Genome-wide identification and characterization of the late embryogenesis abundant (LEA) protein-encoding gene family related to water deficit response in Theobroma cacao

Genome-wide identification and characterization of the late embryogenesis abundant (LEA) protein-encoding gene family related to water deficit response in Theobroma cacao | 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 Short Report Genome-wide identification and characterization of the late embryogenesis abundant (LEA) protein-encoding gene family related to water deficit response in Theobroma cacao Ginna Patricia Velasco Anacona, Julian Alejandro Giraldo Murcia, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8999141/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 Late Embryogenesis Abundant (LEA) proteins play essential roles in plant adaptation to water deficit; however, their genomic organization and stress-responsive regulation remain unexplored in Theobroma cacao . This study represents the first genome-wide identification and characterization of the LEA gene family in cacao and evaluates their involvement in drought response. A total of 30 LEA genes were identified and classified into eight subfamilies based on conserved domains, motif composition, and phylogenetic relationships. Gene structure, chromosomal distribution, and duplication analyses revealed that both tandem and segmental duplication events contributed to family expansion. Promoter analysis showed enrichment of stress- and hormone-responsive cis-acting elements, supporting their regulatory role under abiotic stress. Predicted subcellular localization suggested chloroplast targeting for several LEA-2 members, indicating potential involvement in photosynthetic protection. Expression profiling via RT-qPCR in three cacao clones with contrasting drought tolerance revealed genotype-specific responses. Notably, clone ICS 60 exhibited strong induction of LEA-1, LEA-3, and LEA-5 genes under stress, correlating with greater physiological stress and limited recovery. In contrast, TSH 565 showed moderate induction of SMP and DHN genes, associated with improved recovery, while EET 8 maintained stable expression and physiological parameters. These findings provide new insights into the molecular and physiological mechanisms underlying drought tolerance in cacao and identify candidate genes for breeding climate-resilient cultivars. LEA proteins Theobroma cacao genome-wide analysis drought tolerance gene expression profiling climate-resilient breeding Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Introduction Plants have evolved unique molecular mechanisms and physiological responses to mitigate the effects of external stresses, a phenomenon known as plant resilience (Nguyen et al. 2022 ). These stresses include abiotic and biotic factors such as drought (Haghpanah et al. 2024 ), extreme temperatures (Zhang et al. 2023a ), salinity (Balasubramaniam et al. 2023 ), ultraviolet (UV) radiation (Gao et al. 2025 ), pathogenic bacteria, and harmful insects (Mahanta et al. 2025 ). Among these, water stress represents one of the most significant challenges for plants. To cope with such stressors, plants utilize Late Embryogenesis Abundant (LEA) proteins, which are widely distributed across the plant kingdom and act as osmoprotectants and desiccation damage repair agents (Olvera-Carrillo et al. 2011 ). LEA proteins are glycine-rich, have low molecular weights (10–30 kDa), and play a crucial role in protecting plants against extreme environmental conditions, particularly drought (Chen et al. 2019 ). LEA proteins were initially identified in mature wheat and cotton embryos (Shih et al. 2010 ). Beyond plants, these proteins are also present in animals and microorganisms, including bacteria and fungi (Campos et al. 2013 ). In plants, LEA proteins are categorized into eight groups: LEA-1, LEA-2, LEA-3, LEA-4, LEA-5, LEA-6, dehydrin (DHN), and seed maturation protein (SMP), based on sequence homology and conserved motifs in the Pfam database (Artur et al. 2019 ). For instance, LEA-1 proteins are highly conserved and characterized by a 20-amino acid signature motif (Campos et al. 2013 ), whereas LEA-2 proteins have fewer random coils and contain the water stress and hypersensitive response (WHy) domain (Pantelić et al. 2022 ). Additionally, DHN proteins contain K-segments, with some also possessing Y- or S-segments (Hanin et al. 2011 ). These structural variations suggest diverse functional roles in plant development and stress responses. The LEA gene family has been analyzed at the genome-wide level in several plant species, including Arabidopsis thaliana (Hundertmark and Hincha 2008 ), Citrus sinensis (Pedrosa et al. 2015 ), Zea mays (Zhang et al. 2023b ), Oryza sativa (Wang et al. 2007 ), Cucumis sativus (Zhou et al. 2017 ), Manihot esculenta (Wu et al. 2018 ), Camellia sinensis (Wang et al. 2019 ), Solanum tuberosum (Chen et al. 2019 ), Triticum aestivum (Liu et al. 2019 ), Nelumbo spp. (Chen et al. 2023 ), and Fragaria spp. (Lin et al. 2024 ). However, a systematic analysis of LEA genes in the Theobroma cacao genome is lacking, limiting our understanding of their role in stress tolerance, particularly in response to drought, a major challenge for cacao cultivation (De Almeida et al. 2016 ). The high-quality assembly of the T. cacao genome (Motamayor et al. 2013 ) provides valuable resources for conducting a comprehensive genomic study of the LEA gene family and its functional significance in this species. T. cacao , native to the Amazon Basin, is a vital crop for smallholder farmers in Africa, Central America, and South America, serving as a primary source of income (Kongor et al. 2024 ; Esan et al. 2025 ). Cacao beans are essential for the chocolate industry and have applications in cosmetics and pharmaceuticals due to their bioactive compounds (Soares and Oliveira 2022 ). Global cacao production reached 4.69 million tons in 2024/2025, benefiting approximately 40 to 52 million people (International Cocoa Organization (ICCO) 2025 ). However, climate change increasingly threatens cacao cultivation, particularly through water deficits and droughts, which significantly impact its growth and yield (Santos et al. 2014 ; Farrell et al. 2018 ; Hebbar et al. 2020 ). Drought stress affects T. cacao trees by reducing photosynthesis and nutrient uptake, ultimately decreasing productivity (De Almeida et al. 2016 ; Basu et al. 2016 ; Cornejo et al. 2018 ). Water scarcity in cacao leads to yield losses ranging from 10% to 89%, causing vegetative and reproductive organ abscission, reduced photosynthesis, lower water-use efficiency, and decreased dry matter accumulation (Schwendenmann et al. 2010 ; Santos et al. 2014 ; De Almeida et al. 2016 ; Gateau et al. 2018). Despite these adverse effects, T. cacao 's adaptive mechanisms to climate change remain poorly characterized compared to those of other major crops such as rice and maize (Panda et al. 2021 ; Zhao et al. 2025 ; Liu et al. 2025 ; Ismail et al. 2025 ). Given that drought responses in cacao are genotype-specific and influenced by stress severity and duration (Santos et al. 2014 ; De Almeida et al. 2016 ; Osorio et al. 2021), elucidating the genetic basis of water stress tolerance is critical. Here, we conducted the first genome-wide analysis of LEA genes in T. cacao , characterizing their gene structure, conserved domains, phylogenetic relationships, chromosomal distribution, and duplication events. To explore their functional roles, we evaluated LEA gene expression under drought stress via RT-qPCR in three contrasting cacao clones, alongside physiological assessments. Our findings provide novel insights into the LEA gene family’s evolution and stress-responsive regulation, offering molecular tools for breeding climate-resilient cacao varieties. Materials and methods Genome-wide identification of the LEA genes The LEA genes of Arabidopsis thaliana were identified through an extensive literature review, which included a list of these genes from the study by Hundertmark and Hincha (Hundertmark and Hincha 2008 ). All LEA genes cataloged in The Arabidopsis Information Resource (TAIR) ( https://www.arabidopsis.org/ ) were also included. The accession numbers of LEA genes were retrieved and filtered out to create a non-redundant list, where the protein sequence of each accession was obtained and used as a query to identify putative LEA genes in the Theobroma cacao genome using the BLASTP program, with an identity threshold > 50% and an E-value < 1e-15. Characterization and classification of LEA proteins The putative LEA proteins in T. cacao were validated by identifying conserved domains using the PANTHER database (Protein Analysis Through Evolutionary Relationships) ( http://www.pantherdb.org ) (Mi et al. 2021 ), and InterPro ( https://www.ebi.ac.uk/interpro/ ) (Blum et al. 2021 ). This validation was further supported by identifying and analyzing conserved motifs using the online Multiple Expectation Maximization for Motif Elucidation (MEME) tool ( http://meme-suite.org/index.html ), performed in classic mode with the following parameters: any number of repetitions and a maximum of 10 motifs. As a final step, the confirmed LEA proteins were classified according to eight typical Pfam-based conserved domains: PF03760 (LEA-1), PF03168 (LEA-2), PF03242 (LEA-3), PF02987 (LEA-4), PF00477 (LEA-5), PF10714 (LEA-6), PF02496 (ASR, LEA-7), PF00257 (DHN), and PF04927 (SMP). Physicochemical properties and subcellular localization of LEA proteins The physicochemical properties of predicted LEA proteins, including amino acid sequences length, molecular weight (Mw), theoretical isoelectric point (pI), and grand average of hydropathy (GRAVY) index, were calculated using the ProtParam tool ( http://web.expasy.org/protparam/ ) (Gasteiger et al. 2003 ). As for the subcellular localization, predictions were carried out using the WoLF PSORT tool ( http://www.genscript.com/wolf-psort.html ) (Horton et al. 2007 ), Plant-mPLoc ( http://www.csbio.sjtu.edu.cn/bioinf/plant-multi/ ) (Chou and Shen 2010 ), LOCALIZER ( https://localizer.csiro.au/ ) (Sperschneider et al. 2017 ), and BUSCA ( https://busca.biocomp.unibo.it/ ) (Savojardo et al. 2018 ) Alignment and phylogenetic analysis of LEA proteins A multiple sequence alignment of all identified LEA protein sequences in T. cacao was conducted using MAFFT-FFT-NS-i with default parameters (Katoh et al. 2002 ). A maximum likelihood (ML) phylogenetic tree was constructed using the IQ-Tree software ( http://iqtree.cibiv.univie.ac.at ) (Nguyen et al. 2015 ), with the WAG + F+G4 model identified as the best fit according to the Akaike Information Criterion (AIC). Branch support was evaluated using approximate likelihood ratio tests (aLRT) with 1,000 bootstrap replicates. The resulting phylogenetic tree was visualized and annotated using the ITOL web server ( https://itol.embl.de ) (Letunic and Bork 2024 ). Promoter cis-acting element analysis of the LEA genes The upstream sequences (2000 bp) of each LEA coding sequence were extracted from the whole T. cacao genome using TBtools software (Chen et al. 2020 ). The extracted files were submitted to the PlantCare website ( http://bioinformatics.psb.ugent.be/webtools/plantcare ) to predict the cis-acting elements. The results were sorted, enriched through screening, and visualized accordingly. Chromosomal distribution and gene duplication of the LEA genes The chromosomal positions of the LEA genes were obtained from the genomic annotation of T. cacao , and their localization was visualized using TBtools (Chen et al. 2020 ). The occurrence and duplication events of the LEA genes were analyzed and visualized with MCScanX (Wang et al. 2012 ) via TBtools, which categorizes gene duplications into four types: dispersed, proximal, tandem, and WGD/segmental. Synteny analysis and identification of orthologous LEA genes For collinearity analysis, the whole genome of T. cacao (GenBank: GCF_000208745.1) was downloaded, and homologous LEA genes were identified in the genomes of G. hirsutum (GenBank: GCF_007990345.1), S. lycopersicum (GenBank: GCF_036512215.1), and A. thaliana (GenBank: GCF_000001735.4) using BLASTP with an identity threshold > 90% and an E-value < 1e-15, utilizing MCScanX within TBtools. A Venn diagram was employed to identify orthologous LEA genes in T. cacao relative to the other plant species. Plant materials and stress treatment for physiological and gene expression profiling The experiment was conducted during 2021–2022 in the tropical dry forest (bs-T) of northern Huila, Colombia (2°36′55″ N, 75°21′33″ W; 600 m a.s.l.). Three commercial clones of Theobroma cacao L. were selected based on their contrasting drought responses previously reported under regional agroecological conditions: EET 8 (high drought tolerance), TSH 565 (moderate tolerance), and ICS 60 (high susceptibility) (Osorio et al., 2021). Clonal propagation was performed by grafting onto uniform rootstocks. After two months of post-grafting acclimatization, seedlings were transplanted into 5-kg black polypropylene bags containing silty loam soil (pH 6.0) with drainage holes. Plants underwent a three-month acclimation period under well-watered conditions to ensure homogeneous vegetative development prior to stress imposition. Irrigation was maintained at field capacity during this phase. Fertilization was applied according to soil analysis and crop nutritional requirements. For the experimental phase, plants were transferred to 16-L pots containing a 3:1 (v/v) soil:sand substrate to ensure adequate drainage and homogeneous water distribution. Environmental conditions, including air temperature, relative humidity, and photosynthetically active radiation (PAR), were recorded daily using a HOBO 8 weather station (HOBOware, Onset Computer Corp., USA) positioned 0.5 m above ground level. Vapor pressure deficit (VPD) was calculated following standard psychrometric equations (Online Resource 1). The experiment was established under a completely randomized design (CRD) with a two-factor factorial arrangement. The first factor corresponded to water regime, with two levels: well-watered (WW) and drought stress (DS). The second factor included three contrasting Theobroma cacao clones (EET 8, TSH 565, and ICS 60). Each treatment combination included 20 biological replicates per clone. Soil volumetric water content (VWC) was monitored daily at 20 cm depth using a FieldScout TDR-300 Moisture Meter (Spectrum Technologies, USA). Under WW conditions, irrigation was adjusted to maintain soil VWC at 60% field capacity, corresponding to a predawn Leaf water potential ( Ψ leaf ) (MPa) between − 0.60 and − 0.17 MPa. For the DS treatment, irrigation was withheld until Ψ leaf reached − 1.5 MPa, which occurred after 19 days of water deprivation (DAT19). At this point, plants exhibited visible drought symptoms including leaf senescence. Subsequently, plants were rehydrated to field capacity (60% VWC) within 24 hours, followed by an 11-day recovery period to assess plant resilience (DAT30). Relative Leaf Water Content (RWC) RWC was determined following the protocol described by De Almeida et al. ( 2016 ) and based on the method proposed by Slatyer and Shmueli (1967). Briefly, RWC was calculated as the percentage of water content in leaf tissue relative to its fully turgid state, using fresh, turgid, and dry weights. Leaf samples (25 cm² segments) were collected from 20 plants per treatment. Fresh weight was recorded immediately after sampling. Samples were then hydrated in distilled water for 24 h at room temperature to obtain turgid weight. Subsequently, tissues were oven-dried at 70°C until constant weight to determine dry weight. RWC was expressed as a percentage of the maximum water-holding capacity of the tissue. Physiological measurements Ψ leaf was measured predawn (5:00 am − 6:30 am) using a Schölander pressure chamber (PWSC Model F01, EVNCO, Auckland, New Zealand) on the fifth fully expanded leaf from the apex of four plants per treatment (n = 4) for each clone. Gas exchange parameters, including net photosynthetic rate ( A ) (µmol CO₂ m⁻² s⁻¹), transpiration rate ( E ) (mmol H₂O m⁻² s⁻¹), stomatal conductance ( gs ) (mmol H₂O m⁻² s⁻¹), and intercellular CO 2 ( Ci ) (µmol CO 2 mol air⁻¹), were measured between 9:00 am and 11:00 am. These measurements were taken from the third or fourth fully expanded leaf from the apex downward on 12 plants per treatment using a CI-340 Handheld Photosynthesis System measurement system (CID Bio-Science Inc. WA, United States) (Liu, 2020). Based on these parameters, the intrinsic water-use efficiency ( WUEi ) (µmol CO 2 mmol⁻¹ ) was calculated (Zhang et al. 2001 ). RNA extraction and quantitative Real-Time PCR analysis For gene expression, mature leaves were collected from four plants per clone at two time points: day 19 (DAT19, peak drought stress), and day 30 (DAT30, recovery phase) once physiological measurements completed (noon). At each time point, leaves were also collected from the corresponding WW control plants. Samples were immediately preserved in RNAlater® and stored at -80°C until processing. Total RNA was extracted from liquid nitrogen-ground tissue using the GeneJET™ Plant RNA Purification Mini Kit (Thermo Fisher Scientific, USA), with RNA quality verified through concentration measurement using a NP80 NanoPhotometer (Implen GmbH, Germany), integrity assessment by 1% agarose gel electrophoresis and A260/A280 and A260/A230 ratio analysis. cDNA synthesis was performed with 100 ng of total RNA using M-MuLV Reverse Transcriptase (Thermo Fisher Scientific, USA) and oligo(dT)18 primers. We designed sixteen specific primer pairs targeting LEA genes using Primer3Plus Software (Untergasser et al. 2007 ) (Online Resource 2). The reference gene ACPB (acyl carrier protein B), previously validated for cacao gene expression studies (Osorio et al. 2021), was used for normalization. Detailed protocol can be consulted in Online Resource (3). Quantitative PCR was performed in triplicate with four biological replicates per condition, using the DyNAmo Flash SYBR Green qPCR Kit (Thermo Fisher Scientific, CA, USA) on a QuantStudio 1 Real-Time PCR System (Applied Biosystems, CA, USA). The thermal cycling protocol consisted of initial denaturation at 95°C for 7 min, followed by 40 cycles of 95°C for 10 s and 60°C for 30 s. Reaction specificity was confirmed by melting curve analysis (60–95°C). Standard curves were generated for each primer pair to determine amplification efficiencies (Online Resource 4), and relative gene expression was calculated using the 2 − ΔΔCt method (Pfaffl, 2001 ) with efficiency correction (Pfaffl, 2004 ). Statistical analysis We employed multiple statistical approaches to analyze treatment and clonal effects. Generalized linear mixed models (GLMMs) handled fixed and random effects while accommodating non-normal data distributions (Pinheiro 2000 ). Multivariate ANOVA (MANOVA) assessed treatment impacts across correlated physiological variables (Tabachnick 2019 ). The Bonferroni correction-controlled Type I errors in multiple comparisons (Abdi 2007 ). For gene expression data, we used aligned rank transform (ART) ANOVA to address non-normality (Kay 2021 ), followed by ART-contrasts for post-hoc analysis (Elkin 2021 ). All statistical analyses were conducted using R statistical software version 4.4.2. Results Identification of the LEA genes in T. cacao The integration of LEA genes identified by Hundertmark and Hincha (Hundertmark and Hincha 2008 ) with data from The Arabidopsis Information Resource (TAIR) resulted in 106 accession numbers, which were subsequently blasted against the whole T. cacao genome. Following this approach, 30 LEA genes were identified in T. cacao (Table 1 ). All metadata related to these LEA genes is available in Online Resource (5). Table 1 LEA genes identified in the T. cacao genome Group Subfamily Number of genes Number of proteins BLASTP E-value (Range) LEA* 1 3 4 5e − 17 – 7e − 34 LEA* 2 12 19 1e − 54 – 3e − 164 LEA* 3 2 3 1e − 27 – 3e − 58 LEA 4 1 1 4e − 115 LEA 5 3 3 1e − 21 – 5e − 46 LEA 6 1 1 3e − 15 SMP 3 3 2e − 36 – 2e − 65 DHN 5 5 1e − 15 – 1e − 57 *LEA groups showing isoforms Molecular characterization of LEA proteins To verify that these genes encode LEA-related proteins, PANTHER and InterPro were employed to detect conserved domains, while MEME was used to analyze conserved motifs. The domains and motifs of the 30 LEA proteins were found to match the eight typical Pfam-based conserved domains, classifying them into the LEA-1, LEA-2, LEA-3, LEA-4, LEA-5, LEA-6, SMP, and DHN groups, as shown in Fig. 1 . The largest subfamily was LEA-2 with 12 members, followed by the DHN, which contained five members. Notably, some members of the LEA-1, LEA-2, and LEA-3 subfamilies possess isoforms (Table 1 ). The analysis of physicochemical properties revealed that among all LEA proteins, LEA-6 (89 aa) was the shortest, while LEA-4 (438 aa) was the longest, with molecular weights of 9505.37 kDa and 47842.57 kDa, respectively. Isoelectric point analysis indicated that SMP (4.68–5.32), and LEA-3 (9.45–9.82) were the most acidic and basic subfamilies, respectively. Among the 39 LEA proteins analyzed (including isoforms), 19 (49%) exhibited a pI 7. Additionally, the GRAVY values showed that only eight members of LEA-2 (GRAVY > 0) were considered hydrophobic proteins, while all the LEA proteins in the remaining groups (GRAVY < 0) were found to be highly hydrophilic (Table 2 ). The predicted subcellular localization revealed that the eight hydrophobic proteins in the LEA-2 group were primarily localized to the chloroplast. In contrast, all proteins from the other subfamilies were exclusively located in the nucleus, except for the LEA-3 group, which was localized to the mitochondria (Fig. 1 ). Additional physicochemical properties and detailed information for all LEA proteins are provided in Online Resource (6). Table 2 Conserved domains and physicochemical characteristics of LEA proteins in T. cacao Group Subfamily Lenght (aa) Molecular weight (Mw) Isoelectric point (pI) Grand average of hydropathy (GRAVY) Domain InterPro ID LEA 1 127–166 13876.73 − 17698.80 5.08–9.66 -0.923 – -1.302 LEA-1 PF03760 LEA 2 151–311 16437.95–35785.81 4.67–10.02 -0.357–0.290 LEA-2 PF03168 LEA 3 84–94 9698.18–9960.38 9.45–9.82 -0.513 – -0.213 LEA-3 PF03242 LEA 4 438 47842.57 6.25 -1.326 LEA-4 PF02987 LEA 5 156–174 10843.83–18997.39 5.97–9.72 -0.857 – -1.391 LEA-5 PF00477 LEA 6 89 9505.37 5.31 -0.939 LEA-6 PF10714 SMP 237–284 24609.25–29255.68 4.68–5.32 -0.296 – -0.368 SMP PF04927 DHN 114–234 10809.82–26410.60 5.41–9.30 -1.220 – -1.905 DHN PF00257 Phylogenetic analysis of LEA proteins A maximum likelihood (ML) tree was constructed using the full-length LEA protein sequences from T. cacao (Fig. 2 ). Interestingly, the topology revealed that the 39 LEA proteins were clustered into eight distinct groups (LEA-1, LEA-2, LEA-3, LEA-4, LEA-5, LEA-6, SMP, and DHN) with relatively high bootstrap support (> 70%), which further confirmed that they belong to the LEA family. The LEA-2 had the highest representation in the phylogeny, accounting for 49% of all LEA. Identification of cis-acting element in LEA gene promoters To explore the regulatory mechanisms of the LEA gene, a cis-acting element analysis was performed on a 2000 bp sequence of its region promoter, and the identified elements were classified into three categories: environment or stress-responsive, phytohormone or hormone-responsive, and growth or development-related elements (Fig. 3 ). The most abundant category was the environment element 669 (72%), followed by phytohormone 228 (25%), and growth 26 (3%) (Fig. 3 a). Within the environment element category, two prevalent regulatory elements responsible for stress-induced pathways were identified: G-box 148 (22%), and Box 4 with 104 (16%). Among hormone response cis elements, including ABRE 132 (58%), and TCA motifs 25 (11%), which are involved in abscisic acid (ABA), and methyl jasmonate (MeJA) responses, respectively. As for the growth specificity elements, CAT-box was the most abundant 20 (77%) (Fig. 3 b). At the LEA group level, the three categories were predominantly dominated by LEA-2, followed by DHN (Fig. 3 c). Chromosomal localization and gene duplication of LEA genes In the T. cacao LEA gene family, 30 genes were unevenly distributed across the nine chromosomes, except for chromosome seven, which lacked LEA genes, as shown in Fig. 4 . High and low LEA gene densities were detected on chromosomes 5 and 8, which contained 9 and 1 genes, respectively. In terms of LEA distribution, each group was as follows: LEA-1 (Chr5: 2; 22%), LEA-2 (Chr5: 3; 33%, Chr9: 3; 100%), LEA-3 (Chr1: 1; 25%, Chr6: 1; 33%), LEA-4 (Chr5: 1; 11%), LEA-5 (Chr10: 2; 100%), LEA-6 (Chr2: 1; 25%), SMP (Chr5: 1; 11%), and DHN (Chr2: 2; 50%). Tandem duplication and segmental duplication are essential for the evolution of gene families, driving adaptation to varying environmental conditions. Gene duplication events were analyzed with MCScanX, which identified 2 pairs of tandem duplication genes (LEA-1_chr5-1/ LEA-1_chr5-2), and (LEA-5_chr10-1/LEA-5_chr10-2) among the 30 T. cacao LEA genes (Fig. 5 ) Synteny analysis of LEA genes To further deduce the evolutionary origin and orthologous relationship of T. cacao LEA family, comparative syntenic maps with the genomes of G. hirsutum , S. lycopersicum , and A. thaliana were constructed (Fig. 6 a). Analysis of T. cacao and three graminaceous model plants identified 80, 26, and 34 LEA genes homologous to G. hirsutum , S. lycopersicum , and A. thaliana , respectively (Online Resource 7). Notably, among the three graminaceous species, 14 homologs of LEA genes were detected (Fig. 6 b). Among the 14 LEA orthologous genes in T. cacao , the LEA-2 subfamily comprised 6 genes, representing the largest proportion among all subfamilies. This suggests that LEA-2 subfamily genes may play an important role in the expansion of LEA gene family during evolution. Table 3 LEA orthologous genes of T. cacao and G. hirsutum , S. lycopersicum , and A. thaliana Group Subfamily Orthologous gene Symbol gene Initial genomic position Final genomic position LEA 1 LEA-1_chr3-1 LOC18606060 31483181 31483953 LEA-1_chr5-1 LOC18599099 28544724 28545989 2 LEA-2_chr1-1 LOC18614030 33969340 33971585 LEA-2_chr1-2 LOC18614068 34161976 34163125 LEA-2_chr3-1 LOC18606720 35117281 35118884 LEA-2_chr5-1 LOC18597391 10447 13604 LEA-2_chr5-2 LOC18598383 8532798 8533973 LEA-2_chr9-2 LOC18590297 33961964 33962725 3 LEA-3_chr1-1 LOC18613581 31337158 31338048 SMP SMP_chr1-1 LOC18613320 29482148 29483586 SMP_chr4-1 LOC18602997 27963963 27966158 SMP_chr5-1 LOC18600259 37203759 37205712 DHN DHD_chr2-2 LOC18607734 3961359 3962803 DHD_chr8-1 LOC18591660 2487207 2488654 Leaf water potential and relative water content determination Statistically significant differences ( p < 0.05) in Ψ leaf were observed between water statuses on DAT19. In WW conditions, Ψ leaf ranged from − 0.60 to − 0.17 MPa, while those DS experienced a significant reduction to approximately − 1.5 MPa on DAT19. Not all clones exhibited similar effects on Ψ leaf on DAT19. The clone with the highest Ψ leaf was TSH 565 (–1.27 MPa), whereas the clone with the lowest Ψ leaf was ICS 60 (–1.47 MPa). Despite facing nearly three weeks of water deficit stress without irrigation, the three cocoa clones recovered after rewatering, demonstrating tolerance to this level of stress. RWC maintained high values in all WW clones (46.1–60.5%). On DAT19, clones EET 8 and TSH 565 experienced a reduction in RWC, with TSH 565 showing the highest water loss (23%). Clone ICS 60 maintained RWC values similar to its control plants, showing the highest value (68%) compared to the other clones under DS conditions (Table 4 ). Table 4 Changes in Leaf water potential and gas exchange parameters of the three cacao clones under different water states Clone Water states Ψ leaf a (MPa) A b µmol CO₂ m⁻² s⁻¹), gs c (mmol H 2 O m⁻² s⁻¹) Ci d (µmol CO 2 mol air⁻¹) E e (mmol H 2 O m⁻² s⁻¹) RWC f (%) WUEi g (µmol CO 2 mmol⁻¹) EET 8 DAT19 h DS j -1.375 ± 0.103 B -0.448 ± 0.431 B 3.438 ± 0.871 B 1397.603 ± 246.035 AC 0.175 ± 0.045 B 41.433 ± 18.530 A -0.105 ± 0.162 BC WW k -0.170 ± 0.009 A 5.865 ± 0.287 A 29.765 ± 3.535 A 912.783 ± 38.910 B 1.615 ± 0.164 A 60.570 ± 26.877 A 0.210 ± 0.032 A DAT30 i DS -0.475 ± 0.042 A -0.320 ± 0.090 B 32.293 ± 5.095 AC 1317.245 ± 20.361 A 0.333 ± 0.081 A 83.505 ± 3.344 B -0.035 ± 0.010 A WW -0.515 ± 0.129 A 3.210 ± 1.917 AB 10.913 ± 2.246 B 1086.378 ± 102.724 B 1.780 ± 0.196 A 65.803 ± 2.581 A 0.080 ± 0.063 AB THS 565 DAT19 DS -1.275 ± 0.125 B -0.208 ± 0.565 B 4.435 ± 1.147 B 1427.450 ± 163.849 C 0.175 ± 0.036 B 23.505 ± 9.651 A -0.110 ± 0.107 BC WW -0.185 ± 0.009 A 5.050 ± 0.599 A 36.963 ± 7.927 A 1001.760 ± 19.469 AB 1.938 ± 0.351 A 46.198 ± 5.250 A 0.143 ± 0.015 AB DAT30 DS -0.495 ± 0.070 A 1.318 ± 0.921 B 27.108 ± 6.344 BC 1210.045 ± 56.841 AB 0.908 ± 0.216 A 82.200 ± 3.033 B 0.025 ± 0.036 AB WW -0.498 ± 0.078 A 1.578 ± 1.525 B 33.138 ± 9.647 AC 1087.488 ± 75.857 B 1.745 ± 0.153 A 78.643 ± 8.340 B 0.088 ± 0.048 AB ICS 60 DAT19 DS -1.475 ± 0.232 B -0.970 ± 0.326 B 3.298 ± 0.278 B 1675.645 ± 124.570 C 0.165 ± 0.017 B 68.015 ± 29.342 A -0.288 ± 0.083 C WW -0.185 ± 0.010 A 7.250 ± 2.319 A 27.200 ± 5.864 A 814.953 ± 128.488 B 1.450 ± 0.258 A 51.358 ± 3.333 A 0.270 ± 0.088 A DAT30 DS -0.515 ± 0.095 A 3.095 ± 1.465 AB 23.090 ± 3.835 BC 1057.645 ± 101.378 B 0.710 ± 0.146 A 84.018 ± 0.428 B 0.123 ± 0.066 B WW -0.600 ± 0.046 A 5.358 ± 0.272 A 44.588 ± 3.362 A 1014.058 ± 19.694 B 2.568 ± 0.184 A 69.138 ± 2.820 A 0.123 ± 0.013 B a ψleaf , Leaf water potential; b A , net photosynthetic rate; c gs , stomatal conductance; d Ci , intercellular CO2; e E , Transpiration rate; f RWC , Relative leaf water content; g WUEi , intrinsic water-use efficiency; h DAT19, maximum water deficit stress of 19 days; i DAT30, recovery after 11 days of rehydration after DS; j DS, water deficit stress; k WW, well-watered; *The values are mean (n = 4) ± standard error with different letters indicating significant differences by Tukey test ( p < 0.05). Leaf gas exchange As expected, DS significantly affected leaf gas exchange ( p < 0.05), reducing A , E , and gs , while increasing Ci in the evaluated clones. Under WW treatment, A values ranged from 5.0 to 7.2 µmol CO₂ m⁻² s⁻¹, whereas under DS, A was completely inhibited on DAT19, showing negative values between − 0.97 and − 0.20 µmol CO₂ m⁻² s⁻¹, with no significant differences among clones (Table 4 ). Negative A values under light conditions, combined with the higher Ci concentrations observed under DS, indicate photorespiration (Niu et al. 2025). As previously noted, Ci increased significantly in DS plants compared to WW plants. On DAT19, Ci values increased from 814–1001 µmol CO₂ mol⁻¹ to 1397–1675 µmol CO₂ mol⁻¹, representing an average increase of 69% due to DS. The highest Ci values were observed in ICS 60 and TSH 565, while the lowest value was found in clone EET 8, representing a 53% increase. Significant differences ( p < 0.05) were found between clones with the highest and lowest Ci values. A significant reduction in gs (85% on average) was observed after DS treatment in clones compared to their control plants. Under WW, gs values ranged from 27.2 to 36.9 mmol H₂O m⁻² s⁻¹, while under DS, they ranged from 3.2 to 4.4 mmol H₂O m⁻² s⁻¹. WUEi also decreased significantly under DS across all three clones, reaching negative values, as observed for A . Under WW conditions, WUEi ranged from 0.14 to 0.27 µmol CO₂ mmol H₂O⁻¹, while under DS, it ranged from − 0.10 to − 0.28 µmol CO₂ mmol H₂O⁻¹. Notably, under DS, WUEi was significantly lower in clone ICS 60 compared to the other clones, all of which showed negative WUEi values. E followed a similar pattern to gs , A , and WUEi . Finally, A , E , and gs values of DS plants in clones ICS 60 and TSH 565 gradually recovered at DAT30, reaching values similar to WW plants. However, the clone EET 8 did not recover. Interestingly, WUEi reached WW levels at DAT30 in clone ICS 60 and 71% of WW levels at DAT30 in clone TSH 565, with no significant differences between treatments. Gene expression profiling For gene expression, we evaluated the LEA orthologous genes of T. cacao shown in Table 3 and Online Resource (5). Quantitative PCR analysis revealed distinct expression patterns of LEA genes across the three cacao clones in response to water deficit (Online Resource 8). All LEA gene families exhibited significant transcriptional regulation during drought stress (DAT19) and subsequent recovery (DAT30), with marked clonal variations in expression dynamics (Fig. 7 and Online Resource 9). ICS 60 exhibited the highest induction of LEA-1 under DAT19 conditions (18.14), with a sharp decrease during DAT30 (–14.47). TSH 565 showed moderate upregulation in DAT19 (7.17) and a substantial reduction in DAT30 (–33.08), whereas EET 8 maintained a relatively stable and mild expression response (Fig. 7 a). For LEA-2, ICS 60 showed consistent moderate expression in both DAT19 (3.33) and DAT30 (2.58). EET 8 displayed minor variation between DAT19 (1.32) and DAT30 (–1.27), while TSH 565 was downregulated in both phases (–0.70 in DAT19 and − 12.62 in DAT30) (Fig. 7 b). LEA-3 and LEA-5 were upregulated under all conditions, with ICS 60 showing the highest expression levels (Figs. 7 c and 7 e). LEA-4 and LEA-6 exhibited contrasting expression patterns: TSH 565 maintained elevated levels in both DAT19 and DAT30, whereas ICS 60 remained consistently downregulated (Figs. 7 d and 7 f). DHN expression varied by genotype and treatment. ICS 60 and TSH 565 were upregulated during DAT19 but downregulated during DAT30, while EET 8 remained repressed throughout both conditions (Fig. 7 g). For SMP, TSH 565 showed strong induction in DAT19 followed by sharp downregulation during DAT30, whereas ICS 60 exhibited moderate upregulation during recovery (Fig. 7 h). Discussion The present study represents the first comprehensive genome-wide identification and characterization of the LEA protein-encoding gene family in T. cacao , a crop of significant economic importance, particularly in tropical regions. While LEA proteins have been extensively investigated in model organisms and agronomic crops such as A. thaliana (Hundertmark and Hincha 2008 ), O. sativa (Wang et al. 2007 ), Zea mays (Li and Cao 2016 ), S. lycopersicum (Cao and Li 2015 ), and G. hirsutum (Magwanga et al. 2018 ), their presence, structural diversity, and functional roles in T. cacao remained unexplored until now. Given the increasing vulnerability of cacao to climate change-induced water deficit stress, elucidating the molecular mechanisms underlying its adaptive responses is imperative for developing genetically resilient cultivars. This study, therefore, provides a foundational genomic framework for understanding the role of LEA proteins in cacao and their contribution to drought tolerance. We identified 30 LEA genes in the cacao genome, classified into eight groups (LEA-1 to LEA-6, SMP, and DHN), which underscores the functional diversification of this gene family. The largest subfamily, LEA-2, with 12 members, aligns with findings in other crops such as A. thaliana (Hundertmark and Hincha 2008 ), S. lycopersicum (Cao and Li 2015 ), and G. hirsutum (Magwanga et al. 2018 ), where LEA-2 proteins are often the most abundant. This suggests a conserved role for LEA-2 proteins in stress responses across plant species. The presence of isoforms within the LEA-1, LEA-2, and LEA-3 subfamilies further highlights the evolutionary plasticity of the LEA gene family, likely driven by gene duplication and alternative splicing events (Hong et al. 2005; Abdul et al. 2021). These isoforms may enable cacao to fine-tune its response to varying stress conditions, providing a robust and flexible mechanism for drought adaptation. Physicochemical properties of the identified LEA proteins, such as their low molecular weight, high hydrophilicity, and diverse isoelectric points (pI), are consistent with their roles as osmoprotectants and desiccation protectants. The hydrophilic nature of LEA proteins, as indicated by their negative GRAVY values, is crucial for their function in stabilizing cellular structures and preventing protein aggregation during dehydration (Tunnacliffe and Wise 2007 ). As for the subcellular localization predictions revealed that most LEA proteins were localized in the nucleus, with some exceptions, such as LEA-3 proteins, which were predicted to localize in the mitochondria. The localization of LEA-2 proteins in the chloroplast suggests their involvement in protecting the photosynthetic machinery during water stress, a critical function for maintaining photosynthetic efficiency under drought conditions (Yang et al. 2021 ; Qiao et al. 2024 ; Iqbal and Munir 2024 ). This finding aligns with research in other crops, where LEA-2 proteins have been demonstrated to protect chloroplasts during abiotic stress (Magwanga et al. 2018 ; Abdul et al. 2021; Liu et al. 2023 ). The protective role of these proteins is also attributed to their WHy domain (Water stress and Hypersensitive response), which has been shown to stabilize membranes and prevent protein aggregation during dehydration, thereby safeguarding cellular structures (Battaglia et al. 2008 ; Mertens et al. 2018 ). A phylogenetic analysis revealed that the LEA proteins in cacao cluster into eight distinct groups, with high bootstrap support (> 70%). This clustering aligns with the classification based on conserved domains and motifs, further validating the identification of these proteins as members of the LEA family. The LEA-2 subfamily was the most represented, accounting for 49% of all LEA proteins, which mirrors findings in other species, such as A. thaliana, S. lycopersicum , and G. hirsutum (Hundertmark and Hincha 2008 ; Cao and Li 2015 ; Magwanga et al. 2018 ). Evolutionary results also revealed that the LEA gene family in cacao has undergone both tandem and segmental duplication events, which are common mechanisms for gene family expansion and diversification (Artur et al. 2019 ). The identification of two tandem duplication pairs (LEA-1_chr5-1/LEA-1_chr5-2 and LEA-5_chr10-1/LEA-5_chr10-2) suggests that these genes may have evolved to provide cacao with enhanced adaptability to environmental stresses. Cis-acting elements in the promoter regions of LEA genes revealed a predominance of stress-responsive elements, such as G-box (22%) and Box 4 (16%), which are known to be involved in abiotic stress responses (Yamaguchi and Shinozaki 2005). The presence of these elements suggests that the expression of LEA genes in cacao is tightly regulated in response to environmental stresses, particularly drought. Additionally, the identification of hormone-responsive elements, such as ABRE (58%) and TCA motifs (11%), highlights the role of phytohormones in regulating LEA gene expression under stress conditions (Mehrotra et al. 2013 ; Delahaie et al. 2013 ; Stevenson et al. 2016 ), which aligns with findings in Arachis hypogaea (Huang et al. 2022 ). The predominance of stress-responsive elements in the LEA-2 and DHN subfamilies further supports their roles in drought tolerance. The physiological measurements, including Ψ leaf and gas exchange parameters, revealed significant differences among the clones under drought stress. Ψ leaf is a key indicator of plant water status and its ability to uptake soil water and minimize dehydration (Bray 1997 ; Rodríguez et al. 2017). Drought-tolerant genotypes typically maintain less negative Ψ leaf values under stress, supporting water homeostasis and cell turgor (Jarin et al. 2024 ). In this study, Ψ leaf declined in all cacao clones under drought stress, reaching approximately − 1.5 MPa at DAT19, a moderate stress level compared to previous studies reporting values below − 3.0 MPa under prolonged drought (Santos et al. 2014 ; De Almeida et al. 2016 ; Osorio et al. 2021). These differences likely reflect variations in stress intensity, duration, and soil water availability. Field studies indicate that Ψ leaf reductions tend to be less pronounced than in greenhouse conditions due to greater soil water retention, delaying drought perception by the root system (Araque et al. 2012 ; Ávila et al. 2016; De Almeida et al. 2016 ). The TSH 565 clone, previously identified as one of the most drought-tolerant genotypes due to its ability to maintain a less negative Ψ leaf (Balasimha et al. 1991 ; García 2016), exhibited the smallest Ψ leaf reduction in our study, suggesting enhanced water homeostasis in its leaf tissues. Moreover, Ψ leaf recovery after rehydration at DAT30 aligns with previous reports, where cacao clones restored their values following irrigation resumption (García 2016; Kacou et al. 2016; De Almeida et al. 2016 ; Lahive et al. 2019 ). Gas exchange analysis revealed significant declines in A , E , and gs under drought stress, consistent with previous findings in cacao (Rodríguez et al. 2017; Lahive et al. 2019 ). More drought-susceptible clones exhibited an early decline in gs , whereas more tolerant clones, such as TSH 565, showed minimal changes, a trait associated with better drought adaptation (Osorio et al. 2021). Upon rehydration, ICS 60 and TSH 565 recovered their physiological parameters more rapidly, whereas EET 8 showed slower recovery, reinforcing Ψ leaf as a key trait for drought tolerance classification. WUEi declined under DAT19 conditions, as previously reported in cacao (Kacou et al. 2016), but showed differential recovery among genotypes. ICS 60 exhibited the highest WUEi restoration post-rehydration, indicating a superior adaptive capacity to drought, consistent with findings that greater WUEi recovery correlates with increased drought resistance (Lahive et al. 2019 ). Overall, our findings confirm that ICS 60 is the most drought-tolerant clone under these conditions, maintaining a higher RWC despite exhibiting the lowest Ψ leaf . While TSH 565 demonstrated resilience, it experienced greater water loss and only partial WUEi recovery. In contrast, EET 8 showed the lowest recovery capacity. Notably, these results contrast with those of Osorio et al. (2021), who reported that EET 8 performed best under drought stress conditions, whereas ICS 60 exhibited the poorest response. This discrepancy may arise from differences in experimental conditions, such as soil composition, vapor pressure deficit, or the duration and severity of drought stress. Additionally, acclimation responses influenced by prior environmental conditions could contribute to the variation observed across studies. Further research comparing physiological responses across diverse environments is needed to clarify the influence of environmental factors on drought tolerance rankings among cacao clones. These findings underscore the importance of physiological plasticity in drought tolerance and reinforce the relevance of Ψ leaf and WUEi as key criteria for selecting drought-resilient cacao clones in breeding programs. In relation to expression analysis of LEA genes under drought stress revealed significant upregulation in all three cacao clones (EET 8, TSH 565, and ICS 60) at the peak of stress (DAT19), followed by a decrease during the recovery phase (DAT30). This pattern aligns with the known role of LEA proteins in protecting cells during dehydration and their reduced necessity once water availability is restored (Hand et al. 2011 ). The most pronounced upregulation was observed in the ICS 60 clone, which exhibited the highest expression levels of LEA-1, LEA-3, and LEA-5 under drought stress. This suggests that ICS 60 may rely more heavily on LEA proteins for drought tolerance compared to the other clones. Interestingly, the expression patterns of LEA genes varied among the clones, indicating genotype-specific responses to drought stress. For instance, TSH 565 showed a strong upregulation of SMP and DHN genes during drought stress, followed by a sharp downregulation during recovery, suggesting a rapid osmotic adjustment mechanism. In contrast, EET 8 exhibited a more stable expression pattern, with minimal fluctuations in LEA gene expression, indicating a more controlled and less dynamic response to drought stress. The sustained upregulation of LEA-3 and LEA-5 in all clones during both drought stress and recovery phases suggests that these proteins play a continuous role in maintaining cellular stability and dehydration tolerance. This mirrors findings in other crops, where LEA-3 and LEA-5 proteins have been shown to stabilize membranes and prevent protein aggregation under stress conditions (Liu et al. 2016 ; Wang et al. 2024 ). The identification of these molecular signatures provides a foundation for marker-assisted selection of drought-resilient cacao varieties. Conclusions This study employs an integrated approach, combining genomic, phylogenetic, expression, and physiological analyses, to establish a comprehensive molecular framework for understanding cacao's adaptive responses to drought stress. Genome-wide identification and classification revealed 30 LEA genes in Theobroma cacao , organized into eight subfamilies, with LEA-2 being the most abundant, underscoring its critical role in osmotic stress adaptation. Chloroplastic localization of LEA-2 proteins further supports their function in protecting the photosynthetic machinery under stress conditions. Expression analysis demonstrated significant upregulation of LEA genes during drought, with genotype-specific responses. The ICS 60 clone exhibited the highest upregulation of LEA-1, LEA-3, and LEA-5, correlating with severe physiological stress and limited recovery, suggesting a reliance on LEA proteins for acute stress mitigation. In contrast, TSH 565 displayed moderate stress tolerance and improved recovery, associated with rapid osmotic adjustment mediated by SMP and DHN genes. Meanwhile, EET 8 maintained stable LEA expression and physiological parameters, indicative of a balanced, less stress-dependent adaptation strategy. These findings advance our understanding of the molecular mechanisms underlying cacao's drought tolerance and provide actionable insights for breeding more resilient cultivars, crucial for sustaining cacao production in a changing climate. Declarations Data availability statement The raw datasets used during the current study are available from the corresponding author upon reasonable request. Acknowledgments The authors gratefully acknowledge the financial support provided by the project “Differential Gene Expression of Selected Cacao Clones to Determine Their Tolerance to Extreme Climatic Conditions in Huila.” This study was supported by the Sistema de Investigación, Desarrollo Tecnológico e Innovación (SENNOVA) – Centro de Formación Agroindustrial “La Angostura.” The authors also thank the students under the Contrato de Aprendizaje program who participated in sample collection, data recording, and laboratory sample processing, particularly Yennifer Barrios Rico. We further acknowledge the SENNOVA researchers Eliana Lizeth Medina Ríos, Alejandro Garcia and Valentin Murcia, for their valuable technical support and contributions to the development of this study. In addition, we extend our gratitude to the instructors for their academic guidance and mentorship, and to the administrative team for their logistical and operational support, which was essential for the successful execution of this study. Funding This study was funded by the Sistema de Investigación, Desarrollo Tecnológico e Innovación - SENNOVA – Centro de Formación Agroindustrial “La Angostura”, under the project SGPS-9329-2022: "Differential Gene Expression of Selected Cacao Clones to Determine Their Tolerance to Extreme Climatic Conditions in Huila." The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Conflicts of interest The authors declare that there are no conflicts of interest. Ethical approval Not applicable. Author contributions Conceptualization: V-AGP, G-MJA, N-OJE and R-CAF; Methodology: V-AGP, G-MJA, N-OJE and R-CAF; Software: V-AGP, G-MJA, N-OJE and R-CAF; Validation: V-AGP, G-MJA, N-OJE and R-CAF; Formal analysis: V-AGP, G-MJA, N-OJE and R-CAF; Investigation: V-AGP, G-MJA, N-OJE and R-CAF; Data curation: V-AGP, G-MJA, N-OJE and R-CAF; Writing – original draft preparation: V-AGP and R-CAF; Writing – review & editing: V-AGP, G-MJA, N-OJE and R-CAF; Supervision: V-AGP; Project administration: V-AGP; Funding acquisition: V-AGP. All authors have read and agreed to the published version of the manuscript. Authors' ORCID IDs Ginna Patricia Velasco-Anacona: https://orcid.org/0000-0002-8686-7136 Alexis Felipe Rojas-Cruz: https://orcid.org/0000-0003-4467-0914 Noriega-Ortega Jhon Eduar: https://orcid.org/0000-0003-1055-1159 Giraldo-Murcia Julian Alejandro: https://orcid.org/0000-0002-5242-947X References Abdi H (ed) (2007) The Bonferroni and Šidák corrections for multiple comparisons. 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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-8999141","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Short Report","associatedPublications":[],"authors":[{"id":599384487,"identity":"27ef1f3f-00f7-47cf-9fd5-b56d0f3a7103","order_by":0,"name":"Ginna Patricia Velasco Anacona","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA7klEQVRIiWNgGAWjYFAC5gYwxQYiPoAY7AS1MCK0MM4AMZiJ1QK2kAdMEtBgcLyx8eOPGhu7Puneg59tfm2T52NmYPzwMQePljMHm6V5jqUlt8mcS5bO7btt2MbMwCw5cxtuLZIzEhukGRsOJ7NJ5BhI5/bcZgRqYWPmxadl/sPmnz8hWox/W/bctieohV+CsU2Ct+GwHVCLmTTDj9uJhLXwJLZZA/2SANJi2dtwO7mNmbEZr1/Y2A8fvgkMMXv5GTnGN378uW07v7354IePeLTAQGIDiGRsA5MNhNUDgT2E+kOU4lEwCkbBKBhhAADVmkxB4siVKgAAAABJRU5ErkJggg==","orcid":"","institution":"Servicio Nacional de Aprendizaje SENA","correspondingAuthor":true,"prefix":"","firstName":"Ginna","middleName":"Patricia Velasco","lastName":"Anacona","suffix":""},{"id":599384490,"identity":"42385063-e68e-4630-b93d-1f245873cb44","order_by":1,"name":"Julian Alejandro Giraldo Murcia","email":"","orcid":"","institution":"Servicio Nacional de Aprendizaje SENA","correspondingAuthor":false,"prefix":"","firstName":"Julian","middleName":"Alejandro Giraldo","lastName":"Murcia","suffix":""},{"id":599384492,"identity":"eaa7c90a-0b2a-4cc3-972d-8f3530d35ce1","order_by":2,"name":"Jhon Eduar Noriega Ortega","email":"","orcid":"","institution":"Servicio Nacional de Aprendizaje SENA","correspondingAuthor":false,"prefix":"","firstName":"Jhon","middleName":"Eduar Noriega","lastName":"Ortega","suffix":""},{"id":599384497,"identity":"328663a2-f71b-43b8-b523-de4ed485012b","order_by":3,"name":"Alexis Felipe Rojas Cruz","email":"","orcid":"","institution":"Pontificia Universidad Javeriana","correspondingAuthor":false,"prefix":"","firstName":"Alexis","middleName":"Felipe Rojas","lastName":"Cruz","suffix":""}],"badges":[],"createdAt":"2026-03-01 04:23:13","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8999141/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8999141/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":104341165,"identity":"0b50943a-7fb4-4340-9768-4c28a9e927a9","added_by":"auto","created_at":"2026-03-10 16:45:48","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":5442436,"visible":true,"origin":"","legend":"\u003cp\u003ePhylogenetic relationship and sequence characteristics of LEA proteins. \u003cstrong\u003ea)\u003c/strong\u003e Conserved domains possessed by members of each group, where different colored boxes represent different conserved domains. \u003cstrong\u003eb)\u003c/strong\u003e Conserved motifs in each member of the group, where different colored boxes represent different motifs. A maximum of 10 motifs were searched with motif lengths between 10 and 50 residues. Motif occurrence was set to zero or one occurrence per sequence. Subcellular localization is indicated by colored circles next to the phylogeny (red for nucleus, purple for mitochondria, yellow for cytoplasm, and green for chloroplast). Isoforms are denoted by uppercase letters\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-8999141/v1/4341153c7b6aa419fa9c5ae0.png"},{"id":104341168,"identity":"87cd6750-6142-499c-8f0a-b45296f95133","added_by":"auto","created_at":"2026-03-10 16:45:48","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":7132227,"visible":true,"origin":"","legend":"\u003cp\u003eMaximum likelihood (ML) tree of LEA proteins in \u003cem\u003eT. cacao.\u003c/em\u003e The 39 full-length LEA proteins were selected after a detailed individual analysis to construct a phylogenetic tree using the ML method in IQ-Tree with 1,000 bootstrap replicates. The selected LEA proteins are grouped into eight categories based on their protein domains and are distinguished by different colors. The size of the circle on each branch represents bootstrap support \u0026gt; 70. Isoforms are denoted by uppercase letters\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-8999141/v1/bc099ad085637899a46e8156.png"},{"id":104341173,"identity":"d5ca3414-5f3b-4547-8376-7e31e9e9f607","added_by":"auto","created_at":"2026-03-10 16:45:48","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":16723304,"visible":true,"origin":"","legend":"\u003cp\u003eCis-acting elements predicted in 2000 bp sequence upstream of the LEA genes. \u003cstrong\u003ea)\u003c/strong\u003e Heatmap summarizing the statistical density of cis elements in the promoter regions of LEA genes. \u003cstrong\u003eb)\u003c/strong\u003e Histograms showing the total number of cis elements in LEA promoters, categorized into environmental (aquamarine), phytohormonal (orange), and growth-related (yellow) elements. \u003cstrong\u003ec)\u003c/strong\u003e Ratios of cis-acting elements corresponding to the three biological categories for each LEA gene cluster\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-8999141/v1/772211778abac85dd129fb1a.png"},{"id":104341175,"identity":"8b242548-4cac-446d-8d7c-7a93f4b6d0d2","added_by":"auto","created_at":"2026-03-10 16:45:48","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":12059500,"visible":true,"origin":"","legend":"\u003cp\u003eGenomic distribution of LEA on \u003cem\u003eT. cacao \u003c/em\u003echromosomes. The scale on the left denotes chromosome length in megabases (Mb). Chromosome numbers are indicated by the green numerals at the top of each chromosomal representation. Locations of LEA genes are highlighted in black text along the chromosomes. The gradient of color from blue to red represents the relative gene density, with warmer colors corresponding to regions of higher LEA gene density\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-8999141/v1/36789ea966719a6504c26d7c.png"},{"id":104341178,"identity":"c32595c5-90d7-4921-987b-7d0b07599793","added_by":"auto","created_at":"2026-03-10 16:45:48","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":12466152,"visible":true,"origin":"","legend":"\u003cp\u003eSchematic diagram of the duplication patterns of the LEA genes. Red lines connecting genes outside the chromosome indicate tandem duplicated pairs. The heatmap and lines represent gene density on the chromosomes, increasing from blue to green. The chromosome number is displayed within each chromosome.\u003c/p\u003e","description":"","filename":"Figure5.png","url":"https://assets-eu.researchsquare.com/files/rs-8999141/v1/7ac54541892fbb96a4f936c5.png"},{"id":104405996,"identity":"71fb38b9-1bf1-40fd-bbf9-5d6b62e3e908","added_by":"auto","created_at":"2026-03-11 12:24:25","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":27114793,"visible":true,"origin":"","legend":"\u003cp\u003eSynteny analysis of LEA genes between \u003cem\u003eT. cacao\u003c/em\u003eand representative plant species. \u003cstrong\u003ea)\u003c/strong\u003eCollinearity relationship of \u003cem\u003eT. cacao\u003c/em\u003e with \u003cem\u003eG. hirsutum\u003c/em\u003e, \u003cem\u003eS. lycopersicum\u003c/em\u003e, and \u003cem\u003eA. thaliana\u003c/em\u003e, respectively. Gray lines represent aligned blocks between the paired genomes, red lines indicate syntenic LEA gene pairs. \u003cstrong\u003eb)\u003c/strong\u003e Venn diagram showing the LEA orthologous genes of \u003cem\u003eT. cacao\u003c/em\u003e among the three graminaceous species\u003c/p\u003e","description":"","filename":"Figure6.png","url":"https://assets-eu.researchsquare.com/files/rs-8999141/v1/276cfbf612206cb38b1cdb26.png"},{"id":104341169,"identity":"122d27cc-dc6d-44ba-972b-85fcef6295f4","added_by":"auto","created_at":"2026-03-10 16:45:48","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":151687,"visible":true,"origin":"","legend":"\u003cp\u003eDifferential expression patterns of LEA orthologous genes in response to water deficit stress in three \u003cem\u003eT. cacao clones.\u003c/em\u003eRelative gene expression of: \u003cstrong\u003ea) \u003c/strong\u003eLEA-1, \u003cstrong\u003eb)\u003c/strong\u003e LEA-2, \u003cstrong\u003ec)\u003c/strong\u003e LEA-3, \u003cstrong\u003ed)\u003c/strong\u003e LEA-4, \u003cstrong\u003ee)\u003c/strong\u003e LEA-5, \u003cstrong\u003ef)\u003c/strong\u003e LEA-6, \u003cstrong\u003eg)\u003c/strong\u003e DHN, and \u003cstrong\u003eh)\u003c/strong\u003e SMP. Data represent mean log2-fold change values (±SD; n=4 biological replicates) relative to unstressed controls (WW). Distinct lowercase letters denote statistically significant differences (\u003cem\u003ep \u003c/em\u003e\u0026lt;0.05, Tukey's HSD test) between drought stress (DAT19) and recovery (DAT30) time points within each clone\u003c/p\u003e","description":"","filename":"Figure7.png","url":"https://assets-eu.researchsquare.com/files/rs-8999141/v1/2332606a8b99fab6225c26bb.png"},{"id":104784241,"identity":"66582ac1-51c1-4bba-bf3a-d0d78fc5be6c","added_by":"auto","created_at":"2026-03-17 08:06:12","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":76671429,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8999141/v1/2cdb30de-6fc5-4e99-9706-63cf5817f012.pdf"},{"id":104406102,"identity":"cf5c58e6-76ae-4eec-86c2-c8d6f44b100e","added_by":"auto","created_at":"2026-03-11 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16:45:48","extension":"xlsx","order_by":8,"title":"","display":"","copyAsset":false,"role":"supplement","size":12898,"visible":true,"origin":"","legend":"","description":"","filename":"OnlineResource9.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-8999141/v1/3df940860eb58eee8f0de95d.xlsx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Genome-wide identification and characterization of the late embryogenesis abundant (LEA) protein-encoding gene family related to water deficit response in Theobroma cacao","fulltext":[{"header":"Introduction","content":"\u003cp\u003ePlants have evolved unique molecular mechanisms and physiological responses to mitigate the effects of external stresses, a phenomenon known as plant resilience (Nguyen et al. \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). These stresses include abiotic and biotic factors such as drought (Haghpanah et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), extreme temperatures (Zhang et al. \u003cspan citationid=\"CR88\" class=\"CitationRef\"\u003e2023a\u003c/span\u003e), salinity (Balasubramaniam et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), ultraviolet (UV) radiation (Gao et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2025\u003c/span\u003e), pathogenic bacteria, and harmful insects (Mahanta et al. \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Among these, water stress represents one of the most significant challenges for plants. To cope with such stressors, plants utilize Late Embryogenesis Abundant (LEA) proteins, which are widely distributed across the plant kingdom and act as osmoprotectants and desiccation damage repair agents (Olvera-Carrillo et al. \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). LEA proteins are glycine-rich, have low molecular weights (10\u0026ndash;30 kDa), and play a crucial role in protecting plants against extreme environmental conditions, particularly drought (Chen et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eLEA proteins were initially identified in mature wheat and cotton embryos (Shih et al. \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). Beyond plants, these proteins are also present in animals and microorganisms, including bacteria and fungi (Campos et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). In plants, LEA proteins are categorized into eight groups: LEA-1, LEA-2, LEA-3, LEA-4, LEA-5, LEA-6, dehydrin (DHN), and seed maturation protein (SMP), based on sequence homology and conserved motifs in the Pfam database (Artur et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). For instance, LEA-1 proteins are highly conserved and characterized by a 20-amino acid signature motif (Campos et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), whereas LEA-2 proteins have fewer random coils and contain the water stress and hypersensitive response (WHy) domain (Pantelić et al. \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Additionally, DHN proteins contain K-segments, with some also possessing Y- or S-segments (Hanin et al. \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). These structural variations suggest diverse functional roles in plant development and stress responses.\u003c/p\u003e \u003cp\u003eThe LEA gene family has been analyzed at the genome-wide level in several plant species, including \u003cem\u003eArabidopsis thaliana\u003c/em\u003e (Hundertmark and Hincha \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2008\u003c/span\u003e), \u003cem\u003eCitrus sinensis\u003c/em\u003e (Pedrosa et al. \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2015\u003c/span\u003e), \u003cem\u003eZea mays\u003c/em\u003e (Zhang et al. \u003cspan citationid=\"CR89\" class=\"CitationRef\"\u003e2023b\u003c/span\u003e), \u003cem\u003eOryza sativa\u003c/em\u003e (Wang et al. \u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e2007\u003c/span\u003e), \u003cem\u003eCucumis sativus\u003c/em\u003e (Zhou et al. \u003cspan citationid=\"CR91\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), \u003cem\u003eManihot esculenta\u003c/em\u003e (Wu et al. \u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), \u003cem\u003eCamellia sinensis\u003c/em\u003e (Wang et al. \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), \u003cem\u003eSolanum tuberosum\u003c/em\u003e (Chen et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), \u003cem\u003eTriticum aestivum\u003c/em\u003e (Liu et al. \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), \u003cem\u003eNelumbo\u003c/em\u003e spp. (Chen et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), and \u003cem\u003eFragaria\u003c/em\u003e spp. (Lin et al. \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). However, a systematic analysis of LEA genes in the \u003cem\u003eTheobroma cacao\u003c/em\u003e genome is lacking, limiting our understanding of their role in stress tolerance, particularly in response to drought, a major challenge for cacao cultivation (De Almeida et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). The high-quality assembly of the \u003cem\u003eT. cacao\u003c/em\u003e genome (Motamayor et al. \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2013\u003c/span\u003e) provides valuable resources for conducting a comprehensive genomic study of the LEA gene family and its functional significance in this species.\u003c/p\u003e \u003cp\u003e \u003cem\u003eT. cacao\u003c/em\u003e, native to the Amazon Basin, is a vital crop for smallholder farmers in Africa, Central America, and South America, serving as a primary source of income (Kongor et al. \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Esan et al. \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Cacao beans are essential for the chocolate industry and have applications in cosmetics and pharmaceuticals due to their bioactive compounds (Soares and Oliveira \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Global cacao production reached 4.69\u0026nbsp;million tons in 2024/2025, benefiting approximately 40 to 52\u0026nbsp;million people (International Cocoa Organization (ICCO) \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). However, climate change increasingly threatens cacao cultivation, particularly through water deficits and droughts, which significantly impact its growth and yield (Santos et al. \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Farrell et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Hebbar et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Drought stress affects \u003cem\u003eT. cacao\u003c/em\u003e trees by reducing photosynthesis and nutrient uptake, ultimately decreasing productivity (De Almeida et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Basu et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Cornejo et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eWater scarcity in cacao leads to yield losses ranging from 10% to 89%, causing vegetative and reproductive organ abscission, reduced photosynthesis, lower water-use efficiency, and decreased dry matter accumulation (Schwendenmann et al. \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Santos et al. \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; De Almeida et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Gateau et al. 2018). Despite these adverse effects, \u003cem\u003eT. cacao\u003c/em\u003e's adaptive mechanisms to climate change remain poorly characterized compared to those of other major crops such as rice and maize (Panda et al. \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Zhao et al. \u003cspan citationid=\"CR90\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Liu et al. \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Ismail et al. \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Given that drought responses in cacao are genotype-specific and influenced by stress severity and duration (Santos et al. \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; De Almeida et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Osorio et al. 2021), elucidating the genetic basis of water stress tolerance is critical.\u003c/p\u003e \u003cp\u003eHere, we conducted the first genome-wide analysis of LEA genes in \u003cem\u003eT. cacao\u003c/em\u003e, characterizing their gene structure, conserved domains, phylogenetic relationships, chromosomal distribution, and duplication events. To explore their functional roles, we evaluated LEA gene expression under drought stress via RT-qPCR in three contrasting cacao clones, alongside physiological assessments. Our findings provide novel insights into the LEA gene family\u0026rsquo;s evolution and stress-responsive regulation, offering molecular tools for breeding climate-resilient cacao varieties.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eGenome-wide identification of the LEA genes\u003c/h2\u003e \u003cp\u003eThe LEA genes of \u003cem\u003eArabidopsis thaliana\u003c/em\u003e were identified through an extensive literature review, which included a list of these genes from the study by Hundertmark and Hincha (Hundertmark and Hincha \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). All LEA genes cataloged in The Arabidopsis Information Resource (TAIR) (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.arabidopsis.org/\u003c/span\u003e\u003cspan address=\"https://www.arabidopsis.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) were also included. The accession numbers of LEA genes were retrieved and filtered out to create a non-redundant list, where the protein sequence of each accession was obtained and used as a query to identify putative LEA genes in the \u003cem\u003eTheobroma cacao\u003c/em\u003e genome using the BLASTP program, with an identity threshold\u0026thinsp;\u0026gt;\u0026thinsp;50% and an E-value\u0026thinsp;\u0026lt;\u0026thinsp;1e-15.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eCharacterization and classification of LEA proteins\u003c/h3\u003e\n\u003cp\u003eThe putative LEA proteins in \u003cem\u003eT. cacao\u003c/em\u003e were validated by identifying conserved domains using the PANTHER database (Protein Analysis Through Evolutionary Relationships) (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.pantherdb.org\u003c/span\u003e\u003cspan address=\"http://www.pantherdb.org\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) (Mi et al. \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), and InterPro (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.ebi.ac.uk/interpro/\u003c/span\u003e\u003cspan address=\"https://www.ebi.ac.uk/interpro/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) (Blum et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). This validation was further supported by identifying and analyzing conserved motifs using the online Multiple Expectation Maximization for Motif Elucidation (MEME) tool (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://meme-suite.org/index.html\u003c/span\u003e\u003cspan address=\"http://meme-suite.org/index.html\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), performed in classic mode with the following parameters: any number of repetitions and a maximum of 10 motifs. As a final step, the confirmed LEA proteins were classified according to eight typical Pfam-based conserved domains: PF03760 (LEA-1), PF03168 (LEA-2), PF03242 (LEA-3), PF02987 (LEA-4), PF00477 (LEA-5), PF10714 (LEA-6), PF02496 (ASR, LEA-7), PF00257 (DHN), and PF04927 (SMP).\u003c/p\u003e\n\u003ch3\u003ePhysicochemical properties and subcellular localization of LEA proteins\u003c/h3\u003e\n\u003cp\u003eThe physicochemical properties of predicted LEA proteins, including amino acid sequences length, molecular weight (Mw), theoretical isoelectric point (pI), and grand average of hydropathy (GRAVY) index, were calculated using the ProtParam tool (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://web.expasy.org/protparam/\u003c/span\u003e\u003cspan address=\"http://web.expasy.org/protparam/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) (Gasteiger et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2003\u003c/span\u003e). As for the subcellular localization, predictions were carried out using the WoLF PSORT tool (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.genscript.com/wolf-psort.html\u003c/span\u003e\u003cspan address=\"http://www.genscript.com/wolf-psort.html\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) (Horton et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2007\u003c/span\u003e), Plant-mPLoc (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.csbio.sjtu.edu.cn/bioinf/plant-multi/\u003c/span\u003e\u003cspan address=\"http://www.csbio.sjtu.edu.cn/bioinf/plant-multi/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) (Chou and Shen \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2010\u003c/span\u003e), LOCALIZER (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://localizer.csiro.au/\u003c/span\u003e\u003cspan address=\"https://localizer.csiro.au/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) (Sperschneider et al. \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), and BUSCA (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://busca.biocomp.unibo.it/\u003c/span\u003e\u003cspan address=\"https://busca.biocomp.unibo.it/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) (Savojardo et al. \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e2018\u003c/span\u003e)\u003c/p\u003e\n\u003ch3\u003eAlignment and phylogenetic analysis of LEA proteins\u003c/h3\u003e\n\u003cp\u003eA multiple sequence alignment of all identified LEA protein sequences in \u003cem\u003eT. cacao\u003c/em\u003e was conducted using MAFFT-FFT-NS-i with default parameters (Katoh et al. \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2002\u003c/span\u003e). A maximum likelihood (ML) phylogenetic tree was constructed using the IQ-Tree software (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://iqtree.cibiv.univie.ac.at\u003c/span\u003e\u003cspan address=\"http://iqtree.cibiv.univie.ac.at\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) (Nguyen et al. \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2015\u003c/span\u003e), with the WAG\u0026thinsp;+\u0026thinsp;F+G4 model identified as the best fit according to the Akaike Information Criterion (AIC). Branch support was evaluated using approximate likelihood ratio tests (aLRT) with 1,000 bootstrap replicates. The resulting phylogenetic tree was visualized and annotated using the ITOL web server (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://itol.embl.de\u003c/span\u003e\u003cspan address=\"https://itol.embl.de\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) (Letunic and Bork \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e\n\u003ch3\u003ePromoter cis-acting element analysis of the LEA genes\u003c/h3\u003e\n\u003cp\u003eThe upstream sequences (2000 bp) of each LEA coding sequence were extracted from the whole \u003cem\u003eT. cacao\u003c/em\u003e genome using TBtools software (Chen et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). The extracted files were submitted to the PlantCare website (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://bioinformatics.psb.ugent.be/webtools/plantcare\u003c/span\u003e\u003cspan address=\"http://bioinformatics.psb.ugent.be/webtools/plantcare\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) to predict the cis-acting elements. The results were sorted, enriched through screening, and visualized accordingly.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eChromosomal distribution and gene duplication of the LEA genes\u003c/h2\u003e \u003cp\u003eThe chromosomal positions of the LEA genes were obtained from the genomic annotation of \u003cem\u003eT. cacao\u003c/em\u003e, and their localization was visualized using TBtools (Chen et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). The occurrence and duplication events of the LEA genes were analyzed and visualized with MCScanX (Wang et al. \u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e2012\u003c/span\u003e) via TBtools, which categorizes gene duplications into four types: dispersed, proximal, tandem, and WGD/segmental.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eSynteny analysis and identification of orthologous LEA genes\u003c/h3\u003e\n\u003cp\u003eFor collinearity analysis, the whole genome of \u003cem\u003eT. cacao\u003c/em\u003e (GenBank: GCF_000208745.1) was downloaded, and homologous LEA genes were identified in the genomes of \u003cem\u003eG. hirsutum\u003c/em\u003e (GenBank: GCF_007990345.1), \u003cem\u003eS. lycopersicum\u003c/em\u003e (GenBank: GCF_036512215.1), and \u003cem\u003eA. thaliana\u003c/em\u003e (GenBank: GCF_000001735.4) using BLASTP with an identity threshold\u0026thinsp;\u0026gt;\u0026thinsp;90% and an E-value\u0026thinsp;\u0026lt;\u0026thinsp;1e-15, utilizing MCScanX within TBtools. A Venn diagram was employed to identify orthologous LEA genes in \u003cem\u003eT. cacao\u003c/em\u003e relative to the other plant species.\u003c/p\u003e\n\u003ch3\u003ePlant materials and stress treatment for physiological and gene expression profiling\u003c/h3\u003e\n\u003cp\u003eThe experiment was conducted during 2021\u0026ndash;2022 in the tropical dry forest (bs-T) of northern Huila, Colombia (2\u0026deg;36\u0026prime;55\u0026Prime; N, 75\u0026deg;21\u0026prime;33\u0026Prime; W; 600 m a.s.l.). Three commercial clones of \u003cem\u003eTheobroma cacao\u003c/em\u003e L. were selected based on their contrasting drought responses previously reported under regional agroecological conditions: EET 8 (high drought tolerance), TSH 565 (moderate tolerance), and ICS 60 (high susceptibility) (Osorio et al., 2021).\u003c/p\u003e \u003cp\u003eClonal propagation was performed by grafting onto uniform rootstocks. After two months of post-grafting acclimatization, seedlings were transplanted into 5-kg black polypropylene bags containing silty loam soil (pH 6.0) with drainage holes. Plants underwent a three-month acclimation period under well-watered conditions to ensure homogeneous vegetative development prior to stress imposition. Irrigation was maintained at field capacity during this phase. Fertilization was applied according to soil analysis and crop nutritional requirements. For the experimental phase, plants were transferred to 16-L pots containing a 3:1 (v/v) soil:sand substrate to ensure adequate drainage and homogeneous water distribution.\u003c/p\u003e \u003cp\u003eEnvironmental conditions, including air temperature, relative humidity, and photosynthetically active radiation (PAR), were recorded daily using a \u003cem\u003eHOBO 8\u003c/em\u003e weather station (HOBOware, Onset Computer Corp., USA) positioned 0.5 m above ground level. Vapor pressure deficit (VPD) was calculated following standard psychrometric equations (Online Resource 1).\u003c/p\u003e \u003cp\u003eThe experiment was established under a completely randomized design (CRD) with a two-factor factorial arrangement. The first factor corresponded to water regime, with two levels: well-watered (WW) and drought stress (DS). The second factor included three contrasting \u003cem\u003eTheobroma cacao\u003c/em\u003e clones (EET 8, TSH 565, and ICS 60). Each treatment combination included 20 biological replicates per clone.\u003c/p\u003e \u003cp\u003eSoil volumetric water content (VWC) was monitored daily at 20 cm depth using a \u003cem\u003eFieldScout TDR-300\u003c/em\u003e Moisture Meter (Spectrum Technologies, USA). Under WW conditions, irrigation was adjusted to maintain soil VWC at 60% field capacity, corresponding to a predawn Leaf water potential (\u003cem\u003eΨ\u003c/em\u003e\u003csub\u003e\u003cem\u003eleaf\u003c/em\u003e\u003c/sub\u003e) (MPa) between \u0026minus;\u0026thinsp;0.60 and \u0026minus;\u0026thinsp;0.17 MPa. For the DS treatment, irrigation was withheld until \u003cem\u003eΨ\u003c/em\u003e\u003csub\u003e\u003cem\u003eleaf\u003c/em\u003e\u003c/sub\u003e reached\u0026thinsp;\u0026minus;\u0026thinsp;1.5 MPa, which occurred after 19 days of water deprivation (DAT19). At this point, plants exhibited visible drought symptoms including leaf senescence. Subsequently, plants were rehydrated to field capacity (60% VWC) within 24 hours, followed by an 11-day recovery period to assess plant resilience (DAT30).\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eRelative Leaf Water Content (RWC)\u003c/h2\u003e \u003cp\u003eRWC was determined following the protocol described by De Almeida et al. (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) and based on the method proposed by Slatyer and Shmueli (1967). Briefly, RWC was calculated as the percentage of water content in leaf tissue relative to its fully turgid state, using fresh, turgid, and dry weights. Leaf samples (25 cm\u0026sup2; segments) were collected from 20 plants per treatment. Fresh weight was recorded immediately after sampling. Samples were then hydrated in distilled water for 24 h at room temperature to obtain turgid weight. Subsequently, tissues were oven-dried at 70\u0026deg;C until constant weight to determine dry weight. RWC was expressed as a percentage of the maximum water-holding capacity of the tissue.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003ePhysiological measurements\u003c/h2\u003e \u003cp\u003e \u003cem\u003eΨ\u003c/em\u003e \u003csub\u003e \u003cem\u003eleaf\u003c/em\u003e \u003c/sub\u003e was measured predawn (5:00 am\u0026thinsp;\u0026minus;\u0026thinsp;6:30 am) using a \u003cem\u003eSch\u0026ouml;lander\u003c/em\u003e pressure chamber (PWSC Model F01, EVNCO, Auckland, New Zealand) on the fifth fully expanded leaf from the apex of four plants per treatment (n\u0026thinsp;=\u0026thinsp;4) for each clone. Gas exchange parameters, including net photosynthetic rate (\u003cem\u003eA\u003c/em\u003e) (\u0026micro;mol CO₂ m⁻\u0026sup2; s⁻\u0026sup1;), transpiration rate (\u003cem\u003eE\u003c/em\u003e) (mmol H₂O m⁻\u0026sup2; s⁻\u0026sup1;), stomatal conductance (\u003cem\u003egs\u003c/em\u003e) (mmol H₂O m⁻\u0026sup2; s⁻\u0026sup1;), and intercellular CO\u003csub\u003e2\u003c/sub\u003e (\u003cem\u003eCi\u003c/em\u003e) (\u0026micro;mol CO\u003csub\u003e2\u003c/sub\u003e mol air⁻\u0026sup1;), were measured between 9:00 am and 11:00 am. These measurements were taken from the third or fourth fully expanded leaf from the apex downward on 12 plants per treatment using a \u003cem\u003eCI-340\u003c/em\u003e Handheld Photosynthesis System measurement system (CID Bio-Science Inc. WA, United States) (Liu, 2020). Based on these parameters, the intrinsic water-use efficiency (\u003cem\u003eWUEi\u003c/em\u003e) (\u0026micro;mol CO\u003csub\u003e2\u003c/sub\u003e mmol⁻\u0026sup1;\u003cb\u003e)\u003c/b\u003e was calculated (Zhang et al. \u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e2001\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eRNA extraction and quantitative Real-Time PCR analysis\u003c/h2\u003e \u003cp\u003eFor gene expression, mature leaves were collected from four plants per clone at two time points: day 19 (DAT19, peak drought stress), and day 30 (DAT30, recovery phase) once physiological measurements completed (noon). At each time point, leaves were also collected from the corresponding WW control plants. Samples were immediately preserved in RNAlater\u0026reg; and stored at -80\u0026deg;C until processing. Total RNA was extracted from liquid nitrogen-ground tissue using the GeneJET\u0026trade; Plant RNA Purification Mini Kit (Thermo Fisher Scientific, USA), with RNA quality verified through concentration measurement using a \u003cem\u003eNP80\u003c/em\u003e NanoPhotometer (Implen GmbH, Germany), integrity assessment by 1% agarose gel electrophoresis and A260/A280 and A260/A230 ratio analysis. cDNA synthesis was performed with 100 ng of total RNA using \u003cem\u003eM-MuLV\u003c/em\u003e Reverse Transcriptase (Thermo Fisher Scientific, USA) and \u003cem\u003eoligo(dT)18\u003c/em\u003e primers. We designed sixteen specific primer pairs targeting LEA genes using Primer3Plus Software (Untergasser et al. \u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e2007\u003c/span\u003e) (Online Resource 2). The reference gene ACPB (acyl carrier protein B), previously validated for cacao gene expression studies (Osorio et al. 2021), was used for normalization. Detailed protocol can be consulted in Online Resource (3).\u003c/p\u003e \u003cp\u003eQuantitative PCR was performed in triplicate with four biological replicates per condition, using the \u003cem\u003eDyNAmo Flash\u003c/em\u003e SYBR Green qPCR Kit (Thermo Fisher Scientific, CA, USA) on a \u003cem\u003eQuantStudio 1\u003c/em\u003e Real-Time PCR System (Applied Biosystems, CA, USA). The thermal cycling protocol consisted of initial denaturation at 95\u0026deg;C for 7 min, followed by 40 cycles of 95\u0026deg;C for 10 s and 60\u0026deg;C for 30 s. Reaction specificity was confirmed by melting curve analysis (60\u0026ndash;95\u0026deg;C). Standard curves were generated for each primer pair to determine amplification efficiencies (Online Resource 4), and relative gene expression was calculated using the 2\u0026thinsp;\u0026minus;\u0026thinsp;ΔΔCt method (Pfaffl, \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2001\u003c/span\u003e) with efficiency correction (Pfaffl, \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2004\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eWe employed multiple statistical approaches to analyze treatment and clonal effects. Generalized linear mixed models (GLMMs) handled fixed and random effects while accommodating non-normal data distributions (Pinheiro \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2000\u003c/span\u003e). Multivariate ANOVA (MANOVA) assessed treatment impacts across correlated physiological variables (Tabachnick \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). The Bonferroni correction-controlled Type I errors in multiple comparisons (Abdi \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). For gene expression data, we used aligned rank transform (ART) ANOVA to address non-normality (Kay \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), followed by ART-contrasts for post-hoc analysis (Elkin \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). All statistical analyses were conducted using R statistical software version 4.4.2.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003e \u003cb\u003eIdentification of the LEA genes in\u003c/b\u003e \u003cb\u003eT. cacao\u003c/b\u003e\u003c/p\u003e \u003cp\u003eThe integration of LEA genes identified by Hundertmark and Hincha (Hundertmark and Hincha \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2008\u003c/span\u003e) with data from The Arabidopsis Information Resource (TAIR) resulted in 106 accession numbers, which were subsequently blasted against the whole \u003cem\u003eT. cacao\u003c/em\u003e genome. Following this approach, 30 LEA genes were identified in \u003cem\u003eT. cacao\u003c/em\u003e (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). All metadata related to these LEA genes is available in Online Resource (5).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eLEA genes identified in the \u003cem\u003eT. cacao\u003c/em\u003e genome\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGroup\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSubfamily\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNumber of genes\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNumber of proteins\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBLASTP E-value (Range)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLEA*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5e\u003csup\u003e\u0026minus;\u0026thinsp;17\u003c/sup\u003e \u0026ndash; 7e\u003csup\u003e\u0026minus;\u0026thinsp;34\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLEA*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1e\u003csup\u003e\u0026minus;\u0026thinsp;54\u003c/sup\u003e \u0026ndash; 3e\u003csup\u003e\u0026minus;\u0026thinsp;164\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLEA*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1e\u003csup\u003e\u0026minus;\u0026thinsp;27\u003c/sup\u003e \u0026ndash; 3e\u003csup\u003e\u0026minus;\u0026thinsp;58\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLEA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4e\u003csup\u003e\u0026minus;\u0026thinsp;115\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLEA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1e\u003csup\u003e\u0026minus;\u0026thinsp;21\u003c/sup\u003e \u0026ndash; 5e\u003csup\u003e\u0026minus;\u0026thinsp;46\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLEA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3e\u003csup\u003e\u0026minus;\u0026thinsp;15\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSMP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2e\u003csup\u003e\u0026minus;\u0026thinsp;36\u003c/sup\u003e \u0026ndash; 2e\u003csup\u003e\u0026minus;\u0026thinsp;65\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDHN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1e\u003csup\u003e\u0026minus;\u0026thinsp;15\u003c/sup\u003e \u0026ndash; 1e\u003csup\u003e\u0026minus;\u0026thinsp;57\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e*LEA groups showing isoforms\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eMolecular characterization of LEA proteins\u003c/h2\u003e \u003cp\u003eTo verify that these genes encode LEA-related proteins, PANTHER and InterPro were employed to detect conserved domains, while MEME was used to analyze conserved motifs. The domains and motifs of the 30 LEA proteins were found to match the eight typical Pfam-based conserved domains, classifying them into the LEA-1, LEA-2, LEA-3, LEA-4, LEA-5, LEA-6, SMP, and DHN groups, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The largest subfamily was LEA-2 with 12 members, followed by the DHN, which contained five members. Notably, some members of the LEA-1, LEA-2, and LEA-3 subfamilies possess isoforms (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe analysis of physicochemical properties revealed that among all LEA proteins, LEA-6 (89 aa) was the shortest, while LEA-4 (438 aa) was the longest, with molecular weights of 9505.37 kDa and 47842.57 kDa, respectively. Isoelectric point analysis indicated that SMP (4.68\u0026ndash;5.32), and LEA-3 (9.45\u0026ndash;9.82) were the most acidic and basic subfamilies, respectively. Among the 39 LEA proteins analyzed (including isoforms), 19 (49%) exhibited a pI\u0026thinsp;\u0026lt;\u0026thinsp;7, and 20 (51%) a pI\u0026thinsp;\u0026gt;\u0026thinsp;7. Additionally, the GRAVY values showed that only eight members of LEA-2 (GRAVY\u0026thinsp;\u0026gt;\u0026thinsp;0) were considered hydrophobic proteins, while all the LEA proteins in the remaining groups (GRAVY\u0026thinsp;\u0026lt;\u0026thinsp;0) were found to be highly hydrophilic (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The predicted subcellular localization revealed that the eight hydrophobic proteins in the LEA-2 group were primarily localized to the chloroplast. In contrast, all proteins from the other subfamilies were exclusively located in the nucleus, except for the LEA-3 group, which was localized to the mitochondria (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Additional physicochemical properties and detailed information for all LEA proteins are provided in Online Resource (6).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eConserved domains and physicochemical characteristics of LEA proteins in \u003cem\u003eT. cacao\u003c/em\u003e\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026minus;\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGroup\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSubfamily\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLenght (aa)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMolecular weight (Mw)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eIsoelectric point (pI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eGrand average of hydropathy (GRAVY)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eDomain\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eInterPro ID\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLEA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e127\u0026ndash;166\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13876.73 \u0026minus;\u0026thinsp;17698.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e5.08\u0026ndash;9.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c6\"\u003e \u003cp\u003e-0.923 \u0026ndash; -1.302\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eLEA-1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003ePF03760\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLEA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e151\u0026ndash;311\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16437.95\u0026ndash;35785.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4.67\u0026ndash;10.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.357\u0026ndash;0.290\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eLEA-2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003ePF03168\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLEA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e84\u0026ndash;94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9698.18\u0026ndash;9960.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e9.45\u0026ndash;9.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c6\"\u003e \u003cp\u003e-0.513 \u0026ndash; -0.213\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eLEA-3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003ePF03242\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLEA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e438\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e47842.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e6.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-1.326\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eLEA-4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003ePF02987\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLEA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e156\u0026ndash;174\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10843.83\u0026ndash;18997.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e5.97\u0026ndash;9.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c6\"\u003e \u003cp\u003e-0.857 \u0026ndash; -1.391\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eLEA-5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003ePF00477\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLEA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9505.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e5.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.939\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eLEA-6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003ePF10714\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSMP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e237\u0026ndash;284\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24609.25\u0026ndash;29255.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4.68\u0026ndash;5.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c6\"\u003e \u003cp\u003e-0.296 \u0026ndash; -0.368\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eSMP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003ePF04927\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDHN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e114\u0026ndash;234\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10809.82\u0026ndash;26410.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e5.41\u0026ndash;9.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c6\"\u003e \u003cp\u003e-1.220 \u0026ndash; -1.905\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eDHN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003ePF00257\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003ePhylogenetic analysis of LEA proteins\u003c/h2\u003e \u003cp\u003eA maximum likelihood (ML) tree was constructed using the full-length LEA protein sequences from \u003cem\u003eT. cacao\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Interestingly, the topology revealed that the 39 LEA proteins were clustered into eight distinct groups (LEA-1, LEA-2, LEA-3, LEA-4, LEA-5, LEA-6, SMP, and DHN) with relatively high bootstrap support (\u0026gt;\u0026thinsp;70%), which further confirmed that they belong to the LEA family. The LEA-2 had the highest representation in the phylogeny, accounting for 49% of all LEA.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003e\u003cb\u003eIdentification of cis-acting element in LEA gene promoters\u003c/b\u003e\u003c/h2\u003e \u003cp\u003eTo explore the regulatory mechanisms of the LEA gene, a cis-acting element analysis was performed on a 2000 bp sequence of its region promoter, and the identified elements were classified into three categories: environment or stress-responsive, phytohormone or hormone-responsive, and growth or development-related elements (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). The most abundant category was the environment element 669 (72%), followed by phytohormone 228 (25%), and growth 26 (3%) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ea). Within the environment element category, two prevalent regulatory elements responsible for stress-induced pathways were identified: G-box 148 (22%), and Box 4 with 104 (16%). Among hormone response cis elements, including ABRE 132 (58%), and TCA motifs 25 (11%), which are involved in abscisic acid (ABA), and methyl jasmonate (MeJA) responses, respectively. As for the growth specificity elements, CAT-box was the most abundant 20 (77%) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eb). At the LEA group level, the three categories were predominantly dominated by LEA-2, followed by DHN (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ec).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eChromosomal localization and gene duplication of LEA genes\u003c/h2\u003e \u003cp\u003eIn the \u003cem\u003eT. cacao\u003c/em\u003e LEA gene family, 30 genes were unevenly distributed across the nine chromosomes, except for chromosome seven, which lacked LEA genes, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e. High and low LEA gene densities were detected on chromosomes 5 and 8, which contained 9 and 1 genes, respectively. In terms of LEA distribution, each group was as follows: LEA-1 (Chr5: 2; 22%), LEA-2 (Chr5: 3; 33%, Chr9: 3; 100%), LEA-3 (Chr1: 1; 25%, Chr6: 1; 33%), LEA-4 (Chr5: 1; 11%), LEA-5 (Chr10: 2; 100%), LEA-6 (Chr2: 1; 25%), SMP (Chr5: 1; 11%), and DHN (Chr2: 2; 50%).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eTandem duplication and segmental duplication are essential for the evolution of gene families, driving adaptation to varying environmental conditions. Gene duplication events were analyzed with MCScanX, which identified 2 pairs of tandem duplication genes (LEA-1_chr5-1/ LEA-1_chr5-2), and (LEA-5_chr10-1/LEA-5_chr10-2) among the 30 \u003cem\u003eT. cacao\u003c/em\u003e LEA genes (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e)\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003eSynteny analysis of LEA genes\u003c/h2\u003e \u003cp\u003eTo further deduce the evolutionary origin and orthologous relationship of \u003cem\u003eT. cacao\u003c/em\u003e LEA family, comparative syntenic maps with the genomes of \u003cem\u003eG. hirsutum\u003c/em\u003e, \u003cem\u003eS. lycopersicum\u003c/em\u003e, and \u003cem\u003eA. thaliana\u003c/em\u003e were constructed (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ea). Analysis of \u003cem\u003eT. cacao\u003c/em\u003e and three graminaceous model plants identified 80, 26, and 34 LEA genes homologous to \u003cem\u003eG. hirsutum\u003c/em\u003e, \u003cem\u003eS. lycopersicum\u003c/em\u003e, and \u003cem\u003eA. thaliana\u003c/em\u003e, respectively (Online Resource 7). Notably, among the three graminaceous species, 14 homologs of LEA genes were detected (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eb).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAmong the 14 LEA orthologous genes in \u003cem\u003eT. cacao\u003c/em\u003e, the LEA-2 subfamily comprised 6 genes, representing the largest proportion among all subfamilies. This suggests that LEA-2 subfamily genes may play an important role in the expansion of LEA gene family during evolution.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eLEA orthologous genes of \u003cem\u003eT. cacao\u003c/em\u003e and \u003cem\u003eG. hirsutum\u003c/em\u003e, \u003cem\u003eS. lycopersicum\u003c/em\u003e, and \u003cem\u003eA. thaliana\u003c/em\u003e\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGroup\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSubfamily\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOrthologous gene\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSymbol gene\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eInitial genomic position\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eFinal genomic position\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"8\" rowspan=\"9\"\u003e \u003cp\u003eLEA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLEA-1_chr3-1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLOC18606060\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e31483181\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e31483953\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLEA-1_chr5-1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLOC18599099\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e28544724\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e28545989\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLEA-2_chr1-1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLOC18614030\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e33969340\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e33971585\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLEA-2_chr1-2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLOC18614068\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e34161976\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e34163125\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLEA-2_chr3-1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLOC18606720\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e35117281\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e35118884\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLEA-2_chr5-1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLOC18597391\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e10447\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e13604\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLEA-2_chr5-2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLOC18598383\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e8532798\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e8533973\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLEA-2_chr9-2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLOC18590297\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e33961964\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e33962725\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLEA-3_chr1-1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLOC18613581\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e31337158\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e31338048\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eSMP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSMP_chr1-1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLOC18613320\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e29482148\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e29483586\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSMP_chr4-1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLOC18602997\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e27963963\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e27966158\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSMP_chr5-1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLOC18600259\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e37203759\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e37205712\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eDHN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDHD_chr2-2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLOC18607734\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3961359\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3962803\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDHD_chr8-1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLOC18591660\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2487207\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2488654\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003eLeaf water potential and relative water content determination\u003c/h2\u003e \u003cp\u003eStatistically significant differences (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) in \u003cem\u003eΨ\u003c/em\u003e\u003csub\u003e\u003cem\u003eleaf\u003c/em\u003e\u003c/sub\u003e were observed between water statuses on DAT19. In WW conditions, \u003cem\u003eΨ\u003c/em\u003e\u003csub\u003e\u003cem\u003eleaf\u003c/em\u003e\u003c/sub\u003e ranged from \u0026minus;\u0026thinsp;0.60 to \u0026minus;\u0026thinsp;0.17 MPa, while those DS experienced a significant reduction to approximately \u0026minus;\u0026thinsp;1.5 MPa on DAT19. Not all clones exhibited similar effects on \u003cem\u003eΨ\u003c/em\u003e\u003csub\u003e\u003cem\u003eleaf\u003c/em\u003e\u003c/sub\u003e on DAT19. The clone with the highest \u003cem\u003eΨ\u003c/em\u003e\u003csub\u003e\u003cem\u003eleaf\u003c/em\u003e\u003c/sub\u003e was TSH 565 (\u0026ndash;1.27 MPa), whereas the clone with the lowest \u003cem\u003eΨ\u003c/em\u003e\u003csub\u003e\u003cem\u003eleaf\u003c/em\u003e\u003c/sub\u003e was ICS 60 (\u0026ndash;1.47 MPa). Despite facing nearly three weeks of water deficit stress without irrigation, the three cocoa clones recovered after rewatering, demonstrating tolerance to this level of stress. RWC maintained high values in all WW clones (46.1\u0026ndash;60.5%). On DAT19, clones EET 8 and TSH 565 experienced a reduction in RWC, with TSH 565 showing the highest water loss (23%). Clone ICS 60 maintained RWC values similar to its control plants, showing the highest value (68%) compared to the other clones under DS conditions (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eChanges in Leaf water potential and gas exchange parameters of the three cacao clones under different water states\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"10\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eClone\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eWater states\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eΨ\u003c/em\u003e\u003csub\u003e\u003cem\u003eleaf\u003c/em\u003e\u003c/sub\u003e \u003csup\u003ea\u003c/sup\u003e(MPa)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eA\u003c/em\u003e\u003csup\u003eb\u003c/sup\u003e \u0026micro;mol CO₂ m⁻\u0026sup2; s⁻\u0026sup1;),\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003egs\u003c/em\u003e\u003csup\u003ec\u003c/sup\u003e (mmol H\u003csub\u003e2\u003c/sub\u003eO m⁻\u0026sup2; s⁻\u0026sup1;)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003eCi\u003c/em\u003e\u003csup\u003ed\u003c/sup\u003e (\u0026micro;mol CO\u003csub\u003e2\u003c/sub\u003e mol air⁻\u0026sup1;)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cem\u003eE\u003c/em\u003e\u003csup\u003ee\u003c/sup\u003e (mmol H\u003csub\u003e2\u003c/sub\u003eO m⁻\u0026sup2; s⁻\u0026sup1;)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eRWC\u003csup\u003ef\u003c/sup\u003e (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eWUEi\u003csup\u003eg\u003c/sup\u003e (\u0026micro;mol CO\u003csub\u003e2\u003c/sub\u003e mmol⁻\u0026sup1;)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eEET 8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eDAT19\u003csup\u003eh\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDS\u003csup\u003ej\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-1.375\u0026thinsp;\u0026plusmn;\u0026thinsp;0.103 B\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.448\u0026thinsp;\u0026plusmn;\u0026thinsp;0.431 B\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.438\u0026thinsp;\u0026plusmn;\u0026thinsp;0.871 B\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1397.603\u0026thinsp;\u0026plusmn;\u0026thinsp;246.035 AC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.175\u0026thinsp;\u0026plusmn;\u0026thinsp;0.045 B\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e41.433\u0026thinsp;\u0026plusmn;\u0026thinsp;18.530 A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-0.105\u0026thinsp;\u0026plusmn;\u0026thinsp;0.162 BC\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWW\u003csup\u003ek\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.170\u0026thinsp;\u0026plusmn;\u0026thinsp;0.009 A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.865\u0026thinsp;\u0026plusmn;\u0026thinsp;0.287 A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e29.765\u0026thinsp;\u0026plusmn;\u0026thinsp;3.535 A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e912.783\u0026thinsp;\u0026plusmn;\u0026thinsp;38.910 B\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.615\u0026thinsp;\u0026plusmn;\u0026thinsp;0.164 A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e60.570\u0026thinsp;\u0026plusmn;\u0026thinsp;26.877 A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.210\u0026thinsp;\u0026plusmn;\u0026thinsp;0.032 A\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eDAT30\u003csup\u003ei\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.475\u0026thinsp;\u0026plusmn;\u0026thinsp;0.042 A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.320\u0026thinsp;\u0026plusmn;\u0026thinsp;0.090 B\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e32.293\u0026thinsp;\u0026plusmn;\u0026thinsp;5.095 AC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1317.245\u0026thinsp;\u0026plusmn;\u0026thinsp;20.361 A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.333\u0026thinsp;\u0026plusmn;\u0026thinsp;0.081 A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e83.505\u0026thinsp;\u0026plusmn;\u0026thinsp;3.344 B\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-0.035\u0026thinsp;\u0026plusmn;\u0026thinsp;0.010 A\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWW\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.515\u0026thinsp;\u0026plusmn;\u0026thinsp;0.129 A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.210\u0026thinsp;\u0026plusmn;\u0026thinsp;1.917 AB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10.913\u0026thinsp;\u0026plusmn;\u0026thinsp;2.246 B\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1086.378\u0026thinsp;\u0026plusmn;\u0026thinsp;102.724 B\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.780\u0026thinsp;\u0026plusmn;\u0026thinsp;0.196 A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e65.803\u0026thinsp;\u0026plusmn;\u0026thinsp;2.581 A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.080\u0026thinsp;\u0026plusmn;\u0026thinsp;0.063 AB\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eTHS 565\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eDAT19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-1.275\u0026thinsp;\u0026plusmn;\u0026thinsp;0.125 B\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.208\u0026thinsp;\u0026plusmn;\u0026thinsp;0.565 B\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.435\u0026thinsp;\u0026plusmn;\u0026thinsp;1.147 B\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1427.450\u0026thinsp;\u0026plusmn;\u0026thinsp;163.849 C\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.175\u0026thinsp;\u0026plusmn;\u0026thinsp;0.036 B\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e23.505\u0026thinsp;\u0026plusmn;\u0026thinsp;9.651 A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-0.110\u0026thinsp;\u0026plusmn;\u0026thinsp;0.107 BC\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWW\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.185\u0026thinsp;\u0026plusmn;\u0026thinsp;0.009 A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.050\u0026thinsp;\u0026plusmn;\u0026thinsp;0.599 A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e36.963\u0026thinsp;\u0026plusmn;\u0026thinsp;7.927 A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1001.760\u0026thinsp;\u0026plusmn;\u0026thinsp;19.469 AB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.938\u0026thinsp;\u0026plusmn;\u0026thinsp;0.351 A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e46.198\u0026thinsp;\u0026plusmn;\u0026thinsp;5.250 A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.143\u0026thinsp;\u0026plusmn;\u0026thinsp;0.015 AB\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eDAT30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.495\u0026thinsp;\u0026plusmn;\u0026thinsp;0.070 A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.318\u0026thinsp;\u0026plusmn;\u0026thinsp;0.921 B\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e27.108\u0026thinsp;\u0026plusmn;\u0026thinsp;6.344 BC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1210.045\u0026thinsp;\u0026plusmn;\u0026thinsp;56.841 AB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.908\u0026thinsp;\u0026plusmn;\u0026thinsp;0.216 A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e82.200\u0026thinsp;\u0026plusmn;\u0026thinsp;3.033 B\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.025\u0026thinsp;\u0026plusmn;\u0026thinsp;0.036 AB\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWW\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.498\u0026thinsp;\u0026plusmn;\u0026thinsp;0.078 A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.578\u0026thinsp;\u0026plusmn;\u0026thinsp;1.525 B\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e33.138\u0026thinsp;\u0026plusmn;\u0026thinsp;9.647 AC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1087.488\u0026thinsp;\u0026plusmn;\u0026thinsp;75.857 B\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.745\u0026thinsp;\u0026plusmn;\u0026thinsp;0.153 A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e78.643\u0026thinsp;\u0026plusmn;\u0026thinsp;8.340 B\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.088\u0026thinsp;\u0026plusmn;\u0026thinsp;0.048 AB\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eICS 60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eDAT19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-1.475\u0026thinsp;\u0026plusmn;\u0026thinsp;0.232 B\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.970\u0026thinsp;\u0026plusmn;\u0026thinsp;0.326 B\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.298\u0026thinsp;\u0026plusmn;\u0026thinsp;0.278 B\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1675.645\u0026thinsp;\u0026plusmn;\u0026thinsp;124.570 C\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.165\u0026thinsp;\u0026plusmn;\u0026thinsp;0.017 B\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e68.015\u0026thinsp;\u0026plusmn;\u0026thinsp;29.342 A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-0.288\u0026thinsp;\u0026plusmn;\u0026thinsp;0.083 C\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWW\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.185\u0026thinsp;\u0026plusmn;\u0026thinsp;0.010 A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7.250\u0026thinsp;\u0026plusmn;\u0026thinsp;2.319 A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e27.200\u0026thinsp;\u0026plusmn;\u0026thinsp;5.864 A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e814.953\u0026thinsp;\u0026plusmn;\u0026thinsp;128.488 B\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.450\u0026thinsp;\u0026plusmn;\u0026thinsp;0.258 A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e51.358\u0026thinsp;\u0026plusmn;\u0026thinsp;3.333 A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.270\u0026thinsp;\u0026plusmn;\u0026thinsp;0.088 A\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eDAT30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.515\u0026thinsp;\u0026plusmn;\u0026thinsp;0.095 A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.095\u0026thinsp;\u0026plusmn;\u0026thinsp;1.465 AB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e23.090\u0026thinsp;\u0026plusmn;\u0026thinsp;3.835 BC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1057.645\u0026thinsp;\u0026plusmn;\u0026thinsp;101.378 B\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.710\u0026thinsp;\u0026plusmn;\u0026thinsp;0.146 A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e84.018\u0026thinsp;\u0026plusmn;\u0026thinsp;0.428 B\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.123\u0026thinsp;\u0026plusmn;\u0026thinsp;0.066 B\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWW\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.600\u0026thinsp;\u0026plusmn;\u0026thinsp;0.046 A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.358\u0026thinsp;\u0026plusmn;\u0026thinsp;0.272 A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e44.588\u0026thinsp;\u0026plusmn;\u0026thinsp;3.362 A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1014.058\u0026thinsp;\u0026plusmn;\u0026thinsp;19.694 B\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2.568\u0026thinsp;\u0026plusmn;\u0026thinsp;0.184 A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e69.138\u0026thinsp;\u0026plusmn;\u0026thinsp;2.820 A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.123\u0026thinsp;\u0026plusmn;\u0026thinsp;0.013 B\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003csup\u003ea\u003c/sup\u003e \u003cem\u003eψleaf\u003c/em\u003e, Leaf water potential; \u003csup\u003eb\u003c/sup\u003e\u003cem\u003eA\u003c/em\u003e, net photosynthetic rate; \u003csup\u003ec\u003c/sup\u003e\u003cem\u003egs\u003c/em\u003e, stomatal conductance; \u003csup\u003ed\u003c/sup\u003e\u003cem\u003eCi\u003c/em\u003e, intercellular CO2; \u003csup\u003ee\u003c/sup\u003e\u003cem\u003eE\u003c/em\u003e, Transpiration rate; \u003csup\u003ef\u003c/sup\u003e\u003cem\u003eRWC\u003c/em\u003e, Relative leaf water content; \u003csup\u003eg\u003c/sup\u003e\u003cem\u003eWUEi\u003c/em\u003e, intrinsic water-use efficiency; \u003csup\u003eh\u003c/sup\u003eDAT19, maximum water deficit stress of 19 days; \u003csup\u003ei\u003c/sup\u003eDAT30, recovery after 11 days of rehydration after DS; \u003csup\u003ej\u003c/sup\u003eDS, water deficit stress; \u003csup\u003ek\u003c/sup\u003eWW, well-watered; *The values are mean (n\u0026thinsp;=\u0026thinsp;4) \u0026plusmn; standard error with different letters indicating significant differences by Tukey test (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003eLeaf gas exchange\u003c/h2\u003e \u003cp\u003eAs expected, DS significantly affected leaf gas exchange (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), reducing \u003cem\u003eA\u003c/em\u003e, \u003cem\u003eE\u003c/em\u003e, and \u003cem\u003egs\u003c/em\u003e, while increasing \u003cem\u003eCi\u003c/em\u003e in the evaluated clones. Under WW treatment, \u003cem\u003eA\u003c/em\u003e values ranged from 5.0 to 7.2 \u0026micro;mol CO₂ m⁻\u0026sup2; s⁻\u0026sup1;, whereas under DS, \u003cem\u003eA\u003c/em\u003e was completely inhibited on DAT19, showing negative values between \u0026minus;\u0026thinsp;0.97 and \u0026minus;\u0026thinsp;0.20 \u0026micro;mol CO₂ m⁻\u0026sup2; s⁻\u0026sup1;, with no significant differences among clones (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Negative \u003cem\u003eA\u003c/em\u003e values under light conditions, combined with the higher \u003cem\u003eCi\u003c/em\u003e concentrations observed under DS, indicate photorespiration (Niu et al. 2025). As previously noted, \u003cem\u003eCi\u003c/em\u003e increased significantly in DS plants compared to WW plants. On DAT19, \u003cem\u003eCi\u003c/em\u003e values increased from 814\u0026ndash;1001 \u0026micro;mol CO₂ mol⁻\u0026sup1; to 1397\u0026ndash;1675 \u0026micro;mol CO₂ mol⁻\u0026sup1;, representing an average increase of 69% due to DS. The highest \u003cem\u003eCi\u003c/em\u003e values were observed in ICS 60 and TSH 565, while the lowest value was found in clone EET 8, representing a 53% increase. Significant differences (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) were found between clones with the highest and lowest \u003cem\u003eCi\u003c/em\u003e values.\u003c/p\u003e \u003cp\u003eA significant reduction in \u003cem\u003egs\u003c/em\u003e (85% on average) was observed after DS treatment in clones compared to their control plants. Under WW, \u003cem\u003egs\u003c/em\u003e values ranged from 27.2 to 36.9 mmol H₂O m⁻\u0026sup2; s⁻\u0026sup1;, while under DS, they ranged from 3.2 to 4.4 mmol H₂O m⁻\u0026sup2; s⁻\u0026sup1;. \u003cem\u003eWUEi\u003c/em\u003e also decreased significantly under DS across all three clones, reaching negative values, as observed for \u003cem\u003eA\u003c/em\u003e. Under WW conditions, \u003cem\u003eWUEi\u003c/em\u003e ranged from 0.14 to 0.27 \u0026micro;mol CO₂ mmol H₂O⁻\u0026sup1;, while under DS, it ranged from \u0026minus;\u0026thinsp;0.10 to \u0026minus;\u0026thinsp;0.28 \u0026micro;mol CO₂ mmol H₂O⁻\u0026sup1;. Notably, under DS, \u003cem\u003eWUEi\u003c/em\u003e was significantly lower in clone ICS 60 compared to the other clones, all of which showed negative \u003cem\u003eWUEi\u003c/em\u003e values. \u003cem\u003eE\u003c/em\u003e followed a similar pattern to \u003cem\u003egs\u003c/em\u003e, \u003cem\u003eA\u003c/em\u003e, and \u003cem\u003eWUEi\u003c/em\u003e.\u003c/p\u003e \u003cp\u003eFinally, \u003cem\u003eA\u003c/em\u003e, \u003cem\u003eE\u003c/em\u003e, and \u003cem\u003egs\u003c/em\u003e values of DS plants in clones ICS 60 and TSH 565 gradually recovered at DAT30, reaching values similar to WW plants. However, the clone EET 8 did not recover. Interestingly, \u003cem\u003eWUEi\u003c/em\u003e reached WW levels at DAT30 in clone ICS 60 and 71% of WW levels at DAT30 in clone TSH 565, with no significant differences between treatments.\u003c/p\u003e \u003cdiv id=\"Sec23\" class=\"Section3\"\u003e \u003ch2\u003eGene expression profiling\u003c/h2\u003e \u003cp\u003eFor gene expression, we evaluated the LEA orthologous genes of \u003cem\u003eT. cacao\u003c/em\u003e shown in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e and Online Resource (5). Quantitative PCR analysis revealed distinct expression patterns of LEA genes across the three cacao clones in response to water deficit (Online Resource 8). All LEA gene families exhibited significant transcriptional regulation during drought stress (DAT19) and subsequent recovery (DAT30), with marked clonal variations in expression dynamics (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e and Online Resource 9).\u003c/p\u003e \u003cp\u003eICS 60 exhibited the highest induction of LEA-1 under DAT19 conditions (18.14), with a sharp decrease during DAT30 (\u0026ndash;14.47). TSH 565 showed moderate upregulation in DAT19 (7.17) and a substantial reduction in DAT30 (\u0026ndash;33.08), whereas EET 8 maintained a relatively stable and mild expression response (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003ea).\u003c/p\u003e \u003cp\u003eFor LEA-2, ICS 60 showed consistent moderate expression in both DAT19 (3.33) and DAT30 (2.58). EET 8 displayed minor variation between DAT19 (1.32) and DAT30 (\u0026ndash;1.27), while TSH 565 was downregulated in both phases (\u0026ndash;0.70 in DAT19 and \u0026minus;\u0026thinsp;12.62 in DAT30) (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eb). LEA-3 and LEA-5 were upregulated under all conditions, with ICS 60 showing the highest expression levels (Figs.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003ec and \u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003ee). LEA-4 and LEA-6 exhibited contrasting expression patterns: TSH 565 maintained elevated levels in both DAT19 and DAT30, whereas ICS 60 remained consistently downregulated (Figs.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003ed and \u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003ef).\u003c/p\u003e \u003cp\u003eDHN expression varied by genotype and treatment. ICS 60 and TSH 565 were upregulated during DAT19 but downregulated during DAT30, while EET 8 remained repressed throughout both conditions (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eg). For SMP, TSH 565 showed strong induction in DAT19 followed by sharp downregulation during DAT30, whereas ICS 60 exhibited moderate upregulation during recovery (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eh).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe present study represents the first comprehensive genome-wide identification and characterization of the LEA protein-encoding gene family in \u003cem\u003eT. cacao\u003c/em\u003e, a crop of significant economic importance, particularly in tropical regions. While LEA proteins have been extensively investigated in model organisms and agronomic crops such as \u003cem\u003eA. thaliana\u003c/em\u003e (Hundertmark and Hincha \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2008\u003c/span\u003e), \u003cem\u003eO. sativa\u003c/em\u003e (Wang et al. \u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e2007\u003c/span\u003e), \u003cem\u003eZea mays\u003c/em\u003e (Li and Cao \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), \u003cem\u003eS. lycopersicum\u003c/em\u003e (Cao and Li \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2015\u003c/span\u003e), and \u003cem\u003eG. hirsutum\u003c/em\u003e (Magwanga et al. \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), their presence, structural diversity, and functional roles in \u003cem\u003eT. cacao\u003c/em\u003e remained unexplored until now. Given the increasing vulnerability of cacao to climate change-induced water deficit stress, elucidating the molecular mechanisms underlying its adaptive responses is imperative for developing genetically resilient cultivars. This study, therefore, provides a foundational genomic framework for understanding the role of LEA proteins in cacao and their contribution to drought tolerance.\u003c/p\u003e \u003cp\u003eWe identified 30 LEA genes in the cacao genome, classified into eight groups (LEA-1 to LEA-6, SMP, and DHN), which underscores the functional diversification of this gene family. The largest subfamily, LEA-2, with 12 members, aligns with findings in other crops such as \u003cem\u003eA. thaliana\u003c/em\u003e (Hundertmark and Hincha \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2008\u003c/span\u003e), \u003cem\u003eS. lycopersicum\u003c/em\u003e (Cao and Li \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2015\u003c/span\u003e), and \u003cem\u003eG. hirsutum\u003c/em\u003e (Magwanga et al. \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), where LEA-2 proteins are often the most abundant. This suggests a conserved role for LEA-2 proteins in stress responses across plant species. The presence of isoforms within the LEA-1, LEA-2, and LEA-3 subfamilies further highlights the evolutionary plasticity of the LEA gene family, likely driven by gene duplication and alternative splicing events (Hong et al. 2005; Abdul et al. 2021). These isoforms may enable cacao to fine-tune its response to varying stress conditions, providing a robust and flexible mechanism for drought adaptation.\u003c/p\u003e \u003cp\u003ePhysicochemical properties of the identified LEA proteins, such as their low molecular weight, high hydrophilicity, and diverse isoelectric points (pI), are consistent with their roles as osmoprotectants and desiccation protectants. The hydrophilic nature of LEA proteins, as indicated by their negative GRAVY values, is crucial for their function in stabilizing cellular structures and preventing protein aggregation during dehydration (Tunnacliffe and Wise \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). As for the subcellular localization predictions revealed that most LEA proteins were localized in the nucleus, with some exceptions, such as LEA-3 proteins, which were predicted to localize in the mitochondria. The localization of LEA-2 proteins in the chloroplast suggests their involvement in protecting the photosynthetic machinery during water stress, a critical function for maintaining photosynthetic efficiency under drought conditions (Yang et al. \u003cspan citationid=\"CR87\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Qiao et al. \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Iqbal and Munir \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). This finding aligns with research in other crops, where LEA-2 proteins have been demonstrated to protect chloroplasts during abiotic stress (Magwanga et al. \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Abdul et al. 2021; Liu et al. \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). The protective role of these proteins is also attributed to their WHy domain (Water stress and Hypersensitive response), which has been shown to stabilize membranes and prevent protein aggregation during dehydration, thereby safeguarding cellular structures (Battaglia et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Mertens et al. \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eA phylogenetic analysis revealed that the LEA proteins in cacao cluster into eight distinct groups, with high bootstrap support (\u0026gt;\u0026thinsp;70%). This clustering aligns with the classification based on conserved domains and motifs, further validating the identification of these proteins as members of the LEA family. The LEA-2 subfamily was the most represented, accounting for 49% of all LEA proteins, which mirrors findings in other species, such as \u003cem\u003eA. thaliana, S. lycopersicum\u003c/em\u003e, and \u003cem\u003eG. hirsutum\u003c/em\u003e (Hundertmark and Hincha \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Cao and Li \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Magwanga et al. \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Evolutionary results also revealed that the LEA gene family in cacao has undergone both tandem and segmental duplication events, which are common mechanisms for gene family expansion and diversification (Artur et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). The identification of two tandem duplication pairs (LEA-1_chr5-1/LEA-1_chr5-2 and LEA-5_chr10-1/LEA-5_chr10-2) suggests that these genes may have evolved to provide cacao with enhanced adaptability to environmental stresses.\u003c/p\u003e \u003cp\u003eCis-acting elements in the promoter regions of LEA genes revealed a predominance of stress-responsive elements, such as G-box (22%) and Box 4 (16%), which are known to be involved in abiotic stress responses (Yamaguchi and Shinozaki 2005). The presence of these elements suggests that the expression of LEA genes in cacao is tightly regulated in response to environmental stresses, particularly drought. Additionally, the identification of hormone-responsive elements, such as ABRE (58%) and TCA motifs (11%), highlights the role of phytohormones in regulating LEA gene expression under stress conditions (Mehrotra et al. \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Delahaie et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Stevenson et al. \u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), which aligns with findings in \u003cem\u003eArachis hypogaea\u003c/em\u003e (Huang et al. \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The predominance of stress-responsive elements in the LEA-2 and DHN subfamilies further supports their roles in drought tolerance.\u003c/p\u003e \u003cp\u003eThe physiological measurements, including \u003cem\u003eΨ\u003c/em\u003e\u003csub\u003e\u003cem\u003eleaf\u003c/em\u003e\u003c/sub\u003e and gas exchange parameters, revealed significant differences among the clones under drought stress. \u003cem\u003eΨ\u003c/em\u003e\u003csub\u003e\u003cem\u003eleaf\u003c/em\u003e\u003c/sub\u003e is a key indicator of plant water status and its ability to uptake soil water and minimize dehydration (Bray \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e1997\u003c/span\u003e; Rodr\u0026iacute;guez et al. 2017). Drought-tolerant genotypes typically maintain less negative \u003cem\u003eΨ\u003c/em\u003e\u003csub\u003e\u003cem\u003eleaf\u003c/em\u003e\u003c/sub\u003e values under stress, supporting water homeostasis and cell turgor (Jarin et al. \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). In this study, \u003cem\u003eΨ\u003c/em\u003e\u003csub\u003e\u003cem\u003eleaf\u003c/em\u003e\u003c/sub\u003e declined in all cacao clones under drought stress, reaching approximately\u0026thinsp;\u0026minus;\u0026thinsp;1.5 MPa at DAT19, a moderate stress level compared to previous studies reporting values below \u0026minus;\u0026thinsp;3.0 MPa under prolonged drought (Santos et al. \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; De Almeida et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Osorio et al. 2021). These differences likely reflect variations in stress intensity, duration, and soil water availability. Field studies indicate that \u003cem\u003eΨ\u003c/em\u003e\u003csub\u003e\u003cem\u003eleaf\u003c/em\u003e\u003c/sub\u003e reductions tend to be less pronounced than in greenhouse conditions due to greater soil water retention, delaying drought perception by the root system (Araque et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; \u0026Aacute;vila et al. 2016; De Almeida et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2016\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe TSH 565 clone, previously identified as one of the most drought-tolerant genotypes due to its ability to maintain a less negative \u003cem\u003eΨ\u003c/em\u003e\u003csub\u003e\u003cem\u003eleaf\u003c/em\u003e\u003c/sub\u003e (Balasimha et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e1991\u003c/span\u003e; Garc\u0026iacute;a 2016), exhibited the smallest \u003cem\u003eΨ\u003c/em\u003e\u003csub\u003e\u003cem\u003eleaf\u003c/em\u003e\u003c/sub\u003e reduction in our study, suggesting enhanced water homeostasis in its leaf tissues. Moreover, \u003cem\u003eΨ\u003c/em\u003e\u003csub\u003e\u003cem\u003eleaf\u003c/em\u003e\u003c/sub\u003e recovery after rehydration at DAT30 aligns with previous reports, where cacao clones restored their values following irrigation resumption (Garc\u0026iacute;a 2016; Kacou et al. 2016; De Almeida et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Lahive et al. \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eGas exchange analysis revealed significant declines in \u003cem\u003eA\u003c/em\u003e, \u003cem\u003eE\u003c/em\u003e, and \u003cem\u003egs\u003c/em\u003e under drought stress, consistent with previous findings in cacao (Rodr\u0026iacute;guez et al. 2017; Lahive et al. \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). More drought-susceptible clones exhibited an early decline in \u003cem\u003egs\u003c/em\u003e, whereas more tolerant clones, such as TSH 565, showed minimal changes, a trait associated with better drought adaptation (Osorio et al. 2021). Upon rehydration, ICS 60 and TSH 565 recovered their physiological parameters more rapidly, whereas EET 8 showed slower recovery, reinforcing \u003cem\u003eΨ\u003c/em\u003e\u003csub\u003e\u003cem\u003eleaf\u003c/em\u003e\u003c/sub\u003e as a key trait for drought tolerance classification. WUEi declined under DAT19 conditions, as previously reported in cacao (Kacou et al. 2016), but showed differential recovery among genotypes. ICS 60 exhibited the highest \u003cem\u003eWUEi\u003c/em\u003e restoration post-rehydration, indicating a superior adaptive capacity to drought, consistent with findings that greater \u003cem\u003eWUEi\u003c/em\u003e recovery correlates with increased drought resistance (Lahive et al. \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eOverall, our findings confirm that ICS 60 is the most drought-tolerant clone under these conditions, maintaining a higher \u003cem\u003eRWC\u003c/em\u003e despite exhibiting the lowest \u003cem\u003eΨ\u003c/em\u003e\u003csub\u003e\u003cem\u003eleaf\u003c/em\u003e\u003c/sub\u003e. While TSH 565 demonstrated resilience, it experienced greater water loss and only partial \u003cem\u003eWUEi\u003c/em\u003e recovery. In contrast, EET 8 showed the lowest recovery capacity. Notably, these results contrast with those of Osorio et al. (2021), who reported that EET 8 performed best under drought stress conditions, whereas ICS 60 exhibited the poorest response. This discrepancy may arise from differences in experimental conditions, such as soil composition, vapor pressure deficit, or the duration and severity of drought stress. Additionally, acclimation responses influenced by prior environmental conditions could contribute to the variation observed across studies. Further research comparing physiological responses across diverse environments is needed to clarify the influence of environmental factors on drought tolerance rankings among cacao clones. These findings underscore the importance of physiological plasticity in drought tolerance and reinforce the relevance of \u003cem\u003eΨ\u003c/em\u003e\u003csub\u003e\u003cem\u003eleaf\u003c/em\u003e\u003c/sub\u003e and \u003cem\u003eWUEi\u003c/em\u003e as key criteria for selecting drought-resilient cacao clones in breeding programs.\u003c/p\u003e \u003cp\u003eIn relation to expression analysis of LEA genes under drought stress revealed significant upregulation in all three cacao clones (EET 8, TSH 565, and ICS 60) at the peak of stress (DAT19), followed by a decrease during the recovery phase (DAT30). This pattern aligns with the known role of LEA proteins in protecting cells during dehydration and their reduced necessity once water availability is restored (Hand et al. \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). The most pronounced upregulation was observed in the ICS 60 clone, which exhibited the highest expression levels of LEA-1, LEA-3, and LEA-5 under drought stress. This suggests that ICS 60 may rely more heavily on LEA proteins for drought tolerance compared to the other clones. Interestingly, the expression patterns of LEA genes varied among the clones, indicating genotype-specific responses to drought stress. For instance, TSH 565 showed a strong upregulation of SMP and DHN genes during drought stress, followed by a sharp downregulation during recovery, suggesting a rapid osmotic adjustment mechanism. In contrast, EET 8 exhibited a more stable expression pattern, with minimal fluctuations in LEA gene expression, indicating a more controlled and less dynamic response to drought stress. The sustained upregulation of LEA-3 and LEA-5 in all clones during both drought stress and recovery phases suggests that these proteins play a continuous role in maintaining cellular stability and dehydration tolerance. This mirrors findings in other crops, where LEA-3 and LEA-5 proteins have been shown to stabilize membranes and prevent protein aggregation under stress conditions (Liu et al. \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Wang et al. \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). The identification of these molecular signatures provides a foundation for marker-assisted selection of drought-resilient cacao varieties.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThis study employs an integrated approach, combining genomic, phylogenetic, expression, and physiological analyses, to establish a comprehensive molecular framework for understanding cacao's adaptive responses to drought stress. Genome-wide identification and classification revealed 30 LEA genes in \u003cem\u003eTheobroma cacao\u003c/em\u003e, organized into eight subfamilies, with LEA-2 being the most abundant, underscoring its critical role in osmotic stress adaptation. Chloroplastic localization of LEA-2 proteins further supports their function in protecting the photosynthetic machinery under stress conditions. Expression analysis demonstrated significant upregulation of LEA genes during drought, with genotype-specific responses. The ICS 60 clone exhibited the highest upregulation of LEA-1, LEA-3, and LEA-5, correlating with severe physiological stress and limited recovery, suggesting a reliance on LEA proteins for acute stress mitigation. In contrast, TSH 565 displayed moderate stress tolerance and improved recovery, associated with rapid osmotic adjustment mediated by SMP and DHN genes. Meanwhile, EET 8 maintained stable LEA expression and physiological parameters, indicative of a balanced, less stress-dependent adaptation strategy. These findings advance our understanding of the molecular mechanisms underlying cacao's drought tolerance and provide actionable insights for breeding more resilient cultivars, crucial for sustaining cacao production in a changing climate.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eData availability statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe raw datasets used during the current study are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors gratefully acknowledge the financial support provided by the project \u003cem\u003e\u0026ldquo;Differential Gene Expression of Selected Cacao Clones to Determine Their Tolerance to Extreme Climatic Conditions in Huila.\u0026rdquo;\u003c/em\u003e This study was supported by the Sistema de Investigaci\u0026oacute;n, Desarrollo Tecnol\u0026oacute;gico e Innovaci\u0026oacute;n (SENNOVA) \u0026ndash; Centro de Formaci\u0026oacute;n Agroindustrial \u0026ldquo;La Angostura.\u0026rdquo;\u003c/p\u003e\n\u003cp\u003eThe authors also thank the students under the \u003cem\u003eContrato de Aprendizaje\u003c/em\u003e program who participated in sample collection, data recording, and laboratory sample processing, particularly Yennifer Barrios Rico. We further acknowledge the SENNOVA researchers Eliana Lizeth Medina R\u0026iacute;os, Alejandro Garcia and Valentin Murcia, for their valuable technical support and contributions to the development of this study.\u0026nbsp;In addition, we extend our gratitude to the instructors for their academic guidance and mentorship, and to the administrative team for their logistical and operational support, which was essential for the successful execution of this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was funded by the Sistema de Investigaci\u0026oacute;n, Desarrollo Tecnol\u0026oacute;gico e Innovaci\u0026oacute;n - SENNOVA \u0026ndash; Centro de Formaci\u0026oacute;n Agroindustrial \u0026ldquo;La Angostura\u0026rdquo;, under the project SGPS-9329-2022: \u0026quot;Differential Gene Expression of Selected Cacao Clones to Determine Their Tolerance to Extreme Climatic Conditions in Huila.\u0026quot;\u003c/p\u003e\n\u003cp\u003eThe funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of interest\u003c/strong\u003e\u003cbr\u003e\u0026nbsp;The authors declare that there are no conflicts of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical approval\u003c/strong\u003e\u003cbr\u003e\u0026nbsp;Not applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConceptualization: V-AGP, G-MJA, N-OJE and R-CAF; Methodology: V-AGP, G-MJA, N-OJE and R-CAF; Software: V-AGP, G-MJA, N-OJE and R-CAF; Validation: V-AGP, G-MJA, N-OJE and R-CAF; Formal analysis: V-AGP, G-MJA, N-OJE and R-CAF; Investigation: V-AGP, G-MJA, N-OJE and R-CAF; Data curation: V-AGP, G-MJA, N-OJE and R-CAF; Writing \u0026ndash; original draft preparation: V-AGP and R-CAF; Writing \u0026ndash; review \u0026amp; editing: V-AGP, G-MJA, N-OJE and R-CAF; Supervision: V-AGP; Project administration: V-AGP; Funding acquisition: V-AGP. All authors have read and agreed to the published version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; ORCID IDs\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eGinna Patricia Velasco-Anacona: https://orcid.org/0000-0002-8686-7136\u003c/p\u003e\n\u003cp\u003eAlexis Felipe Rojas-Cruz: https://orcid.org/0000-0003-4467-0914\u003c/p\u003e\n\u003cp\u003eNoriega-Ortega Jhon Eduar: https://orcid.org/0000-0003-1055-1159\u003c/p\u003e\n\u003cp\u003eGiraldo-Murcia Julian Alejandro: \u0026nbsp;https://orcid.org/0000-0002-5242-947X\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAbdi H (ed) (2007) The Bonferroni and Šid\u0026aacute;k corrections for multiple comparisons. 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AMB Express 7:182. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1186/s13568-017-0483-1\u003c/span\u003e\u003cspan address=\"10.1186/s13568-017-0483-1\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","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":"LEA proteins, Theobroma cacao, genome-wide analysis, drought tolerance, gene expression profiling, climate-resilient breeding","lastPublishedDoi":"10.21203/rs.3.rs-8999141/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8999141/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eLate Embryogenesis Abundant (LEA) proteins play essential roles in plant adaptation to water deficit; however, their genomic organization and stress-responsive regulation remain unexplored in \u003cem\u003eTheobroma cacao\u003c/em\u003e. This study represents the first genome-wide identification and characterization of the LEA gene family in cacao and evaluates their involvement in drought response. A total of 30 LEA genes were identified and classified into eight subfamilies based on conserved domains, motif composition, and phylogenetic relationships. Gene structure, chromosomal distribution, and duplication analyses revealed that both tandem and segmental duplication events contributed to family expansion. Promoter analysis showed enrichment of stress- and hormone-responsive cis-acting elements, supporting their regulatory role under abiotic stress. Predicted subcellular localization suggested chloroplast targeting for several LEA-2 members, indicating potential involvement in photosynthetic protection. Expression profiling via RT-qPCR in three cacao clones with contrasting drought tolerance revealed genotype-specific responses. Notably, clone ICS 60 exhibited strong induction of LEA-1, LEA-3, and LEA-5 genes under stress, correlating with greater physiological stress and limited recovery. In contrast, TSH 565 showed moderate induction of SMP and DHN genes, associated with improved recovery, while EET 8 maintained stable expression and physiological parameters. These findings provide new insights into the molecular and physiological mechanisms underlying drought tolerance in cacao and identify candidate genes for breeding climate-resilient cultivars.\u003c/p\u003e","manuscriptTitle":"Genome-wide identification and characterization of the late embryogenesis abundant (LEA) protein-encoding gene family related to water deficit response in Theobroma cacao","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-10 16:45:39","doi":"10.21203/rs.3.rs-8999141/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":"7b33ca9f-9e9a-4320-94ed-f01cc7d7db83","owner":[],"postedDate":"March 10th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-03-15T15:39:29+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-10 16:45:39","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8999141","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8999141","identity":"rs-8999141","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}