Dormancy Dynamics in Japanese Plum: Transcriptomic Responses to Variable Climatic Conditions and Chill Requirements

Dormancy Dynamics in Japanese Plum: Transcriptomic Responses to Variable Climatic Conditions and Chill Requirements | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Dormancy Dynamics in Japanese Plum: Transcriptomic Responses to Variable Climatic Conditions and Chill Requirements Sara Herrera, José Ignacio Hormaza, Guillem Ylla, Javier Rodrigo, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7114924/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Dormancy progression in temperate fruit trees is highly sensitive to environmental conditions and chilling accumulation. To investigate the regulation of dormancy in Japanese plum ( Prunus salicina hybrids), we performed a comparative transcriptomic analysis of flower buds from two Japanese plum cultivars with different chilling requirements, "Hiromi Red" (high chill) and "Crimson Glo" (low chill), grown under contrasting climatic climates (semi-arid and Mediterranean subtropical). The study combined phenological observations, quantification of chill and heat requirements, as well as transcriptomic analyses across three key developmental stages: full dormancy (T0), dormancy release (T1), and full recovery (T2). Climate exerted a stronger influence than dormancy stage on gene expression profiles, leading to cultivar- and climate-specific transcriptional responses. Key dormancy-related genes—such as DAM , FT , and SAP1 — exhibited differential expression patterns across climates, suggesting roles in climatic adaptation. Notably, dormancy phases occurred approximately one month earlier under Mediterranean subtropical conditions, accompanied by a marked reduction in chilling requirements. Expression and phylogenetic analyses revealed that environmental conditions had a stronger effect on the transcriptomic profiles than the progression of dormancy itself, potentially due to epigenetic modulation. These findings provide new insights into the molecular mechanisms underlying dormancy in woody perennial species and offer perspectives for developing cultivars better adapted to changing climatic scenarios. Gene & Accession Numbers All sequence data and genome files generated for this study were deposited in the NCBI Sequence Read Archive (SRA) under BioProject PRJNA1276976. Horticulture Bioinformatics Computational Biology Molecular Biology Epigenetics & Genomics Climatic adaptation Chill accumulation Epigenetics Gene expression Phenology Transcriptome Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction Flowering plants exhibit numerous adaptive features to survive adverse environmental conditions. In temperate woody perennials, vegetative growth typically occurs in spring and summer, while dormancy begins in autumn. During dormancy, visible growth ceases but low metabolic activity is maintained, protecting plants from harsh environmental conditions (Horvath, 2009 ; Cooke et al., 2012 ). Dormancy is crucial not only for survival but also for ensuring proper fruit production (Rodrigo, 2000 ; Rohde & Bhalerao, 2007 ). Dormancy is usually differentiated into three phases: paradormancy (late summer), endodormancy (autumn-winter), and ecodormancy (late winter-spring) (Lang et al., 1987 ). During endodormancy, bud growth remains inhibited even under favorable temperatures until they accumulate sufficient chilling (chilling requirements) to transition to the next phase, ecodormancy. During ecodormancy, bud growth resumes upon fulfillment of enough warmth (heat requirements) (Lang et al., 1987 ). Global warming threatens this finely tuned process by reducing chill accumulation in many temperate regions, leading to substantial yield losses (Campoy et al., 2011 ; Luedeling et al., 2011 ). A lack of sufficient winter chilling modifies spring phenology (Beil et al., 2021 ), causing reduced and irregular flowering and fruiting, ultimately leading to lower fruit yield (Kovaleski, 2024 ). Despite over two centuries of research, the regulatory mechanisms of dormancy remain unclear (Fadón et al., 2020a ). Agroclimatic requirements—chill requirements during endodormancy and heat requirements during ecodormancy— are cultivar-specific and determine their adaptation to different regions (Fadón et al., 2020b ). Given their significant agroclimatic implications, these requirements have been extensively evaluated in cultivars of stone fruit tree species such as plum (Guerrero et al., 2024 ), apricot (Ruiz et al., 2007 ; Herrera et al., 2022 ), and sweet cherry (Fadón et al., 2021 ). However, the approaches and models used to estimate these agroclimatic requirements have limitations (Luedeling, 2012 ; Fadón et al., 2023 ), often leading to estimates that cannot be directly applied to regions with different climatic conditions. To address these limitations, recent studies have explored potential biological markers of the transition from endodormancy to ecodormancy, such as male meiosis in apricot (Herrera et al., 2022 ). Since the early century, key dormancy-related genes have been identified, including DORMANCY-ASSOCIATED MADS-box ( DAM ), first identified in peach (Bielenberg et al., 2004 , 2008 ) and later in other fruit tree species (Quesada-Traver et al., 2022 ). Recent transcriptomic research has linked gene expression with hormonal, physiological, and metabolic changes during dormancy (Galindo González et al., 2012 ; Nishitani et al., 2012 ; Zhuang et al., 2013 ; Zhang et al., 2018 ), but most studies have focused on single climatic conditions. Given the challenges derived from global climate change, there is an urgent need for studies assessing dormancy regulation under diverse environmental conditions. Recent transcriptomic research on Prunus species has assessed dormancy regulation in genotypes adapted to different agroclimatic conditions. In sweet cherry, conserved gene expression patterns have been identified, highlighting seven genes predictive of dormancy stages (Vimont et al., 2019 ). Comparative transcriptomic analyses of apricot and peach cultivars with different chilling requirements have been conducted, analyzing floral buds at key chill-hour intervals (Yu et al., 2020 ). Subsequent studies have re-analyzed RNA-seq data to identify key dormancy-related genes in sweet cherry, apricot, and peach (Canton et al., 2021 ), as well as in almond (Calle et al., 2022 ). Recently, the genome sequence and a comparative transcriptome study of two Japanese plum cultivars with different chilling requirements identified six tandemly arrayed PsDAM genes, including PsDAM6 , which could potentially influence dormancy and chilling requirements (Fang et al., 2022 ). To address this gap, this study aims to elucidate genetic basis of dormancy progression mechanisms in the floral buds of Japanese plum (hybrids of P. salicina ) focusing on how environmental conditions influence reproductive development. Using two cultivars with different chilling requirements, we analyzed gene expression under contrasting semi-arid and Mediterranean subtropical conditions to assess the impact of climate on dormancy-related gene expressions and identify key genes involved in endodormancy regulation and transition from endodormancy to ecodormancy. Results Experimental establishment of endodormancy breaking We first evaluated the phenology of two cultivars with different chilling requirements: "Hiromi Red" (HR; high chilling requirement) and "Crimson Glo" (CG; low chilling requirement) under two locations in Spain with contrasting climates: La Almunia de Doña Godina, Zaragoza (semi-arid) and Algarrobo-Costa, Málaga, (Mediterranean subtropical). Both cultivars are interspecific hybrids of P. salicina and other Prunus species, developed by Zaiger Genetics (Milošević & Milošević, 2018 ). In the semi-arid climate, full flowering (FP50) was observed in late February (February 24 for HR; February 19 for CG). In the Mediterranean subtropical climate, flowering was delayed: FP50 occurred 20 days later in HR (March 16) and 11 days later in CG (March 02). In the semi-arid climate, HR and CG reached endodormancy release on December 23 and 10, respectively. Full dormancy dates were set on December 10 for HR and November 25 for CG. Full recovery of bud activity was recorded on December 30 in both cultivars. However, in HR this recovery occurred one week after dormancy release, while in CG it took three weeks (Fig. 1 A, B). A similar but delayed trend was observed in the Mediterranean subtropical climate, where all three time points occurred approximately one month later than in the semi-arid climate. The delay was 35 days for HR and 26 days for CG (Fig. 1 C, D). Chilling and heat requirements varied across cultivars and climates. Under semi-arid conditions, CG required 32 chilling portions (CP) and HR 42 CP, whereas under Mediterranean subtropical conditions, CP values were considerably lower (15 CP for CG, 26 CP for HR). In contrast, heat requirements values were up to 60% higher in the Mediterranean subtropical climate, with 11,395 and 6,998 growing degree hours (GDH) for CG, and 10,878 and 6,567 GDH for HR, respectively. Transcriptomic overview of flower bud development during dormancy The number of mRNA-seq aligned reads to the genome per sample ranged from 41.7M to 57M, with alignment rates between 84.4% and 85.8% (Fig. S1, Table S1). Boxplot of VST normalized counts revealed similar expression distributions across all samples and replicates, with median expression values closely aligned across conditions, indicating comparable overall gene expression levels. However, differences were observed in the number and dispersion of outliers (Fig. S2A). The three replicates clustered closely together, as shown by both the hierarchical clustering dendrogram (Fig. S2B) and the principal component analysis (PCA) plot (Fig. S2C). The first principal component (PC1, 38%) clearly separated the two cultivars while the second principal component (PC2, 29.8%) showed a separation based on climate, regardless of the dormancy stage. Interestingly, CG at full dormancy and HR at endodormancy release under Mediterranean subtropical conditions clustered more closely with semi-arid climate samples than with other samples within the same climate under different dormancy stages. In addition, the heatmap (Fig. S2D) also showed high consistency among replicates, and the gene expression patterns supported the PCA results, suggesting specific transcriptomic responses related to genotype and environment during dormancy. Transcriptomic insights into dormancy regulation in the semi-arid climate In the semi-arid location, clustering analyses and PCA showed clear differentiation between cultivars and dormancy stages (Fig. 2 ). In CG, T1 and T2 were similar, indicating a higher transcriptomic shift from T0 to T1. Both the dendrogram (Fig. 2 A) and the first principal component (Fig. 2 B) showed a clear differentiation between the two cultivars. However, the second principal component showed a clear differentiation among the three dormancy stages in the low chill cultivar (CG), whereas in the high chill cultivar (HR), the T1 and T2 stages did not separate clearly. Analysis of HR samples showed fewer differentially expressed genes (DEGs) across dormancy stages than CG. The highest number of DEGs in HR occurred during full dormancy (3,971 genes, T0) and after dormancy release (2,223 genes, T2) compared to the dormancy release stage (1,212 genes, T1) (Fig. 2 C, Table S2). There was a marked difference between periods, with a 77% reduction of DEGs after dormancy release (647 genes) compared to the period before dormancy release (2,799 genes) (Fig. 2 D, Table S3). In contrast, CG exhibited a higher number of DEGs across all stages, with the largest number at full dormancy (6,682 genes, T0) (Fig. 2 E, Table S4). Compared to HR, the number of DEGs, including both up- and down-regulated genes, was more than double before dormancy release (6,311 genes) and after dormancy release (3,957 genes) (Fig. 2 F, Table S5). Functional enrichment analysis based on Cluster of Orthologous Groups (COG) categories showed a progressive decrease in the number of DEGs across most categories during dormancy in HR, followed by an increase upon the reactivation of activity (Fig. S3A, B, Table S6). At full dormancy (T0), a large number of genes were downregulated, particularly those involved in transcription, signaling and protein regulation (Fig. S3A, Table S6). In contrast, CG exhibited a progressive increase in the number of downregulated genes across dormancy stages, mainly in categories related to cellular processes, signaling and metabolism, while genes involved in information storage and processing remained active initially but were progressively downregulated as dormancy progressed, (Fig. S4A, Table S7). At full dormancy, a higher number of upregulated genes were observed, particularly in categories related to signaling, protein regulation, transcription, and metabolism, although their expression gradually decreased over time. Conversely, genes related to cell cycle reactivation and preparation for active growth —such as those involved in translation, replication, and chromatin modification— became increasingly expressed, with their activity sustained until T2 (Fig. S4B, Table S7). Transcriptomic insights into dormancy regulation in the Mediterranean subtropical climate In the Mediterranean subtropical climate, a similar gene expression pattern to that observed in the semi-arid climate was detected, with a clear separation between the two cultivars (PC1, 47.1%), as well as a distribution based on the dormancy stage (PC2, 26.1%) (Fig. 3 A, B). However, the samples corresponding to full dormancy in HR clustered closer to CG. A significant difference in the number of DEGs was observed between the two cultivars during the dormancy stage (T0). In HR, 5,035 genes showed significantly increased expression, while 5,230 genes showed significantly decreased expression. In contrast, CG exhibited a much smaller number of DEGs, with 1,326 genes upregulated and 1,452 downregulated. The number of DEGs was similar between the two cultivars for T1 and T2 (Fig. 3 C-F, Tables S8-11). In HR, COG category analysis revealed a progressive decrease in the number of DEGs from T0 to T2 (Fig. S5A, B). At full dormancy (T0), a large number of genes were downregulated, particularly in categories related to transcription, signal transduction mechanisms, and post-translational modification, protein turnover, and chaperones (Fig. S5A, Table S12). In parallel, the number of upregulated genes gradually increased from T0 onward, especially in categories involved in metabolism and transcription (Fig. S5B, Table S12). In CG, COG annotation revealed a distinct gene regulation pattern compared to HR, suggesting a progressive general reactivation that intensified once dormancy was overcome. At full dormancy (T0), although several functional categories such as signaling and protein regulation, transcription and carbohydrate metabolism were downregulated (Fig. S6A, Table S13), these same categories also showed a notable number of upregulated genes (Fig. S6B, Table S13). As CG progressed to T1 and T2, the number of upregulated DEGs increased across multiple COG categories. Differential Expression of Key Dormancy-Related Genes In addition to analyzing general processes, we also examined known key dormancy-related genes, including STRESS-ASSOCIATED PROTEIN1 ( SAP1 ) (Prupe.2G010400) (Lloret et al., 2017 ), ALLENE OXYDE CYCLASE ( AOC )- like 1–2 (Prupe.1G306100, Prupe.3G239900) (Lloret et al., 2021 ), DAM (Bielenberg et al., 2004 , 2008 ), FLOWERING LOCUS T ( FT ) (Prupe.6G364900) (Hsu et al., 2011 ; Hao et al., 2015 ), TARGET OF RAPAMYCIN ( TOR )- like (Prupe.8G151300) (Menand et al., 2002 ; Lloret et al., 2017 ) TONOPLAST INTRINSIC PROTEIN ( TIP )- like (Prupe.2G229500) (Ludevid et al., 1992 ; Lloret et al., 2017 ), and LIPOXYGENASE ( LOX )- like (Prupe.2G005300) (Lloret et al., 2021 ). To this end, we first searched for the putative orthologs of these genes in our transcriptome using their sequences from Prunus persica . For most candidate genes, a single sequence was identified, except for the DAM genes, for which two DAM-like sequences were found. Phylogenetic analysis placed one of the two putative DAM ortholog ( evm.model.Chr1.599_syl_v2.0 ) within the DAM6 clade, and it was subsequently renamed as PshDAM6 . Similarly, the other putative ortholog of DAM ( evm.model.Chr1.600.601.603.604_syl_v2.0 ) was placed within the DAM1 clade and renamed as PshDAM1 (Fig. S7). Significant differences in expression were observed in all key dormancy-related genes, except TIP (Fig. 4 ). PshDAM1 expression decreased across dormancy stages, more pronounced in CG and in the Mediterranean subtropical climate. PshDAM6 followed a similar pattern, showing reduced expression at T2, with a steeper decrease in CG and a similar trend under both climates. FT expression increased at T2 under semi-arid conditions but decreased at T2 in the Mediterranean subtropical climate. SAP1 was upregulated in HR during dormancy release in Mediterranean subtropical conditions but fluctuated in CG. In the semi-arid climate, SAP1 expression levels were generally lower, with significant differences observed only after dormancy release in CG. No significant differences were found in TIP expression across stages, cultivars and climates. TOR expression increased after dormancy release, particularly in the Mediterranean subtropical climate. LOX expression was similar across all dormancy stages in both cultivars, regardless of location, with higher expression levels in HR. However, significant differences were only observed for CG in the Mediterranean subtropical climate. In AOC-like1 , a reduction in expression was observed across dormancy stages in both climates, with significant differences at dormancy release. For AOC-like2 , expression levels remained similar across stages in both climates, with significant differences only observed at the resumption of growth in CG under Mediterranean subtropical conditions. Cultivar- and climate-specific upregulated gene expression To explore how gene expression is modulated in response to climatic conditions and genetic background, we analyzed the patterns of DEGs that were upregulated across dormancy stages in both cultivars under semi-arid and Mediterranean subtropical environments. During dormancy (T0), HR showed 3,166 DEGs upregulated under Mediterranean subtropical conditions, whereas only 522 were observed under semi-arid conditions. Interestingly, 606 genes were shared between the two climates. In contrast, in CG, 509 DEGs upregulated were found under Mediterranean subtropical conditions, and 2,498 under semi-arid conditions, with an overlap of only 165 genes between the two climates. Additionally, 136 DEGs were identified between the two cultivars in the Mediterranean subtropical climate, and 102 DEGs in the semi-arid climate. Across both cultivars, 61 DEGs were common to both climates (Fig. 5 A, Tables S14-S18). During dormancy release (T1), no common upregulated DEGs were observed between cultivars and climates. Few DEGs were identified within each climate: 20 in the semi-arid climate and 16 in Mediterranean subtropical climate. However, the number of upregulated DEGs for each cultivar, regardless of climate, was high: 444 for CG and 258 for HR (Fig. 5 B, Tables S19-S22). After dormancy release (T2), more upregulated DEGs were associated with Mediterranean subtropical conditions. Overall, CG exhibited twice as many DEGs as HR (Fig. 5 C, Tables S23-S27). To further evaluate gene function across various categories from the COG database, the majority of genes were grouped into three major functional categories: metabolism (13–49%), information storage and processing (5–30%), and cellular processes and signaling (6–40%) (Fig. 6 , Tables S28-S30). Genes with unclassified functions were assigned to poorly characterized categories, while those mixed or overlapping roles were grouped under "Others" (52 categories, 2–13%). Overall, genes were distributed across twenty-three specific COG functional classes. Across all conditions, a substantial proportion had unknown (22–35%) or unassigned functions (2–8%), indicating that several biological processes remain poorly understood. Functional category distributions were generally consistent, except during dormancy, when metabolic genes dominated (49%). The COG functional classification analysis revealed that most genes were associated with the categories "Carbohydrate transport and metabolism," "Transcription," "Signal transduction mechanisms," and "Posttranslational modification, protein turnover, chaperones". Notable inactivity was observed in categories related to defense mechanisms and secondary metabolite biosynthesis, suggesting a lack of active stress response during this state. Furthermore, low values in categories related to cell division, cytoskeleton organization, and extracellular structures reflected limited growth and expansion over dormancy stages (Fig. 6 , Tables S28-S30). Discussion We analyzed the transcriptomic profiles of two Japanese plum cultivars, "Hiromi Red" and "Crimson Glo," which have high and low chilling requirements, respectively, under semi-arid and Mediterranean subtropical climates. Our findings revealed that climate significantly impacts dormancy progression and gene expression patterns in these cultivars, with transitions between the three dormancy phases occurring approximately one month earlier under Mediterranean subtropical conditions. Discrepancies were observed in the quantification of chilling requirements, with a remarkable reduction in the CP required in the Mediterranean subtropical climate for both cultivars, while their CPs in the semi-arid climate aligned with previous studies (Guerrero et al., 2024 ). Dormancy dynamics and transcriptomic analysis across climates Traditionally considered as a period of inactivity, dormancy is now recognized as a dynamic and complex process involving extensive cellular and molecular activities (Rohde & Bhalerao, 2007 ; Zhao, Ma et al., 2025 ). Transcriptomic studies in Prunus have revealed that both endodormant and ecodormant flower buds exhibit unique and fluctuating transcriptional profiles, with continuous metabolic activities such as starch accumulation (Fadón et al., 2018 ; Yu et al., 2020 ; Calle et al., 2022 ), hormonal fluctuations (Vimont et al., 2019 ; Canton et al., 2021 ; Liu et al., 2025 ), and floral structure differentiation (Lloret et al., 2018 ; Zhao, Li et al., 2025 ). Previous transcriptomic studies in other Prunus species have identified hundreds to thousands of differentially expressed genes at different dormancy stages (Zhu et al., 2015 ; Yu et al., 2020 ) while fewer than 100 DEGs were expressed during full endodormancy. A meta-analysis of RNA-Seq studies in Prunus species (including apricot, almond, peach, and sweet cherry) identified 6,860 genes related to endodormancy, revealing conserved pathways involved in cold acclimation, cell growth control, oxidative signals, soluble sugar regulation, and phytohormone signaling, suggesting that common molecular mechanisms underlie dormancy regulation within this genus. However, the number of DEGs varies among species, cultivars, and dormancy stages (Calle et al., 2022 ). In our study, the high chill cultivar, "Hiromi Red," exhibited a more pronounced reduction in DEGs between the dormancy phases, with a notably higher number of DEGs in both climates compared to previous research in Japanese plum (Fang et al., 2022 ). For the low-chill cultivar, "Crimson Glo," the pattern of DEGs in the semi-arid climate was consistent with that observed for "Sanyueli" (Fang et al., 2022 ), showing a gradual decrease in DEGs during the transition between endodormancy and dormancy release. However, in the Mediterranean subtropical climate, an increase in DEGs was observed after dormancy release. Transcriptomic differentiation influenced by climate and dormancy stage Despite recent RNA-seq studies focusing on dormancy control in Prunus species, our study addresses a significant gap by analyzing transcriptomic responses across different climates using two cultivars with different chilling requirements. PCA results revealed that climate had a greater influence on transcriptomic differentiation than dormancy stage, suggesting that the environmental conditions have a more significant impact on the transcriptomic profiles than the progression of dormancy. This contrasts with previous studies in other Prunus species, such as apricot and peach, where developmental stages had a greater influence on the transcriptomic profile (Yu et al., 2020 ). Among the differentially expressed genes, several key regulators of dormancy have emerged. For example, Lloret et al. ( 2017 ) showed that PpSAP1 in peach is expressed in dormant buds and expression decreases upon dormancy release. In our study, both cultivars showed a similar decreasing expression trend of PpSAP1 , but only under semi-arid conditions. Conversely, under Mediterranean subtropical conditions, a significant increase in PshSAP1 expression was observed, particularly in CG before dormancy release and in HR after dormancy release, suggesting an adaptive role in the adaptation of Japanese plum to different climatic conditions, especially in warmer environments, consistent with the described involvement of PpSAP1 in stress tolerance and cell growth (Lloret et al., 2018 ). In contrast to previous reports in European plum and peach, where higher expression levels of PshTIP were detected after dormancy release, we found no significant differences in PshTIP expression, (Lloret et al., 2017 ; Quesada-Traver et al., 2020 ). However, an increase in PshTOR expression was observed in both cultivars in the Mediterranean subtropical climate, following a pattern similar to the expression of PshSAP1 . The AOC-like 1–2 and LOX-like genes, which are involved in jasmonic acid biosynthesis (Berni et al., 2019 ), have also been linked to dormancy and related physiological processes in other Prunus species (Lloret et al., 2021 ). Prudencio et al. ( 2021 ) observed a decrease in LOX3.1 expression during dormancy release in almond, suggesting that lipoxygenase-mediated lipid peroxidation provides fatty acids for energy production during this process. In peach, an increase in LOX-like, AOC-like1 , and AOC-like2 expression has been reported during dormancy release, with a positive correlation with PpeDAM6 expression, suggesting these genes may play a role in dormancy release (Lloret et al., 2021 ; Puertes et al., 2023 ). In our study, we observed minimal expression changes across dormancy stages for these genes. However, PshAOC-like1 followed a decreasing trend similar to that reported for LOX3.1 in almond (Prudencio et al., 2021 ), indicating that similar mechanisms might be at play in dormancy release across different Prunus species. FT and DAM genes: expression patterns and phylogenetic insights FT-like , a key regulator of growth and flowering processes (Fadón et al., 2020a ), showed increased expression after dormancy release under semi-arid conditions, consistent with previous reports in sweet cherry (Canton et al., 2021 ). However, we observed a decrease in FT expression after dormancy release in the Mediterranean subtropical climate. On the other hand, the DAM genes, which have been identified as key regulators of the dormancy cycle and climate adaptation (Goeckeritz & Hollender, 2021 ), were downregulated in our study after prolonged exposure to cold temperatures, an essential factor for triggering dormancy release in Rosaceae (Falavigna et al., 2019 ). These findings align with those reported in other fruit tree species, where DAM gene expression correlates with the downregulation of FT during dormancy (Lloret et al., 2018 ; Puertes et al., 2023 ). In both semi-arid and Mediterranean subtropical climates, DAM genes showed high expression in dormant buds and low expression after the fulfillment of chilling requirements, which is consistent with previous reports in different species of the Rosaceae, such as Japanese plum (Fang et al., 2022 ), European plum (Quesada-Traver et al., 2020 ), sweet cherry (Rothkegel et al., 2017 ; Vimont et al., 2019 ), peach (Jiménez et al., 2010), Japanese apricot (Zhang et al., 2018 ), and apple (Mimida et al., 2015 ). Interestingly, while a significantly lower DAM expression was reported in the low-chill Japanese plum cultivar "Sanyueli" (Fang et al., 2022 ), our results showed lower DAM expression in the high-chill cultivar, Hiromi Red. These differences may be influenced by epigenetic factors that modulate DAM gene expression (Ríos et al., 2014 ), in response to the specific environmental conditions of each location. Our phylogenetic and synteny analysis revealed that DAM proteins in the Amygdaloideae subfamily of Rosaceae originated from the SHORT VEGETATIVE PHASE (SVP) 2 clade, which also includes AGAMOUS-LIKE (AthAGL24) of Arabidopsis thaliana (Quesada-Traver et al., 2022 ). In several Prunus species six DAM genes have been identified, contrasting with the lower number of DAM genes found in annual model plants (Fang et al., 2022 ; Quesada-Traver et al., 2022 ). The expansion of the DAM genes may have resulted from serial tandem duplications occurring before the diversification of the Prunus genus (Jiménez et al., 2009 ). In our transcriptomic data, we surprisingly detected only PshDAM1 and PshDAM6 , but additional DAM genes might be identified once the genome sequences of these cultivars become available. Interestingly, the phylogenetic analysis of DAM genes revealed that PsDAM genes from the Japanese plum cultivar "Sanyueli" clustered in a separate clade from the DAM sequences, including PshDAM1 and PshDAM6 . Moreover, PsDAM6 exhibited insertions in its introns and a deletion in exon 5, which could affect its function in dormancy regulation. Japanese plum cultivars are the result of hybridization between Prunus salicina and other species (Guerra and Rodrigo, 2015 ) resulting in high genetic diversity and a complex population structure (Guerrero et al., 2021 ). Since inter-species hybridization is a common phenomenon within the Prunus genus (Guerrero et al., 2022 ), this could explain the discrepancies in DAM gene clustering, as these genes may exhibit a combination of characteristics from different species. Location- and cultivar-specific gene expression differences during dormancy stages in low and high chill requirement genotypes The number and distribution of DEGs across cultivars and climates revealed distinct regulatory responses during dormancy and its release. During dormancy (T0), HR showed a higher number of DEGs under Mediterranean subtropical conditions, while CG responded more strongly under semi-arid conditions suggesting that each cultivar responds differently to climatic conditions, likely due to differences in their adaptation and chilling requirements. The low number of shared DEGs between climates and cultivars indicates that dormancy is regulated by highly specific genotype-environment interactions. At T1, few DEGs were identified within each climate, and none were shared between cultivars and climates. This suggests that there is no universal transcriptional response at this stage, and that each cultivar–climate combination activates different genes, showing a strong influence of genotype and environment on dormancy release. After dormancy release (T2), more DEGs were detected under Mediterranean subtropical conditions, suggesting that warmer climates might induce stronger transcriptional activity. CG showed twice as many DEGs as HR, potentially reflecting differences in how each cultivar adjusts gene expression after dormancy. Low-chill cultivars like CG might remain more responsive to environmental signals after dormancy release, while high-chill cultivars like HR could show a weaker gene expression response at this stage. The functional classification of DEGs showed a clear dominance of metabolism-related genes, especially in the full dormancy stage. This suggests that the plant is adjusting its metabolism to focus on basic survival during this early stage (Fadón et al., 2020a ). Genes involved in transcription remain active throughout the dormancy period, highlighting the importance of maintaining gene expression even when most cellular processes are slowed down (Fang et al., 2022 ). The high number of unclassified genes also points to unknown or species-specific functions that are still not well understood. On the other hand, the low presence of genes related to defense, secondary metabolite production, and cell structure suggests reduced plant activity in stress response and growth pathways during dormancy. This differs from previous studies that identified genes associated with stress resistance during the dormancy stage (Yamane et al., 2008 ; Vimont et al., 2019 ; Yu et al., 2020 ; Niu et al., 2024 ). Conclusion Our study provides a comprehensive transcriptomic analysis of dormancy regulation in two Japanese plum cultivars across contrasting climatic conditions. By comparing transcriptomic profiles across cultivars and environments, we have identified both genotype-specific and climate-responsive genes and pathways. The pronounced transcriptional activity observed under warmer conditions highlights the strong impact of environmental conditions on dormancy regulation. These findings provide new insights into the molecular mechanisms underlying dormancy and offer value insights for breeding climate-resilient genotypes and growing cultivars better adapted to changing climatic scenarios. Material & Methods Plant material Shoots and flower buds were collected from two Japanese plum cultivars, "Hiromi Red" and "Crimson Glo" (hybrids of Prunus salicina Lindl.), with contrasting late and early flowering dates, respectively. Trees of the same age and grafted on the same rootstock were grown in two locations in Spain: IHSM La Mayora (IM; Algarrobo-Costa, Málaga, 36°45'23.4"N, 4°02'35.9"W, 25 m altitude, hot-summer Mediterranean climate) and Finca La Redonda (La Almunia de Doña Godina, Zaragoza, 41°27'28.6"N, 1°21'33.7"W, 394 m altitude, cold semi-arid climate). The hot-summer Mediterranean climate (Csa) of Algarrobo-Costa (Peel et al., 2007 ), also referred to as a Mediterranean subtropical climate due to its support for the extensive cultivation of subtropical crops (MAPA, 2023; Junquera et al., 2024 ), is characterized by mild, wet winters, and hot, dry summers. The cold semi-arid climate (BSk) of La Almunia de Doña Godina features cold winters, and hot, dry summers with marked seasonal temperature contrasts and low annual precipitation (Peel et al., 2007 ). Phenological observations of flower buds were carried out twice a week from bud break to flowering, considering full flowering (F50) when 50% of flower buds were in stage F (Baggiolini, 1952 ) that corresponds to stage 65 (full bloom) in the BBCH scale (Meier, 2001 ; Fadón et al., 2015 ). Determination of endodormancy breaking Flower bud growth was evaluated in response to warm conditions after field chilling exposure. Four shoots around 40 cm per cultivar were collected weekly from November to March, placed in a growth chamber (22 ± 1°C, 12 h light photoperiod) and maintained on wet florist foam for 8 days. To determine the end of endodormancy, 10 flower buds were randomly picked and weighed on the first and last day in the growth chamber. Endodormancy was considered overcome when bud weight increased by more than 30% (Brown & Kotob, 1957 ; Tabuenca, 1964 ; Ruiz et al., 2007 ; Fadón & Rodrigo, 2018 ; Guerrero et al., 2024 ). Using the endodormancy release date (T1) as reference, two additional time points were selected: two weeks before dormancy release was considered full dormancy (T0), and a bud weight increase exceeding 50% was used as the criterion for full recovery of activity (T2). Chilling and heat requirement estimation Semi-hourly temperature data were recorded at local weather stations: station 31 (Épila) in Zaragoza (ORESA, 2023), and a hygrometer placed at the experimental station of IHSM La Mayora in Málaga. For each cultivar and location, chill accumulation from September 1st to endodormancy release was quantified in chilling portions (CP) using the Dynamic Model (Fishman et al., 1987 ). Heat requirements were estimated in Growing Degree Hours (GDH) (Richardson et al., 1974 ), from endodormancy release to F50. RNA extraction and library preparation For each time point, flower buds were collected from multiple trees and pooled to create three replicates. Samples were flash frozen in liquid nitrogen and stored at -80ºC. Total RNA was isolated using the Total RNA Purification Kit (Norgen Biotek) and treated with TURBO DNA-freeTM kit (Ambion, Austin, TX, USA) to remove DNA contamination. Thirty-six samples containing 0.74–2.56 µg of RNA were submitted to Novogene (Cambridge, UK) for library preparation and RNA sequencing (Illumina NovaSeq 6000, 150 bp PE). mRNA-seq data processing The P. salicina genome assembly and gene annotations were obtained from P. salicina Sanyueli Genome v2.0 (Liu et al., 2020 ), hosted in the Genome Database for Rosaceae (GDR; accession number tfGDR1044) (Jung et al., 2019). The quality of reads was assessed using FastQC v0.11.9 (Andrews, 2010), and gene expression was quantified with RSEM v1.3.3 (Li and Dewey, 2011 ) using STAR v2.7.9a as read aligner (Dobin et al., 2013 ). Gene counts in each dataset were normalized using the variance-stabilizing transformation (VST) method implemented in the DESeq2 v1.42.0 R package (Love et al., 2014 ), in the statistical software R (R Core Team, 2023 ). Principal component analysis (PCA), hierarchical clustering, boxplots, heatmaps and differential expression (DE) analysis were performed on VST-normalized counts. Differential expression analysis Differential expression analyses were performed with DESeq2 v1.42.0 (Love et al., 2014 ). To gain a more detailed understanding of the regulatory mechanisms underlying dormancy, two types of analyses were conducted: differential expression analysis and functional enrichment analysis, both performed on the datasets from each location. First, to identify genes with dormancy stage-specific regulation within each location, gene expression at each time point was compared to the mean expression levels of the other two time points within each cultivar. Furthermore, to assess the evolutionary dynamics of differentially expressed genes across stages, gene expression at time point T0 was compared with T1, and T1 was compared with T2. Genes with a Benjamini-Hochberg (BH) adjusted P-value lower than 0.01 were selected as differentially expressed in the corresponding contrast. Phylogenetic analysis Protein sequences of the two DAM -like genes identified in this study, together with the longest annotated homologous from related Prunus and other species retrieved from NCBI database (NCBI Resource Coordinators, 2018 ), were aligned using CLUSTALX v.1.82 (Thompson et al., 1997 ). The alignments were subsequently edited as described previously (Lora et al., 2017 ) using GBLOCK v.0.91b (Castresana, 2000 ; Talavera & Castresana, 2007 ). Bayesian analysis was performed using MrBayes (Ronquist et al., 2012 ), following the JTT + Invariant (I) model of amino acid substitutions recommended by MEGA version X (Kumar et al., 2018 ). Trees were sampled every 100 generations for 1,000,000 generations in the Bayesian analysis, with the first 25% of the trees of each run discarded as burn-in. Functional analysis The functional annotation of the obtained protein sequences was performed using the EggNOG database (evolutionary genealogy of genes: Non-supervised Orthologous Groups), version 5.0 (Huertas-Cepas et al., 2019). Protein sequences were analyzed with EggNOG-mapper ( https://eggnog-mapper.embl.de/ ) with default parameters, adjusting the taxonomic scope per query and transferring non-electronic Gene Ontology evidence. The COG (Clusters of Orthologous Groups) functional categories were used to generate graphical representations of the functional distribution using the ggplot2 package (Wickham, 2016 ) in R (R Core Team, 2023 ). Abbreviations AOC ALLENE OXYDE CYCLASE-like CG Crimson Glo COG Cluster of Orthologous Groups CP Chilling Portion DAM DORMANCY-ASSOCIATED MADS-box DEG Differentially Expressed Gene FT FLOWERING LOCUS T GDH Growing Degree Hour HR Hiromi Red LOX LIPOXYGENASE-like PCA Principal Component Analysis SAP1 STRESS-ASSOCIATED PROTEIN1 MSC Mediterranean subtropical climate SAC Semi-arid climate TIP TONOPLAST INTRINSIC PROTEIN-like TOR TARGET OF RAPAMYCIN-like VST Variance-Stabilizing Transformation Declarations Ethics approval and consent to participate Not applicable Consent for publication All authors approve the manuscript and consent to the publication of this work. Availability of data and materials The raw transcriptome datasets are available in the National Center for Biotechnology Information (NCBI, https:// www. ncbi. nlm. nih. gov/) under the BioProject number PRJNA1276976. The scripts used to process and analyze the data are available at GitHub repository https://github.com/sherlg/transcriptomics-dormancy-japanese-plum. Competing interests The authors declare that they have no competing interests. Funding This research was funded by the ADAPFRUTCC project that is supported by the Biodiversity Foundation of the Ministry for the Ecological Transition and the Demographic Challenge, through the call for grants for the implementation of projects that contribute to the Spanish National Climate Change Adaptation Plan (2021-2030); the project PID2020-115473RR-I00, financed by ICIU/AEI/10.13039/501100011033/, Consolidated Group A12–17R funded by the Government of Aragon – European Social Fund, “The ESF invests in your future”, the predoctoral grant PRE2018-084962 funded by MCIN/AEI/10.13039/501100011033 for Sara Herrera, and the Priority Research Area BioS under the program “Excellence Initiative – Research University” at Jagiellonian University in Krakow. Authors' contributions JIH, JR, and JL designed the research. JIH, JR, and JL managed the project. SH and JL collected plant material, conducted field experiments, and performed phenotypic evaluations. SH prepared RNA samples. SH performed, and GY supervised, the bioinformatics analysis. JL carried out the phylogenetic analysis. SH, JIH, JR, and JL wrote the manuscript. SH, JIH, GY, JR, and JL revised the manuscript. All authors read and approved the final version. References Andrews S FastQC: a quality control tool for high throughput sequence data [Internet]. 2010 [cited 2025 May 14]. Available from: https://www.bioinformatics.babraham.ac.uk/projects/fastqc/ Baggiolini M (1952) Stades repères du abricotier. Rev Romande Agric Vitic Arboric 4:28–29 Beil I, Kreyling J, Meyer C, Lemcke N, Malyshev AV (2021) Late to bed, late to rise—Warmer autumn temperatures delay spring phenology by delaying dormancy. Glob Chang Biol 27. 10.1111/gcb.15858 Berni R, Cai G, Xu X, Hausman JF, Guerriero G (2019) Identification of Jasmonic Acid Biosynthetic Genes in Sweet Cherry and Expression Analysis in Four Ancient Varieties from Tuscany. Int J Mol Sci 20(14):3569. 10.3390/ijms20143569 Bielenberg DG, Wang Y, Fan S, Reighard GL, Scorza R, Abbott AG (2004) A deletion affecting several gene candidates is present in the Evergrowing peach mutant. J Hered 95(5):436–444. 10.1093/jhered/esh057 Bielenberg DG, Wang Y, Li Z, Zhebentyayeva T, Fan S, Reighard GL et al (2008) Sequencing and annotation of the evergrowing locus in peach [ Prunus persica (L.) Batsch] reveals a cluster of six MADS-box transcription factors as candidate genes for regulation of terminal bud formation. Tree Genet Genomes 4(3):495–507. 10.1007/s11295-007-0126-9 Brown DS, Kotob FA (1957) Growth of flower buds of apricot, peach, and pear during the rest period. Proc Am Soc Hortic Sci 69:158–164 Calle A, Saski C, Wünsch A, Grimplet J, Gasic K (2022) Identification of key genes related to dormancy control in Prunus species by meta-analysis of RNAseq data. Plants 11(19):2469. 10.3390/plants11192469 Campoy JA, Ruiz D, Egea J (2011) Dormancy in temperate fruit trees in a global warming context: A review. Sci Hortic 130(2):357–372. 10.1016/j.scienta.2011.07.011 Canton M, Forestan C, Bonghi C, Varotto S (2021) Meta-analysis of RNA-Seq studies reveals genes with dominant functions during flower bud endo- to eco-dormancy transition in Prunus species. Sci Rep 11:13173. 10.1038/s41598-021-92600-6 Castresana J (2000) Selection of conserved blocks from multiple alignments for their use in phylogenetic analysis. Mol Biol Evol 17(4):540–552. 10.1093/oxfordjournals.molbev.a026334 Cooke JEK, Eriksson ME, Junttila O (2012) The dynamic nature of bud dormancy in trees: Environmental control and molecular mechanisms. Plant Cell Environ 35(10):1707–1728. 10.1111/j.1365-3040.2012.02552.x Dobin A, Davis CA, Schlesinger F, Drenkow J, Zaleski C, Jha S et al (2013) STAR: ultrafast universal RNA-seq aligner. Bioinformatics 29(1):15–21. 10.1093/bioinformatics/bts635 Fadón E, Do H, Blanke M, Rodrigo J, Luedeling E (2023) Apparent differences in agroclimatic requirements for sweet cherry across climatic settings reveal shortcomings in common phenology models. Agric Meteorol 333:109387. 10.1016/j.agrformet.2023.109387 Fadón E, Fernandez E, Behn H, Luedeling E (2020a) A conceptual framework for winter dormancy in deciduous trees. Agronomy 10(2):241. 10.3390/agronomy10020241 Fadón E, Herrera S, Guerrero BI, Guerra ME, Rodrigo J (2020b) Chilling and heat requirements of temperate stone fruit trees ( Prunus sp). Agronomy 10(3):409. 10.3390/agronomy10030409 Fadón E, Rodrigo J, Luedeling E (2021) Cultivar-specific responses of sweet cherry flowering to rising temperatures during dormancy. Agric Meteorol 307:108486. 10.1016/j.agrformet.2021.108486 Fadón E, Herrero M, Rodrigo J (2018) Dormant flower buds actively accumulate starch over winter in sweet cherry. Front Plant Sci 9:171. 10.3389/fpls.2018.00171 Fadón E, Herrero M, Rodrigo J (2015) Flower development in sweet cherry framed in the BBCH scale. Sci Hortic (Amsterdam) 192:141–147. 10.1016/j.scienta.2015.05.027 Fadón E, Rodrigo J (2018) Unveiling winter dormancy through empirical experiments. Environ Exp Bot 152:28–36. 10.1016/j.envexpbot.2017.11.006 Falavigna VDS, Guitton B, Costes E, Andrés F (2019) I want to (bud) break free: The potential role of DAM and SVP -like genes in regulating dormancy cycle in temperate fruit trees. Front Plant Sci 9:1990. 10.3389/fpls.2018.01990 Fang ZZ, Lin-Wang K, Dai H, Zhou DR, Jiang CC, Espley RV et al (2022) The genome of low-chill Chinese plum Sanyueli ( Prunus salicina Lindl.) provides insights into the regulation of the chilling requirement of flower buds. Mol Ecol Resour 22:1919–1938. 10.1111/1755-0998.13585 Fishman S, Erez A, Couvillon GA (1987) The temperature dependence of dormancy breaking in plants: mathematical analysis of a two-step model involving a cooperative transition. J Theor Biol 124:473–483. 10.1016/S0022-5193(87)80221-7 Galindo González LM, El Kayal W, Ju CJT, Allen CCG, King-Jones S, Cooke JEK (2012) Integrated transcriptomic and proteomic profiling of white spruce stems during the transition from active growth to dormancy. Plant Cell Environ 35(4):682–701. 10.1111/j.1365-3040.2011.02444.x Goeckeritz C, Hollender CA (2021) There is more to flowering than those DAM genes: The biology behind bloom in rosaceous fruit trees. Curr Opin Plant Biol 59:101995. 10.1016/j.pbi.2020.101995 Guerra ME, Rodrigo J (2015) Japanese plum pollination: A review. Sci Hortic 197:674–686. 10.1016/j.scienta.2015.10.032 Guerrero BI, Fadón E, Guerra ME, Rodrigo J (2024) Perspectives on the adaptation of Japanese plum-type cultivars to reduced winter chilling in two regions of Spain. Front Plant Sci 15:1343593. 10.3389/fpls.2024.1343593 Guerrero BI, Guerra ME, Rodrigo J (2022) Simple Sequence Repeat (SSR)-based genetic diversity in interspecific plumcot-type ( Prunus salicina × Prunus armeniaca ) hybrids. Plants 11(9):1241. 10.3390/plants11091241 Guerrero BI, Guerra ME, Herrera S, Irisarri P, Pina A, Rodrigo J (2021) Genetic diversity and population structure of japanese plum-type (Hybrids of P. salicina ) accessions assessed by SSR markers. Agronomy 11(9):1748. 10.3390/agronomy11091748 Hao X, Chao W, Yang Y, Horvath D (2015) Coordinated expression of FLOWERING LOCUS T and DORMANCY ASSOCIATED MADS-BOX -like genes in leafy spurge. PLoS ONE 10(5):e0126030. 10.1371/journal.pone.0126030 Herrera S, Lora J, Fadón E, Hedhly A, Alonso JM, Hormaza JI, Rodrigo J (2022) Male meiosis as a biomarker for endo- to ecodormancy transition in apricot. Front Plant Sci 13:842333. 10.3389/fpls.2022.842333 Horvath DP (2009) Common mechanisms regulate flowering and dormancy. Plant Sci 177(6):523–531. 10.1016/j.plantsci.2009.09.002 Hsu CY, Adams JP, Kim H, No K, Ma C, Strauss SH et al (2011) FLOWERING LOCUS T duplication coordinates reproductive and vegetative growth in perennial poplar. Proc Natl Acad Sci U S A 108(26):10756–10761. 10.1073/pnas.1104713108 Huerta-Cepas J, Szklarczyk D, Heller D et al (2019) eggNOG 5.0: a hierarchical, functionally and phylogenetically annotated orthology resource based on 5090 organisms and 2502 viruses. Nucleic Acids Res 47(D1):D309–D314. 10.1093/nar/gky1085 Jiménez S, Lawton-Rauh AL, Reighard GL, Abbott AG, Bielenberg DG (2009) Phylogenetic analysis and molecular evolution of the dormancy associated MADS-box genes from peach. BMC Plant Biol 9:81. 10.1186/1471-2229-9-81 Jiménez S, Li Z, Reighard G et al Identification of genes associated with growth cessation and bud dormancy entrance using a dormancy-incapable tree mutant. BMC Plant Biol .2010;10;25. 10.1186/1471-2229-10-25 Jung S, Lee T, Cheng CH, Buble K, Zheng P, Yu J, Humann J, Ficklin SP, Gasic K, Scott K, Frank M (2018) 15 years of GDR: New data and functionality in the Genome Database for Rosaceae. Nucleic Acids Res 47(D1):D1137–D1145 Junquera V, Rubenstein DI, Levin SA, Hormaza JI, Vadillo Pérez I, Jiménez Gavilán P (2024) Hydrological collapse in southern Spain under expanding irrigated agriculture: meteorological, hydrological, and structural drought [preprint]. arXiv; Aug 1. Available from: https://doi.org/10.48550/arXiv.2408.00683 Kovaleski AP (2024) The potential for an increasing threat of unseasonal temperature cycles to dormant plants. New Phytol 244(2):377–383. 10.1111/nph.20052 Kumar S, Stecher G, Li M, Knyaz C, Tamura K (2018) Phylogenetic and molecular evolutionary analysis across computing platforms. Mol Biol Evol 35(6):1547–1549. 10.1093/molbev/msy096 Lang G, Early J, Martin G, Darnell R (1987) Endodormancy, paradormancy, and ecodormancy–physiological terminology and classification for dormancy research. HortScience Li B, Dewey CN (2011) RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome. BMC Bioinformatics 12:323. 10.1186/1471-2105-12-323 Liu C, Feng C, Peng W, Hao J, Wang J, Pan J, He Y (2020) Chromosome-level draft genome of a diploid plum ( Prunus salicina ). GigaScience 9(12):giaa130. 10.1093/gigascience/giaa130 Liu X, Wang L, Manzoor MA et al (2025) Unveiling the power of PavGID1s : the critical player in sweet cherry flower bud dormancy release. Plant Mol Biol 115:60. 10.1007/s11103-025-01589-3 Lloret A, Badenes ML, Ríos G (2018) Modulation of dormancy and growth responses in reproductive buds of temperate trees. Front Plant Sci 9:1368. 10.3389/fpls.2018.01368 Lloret A, Conejero A, Leida C, Petri C, Gil-Muñoz F, Burgos L et al (2017) Dual regulation of water retention and cell growth by a stress-associated protein ( SAP ) gene in Prunus . Sci Rep 7:332. 10.1038/s41598-017-00471-7 Lloret A, Quesada-Traver C, Conejero A, Arbona V, Gómez-Mena C, Petri C et al (2021) Regulatory circuits involving bud dormancy factor PpeDAM6 . Hortic Res 8(1):261. 10.1038/s41438-021-00706-9 Lora J, Herrero M, Tucker MR, Hormaza JI (2017) The transition from somatic to germline identity shows conserved and specialized features during angiosperm evolution. New Phytol 216(2):495–509. 10.1111/nph.14330 Love MI, Huber W, Anders S (2014) Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol 15(12):550. 10.1186/s13059-014-0550-8 Ludevid D, Höfte H, Himelblau E, Chrispeels MJ (1992) The Expression Pattern of the Tonoplast Intrinsic Protein gamma-TIP in Arabidopsis thaliana Is Correlated with Cell Enlargement. Plant Physiol 100(4):1633–1639. 10.1104/pp.100.4.1633 Luedeling E (2012) Climate change impacts on winter chill for temperate fruit and nut production: A review. Sci Hortic 144:218–229 Luedeling E, Girvetz EH, Semenov MA, Brown PH (2011) Climate change affects winter chill for temperate fruit and nut trees. PLoS ONE 6(5):e20155. 10.1371/journal.pone.0020155 de Agricultura M Pesca y Alimentación (MAPA). Anuario de estadística 2022 [Internet]. Madrid: Gobierno de España; 2023 [cited 2025 Jul 01]. Available from: https://www.mapa.gob.es/es/estadistica/temas/publicaciones/anuario-de-estadistica/default.aspx Meier U (2001) Growth stages of mono- and dicotyledonous plants: BBCH monograph. Federal Biological Research Centre for Agriculture and Forestry, Germany Menand B, Desnos T, Nussaume L, Berger F, Bouchez D, Meyer C et al (2002) Expression and disruption of the Arabidopsis TOR (target of rapamycin) gene. Proc Natl Acad Sci U S A 99(9):6422–6427. 10.1073/pnas.092141899 Milošević T, Milošević N (2018) Plum ( Prunus spp.) breeding. In: Al-Khayri J, Jain S, Johnson D (eds) Advances in Plant Breeding Strategies: Fruits. Springer, Cham, pp 253–294 Mimida N, Saito T, Moriguchi T, Suzuki A, Komori S, Wada M (2015) Expression of DORMANCY-ASSOCIATED MADS-BOX ( DAM )-like genes in apple. Biol Plant 59:237–244. 10.1007/s10535-015-0503-4 NCBI Resource Coordinators (2018) Database resources of the National Center for Biotechnology Information. Nucleic Acids Res 46(D1):D8–D13 Nishitani C, Saito T, Ubi BE, Shimizu T, Itai A, Saito T et al (2012) Transcriptome analysis of Pyrus pyrifolia leaf buds during transition from endodormancy to ecodormancy. Sci Hortic 147:49–55. 10.1016/j.scienta.2012.09.001 Niu R, Cheng Y, Wang F, Zhang Y, Wang C (2024) Transcriptome analysis provides insights into the safe overwintering of local peach flower buds. Curr Issues Mol Biol 46:13903–13921. 10.3390/cimb46120831 ORESA Oficina del Regante- Gobierno de Aragón [Internet]. 2025 [cited 2025 May 14]. Available from: http://aplicaciones.aragon.es/oresa Peel MC, Finlayson BL, McMahon TA (2007) Updated world map of the Köppen-Geiger climate classification. Hydrol Earth Syst Sci 11(5):1633–1644 Prudencio ÁS, Hoeberichts FA, Dicenta F, Martínez-Gómez P, Sánchez-Pérez R (2021) Identification of early and late flowering time candidate genes in endodormant and ecodormant almond flower buds. Tree Physiol 41(4):589–605. 10.1093/treephys/tpaa151 Puertes A, Polat H, Ramón-Núñez LA, González M, Ancillo G, Zuriaga E et al (2023) Single-bud expression analysis of bud dormancy factors in peach. Plants 12(14):2601. 10.3390/plants12142601 Quesada-Traver C, Guerrero BI, Badenes ML, Rodrigo J, Ríos G, Lloret A (2020) Structure and expression of bud dormancy-associated MADS-box genes ( DAM ) in European plum. Front Plant Sci 11:1288. 10.3389/fpls.2020.01288 Quesada-Traver C, Lloret A, Carretero-Paulet L, Badenes ML, Ríos G (2022) Evolutionary origin and functional specialization of dormancy-associated MADS box (DAM) proteins in perennial crops. BMC Plant Biol 22:473. 10.1186/s12870-022-03856-7 R Core Team (2023) R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna Richardson EA, Seeley SD, Walker DR (1974) A model for estimating the completion of rest for ‘Redhaven’ and ‘Elberta’ peach trees. HortScience 9:331–332 Ríos G, Leida C, Conejero A, Badenes ML (2014) Epigenetic regulation of bud dormancy events in perennial plants. Front Plant Sci 5:247. 10.3389/fpls.2014.00247 Rodrigo J (2000) Spring frosts in deciduous fruit trees—morphological damage and flower hardiness. Sci Hortic 85(3):155–173. 10.1016/S0304-4238(99)00150-8 Rohde A, Bhalerao RP (2007) Plant dormancy in the perennial context. Trends Plant Sci 12(5):217–223. 10.1016/j.tplants.2007.03.012 Ronquist F, Teslenko M, van der Mark P, Ayres DL, Darling A, Höhna S et al (2012) MrBayes 3.2: Efficient Bayesian phylogenetic inference and model choice across a large model space. Syst Biol 61(3):539–542. 10.1093/sysbio/sys029 Rothkegel K, Sánchez E, Montes C, Greve M, Tapia S, Bravo S et al (2017) DNA methylation and small interference RNAs participate in the regulation of MADS-box genes involved in dormancy in sweet cherry ( Prunus avium ). Tree Physiol 37(12):1739–1751. 10.1093/treephys/tpx055 Ruiz D, Campoy JA, Egea J (2007) Chilling and heat requirements of apricot cultivars for flowering. Environ Exp Bot 61(3):254–263. 10.1016/j.envexpbot.2007.06.008 Tabuenca MC (1964) Necesidades de frio invernal de variedades de albaricoquero, melocotonero y peral. Ann Aula Dei 7:113–132 Talavera G, Castresana J (2007) Improvement of phylogenies after removing divergent and ambiguously aligned blocks from protein sequence alignments. Syst Biol 56(4):564–577. 10.1080/10635150701472164 Thompson JD, Gibson TJ, Plewniak F, Jeanmougin F, Higgins DG (1997) The CLUSTAL_X windows interface: Flexible strategies for multiple sequence alignment aided by quality analysis tools. Nucleic Acids Res 25(24):4876–4882. 10.1093/nar/25.24.4876 Vimont N, Fouché M, Campoy JA, Tong M, Arkoun M, Yvin JC et al (2019) From bud formation to flowering: Transcriptomic state defines the cherry developmental phases of sweet cherry bud dormancy. BMC Genomics 20(1):974. 10.1186/s12864-019-6348-z Wickham H (2016) ggplot2: Elegant Graphics for Data Analysis. Springer-, New York Yamane H, Kashiwa Y, Ooka T, Tao R, Yonemori K (2008) Suppression subtractive hybridization and differential screening reveals endodormancy-associated expression of an SVP/AGL24-type MADS-box gene in lateral vegetative buds of Japanese apricot. J Am Soc Hortic Sci 133(5):708–716. 10.21273/JASHS.133.5.708 Yu J, Conrad AO, Decroocq V, Zhebentyayeva T, Williams DE, Bennett D et al (2020) Distinctive gene expression patterns define endodormancy to ecodormancy transition in apricot and peach. Front Plant Sci 11:180. 10.3389/fpls.2020.00180 Zhang Z, Zhuo X, Zhao K, Zheng T, Han Y, Yuan C et al (2018) Transcriptome profiles reveal the crucial roles of hormone and sugar in the bud dormancy of Prunus mume . Sci Rep 8:5090. 10.1038/s41598-018-23108-9 Zhao Y, Ma Y, Qiu H, Zhou L, He K, Ye Y (2025) Wake up: the regulation of dormancy release and bud break in perennial plants. Front Plant Sci 16:1553953. 10.3389/fpls.2025.1553953 Zhao YL, Li Y, Guo DD, Chen XJ, Cao K, Wu JL et al (2025) Spatiotemporally transcriptomic analyses of floral buds reveal the high-resolution landscape of flower development and dormancy regulation in peach. Hortic Res 12(5):uhaf029. 10.1093/hr/uhaf029 Zhu Y, Li Y, Xin D, Chen W, Shao X, Wang Y, Guo W (2015) RNA-Seq-based transcriptome analysis of dormant flower buds of Chinese cherry ( Prunus pseudocerasus ). Gene 555:362–376. 10.1016/j.gene.2014.11.032 Zhuang W, Gao Z, Wang L, Zhong W, Ni Z, Zhang Z (2013) Comparative proteomic and transcriptomic approaches to address the active role of GA4 in Japanese apricot flower bud dormancy release. J Exp Bot 64(16):4953–4966. 10.1093/jxb/ert284 Additional Declarations The authors declare no competing interests. Supplementary Files Additionalfile1.TableS1.xlsx Additional file 1: Table S1. mRNA-seq sample metadata, including: No., Original_code, Sample Name, Replicate, Location, Cultivar, Time_point, Concentration (ng/ul), Volume (ul), Total amount (ug), RIN, Sample QC Results, number of raw reads (M), number of unique mapped reads (M), and percentage of unique mapped reads as reported by the RSEM summary. Additionalfile2.TablesS2S5.xls Additional file 2: Table S2. Differentially expressed genes (padj<0.01) at each stage compared to the other two stages in Japanese plum cultivar "Hiromi Red" cultivar under semi-arid climate. The column "Up_Down" indicates whether the gene was found up- or down-regulated and the column "Time_point" indicates the stage (T0, T1 or T2) in which the test was performed. Table S3. Differentially expressed genes (padj<0.01) between the consecutive dormancy stages in Japanese plum cultivar "Hiromi Red" cultivar under semi-arid climate. The column "Transition" indicates whether the gene was found differentially expressed in the transition from early to mid-stage or from mid to late stage, and the column "Up_Down" indicates whether the gene is up or down regulated in the given transition. Table S4. Differentially expressed genes (padj<0.01) at each stage compared to the other two stages in Japanese plum cultivar "Crimson Glo" under semi-arid climate. The column "Up_Down" indicates whether the gene was found up- or down-regulated and the column "Time_point" indicates the stage (T0, T1 or T2) in which the test was performed. Table S5. Differentially expressed genes (padj<0.01) between the consecutive dormancy stages in Japanese plum cultivar "Crimson Glo" cultivar under semi-arid climate. The column "Transition" indicates whether the gene was found differentially expressed in the transition from early to mid-stage or from mid to late stage, and the column "Up_Down" indicates whether the gene is up or down regulated in the given transition. Additionalfile3.TablesS6S7.xlsx Additional file 3: Table S6.Significantly enriched Cluster of Orthologous Groups (COG) categories (adjusted P-value < 0.01) for differentially expressed genes (DEGs) identified across all dormancy stages in Japanese plum cultivar "Hiromi Red" under semi-arid climate. The dataset includes both upregulated and downregulated DEGs, without distinction by specific time points or regulation direction. The "COG_category" column indicates the functional classification of each DEG based on the COG database, while the "Description" column provides a brief summary of the associated functional category. Additional columns include the corresponding Gene Ontology (GO) terms, KEGG Orthology (KO) identifiers, and KEGG pathways associated with each DEG. Table S7. Significantly enriched Cluster of Orthologous Groups (COG) categories (adjusted P-value < 0.01) for differentially expressed genes (DEGs) identified across all dormancy stages in Japanese plum cultivar "Crimson Glo" under semi-arid climate. The dataset includes both upregulated and downregulated DEGs, without distinction by specific time points or regulation direction. The "COG_category" column indicates the functional classification of each DEG based on the COG database, while the "Description" column provides a brief summary of the associated functional category. Additional columns include the corresponding Gene Ontology (GO) terms, KEGG Orthology (KO) identifiers, and KEGG pathways associated with each DEG. Additionalfile4.TablesS8S11.xlsx Additional file 4: Table S8.Differentially expressed genes (padj<0.01) at each stage compared to the other two stages in Japanese plum cultivar "Hiromi Red" under Mediterranean subtropical climate. The column "Up_Down" indicates whether the gene was found up- or down-regulated and the column "Time_point" indicates the stage (T0, T1 or T2) in which the test was performed. Table S9. Differentially expressed genes (padj<0.01) between the consecutive dormancy stages in Japanese plum cultivar "Hiromi Red" under Mediterranean subtropical climate. The column "Transition" indicates whether the gene was found differentially expressed in the transition from early to mid-stage or from mid to late stage, and the column "Up_Down" indicates whether the gene is up or down regulated in the given transition. Table S10. Differentially expressed genes (padj<0.01) at each stage compared to the other two stages in Japanese plum cultivar "Crimson Glo" under Mediterranean subtropical climate. The column "Up_Down" indicates whether the gene was found up- or down-regulated and the column "Time_point" indicates the stage (T0, T1 or T2) in which the test was performed.Table S11. Differentially expressed genes (padj<0.01) between the consecutive dormancy stages in Japanese plum cultivar "Crimson Glo" under Mediterranean subtropical climate. The column "Transition" indicates whether the gene was found differentially expressed in the transition from early to mid-stage or from mid to late stage, and the column "Up_Down" indicates whether the gene is up or down regulated in the given transition. Additionalfile5.TablesS12S13.xlsx Additional file 5: Table S12. Significantly enriched Cluster of Orthologous Groups (COG) categories (adjusted P-value < 0.01) for differentially expressed genes (DEGs) identified across all dormancy stages in Japanese plum cultivar "Hiromi Red" under Mediterranean subtropical climate. The dataset includes both upregulated and downregulated DEGs, without distinction by specific time points or regulation direction. The "COG_category" column indicates the functional classification of each DEG based on the COG database, while the "Description" column provides a brief summary of the associated functional category. Additional columns include the corresponding Gene Ontology (GO) terms, KEGG Orthology (KO) identifiers, and KEGG pathways associated with each DEG. Table S13. Significantly enriched Cluster of Orthologous Groups (COG) categories (adjusted P-value < 0.01) for differentially expressed genes (DEGs) identified across all dormancy stages in Japanese plum cultivar "Crimson Glo" under Mediterranean subtropical climate. The dataset includes both upregulated and downregulated DEGs, without distinction by specific time points or regulation direction. The "COG_category" column indicates the functional classification of each DEG based on the COG database, while the "Description" column provides a brief summary of the associated functional category. Additional columns include the corresponding Gene Ontology (GO) terms, KEGG Orthology (KO) identifiers, and KEGG pathways associated with each DEG. Additionalfile6.TablesS14S18.xlsx Additional file 6: Table S14.List of DEGs (padj<0.01) common to both Japanese plum cultivars "Hiromi Red" and "Crimson Glo" under both semi-arid and Mediterranean subtropical climates at the full dormancy stage (T0).Table S15. List of DEGs (padj<0.01) uniquely identified in Japanese plum cultivar "Hiromi Red" under both semi-arid and Mediterranean subtropical climates at the full dormancy stage (T0). Table S16. List of DEGs (padj<0.01) uniquely identified in Japanese plum cultivar "Crimson Glo" under both semi-arid and Mediterranean subtropical climates at the full dormancy stage (T0). Table S17. List of DEGs (padj<0.01) identified under semi-arid climate conditions for both Japanese plum cultivars "Hiromi Red" and "Crimson Glo" at the full dormancy stage (T0). Table S18. List of DEGs (padj<0.01) identified under Mediterranean subtropical climate conditions for both Japanese plum cultivars "Hiromi Red" and "Crimson Glo" at the full dormancy stage (T0). Additionalfile7.TablesS19S22.xlsx Additional file 7: Table S19. List of DEGs (padj<0.01) uniquely identified in Japanese plum cultivar "Hiromi Red" under both semi-arid and Mediterranean subtropical climates at the dormancy release stage (T1). Table S20. List of DEGs (padj<0.01) uniquely identified in Japanese plum cultivar "Crimson Glo" under both semi-arid and Mediterranean subtropical climates at the dormancy release stage (T1). Table S21. List of DEGs (padj<0.01) identified under semi-arid climate conditions for both Japanese plum cultivars "Hiromi Red" and "Crimson Glo" at the dormancy release stage (T1). Table S22. List of DEGs (padj<0.01) identified under Mediterranean subtropical climate conditions for both Japanese plum cultivars "Hiromi Red" and "Crimson Glo" at the dormancy release stage (T1). Additionalfile8.TablesS23S27.xlsx Additional file 8: Table S23. List of DEGs (padj<0.01) common to both Japanese plum cultivars "Hiromi Red" and "Crimson Glo" under both semi-arid and Mediterranean subtropical climates at the full recovery stage (T2). Table S24. List of DEGs (padj<0.01) uniquely identified in Japanese plum cultivar "Hiromi Red" under both semi-arid and Mediterranean subtropical climates at the full recovery stage (T2). Table S25. List of DEGs (padj<0.01) uniquely identified in Japanese plum cultivar "Crimson Glo" under both semi-arid and Mediterranean subtropical climates at the full recovery stage (T2). Table S26. List of DEGs (padj<0.01) identified under semi-arid climate conditions for both Japanese plum cultivars "Hiromi Red" and "Crimson Glo" at the full recovery stage (T2). Table S27. List of DEGs (padj<0.01) identified under Mediterranean subtropical climate conditions for both Japanese plum cultivars "Hiromi Red" and "Crimson Glo" at the full recovery stage (T2). Additionalfile9.TablesS28S30.xlsx Additional file 9: Table S28. Enriched DEGs (padj<0.001) identified at the full dormancy stage (T0) under both semi-arid and Mediterranean subtropical climate conditions. The column "Combination" specifies the comparison to which each DEG belongs, including DEGs uniquely identified in Japanese plum cultivars "Hiromi Red" or "Crimson Glo," those common to both cultivars, and those specific to a particular climate. The "COG_category" column indicates the functional classification of each DEG based on the Cluster of Orthologous Groups (COG), while the "Description" column provides a brief summary of the associated functional category. Additional columns display the corresponding Gene Ontology (GO) terms, KEGG Orthology (KO) identifiers, and KEGG pathways associated with each DEG. Table S29.Enriched DEGs (padj<0.001) identified at the dormancy release stage (T1) under both semi-arid and Mediterranean subtropical climate conditions. The column "Combination" specifies the comparison to which each DEG belongs, including DEGs uniquely identified in Japanese plum cultivars "Hiromi Red" or "Crimson Glo," and those specific to a particular climate. The "COG_category" column indicates the functional classification of each DEG based on the Cluster of Orthologous Groups (COG), while the "Description" column provides a brief summary of the associated functional category. Additional columns display the corresponding Gene Ontology (GO) terms, KEGG Orthology (KO) identifiers, and KEGG pathways associated with each DEG. Table S30.Enriched DEGs (padj<0.001) identified at the full recovery stage (T2) under both semi-arid and Mediterranean subtropical climate conditions. The column "Combination" specifies the comparison to which each DEG belongs, including DEGs uniquely identified in Japanese plum cultivars "Hiromi Red" or "Crimson Glo," those common to both cultivars, and those specific to a particular climate. The "COG_category" column indicates the functional classification of each DEG based on the Cluster of Orthologous Groups (COG), while the "Description" column provides a brief summary of the associated functional category. Additional columns display the corresponding Gene Ontology (GO) terms, KEGG Orthology (KO) identifiers, and KEGG pathways associated with each DEG. Additionalfile10.FigureS1.tif Additional file 10: Figure S1. Number of aligned reads in each of the three replicates of the flower bud mRNA-seq samples. Read counts are shown in millions (M). Additionalfile11.FigureS2.tif Additional file 11: Figure S2.mRNA-seq dataset overview for Japanese plum cultivars "Hiromi Red" (blue) and "Crimson Glo" (red) under semi-arid and Mediterranean subtropical climate conditions across three dormancy stages using variance stabilizing transformation (VST). A) Boxplots (B) Hierarchical clustering dendrogram and (C) PCA of the mRNA-seq libraries, both showing that replicates are similar with each other. (D). Heatmap showing the relative expression levels of genes of all the stage-specific samples. Only genes with positive variance were included to highlight the most variable genes. Rows represent genes, and columns represent samples grouped by Stage, Cultivar, and Climate. Both genes and samples were clustered using Euclidean distance and the complete linkage method. Full dormancy (T0): light color; dormancy release (T1): normal color, and full recovery (T2): darker color. Semi-arid climate is represented by circles (○), while Mediterranean subtropical climate is represented by triangles (△). Additionalfile12.FigureS3.tif Additional file 12: Figure S3.Significantly enriched Cluster of Orthologous Groups (COG) categories (adjusted P-value < 0.01) for downregulated and upregulated genes at each dormancy stage in Japanese plum cultivar " Hiromi Red " (A and B, respectively) under semi-arid climate. Additionalfile13.FigureS4.tif Additional file 13: Figure S4.Significantly enriched Cluster of Orthologous Groups (COG) categories (adjusted P-value < 0.01) for downregulated and upregulated genes at each dormancy stage in Japanese plum cultivar " Crimson Glo " (A and B, respectively) under semi-arid climate. Additionalfile14.FigureS5.tif Additional file 14: Figure S5. Significantly enriched Cluster of Orthologous Groups (COG) categories (adjusted P-value < 0.01) for downregulated and upregulated genes at each dormancy stage in Japanese plum cultivar " Hiromi Red " (A and B, respectively) under Mediterranean subtropical climate. Additionalfile15.FigureS6.tif Additional file 15: Figure S6. Significantly enriched Cluster of Orthologous Groups (COG) categories (adjusted P-value < 0.01) for downregulated and upregulated genes at each dormancy stage in Japanese plum cultivar " Crimson Glo " (A and B, respectively) under Mediterranean subtropical climate. Additionalfile16.FigureS7.pdf Additional file 16: Figure S7. Phylogenetic tree of the DAM protein family in Prunus species, inferred from Bayesian analysis. Numbers adjacent to the nodes indicate posterior probabilities; only nodes with values greater than 0.7 are labeled. The scale bar represents 0.5 amino acid substitutions per site. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7114924","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":484728632,"identity":"bdf648b8-eb40-4cd8-a8e3-a5aa3bf64d54","order_by":0,"name":"Sara Herrera","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA50lEQVRIiWNgGAWjYDACCSjNDyJ4gJiNaC2SDSRrMTgA1UIQyM9uPva5ouKevPHx5oMf3jDY2fOxH2B8+AOPFoM7x5JnnjlTbLjtzLFkyTkMyYltPAnMxvisM5DIMWZsbEtg3HYjx0Cah+FAApsEA5s0XofNyP/M2PgvwX7z/PeffwO12AO1sP/E5zCGGznMjI0NCYkbJHjYQLYwtgFtwRsOBjfSjBkbjiUkzziTZmY5xwDkl8RmaXxa5GckP2ZsqEmw7W8//PjGmwo7e/n2wwc/4nUYmqUggrGBeA2jYBSMglEwCrACAGoVRoFKQmD2AAAAAElFTkSuQmCC","orcid":"https://orcid.org/0000-0002-3947-5623","institution":"Estación Experimental de Aula Dei (EEAD-CSIC)","correspondingAuthor":true,"prefix":"","firstName":"Sara","middleName":"","lastName":"Herrera","suffix":""},{"id":484728633,"identity":"6d94ca56-838e-4b93-bd7f-96ab42d6b624","order_by":1,"name":"José Ignacio Hormaza","email":"","orcid":"https://orcid.org/0000-0001-5449-7444","institution":"Instituto de Hortofruticultura Subtropical y Mediterránea La Mayora (IHSM La Mayora-CSIC-UMA)","correspondingAuthor":false,"prefix":"","firstName":"José","middleName":"Ignacio","lastName":"Hormaza","suffix":""},{"id":484728634,"identity":"32b3fcde-8494-4350-8b94-99312e2a1645","order_by":2,"name":"Guillem Ylla","email":"","orcid":"https://orcid.org/0000-0003-4540-0131","institution":"Laboratory of Bioinformatics and Genome Biology, Jagiellonian University","correspondingAuthor":false,"prefix":"","firstName":"Guillem","middleName":"","lastName":"Ylla","suffix":""},{"id":484728635,"identity":"4c3ef181-381f-4ddb-825a-fd594a9ba2fa","order_by":3,"name":"Javier Rodrigo","email":"","orcid":"https://orcid.org/0000-0002-8321-1764","institution":"Centro de Investigación y Tecnología Agroalimentaria de Aragón (CITA)","correspondingAuthor":false,"prefix":"","firstName":"Javier","middleName":"","lastName":"Rodrigo","suffix":""},{"id":484728636,"identity":"bccf2ec6-a089-4e24-8466-16ae422c83c5","order_by":4,"name":"Jorge Lora","email":"","orcid":"https://orcid.org/0000-0001-9713-0431","institution":"Instituto de Hortofruticultura Subtropical y Mediterránea La Mayora (IHSM La Mayora-CSIC-UMA)","correspondingAuthor":false,"prefix":"","firstName":"Jorge","middleName":"","lastName":"Lora","suffix":""}],"badges":[],"createdAt":"2025-07-13 18:09:38","currentVersionCode":1,"declarations":{"humanSubjects":false,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-7114924/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7114924/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":86765551,"identity":"9e51c6b2-e71a-427e-9250-d33e1bc10ddc","added_by":"auto","created_at":"2025-07-15 10:58:41","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":186632,"visible":true,"origin":"","legend":"\u003cp\u003eEstimation of breaking of endodormancy date (❆) for two Japanese plum cultivars (\"Hiromi Red\" and \"Crimson Glo\") under semi-arid (○) and Mediterranean subtropical (△) climates using an experimental methodology. The lines represent the flower bud weight under field conditions (black square) and after 8 days in a growth chamber (gray rhombus). Chilling requirements were considered fulfilled when the increase in flower bud weight in the growth chamber was 30% greater than that observed under field conditions (n = 10). A) Hiromi Red under semi-arid climate. B) Crimson Glo under semi-arid climate. C) Hiromi Red under Mediterranean subtropical climate. D) Crimson Glo under Mediterranean subtropical climate.\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-7114924/v1/9a1c5fe26f1f6af4c4003470.png"},{"id":86766094,"identity":"84739d2f-720e-4714-9774-4f76e7dc4b17","added_by":"auto","created_at":"2025-07-15 11:06:41","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":249682,"visible":true,"origin":"","legend":"\u003cp\u003emRNA-seq dataset overview for Japanese plum cultivars \"Hiromi Red\" (blue) and \"Crimson Glo\" (red) under semi-arid climate conditions across three dormancy stages. (A) Hierarchical clustering dendrogram and (B) PCA of the mRNA-seq libraries, both showing that replicates are similar with each other. (C) Number of significant stage-specific genes in \"Hiromi Red\" (adjusted P-value \u0026lt; 0.01; black: upregulated genes; white: downregulated genes). See Table S2 for the gene list. (D) Number of differentially expressed genes between early and mid-stages, and between mid and late stages in \"Hiromi Red\" (adjusted P-value \u0026lt; 0.01; black: upregulated genes; white: downregulated genes). See Table S3 for the gene list. (E) Number of significantly stage-specific genes in \"Crimson Glo\" (adjusted P-value \u0026lt; 0.01; black: upregulated genes; white: downregulated genes). See Table S4 for the gene list. (F) Number of differentially expressed genes between early and mid-stages, and between mid and late stages in \"Crimson Glo\" (adjusted P-value \u0026lt; 0.01; black: upregulated genes; white: downregulated genes). See Table S5 for the gene list. Full dormancy (T0): light color; dormancy release (T1): normal color, and full recovery (T2): darker color.\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-7114924/v1/de94577d38a3e7620b05ab76.png"},{"id":86766095,"identity":"05a0a422-0a56-4fcd-9a0a-2eade28e473b","added_by":"auto","created_at":"2025-07-15 11:06:41","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":264238,"visible":true,"origin":"","legend":"\u003cp\u003emRNA-seq dataset overview for Japanese plum cultivars \"Hiromi Red\" (blue) and \"Crimson Glo\" (red) under Mediterranean subtropical climate conditions across three dormancy stages. (A) Hierarchical clustering dendrogram and (B) PCA of the mRNA-seq libraries, both showing that replicates are similar with each other. (C) Number of significant stage-specific genes in \"Hiromi Red\" (adjusted P-value \u0026lt; 0.01; black: upregulated genes; white: downregulated genes). See Table S8 for the gene list. (D) Number of differentially expressed genes between early and mid-stages, and between mid and late stages in \"Hiromi Red\" (adjusted P-value \u0026lt; 0.01; black: upregulated genes; white: downregulated genes). See Table S9 for the gene list. (E) Number of significantly stage-specific genes in \"Crimson Glo\" (adjusted P-value \u0026lt; 0.01; black: upregulated genes; white: downregulated genes). See Table S10 for the gene list. (F) Number of differentially expressed genes between early and mid-stages, and between mid and late stages in \"Crimson Glo\" (adjusted P-value \u0026lt; 0.01; black: upregulated genes; white: downregulated genes). See Table S11 for the gene list. Full dormancy (T0): light color; dormancy release (T1): normal color, and full recovery (T2): darker color.\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-7114924/v1/9b8a92d14ac7c9fffb0482b3.png"},{"id":86765556,"identity":"c99dd5e3-ad26-42f7-acd8-983a8ac25681","added_by":"auto","created_at":"2025-07-15 10:58:41","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":606478,"visible":true,"origin":"","legend":"\u003cp\u003eNormalized expression counts by VST for Japanese plum cultivars \"\u003cem\u003eHiromi Red\u003c/em\u003e\" (blue) and \"\u003cem\u003eCrimson Glo\u003c/em\u003e\" (red) under semi-arid and Mediterranean subtropical climate conditions across three dormancy stages in known markers: A) \u003cem\u003eSTRESS-ASSOCIATED PROTEIN1\u003c/em\u003e (\u003cem\u003eSAP1\u003c/em\u003e); B) \u003cem\u003eALLENE OXIDE CYCLASE\u003c/em\u003e (\u003cem\u003eAOC\u003c/em\u003e)-like 1; C) \u003cem\u003eALLENE OXIDE CYCLASE\u003c/em\u003e(\u003cem\u003eAOC\u003c/em\u003e)-like 2; D) \u003cem\u003ePshDAM1\u003c/em\u003e; E) \u003cem\u003ePshDAM6\u003c/em\u003e; F) \u003cem\u003eFLOWERING LOCUS T\u003c/em\u003e (\u003cem\u003eFT\u003c/em\u003e); G) \u003cem\u003eTARGET OF RAPAMYCIN\u003c/em\u003e (\u003cem\u003eTOR\u003c/em\u003e)-like; H) \u003cem\u003eTONOPLAST INTRINSIC PROTEIN\u003c/em\u003e (\u003cem\u003eTIP\u003c/em\u003e)-like; and I) \u003cem\u003eLIPOXYGENASE \u003c/em\u003e(\u003cem\u003eLOX\u003c/em\u003e)-like. Full dormancy (T0): light color; dormancy release (T1): normal color, and full recovery (T2): darker color. Semi-arid climate is represented by circles (○), while Mediterranean subtropical climate is represented by triangles (△).\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-7114924/v1/3b856a40fe7d50304038c1f1.png"},{"id":86766096,"identity":"00ccbbab-4c48-4546-ae27-72bb951913ae","added_by":"auto","created_at":"2025-07-15 11:06:41","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":177243,"visible":true,"origin":"","legend":"\u003cp\u003eUpSet plots showing the differential gene expression (DEG) profiles across three dormancy stages: (A) \u003cstrong\u003eFull dormancy\u003c/strong\u003e, (B) \u003cstrong\u003eDormancy release\u003c/strong\u003e, and (C) \u003cstrong\u003eFull recovery.\u003c/strong\u003e Each plot compares the DEGs in both Japanese plum cultivars \"Hiromi Red\" and \"Crimson Glo\" under both climate conditions; semi-arid (○) and Mediterranean subtropical (△). The intersections in the UpSet plots highlight the overlap and unique DEG sets across cultivars and climate conditions at each stage, with the bars representing the number of DEGs in each combination.\u003c/p\u003e","description":"","filename":"Figure5.png","url":"https://assets-eu.researchsquare.com/files/rs-7114924/v1/9da37e17af4789035f1dcab1.png"},{"id":86765564,"identity":"d7a58874-c24f-4338-87c6-ed6155948dcc","added_by":"auto","created_at":"2025-07-15 10:58:42","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":590709,"visible":true,"origin":"","legend":"\u003cp\u003eNumber distribution of Clusters of Orthologous Groups (COG) functional classification analysis among 23 categories using eggNOG-mapper. (A) \u003cstrong\u003eFull dormancy\u003c/strong\u003e, (B) \u003cstrong\u003eDormancy release\u003c/strong\u003e, and (C) \u003cstrong\u003eFull recovery.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Figure6.png","url":"https://assets-eu.researchsquare.com/files/rs-7114924/v1/84a2779c0cc6c3aa1d3a3b61.png"},{"id":86769011,"identity":"3c621bd9-6a67-40c3-95c5-51cacb1528e8","added_by":"auto","created_at":"2025-07-15 11:30:43","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3092325,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7114924/v1/469d61f8-39c9-4631-8d97-092c687c7915.pdf"},{"id":86765549,"identity":"09fcdb06-19fc-41de-b75f-b8734045f6ff","added_by":"auto","created_at":"2025-07-15 10:58:41","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":14617,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAdditional file 1: Table S1\u003c/strong\u003e. mRNA-seq sample metadata, including: No., Original_code, Sample Name, Replicate, Location, Cultivar, Time_point, Concentration (ng/ul), Volume (ul), Total amount (ug), RIN, Sample QC Results, number of raw reads (M), number of unique mapped reads (M), and percentage of unique mapped reads as reported by the RSEM summary.\u003c/p\u003e","description":"","filename":"Additionalfile1.TableS1.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7114924/v1/0b9f7e6fab48e66a6f41cb66.xlsx"},{"id":86765567,"identity":"0afddbc2-86ab-442d-a56b-2ca0196ebcb7","added_by":"auto","created_at":"2025-07-15 10:58:42","extension":"xls","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":9895424,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAdditional file 2: Table S2\u003c/strong\u003e. Differentially expressed genes (padj\u0026lt;0.01) at each stage compared to the other two stages in Japanese plum cultivar \"Hiromi Red\" cultivar under semi-arid climate. The column \"Up_Down\" indicates whether the gene was found up- or down-regulated and the column \"Time_point\" indicates the stage (T0, T1 or T2) in which the test was performed. \u003cstrong\u003eTable S3\u003c/strong\u003e. Differentially expressed genes (padj\u0026lt;0.01) between the consecutive dormancy stages in Japanese plum cultivar \"Hiromi Red\" cultivar under semi-arid climate. The column \"Transition\" indicates whether the gene was found differentially expressed in the transition from early to mid-stage or from mid to late stage, and the column \"Up_Down\" indicates whether the gene is up or down regulated in the given transition.\u003cstrong\u003e Table S4\u003c/strong\u003e. Differentially expressed genes (padj\u0026lt;0.01) at each stage compared to the other two stages in Japanese plum cultivar \"Crimson Glo\" under semi-arid climate. The column \"Up_Down\" indicates whether the gene was found up- or down-regulated and the column \"Time_point\" indicates the stage (T0, T1 or T2) in which the test was performed.\u003cstrong\u003e Table S5\u003c/strong\u003e. Differentially expressed genes (padj\u0026lt;0.01) between the consecutive dormancy stages in Japanese plum cultivar \"Crimson Glo\" cultivar under semi-arid climate. The column \"Transition\" indicates whether the gene was found differentially expressed in the transition from early to mid-stage or from mid to late stage, and the column \"Up_Down\" indicates whether the gene is up or down regulated in the given transition.\u003c/p\u003e","description":"","filename":"Additionalfile2.TablesS2S5.xls","url":"https://assets-eu.researchsquare.com/files/rs-7114924/v1/9e152284ced303f6ecb8cfa5.xls"},{"id":86766101,"identity":"cc964b91-201f-4910-9992-4ad27c7f86fb","added_by":"auto","created_at":"2025-07-15 11:06:42","extension":"xlsx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":2547122,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAdditional file 3: Table S6.\u003c/strong\u003eSignificantly enriched Cluster of Orthologous Groups (COG) categories (adjusted P-value \u0026lt; 0.01) for differentially expressed genes (DEGs) identified across all dormancy stages in Japanese plum cultivar \"Hiromi Red\" under semi-arid climate. The dataset includes both upregulated and downregulated DEGs, without distinction by specific time points or regulation direction. The \"COG_category\" column indicates the functional classification of each DEG based on the COG database, while the \"Description\" column provides a brief summary of the associated functional category. Additional columns include the corresponding Gene Ontology (GO) terms, KEGG Orthology (KO) identifiers, and KEGG pathways associated with each DEG.\u003cstrong\u003e Table S7\u003c/strong\u003e. Significantly enriched Cluster of Orthologous Groups (COG) categories (adjusted P-value \u0026lt; 0.01) for differentially expressed genes (DEGs) identified across all dormancy stages in Japanese plum cultivar \"Crimson Glo\" under semi-arid climate. The dataset includes both upregulated and downregulated DEGs, without distinction by specific time points or regulation direction. The \"COG_category\" column indicates the functional classification of each DEG based on the COG database, while the \"Description\" column provides a brief summary of the associated functional category. Additional columns include the corresponding Gene Ontology (GO) terms, KEGG Orthology (KO) identifiers, and KEGG pathways associated with each DEG.\u003c/p\u003e","description":"","filename":"Additionalfile3.TablesS6S7.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7114924/v1/dddf23a1dcb54d8399160383.xlsx"},{"id":86765569,"identity":"72f09e6b-c51b-43df-af01-fada439e85c3","added_by":"auto","created_at":"2025-07-15 10:58:42","extension":"xlsx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":6966304,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAdditional file 4: Table S8.\u003c/strong\u003eDifferentially expressed genes (padj\u0026lt;0.01) at each stage compared to the other two stages in Japanese plum cultivar \"Hiromi Red\" under Mediterranean subtropical climate. The column \"Up_Down\" indicates whether the gene was found up- or down-regulated and the column \"Time_point\" indicates the stage (T0, T1 or T2) in which the test was performed.\u003cstrong\u003e Table S9\u003c/strong\u003e. Differentially expressed genes (padj\u0026lt;0.01) between the consecutive dormancy stages in Japanese plum cultivar \"Hiromi Red\" under Mediterranean subtropical climate. The column \"Transition\" indicates whether the gene was found differentially expressed in the transition from early to mid-stage or from mid to late stage, and the column \"Up_Down\" indicates whether the gene is up or down regulated in the given transition.\u003cstrong\u003e Table S10\u003c/strong\u003e. Differentially expressed genes (padj\u0026lt;0.01) at each stage compared to the other two stages in Japanese plum cultivar \"Crimson Glo\" under Mediterranean subtropical climate. The column \"Up_Down\" indicates whether the gene was found up- or down-regulated and the column \"Time_point\" indicates the stage (T0, T1 or T2) in which the test was performed.\u003cstrong\u003eTable S11.\u003c/strong\u003e Differentially expressed genes (padj\u0026lt;0.01) between the consecutive dormancy stages in Japanese plum cultivar \"Crimson Glo\" under Mediterranean subtropical climate. The column \"Transition\" indicates whether the gene was found differentially expressed in the transition from early to mid-stage or from mid to late stage, and the column \"Up_Down\" indicates whether the gene is up or down regulated in the given transition.\u003c/p\u003e","description":"","filename":"Additionalfile4.TablesS8S11.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7114924/v1/0c4ccccce6fd826cbd5427fc.xlsx"},{"id":86767510,"identity":"b6d2aa63-a045-4c9c-9efb-59ca810a152c","added_by":"auto","created_at":"2025-07-15 11:14:42","extension":"xlsx","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":3680573,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAdditional file 5: Table S12\u003c/strong\u003e. Significantly enriched Cluster of Orthologous Groups (COG) categories (adjusted P-value \u0026lt; 0.01) for differentially expressed genes (DEGs) identified across all dormancy stages in Japanese plum cultivar \"Hiromi Red\" under Mediterranean subtropical climate. The dataset includes both upregulated and downregulated DEGs, without distinction by specific time points or regulation direction. The \"COG_category\" column indicates the functional classification of each DEG based on the COG database, while the \"Description\" column provides a brief summary of the associated functional category. Additional columns include the corresponding Gene Ontology (GO) terms, KEGG Orthology (KO) identifiers, and KEGG pathways associated with each DEG.\u003cstrong\u003e Table S13\u003c/strong\u003e. Significantly enriched Cluster of Orthologous Groups (COG) categories (adjusted P-value \u0026lt; 0.01) for differentially expressed genes (DEGs) identified across all dormancy stages in Japanese plum cultivar \"Crimson Glo\" under Mediterranean subtropical climate. The dataset includes both upregulated and downregulated DEGs, without distinction by specific time points or regulation direction. The \"COG_category\" column indicates the functional classification of each DEG based on the COG database, while the \"Description\" column provides a brief summary of the associated functional category. Additional columns include the corresponding Gene Ontology (GO) terms, KEGG Orthology (KO) identifiers, and KEGG pathways associated with each DEG.\u003c/p\u003e","description":"","filename":"Additionalfile5.TablesS12S13.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7114924/v1/2878ebfab0f16630c6184b2d.xlsx"},{"id":86766102,"identity":"792f3903-e000-45df-8173-f62a8aba1f41","added_by":"auto","created_at":"2025-07-15 11:06:42","extension":"xlsx","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":26075,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAdditional file 6: Table S14.\u003c/strong\u003eList of DEGs (padj\u0026lt;0.01) common to both Japanese plum cultivars \"Hiromi Red\" and \"Crimson Glo\" under both semi-arid and Mediterranean subtropical climates at the full dormancy stage (T0).\u003cstrong\u003eTable S15\u003c/strong\u003e. List of DEGs (padj\u0026lt;0.01) uniquely identified in Japanese plum cultivar \"Hiromi Red\" under both semi-arid and Mediterranean subtropical climates at the full dormancy stage (T0). \u003cstrong\u003eTable S16\u003c/strong\u003e. List of DEGs (padj\u0026lt;0.01) uniquely identified in Japanese plum cultivar \"Crimson Glo\" under both semi-arid and Mediterranean subtropical climates at the full dormancy stage (T0). \u003cstrong\u003eTable S17.\u003c/strong\u003e List of DEGs (padj\u0026lt;0.01) identified under semi-arid climate conditions for both Japanese plum cultivars \"Hiromi Red\" and \"Crimson Glo\" at the full dormancy stage (T0). \u003cstrong\u003eTable S18.\u003c/strong\u003e List of DEGs (padj\u0026lt;0.01) identified under Mediterranean subtropical climate conditions for both Japanese plum cultivars \"Hiromi Red\" and \"Crimson Glo\" at the full dormancy stage (T0).\u003c/p\u003e","description":"","filename":"Additionalfile6.TablesS14S18.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7114924/v1/950d19c56e4604e2c6cc9d96.xlsx"},{"id":86765553,"identity":"407690d1-2cf2-46c9-855b-9273340b3edd","added_by":"auto","created_at":"2025-07-15 10:58:41","extension":"xlsx","order_by":7,"title":"","display":"","copyAsset":false,"role":"supplement","size":19354,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAdditional file 7: Table S19\u003c/strong\u003e. List of DEGs (padj\u0026lt;0.01) uniquely identified in Japanese plum cultivar \"Hiromi Red\" under both semi-arid and Mediterranean subtropical climates at the dormancy release stage (T1). \u003cstrong\u003eTable S20\u003c/strong\u003e. List of DEGs (padj\u0026lt;0.01) uniquely identified in Japanese plum cultivar \"Crimson Glo\" under both semi-arid and Mediterranean subtropical climates at the dormancy release stage (T1). \u003cstrong\u003eTable S21\u003c/strong\u003e. List of DEGs (padj\u0026lt;0.01) identified under semi-arid climate conditions for both Japanese plum cultivars \"Hiromi Red\" and \"Crimson Glo\" at the dormancy release stage (T1). \u003cstrong\u003eTable S22\u003c/strong\u003e. List of DEGs (padj\u0026lt;0.01) identified under Mediterranean subtropical climate conditions for both Japanese plum cultivars \"Hiromi Red\" and \"Crimson Glo\" at the dormancy release stage (T1).\u003c/p\u003e","description":"","filename":"Additionalfile7.TablesS19S22.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7114924/v1/c3a3d57b125ce35505a2c432.xlsx"},{"id":86765566,"identity":"b72c456f-7eed-465a-8382-4ccbdd0f920e","added_by":"auto","created_at":"2025-07-15 10:58:42","extension":"xlsx","order_by":8,"title":"","display":"","copyAsset":false,"role":"supplement","size":34774,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAdditional file 8: Table S23\u003c/strong\u003e. List of DEGs (padj\u0026lt;0.01) common to both Japanese plum cultivars \"Hiromi Red\" and \"Crimson Glo\" under both semi-arid and Mediterranean subtropical climates at the full recovery stage (T2). \u003cstrong\u003eTable S24\u003c/strong\u003e. List of DEGs (padj\u0026lt;0.01) uniquely identified in Japanese plum cultivar \"Hiromi Red\" under both semi-arid and Mediterranean subtropical climates at the full recovery stage (T2). \u003cstrong\u003eTable S25.\u003c/strong\u003e List of DEGs (padj\u0026lt;0.01) uniquely identified in Japanese plum cultivar \"Crimson Glo\" under both semi-arid and Mediterranean subtropical climates at the full recovery stage (T2). \u003cstrong\u003eTable S26\u003c/strong\u003e. List of DEGs (padj\u0026lt;0.01) identified under semi-arid climate conditions for both Japanese plum cultivars \"Hiromi Red\" and \"Crimson Glo\" at the full recovery stage (T2). \u003cstrong\u003eTable S27\u003c/strong\u003e. List of DEGs (padj\u0026lt;0.01) identified under Mediterranean subtropical climate conditions for both Japanese plum cultivars \"Hiromi Red\" and \"Crimson Glo\" at the full recovery stage (T2).\u003c/p\u003e","description":"","filename":"Additionalfile8.TablesS23S27.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7114924/v1/e44eb567d0c159915837a42d.xlsx"},{"id":86768004,"identity":"84921459-65c5-4e66-8a10-c42328b8d6f2","added_by":"auto","created_at":"2025-07-15 11:22:42","extension":"xlsx","order_by":9,"title":"","display":"","copyAsset":false,"role":"supplement","size":859741,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAdditional file 9: Table S28\u003c/strong\u003e. Enriched DEGs (padj\u0026lt;0.001) identified at the full dormancy stage (T0) under both semi-arid and Mediterranean subtropical climate conditions. The column \"Combination\" specifies the comparison to which each DEG belongs, including DEGs uniquely identified in Japanese plum cultivars \"Hiromi Red\" or \"Crimson Glo,\" those common to both cultivars, and those specific to a particular climate. The \"COG_category\" column indicates the functional classification of each DEG based on the Cluster of Orthologous Groups (COG), while the \"Description\" column provides a brief summary of the associated functional category. Additional columns display the corresponding Gene Ontology (GO) terms, KEGG Orthology (KO) identifiers, and KEGG pathways associated with each DEG.\u003cstrong\u003e Table S29.\u003c/strong\u003eEnriched DEGs (padj\u0026lt;0.001) identified at the dormancy release stage (T1) under both semi-arid and Mediterranean subtropical climate conditions. The column \"Combination\" specifies the comparison to which each DEG belongs, including DEGs uniquely identified in Japanese plum cultivars \"Hiromi Red\" or \"Crimson Glo,\" and those specific to a particular climate. The \"COG_category\" column indicates the functional classification of each DEG based on the Cluster of Orthologous Groups (COG), while the \"Description\" column provides a brief summary of the associated functional category. Additional columns display the corresponding Gene Ontology (GO) terms, KEGG Orthology (KO) identifiers, and KEGG pathways associated with each DEG.\u003cstrong\u003e Table S30.\u003c/strong\u003eEnriched DEGs (padj\u0026lt;0.001) identified at the full recovery stage (T2) under both semi-arid and Mediterranean subtropical climate conditions. The column \"Combination\" specifies the comparison to which each DEG belongs, including DEGs uniquely identified in Japanese plum cultivars \"Hiromi Red\" or \"Crimson Glo,\" those common to both cultivars, and those specific to a particular climate. The \"COG_category\" column indicates the functional classification of each DEG based on the Cluster of Orthologous Groups (COG), while the \"Description\" column provides a brief summary of the associated functional category. Additional columns display the corresponding Gene Ontology (GO) terms, KEGG Orthology (KO) identifiers, and KEGG pathways associated with each DEG.\u003c/p\u003e","description":"","filename":"Additionalfile9.TablesS28S30.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7114924/v1/baf14a477fe77f6e5a8ee3f3.xlsx"},{"id":86766104,"identity":"246db034-0f69-4861-a899-bcf1bc683f43","added_by":"auto","created_at":"2025-07-15 11:06:42","extension":"tif","order_by":10,"title":"","display":"","copyAsset":false,"role":"supplement","size":1212208,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAdditional file 10: Figure S1.\u003c/strong\u003e Number of aligned reads in each of the three replicates of the flower bud mRNA-seq samples. Read counts are shown in millions (M).\u003c/p\u003e","description":"","filename":"Additionalfile10.FigureS1.tif","url":"https://assets-eu.researchsquare.com/files/rs-7114924/v1/2e7fb04edf488a558fd25d35.tif"},{"id":86765571,"identity":"6a911431-0ec3-4a1e-adf6-78efccfbbc6f","added_by":"auto","created_at":"2025-07-15 10:58:42","extension":"tif","order_by":11,"title":"","display":"","copyAsset":false,"role":"supplement","size":730816,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAdditional file 11: Figure S2.\u003c/strong\u003emRNA-seq dataset overview for Japanese plum cultivars \"Hiromi Red\" (blue) and \"Crimson Glo\" (red) under semi-arid and Mediterranean subtropical climate conditions across three dormancy stages using variance stabilizing transformation (VST). A) Boxplots (B) Hierarchical clustering dendrogram and (C) PCA of the mRNA-seq libraries, both showing that replicates are similar with each other. (D). Heatmap showing the relative expression levels of genes of all the stage-specific samples. Only genes with positive variance were included to highlight the most variable genes. Rows represent genes, and columns represent samples grouped by Stage, Cultivar, and Climate. Both genes and samples were clustered using Euclidean distance and the complete linkage method. Full dormancy (T0): light color; dormancy release (T1): normal color, and full recovery (T2): darker color. Semi-arid climate is represented by circles (○), while Mediterranean subtropical climate is represented by triangles (△).\u003c/p\u003e","description":"","filename":"Additionalfile11.FigureS2.tif","url":"https://assets-eu.researchsquare.com/files/rs-7114924/v1/3c7425fb40946914f0e4954b.tif"},{"id":86766105,"identity":"67b768da-2305-4fa7-98fe-59b5f25c161e","added_by":"auto","created_at":"2025-07-15 11:06:42","extension":"tif","order_by":12,"title":"","display":"","copyAsset":false,"role":"supplement","size":7944620,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAdditional file 12: Figure S3.\u003c/strong\u003eSignificantly enriched Cluster of Orthologous Groups (COG) categories (adjusted P-value \u0026lt; 0.01) for downregulated and upregulated genes at each dormancy stage in Japanese plum cultivar \"\u003cem\u003eHiromi Red\u003c/em\u003e\" (A and B, respectively) under semi-arid climate.\u003c/p\u003e","description":"","filename":"Additionalfile12.FigureS3.tif","url":"https://assets-eu.researchsquare.com/files/rs-7114924/v1/4d39178dd79895865471c5af.tif"},{"id":86766103,"identity":"a4b21080-aa9e-4b17-b6e2-70ccfd2d029e","added_by":"auto","created_at":"2025-07-15 11:06:42","extension":"tif","order_by":13,"title":"","display":"","copyAsset":false,"role":"supplement","size":7945304,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAdditional file 13: Figure S4.\u003c/strong\u003eSignificantly enriched Cluster of Orthologous Groups (COG) categories (adjusted P-value \u0026lt; 0.01) for downregulated and upregulated genes at each dormancy stage in Japanese plum cultivar \"\u003cem\u003eCrimson Glo\u003c/em\u003e\" (A and B, respectively) under semi-arid climate.\u003c/p\u003e","description":"","filename":"Additionalfile13.FigureS4.tif","url":"https://assets-eu.researchsquare.com/files/rs-7114924/v1/7442672a8d07ee0ecadbd47c.tif"},{"id":86765574,"identity":"fe021649-8c3b-407c-b46f-e2d1bab544dd","added_by":"auto","created_at":"2025-07-15 10:58:42","extension":"tif","order_by":14,"title":"","display":"","copyAsset":false,"role":"supplement","size":7652280,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAdditional file 14: Figure S5.\u003c/strong\u003e Significantly enriched Cluster of Orthologous Groups (COG) categories (adjusted P-value \u0026lt; 0.01) for downregulated and upregulated genes at each dormancy stage in Japanese plum cultivar \"\u003cem\u003eHiromi Red\u003c/em\u003e\" (A and B, respectively) under Mediterranean subtropical climate.\u003c/p\u003e","description":"","filename":"Additionalfile14.FigureS5.tif","url":"https://assets-eu.researchsquare.com/files/rs-7114924/v1/1234984f394d772584beed94.tif"},{"id":86765570,"identity":"bb837e1c-6bab-48ea-aec4-f3f9d97c15da","added_by":"auto","created_at":"2025-07-15 10:58:42","extension":"tif","order_by":15,"title":"","display":"","copyAsset":false,"role":"supplement","size":7652948,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAdditional file 15: Figure S6.\u003c/strong\u003e Significantly enriched Cluster of Orthologous Groups (COG) categories (adjusted P-value \u0026lt; 0.01) for downregulated and upregulated genes at each dormancy stage in Japanese plum cultivar \"\u003cem\u003eCrimson Glo\u003c/em\u003e\" (A and B, respectively) under Mediterranean subtropical climate.\u003c/p\u003e","description":"","filename":"Additionalfile15.FigureS6.tif","url":"https://assets-eu.researchsquare.com/files/rs-7114924/v1/8ae42332730cb11a70d4ad87.tif"},{"id":86767513,"identity":"8f3cbb68-c607-45e3-9cc8-e3d5b89f265b","added_by":"auto","created_at":"2025-07-15 11:14:42","extension":"pdf","order_by":16,"title":"","display":"","copyAsset":false,"role":"supplement","size":250179,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAdditional file 16: Figure S7.\u003c/strong\u003e Phylogenetic tree of the DAM protein family in \u003cem\u003ePrunus\u003c/em\u003especies, inferred from Bayesian analysis. Numbers adjacent to the nodes indicate posterior probabilities; only nodes with values greater than 0.7 are labeled. The scale bar represents 0.5 amino acid substitutions per site.\u003c/p\u003e","description":"","filename":"Additionalfile16.FigureS7.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7114924/v1/41af0e788635ba9c43dca636.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eDormancy Dynamics in Japanese Plum: Transcriptomic Responses to Variable Climatic Conditions and Chill Requirements\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eFlowering plants exhibit numerous adaptive features to survive adverse environmental conditions. In temperate woody perennials, vegetative growth typically occurs in spring and summer, while dormancy begins in autumn. During dormancy, visible growth ceases but low metabolic activity is maintained, protecting plants from harsh environmental conditions (Horvath, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Cooke et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). Dormancy is crucial not only for survival but also for ensuring proper fruit production (Rodrigo, \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2000\u003c/span\u003e; Rohde \u0026amp; Bhalerao, \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e2007\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eDormancy is usually differentiated into three phases: paradormancy (late summer), endodormancy (autumn-winter), and ecodormancy (late winter-spring) (Lang et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e1987\u003c/span\u003e). During endodormancy, bud growth remains inhibited even under favorable temperatures until they accumulate sufficient chilling (chilling requirements) to transition to the next phase, ecodormancy. During ecodormancy, bud growth resumes upon fulfillment of enough warmth (heat requirements) (Lang et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e1987\u003c/span\u003e). Global warming threatens this finely tuned process by reducing chill accumulation in many temperate regions, leading to substantial yield losses (Campoy et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Luedeling et al., \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). A lack of sufficient winter chilling modifies spring phenology (Beil et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), causing reduced and irregular flowering and fruiting, ultimately leading to lower fruit yield (Kovaleski, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eDespite over two centuries of research, the regulatory mechanisms of dormancy remain unclear (Fad\u0026oacute;n et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2020a\u003c/span\u003e). Agroclimatic requirements\u0026mdash;chill requirements during endodormancy and heat requirements during ecodormancy\u0026mdash; are cultivar-specific and determine their adaptation to different regions (Fad\u0026oacute;n et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2020b\u003c/span\u003e). Given their significant agroclimatic implications, these requirements have been extensively evaluated in cultivars of stone fruit tree species such as plum (Guerrero et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), apricot (Ruiz et al., \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Herrera et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), and sweet cherry (Fad\u0026oacute;n et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). However, the approaches and models used to estimate these agroclimatic requirements have limitations (Luedeling, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Fad\u0026oacute;n et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), often leading to estimates that cannot be directly applied to regions with different climatic conditions. To address these limitations, recent studies have explored potential biological markers of the transition from endodormancy to ecodormancy, such as male meiosis in apricot (Herrera et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eSince the early century, key dormancy-related genes have been identified, including \u003cem\u003eDORMANCY-ASSOCIATED MADS-box\u003c/em\u003e (\u003cem\u003eDAM\u003c/em\u003e), first identified in peach (Bielenberg et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2004\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2008\u003c/span\u003e) and later in other fruit tree species (Quesada-Traver et al., \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Recent transcriptomic research has linked gene expression with hormonal, physiological, and metabolic changes during dormancy (Galindo Gonz\u0026aacute;lez et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Nishitani et al., \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Zhuang et al., \u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Zhang et al., \u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), but most studies have focused on single climatic conditions. Given the challenges derived from global climate change, there is an urgent need for studies assessing dormancy regulation under diverse environmental conditions.\u003c/p\u003e\u003cp\u003eRecent transcriptomic research on \u003cem\u003ePrunus\u003c/em\u003e species has assessed dormancy regulation in genotypes adapted to different agroclimatic conditions. In sweet cherry, conserved gene expression patterns have been identified, highlighting seven genes predictive of dormancy stages (Vimont et al., \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Comparative transcriptomic analyses of apricot and peach cultivars with different chilling requirements have been conducted, analyzing floral buds at key chill-hour intervals (Yu et al., \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Subsequent studies have re-analyzed RNA-seq data to identify key dormancy-related genes in sweet cherry, apricot, and peach (Canton et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), as well as in almond (Calle et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Recently, the genome sequence and a comparative transcriptome study of two Japanese plum cultivars with different chilling requirements identified six tandemly arrayed \u003cem\u003ePsDAM\u003c/em\u003e genes, including \u003cem\u003ePsDAM6\u003c/em\u003e, which could potentially influence dormancy and chilling requirements (Fang et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eTo address this gap, this study aims to elucidate genetic basis of dormancy progression mechanisms in the floral buds of Japanese plum (hybrids of \u003cem\u003eP. salicina\u003c/em\u003e) focusing on how environmental conditions influence reproductive development. Using two cultivars with different chilling requirements, we analyzed gene expression under contrasting semi-arid and Mediterranean subtropical conditions to assess the impact of climate on dormancy-related gene expressions and identify key genes involved in endodormancy regulation and transition from endodormancy to ecodormancy.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cb\u003eExperimental establishment of endodormancy breaking\u003c/b\u003e\u003c/p\u003e\u003cp\u003eWe first evaluated the phenology of two cultivars with different chilling requirements: \"Hiromi Red\" (HR; high chilling requirement) and \"Crimson Glo\" (CG; low chilling requirement) under two locations in Spain with contrasting climates: La Almunia de Do\u0026ntilde;a Godina, Zaragoza (semi-arid) and Algarrobo-Costa, M\u0026aacute;laga, (Mediterranean subtropical). Both cultivars are interspecific hybrids of \u003cem\u003eP. salicina\u003c/em\u003e and other \u003cem\u003ePrunus\u003c/em\u003e species, developed by Zaiger Genetics (Milošević \u0026amp; Milošević, \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eIn the semi-arid climate, full flowering (FP50) was observed in late February (February 24 for HR; February 19 for CG). In the Mediterranean subtropical climate, flowering was delayed: FP50 occurred 20 days later in HR (March 16) and 11 days later in CG (March 02).\u003c/p\u003e\u003cp\u003eIn the semi-arid climate, HR and CG reached endodormancy release on December 23 and 10, respectively. Full dormancy dates were set on December 10 for HR and November 25 for CG. Full recovery of bud activity was recorded on December 30 in both cultivars. However, in HR this recovery occurred one week after dormancy release, while in CG it took three weeks (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA, B). A similar but delayed trend was observed in the Mediterranean subtropical climate, where all three time points occurred approximately one month later than in the semi-arid climate. The delay was 35 days for HR and 26 days for CG (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC, D).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eChilling and heat requirements varied across cultivars and climates. Under semi-arid conditions, CG required 32 chilling portions (CP) and HR 42 CP, whereas under Mediterranean subtropical conditions, CP values were considerably lower (15 CP for CG, 26 CP for HR). In contrast, heat requirements values were up to 60% higher in the Mediterranean subtropical climate, with 11,395 and 6,998 growing degree hours (GDH) for CG, and 10,878 and 6,567 GDH for HR, respectively.\u003c/p\u003e\u003cp\u003e\u003cb\u003eTranscriptomic overview of flower bud development during dormancy\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe number of mRNA-seq aligned reads to the genome per sample ranged from 41.7M to 57M, with alignment rates between 84.4% and 85.8% (Fig. S1, Table S1). Boxplot of VST normalized counts revealed similar expression distributions across all samples and replicates, with median expression values closely aligned across conditions, indicating comparable overall gene expression levels. However, differences were observed in the number and dispersion of outliers (Fig. S2A). The three replicates clustered closely together, as shown by both the hierarchical clustering dendrogram (Fig. S2B) and the principal component analysis (PCA) plot (Fig. S2C). The first principal component (PC1, 38%) clearly separated the two cultivars while the second principal component (PC2, 29.8%) showed a separation based on climate, regardless of the dormancy stage. Interestingly, CG at full dormancy and HR at endodormancy release under Mediterranean subtropical conditions clustered more closely with semi-arid climate samples than with other samples within the same climate under different dormancy stages. In addition, the heatmap (Fig. S2D) also showed high consistency among replicates, and the gene expression patterns supported the PCA results, suggesting specific transcriptomic responses related to genotype and environment during dormancy.\u003c/p\u003e\u003cp\u003e\u003cb\u003eTranscriptomic insights into dormancy regulation in the semi-arid climate\u003c/b\u003e\u003c/p\u003e\u003cp\u003eIn the semi-arid location, clustering analyses and PCA showed clear differentiation between cultivars and dormancy stages (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). In CG, T1 and T2 were similar, indicating a higher transcriptomic shift from T0 to T1. Both the dendrogram (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA) and the first principal component (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB) showed a clear differentiation between the two cultivars. However, the second principal component showed a clear differentiation among the three dormancy stages in the low chill cultivar (CG), whereas in the high chill cultivar (HR), the T1 and T2 stages did not separate clearly.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eAnalysis of HR samples showed fewer differentially expressed genes (DEGs) across dormancy stages than CG. The highest number of DEGs in HR occurred during full dormancy (3,971 genes, T0) and after dormancy release (2,223 genes, T2) compared to the dormancy release stage (1,212 genes, T1) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC, Table S2). There was a marked difference between periods, with a 77% reduction of DEGs after dormancy release (647 genes) compared to the period before dormancy release (2,799 genes) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eD, Table S3).\u003c/p\u003e\u003cp\u003eIn contrast, CG exhibited a higher number of DEGs across all stages, with the largest number at full dormancy (6,682 genes, T0) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eE, Table S4). Compared to HR, the number of DEGs, including both up- and down-regulated genes, was more than double before dormancy release (6,311 genes) and after dormancy release (3,957 genes) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eF, Table S5).\u003c/p\u003e\u003cp\u003eFunctional enrichment analysis based on Cluster of Orthologous Groups (COG) categories showed a progressive decrease in the number of DEGs across most categories during dormancy in HR, followed by an increase upon the reactivation of activity (Fig. S3A, B, Table S6). At full dormancy (T0), a large number of genes were downregulated, particularly those involved in transcription, signaling and protein regulation (Fig. S3A, Table S6).\u003c/p\u003e\u003cp\u003eIn contrast, CG exhibited a progressive increase in the number of downregulated genes across dormancy stages, mainly in categories related to cellular processes, signaling and metabolism, while genes involved in information storage and processing remained active initially but were progressively downregulated as dormancy progressed, (Fig. S4A, Table S7). At full dormancy, a higher number of upregulated genes were observed, particularly in categories related to signaling, protein regulation, transcription, and metabolism, although their expression gradually decreased over time. Conversely, genes related to cell cycle reactivation and preparation for active growth \u0026mdash;such as those involved in translation, replication, and chromatin modification\u0026mdash; became increasingly expressed, with their activity sustained until T2 (Fig. S4B, Table S7).\u003c/p\u003e\u003cp\u003e\u003cb\u003eTranscriptomic insights into dormancy regulation in the Mediterranean subtropical climate\u003c/b\u003e\u003c/p\u003e\u003cp\u003eIn the Mediterranean subtropical climate, a similar gene expression pattern to that observed in the semi-arid climate was detected, with a clear separation between the two cultivars (PC1, 47.1%), as well as a distribution based on the dormancy stage (PC2, 26.1%) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA, B). However, the samples corresponding to full dormancy in HR clustered closer to CG. A significant difference in the number of DEGs was observed between the two cultivars during the dormancy stage (T0). In HR, 5,035 genes showed significantly increased expression, while 5,230 genes showed significantly decreased expression. In contrast, CG exhibited a much smaller number of DEGs, with 1,326 genes upregulated and 1,452 downregulated. The number of DEGs was similar between the two cultivars for T1 and T2 (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC-F, Tables S8-11).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eIn HR, COG category analysis revealed a progressive decrease in the number of DEGs from T0 to T2 (Fig. S5A, B). At full dormancy (T0), a large number of genes were downregulated, particularly in categories related to transcription, signal transduction mechanisms, and post-translational modification, protein turnover, and chaperones (Fig. S5A, Table S12). In parallel, the number of upregulated genes gradually increased from T0 onward, especially in categories involved in metabolism and transcription (Fig. S5B, Table S12).\u003c/p\u003e\u003cp\u003eIn CG, COG annotation revealed a distinct gene regulation pattern compared to HR, suggesting a progressive general reactivation that intensified once dormancy was overcome. At full dormancy (T0), although several functional categories such as signaling and protein regulation, transcription and carbohydrate metabolism were downregulated (Fig. S6A, Table S13), these same categories also showed a notable number of upregulated genes (Fig. S6B, Table S13). As CG progressed to T1 and T2, the number of upregulated DEGs increased across multiple COG categories.\u003c/p\u003e\u003cp\u003e\u003cb\u003eDifferential Expression of Key Dormancy-Related Genes\u003c/b\u003e\u003c/p\u003e\u003cp\u003eIn addition to analyzing general processes, we also examined known key dormancy-related genes, including \u003cem\u003eSTRESS-ASSOCIATED PROTEIN1\u003c/em\u003e (\u003cem\u003eSAP1\u003c/em\u003e) (Prupe.2G010400) (Lloret et al., \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), \u003cem\u003eALLENE OXYDE CYCLASE\u003c/em\u003e (\u003cem\u003eAOC\u003c/em\u003e)-\u003cem\u003elike 1\u0026ndash;2\u003c/em\u003e (Prupe.1G306100, Prupe.3G239900) (Lloret et al., \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), \u003cem\u003eDAM\u003c/em\u003e (Bielenberg et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2004\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2008\u003c/span\u003e), \u003cem\u003eFLOWERING LOCUS T\u003c/em\u003e (\u003cem\u003eFT\u003c/em\u003e) (Prupe.6G364900) (Hsu et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Hao et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2015\u003c/span\u003e), \u003cem\u003eTARGET OF RAPAMYCIN\u003c/em\u003e (\u003cem\u003eTOR\u003c/em\u003e)-\u003cem\u003elike\u003c/em\u003e (Prupe.8G151300) (Menand et al., \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2002\u003c/span\u003e; Lloret et al., \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) \u003cem\u003eTONOPLAST INTRINSIC PROTEIN\u003c/em\u003e (\u003cem\u003eTIP\u003c/em\u003e)-\u003cem\u003elike\u003c/em\u003e (Prupe.2G229500) (Ludevid et al., \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e1992\u003c/span\u003e; Lloret et al., \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), and \u003cem\u003eLIPOXYGENASE\u003c/em\u003e (\u003cem\u003eLOX\u003c/em\u003e)-\u003cem\u003elike\u003c/em\u003e (Prupe.2G005300) (Lloret et al., \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). To this end, we first searched for the putative orthologs of these genes in our transcriptome using their sequences from \u003cem\u003ePrunus persica\u003c/em\u003e. For most candidate genes, a single sequence was identified, except for the \u003cem\u003eDAM\u003c/em\u003e genes, for which two \u003cem\u003eDAM-like\u003c/em\u003e sequences were found. Phylogenetic analysis placed one of the two putative \u003cem\u003eDAM\u003c/em\u003e ortholog (\u003cem\u003eevm.model.Chr1.599_syl_v2.0\u003c/em\u003e) within the \u003cem\u003eDAM6\u003c/em\u003e clade, and it was subsequently renamed as \u003cem\u003ePshDAM6\u003c/em\u003e. Similarly, the other putative ortholog of \u003cem\u003eDAM\u003c/em\u003e (\u003cem\u003eevm.model.Chr1.600.601.603.604_syl_v2.0\u003c/em\u003e) was placed within the DAM1 clade and renamed as \u003cem\u003ePshDAM1\u003c/em\u003e (Fig. S7).\u003c/p\u003e\u003cp\u003eSignificant differences in expression were observed in all key dormancy-related genes, except \u003cem\u003eTIP\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). \u003cem\u003ePshDAM1\u003c/em\u003e expression decreased across dormancy stages, more pronounced in CG and in the Mediterranean subtropical climate. \u003cem\u003ePshDAM6\u003c/em\u003e followed a similar pattern, showing reduced expression at T2, with a steeper decrease in CG and a similar trend under both climates.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003eFT\u003c/em\u003e expression increased at T2 under semi-arid conditions but decreased at T2 in the Mediterranean subtropical climate. \u003cem\u003eSAP1\u003c/em\u003e was upregulated in HR during dormancy release in Mediterranean subtropical conditions but fluctuated in CG. In the semi-arid climate, \u003cem\u003eSAP1\u003c/em\u003e expression levels were generally lower, with significant differences observed only after dormancy release in CG. No significant differences were found in \u003cem\u003eTIP\u003c/em\u003e expression across stages, cultivars and climates. \u003cem\u003eTOR\u003c/em\u003e expression increased after dormancy release, particularly in the Mediterranean subtropical climate. \u003cem\u003eLOX\u003c/em\u003e expression was similar across all dormancy stages in both cultivars, regardless of location, with higher expression levels in HR. However, significant differences were only observed for CG in the Mediterranean subtropical climate. In \u003cem\u003eAOC-like1\u003c/em\u003e, a reduction in expression was observed across dormancy stages in both climates, with significant differences at dormancy release. For \u003cem\u003eAOC-like2\u003c/em\u003e, expression levels remained similar across stages in both climates, with significant differences only observed at the resumption of growth in CG under Mediterranean subtropical conditions.\u003c/p\u003e\u003cp\u003e\u003cb\u003eCultivar- and climate-specific upregulated gene expression\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTo explore how gene expression is modulated in response to climatic conditions and genetic background, we analyzed the patterns of DEGs that were upregulated across dormancy stages in both cultivars under semi-arid and Mediterranean subtropical environments. During dormancy (T0), HR showed 3,166 DEGs upregulated under Mediterranean subtropical conditions, whereas only 522 were observed under semi-arid conditions. Interestingly, 606 genes were shared between the two climates. In contrast, in CG, 509 DEGs upregulated were found under Mediterranean subtropical conditions, and 2,498 under semi-arid conditions, with an overlap of only 165 genes between the two climates. Additionally, 136 DEGs were identified between the two cultivars in the Mediterranean subtropical climate, and 102 DEGs in the semi-arid climate. Across both cultivars, 61 DEGs were common to both climates (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA, Tables S14-S18).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eDuring dormancy release (T1), no common upregulated DEGs were observed between cultivars and climates. Few DEGs were identified within each climate: 20 in the semi-arid climate and 16 in Mediterranean subtropical climate. However, the number of upregulated DEGs for each cultivar, regardless of climate, was high: 444 for CG and 258 for HR (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB, Tables S19-S22).\u003c/p\u003e\u003cp\u003eAfter dormancy release (T2), more upregulated DEGs were associated with Mediterranean subtropical conditions. Overall, CG exhibited twice as many DEGs as HR (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eC, Tables S23-S27).\u003c/p\u003e\u003cp\u003eTo further evaluate gene function across various categories from the COG database, the majority of genes were grouped into three major functional categories: metabolism (13\u0026ndash;49%), information storage and processing (5\u0026ndash;30%), and cellular processes and signaling (6\u0026ndash;40%) (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e, Tables S28-S30). Genes with unclassified functions were assigned to poorly characterized categories, while those mixed or overlapping roles were grouped under \"Others\" (52 categories, 2\u0026ndash;13%). Overall, genes were distributed across twenty-three specific COG functional classes. Across all conditions, a substantial proportion had unknown (22\u0026ndash;35%) or unassigned functions (2\u0026ndash;8%), indicating that several biological processes remain poorly understood. Functional category distributions were generally consistent, except during dormancy, when metabolic genes dominated (49%).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThe COG functional classification analysis revealed that most genes were associated with the categories \"Carbohydrate transport and metabolism,\" \"Transcription,\" \"Signal transduction mechanisms,\" and \"Posttranslational modification, protein turnover, chaperones\". Notable inactivity was observed in categories related to defense mechanisms and secondary metabolite biosynthesis, suggesting a lack of active stress response during this state. Furthermore, low values in categories related to cell division, cytoskeleton organization, and extracellular structures reflected limited growth and expansion over dormancy stages (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e, Tables S28-S30).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eWe analyzed the transcriptomic profiles of two Japanese plum cultivars, \"Hiromi Red\" and \"Crimson Glo,\" which have high and low chilling requirements, respectively, under semi-arid and Mediterranean subtropical climates. Our findings revealed that climate significantly impacts dormancy progression and gene expression patterns in these cultivars, with transitions between the three dormancy phases occurring approximately one month earlier under Mediterranean subtropical conditions. Discrepancies were observed in the quantification of chilling requirements, with a remarkable reduction in the CP required in the Mediterranean subtropical climate for both cultivars, while their CPs in the semi-arid climate aligned with previous studies (Guerrero et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cb\u003eDormancy dynamics and transcriptomic analysis across climates\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTraditionally considered as a period of inactivity, dormancy is now recognized as a dynamic and complex process involving extensive cellular and molecular activities (Rohde \u0026amp; Bhalerao, \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Zhao, Ma et al., \u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Transcriptomic studies in \u003cem\u003ePrunus\u003c/em\u003e have revealed that both endodormant and ecodormant flower buds exhibit unique and fluctuating transcriptional profiles, with continuous metabolic activities such as starch accumulation (Fad\u0026oacute;n et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Yu et al., \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Calle et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), hormonal fluctuations (Vimont et al., \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Canton et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Liu et al., \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2025\u003c/span\u003e), and floral structure differentiation (Lloret et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Zhao, Li et al., \u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Previous transcriptomic studies in other \u003cem\u003ePrunus\u003c/em\u003e species have identified hundreds to thousands of differentially expressed genes at different dormancy stages (Zhu et al., \u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Yu et al., \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) while fewer than 100 DEGs were expressed during full endodormancy. A meta-analysis of RNA-Seq studies in \u003cem\u003ePrunus\u003c/em\u003e species (including apricot, almond, peach, and sweet cherry) identified 6,860 genes related to endodormancy, revealing conserved pathways involved in cold acclimation, cell growth control, oxidative signals, soluble sugar regulation, and phytohormone signaling, suggesting that common molecular mechanisms underlie dormancy regulation within this genus. However, the number of DEGs varies among species, cultivars, and dormancy stages (Calle et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eIn our study, the high chill cultivar, \"Hiromi Red,\" exhibited a more pronounced reduction in DEGs between the dormancy phases, with a notably higher number of DEGs in both climates compared to previous research in Japanese plum (Fang et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). For the low-chill cultivar, \"Crimson Glo,\" the pattern of DEGs in the semi-arid climate was consistent with that observed for \"Sanyueli\" (Fang et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), showing a gradual decrease in DEGs during the transition between endodormancy and dormancy release. However, in the Mediterranean subtropical climate, an increase in DEGs was observed after dormancy release.\u003c/p\u003e\u003cp\u003e\u003cb\u003eTranscriptomic differentiation influenced by climate and dormancy stage\u003c/b\u003e\u003c/p\u003e\u003cp\u003eDespite recent RNA-seq studies focusing on dormancy control in \u003cem\u003ePrunus\u003c/em\u003e species, our study addresses a significant gap by analyzing transcriptomic responses across different climates using two cultivars with different chilling requirements. PCA results revealed that climate had a greater influence on transcriptomic differentiation than dormancy stage, suggesting that the environmental conditions have a more significant impact on the transcriptomic profiles than the progression of dormancy. This contrasts with previous studies in other \u003cem\u003ePrunus\u003c/em\u003e species, such as apricot and peach, where developmental stages had a greater influence on the transcriptomic profile (Yu et al., \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eAmong the differentially expressed genes, several key regulators of dormancy have emerged. For example, Lloret et al. (\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) showed that \u003cem\u003ePpSAP1\u003c/em\u003e in peach is expressed in dormant buds and expression decreases upon dormancy release. In our study, both cultivars showed a similar decreasing expression trend of \u003cem\u003ePpSAP1\u003c/em\u003e, but only under semi-arid conditions. Conversely, under Mediterranean subtropical conditions, a significant increase in \u003cem\u003ePshSAP1\u003c/em\u003e expression was observed, particularly in CG before dormancy release and in HR after dormancy release, suggesting an adaptive role in the adaptation of Japanese plum to different climatic conditions, especially in warmer environments, consistent with the described involvement of \u003cem\u003ePpSAP1\u003c/em\u003e in stress tolerance and cell growth (Lloret et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). In contrast to previous reports in European plum and peach, where higher expression levels of \u003cem\u003ePshTIP\u003c/em\u003e were detected after dormancy release, we found no significant differences in \u003cem\u003ePshTIP\u003c/em\u003e expression, (Lloret et al., \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Quesada-Traver et al., \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). However, an increase in \u003cem\u003ePshTOR\u003c/em\u003e expression was observed in both cultivars in the Mediterranean subtropical climate, following a pattern similar to the expression of \u003cem\u003ePshSAP1\u003c/em\u003e.\u003c/p\u003e\u003cp\u003eThe \u003cem\u003eAOC-like 1\u0026ndash;2\u003c/em\u003e and \u003cem\u003eLOX-like\u003c/em\u003e genes, which are involved in jasmonic acid biosynthesis (Berni et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), have also been linked to dormancy and related physiological processes in other \u003cem\u003ePrunus\u003c/em\u003e species (Lloret et al., \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Prudencio et al. (\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) observed a decrease in \u003cem\u003eLOX3.1\u003c/em\u003e expression during dormancy release in almond, suggesting that lipoxygenase-mediated lipid peroxidation provides fatty acids for energy production during this process. In peach, an increase in \u003cem\u003eLOX-like, AOC-like1\u003c/em\u003e, and \u003cem\u003eAOC-like2\u003c/em\u003e expression has been reported during dormancy release, with a positive correlation with \u003cem\u003ePpeDAM6\u003c/em\u003e expression, suggesting these genes may play a role in dormancy release (Lloret et al., \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Puertes et al., \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). In our study, we observed minimal expression changes across dormancy stages for these genes. However, \u003cem\u003ePshAOC-like1\u003c/em\u003e followed a decreasing trend similar to that reported for \u003cem\u003eLOX3.1\u003c/em\u003e in almond (Prudencio et al., \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), indicating that similar mechanisms might be at play in dormancy release across different \u003cem\u003ePrunus\u003c/em\u003e species.\u003c/p\u003e\u003cp\u003e\u003cb\u003eFT\u003c/b\u003e \u003cb\u003eand\u003c/b\u003e \u003cb\u003eDAM\u003c/b\u003e \u003cb\u003egenes: expression patterns and phylogenetic insights\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003eFT-like\u003c/em\u003e, a key regulator of growth and flowering processes (Fad\u0026oacute;n et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2020a\u003c/span\u003e), showed increased expression after dormancy release under semi-arid conditions, consistent with previous reports in sweet cherry (Canton et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). However, we observed a decrease in \u003cem\u003eFT\u003c/em\u003e expression after dormancy release in the Mediterranean subtropical climate. On the other hand, the \u003cem\u003eDAM\u003c/em\u003e genes, which have been identified as key regulators of the dormancy cycle and climate adaptation (Goeckeritz \u0026amp; Hollender, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), were downregulated in our study after prolonged exposure to cold temperatures, an essential factor for triggering dormancy release in Rosaceae (Falavigna et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). These findings align with those reported in other fruit tree species, where \u003cem\u003eDAM\u003c/em\u003e gene expression correlates with the downregulation of \u003cem\u003eFT\u003c/em\u003e during dormancy (Lloret et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Puertes et al., \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). In both semi-arid and Mediterranean subtropical climates, \u003cem\u003eDAM\u003c/em\u003e genes showed high expression in dormant buds and low expression after the fulfillment of chilling requirements, which is consistent with previous reports in different species of the Rosaceae, such as Japanese plum (Fang et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), European plum (Quesada-Traver et al., \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), sweet cherry (Rothkegel et al., \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Vimont et al., \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), peach (Jim\u0026eacute;nez et al., 2010), Japanese apricot (Zhang et al., \u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), and apple (Mimida et al., \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Interestingly, while a significantly lower \u003cem\u003eDAM\u003c/em\u003e expression was reported in the low-chill Japanese plum cultivar \"Sanyueli\" (Fang et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), our results showed lower \u003cem\u003eDAM\u003c/em\u003e expression in the high-chill cultivar, Hiromi Red. These differences may be influenced by epigenetic factors that modulate \u003cem\u003eDAM\u003c/em\u003e gene expression (R\u0026iacute;os et al., \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e2014\u003c/span\u003e), in response to the specific environmental conditions of each location.\u003c/p\u003e\u003cp\u003eOur phylogenetic and synteny analysis revealed that DAM proteins in the Amygdaloideae subfamily of Rosaceae originated from the SHORT VEGETATIVE PHASE (SVP) 2 clade, which also includes AGAMOUS-LIKE (AthAGL24) of \u003cem\u003eArabidopsis thaliana\u003c/em\u003e (Quesada-Traver et al., \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). In several \u003cem\u003ePrunus\u003c/em\u003e species six \u003cem\u003eDAM\u003c/em\u003e genes have been identified, contrasting with the lower number of \u003cem\u003eDAM\u003c/em\u003e genes found in annual model plants (Fang et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Quesada-Traver et al., \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The expansion of the \u003cem\u003eDAM\u003c/em\u003e genes may have resulted from serial tandem duplications occurring before the diversification of the \u003cem\u003ePrunus\u003c/em\u003e genus (Jim\u0026eacute;nez et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). In our transcriptomic data, we surprisingly detected only \u003cem\u003ePshDAM1\u003c/em\u003e and \u003cem\u003ePshDAM6\u003c/em\u003e, but additional \u003cem\u003eDAM\u003c/em\u003e genes might be identified once the genome sequences of these cultivars become available.\u003c/p\u003e\u003cp\u003eInterestingly, the phylogenetic analysis of \u003cem\u003eDAM\u003c/em\u003e genes revealed that \u003cem\u003ePsDAM\u003c/em\u003e genes from the Japanese plum cultivar \"Sanyueli\" clustered in a separate clade from the \u003cem\u003eDAM\u003c/em\u003e sequences, including \u003cem\u003ePshDAM1\u003c/em\u003e and \u003cem\u003ePshDAM6\u003c/em\u003e. Moreover, \u003cem\u003ePsDAM6\u003c/em\u003e exhibited insertions in its introns and a deletion in exon 5, which could affect its function in dormancy regulation. Japanese plum cultivars are the result of hybridization between \u003cem\u003ePrunus salicina\u003c/em\u003e and other species (Guerra and Rodrigo, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) resulting in high genetic diversity and a complex population structure (Guerrero et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Since inter-species hybridization is a common phenomenon within the \u003cem\u003ePrunus\u003c/em\u003e genus (Guerrero et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), this could explain the discrepancies in \u003cem\u003eDAM\u003c/em\u003e gene clustering, as these genes may exhibit a combination of characteristics from different species.\u003c/p\u003e\u003cp\u003e\u003cb\u003eLocation- and cultivar-specific gene expression differences during dormancy stages in low and high chill requirement genotypes\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe number and distribution of DEGs across cultivars and climates revealed distinct regulatory responses during dormancy and its release. During dormancy (T0), HR showed a higher number of DEGs under Mediterranean subtropical conditions, while CG responded more strongly under semi-arid conditions suggesting that each cultivar responds differently to climatic conditions, likely due to differences in their adaptation and chilling requirements. The low number of shared DEGs between climates and cultivars indicates that dormancy is regulated by highly specific genotype-environment interactions. At T1, few DEGs were identified within each climate, and none were shared between cultivars and climates. This suggests that there is no universal transcriptional response at this stage, and that each cultivar\u0026ndash;climate combination activates different genes, showing a strong influence of genotype and environment on dormancy release. After dormancy release (T2), more DEGs were detected under Mediterranean subtropical conditions, suggesting that warmer climates might induce stronger transcriptional activity. CG showed twice as many DEGs as HR, potentially reflecting differences in how each cultivar adjusts gene expression after dormancy. Low-chill cultivars like CG might remain more responsive to environmental signals after dormancy release, while high-chill cultivars like HR could show a weaker gene expression response at this stage.\u003c/p\u003e\u003cp\u003eThe functional classification of DEGs showed a clear dominance of metabolism-related genes, especially in the full dormancy stage. This suggests that the plant is adjusting its metabolism to focus on basic survival during this early stage (Fad\u0026oacute;n et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2020a\u003c/span\u003e). Genes involved in transcription remain active throughout the dormancy period, highlighting the importance of maintaining gene expression even when most cellular processes are slowed down (Fang et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The high number of unclassified genes also points to unknown or species-specific functions that are still not well understood. On the other hand, the low presence of genes related to defense, secondary metabolite production, and cell structure suggests reduced plant activity in stress response and growth pathways during dormancy. This differs from previous studies that identified genes associated with stress resistance during the dormancy stage (Yamane et al., \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Vimont et al., \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Yu et al., \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Niu et al., \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eOur study provides a comprehensive transcriptomic analysis of dormancy regulation in two Japanese plum cultivars across contrasting climatic conditions. By comparing transcriptomic profiles across cultivars and environments, we have identified both genotype-specific and climate-responsive genes and pathways. The pronounced transcriptional activity observed under warmer conditions highlights the strong impact of environmental conditions on dormancy regulation. These findings provide new insights into the molecular mechanisms underlying dormancy and offer value insights for breeding climate-resilient genotypes and growing cultivars better adapted to changing climatic scenarios.\u003c/p\u003e"},{"header":"Material \u0026 Methods","content":"\u003cp\u003e\u003cb\u003ePlant material\u003c/b\u003e\u003c/p\u003e\u003cp\u003eShoots and flower buds were collected from two Japanese plum cultivars, \"Hiromi Red\" and \"Crimson Glo\" (hybrids of \u003cem\u003ePrunus salicina\u003c/em\u003e Lindl.), with contrasting late and early flowering dates, respectively. Trees of the same age and grafted on the same rootstock were grown in two locations in Spain: IHSM La Mayora (IM; Algarrobo-Costa, Málaga, 36°45'23.4\"N, 4°02'35.9\"W, 25 m altitude, hot-summer Mediterranean climate) and Finca La Redonda (La Almunia de Doña Godina, Zaragoza, 41°27'28.6\"N, 1°21'33.7\"W, 394 m altitude, cold semi-arid climate). The hot-summer Mediterranean climate (Csa) of Algarrobo-Costa (Peel et al., \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2007\u003c/span\u003e), also referred to as a Mediterranean subtropical climate due to its support for the extensive cultivation of subtropical crops (MAPA, 2023; Junquera et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), is characterized by mild, wet winters, and hot, dry summers. The cold semi-arid climate (BSk) of La Almunia de Doña Godina features cold winters, and hot, dry summers with marked seasonal temperature contrasts and low annual precipitation (Peel et al., \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2007\u003c/span\u003e).\u003c/p\u003e\u003cp\u003ePhenological observations of flower buds were carried out twice a week from bud break to flowering, considering full flowering (F50) when 50% of flower buds were in stage F (Baggiolini, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e1952\u003c/span\u003e) that corresponds to stage 65 (full bloom) in the BBCH scale (Meier, \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2001\u003c/span\u003e; Fadón et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2015\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cb\u003eDetermination of endodormancy breaking\u003c/b\u003e\u003c/p\u003e\u003cp\u003eFlower bud growth was evaluated in response to warm conditions after field chilling exposure. Four shoots around 40 cm per cultivar were collected weekly from November to March, placed in a growth chamber (22 ± 1°C, 12 h light photoperiod) and maintained on wet florist foam for 8 days. To determine the end of endodormancy, 10 flower buds were randomly picked and weighed on the first and last day in the growth chamber. Endodormancy was considered overcome when bud weight increased by more than 30% (Brown \u0026amp; Kotob, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e1957\u003c/span\u003e; Tabuenca, \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e1964\u003c/span\u003e; Ruiz et al., \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Fadón \u0026amp; Rodrigo, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Guerrero et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Using the endodormancy release date (T1) as reference, two additional time points were selected: two weeks before dormancy release was considered full dormancy (T0), and a bud weight increase exceeding 50% was used as the criterion for full recovery of activity (T2).\u003c/p\u003e\u003cp\u003e\u003cb\u003eChilling and heat requirement estimation\u003c/b\u003e\u003c/p\u003e\u003cp\u003eSemi-hourly temperature data were recorded at local weather stations: station 31 (Épila) in Zaragoza (ORESA, 2023), and a hygrometer placed at the experimental station of IHSM La Mayora in Málaga. For each cultivar and location, chill accumulation from September 1st to endodormancy release was quantified in chilling portions (CP) using the Dynamic Model (Fishman et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e1987\u003c/span\u003e). Heat requirements were estimated in Growing Degree Hours (GDH) (Richardson et al., \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e1974\u003c/span\u003e), from endodormancy release to F50.\u003c/p\u003e\u003cp\u003e\u003cb\u003eRNA extraction and library preparation\u003c/b\u003e\u003c/p\u003e\u003cp\u003eFor each time point, flower buds were collected from multiple trees and pooled to create three replicates. Samples were flash frozen in liquid nitrogen and stored at -80ºC. Total RNA was isolated using the Total RNA Purification Kit (Norgen Biotek) and treated with TURBO DNA-freeTM kit (Ambion, Austin, TX, USA) to remove DNA contamination. Thirty-six samples containing 0.74–2.56 µg of RNA were submitted to Novogene (Cambridge, UK) for library preparation and RNA sequencing (Illumina NovaSeq 6000, 150 bp PE).\u003c/p\u003e\u003cp\u003e\u003cb\u003emRNA-seq data processing\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe \u003cem\u003eP. salicina\u003c/em\u003e genome assembly and gene annotations were obtained from \u003cem\u003eP. salicina\u003c/em\u003e Sanyueli Genome v2.0 (Liu et al., \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), hosted in the Genome Database for Rosaceae (GDR; accession number tfGDR1044) (Jung et al., 2019). The quality of reads was assessed using FastQC v0.11.9 (Andrews, 2010), and gene expression was quantified with RSEM v1.3.3 (Li and Dewey, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2011\u003c/span\u003e) using STAR v2.7.9a as read aligner (Dobin et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Gene counts in each dataset were normalized using the variance-stabilizing transformation (VST) method implemented in the DESeq2 v1.42.0 R package (Love et al., \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2014\u003c/span\u003e), in the statistical software R (R Core Team, \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Principal component analysis (PCA), hierarchical clustering, boxplots, heatmaps and differential expression (DE) analysis were performed on VST-normalized counts.\u003c/p\u003e\u003cp\u003e\u003cb\u003eDifferential expression analysis\u003c/b\u003e\u003c/p\u003e\u003cp\u003eDifferential expression analyses were performed with DESeq2 v1.42.0 (Love et al., \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). To gain a more detailed understanding of the regulatory mechanisms underlying dormancy, two types of analyses were conducted: differential expression analysis and functional enrichment analysis, both performed on the datasets from each location. First, to identify genes with dormancy stage-specific regulation within each location, gene expression at each time point was compared to the mean expression levels of the other two time points within each cultivar. Furthermore, to assess the evolutionary dynamics of differentially expressed genes across stages, gene expression at time point T0 was compared with T1, and T1 was compared with T2. Genes with a Benjamini-Hochberg (BH) adjusted P-value lower than 0.01 were selected as differentially expressed in the corresponding contrast.\u003c/p\u003e\u003cp\u003e\u003cb\u003ePhylogenetic analysis\u003c/b\u003e\u003c/p\u003e\u003cp\u003eProtein sequences of the two \u003cem\u003eDAM\u003c/em\u003e-like genes identified in this study, together with the longest annotated homologous from related \u003cem\u003ePrunus\u003c/em\u003e and other species retrieved from NCBI database (NCBI Resource Coordinators, \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), were aligned using CLUSTALX v.1.82 (Thompson et al., \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e1997\u003c/span\u003e). The alignments were subsequently edited as described previously (Lora et al., \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) using GBLOCK v.0.91b (Castresana, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2000\u003c/span\u003e; Talavera \u0026amp; Castresana, \u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). Bayesian analysis was performed using MrBayes (Ronquist et al., \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e2012\u003c/span\u003e), following the JTT + Invariant (I) model of amino acid substitutions recommended by MEGA version X (Kumar et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Trees were sampled every 100 generations for 1,000,000 generations in the Bayesian analysis, with the first 25% of the trees of each run discarded as burn-in.\u003c/p\u003e\u003cp\u003e\u003cb\u003eFunctional analysis\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe functional annotation of the obtained protein sequences was performed using the EggNOG database (evolutionary genealogy of genes: Non-supervised Orthologous Groups), version 5.0 (Huertas-Cepas et al., 2019). Protein sequences were analyzed with EggNOG-mapper (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://eggnog-mapper.embl.de/\u003c/span\u003e\u003cspan address=\"https://eggnog-mapper.embl.de/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) with default parameters, adjusting the taxonomic scope per query and transferring non-electronic Gene Ontology evidence. The COG (Clusters of Orthologous Groups) functional categories were used to generate graphical representations of the functional distribution using the ggplot2 package (Wickham, \u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) in R (R Core Team, \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eAOC ALLENE OXYDE CYCLASE-like\u003c/p\u003e\n\u003cp\u003eCG Crimson Glo\u003c/p\u003e\n\u003cp\u003eCOG Cluster of Orthologous Groups\u003c/p\u003e\n\u003cp\u003eCP Chilling Portion\u003c/p\u003e\n\u003cp\u003eDAM DORMANCY-ASSOCIATED MADS-box\u003c/p\u003e\n\u003cp\u003eDEG Differentially Expressed Gene\u003c/p\u003e\n\u003cp\u003eFT FLOWERING LOCUS T\u003c/p\u003e\n\u003cp\u003eGDH Growing Degree Hour\u003c/p\u003e\n\u003cp\u003eHR Hiromi Red\u003c/p\u003e\n\u003cp\u003eLOX LIPOXYGENASE-like\u003c/p\u003e\n\u003cp\u003ePCA Principal Component Analysis\u003c/p\u003e\n\u003cp\u003eSAP1 STRESS-ASSOCIATED PROTEIN1\u003c/p\u003e\n\u003cp\u003eMSC Mediterranean subtropical climate\u003c/p\u003e\n\u003cp\u003eSAC Semi-arid climate\u003c/p\u003e\n\u003cp\u003eTIP TONOPLAST INTRINSIC PROTEIN-like\u003c/p\u003e\n\u003cp\u003eTOR TARGET OF RAPAMYCIN-like\u003c/p\u003e\n\u003cp\u003eVST Variance-Stabilizing Transformation\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors approve the manuscript and consent to the publication of this work.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe raw transcriptome datasets are available in the National Center for Biotechnology Information (NCBI, https:// www. ncbi. nlm. nih. gov/) under the BioProject number PRJNA1276976. The scripts used to process and analyze the data are available at GitHub repository https://github.com/sherlg/transcriptomics-dormancy-japanese-plum.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was funded by the ADAPFRUTCC project that is supported by the Biodiversity Foundation of the Ministry for the Ecological Transition and the Demographic Challenge, through the call for grants for the implementation of projects that contribute to the Spanish National Climate Change Adaptation Plan (2021-2030); the project PID2020-115473RR-I00, financed by ICIU/AEI/10.13039/501100011033/, Consolidated Group A12\u0026ndash;17R funded by the Government of Aragon \u0026ndash; European Social Fund, \u0026ldquo;The ESF invests in your future\u0026rdquo;, the predoctoral grant PRE2018-084962 funded by MCIN/AEI/10.13039/501100011033 for Sara Herrera, and the Priority Research Area BioS under the program \u0026ldquo;Excellence Initiative \u0026ndash; Research University\u0026rdquo; at Jagiellonian University in Krakow.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eJIH, JR, and JL designed the research. JIH, JR, and JL managed the project. SH and JL collected plant material, conducted field experiments, and performed phenotypic evaluations. SH prepared RNA samples. SH performed, and GY supervised, the bioinformatics analysis. JL carried out the phylogenetic analysis. SH, JIH, JR, and JL wrote the manuscript. SH, JIH, GY, JR, and JL revised the manuscript. All authors read and approved the final version.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAndrews S FastQC: a quality control tool for high throughput sequence data [Internet]. 2010 [cited 2025 May 14]. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.bioinformatics.babraham.ac.uk/projects/fastqc/\u003c/span\u003e\u003cspan address=\"https://www.bioinformatics.babraham.ac.uk/projects/fastqc/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBaggiolini M (1952) Stades rep\u0026egrave;res du abricotier. Rev Romande Agric Vitic Arboric 4:28\u0026ndash;29\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBeil I, Kreyling J, Meyer C, Lemcke N, Malyshev AV (2021) Late to bed, late to rise\u0026mdash;Warmer autumn temperatures delay spring phenology by delaying dormancy. Glob Chang Biol 27. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1111/gcb.15858\u003c/span\u003e\u003cspan address=\"10.1111/gcb.15858\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBerni R, Cai G, Xu X, Hausman JF, Guerriero G (2019) Identification of Jasmonic Acid Biosynthetic Genes in Sweet Cherry and Expression Analysis in Four Ancient Varieties from Tuscany. Int J Mol Sci 20(14):3569. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/ijms20143569\u003c/span\u003e\u003cspan address=\"10.3390/ijms20143569\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBielenberg DG, Wang Y, Fan S, Reighard GL, Scorza R, Abbott AG (2004) A deletion affecting several gene candidates is present in the Evergrowing peach mutant. J Hered 95(5):436\u0026ndash;444. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1093/jhered/esh057\u003c/span\u003e\u003cspan address=\"10.1093/jhered/esh057\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBielenberg DG, Wang Y, Li Z, Zhebentyayeva T, Fan S, Reighard GL et al (2008) Sequencing and annotation of the evergrowing locus in peach [\u003cem\u003ePrunus persica\u003c/em\u003e (L.) Batsch] reveals a cluster of six MADS-box transcription factors as candidate genes for regulation of terminal bud formation. Tree Genet Genomes 4(3):495\u0026ndash;507. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s11295-007-0126-9\u003c/span\u003e\u003cspan address=\"10.1007/s11295-007-0126-9\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBrown DS, Kotob FA (1957) Growth of flower buds of apricot, peach, and pear during the rest period. Proc Am Soc Hortic Sci 69:158\u0026ndash;164\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCalle A, Saski C, W\u0026uuml;nsch A, Grimplet J, Gasic K (2022) Identification of key genes related to dormancy control in \u003cem\u003ePrunus\u003c/em\u003e species by meta-analysis of RNAseq data. Plants 11(19):2469. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/plants11192469\u003c/span\u003e\u003cspan address=\"10.3390/plants11192469\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCampoy JA, Ruiz D, Egea J (2011) Dormancy in temperate fruit trees in a global warming context: A review. Sci Hortic 130(2):357\u0026ndash;372. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.scienta.2011.07.011\u003c/span\u003e\u003cspan address=\"10.1016/j.scienta.2011.07.011\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCanton M, Forestan C, Bonghi C, Varotto S (2021) Meta-analysis of RNA-Seq studies reveals genes with dominant functions during flower bud endo- to eco-dormancy transition in \u003cem\u003ePrunus\u003c/em\u003e species. Sci Rep 11:13173. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/s41598-021-92600-6\u003c/span\u003e\u003cspan address=\"10.1038/s41598-021-92600-6\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCastresana J (2000) Selection of conserved blocks from multiple alignments for their use in phylogenetic analysis. Mol Biol Evol 17(4):540\u0026ndash;552. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1093/oxfordjournals.molbev.a026334\u003c/span\u003e\u003cspan address=\"10.1093/oxfordjournals.molbev.a026334\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCooke JEK, Eriksson ME, Junttila O (2012) The dynamic nature of bud dormancy in trees: Environmental control and molecular mechanisms. Plant Cell Environ 35(10):1707\u0026ndash;1728. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1111/j.1365-3040.2012.02552.x\u003c/span\u003e\u003cspan address=\"10.1111/j.1365-3040.2012.02552.x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDobin A, Davis CA, Schlesinger F, Drenkow J, Zaleski C, Jha S et al (2013) STAR: ultrafast universal RNA-seq aligner. Bioinformatics 29(1):15\u0026ndash;21. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1093/bioinformatics/bts635\u003c/span\u003e\u003cspan address=\"10.1093/bioinformatics/bts635\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFad\u0026oacute;n E, Do H, Blanke M, Rodrigo J, Luedeling E (2023) Apparent differences in agroclimatic requirements for sweet cherry across climatic settings reveal shortcomings in common phenology models. Agric Meteorol 333:109387. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.agrformet.2023.109387\u003c/span\u003e\u003cspan address=\"10.1016/j.agrformet.2023.109387\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFad\u0026oacute;n E, Fernandez E, Behn H, Luedeling E (2020a) A conceptual framework for winter dormancy in deciduous trees. Agronomy 10(2):241. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/agronomy10020241\u003c/span\u003e\u003cspan address=\"10.3390/agronomy10020241\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFad\u0026oacute;n E, Herrera S, Guerrero BI, Guerra ME, Rodrigo J (2020b) Chilling and heat requirements of temperate stone fruit trees (\u003cem\u003ePrunus\u003c/em\u003e sp). Agronomy 10(3):409. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/agronomy10030409\u003c/span\u003e\u003cspan address=\"10.3390/agronomy10030409\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFad\u0026oacute;n E, Rodrigo J, Luedeling E (2021) Cultivar-specific responses of sweet cherry flowering to rising temperatures during dormancy. Agric Meteorol 307:108486. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.agrformet.2021.108486\u003c/span\u003e\u003cspan address=\"10.1016/j.agrformet.2021.108486\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFad\u0026oacute;n E, Herrero M, Rodrigo J (2018) Dormant flower buds actively accumulate starch over winter in sweet cherry. Front Plant Sci 9:171. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3389/fpls.2018.00171\u003c/span\u003e\u003cspan address=\"10.3389/fpls.2018.00171\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFad\u0026oacute;n E, Herrero M, Rodrigo J (2015) Flower development in sweet cherry framed in the BBCH scale. Sci Hortic (Amsterdam) 192:141\u0026ndash;147. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.scienta.2015.05.027\u003c/span\u003e\u003cspan address=\"10.1016/j.scienta.2015.05.027\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFad\u0026oacute;n E, Rodrigo J (2018) Unveiling winter dormancy through empirical experiments. Environ Exp Bot 152:28\u0026ndash;36. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.envexpbot.2017.11.006\u003c/span\u003e\u003cspan address=\"10.1016/j.envexpbot.2017.11.006\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFalavigna VDS, Guitton B, Costes E, Andr\u0026eacute;s F (2019) I want to (bud) break free: The potential role of \u003cem\u003eDAM\u003c/em\u003e and \u003cem\u003eSVP\u003c/em\u003e-like genes in regulating dormancy cycle in temperate fruit trees. Front Plant Sci 9:1990. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3389/fpls.2018.01990\u003c/span\u003e\u003cspan address=\"10.3389/fpls.2018.01990\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFang ZZ, Lin-Wang K, Dai H, Zhou DR, Jiang CC, Espley RV et al (2022) The genome of low-chill Chinese plum Sanyueli (\u003cem\u003ePrunus salicina\u003c/em\u003e Lindl.) provides insights into the regulation of the chilling requirement of flower buds. Mol Ecol Resour 22:1919\u0026ndash;1938. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1111/1755-0998.13585\u003c/span\u003e\u003cspan address=\"10.1111/1755-0998.13585\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFishman S, Erez A, Couvillon GA (1987) The temperature dependence of dormancy breaking in plants: mathematical analysis of a two-step model involving a cooperative transition. J Theor Biol 124:473\u0026ndash;483. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/S0022-5193(87)80221-7\u003c/span\u003e\u003cspan address=\"10.1016/S0022-5193(87)80221-7\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGalindo Gonz\u0026aacute;lez LM, El Kayal W, Ju CJT, Allen CCG, King-Jones S, Cooke JEK (2012) Integrated transcriptomic and proteomic profiling of white spruce stems during the transition from active growth to dormancy. Plant Cell Environ 35(4):682\u0026ndash;701. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1111/j.1365-3040.2011.02444.x\u003c/span\u003e\u003cspan address=\"10.1111/j.1365-3040.2011.02444.x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGoeckeritz C, Hollender CA (2021) There is more to flowering than those \u003cem\u003eDAM\u003c/em\u003e genes: The biology behind bloom in rosaceous fruit trees. Curr Opin Plant Biol 59:101995. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.pbi.2020.101995\u003c/span\u003e\u003cspan address=\"10.1016/j.pbi.2020.101995\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGuerra ME, Rodrigo J (2015) Japanese plum pollination: A review. Sci Hortic 197:674\u0026ndash;686. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.scienta.2015.10.032\u003c/span\u003e\u003cspan address=\"10.1016/j.scienta.2015.10.032\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGuerrero BI, Fad\u0026oacute;n E, Guerra ME, Rodrigo J (2024) Perspectives on the adaptation of Japanese plum-type cultivars to reduced winter chilling in two regions of Spain. Front Plant Sci 15:1343593. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3389/fpls.2024.1343593\u003c/span\u003e\u003cspan address=\"10.3389/fpls.2024.1343593\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGuerrero BI, Guerra ME, Rodrigo J (2022) Simple Sequence Repeat (SSR)-based genetic diversity in interspecific plumcot-type (\u003cem\u003ePrunus salicina\u003c/em\u003e \u0026times; \u003cem\u003ePrunus armeniaca\u003c/em\u003e) hybrids. Plants 11(9):1241. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/plants11091241\u003c/span\u003e\u003cspan address=\"10.3390/plants11091241\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGuerrero BI, Guerra ME, Herrera S, Irisarri P, Pina A, Rodrigo J (2021) Genetic diversity and population structure of japanese plum-type (Hybrids of \u003cem\u003eP. salicina\u003c/em\u003e) accessions assessed by SSR markers. Agronomy 11(9):1748. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/agronomy11091748\u003c/span\u003e\u003cspan address=\"10.3390/agronomy11091748\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHao X, Chao W, Yang Y, Horvath D (2015) Coordinated expression of \u003cem\u003eFLOWERING LOCUS T\u003c/em\u003e and \u003cem\u003eDORMANCY ASSOCIATED MADS-BOX\u003c/em\u003e-like genes in leafy spurge. PLoS ONE 10(5):e0126030. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1371/journal.pone.0126030\u003c/span\u003e\u003cspan address=\"10.1371/journal.pone.0126030\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHerrera S, Lora J, Fad\u0026oacute;n E, Hedhly A, Alonso JM, Hormaza JI, Rodrigo J (2022) Male meiosis as a biomarker for endo- to ecodormancy transition in apricot. Front Plant Sci 13:842333. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3389/fpls.2022.842333\u003c/span\u003e\u003cspan address=\"10.3389/fpls.2022.842333\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHorvath DP (2009) Common mechanisms regulate flowering and dormancy. Plant Sci 177(6):523\u0026ndash;531. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.plantsci.2009.09.002\u003c/span\u003e\u003cspan address=\"10.1016/j.plantsci.2009.09.002\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHsu CY, Adams JP, Kim H, No K, Ma C, Strauss SH et al (2011) FLOWERING LOCUS T duplication coordinates reproductive and vegetative growth in perennial poplar. Proc Natl Acad Sci U S A 108(26):10756\u0026ndash;10761. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1073/pnas.1104713108\u003c/span\u003e\u003cspan address=\"10.1073/pnas.1104713108\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHuerta-Cepas J, Szklarczyk D, Heller D et al (2019) eggNOG 5.0: a hierarchical, functionally and phylogenetically annotated orthology resource based on 5090 organisms and 2502 viruses. Nucleic Acids Res 47(D1):D309\u0026ndash;D314. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1093/nar/gky1085\u003c/span\u003e\u003cspan address=\"10.1093/nar/gky1085\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eJim\u0026eacute;nez S, Lawton-Rauh AL, Reighard GL, Abbott AG, Bielenberg DG (2009) Phylogenetic analysis and molecular evolution of the dormancy associated \u003cem\u003eMADS-box\u003c/em\u003e genes from peach. BMC Plant Biol 9:81. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/1471-2229-9-81\u003c/span\u003e\u003cspan address=\"10.1186/1471-2229-9-81\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eJim\u0026eacute;nez S, Li Z, Reighard G et al Identification of genes associated with growth cessation and bud dormancy entrance using a dormancy-incapable tree mutant. BMC Plant Biol .2010;10;25. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/1471-2229-10-25\u003c/span\u003e\u003cspan address=\"10.1186/1471-2229-10-25\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eJung S, Lee T, Cheng CH, Buble K, Zheng P, Yu J, Humann J, Ficklin SP, Gasic K, Scott K, Frank M (2018) 15 years of GDR: New data and functionality in the Genome Database for Rosaceae. Nucleic Acids Res 47(D1):D1137\u0026ndash;D1145\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eJunquera V, Rubenstein DI, Levin SA, Hormaza JI, Vadillo P\u0026eacute;rez I, Jim\u0026eacute;nez Gavil\u0026aacute;n P (2024) Hydrological collapse in southern Spain under expanding irrigated agriculture: meteorological, hydrological, and structural drought [preprint]. arXiv; Aug 1. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.48550/arXiv.2408.00683\u003c/span\u003e\u003cspan address=\"10.48550/arXiv.2408.00683\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKovaleski AP (2024) The potential for an increasing threat of unseasonal temperature cycles to dormant plants. New Phytol 244(2):377\u0026ndash;383. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1111/nph.20052\u003c/span\u003e\u003cspan address=\"10.1111/nph.20052\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKumar S, Stecher G, Li M, Knyaz C, Tamura K (2018) Phylogenetic and molecular evolutionary analysis across computing platforms. Mol Biol Evol 35(6):1547\u0026ndash;1549. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1093/molbev/msy096\u003c/span\u003e\u003cspan address=\"10.1093/molbev/msy096\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLang G, Early J, Martin G, Darnell R (1987) Endodormancy, paradormancy, and ecodormancy\u0026ndash;physiological terminology and classification for dormancy research. HortScience\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLi B, Dewey CN (2011) RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome. BMC Bioinformatics 12:323. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/1471-2105-12-323\u003c/span\u003e\u003cspan address=\"10.1186/1471-2105-12-323\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLiu C, Feng C, Peng W, Hao J, Wang J, Pan J, He Y (2020) Chromosome-level draft genome of a diploid plum (\u003cem\u003ePrunus salicina\u003c/em\u003e). GigaScience 9(12):giaa130. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1093/gigascience/giaa130\u003c/span\u003e\u003cspan address=\"10.1093/gigascience/giaa130\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLiu X, Wang L, Manzoor MA et al (2025) Unveiling the power of \u003cem\u003ePavGID1s\u003c/em\u003e: the critical player in sweet cherry flower bud dormancy release. Plant Mol Biol 115:60. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s11103-025-01589-3\u003c/span\u003e\u003cspan address=\"10.1007/s11103-025-01589-3\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLloret A, Badenes ML, R\u0026iacute;os G (2018) Modulation of dormancy and growth responses in reproductive buds of temperate trees. Front Plant Sci 9:1368. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3389/fpls.2018.01368\u003c/span\u003e\u003cspan address=\"10.3389/fpls.2018.01368\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLloret A, Conejero A, Leida C, Petri C, Gil-Mu\u0026ntilde;oz F, Burgos L et al (2017) Dual regulation of water retention and cell growth by a stress-associated protein (\u003cem\u003eSAP\u003c/em\u003e) gene in \u003cem\u003ePrunus\u003c/em\u003e. Sci Rep 7:332. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/s41598-017-00471-7\u003c/span\u003e\u003cspan address=\"10.1038/s41598-017-00471-7\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLloret A, Quesada-Traver C, Conejero A, Arbona V, G\u0026oacute;mez-Mena C, Petri C et al (2021) Regulatory circuits involving bud dormancy factor \u003cem\u003ePpeDAM6\u003c/em\u003e. Hortic Res 8(1):261. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/s41438-021-00706-9\u003c/span\u003e\u003cspan address=\"10.1038/s41438-021-00706-9\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLora J, Herrero M, Tucker MR, Hormaza JI (2017) The transition from somatic to germline identity shows conserved and specialized features during angiosperm evolution. New Phytol 216(2):495\u0026ndash;509. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1111/nph.14330\u003c/span\u003e\u003cspan address=\"10.1111/nph.14330\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLove MI, Huber W, Anders S (2014) Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol 15(12):550. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s13059-014-0550-8\u003c/span\u003e\u003cspan address=\"10.1186/s13059-014-0550-8\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLudevid D, H\u0026ouml;fte H, Himelblau E, Chrispeels MJ (1992) The Expression Pattern of the Tonoplast Intrinsic Protein gamma-TIP in \u003cem\u003eArabidopsis thaliana\u003c/em\u003e Is Correlated with Cell Enlargement. Plant Physiol 100(4):1633\u0026ndash;1639. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1104/pp.100.4.1633\u003c/span\u003e\u003cspan address=\"10.1104/pp.100.4.1633\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLuedeling E (2012) Climate change impacts on winter chill for temperate fruit and nut production: A review. Sci Hortic 144:218\u0026ndash;229\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLuedeling E, Girvetz EH, Semenov MA, Brown PH (2011) Climate change affects winter chill for temperate fruit and nut trees. PLoS ONE 6(5):e20155. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1371/journal.pone.0020155\u003c/span\u003e\u003cspan address=\"10.1371/journal.pone.0020155\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ede Agricultura M Pesca y Alimentaci\u0026oacute;n (MAPA). Anuario de estad\u0026iacute;stica 2022 [Internet]. Madrid: Gobierno de Espa\u0026ntilde;a; 2023 [cited 2025 Jul 01]. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.mapa.gob.es/es/estadistica/temas/publicaciones/anuario-de-estadistica/default.aspx\u003c/span\u003e\u003cspan address=\"https://www.mapa.gob.es/es/estadistica/temas/publicaciones/anuario-de-estadistica/default.aspx\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMeier U (2001) Growth stages of mono- and dicotyledonous plants: BBCH monograph. Federal Biological Research Centre for Agriculture and Forestry, Germany\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMenand B, Desnos T, Nussaume L, Berger F, Bouchez D, Meyer C et al (2002) Expression and disruption of the \u003cem\u003eArabidopsis TOR\u003c/em\u003e (target of rapamycin) gene. Proc Natl Acad Sci U S A 99(9):6422\u0026ndash;6427. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1073/pnas.092141899\u003c/span\u003e\u003cspan address=\"10.1073/pnas.092141899\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMilošević T, Milošević N (2018) Plum (\u003cem\u003ePrunus\u003c/em\u003e spp.) breeding. In: Al-Khayri J, Jain S, Johnson D (eds) Advances in Plant Breeding Strategies: Fruits. Springer, Cham, pp 253\u0026ndash;294\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMimida N, Saito T, Moriguchi T, Suzuki A, Komori S, Wada M (2015) Expression of \u003cem\u003eDORMANCY-ASSOCIATED MADS-BOX\u003c/em\u003e (\u003cem\u003eDAM\u003c/em\u003e)-like genes in apple. Biol Plant 59:237\u0026ndash;244. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s10535-015-0503-4\u003c/span\u003e\u003cspan address=\"10.1007/s10535-015-0503-4\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNCBI Resource Coordinators (2018) Database resources of the National Center for Biotechnology Information. Nucleic Acids Res 46(D1):D8\u0026ndash;D13\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNishitani C, Saito T, Ubi BE, Shimizu T, Itai A, Saito T et al (2012) Transcriptome analysis of \u003cem\u003ePyrus pyrifolia\u003c/em\u003e leaf buds during transition from endodormancy to ecodormancy. Sci Hortic 147:49\u0026ndash;55. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.scienta.2012.09.001\u003c/span\u003e\u003cspan address=\"10.1016/j.scienta.2012.09.001\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNiu R, Cheng Y, Wang F, Zhang Y, Wang C (2024) Transcriptome analysis provides insights into the safe overwintering of local peach flower buds. Curr Issues Mol Biol 46:13903\u0026ndash;13921. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/cimb46120831\u003c/span\u003e\u003cspan address=\"10.3390/cimb46120831\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eORESA Oficina del Regante- Gobierno de Arag\u0026oacute;n [Internet]. 2025 [cited 2025 May 14]. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://aplicaciones.aragon.es/oresa\u003c/span\u003e\u003cspan address=\"http://aplicaciones.aragon.es/oresa\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePeel MC, Finlayson BL, McMahon TA (2007) Updated world map of the K\u0026ouml;ppen-Geiger climate classification. Hydrol Earth Syst Sci 11(5):1633\u0026ndash;1644\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePrudencio \u0026Aacute;S, Hoeberichts FA, Dicenta F, Mart\u0026iacute;nez-G\u0026oacute;mez P, S\u0026aacute;nchez-P\u0026eacute;rez R (2021) Identification of early and late flowering time candidate genes in endodormant and ecodormant almond flower buds. Tree Physiol 41(4):589\u0026ndash;605. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1093/treephys/tpaa151\u003c/span\u003e\u003cspan address=\"10.1093/treephys/tpaa151\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePuertes A, Polat H, Ram\u0026oacute;n-N\u0026uacute;\u0026ntilde;ez LA, Gonz\u0026aacute;lez M, Ancillo G, Zuriaga E et al (2023) Single-bud expression analysis of bud dormancy factors in peach. Plants 12(14):2601. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/plants12142601\u003c/span\u003e\u003cspan address=\"10.3390/plants12142601\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eQuesada-Traver C, Guerrero BI, Badenes ML, Rodrigo J, R\u0026iacute;os G, Lloret A (2020) Structure and expression of bud dormancy-associated MADS-box genes (\u003cem\u003eDAM\u003c/em\u003e) in European plum. Front Plant Sci 11:1288. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3389/fpls.2020.01288\u003c/span\u003e\u003cspan address=\"10.3389/fpls.2020.01288\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eQuesada-Traver C, Lloret A, Carretero-Paulet L, Badenes ML, R\u0026iacute;os G (2022) Evolutionary origin and functional specialization of dormancy-associated MADS box (DAM) proteins in perennial crops. BMC Plant Biol 22:473. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s12870-022-03856-7\u003c/span\u003e\u003cspan address=\"10.1186/s12870-022-03856-7\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eR Core Team (2023) R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRichardson EA, Seeley SD, Walker DR (1974) A model for estimating the completion of rest for \u0026lsquo;Redhaven\u0026rsquo; and \u0026lsquo;Elberta\u0026rsquo; peach trees. HortScience 9:331\u0026ndash;332\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eR\u0026iacute;os G, Leida C, Conejero A, Badenes ML (2014) Epigenetic regulation of bud dormancy events in perennial plants. Front Plant Sci 5:247. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3389/fpls.2014.00247\u003c/span\u003e\u003cspan address=\"10.3389/fpls.2014.00247\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRodrigo J (2000) Spring frosts in deciduous fruit trees\u0026mdash;morphological damage and flower hardiness. Sci Hortic 85(3):155\u0026ndash;173. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/S0304-4238(99)00150-8\u003c/span\u003e\u003cspan address=\"10.1016/S0304-4238(99)00150-8\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRohde A, Bhalerao RP (2007) Plant dormancy in the perennial context. Trends Plant Sci 12(5):217\u0026ndash;223. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.tplants.2007.03.012\u003c/span\u003e\u003cspan address=\"10.1016/j.tplants.2007.03.012\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRonquist F, Teslenko M, van der Mark P, Ayres DL, Darling A, H\u0026ouml;hna S et al (2012) MrBayes 3.2: Efficient Bayesian phylogenetic inference and model choice across a large model space. Syst Biol 61(3):539\u0026ndash;542. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1093/sysbio/sys029\u003c/span\u003e\u003cspan address=\"10.1093/sysbio/sys029\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRothkegel K, S\u0026aacute;nchez E, Montes C, Greve M, Tapia S, Bravo S et al (2017) DNA methylation and small interference RNAs participate in the regulation of MADS-box genes involved in dormancy in sweet cherry (\u003cem\u003ePrunus avium\u003c/em\u003e). Tree Physiol 37(12):1739\u0026ndash;1751. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1093/treephys/tpx055\u003c/span\u003e\u003cspan address=\"10.1093/treephys/tpx055\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRuiz D, Campoy JA, Egea J (2007) Chilling and heat requirements of apricot cultivars for flowering. Environ Exp Bot 61(3):254\u0026ndash;263. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.envexpbot.2007.06.008\u003c/span\u003e\u003cspan address=\"10.1016/j.envexpbot.2007.06.008\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTabuenca MC (1964) Necesidades de frio invernal de variedades de albaricoquero, melocotonero y peral. Ann Aula Dei 7:113\u0026ndash;132\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTalavera G, Castresana J (2007) Improvement of phylogenies after removing divergent and ambiguously aligned blocks from protein sequence alignments. Syst Biol 56(4):564\u0026ndash;577. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1080/10635150701472164\u003c/span\u003e\u003cspan address=\"10.1080/10635150701472164\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eThompson JD, Gibson TJ, Plewniak F, Jeanmougin F, Higgins DG (1997) The CLUSTAL_X windows interface: Flexible strategies for multiple sequence alignment aided by quality analysis tools. Nucleic Acids Res 25(24):4876\u0026ndash;4882. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1093/nar/25.24.4876\u003c/span\u003e\u003cspan address=\"10.1093/nar/25.24.4876\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eVimont N, Fouch\u0026eacute; M, Campoy JA, Tong M, Arkoun M, Yvin JC et al (2019) From bud formation to flowering: Transcriptomic state defines the cherry developmental phases of sweet cherry bud dormancy. BMC Genomics 20(1):974. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s12864-019-6348-z\u003c/span\u003e\u003cspan address=\"10.1186/s12864-019-6348-z\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWickham H (2016) ggplot2: Elegant Graphics for Data Analysis. Springer-, New York\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eYamane H, Kashiwa Y, Ooka T, Tao R, Yonemori K (2008) Suppression subtractive hybridization and differential screening reveals endodormancy-associated expression of an \u003cem\u003eSVP/AGL24-type MADS-box\u003c/em\u003e gene in lateral vegetative buds of Japanese apricot. J Am Soc Hortic Sci 133(5):708\u0026ndash;716. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.21273/JASHS.133.5.708\u003c/span\u003e\u003cspan address=\"10.21273/JASHS.133.5.708\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eYu J, Conrad AO, Decroocq V, Zhebentyayeva T, Williams DE, Bennett D et al (2020) Distinctive gene expression patterns define endodormancy to ecodormancy transition in apricot and peach. Front Plant Sci 11:180. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3389/fpls.2020.00180\u003c/span\u003e\u003cspan address=\"10.3389/fpls.2020.00180\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZhang Z, Zhuo X, Zhao K, Zheng T, Han Y, Yuan C et al (2018) Transcriptome profiles reveal the crucial roles of hormone and sugar in the bud dormancy of \u003cem\u003ePrunus mume\u003c/em\u003e. Sci Rep 8:5090. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/s41598-018-23108-9\u003c/span\u003e\u003cspan address=\"10.1038/s41598-018-23108-9\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZhao Y, Ma Y, Qiu H, Zhou L, He K, Ye Y (2025) Wake up: the regulation of dormancy release and bud break in perennial plants. Front Plant Sci 16:1553953. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3389/fpls.2025.1553953\u003c/span\u003e\u003cspan address=\"10.3389/fpls.2025.1553953\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZhao YL, Li Y, Guo DD, Chen XJ, Cao K, Wu JL et al (2025) Spatiotemporally transcriptomic analyses of floral buds reveal the high-resolution landscape of flower development and dormancy regulation in peach. Hortic Res 12(5):uhaf029. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1093/hr/uhaf029\u003c/span\u003e\u003cspan address=\"10.1093/hr/uhaf029\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZhu Y, Li Y, Xin D, Chen W, Shao X, Wang Y, Guo W (2015) RNA-Seq-based transcriptome analysis of dormant flower buds of Chinese cherry (\u003cem\u003ePrunus pseudocerasus\u003c/em\u003e). Gene 555:362\u0026ndash;376. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.gene.2014.11.032\u003c/span\u003e\u003cspan address=\"10.1016/j.gene.2014.11.032\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZhuang W, Gao Z, Wang L, Zhong W, Ni Z, Zhang Z (2013) Comparative proteomic and transcriptomic approaches to address the active role of GA4 in Japanese apricot flower bud dormancy release. J Exp Bot 64(16):4953\u0026ndash;4966. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1093/jxb/ert284\u003c/span\u003e\u003cspan address=\"10.1093/jxb/ert284\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[{"identity":"a5fe7807-f096-47ca-910c-fd2adcf29020","identifier":"10.13039/501100013162","name":"Fundación Biodiversidad","awardNumber":"ADAPFRUTCC","order_by":0},{"identity":"f7fdb657-dc43-4d0a-a911-2c1b4ea3b92c","identifier":"10.13039/501100011033","name":"Agencia Estatal de Investigación","awardNumber":"PID2020-115473RR-I00","order_by":1},{"identity":"f996966d-4589-4931-8eae-aaf50a2bbb52","identifier":"10.13039/501100011033","name":"Agencia Estatal de Investigación","awardNumber":"PRE2018-084962","order_by":2}],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"Fundación Biodiversidad","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Climatic adaptation, Chill accumulation, Epigenetics, Gene expression, Phenology, Transcriptome","lastPublishedDoi":"10.21203/rs.3.rs-7114924/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7114924/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eDormancy progression in temperate fruit trees is highly sensitive to environmental conditions and chilling accumulation. To investigate the regulation of dormancy in Japanese plum (\u003cem\u003ePrunus salicina\u003c/em\u003e hybrids), we performed a comparative transcriptomic analysis of flower buds from two Japanese plum cultivars with different chilling requirements, \"Hiromi Red\" (high chill) and \"Crimson Glo\" (low chill), grown under contrasting climatic climates (semi-arid and Mediterranean subtropical). The study combined phenological observations, quantification of chill and heat requirements, as well as transcriptomic analyses across three key developmental stages: full dormancy (T0), dormancy release (T1), and full recovery (T2). Climate exerted a stronger influence than dormancy stage on gene expression profiles, leading to cultivar- and climate-specific transcriptional responses. Key dormancy-related genes—such as \u003cem\u003eDAM\u003c/em\u003e, \u003cem\u003eFT\u003c/em\u003e, and \u003cem\u003eSAP1\u003c/em\u003e— exhibited differential expression patterns across climates, suggesting roles in climatic adaptation. Notably, dormancy phases occurred approximately one month earlier under Mediterranean subtropical conditions, accompanied by a marked reduction in chilling requirements. Expression and phylogenetic analyses revealed that environmental conditions had a stronger effect on the transcriptomic profiles than the progression of dormancy itself, potentially due to epigenetic modulation. These findings provide new insights into the molecular mechanisms underlying dormancy in woody perennial species and offer perspectives for developing cultivars better adapted to changing climatic scenarios.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGene \u0026amp; Accession Numbers\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll sequence data and genome files generated for this study were deposited in the NCBI Sequence Read Archive (SRA) under BioProject PRJNA1276976.\u003c/p\u003e","manuscriptTitle":"Dormancy Dynamics in Japanese Plum: Transcriptomic Responses to Variable Climatic Conditions and Chill Requirements","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-15 10:58:37","doi":"10.21203/rs.3.rs-7114924/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"9280294c-a81a-4106-b36b-857d246a976f","owner":[],"postedDate":"July 15th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":51457229,"name":"Horticulture"},{"id":51457230,"name":"Bioinformatics"},{"id":51457231,"name":"Computational Biology"},{"id":51457232,"name":"Molecular Biology"},{"id":51457233,"name":"Epigenetics \u0026 Genomics"}],"tags":[],"updatedAt":"2025-07-15T10:58:37+00:00","versionOfRecord":[],"versionCreatedAt":"2025-07-15 10:58:37","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7114924","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7114924","identity":"rs-7114924","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}