To characterize the dynamic changes in sugar and organic acid composition across three key developmental stages in 14 major blueberry cultivars currently cultivated in China, which differ markedly in ripening period and flavor profile, and to elucidate the relationship between PEPC and organic acid metabolism in blueberry fruit, thereby providing theoretical support for blueberry production and flavor quality improvement.

Fruits of 14 blueberry cultivars at three key ripening stages (green, pink, and blue) were used as materials. Soluble sugar and organic acid components were determined by HPLC, and the expression patterns of the PEPC gene were analyzed by qRT-PCR.

During fruit ripening, the accumulation dynamics of TA and TSS varied among different blueberry cultivars and could be classified into three acid-accumulation patterns (continuous decline, stable-decline, and increase-decline) and three sugar-accumulation patterns (continuous increase, stable-increase, and decline-increase). Glucose and fructose were the major soluble sugar components in blueberry fruits, whereas citric acid, quinic acid, and malic acid were the predominant organic acids. Among them, quinic acid exhibited a relatively high coefficient of variation. Cluster analysis based on sugar and organic acid composition divided the 14 cultivars into four groups. In four cultivars, the major organic acids were citric acid, quinic acid, and malic acid; seven cultivars were dominated by citric acid and malic acid; and one cultivar was characterized primarily by citric acid and quinic acid. In these 12 cultivars, the proportions of glucose and fructose were relatively balanced. In contrast, the remaining two cultivars showed a clear predominance of quinic acid, with fructose content significantly higher than that of glucose. Total sugar content in blueberry fruits was significantly positively correlated with glucose and fructose contents, while total organic acid content was extremely significantly positively correlated with the contents of citric acid, quinic acid, oxalic acid, and lactic acid. In the three blueberry cultivars representing different acid-accumulation patterns, PEPC expression increased from the green fruit stage to the pink fruit stage, but was downregulated from the pink fruit stage to the blue fruit stage. During this latter period, the contents of malic acid and citric acid in the fruits also decreased correspondingly.

During blueberry fruit development, the variation patterns of TA and TSS were closely associated with cultivar characteristics. The major soluble sugar components were glucose and fructose, while the predominant organic acids were citric acid, quinic acid, and malic acid. Based on organic acid composition, the cultivars could be categorized into two types: high-citric-acid and high-quinic-acid types. In three blueberry cultivars representing different acid-accumulation patterns, PEPC expression was downregulated from the pink fruit stage to the blue fruit stage, which was consistent with the declining trends of malic acid and citric acid contents, indicating that PEPC is involved in the metabolism of organic acids in blueberry fruits.

The aim of this study was to perform genotyping and genetic diversity analysis of 79 germplasms taken from National Fruit Germplasm Nanjing Peach Resource Nursery by using SSR fluorescent-labeled capillary electrophoresis technology, and to screen primers with high polymorphism, which could be used for identification of peach varieties and genetic relationship analysis and also be used for the establishment of molecular marker-assisted selection system.

De novo sequencing was performed on the female parent Zhongyou No. 4, and SSR markers were developed in the whole genome with a physical distance of 1 Mb as the unit. 79 peach varieties in Nanjing were used as materials for PCR amplification, and the amplified products were detected by polyacrylamide gel electrophoresis and screened for markers with clear target bands and abundant polymorphisms. The 5' end of the screened markers were fluorescently modified, and the PCR products were sequenced on the ABI3730XL sequencer to realize the rescreening of the markers. Genmapper 4.0 software was used to count the sequencing results, and Data Formater 2.1 software converted the bp data obtained by statistics into the data format required by Power Marker v3.25. The selected primers were analyzed for polymorphism, and the fluorescent SSR primers with polymorphism information content (PIC) greater than 0.45 were selected as the core primers of 79 germplasm materials. Using Nei's as a parameter, the UPDM clustering method in NTSYSpc 2.1 software was used to analyze the genetic diversity among cultivars. The Structure v2.3.4 software based on Bayesian model was used to analyze the population genetic structure of 79 accessions.

Based on 79 germplasms, the SSR markers covering the whole gene were screened by polyacrylamide gel electrophoresis, and 207 pairs of primers with good polymorphism were screened out. The 207 pairs of primers were re-screened by SSR fluorescent-labeled capillary electrophoresis technology, and 26 pairs of core primers were finally screened, of which 5 pairs of core primers could completely distinguish 79 varieties. 26 pairs of SSR core primers amplified a total of 174 polymorphic genotypes in 79 peach germplasms, and each pair of primers were amplified 4-13 genotypes, with an average of 6.69 genotypes amplified per pair of primers. The polymorphism information content PIC of each pair of primers was above 0.45. Based on the locus information amplified by 207 pairs of SSR primers in 79 accessions, the genetic relationship map and population genetic structure map of 79 accessions were constructed. 207 pairs of primers divided 79 accessions into 7 groups based on genetic distance and 2 groups based on population structure. The genetic diversity of 79 cultivars was high, and the clustering results of some cultivars were consistent with the pedigree.

The cluster analysis map and population genetic structure map of 79 materials were constructed, revealing the genetic relationship of 79 materials to a certain extent. The overall results showed that due to the complex genetic background of peach, the cultivars according to a single characteristic or determine the relationship between cultivars could not be classified. The screened 26 pairs of core primers could be used for genome-wide identification of linked traits, identification of peach germplasm resources, identification and protection of new varieties, and construction of molecular marker-assisted breeding systems.