J Plant Biotechnol 2022; 49(4): 292-299
Published online December 31, 2022
https://doi.org/10.5010/JPB.2022.49.4.292
© The Korean Society of Plant Biotechnology
Correspondence to : e-mail: poudelpuspa@yahoo.com, puspa.poudel@pakc.tu.edu.np
This is an Open-Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
Anthocyanin, an important component in the grape berry skin, strongly affects grape quality. The transcription factors VvMYBA1 and VvMYBA2 (VvMYBA1/2) control anthocyanin biosynthesis. In addition, cultivation and environmental factors, such as light, influence anthocyanin accumulation. The present study aimed to clarify the effect of shading (reduced light condition) on the transcriptomic regulation of anthocyanin biosynthesis using a red-wine grape cultivar, Vitis vinifera ‘Pinot Noir’, and its white mutant, ‘Pinot Blanc’, caused by the deletion of the red allele of VvMYBA1/2. The grape berry skins were analyzed for anthocyanin content and global gene transcription accumulation. The microarray data were later validated by quantitative real-time PCR. A decisive influence of VvMYBA1/2 on the expression of an anthocyanin-specific gene, UDP glucose: flavonoid 3-O-glucosyltransferase, was observed as expected. In contrast, upstream genes of the pathway, which are shared by other flavonoids, were also expressed in ‘Pinot Blanc’, and the mRNA levels of some of these genes decreased in both cultivars on shading. Thus, the involvement of light-sensitive transcription factor(s) other than VvMYBA1/2 was suggested for the expression control of the upstream genes of the anthocyanin biosynthetic pathway. Furthermore, it was suggested that the effects of these factors are different among isogenes.
Keywords flavonoids, gene expression, shading, VvMYBAs
The quality of grape and grape products such as juice and wine largely depends on the amount and composition of flavonoid phenolics, i.e., anthocyanins, proanthocyanidins and flavonols, in the grape berries. Proanthocyanidins, or condensed tannins, contribute to astringency, whereas anthocyanins are responsible for their color. The accumulation of anthocyanins in grape berry skins starts from veraison and increases gradually until just before full maturity. On the other hand, the proanthocyanidins start to accumulate soon after the berry formation and decline during ripening (Downey et al. 2003a). Another flavonoid group, flavonols, is synthesized around flowering and mainly during ripening in the skin (Downey et al. 2003b). These flavonoid compounds are synthesized through the multi-step phenylpropanoid pathway (Fig. 1). The expression of structural genes in the phenylpropanoid pathway is controlled by transcription factors. For example, the expression of the genes specific for anthocyanin biosynthesis such as
To study the function of
In addition to the genetic control, anthocyanins accumulation in grape berry skins depends on various viticultural factors such as canopy management and irrigation, as well as environmental factors such as temperature and light (Brillante et al. 2018; Goto-Yamamoto et al. 2010; Koyama and Goto-Yamamoto 2008; Mori et al. 2007; Poudel et al. 2009; Yang et al. 2020). Among these factors, light is one of the important abiotic factors that regulate the synthesis of flavonoid compounds in grape berries. It has been demonstrated that a shading condition reduced the amount of anthocyanin and mRNA level of anthocyanin-pathway genes (Jeong et al. 2004). However, its control mechanism is not fully understood. Thus, in order to know if only
To determine the influence of light on transcriptomic changes in the skin of grape berries during ripening, the ‘Pinot Noir’ and ‘Pinot Blanc’ grapevines cultivated at the National Research Institute of Brewing, Higashi-Hiroshima, Japan were used. Branches facing the same direction from north to south orientation rows were taken for both treatments. A single bunch was taken as a replicate and nine bunches from three grapevines of each cultivar with similar size and berry numbers at veraison were selected and covered with three layers of Victoria lawn. This shading treatment reduced the light intensity during the daytime to 18%-20% (Jeong et al. 2004). The non-shaded bunches of the same grapevines were taken as the control. To confirm the temperature variation between shaded and non-shaded bunches, the daytime temperature was measured at 16:00, and it was revealed that shading had a negligible effect on temperature during the daytime. Three bunches each were sampled at veraison, two weeks after veraison (WAV) and 4 WAV. For each replicate (n = 3), 30 berries were collected randomly. The skins peeled from the 30 berries were immediately frozen in liquid nitrogen and kept at -80°C until use. The frozen skins were crushed for homogenization and used for RNA extraction and anthocyanin quantification. The results of 4 WAV of non-shaded ‘Pinot Noir’ and ‘Pinot Blanc’ were used in another publication with a different objective (Poudel et al. 2021), hence those data are not presented in this paper and used for discussion purpose only.
Anthocyanin was extracted from 0.2 g of berry skin in 2.5 mL of 2% formic acid in 70% methanol (v/v) solution for 20 min with sonication. A total of 400 µL aliquot was used for HPLC analysis after centrifugation at 15,000 rpm for 10 min and filtration with a 0.45 µM micro-membrane filter (Toyo Roshi Kaisha Ltd., Japan). The anthocyanin quantification method used in this study was similar to those described by Ali and Strommer (2003). A Hewlett Packard Series 1100 HPLC system and a Zorbax SB-C18 (5 µm, 2.1 × 150 mm) column were used to separate and quantify the anthocyanin based on peak area. The total anthocyanin concentration was expressed as a milligram of malvidin-3-glucoside (Extrasynthese, France) equivalents per gram of fresh berry skin weight.
Total RNA from berry skins for qRT-PCR was isolated according to the protocol reported by Reid et al. (2006) and purified using an RNeasy Plant Mini Kit (Qiagen, USA) following the manufacturer’s protocol. The total RNA isolated from 1 g of berry skin was quality assessed and quantified using a NanoDrop ND-1000 spectrophotometer (NanoDrop Technologies, USA) as well as an RNA Nano chip and RNA 6000 Nano Assay on an Agilent 2100 Bioanalyzer (Agilent Technologies, USA).
Microarray and q-PCR analysis methods used in this experiment were identical as those described in our previous study (Poudel et al. 2020). Briefly, for microarray analysis, complementary DNA (cDNA) was synthesized from a total of 10 µg total RNA. The cDNA was cleaned up, quantified, quality assessed and used for hybridization after labelling with Cy3-Random Nonamers (Roche NimbleGen Inc., USA). The hybridization was done with 4 µg Cy3 labelled cDNA to a NimbleGen gene expression 12 × 135 K array (Roche NimbleGen Inc., USA) according to the manufacturer’s protocol. The image data were acquired and analysed using NimbleGen MS 200 software. The data analysis was performed using GeneSpring software. To extract the differentially expressed genes, we applied a > 3.5 fold cut off. The signal intensities obtained from different replicates were averaged and the ratio between the average signal intensities of shaded to that of non-shaded was calculated. Additionally, to further extract the genes with significantly differentially expressed, a t-test was applied assuming the equal variance (< 0.05).
To determine mRNA levels of the anthocyanin pathway and related genes, qRT-PCR was carried out as described in our previous study (Poudel et al. 2020). Briefly, the qRT-PCR mixture was prepared with cDNA, upper and lower primers (Poudel et al. 2021) and SYBR Green Master Mix (Qiagen), and the final volume was adjusted to 20 µL with RNase-free water. The reaction was performed in a StepOnePlus real-time PCR system and StepOne software version 2.1 (Applied Biosystem, USA). The reaction condition was 95°C for 15 min, followed by 40 cycles at 95°C for 15 s, at each annealing temperature for 20 s and at 72°C for 20 s. The reaction was performed in at least three biological replicates and three analytical replicates for each prepared cDNA sample. The average data were normalized to the ubiquitin control gene.
The bunch-shading treatment was applied at veraison, the grape berries were sampled at 2 WAV and their anthocyanin compositions were analyzed using ‘Pinot Noir’. The shading treatment slightly affected the concentration of anthocyanin at 2 WAV (Table 1). However, the data on anthocyanin content were not different significantly at
Table 1 Anthocyanin content (mg·g-1 fw) in the berry skin of ‘Pinot Noir’ with and without shading
Anthocyanins | Non-shaded | Shaded |
---|---|---|
Delphinidin 3-glucoside | 0.02 ± 0.007 | 0.01 ± 0.001 |
Cyanidin 3-glucoside | 0.01 ± 0.002 | 0.00 ± 0.000 |
Petunidin 3-glucoside | 0.04 ± 0.010 | 0.02 ± 0.003 |
Peonidin 3-glucoside | 0.15 ± 0.010 | 0.14 ± 0.023 |
Malvidin 3-glucoside | 0.58 ± 0.100 | 0.61 ± 0.095 |
Total contents | 0.80 ± 0.134 | 0.78 ± 0.116 |
The transcript level of the structural genes and transcriptional factors involved in anthocyanin biosynthesis as revealed by microarray analysis is presented in Table 2. The log2 ratio of non-shaded to that of shaded revealed that majority of the flavonoid/anthocyanin biosynthesis genes were down regulated, and this effect was much pronounced in red grape Pinot Noir compared to that of white grape Pinot Blanc (Table 2). Among the flavonoid biosynthetic pathway genes such as
Table 2 Transcription level of major flavonoid biosynthetic genes as influenced by light condition
Probe ID | Accession no. | Gene name | PN-NS/PN-S | PB-NS/PB-S |
---|---|---|---|---|
CHR6_JGVV4_543_T01 | GU585850 | Phenylalanine ammonia-lyase 1 ( | -0.18938 | 0.876675 |
CHR13_JGVV19_80_T01 | BQ796207 | Phenylalanine ammonia-lyase 1 ( | 0.014164 | 0.309994 |
CHR14_JGVV68_88_T01 | AB015872 | Chalcone synthase-1 ( | 0.273898 | 0.822124 |
CHR14_JGVV68_87_T01 | AB066275 | Chalcone synthase-2 ( | 0.177767 | 1.194718 |
CHR5_JGVV136_15_T01 | AB066274 | Chalcone synthase-3 ( | -0.10565 | -0.07754 |
CHR6_JGVV61_85_T01 | CB971933 | Chalcone synthase | 1.044293 | 0.057527 |
CHR13_JGVV67_6_T01 | X75963 | Chalcone isomerase ( | -0.04321 | 0.468042 |
CHR18_JGVV1_214_T01 | AY257979 | Flavonol synthase ( | -0.61008 | -0.56749 |
CHR17_JGVV0_280_T01 | DQ786632 | Flavonoid 3’-hydroxylase ( | -0.20072 | 0.137538 |
CHR6_JGVV9_81_T01 | DQ786631 | Flavonoid 3’,5’-hydroxylase ( | -0.00846 | 0.034731 |
CHR6_JGVV9_83_T01 | BM437829 | Flavonoid 3’,5’-hydroxylase | 0.072886 | 0.144696 |
CHR4_JGVV23_54_T01 | X75965 | Flavanone-3-hydroxylase ( | 0.222199 | -0.20184 |
CHR18_JGVV1_1071_T01 | GU585859 | Flavanone-3-hydroxylase 2 ( | 0.05915 | 0.626465 |
CHR18_JGVV1_928_T01 | X75964 | Dihydroflavonol reductase ( | 0.239058 | 0.073193 |
CHR2_JGVV25_429_T01 | X75966 | Leucoanthocyanidin dioxygenase ( | 0.018039 | -0.05549 |
CHR1_JGVV11_360_T01 | AJ865335 | Leucoanthocyandin reductase ( | -0.01258 | -0.3349 |
CHR17_JGVV0_557_T01 | AB372550 | Leucoanthocyandin reductase ( | 0.192885 | 0.186066 |
CHRUN_JGVV361_4_T01 | DQ129684 | Anthocyanidin reductase ( | 0.750263 | 0.362415 |
CHR16_JGVV39_148_T01 | AF000372 | UDP glucose:flavonoid 3-O-glucosyltransferase ( | -0.2948 | -0.55772 |
CHR3_JGVV63_13_T01 | CF214966 | Caffeoyl-CoA O-methyltransferase | -0.5509 | 0.094469 |
CHR7_JGVV31_32_T01 | CB347033 | S-adenosylmethionine-dependent methyltransferase ( | -0.10558 | 0.031087 |
CHR1_JGVV10_262_T01 | GU237132 | Anthocyanin-O-methyltransferase ( | -0.29061 | 0.082774 |
CHR4_JGVV79_54_T01 | CF518071 | Glutathione S-transferase ( | -0.12097 | 0.01651 |
CHR12_JGVV28_290_T01 | CF517304 | Glutathione S-transferase ( | 0.025776 | 0.056984 |
CHR2_JGVV33_33_T01 | AB097923 | Myb-related transcription factor ( | 0.280151 | -0.02786 |
CHR2_JGVV33_30_T01 | CB915151 | My-related transcription factor ( | 0.390959 | 0.072633 |
CHR2_JGVV33_31_T01 | DQ886419 | 0.216586 | 0.185839 | |
CHR2_JGVV33_31_T01 | DQ886420 | 0.216586 | 0.185839 | |
CHR15_JGVV46_313_T01 | AM259485 | 0.071471 | 0.779112 | |
CHR11_JGVV16_111_T01 | EU919682 | -0.0553 | 0.223363 | |
CHR8_JGVV7_172_T01 | AY555190 | Myb transcription factor ( | 0.158022 | 0.43784 |
CHR6_JGVV4_726_T01 | AY899404 | -0.20858 | 0.106131 |
The suppression of anthocyanin biosynthesis genes such as
The microarray analysis also revealed that the genes such as
The results of qRT-PCR are shown in Fig. 2. One-way analysis of variance or multiple comparison was not carried out, since many data are not homoscedastic. However, it is obvious that the mRNA level of
As for
In contrast, mRNA of upstream genes, i.e.,
Among three isogenes of
Thus, isogenes of
Anthocyanin biosynthesis in the grape skin is controlled genetically and influenced by many factors such as light. Comparison of the mRNA levels of anthocyanin biosynthetic pathway genes in ‘Pinot Noir’ and ‘Pinot Blanc’ showed the decisive influence of
This research was supported by the grants from Japan Society for the Promotion of Science, Japan, to P. R. Poudel.
The authors declare that there is not any conflict of interest.
J Plant Biotechnol 2022; 49(4): 292-299
Published online December 31, 2022 https://doi.org/10.5010/JPB.2022.49.4.292
Copyright © The Korean Society of Plant Biotechnology.
Puspa Raj Poudel · Kazuya Koyama · Nami Goto-Yamamoto
National Research Institute of Brewing, 3-7-1 Kagamiyama, Higashi-Hiroshima 739-0046, Japan
Tribhuvan University, Institute of Agriculture and Animal Science, Paklihawa Campus, Siddharthanagar-1, Rupandehi, Lumbini, Nepal
Correspondence to:e-mail: poudelpuspa@yahoo.com, puspa.poudel@pakc.tu.edu.np
This is an Open-Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
Anthocyanin, an important component in the grape berry skin, strongly affects grape quality. The transcription factors VvMYBA1 and VvMYBA2 (VvMYBA1/2) control anthocyanin biosynthesis. In addition, cultivation and environmental factors, such as light, influence anthocyanin accumulation. The present study aimed to clarify the effect of shading (reduced light condition) on the transcriptomic regulation of anthocyanin biosynthesis using a red-wine grape cultivar, Vitis vinifera ‘Pinot Noir’, and its white mutant, ‘Pinot Blanc’, caused by the deletion of the red allele of VvMYBA1/2. The grape berry skins were analyzed for anthocyanin content and global gene transcription accumulation. The microarray data were later validated by quantitative real-time PCR. A decisive influence of VvMYBA1/2 on the expression of an anthocyanin-specific gene, UDP glucose: flavonoid 3-O-glucosyltransferase, was observed as expected. In contrast, upstream genes of the pathway, which are shared by other flavonoids, were also expressed in ‘Pinot Blanc’, and the mRNA levels of some of these genes decreased in both cultivars on shading. Thus, the involvement of light-sensitive transcription factor(s) other than VvMYBA1/2 was suggested for the expression control of the upstream genes of the anthocyanin biosynthetic pathway. Furthermore, it was suggested that the effects of these factors are different among isogenes.
Keywords: flavonoids, gene expression, shading, VvMYBAs
The quality of grape and grape products such as juice and wine largely depends on the amount and composition of flavonoid phenolics, i.e., anthocyanins, proanthocyanidins and flavonols, in the grape berries. Proanthocyanidins, or condensed tannins, contribute to astringency, whereas anthocyanins are responsible for their color. The accumulation of anthocyanins in grape berry skins starts from veraison and increases gradually until just before full maturity. On the other hand, the proanthocyanidins start to accumulate soon after the berry formation and decline during ripening (Downey et al. 2003a). Another flavonoid group, flavonols, is synthesized around flowering and mainly during ripening in the skin (Downey et al. 2003b). These flavonoid compounds are synthesized through the multi-step phenylpropanoid pathway (Fig. 1). The expression of structural genes in the phenylpropanoid pathway is controlled by transcription factors. For example, the expression of the genes specific for anthocyanin biosynthesis such as
To study the function of
In addition to the genetic control, anthocyanins accumulation in grape berry skins depends on various viticultural factors such as canopy management and irrigation, as well as environmental factors such as temperature and light (Brillante et al. 2018; Goto-Yamamoto et al. 2010; Koyama and Goto-Yamamoto 2008; Mori et al. 2007; Poudel et al. 2009; Yang et al. 2020). Among these factors, light is one of the important abiotic factors that regulate the synthesis of flavonoid compounds in grape berries. It has been demonstrated that a shading condition reduced the amount of anthocyanin and mRNA level of anthocyanin-pathway genes (Jeong et al. 2004). However, its control mechanism is not fully understood. Thus, in order to know if only
To determine the influence of light on transcriptomic changes in the skin of grape berries during ripening, the ‘Pinot Noir’ and ‘Pinot Blanc’ grapevines cultivated at the National Research Institute of Brewing, Higashi-Hiroshima, Japan were used. Branches facing the same direction from north to south orientation rows were taken for both treatments. A single bunch was taken as a replicate and nine bunches from three grapevines of each cultivar with similar size and berry numbers at veraison were selected and covered with three layers of Victoria lawn. This shading treatment reduced the light intensity during the daytime to 18%-20% (Jeong et al. 2004). The non-shaded bunches of the same grapevines were taken as the control. To confirm the temperature variation between shaded and non-shaded bunches, the daytime temperature was measured at 16:00, and it was revealed that shading had a negligible effect on temperature during the daytime. Three bunches each were sampled at veraison, two weeks after veraison (WAV) and 4 WAV. For each replicate (n = 3), 30 berries were collected randomly. The skins peeled from the 30 berries were immediately frozen in liquid nitrogen and kept at -80°C until use. The frozen skins were crushed for homogenization and used for RNA extraction and anthocyanin quantification. The results of 4 WAV of non-shaded ‘Pinot Noir’ and ‘Pinot Blanc’ were used in another publication with a different objective (Poudel et al. 2021), hence those data are not presented in this paper and used for discussion purpose only.
Anthocyanin was extracted from 0.2 g of berry skin in 2.5 mL of 2% formic acid in 70% methanol (v/v) solution for 20 min with sonication. A total of 400 µL aliquot was used for HPLC analysis after centrifugation at 15,000 rpm for 10 min and filtration with a 0.45 µM micro-membrane filter (Toyo Roshi Kaisha Ltd., Japan). The anthocyanin quantification method used in this study was similar to those described by Ali and Strommer (2003). A Hewlett Packard Series 1100 HPLC system and a Zorbax SB-C18 (5 µm, 2.1 × 150 mm) column were used to separate and quantify the anthocyanin based on peak area. The total anthocyanin concentration was expressed as a milligram of malvidin-3-glucoside (Extrasynthese, France) equivalents per gram of fresh berry skin weight.
Total RNA from berry skins for qRT-PCR was isolated according to the protocol reported by Reid et al. (2006) and purified using an RNeasy Plant Mini Kit (Qiagen, USA) following the manufacturer’s protocol. The total RNA isolated from 1 g of berry skin was quality assessed and quantified using a NanoDrop ND-1000 spectrophotometer (NanoDrop Technologies, USA) as well as an RNA Nano chip and RNA 6000 Nano Assay on an Agilent 2100 Bioanalyzer (Agilent Technologies, USA).
Microarray and q-PCR analysis methods used in this experiment were identical as those described in our previous study (Poudel et al. 2020). Briefly, for microarray analysis, complementary DNA (cDNA) was synthesized from a total of 10 µg total RNA. The cDNA was cleaned up, quantified, quality assessed and used for hybridization after labelling with Cy3-Random Nonamers (Roche NimbleGen Inc., USA). The hybridization was done with 4 µg Cy3 labelled cDNA to a NimbleGen gene expression 12 × 135 K array (Roche NimbleGen Inc., USA) according to the manufacturer’s protocol. The image data were acquired and analysed using NimbleGen MS 200 software. The data analysis was performed using GeneSpring software. To extract the differentially expressed genes, we applied a > 3.5 fold cut off. The signal intensities obtained from different replicates were averaged and the ratio between the average signal intensities of shaded to that of non-shaded was calculated. Additionally, to further extract the genes with significantly differentially expressed, a t-test was applied assuming the equal variance (< 0.05).
To determine mRNA levels of the anthocyanin pathway and related genes, qRT-PCR was carried out as described in our previous study (Poudel et al. 2020). Briefly, the qRT-PCR mixture was prepared with cDNA, upper and lower primers (Poudel et al. 2021) and SYBR Green Master Mix (Qiagen), and the final volume was adjusted to 20 µL with RNase-free water. The reaction was performed in a StepOnePlus real-time PCR system and StepOne software version 2.1 (Applied Biosystem, USA). The reaction condition was 95°C for 15 min, followed by 40 cycles at 95°C for 15 s, at each annealing temperature for 20 s and at 72°C for 20 s. The reaction was performed in at least three biological replicates and three analytical replicates for each prepared cDNA sample. The average data were normalized to the ubiquitin control gene.
The bunch-shading treatment was applied at veraison, the grape berries were sampled at 2 WAV and their anthocyanin compositions were analyzed using ‘Pinot Noir’. The shading treatment slightly affected the concentration of anthocyanin at 2 WAV (Table 1). However, the data on anthocyanin content were not different significantly at
Table 1 . Anthocyanin content (mg·g-1 fw) in the berry skin of ‘Pinot Noir’ with and without shading.
Anthocyanins | Non-shaded | Shaded |
---|---|---|
Delphinidin 3-glucoside | 0.02 ± 0.007 | 0.01 ± 0.001 |
Cyanidin 3-glucoside | 0.01 ± 0.002 | 0.00 ± 0.000 |
Petunidin 3-glucoside | 0.04 ± 0.010 | 0.02 ± 0.003 |
Peonidin 3-glucoside | 0.15 ± 0.010 | 0.14 ± 0.023 |
Malvidin 3-glucoside | 0.58 ± 0.100 | 0.61 ± 0.095 |
Total contents | 0.80 ± 0.134 | 0.78 ± 0.116 |
The transcript level of the structural genes and transcriptional factors involved in anthocyanin biosynthesis as revealed by microarray analysis is presented in Table 2. The log2 ratio of non-shaded to that of shaded revealed that majority of the flavonoid/anthocyanin biosynthesis genes were down regulated, and this effect was much pronounced in red grape Pinot Noir compared to that of white grape Pinot Blanc (Table 2). Among the flavonoid biosynthetic pathway genes such as
Table 2 . Transcription level of major flavonoid biosynthetic genes as influenced by light condition.
Probe ID | Accession no. | Gene name | PN-NS/PN-S | PB-NS/PB-S |
---|---|---|---|---|
CHR6_JGVV4_543_T01 | GU585850 | Phenylalanine ammonia-lyase 1 ( | -0.18938 | 0.876675 |
CHR13_JGVV19_80_T01 | BQ796207 | Phenylalanine ammonia-lyase 1 ( | 0.014164 | 0.309994 |
CHR14_JGVV68_88_T01 | AB015872 | Chalcone synthase-1 ( | 0.273898 | 0.822124 |
CHR14_JGVV68_87_T01 | AB066275 | Chalcone synthase-2 ( | 0.177767 | 1.194718 |
CHR5_JGVV136_15_T01 | AB066274 | Chalcone synthase-3 ( | -0.10565 | -0.07754 |
CHR6_JGVV61_85_T01 | CB971933 | Chalcone synthase | 1.044293 | 0.057527 |
CHR13_JGVV67_6_T01 | X75963 | Chalcone isomerase ( | -0.04321 | 0.468042 |
CHR18_JGVV1_214_T01 | AY257979 | Flavonol synthase ( | -0.61008 | -0.56749 |
CHR17_JGVV0_280_T01 | DQ786632 | Flavonoid 3’-hydroxylase ( | -0.20072 | 0.137538 |
CHR6_JGVV9_81_T01 | DQ786631 | Flavonoid 3’,5’-hydroxylase ( | -0.00846 | 0.034731 |
CHR6_JGVV9_83_T01 | BM437829 | Flavonoid 3’,5’-hydroxylase | 0.072886 | 0.144696 |
CHR4_JGVV23_54_T01 | X75965 | Flavanone-3-hydroxylase ( | 0.222199 | -0.20184 |
CHR18_JGVV1_1071_T01 | GU585859 | Flavanone-3-hydroxylase 2 ( | 0.05915 | 0.626465 |
CHR18_JGVV1_928_T01 | X75964 | Dihydroflavonol reductase ( | 0.239058 | 0.073193 |
CHR2_JGVV25_429_T01 | X75966 | Leucoanthocyanidin dioxygenase ( | 0.018039 | -0.05549 |
CHR1_JGVV11_360_T01 | AJ865335 | Leucoanthocyandin reductase ( | -0.01258 | -0.3349 |
CHR17_JGVV0_557_T01 | AB372550 | Leucoanthocyandin reductase ( | 0.192885 | 0.186066 |
CHRUN_JGVV361_4_T01 | DQ129684 | Anthocyanidin reductase ( | 0.750263 | 0.362415 |
CHR16_JGVV39_148_T01 | AF000372 | UDP glucose:flavonoid 3-O-glucosyltransferase ( | -0.2948 | -0.55772 |
CHR3_JGVV63_13_T01 | CF214966 | Caffeoyl-CoA O-methyltransferase | -0.5509 | 0.094469 |
CHR7_JGVV31_32_T01 | CB347033 | S-adenosylmethionine-dependent methyltransferase ( | -0.10558 | 0.031087 |
CHR1_JGVV10_262_T01 | GU237132 | Anthocyanin-O-methyltransferase ( | -0.29061 | 0.082774 |
CHR4_JGVV79_54_T01 | CF518071 | Glutathione S-transferase ( | -0.12097 | 0.01651 |
CHR12_JGVV28_290_T01 | CF517304 | Glutathione S-transferase ( | 0.025776 | 0.056984 |
CHR2_JGVV33_33_T01 | AB097923 | Myb-related transcription factor ( | 0.280151 | -0.02786 |
CHR2_JGVV33_30_T01 | CB915151 | My-related transcription factor ( | 0.390959 | 0.072633 |
CHR2_JGVV33_31_T01 | DQ886419 | 0.216586 | 0.185839 | |
CHR2_JGVV33_31_T01 | DQ886420 | 0.216586 | 0.185839 | |
CHR15_JGVV46_313_T01 | AM259485 | 0.071471 | 0.779112 | |
CHR11_JGVV16_111_T01 | EU919682 | -0.0553 | 0.223363 | |
CHR8_JGVV7_172_T01 | AY555190 | Myb transcription factor ( | 0.158022 | 0.43784 |
CHR6_JGVV4_726_T01 | AY899404 | -0.20858 | 0.106131 |
The suppression of anthocyanin biosynthesis genes such as
The microarray analysis also revealed that the genes such as
The results of qRT-PCR are shown in Fig. 2. One-way analysis of variance or multiple comparison was not carried out, since many data are not homoscedastic. However, it is obvious that the mRNA level of
As for
In contrast, mRNA of upstream genes, i.e.,
Among three isogenes of
Thus, isogenes of
Anthocyanin biosynthesis in the grape skin is controlled genetically and influenced by many factors such as light. Comparison of the mRNA levels of anthocyanin biosynthetic pathway genes in ‘Pinot Noir’ and ‘Pinot Blanc’ showed the decisive influence of
This research was supported by the grants from Japan Society for the Promotion of Science, Japan, to P. R. Poudel.
The authors declare that there is not any conflict of interest.
Table 1 . Anthocyanin content (mg·g-1 fw) in the berry skin of ‘Pinot Noir’ with and without shading.
Anthocyanins | Non-shaded | Shaded |
---|---|---|
Delphinidin 3-glucoside | 0.02 ± 0.007 | 0.01 ± 0.001 |
Cyanidin 3-glucoside | 0.01 ± 0.002 | 0.00 ± 0.000 |
Petunidin 3-glucoside | 0.04 ± 0.010 | 0.02 ± 0.003 |
Peonidin 3-glucoside | 0.15 ± 0.010 | 0.14 ± 0.023 |
Malvidin 3-glucoside | 0.58 ± 0.100 | 0.61 ± 0.095 |
Total contents | 0.80 ± 0.134 | 0.78 ± 0.116 |
Table 2 . Transcription level of major flavonoid biosynthetic genes as influenced by light condition.
Probe ID | Accession no. | Gene name | PN-NS/PN-S | PB-NS/PB-S |
---|---|---|---|---|
CHR6_JGVV4_543_T01 | GU585850 | Phenylalanine ammonia-lyase 1 ( | -0.18938 | 0.876675 |
CHR13_JGVV19_80_T01 | BQ796207 | Phenylalanine ammonia-lyase 1 ( | 0.014164 | 0.309994 |
CHR14_JGVV68_88_T01 | AB015872 | Chalcone synthase-1 ( | 0.273898 | 0.822124 |
CHR14_JGVV68_87_T01 | AB066275 | Chalcone synthase-2 ( | 0.177767 | 1.194718 |
CHR5_JGVV136_15_T01 | AB066274 | Chalcone synthase-3 ( | -0.10565 | -0.07754 |
CHR6_JGVV61_85_T01 | CB971933 | Chalcone synthase | 1.044293 | 0.057527 |
CHR13_JGVV67_6_T01 | X75963 | Chalcone isomerase ( | -0.04321 | 0.468042 |
CHR18_JGVV1_214_T01 | AY257979 | Flavonol synthase ( | -0.61008 | -0.56749 |
CHR17_JGVV0_280_T01 | DQ786632 | Flavonoid 3’-hydroxylase ( | -0.20072 | 0.137538 |
CHR6_JGVV9_81_T01 | DQ786631 | Flavonoid 3’,5’-hydroxylase ( | -0.00846 | 0.034731 |
CHR6_JGVV9_83_T01 | BM437829 | Flavonoid 3’,5’-hydroxylase | 0.072886 | 0.144696 |
CHR4_JGVV23_54_T01 | X75965 | Flavanone-3-hydroxylase ( | 0.222199 | -0.20184 |
CHR18_JGVV1_1071_T01 | GU585859 | Flavanone-3-hydroxylase 2 ( | 0.05915 | 0.626465 |
CHR18_JGVV1_928_T01 | X75964 | Dihydroflavonol reductase ( | 0.239058 | 0.073193 |
CHR2_JGVV25_429_T01 | X75966 | Leucoanthocyanidin dioxygenase ( | 0.018039 | -0.05549 |
CHR1_JGVV11_360_T01 | AJ865335 | Leucoanthocyandin reductase ( | -0.01258 | -0.3349 |
CHR17_JGVV0_557_T01 | AB372550 | Leucoanthocyandin reductase ( | 0.192885 | 0.186066 |
CHRUN_JGVV361_4_T01 | DQ129684 | Anthocyanidin reductase ( | 0.750263 | 0.362415 |
CHR16_JGVV39_148_T01 | AF000372 | UDP glucose:flavonoid 3-O-glucosyltransferase ( | -0.2948 | -0.55772 |
CHR3_JGVV63_13_T01 | CF214966 | Caffeoyl-CoA O-methyltransferase | -0.5509 | 0.094469 |
CHR7_JGVV31_32_T01 | CB347033 | S-adenosylmethionine-dependent methyltransferase ( | -0.10558 | 0.031087 |
CHR1_JGVV10_262_T01 | GU237132 | Anthocyanin-O-methyltransferase ( | -0.29061 | 0.082774 |
CHR4_JGVV79_54_T01 | CF518071 | Glutathione S-transferase ( | -0.12097 | 0.01651 |
CHR12_JGVV28_290_T01 | CF517304 | Glutathione S-transferase ( | 0.025776 | 0.056984 |
CHR2_JGVV33_33_T01 | AB097923 | Myb-related transcription factor ( | 0.280151 | -0.02786 |
CHR2_JGVV33_30_T01 | CB915151 | My-related transcription factor ( | 0.390959 | 0.072633 |
CHR2_JGVV33_31_T01 | DQ886419 | 0.216586 | 0.185839 | |
CHR2_JGVV33_31_T01 | DQ886420 | 0.216586 | 0.185839 | |
CHR15_JGVV46_313_T01 | AM259485 | 0.071471 | 0.779112 | |
CHR11_JGVV16_111_T01 | EU919682 | -0.0553 | 0.223363 | |
CHR8_JGVV7_172_T01 | AY555190 | Myb transcription factor ( | 0.158022 | 0.43784 |
CHR6_JGVV4_726_T01 | AY899404 | -0.20858 | 0.106131 |
Journal of
Plant Biotechnology