Auxin can inhibit or promote fruit ripening, depending on the species. Melting flesh (MF) peach fruit (Prunus persica L. Batsch) cultivars produce high levels of ethylene caused by high concentrations of indole-3-acetic acid (IAA), which leads to rapid fruit softening at the late stage of development. In contrast, due to the low concentrations of IAA, the fruit of stony hard (SH) peach cultivars does not soften and produces little ethylene. Auxin seems necessary to trigger the biosynthesis of ethylene in peach fruit; however, the mechanism is not well understood. In this study, we identified miRNA gene family members ppe-miR393a and ppe-miR393b that are differentially expressed in SH and MF fruits. RNA ligase-mediated 5′ rapid amplification of cDNA ends and transient transformation of Nicotiana benthamiana revealed TRANSPORT INHIBITOR RESPONSE 1 (PpTIR1), part of the auxin perception and response system, as a target of ppe-miR393a and b. Yeast 2-hybrid assay and bimolecular fluorescence complementation assay revealed that PpTIR1 physically interacts with an Aux/IAA protein PpIAA13. The results of yeast 1-hybrid assay, electrophoretic mobility shift assay, and dual-luciferase assay indicated that PpIAA13 could directly bind to and trans-activate the promoter of 1-aminocyclopropane-1-carboxylic acid synthase 1 (PpACS1), required for ethylene biosynthesis. Transient overexpression and suppression of ppe-miR393a and PpIAA13 in peach fruit induced and repressed the expression of PpACS1, confirming their regulatory role in ethylene synthesis. Gene expression analysis in developing MF and SH fruits, combined with postharvest α-naphthalene acetic acid (NAA) treatment, supports a role for a ppe-miR393-PpTIR1-PpIAA13-PpACS1 module in regulating auxin-related differences in ethylene production and softening extent in different types of peach.

Objectives: Ethylene plays a pivotal role in the processes of fruit ripening and senescence. Heat treatment has a significant impact on maintaining fruit quality and extending shelf life, while the precise mechanism by which heat treatment prolongs the storage life of melting peach remains to be elucidated. Materials and Methods: Two melting peach varieties, ‘Hujingmilu’ (HJML) and ‘Yulu’ (YL), were treated with hot water at 45 °C for 10 min to explore the effect of postharvest heat treatment during storage and its regulatory mechanism. Results: The enzymatic activities of polygalacturonase (PG) and 1-aminocyclopropane-1-carboxylate (ACC) oxidase (ACO) were inhibited by heat treatment, and the transcript level of PGM was reduced, while PpACO1 was not affected by heat treatment. Moreover, the protein abundance of PpACO1 was not inhibited by heat treatment. Interestingly, nitric oxide (NO) content significantly increased in heat-treated fruit as the S-nitrosylation level of total protein increased. An in vitro assay indicated that PpACO1 could be S-nitrosylated with a reduction of ACO enzymatic activity, suggesting that NO-mediated S-nitrosylation of PpACO1 may be involved in reducing ethylene emission by heat treatment. Conclusions: These findings demonstrated that postharvest heat treatment can lead to an increase in NO content, resulting in S-nitrosylation of PpACO1, thus slowing down endogenous ethylene production and effectively delaying postharvest ripening and softening of fruit.

Genotyping is a key step in molecular breeding. Due to its cost-effectiveness, accuracy, and flexibility, genotyping by target sequencing (GBTS) has become a preferred technology for medium-density genotyping. In this study, a new GBTS array for fresh edible maize was developed using resequencing data from 477 lines. The array contains 5759 SNPs evenly distributed across the maize genome, with average minor allele frequency (MAF) and polymorphism information content (PIC) values of 0.40 and 0.36, respectively. These SNPs are closely associated with 1566 functional genes. Cluster analysis of 198 maize lines based on the GBTS array was consistent with their pedigree relationships. Furthermore, 277 fresh waxy maize lines were genotyped and used for genomic selection analyses of hundred-kernel weight, kernel length, and kernel width. Comparative evaluation of different models indicated that Ridge Regression Best Linear Unbiased Prediction (rrBLUP) was the optimal model, with prediction accuracies of 0.33, 0.64, and 0.36, respectively. Additional analyses using different marker densities based on the rrBLUP model showed that prediction accuracy did not increase when the number of markers exceeded 2000, indicating that this array provides sufficient marker density for genetic analysis and genomic selection. Overall, this array provides a useful tool for genetic studies of fresh edible maize and facilitates the application of genomic selection in breeding programs.

Fruit texture variation in peach (Prunus persica L. Batsch), especially softening accompanied by the melting phase, directly affects marketability and storage. Two tandem endopolygalacturonase (endoPG) genes at the F–M locus, PGF and PGM, determine the melting or nonmelting trait, which is associated with the freestone or clingstone trait. In this study, freestone melting flesh (FMF), clingstone melting flesh (CMF), and clingstone nonmelting flesh (CNMF) cultivars were sampled across various developmental and postharvest stages. PGF–PGM haplotypes were identified using molecular markers, and their contributions to the FMF/CMF/CNMF phenotypes were investigated. In FMF peach, the FMF phenotypes were related to elevated PGF expression with spatiotemporal differences between the flesh near the stone at early developmental stages and the whole flesh at the postharvest stage. PpNAC74 and PpNAC87, specifically expressed in the flesh near skin or stone, cooperatively activated PGF transcription in FMF. Two PGM alleles, PGMSer and PGMPhe, exhibited functional divergence with increased expression of the former dominantly conferring the CMF phenotype, and the recessive PGMPhe determining the CNMF phenotype. PpNAC1–PpNAC72–PpNAC100 synergistically activated PGMSer transcription during ethylene-induced melting in CMF. Transient overexpression or silencing of these PpNACs induced or repressed the expression of target endoPGs and accelerated or delayed softening, respectively. Whole-genome bisulfite sequencing suggested that DNA methylation mediates the expression of key softening-related genes and thus participates in the regulation of the flesh melting and freestone traits. Our findings elucidate the genetic and molecular regulatory network diversification that determines flesh texture and stone adhesion in peach fruit.

Postharvest sucrose depletion severely limits the organoleptic quality and commercial value of sweet corn during ambient storage. To characterize the temporal transcriptional responses associated with cultivar-dependent sugar loss, ears of two supersweet corn hybrids, ‘Shenketian 811’ (SKT) and ‘Overland’ (AFL), were stored under monitored ambient conditions (24–26 °C) for 7 days. Kernel sugars, total soluble solids, whole-ear respiration rates, and transcriptomic profiles were assessed at five time points. Sucrose concentration declined from 77.9 to 30.9 μg mg⁻¹ fresh weight in SKT and from 80.3 to 20.3 μg mg⁻¹ fresh weight in AFL. Weighted gene co-expression network analysis (WGCNA), followed by within-cultivar module–trait analysis, identified one module positively and one negatively associated with sucrose concentration in both cultivars. Subsequent gene-level correlation analysis of the 1071 genes in these modules identified 571 non-redundant sucrose-associated genes, which were enriched in carbon metabolism, glycolysis/gluconeogenesis, the citrate cycle, and starch and sucrose metabolism. Pairwise differential-expression analysis further identified 194 genes showing recurrent storage-responsive or cultivar-dependent expression, of which five genes involved in sucrose cleavage or sucrose–starch interconversion were prioritized. Notably, the cell-wall invertase gene ZmINVCW1 exhibited a sustained AFL-biased expression pattern, which was validated by RT-qPCR, while total cell wall invertase activity was also significantly higher in AFL at multiple sampling points. This time-resolved analysis characterizes recurrent transcriptional responses associated with cultivar-dependent sucrose loss and provides a focused framework for further functional studies of postharvest sucrose retention.

Sweet corn is widely cultivated for fresh consumption and processing, and kernel size and weight are important yield-related traits. However, the genetic architecture of these traits in sweet corn remains poorly understood. In this study, the SHL01 × SHL03 recombinant inbred line (RIL) population was used to investigate the genetic basis of kernel size and weight-related traits using a high-density SNP-based genetic map. Quantitative trait loci (QTL) mapping was conducted in two environments and using the best linear unbiased estimates (BLUEs), followed by candidate-region association analysis to identify candidate genes. A total of 11 unique QTLs were identified from 12 detection records across the two environments and the BLUE dataset. Among them, seven unique QTLs, corresponding to eight detection records, were located on chromosome 7. Several QTLs were located near previously reported loci for kernel-related traits, suggesting a partially shared genetic basis between sweet corn and field corn. Candidate-region association analysis further characterized the major QTL regions and highlighted five potential candidate genes. Among them, Zm00001d020325 (HAK23), encoding a putative potassium transporter, was supported by functional annotation and available expression information, but its haplotypes were not significantly associated with HKW. In contrast, haplotypes defined by variants in neighboring Zm00001d020323 differed in HKW, with the GG haplotype showing the highest mean value. Because these analyses were conducted in overlapping populations, the haplotype results are exploratory. Together, these findings characterize genomic regions associated with mature-kernel traits in sweet corn and identify candidates for further validation.