Data normalization is a key step in gene expression analysis by qPCR. Endogenous control genes are used to estimate variations and experimental errors occurring during sample preparation and expression measurements. However, the transcription level of the most commonly used reference genes can vary considerably in samples obtained from different individuals, tissues, developmental stages and under variable physiological conditions, resulting in a misinterpretation of the performance of the target gene(s). This issue has been scarcely approached in woody species such as grapevine.

Cherimoya (Annona cherimola Mill.) is a subtropical fruit characterized by a significant increase in organic acid levels during ripening, making it an interesting model for studying the relationship between acidity and fruit flavor. In this work, we focused on understanding the balance between the concentration of organic acids and the gene expression and activity of enzymes involved in the synthesis and degradation of these metabolites during the development and ripening of cherimoya cv. “Concha Lisa”. Our results showed an early accumulation of citric acid and other changes associated with the accumulation of transcripts encoding citrate catabolism enzymes. During ripening, a 2-fold increase in malic acid and a 6-fold increase in citric acid were detected. By comparing the contents of these compounds with gene expression and enzymatic activity levels, we determined that cytoplasmic NAD-dependent malate dehydrogenase (cyNAD-MDH) and mitochondrial citrate synthase (mCS) play important regulatory roles in the malic and citric acid biosynthetic pathways.

Berry size is considered as one of the main selection criteria in table grape breeding programs. However, this is a quantitative and polygenic trait, and its genetic determination is still poorly understood. Considering its economic importance, it is relevant to determine its genetic architecture and elucidate the mechanisms involved in its expression. To approach this issue, an RNA-Seq experiment based on Illumina platform was performed (14 libraries), including seedless segregants with contrasting phenotypes for berry weight at fruit setting (FST) and 6–8 mm berries (B68) phenological stages. A group of 526 differentially expressed (DE) genes were identified, by comparing seedless segregants with contrasting phenotypes for berry weight: 101 genes from the FST stage and 463 from the B68 stage. Also, we integrated differential expression, principal components analysis (PCA), correlations and network co-expression analyses to characterize the transcriptome profiling observed in segregants with contrasting phenotypes for berry weight. After this, 68 DE genes were selected as candidate genes, and seven candidate genes were validated by real time-PCR, confirming their expression profiles. We have carried out the first transcriptome analysis focused on table grape seedless segregants with contrasting phenotypes for berry weight. Our findings contributed to the understanding of the mechanisms involved in berry weight determination. Also, this comparative transcriptome profiling revealed candidate genes for berry weight which could be evaluated as selection tools in table grape breeding programs.