Expression Landscape, Evolutionary Insights, and Duplication Patterns of Cinnamyl Alcohol Dehydrogenase Genes Under Macrophomina phaseolina Infection and Salt Stress in Sesame

Expression Landscape, Evolutionary Insights, and Duplication Patterns of Cinnamyl Alcohol Dehydrogenase Genes Under Macrophomina phaseolina Infection and Salt Stress in Sesame | 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 Expression Landscape, Evolutionary Insights, and Duplication Patterns of Cinnamyl Alcohol Dehydrogenase Genes Under Macrophomina phaseolina Infection and Salt Stress in Sesame Mushtaq Ahmad Najar, Gaurab Gangopadhyay This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8161012/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Sesame ( Sesamum indicum ) has been cultivated for centuries, prized for its oil and medicinal properties. With the availability of its genome, the identification and characterization of key gene families have become a research priority. Cinnamyl Alcohol Dehydrogenase ( CAD ) gene plays a pivotal role in the phenylpropanoid pathway by catalysing the final step in lignin biosynthesis, specifically the production of monolignols. In this study, we identified CAD homologs and paralogs in the sesame genome using bioinformatic tools. Comparative synteny analysis with related species such as tomato and potato revealed evolutionary conservation and provided insights into the functional roles of sesame CAD genes ( SiCADs ). Phylogenetic and gene duplication analyses suggest that SiCADs genes have undergone purifying selection, indicating evolutionary pressure to maintain their functional integrity, particularly under environmental stress. To understand the role of these genes in stress responses, we performed RNA-seq analysis under two major stress conditions: infection with Macrophomina phaseolina , the causal agent of charcoal rot, and salt stress (NaCl). Expression profiling revealed that several SiCADs are differentially regulated in both wild ( S. mulayanum ) and cultivated ( S. indicum ) genotypes, with notable differences in expression patterns across stress types and time points. These findings underscore the potential role of SiCADs in defense and stress adaptation. This is the first comprehensive study of the CAD gene family in sesame, offering insights into their evolutionary dynamics and functional relevance. Subsequent, validation of obtained genic simple sequence repeats (gSSRs), will benefit the molecular breeding programs of sesame. The candidate genes identified in this study would provide a resource for gene cloning, functional validation, and molecular breeding, contributing to the development of stress-resilient sesame cultivars. Plant Molecular Biology and Genetics Bioinformatics Sesame CAD gene Macrophomina salt stress Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Figure 11 Figure 12 Figure 13 Figure 14 1. Introduction The Department of Economic and Social affairs of the United Nations, 2015 reported that global population is projected to exceed 9.7 billion by 2050. To feed such massive population, will require development of elite breed of crop varieties which would withstand the increasing threat of abiotic and biotic stress due to global perturbations in seasonal variations. Biotic stress (fungal infestations) and abiotic stress (salt) is becoming global threat to agriculture productivity, adversely affecting many staple crops. Sesamum indicum , an important oil seed crop, is also labile to both type of stress, which limits its agricultural productivity, and geographic distribution. S. indicum is vulnerable to infection by M. phaseolina which can cause charcoal rot, leading to crop loss at seedling stage and at production stage which accounts up to 80% loss (Marquez et al. 2021 ). Study have been carried out which highlights the effect of salt stress on development, yield at germination and seedling stage in sesame (Li et al. 2018 ; Zhang et al. 2019 ). The lignin, a crucial secondary cell wall component has been identified as an epicentre of defense response and involved in salt stress interactions. Cinnamoyl alcohol dehydrogenase ( CAD ) which is involved in the reduction of cinnamal aldehydes into cinnamyl alcohols, the last step in monolignol (Syringyl alcohols and Guiacyl lignin) biosynthesis before oxidative phosphorylation in cell wall by laccases. The diverse CAD s has been functionally validated in many plant species like Arabidopsis (Sibout et al. 2003 ), tobacco (Halpin et al. 1992 ), rice (Zhang et al. 2006a ), and Artesmia annua (Li et al. 2012 ). CAD is a Zn 2+ binding NADPH dependent homodimer responsible for converting cinnamaldehydes to hydroxyphenyl (H), guaiacyl (G), and syringyl (S) monolignols (Mansell et al. 1974 ). Many studies have established the role of CADs ranging from functional to omics analysis in both defense response against fungal pathogens, and salt stress. Following studies indicate role of CADs in fungal infestations viz Magnaporthe oryzae in Orzyae sativa (Meng et al. 2019 ), Ustilago maydis in Zea mays (Ruan et al. 2021 ), Verticillium dahliae in Gossypium hirsutum L.(Li et al. 2022 ), Rhizoctonia solani , Fusarium oxysporum , and Cytospora sp.in Populus trichocarpa (Bagniewska-Zadworna et al. 2014a ). The role of CADs in salt stress is also established by the following studies Orzyae sativa (Leng et al. 2023 ), Arabidopsis thialiana (Chen et al. 2007 ), Triticum aestivum (Yan et al. 2020 ), Gossypium hirsutum L.(Ibrahim et al. 2019 ) and Zea mays (Chen et al. 2022 ). The above studies indicate crucial role of CAD genes, so it necessitates of identifying the entire SiCAD genes in the genome of Sesamum , which would be a great leap in understanding the functional studies under M. phaseolina infection and salt stress. Our focus of this study would be identification, characterization, duplication events, and evolutionary relationship of SiCAD s genes with other crop species. Furthermore, expression analysis of the identified genes both by RNA-seq, and qRT-PCR analysis would be great resource for understanding the patterns of these genes under M. phaseolina infection and salt stress. 2. Material and Methods 2.1. Plant Material The sesame ( Sesamum indicum ) cultivar (Accession No. 7192 NBPGR germplasm collection India) obtained from the NBPGR and S. mulayanum (Courtesy of Mr. K Masuda) was used in all experiments (Fig. 1 ). Seeds were initially subjected to surface sterilization with 4% NaOCl (Sodium hypochlorite) for 10 min, followed by thorough washing with distilled water many times (Najar and Gangopadhyay 2024). Subsequently, the seeds were germinated, and cultivated in plastic pots under standard conditions (daily: 28 ± 1°C for 16 h under 200 µmol m − 2 s − 1 light, followed by 23 ± 1°C for 8 h of darkness) until reaching four true leaves. Four-week-old sesame seedlings at four leaf stage were subjected to biotic and abiotic stresses under identical growth conditions. The biotic stress was induced by inoculating the plants with pathogenic fungus M. phaseolina , following the method as described in our previous publication (Najar and Gangopadhyay 2024). Leaf samples were collected at different time points 0 hour (control), 48 hours, and 96 hours post-inoculation and were immediately stored at -80°C for RNA extraction. Another set of 4-week-old seedlings were subjected to salt stress (NaCl) of 200mM concentration, while control plants were subjected with sterile autoclaved double distilled water. Leaf tissues from both control and salt-treated plants were harvested, flash frozen, and stored at -80°C for subsequent RNA extraction. The experiment was laid out as a complete randomized design (CRD). Leaf tissues from both S. indicum and S. mulayanum were collected in three biological replicates, for each treatment (biotic and abiotic) and control condition. 2.2. DNA extraction and Identification of the Fungus We isolated fungus from infected plant of S. indicum in Madhyamgram Experimental Farm Bose Institute Kolkata, and cultured the fungus on potato dextrose agar (PDA) at 30 ± 1°C in the dark. The microscopic characterisation was done using a Leitz Biomed CD-L0170 compound microscope ( Supplementary Fig. 1 ). Further identification was validated by sequencing internal transcribed spacers (ITS) using rDNA gene cluster consisting of ITS1, 5.8S rDNA and ITS4, was amplified using primer ITS1 5′-TCCGTAGGTGAACCTGCGG-3′ and ITS4 5'- TCCTCCGCTTATTGATATGC-3′ (White et al. 1990 ). 2.3. RNA extraction and cDNA synthesis Frozen stored leaf tissues (100 mg) were used for extracting total RNA from leaves of sesame seedlings subjected to biotic ( Mp -inoculated) and abiotic (salt stress) respectively using the Spectrum™ Plant Total RNA kit (Sigma). To check the purity of the RNA samples 1% agarose gel stained with EtBr and quantification was done by NanoDrop spectrophotometer (NanoDrop® ND1000; Thermo Fisher Scientific Inc., Waltham, MA, USA). The synthesis of cDNA was performed using the QuantiTect® Reverse Transcription kit (QIAGEN) following the manufacturer’s protocol. To remove genomic DNA contamination, an RT-minus control was prepared using the same cDNA synthesis protocol, except without the addition of the reverse transcriptase enzyme. 2.4. Quantitative real-time PCR analysis, and Primer Designing The qRT-PCR analysis was performed using the Maxima SYBR Green/ROX qPCR mix (Thermo Scientific, USA) with gene-specific primers on an AriaMxfast Real-time PCR system (Agilent USA). Subsequently, all synthesized cDNAs samples were diluted 1:3 with nuclease-free water before being used in the qPCR step, following company manufacture protocol. β-actin (NCBI accession: XM_011079162) was used as the reference gene for normalizing candidate gene expression across all samples, and gene-specific primers were designed using NCBI’s Primer-BLAST tool ( Supplementary Table 1). The mRNA expression levels were assessed by calculating the ΔCt, representing the difference between the CT values of the target gene and the reference gene β-actin. Fold changes in gene expression were then determined using the 2^-ΔΔCt method (Livak and Schmittgen 2001 ). 2.5. Identification and Classification of SiCAD Genes in Sesame Genome The CAD gene sequences of Arabidopsis were downloaded from ( https://www.arabidopsis.org/ ). The amino acid sequence of AtCAD family (AT4G37990.1, AT2G21890.1, AT4G39330.1, AT3G19450.1, AT1G72680.1, AT4G37980.1, AT4G34230.1, AT4G37970.1, AT2G21730.1) was selected as the seed to search all related SiCAD genes in sesame genome. Based on genome and proteome sequences of sesame downloaded from ensemble.org ( https://plants.ensembl.org/index.html ) , an extensive survey was performed to identify all related members of SiCAD gene family in the sesame genome. The CAD domains were identified using the HMMER 3.0 ( https://www.ebi.ac.uk/Tools/hmmer/ ) , by searching for conserved Pfam domains designated as zinc-binding dehydrogenase (PF00107) and alcohol dehydrogenase GroES-like domain (PF08240). The SMART program and Pfam were used to further confirm the presence of PF08240 and PF00107. All the candidate genes, which did not contain PF08240 and PF00107 domains were removed. Furthermore, MARCOIL program was employed to detect the coiled coil structure and sequences which does not contain this were removed. The filtered gene sequences were proceeded for physical and chemical attributes using ProtParam tool ( https://web.expasy.org/protparam/ ). 2.6. Phylogenetic Analysis, Gene Structure, Motif-identification and Cis-elements analysis of SiCADs To investiagate the evolutionary relationship between the SiCAD genes of Sesame, Arabidopsis and Oryza sativa , multiple sequence alignment was carried out by using ClustalW program an inbuilt software of MEGA 6.0 software ( https://www.megasoftware.net/ ) (Tamura et al. 2011 ). The gap extension penalty of 0.2 and gap open penalty were set to 10. The alignment results were utilized to construct an unrooted Maximum Likelihood (ML) tree with 1,000 bootstrap replicates, using the web-based bioinformatics platform Gene Structure Display Server 2.0 (GSDS). The web-based bioinformatics tool GSDS was employed, available at http://gsds.cbi.pku.edu.cn for gene structure analysis (exon-intron substructure map) (Hu et al. 2015 ). All protein sequence of 32 SiCAD s including the isoforms were subjected to Multiple Expectation maximizations for Motif Elicitation (MEME) to identify conserved protein motifs. The relevant parameters were set as follows: minimum width of 6, maximum width of 50, the maximum number of motifs was set to 5. To find common promoters, which are widely known for their role in stress and development, identified SiCAD sequences were uploaded to Plant CARE database available on ( http://sphinx.rug.ac.be:8080/PlantCARE/ ) (Lescot et al. 2002 ). 2.7. Chromosomal mapping, Gene Duplications, and Comparative Mapping of Orthologous SiCAD Genes in Sesame , Arabidopsis , Tomato and Potato The SiCAD genes were mapped onto 16 Linkage Groups (LGs) of sesame genome using TBtools (Chen et al. 2020 ). To identify paralogous gene pairs and duplication events within the sesame genome, MCScanX analysis was performed (Wang et al. 2012b ). We eestimated synonymous ( K s ) and non-synonymous ( K a ) substution rates of identified sequences related to four duplicated gene pairs within the sesame genome, using PAL2NAL ( http://www.bork.embl.de/pal2nal ) (Suyama et al. 2006 ). Duplicated genes were identified and visualized by lines following (Dossa et al. 2016 ). Furthermore, synteny analysis and comparative orthology mapping of SiCADs were conducted between sesame and three other species Arabidopsis , tomato, and potato using MCScanX (Wang et al. 2012b ). The parameters used for the MCScanX analysis included an E-value threshold of 1e-10 and number of BlastHits was 5. The resulting synteny relationships were visualzuized by Circos ( https://circos.ca ) (Krzywinski et al. 2009 ). 2.8. Discovery of SSR Markers and Protein Interaction Network Analysis of SiCADs We proceeded with the identified SiCAD genes nucleotide sequence for the presence of Simple Sequence Repeats (SSRs) with the web based tool software ( https://bioinfo.inf..br/websat/ ) and cross checked with another web tool, MISA-web available at http://misaweb.ipk-gatersleben.de/ (Beier et al. 2017 ).The parameters were set to: one to six SSR nucleotide motifs length and minimum repetitions were 10 for mononucleotide, six for for di-nucleotide and five reiterations for other repeat units. In addition, the maximum length between the two SSRS was kept 100 to register as compound SSR. Additionally STRING software https://string-db.org/ helped in showing interaction network of different SiCAD proteins based on interactome of Arabiodopsis and later on improved, visualized by cytoscape ( https://cytoscape.org/ ). 2.9. DNA extraction, PCR amplification, and electrophoresis To validate the SSR markers predicted from our analysis, genomic DNA was extracted from the genotypes comprising of S. indicum (Si), S.mulayanum (Sm), and eight recombinant liens (R1-R8) derived from an earlier interspecific hybridization between Si and Sm (Dutta et al. 2022 ). The PCR amplification was performed in a 25 µL reaction mixture containing 5 × Buffer, 2.0 mmol/L MgCl 2 , 0.1 mmol/L dNTPs, 100 µM of each primer (0.5 µL each of forward and reverse primer, synthesized by SIGMA), 0.5 U Taq polymerase, and 25 ng template DNA. The SSR-PCR amplification was performed with an Applied Biosystems 2720 Thermal Cycler (USA). After initial checking in 1.8 % agarose gel, thePCR products were further resolved in denaturing Urea PAGE (6%) in 1X TBE (Tris–Borate-EDTA) buffer and stained with ethidium bromide for 5 min (Fig. 2 A, B). 2.9.1 Primer Design and Validation of Genic SSR Containing the (AT)₁₁ Repeat Motif SSRs were identified based on a minimum motif length of 15 or 18 base pairs. For genic SSRs containing motifs ≥ 18 bp, primers were designed using with the following parameters: primer length of 18–24 nucleotides, GC content between 40% and 70%, annealing temperature ranging from 54°C to 63°C, and a minimum expected product size of 100 bp http://probes.pw.usda.gov/batchprimer3/overview.html . The primer pair targeting the genic SSR of SiCAD2 containing the (AT)₁₁ repeat motif was designated SSRCAD2. The forward primer (SSRCAD2_F) sequence was 5′-TGTGATATGACGGTTAGCAAAGA-3′ (23 bp), and the reverse primer (SSRCAD2_R) sequence was 5′-CTCGTTCATGACTTAAATTACAGGT-3′ (26 bp). The expected amplicon size for this primer pair was 242 bp, as determined by NCBI in-silico PCR analysis and through 1.8% agarose gel (Fig. 2 A B ). 2.9.2 Gene Ontology (GO) and KEGG Pathway Analysis of SiCADs Candidate Genes The candidate genes were screened for associated GO terms ( https://geneontology.org/ ), and KEGG database ( https://www.kegg.jp/kegg/pathway.html ). The amino acid sequences of the identified SiCADs were subjected to KOBAS 2.0 ( http://kobas.cbi.pku.edu.cn ) (Xie et al. 2011 ). Those enriched Go-terms and pathways were considerd significant which has P < 0.05, further false discovery rate was adjusted using the Benjamini and Hochberg’s stastical test which was kept at threshold P < 0.05. Functional annotation was deduced through BLAST with E-value 1e-5 by leveraging the genome annotation of Arabidopsis from TAIR ( https://www.arabidopsis.org ). 2.9.3 Expression Analysis of SiCAD Genes under M. phaseolina infection and salt stress using RNA-seq data The raw data SRA files were obtained from the NCBI for biotic stress ( M. phaseolina infection) ( https://www.ncbi.nlm.nih.gov/sra/PRJNA642699 ) and abiotic stress (salt stress) ( https://www.ncbi.nlm.nih.gov/bioproject/524278 ). The SRA files were analyzed to check the QC, GC content and adapter content. The adaptor sequences, primers, and low-quality reads were filtered out with Trimmomatic (version 0.39). After removing adaptors, and low-quality reads, the paired-end fastq files were mapped to reference genome of S. indicum ( S_indicum_v1.0 downloaded from https://plants.ensembl.org/Sesamum_indicum/Info/Index ). The obtained reads were annotated by alignment using graph based aligner HISAT2 (version 2.2.1) software with default parameters (Kim et al. 2019 ). The SAM files were converted to BAM files and sorted using SAM tools software (Li et al. 2009 ). Using ultrafast and accurate feature Counts (Version 2.0.5), the mapped reads were annotated with GTF file of S_indicum_v1.0 obtained from https://plants.ensembl.org/Sesamum_indicum/Info/Index . To analyze the sequence depth, expression pattern of the identified SiCAD genes, the count data from both M.phaseolina infection and salt stress was subjected to below formula to calculate the RPKM values: \(\:RKPM=\left[\frac{Raw\:Count}{\frac{Gene\:Length\left(bp\right)}{1000}*\frac{Total\:Reads}{\text{1,000,000}}}\right]\) A heatmap was constructed using the RKPM values of the identified SiCAD genes to visualize their expression patterns. Hierarchical clustering was applied to genes to reveal relationships and grouping based on expression profiles. 2.9.4 Statistical analysis and Visualization The results are expressed as the average of three biological replicates. Data were analyzed using Welch’s two-sample unpaired t -test for independent samples to determine statistical significance. All computations were performed out in RStudio (version 2024.04.2). Data visualization, and significance annotations were generated using the ‘ggplot2’ and ‘ggsignif’ packages, available from the CRAN repository. For heatmaps, bubble plots, and dot plots were organized in comma separated values (CSV) files and imported into the RStudio environment. Heatmaps were generated using the ‘ComplexHeatmap’ and ‘Pheatmap’ package (Available via Bioconductor), and bubble plots were created using ‘ggplot2’ to to enhance graphical representation. 3. Results 3.1. Identification, chromosomal mapping, and duplication analysis of SiCAD genes in the sesame genome A total of 32 SiCAD genes were identified in the sesame genome from the scans of Hmmer and Hidden Markov Model (HMM) domain searches ( Table 1 ). The deduced protein sizes varied from 309 amino acids ( SiCAD31 ) to 719 amino acids ( SiCAD6 ) and the isoelectric points range from 5.17 ( SiCAD31 ) to 9.23 ( SiCAD32 ) ( Table 2 ) . Further, physical characteristics of these SiCADs genes including Ensembl ID, protein molecular weight (MW), and isoelectric point (pI) is shown in Table 2 . Only one gene ( SiCAD1 ), which was located on an unanchored scaffold, could not be mapped to any specific linkage group (LG) (Fig. 3) . All the other CAD genes were unevenly distributed among 15 LGs of 16 LGs in the sesame genome, suggesting that CAD genes may have been widely distributed in the genome of a common ancestor ( Fig. 3 ). The distribution of sesame SiCAD s genes across linkage groups varied. The LG2 contains the highest number of genes, accounting for 18.75% of total identified genes. LG6 and LG13 each contains 5 genes, accounting for 31.26% of the total genes. LG7, LG3, LG8 and LG15 comprisies 34.38% of the total genes. In addition, LG1, LG4, LG12, LG14 possesses only 1 gene which accounts for 12.56% of all SiCAD genes (Fig. 3). To gain deeper insights into the evolutionary patterns of these genes, the synonymous ( Ks ), non-synonymous ( Ka ), and their ratio ( Ka/Ks ) values were analyzed to examine the selective pressure and duplication events among four sesame segmentally duplicated SiCAD gene pairs in sesame. In general, a K a /K s >1 means positive selection, K a /K s <1 indicates purifying selection and K a /K s =1 stands for neutral selection (Zhang et al. 2006b) . The K a /K s ratio for all sesame SiCADs gene varied from 0.05 to 0.40 (Fig. 4, Supplementary Table 2) . These results suggest that the segementally duplicated SiCAD gene pairs ( SiCAD11 and SiCAD5 , SiCAD25 and SiCAD22 , SiCAD27 and SiCAD18 , SiCAD31 and SiCAD27 ) showed K a /K s <1 showing purifying selection pressure. These results suggest these segmentally duplicated SiCAD gene pairs have experienced purifying selection, maintaining their original function possibly through removing deleterious mutations,while potentially allowing for subtle functional divergence over time. 3.2. Conserved Domain analysis and Gene Structure of SiCAD All thirty two SiCAD genes along with their isoforms were submitted to the CDD search tool to uncover the conserved functional domains (https://www.ncbi.nlm.nih.gov/Structure/bwrpsb/bwrpsb.cgi) (Wang et al. 2023a) . Most protein sequences contain ADH_N (Clan:Groes) and ADH_zinc (Clan: NADP_Rossmann) domains a characteristic feature of CAD genes. In addition, the ADH_N superfamily, ADH_zinc_N_2, and MDR superfamily domains are also present in SiCAD amino acid sequences ( Supplementary Fig. 2, Supplementary Table 3 ). The MEME web server was employed to verify the result of domain prediction ( Supplementary Fig. 3 ). Five different motifs were found distributed throughout the SiCADs amino acid sequences, with lengths ranging from 21 to 50 amino acids. The Motif 3 was found in 36 SiCAD protein sequences. In addition, Motif 1 was assigned to 34 SiCAD amino acid sequences indicating a highly conserved protein motif structure with an amino acid length of 29 in both cases (Supplementary Fig. 3) . Analysis of exon-intron boundaries combined with phylogenetic analysis of identified CAD genes showed highly conserved intron-exon organization in 32 SiCAD genes (Fig. 5) . The genes showed variability in gene structure, and some of the SiCAD genes possessed isoforms as depicted (Fig. 5) . Our analysis showed that SiCAD genes from the same clade group observed similar number of introns and exons in their structure’s. In class A SiCAD4 contains 1 exon and SiCAD26 showed 9 exons. In class B, the genes SiCAD23.X1 and SiCAD23.X2 each have 9 exons, while SiCAD15 has 7 exons, SiCAD29 has 6 exons, SiCAD18 has 10 exons, SiCAD28 has 3 exons, and SiCAD31 has 4 exons. Further, in class C, the genes SiCAD7 and SiCAD6 each have 2 exons, SiCAD27 and SiCAD9.X2 each have 4 exons, SiCAD8 and SiCAD21.X2 each have 6 exons, SiCAD32 has 7 exons, and SiCAD1 has 5 exons. In class D, the genes SiCAD14.X1 has 7 exons, SiCAD20 , SiCAD24 , SiCAD22 , SiCAD25 , and SiCAD20.X1 each have 10 exons, SiCAD30 with 6 exons each, SiCAD19 and SiCAD16 each have 8 exons, and SiCAD21.X1 has 5 exons. This organization highlights the diversity in exon numbers across different members of the SiCAD gene family within their respective classes ( Fig. 5) . 3.3. Promoter analysis of the identified SiCADs Differences in cis-elements within the gene promoters suggest that these genes may have diverse roles in plant growth, development, and responses to various stresses. To explore the functions of SiCAD genes in more detail, 1.5 kb of the upstream region from each gene’s transcription start site (TSS) was retrieved and analyzed using the PlantCARE database to identify and quantify the cis-elements ( Fig. 6 ). These cis -elements were divided into three categories, i.e., development responsive, hormone responsive, and stress related-elements. The promoter of SiCAD genes included number of hormone responsive-elements, and stress, especially P-box (gibberellin-responsive element), ABRE (abscisic acid responsiveness), CGTCA-motif (MeJA-responsiveness), and TC-rich repeats (defense and stress responsiveness) ( Fig. 6 ). Additionally, CCAAT-box ( HvMYB1 ) was common occurrence in most of SiCADs, these are well known for their positive role in drought response and osmotic stress (Alexander et al. 2019). These results indicate that the SiCAD genes might have key roles in plant growth, development and response to various stresses in sesame ( Supplementary Table 4 ). In additition, we delved into comprehensive analysis of various binding sites present in our identified SiCADs for the transcription factors involved in stress response, development and growth as illustrated in heatmap ( Fig. 7 ). 3.4. Phylogenetic analysis, Mapping and comparative Synteny Analysis To investigate the evolutionary relationship of sesame SiCAD genes phylogenetic analysis was performed based on the full Length amino acid sequences of SiCADs proteins from Arabidopsis thialiana , Orzya sativa and S. indicum (Fig. 8A) . The tree clearly distinguishes the ten classes (I-X) (Fig. 8A) . Synteny analysis of sesame SiCAD genes compared to those of Arabidopsis could provide more functional aspect of these genes. Hence, we performed a comparative analysis to identify orthologous SiCAD genes between sesame and Arabidospsis , S. lycopersicum, and S. tuberosum genome respectively. In total, seven orthologous genes were linked with identified SiCADs in Arabidopsis ( Fig. 8B ). Synteny analysis revealed that nine genes of S. lycoperiscum showed orthology with identified SiCADs ( Fig. 8C ). In addition, synteny revealed eight genes of S. tuberosum were linked with identified SiCADs ( Fig. 8D ). Interestingly, LG8, LG2 possessed largest ortholog (2 gene pairs) while least one gene pair was detected on LG3, LG7, LG15 in all comparative analysis ( Fig. 8B, C, D ). 3.5. Protein interaction network analysis of SiCADs and identification of SSR markers The protein-protein interaction network is a helpful preface to explore biological functions of unknown proteins. Based on the Arabidopsis interactome, the protein-protein interactions, including functional and physical interactions among SiCAD genes of sesame were predicted (Fig. 9) . Twelve sesame CAD genes were involved in protein-protein interaction. These proteins have been validated and implicated in salinity stress and in defense response to many pathogens. Hence, we hypothesized that SiCAD genes might also be involved in similar function pathways. The genes interacted with PDC1 and F2K13.90 which are implicated in lignin biosynthesis acting as cofactor for alcohol dehydrogenase as per Gene ontology. In addition, the interactions occurred between the isoforms of CAD genes, also as evident from the ( Fig. 9) . Given the significance of SiCAD genes in mediating responses to both biotic and abiotic stresses, tagging these valuable genes could facilitate marker-assisted breeding and contribute to the development of more effective crop improvement strategies. Of of the thirty two SiCAD genes, 20 SiCAD genes exhibited single sequence repeats (SSRs) from mononucleotides (p1) to tetranucleotide (p4) (Supplementary Table 5) . 3.6 Development and Validation of Genic SSR Markers Of the thirty two SiCAD genes predicted, twenty were found to harbor SSR motifs, including mononucleotide (p1), dinucleotide (p2), trinucleotide (p3), and tetranucleotide (p4) repeats. The average gene length analyzed was approximately 4 kb. Using in silico tools, one genic SSR motif with an AT repeat (AT)₁₁ was identified within the coding region of one candidate gene, located from 1658 bp to 1679 bp. To validate the presence and amplification of this SSR, specific primers were designed flanking the repeat region. Initial amplification was performed using 1.8% agarose gel electrophoresis, which revealed a single band of 242 bp across all genotypes tested, suggesting successful and specific amplification ( Fig. 2 A,B ). Further resolution using 6% PAGE allowed us for more precise allele discrimination. A total of 20 alleles were detected among the tested parental and recombinant F6 lines (R1–R8). However, all individuals displayed identical banding profiles for this marker, classifying it as monomorphic across the tested genotypes. Despite the number of detected bands, no allelic polymorphism was observed, suggesting that this SSR marker may be conserved in the studied panel. 3.7. Enrichment Analysis of SiCAD Genes Reveals Key GO Terms and KEGG Pathways Involved in Stress Response GO enrichment analysis was performed on the identified SiCAD genes to uncover their functional differences with statistical significance ( P value < 0.05) and further false discovery rate was done by Benjamini and Hochberg (1995) statistical test with p <0.05. There were 36 GO terms enriched in Si CAD genes. Some important GO terms enriched in our identified genes wereGO:0009809 (Lignin biosynthetic process), GO:0009626 (Plant-type hypersensitive response), GO:0001666 (Response to hypoxia),GO:0009617 (Response to bacterium), GO:0010286 (Heat acclimation), GO:0071456 (Cellular response to hypoxia), GO:0009414 (Response to water deprivation), GO:0046686 (Response to cadmium ion), GO:0009651 (Response to salinity stress) and GO:0009737 (Response to abscisic acid) (Fig. 10A, Supplementary Table 6). The KEGG pathway analysis was employed to dissect pathways associated with identified genes. The pathway analysis was carried under stringent statistical analysis with P value <0.05 and P adjusted value (FDR) <0.05. The major pathways, which were enriched in Metabolic pathways (ath01100), Biosynthesis of secondary metabolites (ath01110), Phenylpropanoid biosynthesis (ath00940), Carbon metabolism (ath01200), Tyrosine metabolism (ath00350) ( Fig. 10 B). 3.8. Expression Analysis of SiCAD Genes from RNA-Seq Data in response to M. phaseolina Infection For understanding the dynamic expression pattern after post-infection with M. phaseolina infection in genotypes S. indicum and S. mulayanum , we thoroughly analyzed the transcriptome data and found that SiCADs showed different RKPM value dynamics post infection ( Fig. 11 A ). Twenty identified SiCADs showed responsiveness to M. phaseolina infection. SiCAD3 , SiCAD5 , SiCAD9 , SiCAD1 0, SiCAD13 showed high RPKM values, suggesting that these might be crucial for M. phaseolina response. In addition, SiCAD1 , SiCAD2 , SiCAD6 , SiCAD7 , SiCAD14 , SiCAD16 , SiCAD17 , SiCAD19 , SiCAD21 , SiCAD23 , SiCAD26 , SiCAD28 , SiCAD29, and SiCAD32 showed zero expression as per RPKM values. 3.9. Expression Analysis of SiCAD under salt stress from RNA-seq data To analyze the expression of the identified genes, the RNA-seq data was analyzed and we found that, there are mainly two classes as shown in Figure. 11B. A Heatmap was generated based on the RPKM value of each gene identified in our study. Hierarchical clustering based upon Pearson correlation was employed to establish the classes. The Hierarchical clustering resulted into two classes, A and B. The expression showed time-dependent change in expression, as we found in SiCAD11, SiCAD19, SiCAD31, and SiCAD5 showed high RKPM value at 24hr in salinity tolerant genotype (Fig. 11B). The RPKM of SiCAD28, SiCAD14, SiCAD18 showed lesser changes under salinity stress across different time points. 3.9.1 Quantitative real-time PCR (qRT-PCR) analysis of selected SiCAD genes under M. phaseolina infection and salt stress in two sesame genotypes To explore the potential role of CAD genes in sesame responses to M. phaseolina and salt stress, we monitored the expression levels of SiCAD genes under progressive M. phaseolina infection and salt stress in two sesame genotypes. Since most SiCAD genes displayed differential expression in leaves, qRT-PCR analysis was perfomed on leaf samples. During M. phaseolina infection, the selected SiCAD genes exhibited varied expression patterns across different time points. In S. indicum , after 48 hours of infection, SiCAD4 (6.5), SiCAD5 (3.9), SiCAD6 (2.5), SiCAD10 (3.2), and SiCAD20 (3.3), showed significant upregulation ( Fig.12B,C,D,F,H) . However, in 96 hours post-infection, a decline in expression was observed for several genes: SiCAD4 (0.86), SiCAD5 (2.24), SiCAD6 (2.11), and SiCAD20 (3.27), indicating temporal modulation of gene expression in response to infection (Fig.12 B-D,H) . In S. mulayanum , at 48 hours post-infection, SiCAD2 (0.89), SiCAD5 (2.12), SiCAD8 (0.96), and SiCAD10 (0.81) showed lower expression levels compared to the control ( Fig.12A,C,E,F ). By 96 hours, expression patterns shifted, with SiCAD2 (7.49) showing strong upregulation, while SiCAD5 (0.63), and SiCAD8 (0.67) remained downregulated relative to the control ( Fig. 12 A, C,E ). In salt stress, S. indicum , SiCAD2 (0.25), SiCAD5 (0.36), SiCAD8 (0.23), and SiCAD10 (0.23) showed notably reduced expression ( Fig. 13 A,C,E,F ). Similarly, in S. mulayanum under 200 mM salt stress, SiCAD5 (0.80), SiCAD6 (0.66), and SiCAD20 (0.32) also showed decreased expression levels with respect to control treatment ( Fig. 13 C,D,H ). In addition, the S. indicum SiCAD4 (0.20), SiCAD6 (0,08), SiCAD8(0.23), SiCAD12 (0.21), and SiCAD20 (0.15), showed reduced expression, but all were non-significant ( Fig.13 B,D,F,G,H) . However, in S. mulayanum SiCAD2 (0.10), SiCAD4 (0,34), SiCAD8 (0.28), SiCAD10 (0.18), and SiCAD12 (0.08), showed decreased expression levels, but were significant as per Welch two sample t test are concerned ( Fig. 13 A,B,E-G ). 4. Discussion 4.1. Segmental Duplications Contribute to the Expansion of the Cinnamyl Alcohol Dehydrogenase (SiCAD) Gene Family in Sesame Due to genomics interventions, CAD homologs genes have been unravelled in many plant species. Studies have identified CAD family genes in many crops, which include nine putative genes in Arabidopsis (Kim et al. 2004 ), fifteen CAD genes in Populus (Barakat et al. 2010 ), ten CAD genes in Nicotiana. tabacum , and four in N. tomentosiformis (Wu et al. 2024a ). In this study, we identified thirty-two SiCADs in sesame genome, classified into three major classes A, B, C, and one minor class D. The sesame genome spans 309.35 Mb, featuring a high chromosome anchoring rate of 97.54% and a contig N50 length of 13.48 Mb (Wang et al. 2022 ). Transposable elements (TEs) accounts to 27.42% of sesame whole genome, alongside with unclassified repetitive sequences comprising (26.30%). Among these, 65.45% of the repetitive elements show divergence rate of < 20% indicating the recent genome dynamics. These results indicate the genome is still evolving and expanding through TE activity (Wang et al. 2022 ). Evolutionary investigation of sesame revealed that the whole genome duplications (WGD) and tetraploid or whole genome triplication (WGT) events are recurrent in sesame species (Miao et al. 2024 ). Higher ratio synteny blocks between ancestral eudicot and tested Sesamum species, further supports the occurrence of WGD and WGT in Sesamum genus (Miao et al. 2024 ). These duplications events indicate high level of evolutionary conservation within the Sesamum genus (Wang et al. 2022 ; Miao et al. 2024 ). These results from genome scale comparison within sesame and other eudicots explains why the CADs family is highly diversified across the Sesamum genome. To evaluate the evolutionary origins and duplication pattern of SiCAD gene family in sesame,we dissected the distribution of the duplicated genes. We found four gene pairs of segmentally duplicated genes in our study (Fig. 4 , Supplementary Table 2 ). In a previous study, (Cheng et al. 2017 ) identified eight PbCAD gene pairs, which contributes to lignin biosynthesis in stone cells in Pyrus bretschneideri . In pomegranate three PgCAD gene pairs were found located at high gene density(Hu et al. 2023 ). In cassava MeCAD six pairs of segmental duplications were reported (An et al. 2024a ). The presence of segmentally duplicated genes SiCAD gene in sesame suggests that gene duplication has contributed to the functional diversification of this gene family. Such duplication events likely enhance the plant ability to adapt biotic and abiotic stress, thereby conferring adaptive evolutionary advantage (Vanneste et al. 2014 ; van Westerhoven et al. 2024 ). To estimate the divergence pattern and the effect of segmental duplication on gene function, we calculated rates of K s and K a substutions rate for the gene pairs. The K a /K s analysis of the four duplicated SiCAD gene pairs revealed that all K a /K s ratios were significantly less than 1 (ranging from 0.0459 to 0.3962), indicating that the duplicated SiCAD genes have mainly undergone purifying selection (Fig. 4 , Supplementary Table 2 ). Purifying selection plays a crucial role in maintaining biological function by eliminating newly arising deleterious mutations. These selections are widespread across natural populations and contributes significantly to the conservation of genomic sequences over long evolutionary periods. Beyond protecting functional sites under direct selection, purifying selection also influences nearby neutral regions, leaving characteristic signatures in genetic diversity patterns, a phenomenon observed across a wide range of organisms (Cvijović et al. 2018 ).These lines of evidences suggests duplicated SiCAD genes are under strong functional constraints following segmental duplication (Roth and Liberles 2006 ). Furthermore, the K s values, ranging between 0.97 and 2.27, imply that these duplications likely originated during an ancient whole-genome duplication event in sesame, consistent with previous reports of polyploidy events in the Sesamum genus (Wang et al. 2023b ). The gene duplication events were dated using K s values, a standard approach for estimating evolutionary divergence. Based on this method, the duplication events for the SiCAD gene pairs were estimated to have occurred approximately 75 to 175 million years ago (MYA), consistent with previous reports of ancient duplication events in sesame (Wang et al. 2013 , 2023c ). 4.2 Gene Orthology Analysis Highlights the Diversified Functional Roles of SiCAD genes in Sesame Synteny provides a robust framework for identifying the conservation of homologous genes and gene order across different plant genomes (Liu et al. 2018 ). In this study, synteny analysis, of sesame SiCADs with model crop Arabidopsis , and more related crops like S. lycoperiscum and S. tuberosum revealed some interesting functional insights (Fig. 8 B-D). Based on a stringent BLAST E value threshold of 1e-10, we identified multiple sesame SiCAD genes as orthologs of Arabidopsis . We found that gene SiCAD5, SiCAD12, SiCAD22, SiCAD25, SiCAD27, SiCAD30, SiCAD31 as ortholog of AT4G37970.1, AT4G34230.1, AT1G77120.1, AT1G77120.1, AT1G23740.1, AT3G56460.1, AT1G23740 respectively. Functional annotation retrieved from the TAIR database ( https://www.arabidopsis.org/ ) ( Supplementary Table 7 ) suggests that SiCAD5 ,and SiCAD12 might be involved in lignin biosynthesis using p-coumaryl aldehyde as substrate (Vanholme et al. 2012 ). Furthermore, comparative synteny analysis approach, between the sesame genome and those of S. lycoperiscum and S. tuberosum revealed conserved syntenic blocks (Fig. 8 C-D). The genes SiCAD5 , SiCAD11 showed orthology with Solyc11g010990.2. 1 in tomato. In potato, SiCAD5 , SiCAD11 , and SiCAD12 were orthologous to PGSC0003DMT400040518 , PGSC0003DMT400041566 , and PGSC0003DMT400066217 , respectively ( Supplementary Table 7 ). These orthologous relationships, supported by synteny analysis and database searches https://solcyc.solgenomics.net/,https://phytozome-next.jgi.doe.gov/ , indicate that these SiCAD genes may be functionally involved in lignin biosynthesis. The integration of high confidence orthologous relationships data strengthens our functional prediction and impart important insights in understanding role of these putative SiCAD in lignin biosynthesis in sesame. Furthermore, based upon Arabidopsis interactome, protein-proteins interaction of sesame CAD genes interacted with pyruvate decarboxylase (PDC1) and carbon-sulphur lyase (F2K13.90), which are implicated in lignin biosynthesis acting as cofactor as for alcohol dehydrogenase as per Gene ontology. In addition, the interactions occurred between the isoforms of SiCAD genes also as evident from PPI network (Fig. 7 ). Unfortunately, the regulation of CADs is not studied in sesame fully, however study by (Najar and Gangopadhyay 2024) elucidated the defense role of Cinnamoyl alcohol dehydrogenase 1 under M. phaseolina infection. 4.3 GO and KEGG Enrichment Analyses Reveal the Involvement of Identified SiCAD Genes in phenylpropanoid biosynthesis pathways We also did GO and KEGG analysis to see the involvement of identified SiCAD genes in biotic and abiotic stress. The following GO terms: GO:0009651, GO:0009809, GO:0009626, which are associated with osmotic stress, lignin biosynthetic process, and plant-type hypersensitive response were enriched in identified SiCAD genes ( Fig. 10 A). In wheat roots under 200mM NaCl stress, GO:0009651 was highly enriched indicating the crucial role of CAD s in salt tolerance (Chen et al. 2024 ). Furthermore, in poplar, the GO term GO:0009651 was significantly altered under salt stress (Cheng et al. 2024 ). The enrichment of GO:0009809 term associated with lignin biosynthesis, indicates the synergistic function of SiCADs in strengthening cell walls as a protective mechanism against various environmental stresses. In the gray blight disease of tea, lignin biosynthetic process (GO:0009809) was significantly enriched along with phenylpropanoid catabolic process (GO:0046271), indicating synthesis of secondary metabolites and cell wall changes triggered by defense response (Wang et al. 2021 ). Phylotranscriptomics revealed enrichment of GO term GO:0009626 associated with plant pathogen interaction, which induces hypersensitive response, under invasion of nectrophic fungus Sclerotinia sclerotiorum in various species of pentapetalae ( Phaseolus vulgaris , Ricinus communis , Arabidopsis thaliana , Helianthus annuus , Solanum lycopersicum , and Beta vulgaris ) (Sucher et al. 2020 ). In our study, we observed KEGG enrichment, which indicated SiCAD s are highly enriched in pathways associated with biosynthesis of secondary metabolites (ath01110), and phenylpropanoid biosynthesis (ath00940) (Fig. 10 B, Fig. 14 , Supplementary Table 8). In mungbean exposed to M. phaseolina infection, there was a concurrent increase in concentration of salicylic acid levels and phenylpropanoid pathway intermediates, such as phenylalanine ammonia lyase ( PAL ), which ultimately induce the synthesis of monolignols which are catalyzed by SiCADs (Kumari et al. 2024 ). Moreover, during M. phaseolina infection in soyabean, there was a significant enrichment of biosynthesis of secondary metabolites, indicating the critical role of the identified SiCADs (Noor and Little 2024 ). In our previous work on M. phaseolina infection (Najar and Gangopadhyay 2024),we also showed the critical role of phenylpropanoid biosynthesis pathway. Combining the results from GO and KEGG enrichment analysis of SiCADs , identification of these genes which have critical role in regulating lignin biosynthesis, as well as their contribution to improving stress tolerance through modifications in lignification of cell wall need to be studied in sesame to further uncover the molecular mechanism. 4.4 SiCAD s Genes might be actively involved in Macrophomina infection in Sesame Fungal diseases of the five most cultivated food crops worldwide were estimated to destroy at least 125 million tonnes of produce every year (Davies et al. 2021 ). M. phaseolina (Tassi) Goid. causes charcoal rot and affects 500 crops species globally, along with sesame (Lodha and Mawar 2020 ). To develop resilient sesame against fungal diseases, the CAD genes manipulation can be a solution due to its critical role in defense response (Lee et al. 2019 ). Studies has established that CAD homologs are actively involved against fungal pathogens by changing the lignin composition of cell wall, thus acting as physical barriers (Lee et al. 2019 ). However, apart from the role in defense, lignins are also actively involved in growth and development (Schilmiller et al. 2009 ; Huang et al. 2010 ). In our study, two contrasting genotypes of sesame were responsive to Macrophomina infection (Fig. 12 ). The results from expression studies established, involvement of CADs in Macrophomina which agrees with previous studies in other plant species (Coelho et al. 2006 ; Bagniewska-Zadworna et al. 2014b ; Wu et al. 2024b ). Under Macrophomina infection, the identified CADs established two classes. The RKPM values obtained from RNA-seq data analysis showed that (≈ 40%) identified SiCADs are actively expressed under M. phaseolina infection (Fig. 11 A ) . Top expressed genes ( SiCAD5, SiCAD10, SiCAD13 ) could be functionally important and evolutionarily conserved. Stress inducible SiCAD9 , SiCAD10 , and SiCAD12 showed upregulation under infection, suggesting involvement in defense/lignin-mediated stress response (Fig. 10 B). In our study, qRT-PCR analysis further validates these findings. In wild genotype, S. mulayanum SiCAD4, SiCAD6, SiCAD8 SiCAD10, SiCAD12 , and SiCAD20 showed lower levels of expression as compared to control at 96-hour post infection. In contrast the cultivated S. indicum showed relatively high expression of SiCAD4, SiCAD5, SiCAD6, SiCAD8, SiCAD10 at 48-hour post infection (Fig. 12 B-F). Notably, SiCAD2 and SiCAD20 showed relatively low and high level of expression at 48hr explaining the dynamic, and genotypic-specific contrasting of induction of SiCADs under M. phaseolina infection (Fig. 12 A,H). However, to fully unravel the regulatory roles and functional significance of these genes, further molecular investigations, including transgenic approaches, are essential. 4.5 SiCADs Genes may be indirectly involved in salt stress in Sesame India has 11098.81km spreading across mainland island as per data by National Hydrographic Organisation (NHO), so salt stress is significantly affecting the productivity of the agricultural land. Several reports suggest the fact is sesame is salt sensitive (Nassery et al. 1979 ). The phenylpropanoid biosynthesis pathway plays a central role in synthesis of monolignols in plants (Boerjan et al. 2003 ; Najar and Gangopadhyay 2024). Various genes, viz. phenylalanine ammonia-lyase ( PAL ), cinnamate 4-hydroxylase ( C4H ), 4-coumarate CoA ligase ( 4CL ), cinnamoyl CoA reductase ( CCR ), caffeoyl CoA O-methyltransferase ( CCoAOMT ), ferulate 5-hydroxylase ( F5H ), caffeate 3-O-methyltransferase ( COMT ), and cinnamyl alcohol dehydrogenase ( CAD ) are involved in the synthesis of monolignols (Syringyl lignins and Guaicyl lignins) with laccase genes (LAC) acting as downstream of final lignins (Boerjan et al. 2003 ; Sibout et al. 2005 ). Although, salt stress influences lignin biosynthetic gene expression, the precise molecular mechanisms are not fully understood (Chun et al. 2019 ). In mulberry, for instance, the relative expression levels of various MaCADs in leaves ranged from 0.015-fold to 0.10-fold, indicating that expression levels are slightly downregulated in leaves under salt stress relative to control (An et al. 2024b ). Similarly, lodging stress in Arabidopsis , revealed that TaCAD1 exhibited a unique organ-specific expression pattern. Its expression was high in stem, very low in the leaf, and undetectable in the root (An et al. 2024b ). This correlates with the data of relative expression levels of the SiCAD genes in our study. In addition, under 150mM NaCl stress in contrasting Medicago sativa genotypes the expression of upstream genes of phenylpropanoid pathway viz Ms4CL2, MsCCoAOMT, MsCOMT, MsCCR, MsC4H , MsPAL1 , and MsPRX1 were upregulated, whereas MsCAD showed relatively lower expression (Rahman et al. 2022 ). Therefore, salt stress induces SiCADs expression, but the level of accumulation can vary based on the plant genotypes and it can be organic specific. In our study, the RNA seq data analysis of identified genes indicated that SiCAD11, SiCAD19 , and SiCAD31 RKPM is much higher in salt susceptible sesame variety over time compared to salt tolerant ones ( Fig. 13 B ) . Time resolved RKPM values suggests early induction of SiCAD4 ,and SiCAD5 in salt-tolerant plants, which may contribute to salt stress adaptation ( Fig. 11 B ) . The highest RPKM values under salt stress were observed for SiCAD5 (156.66), SiCAD11 (428.40), and SiCAD31 (306.73), while other SiCAD s showed relatively lower expression ( Fig. 11 B). All others SiCADs mostly showed less RKPM values under salt stress ( Fig. 11 B). To validate some of SiCADs , we did qRT-PCR, and found that wild genotype S. mulayanum under 200mM salt stress exhibited high levels of expression of SiCAD4, SiCAD5, SiCAD6, SiCAD8, SiCAD20 , as compared to the cultivated S. indicum under 200mM salt stress (Fig. 13 B-E). Conversely, wild genotype S. mulayanum showed lesser expression levels of SiCAD2 , SiCAD10, SiCAD12 than S. indicum ( Fig. 13 A,F,G ). However, the expression levels were low overall than the control, which are consistent with lower levels of SiCADs expression under salt stress (Rahman et al. 2022 ). These results highlight the dynamic, organ-specific, and developmental stage-dependent expression of SiCADs under salt stress. Further studies, including gene introgression and transgenic experiments, are required to unravel the complex regulatory mechanisms underlying these responses. 4.6 Development and Validation of genic SSR During the development of SSR markers, the first step involves mining potential SSR loci from assembled sequences (Zhang et al. 2012a ). Based on their repeat motifs, SSRs can be classified as perfect (e.g., ATATATATATATAT) or imperfect, which may include nucleotide substitutions or indels (e.g., ATATATAGATAT) (Zhang et al. 2012a ). In the present study, we identified 46 SSRs from the SiCAD genes. These SSRs primarily consisted of mononucleotide (p1) and dinucleotide (p2) repeats, while trinucleotide (p3) repeats were rare. A small number of tetranucleotide (p4) repeats were also detected ( Supplementary Table 5 ). No pentanucleotide repeats were observed. Notably, only two tetranucleotide repeats both of the motif (TATC)₆ were found, occurring in SiCAD21X1 and SiCADX2 . Many studies have been reported the development of genomic SSRs and expressed sequence tag (EST)-derived genic SSRs. Genic SSRs, although less polymorphic, are functionally relevant and have been used in major oilseed crops like rapeseed peanut and soybean (Kresovich et al. 1995 ). In sesame, however, relatively few EST-SSRs were developed and used to detect genetic diversity for sesame germplasm (Zhang et al. 2012a , b ; Wang et al. 2012a ; LinHai and YanXin 2017 ; Samaha et al. 2023 ).Their limited polymorphism and potential location outside gene rich regions have restricted their use. In contrast, genomic SSRs are often highly polymorphic and widely distributed across the genome, making them more suitable for diversity analysis (Wang et al. 2011 ). In our study, we identified a dinucleotide (AT)₁₁ repeat within a SiCAD gene, classifying it as a genic SSR. This marker was developed and validated in a set of parental and derived lines (R1–R8). Agarose gel 1.8% and 6% PAGE analysis revealed a total of 20 alleles, all of which were homozygous and monomorphic (Fig. 2 A,B). This confirms the successful validation of our in silico SSR mining and highlights the potential functional importance of this conserved genic SSR. Unlike genomic SSRs, which are more variable, genic SSRs tend to be conserved due to selective constraints in coding or regulatory regions (Zhang et al. 2012a ). Although monomorphic SSRs are typically excluded from diversity studies due to their lack of variation, they still play important roles in plant breeding programs (Zhang et al. 2012a ). Studies have shown that genic monomorphic SSRs can be used to identify true parental combinations within genetically diverse populations (Omer Hama-Ali and Guan Tan; Nazareno and dos Reis 2011 ; Zhao et al. 2023 ). The monomorphic often overlooked, can reveal conserved regions that are critical for maintaining gene function. Moreover, the flanking regions of such monomorphic SSRs can be informative for studying evolutionary relationships and genetic conservation within and across species (Zhang et al. 2012a ). In conclusion, although the genic SSR identified in this study was monomorphic, its conservation and validation across sesame breeding lines suggest its utility as a functionally relevant marker for gene based breeding and evolutionary analyses (Omer Hama-Ali and Guan Tan; Nazareno and dos Reis 2011 ; Zhao et al. 2023 ). 5. Conclusion and Future Prospects In nature, crops are exposed to a combination of stresses that significantly reduce productivity. Manipulating lignin biosynthetic genes, particularly Cinnamyl Alcohol Dehydrogenases (CADs), offers a promising strategy to enhance stress tolerance. This study provides a foundational understanding of SiCAD genes in sesame under M. phaseolina and salt stress, highlighting their structural features, conserved motifs, and evolutionary relationships with well-studied species. Through gene structure analysis, motif identification, and synteny orthology with Arabidopsis , tomato, and potato, we have uncovered insights into the orthology and diversification of SiCADs . Expression profiling under M. phaseolina and salt stress further confirms their dynamic and stress-responsive nature of SiCADs . These findings establish SiCADs may be crucial components in sesame’s defense arsenal against M. phaseolina . However, we need to carry out more molecular studies, how monolignols can improve productivity of sesame through manipulating this important pathway intermediate of phenylpropanoid biosynthesis pathways. Further, the development and validation of gSSRs support our analysis and open new avenues for future researchers working on marker trait associations. Looking forward, advanced breeding approaches and genome editing tools like CRISPR/Cas9 could be employed to fine tune CAD gene function, paving the way for the development of stress-resilient sesame cultivars capable of withstanding both biotic and abiotic stress challenges. Declarations Data availability The datasets generated or analyzed during the current study are available in the present study. Acknowledgements We acknowledge the technical assistance of Mrs. Kaberi Ghosh, Mr. Jadab Ghosh, and Mr. Swarnava Das, Department of Biological Sciences, BI. Funding GG received funding support from the Bose Institute, Department of Science and Technology, Government of India. MAN was supported by the Council of Scientific & Industrial Research (CSIR) under file number 09/015(0555)/2020-EMR-I. The funding agencies had no involvement in the study design, data collection and analysis, decision to publish, or manuscript preparation Contributions MAN: Conceptualization, Methodology, Investigation, Visualization, Bioinformatic Analysis, interpretation of data and statistical analysis. Writing original draft preparation and editing, Writing- review & editing, Software analysis. GG: Conceptualization, Writing, review & editing, Funds acquisition. Corresponding author Gaurab Gangopadhyay Ethics declarations Ethics approval and consent to participate Not applicable. Consent for publication Not applicable. Competing interests The authors declare no competing interests. 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BMC Plant Biol 19:. https://doi.org/10.1186/s12870-019-1665-6 Zhang Z, Li J, Zhao XQ, et al (2006b) KaKs_Calculator: Calculating Ka and Ks Through Model Selection and Model Averaging. Genomics Proteomics Bioinformatics 4:259–263. https://doi.org/10.1016/S1672-0229(07)60007-2 Zhao M, Shu G, Hu Y, et al (2023) Pattern and variation in simple sequence repeat (SSR) at different genomic regions and its implications to maize evolution and breeding. BMC Genomics 24:1–13. https://doi.org/10.1186/S12864-023-09156-0/FIGURES/8 Tables Tables 1 and 2 are available in the Supplementary Files section Additional Declarations The authors declare no competing interests. Supplementary Files SupplementaryTable1.docx Supplementary Table 1 SupplementaryTable2.xlsx Supplementary Table 2 SupplementaryTable3.xlsx Supplementary Table 3 SupplementaryTable4.xlsx Supplementary Table 4 SupplementaryTable5.xlsx Supplementary Table 5 SupplementaryTable6.xlsx Supplementary Table 6 SupplementaryTable7.xlsx Supplementary Table 7 SupplementaryTable8.xlsx Supplementary Table 8 supplementaryFig.1.jpg Supplementary Fig. 1 M. phaseolina isolate: Dark colored mycelium and radial growth pattern. SupplementaryFig.2.jpg Supplementary Fig. 2 Domain architecture of the identified SiCAD associated proteins. Scale bar present the length of amino acid (aa) present in the CDS region of the proteins. SupplementaryFig.3.jpg Supplementary Fig. 3 Motifs identified by MEME tools in Sesame CAD protein sequences. Five motifs were identified and indicated by different colors. Also the motif sequences are also present. 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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-8161012","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":547944189,"identity":"a01b170e-bedc-4517-89e6-e14fcc13a114","order_by":0,"name":"Mushtaq Ahmad Najar","email":"","orcid":"","institution":"Department of Biological Sciences, Bose Institute, EN 80, Sector V, Salt Lake, Kolkata, 700091, India","correspondingAuthor":false,"prefix":"","firstName":"Mushtaq","middleName":"Ahmad","lastName":"Najar","suffix":""},{"id":547944190,"identity":"f18ce86b-fb36-4630-a65f-e5b855fcc4b3","order_by":1,"name":"Gaurab Gangopadhyay","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA0UlEQVRIiWNgGAWjYLACxgYbZgYJGI+ZOC1ppGs5zIDQQgjIu58x+/Bzx3l2/tnNhz98YLCTZ2DnPYBXi+GZHOOZvWduM0vcOZYmOYMh2bCBmS8Bv5aGHGMG3rbbzAYSOWbMPAzMCQzMPAb4tfS/MWb823YOpMX48x+GesJa5IEqmXnbDoC0GEgzMBwmrMVA4lkxs+yZZIhfegyOG7YRtKU/eTPj2x12yeAQ+1FRLc/Pf4aALQcgdDKUy8DAhlc9yJYGCG1HSOEoGAWjYBSMYAAAlC47DY4U4qEAAAAASUVORK5CYII=","orcid":"","institution":"Department of Biological Sciences, Bose Institute, EN 80, Sector V, Salt Lake, Kolkata, 700091, India","correspondingAuthor":true,"prefix":"","firstName":"Gaurab","middleName":"","lastName":"Gangopadhyay","suffix":""}],"badges":[],"createdAt":"2025-11-20 06:31:43","currentVersionCode":1,"declarations":{"humanSubjects":false,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-8161012/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8161012/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":96464595,"identity":"789d65e2-c177-4840-9388-b339f56ce3bc","added_by":"auto","created_at":"2025-11-21 11:02:05","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":587294,"visible":true,"origin":"","legend":"","description":"","filename":"Manuscript.docx","url":"https://assets-eu.researchsquare.com/files/rs-8161012/v1/5d105fd3a642430194270aed.docx"},{"id":96464590,"identity":"0372babb-570a-4012-8ef3-3b7a301a98cc","added_by":"auto","created_at":"2025-11-21 11:02:05","extension":"json","order_by":1,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":342,"visible":true,"origin":"","legend":"","description":"","filename":"rs8161012.json","url":"https://assets-eu.researchsquare.com/files/rs-8161012/v1/222d5e2552c8ff82de674a38.json"},{"id":96464602,"identity":"eb92abfd-93b0-4e1b-8387-52e518fe4ef5","added_by":"auto","created_at":"2025-11-21 11:02:06","extension":"xml","order_by":2,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":264080,"visible":true,"origin":"","legend":"","description":"","filename":"rs81610120enriched.xml","url":"https://assets-eu.researchsquare.com/files/rs-8161012/v1/091907af31bec1abf94104ff.xml"},{"id":96602900,"identity":"83d318cb-8532-4331-bc14-aa7946ab373f","added_by":"auto","created_at":"2025-11-24 09:04:23","extension":"xml","order_by":3,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":260276,"visible":true,"origin":"","legend":"","description":"","filename":"rs81610120structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-8161012/v1/d7bf64fdf693d211c1eabd2b.xml"},{"id":96602915,"identity":"436848d2-2561-4a40-85da-9dce0ef1dd7f","added_by":"auto","created_at":"2025-11-24 09:04:42","extension":"html","order_by":4,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":283225,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8161012/v1/df2450d6769cc538615f0167.html"},{"id":96603244,"identity":"61a71d27-f456-4828-bc05-13ba3508f3ba","added_by":"auto","created_at":"2025-11-24 09:07:45","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":501247,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePlant material A\u003c/strong\u003e) \u003cem\u003eS. indicum\u003c/em\u003e with characteristic white coloured flowers \u003cstrong\u003eB\u003c/strong\u003e) \u003cem\u003eS. mulayanumn \u003c/em\u003ewith pinkish corolla type flowers. These two genotypes are maintained at Madhyamgram experimental farm Bose institute Kolkata.\u003c/p\u003e","description":"","filename":"Fig.1.png","url":"https://assets-eu.researchsquare.com/files/rs-8161012/v1/de695b807aaf7ab8ee714e6c.png"},{"id":96603408,"identity":"a4c5abe3-b49d-4dfa-9bb6-63eed8c50bff","added_by":"auto","created_at":"2025-11-24 09:08:59","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":127192,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAgarose (1.8%) and UREA-PAGE (6%) gel electrophoresis of genic SSR marker.\u003cbr\u003e\nA) \u003c/strong\u003eAgarose gel (1.8%) showing a single amplicon of 242 bp. Lanes: 1 – \u003cem\u003eS. indicum\u003c/em\u003e; 2 – \u003cem\u003eS. mulayanum\u003c/em\u003e; 3–10 – Recombinant lines (R1–R8). M = 100 bp DNA ladder (Thermo Scientific, USA). B) UREA-PAGE (6%) showing a monomorphic banding pattern. Lanes: 1 – \u003cem\u003eS. indicum\u003c/em\u003e; 2 – \u003cem\u003eS. mulayanum\u003c/em\u003e; 3–10 – Recombinant lines (R1–R8). M = O'GeneRuler Ultra Low Range DNA Ladder (Thermo Scientific); lowest band = 10 bp, highest = 300 bp.\u003c/p\u003e","description":"","filename":"Fig.2.png","url":"https://assets-eu.researchsquare.com/files/rs-8161012/v1/6b28dfb3533116c17272f732.png"},{"id":96464606,"identity":"e4710c6e-2706-4867-8c89-3ff5ac75023a","added_by":"auto","created_at":"2025-11-21 11:02:06","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":4050815,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eMapping of sesame \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eSiCAD\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e genes based on their physical positions\u003c/strong\u003e. Vertical bars represent linkage groups (LG) of the sesame genome. The LG numbers are indicated at left side of vertical bar. Red lines linked duplicated genes (Paralogous pairs). The scale indicated the length of the linkage groups.\u003c/p\u003e","description":"","filename":"Fig.3.png","url":"https://assets-eu.researchsquare.com/files/rs-8161012/v1/cc0da3201f5f29b4e43ddb27.png"},{"id":96603319,"identity":"5fa7bfff-6f12-4175-8b47-5a5c25871b62","added_by":"auto","created_at":"2025-11-24 09:08:15","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":135659,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eKa/Ks ratio\u003c/strong\u003e. The gene pairs and there \u003cem\u003eka\u003c/em\u003e/\u003cem\u003eks\u003c/em\u003eratio. These gene pairs were segmentally duplicated pairs (Paralogous pairs).\u003c/p\u003e","description":"","filename":"Fig.4.png","url":"https://assets-eu.researchsquare.com/files/rs-8161012/v1/916543e164f8a796115b70ca.png"},{"id":96603206,"identity":"6b946faa-9142-433d-94a6-f17005627214","added_by":"auto","created_at":"2025-11-24 09:07:31","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":11561109,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eGene Structure Analysis\u003c/strong\u003e: Red wedge indicates exon regions, blue rectangle bars indicate upstream/downstream regions and blue dash indicates intron regions.\u003c/p\u003e","description":"","filename":"Fig.5.png","url":"https://assets-eu.researchsquare.com/files/rs-8161012/v1/fccd3b978e5739cbff6273d1.png"},{"id":96602789,"identity":"d26f1538-8314-4316-9f6b-220c438667c9","added_by":"auto","created_at":"2025-11-24 09:01:44","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":1041170,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCis-element analysis\u003c/strong\u003e: Dot plot illustrates the number of cis elements present in the \u003cem\u003eSiCAD\u003c/em\u003es .We categorised them into three different categories: Development, Hormone and Stress element.\u003c/p\u003e","description":"","filename":"Fig.6.png","url":"https://assets-eu.researchsquare.com/files/rs-8161012/v1/4b0c837c19648015b8d94bdd.png"},{"id":96464600,"identity":"9c325566-af3d-4d1d-b961-7fe9d2951042","added_by":"auto","created_at":"2025-11-21 11:02:06","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":652549,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDistribution of common binding elements in identified SiCADs: \u003c/strong\u003eHeatmap showing number of time common cis-element present.\u003c/p\u003e","description":"","filename":"Fig.7.png","url":"https://assets-eu.researchsquare.com/files/rs-8161012/v1/04f85ad3d0a9eb4ad31b0905.png"},{"id":96602902,"identity":"429f6b4a-a323-40a9-aeed-4d9c070f4364","added_by":"auto","created_at":"2025-11-24 09:04:24","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":1411966,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePhylogentic and Synteny Analyis of sesame with \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eArabiodpsis\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e, \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eSolanum lycoperiscum \u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003eand \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eSolanum tuberosum. \u003c/strong\u003e\u003c/em\u003eA) Phylogentics analysis between Sesame, \u003cem\u003eArabidospis\u003c/em\u003e and Rice resulted in ten classes. B) Synteny Analysis between \u003cem\u003eArabidopsis\u003c/em\u003e and sesame:Red bars indicate the linkages of sesame which are sixteen while as purple bars indicates \u003cem\u003eArabidopsis \u003c/em\u003echromsomes. C) Synteny analysis between \u003cem\u003eS. lycopersicum\u003c/em\u003e and sesame. Red bars indicate LGs of sesame and purple bars indicate the chromsomes of \u003cem\u003eS. lycopersicum\u003c/em\u003e. D) Synteny Analyis between \u003cem\u003eS. tuberosum\u003c/em\u003e and sesame genome. Red bars indicate LGs of sesame and purple bars indicate the chromsomes of \u003cem\u003eS. tuberosum\u003c/em\u003e. The coloured linkers illustrate the orthology between the identified Sesame \u003cem\u003eSiCADs\u003c/em\u003egenes and counter genome.\u003c/p\u003e","description":"","filename":"Fig.8.png","url":"https://assets-eu.researchsquare.com/files/rs-8161012/v1/0644ed460ba48c0a5eaaa431.png"},{"id":96464615,"identity":"13ebc311-0793-4a84-8c22-734e7b4c43f5","added_by":"auto","created_at":"2025-11-21 11:02:06","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":5462281,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eProtein-protein interaction\u003c/strong\u003e between the \u003cem\u003eSiCADs\u003c/em\u003e amino acid sequences based on interactome of model plant \u003cem\u003eArabidopsis. \u003c/em\u003eCircles indicates the genes.\u003c/p\u003e","description":"","filename":"Fig.9.png","url":"https://assets-eu.researchsquare.com/files/rs-8161012/v1/b2de5871b31feb4e5df55262.png"},{"id":96464616,"identity":"7f42c49e-d8a2-476b-96c2-2058470a42df","added_by":"auto","created_at":"2025-11-21 11:02:06","extension":"png","order_by":10,"title":"Figure 10","display":"","copyAsset":false,"role":"figure","size":488324,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eGO and KEGG enrichment analysis\u003c/strong\u003e: A) GO enrichment analysis of the \u003cem\u003eSiCAD\u003c/em\u003efamily,denoting various GO terms associated with the identified genes. B) KEGG enrichment identified various pathways related to \u003cem\u003eSiCAD\u003c/em\u003e genes mainly phenylpropanoid pathway, which is crucial to salt stress.\u003c/p\u003e","description":"","filename":"Fig.10.png","url":"https://assets-eu.researchsquare.com/files/rs-8161012/v1/9c4d3c59fc33a3de4ae31624.png"},{"id":96464620,"identity":"9942e9fc-b960-4a4d-9d55-d1a5f915260b","added_by":"auto","created_at":"2025-11-21 11:02:06","extension":"png","order_by":11,"title":"Figure 11","display":"","copyAsset":false,"role":"figure","size":554105,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eHeatmap of RKPM values from RNA seq data\u003c/strong\u003e: A) Identified \u003cem\u003eSiCADs\u003c/em\u003e and there RPKM values obtained from RNA seq data concering salt stress at different time intervals in sesame. SS (Salt susceptible) and ST (Salt tolerant) B). Identified \u003cem\u003eSiCADs\u003c/em\u003e in two genotypes \u003cem\u003eS.indicum\u003c/em\u003e and \u003cem\u003eS.mulayunum\u003c/em\u003e showing RPKM values. SIC (\u003cem\u003eS.indiucm\u003c/em\u003econtrol), SII (\u003cem\u003eS.indicum\u003c/em\u003e infected), SMC (\u003cem\u003eS.mulayanum\u003c/em\u003e control) and SMI (\u003cem\u003eS.mulayanum\u003c/em\u003e infected).\u003c/p\u003e","description":"","filename":"Fig.11.png","url":"https://assets-eu.researchsquare.com/files/rs-8161012/v1/4d655ae0c099a778ab30f5b1.png"},{"id":96464617,"identity":"b9310a13-48d0-4412-a52d-4a6ae1ee576b","added_by":"auto","created_at":"2025-11-21 11:02:06","extension":"png","order_by":12,"title":"Figure 12","display":"","copyAsset":false,"role":"figure","size":592608,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eRelative expression levels of genes concerning \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eM.phaseolina \u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003einfection \u003c/strong\u003eA) \u003cem\u003eSiCAD2 \u003c/em\u003eB)\u003cem\u003e SiCAD4 \u003c/em\u003eC)\u003cem\u003e SiCAD5 \u003c/em\u003eD)\u003cem\u003e SiCAD6 \u003c/em\u003eE)\u003cem\u003e SiCAD8 \u003c/em\u003eF)\u003cem\u003e SiCAD10 \u003c/em\u003eG)\u003cem\u003e SiCAD12 \u003c/em\u003eand\u003cem\u003e \u003c/em\u003eH)\u003cem\u003e SiCAD20\u003c/em\u003e. The expression of these genes in two sesame genotypes (\u003cem\u003eS. indicum\u003c/em\u003e—SI, \u003cem\u003eS. mulayanum\u003c/em\u003e—SM) in control and induced \u003cem\u003eMacrophomina\u003c/em\u003e-infection after 48hr and 96hr. Error bars represent standard deviation (SD) values (n= 3), \u003cem\u003eP\u003c/em\u003e\u0026lt; 0.05. (* p \u0026lt; 0.05, ** p \u0026lt; 0.01, *** p \u0026lt; 0.001, **** p \u0026lt; 0.0001).Welch two sample t-test for control vs 48hr, control vs 96hr in two genotypes.\u003c/p\u003e","description":"","filename":"Fig.12.png","url":"https://assets-eu.researchsquare.com/files/rs-8161012/v1/2ad9119fc58c090efdbf0977.png"},{"id":96602992,"identity":"e9ec211b-d6b6-4e56-96b3-fd7fda5eddb1","added_by":"auto","created_at":"2025-11-24 09:05:49","extension":"png","order_by":13,"title":"Figure 13","display":"","copyAsset":false,"role":"figure","size":350618,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eRelative expression levels of genes concerning salt stress \u003c/strong\u003eA) \u003cem\u003eSiCAD2 \u003c/em\u003eB)\u003cem\u003e SiCAD4 \u003c/em\u003eC)\u003cem\u003e SiCAD5 \u003c/em\u003eD)\u003cem\u003e SiCAD6 \u003c/em\u003eE)\u003cem\u003e SiCAD8 \u003c/em\u003eF)\u003cem\u003e SiCAD10 \u003c/em\u003eG)\u003cem\u003e SiCAD12 and \u003c/em\u003eH)\u003cem\u003e SiCAD20\u003c/em\u003e. The expression of these genes in two sesame genotypes (\u003cem\u003eS. indicum\u003c/em\u003e—SI, \u003cem\u003eS. mulayanum\u003c/em\u003e—SM) in control and 200mM NaCl concentration. Error bars represent standard deviation (SD) values (n= 3), \u003cem\u003eP\u003c/em\u003e\u0026lt; 0.05. Welch two sample t-test for control vs 200mM NaCl between genotypes. (* p \u0026lt; 0.05, ** p \u0026lt; 0.01, *** p \u0026lt; 0.001, **** p \u0026lt; 0.0001).\u003c/p\u003e","description":"","filename":"Fig.13.png","url":"https://assets-eu.researchsquare.com/files/rs-8161012/v1/358c56034424c9fd2ca41abf.png"},{"id":96464619,"identity":"cc230121-d986-4c56-b976-495223c53e31","added_by":"auto","created_at":"2025-11-21 11:02:06","extension":"png","order_by":14,"title":"Figure 14","display":"","copyAsset":false,"role":"figure","size":399181,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eChord Plot : \u003c/strong\u003eComprehensive analsysis of \u003cem\u003eSiCADs\u003c/em\u003e identified, which are involved in phenylpropanoid biosynthesis pathway and Biosynthesis of secondary metabolites.\u003c/p\u003e","description":"","filename":"Fig.14.png","url":"https://assets-eu.researchsquare.com/files/rs-8161012/v1/9c12e179867cafd7c197a84f.png"},{"id":96708096,"identity":"e0a1b931-3e6c-4bc3-8d49-6a8f82bce6d7","added_by":"auto","created_at":"2025-11-25 09:56:35","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":29709760,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8161012/v1/d0defeb5-c494-402a-a605-d8d6a8bff577.pdf"},{"id":96603274,"identity":"1bfa6a2f-1b72-4b14-8d12-a85dfb641cb2","added_by":"auto","created_at":"2025-11-24 09:07:56","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":15814,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary Table 1\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"SupplementaryTable1.docx","url":"https://assets-eu.researchsquare.com/files/rs-8161012/v1/c0ac1f5e24912a6a778bdc3d.docx"},{"id":96603480,"identity":"c292c144-de75-409e-9a63-64c3e09b7faf","added_by":"auto","created_at":"2025-11-24 09:09:31","extension":"xlsx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":9376,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary Table 2\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"SupplementaryTable2.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-8161012/v1/6972f5ee7e822664da93776e.xlsx"},{"id":96464596,"identity":"e0e8ed8f-a939-4af4-a76e-cd0b7f9b107b","added_by":"auto","created_at":"2025-11-21 11:02:06","extension":"xlsx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":13948,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary Table 3\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"SupplementaryTable3.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-8161012/v1/f0ef1f8bbf49fafa743c1aaf.xlsx"},{"id":96603668,"identity":"1c70dbde-e2b0-4274-802e-928a502bb9af","added_by":"auto","created_at":"2025-11-24 09:10:59","extension":"xlsx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":435001,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary Table 4\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"SupplementaryTable4.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-8161012/v1/40c06da4b86c00cf56e3ee98.xlsx"},{"id":96603354,"identity":"5a02ea92-8dc7-466c-a590-3c0ede88fff2","added_by":"auto","created_at":"2025-11-24 09:08:32","extension":"xlsx","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":11138,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary Table 5\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"SupplementaryTable5.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-8161012/v1/0aa425fbb8d6f0eae70e65e4.xlsx"},{"id":96602977,"identity":"246fc2f4-9e51-4727-ab24-4eb4abbbe676","added_by":"auto","created_at":"2025-11-24 09:05:42","extension":"xlsx","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":12190,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary Table 6\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"SupplementaryTable6.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-8161012/v1/4d10049da29726de93a8f194.xlsx"},{"id":96464597,"identity":"c38d9fee-79e8-4fe0-a8df-4b26f76363ae","added_by":"auto","created_at":"2025-11-21 11:02:06","extension":"xlsx","order_by":7,"title":"","display":"","copyAsset":false,"role":"supplement","size":11325,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary Table 7\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"SupplementaryTable7.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-8161012/v1/88a3616b49a1f18511c89a8a.xlsx"},{"id":96603047,"identity":"7ae67b29-d1a8-4827-b17a-cfc0232b7c13","added_by":"auto","created_at":"2025-11-24 09:06:21","extension":"xlsx","order_by":8,"title":"","display":"","copyAsset":false,"role":"supplement","size":9793,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary Table 8\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"SupplementaryTable8.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-8161012/v1/e66164c6f48c30804e16ceea.xlsx"},{"id":96464599,"identity":"5c933dcb-8680-4147-8373-c15417f4442a","added_by":"auto","created_at":"2025-11-21 11:02:06","extension":"jpg","order_by":9,"title":"","display":"","copyAsset":false,"role":"supplement","size":36135,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary Fig. 1 \u003c/strong\u003e\u0026nbsp;\u003cem\u003eM. phaseolina\u003c/em\u003e\u003cstrong\u003e \u003c/strong\u003eisolate: Dark colored mycelium and radial growth pattern.\u003c/p\u003e","description":"","filename":"supplementaryFig.1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8161012/v1/fc72bc1279c262369a7f9161.jpg"},{"id":96464612,"identity":"3e521199-b6f2-474b-a648-58a0cfab8e5a","added_by":"auto","created_at":"2025-11-21 11:02:06","extension":"jpg","order_by":10,"title":"","display":"","copyAsset":false,"role":"supplement","size":220280,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary Fig. 2\u003c/strong\u003e \u0026nbsp;Domain architecture of the identified \u003cem\u003eSiCAD\u003c/em\u003e associated proteins. Scale bar present the length of amino acid (aa) present in the CDS region of the proteins.\u003c/p\u003e","description":"","filename":"SupplementaryFig.2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8161012/v1/de84e4795cc13395a3d3d617.jpg"},{"id":96464618,"identity":"75a9e2b4-a77a-455e-a911-99c75cb5216a","added_by":"auto","created_at":"2025-11-21 11:02:06","extension":"jpg","order_by":11,"title":"","display":"","copyAsset":false,"role":"supplement","size":403137,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary Fig. 3 \u003c/strong\u003eMotifs identified by MEME tools in Sesame CAD protein sequences. Five motifs were identified and indicated by different colors. Also the motif sequences are also present.\u003c/p\u003e","description":"","filename":"SupplementaryFig.3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8161012/v1/37d513f5061232783195e8ea.jpg"},{"id":96464610,"identity":"1c8d70da-22e6-4413-9bea-bc444fce8641","added_by":"auto","created_at":"2025-11-21 11:02:06","extension":"docx","order_by":12,"title":"","display":"","copyAsset":false,"role":"supplement","size":29408,"visible":true,"origin":"","legend":"","description":"","filename":"Table.docx","url":"https://assets-eu.researchsquare.com/files/rs-8161012/v1/c1dc66758fa746df51cfe112.docx"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eExpression Landscape, Evolutionary Insights, and Duplication Patterns of Cinnamyl Alcohol Dehydrogenase Genes Under \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eMacrophomina phaseolina\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e Infection and Salt Stress in Sesame\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eThe Department of Economic and Social affairs of the United Nations, 2015 reported that global population is projected to exceed 9.7\u0026nbsp;billion by 2050. To feed such massive population, will require development of elite breed of crop varieties which would withstand the increasing threat of abiotic and biotic stress due to global perturbations in seasonal variations. Biotic stress (fungal infestations) and abiotic stress (salt) is becoming global threat to agriculture productivity, adversely affecting many staple crops. \u003cem\u003eSesamum indicum\u003c/em\u003e, an important oil seed crop, is also labile to both type of stress, which limits its agricultural productivity, and geographic distribution. \u003cem\u003eS. indicum\u003c/em\u003e is vulnerable to infection by \u003cem\u003eM. phaseolina\u003c/em\u003e which can cause charcoal rot, leading to crop loss at seedling stage and at production stage which accounts up to 80% loss (Marquez et al. \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Study have been carried out which highlights the effect of salt stress on development, yield at germination and seedling stage in sesame (Li et al. \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Zhang et al. \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe lignin, a crucial secondary cell wall component has been identified as an epicentre of defense response and involved in salt stress interactions. \u003cem\u003eCinnamoyl alcohol dehydrogenase\u003c/em\u003e (\u003cem\u003eCAD\u003c/em\u003e) which is involved in the reduction of cinnamal aldehydes into cinnamyl alcohols, the last step in monolignol (Syringyl alcohols and Guiacyl lignin) biosynthesis before oxidative phosphorylation in cell wall by laccases. The diverse \u003cem\u003eCAD\u003c/em\u003es has been functionally validated in many plant species like \u003cem\u003eArabidopsis\u003c/em\u003e (Sibout et al. \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2003\u003c/span\u003e), tobacco (Halpin et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e1992\u003c/span\u003e), rice (Zhang et al. \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e2006a\u003c/span\u003e), and \u003cem\u003eArtesmia annua\u003c/em\u003e (Li et al. \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). \u003cem\u003eCAD\u003c/em\u003e is a Zn\u003csup\u003e2+\u003c/sup\u003e binding NADPH dependent homodimer responsible for converting cinnamaldehydes to hydroxyphenyl (H), guaiacyl (G), and syringyl (S) monolignols (Mansell et al. \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e1974\u003c/span\u003e). Many studies have established the role of \u003cem\u003eCADs\u003c/em\u003e ranging from functional to omics analysis in both defense response against fungal pathogens, and salt stress. Following studies indicate role of \u003cem\u003eCADs\u003c/em\u003e in fungal infestations viz \u003cem\u003eMagnaporthe oryzae\u003c/em\u003e in \u003cem\u003eOrzyae sativa\u003c/em\u003e (Meng et al. \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), \u003cem\u003eUstilago maydis in Zea mays\u003c/em\u003e (Ruan et al. \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), \u003cem\u003eVerticillium dahliae\u003c/em\u003e in \u003cem\u003eGossypium hirsutum\u003c/em\u003e L.(Li et al. \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), \u003cem\u003eRhizoctonia solani\u003c/em\u003e, \u003cem\u003eFusarium oxysporum\u003c/em\u003e, and \u003cem\u003eCytospora\u003c/em\u003e sp.in \u003cem\u003ePopulus trichocarpa\u003c/em\u003e (Bagniewska-Zadworna et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2014a\u003c/span\u003e). The role of \u003cem\u003eCADs\u003c/em\u003e in salt stress is also established by the following studies \u003cem\u003eOrzyae sativa\u003c/em\u003e(Leng et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), \u003cem\u003eArabidopsis thialiana\u003c/em\u003e (Chen et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2007\u003c/span\u003e), \u003cem\u003eTriticum aestivum\u003c/em\u003e (Yan et al. \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e2020\u003c/span\u003e),\u003cem\u003eGossypium hirsutum\u003c/em\u003e L.(Ibrahim et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) and \u003cem\u003eZea mays\u003c/em\u003e (Chen et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe above studies indicate crucial role of CAD genes, so it necessitates of identifying the entire \u003cem\u003eSiCAD\u003c/em\u003e genes in the genome of \u003cem\u003eSesamum\u003c/em\u003e, which would be a great leap in understanding the functional studies under \u003cem\u003eM. phaseolina\u003c/em\u003e infection and salt stress. Our focus of this study would be identification, characterization, duplication events, and evolutionary relationship of \u003cem\u003eSiCAD\u003c/em\u003es genes with other crop species. Furthermore, expression analysis of the identified genes both by RNA-seq, and qRT-PCR analysis would be great resource for understanding the patterns of these genes under \u003cem\u003eM. phaseolina\u003c/em\u003e infection and salt stress.\u003c/p\u003e"},{"header":"2. Material and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\n \u003ch2\u003e2.1. Plant Material\u003c/h2\u003e\n \u003cp\u003eThe sesame (\u003cem\u003eSesamum indicum\u003c/em\u003e) cultivar (Accession No. 7192 NBPGR germplasm collection India) obtained from the NBPGR and \u003cem\u003eS. mulayanum\u003c/em\u003e (Courtesy of Mr. K Masuda) was used in all experiments (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). Seeds were initially subjected to surface sterilization with 4% NaOCl (Sodium hypochlorite) for 10 min, followed by thorough washing with distilled water many times (Najar and Gangopadhyay 2024). Subsequently, the seeds were germinated, and cultivated in plastic pots under standard conditions (daily: 28\u0026thinsp;\u0026plusmn;\u0026thinsp;1\u0026deg;C for 16 h under 200 \u0026micro;mol m\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e s\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e light, followed by 23\u0026thinsp;\u0026plusmn;\u0026thinsp;1\u0026deg;C for 8 h of darkness) until reaching four true leaves.\u003c/p\u003e\n \u003cp\u003eFour-week-old sesame seedlings at four leaf stage were subjected to biotic and abiotic stresses under identical growth conditions. The biotic stress was induced by inoculating the plants with pathogenic fungus \u003cem\u003eM. phaseolina\u003c/em\u003e, following the method as described in our previous publication (Najar and Gangopadhyay 2024). Leaf samples were collected at different time points 0 hour (control), 48 hours, and 96 hours post-inoculation and were immediately stored at -80\u0026deg;C for RNA extraction. Another set of 4-week-old seedlings were subjected to salt stress (NaCl) of 200mM concentration, while control plants were subjected with sterile autoclaved double distilled water. Leaf tissues from both control and salt-treated plants were harvested, flash frozen, and stored at -80\u0026deg;C for subsequent RNA extraction. The experiment was laid out as a complete randomized design (CRD). Leaf tissues from both \u003cem\u003eS. indicum\u003c/em\u003e and \u003cem\u003eS. mulayanum\u003c/em\u003e were collected in three biological replicates, for each treatment (biotic and abiotic) and control condition.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\n \u003ch2\u003e2.2. DNA extraction and Identification of the Fungus\u003c/h2\u003e\n \u003cp\u003eWe isolated fungus from infected plant of \u003cem\u003eS. indicum\u003c/em\u003e in Madhyamgram Experimental Farm Bose Institute Kolkata, and cultured the fungus on potato dextrose agar (PDA) at 30\u0026thinsp;\u0026plusmn;\u0026thinsp;1\u0026deg;C in the dark. The microscopic characterisation was done using a Leitz Biomed CD-L0170 compound microscope (\u003cstrong\u003eSupplementary Fig.\u0026nbsp;1\u003c/strong\u003e). Further identification was validated by sequencing internal transcribed spacers (ITS) using rDNA gene cluster consisting of ITS1, 5.8S rDNA and ITS4, was amplified using primer ITS1 5\u0026prime;-TCCGTAGGTGAACCTGCGG-3\u0026prime; and ITS4 5\u0026apos;- TCCTCCGCTTATTGATATGC-3\u0026prime; (White et al. \u003cspan class=\"CitationRef\"\u003e1990\u003c/span\u003e).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\n \u003ch2\u003e2.3. RNA extraction and cDNA synthesis\u003c/h2\u003e\n \u003cp\u003eFrozen stored leaf tissues (100 mg) were used for extracting total RNA from leaves of sesame seedlings subjected to biotic (\u003cem\u003eMp\u003c/em\u003e-inoculated) and abiotic (salt stress) respectively using the Spectrum\u0026trade; Plant Total RNA kit (Sigma). To check the purity of the RNA samples 1% agarose gel stained with EtBr and quantification was done by NanoDrop spectrophotometer (NanoDrop\u0026reg; ND1000; Thermo Fisher Scientific Inc., Waltham, MA, USA). The synthesis of cDNA was performed using the QuantiTect\u0026reg; Reverse Transcription kit (QIAGEN) following the manufacturer\u0026rsquo;s protocol. To remove genomic DNA contamination, an RT-minus control was prepared using the same cDNA synthesis protocol, except without the addition of the reverse transcriptase enzyme.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\n \u003ch2\u003e2.4. Quantitative real-time PCR analysis, and Primer Designing\u003c/h2\u003e\n \u003cp\u003eThe qRT-PCR analysis was performed using the Maxima SYBR Green/ROX qPCR mix (Thermo Scientific, USA) with gene-specific primers on an AriaMxfast Real-time PCR system (Agilent USA). Subsequently, all synthesized cDNAs samples were diluted 1:3 with nuclease-free water before being used in the qPCR step, following company manufacture protocol. \u0026beta;-actin (NCBI accession: XM_011079162) was used as the reference gene for normalizing candidate gene expression across all samples, and gene-specific primers were designed using NCBI\u0026rsquo;s Primer-BLAST tool (\u003cstrong\u003eSupplementary Table\u0026nbsp;1).\u003c/strong\u003e The mRNA expression levels were assessed by calculating the \u0026Delta;Ct, representing the difference between the CT values of the target gene and the reference gene \u0026beta;-actin. Fold changes in gene expression were then determined using the 2^-\u0026Delta;\u0026Delta;Ct method (Livak and Schmittgen \u003cspan class=\"CitationRef\"\u003e2001\u003c/span\u003e).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\n \u003ch2\u003e2.5. Identification and Classification of \u003cem\u003eSiCAD\u003c/em\u003e Genes in Sesame Genome\u003c/h2\u003e\n \u003cp\u003eThe CAD gene sequences of \u003cem\u003eArabidopsis\u003c/em\u003e were downloaded from (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.arabidopsis.org/\u003c/span\u003e\u003c/span\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e).\u003c/span\u003e The amino acid sequence of \u003cem\u003eAtCAD\u003c/em\u003e family (AT4G37990.1, AT2G21890.1, AT4G39330.1, AT3G19450.1, AT1G72680.1, AT4G37980.1, AT4G34230.1, AT4G37970.1, AT2G21730.1) was selected as the seed to search all related \u003cem\u003eSiCAD\u003c/em\u003e genes in sesame genome. Based on genome and proteome sequences of sesame downloaded from ensemble.org (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://plants.ensembl.org/index.html\u003c/span\u003e\u003c/span\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e)\u003c/span\u003e, an extensive survey was performed to identify all related members of \u003cem\u003eSiCAD\u003c/em\u003e gene family in the sesame genome. The CAD domains were identified using the HMMER 3.0 (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.ebi.ac.uk/Tools/hmmer/\u003c/span\u003e\u003c/span\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e)\u003c/span\u003e, by searching for conserved Pfam domains designated as zinc-binding dehydrogenase (PF00107) and alcohol dehydrogenase GroES-like domain (PF08240).\u003c/p\u003e\n \u003cp\u003eThe SMART program and Pfam were used to further confirm the presence of PF08240 and PF00107. All the candidate genes, which did not contain PF08240 and PF00107 domains were removed. Furthermore, MARCOIL program was employed to detect the coiled coil structure and sequences which does not contain this were removed. The filtered gene sequences were proceeded for physical and chemical attributes using ProtParam tool (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://web.expasy.org/protparam/\u003c/span\u003e\u003c/span\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e).\u003c/span\u003e\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\n \u003ch2\u003e2.6. Phylogenetic Analysis, Gene Structure, Motif-identification and Cis-elements analysis of \u003cem\u003eSiCADs\u003c/em\u003e\u003c/h2\u003e\n \u003cp\u003eTo investiagate the evolutionary relationship between the \u003cem\u003eSiCAD\u003c/em\u003e genes of Sesame, \u003cem\u003eArabidopsis\u003c/em\u003e and \u003cem\u003eOryza sativa\u003c/em\u003e, multiple sequence alignment was carried out by using ClustalW program an inbuilt software of MEGA 6.0 software (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.megasoftware.net/\u003c/span\u003e\u003c/span\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e)\u003c/span\u003e (Tamura et al. \u003cspan class=\"CitationRef\"\u003e2011\u003c/span\u003e). The gap extension penalty of 0.2 and gap open penalty were set to 10. The alignment results were utilized to construct an unrooted Maximum Likelihood (ML) tree with 1,000 bootstrap replicates, using the web-based bioinformatics platform Gene Structure Display Server 2.0 (GSDS). The web-based bioinformatics tool GSDS was employed, available at \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://gsds.cbi.pku.edu.cn\u003c/span\u003e\u003c/span\u003e for gene structure analysis (exon-intron substructure map) (Hu et al. \u003cspan class=\"CitationRef\"\u003e2015\u003c/span\u003e). All protein sequence of 32 \u003cem\u003eSiCAD\u003c/em\u003es including the isoforms were subjected to Multiple Expectation maximizations for Motif Elicitation (MEME) to identify conserved protein motifs. The relevant parameters were set as follows: minimum width of 6, maximum width of 50, the maximum number of motifs was set to 5.\u003c/p\u003e\n \u003cp\u003eTo find common promoters, which are widely known for their role in stress and development, identified \u003cem\u003eSiCAD\u003c/em\u003e sequences were uploaded to Plant CARE database available on (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://sphinx.rug.ac.be:8080/PlantCARE/\u003c/span\u003e\u003c/span\u003e) (Lescot et al. \u003cspan class=\"CitationRef\"\u003e2002\u003c/span\u003e).\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e2.7. Chromosomal mapping, Gene Duplications, and Comparative Mapping of Orthologous\u003c/strong\u003e \u003cstrong\u003eSiCAD\u003c/strong\u003e \u003cstrong\u003eGenes in Sesame\u003c/strong\u003e, \u003cstrong\u003eArabidopsis\u003c/strong\u003e, \u003cstrong\u003eTomato and Potato\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eThe \u003cem\u003eSiCAD\u003c/em\u003e genes were mapped onto 16 Linkage Groups (LGs) of sesame genome using TBtools (Chen et al. \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e). To identify paralogous gene pairs and duplication events within the sesame genome, MCScanX analysis was performed (Wang et al. \u003cspan class=\"CitationRef\"\u003e2012b\u003c/span\u003e). We eestimated synonymous (\u003cem\u003eK\u003c/em\u003e\u003csub\u003e\u003cem\u003es\u003c/em\u003e\u003c/sub\u003e) and non-synonymous (\u003cem\u003eK\u003c/em\u003e\u003csub\u003e\u003cem\u003ea\u003c/em\u003e\u003c/sub\u003e) substution rates of identified sequences related to four duplicated gene pairs within the sesame genome, using PAL2NAL (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.bork.embl.de/pal2nal\u003c/span\u003e\u003c/span\u003e) (Suyama et al. \u003cspan class=\"CitationRef\"\u003e2006\u003c/span\u003e). Duplicated genes were identified and visualized by lines following (Dossa et al. \u003cspan class=\"CitationRef\"\u003e2016\u003c/span\u003e). Furthermore, synteny analysis and comparative orthology mapping of \u003cem\u003eSiCADs\u003c/em\u003e were conducted between sesame and three other species \u003cem\u003eArabidopsis\u003c/em\u003e, tomato, and potato using MCScanX (Wang et al. \u003cspan class=\"CitationRef\"\u003e2012b\u003c/span\u003e). The parameters used for the MCScanX analysis included an E-value threshold of 1e-10 and number of BlastHits was 5. The resulting synteny relationships were visualzuized by Circos (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://circos.ca\u003c/span\u003e\u003c/span\u003e) (Krzywinski et al. \u003cspan class=\"CitationRef\"\u003e2009\u003c/span\u003e).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\n \u003ch2\u003e2.8. Discovery of SSR Markers and Protein Interaction Network Analysis of \u003cem\u003eSiCADs\u003c/em\u003e\u003c/h2\u003e\n \u003cp\u003eWe proceeded with the identified \u003cem\u003eSiCAD\u003c/em\u003e genes nucleotide sequence for the presence of Simple Sequence Repeats (SSRs) with the web based tool software (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://bioinfo.inf..br/websat/\u003c/span\u003e\u003c/span\u003e) and cross checked with another web tool, MISA-web available at \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://misaweb.ipk-gatersleben.de/\u003c/span\u003e\u003c/span\u003e (Beier et al. \u003cspan class=\"CitationRef\"\u003e2017\u003c/span\u003e).The parameters were set to: one to six SSR nucleotide motifs length and minimum repetitions were 10 for mononucleotide, six for for di-nucleotide and five reiterations for other repeat units. In addition, the maximum length between the two SSRS was kept 100 to register as compound SSR. Additionally STRING software \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://string-db.org/\u003c/span\u003e\u003c/span\u003e helped in showing interaction network of different \u003cem\u003eSiCAD\u003c/em\u003e proteins based on interactome of \u003cem\u003eArabiodopsis\u003c/em\u003e and later on improved, visualized by cytoscape (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://cytoscape.org/\u003c/span\u003e\u003c/span\u003e).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\n \u003ch2\u003e2.9. DNA extraction, PCR amplification, and electrophoresis\u003c/h2\u003e\n \u003cp\u003eTo validate the SSR markers predicted from our analysis, genomic DNA was extracted from the genotypes comprising of \u003cem\u003eS. indicum\u003c/em\u003e (Si), \u003cem\u003eS.mulayanum\u003c/em\u003e (Sm), and eight recombinant liens (R1-R8) derived from an earlier interspecific hybridization between Si and Sm (Dutta et al. \u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e). The PCR amplification was performed in a 25 \u0026micro;L reaction mixture containing 5 \u0026times; Buffer, 2.0 mmol/L MgCl\u003csub\u003e2\u003c/sub\u003e, 0.1 mmol/L dNTPs, 100 \u0026micro;M of each primer (0.5 \u0026micro;L each of forward and reverse primer, synthesized by SIGMA), 0.5 U \u003cem\u003eTaq\u003c/em\u003e polymerase, and 25 ng template DNA. The SSR-PCR amplification was performed with an Applied Biosystems 2720 Thermal Cycler (USA). After initial checking in 1.8 % agarose gel, thePCR products were further resolved in denaturing Urea PAGE (6%) in 1X TBE (Tris\u0026ndash;Borate-EDTA) buffer and stained with ethidium bromide for 5 min (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eA, B).\u003c/p\u003e\n \u003cdiv id=\"Sec11\" class=\"Section3\"\u003e\n \u003ch2\u003e2.9.1 Primer Design and Validation of Genic SSR Containing the (AT)₁₁ Repeat Motif\u003c/h2\u003e\n \u003cp\u003eSSRs were identified based on a minimum motif length of 15 or 18 base pairs. For genic SSRs containing motifs\u0026thinsp;\u0026ge;\u0026thinsp;18 bp, primers were designed using with the following parameters: primer length of 18\u0026ndash;24 nucleotides, GC content between 40% and 70%, annealing temperature ranging from 54\u0026deg;C to 63\u0026deg;C, and a minimum expected product size of 100 bp \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://probes.pw.usda.gov/batchprimer3/overview.html\u003c/span\u003e\u003c/span\u003e. The primer pair targeting the genic SSR of \u003cem\u003eSiCAD2\u003c/em\u003e containing the (AT)₁₁ repeat motif was designated SSRCAD2. The forward primer (SSRCAD2_F) sequence was 5\u0026prime;-TGTGATATGACGGTTAGCAAAGA-3\u0026prime; (23 bp), and the reverse primer (SSRCAD2_R) sequence was 5\u0026prime;-CTCGTTCATGACTTAAATTACAGGT-3\u0026prime; (26 bp). The expected amplicon size for this primer pair was 242 bp, as determined by NCBI in-silico PCR analysis and through 1.8% agarose gel (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eA \u003cstrong\u003eB\u003c/strong\u003e).\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec12\" class=\"Section3\"\u003e\n \u003ch2\u003e2.9.2 Gene Ontology (GO) and KEGG Pathway Analysis of \u003cem\u003eSiCADs\u003c/em\u003e Candidate Genes\u003c/h2\u003e\n \u003cp\u003eThe candidate genes were screened for associated GO terms (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://geneontology.org/\u003c/span\u003e\u003c/span\u003e), and KEGG database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.kegg.jp/kegg/pathway.html\u003c/span\u003e\u003c/span\u003e). The amino acid sequences of the identified \u003cem\u003eSiCADs\u003c/em\u003e were subjected to KOBAS 2.0 (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://kobas.cbi.pku.edu.cn\u003c/span\u003e\u003c/span\u003e) (Xie et al. \u003cspan class=\"CitationRef\"\u003e2011\u003c/span\u003e). Those enriched Go-terms and pathways were considerd significant which has \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, further false discovery rate was adjusted using the Benjamini and Hochberg\u0026rsquo;s stastical test which was kept at threshold \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05. Functional annotation was deduced through BLAST with E-value 1e-5 by leveraging the genome annotation of \u003cem\u003eArabidopsis\u003c/em\u003e from TAIR (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.arabidopsis.org\u003c/span\u003e\u003c/span\u003e).\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec13\" class=\"Section3\"\u003e\n \u003ch2\u003e2.9.3 Expression Analysis of \u003cem\u003eSiCAD\u003c/em\u003e Genes under \u003cem\u003eM. phaseolina\u003c/em\u003e infection and salt stress using RNA-seq data\u003c/h2\u003e\n \u003cp\u003eThe raw data SRA files were obtained from the NCBI for biotic stress (\u003cem\u003eM. phaseolina\u003c/em\u003e infection) (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.ncbi.nlm.nih.gov/sra/PRJNA642699\u003c/span\u003e\u003c/span\u003e) and abiotic stress (salt stress) (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.ncbi.nlm.nih.gov/bioproject/524278\u003c/span\u003e\u003c/span\u003e). The SRA files were analyzed to check the QC, GC content and adapter content. The adaptor sequences, primers, and low-quality reads were filtered out with Trimmomatic (version 0.39). After removing adaptors, and low-quality reads, the paired-end fastq files were mapped to reference genome of \u003cem\u003eS. indicum\u003c/em\u003e ( S_indicum_v1.0 downloaded from \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://plants.ensembl.org/Sesamum_indicum/Info/Index\u003c/span\u003e\u003c/span\u003e).\u003c/p\u003e\n \u003cp\u003eThe obtained reads were annotated by alignment using graph based aligner HISAT2 (version 2.2.1) software with default parameters (Kim et al. \u003cspan class=\"CitationRef\"\u003e2019\u003c/span\u003e). The SAM files were converted to BAM files and sorted using SAM tools software (Li et al. \u003cspan class=\"CitationRef\"\u003e2009\u003c/span\u003e). Using ultrafast and accurate feature Counts (Version 2.0.5), the mapped reads were annotated with GTF file of S_indicum_v1.0 obtained from \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://plants.ensembl.org/Sesamum_indicum/Info/Index\u003c/span\u003e\u003c/span\u003e.\u003c/p\u003e\n \u003cp\u003eTo analyze the sequence depth, expression pattern of the identified \u003cem\u003eSiCAD\u003c/em\u003e genes, the count data from both \u003cem\u003eM.phaseolina\u003c/em\u003e infection and salt stress was subjected to below formula to calculate the RPKM values:\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:RKPM=\\left[\\frac{Raw\\:Count}{\\frac{Gene\\:Length\\left(bp\\right)}{1000}*\\frac{Total\\:Reads}{\\text{1,000,000}}}\\right]\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003cp\u003eA heatmap was constructed using the RKPM values of the identified \u003cem\u003eSiCAD\u003c/em\u003e genes to visualize their expression patterns. Hierarchical clustering was applied to genes to reveal relationships and grouping based on expression profiles.\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec14\" class=\"Section3\"\u003e\n \u003ch2\u003e2.9.4 Statistical analysis and Visualization\u003c/h2\u003e\n \u003cp\u003eThe results are expressed as the average of three biological replicates. Data were analyzed using Welch\u0026rsquo;s two-sample unpaired \u003cem\u003et\u003c/em\u003e-test for independent samples to determine statistical significance. All computations were performed out in RStudio (version 2024.04.2). Data visualization, and significance annotations were generated using the \u0026lsquo;ggplot2\u0026rsquo; and \u0026lsquo;ggsignif\u0026rsquo; packages, available from the CRAN repository. For heatmaps, bubble plots, and dot plots were organized in comma separated values (CSV) files and imported into the RStudio environment. Heatmaps were generated using the \u0026lsquo;ComplexHeatmap\u0026rsquo; and \u0026lsquo;Pheatmap\u0026rsquo; package (Available via Bioconductor), and bubble plots were created using \u0026lsquo;ggplot2\u0026rsquo; to to enhance graphical representation.\u003c/p\u003e\n \u003c/div\u003e\n\u003c/div\u003e"},{"header":"3. Results","content":"\u003cp\u003e\u003cstrong\u003e3.1. Identification, chromosomal mapping, and duplication analysis of \u003cem\u003eSiCAD\u0026nbsp;\u003c/em\u003egenes in the sesame genome\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA total of 32 \u003cem\u003eSiCAD\u003c/em\u003e genes were identified in the sesame genome from the scans of Hmmer and Hidden Markov Model (HMM) domain searches (\u003cstrong\u003eTable 1\u003c/strong\u003e). The deduced protein sizes varied from 309 amino acids (\u003cem\u003eSiCAD31\u003c/em\u003e) to 719 amino acids (\u003cem\u003eSiCAD6\u003c/em\u003e) and the isoelectric points range from 5.17 (\u003cem\u003eSiCAD31\u003c/em\u003e) to 9.23 (\u003cem\u003eSiCAD32\u003c/em\u003e) (\u003cstrong\u003eTable 2\u003c/strong\u003e\u003cstrong\u003e)\u003c/strong\u003e.\u0026nbsp;Further, physical\u0026nbsp;characteristics of these \u003cem\u003eSiCADs\u0026nbsp;\u003c/em\u003egenes including Ensembl ID, protein molecular weight (MW), and isoelectric point (pI) is\u0026nbsp;shown in \u003cstrong\u003eTable 2\u003c/strong\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOnly one gene (\u003cem\u003eSiCAD1\u003c/em\u003e), which was located on an unanchored scaffold, could not be mapped to any specific linkage group (LG)\u0026nbsp;\u003cstrong\u003e(Fig. 3)\u003c/strong\u003e\u003cstrong\u003e.\u0026nbsp;\u003c/strong\u003eAll the other \u003cem\u003eCAD\u003c/em\u003e genes were unevenly distributed among 15 LGs of 16 LGs in the sesame\u0026nbsp;genome, suggesting that \u003cem\u003eCAD\u003c/em\u003e genes may have been widely distributed in the genome of a common ancestor \u003cstrong\u003e(\u003c/strong\u003e\u003cstrong\u003eFig. 3\u003c/strong\u003e\u003cstrong\u003e).\u003c/strong\u003eThe distribution of sesame \u003cem\u003eSiCAD\u003c/em\u003es genes across linkage groups varied. The LG2 contains the highest number of genes, accounting for 18.75% of total identified genes. \u0026nbsp;LG6 and LG13 each contains 5 genes, accounting for 31.26% of the total genes. LG7, LG3, LG8 and LG15 comprisies 34.38% of the total genes.\u0026nbsp;In addition, LG1, LG4, LG12, LG14 possesses only 1 gene which accounts for 12.56% of all \u003cem\u003eSiCAD\u003c/em\u003e genes\u0026nbsp;\u003cstrong\u003e(Fig. 3).\u003c/strong\u003e To gain deeper insights into the evolutionary patterns of these genes, the synonymous (\u003cem\u003eKs\u003c/em\u003e), non-synonymous (\u003cem\u003eKa\u003c/em\u003e), and their ratio (\u003cem\u003eKa/Ks\u003c/em\u003e) values were\u0026nbsp;analyzed to examine the selective pressure and duplication events among four sesame \u0026nbsp;segmentally duplicated \u003cem\u003eSiCAD\u0026nbsp;\u003c/em\u003egene pairs in sesame. In general, a \u003cem\u003eK\u003csub\u003ea\u003c/sub\u003e/K\u003csub\u003es\u003c/sub\u003e\u003c/em\u003e\u0026gt;1 means positive selection, \u003cem\u003eK\u003csub\u003ea\u003c/sub\u003e/K\u003csub\u003es\u003c/sub\u003e\u003c/em\u003e\u0026lt;1 indicates purifying selection and \u003cem\u003eK\u003csub\u003ea\u003c/sub\u003e/K\u003csub\u003es\u003c/sub\u003e\u003c/em\u003e=1 stands for neutral selection (Zhang et al. 2006b)\u003cstrong\u003e.\u0026nbsp;\u003c/strong\u003eThe \u003cem\u003eK\u003csub\u003ea\u003c/sub\u003e/K\u003csub\u003es\u0026nbsp;\u003c/sub\u003e\u003c/em\u003eratio for all sesame \u003cem\u003eSiCADs\u003c/em\u003e gene varied from 0.05 to 0.40 \u003cstrong\u003e(Fig. 4, Supplementary Table 2)\u003c/strong\u003e\u003cstrong\u003e.\u003c/strong\u003e These results suggest that the segementally duplicated \u003cem\u003eSiCAD\u003c/em\u003e gene pairs\u0026nbsp;(\u003cem\u003eSiCAD11\u003c/em\u003e and \u003cem\u003eSiCAD5\u003c/em\u003e,\u0026nbsp;SiCAD25 and \u003cem\u003eSiCAD22\u003c/em\u003e, \u003cem\u003eSiCAD27\u003c/em\u003e and \u003cem\u003eSiCAD18\u003c/em\u003e, \u003cem\u003eSiCAD31\u003c/em\u003e and \u003cem\u003eSiCAD27\u003c/em\u003e) showed \u003cem\u003eK\u003csub\u003ea\u003c/sub\u003e/K\u003csub\u003es\u003c/sub\u003e\u003c/em\u003e\u0026lt;1 showing purifying selection pressure.\u0026nbsp;These results suggest these segmentally duplicated \u003cem\u003eSiCAD\u003c/em\u003e gene pairs have experienced purifying selection, maintaining their original function possibly through removing deleterious mutations,while potentially allowing for subtle functional divergence over time.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.2. Conserved Domain analysis and Gene Structure of \u003cem\u003eSiCAD\u003c/em\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll thirty two \u003cem\u003eSiCAD\u003c/em\u003e genes along with their isoforms were submitted to the CDD search tool to uncover the conserved functional domains (https://www.ncbi.nlm.nih.gov/Structure/bwrpsb/bwrpsb.cgi) (Wang et al. 2023a)\u003cstrong\u003e.\u0026nbsp;\u003c/strong\u003eMost protein sequences contain ADH_N (Clan:Groes)\u0026nbsp;and ADH_zinc (Clan:\u0026nbsp;NADP_Rossmann)\u0026nbsp;domains a characteristic feature of \u003cem\u003eCAD\u003c/em\u003e genes. In addition, the ADH_N superfamily, ADH_zinc_N_2, and MDR superfamily\u0026nbsp;domains\u0026nbsp;are also present in \u003cem\u003eSiCAD\u003c/em\u003e amino acid \u0026nbsp;sequences (\u003cstrong\u003eSupplementary Fig. 2, Supplementary Table 3\u003c/strong\u003e). The MEME web server was employed to verify the result of domain prediction (\u003cstrong\u003eSupplementary Fig. 3\u003c/strong\u003e). Five different motifs were found distributed throughout the \u003cem\u003eSiCADs\u003c/em\u003e amino acid sequences, with lengths ranging from 21 to 50 amino acids. The Motif 3 was found in 36 SiCAD protein sequences. In addition, Motif 1 was assigned to 34 \u003cem\u003eSiCAD\u003c/em\u003e amino acid sequences indicating a highly conserved protein motif structure with an amino acid length of 29 in both cases \u003cstrong\u003e(Supplementary Fig. 3)\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003eAnalysis of exon-intron boundaries combined with phylogenetic analysis of identified CAD genes showed highly conserved intron-exon organization in 32 \u003cem\u003eSiCAD\u003c/em\u003e genes \u003cstrong\u003e(Fig. 5)\u003c/strong\u003e. The genes showed variability in gene structure, and some of the \u003cem\u003eSiCAD\u0026nbsp;\u003c/em\u003egenes possessed isoforms as depicted \u003cstrong\u003e(Fig. \u0026nbsp;5)\u003c/strong\u003e. Our analysis showed that \u003cem\u003eSiCAD\u003c/em\u003e genes from the same clade group observed similar number of introns and exons in their structure\u0026rsquo;s. In class A \u003cem\u003eSiCAD4\u003c/em\u003e contains 1 exon \u0026nbsp;and \u003cem\u003eSiCAD26\u003c/em\u003e showed 9 exons. In class B, the genes \u003cem\u003eSiCAD23.X1\u003c/em\u003e and \u003cem\u003eSiCAD23.X2\u003c/em\u003e each have 9 exons, while \u003cem\u003eSiCAD15\u003c/em\u003e has 7 exons, \u003cem\u003eSiCAD29\u003c/em\u003e has 6 exons, \u003cem\u003eSiCAD18\u003c/em\u003e has 10 exons, \u003cem\u003eSiCAD28\u003c/em\u003e has 3 exons, and \u003cem\u003eSiCAD31\u003c/em\u003e has 4 exons. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFurther, in class C, the genes \u003cem\u003eSiCAD7\u003c/em\u003e and \u003cem\u003eSiCAD6\u003c/em\u003e each have 2 exons, \u003cem\u003eSiCAD27\u003c/em\u003e and \u003cem\u003eSiCAD9.X2\u003c/em\u003e each have 4 exons, \u003cem\u003eSiCAD8\u003c/em\u003e and \u003cem\u003eSiCAD21.X2\u003c/em\u003e each have 6 exons, \u003cem\u003eSiCAD32\u0026nbsp;\u003c/em\u003ehas 7 exons, and \u003cem\u003eSiCAD1\u003c/em\u003e has 5 exons. In class D, the genes \u003cem\u003eSiCAD14.X1\u003c/em\u003e has 7 exons, \u003cem\u003eSiCAD20\u003c/em\u003e, \u003cem\u003eSiCAD24\u003c/em\u003e, \u003cem\u003eSiCAD22\u003c/em\u003e, \u003cem\u003eSiCAD25\u003c/em\u003e, and \u003cem\u003eSiCAD20.X1\u003c/em\u003e each have 10 exons, \u003cem\u003eSiCAD30\u003c/em\u003e\u0026nbsp; with 6 exons each, \u003cem\u003eSiCAD19\u003c/em\u003e and \u003cem\u003eSiCAD16\u003c/em\u003e each have 8 exons, and \u003cem\u003eSiCAD21.X1\u003c/em\u003e has 5 exons. This organization highlights the diversity in exon numbers across different members of the \u003cem\u003eSiCAD\u003c/em\u003e gene family within their respective classes (\u003cstrong\u003eFig. 5)\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.3. Promoter analysis of the identified \u003cem\u003eSiCADs\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDifferences in cis-elements within the gene promoters suggest that these genes may have diverse roles in plant growth, development, and responses to various stresses. To explore the functions of \u003cem\u003eSiCAD\u003c/em\u003e genes in more detail, 1.5 kb of the upstream region from each gene\u0026rsquo;s transcription start site (TSS) was retrieved and analyzed using the PlantCARE database to identify and quantify the cis-elements (\u003cstrong\u003eFig. 6 ).\u003c/strong\u003e These \u003cem\u003ecis\u003c/em\u003e-elements were divided into \u0026nbsp;three categories, i.e., development responsive, hormone responsive, and stress related-elements. The promoter of \u003cem\u003eSiCAD\u003c/em\u003e genes included number of hormone responsive-elements, and stress, especially P-box (gibberellin-responsive element), ABRE (abscisic acid responsiveness), CGTCA-motif (MeJA-responsiveness), and TC-rich repeats (defense and stress responsiveness) (\u003cstrong\u003eFig. 6\u003c/strong\u003e). Additionally, CCAAT-box (\u003cem\u003eHvMYB1\u003c/em\u003e) was common occurrence in most of SiCADs, these are well known for their positive role in drought response and osmotic stress (Alexander et al. 2019). These results indicate that the \u003cem\u003eSiCAD\u0026nbsp;\u003c/em\u003egenes might have key \u0026nbsp; roles in plant growth, development and response to various stresses in sesame (\u003cstrong\u003eSupplementary\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eTable 4\u003c/strong\u003e). In additition, we delved into comprehensive analysis of various binding sites present in our identified \u003cem\u003eSiCADs\u0026nbsp;\u003c/em\u003efor the transcription factors involved in stress response, development and growth as illustrated in heatmap (\u003cstrong\u003eFig. 7\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.4. Phylogenetic analysis, Mapping and comparative Synteny Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo investigate the evolutionary relationship of sesame \u003cem\u003eSiCAD\u0026nbsp;\u003c/em\u003egenes phylogenetic analysis was performed based on the full Length amino acid sequences of \u003cem\u003eSiCADs\u003c/em\u003e proteins from \u003cem\u003eArabidopsis thialiana\u003c/em\u003e, \u003cem\u003eOrzya sativa\u003c/em\u003e and \u003cem\u003eS. indicum\u0026nbsp;\u003c/em\u003e\u003cstrong\u003e(Fig. 8A)\u003c/strong\u003e. The tree clearly distinguishes the ten classes (I-X) \u003cstrong\u003e(Fig. 8A)\u003c/strong\u003e. Synteny analysis of sesame \u003cem\u003eSiCAD\u003c/em\u003e genes compared to those of \u003cem\u003eArabidopsis\u0026nbsp;\u003c/em\u003ecould provide more functional aspect of these genes. Hence, we performed a comparative analysis to identify orthologous \u003cem\u003eSiCAD\u003c/em\u003e genes between sesame and \u003cem\u003eArabidospsis\u003c/em\u003e, \u003cem\u003eS. lycopersicum,\u003c/em\u003e and \u003cem\u003eS. tuberosum\u003c/em\u003e genome respectively. In total, seven orthologous genes were linked with identified \u003cem\u003eSiCADs\u0026nbsp;\u003c/em\u003ein\u003cem\u003e\u0026nbsp;Arabidopsis\u003c/em\u003e (\u003cstrong\u003eFig. 8B\u003c/strong\u003e). Synteny analysis revealed that nine genes of \u003cem\u003eS. lycoperiscum\u003c/em\u003e showed orthology with identified \u003cem\u003eSiCADs\u003c/em\u003e (\u003cstrong\u003eFig. 8C\u003c/strong\u003e). In addition, synteny revealed eight genes of \u003cem\u003eS. tuberosum\u003c/em\u003e were linked with identified \u003cem\u003eSiCADs\u003c/em\u003e (\u003cstrong\u003eFig. 8D\u003c/strong\u003e). Interestingly, LG8, LG2 possessed largest ortholog (2 gene pairs) while least one gene pair was detected on LG3, LG7, LG15 in all comparative analysis (\u003cstrong\u003eFig. 8B, C, D\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.5. Protein interaction network analysis of \u003cem\u003eSiCADs\u003c/em\u003e and identification of SSR markers\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe protein-protein interaction network is a helpful preface to explore biological functions of unknown proteins. Based on the \u003cem\u003eArabidopsis\u003c/em\u003e interactome, the protein-protein interactions, including functional and physical interactions among \u003cem\u003eSiCAD\u003c/em\u003e genes of sesame were predicted \u003cstrong\u003e(Fig. 9)\u003c/strong\u003e. Twelve sesame CAD genes were involved in protein-protein interaction. These proteins have been validated and implicated in salinity stress and in defense response to many pathogens. Hence, we hypothesized that \u003cem\u003eSiCAD\u003c/em\u003e genes might also be involved in similar function pathways. The genes interacted with \u003cem\u003ePDC1\u003c/em\u003e and \u003cem\u003eF2K13.90\u003c/em\u003e which are implicated in lignin biosynthesis acting as cofactor for alcohol dehydrogenase as per Gene ontology. In addition, the interactions occurred between the isoforms of CAD genes, also as evident from the (\u003cstrong\u003eFig. 9)\u003c/strong\u003e. Given the significance of \u003cem\u003eSiCAD\u003c/em\u003e genes in mediating responses to both biotic and abiotic stresses, tagging these valuable genes could facilitate marker-assisted breeding and contribute to the development of more effective crop improvement strategies. Of of the thirty two \u003cem\u003eSiCAD\u003c/em\u003e genes, 20 \u003cem\u003eSiCAD\u003c/em\u003e genes exhibited single sequence repeats (SSRs) from mononucleotides (p1) to tetranucleotide (p4) \u003cstrong\u003e(Supplementary Table 5)\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.6 Development and Validation of Genic SSR Markers\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOf the thirty two \u003cem\u003eSiCAD\u003c/em\u003e genes predicted, twenty were found to harbor SSR motifs, including mononucleotide (p1), dinucleotide (p2), trinucleotide (p3), and tetranucleotide (p4) repeats. The average gene length analyzed was approximately 4 kb. Using \u003cem\u003ein silico\u003c/em\u003e tools, one genic SSR motif with an AT repeat (AT)₁₁ was identified within the coding region of one candidate gene, located from 1658 bp to 1679 bp. To validate the presence and amplification of this SSR, specific primers were designed flanking the repeat region. Initial amplification was performed using 1.8% agarose gel electrophoresis, which revealed a single band of 242 bp across all genotypes tested, suggesting successful and specific amplification (\u003cstrong\u003eFig. 2 A,B\u003c/strong\u003e). Further resolution using 6% PAGE allowed us for more precise allele discrimination. A total of 20 alleles were detected among the tested parental and recombinant F6 lines (R1\u0026ndash;R8). However, all individuals displayed identical banding profiles for this marker, classifying it as monomorphic across the tested genotypes. Despite the number of detected bands, no allelic polymorphism was observed, suggesting that this SSR marker may be conserved in the studied panel.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.7. Enrichment Analysis of \u003cem\u003eSiCAD\u003c/em\u003e Genes Reveals Key GO Terms and KEGG Pathways Involved in Stress Response\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eGO enrichment analysis was performed on the identified \u003cem\u003eSiCAD\u003c/em\u003e genes to uncover their functional differences with statistical significance (\u003cem\u003eP\u003c/em\u003e value\u0026thinsp;\u0026lt;\u0026thinsp;0.05) and further false discovery rate was done by Benjamini and Hochberg (1995) statistical test with p \u0026lt;0.05. There were 36 GO terms enriched in Si\u003cem\u003eCAD\u0026nbsp;\u003c/em\u003egenes. Some important GO terms enriched in our identified genes\u0026nbsp;wereGO:0009809 (Lignin biosynthetic process), GO:0009626 (Plant-type hypersensitive response), GO:0001666 (Response to hypoxia),GO:0009617 (Response to bacterium), GO:0010286 (Heat acclimation), GO:0071456 (Cellular response to hypoxia), GO:0009414 (Response to water deprivation), GO:0046686 (Response to cadmium ion), GO:0009651 (Response to salinity stress) and GO:0009737 (Response to abscisic acid) \u003cstrong\u003e(Fig. 10A, Supplementary Table 6).\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe KEGG pathway analysis was employed to dissect pathways associated with identified genes. The pathway analysis was carried under stringent statistical analysis with P value \u0026lt;0.05 and P adjusted value (FDR) \u0026lt;0.05. The major pathways, which were enriched in Metabolic pathways (ath01100), Biosynthesis of secondary metabolites (ath01110), Phenylpropanoid biosynthesis (ath00940), Carbon metabolism (ath01200), Tyrosine metabolism (ath00350) (\u003cstrong\u003eFig. 10 B).\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.8. Expression Analysis of \u003cem\u003eSiCAD\u003c/em\u003e Genes from RNA-Seq Data in response to \u003cem\u003eM. phaseolina\u003c/em\u003e Infection\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFor understanding the dynamic expression pattern after post-infection with M.\u003cem\u003e\u0026nbsp;phaseolina\u003c/em\u003e infection in genotypes \u003cem\u003eS. indicum\u003c/em\u003e and \u003cem\u003eS. mulayanum\u003c/em\u003e, we thoroughly analyzed the transcriptome data and found that \u003cem\u003eSiCADs\u003c/em\u003e showed different RKPM value dynamics post infection (\u003cstrong\u003eFig. 11 A\u003c/strong\u003e).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTwenty identified \u003cem\u003eSiCADs\u003c/em\u003e showed responsiveness to \u003cem\u003eM. phaseolina\u003c/em\u003e infection. \u003cem\u003eSiCAD3\u003c/em\u003e, \u003cem\u003eSiCAD5\u003c/em\u003e, \u003cem\u003eSiCAD9\u003c/em\u003e, \u003cem\u003eSiCAD1\u003c/em\u003e0, \u003cem\u003eSiCAD13\u003c/em\u003e showed high RPKM values, suggesting that these might be crucial for \u003cem\u003eM. phaseolina\u003c/em\u003e response. In addition, \u003cem\u003eSiCAD1\u003c/em\u003e,\u003cem\u003e\u0026nbsp;SiCAD2\u003c/em\u003e,\u003cem\u003e\u0026nbsp;SiCAD6\u003c/em\u003e,\u003cem\u003e\u0026nbsp;SiCAD7\u003c/em\u003e,\u003cem\u003e\u0026nbsp;SiCAD14\u003c/em\u003e,\u003cem\u003e\u0026nbsp;SiCAD16\u003c/em\u003e, \u003cem\u003eSiCAD17\u003c/em\u003e,\u003cem\u003e\u0026nbsp;SiCAD19\u003c/em\u003e, \u003cem\u003eSiCAD21\u003c/em\u003e,\u003cem\u003e\u0026nbsp;SiCAD23\u003c/em\u003e,\u003cem\u003e\u0026nbsp;SiCAD26\u003c/em\u003e,\u003cem\u003e\u0026nbsp;SiCAD28\u003c/em\u003e,\u003cem\u003e\u0026nbsp;SiCAD29,\u0026nbsp;\u003c/em\u003eand\u003cem\u003e\u0026nbsp;SiCAD32\u003c/em\u003e showed zero expression as per RPKM values.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.9. Expression Analysis of \u003cem\u003eSiCAD\u003c/em\u003e under salt stress from RNA-seq data\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo analyze the expression of the identified genes, the RNA-seq data was analyzed and we found that, there are mainly two classes as shown in \u003cstrong\u003eFigure. 11B.\u003c/strong\u003e A Heatmap was generated based on the RPKM value of each gene identified in our study. Hierarchical clustering based upon Pearson correlation was employed to establish the classes. The Hierarchical clustering resulted into two classes, A and B. The expression showed time-dependent change in expression, as we found in \u003cem\u003eSiCAD11, SiCAD19, SiCAD31,\u0026nbsp;\u003c/em\u003eand\u003cem\u003e\u0026nbsp;SiCAD5\u003c/em\u003e showed high RKPM value at 24hr in salinity tolerant genotype \u003cstrong\u003e(Fig. 11B).\u003c/strong\u003e The RPKM of \u003cem\u003eSiCAD28, SiCAD14, SiCAD18\u003c/em\u003e showed lesser changes under salinity stress across different time points.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.9.1 Quantitative real-time PCR (qRT-PCR) analysis of selected \u003cem\u003eSiCAD\u003c/em\u003e genes under \u003cem\u003eM. phaseolina\u003c/em\u003e infection and salt stress in two sesame genotypes\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo explore the potential role of \u003cem\u003eCAD\u0026nbsp;\u003c/em\u003egenes in sesame responses to \u003cem\u003eM. phaseolina\u003c/em\u003e and salt stress, we monitored the expression levels of \u003cem\u003eSiCAD\u003c/em\u003e genes under progressive \u003cem\u003eM. phaseolina\u003c/em\u003e infection and salt stress in two sesame genotypes. Since most \u003cem\u003eSiCAD\u003c/em\u003e genes displayed differential expression in leaves, qRT-PCR analysis was perfomed on leaf samples.\u003c/p\u003e\n\u003cp\u003eDuring \u003cem\u003eM. phaseolina\u003c/em\u003e infection, the selected \u003cem\u003eSiCAD\u003c/em\u003e genes exhibited varied expression patterns across different time points. In \u003cem\u003eS. indicum\u003c/em\u003e, after 48 hours of infection, \u003cem\u003eSiCAD4\u003c/em\u003e (6.5), \u003cem\u003eSiCAD5\u003c/em\u003e (3.9), \u003cem\u003eSiCAD6\u003c/em\u003e (2.5), \u003cem\u003eSiCAD10\u003c/em\u003e (3.2), and \u003cem\u003eSiCAD20\u003c/em\u003e (3.3), showed significant upregulation (\u003cstrong\u003eFig.12B,C,D,F,H)\u003c/strong\u003e. However, in 96 hours post-infection, a decline in expression was observed for several genes: \u003cem\u003eSiCAD4\u003c/em\u003e (0.86), \u003cem\u003eSiCAD5\u003c/em\u003e (2.24), \u003cem\u003eSiCAD6\u003c/em\u003e (2.11), and \u003cem\u003eSiCAD20\u003c/em\u003e (3.27), indicating temporal modulation of gene expression in response to infection \u003cstrong\u003e(Fig.12 B-D,H)\u003c/strong\u003e. In \u003cem\u003eS. mulayanum\u003c/em\u003e, at 48 hours post-infection, \u003cem\u003eSiCAD2\u003c/em\u003e (0.89),\u003cem\u003eSiCAD5\u003c/em\u003e (2.12), \u003cem\u003eSiCAD8\u003c/em\u003e (0.96), \u0026nbsp;and \u003cem\u003eSiCAD10\u003c/em\u003e (0.81) showed lower expression levels compared to the control (\u003cstrong\u003eFig.12A,C,E,F\u003c/strong\u003e). By 96 hours, expression patterns shifted, with \u003cem\u003eSiCAD2\u003c/em\u003e (7.49) showing strong upregulation, while\u003cem\u003eSiCAD5\u003c/em\u003e (0.63), and \u003cem\u003eSiCAD8\u003c/em\u003e (0.67) remained downregulated relative to the control (\u003cstrong\u003eFig. 12 A, C,E\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003eIn salt stress, \u003cem\u003eS. indicum\u003c/em\u003e, \u003cem\u003eSiCAD2\u003c/em\u003e (0.25), \u003cem\u003eSiCAD5\u003c/em\u003e (0.36), \u003cem\u003eSiCAD8\u003c/em\u003e (0.23), and \u003cem\u003eSiCAD10\u003c/em\u003e (0.23) showed notably reduced expression (\u003cstrong\u003eFig. 13 A,C,E,F\u003c/strong\u003e). Similarly, in \u003cem\u003eS. mulayanum\u003c/em\u003e under 200 mM salt stress, \u003cem\u003eSiCAD5\u003c/em\u003e (0.80), \u003cem\u003eSiCAD6\u003c/em\u003e (0.66), and \u003cem\u003eSiCAD20\u003c/em\u003e (0.32) also showed decreased expression levels with respect to control treatment (\u003cstrong\u003eFig. 13 C,D,H\u003c/strong\u003e). In addition, the \u003cem\u003eS. indicum SiCAD4\u003c/em\u003e \u003cem\u003e(0.20),\u0026nbsp;\u003c/em\u003eSiCAD6 (0,08), SiCAD8(0.23),\u003cem\u003e\u0026nbsp;SiCAD12\u003c/em\u003e(0.21), and\u003cem\u003e\u0026nbsp;SiCAD20 (0.15),\u0026nbsp;\u003c/em\u003eshowed reduced expression, but all were non-significant (\u003cstrong\u003eFig.13 B,D,F,G,H)\u003c/strong\u003e. However, in \u003cem\u003eS. mulayanum\u003c/em\u003e \u003cem\u003eSiCAD2\u003c/em\u003e (0.10), \u003cem\u003eSiCAD4\u003c/em\u003e (0,34), \u003cem\u003eSiCAD8\u003c/em\u003e(0.28), \u003cem\u003eSiCAD10\u003c/em\u003e (0.18), and \u003cem\u003eSiCAD12\u003c/em\u003e (0.08), showed decreased expression levels, but were significant as per Welch two sample t test are concerned (\u003cstrong\u003eFig. 13 A,B,E-G\u003c/strong\u003e).\u003c/p\u003e"},{"header":"4. Discussion","content":"\u003cp\u003e\u003cb\u003e4.1. Segmental Duplications Contribute to the Expansion of the Cinnamyl Alcohol Dehydrogenase (SiCAD) Gene Family in Sesame\u003c/b\u003e\u003c/p\u003e\u003cp\u003eDue to genomics interventions, \u003cem\u003eCAD\u003c/em\u003e homologs genes have been unravelled in many plant species. Studies have identified CAD family genes in many crops, which include nine putative genes in \u003cem\u003eArabidopsis\u003c/em\u003e (Kim et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2004\u003c/span\u003e), fifteen CAD genes in \u003cem\u003ePopulus\u003c/em\u003e (Barakat et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2010\u003c/span\u003e), ten CAD genes in \u003cem\u003eNicotiana. tabacum\u003c/em\u003e, and four in \u003cem\u003eN. tomentosiformis\u003c/em\u003e (Wu et al. \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e2024a\u003c/span\u003e). In this study, we identified thirty-two \u003cem\u003eSiCADs\u003c/em\u003e in sesame genome, classified into three major classes A, B, C, and one minor class D. The sesame genome spans 309.35 Mb, featuring a high chromosome anchoring rate of 97.54% and a contig N50 length of 13.48 Mb (Wang et al. \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Transposable elements (TEs) accounts to 27.42% of sesame whole genome, alongside with unclassified repetitive sequences comprising (26.30%). Among these, 65.45% of the repetitive elements show divergence rate of \u0026lt;\u0026thinsp;20% indicating the recent genome dynamics. These results indicate the genome is still evolving and expanding through TE activity (Wang et al. \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Evolutionary investigation of sesame revealed that the whole genome duplications (WGD) and tetraploid or whole genome triplication (WGT) events are recurrent in sesame species (Miao et al. \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Higher ratio synteny blocks between ancestral eudicot and tested \u003cem\u003eSesamum\u003c/em\u003e species, further supports the occurrence of WGD and WGT in \u003cem\u003eSesamum\u003c/em\u003e genus (Miao et al. \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). These duplications events indicate high level of evolutionary conservation within the \u003cem\u003eSesamum\u003c/em\u003e genus (Wang et al. \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Miao et al. \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). These results from genome scale comparison within sesame and other eudicots explains why the CADs family is highly diversified across the \u003cem\u003eSesamum\u003c/em\u003e genome.\u003c/p\u003e\u003cp\u003eTo evaluate the evolutionary origins and duplication pattern of \u003cem\u003eSiCAD\u003c/em\u003e gene family in sesame,we dissected the distribution of the duplicated genes. We found four gene pairs of segmentally duplicated genes in our study (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, \u003cb\u003eSupplementary Table\u0026nbsp;2\u003c/b\u003e). In a previous study, (Cheng et al. \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) identified eight \u003cem\u003ePbCAD\u003c/em\u003e gene pairs, which contributes to lignin biosynthesis in stone cells in \u003cem\u003ePyrus bretschneideri\u003c/em\u003e. In pomegranate three \u003cem\u003ePgCAD\u003c/em\u003e gene pairs were found located at high gene density(Hu et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). In cassava \u003cem\u003eMeCAD\u003c/em\u003e six pairs of segmental duplications were reported (An et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2024a\u003c/span\u003e). The presence of segmentally duplicated genes \u003cem\u003eSiCAD\u003c/em\u003e gene in sesame suggests that gene duplication has contributed to the functional diversification of this gene family. Such duplication events likely enhance the plant ability to adapt biotic and abiotic stress, thereby conferring adaptive evolutionary advantage (Vanneste et al. \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; van Westerhoven et al. \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eTo estimate the divergence pattern and the effect of segmental duplication on gene function, we calculated rates of \u003cem\u003eK\u003c/em\u003e\u003csub\u003e\u003cem\u003es\u003c/em\u003e\u003c/sub\u003e and \u003cem\u003eK\u003c/em\u003e\u003csub\u003e\u003cem\u003ea\u003c/em\u003e\u003c/sub\u003e substutions rate for the gene pairs. The \u003cem\u003eK\u003c/em\u003e\u003csub\u003e\u003cem\u003ea\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e/K\u003c/em\u003e\u003csub\u003e\u003cem\u003es\u003c/em\u003e\u003c/sub\u003e analysis of the four duplicated \u003cem\u003eSiCAD\u003c/em\u003e gene pairs revealed that all \u003cem\u003eK\u003c/em\u003e\u003csub\u003e\u003cem\u003ea\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e/K\u003c/em\u003e\u003csub\u003e\u003cem\u003es\u003c/em\u003e\u003c/sub\u003e ratios were significantly less than 1 (ranging from 0.0459 to 0.3962), indicating that the duplicated \u003cem\u003eSiCAD\u003c/em\u003e genes have mainly undergone purifying selection (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, \u003cb\u003eSupplementary Table\u0026nbsp;2\u003c/b\u003e). Purifying selection plays a crucial role in maintaining biological function by eliminating newly arising deleterious mutations. These selections are widespread across natural populations and contributes significantly to the conservation of genomic sequences over long evolutionary periods. Beyond protecting functional sites under direct selection, purifying selection also influences nearby neutral regions, leaving characteristic signatures in genetic diversity patterns, a phenomenon observed across a wide range of organisms (Cvijović et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).These lines of evidences suggests duplicated \u003cem\u003eSiCAD\u003c/em\u003e genes are under strong functional constraints following segmental duplication (Roth and Liberles \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). Furthermore, the \u003cem\u003eK\u003c/em\u003e\u003csub\u003e\u003cem\u003es\u003c/em\u003e\u003c/sub\u003e values, ranging between 0.97 and 2.27, imply that these duplications likely originated during an ancient whole-genome duplication event in sesame, consistent with previous reports of polyploidy events in the \u003cem\u003eSesamum\u003c/em\u003e genus (Wang et al. \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e2023b\u003c/span\u003e). The gene duplication events were dated using \u003cem\u003eK\u003c/em\u003e\u003csub\u003e\u003cem\u003es\u003c/em\u003e\u003c/sub\u003e values, a standard approach for estimating evolutionary divergence. Based on this method, the duplication events for the \u003cem\u003eSiCAD\u003c/em\u003e gene pairs were estimated to have occurred approximately 75 to 175\u0026nbsp;million years ago (MYA), consistent with previous reports of ancient duplication events in sesame (Wang et al. \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2013\u003c/span\u003e, \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e2023c\u003c/span\u003e).\u003c/p\u003e\u003cdiv id=\"Sec25\" class=\"Section2\"\u003e\u003ch2\u003e4.2 Gene Orthology Analysis Highlights the Diversified Functional Roles of \u003cem\u003eSiCAD\u003c/em\u003e genes in Sesame\u003c/h2\u003e\u003cp\u003eSynteny provides a robust framework for identifying the conservation of homologous genes and gene order across different plant genomes (Liu et al. \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). In this study, synteny analysis, of sesame \u003cem\u003eSiCADs\u003c/em\u003e with model crop \u003cem\u003eArabidopsis\u003c/em\u003e, and more related crops like \u003cem\u003eS. lycoperiscum\u003c/em\u003e and \u003cem\u003eS. tuberosum\u003c/em\u003e revealed some interesting functional insights (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003eB-D). Based on a stringent BLAST E value threshold of 1e-10, we identified multiple sesame \u003cem\u003eSiCAD\u003c/em\u003e genes as orthologs of \u003cem\u003eArabidopsis\u003c/em\u003e. We found that gene \u003cem\u003eSiCAD5, SiCAD12, SiCAD22, SiCAD25, SiCAD27, SiCAD30, SiCAD31\u003c/em\u003e as ortholog of \u003cem\u003eAT4G37970.1, AT4G34230.1, AT1G77120.1, AT1G77120.1, AT1G23740.1, AT3G56460.1, AT1G23740\u003c/em\u003e respectively. Functional annotation retrieved from the TAIR database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.arabidopsis.org/\u003c/span\u003e\u003cspan address=\"https://www.arabidopsis.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) (\u003cb\u003eSupplementary Table\u0026nbsp;7\u003c/b\u003e) suggests that \u003cem\u003eSiCAD5\u003c/em\u003e,and \u003cem\u003eSiCAD12\u003c/em\u003e might be involved in lignin biosynthesis using p-coumaryl aldehyde as substrate (Vanholme et al. \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). Furthermore, comparative synteny analysis approach, between the sesame genome and those of \u003cem\u003eS. lycoperiscum\u003c/em\u003e and \u003cem\u003eS. tuberosum\u003c/em\u003e revealed conserved syntenic blocks (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003eC-D). The genes \u003cem\u003eSiCAD5\u003c/em\u003e, \u003cem\u003eSiCAD11\u003c/em\u003e showed orthology with \u003cem\u003eSolyc11g010990.2.\u003c/em\u003e1 in tomato. In potato, \u003cem\u003eSiCAD5\u003c/em\u003e, \u003cem\u003eSiCAD11\u003c/em\u003e, and \u003cem\u003eSiCAD12\u003c/em\u003e were orthologous to \u003cem\u003ePGSC0003DMT400040518\u003c/em\u003e, \u003cem\u003ePGSC0003DMT400041566\u003c/em\u003e, and \u003cem\u003ePGSC0003DMT400066217\u003c/em\u003e, respectively (\u003cb\u003eSupplementary Table\u0026nbsp;7\u003c/b\u003e). These orthologous relationships, supported by synteny analysis and database searches \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://solcyc.solgenomics.net/,https://phytozome-next.jgi.doe.gov/\u003c/span\u003e\u003cspan address=\"https://solcyc.solgenomics.net/,https://phytozome-next.jgi.doe.gov/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e, indicate that these \u003cem\u003eSiCAD\u003c/em\u003e genes may be functionally involved in lignin biosynthesis. The integration of high confidence orthologous relationships data strengthens our functional prediction and impart important insights in understanding role of these putative \u003cem\u003eSiCAD\u003c/em\u003e in lignin biosynthesis in sesame.\u003c/p\u003e\u003cp\u003eFurthermore, based upon \u003cem\u003eArabidopsis\u003c/em\u003e interactome, protein-proteins interaction of sesame CAD genes interacted with pyruvate decarboxylase (PDC1) and carbon-sulphur lyase (F2K13.90), which are implicated in lignin biosynthesis acting as cofactor as for alcohol dehydrogenase as per Gene ontology. In addition, the interactions occurred between the isoforms of \u003cem\u003eSiCAD\u003c/em\u003e genes also as evident from PPI network (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e). Unfortunately, the regulation of CADs is not studied in sesame fully, however study by (Najar and Gangopadhyay 2024) elucidated the defense role of \u003cem\u003eCinnamoyl alcohol dehydrogenase 1\u003c/em\u003e under \u003cem\u003eM. phaseolina\u003c/em\u003e infection.\u003c/p\u003e\u003cp\u003e\u003cb\u003e4.3 GO and KEGG Enrichment Analyses Reveal the Involvement of Identified\u003c/b\u003e \u003cb\u003eSiCAD\u003c/b\u003e \u003cb\u003eGenes in phenylpropanoid biosynthesis pathways\u003c/b\u003e\u003c/p\u003e\u003cp\u003eWe also did GO and KEGG analysis to see the involvement of identified \u003cem\u003eSiCAD\u003c/em\u003e genes in biotic and abiotic stress. The following GO terms: GO:0009651, GO:0009809, GO:0009626, which are associated with osmotic stress, lignin biosynthetic process, and plant-type hypersensitive response were enriched in identified \u003cem\u003eSiCAD\u003c/em\u003e genes \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e10\u003c/span\u003eA). In wheat roots under 200mM NaCl stress, GO:0009651 was highly enriched indicating the crucial role of \u003cem\u003eCAD\u003c/em\u003es in salt tolerance (Chen et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Furthermore, in poplar, the GO term GO:0009651 was significantly altered under salt stress (Cheng et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). The enrichment of GO:0009809 term associated with lignin biosynthesis, indicates the synergistic function of \u003cem\u003eSiCADs\u003c/em\u003e in strengthening cell walls as a protective mechanism against various environmental stresses. In the gray blight disease of tea, lignin biosynthetic process (GO:0009809) was significantly enriched along with phenylpropanoid catabolic process (GO:0046271), indicating synthesis of secondary metabolites and cell wall changes triggered by defense response (Wang et al. \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Phylotranscriptomics revealed enrichment of GO term GO:0009626 associated with plant pathogen interaction, which induces hypersensitive response, under invasion of nectrophic fungus \u003cem\u003eSclerotinia sclerotiorum\u003c/em\u003e in various species of pentapetalae (\u003cem\u003ePhaseolus vulgaris\u003c/em\u003e, \u003cem\u003eRicinus communis\u003c/em\u003e, \u003cem\u003eArabidopsis thaliana\u003c/em\u003e, \u003cem\u003eHelianthus annuus\u003c/em\u003e, \u003cem\u003eSolanum lycopersicum\u003c/em\u003e, and \u003cem\u003eBeta vulgaris\u003c/em\u003e) (Sucher et al. \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). In our study, we observed KEGG enrichment, which indicated \u003cem\u003eSiCAD\u003c/em\u003es are highly enriched in pathways associated with biosynthesis of secondary metabolites (ath01110), and phenylpropanoid biosynthesis (ath00940) (Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e10\u003c/span\u003eB, Fig.\u0026nbsp;\u003cspan refid=\"Fig14\" class=\"InternalRef\"\u003e14\u003c/span\u003e, \u003cb\u003eSupplementary Table\u0026nbsp;8).\u003c/b\u003e In mungbean exposed to \u003cem\u003eM. phaseolina\u003c/em\u003e infection, there was a concurrent increase in concentration of salicylic acid levels and phenylpropanoid pathway intermediates, such as phenylalanine ammonia lyase (\u003cem\u003ePAL\u003c/em\u003e), which ultimately induce the synthesis of monolignols which are catalyzed by \u003cem\u003eSiCADs\u003c/em\u003e (Kumari et al. \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Moreover, during \u003cem\u003eM. phaseolina\u003c/em\u003e infection in soyabean, there was a significant enrichment of biosynthesis of secondary metabolites, indicating the critical role of the identified \u003cem\u003eSiCADs\u003c/em\u003e (Noor and Little \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). In our previous work on \u003cem\u003eM. phaseolina\u003c/em\u003e infection (Najar and Gangopadhyay 2024),we also showed the critical role of phenylpropanoid biosynthesis pathway. Combining the results from GO and KEGG enrichment analysis of \u003cem\u003eSiCADs\u003c/em\u003e, identification of these genes which have critical role in regulating lignin biosynthesis, as well as their contribution to improving stress tolerance through modifications in lignification of cell wall need to be studied in sesame to further uncover the molecular mechanism.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec26\" class=\"Section2\"\u003e\u003ch2\u003e4.4 \u003cem\u003eSiCAD\u003c/em\u003es Genes might be actively involved in \u003cem\u003eMacrophomina\u003c/em\u003e infection in Sesame\u003c/h2\u003e\u003cp\u003eFungal diseases of the five most cultivated food crops worldwide were estimated to destroy at least 125\u0026nbsp;million tonnes of produce every year (Davies et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). \u003cem\u003eM. phaseolina\u003c/em\u003e (Tassi) Goid. causes charcoal rot and affects 500 crops species globally, along with sesame (Lodha and Mawar \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). To develop resilient sesame against fungal diseases, the \u003cem\u003eCAD\u003c/em\u003e genes manipulation can be a solution due to its critical role in defense response (Lee et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Studies has established that \u003cem\u003eCAD\u003c/em\u003e homologs are actively involved against fungal pathogens by changing the lignin composition of cell wall, thus acting as physical barriers (Lee et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). However, apart from the role in defense, lignins are also actively involved in growth and development (Schilmiller et al. \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Huang et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). In our study, two contrasting genotypes of sesame were responsive to \u003cem\u003eMacrophomina\u003c/em\u003e infection (Fig.\u0026nbsp;\u003cspan refid=\"Fig12\" class=\"InternalRef\"\u003e12\u003c/span\u003e). The results from expression studies established, involvement of \u003cem\u003eCADs\u003c/em\u003e in \u003cem\u003eMacrophomina\u003c/em\u003e which agrees with previous studies in other plant species (Coelho et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Bagniewska-Zadworna et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2014b\u003c/span\u003e; Wu et al. \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e2024b\u003c/span\u003e). Under \u003cem\u003eMacrophomina\u003c/em\u003e infection, the identified \u003cem\u003eCADs\u003c/em\u003e established two classes. The RKPM values obtained from RNA-seq data analysis showed that (\u0026asymp;\u0026thinsp;40%) identified \u003cem\u003eSiCADs\u003c/em\u003e are actively expressed under \u003cem\u003eM. phaseolina\u003c/em\u003e infection (Fig.\u0026nbsp;\u003cspan refid=\"Fig11\" class=\"InternalRef\"\u003e11\u003c/span\u003eA\u003cb\u003e)\u003c/b\u003e. Top expressed genes (\u003cem\u003eSiCAD5, SiCAD10, SiCAD13\u003c/em\u003e) could be functionally important and evolutionarily conserved. Stress inducible \u003cem\u003eSiCAD9\u003c/em\u003e, \u003cem\u003eSiCAD10\u003c/em\u003e, and SiCAD12 showed upregulation under infection, suggesting involvement in defense/lignin-mediated stress response (Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e10\u003c/span\u003eB). In our study, qRT-PCR analysis further validates these findings. In wild genotype, \u003cem\u003eS. mulayanum SiCAD4, SiCAD6, SiCAD8 SiCAD10, SiCAD12\u003c/em\u003e, and \u003cem\u003eSiCAD20\u003c/em\u003e showed lower levels of expression as compared to control at 96-hour post infection. In contrast the cultivated \u003cem\u003eS. indicum\u003c/em\u003e showed relatively high expression of \u003cem\u003eSiCAD4, SiCAD5, SiCAD6, SiCAD8, SiCAD10\u003c/em\u003e at 48-hour post infection (Fig.\u0026nbsp;\u003cspan refid=\"Fig12\" class=\"InternalRef\"\u003e12\u003c/span\u003eB-F). Notably, \u003cem\u003eSiCAD2\u003c/em\u003e and \u003cem\u003eSiCAD20\u003c/em\u003e showed relatively low and high level of expression at 48hr explaining the dynamic, and genotypic-specific contrasting of induction of \u003cem\u003eSiCADs\u003c/em\u003e under \u003cem\u003eM. phaseolina\u003c/em\u003e infection (Fig.\u0026nbsp;\u003cspan refid=\"Fig12\" class=\"InternalRef\"\u003e12\u003c/span\u003eA,H). However, to fully unravel the regulatory roles and functional significance of these genes, further molecular investigations, including transgenic approaches, are essential.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec27\" class=\"Section2\"\u003e\u003ch2\u003e4.5 \u003cem\u003eSiCADs\u003c/em\u003e Genes may be indirectly involved in salt stress in Sesame\u003c/h2\u003e\u003cp\u003eIndia has 11098.81km spreading across mainland island as per data by National Hydrographic Organisation (NHO), so salt stress is significantly affecting the productivity of the agricultural land. Several reports suggest the fact is sesame is salt sensitive (Nassery et al. \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e1979\u003c/span\u003e). The phenylpropanoid biosynthesis pathway plays a central role in synthesis of monolignols in plants (Boerjan et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2003\u003c/span\u003e; Najar and Gangopadhyay 2024). Various genes, viz. phenylalanine ammonia-lyase (\u003cem\u003ePAL\u003c/em\u003e), cinnamate 4-hydroxylase (\u003cem\u003eC4H\u003c/em\u003e), 4-coumarate CoA ligase (\u003cem\u003e4CL\u003c/em\u003e), cinnamoyl CoA reductase (\u003cem\u003eCCR\u003c/em\u003e), caffeoyl CoA O-methyltransferase (\u003cem\u003eCCoAOMT\u003c/em\u003e), ferulate 5-hydroxylase (\u003cem\u003eF5H\u003c/em\u003e), caffeate 3-O-methyltransferase (\u003cem\u003eCOMT\u003c/em\u003e), and cinnamyl alcohol dehydrogenase (\u003cem\u003eCAD\u003c/em\u003e) are involved in the synthesis of monolignols (Syringyl lignins and Guaicyl lignins) with laccase genes (LAC) acting as downstream of final lignins (Boerjan et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2003\u003c/span\u003e; Sibout et al. \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). Although, salt stress influences lignin biosynthetic gene expression, the precise molecular mechanisms are not fully understood (Chun et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). In mulberry, for instance, the relative expression levels of various \u003cem\u003eMaCADs\u003c/em\u003e in leaves ranged from 0.015-fold to 0.10-fold, indicating that expression levels are slightly downregulated in leaves under salt stress relative to control (An et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2024b\u003c/span\u003e). Similarly, lodging stress in \u003cem\u003eArabidopsis\u003c/em\u003e, revealed that \u003cem\u003eTaCAD1\u003c/em\u003e exhibited a unique organ-specific expression pattern. Its expression was high in stem, very low in the leaf, and undetectable in the root (An et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2024b\u003c/span\u003e). This correlates with the data of relative expression levels of the \u003cem\u003eSiCAD\u003c/em\u003e genes in our study. In addition, under 150mM NaCl stress in contrasting \u003cem\u003eMedicago sativa\u003c/em\u003e genotypes the expression of upstream genes of phenylpropanoid pathway viz \u003cem\u003eMs4CL2, MsCCoAOMT, MsCOMT, MsCCR, MsC4H\u003c/em\u003e, \u003cem\u003eMsPAL1\u003c/em\u003e, and \u003cem\u003eMsPRX1\u003c/em\u003e were upregulated, whereas \u003cem\u003eMsCAD\u003c/em\u003e showed relatively lower expression (Rahman et al. \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Therefore, salt stress induces \u003cem\u003eSiCADs\u003c/em\u003e expression, but the level of accumulation can vary based on the plant genotypes and it can be organic specific. In our study, the RNA seq data analysis of identified genes indicated that \u003cem\u003eSiCAD11, SiCAD19\u003c/em\u003e, and \u003cem\u003eSiCAD31\u003c/em\u003e RKPM is much higher in salt susceptible sesame variety over time compared to salt tolerant ones \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig13\" class=\"InternalRef\"\u003e13\u003c/span\u003eB\u003cb\u003e)\u003c/b\u003e. Time resolved RKPM values suggests early induction of \u003cem\u003eSiCAD4\u003c/em\u003e,and \u003cem\u003eSiCAD5\u003c/em\u003e in salt-tolerant plants, which may contribute to salt stress adaptation \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig11\" class=\"InternalRef\"\u003e11\u003c/span\u003eB\u003cb\u003e)\u003c/b\u003e. The highest RPKM values under salt stress were observed for \u003cem\u003eSiCAD5\u003c/em\u003e (156.66), \u003cem\u003eSiCAD11\u003c/em\u003e (428.40), and \u003cem\u003eSiCAD31\u003c/em\u003e (306.73), while other \u003cem\u003eSiCAD\u003c/em\u003es showed relatively lower expression \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig11\" class=\"InternalRef\"\u003e11\u003c/span\u003eB). All others \u003cem\u003eSiCADs\u003c/em\u003e mostly showed less RKPM values under salt stress \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig11\" class=\"InternalRef\"\u003e11\u003c/span\u003eB). To validate some of \u003cem\u003eSiCADs\u003c/em\u003e, we did qRT-PCR, and found that wild genotype \u003cem\u003eS. mulayanum\u003c/em\u003e under 200mM salt stress exhibited high levels of expression of \u003cem\u003eSiCAD4, SiCAD5, SiCAD6, SiCAD8, SiCAD20\u003c/em\u003e, as compared to the cultivated \u003cem\u003eS. indicum\u003c/em\u003e under 200mM salt stress (Fig.\u0026nbsp;\u003cspan refid=\"Fig13\" class=\"InternalRef\"\u003e13\u003c/span\u003eB-E). Conversely, wild genotype \u003cem\u003eS. mulayanum\u003c/em\u003e showed lesser expression levels of \u003cem\u003eSiCAD2\u003c/em\u003e, \u003cem\u003eSiCAD10, SiCAD12\u003c/em\u003e than \u003cem\u003eS. indicum\u003c/em\u003e \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig13\" class=\"InternalRef\"\u003e13\u003c/span\u003eA,F,G\u003cb\u003e).\u003c/b\u003e However, the expression levels were low overall than the control, which are consistent with lower levels of \u003cem\u003eSiCADs\u003c/em\u003e expression under salt stress (Rahman et al. \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). These results highlight the dynamic, organ-specific, and developmental stage-dependent expression of \u003cem\u003eSiCADs\u003c/em\u003e under salt stress. Further studies, including gene introgression and transgenic experiments, are required to unravel the complex regulatory mechanisms underlying these responses.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec28\" class=\"Section2\"\u003e\u003ch2\u003e4.6 Development and Validation of genic SSR\u003c/h2\u003e\u003cp\u003eDuring the development of SSR markers, the first step involves mining potential SSR loci from assembled sequences (Zhang et al. \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e2012a\u003c/span\u003e). Based on their repeat motifs, SSRs can be classified as perfect (e.g., ATATATATATATAT) or imperfect, which may include nucleotide substitutions or indels (e.g., ATATATAGATAT) (Zhang et al. \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e2012a\u003c/span\u003e). In the present study, we identified 46 SSRs from the \u003cem\u003eSiCAD\u003c/em\u003e genes. These SSRs primarily consisted of mononucleotide (p1) and dinucleotide (p2) repeats, while trinucleotide (p3) repeats were rare. A small number of tetranucleotide (p4) repeats were also detected (\u003cb\u003eSupplementary Table\u0026nbsp;5\u003c/b\u003e). No pentanucleotide repeats were observed. Notably, only two tetranucleotide repeats both of the motif (TATC)₆ were found, occurring in \u003cem\u003eSiCAD21X1\u003c/em\u003e and \u003cem\u003eSiCADX2\u003c/em\u003e.\u003c/p\u003e\u003cp\u003eMany studies have been reported the development of genomic SSRs and expressed sequence tag (EST)-derived genic SSRs. Genic SSRs, although less polymorphic, are functionally relevant and have been used in major oilseed crops like rapeseed peanut and soybean (Kresovich et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e1995\u003c/span\u003e). In sesame, however, relatively few EST-SSRs were developed and used to detect genetic diversity for sesame germplasm (Zhang et al. \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e2012a\u003c/span\u003e, \u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003eb\u003c/span\u003e; Wang et al. \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2012a\u003c/span\u003e; LinHai and YanXin \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Samaha et al. \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).Their limited polymorphism and potential location outside gene rich regions have restricted their use. In contrast, genomic SSRs are often highly polymorphic and widely distributed across the genome, making them more suitable for diversity analysis (Wang et al. \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e2011\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eIn our study, we identified a dinucleotide (AT)₁₁ repeat within a \u003cem\u003eSiCAD\u003c/em\u003e gene, classifying it as a genic SSR. This marker was developed and validated in a set of parental and derived lines (R1\u0026ndash;R8). Agarose gel 1.8% and 6% PAGE analysis revealed a total of 20 alleles, all of which were homozygous and monomorphic (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA,B). This confirms the successful validation of our \u003cem\u003ein silico\u003c/em\u003e SSR mining and highlights the potential functional importance of this conserved genic SSR. Unlike genomic SSRs, which are more variable, genic SSRs tend to be conserved due to selective constraints in coding or regulatory regions (Zhang et al. \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e2012a\u003c/span\u003e). Although monomorphic SSRs are typically excluded from diversity studies due to their lack of variation, they still play important roles in plant breeding programs (Zhang et al. \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e2012a\u003c/span\u003e). Studies have shown that genic monomorphic SSRs can be used to identify true parental combinations within genetically diverse populations (Omer Hama-Ali and Guan Tan; Nazareno and dos Reis \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Zhao et al. \u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). The monomorphic often overlooked, can reveal conserved regions that are critical for maintaining gene function. Moreover, the flanking regions of such monomorphic SSRs can be informative for studying evolutionary relationships and genetic conservation within and across species (Zhang et al. \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e2012a\u003c/span\u003e). In conclusion, although the genic SSR identified in this study was monomorphic, its conservation and validation across sesame breeding lines suggest its utility as a functionally relevant marker for gene based breeding and evolutionary analyses (Omer Hama-Ali and Guan Tan; Nazareno and dos Reis \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Zhao et al. \u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e"},{"header":"5. Conclusion and Future Prospects","content":"\u003cp\u003eIn nature, crops are exposed to a combination of stresses that significantly reduce productivity. Manipulating lignin biosynthetic genes, particularly \u003cem\u003eCinnamyl Alcohol Dehydrogenases\u003c/em\u003e (CADs), offers a promising strategy to enhance stress tolerance. This study provides a foundational understanding of \u003cem\u003eSiCAD\u003c/em\u003e genes in sesame under \u003cem\u003eM. phaseolina\u003c/em\u003e and salt stress, highlighting their structural features, conserved motifs, and evolutionary relationships with well-studied species. Through gene structure analysis, motif identification, and synteny orthology with \u003cem\u003eArabidopsis\u003c/em\u003e, tomato, and potato, we have uncovered insights into the orthology and diversification of \u003cem\u003eSiCADs\u003c/em\u003e. Expression profiling under \u003cem\u003eM. phaseolina\u003c/em\u003e and salt stress further confirms their dynamic and stress-responsive nature of \u003cem\u003eSiCADs\u003c/em\u003e. These findings establish \u003cem\u003eSiCADs\u003c/em\u003e may be crucial components in sesame\u0026rsquo;s defense arsenal against \u003cem\u003eM. phaseolina\u003c/em\u003e. However, we need to carry out more molecular studies, how monolignols can improve productivity of sesame through manipulating this important pathway intermediate of phenylpropanoid biosynthesis pathways. Further, the development and validation of gSSRs support our analysis and open new avenues for future researchers working on marker trait associations. Looking forward, advanced breeding approaches and genome editing tools like CRISPR/Cas9 could be employed to fine tune \u003cem\u003eCAD\u003c/em\u003e gene function, paving the way for the development of stress-resilient sesame cultivars capable of withstanding both biotic and abiotic stress challenges.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated or analyzed during the current study are available in the present study.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe acknowledge the technical assistance of Mrs. Kaberi Ghosh, Mr. Jadab Ghosh, and Mr. Swarnava Das, Department of Biological Sciences, BI.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eGG received funding support from the Bose Institute, Department of Science and Technology, Government of India. MAN was supported by the Council of Scientific \u0026amp; Industrial Research (CSIR) under file number 09/015(0555)/2020-EMR-I. The funding agencies had no involvement in the study design, data collection and analysis, decision to publish, or manuscript preparation\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eContributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMAN: Conceptualization, Methodology, Investigation, Visualization, Bioinformatic Analysis, interpretation of data and statistical analysis. Writing original draft preparation and editing, Writing- review \u0026amp; editing, Software analysis. GG: Conceptualization, Writing, review \u0026amp; editing, Funds acquisition.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCorresponding author\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGaurab Gangopadhyay\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics declarations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEthics approval and consent to participate Not applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eAlexander RD, Wendelboe-Nelson C, Morris PC (2019) The barley transcription factor HvMYB1 is a positive regulator of drought tolerance. 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J Proteomics 220:103756. https://doi.org/10.1016/J.JPROT.2020.103756\u003c/li\u003e\n \u003cli\u003eZhang H, Wei L, Miao H, et al (2012a) Development and validation of genic-SSR markers in sesame by RNA-seq. BMC Genomics 13:1\u0026ndash;11. https://doi.org/10.1186/1471-2164-13-316/FIGURES/4\u003c/li\u003e\n \u003cli\u003eZhang H, Wei L, Miao H, et al (2012b) Development and validation of genic-SSR markers in sesame by RNA-seq. BMC Genomics 13:1\u0026ndash;11. https://doi.org/10.1186/1471-2164-13-316/FIGURES/4\u003c/li\u003e\n \u003cli\u003eZhang K, Qian Q, Huang Z, et al (2006a) GOLD HULL AND INTERNODE2 encodes a primarily multifunctional cinnamyl-alcohol dehydrogenase in rice. Plant Physiol 140:972\u0026ndash;983. https://doi.org/10.1104/pp.105.073007\u003c/li\u003e\n \u003cli\u003eZhang Y, Li D, Zhou R, et al (2019) Transcriptome and metabolome analyses of two contrasting sesame genotypes reveal the crucial biological pathways involved in rapid adaptive response to salt stress. BMC Plant Biol 19:. https://doi.org/10.1186/s12870-019-1665-6\u003c/li\u003e\n \u003cli\u003eZhang Z, Li J, Zhao XQ, et al (2006b) KaKs_Calculator: Calculating Ka and Ks Through Model Selection and Model Averaging. Genomics Proteomics Bioinformatics 4:259\u0026ndash;263. https://doi.org/10.1016/S1672-0229(07)60007-2\u003c/li\u003e\n \u003cli\u003eZhao M, Shu G, Hu Y, et al (2023) Pattern and variation in simple sequence repeat (SSR) at different genomic regions and its implications to maize evolution and breeding. BMC Genomics 24:1\u0026ndash;13. https://doi.org/10.1186/S12864-023-09156-0/FIGURES/8\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTables 1 and 2 are available in the Supplementary Files section\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[{"identity":"8b289c70-16a8-46ac-8830-36be7c3009a5","identifier":"10.13039/501100001412","name":"Council of Scientific and Industrial Research, India","awardNumber":"09/015(0555)/2020-EMR-I","order_by":0}],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"Bose Institute, Department of Science and Technology, Government of India","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Sesame, CAD gene, Macrophomina, salt stress","lastPublishedDoi":"10.21203/rs.3.rs-8161012/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8161012/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eSesame (\u003cem\u003eSesamum indicum\u003c/em\u003e) has been cultivated for centuries, prized for its oil and medicinal properties. With the availability of its genome, the identification and characterization of key gene families have become a research priority. Cinnamyl Alcohol Dehydrogenase (\u003cem\u003eCAD\u003c/em\u003e) gene plays a pivotal role in the phenylpropanoid pathway by catalysing the final step in lignin biosynthesis, specifically the production of monolignols. In this study, we identified \u003cem\u003eCAD \u003c/em\u003ehomologs and paralogs in the sesame genome using bioinformatic tools. Comparative synteny analysis with related species such as tomato and potato revealed evolutionary conservation and provided insights into the functional roles of sesame \u003cem\u003eCAD \u003c/em\u003egenes (\u003cem\u003eSiCADs\u003c/em\u003e). Phylogenetic and gene duplication analyses suggest that \u003cem\u003eSiCADs \u003c/em\u003egenes have undergone purifying selection, indicating evolutionary pressure to maintain their functional integrity, particularly under environmental stress.\u003c/p\u003e\n\u003cp\u003eTo understand the role of these genes in stress responses, we performed RNA-seq analysis under two major stress conditions: infection with \u003cem\u003eMacrophomina phaseolina\u003c/em\u003e, the causal agent of charcoal rot, and salt stress (NaCl). Expression profiling revealed that several \u003cem\u003eSiCADs\u003c/em\u003e are differentially regulated in both wild (\u003cem\u003eS. mulayanum\u003c/em\u003e) and cultivated (\u003cem\u003eS. indicum\u003c/em\u003e) genotypes, with notable differences in expression patterns across stress types and time points. These findings underscore the potential role of \u003cem\u003eSiCADs\u003c/em\u003e in defense and stress adaptation. This is the first comprehensive study of the \u003cem\u003eCAD \u003c/em\u003egene family in sesame, offering insights into their evolutionary dynamics and functional relevance. Subsequent, validation of obtained genic simple sequence repeats (gSSRs), will benefit the molecular breeding programs of sesame. The candidate genes identified in this study would provide a resource for gene cloning, functional validation, and molecular breeding, contributing to the development of stress-resilient sesame cultivars.\u003c/p\u003e","manuscriptTitle":"Expression Landscape, Evolutionary Insights, and Duplication Patterns of Cinnamyl Alcohol Dehydrogenase Genes Under Macrophomina phaseolina Infection and Salt Stress in Sesame","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-21 11:02:01","doi":"10.21203/rs.3.rs-8161012/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"9460e7d2-e074-489e-a41d-1a2afe2e03ce","owner":[],"postedDate":"November 21st, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":58299462,"name":"Plant Molecular Biology and Genetics"},{"id":58299463,"name":"Bioinformatics"}],"tags":[],"updatedAt":"2025-11-21T11:02:01+00:00","versionOfRecord":[],"versionCreatedAt":"2025-11-21 11:02:01","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8161012","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8161012","identity":"rs-8161012","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}