments, indicating that this gene is likely to be a pseudogene. This result is consistent with the annotation of its homologous gene in Arabidopsis. These results provide a basis for predicting the functions of StKFB members, but their specific functions need to be verified by future experiments.

Conclusion

In this study, a total of 44 StKFB genes were identified in potato genome. A series of analyses for these members, including gene structure, motif composition, phylogenetic relationship, duplication events, syntenic relationship and expression profiling were conducted. The StKFBs were classified into 5 groups according to the classification schemes of other plant species. Two pairs and one pair of genes were predicted to be tandemly duplicated and segmentally duplicated genes, respectively. The syntenic analysis showed that the KFBs in potato were closely related to the KFBs in tomato and pepper. Expression profiles of StKFBs manifested their distinct expression patterns in various tissues and in response to diversified stresses, and their potential roles in anthocyanin biosynthesis. These findings are helpful to screen candidate StKFBs for further functional characterization, and provide the basis for genetic improvement of potato agronomic traits.

Materials and methods

Identification of KFB family members in potato

The profile HMMs (Hidden Markov Models) of F-box domains and Kelch domains downloaded from Pfam database [36] were used to search the StKFB members from the annotated protein sequences of potato (DM v4.03/v4.04) [38] using Hmmsearch program in HMMER software package v3.0 [37] (http://hmmer.org/) with default parameters. Potato protein sequences were acquired from Spud DB Potato Genomics Resources (http://spuddb.uga.edu/). Furthermore, A. thaliana KFB protein sequences (TAIR10), downloaded from TAIR database (https://www.arabidopsis.org/Blast/index.jsp), were used as queries to blast against the potato protein sequences with E-value ≤1e-5. These putative StKFB members were analyzed in PfamScan database [39] (https://www.ebi.ac.uk/Tools/pfa/pfamscan/) to remove the KFBs lacking the conserved domains. The repetitive sequences were also eliminated after multiple protein sequence alignment by MUSCLE algorithm [71] as implemented in MEGA X software [72]. The chromosome location, CDS and genomic length of the predicted StKFB genes were obtained from Spud DB Potato Genomics Resources. The number of Kelch repeat motifs included in each StKFB protein was calculated using PfamScan website (https://www.ebi.ac.uk/Tools/pfa/pfamscan/). Multi-sequence alignment and secondary structures prediction of F-box domains were conducted by DNAMAN X software v10.0.2.128 and the online tool provided by NovoPro Bioscience Inc. (https://www.novopro.cn/tools/secondary-structure-prediction.html), respectively. The tertiary structures of Kelch motifs with different numbers were predicted by SWISS-MODEL website [73] (https://swissmodel.expasy.org/interactive).

Prediction of physicochemical properties and subcellular localization of StKFB members

The numbers of amino acids, theoretical molecular weights (MW), isoelectric points (pI) and grand average of hydropathicity (GRAVY) of these identified StKFB proteins were computed using ProtParam software provided by ExPasy website [74] (https://web.expasy.org/protparam/). Subcellular localization of StKFB family members was predicted by Plant-mPLoc website [75] (http://www.csbio.sjtu.edu.cn/bioinf/plant-multi/) and ProtComp 9.0 [76] (http://www.softberry.com/berry.phtml?topic=protcomppl&group=programs&subgroup=proloc).

Chromosomal localization and gene duplication analysis of StKFBs

All StKFB genes were mapped on the potato chromosomes using Circos software [40] (http://circos.ca/software/download/) based on the physical position information obtained from the Spud DB Potato Genomics Resources (http://spuddb.uga.edu/). Gene duplication events of StKFBs were analyzed by Multiple collinear scanning toolkits (MCScanX) [77] (https://github.com/wyp1125/MCScanx) with default parameters. The synonymous substitution (Ks) and non-synonymous substitution (Ka) was calculated by TBtools software [78] (https://github.com/CJ-Chen/TBtools/releases). The divergence time of duplicated StKFB genes was estimated according to the method of Shen and Yuan [43].

Analyses of conserved motifs and exon-intron organization

Conserved motifs of the putative StKFB proteins were identified by Multiple Em for Motif Elicitation (MEME) software v5.3.0 (http://meme-suite.org/meme-software/5.3.0/meme-5.3.0.tar.gz) [46]. The parameters were set as follows: the number of motifs searched was set to 20 and the range of the motif length was set to 6–200 residues. All motifs were further annotated with InterProScan (http://www.ebi.ac.uk/interpro/) [47, 48].

The CDS file and genomic sequences file of 44 StKFB genes were downloaded from Spud DB Potato Genomics Resources (http://spuddb.uga.edu/). The exon and intron distribution of StKFBs was depicted by comparing the CDS of StKFBs with their corresponding genomic DNA sequences using Gene Structure Display Server (GSDS 2.0) [79] (http://gsds.gao-lab.org/).

Phylogenetic analysis and classification of KFB family members

The protein files of potato (DM v4.03/v4.04) [38], Arabidopsis (TAIR10), rice (Oryza sativa v7.0) and upland cotton (Gossypium hirsutum v1.1) were downloaded from Spud DB Potato Genomics Resources (http://spuddb.uga.edu/), TAIR database (https://www.arabidopsis.org/download/index-auto.jsp?dir=%2Fdownload_files%2FProteins%2FTAIR10_protein_lists), Rice Genome Annotation Project database (http://rice.plantbiology.msu.edu/), and Cotton Research Institute database (https://mascotton.njau.edu.cn/info/1054/1118.htm), respectively. Then the identification method of potato KFBs was used to search for KFB members of other species. A total of 284 KFB proteins, including 44 StKFBs, 115 AtKFBs, 39 OsKFBs and 86 GhKFBs, were considered for construction of an inter-species phylogenetic tree. Multiple sequence alignment of these KFB proteins was performed using MUSCLE algorithm [71]. The maximum-likelihood (ML) method [80] of IQ-TREE software v2.1.4 [44, 45] (http://www.iqtree.org/) was applied to construct the phylogenetic tree with 1000 bootstrap replicates. The model VT + F + R7 was automatically evaluated as the best-fit model through ModelFinder [81] analysis. Potato KFB members were categorized into different groups based on the KFB classification schemes of Arabidopsis, rice and upland cotton.

Moreover, a phylogenetic tree of KFB proteins from potato was also constructed and analyzed. Multiple sequence alignment of the 44 potato KFB proteins was carried out using MUSCLE algorithm [71], and the phylogenetic tree was constructed by the unrooted neighbor-joining [82] method with 1000 bootstrap replicates using IQ-TREE software.

Synteny analysis of KFB genes in potato and other plant species

Protein sequences of potato, Arabidopsis, rice and upland cotton were obtained using the method described above. Protein sequence files of tomato (Solanum lycopersicum) (ITAG4.0) and pepper (Capsicum annuum) (ASM51225v2) were obtained from Phytozome v13 (https://phytozome-next.jgi.doe.gov/) and EnsemblPlants (http://ftp.ensemblgenomes.org/pub/plants/release-52/fasta/capsicum_annuum/), respectively. The Makeblastdb program [83] (https://www.ncbi.nlm.nih.gov/books/NBK569841/) was applied to build local databases of protein sequences from these six plant species, and the potato protein sequences were then compared pairwise with those of five other species using Blastp [84]. The Syntenic relationship was analyzed by MCScanX software [77] (https://github.com/wyp1125/MCScanx).

Plant materials and anthocyanin determination

In this study, three tetraploid cultivars (‘Jin-16’ with yellow skin and yellow flesh, ‘Red Rose-2’ with red skin and red flesh, and ‘Xisen-8’ with purple skin and purple flesh) were used as plant materials. The tissue culture plantlets of ‘Jin-16’ were preserved in the College of Agriculture, Shanxi Agricultural University. The virus-free seedlings of ‘Red Rose-2’ and ‘Xisen-8’ were kindly provided by Leling Xisen Potato Industry Co. Ltd. (Leling, Shandong, China). They were cultured in MS medium at 22 ± 1 °C under 16 h light/8 h dark regime. The 1-month-old tissue culture plantlets were transferred into pots with soil and grown in the greenhouse at 22 ± 1 °C under 16 h light/8 h dark regime. After 3 months, fresh tubers were harvested for anthocyanin determination and RNA extraction.

Three potato tubers with similar sizes were selected from each potato variety and blended separately. Anthocyanin was extracted according to the method used by Wang et al. [85]. The potato flesh from each tuber was ground into powder and then exposed to HCl-methanol solution (1:99 by volume) at 4 °C for 6–8 h under darkness until the tissues were completely decolorized. After centrifuging at 12000 rpm for 10 min, the absorbance values of supernatants were determined at 530 nm using a UV-2450 spectrophotometer (Shimadzu, Kyoto, Japan). Each sample had three replicates to ensure the results reliable.

Total RNA extraction, library construction and transcriptome sequencing

Total RNA was isolated from the collected samples using the Quick RNA Isolation Kit (Huayueyang, Beijing, China). Electrophoresis was then performed with 1% agarose gel to monitor the presence of RNA degradation and DNA contamination. Nanodrop 1000 spectrophotometer (Thermo Scientific) was utilized to measure the purity and concentration of RNA samples. After integrity testing by Agilent 2100 BioAnalyzer (Agilent Technologies), the total RNA samples were used for the construction of cDNA libraries and validation of deep sequencing results. .

Total RNA with ribosomal RNA removal was trimmed into shorter fragments of 250 ~ 300 bp using fragmentation buffer. The first strand of cDNA was synthesized using fragment RNA as template and random oligonucleotide as primer. The second strand of cDNA was subsequently synthesized using dNTPs as raw materials in the DNA polymerase I system. After end-repair, 3′ end adenylation and ligation of the Illumina sequencing adapters, the double-stranded cDNA fragments were purified and amplified by PCR to construct the final libraries. Three biological replicates were set for each potato cultivar. Therefore, 9 libraries were constructed, containing Jin-16_1, Jin-16_2, Jin-16_3, Red Rose-2_1, Red Rose-2_2, Red Rose-2_3, Xisen-8_1, Xisen-8_2 and Xisen-8_3. After quantitative and qualitative determination of all libraries, RNA sequencing was carried out on an Illumina novaseq 6000 platform provided by Novogene Bioinformatics Technology Co. Ltd. (Beijing, China), and 150 bp paired-end reads were generated. The obtained raw reads were processed by getting rid of the low-quality reads, the reads with sequencing adapters and poly-N sequences. The clean reads were acquired and aligned to a potato reference genome (DM v4.03/v4.04) using HISAT2 software [86]. The mapped reads were spliced and assembled into transcripts using Stringtie software [87] and Cuffmerge software [88]. The obtained transcripts were annotated by Cuffcompare 2.2.1 (http://cole-trapnell-lab.github.io/cufflinks/manual/). The FPKM values (fragments per kilobase of transcript sequence per millions base pairs sequenced) of genes were calculated using Stringtie software. The dataset was deposited in the NCBI Sequence Read Archive under the Bioproject accession PRJNA729884 (available from https://dataview.ncbi.nlm.nih.gov/object/PRJNA729884?reviewer=ntlkjmravag9c9ousg57ps9k86).

RNA-seq analysis of StKFB genes

The publicly available dataset for FPKM values of all the representative transcripts across 40DM and 16 RH libraries: DM_RH_RNA-Seq_FPKM_expression_matrix_for_DM_v4.03_13dec2013_desc.xlsx (http://spuddb.uga.edu/pgsc_download.shtml) [38] was used to examine expression patterns of 44 StKFBs in 13 potato tissues, including roots, shoots, leaves, petioles, stolon, tubers, stamens, sepals, carpels, petals, whole flowers, immature and mature fruits. This dataset was also applied to analyze the expression levels of StKFBs in whole potato plants with different treatments. For abiotic stresses, the plants were exposed to stresses for 24 h including salinity (150 mM NaCl), drought (260 μM mannitol), heat (35 °C), as well as hormone treatments like ABA (50 μM), IAA (10 μM) and GA3 (50 μM). For biotic stress, the sequencing data was obtained from mixed samples of potatoes infected with Phytophthora infestans for 24, 36 and 72 h. In addition, the transcriptome sequencing data obtained in our lab was used to perform the expression analysis of StKFBs in tubers from cultivars containing various levels of anthocyanin content (cultivar ‘Jin-16’, ‘Red Rose-2’ and ‘Xisen-8’). Each variety had three biological replicates. The lg (FPKM+ 1) values were normalized using Scale function and displayed in heatmaps using tidyverse v. 1.3.1 (https://search.r-project.org/CRAN/refmans/tidyverse/html/tidyverse-package.html), ggplot2 v. 3.3.5 (https://cran.r-project.org/web/packages/ggplot2/index.html) and pheatmap v. 1.0.12 (https://CRAN.R-project.org/package=pheatmap) packages in RStudio. Furthermore, the correlation between the expression patterns of StKFB genes was analyzed based on the Pearson correlation coefficient [89] and graphically presented using corrplot package v. 0.92 (https://cran.r-project.org/web/packages/corrplot/).

Expression analysis of selected StKFBs by qRT-PCR

Quantitative real-time polymerase chain reaction (qRT-PCR) was carried out with the TB Green™ Premix Ex Taq™ (Tli RNase H Plus) (Takara, Dalian, China) on CFX96 PCR System (Bio-Rad, USA). Primers of these StKFB genes were designed by Primer-Blast [90] in NCBI website (https://www.ncbi.nlm.nih.gov/tools/primer-blast/), and their specificity was tested by dissociation curve analysis. The 10 μl reaction volume samples, containing 5 μL TB Green, 1 μL diluted cDNA sample, 0.4 μL 10 μM solution of each primer and 3.2 μL ddH2O, were used for PCR with the following cycling program: 95 °C for 3 min, followed by 40 cycles of 95 °C for 10 s, 60 °C for 30 s, and 72 °C for 20 s. Dissolution curves were obtained by heating the amplicon from 60 °C (5 s) to 95 °C (50 s). The relative expression of selected StKFB genes was calibrated against the reference gene EF1α using the method of 2-∆∆Ct [33]. Three tubers selected from each potato cultivar were mixed into one sample, and each sample had three replicates. The relative expression amounts of genes were displayed in boxplots using tidyverse v. 1.3.1 (https://search.r-project.org/CRAN/refmans/tidyverse/html/tidyverse-package.html), cowplot v. 1.1.1 (https://CRAN.R-project.org/package=cowplot), ggplot2 v. 3.3.5 (https://cran.r-project.org/web/packages/ggplot2/index.html) and ggsci v. 2.9 (https://CRAN.R-project.org/package=ggsci) packages in RStudio. Results were presented as means ± SD. The one-way ANOVA of variance was used to conduct the statistical analyses of qRT-PCR results by SPSS software v26 [91]. The Duncan’s Multiple Range Test (DMRT) post hoc test was used to measure specific differences between pairs of means at 0.05 level of significance. The Bonferroni algorithm provided by SPSS software v26 was used for p-values correction [92].

Availability of data and materials

The datasets generated and/or analyzed for this work were deposited in the NCBI Sequence Read Archive under the Bioproject accession PRJNA729884, available from https://dataview.ncbi.nlm.nih.gov/object/PRJNA729884?reviewer=ntlkjmravag9c9ousg57ps9k86. Other datasets used in this study are included in this published article and its supplementary information files.

Abbreviations

AFR:

Attenuated Far-red Response

ABA:

Abscisic acid

CCR:

Cinnamoyl-CoA reductase

CDS:

Coding sequence

CDF:

Cycling Dof Factor

CFK1:

COP9 interacting F-box Kelch 1

CHS:

Chalcone synthase

CO:

CONSTANS

CTG10:

Cold Temperature Germinating 10

DMRT:

Duncan’s Multiple Range Test

E3:

Ubiquitin-ligation enzymes

FKF1:

Flavin-binding Kelch repeat F-box 1

GA3 :

Gibberellin A3

GRAVY:

Grand average of hydropathicity

GSDS:

Gene Structure Display Server

HMM:

Hidden Markov Model

IAA:

Indole-3-acetic acid

KFB:

Kelch repeat F-box

Ka:

The number of non-synonymous substitutions per non-synonymous site

Ks:

The number of nonsynonymous substitutions per nonsynonymous site

LKP2:

Light, oxygen or voltage Kelch protein 2

LOV:

Light, Oxygen or Voltage

MeJA:

Methyl jasmonate

MEME:

Multiple Em for Motif Elicitation

ML:

Maximum-likelihood

MW:

Molecular weights

Mya:

Million years ago

NJ:

Neighbor- joining

PAL:

Phenylalanine ammonia-lyase

PAS:

Per-Arnt-Sim

PGSC:

Potato Genome Sequencing Consortium

pI:

Isoelectric point

PIF1:

Phytochrome Interacting Factor 1

qRT-PCR:

quantitative real-time polymerase chain reaction

rRNA:

Ribosomal RNA

SCF:

Skp1-Cullin-F-box

SFB:

S-haplotype-specific F-box

SKP1:

S-phase Kinase-associated Protein 1

UPS:

Ubiquitination-26 s proteasome system

ZTL:

ZEITLUPE

References

  1. Yu H, Jiang M, Xing B, Liang L, Zhang B, Liang Z. Systematic analysis of Kelch repeat F-box (KFB) protein gene family and identification of phenolic acid regulation members in salvia miltiorrhiza Bunge. Genes. 2020;11(5):557.

    Article  PubMed Central  CAS  Google Scholar 

  2. Li H, Wei C, Meng Y, Fan R, Zhao W, Wang X, et al. Identification and expression analysis of some wheat F-box subfamilies during plant development and infection by Puccinia triticina. Plant Physiol Biochem. 2020;155:535–48.

    Article  CAS  PubMed  Google Scholar 

  3. Kipreos ET, Pagano M. The F-box protein family. Genome Biol. 2000;1(5):REVIEWS3002.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Song J, Shang L, Chen S, Lu Y, Zhang Y, Ouyang B, et al. Interactions between ShPP2-1, an F-box family gene, and ACR11A regulate cold tolerance of tomato. Hortic Res. 2021;8(1):148.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  5. Xu G, Ma H, Nei M, Kong H. Evolution of F-box genes in plants: different modes of sequence divergence and their relationships with functional diversification. Proc Natl Acad Sci U S A. 2009;106(3):835–40.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Gagne JM, Downes BP, Shiu SH, Durski AM, Vierstra RD. The F-box subunit of the SCF E3 complex is encoded by a diverse superfamily of genes in Arabidopsis. Proc Natl Acad Sci U S A. 2002;99(17):11519–24.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Abd-Hamid NA, Ahmad-Fauzi MI, Zainal Z, Ismail I. Diverse and dynamic roles of F-box proteins in plant biology. Planta. 2020;251(3):68.

    Article  CAS  PubMed  Google Scholar 

  8. Prag S, Adams JC. Molecular phylogeny of the kelch-repeat superfamily reveals an expansion of BTB/kelch proteins in animals. BMC Bioinformatics. 2003;4:42.

    Article  PubMed  PubMed Central  Google Scholar 

  9. Adams J, Kelso R, Cooley L. The kelch repeat superfamily of proteins: propellers of cell function. Trends Cell Biol. 2000;10(1):17–24.

    Article  CAS  PubMed  Google Scholar 

  10. Kopec KO, Lupas AN. β-Propeller blades as ancestral peptides in protein evolution. Plos One. 2013;8(10):e77074.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Ito N, Phillips SE, Yadav KD, Knowles PF. Crystal structure of a free radical enzyme, galactose oxidase. J Mol Biol. 1994;238(5):794–814.

    Article  CAS  PubMed  Google Scholar 

  12. Hassan MN, Zainal Z, Ismail I. Plant kelch containing F-box proteins: structure, evolution and functions. RSC Adv. 2015;5:42808–14.

    Article  CAS  Google Scholar 

  13. Imaizumi T, Tran HG, Swartz TE, Briggs WR, Kay SA. FKF1 is essential for photoperiodic-specific light signalling in Arabidopsis. Nature. 2003;426(6964):302–6.

    Article  CAS  PubMed  Google Scholar 

  14. Zhang XB, Gou MY, Liu CJ. Arabidopsis Kelch repeat F-box proteins regulate phenylpropanoid biosynthesis via controlling the turnover of phenylalanine ammonia-lyase. Plant Cell. 2013;25(12):4994–5010.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Jia Y, Gu H, Wang X, Chen Q, Shi S, Zhang J, et al. Molecular cloning and characterization of an F-box family gene CarF-box 1 from chickpea (Cicer arietinum L.). Mol Biol Rep. 2012;39(3):2337–45.

    Article  CAS  PubMed  Google Scholar 

  16. Wei C, Fan R, Meng Y, Yang Y, Wang X, Laroche A, et al. Molecular identification and acquisition of interacting partners of a novel wheat F-box/Kelch gene TaFBK. Physiol Mol Plant Pathol. 2020;112:101564.

    Article  CAS  Google Scholar 

  17. Franciosini A, Lombardi B, Iafrate S, Pecce V, Mele G, Lupacchini L, et al. The Arabidopsis COP9 SIGNALOSOME INTERACTING F-BOX KELCH1 protein forms an SCF ubiquitin ligase and regulates hypocotyl elongation. Mol Plant. 2013;6(5):1616–29.

    Article  CAS  PubMed  Google Scholar 

  18. Chen Y, Xu Y, Luo W, Li W, Chen N, Zhang D, et al. The F-box protein OsFBK12 targets OsSAMS1 for degradation and affects pleiotropic phenotypes, including leaf senescence, in rice. Plant Physiol. 2013;163(4):1673–85.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Kloosterman B, Abelenda JA, Gomez Mdel M, Oortwijn M, de Boer JM, Kowitwanich K, et al. Naturally occurring allele diversity allows potato cultivation in northern latitudes. Nature. 2013;495(7440):246–50.

    Article  CAS  PubMed  Google Scholar 

  20. Kondhare KR, Vetal PV, Kalsi HS, Banerjee AK. BEL1-like protein (StBEL5) regulates CYCLING DOF FACTOR1 (StCDF1) through tandem TGAC core motifs in potato. J Plant Physiol. 2019;241:153014.

    Article  CAS  PubMed  Google Scholar 

  21. Majee M, Kumar S, Kathare PK, Wu S, Gingerich D, Nayak NR, et al. KELCH F-BOX protein positively influences Arabidopsis seed germination by targeting PHYTOCHROME-INTERACTING FACTOR1. Proc Natl Acad Sci U S A. 2018;115(17):E4120–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Harmon FG, Kay SA. The F box protein AFR is a positive regulator of phytochrome A-mediated light signaling. Curr Biol. 2003;13(23):2091–6.

    Article  CAS  PubMed  Google Scholar 

  23. Kim J, Geng R, Gallenstein RA, Somers DE. The F-box protein ZEITLUPE controls stability and nucleocytoplasmic partitioning of GIGANTEA. Development. 2013;140(19):4060–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Lee BD, Cha JY, Kim MR, Shin GI, Paek NC, Kim WY. Light-dependent suppression of COP1 multimeric complex formation is determined by the blue-light receptor FKF1 in Arabidopsis. Biochem Biophys Res Commun. 2019;508(1):191–7.

    Article  CAS  PubMed  Google Scholar 

  25. Li F, Zhang X, Hu R, Wu F, Ma J, Meng Y, et al. Identification and molecular characterization of FKF1 and GI homologous genes in soybean. Plos One. 2013;8(11):e79036.

    Article  PubMed  PubMed Central  Google Scholar 

  26. Xue ZG, Zhang XM, Lei CF, Chen XJ, Fu YF. Molecular cloning and functional analysis of one ZEITLUPE homolog GmZTL3 in soybean. Mol Biol Rep. 2012;39(2):1411–8.

    Article  CAS  PubMed  Google Scholar 

  27. Curtis RHC, Pankaj PSJ, Napier J, Matthes MC. The Arabidopsis F-box/Kelch-repeat protein At2g44130 is upregulated in giant cells and promotes nematode susceptibility. Mol Plant-Microbe Interact. 2013;26(1):36–43.

    Article  CAS  PubMed  Google Scholar 

  28. Feder A, Burger J, Gao S, Lewinsohn E, Katzir N, Schaffer AA, et al. A Kelch domain-containing F-box coding gene negatively regulates flavonoid accumulation in muskmelon. Plant Physiol. 2015;169(3):1714–26.

    PubMed  PubMed Central  Google Scholar 

  29. Zhang X, Abrahan C, Colquhoun TA, Liu CJ. A proteolytic regulator controlling chalcone synthase stability and flavonoid biosynthesis in Arabidopsis. Plant Cell. 2017;29(5):1157–74.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Yuan N, Balasubramanian VK, Chopra R, Mendu V. The photoperiodic flowering time regulator FKF1 negatively regulates cellulose biosynthesis. Plant Physiol. 2019;180(4):2240–53.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Tang R, Niu S, Zhang G, Chen G, Haroon M, Yang Q, et al. Physiological and growth responses of potato cultivars to heat stress. Botany. 2018;96:897–912.

    Article  CAS  Google Scholar 

  32. Xie CH, Liu J. transition of potato from a famine relief crop to staple food in China. J Huazhong Agric Univ (in Chinese). 2021;40(4):19–26.

    Google Scholar 

  33. Tang R, Zhu W, Song X, Lin X, Cai J, Wang M, et al. Genome-wide identification and function analyses of heat shock transcription factors in potato. Front Plant Sci. 2016;7:490.

    PubMed  PubMed Central  Google Scholar 

  34. Liu F, Yang Y, Gao J, Ma C, Bi Y. A comparative transcriptome analysis of a wild purple potato and its red mutant provides insight into the mechanism of anthocyanin transformation. Plos One. 2018;13(1):e0191406.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  35. Luthra SK, Tiwari JK, Kaundal B, Raigond P. Breeding for coloured flesh potatoes: molecular, agronomical and nutritional profiling. Potato J. 2018;45(2):81–92.

    Google Scholar 

  36. Mistry J, Chuguransky S, Williams L, Qureshi M, Salazar GA, Sonnhammer ELL, et al. Pfam: the protein families database in 2021. Nucleic Acids Res. 2020;49(D1):D412–9.

    Article  PubMed Central  CAS  Google Scholar 

  37. Mistry J, Finn RD, Eddy SR, Bateman A, Punta M. Challenges in homology search: HMMER3 and convergent evolution of coiled-coil regions. Nucleic Acids Res. 2013;41(12):e121.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. PGSC. (potato genome sequencing consortium). Genome sequence and analysis of the tuber crop potato. Nature. 2011;475:189–95.

    Article  CAS  Google Scholar 

  39. Madeira F, Park YM, Lee J, Buso N, Gur T, Madhusoodanan N, et al. The EMBL-EBI search and sequence analysis tools APIs in 2019. Nucleic Acids Res. 2019;47(W1):W636-41.

  40. Krzywinski M, Schein J, Birol I, Connors J, Gascoyne R, Horsman D, et al. Circos: an information aesthetic for comparative genomics. Genome Res. 2009;19(9):1639–45.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Sun YJ, Zhou XF, Ma H. Genome-wide analysis of Kelch repeat containing F-box family. J Integr Plant Biol. 2007;49(6):940–52.

    Article  CAS  Google Scholar 

  42. Vatansever R, Koc I, Ozyigit II, Sen U, Uras ME, Anjum NA, et al. Genome-wide identification and expression analysis of sulfate transporter (SULTR) genes in potato (Solanum tuberosum L.). Planta. 2016;244(6):1167–83.

    Article  CAS  PubMed  Google Scholar 

  43. Shen C, Yuan J. Genome-wide investigation and expression analysis of K(+)-transport-related gene families in Chinese cabbage (Brassica rapa ssp. pekinensis). Biochem Genet. 2021;59(1):256–82.

    Article  CAS  PubMed  Google Scholar 

  44. Nguyen LT, Schmidt HA, von Haeseler A, Minh BQ. IQ-TREE: a fast and effective stochastic algorithm for estimating maximum-likelihood phylogenies. Mol Biol Evol. 2015;32(1):268–74.

    Article  CAS  PubMed  Google Scholar 

  45. Minh BQ, Schmidt HA, Chernomor O, Schrempf D, Woodhams MD, von Haeseler A, et al. IQ-TREE 2: new models and efficient methods for phylogenetic inference in the genomic era. Mol Biol Evol. 2020;37(5):1530–4.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Li J, Wang Z, Qi B, Zhang J, Yang H. MEMe: a mutually enhanced modeling method for efficient and effective human pose estimation. Sensors (Basel). 2022;22(2):632.

  47. Wei J, Tiika RJ, Cui G, Ma Y, Yang H, Duan H. Transcriptome-wide identification and expression analysis of the KT/HAK/KUP family in Salicornia europaea L. under varied NaCl and KCl treatments. PeerJ. 2022;10:e12989.

    Article  PubMed  PubMed Central  Google Scholar 

  48. Blum M, Chang HY, Chuguransky S, Grego T, Kandasaamy S, Mitchell A, et al. The InterPro protein families and domains database: 20 years on. Nucleic Acids Res. 2021;49(D1):D344–54.

    Article  CAS  PubMed  Google Scholar 

  49. Liu R, Wu M, Liu HL, Gao YM, Chen J, Yan HW, et al. Genome-wide identification and expression analysis of the NF-Y transcription factor family in Populus. Physiol Plant. 2021;171:309–27.

    Article  CAS  PubMed  Google Scholar 

  50. Liu M, Ma Z, Wang A, Zheng T, Huang L, Sun W, et al. Genome-wide investigation of the auxin response factor gene family in tartary buckwheat (Fagopyrum tataricum). Int J Mol Sci. 2018;19(11):3526.

    Article  PubMed Central  CAS  Google Scholar 

  51. Andrade MA, González-Guzmán M, Serrano R, Rodríguez PL. A combination of the F-box motif and kelch repeats defines a large Arabidopsis family of F-box proteins. Plant Mol Biol. 2001;46(5):603–14.

    Article  CAS  PubMed  Google Scholar 

  52. Lechner E, Achard P, Vansiri A, Potuschak T, Genschik P. F-box proteins everywhere. Curr Opin Plant Biol. 2006;9(6):631–8.

    Article  CAS  PubMed  Google Scholar 

  53. Horn-Ghetko D, Krist DT, Prabu JR, Baek K, Mulder MPC, Klügel M, et al. Ubiquitin ligation to F-box protein targets by SCF-RBR E3-E3 super-assembly. Nature. 2021;590(7847):671–6.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Nelson DC, Lasswell J, Rogg LE, Cohen MA, Bartel B. FKF1, a clock-controlled gene that regulates the transition to flowering in Arabidopsis. Cell. 2000;101(3):331–40.

    Article  CAS  PubMed  Google Scholar 

  55. Somers DE, Kim WY, Geng R. The F-box protein ZEITLUPE confers dosage-dependent control on the circadian clock, photomorphogenesis, and flowering time. Plant Cell. 2004;16(3):769–82.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. Musavizadeh Z, Najafi-Zarrini H, Kazemitabar SK, Hashemi SH, Faraji S, Barcaccia G, et al. Genome-wide analysis of potassium channel genes in rice: expression of the OsAKT and OsKAT genes under salt stress. Genes (Basel). 2021;12(5):784.

  57. Abdullah FS, Mehmood F, Malik HMT, Ahmed I, Heidari P, Poczai P. The GASA gene family in cacao (Theobroma cacao, Malvaceae): genome wide identification and expression analysis. Agronomy. 2021;11(7):1425.

  58. Ma L, Zhang C, Zhang B, Tang F, Li F, Liao Q, et al. A nonS-locus F-box gene breaks self-incompatibility in diploid potatoes. Nat Commun. 2021;12(1):4142.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  59. Suárez-López KW, Robson F, Onouchi H, Valverde F, Coupland G. CONSTANS mediates between the circadian clock and the control of flowering in Arabidopsis. Nature. 2001;410(6832):1116–20.

    Article  PubMed  Google Scholar 

  60. Nakasako M, Matsuoka D, Zikihara K, Tokutomi S. Quaternary structure of LOV-domain containing polypeptide of Arabidopsis FKF1 protein. FEBS Lett. 2005;579(5):1067–71.

    Article  CAS  PubMed  Google Scholar 

  61. Han SH, Yoo SC, Lee BD, An G, Paek NC. Rice FLAVIN-BINDING, KELCH REPEAT, F-BOX 1 (OsFKF1) promotes flowering independent of photoperiod. Plant Cell Environ. 2015;38(12):2527–40.

    Article  CAS  PubMed  Google Scholar 

  62. Ogura Y, Komatsu A, Zikihara K, Nanjo T, Tokutomi S, Wada M, et al. Blue light diminishes interaction of PAS/LOV proteins, putative blue light receptors in Arabidopsis thaliana, with their interacting partners. J Plant Res. 2008;121(1):97–105.

    Article  CAS  PubMed  Google Scholar 

  63. Xu GY, Cui YC, Wang ML, Li MJ, Yin XM, Xia XJ. OsMsr9, a novel putative rice F-box containing protein, confers enhanced salt tolerance in transgenic rice and Arabidopsis. Mol Breed. 2014;34:1055–64.

    Article  CAS  Google Scholar 

  64. Zhou SM, Sun XD, Yin SH, Kong XZ, Zhou S, Xu Y, et al. The role of the F-box gene TaFBA1 from wheat (Triticum aestivum L.) in drought tolerance. Plant Physiol Biochem. 2014;84:213–23.

    Article  CAS  PubMed  Google Scholar 

  65. Yu Y, Wang P, Bai Y, Wang Y, Wan H, Liu C, et al. The soybean F-box protein GmFBX176 regulates ABA-mediated responses to drought and salt stress. Environ Exp Bot. 2020;176:104056.

    Article  CAS  Google Scholar 

  66. Paquis S, Mazeyrat-Gourbeyre F, Fernandez O, Crouzet J, Clement C, Baillieul F, et al. Characterization of a F-box gene up-regulated by phytohormones and upon biotic and abiotic stresses in grapevine. Mol Biol Rep. 2011;38(5):3327–37.

    Article  CAS  PubMed  Google Scholar 

  67. Borah P, Khurana JP. The OsFBK1 E3 ligase subunit affects anther and root secondary cell wall thickenings by mediating turnover of a cinnamoyl-CoA reductase. Plant Physiol. 2018;176(3):2148–65.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  68. Sehitoglu MH, Farooqi AA, Qureshi MZ, Butt G, Aras A. Anthocyanins: targeting of signaling networks in cancer cells. Asian Pac J Cancer Prev. 2014;15(5):2379–81.

    Article  PubMed  Google Scholar 

  69. Sarkar B, Kumar D, Sasmal D, Mukhopadhyay K. Antioxidant and DNA damage protective properties of anthocyanin-rich extracts from Hibiscus and Ocimum: a comparative study. Nat Prod Res. 2014;28(17):1393–8.

    Article  CAS  PubMed  Google Scholar 

  70. He W, Zeng M, Chen J, Jiao Y, Niu F, Tao G, et al. Identification and quantitation of anthocyanins in purple-fleshed sweet potatoes cultivated in China by UPLC-PDA and UPLC-QTOF-MS/MS. J Agric Food Chem. 2016;64(1):171–7.

    Article  CAS  PubMed  Google Scholar 

  71. Edgar RC. MUSCLE: a multiple sequence alignment method with reduced time and space complexity. BMC Bioinform. 2004;5:113.

    Article  CAS  Google Scholar 

  72. Kumar S, Stecher G, Li M, Knyaz C, Tamura K. MEGA X: molecular evolutionary genetics snalysis across vomputing platforms. Mol Biol Evol. 2018;35(6):1547–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  73. Waterhouse A, Bertoni M, Bienert S, Studer G, Tauriello G, Gumienny R, et al. SWISS-MODEL: homology modelling of protein structures and complexes. Nucleic Acids Res. 2018;46(W1):W296–303.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  74. 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  PubMed  PubMed Central  Google Scholar 

  75. Chou KC, Shen HB. Plant-mPLoc: a top-down strategy to augment the power for predicting plant protein subcellular localization. Plos One. 2010;5(6):e11335.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  76. Jing L, Guo D, Hu W, Niu X. The prediction of a pathogenesis-related secretome of Puccinia helianthi through high-throughput transcriptome analysis. BMC Bioinform. 2017;18(1):166.

    Article  CAS  Google Scholar 

  77. Wang Y, Tang H, Debarry JD, Tan X, Li J, Wang X, et al. MCScanX: a toolkit for detection and evolutionary analysis of gene synteny and collinearity. Nucleic Acids Res. 2012;40(7):e49.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  78. Chen C, Chen H, Zhang Y, Thomas HR, Frank MH, He Y, et al. TBtools: An integrative toolkit developed for interactive analyses of big biological data. Mol Plant. 2020;13(8):1194–202.

    Article  CAS  PubMed  Google Scholar 

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

    Article  PubMed  Google Scholar 

  80. Dhar A, Minin VN. Maximum likelihood phylogenetic inference. In: Encyclopedia of Evolutionary Biology; 2016. p. 499–506.

    Chapter  Google Scholar 

  81. Kalyaanamoorthy S, Minh BQ, Wong TKF, von Haeseler A, Jermiin LS. ModelFinder: fast model selection for accurate phylogenetic estimates. Nat Methods. 2017;14(6):587–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  82. Davidson R, Campo AMD. Combinatorial and computational investigations of neighbor-joining bias. Front Genet. 2020;11:584785.

  83. Johnson M, Zaretskaya I, Raytselis Y, Merezhuk Y, McGinnis S, Madden TL. NCBI BLAST: a better web interface. Nucleic Acids Res. 2008;36(Web Server issue):W5–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  84. Jacob A, Lancaster J, Buhler J, Harris B, Chamberlain RD. Mercury BLASTP: accelerating protein sequence alignment. ACM Trans Reconfigurable Technol Syst. 2008;1(2):9.

    Article  PubMed  PubMed Central  Google Scholar 

  85. Wang YC, Wang N, Xu HF, Jiang SH, Fang HC, Su MY, et al. Auxin regulates anthocyanin biosynthesis through the aux/IAA-ARF signaling pathway in apple. Hortic Res. 2018;5:59.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  86. Kim D, Paggi JM, Park C, Bennett C, Salzberg SL. Graph-based genome alignment and genotyping with HISAT2 and HISAT-genotype. Nat Biotechnol. 2019;37(8):907–15.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  87. Pertea M, Pertea GM, Antonescu CM, Chang TC, Mendell JT, Salzberg SL. StringTie enables improved reconstruction of a transcriptome from RNA-seq reads. Nat Biotechnol. 2015;33(3):290–5.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  88. Rupp O, Becker J, Brinkrolf K, Timmermann C, Borth N, Puhler A, et al. Construction of a public CHO cell line transcript database using versatile bioinformatics analysis pipelines. Plos One. 2014;9(1):e85568.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  89. Ly A, Marsman M, Wagenmakers EJ. Analytic posteriors for Pearson's correlation coefficient. Stat Neerl. 2018;72(1):4–13.

    Article  PubMed  Google Scholar 

  90. Ye J, Coulouris G, Zaretskaya I, Cutcutache I, Rozen S, Madden TL. Primer-BLAST: a tool to design target-specific primers for polymerase chain reaction. BMC Bioinform. 2012;13:134.

    Article  CAS  Google Scholar 

  91. IBM Corp. IBM SPSS statistics for windows, version 26.0. Armonk: IBM Corp; 2019.

    Google Scholar 

  92. Ranstam J. Multiple P-values and Bonferroni correction. Osteoarthr Cartil. 2016;24(5):763–4.

    Article  CAS  Google Scholar 

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Acknowledgements

The authors are grateful to Leling Xisen Potato Industry Co. Ltd. (Leling, Shandong, China) for providing the virus-free seedlings of ‘Red Rose-2’ and ‘Xisen-8’.

Funding

This work was supported by the National Natural Science Foundation for Young Scientists of China (31900450), Science and Technology Innovation Project of Higher Education of Shanxi Province (2019 L0388), and Science and Technology Innovation Fund of Shanxi Agricultural University (2018YJ28).

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XYJ, RMT conceived and designed the original research plans; RMT, HTD collected the samples; RMT, LHH and YRS determined the content of anthocyanin; RMT, HTD, XQL and QY analyzed the data and performed the bioinformatics analysis; HTD and PL performed qRT-PCR analysis; XYJ and RMT wrote the manuscript; XQL, QY and RMT revised the manuscript. All authors have read and approved the manuscript.

Corresponding authors

Correspondence to Xiaoyun Jia or Xiu-Qing Li.

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Supplementary Information

Additional file 1 Table S1.

The information of profile HMMs of F-box and Kelch domains in Pfam database. Table S2. The sequences and positions information of F-box domains in 44 StKFB members. Table S3. The sequences and positions information of Kelch motifs in 44 StKFB members. Table S4. The 20 conserved motifs in StKFB proteins identified by MEME software and motifs annotation analysis by InterProScan. Table S5. The orthologous KFB genes identified by comparison between potato and other plants. Table S6. Expression profiles of 44 StKFB genes in different potato tissues, in potato plants with different treatments and in tubers with different colors. The FPKM values of 44 StKFB genes in different potato tissues and in potato plants with different treatments were extracted from RNA-Seq Gene Expression Data: DM_RH_RNA-Seq_FPKM_expression_matrix_for_DM_v4.03_13dec2013_desc.xlsx, the excel file of FPKM values of all the representative transcripts across 40 DM and 16 RH libraries (http://spuddb.uga.edu/pgsc_download.shtml); the FPKM values in tubers with different colors was extracted from RNA-seq data in our lab deposited in the NCBI Sequence Read Archive under the Bioproject accession PRJNA729884. Table S7. Quality of transcriptome sequencing of potato tuber with three colors. Raw reads: Number of reads in raw data; Clean reads: Number of reads filtered from raw data; Raw bases: The number of bases in the raw data; Clean bases: The number of bases filtered from the raw data; Error rate: Error rate of data sequencing; Q20: Percentage of bases with a Phred value greater than 20; Q30: Percentage of bases with a Phred value greater than 30; GC content: The percentage of G and C in clean reads. Table S8. Sequence alignment results of reads mapped to the reference genome (DM v4.03/v4.04). Total reads: the number of clean reads used for mapping analysis; Total mapped: the number of reads that could be mapped to the reference genome; Multiple mapped: the number of reads mapped to multiple locations in the reference genome; Uniquely mapped: the number of reads mapped to single location in the reference genome; Read-1 and Read-2: the number of reads mapped to the reference genome in Read 1 and Read 2, respectively; Reads mapped to ‘+’ and Reads mapped to ‘-’: the number of reads mapped to the positive and negative strands of the reference genome, respectively; Non-splice reads: the number of reads with the entire segment mapped to exons; Splice reads: the number of segmented reads mapped on two different exons; Reads mapped in proper pairs:the number of reads paired mapped to the reference genome; Proper-paired reads map to different chrom: the number of paired reads mapped to different chromosomes in the reference genome. Table S9. All primers used in qRT-PCR. Table S10. The annotation of 44 StKFBs and their corresponding orthologous genes in Arabidopsis thaliana. The potato StKFB protein sequences were aligned with those of Arabidopsis thaliana using Blastp.

Additional file 2.

CDS and protein sequences of 44 StKFBs.

Additional file 3 Fig. S1.

Gene duplication analysis of potato genome. The local database of potato protein sequences was established by Makeblastdb program. And pairwise comparisons were made between potato protein sequences by Blastp with E-value ≤1e-10. The gene duplication analysis result was obtained by duplicate_gene_classifier program provided in MCScanX software. Singleton: single copy genes; Proximal: adjacent but discontinuous repetitive genes on the same chromosome; Tandem: tandem duplications; WGD or segmental: whole genome duplications or segmental duplications; Dispersed: dispersed genes. Fig. S2. Sequence logos of conserved motifs in StKFB proteins. The 20 conserved motifs of the putative StKFB proteins were identified by MEME software v5.3.0. Fig. S3. The correlation analysis between the expression patterns of StKFBs in diverse potato tissues (a), in potato plants with different treatments (b) and in three colored potato tubers (c). The correlation between the expression levels (FPKM values) of StKFBs was analyzed by Pearson’s correlation coefficient and plotted using the corrplot package v. 0.92 (https://cran.r-project.org/web/packages/corrplot/). Fig. S4. Dissociation curves of primers for qRT-PCR. Dissolution curves were obtained by heating the amplicon from 60 °C (5 s) to 95 °C (50 s) on CFX96 PCR System (Bio-Rad, USA). Fig. S5. Comparison of the expression levels of the 9 selected StKFB genes determined by qRT-PCR and transcriptome sequencing. The boxplots were plotted using tidyverse v. 1.3.1, cowplot v. 1.1.1, ggplot2 v. 3.3.5 and ggsci v. 2.9 packages in RStudio. Values are means ± SD of three replicates in each experiment. Bars with different lowercase letters represent significant difference at p < 0.05. Fig. S6. Conserved domain analysis of StKFB01, AtFKF1, OsFKF1 and StKFB27. The conserved domain analysis was conducted by Conserved Domain Search tool (https://www.ncbi.nlm.nih.gov/Structure/cdd/wrpsb.cgi) in NCBI.

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Tang, R., Dong, H., He, L. et al. Genome-wide identification, evolutionary and functional analyses of KFB family members in potato. BMC Plant Biol 22, 226 (2022). https://doi.org/10.1186/s12870-022-03611-y

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Keywords

  • Potato
  • KFB gene family
  • Synteny analysis
  • Expression pattern
  • Anthocyanin biosynthesis