Comparative transcriptomic analysis transcription factors and hormones during the flower bud differentiation in ‘Red Globe’ grape under red-blue combined light

doi:10.21203/rs.3.rs-1625176/v1

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Comparative transcriptomic analysis transcription factors and hormones during the flower bud differentiation in ‘Red Globe’ grape under red-blue combined light

https://doi.org/10.21203/rs.3.rs-1625176/v1

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published 01 Jun, 2023

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Grape is a globally significant fruit in the world. Flower bud differentiation of grape is closely related to light quality. In order to understand the regulation mechanism of grape flower bud differentiation under red-blue combined light, the transcriptome and hormone content were determined in four stages of flower bud differentiation. The contents of IAA and ABA in grape buds at all stages of flower bud differentiation under red-blue combined light were higher than those in control. However, the contents of CKs and GAs fluctuated continuously during the process. Moreover, it was found that many differential expression genes (DEGs) were involved in auxin, cytokinin, gibberellin, and the abscisic acid signal transduction pathway. There were significant differences in the genes of AUX/IAA, SAUR, A-RR, and ABF between the red-blue combination light treatment and the control buds, especially the ABF genes were utterly different. The expression of GBF4 and AI5L2 in control were always low, while the expression under the red-blue combined light increased. AI5L7 and AI5L5 showed an upward trend in control and gradually decreased under the red-blue combined light. Through weighted gene co-expression network analysis (WGCNA), transcription factors WRKY family WRK48, ERF family EF110, ABR1, CAMTA family CAMTA3, HSF family HSFA3 may be involved in the regulation of the GBF4 gene. This study will lay a foundation for further analysis of grape flower bud differentiation regulation under red-blue combined light.

Grape (Vitis vinifera L.) is a globally significant fruit that is cultivated on all continents. Whether it is fresh food or wine, it has significant economic significance and is one of the most economically profitable fruit crops ^[1]. The quality and quantity of grapes are the most critical standards for grape cultivation, directly affected by flower bud differentiation ^[2]. Compared with one-year-old plants, flower bud differentiation of grape is an unusual process ^[3]. The shoot meristem generates both nutritional and reproductive structures, and the uncommitted primordia (also called anlagen) generated by stem meristem differentiates into tendrils or inflorescences, which completes flowering in the second year ^[4].

Grape flower bud differentiation is a very complex biological process, which is produced by the integration of the external environment and internal factors ^[5]. In the model plant Arabidopsis thaliana, flower development involves six pathways：the photoperiod, gibberellin, vernalization, autonomous, aging pathways, and glycometabolism pathways regulate floral-specific genes, resulting in the physiological transformation of the vegetative meristem into floral meristem ^[6]. These pathways converge to regulate the expression of flowering-related genes, such as FLOWER LOCUS T (FT), CONSTANS (CO), SUPPRESSOR OF OVEREXPRESSION OF CO1 (SOC1), LEAFY (LFY), APETALA1 (AP1), APETALA2 (AP2), and APETALA3 (AP3), and irreversibly induce the transformation from vegetative meristem to floral meristem ^[7]. Flower development pathway genes or genes involved in photoperiod or vernalization were also identified in the grape genome, most of which were flowering signal integrators, floral meristem recognition genes, and floral organ recognition genes, such as MADS-box family genes and VvFT/TFL1 family genes promoting flowering early ^[8]. The ortholog of VvFT, Arabidopsis thaliana FLOWERING LOCUST, is related to the seasonal flowering induction in latent buds and inflorescence and flower development ^[9]. The expression of VvLFY is related to inflorescence and flower development ^[10]. The homologs of VvFUL and VvAP1 appear in the early stages of lateral meristem development and are maintained in both inflorescence and tendril primordia ^{[11, 12]}.

As an essential environmental factor, light drives photosynthesis and participates in most processes of regulating the plant life cycle, which is an essential factor affecting plant flower bud differentiation ^[13]. Light quality is an important signal affecting plant morphogenesis and a key factor for morphogenesis and flower bud formation ^[14]. Plants perceive the quality of light through photoreceptors. Photoreceptors are classified as photosensitive pigments (Phys) (absorption of red/far-red light), cryptochromes (Crys) (absorption of blue/ultraviolet A (UV-A) light), phototaxis, Zeitlupe (ZTL/FKF1/LKP2) family members, and UV-B absorption of UVR8 family members ^[15-17]. Photosensitizers and cryptochromes are responsible for plant morphological and developmental changes ^{[18, 19]}. Therefore, the research on the effect of light quality on plant growth and development mainly focuses on red and blue light. In addition, The combination of red and blue light forms a spectral absorption peak suitable for plant photosynthesis and morphogenesis, forming fully developed flower buds and increasing the number of buds ^{[20, 21]}. Therefore, two wavelengths (blue and red) are necessary for plants.

Although some progress has been made in studying the grape flower bud differentiation process ^{[22, 23]}, the regulatory mechanism of grape flower bud differentiation under red-blue combined light is still unclear. In this study, based on previous screening of red-blue combined light, red light: blue light = 4: 1 (S) light supplement treatment was conducted on ‘Red Globe’ grape, and the hormone content at different stages of flower bud differentiation was determined by high-performance liquid chromatography (HPLC) with no light supplement as the control. The differentially expressed genes significantly involved in flower bud differentiation were analyzed by comparative transcriptomics. The transcription factors involved in the regulation of critical genes in flower bud differentiation were analyzed by WGCNA. This study will preliminarily clarify the regulatory mechanism of grape flower bud differentiation under red-blue combined light and lay the foundation for further research.

Flower bud differentiation of ‘Red Globe’ grape under red-blue light combination. Before the transcriptome study, we analyzed the floral bud development process in morphological analysis (Fig. 1). In the first stage (April 30), the budding body was flat green; the growth point was conical, the bud scale was not lignification, the T1 branch diameter was less than S1, two groups of flower buds were information of Anlagen or uncommitted primordia stage (Supplementary Figure S1). In the second stage (June 30), the buds expanded, green, and increased. The branches of S2 began to turn from green to brown. Some buds of T2 and S2 were at the stage of differentiation of Anlagen to form inflorescence primordia. In the third stage (July 30), the buds became plump and brown. 70% of the flower buds in T3 were at the stage of differentiation of Anlagen to form inflorescence primordia, while the buds in S3 reached 90%. S4 stage (September 15), bud hard, dark brown, scales semi-lignified, T4 and S4 bud all in the differentiation of Anlagen to form inflorescence primordia stage.

Changes of hormone content during flower bud development. Flower bud differentiation is closely related to hormones. Therefore, the contents of IAA, CKs, GAs, and ABA in flower buds of red-blue light combination and control at four stages were determined by HPLC. HPLC analysis showed that the contents of these hormones changed significantly in different flower bud differentiation stages. The IAA content in the control was the highest in the second stage (Fig. 2A) and then decreased with development. Interestingly, the IAA content in the red-blue combination light treatment was always higher than control, reaching the highest in the third and lowest in the fourth stages. As shown in Fig. 2B, the trend of CKs content in the two treatments was utterly different. The CKs content in the flower bud increased gradually under the control, and the highest in the second stage and the lowest in the fourth stage under the red-blue combination light treatment. GAs content fluctuated in the flower bud differentiation stage. The control was higher than the red-blue combination light in the first and the third stage of flower bud differentiation (Fig. 2C). The ABA content in flower bud differentiation under control was consistently lower than that under red-blue combination light treatment. In the third stage, the ABA content of control was the lowest, and that of red-blue combination light treatment was the highest, 24.6% higher than that of control (Fig. 2D).

Analysis of differentially expressed genes. We constructed a transcriptome sequencing library for the four stages of flower buds under two treatments, and 183.27 Gb clean reads were obtained. Clean reads of each sample were above 6.19 Gb, and the Q30 base percentage was above 93.28% (Supplementary Table S2). Sample PCA analysis shows that the samples collected in this study have a high identity (Supplementary Figure S2). The differentially expressed genes were identified by DESeq2 software, and the differentially expressed genes were found to have different expression trends in red-blue combination light treatment and control (Fig. 3A-C). Compared with T1, 2314 common DEGs and 611, 1367, and 3072 specific expression genes were found in grape buds identified in T2, T3, and T4. There were 2262, 3328, and 3342 upregulated genes and 1896, 3290, and 4310 down-regulated genes among T1 vs. T2, T1 vs. T3, and T1 vs. T4, respectively (Fig. 3D, G). Compared with S1, there were 1889 common DEGs and 591,1550,1613 unique expression genes in S2, S3, and S4. S1 vs. S2, S1 vs. S3, and S1 vs. S4, there were 1691, 2546, and 2116 up-regulated genes and 1736, 3131, and 3161 down-regulated genes (Fig. 3E, H). Analysis between T1 vs. S1, T2 vs. S2, T3 vs. S3, and T4 vs. S4 showed that 1214, 1292, 1744, and 1912 genes were up-regulated, and 819, 1263, 1983, and 674 genes were down-regulated at four different maturation stages (Fig. 3F, I). In the third stage, the up- and down-regulated genes increased significantly, indicating that these genes played a crucial regulatory role in the process of grape flower bud differentiation.

Annotation of DEGs. We performed GO functional annotation and KEGG pathway analysis of DEGs. Through GO functional annotation, 6129 genes were annotated as 50 functional branches of cell components, biological processes, and molecular functions. For all up- and down-regulated DEGs. The first ten annotated GO terms are binding (GO: 0005488), cell part (GO: 0044464), catalytic activity (GO: 0003824), cell process (GO: 0009987), metabolic process (GO: 0008152), membrane part (GO: 0044425), membrane (GO: 0016020), organelle (GO: 0043226), biological regulation (GO: 0065007) and response to stimulus (GO: 0050896). Among all the up-regulated DEGs, 1995, 1902, 1853, 1673, 1668, 1394, 1173, 1102, 773, and 441 annotated these 10 GO terms. In the down-regulated DEGs, the numbers were 1783, 1684, 1521, 1445, 1412, 1374, 1204, 953, 747 and 418, respectively (Supplementary Figure S3, Supplementary Table S3).

KEGG pathway analysis showed that the plant hormone signal transduction path-way (map04075) played an essential role in grape flower bud differentiation. The plant hormone signal transduction pathway was enriched in the four stages under red-blue combination light treatment and control in the down-regulated DEGs. In addition, other enrichment pathways include flavonoid biosynthesis (map00941), flavonoid and flavonol biosynthesis (map00944), circadian rhythm-plant (map04712), and glycine, serine, and threonine metabolism (map00260). The plant hormone signal transduction pathway was also significantly enriched in the four stages under red-blue combination light treatment and control in the up-regulated genes. In addition, the most enriched pathways are plant-pathogen interaction (map04626), and other enrichment pathways include MAPK signaling pathway-plant (map04016), glycerophospholipid metabolism (map00564), phenylpropanoid biosynthesis (map00940), and monoterpenoid biosynthesis (map00902) (Fig. 4, Supplementary Table S4). The results showed that grape flower bud differentiation was a very complex biological process. In addition to plant hormone signal transduction, MAPK signal transduction, phenylpropanoid biosynthesis, flavonoid biosynthesis, and circadian rhythm-plant are also involved in this process.

DEGs related to plant hormone signal transduction. Previous studies have shown that grape flower bud differentiation is closely related to plant hormone signaling. In this study, we found that DEGs in plant hormone signal transduction are mainly concentrated in auxin, cytokinin, gibberellin, and abscisic acid pathways (Fig. 5), 36 EDGs involved in these pathways include auxin pathway TIR1 (VIT_14s0030g0124), AUX/IAA (VIT_05s0020g01070, VIT_09s0002g05160, VIT_05s0020g04690, VIT_05s0049g01970), ARF (VIT_11s0016g00640), GH3 (VIT_07s0104g00800, VIT_03s0091g0031) and SAUR (VIT_19s0085g00010, VIT_09s0002g00670, VIT_15s0048g00530, VIT_01s0146g00180, VIT_03s0038g01150); cy-tokinin pathway CRE1 (VIT_12s0057g00690), B-ARR (VIT_17s0000g10100), A-ARR (VIT_08s0007g05390, VIT_17s0000g07580, VIT_01s0026g00940, VIT_13s0067g03510, VIT_18s0001g02540); gibberellin pathway GID2 (VIT_07s0129g01000), TF (VIT_07s0005g02510, VIT_14s0060g00260); abscisic acid pathway PYR/PYL (VIT_15s0046g01050), PP2C (VIT_16s0022g02210, VIT_06s0004g05460, VIT_16s0050g02680), SnRK2 (VIT_07s0197g00080, VIT_12s0035g00310) and ABF (VIT_18s0072g00470, VIT_03s0063g00310, VIT_18s0001g10450, VIT_04s0069g01150, VIT_12s0034g00110). Further analysis showed that the expression of TIR1, AUX/IAA, and ARF genes was relatively high in the early stage of flower bud differentiation, while the expression was down-regulated in the later stage of differentiation. The expression of GH3 was gradually increased in flower bud differentiation. In addition, the expression trend of the SAUR gene was utterly different between the red-blue combination light and control. The expression of the A-ARR gene was high at the early stage of flower bud differentiation and then decreased, while the expression trend was opposite under the red-blue combina-tion light. The expression trend of the TF gene in the control and red-blue combination light treatments was utterly different. The former was highly expressed at the early stage of flower bud differentiation and was low at the late stage, while the latter remained at a low throughout the flower bud differentiation stage. In the control, the expression of the PP2C gene increased with the process of flower bud differentiation, while in the red-blue combination light treatment, the expression decreased with the process of flower bud dif-ferentiation. The expression trends of the ABF gene in the two groups were different. The control's expression of GBF4 (VIT_18s0072g00470) and AI5L2 (VIT_04s0069g01150) re-mained at a low level, while the expression in the red-blue combination light treatment increased with the process of flower bud differentiation, reaching the highest in the third stage. AI5L7 (VIT_03s0063g00310) and AI5L5 (VIT_18s0001g10450) showed an upward trend in the control and gradually decreased under the red-blue combination light. The results showed that these signaling genes played an important role in grape flower bud differentiation.

qRT-PCR validates gene expression profiles. To validate our sequencing results, DEGs involved in plant hormone signal transduction, flavonoid biosynthesis and MAPK signal transduction pathways were randomly selected for qPCR analysis, including ARR4 (VIT_01s0026g00940), PIF3 (VIT_14s0060g00260), GBF4 (VIT_18s0072g00470), HST (VIT_09s0018g01190), C75A1 (VIT_06s0009g02840), CAMT (VIT_03s0063g00140), CML46 (VIT_14s0108g01000), YODA (VIT_02s0025g03850), M2K5 (VIT_09s0018g01820). qRT-PCR results showed that the expression patterns of these genes were consistent with those in RNA-seq data, with the correlation coefficient R = 0.82. These results showed that the gene expression pattern revealed by RNA-seq data was reliable and could be used for further analysis (Fig. 6).

Screening through WGCNA for the transcription factors regulating grape flower bud differentiation. In this study, a total of 24 samples from four stages of grape flower bud differentiation under red-blue combination light treatment and control were used for weighted WGCNA analysis (Supplementary Fig. 4S). Through dynamic genes changes in different developmental stages and correlation analysis between samples, possible transcription factors regulating flower bud differentiation were discussed. Firstly, the expression patterns of 25844 DEGs extracted from transcriptome sequencing were analyzed by WGCNA, and they were divided into 19 modules (Fig. 7A, Supplementary Table S5) according to the similarity of expression patterns. These modules can be divided into two main branches (one for two modules, the other for 17 modules) (Fig. 7B). The correlation between the expression patterns of each module and different stages of grape flower bud differentiation was analyzed. The results showed that the modules ‘red’, ‘green’ and ‘magenta’ were highly correlated with the third stage of the fastest flower bud differentiation under red-blue combined light treatment, indicating that these modules were closely related to the flower bud differentiation of grapes (Fig. 7C). A total of 2373 genes were found in these modules, and the gene association networks of 2373 genes were constructed. According to the degree of connection, the first 50 genes are considered Hub genes. Among these 50 Hub genes, seven transcription factors were found, including ERF family EF110 (VIT_18s0072g00260), ABR1 (VIT_07s0031g01980), bHLH family BH025 (VIT_00s0824g00020), BH025 (VIT_00s0927g00010), WRKY family WRK48 (VIT_05s0077g00730), and CAMTA3 (VIT_07s0141g00250). NF-X1family NFXL2 (VIT_13s0067g00920) and bZIP family GBF4 (VIT_18s0072g00470) (Supplementary Figure S5, Supplementary Table S6). As highly connected Hub genes, these transcription factors may regulate flower bud differentiation of grape.

The bZIP family genes are related to the ABA signal. In order to further analyze the transcription factors regulated by the GBF4 gene in the gibberellin pathway, the genes related to GBF4 in the ‘green’ module with edge weight (≥ 0.4) are selected for analysis (Fig. 8, Supplementary Table S7). It was found that 42 genes were regulated by GBF4 (VIT_18s0072g00470), including hub transcription factor WRKY family WRK48 (VIT_05s0077g00730), ERF family EF110 (VIT_18s0072g00260), ABR1 (VIT_07s0031g01980), CAMTA family CAMTA3 (VIT_07s0141g00250), HSF family HSFA3 (VIT_08s0007g0390) and other non-Hub transcription factor genes have a certain regulatory relationship with the GBF4 gene.

The grape yield depends on the number of flower bud differentiation. Plant hormones are the key factors in controlling the induction of flowering and interacting with each other during plant development ^{[24, 25]}. The types and contents of hormones in grape bud varied considerably at different developmental stages. In this study, ‘Red Globe’ was used as the experimental material, and the supplemental treatment of red-blue combined light was carried out. With no supplemental light as the control, four main hormones in four stages of flower bud differentiation were identified. IAA is the earliest plant hormone discovered by people, necessary for plants' average growth and development ^[26]. The IAA content in flower buds under red-blue combined light treatment is higher than that in the control, and it shows a trend of increasing first and then decreasing in the process of flower bud differentiation, reaching the highest at the third stage. Higher IAA content guarantees good flower bud formation, consistent with previous studies ^[27]. CKs can promote the inflorescence development of lateral meristem in grapes ^[28]. The content of CKs in flower bud increased during flower bud differentiation under the control, while the red-blue combined light treatment had utterly different trends. GAs is related to the initiation of flowering transformation and floral primordium ^{[29, 30]}, which is also a hot topic in current research ^[31]. Unlike CKs, GAs promoted the differentiation of lateral meristem and inhibited the development of inflorescence, which was beneficial to the development of the grape tendril. The grape plants after GAs gene mutation were short, and grape tendril differentiated into inflorescence ^[32]. Interestingly, similar results were also observed in this study. The third stage of flower bud differentiation was the fastest, and the red-blue combined light treatment was lower than the control. In addition, there was a significant difference in ABA between normal and malformed flowers ^[33]. In this study, the red-blue combined light treatment was higher than the control at the early stage of flower bud differentiation and even 24.6% higher at the third stage, proving that ABA plays a vital role in flower bud differentiation. However, the regulation mechanism of hormone balance is complex. Like other perennial woody plants, grape flower bud differentiation requires a balance between hormones ^[34].

In this study, 36 DEGs were annotated to auxin, cytokinin, gibberellin, and abscisic acid signal transduction pathways. In the auxin signal transduction pathway, the expression of TIR1, AUX/IAA, and ARF genes were relatively high at the early stage of flower bud differentiation, while they were down-regulated at the late stage of differentiation, which was consistent with previous studies ^[35]. Studies have shown that ARF, combined with auxin response element AUX/IAA, plays a central role in transforming local auxin concentration into specific gene expression output and flowering initiation ^[36] and regulates the development of floral organs^[37]. In this study, four AUX/IAA genes and one ARF gene regulate the auxin pathway. The expression of IAA17 and ARFS genes in red-blue combined light was utterly inconsistent with that in the control treatment, indicating that these genes played an essential role in responding to flower bud differentiation under red-blue combined light. In the cytokinin signal transduction pathway, the ARR gene participates in the circadian rhythm mechanism under a light environment, activates the function of flowering-induced gene SOC1 to mediate the flowering of Arabidopsis^[38], and is highly expressed in the branches with a high flowering rate of apple trees ^[39]. The six ARR genes obtained in this study first increase and then decrease during flower bud differentiation and show significant indigenous differences in the two treatments, confirming the positive effect of ARR family genes on flower bud differentiation. GID and TF are genes that positively regulate the expression of LFY, SOC1, FT, SPL, and other genes to promote flower bud differentiation, which DELLA inhibits. The essential genes involved in flower bud differentiation in these gibberellin signal transduction pathways are also identified in this study. Unlike previous studies, the red and blue light treatment with a high flower rate in this study is lower than the control group, which may be due to the down-regulation of gibberellin response genes without the effect of the DELLA gene ^[40]. The three signal components of PYR/PYL, PP2C, and SnRK2 constitute the core abscisic acid signaling pathway ^[41], and positively regulate the flowering of long-day plants ^[42]. In addition, five ABF genes were also found to be involved in grape flower bud differentiation, indicating that ABF can be phosphorylated by SnRK2, affecting flower bud differentiation ^[43].

WGCNA has been used in numerous species to elucidate the interaction between physiological characteristics and gene expression ^{[44, 45]}. WGCNA was used to evaluate transcript expression and trait changes at different stages of germination and differentiation under red and blue light, and three modules, ‘red,’ ‘green,’ and ‘magenta,’ were highly related to flower bud differentiation, were screened. In these modules, eight transcription factors were identified as Hub genes, including ERF family, bHLH family, WRKY family, CAMTA family, NF-X1 family, and bZIP family, suggesting that these transcription factors may be involved in grape flower bud differentiation under red-blue combined light. Previous transcriptome sequencing studies found that transcription factors such as MYB, MADS-box, WRKY, ERF, and bHLH played an essential role in flower bud differentiation^[46]. MYB gene can regulate floral organ development and even mediate gibberellin signal transduction in flowering response ^[47]. MADS-box gene is involved in the regulation of floral meristem initiation and development ^[48]. In addition, bZIP and ERF are related to floral bud differentiation hormone signal response ^[49]. The bZIP family gene GBF4 is a unique gene in the ABA signal transduction pathway. So far, there are few reports on this gene's regulation of flower bud differentiation. This study found that WRKY, ERF, CAMTA, and HSF family genes were involved in the transcriptional regulation of GBF4 through weight co-expression analysis. WRKY family members were the key factors in the abscisic acid response pathway, which could accelerate flowering by regulating AP1 ^[50], and HSF was involved in environmental stress response to regulate flowering and development of plants ^[51]. The above transcription factors involved in plant hormone signal transduction regulation lacked clear evidence, but our study provided a theoretical basis for further confirming the regulatory mechanism of grape flower bud differentiation under red-blue combined light.

Overall, the comparative transcriptome analysis of the differential genes involved in the plant hormone signal transduction pathway showed significant differences in AUX/IAA, SAUR, A-RR, and ABF in red-blue combined light treatment and control buds, especially the ABF genes were utterly different. The GBF4 (VIT_18s0072g00470) and AI5L2 (VIT_04s0069g01150) expression in control remained low, while the expression under the red-blue combined light increased with the process of flower bud differentiation. AI5L7 (VIT_03s0063g00310) and AI5L5 (VIT_18s0001g10450) showed an upward trend in control and gradually decreased under red-blue combined light. It is speculated that the difference of ABF family gene regulation plays a vital role in grape flower bud differentiation response to red-blue combined light. Weighted gene co-expression network analysis showed that Hub transcription factor WRK48 (VIT_05s0077g00730), ERF family EF110 (VIT_18s0072g00260), ABR1 (VIT_07s0031g01980), CAMTA family CAMTA3 (VIT_07s0141g00250), HSF family HSFA3 (VIT_08s0007g0390) may be involved in the regulation of GBF4 gene.

Plant materials. The test material was 10-year-old Viti's vinifera cv. ‘Red Globe’ grapes. The experiment was carried out in the shade of 2021 in the sunlight greenhouse of Helan County Gardening Industrial Park, Yinchuan City. Our previous studies have shown that red light: blue light = 4: 1 (S) can significantly increase the flowering rate of ‘Red Globe’ grapes (unpublished). Therefore, in this study, red light: blue light = 4: 1 (S) LED plant lights were selected, and no light supplement was used as a control (T). Light tubes were placed at 30 cm above the test line trees, and the leaf light intensity was maintained at 300 µmol m^− 2 s^− 1 for 14 hours per day from 8: 00–22: 00. In the first stage (T1 and S1, 30 April), the second stage (T2 and S2, 15 June), the third stage (T3 and S3, 30 July), and the fourth stage (T2 and S2, 15 September) of flower bud differentiation, 26 healthy branches were selected and removed with a sharp scalpel. Twenty buds were fixed in FAA (formalde-hyde-acetic acid-ethanol) for paraffin sections, and the other buds were immediately frozen in liquid nitrogen and stored at -80℃ until further analysis.

Physiological analysis of flower bud at different stages. Flower buds of four developmental stages were used for paraffin section making and hormone determination. Flower buds fixed in FAA are dehydrated in ethanol series and then transparent, wax-immersed, embedded, and patched in a dehydrator. Paraffin blocks containing flower buds were sliced with a semi-automatic slicer (Leica RM2245), stained with saffron-solid green, and sealed with neutral gum. Observation under an optical microscope (Olympus BX53) using SC180 image analysis system to obtain images^[52], and the flower bud differentiation stage was divided ^[53]. Auxin (IAA), cytokinin (CKs), gibberellin (GAs), and abscisic acid (ABA) were quantified by ultra-performance liquid chromatography spectrometry (ACQUITY H-Class, QDA) ^[54], with three biological replicates.

RNA sequencing and expression analysis. The RNA of samples was extracted using the OminiPlant RNA Kit (DNase I) kit (Beijing ComWin Biotech Co., Ltd. Beijing, China). Nanodrop2000 was used to detect the concentration and purity of RNA, agarose gel electrophoresis was used to detect RNA integrity, and Agilent2100 was used to determine the RIN value for further quantitative real-time reverse transcription-PCR (qRT-PCR) and RNA-seq determination. The Illumina HiSeq 2500 sequencing platform is used to perform RNA-seq. After sequencing raw reads, they are processed to get clean reads of high quality. The clean reads after quality control were aligned with the reference genome (http://plants.ensembl.org/Vitis_vinifera/Info/Index) using HISAT2 software ^[55] to obtain the mapped reads for subsequent analysis.

GO and KEGG pathway enrichment analysis. Differential expression analysis of samples was carried out using the expression difference analysis software DESeq2 ^[56]. Differential expression genes between different samples were screened out using FPKM (Fragments Per Kilobases per Million reads) value and |log₂fold changes| ≥ 1, and the corrected Padjust < 0.05 as the screening standard study the function of differential genes. The differentially expressed genes in gene concentration were compared with gene ontology (GO) and kyoto encyclopedia of genes and genomes (KEGG) databases to obtain genes' functional annotation and related metabolic pathway information in different samples.

RNA-seq data confirmation through qRT-PCR. In this study, qRT-PCR was used to validate RNA-Seq results. Real-time fluorescence quantitative PCR verified candidate DEG genes related to hormone signal transduction and other metabolic pathways. The reference gene was Actin1 (GenBank: XP_008654957.1). The primers (Supplementary Table S1) were designed by Primer 6.0 software and synthesized by Sangon (Shanghai, China). RNA and transcriptome sequencing samples for the same batch, qRT-PCR using ChamQ Universal SYBR qPCR Master Mix kit (Vazyme Biotech Co., Ltd. Nanjing, China). The reaction procedure was as follows: reverse transcription at 50 for 5 min, predenaturation at 95℃ for 10 min, denaturation at 95℃ for 10 s, annealing at 60℃ for 30 s, 40 cycles, and three biological repeats. The gene expression level was calculated by the 2^−ΔΔCt method.

Gene network construction and visualization. To further study the hormone regulation mechanism and possible transcription factors in grape flower buds, we used the WGCNA (v1.63) package in R to construct the co-expression network ^[57]. The soft threshold of co-expression network clustering is selected according to the FPKM value of all genes in the sample, R² > 0.8 is the norm, and the soft threshold is 9. All FPKM values were transformed into a topological overlap matrix (TOM), and each gene was clustered by hierarchical clustering ^[58]. The dynamic tree cutting method divides genes into different co-expression modules. The minimum number of genes in each co-expression module is set to 30, and the co-expression modules with similar clustering are merged with 0.3 as the boundary. The correlation between different modules and the degree of genes in the module (module membership, MM) are calculated. Find key modules related to flower bud differentiation for subsequent analysis. Using Cytoscape_V.3.8.0 to visualize the regulatory network mapping.

Acknowledgements

The work was supported by National Natural Science Foundation of China (31360493), Key R & D Projects in Ningxia (2021BEF02016) and Graduate Innovation Project of Ningxia University (GIP2020-09).

Author Contributions

Y.Z., X.L. and M.Y. conceived and designed the experiments. Y.Z., X.L., M.Y., J.Z. and S.D. performed the research and analyzed the data. Y.Z. and X.L. wrote the paper. All authors inter-preted the data and contributed to drafting the manuscript. All authors have read and agreed to the published version of the manuscript.

Competing interests

Te authors declare no competing interests.

Declarations

The collection of ‘Red Globe’ grapes in this work has been permited by Helan County Gardening Industrial Park, Yinchuan City.

Ethical standards

The conducted experiments comply with the laws of China.

Data availability

Data supporting the results and conclusions are included in both the article and additional files. All the transcriptome data have been deposited in the NCBI Sequence Read Archive (SRA) under accession number: PRJNA843849 (http://www.ncbi.nlm.nih.gov/sra).

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No competing interests reported.

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Comparative transcriptomic analysis transcription factors and hormones during the flower bud differentiation in ‘Red Globe’ grape under red-blue combined light

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