Skip to main content

Genome-wide identification, evolution, and role of SPL gene family in beet (Beta vulgaris L.) under cold stress

Abstract

Background

SPL transcription factors play vital roles in regulating plant growth, development, and abiotic stress responses. Sugar beet (Beta vulgaris L.), one of the world’s main sugar-producing crops, is a major source of edible and industrial sugars for humans. Although the SPL gene family has been extensively identified in other species, no reports on the SPL gene family in sugar beet are available.

Results

Eight BvSPL genes were identified at the whole-genome level and were renamed based on their positions on the chromosome. The gene structure, SBP domain sequences, and phylogenetic relationship with Arabidopsis were analyzed for the sugar beet SPL gene family. The eight BvSPL genes were divided into six groups (II, IV, V, VI, VII, and VIII). Of the BvSPL genes, no tandem duplication events were found, but one pair of segmental duplications was present. Multiple cis-regulatory elements related to growth and development were identified in the 2000-bp region upstream of the BvSPL gene start codon (ATG). Using quantitative real-time polymerase chain reaction (qRT-PCR), the expression profiles of the eight BvSPL genes were examined under eight types of abiotic stress and during the maturation stage. BvSPL transcription factors played a vital role in abiotic stress, with BvSPL3 and BvSPL6 being particularly noteworthy.

Conclusion

Eight sugar beet SPL genes were identified at the whole-genome level. Phylogenetic trees, gene structures, gene duplication events, and expression profiles were investigated. The qRT-PCR analysis indicated that BvSPLs play a substantial role in the growth and development of sugar beet, potentially participating in the regulation of root expansion and sugar accumulation.

Peer Review reports

Background

Sugar beet (Beta vulgaris L., 2n = 18) is an economically important crop grown in temperate and cold temperate regions and is the raw material for approximately 30% of the world’s sugar [1]. Sugar beet is also an important raw material for bioethanol and animal feed worldwide [23]. According to previous research, sugar beet originated from a halophyte known as Beta maritima L [4].. Through artificial domestication and cultivation, sugar beet is mainly used for feed and food, and edible sugar beet is further divided into industrial and edible types [5,6,7,8,9]. Currently, sugar beet is widely grown in Europe and temperate regions, making it an important economic crop [1011].

Transcription factors play important role in biology [1213]. Currently, transcription factors such as bHLH [14], MYB [1516], HSP [17,18,19,20], and bZIP [2122] are widely found in plants and animals. They perform various functions during the growth and developmental stages of organisms to ensure normal growth and development. Therefore, systematic research on biological transcription factors is important. Squamosa Promoter-Binding Protein-Like (SPL) is a plant-specific transcription factor that regulates plant growth and development. The SPL gene was first discovered in 1996, and Klein et al. isolated it from the Antirrhinum majus inflorescence cDNA library. Because it can recognize and bind to the SQUAMOSA promoter, it was named SBP1 and SBP2 [23]. The SBP domain encoded by the SPL gene is highly conserved and contains approximately 76 amino acid residues [23,24,25]. The SBP domain is divided into three main parts: Zn-1 (Cys-Cys-Cys-His), Zn-2 (Cys-Cys-His-Cys), and a nuclear localization signal (NLS) located at the C-terminal [25,26,27]. According to the gene structure and phylogenetic tree, 16 Arabidopsis SPL family members were identified and divided into eight subgroups (I–VIII) [24, 28]. These Arabidopsis SPL family members have been shown to play important roles in the development of Arabidopsis stems, leaves, and flowers [2930]. To date, whole-genome identification and analysis of SPL transcription factors in many plants have been completed, including Arabidopsis [24, 28], rice [31, 32], millet [33], quinoa [34], corn [35], tomato [36], buckwheat [37], barley [38], and wheat [39].

SPL transcription factors play vital roles in plant growth and development. For instance, in Switchgrass, when PvSPL2 expression is suppressed, biomass yield can be enhanced, and the total soluble sugar content can be increased [40]. In Arabidopsis, under heat stress, SPL genes are downregulated by miR156 to counter the effects of high temperatures [41]. ZmSPL in maize regulates several aspects of maize morphology, such as plant height, tillering, and grains [42]. OsSPL3 in rice can regulate plant cold resistance [43], and OsSPL14 has been associated with tiller number, grain weight, and disease resistance in rice [44,45,46]. Many plant SPL genes have been discovered and identified, and the functions of some SPL genes have been studied. Sugar beet has substantial economic value; however, the SPL gene family in sugar beet has not yet been identified. Therefore, it is important to perform genome-wide mining and the systematic identification of SPL genes in sugar beet.

Therefore, building upon the sugar beet genome, we systematically excavated, identified, and researched BvSPL genes in sugar beet. In this study, we identified eight BvSPL genes and analyzed their chromosomal distribution, gene duplication events, cis-acting elements, gene structures, and conserved motifs. Moreover, we analyzed the evolutionary relationship between the SPL genes of Arabidopsis, rice, maize, buckwheat, sorghum, and tomato and BvSPL genes in sugar beet. Additionally, we investigated the expression of BvSPL genes under eight forms of non-biological stress in sugar beet seedlings and in different tissues of mature sugar beet, thereby providing a foundation for studying the biological functions of BvSPL genes in sugar beet. In summary, a systematic analysis of the sugar beet SPL gene family was conducted to identify that BvSPL genes have critical roles in the growth and developmental processes of sugar beet. This lays a foundation and provides a reference for future sugar beet research.

Results

Identification of sugar beet SPL genes

Based on the complete sugar beet genome, two BLAST methods were used to obtain the SPL genes. After eliminating duplicate genes, eight SPL genes were identified. Depending on the location of the eight SPL genes on the nine chromosomes, we named them BvSPL1BvSPL8. The biological characteristics of the eight BvSPLs were analyzed, including the length of the amino acid sequence, protein molecular weight, protein hydrophilicity, protein isoelectric point, and subcellular localization (Table S1). Subcellular localization prediction revealed that all eight BvSPL genes were located in the cell nucleus. The BvSPL protein with the most amino acids had 996 (BvSPL4), whereas that with the fewest amino acids had only 267 (BvSPL3). The isoelectric point ranged from 5.61 (BvSPL4) to 9.63 (BvSPL3), and the protein molecular weight ranged from 30.33 kDa (BvSPL3) to 110.70 kDa (BvSPL4). All BvSPL proteins were found to be hydrophilic.

Phylogenetic analysis, classification, and multiple sequence alignment of BvSPL genes

To study the evolutionary relationship between sugar beet SPL genes, a phylogenetic tree with a bootstrap value of 1000 was constructed using the neighbor-joining (NJ) method, which included eight sugar beet SPL proteins and 16 Arabidopsis thaliana SPL proteins (Table S2). Based on the AtSPL classification method [24, 28], the BvSPL gene family was divided into six subgroups (II, IV, V, VI, VII, and VIII; Fig. 1A). Compared to the AtSPL gene family, the BvSPL gene family lacked subgroups I and III. Of these subfamilies, subgroups II and VII each contained two BvSPL members, and subgroups IV, V, VI, and VIII each contained one BvSPL member. After aligning AtSPL and BvSPL genes according to their respective subgroups, and based on the characteristics of the SBP domain, the SBP domains of the BvSPL genes were obtained (Fig. 1B).

Fig. 1
figure 1

(A) Phylogenetic tree of the relationship between Beta vulgaris and Arabidopsis thaliana SPL proteins. Different block colors represent different subgroups, with green stars representing Arabidopsis thaliana and red triangles representing Beta vulgaris in the legend. (B) Multiple sequence alignment of the SBP domains of different subgroups of Beta vulgaris and Arabidopsis thaliana

The sequence of the SBP domain of the BvSPL gene was approximately 74 amino acids long, of which the CQQC, SCR, and RRR sequences in the SBP domain were highly conserved. All BvSPLs contained two zinc-finger structures (Zn-1 and Zn-2) and a bipartite nuclear localization signal (NLS) motif. However, the Zn-2 (Cys-Cys-His-Cys) sequence of BvSPL3 in subgroup VI had mutated and contained 15 more amino acids than the Zn-2 sequence of the AtSPL protein. Such mutations may cause changes in the zinc finger binding site, thereby affecting protein conformation and endowing the BvSPL3 gene with new functions. In the other subgroups, Zn-1, Zn-2, and NLS were highly conserved, and the phenomenon that occurred in BvSPL3 in subgroup VI was not observed.

Analysis of gene structure, motif composition, and cis-acting elements of the BvSPL gene family

Eight BvSPL genes were identified at the genome-wide level; a phylogenetic tree of the full-length sequences of eight BvSPL proteins was constructed; and gene structure, sequence composition, and cis-acting elements were analyzed (Fig. 2; Table S3). The intron–exon structures of the same subgroup were similar, but there were large differences between the subfamilies. For example, sub-group II (BvSPL1 and BvSPL4) all had ten exons, while sub-group VII (BvSPL5 and BvSPL7) all had three exons. The other four sub-groups (IV, V, VI, and VIII) had fewer exons, with an average of only 3.5 introns, which was close to sub-group VII. All BvSPL genes contained the SBP domain and subgroup II contained both the SBP and ANK domains (Fig. 2B).

Fig. 2
figure 2

Phylogenetic relationship, gene structure, motif distribution, and cis-acting elements of sugar beet SPL genes. Among them, the number marked on the Node represents the confidence level. (A) Phylogenetic tree of the sugar beet SPL family, each node has 1000 repetitions. (B) Schematic diagram of the gene structure of sugar beet SPL genes, including UTR (untranslated region), CDS (coding sequence), domains (SBP, ANK domains), and introns (Number indicates the phase of the corresponding intron.). Light green represents UTR, yellow represents CDS, pink represents the structural domain SBP, and dark green represents structural domain ANK. (C) Conserved amino acid motifs (motifs 1–10) in BvSPL proteins: the line represents the relative length of the protein. (D) Cis-acting elements in the 2000 bp promoter sequence upstream of the BvSPL genes; different color blocks represent different cis-acting elements

To explore the conserved motifs of the eight BvSPL proteins, we used the MEME website to analyze ten conservative motifs of the BvSPL family (Fig. 2C; Table S3). Motifs 1, 2, and 3 were found to exist in the entire BvSPL family, and they were arranged in a specific order of motifs 2, 1, and 3 on the BvSPL protein sequence. However, motifs 4, 5, 6, 7, 8, and 9 only existed in sub-group II, whereas motif 10 only existed in BvSPL5 of sub-groups II and VII.

A similar arrangement of motifs indicates relatively conserved protein structures. All BvSPL proteins had a specific arrangement of motifs 2, 1, and 3, indicating that the BvSPL family was relatively evolutionarily conserved. The arrangement of motifs also supported the reliability of subgrouping the BvSPL family.

To elucidate the function of BvSPL genes, the cis-acting elements in the 2 kb promoter region upstream of the BvSPL genes were investigated (Fig. 2D; Table S3). Of the cis-acting elements of BvSPL, elements related to light were the most abundant, and all BvSPL genes contained these elements. The following elements were related to plant hormones: MeJA (TGACG-motif, CGTCA-motif), abscisic acid (ABRE), salicylic acid (TCA-element), and gibberellin (P-box, GARE-motif). BvSPL genes also have cis-acting elements related to growth and development, such as cis-regulatory elements related to meristem expression and elements involved in defense and stress responses. BvSPL3 had cis-acting elements that responded to low temperatures and BvSPL3 also had high expression under low-temperature stress. These results indicate that the BvSPL gene family plays an important role in plant growth and development.

Chromosome distribution and gene replication of the BvSPL gene

We determined the physical location map of the eight BvSPL genes on the chromosome using the sugar beet genome (Fig. 3A). Eight BvSPL genes were unevenly distributed across the nine sugar beet linkage groups (LGs), and the entire BvSPL family was distributed on only four chromosomes (Chr3, Chr4, Chr5, and Chr6). Of them, Chr6 had the highest number of BvSPL genes (four; ~50%). The least abundant was on Chr4 and Chr5, both of which contained only one BvSPL gene (~ 12.5%). The remaining two BvSPL genes were found on Chr3 (~ 25%). When one or more identical gene regions appear within 200 kb of a chromosome, it is referred to as a tandem duplication event. However, no tandem duplication events were not observed in the BvSPL family. A segmental duplication event was observed in the BvSPL gene family (Fig. 3B; Table S4). This segmental duplication event occurred on Chr6, and the genes involved in the segmental duplication were all members of subfamily VII (BvSPL5 and BvSPL7), which also supports the subgroup grouping of the BvSPL family. Gene duplication events play an indispensable role in the generation of new functions and in gene amplification. The BvSPL gene family does not have tandem duplication events; however, there is a pair of segmental duplication events. Therefore, we believe that tandem duplication events have not played a role in the expansion of the BvSPL family, while segmental duplication has played a certain role in the expansion of the BvSPL family.

Fig. 3
figure 3

(A) Distribution of the eight BvSPL genes in beet chromosomes, with gene density on chromosomes (Bin size = 100,000). (B) Chromosome distribution and gene duplication relationship of sugar beet SPL genes. The colored lines represent gene pairs between different chromosomes: the red line represents the BvSPL gene pair; from the inside out, the first and second outer circles are chromosome density (Bin size = 100,000), the third is the chromosome; the chromosome color is consistent with the gene pair line color on the chromosome

Evolutionary analysis of BvSPL and SPL genes in different species

To study the evolutionary relationships of the SPL family among different species, a collinearity map (Fig. 4A; Table S5) and a phylogenetic tree (Fig. 4B; Table S6) of BvSPL with six species (three dicotyledons: Arabidopsis thaliana, Solanum lycopersicum, and Fagopyrum tataricum, and three monocotyledons: Oryza sativa, Zea mays, and Sorghum bicolor) were constructed. Of the homologous genes of BvSPL and SPL in the six species (Fig. 4A; Table S5), the homologous pair numbers were A. thaliana (seven pairs), S. lycopersicum (six pairs), F. tataricum (five pairs), O. sativa (four pairs), Z. mays (zero pairs), and S. bicolor (zero pairs). Compared with monocotyledons, BvSPL genes have more homologous genes than dicotyledonous plants. This suggests that the BvSPL genes may have originated from the ancestors of dicotyledonous plants after the differentiation of monocotyledons and dicotyledons. The BvSPL3 gene has homologous genes with the three dicotyledonous plants, but not with monocotyledonous plants, indicating that the BvSPL3 gene may have formed after the differentiation of monocotyledons and dicotyledons.

Fig. 4
figure 4

(A) Collinearity analysis of beet with six plants (Arabidopsis thaliana, Solanum lycopersicum, Fagopyrum tataricum, Oryza sativa, Zea mays, and Sorghum bicolor). Red lines represent the species’ beet SPL genes and gene pairs, and gray represents collinear blocks in the beet and the species’ genomes. (B) The phylogenetic tree and motif composition of the SPL proteins of beet and six plants (Arabidopsis thaliana, Solanum lycopersicum, Fagopyrum tataricum, Oryza sativa, Zea mays, and Sorghum bicolor). Different module colors represent different motifs. The numbers on the evolutionary tree represent confidence levels. Red fonts represent BvSPL

We constructed a phylogenetic tree of BvSPL proteins and proteins from six other species, and used the MEME website to analyze the protein-conserved motifs of the seven species (Table S6). In the analysis of protein-conserved motifs, motifs 1, 2, 4, and 6 were found in almost all SPL proteins. This suggests that the plant SPL family may have existed before the differentiation of monocotyledons and dicotyledons. Although they evolved in different directions after the differentiation of monocotyledons and dicotyledons, they remained relatively conserved as a whole. From the phylogenetic tree, although BvSPL had only five pairs of homologous genes with Tartary buckwheat SPL, we found that BvSPL was mainly aggregated with Tartary buckwheat SPL genes. Therefore, we inferred that the BvSPL gene family was closer to the F. tataricum SPL gene family.

Expression patterns of the BvSPL gene under different abiotic stresses

To elucidate the physiological functions of BvSPL genes under abiotic stress, qRT-PCR was used to detect gene expression in the roots, stems, and leaves of beet seedlings under eight types of abiotic stresses (PEG, flooding, darkness, salt, acid, alkali, cold, and heat). We found that some genes exhibited marked expression or suppression under abiotic stress and many genes showed related expression under certain types of abiotic stress (Fig. 5A, Fig. S1). For instance, BvSPL6 was substantially upregulated in the roots under all stress conditions but was downregulated in the stems and leaves. In the roots, the upregulation of BvSPL6 was extremely high, with most of the differences being more than 20-fold. We also discovered that BvSPL3 responded to all types of stress and displayed an extremely high, short-term (2 h) response in leaves under cold stress (-4 ℃). Many genes were initially downregulated, followed by upregulation under abiotic stress. For example, under drought stress, the response of BvSPL2 in the roots, stems, and leaves initially decreased and then increased. Many genes were gradually up-regulated or down-regulated. Under salt (NaCl) stress, the expression of BvSPL5 in the roots, stems, and leaves gradually decreased. Under alkali stress (NaOH), the expression of BvSPL3 gradually increased under alkaline stress. Under heat stress (40 ℃), the expression of BvSPL genes changed markedly only after 24 h, and was mainly downregulated in roots, stems, and leaves. Therefore, we inferred that BvSPL genes are important for resistance to high temperatures.

Fig. 5
figure 5

(A) Relative expression levels and gene expression correlations of BvSPL genes in beet seedling roots, stems, and leaves at 0 h, 2 h, and 24 h under eight types of abiotic stress detected using quantitative real-time polymerase chain reaction (qRT-PCR). The lowercase letters above the bars indicate significant treatment differences (α = 0.05, LSD). The expression level of BvSPL gene was normalized to the expression level of BvACTIN, and its relative expression level was displayed at 0 h, 2 and 24 h. (B) Correlation of BvSPL gene expression under eight types of abiotic stress. The expression values of the color gradient mapping from low (blue) to high (red) on the right side of the figure. (C) Predicted protein–protein interaction network of beet BvSPL proteins within the beet. Orange represents BvSPL proteins; blue represents other proteins within the beet; the larger the circle, the more interacting proteins there are

Using gene heatmaps, the correlations between gene expressions were investigated. The correlation of BvSPL gene expression under different types of abiotic stress, and the correlation of gene expression under single stress (Fig. 5A, B, Fig. S1) were investigated. Under alkaline stress (NaOH), positive correlation areas (BvSPL2, BvSPL5, and BvSPL7; BvSPL1, BvSPL3, and BvSPL4) and negative correlation areas (BvSPL1 and BvSPL4 with BvSPL2; BvSPL5, BvSPL6, and BvSPL7). We also found positive and negative correlation areas for other types of stress.

We then analyzed the correlation between BvSPL gene expression and eight types of abiotic stresses (Fig. 5B). We found that only a few genes had strong correlations, such as BvSPL2, BvSPL7, and BvSPL8. However, most BvSPL genes had no strong positive or negative correlations; therefore, we speculated that the correlation of expression among BvSPL genes was low.

We predicted the interactions among the eight BvSPL proteins using the STRING online website to speculate on possible protein–protein interactions (Fig. 5C). We found no direct protein–protein interactions among the BvSPL family members, and BvSPL5 did not interact with proteins within the beet. However, BvSPL2, BvSPL7, and BvSPL8 interacted with beet proteins XP_010673830.1, XP_010692327.1, and XP_010693088.1. Therefore, we speculated that BvSPL2, BvSPL7, and BvSPL8 might regulate each other’s expression through three proteins, XP_010673830.1, XP_010692327.1, and XP_010693088.1, as intermediary bridges. This may also be true for BvSPL1 and BvSPL4. This aligns with the gene expression correlation shown in Fig. 5B.

Expression pattern of BvSPL gene in sugar beet maturation

Beetroots have substantial economic value; therefore, we tested the expression of BvSPL genes in the roots, stems, and leaves of mature beet (Fig. 6A, Fig. S1). We found that BvSPL3 and BvSPL6 were highly expressed in the roots, and BvSPL3 was highly expressed in the leaves. However, the expression of BvSPL7 was significantly down-regulated in both stems and leaves. The expression of BvSPL5 was down-regulated in roots and BvSPL8 in stems. All these suggest that the sugar beet SPL family plays an important role in the maturation of sugar beet.

Fig. 6
figure 6

(A) The expression patterns of eight SPL genes in mature sugar beet roots, stems, and leaves were detected using quantitative real-time polymerase chain reaction (qRT-PCR) technology. The lowercase letters above the bars indicate significant differences between treatments (α = 0.05, LSD). The expression level of BvSPL gene was normalized to the expression level of BvACTIN, and its relative expression level was displayed at 0 h, 2 and 24 h. (B) Correlation analysis of the expression of BvSPL genes in mature beet. The expression values of the color gradient mapping from low (blue) to high (red) on the right side of the figure

In the correlation analysis (Fig. 6B), clear positive and negative areas of correlation were found. There were seven genes in the positively correlated area and one gene (BvSPL5) in the negatively correlated area. We found that BvSPL5 was negatively correlated with seven other genes except for BvSPL2. BvSPL3, BvSPL6, and BvSPL7 had a correlation of unity and were all expressed at much higher levels in beetroots than in stems and leaves. However, BvSPL3 was highly expressed in both roots and leaves, whereas BvSPL6 and BvSPL7 were extremely low in stems and leaves, but higher in roots. Therefore, we believe that there is a coupling phenomenon in the correlation between BvSPL3, BvSPL6 and BvSPL7.

Discussion

Evolution of SPL gene family in sugar beet

SPL transcription factors in plants are involved in important physiological processes such as plant growth, metabolism, gibberellin signal transduction, and leaf formation [47]. In the present study, the beet SPL transcription factor family was systematically analyzed and the functions of eight BvSPL genes were explored. Analysis of the physicochemical properties of the eight BvSPL genes revealed that the physicochemical properties of BvSPL3 differed substantially from those of the other seven BvSPL genes. This indicates that the grand average hydrophobicity of the BvSPL3 protein was − 1.24, which was the lowest in the beet SPL family. For the Instability Index, the BvSPL3 protein (49.05) was also the lowest. The molecular weight (~ 30.3 kDa) and length (267) of BvSPL3 were the lowest, whereas its isoelectric point (9.63) was the highest. In the entire beet SPL family, BvSPL3 is closer to BvSPL1 and BvSPL4, which are more closely related in terms of evolution; however, its physicochemical information is opposite to that of BvSPL1 and BvSPL4. In the expansion and contraction of beet SPL gene family members, tandem duplication did not play a role in the amplification of the BvSPL family, whereas segment duplication played a role. In the multi-sequence alignment, the Zn-2 region of the BvSPL3 gene has 15 more amino acids than the other BvSPL genes. In the evolutionary analysis of the SPL transcription factor family of dicotyledonous plants, it was found that the BvSPL3 gene had genes homologous to three dicotyledonous plant SPL genes, indicating that the BvSPL3 gene may be a relatively primitive gene. However, the BvSPL3 gene may be a special SPL gene that has evolved in beet to adapt to survival and has undergone gene sequence changes. Therefore, we speculate that the BvSPL3 gene plays an extremely important role in the growth and development of beet and may be related to the swelling of beetroot.

In the evolution of the sugar beet SPL transcription factor family, three monocotyledonous plants (O. sativa [3132], Z. mays [35], and S. bicolor [35]) and three dicotyledonous plants (A. thaliana [24,25,26,27,28], S. lycopersicum [36], and F. titanium [37]) were selected for a comparative analysis of the SPL transcription factor families (Fig. 4). Phylogenetically, sugar beet SPL members clustered more with buckwheat and tomatoes, a finding that is consistent with that of Dohm et al. [1].. In the analysis of the conserved sequences of sugar beet SPL and those of the six species, most SPL proteins shared highly similar conserved sequences, including sequences 1, 2, 4, and 6. In the collinearity analysis, sugar beet SPL genes had more homologous genes with dicotyledons. BvSPL3 and BvSPL8 had homologous genes in the three dicotyledons but not in monocotyledons. This suggests that these three genes may be unique genes that evolved in dicotyledons after the differentiation of monocots and dicots.

Research has suggested that introns can produce different exon combinations through selective splicing during protein translation, thus translating different proteins and increasing their complexity [48, 49]. Furthermore, introns have been found to function independently of their coding genes. For example, introns can regulate cell starvation resistance through the TORC1 and PKA nutrient-sensing pathways [50]. Analysis of the beet SPL transcription factor family revealed that subfamily II had far more introns than the other subfamilies. Most researchers believe that in the ancient ancestors of organisms, there were a large number of introns, but with the evolution of organisms, a large number of introns were lost, which is the early intron hypothesis [51,52,53,54]. Therefore, we speculate that SPL subfamily II is older than the other subfamilies.

Response of beet SPL gene to abiotic stress and its spatiotemporal expression in different tissues

In organisms, gene expression is often a prerequisite for gene function, and gene expression patterns are usually related to gene function [55]. The SPL gene is widely involved in plant growth and development and plays a vital role in promoting the transition of plants from the seedling stage to the mature stage [56, 57]. For example, in A. thaliana, AtSPL3, AtSPL4, and AtSPL5 genes are involved in morphogenesis [30]. We examined the gene expression of all members of the beet SPL family under eight abiotic stress conditions (Fig. 5, Fig. S1). The results showed high expression or repression of BvSPL genes in abiotic stress, such as BvSPL1, BvSPL3, BvSPL5, and BvSPL6. In abiotic stress, there was a phenomenon where the gene expression of BvSPL genes first increased and then decreased, or decreased and then increased. For instance, under alkaline stress (0.2 mol/L NaOH), BvSPL2 showed a decrease in expression, followed by an increase in expression across the roots, stems, and leaves, similar to BvSPL5 in the stems and leaves. Under drought stress (PEG6000), BvSPL4, BvSPL7, and BvSPL8 showed an increase, followed by a decrease in the roots and stems. Similar phenomena were observed under other stress conditions. This suggests that these genes may be fast-responding and capable of helping beet resist damage caused by adverse conditions in the short term. Similar phenomena have been observed in other species [33, 58].

Sugar beet can withstand a variety of abiotic stresses, such as salinity, drought, cold, and heat [59,60,61,62,63,64]. Therefore, we speculate that the SPL gene family plays an important role in abiotic stress resistance in sugar beet. BvSPL3 and BvSPL6 may play strong roles in helping sugar beet resist abiotic stress. Under eight types of stress conditions, the BvSPL6 gene was highly expressed in the roots, whereas its expression was suppressed in the stems and leaves. This indicates that the BvSPL6 gene might be a key gene in sugar beet for controlling plant stress resistance, with sugar beet resisting abiotic stress either directly through the expression of BvSPL6 or by regulating the expression of other genes through BvSPL6. Whether BvSPL6 assists sugar beet in resisting abiotic stress through direct expression or acts as a messenger to help sugar beet resist abiotic stress by indirectly regulating other genes, BvSPL6 is a key gene in sugar beet resisting abiotic stress and is worth investigating.

BvSPL3 exhibited extremely high gene expression in leaves under cold stress. Cold temperatures are critical factors limiting the economic yield of sugar beet, particularly long-term cold temperatures during the seedling growth phase, which can ultimately lead to slow root growth and reduced sugar output [64, 65]. Cold temperatures can also lead to a decrease in photosynthetic efficiency, CO2 assimilation rate, and leaf transpiration rate in sugar beet seedlings, thereby affecting sugar beet growth and development [66, 67]. Therefore, we hypothesized that BvSPL3 may help sugar beet alleviate these situations. Under heat stress, most sugar beet SPL genes show gene expression suppression in sugar beet roots, stems, and leaves, indicating that the sugar beet SPL family is of significant importance to the heat tolerance of sugar beet.

In this study, we examined the expression levels of BvSPL genes in mature sugar beet (Fig. 5, Fig. S1). BvSPL3 and BvSPL6 were highly expressed in the roots, with BvSPL3 showing a differential expression up to 90 times. The sugar beetroot is where sugar accumulates and is also the most important economic value of sugar beet. In sugar beet, BvCPD was found to promote the development of thin-walled cells and vascular bundles of the main root of sugar beet, thereby affecting the growth and development of the main root of sugar beet, ultimately affecting the size of the main root of sugar beet [68]. The protein encoded by BvTST2.1 in sugar beet is a sucrose-specific transport protein, which is responsible for the absorption of sucrose in the vacuoles of the main root of sugar beet. Its expression promotes sucrose accumulation in sugar beet roots [69]. The high expression of BvSPL3 and BvSPL6 in the main roots of mature sugar beet suggests that they may influence the size of the main root and sugar accumulation. In conclusion, BvSPL3 and BvSPL6 warrant further investigation.

Conclusion

This is the first study to analyze the SPL gene family in sugar beet on a whole-genome scale. Based on the whole genome, eight members of the sugar beet SPL gene family were identified and the gene structure, conservative motifs, subfamily grouping, evolutionary relationships, abiotic stress, and spatio-temporal expression patterns of the eight BvSPL genes were analyzed, thereby inferring their possible biological functions. In evolution, fragment duplication of the sugar beet SPL family has played a certain role in the expansion of the sugar beet SPL family. The BvSPL6 gene was highly expressed in roots under eight abiotic stresses, and also in roots at maturity. BvSPL3 may also have important biological functions in sugar beet resistance to cold stress. In the mature period, BvSPL3 may play a certain role in sugar beet enlargement or sugar accumulation.

Materials and methods

Sugar beet material and abiotic stress

The B. vulgaris variety (2n = 18) MA097 (Denmark Mairuibo International Seed Industry Co., Ltd., The Harbin Representative Office, Harbin, China) used in this experiment was provided by Professor Ruan Jingjun. Plant materials were grown in an artificial climate room at the College of Agriculture, Guizhou University. After waiting for the sugar beet to mature, samples of the root, stem, and leaves from beet with good growth status and similar morphology (five replicates) were taken and immediately stored at -80 °C. When sugar beet seedlings grown in the same artificial climate room reached 21 d, they were subjected to abiotic stress (acid: 0.2 mol/L HCl, alkali: 0.2 mol/L NaOH, salt: 5% NaCl, drought: 30% PEG6000, flooding: submerging the entire plant, darkness: complete darkness, heat: 40 °C, cold: 4 °C). For the acid, alkali, salt, and drought treatments, the roots were submerged in solutions of the same volume. After 0 h, 2 h, and 24 h of treatment, samples of the root, stem, and leaves (five replicates) were taken and immediately stored at -80 °C.

Whole genome identification of sugar beet BvSPL genes

The sugar beet genome was downloaded from the genome website (https://plants.ensembl.org/data/ftp/index.html) and gene and amino acid sequences were extracted. SPL gene information was obtained from Arabidopsis (https://www.Arabidopsis.org/) and rice (http://Rice) and potential sugar beet SPL proteins from Arabidopsis and rice SPL amino acid sequences were identified using BLASTp (score ≥ 100, e value ≤ 1e − 10).

Next, we obtained a Hidden Markov Model (HMM) consistent with the SPL structural domain (PF03110) from the Pfam protein family database (htxxp://pfam.sanger.ac.uk/) and used HMMER3.3.2 software (default parameters) (htxxp://HMMER.org/) to search for SPL proteins. All possible BvSPL genes used were SMART (htxxp://smart.embl-heidelberg.de/) and CD-Search (https://www.ncbi.nlm.nih.gov/Structure/cdd/cdd.shtml) was used to confirm the structural domains of all possible BvSPL proteins to finally obtain the BvSPL genes.

The protein-coding sequence length, molecular weight (MW), isoelectric point (pI), subcellular localization, grand average hydrophobicity, and instability index (II) of the BvSPL genes were determined. Subcellular localization was obtained from the WoLF PSORT website (htxxps://psort.hgc.jp/), MW and PI were obtained from the ExPASy website (htxxp://web.expasy.org/protparam/), and the Grand Average of Hydropathicity and Instability Index (II) was obtained using TBtools software (htxxps://github.com/CJ-Chen/TBtools).

RNA extraction, cDNA reverse transcription, and qRT-PCR analysis of total material

RNA was extracted using a plant RNA extraction kit (Takara Biomedical Technology Co., Ltd., Beijing, China). The concentration and purity of total RNA were measured using a spectrophotometer and reverse transcribed into cDNA using the Hiscript II Q RT Supermix for qPCR kit (Vazyme Biotech Co, Ltd., Nanjing, China). The qRT-PCR primers were designed using Primer Premier 5.0. The internal reference gene was BvACTIN [7071]. The qRT-PCR was performed using SYBR Premix Ex Taq II (Takara Biomedical Technology Co., Ltd., Beijing, China) and repeated at least three times. The relative gene expression was calculated using the 2−(ΔΔCt) method.

BvSPL gene structure, cis-acting elements, conserved motifs, and protein interactions

The TBtools software was used to align BvSPL genes with sugar beet genes and to construct a BvSPL gene map. The PlantCare website (http://bioinformatics.psb.ugent.be/webtools/plantcare/html/) was used to predict the possible cis-acting elements (upstream of 2000 bp) in the promoter of the BvSPL gene family. The MEME website (htxxps://meme-suite.org/meme/tools/MEME) was used to analyze the ten most conserved motifs in the full-length protein sequence of the BvSPL family. MEGA11 software was used to align the SPL protein structural domains based on different subgroups of sugar beet and Arabidopsis using the default ClustalW parameters. The STRING website (htxxps://cn.string-db.org/) was used to predict potential protein interactions within the sugar beet BvSPL family, and the results were visualized using the Cytoscape software.

Chromosomal distribution and gene duplication of BvSPL genes

The physical location information of BvSPL genes and the gene density information of the chromosomes were extracted from the sugar beet genome and plotted. The MCScan X package was used to analyze gene duplication events of the BvSPL genes (default parameters), and TBtools software (https://github.com/CJ-Chen/TBtools) was used for homology analysis and plotting.

Statistical analysis

JMP software (version 6.0) was used for the analysis of variance (ANOVA) and conducted Least Significant Difference (LSD) comparisons at a significance level of 0.05 (p < 0.05). Origin software was used to plot the histograms of gene expression levels.

Data availability

The entire Beta vulgaris genome sequence information was obtained from the Ensembl Genomes website (http://ensemblgenomes.org/). B. vulgaris variety (2n = 18) MA097 used in the experiment was supplied by Prof. Jingjun Ruan of Guizhou University. The datasets supporting the conclusions of this study are included in the article and its additional files.

Abbreviations

qRT-PCR:

Quantitative real-time polymerase chain reaction

SPL:

Squamosa Promoter-Binding Protein-Like

NLS:

Nuclear localization signal

PEG:

Polyethylene glycol

TORC:

Transducer complexes of activity-regulated

PKA:

Protein kinase

HMM:

Hidden Markov Model

MW:

Molecular weight

pI:

Isoelectric point

ANOVA:

Analysis of variance

LSD:

Least Significant Difference

References

  1. Dohm JC, Minoche AE, Holtgräwe D, Capella-Gutiérrez S, Zakrzewski F, Tafer H, Rupp O, Sörensen TR, Stracke R, Reinhardt R, et al. The genome of the recently domesticated crop plant sugar beet (Beta vulgaris). Nature. 2014;505(7484):546–9. https://doi.org/10.1038/nature12817.

    Article  CAS  PubMed  Google Scholar 

  2. Haankuku C, Epplin FM, Kakani VG. Industrial sugar beets to biofuel: field to fuel production system and cost estimates. Biomass & Bioenergy. 2015;80(SEP):267–77. https://doi.org/10.1016/j.biombioe.2015.05.027.

    Article  Google Scholar 

  3. Simona C, BÂRSAN, Ancuţa Maria IVAN, Luca LC, Luca E. Sugar beet (beta vulgaris L.) yields and potential for bioethanol production under irrigation regime. Notulae Botanicae Horti Agrobotanici Cluj-Napoca. 2015;43(2):455–61. https://doi.org/10.15835/nbha43210131.

    Article  Google Scholar 

  4. Biancardi E, Panella LW, Lewellen RT. Beta maritima, the origin of beets. Ann Bot. 2011. https://doi.org/10.1007/978-1-4614-0842-0.

    Article  Google Scholar 

  5. Lange W. Taxonomy and cultonomy of beet (Beta vulgaris L). Bot J Linn Soc. 1999;130(1):81–96. https://doi.org/10.1006/bojl.1998.0250.

    Article  Google Scholar 

  6. Lee JH, Son CW, Kim MY, Kim MH, Kim HR, Kwak ES, Kim S, Kim MR. Red beet (Beta vulgaris L.) leaf supplementation improves antioxidant status in C57BL/6J mice fed high fat high cholesterol diet. Nutr Res Pract. 2009;3(2):114–21. https://doi.org/10.4162/nrp.2009.3.2.114.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Zhang Y, Nan J, Yu B. OMICS Technologies and Applications in Sugar Beet. Front Plant Sci. 2016;7:900. https://doi.org/10.3389/fpls.2016.00900.

    Article  PubMed  PubMed Central  Google Scholar 

  8. Hussein HA, Mekki BB, El-Sadek MEA, El Lateef EE. Effect of L-Ornithine application on improving drought tolerance in sugar beet plants. Heliyon. 2019;5(10):e02631. https://doi.org/10.1016/j.heliyon.2019.e02631.

    Article  PubMed  PubMed Central  Google Scholar 

  9. Magaña C, Núñez-Sánchez N, Fernández-Cabanás VM, García P, Serrano A, Pérez-Marín D, Pemán JM, Alcalde E. Direct prediction of bioethanol yield in sugar beet pulp using near infrared spectroscopy. Bioresour Technol. 2011;102(20):9542–9. https://doi.org/10.1016/j.biortech.2011.07.045.

    Article  CAS  PubMed  Google Scholar 

  10. Kumar S, Brooks SL. Use of red beet (beta vulgaris l.) for antimicrobial applications—a critical review. Food & Bioprocess Technology. 2017;11:17–42. https://doi.org/10.1007/s11947-017-1942-z.

    Article  CAS  Google Scholar 

  11. Ribeiro IC, Pinheiro C, Ribeiro CM, Veloso MM, Simoes-Costa MC, Evaristo I, Paulo OS, Ricardo CP. Genetic Diversity and Physiological Performance of Portuguese wild beet (Beta vulgaris spp. maritima) from three contrasting habitats. Front Plant Sci. 2016;7:1293. https://doi.org/10.3389/fpls.2016.01293.

    Article  PubMed  PubMed Central  Google Scholar 

  12. Hrmova M, Hussain SS. Plant Transcription Factors Involved in Drought and Associated stresses. Int J Mol Sci. 2021;22(11):5662. https://doi.org/10.3390/ijms22115662.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Diacou R, Nandigrami P, Fiser A, Liu W, Ashery-Padan R, Cvekl A. Cell fate decisions, transcription factors and signaling during early retinal development. Prog Retin Eye Res. 2022;91:101093. https://doi.org/10.1016/j.preteyeres.2022.101093.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Zeng Z, Wang Y, Johnson NAN, Wang GD, Yao Q, Chen KP. Identification and phylogenetic analysis of Basic Helix-Loop-Helix genes in the Diamondback Moth. J Insect Sci (Online). 2018;18(3):17. https://doi.org/10.1093/jisesa/iey057.

    Article  CAS  Google Scholar 

  15. Davidson CJ, Guthrie EE, Lipsick JS. Duplication and maintenance of the myb genes of vertebrate animals. Biology open. 2013;2(2):101–10. https://doi.org/10.1242/bio.20123152.

    Article  CAS  PubMed  Google Scholar 

  16. Sabir IA, Manzoor MA, Shah IH, Liu X, Zahid MS, Jiu S, Wang J, Abdullah, Zhang C. MYB transcription factor family in sweet cherry (Prunus avium L.): genome-wide investigation, evolution, structure, characterization and expression patterns. BMC Plant Biol. 2022;22(1):2. https://doi.org/10.1186/s12870-021-03374-y.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Fang Y, Shimei Y, Xue L, Jiahai W, Li S. Bioinformatics Analysis of Hsp70s Gene Family in Lotus japonicus. J Mountain Agric Biol. 2020;39(05):1–8. https://doi.org/10.15958/j.cnki.sdnyswxb.2020.05.001.

    Article  Google Scholar 

  18. Si FL, Qiao L, He QY, Zhou Y, Yan ZT, Chen B. HSP superfamily of genes in the malaria vector Anopheles sinensis: diversity, phylogenetics and association with pyrethroid resistance. Malar J. 2019;18(1):132. https://doi.org/10.1186/s12936-019-2770-6.

    Article  PubMed  PubMed Central  Google Scholar 

  19. Hui Z, Li S, De-gang Z. Bioinformatics Analysis of HspQ Gene in Escherichia coli. J Mountain Agric Biol. 2018;37(05):57–61. https://doi.org/10.15958/j.cnki.sdnyswxb.2018.05.011.

    Article  Google Scholar 

  20. Chen J, Gao T, Wan S, Zhang Y, Yang J, Yu Y, Wang W. Genome-wide identification, classification and expression analysis of the HSP Gene Superfamily in Tea Plant (Camellia sinensis). Int J Mol Sci. 2018;19(9):2633. https://doi.org/10.3390/ijms19092633.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Aichmüller CF, Iskar M, Jones DTW, Korshunov A, Radlwimmer B, Kool M, Ernst A, Pfister SM, Lichter P, Zapatka M. Pilocytic astrocytoma demethylation and transcriptional landscapes link bZIP transcription factors to immune response. Neurooncology. 2020;22(9):1327–38. https://doi.org/10.1093/neuonc/noaa035.

    Article  CAS  Google Scholar 

  22. Liu M, Wen Y, Sun W, Ma Z, Huang L, Wu Q, Tang Z, Bu T, Li C, Chen H. Genome-wide identification, phylogeny, evolutionary expansion and expression analyses of bZIP transcription factor family in tartaty buckwheat. BMC Genomics. 2019;20(1):483. https://doi.org/10.1186/s12864-019-5882-z.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Klein J, Saedler H, Huijser P. A new family of DNA binding proteins includes putative transcriptional regulators of the Antirrhinum majus floral meristem identity gene SQUAMOSA. Mol Gen Genetics: MGG. 1996;250(1):7–16. https://doi.org/10.1007/BF02191820.

    Article  CAS  PubMed  Google Scholar 

  24. Cardon G, Höhmann S, Klein J, Nettesheim K, Saedler H, Huijser P. Molecular characterization of the Arabidopsis SBP-box genes. Gene. 1999;237(1):91–104. https://doi.org/10.1016/s0378-1119(99)00308-x.

    Article  CAS  PubMed  Google Scholar 

  25. Birkenbihl RP, Jach G, Saedler H, Huijser P. Functional dissection of the plant-specific SBP-domain: overlap of the DNA-binding and nuclear localization domains. J Mol Biol. 2005;352(3):585–96. https://doi.org/10.1016/j.jmb.2005.07.013.

    Article  CAS  PubMed  Google Scholar 

  26. Yamasaki K, Kigawa T, Inoue M, Tateno M, Yamasaki T, Yabuki T, Aoki M, Seki E, Matsuda T, Nunokawa E, et al. A novel zinc-binding motif revealed by solution structures of DNA-binding domains of Arabidopsis SBP-family transcription factors. J Mol Biol. 2004;337(1):49–63. https://doi.org/10.1016/j.jmb.2004.01.015.

    Article  CAS  PubMed  Google Scholar 

  27. Yamasaki K, Kigawa T, Inoue M, Yamasaki T, Yabuki T, Aoki M, Seki E, Matsuda T, Tomo Y, Terada T, et al. An Arabidopsis SBP-domain fragment with a disrupted C-terminal zinc-binding site retains its tertiary structure. FEBS Lett. 2006;580(8):2109–16. https://doi.org/10.1016/j.febslet.2006.03.014.

    Article  CAS  PubMed  Google Scholar 

  28. Xu M, Hu T, Zhao J, Park MY, Earley KW, Wu G, Yang L, Poethig RS. Developmental functions of miR156-Regulated SQUAMOSA promoter binding protein-like (SPL) genes in Arabidopsis thaliana. PLoS Genet. 2016;12(8):e1006263. https://doi.org/10.1371/journal.pgen.1006263.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Usami T, Horiguchi G, Yano S, Tsukaya H. The more and smaller cell mutants of Arabidopsis thaliana identify novel roles for SQUAMOSA promoter binding protein-like genes in the control of heteroblasty. Development. 2009;136(6):955–64. https://doi.org/10.1242/dev.028613.

    Article  CAS  PubMed  Google Scholar 

  30. Wu G, Poethig RS. Temporal regulation of shoot development in Arabidopsis thaliana by miR156 and its target SPL3. Development. 2006;133(18):3539–47. https://doi.org/10.1242/dev.02521.

    Article  CAS  PubMed  Google Scholar 

  31. Yang Z, Wang X, Gu S, Hu Z, Xu H, Xu C. Comparative study of SBP-box gene family in Arabidopsis and rice. Gene. 2008;407(1–2):1–11. https://doi.org/10.1016/j.gene.2007.02.034.

    Article  CAS  PubMed  Google Scholar 

  32. Zhong H, Kong W, Gong Z, Fang X, Deng X, Liu C, Li Y. Evolutionary analyses reveal diverged patterns of SQUAMOSA promoter binding protein-like (SPL) Gene Family in Oryza Genus. Front Plant Sci. 2019;10:565. https://doi.org/10.3389/fpls.2019.00565.

    Article  PubMed  PubMed Central  Google Scholar 

  33. Lai D, Fan Y, Xue G, He A, Yang H, He C, Li Y, Ruan J, Yan J, Cheng J. Genome-wide identification and characterization of the SPL gene family and its expression in the various developmental stages and stress conditions in foxtail millet (Setaria italica). BMC Genomics. 2022;23(1):389. https://doi.org/10.1186/s12864-022-08633-2.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Ren Y, Ma R, Fan Y, Zhao B, Cheng P, Fan Y, Wang B. Genome-wide identification and expression analysis of the SPL transcription factor family and its response to abiotic stress in Quinoa (Chenopodium quinoa). BMC Genomics. 2022;23(1):773. https://doi.org/10.1186/s12864-022-08977-9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Peng X, Wang Q, Zhao Y, Li X, Ma Q. Comparative genome analysis of the SPL gene family reveals novel evolutionary features in maize. Genet Mol Biology. 2019;42(2):380–94. https://doi.org/10.1590/1678-4685-GMB-2017-0144.

    Article  CAS  Google Scholar 

  36. Salinas M, Xing S, Höhmann S, Berndtgen R, Huijser P. Genomic organization, phylogenetic comparison and differential expression of the SBP-box family of transcription factors in tomato. Planta. 2012;235(6):1171–84. https://doi.org/10.1007/s00425-011-1565-y.

    Article  CAS  PubMed  Google Scholar 

  37. Liu M, Sun W, Ma Z, Huang L, Wu Q, Tang Z, Bu T, Li C, Chen H. Genome-wide identification of the SPL gene family in Tartary Buckwheat (Fagopyrum tataricum) and expression analysis during fruit development stages. BMC Plant Biol. 2019;19(1):299. https://doi.org/10.1186/s12870-019-1916-6.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Tripathi RK, Bregitzer P, Singh J. Genome-wide analysis of the SPL/miR156 module and its interaction with the AP2/miR172 unit in barley. Sci Rep. 2018;8(1):7085. https://doi.org/10.1038/s41598-018-25349-0.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Zhu T, Liu Y, Ma L, Wang X, Zhang D, Han Y, Ding Q, Ma L. Genome-wide identification, phylogeny and expression analysis of the SPL gene family in wheat. BMC Plant Biol. 2020;20(1):420. https://doi.org/10.1186/s12870-020-02576-0.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Wu Z, Cao Y, Yang R, Qi T, Hang Y, Lin H, Zhou G, Wang ZY, Fu C. Switchgrass SBP-box transcription factors PvSPL1 and 2 function redundantly to initiate side tillers and affect biomass yield of energy crop. Biotechnol Biofuels. 2016;9:101. https://doi.org/10.1186/s13068-016-0516-z.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Stief A, Altmann S, Hoffmann K, Pant BD, Scheible WR, Bäurle I. Arabidopsis miR156 regulates tolerance to Recurring Environmental Stress through SPL transcription factors. Plant Cell. 2014;26(4):1792–807. https://doi.org/10.1105/tpc.114.123851.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Wei H, Zhao Y, Xie Y, Wang H. Exploiting SPL genes to improve maize plant architecture tailored for high-density planting. J Exp Bot. 2018;69(20):4675–88. https://doi.org/10.1093/jxb/ery258.

    Article  CAS  PubMed  Google Scholar 

  43. Zhou M, Tang W. MicroRNA156 amplifies transcription factor-associated cold stress tolerance in plant cells. Mol Genet Genomics: MGG. 2019;294(2):379–93. https://doi.org/10.1007/s00438-018-1516-4.

    Article  CAS  PubMed  Google Scholar 

  44. Wang L, Zhang Q. Boosting Rice yield by fine-tuning SPL gene expression. Trends Plant Sci. 2017;22(8):643–6. https://doi.org/10.1016/j.tplants.2017.06.004.

    Article  CAS  PubMed  Google Scholar 

  45. Jiao Y, Wang Y, Xue D, Wang J, Yan M, Liu G, Dong G, Zeng D, Lu Z, Zhu X, et al. Regulation of OsSPL14 by OsmiR156 defines ideal plant architecture in rice. Nat Genet. 2010;42(6):541–4. https://doi.org/10.1038/ng.591.

    Article  CAS  PubMed  Google Scholar 

  46. Lu Z, Yu H, Xiong G, Wang J, Jiao Y, Liu G, Jing Y, Meng X, Hu X, Qian Q, et al. Genome-wide binding analysis of the transcription activator ideal plant architecture1 reveals a complex network regulating rice plant architecture. Plant Cell. 2013;25(10):3743–59. https://doi.org/10.1105/tpc.113.113639.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Chen X, Zhang Z, Liu D, Zhang K, Li A, Mao L. SQUAMOSA promoter-binding protein-like transcription factors: star players for plant growth and development. J Integr Plant Biol. 2010;52(11):946–51. https://doi.org/10.1111/j.1744-7909.2010.00987.x.

    Article  CAS  PubMed  Google Scholar 

  48. Kriventseva EV, Koch I, Apweiler R, Vingron M, Bork P, Gelfand MS, Sunyaev S. Increase of functional diversity by alternative splicing. Trends Genet. 2003;19(3):124–8. https://doi.org/10.1016/S0168-9525(03)00023-4.

    Article  CAS  PubMed  Google Scholar 

  49. Stetefeld J, Ruegg MA. Structural and functional diversity generated by alternative mRNA splicing. Trends Biochem Sci. 2005;30(9):515–21. https://doi.org/10.1016/j.tibs.2005.07.001.

    Article  CAS  PubMed  Google Scholar 

  50. Parenteau J, Maignon L, Berthoumieux M, Catala M, Gagnon V, Abou Elela S. Introns are mediators of cell response to starvation. Nature. 2019;565(7741):612–7. https://doi.org/10.1038/s41586-018-0859-7.

    Article  CAS  PubMed  Google Scholar 

  51. Shabalina SA, Ogurtsov AY, Spiridonov AN, Novichkov PS, Spiridonov NA, Koonin EV. Distinct patterns of expression and evolution of intronless and intron-containing mammalian genes. Mol Biol Evol. 2010;27(8):1745–9. https://doi.org/10.1093/molbev/msq086.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Roy SW, Gilbert W. The evolution of spliceosomal introns: patterns, puzzles and progress. Nat Rev Genet. 2006;7(3):211–21. https://doi.org/10.1038/nrg1807.

    Article  CAS  PubMed  Google Scholar 

  53. Chorev M, Carmel L. The function of introns. Front Genet. 2012;3:55. https://doi.org/10.3389/fgene.2012.00055.

    Article  PubMed  PubMed Central  Google Scholar 

  54. Jo BS, Choi SS, Introns. The functional benefits of introns in genomes. Genomics & Informatics. 2015;13(4):112–8. https://doi.org/10.5808/GI.2015.13.4.112.

    Article  Google Scholar 

  55. Zhou Q, Zhang S, Chen F, Liu B, Wu L, Li F, Zhang J, Bao M, Liu G. Genome-wide identification and characterization of the SBP-box gene family in Petunia. BMC Genomics. 2018;19(1):193. https://doi.org/10.1186/s12864-018-4537-9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. Wang JW. Regulation of flowering time by the miR156-mediated age pathway. J Exp Bot. 2014;65(17):4723–30. https://doi.org/10.1093/jxb/eru246.

    Article  CAS  PubMed  Google Scholar 

  57. Bäurle I, Dean C. The timing of developmental transitions in plants. Cell. 2006;125(4):655–64. https://doi.org/10.1016/j.cell.2006.05.005.

    Article  CAS  PubMed  Google Scholar 

  58. Fan Y, Yang H, Lai D, He A, Xue G, Feng L, Chen L, Cheng XB, Ruan J, Yan J, et al. Genome-wide identification and expression analysis of the bHLH transcription factor family and its response to abiotic stress in sorghum [Sorghum bicolor (L.) Moench]. BMC Genomics. 2021;22(1):415. https://doi.org/10.1186/s12864-021-07652-9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  59. Skorupa M, Gołębiewski M, Kurnik K, Niedojadło J, Kęsy J, Klamkowski K, Wójcik K, Treder W, Tretyn A, Tyburski J. Salt stress vs. salt shock - the case of sugar beet and its halophytic ancestor. BMC Plant Biol. 2019;19(1):57. https://doi.org/10.1186/s12870-019-1661-x.

    Article  PubMed  PubMed Central  Google Scholar 

  60. Rozema J, Cornelisse D, Zhang Y, Li H, Bruning B, Katschnig D, Broekman R, Ji B, van Bodegom P. Comparing salt tolerance of beet cultivars and their halophytic ancestor: consequences of domestication and breeding programmes. AoB PLANTS. 2014;7:plu083. https://doi.org/10.1093/aobpla/plu083.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  61. Wiśniewska A, Andryka-Dudek P, Czerwiński M, Chołuj D. Fodder beet is a reservoir of drought tolerance alleles for sugar beet breeding. Plant Physiol Biochemistry: PPB. 2019;145:120–31. https://doi.org/10.1016/j.plaphy.2019.10.031.

    Article  CAS  Google Scholar 

  62. Stagnari F, Galieni A, Speca S, Pisante M. Water stress effects on growth, yield and quality traits of red beet[J]. Sci Hort. 2014;165:13–22. https://doi.org/10.1016/j.scienta.2013.10.026.

    Article  CAS  Google Scholar 

  63. Subbarao GV, Wheeler RM, Levine LH, Stutte GW. Glycine betaine accumulation, ionic and water relations of red-beet at contrasting levels of sodium supply. J Plant Physiol. 2001;158(6):767–76. https://doi.org/10.1078/0176-1617-00309.

    Article  CAS  PubMed  Google Scholar 

  64. Yolcu S, Alavilli H, Ganesh P, Asif M, Kumar M, Song K. An insight into the Abiotic stress responses of cultivated beets (Beta vulgaris L). Plants (Basel Switzerland). 2021;11(1):12. https://doi.org/10.3390/plants11010012.

    Article  CAS  PubMed  Google Scholar 

  65. Moliterni VM, Paris R, Onofri C, Orrù L, Cattivelli L, Pacifico D, Avanzato C, Ferrarini A, Delledonne M, Mandolino G. Early transcriptional changes in Beta vulgaris in response to low temperature. Planta. 2015;242(1):187–201. https://doi.org/10.1007/s00425-015-2299-z.

    Article  CAS  PubMed  Google Scholar 

  66. Keller I, Müdsam C, Rodrigues CM, Kischka D, Zierer W, Sonnewald U, Harms K, Czarnecki O, Fiedler-Wiechers K, Koch W, et al. Cold-Triggered induction of ROS- and raffinose metabolism in freezing-sensitive taproot tissue of Sugar Beet. Front Plant Sci. 2021;12:715767. https://doi.org/10.3389/fpls.2021.715767.

    Article  PubMed  PubMed Central  Google Scholar 

  67. Rodrigues CM, Müdsam C, Keller I, Zierer W, Czarnecki O, Corral JM, Reinhardt F, Nieberl P, Fiedler-Wiechers K, Sommer F, et al. Vernalization alters Sink and Source identities and reverses Phloem translocation from taproots to shoots in Sugar Beet. Plant Cell. 2020;32(10):3206–23. https://doi.org/10.1105/tpc.20.00072.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  68. Guo X, Li Y, Li N, Li G, Sun Y, Zhang S. BvCPD promotes parenchyma cell and vascular bundle development in sugar beet (Beta vulgaris L.) taproot. Front Plant Sci. 2023;14:1271329. https://doi.org/10.3389/fpls.2023.1271329.

    Article  PubMed  PubMed Central  Google Scholar 

  69. Jung B, Ludewig F, Schulz A, Meißner G, Wöstefeld N, Flügge UI, Pommerrenig B, Wirsching P, Sauer N, Koch W, et al. Identification of the transporter responsible for sucrose accumulation in sugar beet taproots. Nat Plants. 2015;1:14001. https://doi.org/10.1038/nplants.2014.1.

    Article  CAS  PubMed  Google Scholar 

  70. Wu GQ, Li ZQ, Cao H, Wang JL. Genome-wide identification and expression analysis of the WRKY genes in sugar beet (Beta vulgaris L.) under alkaline stress. PeerJ. 2019;7:e7817. https://doi.org/10.7717/peerj.7817.

    Article  PubMed  PubMed Central  Google Scholar 

  71. Wu GQ, Wang JL, Li SJ. Genome-wide identification of Na+/H + antiporter (NHX) genes in Sugar Beet (Beta vulgaris L.) and their regulated expression under salt stress. Genes. 2019;10(5):401. https://doi.org/10.3390/genes10050401.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

We thank all of the colleagues in our laboratory for providing useful discussions and technical assistance. We are very grateful to the editor and reviewers for critically evaluating the manuscript and providing constructive comments for its improvement.

Funding

This work was supported by the Key Laboratory of Molecular Breeding for Grain and Oil Crops in Guizhou Province (Qiankehezhongyindi (2023) 008), the Key Laboratory of Functional Agriculture of Guizhou Provincial Higher Education Institutions (Qianjiaoji (2023) 007) and the National Science Foundation of China (32161143005, 32160669, 32372051).

Author information

Authors and Affiliations

Authors

Contributions

G.X., W.W. (Weijiao Wu), and Y.F. conceived and designed the research. G.X., W.W. (Wenfeng Weng), X.Y., C.M., Q.B., and R.X. performed the experiments. G.X. and X.Y. performed the data analysis and wrote the manuscript. J.R. and J.C. supervised the research. J.R. revised the manuscript. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Jingjun Ruan.

Ethics declarations

Ethics approval and consent to participate

These plant materials are widely used all over the world and no permits are required for the collection of plant samples. The plant materials are maintained in accordance with the institutional guidelines of the College of Agriculture, Guizhou University, China. This article does not contain any studies with human participants or animals performed by the authors. These methods were carried out in accordance with relevant guidelines and regulations.

Consent for publication

Not Applicable.

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s Note

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

Electronic supplementary material

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Xue, G., Wu, W., Fan, Y. et al. Genome-wide identification, evolution, and role of SPL gene family in beet (Beta vulgaris L.) under cold stress. BMC Genomics 25, 101 (2024). https://doi.org/10.1186/s12864-024-09995-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s12864-024-09995-5

Keywords