Transcriptomic and Metabolomic Profiling Reveals the Variations in Carbohydrate Metabolism between Two Blueberry Cultivars

Abstract

Blueberry is a high-quality fruit tree with significant nutritional and economic value, but the intricate mechanism of sugar accumulation in its fruit remains unclear. In this study, the ripe fruits of blueberry cultivars 'Anna' and 'Misty' were utilized as experimental materials, and physiological and multi-omics methodologies were applied to analyze the regulatory mechanisms of the difference in sugar content between them. The results demonstrated that the 'Anna' fruit was smaller and had less hardness than the 'Misty' fruit, as well as higher sugar content, antioxidant capability, and lower active substance content. A total of 7067 differentially expressed genes (DEGs) (3674 up-regulated and 3393 down-regulated) and 140 differentially abundant metabolites (DAMs) (82 up-regulated and 58 down-regulated) were identified between the fruits of the two cultivars. According to KEGG analysis, DEGs were primarily abundant in phenylpropanoid synthesis and hormone signal transduction pathways, whereas DAMs were primarily enriched in ascorbate and aldarate metabolism, phenylpropanoid biosynthesis, and the pentose phosphate pathway. A combined multi-omics study showed that 116 DEGs and 3 DAMs in starch and sucrose metabolism (48 DEGs and 1 DAM), glycolysis and gluconeogenesis (54 DEGs and 1 DAM), and the pentose phosphate pathway (14 DEGs and 1 DAM) were significantly enriched. These findings suggest that blueberries predominantly increase sugar accumulation by activating carbon metabolism network pathways. Moreover, we identified critical transcription factors linked to the sugar response. This study presents new understandings regarding the molecular mechanisms underlying blueberry sugar accumulation and will be helpful in improving blueberry fruit quality through breeding.

Keywords: blueberry; fruit quality; glycolysis/gluconeogenesis; pentose phosphate pathway; starch and sucrose metabolism; sugar accumulation.

Figure 1

Fruit appearance of ‘Anna’ and ‘Misty’ blueberry cultivars.

Figure 2

Antioxidant system, bioactive substances, and flavor indexes of ‘Anna’ and ‘Misty’ blueberry cultivars. (A) fruit weight, (B) transverse diameter, (C) vertical diameter, (D) the generation rate of O₂^·−, (E) H₂O₂ content, (F) MDA content, (G) SOD activity, (H) POD activity, (I) T-AOC, (J) fruit firmness, (K) total phenol content, (L) anthocyanin content, (M) ellagic acid content, (N) flavonoids content, (O) soluble solids content, (P) total acid content, (Q) solidity-acid ratio, (R) sucrose content, (S) glucose content, and (T) fructose content were measured in blueberry fruits. Columns with different letters indicate significant differences between ‘Anna’ and ‘Misty’ (p < 0.05).

Figure 3

Transcriptomic analysis of the ‘Anna’ and ‘Misty’ blueberry cultivars. (A) Venn diagram of all identified genes. (B) Volcano plot of all identified genes; red represents up-regulated genes, green represents down-regulated genes, and blue represents genes that did not change significantly. (C) The number of DEGs. (D) Heatmap of all identified genes.

Figure 4

GO enrichment analysis of the up-regulated DEGs (A) and down-regulated DEGs (B). KEGG enrichment analysis of the up-regulated DEGs (C) and down-regulated DEGs (D).

Figure 5

Number of DEGs involved in the top 20 TF families.

Figure 6

Metabolite profiling and classification using the HMDB, KEGG, and LIPID MAPS databases. The HMDB annotation of the metabolites in the positive (A) and negative (B) ion modes. The KEGG pathway annotation of the metabolites in the positive (C) and negative (D) ion modes. The LIPID MAPS annotation of the metabolites in the positive (E) and negative (F) ion modes.

Figure 7

KEGG enrichment analysis of DAMs in the positive (A) and negative (B) ion modes.

Figure 8

DAMs and DEGs association studies in starch and sucrose metabolism, glycolysis/gluconeogenesis, and the pentose phosphate pathway. The scales were generated using log₂ (fold change) values. The expression levels of DEGs and DAMs are shown from green to red and yellow to purple (low to high) in the comparison of ‘Anna’ vs. ‘Misty’, respectively. HXK, hexokinase; FRK, fructokinase; FOS, beta-fructofuranosidase; Gluc, glucan endo-1,3-beta-glucosidase; GCase, beta-glucosidase; EGase, endoglucanase; SPS, sucrose-phosphate synthase; SUS, sucrose synthase; PGM, phosphoglucomutase; AGPase, ADP-glucose pyrophosphorylase; TPS, trehalose 6-phosphate synthase; TPP, trehalose 6-phosphate phosphatase; TREH, alpha,alpha-trehalase; GBSS, granule-bound starch synthase; AMY, alpha-amylase; BAM, beta-amylase; ISA, isoamylase; SS, starch synthase; HK, hexokinase; AEP, aldose 1-epimerase; G6PE, glucose-6-phosphate 1-epimerase; FBPase, fructose-1,6-bisphosphatase; PFK, ATP-dependent phosphofructokinase; PFP, pyrophosphate-dependent fructose-6-phosphate phosphotransferase; FBA, fructose-bisphosphate aldolase; TPI, triosephosphate isomerase; G3PDH, glyceraldehyde 3-phosphate dehydrogenase; GAPDH, glyceraldehyde-3-phosphate dehydrogenase; PGK, phosphoglycerate kinase; PGAM, 2,3-bisphosphoglycerate-dependent phosphoglycerate mutase; ENO, enolase; PK, pyruvate kinase; PDHA1, pyruvate dehydrogenase E1 component subunit alpha; PDC, pyruvate decarboxylase; DLD, dihydrolipoyl dehydrogenase; AAE, butyrate-CoA ligase; ALDH, aldehyde dehydrogenase; ADH, alcohol dehydrogenase; AR, aldose reductase; GK, gluconokinase; G6PDH, glucose-6-phosphate 1-dehydrogenase; 6PGL, 6-phosphogluconolactonase; TA, transaldolase; RPI, ribose 5-phosphate isomerase A.