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Background

Cold resistance is an important characteristic of sustainable development in the grape industry. Analyzing cold resistance genes provides molecular theoretical support for high-quality cold resistance breeding through cross breeding between grape varieties. The intraspecific recurrent selection in Vitis vinifera (V. vinifera) method uses high-quality varieties as breeding materials, and utilizes the substitution and accumulation of minor resistance genes, which is an effective method for high-quality grape disease resistance breeding.

Results

This study aimed to identify and genetically analyze the cold resistance of the V. viniferahybrid population (Ecolly x Dunkelfelder), screen for highly resistant and sensitive plant samples, and use high-throughput sequencing to perform transcriptome sequencing and related differential gene expression analysis on each sample. The results showed that the cold resistance of the hybrid offspring population was a continuous quantitative trait inheritance, with 38 differentially expressed genes (7 upregulated genes and 31 downregulated genes) between the high resistance and sensitive types. GO enrichment analysis showed that differential genes were mainly enriched in the biosynthesis process of aromatic compounds, organic cyclic compounds, transcription cis regulatory region binding, transcription regulatory region nucleic acid binding, sequence specific double stranded DNA binding, double stranded DNA binding, and sequence specific DNA binding. KEGG analysis revealed differentially expressed genes, with pathways mainly enriched in the biosynthesis pathways of hexene, diarylheptanoid and gingerol, flavonoid biosynthesis, glycerophospholipid metabolism, and phenylpropanoid biosynthesis.

Conclusion

Through the analysis of cold resistance related genes in various pathways, it was found that the cold resistance genes of V. vinifera were mainly related to secondary metabolites, lipid, carbohydrate, amino acid synthesis metabolism, and transcription factor regulation.

As a temperate crop, vitis have high nutritional value and economic benefits, and their growth conditions require high light and suitable temperature [1]. The low temperature and cold weather in winter affect the healthy development of the grape industry. Traditional soil burial and cold prevention techniques not only cause surface damage and soil wind erosion, but also increase labor costs, leading to a decline in market competitiveness [2, 3]. Different grape varieties have different cold tolerance, so hybrid breeding is a conventional method of grape breeding, and it is also the main way of breeding cold resistant grapes at present. The cold resistance of grape plants mainly exists in wild mountain grape varieties [4], Vitis riparia, Vitis labrusca, and the interspecific hybrid offspring of these grapes [5]. However, the traditional breeding method for cold resistance mainly involves simple interspecific hybridization, which neglects the quality improvement of hybrid offspring. The fruit quality of interspecific hybridization is more inclined towards cold resistant parents and is not suitable for large-scale promotion [6, 7]. The fruit quality of V. vinifera is excellent. Although they exhibit low resistance or sensitivity to cold, there are differences in cold resistance among varieties. The reason for this difference is the existence of multiple genes with slight cold resistance in Eurasian grape varieties, which can be stably inherited [8, 9]. The use of Vitis. vinifera (V. vinifera) intraspecific recurrent selection method can ensure continuous improvement of cold resistance in breeding materials and the breeding of high-quality cold resistant new varieties while ensuring high-quality fruit quality.

The cold resistance of grapes is comprehensively constrained by their own structure and external conditions, and is a quantitative trait controlled by micro effect multi genes [10]. This type of gene is rapidly expressed in grape plants when they sense cold signals, improving their cold tolerance and being regulated by multiple pathways [11]. Cold resistance functional genes regulate cold resistance by synthesizing corresponding functional proteins, such as cold regulated genes (COR), plant antifreeze protein (AFP) genes, fatty acid desaturase (FAD) genes, and osmoregulation related genes. The phospholipid binding protein gene VvBAP1 in Eurasian grapes can enhance the activity of antioxidant enzymes (SOD and POD) by regulating and controlling soluble sugar content, thereby enhancing the cold resistance of grapes [12]. The accumulation of ABA in woody tissue during grape cold acclimation upregulates the grape raffinose family gene VivRafS5, leading to the synthesis of raffinose [13]; Overexpressed late embryo enriched protein (LEA) family gene VamDHN3 participates in the adaptive response of grapes to cold and osmotic stress by enhancing the stability of grape cell membranes [14]. Several types of transcription factors have been isolated and identified to participate in plant responses to cold stress, including WRKY family transcription factors, MYB family transcription factors, bHLH type transcription factors [15–17]. Overexpression of the transcription factor genes mentioned above can activate the expression of downstream genes and improve plant cold resistance. Low temperature can promote the release of ethylene (ET), and endogenous ET can enhance the cold resistance of grapes. The ERF transcription factor VaERF057 is located downstream of the ET signaling pathway and is considered a positive regulator of cold tolerance [18].

In order to fully utilize the micro effective cold resistance multi genes present in V. vinifera and select high-quality cold resistance new varieties, we used high-quality V. vinifera hybrid varieties "Ecolly" and "Dunkelfelder" as breeding intermediate materials to continue intra specific hybridization, and identified and genetically analyzed the cold resistance of the hybrid offspring. Selecting plants with high cold resistance and sensitivity under natural conditions for transcriptomic analysis, starting from the synthesis and metabolism of secondary metabolites, lipids, carbohydrates, and amino acids, as well as transcription factors, to explore the expression differences of micro effective cold resistance genes in V. vinifera, providing molecular theoretical references for the selection of high-quality cold resistance varieties through V. vinifera intraspecific recurrent selection.

Genetic analyses of the hybrid parents ECL and DKF, as well as the cross progeny populations, using the results of differential thermal analysis (DTA) in two consecutive overwintering seasons, showed that there was no significant difference in cold tolerance between the hybrid parents ECL and DKF between different years (Fig. 1A). The mHTE values of the winter buds of ECL were lower than those of DKF in both overwintering seasons. Genetic analysis of the winter bud mHTE values of the hybrid populations in the two overwintering seasons showed that the winter bud mHTE values of the progeny populations of the hybrid combinations showed a skewed normal distribution, which was characterized by the inheritance of quantitative traits under the control of multiple genes (Fig. 1B, 1C). The mHTE values of this population were distributed from − 14℃ to -7℃, and the cold resistance class was determined to be in five classes of high resistance, resistance, middle resistance, low resistance and sensitivity based on the average affiliation value. Therefore, in the subsequent transcriptomics experiments, representative plant samples were selected for analysis in the two classes of high resistance (Group C) and sensitivity (Group D), respectively (Table 1).

The result of electrophoresis of 4 grape treated samples (Group C, Group D) showed that the RNA of all samples was intact, which could be used in follow-up experiments. As shown in the Table 2, clean data for all samples was obtained from the cDNA library, with clean data greater than 7G per sample. The proportion of Q20 and Q30 bases were more than 96.8% and 90% respectively, and the GC content was between 45% and 46%. A large number of FM indexes were used to cover the whole genome, and the reads from RNA-seq were quickly and accurately compared with the genome by HISAT2, it was found that the proportion of the sequenced reads successfully aligned to the genome was higher than 87%. In order to determine the reliability of the samples, the correlation analysis of the biological replicates of each group was carried out. The results showed that the correlations between the replicates were all R²≥98%, which further indicated that the transcriptome sequencing quality was high and the samples were reliable, available for follow-up analysis.

For the overall quality assessment of RNA-seq to further understand the transcriptome differences between the high cold resistance group (Group C) and the control group (Group D) of V. vinifera, we performed the distribution and characteristics of the expression quantities FPKM across samples were also analyzed (Fig. 2A), and it was found that more than 50% of the genes in all samples had log10(FPKM) concentrated between 0 and 2, with the mean log10(FPKM) at positions around 1. Gene cold resistance classes were analyzed for both upregulated and downregulated DEGs overall, with log2fold-change > 1 and log2fold-change < -1, and FDR < 0.05. In this study, the transcription samples were compared and the differences of gene expression among grape plants with different resistance were presented. Between Group C and Group D, the total number of differential genes was 38, with 7 up-regulated and 31 down-regulated (Fig. 2B). The volcano plot shows the distribution of up-and down-regulated genes (Fig. 2C).

KEGG enrichment analysis of DEGs from both groups of plants (Fig. 4A) revealed co-distribution in two categories, including cellular processes and metabolic pathways. Cellular processes had differential genes only in the transport and catabolic pathways. Metabolic pathways had differential genes in lipid metabolism, metabolism of terpenoids and polyketides, biosynthesis of other secondary metabolites, carbohydrate metabolism, amino acid metabolism, metabolism of cofactors and vitamins, and metabolic pathways of other amino acids. KEGG functional enrichment analysis was performed for the two comparison groups, calculated to FDR values by a test of assumptions, and the top 20 FDR values were analyzed for significant levels of pathway enrichment (Fig. 4B). Pathways were mainly enriched in stilbenoid, diarylheptanoid and gingerol biosynthesis, flavonoid biosynthesis, glycerophospholipid metabolism and phenylpropanoid biosynthesis pathways.

There are 38 annotated genes in Group C and Group D, which encode spermidine hydroxycinnamoyl transferase, 1-deoxy-D-ketose-5-phosphate synthase 2, and gimerene D synthase and so on. KEGG enrichment analysis of the differential genes (Table 3) showed that they were mainly enriched in 8 pathways, effects of secondary metabolites, lipid metabolism, terpenes and polyketones metabolism, carbohydrate and amino acid transport and catabolism.

Plant cold resistance is a long-term adaptation to low temperature environment process, through natural selection and its own genetic variation to obtain cold resistance. The cold resistance of V. vinifera is distributed continuously and controlled by multi-genes. The difference of cold resistance between different plants may be controlled by minor gene in the comparison between the two groups of plants with different cold resistance, we carried out GO enrichment and KEGG enrichment analysis, and screened a number of different genes. According to this difference, we will analyze the expression of cold resistance genes in V. vinifera intraspecific hybrid population from the aspects of secondary metabolites, lipid metabolism, amino acid metabolism, carbohydrate metabolism and transcription factors.

Among the genes related to secondary metabolite anabolism, the expression level of Group C was significantly higher than that of Group D (Fig. 5A), the expression level of CYP76F14 gene in Group C was about twice that of S1024. Dxs and GERD genes were also expressed differently between the two groups, and Dxs was hardly expressed in Group D. the expression level of GERD gene in Group C was 6.3-fold higher than that in S1024, the amount of GERD gene expression in Group D was 6.3-fold higher for S1035 than for S1023. The VIT_00023653001 and VIT_00023651001 genes, which simultaneously regulate flavonoid biosynthesis, diphenylethene, diarylheptane and gingerol biosynthesis and phenylpropanoid biosynthesis, were only expressed in Group D, the expression level of S1023 was significantly higher than that of S1035.

Among the genes related to lipid metabolism, there were three differentially expressed genes (Fig. 5B). The gene encoding NMT was significantly higher in Group C than in Group D, and the gene encoding GDE1 was significantly higher in Group D than in Group C, genes encoding ACOX1; ACOX3 were only expressed in Group D. Among the genes related to cofactor and vitamin metabolism, only the Dxs gene showed differential expression, and only trace expression in Group D.

In this study, we identified two differentially expressed genes related to carbohydrate anabolism, and VIT_00018579001 coworkers regulate carbohydrate anabolism and amino acid metabolism. Overall, VIT_00018579001 gene expression in Group D was significantly higher than that in Group C, and almost no expression in Group C (Fig. 5C). The GLGC gene expression level in Group C was higher than that in Group D, and the S1022 gene expression level was 2-fold higher than that of S1024. The expression level of DHQ-SDH in Group C was significantly higher than that in Group D, and the expression level of S1024 was 3.2-fold higher than that of S1022.

The transcription factors identified in this study included MYB, HB and MADS families, and the transcription factors of these families were analyzed. A total of 1 MYB transcription factors were detected (Fig. 5D). The expression level of MYB transcription factor genes in two samples of Group C was significantly higher than that in Group D. Three transcription factors (VIT_00012250001, VIT_00018450001, VIT_00036549001 named MADS-1, MADS-2, MADS-3, respectively) were detected in the Mads family. Three transcription factors VIT_00009273001, VIT_00031241001 and VIT_00004811001 (named HB-1, HB-2 and HB-3, respectively) were also found in the two comparison groups, and no expression of HB-1 and HB-3 genes was detected in Group D, HB-2 was also only slightly expressed.