Molecular and Physiological Mechanisms of the Cadmium Response in Seedlings of Two Theobroma cacao L. Genotypes

Molecular and Physiological Mechanisms of the Cadmium Response in Seedlings of Two Theobroma cacao L. Genotypes | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Molecular and Physiological Mechanisms of the Cadmium Response in Seedlings of Two Theobroma cacao L. Genotypes Paola Delgadillo-Durán, Francisco Miguel Menéndez-Burns, Caren Rodríguez-Medina, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8509096/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 6 You are reading this latest preprint version Abstract Aims Understanding the mechanisms of cadmium (Cd) accumulation in cacao plants is critical for mitigating health risks associated with Cd exposure through chocolate consumption and for guiding plant breeding strategies. A general and genotype-specific molecular and physiological responses were characterized. Methods The seedlings of the two cacao genotypes, PA121 and TSH660, were exposed to 0 and 10 ppm Cd in hydroponic conditions. Leaf and root samples were collected at 0, 24, and 48 h (RNAseq) and at 60 days post-treatment (ICP-OES). Gene expression profiles of Cd-treated and untreated plants were compared using differential gene expression (DEG) and gene ontology analyses. Gas exchange and abscisic acid (ABA) measurements were conducted on greenhouse-grown seedlings of genotype PA121. Results The number of DEGs recorded in roots was nearly twice as high as in leaves at 48 h after Cd exposure. Shared and genotype-specific DEGs related to detoxification, reactive oxygen species, and hormone pathways were upregulated in roots, and carbohydrate, tricarboxylic acid cycle, fatty acid, and terpenoid synthesis DEGs were activated in leaves. Additionally, genes from Cd-transport families, such as ZIP/IRT and NRAMP, were downregulated in roots. More significantly, ABA-associated biosynthetic and signaling transcripts and ABA abundance increased in roots after Cd treatment. PA121 seedlings exposed to 12 ppm Cd exhibited reduced stomatal conductance without a significant decline in photosynthesis. Conclusions These findings are consistent with a model in which Cd triggers ABA-linked root signaling that reduces stomatal conductance and mass flow and reduces expression of active Cd2+ transport, thereby limiting Cd uptake. Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Introduction Cadmium (Cd), a heavy metal element with acute toxicity to humans, has been detected in cacao seeds from several Latin American and Caribbean countries at levels exceeding the EU regulatory limit (Meter et al., 2019 ). Cd accumulation in edible plant tissues poses a significant risk to human health. In plants, heavy metal stress has driven the evolution of coping mechanisms such as sequestration, chelation, compartmentalization, and exclusion from the stele via physical barriers (Lux et al., 2011 ). Cd enters plants primarily through the roots and is redistributed via transport pathways shared with essential micronutrients (Lux et al., 2011 ; Rai et al., 2019 ). Sensitivity to Cd is typically characterized by pronounced growth inhibition and strong molecular responses (Rui et al., 2016 ; Feng et al., 2018 ). Cd tolerance, in contrast, refers to the ability to maintain growth despite high Cd exposure without necessarily hyperaccumulating the metal (Ernst et al., 2008 ). For food crops, an ideal phenotype would combine normal growth on Cd-contaminated soils with the ability to exclude Cd from edible tissues (Wang et al., 2021 ). Cd movement toward the root stele occurs primarily by mass flow (Barber, 1995 ; Sterckeman et al., 2004 ). Several micronutrient transporters have been functionally validated in cacao, including members of the NRAMP family, TcNRAMP6 and TcNRAMP5, as well as TcHMA3, which mediate Zn and Cd transmembrane transport (Ullah et al., 2018 ; Moore et al., 2020a ). Similarly, TcIRT1 has been shown to facilitate the uptake of Cd 2+ and Fe 2+ (Dashner, 2024 ). Beyond transport, structural components, such as lignin, also play a role in Cd stress responses. Lignin, a major secondary cell wall component, binds positively charged particles (Parrotta et al., 2015 ), and its biosynthesis is commonly upregulated in plants in response to Cd exposure (Yang et al., 2007 ; Kováčik and Klejdus, 2008 ; Lux et al., 2011 ; Elobeid et al., 2012 ; Rui et al., 2016 ). Subcellular localization of Cd in Arabidopsis thaliana roots suggests that Cd precipitates with sulfur (S) in the endodermis and with phosphorus (P) in the apoplast (Van Belleghem et al., 2007 ). Cd's high affinity for thiol groups could explain why sulfur uptake often increases following Cd treatment (Ernst et al., 2008 ). High-affinity sulfur transporters ( SULTRs ) are upregulated after Cd treatment in A. thaliana (Herbette et al., 2006 ), Oryza sativa (Dubey et al., 2014 ), and other species (Verbruggen et al., 2009 ). Early signaling responses to Cd stress include a rapid spike in calcium levels in A. thaliana (Zhang et al., 2023a ), followed by an increase in reactive oxygen species (ROS), a pattern also observed in tobacco, pea, and alfalfa (Chmielowska-Bąk et al., 2014 ). ROS accumulation in response to Cd is time- and dose-dependent, as shown in soybean roots (Pérez-Chaca et al., 2014 ) and in Nicotiana tabacum cells, where ROS originate from multiple subcellular locations (Garnier et al., 2006 ). Antioxidant defenses are activated in parallel, including regulation of glutathione-S transferase ( GST ) genes in A. thaliana (Herbette et al., 2006 ), Cosmos bipinnatus (Liu et al., 2017 ), and Ocimum gratissimum (Wang et al., 2023a ). Hormonal modulation is another hallmark of Cd stress. Abscisic acid (ABA) levels increase in Solanum tuberosum roots (Stroiński et al., 2013 )d sativa leaves within 72 h of Cd treatment (Hsu and Kao, 2003 ). Ethylene production rises in Glycine max roots (6–24 h) (Chmielowska-Bak et al., 2013 ), Pisum sativum (at 14 days) (Rodriguez-Serrano et al., 2009 )d thaliana leaves (24 h) (Schellingen et al., 2014 ). Conversely, indole-3-acetic acid (IAA) levels decrease in A. thaliana roots (7 days) and Populus trichocharpa stems (24 days) (Chmielowska-Bąk et al., 2014 ). In our study, we observed differences in gene expression between control and Cd-treated plants, as well as between two genotypes differing in Cd uptake. We also propose a potential link between the observed molecular responses and hormone accumulation in leaves of young cacao plants. Our results could provide a basis for identifying markers for marker-assisted selection and targets for gene editing to develop cacao varieties with reduced Cd accumulation. Materials and methods Plant material and growth conditions Plants used for Cd concentration measurement, growth parameters, and RNA purification were grown in the AGROSAVIA Research Center located in Palmira, Valle del Cauca, Colombia (3°31'12 "N, 76°19'50''W at ~ 100 m.a.s.l.), with an average annual temperature of 26°C and relative humidity of 65%. Plants were grown from seeds obtained from two clonally propagated mother plants. Genotypes TSH660 and PA121 were selected based on differences in Cd accumulation observed in their progeny during an initial hydroponic experiment (Hernández-Varela et al., 2025, in preparation). Open-pollinated seeds from the mother plants of both genotypes were germinated in sand, grown for two months in a greenhouse, and transferred to 150 L containers with half-strength Hoagland's solution (Hoagland and Arnon, 1950) (7.5 mM N, 3.5 mM K, 2.5 mM Ca, 0.5 mM P, 0.1 mM S, 1 mM Mg, 1.01 mM Fe, 0.5 mM B, 0.5 mM Mn, 0.05 mM Zn, 0.02 mM Cu, and 0.01 mM Mo). For transcriptome analysis, seedlings were grown in three individual 150 L tanks, each housing one plant of each genotype, totaling three plants per genotype. After four weeks, Cd(NO 3 ) 2 was added to a concentration of 10 ppm Cd (~ 0.089 mM Cd), increasing total nitrogen (N) by 0.027 mM. After two months of Cd exposure, Cd concentration in leaves and roots, and plant growth parameters were measured. Plants used for gas exchange and phytohormone quantification were grown at The Pennsylvania State University, University Park, PA, USA, in a greenhouse with controlled conditions: 16 hours at 5355.9 Lux (SD = 5516.9 Lux), 29.82°C (SD = 5.9°C), and humidity at 73.84% RH (SD = 15.43% RH). Forty-eight seeds from open-pollinated PA121 mother plants were obtained from the USDA, ARS Tropical Agriculture Research Station in Mayagüez, Puerto Rico. They were germinated in 32-Star Deep Plug Trays (T.O. Plastics, Clearwater, MN) filled with sand and misted for 2 minutes every 8 minutes. Plants were transferred after a week to 7 in D40H Deepots™ (Stuwe & Sons, Tangent, Oregon) with two drippers (flow rate of 22 mL minute − 1 ), and fertigated with a modified Hoagland's solution (16 mM N, 6 mM K, 4 mM Ca, 2 mM P, 1 mM S, 1 mM Mg, 0.00537 mM Fe, 0.05 mM Cl, 0.025 mM B, 0.002 mM B, 0.002 mM Zn, 0.0005 mM Cu, 0.00350 mM Mo) twice a day at 8 a.m. and 6 p.m. for 2 minutes each time for 3 months before 48 plants were randomly assigned to 3 treatment levels (n = 16) of Cd 2+ ion (added CdCl 2) : ~0.055 mM (6.13 ppm), ~ 0.1096 mM (12.26 ppm) or without Cd 2+ treatment. Cd Analysis Cd concentrations were measured at the AGROSAVIA Research Center, Tibaitatá (Mosquera, Colombia) using inductively coupled plasma optical emission spectrometry (ICP-OES Thermo Scientific ICAP 6500) following a modified method of the US EPA (US Environmental Protection Agency, 1996 ; US Environmental Protection Agency, 2007 ). Calibration curves were performed using the standard reference material from the National Institute of Standards and Technology, a solution of 1000 mg/L Cd prepared by digesting Cd(NO₃)₂ in 0.5 mol/L HNO₃ (Certipur®). Calibration curves were performed using reference cacao material from genotype WEPAL IPE 965 (WEPAL, 2019 ) provided by Wageningen Agricultural University (Netherlands). Tissue sampling, RNA purification, RNA‑Seq library preparation, and sequencing Leaves at developmental stage C (Fister et al., 2016 ) were excised from plants once before the application of Cd (time point 0) and then 24 and 48 hours after the application of Cd (AC), then immediately frozen in liquid nitrogen, and stored at -80 ºC. Root tissues were sampled similarly from the same plants at 0 and 48 hours. One hundred mg of tissue from each sample was ground in liquid nitrogen using a mortar and pestle and used to purify total RNA with the PureLink™ Plant RNA Reagent, following the protocol of Yockteng et al . (2013). RNA concentrations were determined spectrophotometrically using a NanoDrop® 2000 (ThermoScientific). RNA was separated on a 1% agarose gel and stained with GelRed® (Biotium) to confirm RNA integrity. Barcoded libraries were made from 1 µg of RNA using the TruSeq RNA Library Prep Kit v2, following the manufacturer's Instructions (Illumina, San Diego, CA). The quality of each library was assessed using a high-sensitivity DNA kit on an Agilent TapeStation 4200 (Agilent Technologies, Santa Clara, CA). In total, 18 libraries from leaf tissue and 12 from root tissue were constructed and sequenced using a 150 bp paired-end strategy on an Illumina HiSeq X system, dedicating one lane to each replicate tank, targeting a 300 bp insert size. Sequencing was performed at Macrogen Inc. (Seoul, South Korea). Transcriptome assembly and read mapping Adapters and low-quality reads were removed using Trimmomatic (Bolger, Lohse, and Usadel, 2014 ), and the quality of the remaining reads was verified using FastQC (Andrews, 2010 ). Filtered reads were mapped using Hisat2 (Kim et al., 2019 ) to a GFF annotation containing the last exon of each gene model of Criollo B97 from Belize V2 reference genome (Argout et al., 2017 ) (Figure S1 A-P). Fractional counts were calculated using the featureCounts package (Liao, Smyth, and Shi, 2014 ). Genes with less than 10 normalized reads across samples were removed. Log2 fold change calculation, filtering, and size factor estimation DEGs were identified using functions from the package DESeq2 (Michael et al., 2022 ) and an ad hoc R function created to minimize type I error and maximize DEG discovery. The function had three main capabilities: 1) filtering genes based on mapping events across libraries, as performed by the edgeR package (Robinson, McCarthy, and Smyth, 2010 ); 2) utilizing the row variance for the independent filtering statistic as suggested previously (Bourgon et al., 2010 ); 3) performing steps one and two and normalization using gene dispersion values only using libraries included in the comparison. An adjusted p-value cut-off of 0.05 was applied. The gene expression model included "genotype" and "time after Cd treatment (AC)" as the main effects and a blocking factor to account for tank-to-tank variation. The interaction between time AC and genotype was examined. Since each plant was continuously sampled throughout the experiment, each plant is nested within the interaction of the "genotype" and "block" terms. PA121 and 0 h were used as references. Another set of models without "genotype" was applied to compute log2-fold changes of combined genotypes (model matrix and contrast weights; Table S1 A-C). Ortholog classification, pathway mapping, and subcellular localization prediction DEGs were reciprocally blasted using CRB-BLAST (Aubry et al., 2014 ) to the coding sequences (CDS) of the A. thaliana genome (arabidopsis.org) using three E-value cut-offs: 10 − 2 , 10 − 3 , and 10 − 5 . Gene families were then identified using PlantTribes2 (Wafula et al., 2023 ). KEGG pathway mapping (Kanehisa et al., 2017 ) was performed using orthogroups identified by KOFAM KOALA (Aramaki et al., 2020 ). Subcellular localization was predicted using DeepLoc2 (Thumuluri et al., 2022 ). Gene Ontology term enrichment analysis and clustering Gene Ontology (GO) terms (Ashburner et al., 2000 ; Aleksander et al., 2023 ) were assigned using Blast2GO (Götz et al., 2008 ). Overrepresentation analysis (ORA) was done using Fisher's hypergeometric test in the "Fast GSEA" package (Korotkevich, Sukhov, and Sergushichev, 2019 ) against reference genes with at least one normalized count across their respective tissue-specific libraries. GO term semantic similarity indices and clustering were performed using "SimplifyEnrichment" (Gu and Hübschmann, 2022 ), the Rel method (Schlicker et al., 2006 ), and the binary-cut algorithm (Mezentsev, 2017 ). Graphs were produced with R packages (Wickham, 2009 ; Gu, Eils, and Schlesner, 2016 ). Photosynthesis and Gas exchange measurements Photosynthesis (A) and gas exchange (Gs) were measured using a LI-6400 XT photosynthesis system with a Leaf Fluorescence Chamber (LCF) (Li-Cor ®, Lincoln, NE) in survey mode. The system had a constant flow of 500 µmol s − 1 , complete desiccant bypass, reference CO 2 of 400 µmol mol − 1 , and light set to match the outside of the chamber at 6210 Lux. Measurements were taken at 8:00 a.m. and 1:00 p.m. for two days after the onset of the treatments. Hormone quantification The methods were adapted from published protocols (Trapp et al., 2014 ; Floková et al., 2020 ). Plants were uprooted and cleaned in water, from which fully developed E-leaves and adventitious root material were separated in super-cold conditions (dry ice). One hundred mg of frozen tissue per sample was ground in liquid nitrogen. One mL of extraction buffer (7 parts methanol to 3 parts water, with 5 nM of labeled standards) was added, samples were vortexed and left to shake for 30’/4°C. Tubes were centrifuged at 16,000x g for 5’/4°C, and the supernatant was freeze-dried with centrifugation. Samples were resuspended in fresh extraction buffer without internal standards using sonication in an ice bath for 10 minutes, centrifuged at 16,000x g for 5’/4°C, and the supernatant was analyzed by The Huck Institutes' Metabolomics Core Facility (RRID: SCR_023864) using a Sciex ZenoTOF 7600 LC-MS. Results Genotypic variation in Cd uptake in roots and leaves of hydroponically grown cacao seedlings The Cd concentrations in tissues of 2 month-old plants treated with 10 ppm Cd were significantly higher than those of the controls, both in leaves (one-sided t-test, t = 4.2205, df = 19, p = 2.315x10 − 4 ) and in roots (one-sided t-test, t = 16.459, df = 20, p = 2.05x10 − 13 ) (Table 1 ) (Fig. 1 A, B). On average, Cd concentration in the roots was higher than in leaves, regardless of treatment (Table 1 ). Table 1 Cd concentration and mass of plants treated with Cd Tissue (Leaves v Roots) Genotype (PA121 v TSH660) (N) Cd treatment (10 ppm vs 0 ppm) Cd measured (ppm) (95% C.I) Cd measured (ppm) (95% C.I) Dry weight (g) (95% C.I) Dry weight (g) (95% C.I) Leaves PA121 (N = 3) 0 ppm 0.3 (C.I. 0.27) 0.43 (C.I. 0.3) 25.3 (C.I. 6.7) 18.3 (C.I. 9) TSH660 (N = 3) 0.5 (C.I. 0.98) 11.2 (C.I. 13.9) PA121 (N = 9) 10 ppm 97.4 (C.I. 38.6) 52.3 (C.I. 25.7) 7.3 (C.I. 2) 6.7 (C.I. 1.2) TSH660 (N = 11) 15.3 (C.I. 13) 6.2 (C.I. 1.9) Roots PA121 (N = 3) 0 ppm 7.5 (C.I. 22) 4.6 (C.I. 6.7) 7.6 (C.I. 5) 5.97 (C.I. 2.8) TSH660 (N = 3) 1.7 (C.I. 1.9) 4.3 (C.I. 5.7) PA121 (N = 10) 10 ppm 1416.3 (C.I. 118.8) 1143.1 (C.I. 144.2) 2.4 (C.I. 1) 2.5 (C.I. 0.5) TSH660 (N = 11) 895.1 (C.I. 122.8) 2.6 (C.I. 0.5) In Cd-treated PA121 roots, the mean Cd concentration was ~ 1.6-fold higher than the average recorded for Cd-treated TSH660 roots (Table 1 ) (Fig. 1 A). The average concentration in Cd-treated PA121 leaves was ~ 6.4-fold higher than the average recorded for Cd-treated TSH660 leaves (Table 1 ) (Fig. 1 B). Cd concentrations in tissues from the two genotypes grown at 0 ppm Cd were not significantly different (Table 1 ). These results demonstrate that under our experimental conditions, progeny from open-pollinated PA121 accumulated more Cd in leaf and root tissues than those from TSH660. We designated the progeny from PA121 as the high accumulator, PA121(HA), and the progeny from TSH660 as the low accumulator, TSH660(LA). Exposure to 10 ppm Cd significantly stunted plant growth, resulting in similar overall biomass between the two genotypes (Table 1 ; Figs. 1 C and D). Under control conditions (0 ppm Cd), PA121 exhibited significantly greater leaf mass than TSH660 (one-sided t = 3.9361, df = 2.8835, p = 0.0157) and marginally greater root mass (one-sided t = 1.8287, df = 3.952, p = 0.07115). Differential gene expression after cadmium treatment The 18 transcriptome libraries averaged over 16 million reads per sample, with an average mapping rate of 85.7%. Differentially expressed genes (DEGs) were obtained from 14 linear contrasts (Table S1 B-C). The number of DEGs from the main contrasts, the percent of upregulated DEGs of these contrasts, and selected intersections are represented in Fig. 2 . A table with all differential expression results is presented in Table S2 . After 48h of Cd treatment, we identified 4185 shared DEGs in roots (shared response, Fig. 2 A). The shared response in leaves had significantly fewer DEGs than in roots; in leaves, 1162 at 24h AC and 1999 at 48h AC (Fig. 2 A). In the shared response, the number of downregulated DEGs was higher in the roots (2344/4185 DEGs or 56%). Conversely, upregulation was higher in leaves (1127/1999 DEGs or 56.4%), deviating significantly from a 1:1 expectation (X 2 = 82.21, df = 1, p-value < 2.2x10 − 16 , Fig. 2 C). PA121(HA) had 2297 DEGs in roots 48h AC, and 1538 and 604 in leaves 48h and 24h AC, respectively (Fig. 2 A). The number of downregulated DEGs was greater than expected in roots, while in leaves, upregulated DEGs were greater than expected (X 2 = 112.45, df = 1, p-value < 2.2x10 − 16 ). On the other hand, TSH660(LA) had 2396 DEGs in roots 48h AC, slightly higher than in PA121(HA) (Fig. 2 A). In leaves, TSH660(LA) showed 180 DEGs at 48h and 57 DEGs at 24h, fewer than PA121(HA), which showed 547 and 1358 DEGs at 24h and 48h, respectively (Fig. 2 A). Nevertheless, the number of downregulated DEGs in TSH660(LA) roots still deviated significantly from a 1:1 expectation (X 2 = 11.849, df = 1, p-value = 0.0005771) (Fig. 2 C). GO Term enrichment analysis To gain insight into the mechanisms activated during Cd-response, enriched Gene Ontology (GO) terms from ten predefined sets of DEGs were identified (Table 2 , Table S3 ). In roots, the enriched GO terms in these sets of DEGs were combined, resulting in a total of 199 unique Biological Process (BP), 90 Molecular Function (MF), and 41 Cellular Component (CC) GO terms. In leaves, there were 63 BP, 18 MF, and 7 CC unique GO terms. After calculating semantic similarities and removing GO terms with zero similarity, 37 BP, 27 MF, and 7 CC remained in roots, and 14 BP in leaves. BP GO was prioritized because it exhibited the most enriched GO terms and provided the most informative GO categories. BP GO produced eight clusters, with at least two GO terms per cluster, a relaxed criterion that ensured maximal retention of GO terms (Fig. 3 , Table 3 ). The clustering analysis for MF is presented in Figure S2 . A second hypergeometric test compared GO term names in each cluster to the names within their ontology, identifying enriched keywords used to label each cluster (Table 3 , Fig. 3 A, B). Table 2 GO term enrichment results. The column (DEG Set) states the comparison, the second column lists the number of DEGs, followed by the number of enriched BP GO in roots, and the third column lists the enriched BP GO in leaves. The 10 sets included are those that had enriched BP GO (non-zero). N° DEG Set DEG / Enriched BP GO Roots DEG / Enriched BP GO Leaves 1 Tc48h/0h (shared response) 4185 / 120 1999 / 30 2 PA121HA 48h/0h 2297 / 86 1538 / 16 3 TSH660LA 48h/0h 2396 / 64 180 / 11 4 Intersection of 2 & 3 1378 / 51 114 / 9 5 Complements TSH660LA 1018 / 4 66 / 0 6 Complements PA121HA 919 / 0 1424 / 9 Table 3 GO term clusters Clusters in Root Cluster Name Number (GO terms) Genotype 1 Blue light abscisic activated defense and ion response signaling pathway 19 Both 2 Catabolic process 4 Both 3 Response 2 Both 4 Unnamed 2 Both 5 Signaling 2 HA only (PA121) 6 Ion transport 4 Both 7 Dephosphorylation 2 Both 8 Cell 2 Clusters in Leaf Cluster Name 1 Protein refolding 3 Both 2 Cellular heat response 9 Both 3 Cell detoxification 2 LA only (TSH660) Cd activation of indole acetic acid, abscisic acid, melatonin, strigolactone, and ethylene biosynthetic and signaling pathways in roots DEGs contributing to each enriched BP GO term in the "blue light-activated abscisic acid, defense, and ion response" cluster were classified into orthologous protein families and mapped to KEGG pathways. Gene families identified using KOFAM were consolidated with those identified using PlantTribes2. Genes were mapped to the biosynthetic steps and signal transduction components of various phytohormones, including indole-3-acetic acid (IAA or Auxin), abscisic acid (ABA), strigolactones, melatonin (Mt), ethylene, and strictosidine (Fig. 4 ). Mapping results are presented in Table S4 . Indoles In the indole biosynthetic pathway (Fig. 4 A and D), two orthologs of a terminal amino acid transferase ( TAA ) gene family, which deaminases Trp to indole-3-pyruvic acid (IPA), XM_007019556.2 and XM_007019553.2, were downregulated. The first one was significantly downregulated 21-fold (-4.39 log 2 -fold) when combining both genotypes, and the second one was downregulated 1.7-fold (-0.8 log 2 -fold) only in PA121(HA) (Fig. 4 A). Additionally, seven downstream signaling components of the IAA, members of the AUX/IAA gene family, were upregulated, except for XM_007034894.2, an ortholog of AtIAA14 , which was downregulated ~ 4-fold (Table S2 and Fig. 4 D). A SNAT gene that acetylates serotonin (XM_007045624.2) was upregulated 3.11-fold (1.64 log 2 -fold) at 48h AC in TSH660(HA) (Fig. 4 A). One candidate of a caffeoyl-methyltransferase ( COMT , XM_018121419.1) was downregulated 2.5-fold (-1.33 log 2 -fold) in both genotypes, while another (XM_018120814.1) was upregulated 43.1-fold (5.4 log 2 -fold) in TSH660(LA). A marked difference was observed between TSH660(LA) and PA121(HA) strictosidine synthase ( SS ) genes, SS1 and SS2 . Changes in expression occurred only in TSH660(HA). The SS1 gene XM_018120572.1 was downregulated 2.54-fold (-1.3 log 2 -fold) and three genes, XM_018126632.1, XM_018127382.1, and XM_007046480.2, were upregulated 3.11-fold (1.6 log 2 -fold), 4-fold (2 log 2 -fold), and 4.6-fold (2.2 log 2 -fold) respectively. Apocarotenoids Several key genes encoding enzymes central to the ABA biosynthetic pathway were strongly upregulated in response to Cd treatment (Fig. 4 B and F). The shared response identified a 5.9-fold (2.56 log 2 -fold) upregulation of an ortholog to β-carotene hydrolase 1 ( BCH1 ), XM_007038743.2, and a 1.76-fold (0.81 log 2 -fold) upregulation of an ortholog to zeaxanthin epoxidase ( ZEP ), XM_007028495.2. Two orthologs of 9-cis epoxy dioxygenase ( NCED ), XM_007022118.2 and XM_018118862.1, were upregulated 7.5-fold (2.9 log 2 -fold) and 8.6-fold (3.1 log 2 -fold), respectively. Three xanthoxin dehydrogenases ( XDH ) were upregulated, and three were downregulated. Notably, XM_007027846.2 was upregulated 13.5-fold (3.21 log 2 -fold) in TSH660(LA). In the indole aldehyde oxygenase ( IAO ) family, XM_007015509.2 was upregulated 2.3-fold (1.22 log2-fold), while XM_018127404.1 was downregulated 6.5-fold (-2.7 log 2 -fold). One ABA-hydroxylase ( ABAH ) candidate gene, XM_007016306.2, was upregulated 20.2-fold (4.34 log2-fold) in both genotypes, and another, XM_007042365.2, 8.6-fold (3.11 log 2 -fold) only in PA121(HA). On the other hand, one ABAH , XM_018116623.1, was downregulated 4.8-fold (-2.26 log 2 -fold) in PA121(HA) (Fig. 4 B and F). Furthermore, signaling components downstream of ABA, the ABA receptor gene family PYL , XM_007008792.2, XM_007024407.2, XM_007026527.2, and XM_018127083.1, were downregulated 4.92-fold (-2.3 log 2 -fold), 31.2-fold (~ -5 log 2 -fold), 4.1-fold (-2.0 log 2 -fold), and 3.4-fold (-1.8 log 2 -fold), while one, XM_007051517.2, was upregulated 2.9-fold (1.5 log 2 -fold) (Fig. 4 F). Finally, a key step in strigolactone synthesis, the CCD8 gene, also known as MAX4 (XM_007052456.2), was upregulated 2.7-fold (1.43 log 2 -fold) (Fig. 4 B). Furthermore, two downstream receptors of strigolactones (Chen, Nelson, and Shukla, 2022 ), one annotated as a D14, ortholog of AtKAI2 , XM_018128515.1, was downregulated 1.9-fold (~ 0.9 log 2 -fold), and another MAX2 ortholog, XM_018123475.1, was upregulated 1.9-fold (0.9 log 2 -fold) (Table S2 ). Ethylene The aminocyclopropane oxidase ( ACO ) XM_007019139.2 was downregulated 6.45-fold (-2.69 log 2 -fold) in the shared response. The ACO XM_007026145.2 was upregulated 2.12-fold (1.08 log 2 -fold) in PA121(HA) and the ACO XM_007012805.2 was upregulated 2.43-fold (1.28 log 2 -fold) in TSH660(LA) (Fig. 4 C and E). Catabolism cluster, including regulation of GST, Lignin-forming peroxidases, ROS modulation, and sugar-mediated stress response in roots The DEGs in the second-largest cluster, "catabolic process" included enzymes with catabolic functions, such as peroxidases (PER), glutathione S-transferases (GST), and enzymes involved in carbohydrate degradation, as well as chitinases (Fig. 5 A). The PER included 31 genes annotated as lignin-forming peroxidases ( LFP ) (Fig. 5 A). Of those, 25 were downregulated. In addition, 20 genes were genotype-specific to TSH660(LA) and 26 to PA121(HA), with an overlap of 17 genes between both genotypes. One LFP , XM_007045286.2, was strongly upregulated 175.7-fold (7.5 log 2 -fold) in TSH660(LA) (Fig. 5 A). In contrast to most other LFPs , XM_007011153.2 and XM_007011167.2 exhibited similar responses in roots and leaves (Fig. 5 A). The next largest family in this cluster was the GST, which contained 21 genes (Fig. 5 A). In the shared response, 15 were downregulated (Fig. 5 A). In the genotype-specific response, only ten genes were significant for TSH660(LA) and 13 for PA121(HA), with an overlap of seven genes between genotypes (Fig. 5 A). There were ten carbohydrate catabolism genes, ten genotype-specific to PA121(HA), and eight genotype-specific to TSH660(LA) (Fig. 5 A). The two DEGs that were exclusive to PA121(HA) were an alpha-glucan water dikinase ( GWD ) gene, XM_007027585.2, and a phosphoglucan phosphatase LSEX4 , XM_007011190.2 (Fig. 5 A). Interestingly, we identified an alpha-amylase that was upregulated only in leaves of PA121(HA) (Fig. 5 A). Finally, 17 chitinases in the catabolism cluster are represented in the shared response: 12 are specific to PA121(HA), and nine are specific to TSH660(LA), with an overlap of seven DEGs (Fig. 5 A). One marked difference between genotypes was the 6.7-fold (-2.8 log 2 -fold) downregulation of XM_007033739.2, an EP3 chitinase in PA121(HA) roots (Fig. 5 A). In leaves of PA121(HA) the endochitinases ortholog ( CHT1 ), XM_007041606.2 was 15.8-fold (3.98 log 2 -fold) upregulated, the endochitinases EP3 , XM_018119383.1 was 76.7-fold (6.3 log 2 -fold) upregulated, and the chitinase-2 ( CHT2 ), XM_018127043.1, was 15.4-fold (3.9-log 2 fold) upregulated (Fig. 5 A). Ion transport clusters indicating regulation of nitrogen, sulfur, and phosphate transporters The ion transport cluster contains six sulfur (S), 21 nitrogen (N), and seven phosphate (P) transporters. This cluster also includes 16 calcium (Ca) transporters, 10 aquaporins, four annexins, and five receptor class proteins (Fig. 5 B). Nitrogen transporters fell into two orthogroups of NRT1/PTR gene families, one containing 19 members ( NTR/PTR1 ), of which eight were downregulated (Fig. 5 B). NTR1/PTR1 had 15 genotype-specific DEGs to PA121(HA), 13 to TSH660(LA), with an overlap of ten (Fig. 5 A). The six S transporters belong to a single family ( SULTR ), with four of them being downregulated. Additionally, four were genotype-specific to each, with an overlap of two (Fig. 5 B). P transporters had 2 DEGs in the PHO1 gene family and five in the IPT family (Fig. 5 B). In the IPTs , TSH660(LA) had two downregulated genotype-specific genes. In PA121(HA), while five IPT genes were significantly downregulated, one IPT , XM_018122229.1, was upregulated 3.9-fold (1.97 log 2 -fold) (Fig. 5 B). Membrane intrinsic proteins (aquaporins) have five tonoplast intrinsic proteins ( TIP ), four plasma membrane intrinsic proteins ( PIP ), and one NOD25 intrinsic protein ( NIP ). One PIP gene, XM_007016678.2 ( TcPIP2-2 ), exhibited a relatively high 2-fold (1 log 2 -fold) upregulation, exclusive to TSH660(LA). More Ca transporters were regulated in PA121(HA), which had seven genotype-specific DEGs compared to four in TSH660(LA). Despite this, one member of the CAX2 gene family, XM_007016045.2, was 15-fold (3.99-log2-fold) upregulated specifically in TSH660(LA). This contrasted with the 1.3-fold upregulation in PA121(HA), which did not pass the significance cut-off (Fig. 5 B). Interestingly, in leaves, this gene was genotype-specific to PA121(HA) and was downregulated 5.4-fold (-2.42 log 2 -fold) (Fig. 5 B). The potential overlap between the phosphate starvation response (PSR) in A. thaliana (Wang et al., 2023b ) and the ion transport cluster in the Cd response in cacao was determined using the PSR genes from Table S1 in Z. Wang et al. (2023). In each gene family identified using PlantTribes2, genes from either A. thaliana or cacao had to all be regulated in the same manner (all upregulated or downregulated, Table S5 ). The log 2 -fold averaged by gene families is plotted in Fig. 5 C. In the ion transport cluster, all CAX1 , PHO1 , CNGC , and NIP were downregulated in cacao and upregulated in A. thaliana (Fig. 5 C). In the catabolism cluster, the peroxidases-2 ( PER2 ) and chitinases-1 ( CHT1 ) were all downregulated in the cacao, while upregulated in the A. thaliana , except for the peroxiredoxin-2f gene family, which was downregulated in both (Fig. 5 C). Metal transporter gene families regulated by Cd in cacao By searching the cacao genome for 16 gene superfamilies involved in metal or coordination compound transmembrane transport, 82 DEGs encoding metal transporters or metal detoxification genes were identified, 75 in roots and 12 in leaves. Their subcellular localization was then predicted (Fig. 5 D, Table S6). Seven were leaf-specific and 70 root-specific (Fig. 5 D). Our results indicated that A Cd/Zn transporting PIB-2 HMA gene (XM_018127237.1) was downregulated 1.7-fold (-0.77 log 2 -fold) in the leaves of the PA121(HA) 48 h AC (Fig. 5 D). This protein is predicted to be localized to the cytosol membrane (CM). TcHMA1 (XM_007047334.2) was also downregulated 2.1-fold (1.1 log 2 -fold) in PA121(HA) leaves at 48h AC. In roots, the orthologs to HMA5 and RAN1 included two distinct members. The first one, TcHMA5 (XM_018116084.1), predicted to localize to the CM, was downregulated 2.3-fold (-1.22 log 2 -fold) in PA121(HA) at 48 h AC. Conversely, TcRAN1 (XM_007040138.2), predicted to localize to the chloroplast membrane, was upregulated 3-fold (1.6 log 2 -fold) in TSH660(LA) at 48h AC (Fig. 5 D). TcNRAMP6 (XM_018122485.1) was downregulated 3.4-fold (1.77 log 2 -fold) in roots of both genotypes 48h AC. TcNRAMP5 (XM_018125489) was downregulated 9.64-fold (-3.26 log 2 -fold) in the roots and was genotype-specific to TSH660(LA) 48 h after Cd (Fig. 5 D). The ZIP gene, TcIRT1 (XM_018122962.1), was strongly downregulated in response to Cd treatment in both genotypes, 76.79-fold (-6.27 log 2 -fold) in PA121(HA) and 39.24-fold (-5.29 log 2 -fold) in TSH660(LA). Additionally, PA121(HA) had one ZIP family member, XM_018127227.1, downregulated 2.93-fold (-1.55 log 2 -fold) in roots 48h AC. Plant Cd resistance ( PCRs ) were mostly downregulated in roots, with one member (XM_018116355.1) being upregulated in the leaves of PA121(HA) (Fig. 5 D). The vacuolar iron transporter ( VIT ), XM_007042978.2, was 20-fold (-4.32 log 2 -fold) downregulated, and one Yellow Stripe-Leaf ( YSL ), XM_007039100.2, was upregulated in roots of both genotypes while being downregulated in the leaves of PA121(HA) (Fig. 5 D). GO term clusters and DEGs mapping to TCA, carbohydrate, and fatty acid metabolic pathways KEGG pathway analysis mapped 561 genes from Cellular Heat Response (CHR) leaf cluster (Fig. 3 B) to 236 different pathways and clustered once more using the binary-cut algorithm (Table S7 and Figure S3 ). After this, thirty-nine genes with shared pathways were selected and used to create ad hoc groups related to carbohydrate metabolism (CHO), fatty acid (FA) metabolism, the tricarboxylic acid cycle (TCA), and terpenoid biosynthesis (Fig. 6 ). Twenty-eight of the 39 genes were significantly upregulated in PA121(HA) (Fig. 6 ). One DEG shared by both genotypes, a cupredoxin ascorbate oxidase (XM_007016622.2), was upregulated 10.3-fold (3.4 log 2 -fold) at 48h AC. In the terpenoid group, an NCED (XM_007022118.2) was upregulated 5.6-fold (2.5 log 2 -fold), and a purple acid phosphatase ortholog (XM_018116461.1) was downregulated 2.6-fold (1.4 log 2 -fold); both genes are related to ABA signaling. The shared response in the carbohydrate cluster included a cell wall invertase 1, XM_018122432.1, which was upregulated 7-fold (2.8 log2-fold), and a beta-amylase, XM_018117250.1, downregulated 4.7-fold (2.2 log 2 -fold). All DEGs were specific to PA121(HA) in the fatty acid cluster. Eceriferum had two members: one downregulated (XM_018115329.1) 3-fold (-1.6 log 2 -fold) and another (XM_007008667.2) upregulated 10.7-fold (3.4 log 2 -fold). Cell wall invertases ( CWIN ), raffinose synthase ( RS ), and galactinol transferase ( GalT ) were upregulated in PA121(HA) leaves. One CWIN , XM_018117430.1, was downregulated in TSH660(LA) roots. Genes with convergent and divergent gene expression patterns In this analysis, convergent genes were defined as those that were differentially expressed at 0 h but not at 48 h. Conversely, divergent genes were not differentially expressed at 0 h but became so at 48 h AC. In roots, 322 convergent genes and 308 divergent genes were identified. In the divergent group, 45 genes became divergent due to changes in expression in PA121(HA) and 54 genes due to changes in expression in TSH660(LA). The convergent and divergent genes in leaves were similarly identified, as 182 and 867 DEGs, respectively. In leaves, 338 genes became convergent due to changes in expression specific to PA121(HA) and six due to changes in expression specific to TSH660(LA). The convergent and divergent genes were cross-referenced to genes contributing to each semantic similarity cluster (Table 3 ). The list of genes is provided in Table S8. The expression changes for the top genes in both groups were plotted by tissue in Figure S4 . Cd treatment in PA121 reduced gas exchange in cacao leaves and increased ABA concentration in roots To test whether ABA-related transcriptional changes under Cd exposure translated into physiological responses, we measured stomatal conductance (Gs), photosynthesis (A), and ABA concentrations in cacao seedlings under 0, 6, and 12 ppm Cd 2+ . Cd treatment had a significant effect on stomatal conductance (one-way ANOVA, p = 0.0192), accounting for 20.8% of its variation (Fig. 7 A); however, photosynthesis was unaffected (p = 0.6151) (Fig. 7 B). Tukey's post hoc test indicated that plants treated with 12 ppm Cd had significantly lower Gs than the control group at the end of the experiment (difference = -0.0119, p-adj. = 0.0145). No significant differences were observed between plants treated with six ppm Cd and the controls (difference = -0.0051, p-adj. = 0.4242) or between plants treated with 12 ppm and six ppm (difference = -0.0067, p-adj. = 0.2363) (Fig. 7 A). In plants treated with 12 ppm, a significant difference in Gs was observed between the morning of the first day and the afternoon of the second day (difference = -0.0190, p = 0.0499) (Fig. 7 C). Like before, no significant changes in A were detected (Fig. 7 D). After 36 hours, the mean ABA concentration in roots was significantly higher in the 12-ppm group (1.95 nM) compared to the control group (0.21 nM) (t = 4.0822, df = 2.0528, p = 0.0264) (Fig. 7 E). No significant difference between the treated and control groups was observed in leaf ABA concentrations (t = 0.3749, df = 3.0921, p = 0.366) (Fig. 7 F). Discussion Theobroma cacao exhibits both physiological and molecular adaptations to cadmium (Cd) exposure. TSH660(LA) genotype inherently absorbs significantly less Cd in its roots, approximately 63% of the amount absorbed by PA121(HA) genotype, and translocates markedly less to its leaves, at only ~ 15.7% of the PA121(HA) levels (Fig. 1 A-B). In contrast, PA121(HA) tolerated a higher Cd uptake and translocation, as well as a more robust activation of stress-response genes in leaves. These divergent strategies are reflected at the transcriptomic level: TSH660(LA) shows fewer differentially expressed genes (DEGs) in its leaves, consistent with an avoidance mechanism. PA121(HA), on the other hand, exhibits a substantially higher number of DEGs in its leaves (Fig. 2 A), with enrichment in genes associated with heat stress responses (Fig. 3 B), including heat shock proteins typically activated under abiotic and biotic stress conditions. In cacao, at 48 h after Cd exposure, the number of DEGs was nearly twice as high in roots (4185) as in leaves (1999) (Fig. 2 B). In leaves, PA121(HA) had 1538 DEGs compared to 180 in TSH660(LA), where in roots, both genotypes showed a similar number of DEGs (Fig. 2 B). The higher number of DEGs in roots aligns with findings in Solanum lycopersicum (Chen et al., 2023 ), Brassica juncea (Thakur et al., 2019 ), Nicotiana rustica (Zhang et al., 2021 )d thaliana (Herbette et al., 2006 ), but not in N. tabacum (Zhang et al., 2021 ). In cacao, both genotypes exhibited a higher proportion of downregulated genes in roots and more upregulated genes in leaves; a pattern not consistently observed in the other species cited. Despite differences in gene expression and Cd accumulation in leaves and roots, the mechanisms of Cd response in both genotypes share common features. These include a stress-detection and fast-acting signaling phase, followed by hormone-mediated signaling. These cause transcriptional changes that may result in reducing Cd toxicity, such as divalent cation uptake downregulation (Fig. 5 D); N and P uptake regulation (Fig. 5 C); regulation of chelating molecules (Fig. 5 A); and other adaptations related to water use, which include reduced stomatal conductance (Fig. 7 A-C), and transcriptional changes that may be related to lowering the plants water potential and increasing leaf thickness (Figs. 5 and 6 ). We also anticipate an adverse effect on growth (Fig. 1 C-D). Figure 8 integrates the data and the proposed model. Although T. cacao is increasingly recognized as a model system for tropical perennial trees, the mechanisms underlying Cd²⁺ sensing remain poorly understood. We hypothesize that ROS and Ca²⁺ signaling occur in cacao plants, and, similar to A. thaliana , early responses to Cd involve a rapid calcium spike (Zhang et al., 2023b ), followed by an increase in reactive oxygen species (ROS), a pattern also observed in other plant species (Chmielowska-Bąk et al., 2014 ). Following this initial sensing event, hormone signaling can induce changes in gene expression. Consistent with this hypothesis, the largest cluster of GO terms in roots comprised 19 biological process (BP) categories, including 767 differentially expressed genes (DEGs) involved in key biosynthetic and signaling pathways for ABA, IAA, strigolactone, and ethylene (Fig. 4 ). Likewise, ABA concentration increased in the roots of PA121(HA) (Fig. 7 E). Plants of the genotype TSH660(LA) were not available at the time of the hormone quantification. While acknowledging this limitation, our findings establish a foundation for future investigations into hormone signaling under Cd stress in cacao, including studies across different genotypes and experiments employing hormone inhibitors or ABA-related mutants. Cd is thought to alter water-use efficiency (WUE), prompting investigations into its link between drought tolerance and Cd accumulation in cacao (Ortiz-Álvarez et al., 2023 ). This relationship is plausible because reduced stomatal conductance lowers water loss to the atmosphere, which slows mass flow and consequently limits the uptake of solutes (Marschner and Rengel, 2011), including Cd (Page and Feller, 2015). Under our conditions, Cd significantly reduced stomatal conductance (Fig. 7 A-B). This result agrees with previous publications that have reported negative effect of Cd on transpiration in cacao (dos Santos et al., 2020 ; Barroso et al., 2023 ). Both studies also reported a reduction in photosynthesis, suggesting another unintended effect of forced stomatal closure. Under our experimental conditions, photosynthesis remained unchanged (Fig. 7 C–D), likely due to the much shorter treatment duration. To further explore the link between Cd exposure and WUE, we analyzed a previously published transcriptome data of cacao drought response (CDR) (Kulesza et al., 2024 ) where, similarly to cacao Cd response, we observed a strong correlation between the log2-fold changes of ABA-related genes, including LEA and PYL . However, some differences emerged. For instance, Cd affected the expression of nine IAA/ARP genes, while only six were differentially expressed in the CDR; of those, only three showed similar regulation patterns. A comparable trend was observed in the ethylene response factor ( ERF ) gene family. Additionally, transcriptional changes associated with reduced water availability were reflected in the largest GO term cluster in leaves, identified as “cellular response to heat” (Table 3 ). Within this cluster, induction of Eceriferum gene expression in leaves was observed, indicative of potential enhanced cutin biosynthesis and cuticular thickening, processes that likely contribute to reduced water loss due to transpiration. Furthermore, key enzymes for raffinose synthesis, identified as carbohydrate metabolism in leaves (Fig. 6 ), galactinol synthase ( GOLS1 ), raffinose synthase ( RS ), and galactosyltransferase ( GalT ) (Elsayed et al., 2014 ), were significantly upregulated. Seven additional GalT and RS genes (Table S2 ) exhibited similar expression patterns to those observed in the cacao drought response. Stagnation of mass flow alone may not suffice to limit Cd uptake, as the acquisition of most micronutrients (e.g., Fe, Mn, Zn, Cu) predominantly occurs via active transport, enabling efficient assimilation even at low external concentrations. TcIRT1 , a key gene in Strategy I Fe uptake (Dashner, 2024 ), was strongly downregulated in roots: 48-fold in PA121(HA) and 22.72-fold in TSH660(LA) (Fig. 5 D). Similarly, its Arabidopsis ortholog ( AtIRT1 ) was induced under Fe deficiency but was downregulated when Fe deficiency was combined with 90 µM Cd (Connolly et al., 2003 ), and after Cd exposure alone (Herbette et al., 2006 ). Together, these findings suggest a regulatory mechanism in which the expression of Cd-permeable transporters, such as AtIRT1 and TcIRT1 , is attenuated to limit Cd uptake. ABA has also been linked to IRT1 downregulation under cadmium exposure in A. thaliana , suggesting a hormonal role in restricting Cd uptake (Shen et al., 2022 ). TcNRAMP6 and TcNRAMP5 , which mediate transmembrane transport of Zn and Cd (Ullah et al., 2018 ), exhibited differential expression. TcNRAMP6 was upregulated in both genotypes, whereas TcNRAMP5 was downregulated in TSH660 (LA) (Fig. 5 D). These patterns suggest that suppression of specific NRAMP transporters may contribute to limiting Cd uptake. Evidence from Arabidopsis NRAMP knockout lines supports this hypothesis (Cailliatte et al., 2009 ). Similarly, Cd xylem translocation was reduced in O. sativa RNAi lines (Ishimaru et al., 2012 ). A comparable trend occurs Nicotiana tabacum , which accumulates less Cd than Nicotiana rustica and downregulates NtNRAMP2 and NtNRAMP6 in response to Cd exposure (Zhang et al., 2021 ). Although further functional validation in cacao is required, repression of Cd-permeable transporters appears to be a conserved mechanism across species for restricting Cd accumulation. Among the heavy metal ATPases in cacao, only TcHMA3 has been functionally characterized to date (Moore et al., 2020b ). In our study, TcHMA3 is strongly downregulated in the roots of PA121(HA) after 48 h of Cd exposure (Fig. 5 D). This transcriptional response contrasts with AtHMA3 , which was upregulated after 30 h of exposure to 50 µM Cd (Herbette et al., 2006 ), but resembles the behavior of AtHMA2 and AtHMA4 , both of which are repressed by the transcription factors AtMYC2 and AtMYB43 following Cd exposure (Zheng et al., 2022 ; Cao et al., 2024 ). Given that AtHMA2 and AtHMA4 function as xylem loaders (Hussain et al., 2004 ) and AtHMA3 mediates vacuolar sequestration (Morel et al., 2008 ), the divergent regulation observed in cacao warrants further investigation into the evolutionary dynamics and functional specialization of the HMA family in this species. In addition, TcHMA5 (XM_007040138.2), an ortholog to the ethylene-coupled Cu transporter AtRAN1 (Li et al., 2017 ), was upregulated in the roots of TSH660(LA) (Fig. 5 D), coinciding with changes in ethylene-related gene expression and signaling. This pattern suggests that TcHMA5 may function similarly to RAN1 and is consistent with its increased expression during leaf maturation (Kulesza et al., 2024 ). Furthermore, TcHMA1 , whose Arabidopsis ortholog, AtHMA1 , contributes to Zn detoxification (Kim et al., 2009 ), was downregulated in PA121(HA) leaves. These observations highlight genotype-specific regulation of HMA transporters under Cd stress. Chelation, sequestration, and precipitation are critical processes in Cd detoxification. Nitrogen (N) and phosphorus (P) can directly precipitate (Van Belleghem et al., 2007 ), whereas sulfur (S) acts as a reducing agent in molecules such as glutathione S-transferases (GSTs), which mobilize Cd bound to glutathione (GSH) and detoxify ROS (Flores et al., 2000 ). In our study, we observed transcriptional changes in genes encoding for N, P, and S transporters (Fig. 5 B-C). Changes in abundance or chelation were not tested directly, so we limit our discussion to their transcriptional behavior. Notably, given lignin’s capacity for metal chelation, the downregulation of genes for lignin-forming proteins (Fig. 5 A) is intriguing. LFP suppression has been associated with increased levels of monolignols, such as coumarins (Abdur Rahim et al., 2022 ). This raises an important question regarding the role of monolignols in the Cd response: whether they act as direct coordination compounds facilitating Cd mobilization or serve as precursors required for mobilizing other elements (Tsai and Schmidt, 2017 ). In this study, no single factor was identified as the primary driver of differences in Cd uptake in cacao. However, we detected distinct differentially expressed genes (DEGs) that provide a foundation for future functional validation. The proposed model integrates observations from cacao with evidence from other species into a cohesive hypothesis involving water-use efficiency, specialized elemental transport, chelation, and detoxification. Experimental limitations, such as cacao’s long juvenile phase, strict material exchange regulations, and controlled growth requirements, also constrained the number and frequency of experiments. Several hypotheses are outlined for future research aimed at developing climate-resilient, low-Cd cacao varieties. Importantly, this work represents the first published whole-transcriptome study of Cd response for the species. In conclusion, this study reveals a coordinated physiological and molecular response in cacao aimed at mitigating Cd uptake and toxicity. This response involves hormonal signaling, reduced mass flow, modulation of nutrient and ion transport, and activation of detoxification pathways. Future research should focus on validating this model through investigations of cellular redox dynamics, monolignol-mediated chelation, root structural adaptations, and controlled phytohormone or inhibitor applications. Given the substantial overlap between drought and Cd responses, integrating not only both stressors (Ortiz-Álvarez et al., 2023 ) but also multiple kinds of omics may accelerate the development of climate-resilient, low-Cd cacao varieties. Finally, the molecular features identified here represent promising targets for marker-assisted selection and gene-editing strategies in cacao improvement. Declarations Conflict of Interest The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. Funding This work was funded by the “Ministerio de Ciencia, Tecnología e Innovación de Colombia” Agreements TV-18 and TV-19 through the “Corporación Colombiana de Investigación Agropecuaria” (AGROSAVIA), under the project: “Selección de parentales de cacao por resistencia a enfermedades y estrés hídrico, productividad, compatibilidad, menor absorción de cadmio y calidad”, ID 1000429, by the Pennsylvania State University College of Agricultural Sciences, the Huck Institutes of the Life Sciences, the Endowed Program in the Molecular Biology of Cacao and USDA Hatch appropriations under Project #PEN05003 and Accession #7007428 and Project #PEN4879 and Accession #7005892. Acknowledgments The authors would like to acknowledge the Huck Institutes' Metabolomics Core Facility (RRID: SCR_023864) for the use of the Sciex ZenoTOF 7600 LC-MS and Sergei Koshkin for helpful discussions, the team at USDA, ARS Tropical Agriculture Research Station in Mayagüez, Puerto Rico, for their service in providing cacao pods for our experiment, and Dr. Naomi Altman for supporting the statistical model design. They would also like to acknowledge BioRender® for providing a template for Figure 8, and OpenAI's ChatGPT and Grammarly for writing refinement and grammatical editing. Author Contributions PD-D designed the research, contributed new laboratory methods and assays, assembled the transcriptome, analyzed data, and wrote the paper. FMM-B, MG and SM designed the physiological experiments. FMM-B performed and analyzed the physiological experiments, contributed new analytical methods for phytohormone purification, contributed to the transcriptome assembly, contributed new analytical and computational tools, analyzed data, prepared all figures, and wrote the paper. IA and NC contributed to the transcriptome assembly and analyzed data. MG and SM participated in the interpretation of the results and contributed to writing the manuscript. ACM designed the research. CR-M performed and set up greenhouse experiments to measure growth, Cd concentration, RNA purification, and sampled material. RY designed the research, collected samples, analyzed data, and contributed to writing the manuscript. Data Availability Statement The reads used in the current study are available at GenBank (https://www.ncbi.nlm.nih.gov/genbank/) under the BioProject ID: PRJNA943175. The Licor 6400XT output and cleaned data used for gas exchange analyses are available on Zenodo (https://doi.org/10.5281/zenodo.17316758.). The scripts and analytical workflows used for data cleaning, statistical modeling, and figure generation are available in the associated GitHub repository at https://github.com/FranciscoMenendez/cacao-cadmium-response. The sequences obtained in this project belong to the Colombian State, as the country of origin of the genetic material, in accordance with the Convention on Biological Diversity, the Nagoya Protocol, and Andean Decision 391. 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New Phytologist 234: 884–901 Supplementary Files FigureS1pvaldoff.pdf FigureS2MolecularFunctionClustersinRoots48h.pdf FigureS3LeafKeggheatmap.pdf FigureS4ConvergentDivergentTop5.pdf SupplementarytablesS1S8DelgadilloMenendezplantsoil.xlsx Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Major revisions 23 Mar, 2026 Reviewers agreed at journal 02 Feb, 2026 Reviewers invited by journal 02 Feb, 2026 Editor invited by journal 20 Jan, 2026 Editor assigned by journal 20 Jan, 2026 First submitted to journal 14 Jan, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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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-8509096","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":584202043,"identity":"9194feef-f2cf-4a58-89ee-3fb7bc789043","order_by":0,"name":"Paola Delgadillo-Durán","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Paola","middleName":"","lastName":"Delgadillo-Durán","suffix":""},{"id":584202044,"identity":"d9d91065-e5a1-48af-905f-9bfdeda677d4","order_by":1,"name":"Francisco Miguel Menéndez-Burns","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Francisco","middleName":"Miguel","lastName":"Menéndez-Burns","suffix":""},{"id":584202045,"identity":"cd8587ed-3056-47dd-b775-7f1a2d180f41","order_by":2,"name":"Caren Rodríguez-Medina","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Caren","middleName":"","lastName":"Rodríguez-Medina","suffix":""},{"id":584202046,"identity":"58d1afd9-9286-4e46-a006-744208df91a7","order_by":3,"name":"Andrea Constanza Montenegro","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Andrea","middleName":"Constanza","lastName":"Montenegro","suffix":""},{"id":584202047,"identity":"5e715975-3228-4d8a-9543-162ebe134075","order_by":4,"name":"Albert Istvan","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Albert","middleName":"","lastName":"Istvan","suffix":""},{"id":584202048,"identity":"3f014c01-4113-4aa7-bcbd-4cc2e8877dd4","order_by":5,"name":"Mark J. 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11:56:55","extension":"xlsx","order_by":9,"title":"","display":"","copyAsset":false,"role":"supplement","size":55840548,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementarytablesS1S8DelgadilloMenendezplantsoil.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-8509096/v1/544a90d2c9910cd6ac12e961.xlsx"}],"financialInterests":"","formattedTitle":"Molecular and Physiological Mechanisms of the Cadmium Response in Seedlings of Two Theobroma cacao L. Genotypes","fulltext":[{"header":"Introduction","content":"\u003cp\u003eCadmium (Cd), a heavy metal element with acute toxicity to humans, has been detected in cacao seeds from several Latin American and Caribbean countries at levels exceeding the EU regulatory limit (Meter et al., \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Cd accumulation in edible plant tissues poses a significant risk to human health. In plants, heavy metal stress has driven the evolution of coping mechanisms such as sequestration, chelation, compartmentalization, and exclusion from the stele via physical barriers (Lux et al., \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). Cd enters plants primarily through the roots and is redistributed via transport pathways shared with essential micronutrients (Lux et al., \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Rai et al., \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Sensitivity to Cd is typically characterized by pronounced growth inhibition and strong molecular responses (Rui et al., \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Feng et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Cd tolerance, in contrast, refers to the ability to maintain growth despite high Cd exposure without necessarily hyperaccumulating the metal (Ernst et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). For food crops, an ideal phenotype would combine normal growth on Cd-contaminated soils with the ability to exclude Cd from edible tissues (Wang et al., \u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eCd movement toward the root stele occurs primarily by mass flow (Barber, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e1995\u003c/span\u003e; Sterckeman et al., \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). Several micronutrient transporters have been functionally validated in cacao, including members of the NRAMP family, TcNRAMP6 and TcNRAMP5, as well as TcHMA3, which mediate Zn and Cd transmembrane transport (Ullah et al., \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Moore et al., \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2020a\u003c/span\u003e). Similarly, TcIRT1 has been shown to facilitate the uptake of Cd\u003csup\u003e2+\u003c/sup\u003e and Fe\u003csup\u003e2+\u003c/sup\u003e (Dashner, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Beyond transport, structural components, such as lignin, also play a role in Cd stress responses. Lignin, a major secondary cell wall component, binds positively charged particles (Parrotta et al., \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2015\u003c/span\u003e), and its biosynthesis is commonly upregulated in plants in response to Cd exposure (Yang et al., \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Kov\u0026aacute;čik and Klejdus, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Lux et al., \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Elobeid et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Rui et al., \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Subcellular localization of Cd in \u003cem\u003eArabidopsis thaliana\u003c/em\u003e roots suggests that Cd precipitates with sulfur (S) in the endodermis and with phosphorus (P) in the apoplast (Van Belleghem et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). Cd's high affinity for thiol groups could explain why sulfur uptake often increases following Cd treatment (Ernst et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). High-affinity sulfur transporters (\u003cem\u003eSULTRs\u003c/em\u003e) are upregulated after Cd treatment in \u003cem\u003eA. thaliana\u003c/em\u003e (Herbette et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2006\u003c/span\u003e), \u003cem\u003eOryza sativa\u003c/em\u003e (Dubey et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2014\u003c/span\u003e), and other species (Verbruggen et al., \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e2009\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eEarly signaling responses to Cd stress include a rapid spike in calcium levels in \u003cem\u003eA. thaliana\u003c/em\u003e (Zhang et al., \u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e2023a\u003c/span\u003e), followed by an increase in reactive oxygen species (ROS), a pattern also observed in tobacco, pea, and alfalfa (Chmielowska-Bąk et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). ROS accumulation in response to Cd is time- and dose-dependent, as shown in soybean roots (P\u0026eacute;rez-Chaca et al., \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) and in \u003cem\u003eNicotiana tabacum\u003c/em\u003e cells, where ROS originate from multiple subcellular locations (Garnier et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). Antioxidant defenses are activated in parallel, including regulation of glutathione-S transferase (\u003cem\u003eGST\u003c/em\u003e) genes in \u003cem\u003eA. thaliana\u003c/em\u003e (Herbette et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2006\u003c/span\u003e), \u003cem\u003eCosmos bipinnatus\u003c/em\u003e (Liu et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), and \u003cem\u003eOcimum gratissimum\u003c/em\u003e (Wang et al., \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e2023a\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eHormonal modulation is another hallmark of Cd stress. Abscisic acid (ABA) levels increase in Solanum tuberosum roots (Stroiński et al., \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2013\u003c/span\u003e)d \u003cem\u003esativa\u003c/em\u003e leaves within 72 h of Cd treatment (Hsu and Kao, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2003\u003c/span\u003e). Ethylene production rises in \u003cem\u003eGlycine max\u003c/em\u003e roots (6\u0026ndash;24 h) (Chmielowska-Bak et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), \u003cem\u003ePisum sativum\u003c/em\u003e (at 14 days) (Rodriguez-Serrano et al., \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2009\u003c/span\u003e)d \u003cem\u003ethaliana\u003c/em\u003e leaves (24 h) (Schellingen et al., \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Conversely, indole-3-acetic acid (IAA) levels decrease in \u003cem\u003eA. thaliana\u003c/em\u003e roots (7 days) and \u003cem\u003ePopulus trichocharpa\u003c/em\u003e stems (24 days) (Chmielowska-Bąk et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2014\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn our study, we observed differences in gene expression between control and Cd-treated plants, as well as between two genotypes differing in Cd uptake. We also propose a potential link between the observed molecular responses and hormone accumulation in leaves of young cacao plants. Our results could provide a basis for identifying markers for marker-assisted selection and targets for gene editing to develop cacao varieties with reduced Cd accumulation.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cp\u003ePlant material and growth conditions\u003c/p\u003e \u003cp\u003ePlants used for Cd concentration measurement, growth parameters, and RNA purification were grown in the AGROSAVIA Research Center located in Palmira, Valle del Cauca, Colombia (3\u0026deg;31'12 \"N, 76\u0026deg;19'50''W at ~\u0026thinsp;100 m.a.s.l.), with an average annual temperature of 26\u0026deg;C and relative humidity of 65%. Plants were grown from seeds obtained from two clonally propagated mother plants. Genotypes TSH660 and PA121 were selected based on differences in Cd accumulation observed in their progeny during an initial hydroponic experiment (Hern\u0026aacute;ndez-Varela et al., 2025, in preparation). Open-pollinated seeds from the mother plants of both genotypes were germinated in sand, grown for two months in a greenhouse, and transferred to 150 L containers with half-strength Hoagland's solution (Hoagland and Arnon, 1950) (7.5 mM N, 3.5 mM K, 2.5 mM Ca, 0.5 mM P, 0.1 mM S, 1 mM Mg, 1.01 mM Fe, 0.5 mM B, 0.5 mM Mn, 0.05 mM Zn, 0.02 mM Cu, and 0.01 mM Mo). For transcriptome analysis, seedlings were grown in three individual 150 L tanks, each housing one plant of each genotype, totaling three plants per genotype. After four weeks, Cd(NO\u003csub\u003e3\u003c/sub\u003e)\u003csub\u003e2\u003c/sub\u003e was added to a concentration of 10 ppm Cd (~\u0026thinsp;0.089 mM Cd), increasing total nitrogen (N) by 0.027 mM. After two months of Cd exposure, Cd concentration in leaves and roots, and plant growth parameters were measured.\u003c/p\u003e \u003cp\u003ePlants used for gas exchange and phytohormone quantification were grown at The Pennsylvania State University, University Park, PA, USA, in a greenhouse with controlled conditions: 16 hours at 5355.9 Lux (SD\u0026thinsp;=\u0026thinsp;5516.9 Lux), 29.82\u0026deg;C (SD\u0026thinsp;=\u0026thinsp;5.9\u0026deg;C), and humidity at 73.84% RH (SD\u0026thinsp;=\u0026thinsp;15.43% RH). Forty-eight seeds from open-pollinated PA121 mother plants were obtained from the USDA, ARS Tropical Agriculture Research Station in Mayag\u0026uuml;ez, Puerto Rico. They were germinated in 32-Star Deep Plug Trays (T.O. Plastics, Clearwater, MN) filled with sand and misted for 2 minutes every 8 minutes. Plants were transferred after a week to 7 in D40H Deepots\u0026trade; (Stuwe \u0026amp; Sons, Tangent, Oregon) with two drippers (flow rate of 22 mL minute\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e), and fertigated with a modified Hoagland's solution (16 mM N, 6 mM K, 4 mM Ca, 2 mM P, 1 mM S, 1 mM Mg, 0.00537 mM Fe, 0.05 mM Cl, 0.025 mM B, 0.002 mM B, 0.002 mM Zn, 0.0005 mM Cu, 0.00350 mM Mo) twice a day at 8 a.m. and 6 p.m. for 2 minutes each time for 3 months before 48 plants were randomly assigned to 3 treatment levels (n\u0026thinsp;=\u0026thinsp;16) of Cd\u003csup\u003e2+\u003c/sup\u003e ion (added CdCl\u003csub\u003e2)\u003c/sub\u003e: ~0.055 mM (6.13 ppm), ~\u0026thinsp;0.1096 mM (12.26 ppm) or without Cd\u003csup\u003e2+\u003c/sup\u003e treatment.\u003c/p\u003e \u003cp\u003eCd Analysis\u003c/p\u003e \u003cp\u003eCd concentrations were measured at the AGROSAVIA Research Center, Tibaitat\u0026aacute; (Mosquera, Colombia) using inductively coupled plasma optical emission spectrometry (ICP-OES Thermo Scientific ICAP 6500) following a modified method of the US EPA (US Environmental Protection Agency, \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e1996\u003c/span\u003e; US Environmental Protection Agency, \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). Calibration curves were performed using the standard reference material from the National Institute of Standards and Technology, a solution of 1000 mg/L Cd prepared by digesting Cd(NO₃)₂ in 0.5 mol/L HNO₃ (Certipur\u0026reg;). Calibration curves were performed using reference cacao material from genotype WEPAL IPE 965 (WEPAL, \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) provided by Wageningen Agricultural University (Netherlands).\u003c/p\u003e \u003cp\u003eTissue sampling, RNA purification, RNA‑Seq library preparation, and sequencing\u003c/p\u003e \u003cp\u003eLeaves at developmental stage C (Fister et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) were excised from plants once before the application of Cd (time point 0) and then 24 and 48 hours after the application of Cd (AC), then immediately frozen in liquid nitrogen, and stored at -80 \u0026ordm;C. Root tissues were sampled similarly from the same plants at 0 and 48 hours. One hundred mg of tissue from each sample was ground in liquid nitrogen using a mortar and pestle and used to purify total RNA with the PureLink\u0026trade; Plant RNA Reagent, following the protocol of Yockteng \u003cem\u003eet al\u003c/em\u003e. (2013). RNA concentrations were determined spectrophotometrically using a NanoDrop\u0026reg; 2000 (ThermoScientific). RNA was separated on a 1% agarose gel and stained with GelRed\u0026reg; (Biotium) to confirm RNA integrity. Barcoded libraries were made from 1 \u0026micro;g of RNA using the TruSeq RNA Library Prep Kit v2, following the manufacturer's Instructions (Illumina, San Diego, CA). The quality of each library was assessed using a high-sensitivity DNA kit on an Agilent TapeStation 4200 (Agilent Technologies, Santa Clara, CA). In total, 18 libraries from leaf tissue and 12 from root tissue were constructed and sequenced using a 150 bp paired-end strategy on an Illumina HiSeq X system, dedicating one lane to each replicate tank, targeting a 300 bp insert size. Sequencing was performed at Macrogen Inc. (Seoul, South Korea).\u003c/p\u003e \u003cp\u003eTranscriptome assembly and read mapping\u003c/p\u003e \u003cp\u003eAdapters and low-quality reads were removed using Trimmomatic (Bolger, Lohse, and Usadel, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2014\u003c/span\u003e), and the quality of the remaining reads was verified using FastQC (Andrews, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). Filtered reads were mapped using Hisat2 (Kim et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) to a GFF annotation containing the last exon of each gene model of Criollo B97 from Belize V2 reference genome (Argout et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) (Figure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003eA-P). Fractional counts were calculated using the \u003cem\u003efeatureCounts\u003c/em\u003e package (Liao, Smyth, and Shi, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Genes with less than 10 normalized reads across samples were removed.\u003c/p\u003e \u003cp\u003eLog2 fold change calculation, filtering, and size factor estimation\u003c/p\u003e \u003cp\u003eDEGs were identified using functions from the package DESeq2 (Michael et al., \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) and an \u003cem\u003ead hoc\u003c/em\u003e R function created to minimize type I error and maximize DEG discovery. The function had three main capabilities: 1) filtering genes based on mapping events across libraries, as performed by the edgeR package (Robinson, McCarthy, and Smyth, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2010\u003c/span\u003e); 2) utilizing the row variance for the independent filtering statistic as suggested previously (Bourgon et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2010\u003c/span\u003e); 3) performing steps one and two and normalization using gene dispersion values only using libraries included in the comparison. An adjusted p-value cut-off of 0.05 was applied.\u003c/p\u003e \u003cp\u003eThe gene expression model included \"genotype\" and \"time after Cd treatment (AC)\" as the main effects and a blocking factor to account for tank-to-tank variation. The interaction between time AC and genotype was examined. Since each plant was continuously sampled throughout the experiment, each plant is nested within the interaction of the \"genotype\" and \"block\" terms. PA121 and 0 h were used as references. Another set of models without \"genotype\" was applied to compute log2-fold changes of combined genotypes (model matrix and contrast weights; Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e A-C).\u003c/p\u003e \u003cp\u003eOrtholog classification, pathway mapping, and subcellular localization prediction\u003c/p\u003e \u003cp\u003eDEGs were reciprocally blasted using CRB-BLAST (Aubry et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) to the coding sequences (CDS) of the \u003cem\u003eA. thaliana\u003c/em\u003e genome (arabidopsis.org) using three E-value cut-offs: 10\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e, 10\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e, and 10\u003csup\u003e\u0026minus;\u0026thinsp;5\u003c/sup\u003e. Gene families were then identified using PlantTribes2 (Wafula et al., \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). KEGG pathway mapping (Kanehisa et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) was performed using orthogroups identified by KOFAM KOALA (Aramaki et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Subcellular localization was predicted using DeepLoc2 (Thumuluri et al., \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eGene Ontology term enrichment analysis and clustering\u003c/p\u003e \u003cp\u003eGene Ontology (GO) terms (Ashburner et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2000\u003c/span\u003e; Aleksander et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) were assigned using Blast2GO (G\u0026ouml;tz et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). Overrepresentation analysis (ORA) was done using Fisher's hypergeometric test in the \"Fast GSEA\" package (Korotkevich, Sukhov, and Sergushichev, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) against reference genes with at least one normalized count across their respective tissue-specific libraries. GO term semantic similarity indices and clustering were performed using \"SimplifyEnrichment\" (Gu and H\u0026uuml;bschmann, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), the Rel method (Schlicker et al., \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2006\u003c/span\u003e), and the binary-cut algorithm (Mezentsev, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Graphs were produced with R packages (Wickham, \u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Gu, Eils, and Schlesner, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2016\u003c/span\u003e).\u003c/p\u003e \u003cp\u003ePhotosynthesis and Gas exchange measurements\u003c/p\u003e \u003cp\u003ePhotosynthesis (A) and gas exchange (Gs) were measured using a LI-6400 XT photosynthesis system with a Leaf Fluorescence Chamber (LCF) (Li-Cor \u0026reg;, Lincoln, NE) in survey mode. The system had a constant flow of 500 \u0026micro;mol s\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, complete desiccant bypass, reference CO\u003csub\u003e2\u003c/sub\u003e of 400 \u0026micro;mol mol\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, and light set to match the outside of the chamber at 6210 Lux. Measurements were taken at 8:00 a.m. and 1:00 p.m. for two days after the onset of the treatments.\u003c/p\u003e \u003cp\u003eHormone quantification\u003c/p\u003e \u003cp\u003eThe methods were adapted from published protocols (Trapp et al., \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Flokov\u0026aacute; et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Plants were uprooted and cleaned in water, from which fully developed E-leaves and adventitious root material were separated in super-cold conditions (dry ice). One hundred mg of frozen tissue per sample was ground in liquid nitrogen. One mL of extraction buffer (7 parts methanol to 3 parts water, with 5 nM of labeled standards) was added, samples were vortexed and left to shake for 30\u0026rsquo;/4\u0026deg;C. Tubes were centrifuged at 16,000x\u003cem\u003eg\u003c/em\u003e for 5\u0026rsquo;/4\u0026deg;C, and the supernatant was freeze-dried with centrifugation. Samples were resuspended in fresh extraction buffer without internal standards using sonication in an ice bath for 10 minutes, centrifuged at 16,000x\u003cem\u003eg\u003c/em\u003e for 5\u0026rsquo;/4\u0026deg;C, and the supernatant was analyzed by The Huck Institutes' Metabolomics Core Facility (RRID: SCR_023864) using a Sciex ZenoTOF 7600 LC-MS.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eGenotypic variation in Cd uptake in roots and leaves of hydroponically grown cacao seedlings\u003c/p\u003e \u003cp\u003eThe Cd concentrations in tissues of 2 month-old plants treated with 10 ppm Cd were significantly higher than those of the controls, both in leaves (one-sided t-test, t\u0026thinsp;=\u0026thinsp;4.2205, \u003cem\u003edf\u003c/em\u003e\u0026thinsp;=\u0026thinsp;19, p\u0026thinsp;=\u0026thinsp;2.315x10\u003csup\u003e\u0026minus;\u0026thinsp;4\u003c/sup\u003e) and in roots (one-sided t-test, t\u0026thinsp;=\u0026thinsp;16.459, \u003cem\u003edf\u003c/em\u003e\u0026thinsp;=\u0026thinsp;20, p\u0026thinsp;=\u0026thinsp;2.05x10\u003csup\u003e\u0026minus;\u0026thinsp;13\u003c/sup\u003e) (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA, B). On average, Cd concentration in the roots was higher than in leaves, regardless of treatment (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\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\u003eCd concentration and mass of plants treated with Cd\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTissue (Leaves v Roots)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGenotype\u003c/p\u003e \u003cp\u003e(PA121 v TSH660) (N)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCd treatment (10 ppm vs 0 ppm)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCd measured (ppm) (95% C.I)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCd measured (ppm)\u003c/p\u003e \u003cp\u003e(95% C.I)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eDry weight (g) (95% C.I)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eDry weight (g) (95% C.I)\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\u003eLeaves\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePA121 (N\u0026thinsp;=\u0026thinsp;3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0 ppm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.3 (C.I. 0.27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.43 (C.I. 0.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e25.3 (C.I. 6.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e18.3 (C.I. 9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTSH660 (N\u0026thinsp;=\u0026thinsp;3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.5 (C.I. 0.98)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e11.2 (C.I. 13.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePA121 (N\u0026thinsp;=\u0026thinsp;9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e10 ppm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e97.4 (C.I. 38.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e52.3 (C.I. 25.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7.3 (C.I. 2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e6.7 (C.I. 1.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTSH660 (N\u0026thinsp;=\u0026thinsp;11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15.3 (C.I. 13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.2 (C.I. 1.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eRoots\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePA121 (N\u0026thinsp;=\u0026thinsp;3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0 ppm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.5 (C.I. 22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e4.6 (C.I. 6.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7.6 (C.I. 5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e5.97 (C.I. 2.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTSH660 (N\u0026thinsp;=\u0026thinsp;3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.7 (C.I. 1.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.3 (C.I. 5.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePA121 (N\u0026thinsp;=\u0026thinsp;10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e10 ppm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1416.3 (C.I. 118.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e1143.1 (C.I. 144.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.4 (C.I. 1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e2.5 (C.I. 0.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTSH660 (N\u0026thinsp;=\u0026thinsp;11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e895.1 (C.I. 122.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.6 (C.I. 0.5)\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\u003eIn Cd-treated PA121 roots, the mean Cd concentration was ~\u0026thinsp;1.6-fold higher than the average recorded for Cd-treated TSH660 roots (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA). The average concentration in Cd-treated PA121 leaves was ~\u0026thinsp;6.4-fold higher than the average recorded for Cd-treated TSH660 leaves (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB). Cd concentrations in tissues from the two genotypes grown at 0 ppm Cd were not significantly different (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). These results demonstrate that under our experimental conditions, progeny from open-pollinated PA121 accumulated more Cd in leaf and root tissues than those from TSH660. We designated the progeny from PA121 as the high accumulator, PA121(HA), and the progeny from TSH660 as the low accumulator, TSH660(LA).\u003c/p\u003e \u003cp\u003eExposure to 10 ppm Cd significantly stunted plant growth, resulting in similar overall biomass between the two genotypes (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e; Figs.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC and D). Under control conditions (0 ppm Cd), PA121 exhibited significantly greater leaf mass than TSH660 (one-sided t\u0026thinsp;=\u0026thinsp;3.9361, df\u0026thinsp;=\u0026thinsp;2.8835, p\u0026thinsp;=\u0026thinsp;0.0157) and marginally greater root mass (one-sided t\u0026thinsp;=\u0026thinsp;1.8287, df\u0026thinsp;=\u0026thinsp;3.952, p\u0026thinsp;=\u0026thinsp;0.07115).\u003c/p\u003e \u003cp\u003eDifferential gene expression after cadmium treatment\u003c/p\u003e \u003cp\u003eThe 18 transcriptome libraries averaged over 16\u0026nbsp;million reads per sample, with an average mapping rate of 85.7%. Differentially expressed genes (DEGs) were obtained from 14 linear contrasts (Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003eB-C). The number of DEGs from the main contrasts, the percent of upregulated DEGs of these contrasts, and selected intersections are represented in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. A table with all differential expression results is presented in Table \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003eAfter 48h of Cd treatment, we identified 4185 shared DEGs in roots (shared response, Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). The shared response in leaves had significantly fewer DEGs than in roots; in leaves, 1162 at 24h AC and 1999 at 48h AC (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). In the shared response, the number of downregulated DEGs was higher in the roots (2344/4185 DEGs or 56%). Conversely, upregulation was higher in leaves (1127/1999 DEGs or 56.4%), deviating significantly from a 1:1 expectation (X\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;82.21, df\u0026thinsp;=\u0026thinsp;1, p-value\u0026thinsp;\u0026lt;\u0026thinsp;2.2x10\u003csup\u003e\u0026minus;\u0026thinsp;16\u003c/sup\u003e, Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC).\u003c/p\u003e \u003cp\u003ePA121(HA) had 2297 DEGs in roots 48h AC, and 1538 and 604 in leaves 48h and 24h AC, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). The number of downregulated DEGs was greater than expected in roots, while in leaves, upregulated DEGs were greater than expected (X\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;112.45, df\u0026thinsp;=\u0026thinsp;1, p-value\u0026thinsp;\u0026lt;\u0026thinsp;2.2x10\u003csup\u003e\u0026minus;\u0026thinsp;16\u003c/sup\u003e). On the other hand, TSH660(LA) had 2396 DEGs in roots 48h AC, slightly higher than in PA121(HA) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). In leaves, TSH660(LA) showed 180 DEGs at 48h and 57 DEGs at 24h, fewer than PA121(HA), which showed 547 and 1358 DEGs at 24h and 48h, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). Nevertheless, the number of downregulated DEGs in TSH660(LA) roots still deviated significantly from a 1:1 expectation (X\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;11.849, df\u0026thinsp;=\u0026thinsp;1, p-value\u0026thinsp;=\u0026thinsp;0.0005771) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC).\u003c/p\u003e \u003cp\u003eGO Term enrichment analysis\u003c/p\u003e \u003cp\u003eTo gain insight into the mechanisms activated during Cd-response, enriched Gene Ontology (GO) terms from ten predefined sets of DEGs were identified (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, Table \u003cspan refid=\"MOESM3\" class=\"InternalRef\"\u003eS3\u003c/span\u003e). In roots, the enriched GO terms in these sets of DEGs were combined, resulting in a total of 199 unique Biological Process (BP), 90 Molecular Function (MF), and 41 Cellular Component (CC) GO terms. In leaves, there were 63 BP, 18 MF, and 7 CC unique GO terms. After calculating semantic similarities and removing GO terms with zero similarity, 37 BP, 27 MF, and 7 CC remained in roots, and 14 BP in leaves. BP GO was prioritized because it exhibited the most enriched GO terms and provided the most informative GO categories. BP GO produced eight clusters, with at least two GO terms per cluster, a relaxed criterion that ensured maximal retention of GO terms (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). The clustering analysis for MF is presented in Figure \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e. A second hypergeometric test compared GO term names in each cluster to the names within their ontology, identifying enriched keywords used to label each cluster (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA, B).\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\u003e\u003cb\u003eGO term enrichment results.\u003c/b\u003e The column (DEG Set) states the comparison, the second column lists the number of DEGs, followed by the number of enriched BP GO in roots, and the third column lists the enriched BP GO in leaves. The 10 sets included are those that had enriched BP GO (non-zero).\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eN\u0026deg;\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDEG Set\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDEG / Enriched BP GO Roots\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDEG / Enriched BP GO Leaves\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTc48h/0h (shared response)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4185 / 120\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1999 / 30\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePA121HA 48h/0h\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2297 / 86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1538 / 16\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTSH660LA 48h/0h\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2396 / 64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e180 / 11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIntersection of 2 \u0026amp; 3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1378 / 51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e114 / 9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eComplements TSH660LA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1018 / 4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e66 / 0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eComplements PA121HA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e919 / 0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1424 / 9\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 \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\u003eGO term clusters\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\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=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eClusters in Root\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCluster Name\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNumber\u003c/p\u003e \u003cp\u003e(GO terms)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eGenotype\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBlue light abscisic activated defense and ion response signaling pathway\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBoth\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCatabolic process\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBoth\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eResponse\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBoth\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUnnamed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBoth\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSignaling\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHA only (PA121)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIon transport\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBoth\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDephosphorylation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBoth\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCell\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eClusters in Leaf\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCluster Name\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eProtein refolding\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBoth\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCellular heat response\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBoth\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCell detoxification\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLA only (TSH660)\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\u003eCd activation of indole acetic acid, abscisic acid, melatonin, strigolactone, and ethylene biosynthetic and signaling pathways in roots\u003c/p\u003e \u003cp\u003eDEGs contributing to each enriched BP GO term in the \"blue light-activated abscisic acid, defense, and ion response\" cluster were classified into orthologous protein families and mapped to KEGG pathways. Gene families identified using KOFAM were consolidated with those identified using PlantTribes2. Genes were mapped to the biosynthetic steps and signal transduction components of various phytohormones, including indole-3-acetic acid (IAA or Auxin), abscisic acid (ABA), strigolactones, melatonin (Mt), ethylene, and strictosidine (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Mapping results are presented in Table \u003cspan refid=\"MOESM4\" class=\"InternalRef\"\u003eS4\u003c/span\u003e.\u003c/p\u003e\n\u003ch3\u003eIndoles\u003c/h3\u003e\n\u003cp\u003eIn the indole biosynthetic pathway (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA and D), two orthologs of a terminal amino acid transferase (\u003cem\u003eTAA\u003c/em\u003e) gene family, which deaminases Trp to indole-3-pyruvic acid (IPA), XM_007019556.2 and XM_007019553.2, were downregulated. The first one was significantly downregulated 21-fold (-4.39 log\u003csub\u003e2\u003c/sub\u003e-fold) when combining both genotypes, and the second one was downregulated 1.7-fold (-0.8 log\u003csub\u003e2\u003c/sub\u003e-fold) only in PA121(HA) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA). Additionally, seven downstream signaling components of the IAA, members of the \u003cem\u003eAUX/IAA\u003c/em\u003e gene family, were upregulated, except for XM_007034894.2, an ortholog of \u003cem\u003eAtIAA14\u003c/em\u003e, which was downregulated\u0026thinsp;~\u0026thinsp;4-fold (Table \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eD). A \u003cem\u003eSNAT\u003c/em\u003e gene that acetylates serotonin (XM_007045624.2) was upregulated 3.11-fold (1.64 log\u003csub\u003e2\u003c/sub\u003e-fold) at 48h AC in TSH660(HA) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA). One candidate of a caffeoyl-methyltransferase (\u003cem\u003eCOMT\u003c/em\u003e, XM_018121419.1) was downregulated 2.5-fold (-1.33 log\u003csub\u003e2\u003c/sub\u003e-fold) in both genotypes, while another (XM_018120814.1) was upregulated 43.1-fold (5.4 log\u003csub\u003e2\u003c/sub\u003e-fold) in TSH660(LA). A marked difference was observed between TSH660(LA) and PA121(HA) strictosidine synthase (\u003cem\u003eSS\u003c/em\u003e) genes, \u003cem\u003eSS1\u003c/em\u003e and \u003cem\u003eSS2\u003c/em\u003e. Changes in expression occurred only in TSH660(HA). The \u003cem\u003eSS1\u003c/em\u003e gene XM_018120572.1 was downregulated 2.54-fold (-1.3 log\u003csub\u003e2\u003c/sub\u003e-fold) and three genes, XM_018126632.1, XM_018127382.1, and XM_007046480.2, were upregulated 3.11-fold (1.6 log\u003csub\u003e2\u003c/sub\u003e-fold), 4-fold (2 log\u003csub\u003e2\u003c/sub\u003e-fold), and 4.6-fold (2.2 log\u003csub\u003e2\u003c/sub\u003e-fold) respectively.\u003c/p\u003e\n\u003ch3\u003eApocarotenoids\u003c/h3\u003e\n\u003cp\u003eSeveral key genes encoding enzymes central to the ABA biosynthetic pathway were strongly upregulated in response to Cd treatment (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB and F). The shared response identified a 5.9-fold (2.56 log\u003csub\u003e2\u003c/sub\u003e-fold) upregulation of an ortholog to β-carotene hydrolase 1 (\u003cem\u003eBCH1\u003c/em\u003e), XM_007038743.2, and a 1.76-fold (0.81 log\u003csub\u003e2\u003c/sub\u003e-fold) upregulation of an ortholog to zeaxanthin epoxidase (\u003cem\u003eZEP\u003c/em\u003e), XM_007028495.2. Two orthologs of 9-cis epoxy dioxygenase (\u003cem\u003eNCED\u003c/em\u003e), XM_007022118.2 and XM_018118862.1, were upregulated 7.5-fold (2.9 log\u003csub\u003e2\u003c/sub\u003e-fold) and 8.6-fold (3.1 log\u003csub\u003e2\u003c/sub\u003e-fold), respectively. Three xanthoxin dehydrogenases (\u003cem\u003eXDH\u003c/em\u003e) were upregulated, and three were downregulated. Notably, XM_007027846.2 was upregulated 13.5-fold (3.21 log\u003csub\u003e2\u003c/sub\u003e-fold) in TSH660(LA). In the indole aldehyde oxygenase (\u003cem\u003eIAO\u003c/em\u003e) family, XM_007015509.2 was upregulated 2.3-fold (1.22 log2-fold), while XM_018127404.1 was downregulated 6.5-fold (-2.7 log\u003csub\u003e2\u003c/sub\u003e-fold). One ABA-hydroxylase (\u003cem\u003eABAH\u003c/em\u003e) candidate gene, XM_007016306.2, was upregulated 20.2-fold (4.34 log2-fold) in both genotypes, and another, XM_007042365.2, 8.6-fold (3.11 log\u003csub\u003e2\u003c/sub\u003e-fold) only in PA121(HA). On the other hand, one \u003cem\u003eABAH\u003c/em\u003e, XM_018116623.1, was downregulated 4.8-fold (-2.26 log\u003csub\u003e2\u003c/sub\u003e-fold) in PA121(HA) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB and F). Furthermore, signaling components downstream of ABA, the ABA receptor gene family \u003cem\u003ePYL\u003c/em\u003e, XM_007008792.2, XM_007024407.2, XM_007026527.2, and XM_018127083.1, were downregulated 4.92-fold (-2.3 log\u003csub\u003e2\u003c/sub\u003e-fold), 31.2-fold (~ -5 log\u003csub\u003e2\u003c/sub\u003e-fold), 4.1-fold (-2.0 log\u003csub\u003e2\u003c/sub\u003e-fold), and 3.4-fold (-1.8 log\u003csub\u003e2\u003c/sub\u003e-fold), while one, XM_007051517.2, was upregulated 2.9-fold (1.5 log\u003csub\u003e2\u003c/sub\u003e-fold) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eF).\u003c/p\u003e \u003cp\u003eFinally, a key step in strigolactone synthesis, the \u003cem\u003eCCD8\u003c/em\u003e gene, also known as \u003cem\u003eMAX4\u003c/em\u003e (XM_007052456.2), was upregulated 2.7-fold (1.43 log\u003csub\u003e2\u003c/sub\u003e-fold) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB). Furthermore, two downstream receptors of strigolactones (Chen, Nelson, and Shukla, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), one annotated as a D14, ortholog of \u003cem\u003eAtKAI2\u003c/em\u003e, XM_018128515.1, was downregulated 1.9-fold (~\u0026thinsp;0.9 log\u003csub\u003e2\u003c/sub\u003e-fold), and another \u003cem\u003eMAX2\u003c/em\u003e ortholog, XM_018123475.1, was upregulated 1.9-fold (0.9 log\u003csub\u003e2\u003c/sub\u003e-fold) (Table \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e).\u003c/p\u003e\n\u003ch3\u003eEthylene\u003c/h3\u003e\n\u003cp\u003eThe aminocyclopropane oxidase (\u003cem\u003eACO\u003c/em\u003e) XM_007019139.2 was downregulated 6.45-fold (-2.69 log\u003csub\u003e2\u003c/sub\u003e-fold) in the shared response. The \u003cem\u003eACO\u003c/em\u003e XM_007026145.2 was upregulated 2.12-fold (1.08 log\u003csub\u003e2\u003c/sub\u003e-fold) in PA121(HA) and the \u003cem\u003eACO\u003c/em\u003e XM_007012805.2 was upregulated 2.43-fold (1.28 log\u003csub\u003e2\u003c/sub\u003e-fold) in TSH660(LA) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC and E).\u003c/p\u003e \u003cp\u003eCatabolism cluster, including regulation of GST, Lignin-forming peroxidases, ROS modulation, and sugar-mediated stress response in roots\u003c/p\u003e \u003cp\u003eThe DEGs in the second-largest cluster, \"catabolic process\" included enzymes with catabolic functions, such as peroxidases (PER), glutathione S-transferases (GST), and enzymes involved in carbohydrate degradation, as well as chitinases (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA). The PER included 31 genes annotated as lignin-forming peroxidases (\u003cem\u003eLFP\u003c/em\u003e) (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA). Of those, 25 were downregulated. In addition, 20 genes were genotype-specific to TSH660(LA) and 26 to PA121(HA), with an overlap of 17 genes between both genotypes. One \u003cem\u003eLFP\u003c/em\u003e, XM_007045286.2, was strongly upregulated 175.7-fold (7.5 log\u003csub\u003e2\u003c/sub\u003e-fold) in TSH660(LA) (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA). In contrast to most other \u003cem\u003eLFPs\u003c/em\u003e, XM_007011153.2 and XM_007011167.2 exhibited similar responses in roots and leaves (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA). The next largest family in this cluster was the GST, which contained 21 genes (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA). In the shared response, 15 were downregulated (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA). In the genotype-specific response, only ten genes were significant for TSH660(LA) and 13 for PA121(HA), with an overlap of seven genes between genotypes (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA). There were ten carbohydrate catabolism genes, ten genotype-specific to PA121(HA), and eight genotype-specific to TSH660(LA) (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA). The two DEGs that were exclusive to PA121(HA) were an alpha-glucan water dikinase (\u003cem\u003eGWD\u003c/em\u003e) gene, XM_007027585.2, and a phosphoglucan phosphatase \u003cem\u003eLSEX4\u003c/em\u003e, XM_007011190.2 (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA). Interestingly, we identified an alpha-amylase that was upregulated only in leaves of PA121(HA) (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA).\u003c/p\u003e \u003cp\u003eFinally, 17 chitinases in the catabolism cluster are represented in the shared response: 12 are specific to PA121(HA), and nine are specific to TSH660(LA), with an overlap of seven DEGs (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA). One marked difference between genotypes was the 6.7-fold (-2.8 log\u003csub\u003e2\u003c/sub\u003e-fold) downregulation of XM_007033739.2, an \u003cem\u003eEP3\u003c/em\u003e chitinase in PA121(HA) roots (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA). In leaves of PA121(HA) the endochitinases ortholog (\u003cem\u003eCHT1\u003c/em\u003e), XM_007041606.2 was 15.8-fold (3.98 log\u003csub\u003e2\u003c/sub\u003e-fold) upregulated, the endochitinases \u003cem\u003eEP3\u003c/em\u003e, XM_018119383.1 was 76.7-fold (6.3 log\u003csub\u003e2\u003c/sub\u003e-fold) upregulated, and the chitinase-2 (\u003cem\u003eCHT2\u003c/em\u003e), XM_018127043.1, was 15.4-fold (3.9-log\u003csub\u003e2\u003c/sub\u003efold) upregulated (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA).\u003c/p\u003e \u003cp\u003eIon transport clusters indicating regulation of nitrogen, sulfur, and phosphate transporters\u003c/p\u003e \u003cp\u003eThe ion transport cluster contains six sulfur (S), 21 nitrogen (N), and seven phosphate (P) transporters. This cluster also includes 16 calcium (Ca) transporters, 10 aquaporins, four annexins, and five receptor class proteins (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB). Nitrogen transporters fell into two orthogroups of \u003cem\u003eNRT1/PTR\u003c/em\u003e gene families, one containing 19 members (\u003cem\u003eNTR/PTR1\u003c/em\u003e), of which eight were downregulated (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB). \u003cem\u003eNTR1/PTR1\u003c/em\u003e had 15 genotype-specific DEGs to PA121(HA), 13 to TSH660(LA), with an overlap of ten (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA). The six S transporters belong to a single family (\u003cem\u003eSULTR\u003c/em\u003e), with four of them being downregulated. Additionally, four were genotype-specific to each, with an overlap of two (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB). P transporters had 2 DEGs in the \u003cem\u003ePHO1\u003c/em\u003e gene family and five in the \u003cem\u003eIPT\u003c/em\u003e family (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB). In the \u003cem\u003eIPTs\u003c/em\u003e, TSH660(LA) had two downregulated genotype-specific genes. In PA121(HA), while five \u003cem\u003eIPT\u003c/em\u003e genes were significantly downregulated, one \u003cem\u003eIPT\u003c/em\u003e, XM_018122229.1, was upregulated 3.9-fold (1.97 log\u003csub\u003e2\u003c/sub\u003e-fold) (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB). Membrane intrinsic proteins (aquaporins) have five tonoplast intrinsic proteins (\u003cem\u003eTIP\u003c/em\u003e), four plasma membrane intrinsic proteins (\u003cem\u003ePIP\u003c/em\u003e), and one NOD25 intrinsic protein (\u003cem\u003eNIP\u003c/em\u003e). One \u003cem\u003ePIP\u003c/em\u003e gene, XM_007016678.2 (\u003cem\u003eTcPIP2-2\u003c/em\u003e), exhibited a relatively high 2-fold (1 log\u003csub\u003e2\u003c/sub\u003e-fold) upregulation, exclusive to TSH660(LA). More Ca transporters were regulated in PA121(HA), which had seven genotype-specific DEGs compared to four in TSH660(LA). Despite this, one member of the \u003cem\u003eCAX2\u003c/em\u003e gene family, XM_007016045.2, was 15-fold (3.99-log2-fold) upregulated specifically in TSH660(LA). This contrasted with the 1.3-fold upregulation in PA121(HA), which did not pass the significance cut-off (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB). Interestingly, in leaves, this gene was genotype-specific to PA121(HA) and was downregulated 5.4-fold (-2.42 log\u003csub\u003e2\u003c/sub\u003e-fold) (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB).\u003c/p\u003e \u003cp\u003eThe potential overlap between the phosphate starvation response (PSR) in \u003cem\u003eA. thaliana\u003c/em\u003e (Wang et al., \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e2023b\u003c/span\u003e) and the ion transport cluster in the Cd response in cacao was determined using the PSR genes from Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e in Z. Wang et al. (2023). In each gene family identified using PlantTribes2, genes from either \u003cem\u003eA. thaliana\u003c/em\u003e or cacao had to all be regulated in the same manner (all upregulated or downregulated, Table \u003cspan refid=\"MOESM5\" class=\"InternalRef\"\u003eS5\u003c/span\u003e). The log\u003csub\u003e2\u003c/sub\u003e-fold averaged by gene families is plotted in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eC. In the ion transport cluster, all \u003cem\u003eCAX1\u003c/em\u003e, \u003cem\u003ePHO1\u003c/em\u003e, \u003cem\u003eCNGC\u003c/em\u003e, and \u003cem\u003eNIP\u003c/em\u003e were downregulated in cacao and upregulated in \u003cem\u003eA. thaliana\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eC). In the catabolism cluster, the peroxidases-2 (\u003cem\u003ePER2\u003c/em\u003e) and chitinases-1 (\u003cem\u003eCHT1\u003c/em\u003e) were all downregulated in the cacao, while upregulated in the \u003cem\u003eA. thaliana\u003c/em\u003e, except for the peroxiredoxin-2f gene family, which was downregulated in both (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eC).\u003c/p\u003e \u003cp\u003eMetal transporter gene families regulated by Cd in cacao\u003c/p\u003e \u003cp\u003eBy searching the cacao genome for 16 gene superfamilies involved in metal or coordination compound transmembrane transport, 82 DEGs encoding metal transporters or metal detoxification genes were identified, 75 in roots and 12 in leaves. Their subcellular localization was then predicted (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eD, Table S6). Seven were leaf-specific and 70 root-specific (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eD). Our results indicated that A Cd/Zn transporting PIB-2 \u003cem\u003eHMA\u003c/em\u003e gene (XM_018127237.1) was downregulated 1.7-fold (-0.77 log\u003csub\u003e2\u003c/sub\u003e-fold) in the leaves of the PA121(HA) 48 h AC (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eD). This protein is predicted to be localized to the cytosol membrane (CM). \u003cem\u003eTcHMA1\u003c/em\u003e (XM_007047334.2) was also downregulated 2.1-fold (1.1 log\u003csub\u003e2\u003c/sub\u003e-fold) in PA121(HA) leaves at 48h AC. In roots, the orthologs to HMA5 and RAN1 included two distinct members. The first one, \u003cem\u003eTcHMA5\u003c/em\u003e (XM_018116084.1), predicted to localize to the CM, was downregulated 2.3-fold (-1.22 log\u003csub\u003e2\u003c/sub\u003e-fold) in PA121(HA) at 48 h AC. Conversely, \u003cem\u003eTcRAN1\u003c/em\u003e (XM_007040138.2), predicted to localize to the chloroplast membrane, was upregulated 3-fold (1.6 log\u003csub\u003e2\u003c/sub\u003e-fold) in TSH660(LA) at 48h AC (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eD). \u003cem\u003eTcNRAMP6\u003c/em\u003e (XM_018122485.1) was downregulated 3.4-fold (1.77 log\u003csub\u003e2\u003c/sub\u003e-fold) in roots of both genotypes 48h AC. \u003cem\u003eTcNRAMP5\u003c/em\u003e (XM_018125489) was downregulated 9.64-fold (-3.26 log\u003csub\u003e2\u003c/sub\u003e-fold) in the roots and was genotype-specific to TSH660(LA) 48 h after Cd (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eD). The ZIP gene, \u003cem\u003eTcIRT1\u003c/em\u003e (XM_018122962.1), was strongly downregulated in response to Cd treatment in both genotypes, 76.79-fold (-6.27 log\u003csub\u003e2\u003c/sub\u003e-fold) in PA121(HA) and 39.24-fold (-5.29 log\u003csub\u003e2\u003c/sub\u003e-fold) in TSH660(LA). Additionally, PA121(HA) had one \u003cem\u003eZIP\u003c/em\u003e family member, XM_018127227.1, downregulated 2.93-fold (-1.55 log\u003csub\u003e2\u003c/sub\u003e-fold) in roots 48h AC. Plant Cd resistance (\u003cem\u003ePCRs\u003c/em\u003e) were mostly downregulated in roots, with one member (XM_018116355.1) being upregulated in the leaves of PA121(HA) (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eD). The vacuolar iron transporter (\u003cem\u003eVIT\u003c/em\u003e), XM_007042978.2, was 20-fold (-4.32 log\u003csub\u003e2\u003c/sub\u003e-fold) downregulated, and one Yellow Stripe-Leaf (\u003cem\u003eYSL\u003c/em\u003e), XM_007039100.2, was upregulated in roots of both genotypes while being downregulated in the leaves of PA121(HA) (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eD).\u003c/p\u003e \u003cp\u003eGO term clusters and DEGs mapping to TCA, carbohydrate, and fatty acid metabolic pathways\u003c/p\u003e \u003cp\u003eKEGG pathway analysis mapped 561 genes from Cellular Heat Response (CHR) leaf cluster (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB) to 236 different pathways and clustered once more using the binary-cut algorithm (Table S7 and Figure \u003cspan refid=\"MOESM3\" class=\"InternalRef\"\u003eS3\u003c/span\u003e). After this, thirty-nine genes with shared pathways were selected and used to create \u003cem\u003ead hoc\u003c/em\u003e groups related to carbohydrate metabolism (CHO), fatty acid (FA) metabolism, the tricarboxylic acid cycle (TCA), and terpenoid biosynthesis (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). Twenty-eight of the 39 genes were significantly upregulated in PA121(HA) (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). One DEG shared by both genotypes, a cupredoxin ascorbate oxidase (XM_007016622.2), was upregulated 10.3-fold (3.4 log\u003csub\u003e2\u003c/sub\u003e-fold) at 48h AC. In the terpenoid group, an \u003cem\u003eNCED\u003c/em\u003e (XM_007022118.2) was upregulated 5.6-fold (2.5 log\u003csub\u003e2\u003c/sub\u003e-fold), and a purple acid phosphatase ortholog (XM_018116461.1) was downregulated 2.6-fold (1.4 log\u003csub\u003e2\u003c/sub\u003e-fold); both genes are related to ABA signaling. The shared response in the carbohydrate cluster included a cell wall invertase 1, XM_018122432.1, which was upregulated 7-fold (2.8 log2-fold), and a beta-amylase, XM_018117250.1, downregulated 4.7-fold (2.2 log\u003csub\u003e2\u003c/sub\u003e-fold). All DEGs were specific to PA121(HA) in the fatty acid cluster. Eceriferum had two members: one downregulated (XM_018115329.1) 3-fold (-1.6 log\u003csub\u003e2\u003c/sub\u003e-fold) and another (XM_007008667.2) upregulated 10.7-fold (3.4 log\u003csub\u003e2\u003c/sub\u003e-fold). Cell wall invertases (\u003cem\u003eCWIN\u003c/em\u003e), raffinose synthase (\u003cem\u003eRS\u003c/em\u003e), and galactinol transferase (\u003cem\u003eGalT\u003c/em\u003e) were upregulated in PA121(HA) leaves. One \u003cem\u003eCWIN\u003c/em\u003e, XM_018117430.1, was downregulated in TSH660(LA) roots.\u003c/p\u003e \u003cp\u003eGenes with convergent and divergent gene expression patterns\u003c/p\u003e \u003cp\u003eIn this analysis, convergent genes were defined as those that were differentially expressed at 0 h but not at 48 h. Conversely, divergent genes were not differentially expressed at 0 h but became so at 48 h AC. In roots, 322 convergent genes and 308 divergent genes were identified. In the divergent group, 45 genes became divergent due to changes in expression in PA121(HA) and 54 genes due to changes in expression in TSH660(LA). The convergent and divergent genes in leaves were similarly identified, as 182 and 867 DEGs, respectively. In leaves, 338 genes became convergent due to changes in expression specific to PA121(HA) and six due to changes in expression specific to TSH660(LA). The convergent and divergent genes were cross-referenced to genes contributing to each semantic similarity cluster (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). The list of genes is provided in Table S8. The expression changes for the top genes in both groups were plotted by tissue in Figure \u003cspan refid=\"MOESM4\" class=\"InternalRef\"\u003eS4\u003c/span\u003e.\u003c/p\u003e \u003cp\u003eCd treatment in PA121 reduced gas exchange in cacao leaves and increased ABA concentration in roots\u003c/p\u003e \u003cp\u003eTo test whether ABA-related transcriptional changes under Cd exposure translated into physiological responses, we measured stomatal conductance (Gs), photosynthesis (A), and ABA concentrations in cacao seedlings under 0, 6, and 12 ppm Cd\u003csup\u003e2+\u003c/sup\u003e. Cd treatment had a significant effect on stomatal conductance (one-way ANOVA, p\u0026thinsp;=\u0026thinsp;0.0192), accounting for 20.8% of its variation (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eA); however, photosynthesis was unaffected (p\u0026thinsp;=\u0026thinsp;0.6151) (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eB). Tukey's post hoc test indicated that plants treated with 12 ppm Cd had significantly lower Gs than the control group at the end of the experiment (difference = -0.0119, p-adj. = 0.0145). No significant differences were observed between plants treated with six ppm Cd and the controls (difference = -0.0051, p-adj. = 0.4242) or between plants treated with 12 ppm and six ppm (difference = -0.0067, p-adj. = 0.2363) (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eA). In plants treated with 12 ppm, a significant difference in Gs was observed between the morning of the first day and the afternoon of the second day (difference = -0.0190, p\u0026thinsp;=\u0026thinsp;0.0499) (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eC). Like before, no significant changes in A were detected (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eD). After 36 hours, the mean ABA concentration in roots was significantly higher in the 12-ppm group (1.95 nM) compared to the control group (0.21 nM) (t\u0026thinsp;=\u0026thinsp;4.0822, df\u0026thinsp;=\u0026thinsp;2.0528, p\u0026thinsp;=\u0026thinsp;0.0264) (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eE). No significant difference between the treated and control groups was observed in leaf ABA concentrations (t\u0026thinsp;=\u0026thinsp;0.3749, df\u0026thinsp;=\u0026thinsp;3.0921, p\u0026thinsp;=\u0026thinsp;0.366) (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eF).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003e \u003cem\u003eTheobroma cacao\u003c/em\u003e exhibits both physiological and molecular adaptations to cadmium (Cd) exposure. TSH660(LA) genotype inherently absorbs significantly less Cd in its roots, approximately 63% of the amount absorbed by PA121(HA) genotype, and translocates markedly less to its leaves, at only\u0026thinsp;~\u0026thinsp;15.7% of the PA121(HA) levels (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA-B). In contrast, PA121(HA) tolerated a higher Cd uptake and translocation, as well as a more robust activation of stress-response genes in leaves. These divergent strategies are reflected at the transcriptomic level: TSH660(LA) shows fewer differentially expressed genes (DEGs) in its leaves, consistent with an avoidance mechanism. PA121(HA), on the other hand, exhibits a substantially higher number of DEGs in its leaves (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA), with enrichment in genes associated with heat stress responses (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB), including heat shock proteins typically activated under abiotic and biotic stress conditions.\u003c/p\u003e \u003cp\u003eIn cacao, at 48 h after Cd exposure, the number of DEGs was nearly twice as high in roots (4185) as in leaves (1999) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB). In leaves, PA121(HA) had 1538 DEGs compared to 180 in TSH660(LA), where in roots, both genotypes showed a similar number of DEGs (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB). The higher number of DEGs in roots aligns with findings in \u003cem\u003eSolanum lycopersicum\u003c/em\u003e (Chen et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), \u003cem\u003eBrassica juncea\u003c/em\u003e (Thakur et al., \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), \u003cem\u003eNicotiana rustica\u003c/em\u003e (Zhang et al., \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e2021\u003c/span\u003e)d \u003cem\u003ethaliana\u003c/em\u003e (Herbette et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2006\u003c/span\u003e), but not in \u003cem\u003eN. tabacum\u003c/em\u003e (Zhang et al., \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). In cacao, both genotypes exhibited a higher proportion of downregulated genes in roots and more upregulated genes in leaves; a pattern not consistently observed in the other species cited.\u003c/p\u003e \u003cp\u003eDespite differences in gene expression and Cd accumulation in leaves and roots, the mechanisms of Cd response in both genotypes share common features. These include a stress-detection and fast-acting signaling phase, followed by hormone-mediated signaling. These cause transcriptional changes that may result in reducing Cd toxicity, such as divalent cation uptake downregulation (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eD); N and P uptake regulation (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eC); regulation of chelating molecules (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA); and other adaptations related to water use, which include reduced stomatal conductance (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eA-C), and transcriptional changes that may be related to lowering the plants water potential and increasing leaf thickness (Figs.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e and \u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). We also anticipate an adverse effect on growth (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC-D). Figure\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e integrates the data and the proposed model.\u003c/p\u003e \u003cp\u003eAlthough \u003cem\u003eT. cacao\u003c/em\u003e is increasingly recognized as a model system for tropical perennial trees, the mechanisms underlying Cd\u0026sup2;⁺ sensing remain poorly understood. We hypothesize that ROS and Ca\u0026sup2;⁺ signaling occur in cacao plants, and, similar to \u003cem\u003eA. thaliana\u003c/em\u003e, early responses to Cd involve a rapid calcium spike (Zhang et al., \u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e2023b\u003c/span\u003e), followed by an increase in reactive oxygen species (ROS), a pattern also observed in other plant species (Chmielowska-Bąk et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Following this initial sensing event, hormone signaling can induce changes in gene expression. Consistent with this hypothesis, the largest cluster of GO terms in roots comprised 19 biological process (BP) categories, including 767 differentially expressed genes (DEGs) involved in key biosynthetic and signaling pathways for ABA, IAA, strigolactone, and ethylene (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Likewise, ABA concentration increased in the roots of PA121(HA) (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eE). Plants of the genotype TSH660(LA) were not available at the time of the hormone quantification. While acknowledging this limitation, our findings establish a foundation for future investigations into hormone signaling under Cd stress in cacao, including studies across different genotypes and experiments employing hormone inhibitors or ABA-related mutants.\u003c/p\u003e \u003cp\u003eCd is thought to alter water-use efficiency (WUE), prompting investigations into its link between drought tolerance and Cd accumulation in cacao (Ortiz-\u0026Aacute;lvarez et al., \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). This relationship is plausible because reduced stomatal conductance lowers water loss to the atmosphere, which slows mass flow and consequently limits the uptake of solutes (Marschner and Rengel, 2011), including Cd (Page and Feller, 2015). Under our conditions, Cd significantly reduced stomatal conductance (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eA-B). This result agrees with previous publications that have reported negative effect of Cd on transpiration in cacao (dos Santos et al., \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Barroso et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Both studies also reported a reduction in photosynthesis, suggesting another unintended effect of forced stomatal closure. Under our experimental conditions, photosynthesis remained unchanged (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eC\u0026ndash;D), likely due to the much shorter treatment duration.\u003c/p\u003e \u003cp\u003eTo further explore the link between Cd exposure and WUE, we analyzed a previously published transcriptome data of cacao drought response (CDR) (Kulesza et al., \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) where, similarly to cacao Cd response, we observed a strong correlation between the log2-fold changes of ABA-related genes, including \u003cem\u003eLEA\u003c/em\u003e and \u003cem\u003ePYL\u003c/em\u003e. However, some differences emerged. For instance, Cd affected the expression of nine \u003cem\u003eIAA/ARP\u003c/em\u003e genes, while only six were differentially expressed in the CDR; of those, only three showed similar regulation patterns. A comparable trend was observed in the ethylene response factor (\u003cem\u003eERF\u003c/em\u003e) gene family. Additionally, transcriptional changes associated with reduced water availability were reflected in the largest GO term cluster in leaves, identified as \u0026ldquo;cellular response to heat\u0026rdquo; (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Within this cluster, induction of Eceriferum gene expression in leaves was observed, indicative of potential enhanced cutin biosynthesis and cuticular thickening, processes that likely contribute to reduced water loss due to transpiration. Furthermore, key enzymes for raffinose synthesis, identified as carbohydrate metabolism in leaves (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e), galactinol synthase (\u003cem\u003eGOLS1\u003c/em\u003e), raffinose synthase (\u003cem\u003eRS\u003c/em\u003e), and galactosyltransferase (\u003cem\u003eGalT\u003c/em\u003e) (Elsayed et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2014\u003c/span\u003e), were significantly upregulated. Seven additional \u003cem\u003eGalT\u003c/em\u003e and \u003cem\u003eRS\u003c/em\u003e genes (Table \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e) exhibited similar expression patterns to those observed in the cacao drought response.\u003c/p\u003e \u003cp\u003eStagnation of mass flow alone may not suffice to limit Cd uptake, as the acquisition of most micronutrients (e.g., Fe, Mn, Zn, Cu) predominantly occurs via active transport, enabling efficient assimilation even at low external concentrations. \u003cem\u003eTcIRT1\u003c/em\u003e, a key gene in Strategy I Fe uptake (Dashner, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), was strongly downregulated in roots: 48-fold in PA121(HA) and 22.72-fold in TSH660(LA) (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eD). Similarly, its Arabidopsis ortholog (\u003cem\u003eAtIRT1\u003c/em\u003e) was induced under Fe deficiency but was downregulated when Fe deficiency was combined with 90 \u0026micro;M Cd (Connolly et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2003\u003c/span\u003e), and after Cd exposure alone (Herbette et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). Together, these findings suggest a regulatory mechanism in which the expression of Cd-permeable transporters, such as \u003cem\u003eAtIRT1\u003c/em\u003e and \u003cem\u003eTcIRT1\u003c/em\u003e, is attenuated to limit Cd uptake. ABA has also been linked to \u003cem\u003eIRT1\u003c/em\u003e downregulation under cadmium exposure in \u003cem\u003eA. thaliana\u003c/em\u003e, suggesting a hormonal role in restricting Cd uptake (Shen et al., \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cem\u003eTcNRAMP6\u003c/em\u003e and \u003cem\u003eTcNRAMP5\u003c/em\u003e, which mediate transmembrane transport of Zn and Cd (Ullah et al., \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), exhibited differential expression. \u003cem\u003eTcNRAMP6\u003c/em\u003e was upregulated in both genotypes, whereas \u003cem\u003eTcNRAMP5\u003c/em\u003e was downregulated in TSH660 (LA) (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eD). These patterns suggest that suppression of specific NRAMP transporters may contribute to limiting Cd uptake. Evidence from Arabidopsis NRAMP knockout lines supports this hypothesis (Cailliatte et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). Similarly, Cd xylem translocation was reduced in \u003cem\u003eO. sativa\u003c/em\u003e RNAi lines (Ishimaru et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). A comparable trend occurs \u003cem\u003eNicotiana tabacum\u003c/em\u003e, which accumulates less Cd than \u003cem\u003eNicotiana rustica\u003c/em\u003e and downregulates \u003cem\u003eNtNRAMP2\u003c/em\u003e and \u003cem\u003eNtNRAMP6\u003c/em\u003e in response to Cd exposure (Zhang et al., \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Although further functional validation in cacao is required, repression of Cd-permeable transporters appears to be a conserved mechanism across species for restricting Cd accumulation.\u003c/p\u003e \u003cp\u003eAmong the heavy metal ATPases in cacao, only \u003cem\u003eTcHMA3\u003c/em\u003e has been functionally characterized to date (Moore et al., \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2020b\u003c/span\u003e). In our study, \u003cem\u003eTcHMA3\u003c/em\u003e is strongly downregulated in the roots of PA121(HA) after 48 h of Cd exposure (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eD). This transcriptional response contrasts with \u003cem\u003eAtHMA3\u003c/em\u003e, which was upregulated after 30 h of exposure to 50 \u0026micro;M Cd (Herbette et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2006\u003c/span\u003e), but resembles the behavior of \u003cem\u003eAtHMA2\u003c/em\u003e and \u003cem\u003eAtHMA4\u003c/em\u003e, both of which are repressed by the transcription factors \u003cem\u003eAtMYC2\u003c/em\u003e and \u003cem\u003eAtMYB43\u003c/em\u003e following Cd exposure (Zheng et al., \u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Cao et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Given that \u003cem\u003eAtHMA2\u003c/em\u003e and \u003cem\u003eAtHMA4\u003c/em\u003e function as xylem loaders (Hussain et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2004\u003c/span\u003e) and \u003cem\u003eAtHMA3\u003c/em\u003e mediates vacuolar sequestration (Morel et al., \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2008\u003c/span\u003e), the divergent regulation observed in cacao warrants further investigation into the evolutionary dynamics and functional specialization of the HMA family in this species.\u003c/p\u003e \u003cp\u003eIn addition, \u003cem\u003eTcHMA5\u003c/em\u003e (XM_007040138.2), an ortholog to the ethylene-coupled Cu transporter \u003cem\u003eAtRAN1\u003c/em\u003e (Li et al., \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), was upregulated in the roots of TSH660(LA) (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eD), coinciding with changes in ethylene-related gene expression and signaling. This pattern suggests that TcHMA5 may function similarly to RAN1 and is consistent with its increased expression during leaf maturation (Kulesza et al., \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Furthermore, \u003cem\u003eTcHMA1\u003c/em\u003e, whose Arabidopsis ortholog, \u003cem\u003eAtHMA1\u003c/em\u003e, contributes to Zn detoxification (Kim et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2009\u003c/span\u003e), was downregulated in PA121(HA) leaves. These observations highlight genotype-specific regulation of HMA transporters under Cd stress.\u003c/p\u003e \u003cp\u003eChelation, sequestration, and precipitation are critical processes in Cd detoxification. Nitrogen (N) and phosphorus (P) can directly precipitate (Van Belleghem et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2007\u003c/span\u003e), whereas sulfur (S) acts as a reducing agent in molecules such as glutathione S-transferases (GSTs), which mobilize Cd bound to glutathione (GSH) and detoxify ROS (Flores et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2000\u003c/span\u003e). In our study, we observed transcriptional changes in genes encoding for N, P, and S transporters (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB-C). Changes in abundance or chelation were not tested directly, so we limit our discussion to their transcriptional behavior. Notably, given lignin\u0026rsquo;s capacity for metal chelation, the downregulation of genes for lignin-forming proteins (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA) is intriguing. \u003cem\u003eLFP\u003c/em\u003e suppression has been associated with increased levels of monolignols, such as coumarins (Abdur Rahim et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). This raises an important question regarding the role of monolignols in the Cd response: whether they act as direct coordination compounds facilitating Cd mobilization or serve as precursors required for mobilizing other elements (Tsai and Schmidt, \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn this study, no single factor was identified as the primary driver of differences in Cd uptake in cacao. However, we detected distinct differentially expressed genes (DEGs) that provide a foundation for future functional validation. The proposed model integrates observations from cacao with evidence from other species into a cohesive hypothesis involving water-use efficiency, specialized elemental transport, chelation, and detoxification. Experimental limitations, such as cacao\u0026rsquo;s long juvenile phase, strict material exchange regulations, and controlled growth requirements, also constrained the number and frequency of experiments. Several hypotheses are outlined for future research aimed at developing climate-resilient, low-Cd cacao varieties. Importantly, this work represents the first published whole-transcriptome study of Cd response for the species.\u003c/p\u003e \u003cp\u003eIn conclusion, this study reveals a coordinated physiological and molecular response in cacao aimed at mitigating Cd uptake and toxicity. This response involves hormonal signaling, reduced mass flow, modulation of nutrient and ion transport, and activation of detoxification pathways. Future research should focus on validating this model through investigations of cellular redox dynamics, monolignol-mediated chelation, root structural adaptations, and controlled phytohormone or inhibitor applications. Given the substantial overlap between drought and Cd responses, integrating not only both stressors (Ortiz-\u0026Aacute;lvarez et al., \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) but also multiple kinds of omics may accelerate the development of climate-resilient, low-Cd cacao varieties. Finally, the molecular features identified here represent promising targets for marker-assisted selection and gene-editing strategies in cacao improvement.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eConflict of Interest\u003c/p\u003e\n\u003cp\u003eThe authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.\u003c/p\u003e\n\u003cp\u003eFunding\u003c/p\u003e\n\u003cp\u003eThis work was funded by the \u0026ldquo;Ministerio de Ciencia, Tecnolog\u0026iacute;a e Innovaci\u0026oacute;n de Colombia\u0026rdquo; Agreements TV-18 and TV-19 through the \u0026ldquo;Corporaci\u0026oacute;n Colombiana de Investigaci\u0026oacute;n Agropecuaria\u0026rdquo; (AGROSAVIA), under the project: \u0026ldquo;Selecci\u0026oacute;n de parentales de cacao por resistencia a enfermedades y estr\u0026eacute;s h\u0026iacute;drico, productividad, compatibilidad, menor absorci\u0026oacute;n de cadmio y calidad\u0026rdquo;, ID 1000429, by the Pennsylvania State University College of Agricultural Sciences, the Huck Institutes of the Life Sciences, the Endowed Program in the Molecular Biology of Cacao and USDA Hatch appropriations under Project #PEN05003 and Accession #7007428 and Project #PEN4879 and Accession #7005892.\u003c/p\u003e\n\u003cp\u003eAcknowledgments\u003c/p\u003e\n\u003cp\u003eThe authors would like to acknowledge the Huck Institutes\u0026apos; Metabolomics Core Facility (RRID: SCR_023864) for the use of the Sciex ZenoTOF 7600 LC-MS and Sergei Koshkin for helpful discussions,\u0026nbsp;the team at USDA, ARS Tropical Agriculture Research Station in Mayag\u0026uuml;ez, Puerto Rico, for their service in providing cacao pods for our experiment, and Dr. Naomi Altman for supporting the statistical model design. They would also like to acknowledge BioRender\u0026reg; for providing a template for Figure 8, and OpenAI\u0026apos;s ChatGPT and Grammarly for writing refinement and grammatical editing.\u003c/p\u003e\n\u003cp\u003eAuthor Contributions\u003c/p\u003e\n\u003cp\u003ePD-D designed the research, contributed new laboratory methods and assays, assembled the transcriptome, analyzed data, and wrote the paper. FMM-B, MG and SM designed the physiological experiments. FMM-B performed and analyzed the physiological experiments, contributed new analytical methods for phytohormone purification, contributed to the transcriptome assembly, contributed new analytical and computational tools, analyzed data, prepared all figures, and wrote the paper. IA and NC contributed to the transcriptome assembly and analyzed data. MG and SM participated in the interpretation of the results and contributed to writing the manuscript. ACM designed the research. CR-M performed and set up greenhouse experiments to measure growth, Cd concentration, RNA purification, and sampled material. RY designed the research, collected samples, analyzed data, and contributed to writing the manuscript.\u003c/p\u003e\n\u003cp\u003eData Availability Statement\u003c/p\u003e\n\u003cp\u003eThe reads used in the current study are available at GenBank (https://www.ncbi.nlm.nih.gov/genbank/) under the BioProject ID: PRJNA943175. The Licor 6400XT output and cleaned data used for gas exchange analyses are available on Zenodo (https://doi.org/10.5281/zenodo.17316758.). The scripts and analytical workflows used for data cleaning, statistical modeling, and figure generation are available in the associated GitHub repository at https://github.com/FranciscoMenendez/cacao-cadmium-response. The sequences obtained in this project belong to the Colombian State, as the country of origin of the genetic material, in accordance with the Convention on Biological Diversity, the Nagoya Protocol, and Andean Decision 391.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eAbdur Rahim M, Atikur Rahman M, Korea Md Mizanur Rahman S, Song C, Li X, Jia B, Liu L, Wei P, Aamir Manzoor M, Wang F, et al (2022) Comparative Transcriptomics Unveil the Crucial Genes Involved in Coumarin Biosynthesis in Peucedanum praeruptorum Dunn. doi: 10.3389/fpls.2022.899819\u003c/li\u003e\n \u003cli\u003eAleksander SA, Balhoff J, Carbon S, Cherry JM, Drabkin HJ, Ebert D, Feuermann M, Gaudet P, Harris NL, Hill DP, et al\u0026nbsp;(2023) The Gene Ontology knowledgebase in 2023. 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New Phytologist 234: 884\u0026ndash;901\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"plant-and-soil","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"plso","sideBox":"Learn more about [Plant and Soil](https://www.springer.com/journal/11104)","snPcode":"11104","submissionUrl":"https://submission.nature.com/new-submission/11104/3","title":"Plant and Soil","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-8509096/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8509096/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eAims\u003c/p\u003e\n\u003cp\u003eUnderstanding the mechanisms of cadmium (Cd) accumulation in cacao plants is critical for mitigating health risks associated with Cd exposure through chocolate consumption and for guiding plant breeding strategies. A general and genotype-specific molecular and physiological responses were characterized.\u003c/p\u003e\n\u003cp\u003eMethods\u003c/p\u003e\n\u003cp\u003eThe seedlings of the two cacao genotypes, PA121 and TSH660, were exposed to 0 and 10 ppm Cd in hydroponic conditions. Leaf and root samples were collected at 0, 24, and 48 h (RNAseq) and at 60 days post-treatment (ICP-OES). Gene expression profiles of Cd-treated and untreated plants were compared using differential gene expression (DEG) and gene ontology analyses. Gas exchange and abscisic acid (ABA) measurements were conducted on greenhouse-grown seedlings of genotype PA121.\u003c/p\u003e\n\u003cp\u003eResults\u003c/p\u003e\n\u003cp\u003eThe number of DEGs recorded in roots was nearly twice as high as in leaves at 48 h after Cd exposure. Shared and genotype-specific DEGs related to detoxification, reactive oxygen species, and hormone pathways were upregulated in roots, and carbohydrate, tricarboxylic acid cycle, fatty acid, and terpenoid synthesis DEGs were activated in leaves. Additionally, genes from Cd-transport families, such as ZIP/IRT and NRAMP, were downregulated in roots. More significantly, ABA-associated biosynthetic and signaling transcripts and ABA abundance increased in roots after Cd treatment. PA121 seedlings exposed to 12 ppm Cd exhibited reduced stomatal conductance without a significant decline in photosynthesis.\u003c/p\u003e\n\u003cp\u003eConclusions\u003c/p\u003e\n\u003cp\u003eThese findings are consistent with a model in which Cd triggers ABA-linked root signaling that reduces stomatal conductance and mass flow and reduces expression of active Cd2+ transport, thereby limiting Cd uptake.\u003c/p\u003e","manuscriptTitle":"Molecular and Physiological Mechanisms of the Cadmium Response in Seedlings of Two Theobroma cacao L. 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