Terpene synthase (TPS) is related to the production of aromatic substances, but there are few studies on the impact of abiotic stress on TPS and its molecular mechanism, especially in peaches. This study found that salt resistance and abscisic acid (ABA) sensitivity of transgenic tomatoes were enhanced by overexpression of PpTPS1. Moreover, it was found that PpTPS1 interacted with and antagonized the expression of the bZIP transcription factor ABA INSENSITIVE 5 (PpABI5), which is thought to play an important role in salt suitability. In addition, PpTCP1, PpTCP13, and PpTCP15 were found to activate the expression of PpTPS1 by yeast one-hybrid (Y1H) and dual-luciferase assays, and they could also be induced by ABA. In summary, PpTPS1 may be involved in the ABA signaling regulatory pathway and play an important role in salt acclimation, providing a new reference gene for the improvement of salt resistance in peaches.

Drought stress is a serious abiotic stress source that affects the growth and fruit quality of peach trees. However, the molecular mechanism of the NUDIX hydrolase family in peaches in response to drought stress is still unclear. Here, we isolated and identified the PpNUDX8 (Prupe.5G062300.1) gene from the peach NUDIX hydrolase family, and found that PpNUDX8 has a typical NUDIX hydrolase domain. In this study, we performed 15% PEG6000 drought treatment on peach seedlings, and qRT–PCR analysis showed that 15% PEG6000 induced the transcription level of PpNUDX8. Overexpression of PpNUDX8 reduced the tolerance of calli to 4% PEG6000 treatment. Compared with wild-type apple calli, PpNUDX8 transgenic apple calli had a lower fresh weight and higher MDA content. After 15% PEG6000 drought treatment, PpNUDX8 transgenic tobacco had a greater degree of wilting and shorter primary roots than Under control conditions. The chlorophyll, soluble protein, and proline contents in the transgenic tobacco decreased, and the MDA content and relative conductivity increased. At the same time, PpNUDX8 negatively regulated ABA signal transduction and reduced the transcriptional expression of stress response genes. In addition, PpNUDX8 was not sensitive to ABA, overexpression of PpNUDX8 reduced the expression of the ABA synthesis-related gene NCED6 and increases the expression of the ABA decomposition-related gene CYP1 in tobacco, which in turn leads to a decrease in the ABA content in tobacco. In addition, Under control conditions, overexpression of PpNUDX8 destroyed the homeostasis of NAD and reduced nicotinamide adenine dinucleotide (NADH) in tobacco. After 15% PEG6000 drought treatment, the changes in NAD and NADH in PpNUDX8 transgenic tobacco were more severe than those in WT tobacco. In addition, PpNUDX8 also interacted with PpSnRk1γ (Prupe.6G323700.1).

Introduction Because of its small genome size and relatively short juvenile period, peach (Prunus persica L.) is an important model species in the Rosaceae (Shulaev et al., 2008). Peach fruit can be classified as flat or round, with the flat shape being dominant over the round shape (Lesley, 1940). Previous linkage maps revealed that fruit shape is controlled by a S-locus that co-segregates with molecular markers MA040a and MA014a at the distal end of scaffold Pp06 (Dirlewanger et al., 2006). It has also been found that this S-locus was associated highly with SSR marker UDP98-412 (Picañol et al., 2013). Moreover, it has recently been reported that fruit shape variance is strongly associated with an A/T polymorphism at a locus located at 25,060,196 bp of scaffold Pp06. In addition, fruits with a homozygous T/T genotype at this locus are round, whereas fruits with heterozygous (A/T) and homozygous A/A genotypes at this locus are flat (Cao et al., 2016). Fruit shape has also been related to a 10kb deletion that affects the function of the leucine-rich receptor-like kinase (LRR-RLK) gene Prupe.6G281100 (López-Girona et al., 2017). The ortholog of this gene in Arabidopsis thaliana is responsible for regulating meristem size and organization (Mandel et al., 2016). Bud sports are a common somatic mutation found in many plant species, including fruit trees and provide many novel variants that can be bred by plant breeders. Fruit shape differences occasionally result from bud sports (López-Girona et al., 2017). Although previous studies have suggested that bud sports may occur both on the whole genome and individual gene levels (Foster and Aranzana, 2018) to date the precise molecular mechanisms responsible for bud sports that result in fruit-shape alteration are unknown. Loss of heterozygosity (LOH) events are common genetic events found in many types of cancer (Koufos et al., 1985; Yokota et al., 1987; Deng et al., 1996; Gatto et al., 2014; Muzumdar et al., 2016). Early studies that used microsatellite-based whole-genome analyses to study LOH events in cancer found that cancer progression often resulted from LOH events at particular loci (Koufos et al., 1985; Naylor et al., 1987; Emi et al., 1992). Later studies used SNP arrays to analyze LOH event prevalence in cancer cells, and found that extensive LOH occurrence was indicative of instability of the whole genome rather at individual loci (Lindblad-Toh et al., 2000). In contrast to cancer biology, few LOH events have been documented in plants. Wang et al. (1999) reported an LOH event that occurred at a specific locus in F1 rice hybrid plants, and Xu et al. (2007) used whole genome data for rice hybrids to identify LOH events in F1 progeny. A third report studied LOH events in Arabidopsis thaliana regenerants, and found that LOH events had occurred at individual loci distributed across three of five scaffolds of the A. thaliana genome (Zimina et al., 2016). LOH events have also been documented at the berry colour locus in grapevine (Vezzulli et al., 2012; Pelsy et al., 2015; Carbonell-Bejerano et al., 2017; Migliaro et al., 2017). Since markers can provide information about the sequences flanking LOH loci, the availability of new genetic markers can help to more efficiently explore LOH events in plants. NGS methods, which can provide hundreds of millions of informative SNP markers for genetic studies (Metzker, 2010), have been used to study peach domestication and to characterize the genetic differences between peach varieties (Verde et al., 2013; Cao et al., 2014). In addition, GWAS analyses are now commonly used to examine the genetic variance responsible for important agronomic traits in Arabidopsis thaliana (Atwell et al., 2010), rice (Huang et al., 2010), and peach (Micheletti et al., 2015; Cao et al., 2016) In this study, we used an NGS-focused approach to study genomic differences between flat peach and its bud sport genome. We obtained an SNP set that we used to explore the genomic mechanism responsible for fruit shape variance in the bud sport. In addition, a GWAS was performed to relate genetic variance to fruit shape variance in cultivated peach. Finally, we discuss the possible mechanisms that may be responsible for the LOH event that we identify as determining fruit shape. Materials and methodsPlant materials A single eight-year-old specimen of the flat peach cultivar ‘Zhaoyue’ (P. persica L.) was grown in the orchard of the experimental station of Shandong Agriculture University, Taian, China. The base of one branch of this tree produces normal flat-shaped fruit while the top of the same branch bears round-shaped fruit (Supplementary Figure S1). The focal tree was maintained as other peach trees in the orchard were. The bud sport was stable for at least three years. Sample collection and DNA extraction To avoiding sampling chimeras, we selected only fruits produced at locations far from the intermediary shoots that contained both round and flat peaches. Thus we obtained a bud sport-type sample by selecting round-type fruit from the topmost branches (indicated by label 7 of Figure 1), while wild-type flat fruits were sampled from the bottommost branches (indicated by label 1 of Figure 1). More than 50 healthy fruits were collected from both wild-type and bud sport mutant shoots approximately 90 days after flowering, which is when fruit shape is definitively established. Fruit mesocarps from five or more fruits were pooled for both the wild-type and bud sport mutant samples. Mesocarps and not leaves were sampled since the mesocarp develops only from LII layer cells. At least 10 biological duplicates were obtained for both samples. All samples were frozen in liquid nitrogen and stored at -80°C for later DNA extraction. DNA was extracted from each sample using a Tiangen DNA extraction kit, as per the manufacturer’s instructions. Next, 10+ DNA samples were pooled for NGS sequencing. Two...

Accurate detection of apple blossoms is critical for monitoring flowering status and optimizing agricultural management. Traditional methods often fail to address challenges such as overlapping petals and environmental variability, leading to inefficiency and inaccuracy. In this paper, LEAF-Net, a modified YOLOv11-based target detection model, is proposed. The original C3k2 module in YOLOv11 lacks a targeted attention mechanism and exhibits insufficient enhancement of key features such as petal edges. Therefore, we propose our model, LEAF-Net, which incorporates a Multi-scale Attention Enhanced Block (MAEB) that enhances edge feature extraction through a hierarchical attention mechanism and reconstructs the C3k2 module. A Frequency-aware Feature Pyramid Network (Freq-FPN) that optimizes multi-scale feature fusion while preserving high-frequency details; and a comprehensive apple blossom dataset capturing diverse growth stages and environmental conditions. To address the dataset deficiencies, a specialized apple blossom dataset with complex backgrounds is constructed. Experimental results demonstrate state-of-the-art performance, with LEAF-Net achieving 90.4% mAP50 and 70.4% mAP50-95, significantly outperforming existing benchmarks. The framework’s computational efficiency (7.1 GFLOPs) and adaptability make it suitable for real-time deployment in precision agriculture. These advancements provide an extensible framework for precision orchard surveillance, thereby paving the way for their adaptive deployment in diverse agricultural automation contexts.