Skip to main content
Download PDF

Transcriptomic analysis of tuberous root in two sweet potato varieties reveals the important genes and regulatory pathways in tuberous root development

BMC Genomics volume 23, Article number: 473 (2022) Cite this article

Abstract

Background

Tuberous root formation and development is a complex process in sweet potato, which is regulated by multiple genes and environmental factors. However, the regulatory mechanism of tuberous root development is unclear.

Results

In this study, the transcriptome of fibrous roots (R0) and tuberous roots in three developmental stages (Rl, R2, R3) were analyzed in two sweet potato varieties, GJS-8 and XGH. A total of 22,914 and 24,446 differentially expressed genes (DEGs) were identified in GJS-8 and XGH respectively, 15,920 differential genes were shared by GJS-8 and XGH. KEGG pathway enrichment analysis showed that the DEGs shared by GJS-8 and XGH were mainly involved in “plant hormone signal transduction” “starch and sucrose metabolism” and “MAPK signal transduction”. Trihelix transcription factor (Tai6.25300) was found to be closely related to tuberous root enlargement by the comprehensive analysis of these DEGs and weighted gene co-expression network analysis (WGCNA).

Conclusion

A hypothetical model of genetic regulatory network for tuberous root development of sweet potato is proposed, which emphasizes that some specific signal transduction pathways like “plant hormone signal transduction” “Ca2+signal” “MAPK signal transduction” and metabolic processes including “starch and sucrose metabolism” and “cell cycle and cell wall metabolism” are related to tuberous root development in sweet potato. These results provide new insights into the molecular mechanism of tuberous root development in sweet potato.

Peer Review reports

Introduction

Sweet potato (Ipomoea batatas L) is a dicotyledonous plant of the family Convolvulaceae, growing in tropical, subtropical, and temperate regions, it is the most important rhizome crop after potato and cassava, and one of the most important food crops in the world [1], with an annual global output of more than 100 million tons. China is the largest sweet potato producer in the world, accounting for 80–85% of the global output [1]. Sweet potato is nutritious and contains many ingredients for human health, which has the medicinal values such as anti-cancer, anti-diabetes and anti-inflammatory activity [2, 3], and has been selected as one of the test foods for long-term space travel [4]. The tuberous root of sweet potato is rich in starch and soluble sugar, and its biomass is the highest in all crops. Sweet potato is listed as the key raw material for ethanol production because of its high starch content [5]. How to improve the yield and quality of sweet potato has become a top priority.

Endogenous hormones play an important role in the process of tuberous root expansion. Cytokinin (CTK) and abscisic acid (ABA) are involved in the formation of stored roots [6,7,8,9,10,11], t-zeatin is thought to play an important role in the induction of tuberous roots by activating the primary cambium. ABA regulates the thickening of tuberous roots by activating the cell division of meristem. The content of Auxin (IAA) increased gradually at the initial stage of root expansion in sweet potato tuberous root, and began to decrease after the beginning of secondary growth, while the content of ABA and cytokinin was steadily increased [12, 13]. In tuberous root, the content of jasmonic acid (JA) was very high, while the contents in burdock root and fibrous root were less [14].

The growth and expansion of tuberous root in sweet potato are genetically regulated. Previous studies have shown that MADS-box, KNOX genes were highly expressed and related to the expansion of tuberous root in sweet potato [15,16,17]. The overexpression of SRD1 gene promoted the proliferation of cambium cells and xylem cells, and played a role in auxin-mediated initial root thickening [12]. SRF6 was the most abundantly expressed in tuberous root, and its mRNA was located around the primary cambium and meristem of the xylem, promoting the thickening of the tuberous root [18, 19]. Besides, an expansin coding gene IbEXP1 was found to play an inhibitory role in the proliferation of cambium cells and xylem cells, which in turn inhibited the initial expansion of tuberous root in sweet potato [19]. The tuberous root development of sweet potato is regulated by multiple genes. However, few genes related to tuberous root development have been identified, and no specific genes regulating tuberous root development of sweet potato have been found, so more researches are needed to reveal the molecular mechanism of tuberous root development of sweet potato.

With the rapid development of sequencing and molecular technology, the study on the molecular mechanism of underlying tuberous root expansion in sweet potato has made great progress. However, the development of tuberous root in sweet potato is a complex biological process, and its mechanism is not clear. Sweet potato is a heterohexaploid plant (2n = 6x = 90) with a genome of 4.4 GB [20]. There are some studies on the development mechanism of sweet potato tuberous root at the transcriptional level. It was found that some specific genes and proteins associated with starch and phytohormone synthesis as well as various transcription factors are involved in storage root formation and development [17, 21,22,23], but there are many genes should be found at transcriptional level. In the meanwhile, previous studies were based on a single variety, however, there are great genetic differences among varieties. It is difficult to explain the general mechanism and variety specificity from transcriptomic analysis using a single variety. In this study, two main sweet potato cultivars with similar developmental processes but having great genetic differences and usually planted in Guangxi Zhuang Autonomous Region of PR China, Xiguahong (XGH, orange flesh sweet potato) and Guijingshu 8 (GJS-8, purple flesh sweet potato), were used as plant materials. RNA sequencing and weighted gene co-expression network analysis (WGCNA) were performed to identify the key candidate genes mediating tuberous root development.

Results

Identification of differentially expressed genes between fibrous root and tuberous root

To explore the molecular mechanism of the formation and development of tuberous roots of sweet potato, 8 cDNA libraries were generated from the fibrous roots(R0) and the tuberous roots at different development stages (R1, R2, R3) in GJS-8 and XGH. Based on Illumina sequencing, a total of 1,514,457,568 original readings were obtained. After removing the connectors, unknown bases and low-quality reads, 1,486,623,198 clean readings were obtained, with an error rate of less than 0.03, Q20 > 97%, Q30 > 93%, which met the quality requirements of database construction. These clean readings were compared to the sweet potato genome using HISAT2 platform, and each library compared the number of reads on the genome to more than 69%. The number of reads aligned to the unique location of the reference genome was more than 63%, and the number of reads aligned to multiple locations of the reference genome was about 3.2–3.8% (Table 1). The sample correlation heat map showed that the R2 value among three biological repetitive samples was greater than 0.8, and that of most of samples was greater than 0.9, indicating that this experiment was highly repeatable and the data were reliable (Fig. 1).

Table 1 Quality statistics of original sequencing data and alignment analysis of filtered data with reference genome sequence
Full size table
Fig. 1
figure 1

Correlation analysis between sample replicates

Full size image

The expression levels of genes were measured and analyzed. Taking | log2 (FoldChange) | > 1 and padj < 0.05 as the standard, we identified 31,440 differentially expressed genes (DEGs) for the tuberous roots (R1, R2 and R3) vs. fibrous root in GJS-8 and XGH, of which 22,914 were in GJS-8, and 24,446 DEGs in XGH. GJS-8 and XGH shared 15,920 DEGs, of which 5133 DEGs in R1 stage, 5948 in R2 stage, and 11,607 in R3 stage (Fig. 2A). In addition, there were 2705 common genes involved in the whole tuberous root development process in GJS-8 and XGH (Fig. 2B).

Fig. 2
figure 2

The number of differentially expressed genes between tuberous root and fiber root at different stages of GJS-8 and XGH. a Statistics on the number of differential genes in different situations. b The number of differential genes between GJS-8 and XGH

Full size image

GO and KEGG enrichment analysis of DEGs

To further determine the main biological functions of all DEGs shared by GJS-8 and XGH in the process of tuberous root development, functional annotation was performed by mapping all common DEGs to gene ontology (GO) terms in the GO database. GO enrichment analysis was implemented using a Bonferroni-corrected p ≤ 0.05 as the threshold. Based on this criterion, 33 biological process terms, 3 cellular component terms and 36 molecular function terms were significantly enriched in R1 vs. R0 comparison. Among the DEGs between R1 vs. R0, the “cellular carbohydrate metabolic process” and “single-organism carbohydrate metabolic process” were the major terms of biological process, the “cell wall” and “external encapsulating structure” were the major terms of cellular component, and the “nucleic acid binding transcription factor activity” was the most represented molecular function term (Table S1). A total of 91 biological process terms, 7 cellular component terms and 49 molecular function terms were significantly enriched in R2 vs. R0 comparison. Among the DEGs between R2 vs. R0, the “response to stress” and “single-organism carbohydrate metabolic process” were the major terms of biological process, the “cell periphery”, “cell wall” and “external encapsulating structure” were the major terms of cellular component, and the “nucleic acid binding transcription factor activity” was the most represented molecular function term (Table S2). Moreover, 75 biological process terms, 6 cellular component terms, and 39 molecular function terms were significantly enriched in R3 vs. R0 comparisons. Among the DEGs between R3 vs. R0, the “ion transport” and “cell communication” were the major terms of biological process, “cell periphery” “cell wall” and “external encapsulating structure” were major terms of cellular component, and “nucleic acid binding transcription factor activity” was the most represented molecular function term (Table S3).

To further determine the metabolic or signal transduction pathways that common DEGs may participate in tuberous root development, pathway enrichment analysis was performed by using KEGG database. A total of 5133 (R1 vs. R0), 5948 (R2 vs. R0), and 11,607 (R3 vs. R0) DEGs were respectively assigned to 101, 105, and 110 pathways by KEGG pathway enrichment analysis. Nine pathways were identified as significantly enriched pathways in R1 vs. R0 and R2 vs. R0, respectively, and 13 were identified as significantly enriched pathways in R3 vs. R0 (Q ≤ 0.05) (Table 2; Fig. 3). The “Starch and sucrose metabolism (sot00500)” “MAPK signaling pathway - plant (sot04016)” “plant hormone signal transductiont (sot04075)” and “plant-pathogen interaction (sot04626)” were the major represented pathways among the DEGs of R1 vs. R0 and R2 vs. R0. Among the DEGs between R3 vs. R0, the “Starch and sucrose metabolism (sot00500)” “MAPK signaling pathway - plant (sot04016)” “Circadian rhythm - plant (sot04712)” and “Plant-pathogen interaction (sot04626)” were the major represented pathways. The results suggest that genes involved in regulation of plant hormone levels, metabolism and signal transduction played vital roles in tuberous root of sweet potato.

Table 2 KEGG enrichment analysis of common differential genes in different stages of GJS-8 and XGH
Full size table
Fig. 3
figure 3

KEGG enrichment analysis of DEGs shared by GJS-8 and XGH at R1, R2, R3 stages. a DEGs shared by GJS-8 and XGH at R1 stage; b DEGs shared by GJS-8 and XGH at R2 stage; c DEGs shared by GJS-8 and XGH at R3 stage

Full size image

Comprehensive analysis of differential expression of signal transduction pathway genes

The KEGG enrichment analysis of the DEGs shared by GJS-8 and XGH during tuberous root expansion showed that they were significantly enriched in many signal transduction pathways. Furthermore, these DEGs were annotated using NR, GO, and KEGG annotations, and a large number of DEGs were involved in signal transduction, cell wall, cell division, starch and sucrose metabolism pathways, indicating that signal transduction pathways played an important role in the process of sweet potato tuberous root expansion. Therefore, we analyzed the related genes of these pathways.

Hormone signal

In this study, a total of 58 genes related to biosynthesis, metabolism and signal transduction of various hormones were identified (Table S4). The auxin signal transduction pathway was the most active, followed by ethylene signal transduction pathway. The genes related to hormone signal transduction in two varieties at the same developmental stage were further analyzed. In the auxin pathway, 3 AUX/IAA (Tai6.27980, Tai6.39648, and Tai6.22518) and 1 CH3(Tai6.36369) were significantly up-regulated in R1 phase; 1 AUX1(Tai6.1708), 1 SAUR (Tai6.14155), 1 AUX/IAA (Tai6.27980), and 2 ARF (Tai6.44587, Tai6.23113) were significantly up-regulated in R3 phase. In the ethylene pathway, 1 ERF (Tai6.17891) was significantly up-regulated in R1 phase, 1 ETR (Tai6.12247), 1 SIMKK (Tai6.10820) and 1 ERF (Tai6.10820) were significantly up-regulated in R2 phase, 5 ethylene-related genes (ETR: Tai6.12247, SIMKK: Tai6.10820, EIN2: Tai6.36354, EBF: Tai6.54900, and EIN3: Tai6.48960) were significantly up-regulated in R3 phase. In cytokinin signal transduction pathway, 1 AHP (Tai6.10485) was significantly enhanced during tuberous root development. In the abscisic acid pathway, 1 PYR/RYL (Tai6.18308) was significantly up-regulated in R1and R3 phase, 1 ABF (Tai6.48900) was significantly up-regulated in R2 phase. In the gibberellin pathway, 1 TF (Tai6.39357) was significantly up-regulated in R2, R2 and R3 phase. In the brassinolide pathway, 2 CYCD3(Tai6.43006, Tai6.37902) were significantly up-regulated in R2 phase. In the salicylic acid pathway, 2 NPR1(Tai6.32738, Tai6.52704) were significantly up-regulated in R1 phase,1 NPR1(Tai6.52704) was significantly up-regulated in R1 phase.

MAPK, calcium and phospholipid signaling

Among the DEGs shared by XGH and GJS-8, 1 mitogen-activated protein kinases (MAPK) gene (Tai6.51134) was up-regulated in whole expansion stage, 1 MAPK (Tai6.44720) was up-regulated in R1 and R2 stages, 1 MAPK (Tai6.10820) was up-regulated in R2 and R3 stages, 4 MAPK (Tai6.53239, Tai6.7760, Tai6.9123, and Tai6.4327) were up-regulated in R3 stage, 10 MAPK genes were down-regulated during whole expansion stage, 10 MAPK genes were down-regulated in R2 and R3 stages (Table S5).

A total of 147 calcium signal related to genes, including 36 calcium-dependent protein kinases (CDPKs), 40 calcium-binding proteins (CBPs), 45 calmodulin/calmodulin-binding protein (CaM/CaM-binding), and 26 Calreticulin (CBL) were identified from the common DEGs of two varieties (Table S6). It is worth noting that most of genes were down-regulated in whole expansion stage.

A total of 22 phospholipid signal-related genes were identified from the common DEGs of two varieties (Table S7). Among them, 6 genes were significantly up-regulated in R1, R2 and R3 stages, 4 genes were significantly down-regulated in R1, R2 and R3 stages.

Light signal

Sixty-five photoperiod related genes were identified as DEGs shared by XGH and GJS-8 during tuberous root development (Table S8). These genes included 20 CONSTANS-likes (COL), 5 phototropins, 14 GATA transcription factors (GATA), 12 LOB domain-containing proteins (LOB), 6 COP-interactive proteins genes (COP) and 8 phytochromes. In R1 stage, 15 genes were significantly up-regulated, including 3 phototropins, 4 COLs, 1 LOB, 1 COP and 6 phytochromes. In R2 stage, 21 genes were significantly up-regulated, including 7 COLs, 1 phototropin, 1 GATA, 3 LOBs, 3 COPs and 6 phytochrome genes. In R3 stage, 24 genes, including 3 phototropins, 8 COLs, 1 GATA, 4 LOBs, 4 COPs and 6 phytochromes, were significantly up-regulated.

Cell wall and cell cycle

We identified 95 genes related to cell wall and cell cycle from the DEGs shared by GJS-8 and XGH (Table S9), including 29 xyloglucan endotransglucosylase/hydrolases (XTH), 22 expansins, 3 extensins, 8 cell division proteases (FtsZ), 6 cell division cycle 5-like proteins (CDC5), 9 cell division control proteins (CDC), 7 cyclin-dependent kinases (CDKs) and 11 cyclin-dependent kinase inhibitors (CDKIs). Among these genes, most of XTH and CDC genes were down-regulated, and most of the genes related to FtsZ, CDC5 and CDKIs were up-regulated.

Starch and sucrose metabolism

Seventy genes related to starch and sucrose metabolism were identified from the DEGs shared by GJS-8 and XGH (Table S10), including 13 sucrose synthases (SuSy), 2 sucrose phosphate synthases (SPS), 10 starch synthases (SS), 5 invertase genes (INV), 10 granule-bound starch synthases (GBSS), 4 soluble starch synthases (SSS), 11 starch branching enzymes (SBE), 5 Beta-amylases, 5 alpha-amylases, and 5 isoamylases. Most of the genes were significantly up-regulated during the root expansion stage in sweet potato, and only a few genes were down-regulated.

Transcription factor

In this study, 296 TF genes were identified as DEGs shared by GJS-8 and XGH. Among them, 126 TFs were up-regulated, and 170 TFs were down-regulated during the tuberous root development (Table S11). WRKYs, HBs, MYBs were the major represented TF families (Fig. 4). Twenty-nine transcription factors in these families were significantly up-regulated, and their expression levels increased successively in the R1, R2 and R3 stages of tuberous root development in two cultivars, it mainly included the family of HB, C2H2, MYB transcription factors (Fig. 5).

Fig. 4
figure 4

The number of transcription factors expressed significantly differentially in the R1, R2 and R3 stages of tuberous root expansion in GJS-8 and XGH

Full size image
Fig. 5
figure 5

Heat map of highly expressed transcription factors. Every row shows a different TF gene. Red, white, and blue indicate slow, middle and high levels of mRNA expression, respectively. (a) Expression of transcription factors in GJS-8; (b) Expression of transcription factors in XGH

Full size image

Weighted gene co-expression network analysis

To further understand the relationship between gene expression and tuberous root development, the weighted gene co-expression network analysis (WGCNA) was performed. In this study, β (soft-power threshold) = 9 was set to guarantee high scale independence and low mean connectivity (near 0) (Fig. 6A). The dissimilarity of the modules was set as 0.75, and a total of 14 modules were generated (Fig. 6B). The module trait relationship was shown in Fig. 6C. Green modules are highly related to tuberous root development (r > 0.80, p < 0.005). GO enrichment analysis was further carried out on the genes of green module (Table S12). The result showed that the biological processes were the most enriched in this module related to energy metabolism and transport. In addition, it was also significantly enriched in mRNA processing, hormone response, endogenous stimulus response and stress response. KEGG enrichment analysis showed that the green module was significantly enriched in transcription factors, plant circadian rhythm (sot04712), MAPK plant signal pathway (sot04016), and plant hormone signal transduction (sot04075) (Table S13).

Fig. 6
figure 6

Soft-thresholding values estimation and module identification. a Scale independence and mean connectivity of various soft-thresholding values (β). b Dendrogram of all filtered genes enriched according to a dissimilarity measure (1-TOM) and the cluster module colors. c Heatmap of the correlation between the root tuber expansion traits and MEs of bladder cancer. The darker the module color, the more significant their relationship

Full size image

The gene connectivity in the modules represents the regulatory relationship between the gene and other genes. The higher the connectivity, the greater the regulatory role of the gene in the modules, the more likely it was a hub gene. The gene with the highest connectivity in the green module was selected as the core gene of the module. This gene encoded a trihelix transcription factor (Tai6.25300). The homology of this gene in Arabidopsis is AT1G13450.1 (trihelix transcription factor: GT-1). A total of 1272 genes interacted with trihelix, including genes related to light signaling, calcium signaling, and plant hormone signaling, implying the processes the genes involved were potentially co-regulated. The interaction network of core genes was visualized by Cytoscape software. Because there were many genes interacting with hub genes, only partial genes were shown here (Fig. 7).

Fig. 7
figure 7

Trihelix transcription factor interactions based on co-expression pattern

Full size image

Genes with significant differences in tuberous root development between two varieties

Taking | log2 (FoldChange) | > 1 and padj < 0.05 as the standard, we identified 18,028 differentially expressed genes (DEGs) for the GJS_8 vs. XGH (R1, R2 and R3), of which 12,792 were in R1 stage, 9979 in R2 stage and 8828 DEGs in R3. KEGG enrichment analysis showed that the up-regulated genes were significantly enriched to phenylpropanoid biosynthesis (sot00940), flavonoid biosynthesis (sot00941), starch and sucrose metabolism (sot00500) and pentose and glucuronate interconversions pathway (sot00040) in stage R1. In stage R2, the up-regulated genes were significantly enriched to the flavonoid biosynthesis pathway (sot00941). In R3 stage, the up-regulated genes were not significantly enriched to any pathway. In addition, 88 MYB, 86 bHLH, 3 WD40 transcription factors, and 30 anthocyanin biosynthesis related genes [6 trans-cinnamate 4-monooxygenases (C4H), 12 4-coumarate--CoA ligases (4CL), 8 chalcone synthases (CHS), 2 chalcone-flavanone isomerases (CHIL), 2 leucoanthocyanidin dioxygenases (LDOX/ANS)] were identified from these DEGs (Table S14). The difference of these anthocyanin related genes was the greatest in the R1 stage of the two varieties, and the difference was more than 10 times.

Verification of gene expression patterns by qRT-PCR

In order to verify the accuracy of RNA-Seq results, we randomly selected 6 genes (Tai6.25300, Tai6.22648, Tai6.3107, Tai6.42353, Tai6.46822, and Tai6.24971) for qRT-PCR analysis. The results showed that the expression pattern of these 6 differential genes was similar to that of RNA-Seq (Fig. 8). The results indicated that the RNA-Seq was reliable.

Fig. 8
figure 8

qRT-PCR validation profiles of six randomly selected genes. The data was normalized by using UBI as an internal reference. The expression level of fibrous root(R0) in each cultivar was used as reference state, which was set to 1, and fold change values were shown here. (a) Trihelix transcription factor (Tai6.25300); (b) BEL (Tai6.22648); (c) CONSTANS-like (Tai6.3107); (d) BEL (Tai6.42353); (e) BEL (Tai6.46822); (f) auxin-responsive protein (Tai6.24971)

Full size image

Discussion

The formation and development of the tuberous root of sweet potato is a complex process, which mainly involves the formation of vascular cambium and secondary cambium. After the formation of round vascular cambium, the tuberous root begins to thicken, then the cells continue to proliferate and expand to form a secondary cambium, which is accompanied by the continuous accumulation of starch and other substances, resulting in the continuous enlargement of the tuberous root.

Previous studies showed that the meristems are always active during tuberous root bulking, the transcriptome data obtained in this study reveal that the regulators of meristem development, such as LBD4 (LOB domain-containing protein 4, Tai6.18322, and Tai6.27010), WOX4 (WUSCHEL HOMEOBOX RELATED 14, Tai6.17770, and Tai6.44989) were significantly upregulated at tuberous root development, which is consistent with the results of previous studies [23]. Moreover, the genes are involved in cell division, including cell division protein FtsZ (FtsZ), cell division cycle 5 (CDC5), cell division control protein (CDC), and cyclin-dependent kinase (CDK), their expression levels were significantly enhanced in the tuberous root expansion stage (Table S9). The Genes involved in cell extension and expansion, including extension, XET, and expansin, also were significantly enhanced in the tuberous root expansion stage (Table S9). These results indicate that the formation and development of tuberous roots are inseparable from the active meristems and cell division.

A series of studies have shown that the initiation and induction of root/tuber is affected by the environment. For potatoes, photoperiod is essential for tuber formation [24]. Moreover, light is also important for the expansion of Rehmannia glutinosa tuberous root [25]. Photoperiod response protein, lateral organ boundaries protein (LOB), and GATA transcription factor are important members of photoperiod regulation. In this study, the expression of LOB (Tai6.27900) and GATA (Tai6.27468) were significantly enhanced during the tuberous root expansion stage. Furthermore, genes related to light signal transduction including phototropin, CONSTANS, and COP-interactive proteins were also significantly enhanced during the tuberous root expansion stage (Table S8). However, their peaks and expression patterns were obviously different, suggesting that light regulation is very critical to tuberous root formation and continuous development.

Moreover, genes detected in the roots may also be transcribed in the leaves and then transported to the root. For example, after being transcribed in leaves, potato stBEL5 mRNA was transported through the phloem to the stolon tip for translation into protein, thereby promoting the formation of storage organs [26]. In this study, 14 BELs genes were consistently up-regulated during the tuberous root expansion stage (Table S8), which suggest that these genes may be functionally similar to the stBEL5. Although the storage organs of potato and sweet potato are different, they may have similar regulatory systems. Therefore, they may be involved in light signal-regulated tuberous root development via similar mechanisms.

The relationship between hormones and tuberous root swelling

Hormones are important signals in plant root development [27, 28]. In this study, the plant hormone signal transduction pathway was one of the most enriched KEGG pathways in tuberous root expansion stage. Auxin plays an important role in cambium cell proliferation and cell expansion [12], also maintains the meristem state of cambium cells and increase the number of xylem elements [29]. In the studies of radish, Rehmannia glutinosa and Callerya speciosa, the expressions of auxin-related genes were significantly up-regulated during tuberous root expansion stage [25, 30, 31]. In this study, 7 auxin-related genes (AUX / IAA, ARF, SAUR, and CH3) were up-regulated in tuberous root expansion stage, implying that they may relate to cell expansion in the secondary growth of cambium.

The results showed that cytokinin was involved in the proliferation and development of cambium cells, and the expression reached the highest level in the rapid growth stage of tuberous root, which was related to the development and formation of tuberous root / tuber [29, 32,33,34]. In this study, the expression of cytokinin related gene (Tai6.10485) was significantly up-regulated during tuberous root expansion, suggesting that cytokinin may promote root expansion by participating in the development of cambium.

Ethylene is a key regulator of rhizome induction and development [35], which promotes tuber formation by inhibiting GA biosynthesis [36]. Moreover, it has been shown that GA, auxin,and ethylene affect cell growth in the root by opposing the action of DELLA proteins. In this study, the expressions of ethylene-related genes were significantly up-regulated during tuberous root expansion (Table S4). Overall, these results suggest that these hormone signals related genes play vital roles during the tuberous root expansion stage.

Multiple signal pathways are activated to regulate tuberous root development

Cellular processes involved in a series of signaling pathways are usually triggered by specific stimuli and hormones. Phospholipid signal plays an important role in root growth, cell division, and hormone regulation [37, 38]. It was reported that the expression levels of phospholipid signal-related genes/proteins were increased in the early stage of tuberous root expansion in Rehmannia glutinosa. In addition, the phospholipid-calcium signal system regulated potato tuber formation [25, 39]. In this study, 6 phospholipid signal-related genes were up-regulated in the stage of tuberous root expansion in GJS-8 and XGH, and the expression profiles in two varieties were quite similar, indicating that phospholipid signal was involved in the initiation and of tuberous root expansion.

Calcium is one of the main nutrients and is involved in almost the whole process of plant growth, including the controls of cell division, differentiation, and stress response as the second messenger [40, 41]. Studies revealed that CDPK played a role in the signal pathway of root initiation in potato and cassava, and exogenous calcium levels could affect the quantity and weight of potato tuber [42,43,44]. In addition, Ca2+ concentration and calcium signal- related genes (CBP, CBL, CaM, and CDPK) were significantly up-regulated during tuberous root formation in Rehmannia Glutinosa [25]. In this study, there was an increase in the stage of tuberous root expansion in the expression level of calcium signaling-related genes, including 9 CDPKs, 8 CBLs, and 1 CaM (Table S6), which suggests that calcium signal is involved in the formation and expansion of tuberous root in sweet potato. In addition, some genes related to the MAPK signaling pathway were up-regulated during tuberous root expansion development (Table S5), suggesting that the MAPK signal participats in the initiation and expansion of tuberous root formation. It has been shown that the MAPK signal plays an important role in cell cycle regulation, hormone, and stress response  [45].

Transcription factor regulation and weighted gene co-expression network analysis

Transcription factors play an important role in the regulation of plant growth and development and secondary metabolism. Many transcription factors have been identified to play key roles in organ development, including MADS, bHLH, MYB, NAC, GRAS et al. In this study, we identified 29 transcription factors that were significantly up-regulated during the tuberous root expansion stage in two varieties. Their expression levels increased successively (Fig. 5). Among these TFs, MYBs and HBs were the main transcription factors with large up-regulation multiples. One trihelix transcription factor gene (Tai6.25300) was identified as a tuberous root expansion-related gene through WGCNA analysis, its homologous gene in Arabidopsis was AT1G13450.1(Trihelix, GT-1), which was considered to be a molecular switch responded to light signals through Ca2+-dependent phosphorylation/dephosphorylation [46]. The Trihelix factor is a plant-specific triple helix DNA binding transcription factor. Many studies have proved that the trihelix transcription factor was involved in plant light response [47, 48]. In this study, the expression of light signal related-genes was coordinated with Tai6.25300, and significantly up-regulated during tuberous root development. Moreover, qRT-PCR confirmed that the expression of Tai6.25300 was up-regulated and increased successively during tuberous root development in two varieties, suggesting that Tai6.23500 was closely related to tuberous root development. We infer that Tai6.25300 participates in tuberous root expansion by positively regulating light signal related genes.

MYBs were involved in cell cycle regulation, plant morphogenesis, cell wall synthesis, secondary metabolism, xylem/phloem differentiation, root radial pattern formation, and so on [49, 50]. Furthermore, previous studies have found that the transcriptional level of MYB was significantly up-regulated during rhizome development [30, 51], and MYBs were highly expressed at the rapid thickening stages of Callerya speciosa [36]. In this study, 32 MYB transcription factors were significantly differentially expressed as tuberous root development, of which 8 were significantly up-regulated. Homeodomain (Homebox, HB) transcription factors are very important regulatory proteins in plants, which are mainly divided into 14 categories, including KNOX, BEL, and HD-ZIP, etc. Arabidopsis HB transcription factors were involved in cell division, differentiation, replication, growth, and regulation of the early development of vascular tissue [52, 53], In addition, the members of HB family were also involved in the regulation of cambium cell differentiation to phloem and lignin biosynthesis [54, 55]. RNA-Seq data revealed that 3 homeobox genes were notably upregulated during the formation and thickening of storage roots [22]. In this study, 36 HB transcription factors were significantly differentially expressed in tuberous root development, of which 26 were significantly up-regulated.

To sum up, these results suggest that transcription factors may drive root/stem growth through cell cycle regulation, cell division, and secondary wall strength. The TFs revealed in this study may be the important candidate genes for breeding sweet potato with high production in the future.

Starch and sucrose metabolism regulation

Sucrose and starch accumulation occurs during the bulking of storage roots, they are considered to be one of the most important carbohydrates, and play an important role in the formation of storage organs. Sucrose invertase and sucrose synthase were involved in the introduction and accumulation of sucrose in storage roots [56]. In addition, sucrose synthase was related to the tuber /tuberous root growth of potato and radish and was a key enzyme in the early development of radish storage root [57,58,59,60]. In this study, 5 SuSy genes were significantly up-regulated during tuberous root development in GJS-8 and XGH, while 2 INV genes were significantly down-regulated (Table S10), Invertase was active in fibrous roots of sweet potato but rapidly decreased to an undetectable level during storage root development [61]. Furthermore, Jackson showed that high content of sucrose was required as a necessary condition during the formation of storage organs [62]. In the present study, SPS (Tai6.24187), the major source of sucrose synthesis activity [63], was up-regulated during tuberous roots expansion. This result was consistent with previous studies in radish that found up-regulation of SPS playing a major role in the thickening stage of radish taproot [64].

The accumulation of starch occurs at the same time as the expansion of storage organs. It has shown that the expansions of potato and lotus root tubers were highly coordinated with the accumulation of starch [65, 66]. The expansion of cassava root was synchronized with the accumulation of starch [67], and granule-bound starch synthase (GBSS) has been shown to affect starch synthesis in storage organs [68]. In this study, 22 starch-related genes (6 GBSSs, 4 SSSs, 8 SBEs, and 4 isoamylases) were significantly up-regulated during root tuber expansion (Table S10), which was similar to previous studies. SBE, GBSS, and SS-related genes were significantly up-regulated during root expansion of Panax notoginseng [69]. These starch and sucrose metabolism genes play important roles in tuberous root expansion.

Genes with significant differences in tuberous root development between two varieties

GJS_8 and XGH are two varieties with different anthocyanin content. GJS_8 has higher anthocyanin content than XGH. Anthocyanins are water-soluble pigments and an important class of flavonoids. We found that there was a large number of genes with significant differences in tuberous root development between two varieties. KEGG enrichment analysis showed that the DEGs were significantly enriched to phenylpropanoid biosynthesis (sot00940), flavonoid biosynthesis (sot00941), and starch and sucrose metabolism pathway (sot00500). It was also found that phenylpropanoid biosynthesis and flavonoid biosynthesis was significantly enriched in the process of anthocyanin biosynthesis [70]. In addition, we identified a large number of MYB, bHLH, WD40 transcription factors, and anthocyanin biosynthesis genes from these differential genes, including 6 MYBs,17 bHLHs, 3 C4Hs, 5 4CLs,6 CHSs, 2CHILs, and 2 LDOX/ANSs, which were significantly differentially expressed between GJS_8 and XGH and also significant differentially expressed between tuberous root and fiber root, especially in GJS_8 tuberous root. A large number of studies have shown that MYB, bHLH, and WD40 transcription factors were the regulators of flavonoid biosynthesis, and the results also showed that IbMYB1 controls the biosynthesis of anthocyanins in sweet potato [71]. It was found that 10 anthocyanin biosynthesis genes were significantly up-regulated during Aronia melanocarpa fruit development [72]. Hence, it shows that anthocyanin biosynthesis related-genes may be involved in the tuberous root development in sweet potato, and their regulatory mechanism should be studied in the next step.

Regulatory networks associated with tuberous root development

Tuberous root development is a complex regulatory process, which is affected by many factors. In this study, through transcriptome analysis, combined with previous research results, a hypothetical model of sweet potato tuberous root development regulatory network is proposed (Fig. 9). The cells in the vascular cambium divide and expand continuously to produce secondary xylem and secondary phloem, resulting in the expansion of tuberous root. Cell proliferation is regulated through several signal transduction pathways (light, Phospholipid, calcium, MAPK, hormone, and transcription signaling) and metabolism possesses (cell wall, sucrose, and starch metabolism). Several genes including photoperiod (LOB, GATA, Phototropin, COL, and COP), calcium signal (CDPK, CBL, and CaM), MAPK signal, auxin-related genes (Aux/IAA, CH3, ARF, and SAUR), HB transcription factors (BELL, KNOX, and HD-ZIP), are highly expressed to promote cell differentiation, division, expansion and sucrose and starch accumulation at the secondary structure. In addition, FtsZ, CDC, CDK, XTH, expansin, and extension, are involved in cell division extension and expansion. Finally, SuSy, SPS, SSS, GBSS, and SBE are involved in the hydrolysis of sucrose and the synthesis of starch. Further functional identification studies were needed to confirm the functions of these potential genes.

Fig. 9
figure 9

A hypothetical model of regulatory network related to tuberous root expansion in sweet potato

Full size image

Conclusion

Integrated transcriptomic and WGCNA analyses were performed in the study, there were 15,920 differential genes shared by XGH and GJS-8. GO and KEGG pathway enrichment analysis revealed that these DEGs were mainly involved in plant hormone signal transduction, starch and sucrose metabolism, MAPK signal transduction, light signal, phospholipid signal, calcium signal, transcription factor, cell wall, and cell cycle. Furthermore, WGCNA and qRT-PCR analysis suggested that Tai6.25300 played an important role in tuberous root development in sweet potato. A hypothetical model of a genetic regulatory network associated with tuberous roots in sweet potato is put forward. The tuberous root development of sweet potato is mainly attributed to cell differentiation, division, and expansion, which are regulated and promoted by certain specific signal transduction pathways and metabolism processes. These findings can not only provide novel insights into the molecular regulation mechanism of tuberous root expansion, but also support theoretical basis for genetic improvement of sweet potato.

Materials and methods

Materials

Two sweet potato varieties, GJS-8 and XGH were used in this study. They were planted in the experimental farm of Hepu Institute of Agricultural Science in Beihai, Guangxi. At 90 days after planting, Sample collection refers to Ku et al’s method [14], Fibrous roots (R0:RGJ8_0, RXGH_0; 1 mm diameter) and developing tuberous roots [(R1:RGJ8_1, RXGH_1; 1 cm diameter, less than 2 g), (R2:RGJ8_2, RXGH_2; 3 cm diameter, 5-10 g), (R3:RGJ8_3, RXGH_3; 5 cm diameter, approx 50 g)] were collected,respectively (Fig. 10). Three plants were selected randomly from every repetition each time. At least five roots were mixed as a biological biological repetition. For the big tuberous root samples, five fresh tuberous roots from a repetition were washed with distilled water, cut down into slices, and mixed as a biological repetition. Three biological replicates were performed. The samples were stored at − 80 °C for extracting total RNA.

Fig. 10
figure 10

Anatomical diagram with sampling diagram. a GJS_8; b XGH

Full size image

RNA extraction, cDNA library construction, and RNA-Seq

A conventional trizol method was used to extract RNA from the samples. The concentration and purity of total RNA were determined by a NanoPhotometer® spectrophotometer (IMPLEN, CA, USA). RNA integrity was assessed using the RNA Nano 6000 Assay Kit of the Bioanalyzer 2100 system (AgilentTechnologies, CA, USA). Sequencing libraries were generated using NEBNext®UltraTM RNA Library Prep Kit for Illumina® (NEB, USA).

RNA sequencing and data analysis

3 μg total RNA from each sample was used as the input material, fragmentation was carried out using divalent cations under elevated temperature in NEBNext First Strand Synthesis Reaction Buffer (5X). First strand cDNA was synthesized using random hexamer primer and M-MuLV Reverse Transcriptase (RNase H-). Second strand cDNA synthesis was subsequently performed using DNA Polymerase I and RNase H. Remaining overhangs were converted into blunt ends via exonuclease/polymerase activities. After adenylation of 3′ ends of DNA fragments, NEBNext Adaptor with hairpin loop structure were ligated to prepare for hybridization. In order to select cDNA fragments of preferentially 250 ~ 300 bp in length, the library fragments were purified with AMPure XP system (Beckman Coulter, Beverly, USA). Then 3 μl USER Enzyme (NEB, USA) was used with size-selected, adaptor-ligated cDNA at 37 °C for 15 min followed by 5 min at 95 °C before PCR. Then PCR was performed with Phusion High -Fidelity DNA polymerase, Universal PCR primers and Index (X) Primer. At last, PCR products were purified (AMPure XP system) and library quality was assessed on the Agilent Bioanalyzer 2100 system. Clean reads were obtained by removing reads containing an adapter, reads containing ploy-N and low-quality reads from the raw data. The clean reads were then aligned with the sweet potato genome (http://public-genomes-ngs.molgen.mpg.de/cgi-bin/hgGateway?hgsid=9052&clade=plant&org=Ipomoea+batatas&db=ipoBat4 ) [23]. Feature Counts v1.5.0-p3 was used to count the read numbers mapped to each gene, and the FPKM of each gene was then calculated based on the length of the gene and the read count mapped to the gene [23]. Genes with an adjusted P-value < 0.05 and | log2 (FoldChange) | > 1 obtained by DESeq2 were considered DEGs.

Functional annotation

Gene Ontology (GO) enrichment analysis of the DEGs was implemented using the cluster Profiler R package, and the gene length bias was corrected during this process [73]. KOBAS software was used to test the statistical enrichment of the DEGs in Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways [74]. To obtain more information about the DEGs, the DEGs were annotated using seven databases: NR (NCBI nonredundant pro-tein), NT (NCBI Nucleotide Sequences), Gene Ontology (GO), KO (KO, KEGG Orthology), KOG (Eukaryotic Or Thologous Groups), Pfam (Protein Family Database) and Swiss-Prot (a manually annotated and reviewed protein sequence database). All the DEGs were subjected to hierarchical clustering analysis using the average linkage method [75].

Weighted gene co-expression network analysis

The DEGs detected with DESeq2 were combined and the TPM values for the 24 samples were determined. Each TPM value was increased by 0.01 and further transformed by a log10 calculation. The converted data were analyzed with the R package WGCNA (version 1.66), with a power value of 9 [76, 77].

Validation of the DEGs data using qRT-PCR

Total RNAs were extracted from the tuberous samples (fibrous root, tuberous roots less than 2 g, tuberous roots 5-10 g, tuberous roots greater than 50 g) with Trizol® Reagent (Magen, China). and then reverse transcribed into cDNA with HiScript III SuperMix for qPCR(+gDNA wiper) (Vazyme, China). qRT-PCR was carried out using SYBR Premix Ex TaqII Kit (TaKaRa, Dalian, China) on a Bio-Rad iQ5 Real-time PCR System (Bio-Rad Laboratories, CA, USA), Ten μl reaction solution contained 5 μl SYBR Green I Master, 1 μl specific Primer, 1 μl cDNA samples, 3 μl RNase-Free H2O. One-third dilution of the cDNA sample was used, and the reaction conditions were: 30s at 95 °C followed by 40 cycles of 30s at 95 °C, and 30s at 60 °C. Each sample had three biological replicates with three technical replicates for each biological replicate. The relative expression level was calculated by the equation ratio 2-ΔΔCt. The primers of selected genes were designed using primer 5 software (Table S15), and UBI gene was used as the internal control.

Availability of data and materials

The materials of this study were provided by the College of Agriculture at Hepu Institute of Agricultural Science. Correspondence and requests for materials should be addressed to Longfei He (lfhe@gxu.edu.cn). The raw sequencing data have submitted to the NCBI SRA database (PRJNA678375).

Abbreviations

CTK:

Cytokinin

ABA:

Abscisic acid

IAA:

Auxin

GA:

Gibberellin

MAPK:

Mitogen-activated protein kinases

CDPK:

Calcium-dependent protein kinases

CBP:

Calcium-binding proteins

CaM/CaM-Binding:

Calmodulin/calmodulin-binding protein

CBL:

Calreticulin

COL:

CONSTANS-like

XTH:

Xyloglucan endotransglucosylase/hydrolases

FtsZ:

Cell division proteases

CDC5:

Cell division cycle 5-like proteins

CDC:

Cell division control proteins

CDK:

Cyclin-dependent kinasess

CDKI:

Cyclin-dependent kinase inhibitors

SuSy:

Sucrose synthases

SPS:

Sucrose phosphate synthases

INV:

Invertase genes

GBSS:

Granule- bound starch synthases

SSS:

Soluble starch synthases

SBE:

Starch branching enzymes

WGCNA:

Co-expression network analysis

References

  1. Marques JM, da Silva TF, Vollu RE, Blank AF, Ding GC, Seldin L, et al. Plant age and genotype affect the bacterial community composition in the tuber rhizosphere of field-grown sweet potato plants. FEMS Microbiol Ecol. 2014;88(2):424–35.

    Article  CAS  PubMed  Google Scholar 

  2. Kang L, Ji CY, Kim SH, Ke Q, Park SC, Kim HS, et al. Suppression of the β-carotene hydroxylase gene increases β-carotene content and tolerance to abiotic stress in transgenic sweetpotato plants. Plant Physiol Biochem. 2017;117:24–33.

    Article  CAS  PubMed  Google Scholar 

  3. Wang S, Nie S, Zhu F. Chemical constituents and health effects of sweet potato. Food Res Int. 2016;89(Pt 1):90–116.

    Article  CAS  PubMed  Google Scholar 

  4. Wilson CD, Pace RD, Bromfield E, Jones G, Lu JY. Sweet potato in a vegetarian menu plan for NASA's advanced life support program. Life Support Biosph Sci. 1998;5(3):347–51.

    CAS  PubMed  Google Scholar 

  5. Dai-Fu MA, Qiang L, Cao QH, Niu FX, Xie YP, Tang J. Development and prospect of sweetpotato industry and its technologies in China. Jiangsu Agric J. 2012;28(005):969–73.

    Google Scholar 

  6. Matsuo T, Yoneda T, Itoo S. Identification of free cytokinins and the changes in endogenous levels during tuber development of sweet potato (Ipomoea batatas lam.). Plant cell. Physiology. 1983;24(7):1305–1.

    CAS  Google Scholar 

  7. Matsuo T, Mitsuzono H, Okada R, Itoo S. Variations in the levels of major free cytokinins and free abscisic acid during tuber development of sweet potato. J Plant Growth Regul. 1988;7(4):249–58.

    Article  CAS  Google Scholar 

  8. Suye S, Sugiyama T, Hashizume T. Mass spectrometric determination of Ribosyl trans-Zeatin from sweet potato tubers (Ipomoea batatas L. cv. Kohkei no. 14). Agric Biol Chem. 1983;47:1665–6.

    CAS  Google Scholar 

  9. Sugiyama T, Hashizume T. Cytokinins in developing tuberous roots of sweet potato (Ipomoea batatas). Agric Biol Chem. 1989;53:49–52.

    CAS  Google Scholar 

  10. Nakatani M, Komeichi M. Changes in the endogenous level of zeatin riboside, abscisic acid and indole acetic acid during formation and thickening of tuberous roots in sweet potato. Japan J Crop Sci. 2008;60(1):91–100.

    Article  Google Scholar 

  11. Nakatani M, Komeichi M. Distribution of endogenous zeatin riboside and abscisic acid in tuberous roots of sweet potato. Japan J Crop Sci. 2008;60:322–3.

    Article  Google Scholar 

  12. Noh SA, Lee HS, Huh EJ, Huh GH, Paek KH, Shin JS, et al. SRD1 is involved in the auxin-mediated initial thickening growth of storage root by enhancing proliferation of metaxylem and cambium cells in sweetpotato (Ipomoea batatas). J Exp Bot. 2010;61(5):1337–49.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Wang QM, Zhang LM, Guan YA, Wang ZL. Endogenous hormone concentration in developing tuberous roots of different sweet potato genotypes. Agric Sci China. 2006;5(012):919–27.

    Article  CAS  Google Scholar 

  14. Ku AT, Huang YS, Wang YS, Ma D, Yeh KW. IbMADS1 (Ipomoea batatas MADS-box 1 gene) is involved in tuberous root initiation in sweet potato (Ipomoea batatas). Ann Bot. 2008;102(1):57–67.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Kim SH, Mizuno K, Fujimura T. Isolation of MADS-box genes from sweet potato (Ipomoea batatas (L.) lam.) expressed specifically in vegetative tissues. Plant cell. Physiology. 2002;43(3):314–22.

    CAS  Google Scholar 

  16. Tanaka M, Kato N, Nakayama H, Nakatani M, Takahata Y. Expression of class I knotted1-like homeobox genes in the storage roots of sweet potato (Ipomoea batatas). J Plant Physiol. 2008;165(16):1726–35.

    Article  CAS  PubMed  Google Scholar 

  17. Firon N, LaBonte D, Villordon A, Kfir Y, Solis J, Lapis E, et al. Transcriptional profiling of sweet potato (Ipomoea batatas) roots indicates down-regulation of lignin biosynthesis and up-regulation of starch biosynthesis at an early stage of storage root formation. BMC Genomics. 2013;14(1):460.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Tanaka M, Takahata Y, Nakatani M. Analysis of genes developmentally regulated during storage root formation of sweet potato. J Plant Physiol. 2005;162(1):91–102.

    Article  CAS  PubMed  Google Scholar 

  19. Noh SA, Lee HS, Kim YS, Paek KH, Shin JS, Bae JM. Down-regulation of the IbEXP1 gene enhanced storage root development in sweet potato. J Exp Bot. 2013;64(1):129–42.

    Article  CAS  PubMed  Google Scholar 

  20. Yang J, Moeinzadeh MH, Kuhl H, Helmuth J, Xiao P, Haas S, et al. Haplotype-resolved sweet potato genome traces back its hexaploidization history. Nature Plants. 2017;3(9):696–703.

    Article  CAS  PubMed  Google Scholar 

  21. Wang Z, Fang B, Chen J, Zhang X, Luo Z, Huang L, et al. De novo assembly and characterization of root transcriptome using Illumina paired-end sequencing and development of cSSR markers in sweet potato (Ipomoea batatas). BMC Genomics. 2010;11:726.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Wang Z, Fang B, Chen X, Liao M, Chen J, Zhang X, et al. Temporal patterns of gene expression associated with tuberous root formation and development in sweetpotato (Ipomoea batatas). BMC Plant Biol. 2015;15:180.

    Article  PubMed  PubMed Central  Google Scholar 

  23. Dong T, Zhu M, Yu J, Han R, Tang C, Xu T, et al. RNA-Seq and iTRAQ reveal multiple pathways involved in storage root formation and development in sweet potato (Ipomoea batatas L.). BMC Plant Biol. 2019;19(1):136.

    Article  PubMed  PubMed Central  Google Scholar 

  24. Kondhare KR, Malankar NN, Devani RS, Banerjee AK. Genome-wide transcriptome analysis reveals small RNA profiles involved in early stages of stolon-to-tuber transitions in potato under photoperiodic conditions. BMC Plant Biol. 2018;18(1):284.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Li M, Yang Y, Li X, Gu L, Wang F, Feng F, et al. Analysis of integrated multiple 'omics' datasets reveals the mechanisms of initiation and determination in the formation of tuberous roots in Rehmannia glutinosa. J Exp Bot. 2015;66(19):5837–51.

    Article  CAS  PubMed  Google Scholar 

  26. Chen H, Banerjee AK, Hannapel DJ. The tandem complex of BEL and KNOX partners is required for transcriptional repression of ga20ox1. Plant J. 2004;38(2):276–84.

    Article  CAS  PubMed  Google Scholar 

  27. Jung JK, McCouch S. Getting to the roots of it: genetic and hormonal control of root architecture. Front Plant Sci. 2013;4:186.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Ljung K. Auxin metabolism and homeostasis during plant development. Development. 2013;140(5):943–50.

    Article  CAS  PubMed  Google Scholar 

  29. Nieminen K, Immanen J, Laxell M, Kauppinen L, Tarkowski P, Dolezal K, et al. Cytokinin signaling regulates cambial development in poplar. Proc Natl Acad Sci U S A. 2008;105(50):20032–7.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Yu R, Wang J, Xu L, Wang Y, Wang R, Zhu X, et al. Transcriptome profiling of taproot reveals complex regulatory networks during taproot thickening in radish (Raphanus sativus L.). Front Plant Sci. 2016;7:1210.

    Article  PubMed  PubMed Central  Google Scholar 

  31. Yao S, Lan Z, Huang R, Tan Y, Huang D, Gu J, et al. Hormonal and transcriptional analyses provides new insights into the molecular mechanisms underlying root thickening and isoflavonoid biosynthesis in Callerya speciosa (champ. Ex Benth.) Schot. Sci Rep. 2021;11(1):9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Hejátko J, Ryu H, Kim GT, Dobesová R, Choi S, Choi SM, et al. The histidine kinases CYTOKININ-INDEPENDENT1 and ARABIDOPSIS HISTIDINE KINASE2 and 3 regulate vascular tissue development in Arabidopsis shoots. Plant Cell. 2009;21(7):2008–21.

    Article  PubMed  PubMed Central  Google Scholar 

  33. Kumar D, Wareing PF. Factors controlling stolon development in the potato plant. New Phytol. 1972;71(4):639–48.

    Article  CAS  Google Scholar 

  34. Yasunori K. Changes in levels of butanol- and water-soluble cytokinins during the life cycle of potato tubers. Plant Cell Physiol. 1982;23(5):843–9.

    Google Scholar 

  35. Rayirath UP, Lada RR, Caldwell CD, Asiedu SK, Sibley KJ. Role of ethylene and jasmonic acid on rhizome induction and growth in rhubarb (Rheum rhabarbarum L.). Plant Cell Tissue Organ Cult. 2011;105(2):253–63.

    Article  CAS  Google Scholar 

  36. Mingo-Castel AM, Negm FB, Smith OE. Effect of carbon dioxide and ethylene on tuberization of isolated potato stolons cultured in vitro. Plant Physiol. 1974;53(6):798–801.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Lee Y, Bak G, Choi Y, Chuang W, Cho HT, Lee Y. Roles of phosphatidylinositol 3-kinase in root hair growth. Plant Physiol. 2008;147(2):624–35.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Xue HW, Chen X, Mei Y. Function and regulation of phospholipid signalling in plants. Biochem J. 2009;421(2):145–56.

    Article  CAS  PubMed  Google Scholar 

  39. Cenzano A, Cantoro R, Racagni G, De Los S-BC, Hernandez-Sotomayor T, Abdala G. Phospholipid and phospholipase changes by jasmonic acid during stolon to tuber transition of potato. Plant Growth Regul. 2008;56(3):307–16.

    Article  CAS  Google Scholar 

  40. Dudits D, Abrahám E, Miskolczi P, Ayaydin F, Bilgin M, Horváth GV. Cell-cycle control as a target for calcium, hormonal and developmental signals: the role of phosphorylation in the retinoblastoma-centred pathway. Ann Bot. 2011;107(7):1193–202.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Chen T, Wu X, Chen Y, Li X, Huang M, Zheng M, et al. Combined proteomic and cytological analysis of Ca2+-calmodulin regulation in Picea meyeri pollen tube growth. Plant Physiol. 2009;149(2):1111–26.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Gargantini PR, Giammaria V, Grandellis C, Feingold SE, Maldonado S, Ulloa RM. Genomic and functional characterization of StCDPK1. Plant Mol Biol. 2009;70(1–2):153–72.

    Article  CAS  PubMed  Google Scholar 

  43. Sojikul P, Kongsawadworakul P, Viboonjun U, Thaiprasit J, Intawong B, Narangajavana J, et al. AFLP-based transcript profiling for cassava genome-wide expression analysis in the onset of storage root formation. Physiol Plant. 2010;140(2):189–98.

    Article  CAS  PubMed  Google Scholar 

  44. Yao Y, Min Y, Geng MT, Wu XH, Hu XW, Fu SP, et al. The effects of calcium on the in vitro cassava storage root formation. Adv Mater Res. 2013;726-731:4529–33.

    Article  Google Scholar 

  45. Hirt H. Connecting oxidative stress, auxin, and cell cycle regulation through a plant mitogen-activated protein kinase pathway. Proc Natl Acad Sci U S A. 2000;97(6):2405–7.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Nagata T, Niyada E, Fujimoto N, Nagasaki Y, Noto K, Miyanoiri Y, et al. Solution structures of the trihelix DNA-binding domains of the wild-type and a phosphomimetic mutant of Arabidopsis GT-1: mechanism for an increase in DNA-binding affinity through phosphorylation. Proteins. 2010;78(14):3033–47.

    Article  CAS  PubMed  Google Scholar 

  47. Nagano Y. Several features of the GT-factor trihelix domain resemble those of the Myb DNA-binding domain. Plant Physiol. 2000;124(2):491–4.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Kuhn RM, Caspar T, Dehesh K, Quail PH. DNA binding factor GT-2 from Arabidopsis. Plant Mol Biol. 1993;23(2):337–48.

    Article  CAS  PubMed  Google Scholar 

  49. Zhao C, Craig JC, Petzold HE, Dickerman AW, Beers EP. The xylem and phloem transcriptomes from secondary tissues of the Arabidopsis root-hypocotyl. Plant Physiol. 2005;138(2):803–18.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Zhong R, Lee C, McCarthy RL, Reeves CK, Jones EG, Ye ZH. Transcriptional activation of secondary wall biosynthesis by rice and maize NAC and MYB transcription factors. Plant Cell Physiol. 2011;52(10):1856–71.

    Article  CAS  PubMed  Google Scholar 

  51. Xie Y, Xu L, Wang Y, Fan L, Chen Y, Tang M, et al. Comparative proteomic analysis provides insight into a complex regulatory network of taproot formation in radish (Raphanus sativus L.). horticulture. Research. 2018;5:51.

    Google Scholar 

  52. Chan RL, Gago GM, Palena CM, Gonzalez DH. Homeoboxes in plant development. Biochimica et Biophysica Acta (BBA). 1998;1442(1):1–19.

    Article  CAS  Google Scholar 

  53. Hur YS, Um JH, Kim S, Kim K, Park HJ, Lim JS, et al. Arabidopsis thaliana homeobox 12 (ATHB12), a homeodomain-leucine zipper protein, regulates leaf growth by promoting cell expansion and endoreduplication. New Phytol. 2015;205(1):316–28.

    Article  CAS  PubMed  Google Scholar 

  54. Tornero P, Conejero V, Vera P. Phloem-specific expression of a plant homeobox gene during secondary phases of vascular development. Plant J. 1996;9(5):639–48.

    Article  CAS  PubMed  Google Scholar 

  55. Xu XR, Gao ZM, Lou YF, Yang KB, Shan XM, Zhu CL. Identification of homeobox genes associated with lignification and their expression patterns in bamboo shoots. Biomolecules. 2019;9:862.

    Article  CAS  PubMed Central  Google Scholar 

  56. Ruan YL. Sucrose metabolism: gateway to diverse carbon use and sugar signaling. Annu Rev Plant Biol. 2014;65:33–67.

    Article  CAS  PubMed  Google Scholar 

  57. Zrenner R, Salanoubat M, Willmitzer L, Sonnewald U. Evidence of the crucial role of sucrose synthase for sink strength using transgenic potato plants (Solanum tuberosum L.). Plant J. 1995;7(1):97–107.

    Article  CAS  PubMed  Google Scholar 

  58. Rouhier H, Usuda H. Spatial and temporal distribution of sucrose synthase in the radish hypocotyl in relation to thickening growth. Plant Cell Physiol. 2001;42(6):583–93.

    Article  CAS  PubMed  Google Scholar 

  59. Hideaki U, Taku D, Kousuke S, Hiroo F. Development of sink capacity of the "storage root" in a radish cultivar with a high ratio of “storage root” to shoot. Plant Cell Physiol. 1999;4:4.

    Google Scholar 

  60. Mitsui Y, Shimomura M, Komatsu K, Namiki N, Shibata-Hatta M, Imai M, et al. The radish genome and comprehensive gene expression profile of tuberous root formation and development. Sci Rep. 2015;5:10835.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  61. Li XQ, Zhang D. Gene expression activity and pathway selection for sucrose metabolism in developing storage root of sweet potato. Plant Cell Physiol. 2003;44(6):630–6.

    Article  CAS  PubMed  Google Scholar 

  62. Jackson SD. Multiple signaling pathways control tuber induction in potato. Plant Physiol. 1999;119(1):1–8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  63. Ren X, Zhang J. Research progresses on the key enzymes involved in sucrose metabolism in maize. Carbohydr Res. 2013;368:29–34.

    Article  CAS  PubMed  Google Scholar 

  64. Yu R, Xu L, Zhang W, Wang Y, Luo X, Wang R, et al. De novo taproot transcriptome sequencing and analysis of major genes involved in sucrose metabolism in radish (Raphanus sativus L.). Front Plant Sci. 2016;7:585.

    Article  PubMed  PubMed Central  Google Scholar 

  65. Abelenda JA, Navarro C, Prat S. From the model to the crop: genes controlling tuber formation in potato. Curr Opin Biotechnol. 2011;22(2):287–92.

    Article  CAS  PubMed  Google Scholar 

  66. Yang M, Zhu L, Pan C, Xu L, Liu Y, Ke W, et al. Transcriptomic analysis of the regulation of rhizome formation in temperate and tropical Lotus (Nelumbo nucifera). Sci Rep. 2015;5:13059.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  67. Wang X, Chang L, Tong Z, Wang D, Yin Q, Wang D, et al. Proteomics profiling reveals carbohydrate metabolic enzymes and 14-3-3 proteins play important roles for starch accumulation during cassava root Tuberization. Sci Rep. 2016;6:19643.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  68. Kuipers A, Jacobsen E, Visser R. Formation and deposition of amylose in the potato tuber starch granule are affected by the reduction of granule-bound starch synthase gene expression. Plant Cell. 1994;6(1):43–52.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  69. Li XJ, Yang JL, Hao B, Lu YC, Qian ZL, Li Y, et al. Comparative transcriptome and metabolome analyses provide new insights into the molecular mechanisms underlying taproot thickening in Panax notoginseng. BMC Plant Biol. 2019;19(1):451.

    Article  PubMed  PubMed Central  Google Scholar 

  70. Qin Z, Hou F, Li A, Dong S, Huang C, Wang Q, et al. Comparative analysis of full-length transcriptomes based on hybrid population reveals regulatory mechanisms of anthocyanin biosynthesis in sweet potato (Ipomoea batatas (L.) lam). BMC Plant Biol. 2020;20(1):299.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  71. Mano H, Ogasawara F, Sato K, Higo H, Minobe Y. Isolation of a regulatory gene of anthocyanin biosynthesis in tuberous roots of purple-fleshed sweet potato. Plant Physiol. 2007;143(3):1252–68.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  72. Mahoney JD, Wang S, Iorio LA, Wegrzyn JL, Dorris M, Martin D, et al. De novo assembly of a fruit transcriptome set identifies AmMYB10 as a key regulator of anthocyanin biosynthesis in Aronia melanocarpa. BMC Plant Biol. 2022;22(1):143.

    Article  PubMed  PubMed Central  Google Scholar 

  73. Young MD, Wakefield MJ, Smyth GK, Oshlack A. Gene ontology analysis for RNA-seq: accounting for selection bias. Genome Biol. 2010;11(2):R14.

    Article  PubMed  PubMed Central  Google Scholar 

  74. Mao X, Tao C, Olyarchuk JG, Wei L. Automated genome annotation and pathway identification using the KEGG Orthology (KO) as a controlled vocabulary. Bioinformatics. 2005;21(19):3787.

    Article  CAS  PubMed  Google Scholar 

  75. Eisen MB, Spellman PT, Brown PO, Botstein D. Cluster analysis and display of genome-wide expression patterns. Proc Natl Acad Sci U S A. 1998;95(25):14863–8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  76. Langfelder P, Horvath S. WGCNA: an R package for weighted correlation network analysis. BMC Bioinformatics. 2008;9:559.

    Article  PubMed  PubMed Central  Google Scholar 

  77. Zhang B, Horvath S. A general framework for weighted gene co-expression network analysis. Stat Appl Genet Mol Biol. 2005;4:Article17.

    Article  PubMed  Google Scholar 

Download references

Acknowledgements

We thank Miss Yunyi Zhou, Xia Li and Yuting Li for providing the experiment guidance.

Method declaration

All methods are implemented in accordance with relevant guidelines and regulations in this manuscript.

Funding

This work was supported by the National Natural Science Foundation of China (Grant No. 32060419, 32060469), the Guangxi Innovation Team Project of Tubers of Modern Agricultural Industrial Technology System of China (nycytxgxcxtd-11).

Author information

Authors and Affiliations

  1. National Demonstration Center for Experimental Plant Science Education, College of Agriculture, Guangxi University, Nanning, 530004, People’s Republic of China

    Zhaoqin Cai, Zhipeng Cai, Jingli Huang, Aiqin Wang, Aaron Ntambiyukuri, Jie Zhan, Dong Xiao & Longfei He

  2. Guangxi South Subtropical Agricultural Science Research Institute, Chongzuo, 532406, People’s Republic of China

    Zhaoqin Cai

  3. Guangxi Colleges and Universities Key Laboratory of Crop Cultivation and Tillage, Nanning, 530004, People’s Republic of China

    Aiqin Wang, Jie Zhan, Dong Xiao & Longfei He

  4. Hepu Institute of Agricultural Sciences, Beihai, 536101, People’s Republic of China

    Bimei Chen & Ganghui Zheng

  5. Maize Research Institute of Guangxi Academy of Agricultural Sciences, Nanning, 530007, People’s Republic of China

    Huifeng Li & Yongmei Huang

Authors
  1. Zhaoqin Cai
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Zhipeng Cai
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Jingli Huang
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Aiqin Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Aaron Ntambiyukuri
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Bimei Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Ganghui Zheng
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Huifeng Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Yongmei Huang
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Jie Zhan
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Dong Xiao
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. Longfei He
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

DX and LFH have designed experiments, and revised the manuscript. ZQC, ZPC, JLH, AQW,and Ntambiyukuri have analyzed the sequencing data for transcriptome assembly. BMC, GHZ, HFL, and YMH supported the materials. ZQC and JZ have developed qPCR experiments. ZQC have written the manuscript. The author(s) read and approved the final manuscript.

Corresponding authors

Correspondence to Dong Xiao or Longfei He.

Ethics declarations

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no conflict of interest.

Additional information

Publisher’s Note

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

Supplementary Information

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

Cai, Z., Cai, Z., Huang, J. et al. Transcriptomic analysis of tuberous root in two sweet potato varieties reveals the important genes and regulatory pathways in tuberous root development. BMC Genomics 23, 473 (2022). https://doi.org/10.1186/s12864-022-08670-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s12864-022-08670-x

Keywords

BMC Genomics

ISSN: 1471-2164

Contact us