Integrated transcriptomic and endogenous hormones analyses revealed the molecular mechanism of light and auxin for the regeneration of callus tissue in seashore paspalum

Integrated transcriptomic and endogenous hormones analyses revealed the molecular mechanism of light and auxin for the regeneration of callus tissue in seashore paspalum | 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 Integrated transcriptomic and endogenous hormones analyses revealed the molecular mechanism of light and auxin for the regeneration of callus tissue in seashore paspalum Kai Jiang, Xiaochen Hu, Qi Sun, Yuzhu Wang, Xuanyang Wu, Guofeng Yang, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4615496/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 Background: Seashore paspalum ( Paspalum vaginatum O. Swartz) is a halophyte known for its exceptional salt tolerance and ecological adaptability. It is an excellent candidate for studying salt tolerance mechanisms and screening salt tolerance genes. However, the difficulties with callus tissue regeneration and the influence of genotype during cultivation provide a significant obstacle to the process of molecular breeding employing genetic transformation and gene editing techniques in seashore paspalum. Results: To elucidate the molecular mechanism of callus regeneration in seashore paspalum, this study analyzed the content of endogenous hormones and investigated the effects of light, KT, and genotype on callus regeneration; Through transcriptome analysis between different treatments, the molecular mechanisms were explored. Under light conditions, almost all callus tissues of genotype I could produce regenerated green buds, but genotype II could not regenerate. A total of 106.2 Gb clean readings were obtained from 12 cDNA sample libraries in four regeneration states (CK, KT-D, KT-L, and KT-L-NR). The Pearson correlation coefficients, principal component analysis, and DEG hierarchical clustering heatmap analysis results indicated good intra-group repeatability and reliable data. The specific expression genes induced by different genotypes (KT-L-NR vs KT-L) (3083) were significantly higher than those in other groups by Venn plot analysis. A total of 73 endogenous hormone substances were quantitatively detected in all samples. KEGG enrichment analysis showed that all comparison groups significantly enriched differentially changed hormones (DCHs) in diterpenoid biosynthesis and plant hormone signal transduction pathways. In KT-L, GA 5 and GA 51 were significantly higher than those in other groups, while GA 20 and GA 29 were significantly lower. KT-L-NR showed noticeably higher levels of GA 3 , GA 20 , and GA 29 , which could be a contributing cause to the incapacity of callus regeneration. The expression level of GA2ox (Pavag03G280900. v3.1) was very high, significantly negatively regulating GA 51 . In KT-L, the content of ABA and JA were the lowest and significantly lower than that in KT-L-NR. The content of indole-3-acetic acid (IAA) in KT-L and KT-L-NR were significantly higher than that in CK and KT-D, indicating that light played an important role in synthesizing of IAA, which was beneficial for the regeneration of callus tissue. Conclusions: This is the first report on callus regeneration mechanisms of seashore paspalum by combined transcriptome and endogenous hormone profiling. The results will improve the understanding of molecular mechanisms and the effects of endogenous hormones, and provide new insights to address the issue of genotype dependence in callus regeneration. seashore paspalum regeneration light genotype endogenous hormones Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Background Seashore paspalum ( Paspalum vaginatum O. Swartz, 2n = 2x = 20) is a halophytic warm-season grass, which is commonly used on landscape areas, golf courses and athletic fields[ 1 , 2 ]. Seashore paspalum grows in saline regions of landscapes and exhibits tremendous potential for being used under stressful and harsh environmental conditions. The plant is favored owing to its high tolerance to salt, water logging, and adaptation to conditions of weak shade and low irradiance. Seashore paspalum has been found to have greater salt resistance when compared to other grass species[ 3 , 4 ]. Some varieties are used in areas with limited access to fresh water, with high soil salinity, or turf is irrigated using wastewater[ 5 ]. Agrobacterium-mediated transformation of seashore paspalum has been established[ 6 ]. The genome assembly for the genotype of seashore paspalum (PI 509022) has been completed[ 5 ], and a transcriptome profile for salt resistance has been provided[ 7 ]. The selection of transgenic plants expressing CdNF-YC genes has improved drought and salt tolerance[ 8 ], and more gene functions related to salt tolerance have been identified[ 9 ]. Genetic transformation is a pivotal method for investigating gene function and advancing molecular breeding. The success of genetic transformation in monocotyledonous plants hinges on in vitro tissue culture and regeneration, which also represents a significant bottleneck in plant transformation[ 10 ]. The problem of difficult regeneration of callus tissue seriously restricts the process of molecular breeding of seashore paspalum using genetic transformation and gene editing techniques. To date, there have been no reports on the molecular mechanisms underlying regeneration in seashore paspalum. Genetic transformation and genome editing technology can drastically reduce plant breeding times and endow breeding lines with inheritable excellent target traits, which will breed new varieties with higher commercial promotion value[ 11 ]. Agrobacterium- mediated transformation and subsequent whole-plant regeneration from individual cells are optimal methods for generating target traits in transgenic plants. However, plant regeneration and transformation through somatic embryogenesis have significant technological bottlenecks that severely limit the efficiency of obtaining new germplasm[ 12 ]. The plant embryogenic callus (EC) is an irregular embryogenic cell mass with robust regenerative capabilities that can be used for propagation and genetic transformation[ 13 ]. Callus regeneration is an important process in the genetic transformation system of seashore paspalum. The efficiency of callus proliferation and regeneration directly affects establishing an efficient and stable genetic transformation system. The process of plant regeneration is regulated by intracellular genetic factors and extracellular environment-inducing factors, resulting from an interaction between genotype and environmental conditions. Plant hormones, genotype, and environment are the most important factors involved in the initiation of regeneration. Light plays a decisive role in the dedifferentiation and regeneration of callus tissue[ 14 ]. Callus regeneration is closely related to the types and concentrations of hormones. Kinetin (KT) plays an important role in plant callus regeneration [ 15 ]. Seeds of the seashore paspalum hybrid 'Sea Spray' (Hyb.7 x Q36313) were used to establish a genetic transformation system, and each seed represents a genotype. Partial genotype has a high regeneration ability, the others are scarce, even recalcitrant to regenerate. Genotype dependency hinders transgenic development utilization in seashore paspalum[ 6 ]. It is crucial to have an insight into the molecular mechanisms and influencing factors of regeneration. The differentiation and regeneration of calli are complex processes, regulated by gene expression. In some plants such as Arabidopsis, the molecular mechanisms during plant regeneration have been revealed[ 16 ]. The WOX11-LBD16 pathway facilitates the acquisition of totipotency in callus cells, establishing a root primordium-like identity within the newly formed callus in Arabidopsis[ 17 ]. WOX genes which have a role in the regeneration were specifically upregulated in high-regeneration lines of maize[ 14 ]. Overexpression of PtWOX11 promoted the formation of calli and regulated the regeneration of new shoots in poplar[ 18 ]. Overexpression of plant transcription factors such as WUSCHEL[ 19 ], WIND1[ 20 ], and BOOM AP2/ERF[ 21 ] have been shown to enhance regeneration. With the rapid development of high-throughput sequencing and mass spectrometry technology, an abundance of data from transcriptomics and metabolomics has been produced, offering valuable insights into the mechanisms of callus regeneration. Transcriptome studies make it possible to efficiently and quickly analyze differentially expressed genes and functionally annotate regulatory pathways[ 22 ]. Integrated transcriptomic and endogenous hormone content analysis insighted uncovering regeneration mechanism in Osmanthus fragrans calli[ 23 ]. Some potential genes linked to somatic embryogenesis were discovered by examining the transcriptome profile and gene expression regulation alterations of embryogenic callus and redifferentiation in hybrid sweetgum[ 24 ]. The molecular response to exogenous auxin signaling during in vitro cotton embryonic redifferentiation has been revealed by dynamic transcriptome analysis[ 25 ]. The auxin and cytokinin signaling pathways have been proven critical in redifferentiation[ 26 ]. Based on functional annotations in maize, a few closely related genes for callus regeneration have been found, and the functions of hormones and light in regeneration have been examined[ 14 ]. The results of multi-omics joint analysis can be beneficial for enriching the molecular regulatory network during regeneration and provide a new perspective for improving the efficiency of genetic transformation. In this study, we conducted a comprehensive analysis of the transcriptome and endogenous hormones to elucidate the roles and molecular mechanisms of light, KT, and genotypes in the regeneration process of seashore paspalum. This provides a foundation for clarifying the regeneration mechanism of seashore paspalum. Results Callus induction and regeneration The callus tissue induced by genotype Ⅰ and genotype Ⅱ has an excellent growth state on induction medium, and the callus tissue presented a yellow and compact granular shape ( Figure. 1A, 1B, 1C) . When the callus tissue was transferred to MG medium containing KT, it almost did not regenerate under dark conditions, and the callus tissue still maintained a yellow and compact granular shape. Callus produced a small number of regenerated buds, but the buds appeared white due to lack of light ( Figure. 1D, 1E, 1F) . Under light conditions, the callus of genotype Ⅰ turned green after 7 days and the shoots regenerated after 4 weeks with 100% regeneration rate ( Figure. 1G, 1H,1I) . In contrast, genotype Ⅱ calli were comparatively soft, granular, dark yellow, merely proliferating, and exhibited nearly no regeneration under light conditions ( Figure. 1J, 1K, 1L) . Sequencing annotation analysis statistics of different transcriptome To analyze the transcriptome and gene expression profiles of different influencing factors (KT, light, and genotype) during the regeneration process, 12 cDNA samples were extracted from the four states of calli (CK, KT-D, KT-L, and KT-L-NR) and sequenced using the Illumina NovaSeq 6000 system. All sample transcriptome data underwent low-quality data filtering, and the basic quality data was subjected to statistical analysis. A total of 12 samples obtained clean readings of 106.2 Gb, with each sample being sequential with more than 57 million raw reads and more than 55 million clean reads. After removing the adaptor sequences and low-quality reads, the Q20 quality of each sample was stable above 97.4%, the Q30 percentage was over 93.0%, and the GC content was between 52.7 and 54.4%, and the base error rate was low at 0.03%. More than 94.3% of paired-end reads were mapped to the seashore paspalum reference genome, per sample with an average unique mapping reads rate of 89.3%. The rate of reads mapped to the sense strand and antisense strand ranged from 44.0–44.9% (Table 1 ). Table 1 Statistics of the base quality from four libraries Sample Raw Reads Clean Reads Clean Base (G) Q20 (%) Q30 (%) GC Content (%) Mapped reads Unique mapped reads Multi mapped reads Reads map to sense strand Reads map to antisense strand CK-1 62838690 60778320 9.12 97.74 93.71 53.16 57846778 (95.18%) 54505544 (89.68%) 3341234 (5.50%) 27240261 (44.82%) 27265283 (44.86%) CK-2 60110900 58468030 8.77 97.6 93.36 52.88 55450905 (94.84%) 52494073 (89.78%) 2956832 (5.06%) 26232039 (44.87%) 26262034 (44.92%) CK-3 58963316 57490556 8.62 97.73 93.66 53.26 54659223 (95.08%) 51564828 (89.69%) 3094395 (5.38%) 25771856 (44.83%) 25792972 (44.86%) KT-D-1 58759546 57179762 8.58 97.65 93.51 54.09 54280304 (94.93%) 51361559 (89.82%) 2918745 (5.10%) 25672434 (44.90%) 25689125 (44.93%) KT-D-2 58984434 57249856 8.59 97.69 93.6 54.42 54494833 (95.19%) 50814011 (88.76%) 3680822 (6.43%) 25389745 (44.35%) 25424266 (44.41%) KT-D-3 60507436 58787680 8.82 97.81 93.86 53.15 55797903 (94.91%) 52441572 (89.21%) 3356331 (5.71%) 26199692 (44.57%) 26241880 (44.64%) KT-L-1 59094690 56927426 8.54 97.71 93.66 53.94 53978807 (94.82%) 50750242 (89.15%) 3228565 (5.67%) 25350320 (44.53%) 25399922 (44.62%) KT-L-2 57880802 55926246 8.39 97.56 93.44 53.58 52886504 (94.56%) 50113586 (89.61%) 2772918 (4.96%) 25021366 (44.74%) 25092220 (44.87%) KT-L-3 64528494 62513252 9.38 97.46 93.15 54.11 58985934 (94.36%) 56021556 (89.62%) 2964378 (4.74%) 27985322 (44.77%) 28036234 (44.85%) KT-L-NR-1 64769556 63021878 9.45 97.55 93.21 52.75 59659302 (94.66%) 56048800 (88.94%) 3610502 (5.73%) 28010634 (44.45%) 28038166 (44.49%) KT-L-NR-2 60130944 58593118 8.79 97.56 93.25 53.05 55458519 (94.65%) 52301388 (89.26%) 3157131 (5.39%) 26132637 (44.60%) 26168751 (44.66%) KT-L-NR-3 64120544 61378058 9.21 97.45 93.09 53.31 57979807 (94.46%) 54139319 (88.21%) 3840488 (6.26%) 27046786 (44.07%) 27092533 (44.14%) Raw Reads: Total number of original reads; Clean Reads: The total number of high-quality data bases after filtering the original reads; Clean Base(G): Total number of high-quality reads; Q20 (%)/Q30 (%): Percentage of bases with a Phred value above Q20/Q30 in clean data; GC content: Percentage of G and C bases out of the total bases in clean data; Mapped reads: the number of reads that can be matched to the reference genome (proportion of matched reads); Unique/ Multi mapped reads: the number of reads that match to a unique/multiple multiple position in the reference genome sequence (proportion of mapped reads); Reads map to sense/antisense strand: the number of reads comparison to the sense/antisense strand of the genome after UMI deduplication, (proportion of mapped reads). DEGs identification and enrichment analyses To reflect the correlation of gene expression in any two samples, we calculated the Pearson correlation coefficients for all gene expression levels between each two samples and reflected these coefficients in the form of a heat map. The average Pearson correlation coefficients between all samples within a group were greater than 0.83, with the highest being 0.99, indicating three repeated samples within the group had good repeatability ( Figure. 2A ). The significant differentially expressed genes (DEGs) were selected by setting |log2fold change| ≥ 1 and p value ≤ 0.05 as criterions. In this study, a total of 15771 significant DEGs were observed in the four comparison groups related to regeneration. Genotypes have a significant impact on gene expression levels, the total number of DEGs was the highest. The group with the largest number of DEGs was the (KT-L-NR vs KT-L) group, with 1350 downregulated genes and 3550 upregulated genes. While under the same KT conditions, the lowest number of significant DEGs (196 downregulated and 338 upregulated) was detected between the KT-L and KT-D groups ( Figure. 2B ). Before doing the unsupervised PCA (principal component analysis), data was unit variance-scaled. Unsupervised PCA was carried out using the statistics function ‘prcomp’ in R1, which was useful for utilizing a small number of primary components to analyze the internal structure of several variables. The transcriptome data of callus regeneration were subject to PCA analysis. In the PCA score plot, the first principal component (PC1) and the second principal component (PC2) represented 25.8% and 19.0% of the total variance, respectively and the cumulative contribution rate of PC1× PC2 reached 44.8%. The callus statuses CK, KT-D, KT-L, and KT-L-NR could be almost completely separated, indicating that the genes expressed differently; the compact cluster formed by the three biological repeats of each status showed that the materials were sufficiently reproducible and appropriate for further qualitative and quantitative analyses. ( Figure. 2C ). Venn diagram analysis showed 212 DEGs were detected in common among all three comparison groups, and 197, 2588, and 3083 specific DEGs in comparison groups (KT-L vs KT-D, KT-D vs CK, and KT-L-NR vs KT-L), respectively. In the stage of embryonic regeneration, the specific expression genes induced by different genotypes (KT-L-NR vs KT-L) (3083) were much higher than those induced by KT or light conditions during the regeneration process. The number of specific expression genes induced by KT (KT-D vs CK) was 2588, which was higher than the 197 specific expression genes induced by light (KT-L vs KT-D) ( Figure. 2D ). Blue and red on the heat map represent low and high DEG expression levels, respectively. The hierarchical clustering of DEGs in all the biological replicates was classified into the same cluster, which indicated a robust correlation between replicates and the high reliability of our data. The heat map also revealed that some DEGs were specifically accumulated in the KT-L, but some only existed in the KT-L-NR ( Figure. 2E ). There were 2484 transcription factors associated with 91 gene families among the induced genes. Of these genes, 149 genes are transcription factors of the AP2/ERF-ERF family, followed by BASIC/HELIX–LOOP–HELIX (bHLH) transcription factors with 147 members that exhibited changes in expression after induction. Following induction, there were noticeable alterations in the expression of 136 NACs, 133 MYBs, 115 C 2 H 2 s, and 113 WRKYs, among other transcription factors ( Figure. 2F ). GO and KEGG enrichment analysis of DEGs in different callus To further elucidate the effects of KT, light, and genotype on the transcription levels of key genes in callus regeneration, we separately investigated GO and KEGG enrichment analyses of the DEGs in the comparison groups (KT-D vs CK, KT-L vs KT-D, and KT-L-NR vs KT-L). All comparison groups were associated with three ontologies in the GO database enrichment analysis: ‘biological process’, ‘cellular component’, and ‘molecular function’. In the enrichment analysis results of three comparison groups, the 50 GO terms with the lowest FDR were selected, and constructed a column chart to visualize the enrichment items. Three comparison groups have different levels of enriched Go entries in three ontologies. The GO analysis revealed that the DEGs were mostly enriched in biological processes. In the cellular component, KT-D vs CK had the lowest enriched GO terms; in the molecular function, KT-L vs KT-D had the lowest enriched GO terms. Within the biological process, the enriched GO terms in both KT-L vs KT-D and KT-L-NR vs KT-L were 'photosynthesis' and 'generation of precursor metabolites and energy' and the different term enrichment for KT-D vs CK included ‘cellular polysaccharide metabolic process’ and ‘response to oxidative stress’. Within the cellular component, the enriched GO terms in both KT-L vs KT-D and KT-L-NR vs KT-L were 'photosynthetic membrane’ and ‘thylakoid membrane’ and also the different term enrichment for KT-D vs CK included ‘anchored component of membrane’ and ‘intrinsic component of plasma membrane’. Within the molecular function the enriched GO terms in both KT-D vs CK and KT-L-NR vs KT-L were 'hydrolase activity, hydrolyzing O-glycosyl compounds’ ( Figure. 3A; 3B and 3C ). To elucidate the functions of the DEGs, KEGG functional enrichment analysis was performed. We mapped the top 20 paths with the lowest Q-value. The pathway was shown to be more significantly enriched when the Q-value value was smaller; the number of enriched DEGs was indicated by a larger point; and the ratio of enriched DEGs to annotated genes was greater when the Rich factor was larger. Based on the KEGG functional enrichment analysis, the number of DEGs involved in metabolic pathways was the largest in all comparison groups ( Figure. 3D; 3E and 3F ). In KT-L vs KT-D, the significantly and specific enriched pathways were involved in photosynthesis -antenna proteins and porphyrin metabolism. Photosynthesis, metabolic pathways, carbon fixation in photosynthetic organisms, porphyrin metabolism, and carbon metabolism pathways play a critical role in the seashore paspalum regeneration (Figure. 3E) . Hierarchical clustering analysis suggested that the overview of the relative changes of DEGs among the comparison groups (KT-D vs CK, KT-L vs KT-D and KT-L-NR vs KT-L). The heatmap displayed tight clustering, indicating strong repeatability in biological replicates and a close correlation of the DEGs between groups ( Figure. 3G; 3H and 3I ). Plant hormones analysis based on KEGG enrichment To explore the role of plant hormones in the regeneration process of callus tissue, this study utilized plant hormones analysis platform based on LC-MS/MS to determine hormone levels in four groups of samples. In this study, a total of 73 substances belonging to 8 major categories of plant hormones were quantitatively detected in the 4 samples, including 27 cytokinins (CK), 17 auxins, 11 gibberellin (GA), 9 jasmonite acids (JA), 5 salicylic acids (SA), 2 abscisic acids (ABA), 1 ethylene (ETH) and 1 melatonin (MLT) ( Figure. 4A ). To identify the plant hormones that play an important regulatory role in the regeneration process of callus tissue, we analyzed the differential hormones using thresholds for fold change ≥ 2 and fold change ≤ 0.5 to screen differentially changed hormones (DCHs). In KT-D vs CK, KT-L vs KT-D, and KT-L-NR vs KT-L, the upregulated DCHs were 19, 22, and 20, respectively, while the downregulated DCHs were 12, 21, and 18 ( Figure. 4B ). KEGG enrichment analysis revealed that DCHs were substantially enriched in the diterpenoid biosynthesis and plant hormone signal transduction pathways across all comparison groups ( Figure. 4C; 4D and 4E ). Endogenous gibberellin content and metabolic pathways analysis GA quantification results showed that GA 4 was only detected in CK (Fig. 5 A), and GA 53 was only detected in KT-D (Fig. 5 B). In the treatment groups (KT-L, KT-D, and KT-L-NR) following the addition of KT, no GA 4 was found; nevertheless, the level of GA 19 was significantly higher than that of CK. Concurrently, in the non-regenerable genotype KT-L-NR, the content of GA 19 was significantly lower than in KT-L and KT-D (Fig. 5 C). In KT-L, GA 5 and GA 51 were significantly higher than those in other groups (Fig. 5 D; 5 E), while GA 20 and GA 29 were significantly lower than those in other groups (Fig. 5 F; 5 G). GA 3 was only detected in KT-L-NR (Fig. 5 H). It is evident that the addition of KT greatly enhanced the content of GA 19 while drastically decreasing the content of GA 4 ; while the content of GA 5 and GA 51 increased dramatically in KT-L under light conditions. Changes in the contents of these substances may be the main contributors to the regeneration of callus tissue in seashore paspalum. In contrast to KT-L, non-regenerable genotypes showed noticeably higher levels of GA 3 , GA 20 , and GA 29 under the same conditions, which could be a contributing cause to the incapacity of callus regeneration. Through joint analysis of endogenous hormone and transcriptome data, DEGs identified in the diterpenoid biosynthesis metabolic pathway included 1 gibberellin 13-oxidase ( CYP714B ) gene, 3 gibberellin-44 dioxygenase ( GA20ox ) genes, and 7 gibberellin 2beta-dioxygenas ( GA2ox ) genes. The CYP714B gene and GA20ox genes were significantly upregulated in KT-D vs CK, positively regulating the synthesis of GA 53 and GA 19 . There was one GA2ox gene significantly downregulated in KT-L vs KT-D and KT-D vs CK, negatively regulating the synthesis of GA 51 and GA 29 . The expression level of GA2ox (Pavag03G280900. v3.1) was very high, significantly negatively regulating GA 51 . In the plant hormone signal transduction metabolic pathway, DEGs included 9 gibberellin receptor GID1 genes, 15 DELLA genes, and 16 phytochrome-interacting factor 3 ( PIF3 ) genes, which were involved in regulating biological processes such as germination in the GA 4 signaling pathway (Fig. 5 I). Endogenous hormone content and signal transduction pathways analysis The ABA content was the lowest in KT-L which significantly lower than that in KT-L-NR (Fig. 6 A), and no ABA-GE was detected (Fig. 6 B). The JA content in KT-L was also lower than that in other groups, and significantly lower than KT-L-NR (Fig. 6 C). The JA-ILE contents in CK and KT-L-NR were significantly higher than that in KT-L (Fig. 6 D). The low contents of ABA and JA in the regeneration group indicated that they may have a negative impact on the regeneration capacity. Through joint analysis of endogenous hormone and transcriptome data, DEGs identified in ABA signal transduction pathway included 4 protein phosphatase 2C ( PP2C ) genes, 2 SNRK2 genes, and 5 ABA-responsive element binding factor ( ABF ) genes; and in JA signal transduction included 1 jasmonic acid-amino synthetase ( JAR1 ) gene, 9 jasmonate ZIM domain-containing protein ( JAZ ) genes, and 10 ( MYC2 ) genes (Fig. 6 M). The contents of indole-3-acetic acid (IAA) in KT-L and KT-L-NR were significantly higher than that in CK and KT-D, suggesting that light plays a crucial role in stimulating the synthesis of IAA, which was beneficial for the regeneration of callus tissue (Fig. 6 E). Furthermore, the contents of indole-3-acetyl-L-tryptophan (IAA-Trp), indole-3-acetyl-L-valine methyl ester (IAA-Val-Me), and tryptamine (TRA) were the highest in KT-L, all significantly higher than those in CK (Fig. 6 F; 6 G and 6 H). These findings suggest that IAA and its related compounds like IAA-Trp, IAA-Val-Me, and TRA all contribute to promoting effect on the regeneration of seashore paspalum. Both KT and light factors have important promoting effects on callus regeneration. Both KT and kinetin riboside (KR) levels were significantly higher in KT-D, KT-L, and KT-L-NR than in CK (Fig. 6 I; 6 J). Trans-zeatin riboside (tZR) was only detected in KT-L, with N6-isopentenyl adenine (IP) content being the lowest, significantly lower than KT-L-NR (Fig. 6 K; 6 L). These results indicate that the addition of exogenous KT can substantially increase the content of endogenous KT and KR, which are essential for the regeneration of seashore paspalum. Validation of transcriptomic data using qRT-qPCR To confirm the expression patterns of a subset of DEGs identified by Illumina sequencing, eight genes were randomly selected that related to the diterpenoid biosynthesis metabolic pathway and plant hormone signal transduction for qRT-PCR verification. The RT-PCR results showed the expression levels of these genes obtained by qRT-PCR analysis were consistent with the FPKM value trends obtained by the RNA-seq data, which indicated the reliability and accurately of the gene expression data measured by RNA-seq (Fig. 7 ). Discussion As a halophyte with extremely high salt tolerance and ecological adaptability, seashore paspalum has enormous potential for application in saline-alkali land improvement and soil remediation. The molecular mechanism research on the extremely high salt tolerance of seashore paspalum can provide a theoretical basis and genetic resources for the molecular breeding of turfgrass and crops. At present, a genetic transformation system has been established for seashore paspalum. Research on salt tolerance mechanisms and molecular design breeding processes of seashore paspalum has been limited due to issues such as genotype dependence and regeneration difficulties that have arisen during the establishment of CRISPR/Cas9 genome editing systems and the screening of genetically modified materials. This is the first report on callus regeneration mechanisms of seashore paspalum by combined transcriptome and endogenous hormone profiling. This study analyzed the content of endogenous hormones and investigated the effects of light, KT, and genotype on callus regeneration; the molecular mechanisms were explored by combining transcriptome analysis. The findings will advance knowledge of endogenous hormone effects and molecular mechanisms, as well as offer fresh perspectives on the problem of genotype dependence in callus regeneration. Genotype dependency analysis based on hormone differences The universal genotype dependence of tissue culture protocols has impeded the improvement and breeding of crop varieties through genetic transformation or genome editing [ 27 , 28 ]. Usually, genetic transformation systems have been established only in a limited number of species and optimized for specific genotypes [ 29 ]. Moreover, most commercially valuable varieties exhibit recalcitrance or only marginal transformability [ 30 ]. The utilization of gene editing technologies for the precise fine-tuning and introduction of desirable traits in newly released elite commercial varieties has been hindered by the restricted range of receptive genotypes with less genetic background and agronomic values. Genotype dependence remains insurmountable and universal in crops including barley [ 27 ], wheat [ 31 ], sorghum [ 32 ], and cotton [ 33 ]. To eliminate genotype reliance in plant transformation, several strategies have been tried recently. The genotype-independent transformation has been established in maize by transforming the maize's major transcription factors, Baby Boom ( Bbm ) and Wuschel2 ( Wus2 ) into immature maize embryos of some previously nontransformable maize inbred lines and high transformation frequencies have been obtained. Some monocots, including ( Sorghum bicolor ) immature embryos and indica rice ( Oryza sativa ssp indica ) callus, have improved transformation by expressing maize Bbm and Wus2 genes[ 34 ]. In sorghum, Wus2 -enabled transformation raises the frequency of CRISPR/Cas-targeted genome editing in addition to the transformation efficiency. Wus2 -induced direct somatic embryogenesis and regeneration reduces the duration of tissue culture cycles dramatically and avoids genotype-dependent callus development [ 32 ]. Pollen transfected with DNA-coated magnetic nanoparticles was efficiently delivered into maize inbred lines that are resistant to tissue culture-mediated transformation by a genotype-independent pollen transfection technology [ 35 ]. A shoot apical meristem cell-mediated transformation (SAMT) has been developed, which enables an efficient transformation and CRISPR/Cas9-mediated genome editing system for various recalcitrant cotton genotypes [ 33 ]. However, research on the relationship between genotype dependence and endogenous hormones in plants has not been documented. This study provides new ideas for addressing genotype dependence by analyzing the differences in endogenous hormones and key regulatory genes between regenerative and non-regenerative genotypes. During the regeneration process, genotypes have a significant impact on gene expression levels, the total number of DEGs in the KT-L vs KT-L-NR group was the highest, with 1350 downregulated genes and 3550 upregulated genes; while the specific expression genes were 3083 which were much higher than those induced by KT or light conditions. The hierarchical clustering of DEGs was also clearly different in KT-L vs KT-L-NR. The role of endogenous hormones in callus regeneration The process of callus regeneration is closely related to the types, concentrations, and dynamic balance of endogenous hormones in callus that were also controlled by exogenous hormones[ 23 ]. The beginning of proliferation centers in explants and the plant architecture are impacted by the amounts of endogenous hormones[ 36 ]. Callus tissue can only differentiate into adventitious buds under appropriate external conditions, and the composition and content of endogenous hormones are also different in different states. Previous studies have mainly focused on the effects of external conditions or the supplementation of media with nutrients and phytohormones in culture media on callus induction. Some studies have identified the involvement of endogenous hormones in the morphological reactions of callus tissue, and their concentrations are temporally regulated in response to external culture conditions[ 37 ]. The effects of endogenous hormone content and types on callus induction were evaluated in explants such as wheat[ 38 ], maize[ 39 ], and Medicago truncatula Gaertn[ 40 ]. However, there have been no reports on the changes and effects of endogenous hormones during the regeneration stage of callus tissue. We used the LC-MS/MS hormone analysis platform to measure and analyze the content and differences of endogenous hormones during the regeneration process of callus tissue in seaside paspalum. A total of 73 substances were detected in 8 categories of plant hormones. In our study, the gibberellins (GA3, 4, 5, 19, 20, 29, 51 and 53), abscisic acid (ABA, ABA-GE), jasmonic (JA, JA-ILE), auxins (IAA, IAA-Trp, IAA-Val-Me and TRA) and cytokinins (CK, KR, tZR and IP) were presented in the process of callus regeneration and influenced by genotype or external conditions. GAs regulate a multitude of developmental processes throughout the entire life cycle of plants[ 41 ]. The researchs related to the effect of GAs on somatic embryogenesis (SE) and callus regeneration mainly comes from studies on adding exogenous GAs to the culture medium; and there are differences in the role of GA on SE[ 42 ]. The research on endogenous hormones mainly focuses on the induction stage of callus tissue, but there have been no reports on the role of endogenous GA in callus regeneration. Compared to the non-embryogenic callus of maize, the contents of endogenous GAs (GA 1 , GA 3 , GA 20 ) were significantly higher in the embryogenic callus[ 39 ], which was consistent with the results in Medicago truncatula Gaertn[ 43 ]. Endogenous gibberellins are required for embryo production and embryogenic callus growth in Medicago. All the active gibberellins (GA 1 , GA 3 , GA 6 , and GA 4 , GA 7 ) were presented in the SE progress from the leaf explants of non-embryogenic (M9) and embryogenic (M9-10a). The levels of GA 3 and GA 6 were found to elevate in the M9-10a genotype as the induction phase advanced. Among all the bioactive gibberellins detected, only GA 3 appeared to be correlated with the SE initiation[ 40 ]. The GA 3 content in Golden Promise varieties of barley ( Hordeum vulgar L.) was much higher than that in local varieties, that may indicated a direct correlation between the amount of GA 3 hormone and the percentage of regeneration[ 42 ]. However, endogenous GAs need to be downregulated to promote SE in studies on Arabidopsis [ 44 ] and carrots[ 45 ].In our study, GA 5 and GA 51 were considerably higher and GA 20 and GA 29 were not detected in regenerable genotypes (KT-L). Non-regenerable genotypes exhibited notably greater levels of GA 20 and GA 29 , and GA 3 only detected in KT-L-NR which may be a factor in the incapacity of callus regeneration. Genes within the GA2ox family are pivotal in the GAs metabolic pathway, primarily facilitating the inactivation of GAs[ 46 ]. Overexpression of GA2ox genes can lead to the degradation of bioactive GAs in plants, culminating in a dwarf phenotype. In rice, the overexpression of the genes OsGA2ox1 , OsGA2ox6 , and OsGA2ox9 results in diminished plant stature. In wheat, the ectopic expression of the soybean PcGA2ox1 gene significantly diminishes GA levels, thereby reducing plant height[ 47 ]. GA2ox was stimulated to inactivate certain bioactive GAs to maintain appropriate ABA to GA ratios, thereby facilitating the SE response in Medicago [ 48 ]. Similarly, GA2ox ( Pavag03G280900. v3.1 ) significantly negatively regulated GA 51 , which expressed very high. Therefore, we speculated that GA2ox may be a key gene involved in regulating callus regeneration. Endogenous hormones in plants form a complex signaling network that affects cell growth and development by regulating key genes involved in cell proliferation[ 49 ]. Many genes have been identified from plant hormone signaling pathways, including candidate genes that regulate seashore paspalum callus regeneration such as PvMYC2 in JA plant hormone signal transduction metabolism pathways that may be involved in gene network regulation during callus regeneration. MYC transcription factors serve as regulators of plant growth and development, acting either as activators or repressors of JA-related gene expression. The repression of MYC could plausibly lead to diminished JA levels in Pinellia ternata [ 50 ]. Our findings align with the conclusions drawn from the aforementioned studies. These results will provide molecular strategies for overcoming the genotype dependence problem in seashore paspalum regeneration difficulties. ABA played an important role in the induction of callus tissue in some plant species[ 50 ]. In carrot tissue culture systems, high endogenous ABA content may play an important role in embryonic development ability[ 51 ], and the endogenous ABA level in embryogenic carrot cells was greater than that in non-embryogenic cells[ 39 , 52 ]. But the amount of endogenous ABA and percentage of regeneration were inversely related in barley. High regeneration rate barley varieties (Golden Promise cultivar) have significantly lower ABA content than low regeneration rate varieties (Iranian cultivars)[ 42 ]. Compared with non-embryogenic (M9), the callus quality of embryogenic (M9-10a) was significantly higher, which may be related to the lower ABA content in this callus tissue of Medicago [ 40 ]. Our results were consistent with the above finding in barley and medicago. The ABA content in the regenerative genotype (KT-L) was significantly lower than that in the non-regenerative genotype (KT-L-NR); and lower than that in the differentiation stage. It can be seen that low ABA content was one of the key factors for callus regeneration in seashore paspalum. ABA production from ABA-GE that can regulate the local ABA concentration, mediated by β-glucosidase present in vacuoles[ 53 ]. ABA-GE detected in initial explants of Medicago were higher in non-embryogenic (M9) than in the embryogenic (M9-10a)[ 43 ]. Unlike this, we did not detect ABA-GE in the regenerative genotype (KT-L). JA facilitates the activation and regeneration of stem cells in the growth and developmental processes of plant tissues[ 54 ]. However, some researches have reported inconsistent conclusions. JA has an inhibitory effect on the formation of callus tissue[ 55 ], combating plant organ differentiation by inhibiting cell proliferation and expansion[ 56 ]. Low concentrations of endogenous JA have been shown to stimulate callus proliferation and development in both garlic[ 36 ] and Pinellia ternata [ 50 ], a finding that is consistent with our studies on callus regeneration of seashore paspalum. Meanwhile, JA-ILE was also the lowest in regenerated callus tissue. Previous research has established that IAA is crucial for callus differentiation in tissue culture systems[ 57 , 58 ]. Endogenous IAA levels were higher in embryogenic cells compared to non-embryogenic cells in carrot tissue[ 59 ]. Higher endogenous levels of IAA within explants are essential for the initiation and proliferation of garlic callus[ 36 ]. Tryptophan (TRP) represents a rate-limiting factor in the auxin biosynthesis and its derivatives, with its catabolism product, tryptamine (TRA), potentially exerting a positive influence on callus formation in Pinellia ternata [ 50 ]. Consistent with the aforementioned findings, IAA and related substances (IAA-Trp, IAA-Val-Me, and TRA) were detected at the highest concentrations in the regeneration genotype (KT-L), significantly higher than that in the control (CK). Natural CKs, a class of adenine derivatives, are categorized into two distinct states: free-state CKs and bound-state CKs. Both the type and concentration of CKs in culture medium significantly influence callus proliferation and plant regeneration[ 60 ]. when CKs were introduced into the regeneration medium, not only initiate callogenesis and promote de novo shoot formation but also exert impacts on the endogenous CKs balance[ 61 ]. In hydroponic cuttings of Pinellia ternata , endogenous CKs serve as the central hormone regulating the formation of calli[ 50 ]. There were few reports on the relationship between endogenous CK content and callus regeneration. In our study, the supplementation of exogenous KT to the culture medium resulted in a significant increase in the levels of endogenous KT and KR within callus tissue. Additionally, tZR was exclusively detected in the regenerated callus tissue (KT-L). These observations suggest that the modulation of hormone levels, particularly cytokinins, can significantly influence callus tissue regeneration, thereby offering a potential strategy to enhance regeneration efficiency. Conclusions Seashore paspalum, a halophyte with remarkable salt tolerance and ecological adaptability. However, callus tissue regeneration challenges and genotype effects have significantly hindered molecular breeding efforts through genetic transformation and gene editing. Our study presents the first integrated analysis of the transcriptome and endogenous hormone profiles in seashore paspalum to delineate the callus regeneration mechanisms. By examining the interplay of light, KT, and genotypes, our research has uncovered key molecular and hormonal factors that govern the regeneration process. This work provides critical insights into genotype dependence in callus regeneration and lays a foundational framework for developing strategies to improve regeneration efficiency. Methods Plant growth and treatments Embryogenic callus inducted from seeds of the seashore paspalum ( Paspalum vaginatum O. Swartz) cultivar ‘Sea Spray’ in the dark at 25°С. All materials has been deposited in a publicly Grass Science Laboratory oof Qingdao Agricultural University. Embryogenic calli derived from the embryo of genotype Ⅰ and genotype Ⅱ were cultured in one dish as an individual clone on an induction medium (MS2.5) for proliferation and subcultured every 4 weeks[ 6 ]. After subculturing for 5 months, high-quality compact embryogenic calli of genotype Ⅰ and genotype Ⅱ were transferred to a regeneration medium (MG) containing MS basal medium supplemented with 0.2 mg L − 1 kinetin for regeneration under 16 h photoperiod (200 µmol m − 2 s − 1 )[ 6 ]. Callus tissues with the same status were cultured under different conditions for 4 weeks; Four statuses of callus development were defined: CK , calli under dark on MS2.5; KT-D , calli under dark on MG; KT-L , calli of genotype Ⅰ under light on MG; KT-L-NR , calli of genotype Ⅱ under light on MG. Collect samples of callus tissues from four distinct states and promptly observe and photograph them under a microscope. Callus tissue was sampled using liquid nitrogen and stored at − 80°C for measuring separately RNA isolation and endogenous hormone determination. All experimental treatments were set with three replicates. Tissue Paraffin Section Preparation To compare the cytological characteristics of callus, four statuses of callus (CK, KT-D, KT-L and KT-L-NR) were promptly fixed in FAA (75% ethanol: acetic acid: formaldehyde, 90:5:5, v/v/v). Fixation at room temperature for longer than 24 hours, and twice aspirating for 15 minutes each time. Subsequently, fixed samples were dehydrated with a graded series of ethanol (75%, 85%, 90%, 95%, and 100%—each step for 25 min twice, v/v)). Next, the samples were immersed in the same volume of tert-butanol and melted paraffin. Following that, the samples were cooled in the carton while embedded in pure paraffin. Sections (5 µm in thickness) were cut using a microtome (Leica Instrument RM2016, Shanghai, China) and stained with toluidine blue dye (Servicebio G1032, Wuhan, China) for 5 min. Cell proliferation was observed using a microscope (Nikon Eclipse E100, Nikon DS-U3, Nikon Instruments (Shanghai) Co., Ltd., Shanghai, China) in bright field mode. RNA Extraction and Illumina Sequencing Total RNA was extracted from calli of four statuses using the Plant Total RNA Extraction Kit (TIANGEN Biotech, Beijing, China) according to the manufacturer's instructions. cDNA was synthesized using the PrimeScript RT reagent kit with a gDNA eraser (Takara, Dalian, China). The quality and integrity of the RNA samples were assessed using the Agilent 2100 Bioanalyzer (Agilent Technologies, CA, USA), NanoDrop2000 (Thermo Fisher Scientific, MA, USA), and agarose gel electrophoresis. Following the manufacturer's instructions, sequencing libraries were generated using NEBNext Ultra™ RNA Library Prep Kit for Illumina (NEB, Ipswich, MA, USA). Four libraries (CK, KT-D, KT-L, and KT-L-NR) were constructed for the RNA-seq analysis using Illumina NovaSeq 6000 system (Illumina, San Diego, CA, USA) by Biomarker Technologies (Beijing, China). For the construction of a single cDNA library, it is required that the total RNA per sample ≥ 1 µg, OD 260/280 ≥1.8, and RIN value ≥ 6.5. The RNA-seq analysis was performed after the sample quality validation. Sequencing data analysis To obtain clean data, low-quality reads and reads containing adapters were discarded. Before data analysis, stringent quality control was applied to ensure that these reads possessed sufficient quality for the accuracy of subsequent analysis. Using the DESeq2 program (v1.6.3, open source, http://www.bioconductor.org/ ), differential expression analysis across samples was conducted to obtain differentially expressed genes (DEGs). The parameters were FDR ≤ 0.05 and |log2FC| (FC, fold change) ≥ 1. The seashore paspalum reference genome ( https://phytozome-next.jgi.doe.gov/info/Pvaginatum_v3_1 ) was used as the reference genome. Three replicates of standardized sequencing data with repeatability were applied for analysis. Gene function was annotated using commonly utilized databases. GO-Term Finder (v0.86, http://search.cpan.org/dist/GO-TermFinder/ ) provided descriptions for the GO terms of molecular function, biological process, and cellular component. GO terms with a p-value < 0.05 were considered significant. The Kyoto Encyclopedia of Genes and Genomes (KEGG) databases ( http://en.wikipedia.org/wiki/KEGG ) were used to determine which pathways were enriched. Significant metabolic pathways and functional categories were identified within differentially expressed genes, with FDR ≤ 0.05. Quantitative Real-Time PCR analysis Quantitative Real-Time PCR (RT-qPCR) was used to validate six genes that may have roles in callus regeneration in four stages that matched transcriptome sequencing. RT-qPCR was performed using the ACTIN gene as a reference. The forward and reverse primers listed in Table 2 were designed using Primer 5.0. The amplification program was as follows: 10 min at 95°C, and then 10 s at 95°C, 10 s at 60°C, and 20 s at 72°C for 40 cycles. To ensure accurate and consistent results, three technical duplicates were carried out for both the test and reference genes in every sample. Relative transcript levels for each gene were calculated using the 2 −ΔΔCt method. Duncan’s multiple range test and variance (ANOVA) analysis were conducted to determine the significant difference (p-values < 0.05) using SPSS 22.0 software (SPSS Inc., Chicago, IL, USA). Results were shown as mean ± standard error of biological replications. Table 2 Primers used for qRT-PCR Gene name Primer Sequence (5′–3′) Pv-Actin Forward CTTCTCTCAGCACTTTCCAACA ( Pavag03G414200.1 ) Reverse AAACATAACCTGCAATCTCTCC PvGA2ox Forward GCAGATCATCTCCGTGCTCA ( PavagK145700.v3.1 ) Reverse CAGTACACCTGAGCCACCTG PvGID1 Forward GTGATGTCCGTGGACTACCG ( Pavag01G411900.v3.1 ) Reverse GTCTCCGAGATGCACACCAG PvDELLA Forward ATCCTGGAGTCGTTCCTCGA ( Pavag02G332900.v3.1 ) Reverse TCCTCCAGCGAGTCCATGTA PvKAO Forward ACATGATGGACCGGCTGATC ( Pavag10G007100.v3.1 ) Reverse GACGGAGATCTCGAGCTTGG PvCYP714B Forward TGAGAGCACAGCAGTCACAG ( Pavag01G365100.v3.1 ) Reverse GCTCTGGCTCCACAATGAGT PvTF Forward CACCATGTCGCCGATGACTA ( Pavag03G251100.v3.1 ) Reverse AAGTACTCGTCGGTTGCCTG PvSNRK2 Forward ACAAGTACGAGCCAGTTCGG ( Pavag09G156200.v3.1 ) Reverse GGGTAAGCTCCCACAAGCAT Endogenous hormone level identification HPLC grade acetonitrile (ACN) and methanol (MeOH) were acquired from Merck (Darmstadt, Germany). All experiments were conducted using MilliQ water (Millipore, Bradford, USA). All of the standards were purchased from isoReag (Shanghai, China) and Olchemim Ltd. (Olomouc, Czech Republic). The stock solutions of standards were prepared at the concentration of 1 mg/mL in MeOH and stored at -20°C. Before analysis, the stock solutions were diluted with MeOH to create working solutions. Samples of callus tissues from four distinct states (CK, KT-D, KT-L, and KT-L-NR) were ground into powder (50 Hz, 60 s) in liquid nitrogen and then stored at -80°C. 50 mg of the material was weighed and then dissolved in 1 mL of methanol/water/formic acid (15:4:1, V/V/V). To serve as internal standards (IS) for the quantitation, 10 µL of an internal standard mixed solution (100 ng/mL) was added to the extract. The supernatant was transferred to plastic microtubules and evaporation to dryness, it was dissolved in 100 µ in 80% methanol (V/V); and filtered through a 0.22 µm membrane filter for LC-MS/MS analysis. A UPLC-ESI-MS/MS system (UPLC, ExionLC™ AD, https://sciex.com.cn/ ; MS, QTRAP® 6500+, https://sciex.com.cn/ ) was utilized to analyze the sample extracts. The following were the analytical conditions: LC: column, Waters ACQUITY UPLC HSS T3 C18 (100 mm×2.1 mm i.d., 1.8 µm); solvent system, water with 0.04% acetic acid (A), acetonitrile with 0.04% acetic acid (B); gradient program, started at 5% B (0–1 min), increased to 95% B (1–8 min), 95% B (8–9 min), and finally ramping back to 5% B (9.1–12 min); flow rate, 0.35 mL/min; temperature, 40°C; injection volume: 2 µL. Linear ion trap (LIT) and triple quadrupole (QQQ) scans were acquired on a triple quadrupole-linear ion trap mass spectrometer (QTRAP), QTRAP® 6500 + LC-MS/MS System, equipped with an ESI Turbo Ion-Spray interface, operating in both positive and negative ion mode and controlled by Analyst 1.6.3 software (Sciex). Data from three replicates were analyzed by using one-way ANOVA. All statistical analysis was performed by Statistical Package for the Social Sciences (SPSS 17.0). Results are shown as mean ± standard error of biological replications. The means were separated using Duncan’s multiple range test (p < 0.05). Abbreviations KT: Kinetin; DEGs: differentially expressed genes; FDR: false discovery rate; GO: Gene Ontology; KEGG: Kyoto Encyclopedia of Genes and Genomes; GA: gibberellin; CK: cytokinin; JA: jasmonic acid; SA: salicylic acid; ABA: abscisic acid, ETH: ethylene; MLT: melatonin; DCHs: differentially changed hormones; CYP714B : gibberellin 13-oxidase, GA20ox : gibberellin-44 dioxygenase; GA2ox : gibberellin 2beta-dioxygenas; PIF3 : phytochrome-interacting factor 3; PP2C: protein phosphatase 2C; ABF: ABA responsive element binding factor; JAR1: jasmonic acid-amino synthetase; JAZ: jasmonate ZIM domain-containing protein; IAA: indole-3-acetic acid; IAA-Trp: indole-3-acetyl-L-tryptophan, IAA-Val-Me: indole-3-acetyl-L-valine methyl ester, TRA: tryptamine; KR: kinetin riboside; IP: N6-isopentenyladenine; tZR: trans-zeatin riboside; SE: somatic embryogenesis; Declarations Ethics approval and consent to participate The use of plant parts in the present study complies with international, national, and/or institutional guidelines. Our research team is affiliated with the Key Laboratory of the Yellow River Delta Grassland Resources and Ecology of the Chinese Forestry and Grassland Administration. We have obtained the permission to collect Seashore Paspalum. Consent for publication Not applicable. Availability of data and materials The datasets generated and/or analysed during the current study are available in the NCBI repository, [https://www.ncbi.nlm.nih.gov/bioproject/PRJNA1128878]. Competing interests The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. Funding This work was supported by the National Natural Science Foundation of China (32101423), the Foundation Project of Shandong Natural Science Foundation (ZR2021MC066), and Fundamental Research Funds for the Universities (6631120002). the Foundation Project of Shandong Natural Science Foundation Authors’ contributions X. W. and K. 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Duan X, Chen L, Liu Y, Chen H, Wang F, Hu Y. Integrated physicochemical, hormonal, and transcriptomic analysis reveals the underlying mechanism of callus formation in Pinellia ternata hydroponic cuttings. Front Plant Sci . 2023;20:14:1189499. Kiyosue T, Nakajima M, Yamaguchi I, Satoh S, Kamada H, Harada H. Endogenous levels of abscisic acid in embryogenic cells, nonembryogenic cells and somatic embryos of carrot ( Daucus carota L. ). Biochem Physiol Pflanz. 1992;188:343–347. Pérez-Jiménez M, Cantero-Navarro E, Pérez-Alfocea F, Le-Disquet I, Guivarc’h A, Cos-Terrer J. Relationship between endogenous hormonal content and somatic organogenesis in callus of peach ( Prunus persica L. Batsch ) cultivars and Prunus persica×Prunus dulcis rootstocks. J Plant Physiol . 2014;171(8):619–624. Xu Z-Y, Lee KH, Dong T, Jeong JC, Jin JB, Kanno Y, Kim DH, Kim SY, Seo M, Bressan RA, et al. A vacuolar β-glucosidase homolog that possesses glucose-conjugated abscisic acid hydrolyzing activity plays an important role in osmotic stress responses in Arabidopsis . Plant Cell . 2012;24(5):2184–99. Zhou W, Lozano-Torres JL, Blilou I, Zhang X, Zhai Q, Smant G, Li C, Scheres B. A jasmonate signaling network activates root stem cells and promotes regeneration. Cell. 2019;177(4):942-956.e14. Iwase A, Harashima H, Ikeuchi M, Rymen B, Ohnuma M,aki S, Morohashi K, Kurata T, Nakata M, Ohme-Takagi M, et al. WIND1 Promotes shoot regeneration through transcriptional activation of ENHANCER OF SHOOT REGENERATION1 in Arabidopsis. Plant Cell .2017;29(1):54-69. Noir S, Bömer M, Takahashi N, Ishida T, Tsui T-L, Balbi V, Shanahan H, Sugimoto K, Devoto A. Jasmonate controls leaf growth by repressing cell proliferation and the onset of endoreduplication while maintaining a potential stand-by mode. Plant Physiol. 2013;161(4):1930–51. Ikeuchi M, Sugimoto K, Iwase A. Plant Callus: mechanisms of induction and repression. Plant Cell . 2013;25(9):3159–73. Yu J, Liu W, Liu J, Qin P, Xu L. Auxin control of root organogenesis from callus in tissue culture. Front Plant Sci . 2017;8;8:1385. Jiménez VM, Bangerth F. Endogenous hormone levels in explants and in embryogenic and non‐embryogenic cultures of carrot. Physiol Plantarum . 2001;111(3):389–395. Moyo M, Amoo SO, Aremu AO, Gruz J, Šubrtová M, Doležal K, Staden JV. Plant regeneration and biochemical accumulation of hydroxybenzoic and hydroxycinnamic acid derivatives in Hypoxis hemerocallidea organ and callus cultures. Plant Sci. 2014;227:157–64. Ćosić T, Raspor M, Motyka V, Cingel A, Ninković S. In vitro growth and regeneration of brassica oleracea var. gongylodes: a decade of research. Horticulturae . 2023;9(6):674. Additional Declarations No competing interests reported. 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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-4615496","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":331091875,"identity":"a3875d10-7e6c-4e8e-aad5-8044a5dd7783","order_by":0,"name":"Kai Jiang","email":"","orcid":"","institution":"Qingdao Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"Kai","middleName":"","lastName":"Jiang","suffix":""},{"id":331091878,"identity":"e6fcf790-23fd-4676-b72e-98fc19d2dd63","order_by":1,"name":"Xiaochen Hu","email":"","orcid":"","institution":"Qingdao Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"Xiaochen","middleName":"","lastName":"Hu","suffix":""},{"id":331091881,"identity":"87fafa65-ef57-40ce-a4ea-3c62a5ed3c86","order_by":2,"name":"Qi Sun","email":"","orcid":"","institution":"Qingdao Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"Qi","middleName":"","lastName":"Sun","suffix":""},{"id":331091882,"identity":"43bf7761-018f-407a-b548-90ed2fe8274d","order_by":3,"name":"Yuzhu Wang","email":"","orcid":"","institution":"Qingdao Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"Yuzhu","middleName":"","lastName":"Wang","suffix":""},{"id":331091884,"identity":"27e4bb13-b490-47bd-abf7-183d126a8be2","order_by":4,"name":"Xuanyang Wu","email":"","orcid":"","institution":"Qingdao Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"Xuanyang","middleName":"","lastName":"Wu","suffix":""},{"id":331091885,"identity":"1902c3c4-2b23-4a8e-bc42-b96251a47174","order_by":5,"name":"Guofeng Yang","email":"","orcid":"","institution":"Qingdao Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"Guofeng","middleName":"","lastName":"Yang","suffix":""},{"id":331091888,"identity":"1d762001-bc84-4ab0-a2a5-7261453f8226","order_by":6,"name":"Zeng-yu Wang","email":"","orcid":"","institution":"Qingdao Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"Zeng-yu","middleName":"","lastName":"Wang","suffix":""},{"id":331091889,"identity":"1e72fd62-ac56-48c2-9965-08953bc2d74a","order_by":7,"name":"Xueli Wu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAyUlEQVRIiWNgGAWjYHACxgMJBv942NgbGx9+IFbPgYSKAzL8PIebjSWI1sJw5oCN5Iz0NgEeYpQb3Eg+cOBh2x0eg5sP2xgkGOzkdBsIaJGckZZwILHtGY/B7cS2BwUMycZmBwho4ZfIMQBqYQZpaTeQYDiQuI2QFjaJ/A8QLTcPtknwEKMFaAswxM4c5pGcwUikFsmeZwbAQE7j4edJBAayARF+MTie/PDhDwMbezb24w8ffqiwkyOoBd0E0pSPglEwCkbBKMABAMm6RxvST3c0AAAAAElFTkSuQmCC","orcid":"","institution":"Qingdao Agricultural University","correspondingAuthor":true,"prefix":"","firstName":"Xueli","middleName":"","lastName":"Wu","suffix":""}],"badges":[],"createdAt":"2024-06-21 07:07:18","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4615496/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4615496/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":61321570,"identity":"769cac66-80ff-44e7-af31-d484f94bc23c","added_by":"auto","created_at":"2024-07-29 13:13:19","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":9692619,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eMorphology of callus regeneration under different treatments.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCalli of CK (genotype Ⅰ) under dark on MS2.5 (A), microscopic structure (B), and paraffin section (C); Calli of KT-D (genotype Ⅰ)under dark on MG (D), microscopic structure (E), and paraffin section (F); Calli of KT-L (genotype Ⅰ) under light on MG (G), microscopic structure (H), and paraffin section (I); Calli of KT-L-NR (genotype Ⅱ) under light on MG (J), microscopic structure (K), and paraffin section (L).\u003c/p\u003e","description":"","filename":"Fig1.png","url":"https://assets-eu.researchsquare.com/files/rs-4615496/v1/e05c75d14a17642b2c128910.png"},{"id":61321564,"identity":"5872d4ee-6fea-4cb3-9865-fb577f065a31","added_by":"auto","created_at":"2024-07-29 13:13:18","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1511943,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTranscriptome data analysis of callus regeneration.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe heatmap of Pearson correlation coefficients between each group (A); The number of up-regulated or down-regulated DEGs during regeneration process at kinetin, light and genotype treatments (B); Principle component analysis (PCA) of transcriptome samples in four groups (C); Venn diagram of DEGs between different comparison groups (D); Heatmap with hierarchical clustering analysis of DEGs in the transcriptome (E); Pie chart showing the TFs number categorized by TF family (F).\u003c/p\u003e","description":"","filename":"Fig2.png","url":"https://assets-eu.researchsquare.com/files/rs-4615496/v1/9460d8d748aaab4dbe1c1512.png"},{"id":61321565,"identity":"d15b35ba-ed56-4c76-98a5-920289661f84","added_by":"auto","created_at":"2024-07-29 13:13:19","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":4426987,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eGO and KEGG enrichment analysis, and hierarchical clustering analysis of all DEGs.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eGO enrichment analyses of the DEGs in comparison groups (A, B, C); Bubble plot of KEGG pathway enrichment analysis of DEGs in comparison groups (D, E, F); Heatmap with hierarchical clustering analysis of DEGs among different groups (G, H, I).\u003c/p\u003e","description":"","filename":"Fig3.png","url":"https://assets-eu.researchsquare.com/files/rs-4615496/v1/1b5727587d250d499d7d67a4.png"},{"id":61321571,"identity":"e13d31a9-5832-42db-aebe-f155afca8a2d","added_by":"auto","created_at":"2024-07-29 13:13:19","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":1921760,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePlant hormones analysis of different comparison groups\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePie chart showing the substances number categorized by plant hormones (A); The number of up-regulated or down-regulated differentially changed hormones (DCHs) (fold change ≥2 and fold change ≤0.5) during regeneration process at kinetin, light and genotype treatments (B); The bar chart of enriched KEGG pathways of DCHs in different comparison groups (C, D, E).\u003c/p\u003e","description":"","filename":"Fig4.png","url":"https://assets-eu.researchsquare.com/files/rs-4615496/v1/14690bcb3a3abbdf7791effc.png"},{"id":61321568,"identity":"65511488-bc96-4144-8e31-a7c9e8741b1d","added_by":"auto","created_at":"2024-07-29 13:13:19","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":2037778,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eEndogenous gibberellin contents and metabolic pathways.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe content of GA\u003csub\u003e4\u003c/sub\u003e (A), GA\u003csub\u003e53\u003c/sub\u003e (B), GA\u003csub\u003e19\u003c/sub\u003e (C), GA\u003csub\u003e5\u003c/sub\u003e (D), GA\u003csub\u003e51\u003c/sub\u003e (E), GA\u003csub\u003e20\u003c/sub\u003e (F), GA\u003csub\u003e29\u003c/sub\u003e (G), and GA\u003csub\u003e3\u003c/sub\u003e (H) in four treatment groups (KT-L, KT-D, and KT-L-NR). Means of three independent experiments and standard errors were presented; the different letter above the column indicated significant difference at P \u0026lt; 0.05. Base on conjoint analysis of hormones and transcriptomic, the schematic diagrams of the diterpenoid biosynthesis metabolism pathways and the transcriptional levels of several genes (I). In the diagrams, the hormones were marked by orange, and connection pathway was indicated by green; positive and negative infinity values were assigned 10 and -10 respectively to drew a heat map. The heatmap values represent the log2fold change in different comparison groups. Red color indicated a high expression level, while green was low.\u003c/p\u003e","description":"","filename":"Fig5.png","url":"https://assets-eu.researchsquare.com/files/rs-4615496/v1/1ae5b4dc57021f9b529b540d.png"},{"id":61321569,"identity":"1d40a9c7-44f4-4666-ad5d-5bb15f2d1270","added_by":"auto","created_at":"2024-07-29 13:13:19","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":1423417,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eEndogenous hormones contents and metabolic pathways.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe content of ABA (A), ABA-GE (B), JA (C), JA-ILE (D), IAA (E), IAA-Trp (F), IAA-val-Me (G), TRA (H), KT (I), KR (J), tZR (K), and IP (L) in four treatment groups (KT-L, KT-D, and KT-L-NR). Means of three independent experiments and standard errors were presented; the different letter above the column indicated significant difference at P \u0026lt; 0.05. Base on conjoint analysis of hormones and transcriptomic, the plant hormone signal transduction metabolism pathways and the transcriptional levels of several genes (M). In the diagrams, the hormones were marked by orange, and connection pathway was indicated by green; positive and negative infinity values were assigned 10 and -10 respectively to drew a heat map. The heatmap values represent the log2fold change in different comparison groups. Red color indicated a high expression level, while green was low.\u003c/p\u003e","description":"","filename":"Fig6.png","url":"https://assets-eu.researchsquare.com/files/rs-4615496/v1/ba83c4c62ee44bca72799702.png"},{"id":61322368,"identity":"9de2893b-891c-406f-a08f-78bb45f473bc","added_by":"auto","created_at":"2024-07-29 13:21:19","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":161783,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eGene expression analysis of transcriptome and qRT-PCR data.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTranscriptome data are presented as Log2 fold changes of FPKM values, with comparisons made between treatments KT-D, KT-L, or KT-L-NR versus the control CK. The relative gene expression levels, as determined by qRT-PCR, were quantified using the Log2(2^-ΔΔCt) method. The presented data represent the mean of three independent experiments, with error bars indicating the standard error.\u003c/p\u003e","description":"","filename":"Fig7.png","url":"https://assets-eu.researchsquare.com/files/rs-4615496/v1/bb4266314d4766353f8eba1b.png"},{"id":102296073,"identity":"e681d20c-cffb-4d79-a90b-254db6a85410","added_by":"auto","created_at":"2026-02-10 10:17:14","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":29749912,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4615496/v1/42738af8-33c3-4584-af85-c75d5695a034.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Integrated transcriptomic and endogenous hormones analyses revealed the molecular mechanism of light and auxin for the regeneration of callus tissue in seashore paspalum","fulltext":[{"header":"Background","content":"\u003cp\u003eSeashore paspalum (\u003cem\u003ePaspalum vaginatum\u003c/em\u003e O. Swartz, 2n\u0026thinsp;=\u0026thinsp;2x\u0026thinsp;=\u0026thinsp;20) is a halophytic warm-season grass, which is commonly used on landscape areas, golf courses and athletic fields[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Seashore paspalum grows in saline regions of landscapes and exhibits tremendous potential for being used under stressful and harsh environmental conditions. The plant is favored owing to its high tolerance to salt, water logging, and adaptation to conditions of weak shade and low irradiance. Seashore paspalum has been found to have greater salt resistance when compared to other grass species[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Some varieties are used in areas with limited access to fresh water, with high soil salinity, or turf is irrigated using wastewater[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Agrobacterium-mediated transformation of seashore paspalum has been established[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. The genome assembly for the genotype of seashore paspalum (PI 509022) has been completed[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e], and a transcriptome profile for salt resistance has been provided[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. The selection of transgenic plants expressing \u003cem\u003eCdNF-YC\u003c/em\u003e genes has improved drought and salt tolerance[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e], and more gene functions related to salt tolerance have been identified[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Genetic transformation is a pivotal method for investigating gene function and advancing molecular breeding. The success of genetic transformation in monocotyledonous plants hinges on in vitro tissue culture and regeneration, which also represents a significant bottleneck in plant transformation[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. The problem of difficult regeneration of callus tissue seriously restricts the process of molecular breeding of seashore paspalum using genetic transformation and gene editing techniques. To date, there have been no reports on the molecular mechanisms underlying regeneration in seashore paspalum.\u003c/p\u003e \u003cp\u003eGenetic transformation and genome editing technology can drastically reduce plant breeding times and endow breeding lines with inheritable excellent target traits, which will breed new varieties with higher commercial promotion value[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. \u003cem\u003eAgrobacterium-\u003c/em\u003emediated transformation and subsequent whole-plant regeneration from individual cells are optimal methods for generating target traits in transgenic plants. However, plant regeneration and transformation through somatic embryogenesis have significant technological bottlenecks that severely limit the efficiency of obtaining new germplasm[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. The plant embryogenic callus (EC) is an irregular embryogenic cell mass with robust regenerative capabilities that can be used for propagation and genetic transformation[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Callus regeneration is an important process in the genetic transformation system of seashore paspalum. The efficiency of callus proliferation and regeneration directly affects establishing an efficient and stable genetic transformation system. The process of plant regeneration is regulated by intracellular genetic factors and extracellular environment-inducing factors, resulting from an interaction between genotype and environmental conditions. Plant hormones, genotype, and environment are the most important factors involved in the initiation of regeneration. Light plays a decisive role in the dedifferentiation and regeneration of callus tissue[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Callus regeneration is closely related to the types and concentrations of hormones. Kinetin (KT) plays an important role in plant callus regeneration [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Seeds of the seashore paspalum hybrid 'Sea Spray' (Hyb.7 x Q36313) were used to establish a genetic transformation system, and each seed represents a genotype. Partial genotype has a high regeneration ability, the others are scarce, even recalcitrant to regenerate. Genotype dependency hinders transgenic development utilization in seashore paspalum[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. It is crucial to have an insight into the molecular mechanisms and influencing factors of regeneration.\u003c/p\u003e \u003cp\u003eThe differentiation and regeneration of calli are complex processes, regulated by gene expression. In some plants such as Arabidopsis, the molecular mechanisms during plant regeneration have been revealed[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. The WOX11-LBD16 pathway facilitates the acquisition of totipotency in callus cells, establishing a root primordium-like identity within the newly formed callus in Arabidopsis[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. WOX genes which have a role in the regeneration were specifically upregulated in high-regeneration lines of maize[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Overexpression of \u003cem\u003ePtWOX11\u003c/em\u003e promoted the formation of calli and regulated the regeneration of new shoots in poplar[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Overexpression of plant transcription factors such as WUSCHEL[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e], WIND1[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e], and BOOM AP2/ERF[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e] have been shown to enhance regeneration.\u003c/p\u003e \u003cp\u003eWith the rapid development of high-throughput sequencing and mass spectrometry technology, an abundance of data from transcriptomics and metabolomics has been produced, offering valuable insights into the mechanisms of callus regeneration. Transcriptome studies make it possible to efficiently and quickly analyze differentially expressed genes and functionally annotate regulatory pathways[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Integrated transcriptomic and endogenous hormone content analysis insighted uncovering regeneration mechanism in \u003cem\u003eOsmanthus fragrans\u003c/em\u003e calli[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Some potential genes linked to somatic embryogenesis were discovered by examining the transcriptome profile and gene expression regulation alterations of embryogenic callus and redifferentiation in hybrid sweetgum[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. The molecular response to exogenous auxin signaling during in vitro cotton embryonic redifferentiation has been revealed by dynamic transcriptome analysis[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. The auxin and cytokinin signaling pathways have been proven critical in redifferentiation[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Based on functional annotations in maize, a few closely related genes for callus regeneration have been found, and the functions of hormones and light in regeneration have been examined[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. The results of multi-omics joint analysis can be beneficial for enriching the molecular regulatory network during regeneration and provide a new perspective for improving the efficiency of genetic transformation.\u003c/p\u003e \u003cp\u003eIn this study, we conducted a comprehensive analysis of the transcriptome and endogenous hormones to elucidate the roles and molecular mechanisms of light, KT, and genotypes in the regeneration process of seashore paspalum. This provides a foundation for clarifying the regeneration mechanism of seashore paspalum.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eCallus induction and regeneration\u003c/h2\u003e \u003cp\u003eThe callus tissue induced by genotype Ⅰ and genotype Ⅱ has an excellent growth state on induction medium, and the callus tissue presented a yellow and compact granular shape (\u003cb\u003eFigure. 1A, 1B, 1C)\u003c/b\u003e. When the callus tissue was transferred to MG medium containing KT, it almost did not regenerate under dark conditions, and the callus tissue still maintained a yellow and compact granular shape. Callus produced a small number of regenerated buds, but the buds appeared white due to lack of light (\u003cb\u003eFigure. 1D, 1E, 1F)\u003c/b\u003e. Under light conditions, the callus of genotype Ⅰ turned green after 7 days and the shoots regenerated after 4 weeks with 100% regeneration rate (\u003cb\u003eFigure. 1G, 1H,1I)\u003c/b\u003e. In contrast, genotype Ⅱ calli were comparatively soft, granular, dark yellow, merely proliferating, and exhibited nearly no regeneration under light conditions (\u003cb\u003eFigure. 1J, 1K, 1L)\u003c/b\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eSequencing annotation analysis statistics of different transcriptome\u003c/h2\u003e \u003cp\u003eTo analyze the transcriptome and gene expression profiles of different influencing factors (KT, light, and genotype) during the regeneration process, 12 cDNA samples were extracted from the four states of calli (CK, KT-D, KT-L, and KT-L-NR) and sequenced using the Illumina NovaSeq 6000 system. All sample transcriptome data underwent low-quality data filtering, and the basic quality data was subjected to statistical analysis. A total of 12 samples obtained clean readings of 106.2 Gb, with each sample being sequential with more than 57\u0026nbsp;million raw reads and more than 55\u0026nbsp;million clean reads. After removing the adaptor sequences and low-quality reads, the Q20 quality of each sample was stable above 97.4%, the Q30 percentage was over 93.0%, and the GC content was between 52.7 and 54.4%, and the base error rate was low at 0.03%. More than 94.3% of paired-end reads were mapped to the seashore paspalum reference genome, per sample with an average unique mapping reads rate of 89.3%. The rate of reads mapped to the sense strand and antisense strand ranged from 44.0\u0026ndash;44.9% (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eStatistics of the base quality from four libraries\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"12\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSample\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRaw Reads\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eClean Reads\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eClean Base\u003c/p\u003e \u003cp\u003e(G)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eQ20\u003c/p\u003e \u003cp\u003e(%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eQ30\u003c/p\u003e \u003cp\u003e(%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eGC Content\u003c/p\u003e \u003cp\u003e(%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eMapped reads\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eUnique mapped reads\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eMulti mapped reads\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003eReads map to sense\u003c/p\u003e \u003cp\u003estrand\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003eReads map to antisense\u003c/p\u003e \u003cp\u003estrand\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCK-1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e62838690\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e60778320\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e97.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e93.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e53.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e57846778 (95.18%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e54505544 (89.68%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e3341234 (5.50%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e27240261 (44.82%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e27265283 (44.86%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCK-2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e60110900\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e58468030\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e97.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e93.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e52.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e55450905 (94.84%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e52494073 (89.78%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e2956832 (5.06%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e26232039 (44.87%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e26262034 (44.92%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCK-3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e58963316\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e57490556\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e97.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e93.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e53.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e54659223 (95.08%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e51564828 (89.69%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e3094395 (5.38%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e25771856 (44.83%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e25792972 (44.86%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKT-D-1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e58759546\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e57179762\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e97.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e93.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e54.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e54280304 (94.93%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e51361559 (89.82%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e2918745 (5.10%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e25672434 (44.90%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e25689125 (44.93%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKT-D-2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e58984434\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e57249856\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e97.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e93.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e54.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e54494833 (95.19%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e50814011 (88.76%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e3680822 (6.43%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e25389745 (44.35%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e25424266 (44.41%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKT-D-3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e60507436\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e58787680\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e97.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e93.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e53.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e55797903 (94.91%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e52441572 (89.21%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e3356331 (5.71%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e26199692 (44.57%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e26241880 (44.64%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKT-L-1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e59094690\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e56927426\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e97.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e93.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e53.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e53978807 (94.82%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e50750242 (89.15%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e3228565 (5.67%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e25350320 (44.53%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e25399922 (44.62%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKT-L-2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e57880802\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e55926246\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e97.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e93.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e53.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e52886504 (94.56%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e50113586 (89.61%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e2772918 (4.96%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e25021366 (44.74%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e25092220 (44.87%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKT-L-3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e64528494\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e62513252\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e97.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e93.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e54.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e58985934 (94.36%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e56021556 (89.62%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e2964378 (4.74%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e27985322 (44.77%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e28036234 (44.85%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKT-L-NR-1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e64769556\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e63021878\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e97.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e93.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e52.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e59659302 (94.66%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e56048800 (88.94%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e3610502 (5.73%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e28010634 (44.45%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e28038166 (44.49%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKT-L-NR-2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e60130944\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e58593118\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e97.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e93.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e53.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e55458519 (94.65%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e52301388 (89.26%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e3157131 (5.39%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e26132637 (44.60%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e26168751 (44.66%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKT-L-NR-3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e64120544\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e61378058\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e97.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e93.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e53.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e57979807 (94.46%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e54139319 (88.21%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e3840488 (6.26%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e27046786 (44.07%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e27092533 (44.14%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"12\"\u003eRaw Reads: Total number of original reads; Clean Reads: The total number of high-quality data bases after filtering the original reads; Clean Base(G): Total number of high-quality reads; Q20 (%)/Q30 (%): Percentage of bases with a Phred value above Q20/Q30 in clean data; GC content: Percentage of G and C bases out of the total bases in clean data; Mapped reads: the number of reads that can be matched to the reference genome (proportion of matched reads); Unique/ Multi mapped reads: the number of reads that match to a unique/multiple multiple position in the reference genome sequence (proportion of mapped reads); Reads map to sense/antisense strand: the number of reads comparison to the sense/antisense strand of the genome after UMI deduplication, (proportion of mapped reads).\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eDEGs identification and enrichment analyses\u003c/h2\u003e \u003cp\u003eTo reflect the correlation of gene expression in any two samples, we calculated the Pearson correlation coefficients for all gene expression levels between each two samples and reflected these coefficients in the form of a heat map. The average Pearson correlation coefficients between all samples within a group were greater than 0.83, with the highest being 0.99, indicating three repeated samples within the group had good repeatability (\u003cb\u003eFigure. 2A\u003c/b\u003e). The significant differentially expressed genes (DEGs) were selected by setting |log2fold change| \u0026ge; 1 and p value\u0026thinsp;\u0026le;\u0026thinsp;0.05 as criterions. In this study, a total of 15771 significant DEGs were observed in the four comparison groups related to regeneration. Genotypes have a significant impact on gene expression levels, the total number of DEGs was the highest. The group with the largest number of DEGs was the (KT-L-NR vs KT-L) group, with 1350 downregulated genes and 3550 upregulated genes. While under the same KT conditions, the lowest number of significant DEGs (196 downregulated and 338 upregulated) was detected between the KT-L and KT-D groups (\u003cb\u003eFigure. 2B\u003c/b\u003e).\u003c/p\u003e \u003cp\u003eBefore doing the unsupervised PCA (principal component analysis), data was unit variance-scaled. Unsupervised PCA was carried out using the statistics function \u0026lsquo;prcomp\u0026rsquo; in R1, which was useful for utilizing a small number of primary components to analyze the internal structure of several variables. The transcriptome data of callus regeneration were subject to PCA analysis. In the PCA score plot, the first principal component (PC1) and the second principal component (PC2) represented 25.8% and 19.0% of the total variance, respectively and the cumulative contribution rate of PC1\u0026times; PC2 reached 44.8%. The callus statuses CK, KT-D, KT-L, and KT-L-NR could be almost completely separated, indicating that the genes expressed differently; the compact cluster formed by the three biological repeats of each status showed that the materials were sufficiently reproducible and appropriate for further qualitative and quantitative analyses. (\u003cb\u003eFigure. 2C\u003c/b\u003e).\u003c/p\u003e \u003cp\u003eVenn diagram analysis showed 212 DEGs were detected in common among all three comparison groups, and 197, 2588, and 3083 specific DEGs in comparison groups (KT-L vs KT-D, KT-D vs CK, and KT-L-NR vs KT-L), respectively. In the stage of embryonic regeneration, the specific expression genes induced by different genotypes (KT-L-NR vs KT-L) (3083) were much higher than those induced by KT or light conditions during the regeneration process. The number of specific expression genes induced by KT (KT-D vs CK) was 2588, which was higher than the 197 specific expression genes induced by light (KT-L vs KT-D) (\u003cb\u003eFigure. 2D\u003c/b\u003e).\u003c/p\u003e \u003cp\u003eBlue and red on the heat map represent low and high DEG expression levels, respectively. The hierarchical clustering of DEGs in all the biological replicates was classified into the same cluster, which indicated a robust correlation between replicates and the high reliability of our data. The heat map also revealed that some DEGs were specifically accumulated in the KT-L, but some only existed in the KT-L-NR (\u003cb\u003eFigure. 2E\u003c/b\u003e).\u003c/p\u003e \u003cp\u003eThere were 2484 transcription factors associated with 91 gene families among the induced genes. Of these genes, 149 genes are transcription factors of the AP2/ERF-ERF family, followed by BASIC/HELIX\u0026ndash;LOOP\u0026ndash;HELIX (bHLH) transcription factors with 147 members that exhibited changes in expression after induction. Following induction, there were noticeable alterations in the expression of 136 NACs, 133 MYBs, 115 C\u003csub\u003e2\u003c/sub\u003eH\u003csub\u003e2\u003c/sub\u003es, and 113 WRKYs, among other transcription factors (\u003cb\u003eFigure. 2F\u003c/b\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eGO and KEGG enrichment analysis of DEGs in different callus\u003c/h2\u003e \u003cp\u003eTo further elucidate the effects of KT, light, and genotype on the transcription levels of key genes in callus regeneration, we separately investigated GO and KEGG enrichment analyses of the DEGs in the comparison groups (KT-D vs CK, KT-L vs KT-D, and KT-L-NR vs KT-L). All comparison groups were associated with three ontologies in the GO database enrichment analysis: \u0026lsquo;biological process\u0026rsquo;, \u0026lsquo;cellular component\u0026rsquo;, and \u0026lsquo;molecular function\u0026rsquo;. In the enrichment analysis results of three comparison groups, the 50 GO terms with the lowest FDR were selected, and constructed a column chart to visualize the enrichment items. Three comparison groups have different levels of enriched Go entries in three ontologies. The GO analysis revealed that the DEGs were mostly enriched in biological processes. In the cellular component, KT-D vs CK had the lowest enriched GO terms; in the molecular function, KT-L vs KT-D had the lowest enriched GO terms. Within the biological process, the enriched GO terms in both KT-L vs KT-D and KT-L-NR vs KT-L were 'photosynthesis' and 'generation of precursor metabolites and energy' and the different term enrichment for KT-D vs CK included \u0026lsquo;cellular polysaccharide metabolic process\u0026rsquo; and \u0026lsquo;response to oxidative stress\u0026rsquo;. Within the cellular component, the enriched GO terms in both KT-L vs KT-D and KT-L-NR vs KT-L were 'photosynthetic membrane\u0026rsquo; and \u0026lsquo;thylakoid membrane\u0026rsquo; and also the different term enrichment for KT-D vs CK included \u0026lsquo;anchored component of membrane\u0026rsquo; and \u0026lsquo;intrinsic component of plasma membrane\u0026rsquo;. Within the molecular function the enriched GO terms in both KT-D vs CK and KT-L-NR vs KT-L were 'hydrolase activity, hydrolyzing O-glycosyl compounds\u0026rsquo; (\u003cb\u003eFigure. 3A; 3B and 3C\u003c/b\u003e).\u003c/p\u003e \u003cp\u003eTo elucidate the functions of the DEGs, KEGG functional enrichment analysis was performed. We mapped the top 20 paths with the lowest Q-value. The pathway was shown to be more significantly enriched when the Q-value value was smaller; the number of enriched DEGs was indicated by a larger point; and the ratio of enriched DEGs to annotated genes was greater when the Rich factor was larger. Based on the KEGG functional enrichment analysis, the number of DEGs involved in metabolic pathways was the largest in all comparison groups (\u003cb\u003eFigure. 3D; 3E and 3F\u003c/b\u003e). In KT-L vs KT-D, the significantly and specific enriched pathways were involved in photosynthesis -antenna proteins and porphyrin metabolism. Photosynthesis, metabolic pathways, carbon fixation in photosynthetic organisms, porphyrin metabolism, and carbon metabolism pathways play a critical role in the seashore paspalum regeneration \u003cb\u003e(Figure. 3E)\u003c/b\u003e. Hierarchical clustering analysis suggested that the overview of the relative changes of DEGs among the comparison groups (KT-D vs CK, KT-L vs KT-D and KT-L-NR vs KT-L). The heatmap displayed tight clustering, indicating strong repeatability in biological replicates and a close correlation of the DEGs between groups (\u003cb\u003eFigure. 3G; 3H and 3I\u003c/b\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003ePlant hormones analysis based on KEGG enrichment\u003c/h2\u003e \u003cp\u003eTo explore the role of plant hormones in the regeneration process of callus tissue, this study utilized plant hormones analysis platform based on LC-MS/MS to determine hormone levels in four groups of samples. In this study, a total of 73 substances belonging to 8 major categories of plant hormones were quantitatively detected in the 4 samples, including 27 cytokinins (CK), 17 auxins, 11 gibberellin (GA), 9 jasmonite acids (JA), 5 salicylic acids (SA), 2 abscisic acids (ABA), 1 ethylene (ETH) and 1 melatonin (MLT) (\u003cb\u003eFigure. 4A\u003c/b\u003e). To identify the plant hormones that play an important regulatory role in the regeneration process of callus tissue, we analyzed the differential hormones using thresholds for fold change\u0026thinsp;\u0026ge;\u0026thinsp;2 and fold change\u0026thinsp;\u0026le;\u0026thinsp;0.5 to screen differentially changed hormones (DCHs). In KT-D vs CK, KT-L vs KT-D, and KT-L-NR vs KT-L, the upregulated DCHs were 19, 22, and 20, respectively, while the downregulated DCHs were 12, 21, and 18 (\u003cb\u003eFigure. 4B\u003c/b\u003e). KEGG enrichment analysis revealed that DCHs were substantially enriched in the diterpenoid biosynthesis and plant hormone signal transduction pathways across all comparison groups (\u003cb\u003eFigure. 4C; 4D and 4E\u003c/b\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eEndogenous gibberellin content and metabolic pathways analysis\u003c/h2\u003e \u003cp\u003eGA quantification results showed that GA\u003csub\u003e4\u003c/sub\u003e was only detected in CK (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA), and GA\u003csub\u003e53\u003c/sub\u003e was only detected in KT-D (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB). In the treatment groups (KT-L, KT-D, and KT-L-NR) following the addition of KT, no GA\u003csub\u003e4\u003c/sub\u003e was found; nevertheless, the level of GA\u003csub\u003e19\u003c/sub\u003e was significantly higher than that of CK. Concurrently, in the non-regenerable genotype KT-L-NR, the content of GA\u003csub\u003e19\u003c/sub\u003e was significantly lower than in KT-L and KT-D (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eC). In KT-L, GA\u003csub\u003e5\u003c/sub\u003e and GA\u003csub\u003e51\u003c/sub\u003e were significantly higher than those in other groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eD; \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eE), while GA\u003csub\u003e20\u003c/sub\u003e and GA\u003csub\u003e29\u003c/sub\u003e were significantly lower than those in other groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eF; \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eG). GA\u003csub\u003e3\u003c/sub\u003e was only detected in KT-L-NR (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eH). It is evident that the addition of KT greatly enhanced the content of GA\u003csub\u003e19\u003c/sub\u003e while drastically decreasing the content of GA\u003csub\u003e4\u003c/sub\u003e; while the content of GA\u003csub\u003e5\u003c/sub\u003e and GA\u003csub\u003e51\u003c/sub\u003e increased dramatically in KT-L under light conditions. Changes in the contents of these substances may be the main contributors to the regeneration of callus tissue in seashore paspalum. In contrast to KT-L, non-regenerable genotypes showed noticeably higher levels of GA\u003csub\u003e3\u003c/sub\u003e, GA\u003csub\u003e20\u003c/sub\u003e, and GA\u003csub\u003e29\u003c/sub\u003e under the same conditions, which could be a contributing cause to the incapacity of callus regeneration.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThrough joint analysis of endogenous hormone and transcriptome data, DEGs identified in the diterpenoid biosynthesis metabolic pathway included 1 gibberellin 13-oxidase (\u003cem\u003eCYP714B\u003c/em\u003e) gene, 3 gibberellin-44 dioxygenase (\u003cem\u003eGA20ox\u003c/em\u003e) genes, and 7 gibberellin 2beta-dioxygenas (\u003cem\u003eGA2ox\u003c/em\u003e) genes. The \u003cem\u003eCYP714B\u003c/em\u003e gene and \u003cem\u003eGA20ox\u003c/em\u003e genes were significantly upregulated in KT-D vs CK, positively regulating the synthesis of GA\u003csub\u003e53\u003c/sub\u003e and GA\u003csub\u003e19\u003c/sub\u003e. There was one \u003cem\u003eGA2ox\u003c/em\u003e gene significantly downregulated in KT-L vs KT-D and KT-D vs CK, negatively regulating the synthesis of GA\u003csub\u003e51\u003c/sub\u003e and GA\u003csub\u003e29\u003c/sub\u003e. The expression level of \u003cem\u003eGA2ox\u003c/em\u003e (Pavag03G280900. v3.1) was very high, significantly negatively regulating GA\u003csub\u003e51\u003c/sub\u003e. In the plant hormone signal transduction metabolic pathway, DEGs included 9 gibberellin receptor \u003cem\u003eGID1\u003c/em\u003e genes, 15 \u003cem\u003eDELLA\u003c/em\u003e genes, and 16 phytochrome-interacting factor 3 (\u003cem\u003ePIF3\u003c/em\u003e) genes, which were involved in regulating biological processes such as germination in the GA\u003csub\u003e4\u003c/sub\u003e signaling pathway (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eI).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eEndogenous hormone content and signal transduction pathways analysis\u003c/h2\u003e \u003cp\u003eThe ABA content was the lowest in KT-L which significantly lower than that in KT-L-NR (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eA), and no ABA-GE was detected (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eB). The JA content in KT-L was also lower than that in other groups, and significantly lower than KT-L-NR (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eC). The JA-ILE contents in CK and KT-L-NR were significantly higher than that in KT-L (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eD). The low contents of ABA and JA in the regeneration group indicated that they may have a negative impact on the regeneration capacity. Through joint analysis of endogenous hormone and transcriptome data, DEGs identified in ABA signal transduction pathway included 4 protein phosphatase 2C (\u003cem\u003ePP2C\u003c/em\u003e) genes, 2 \u003cem\u003eSNRK2\u003c/em\u003e genes, and 5 ABA-responsive element binding factor (\u003cem\u003eABF\u003c/em\u003e) genes; and in JA signal transduction included 1 jasmonic acid-amino synthetase (\u003cem\u003eJAR1\u003c/em\u003e) gene, 9 jasmonate ZIM domain-containing protein (\u003cem\u003eJAZ\u003c/em\u003e) genes, and 10 (\u003cem\u003eMYC2\u003c/em\u003e) genes (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eM).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe contents of indole-3-acetic acid (IAA) in KT-L and KT-L-NR were significantly higher than that in CK and KT-D, suggesting that light plays a crucial role in stimulating the synthesis of IAA, which was beneficial for the regeneration of callus tissue (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eE). Furthermore, the contents of indole-3-acetyl-L-tryptophan (IAA-Trp), indole-3-acetyl-L-valine methyl ester (IAA-Val-Me), and tryptamine (TRA) were the highest in KT-L, all significantly higher than those in CK (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eF; \u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eG and \u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eH). These findings suggest that IAA and its related compounds like IAA-Trp, IAA-Val-Me, and TRA all contribute to promoting effect on the regeneration of seashore paspalum. Both KT and light factors have important promoting effects on callus regeneration.\u003c/p\u003e \u003cp\u003eBoth KT and kinetin riboside (KR) levels were significantly higher in KT-D, KT-L, and KT-L-NR than in CK (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eI; \u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eJ). Trans-zeatin riboside (tZR) was only detected in KT-L, with N6-isopentenyl adenine (IP) content being the lowest, significantly lower than KT-L-NR (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eK; \u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eL). These results indicate that the addition of exogenous KT can substantially increase the content of endogenous KT and KR, which are essential for the regeneration of seashore paspalum.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eValidation of transcriptomic data using qRT-qPCR\u003c/h2\u003e \u003cp\u003eTo confirm the expression patterns of a subset of DEGs identified by Illumina sequencing, eight genes were randomly selected that related to the diterpenoid biosynthesis metabolic pathway and plant hormone signal transduction for qRT-PCR verification. The RT-PCR results showed the expression levels of these genes obtained by qRT-PCR analysis were consistent with the FPKM value trends obtained by the RNA-seq data, which indicated the reliability and accurately of the gene expression data measured by RNA-seq (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eAs a halophyte with extremely high salt tolerance and ecological adaptability, seashore paspalum has enormous potential for application in saline-alkali land improvement and soil remediation. The molecular mechanism research on the extremely high salt tolerance of seashore paspalum can provide a theoretical basis and genetic resources for the molecular breeding of turfgrass and crops. At present, a genetic transformation system has been established for seashore paspalum. Research on salt tolerance mechanisms and molecular design breeding processes of seashore paspalum has been limited due to issues such as genotype dependence and regeneration difficulties that have arisen during the establishment of CRISPR/Cas9 genome editing systems and the screening of genetically modified materials. This is the first report on callus regeneration mechanisms of seashore paspalum by combined transcriptome and endogenous hormone profiling. This study analyzed the content of endogenous hormones and investigated the effects of light, KT, and genotype on callus regeneration; the molecular mechanisms were explored by combining transcriptome analysis. The findings will advance knowledge of endogenous hormone effects and molecular mechanisms, as well as offer fresh perspectives on the problem of genotype dependence in callus regeneration.\u003c/p\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eGenotype dependency analysis based on hormone differences\u003c/h2\u003e \u003cp\u003eThe universal genotype dependence of tissue culture protocols has impeded the improvement and breeding of crop varieties through genetic transformation or genome editing [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Usually, genetic transformation systems have been established only in a limited number of species and optimized for specific genotypes [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Moreover, most commercially valuable varieties exhibit recalcitrance or only marginal transformability [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. The utilization of gene editing technologies for the precise fine-tuning and introduction of desirable traits in newly released elite commercial varieties has been hindered by the restricted range of receptive genotypes with less genetic background and agronomic values. Genotype dependence remains insurmountable and universal in crops including barley [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e], wheat [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e], sorghum [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e], and cotton [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. To eliminate genotype reliance in plant transformation, several strategies have been tried recently. The genotype-independent transformation has been established in maize by transforming the maize's major transcription factors, \u003cem\u003eBaby Boom\u003c/em\u003e (\u003cem\u003eBbm\u003c/em\u003e) and \u003cem\u003eWuschel2\u003c/em\u003e (\u003cem\u003eWus2\u003c/em\u003e) into immature maize embryos of some previously nontransformable maize inbred lines and high transformation frequencies have been obtained. Some monocots, including (\u003cem\u003eSorghum bicolor\u003c/em\u003e) immature embryos and indica rice (\u003cem\u003eOryza sativa ssp indica\u003c/em\u003e) callus, have improved transformation by expressing maize \u003cem\u003eBbm\u003c/em\u003e and \u003cem\u003eWus2\u003c/em\u003e genes[\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. In sorghum, \u003cem\u003eWus2\u003c/em\u003e-enabled transformation raises the frequency of CRISPR/Cas-targeted genome editing in addition to the transformation efficiency. \u003cem\u003eWus2\u003c/em\u003e-induced direct somatic embryogenesis and regeneration reduces the duration of tissue culture cycles dramatically and avoids genotype-dependent callus development [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Pollen transfected with DNA-coated magnetic nanoparticles was efficiently delivered into maize inbred lines that are resistant to tissue culture-mediated transformation by a genotype-independent pollen transfection technology [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. A shoot apical meristem cell-mediated transformation (SAMT) has been developed, which enables an efficient transformation and CRISPR/Cas9-mediated genome editing system for various recalcitrant cotton genotypes [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eHowever, research on the relationship between genotype dependence and endogenous hormones in plants has not been documented. This study provides new ideas for addressing genotype dependence by analyzing the differences in endogenous hormones and key regulatory genes between regenerative and non-regenerative genotypes. During the regeneration process, genotypes have a significant impact on gene expression levels, the total number of DEGs in the KT-L vs KT-L-NR group was the highest, with 1350 downregulated genes and 3550 upregulated genes; while the specific expression genes were 3083 which were much higher than those induced by KT or light conditions. The hierarchical clustering of DEGs was also clearly different in KT-L vs KT-L-NR.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eThe role of endogenous hormones in callus regeneration\u003c/h2\u003e \u003cp\u003eThe process of callus regeneration is closely related to the types, concentrations, and dynamic balance of endogenous hormones in callus that were also controlled by exogenous hormones[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. The beginning of proliferation centers in explants and the plant architecture are impacted by the amounts of endogenous hormones[\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. Callus tissue can only differentiate into adventitious buds under appropriate external conditions, and the composition and content of endogenous hormones are also different in different states. Previous studies have mainly focused on the effects of external conditions or the supplementation of media with nutrients and phytohormones in culture media on callus induction. Some studies have identified the involvement of endogenous hormones in the morphological reactions of callus tissue, and their concentrations are temporally regulated in response to external culture conditions[\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. The effects of endogenous hormone content and types on callus induction were evaluated in explants such as wheat[\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e], maize[\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e], and \u003cem\u003eMedicago truncatula\u003c/em\u003e Gaertn[\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. However, there have been no reports on the changes and effects of endogenous hormones during the regeneration stage of callus tissue. We used the LC-MS/MS hormone analysis platform to measure and analyze the content and differences of endogenous hormones during the regeneration process of callus tissue in seaside paspalum. A total of 73 substances were detected in 8 categories of plant hormones. In our study, the gibberellins (GA3, 4, 5, 19, 20, 29, 51 and 53), abscisic acid (ABA, ABA-GE), jasmonic (JA, JA-ILE), auxins (IAA, IAA-Trp, IAA-Val-Me and TRA) and cytokinins (CK, KR, tZR and IP) were presented in the process of callus regeneration and influenced by genotype or external conditions.\u003c/p\u003e \u003cp\u003eGAs regulate a multitude of developmental processes throughout the entire life cycle of plants[\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. The researchs related to the effect of GAs on somatic embryogenesis (SE) and callus regeneration mainly comes from studies on adding exogenous GAs to the culture medium; and there are differences in the role of GA on SE[\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. The research on endogenous hormones mainly focuses on the induction stage of callus tissue, but there have been no reports on the role of endogenous GA in callus regeneration. Compared to the non-embryogenic callus of maize, the contents of endogenous GAs (GA\u003csub\u003e1\u003c/sub\u003e, GA\u003csub\u003e3\u003c/sub\u003e, GA\u003csub\u003e20\u003c/sub\u003e) were significantly higher in the embryogenic callus[\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e], which was consistent with the results in \u003cem\u003eMedicago truncatula\u003c/em\u003e Gaertn[\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. Endogenous gibberellins are required for embryo production and embryogenic callus growth in Medicago. All the active gibberellins (GA\u003csub\u003e1\u003c/sub\u003e, GA\u003csub\u003e3\u003c/sub\u003e, GA\u003csub\u003e6\u003c/sub\u003e, and GA\u003csub\u003e4\u003c/sub\u003e, GA\u003csub\u003e7\u003c/sub\u003e) were presented in the SE progress from the leaf explants of non-embryogenic (M9) and embryogenic (M9-10a). The levels of GA\u003csub\u003e3\u003c/sub\u003e and GA\u003csub\u003e6\u003c/sub\u003e were found to elevate in the M9-10a genotype as the induction phase advanced. Among all the bioactive gibberellins detected, only GA\u003csub\u003e3\u003c/sub\u003e appeared to be correlated with the SE initiation[\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. The GA\u003csub\u003e3\u003c/sub\u003e content in Golden Promise varieties of barley (\u003cem\u003eHordeum vulgar\u003c/em\u003e L.) was much higher than that in local varieties, that may indicated a direct correlation between the amount of GA\u003csub\u003e3\u003c/sub\u003e hormone and the percentage of regeneration[\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. However, endogenous GAs need to be downregulated to promote SE in studies on \u003cem\u003eArabidopsis\u003c/em\u003e[\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e] and carrots[\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e].In our study, GA\u003csub\u003e5\u003c/sub\u003e and GA\u003csub\u003e51\u003c/sub\u003e were considerably higher and GA\u003csub\u003e20\u003c/sub\u003e and GA\u003csub\u003e29\u003c/sub\u003e were not detected in regenerable genotypes (KT-L). Non-regenerable genotypes exhibited notably greater levels of GA\u003csub\u003e20\u003c/sub\u003e and GA\u003csub\u003e29\u003c/sub\u003e, and GA\u003csub\u003e3\u003c/sub\u003e only detected in KT-L-NR which may be a factor in the incapacity of callus regeneration.\u003c/p\u003e \u003cp\u003eGenes within the \u003cem\u003eGA2ox\u003c/em\u003e family are pivotal in the GAs metabolic pathway, primarily facilitating the inactivation of GAs[\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. Overexpression of \u003cem\u003eGA2ox\u003c/em\u003e genes can lead to the degradation of bioactive GAs in plants, culminating in a dwarf phenotype. In rice, the overexpression of the genes \u003cem\u003eOsGA2ox1\u003c/em\u003e, \u003cem\u003eOsGA2ox6\u003c/em\u003e, and \u003cem\u003eOsGA2ox9\u003c/em\u003e results in diminished plant stature. In wheat, the ectopic expression of the soybean \u003cem\u003ePcGA2ox1\u003c/em\u003e gene significantly diminishes GA levels, thereby reducing plant height[\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. GA2ox was stimulated to inactivate certain bioactive GAs to maintain appropriate ABA to GA ratios, thereby facilitating the SE response in \u003cem\u003eMedicago\u003c/em\u003e[\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. Similarly, \u003cem\u003eGA2ox\u003c/em\u003e (\u003cem\u003ePavag03G280900. v3.1\u003c/em\u003e) significantly negatively regulated GA\u003csub\u003e51\u003c/sub\u003e, which expressed very high. Therefore, we speculated that \u003cem\u003eGA2ox\u003c/em\u003e may be a key gene involved in regulating callus regeneration. Endogenous hormones in plants form a complex signaling network that affects cell growth and development by regulating key genes involved in cell proliferation[\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. Many genes have been identified from plant hormone signaling pathways, including candidate genes that regulate seashore paspalum callus regeneration such as \u003cem\u003ePvMYC2\u003c/em\u003e in JA plant hormone signal transduction metabolism pathways that may be involved in gene network regulation during callus regeneration. \u003cem\u003eMYC\u003c/em\u003e transcription factors serve as regulators of plant growth and development, acting either as activators or repressors of JA-related gene expression. The repression of \u003cem\u003eMYC\u003c/em\u003e could plausibly lead to diminished JA levels in \u003cem\u003ePinellia ternata\u003c/em\u003e[\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]. Our findings align with the conclusions drawn from the aforementioned studies. These results will provide molecular strategies for overcoming the genotype dependence problem in seashore paspalum regeneration difficulties.\u003c/p\u003e \u003cp\u003eABA played an important role in the induction of callus tissue in some plant species[\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]. In carrot tissue culture systems, high endogenous ABA content may play an important role in embryonic development ability[\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e], and the endogenous ABA level in embryogenic carrot cells was greater than that in non-embryogenic cells[\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e]. But the amount of endogenous ABA and percentage of regeneration were inversely related in barley. High regeneration rate barley varieties (Golden Promise cultivar) have significantly lower ABA content than low regeneration rate varieties (Iranian cultivars)[\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. Compared with non-embryogenic (M9), the callus quality of embryogenic (M9-10a) was significantly higher, which may be related to the lower ABA content in this callus tissue of Medicago [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. Our results were consistent with the above finding in barley and medicago. The ABA content in the regenerative genotype (KT-L) was significantly lower than that in the non-regenerative genotype (KT-L-NR); and lower than that in the differentiation stage. It can be seen that low ABA content was one of the key factors for callus regeneration in seashore paspalum. ABA production from ABA-GE that can regulate the local ABA concentration, mediated by β-glucosidase present in vacuoles[\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e]. ABA-GE detected in initial explants of Medicago were higher in non-embryogenic (M9) than in the embryogenic (M9-10a)[\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. Unlike this, we did not detect ABA-GE in the regenerative genotype (KT-L).\u003c/p\u003e \u003cp\u003eJA facilitates the activation and regeneration of stem cells in the growth and developmental processes of plant tissues[\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e]. However, some researches have reported inconsistent conclusions. JA has an inhibitory effect on the formation of callus tissue[\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e], combating plant organ differentiation by inhibiting cell proliferation and expansion[\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e]. Low concentrations of endogenous JA have been shown to stimulate callus proliferation and development in both garlic[\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e] and \u003cem\u003ePinellia ternata\u003c/em\u003e[\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e], a finding that is consistent with our studies on callus regeneration of seashore paspalum. Meanwhile, JA-ILE was also the lowest in regenerated callus tissue.\u003c/p\u003e \u003cp\u003ePrevious research has established that IAA is crucial for callus differentiation in tissue culture systems[\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e, \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e]. Endogenous IAA levels were higher in embryogenic cells compared to non-embryogenic cells in carrot tissue[\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e]. Higher endogenous levels of IAA within explants are essential for the initiation and proliferation of garlic callus[\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. Tryptophan (TRP) represents a rate-limiting factor in the auxin biosynthesis and its derivatives, with its catabolism product, tryptamine (TRA), potentially exerting a positive influence on callus formation in \u003cem\u003ePinellia ternata\u003c/em\u003e[\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]. Consistent with the aforementioned findings, IAA and related substances (IAA-Trp, IAA-Val-Me, and TRA) were detected at the highest concentrations in the regeneration genotype (KT-L), significantly higher than that in the control (CK).\u003c/p\u003e \u003cp\u003eNatural CKs, a class of adenine derivatives, are categorized into two distinct states: free-state CKs and bound-state CKs. Both the type and concentration of CKs in culture medium significantly influence callus proliferation and plant regeneration[\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e]. when CKs were introduced into the regeneration medium, not only initiate callogenesis and promote de novo shoot formation but also exert impacts on the endogenous CKs balance[\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e]. In hydroponic cuttings of \u003cem\u003ePinellia ternata\u003c/em\u003e, endogenous CKs serve as the central hormone regulating the formation of calli[\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]. There were few reports on the relationship between endogenous CK content and callus regeneration. In our study, the supplementation of exogenous KT to the culture medium resulted in a significant increase in the levels of endogenous KT and KR within callus tissue. Additionally, tZR was exclusively detected in the regenerated callus tissue (KT-L). These observations suggest that the modulation of hormone levels, particularly cytokinins, can significantly influence callus tissue regeneration, thereby offering a potential strategy to enhance regeneration efficiency.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusions","content":"\u003cp\u003eSeashore paspalum, a halophyte with remarkable salt tolerance and ecological adaptability. However, callus tissue regeneration challenges and genotype effects have significantly hindered molecular breeding efforts through genetic transformation and gene editing. Our study presents the first integrated analysis of the transcriptome and endogenous hormone profiles in seashore paspalum to delineate the callus regeneration mechanisms. By examining the interplay of light, KT, and genotypes, our research has uncovered key molecular and hormonal factors that govern the regeneration process. This work provides critical insights into genotype dependence in callus regeneration and lays a foundational framework for developing strategies to improve regeneration efficiency.\u003c/p\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003cdiv id=\"Sec16\" class=\"Section3\"\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e\u003c/p\u003e \u003c/div\u003e "},{"header":"Methods","content":"\u003ch2\u003ePlant growth and treatments\u003c/h2\u003e\u003cp\u003eEmbryogenic callus inducted from seeds of the seashore paspalum (\u003cem\u003ePaspalum vaginatum\u003c/em\u003e O. Swartz) cultivar ‘Sea Spray’ in the dark at 25°С. All materials has been deposited in a publicly Grass Science Laboratory oof Qingdao Agricultural University. Embryogenic calli derived from the embryo of genotype Ⅰ and genotype Ⅱ were cultured in one dish as an individual clone on an induction medium (MS2.5) for proliferation and subcultured every 4 weeks[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. After subculturing for 5 months, high-quality compact embryogenic calli of genotype Ⅰ and genotype Ⅱ were transferred to a regeneration medium (MG) containing MS basal medium supplemented with 0.2 mg L\u003csup\u003e− 1\u003c/sup\u003e kinetin for regeneration under 16 h photoperiod (200 µmol m\u003csup\u003e− 2\u003c/sup\u003e s\u003csup\u003e− 1\u003c/sup\u003e)[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eCallus tissues with the same status were cultured under different conditions for 4 weeks; Four statuses of callus development were defined: \u003cb\u003eCK\u003c/b\u003e, calli under dark on MS2.5; \u003cb\u003eKT-D\u003c/b\u003e, calli under dark on MG; \u003cb\u003eKT-L\u003c/b\u003e, calli of genotype Ⅰ under light on MG; \u003cb\u003eKT-L-NR\u003c/b\u003e, calli of genotype Ⅱ under light on MG. Collect samples of callus tissues from four distinct states and promptly observe and photograph them under a microscope. Callus tissue was sampled using liquid nitrogen and stored at − 80°C for measuring separately RNA isolation and endogenous hormone determination. All experimental treatments were set with three replicates.\u003c/p\u003e\u003ch2\u003eTissue Paraffin Section Preparation\u003c/h2\u003e\u003cp\u003eTo compare the cytological characteristics of callus, four statuses of callus (CK, KT-D, KT-L and KT-L-NR) were promptly fixed in FAA (75% ethanol: acetic acid: formaldehyde, 90:5:5, v/v/v). Fixation at room temperature for longer than 24 hours, and twice aspirating for 15 minutes each time. Subsequently, fixed samples were dehydrated with a graded series of ethanol (75%, 85%, 90%, 95%, and 100%—each step for 25 min twice, v/v)). Next, the samples were immersed in the same volume of tert-butanol and melted paraffin. Following that, the samples were cooled in the carton while embedded in pure paraffin. Sections (5 µm in thickness) were cut using a microtome (Leica Instrument RM2016, Shanghai, China) and stained with toluidine blue dye (Servicebio G1032, Wuhan, China) for 5 min. Cell proliferation was observed using a microscope (Nikon Eclipse E100, Nikon DS-U3, Nikon Instruments (Shanghai) Co., Ltd., Shanghai, China) in bright field mode.\u003c/p\u003e\u003ch2\u003eRNA Extraction and Illumina Sequencing\u003c/h2\u003e\u003cp\u003e Total RNA was extracted from calli of four statuses using the Plant Total RNA Extraction Kit (TIANGEN Biotech, Beijing, China) according to the manufacturer's instructions. cDNA was synthesized using the PrimeScript RT reagent kit with a gDNA eraser (Takara, Dalian, China). The quality and integrity of the RNA samples were assessed using the Agilent 2100 Bioanalyzer (Agilent Technologies, CA, USA), NanoDrop2000 (Thermo Fisher Scientific, MA, USA), and agarose gel electrophoresis. Following the manufacturer's instructions, sequencing libraries were generated using NEBNext Ultra™ RNA Library Prep Kit for Illumina (NEB, Ipswich, MA, USA). Four libraries (CK, KT-D, KT-L, and KT-L-NR) were constructed for the RNA-seq analysis using Illumina NovaSeq 6000 system (Illumina, San Diego, CA, USA) by Biomarker Technologies (Beijing, China). For the construction of a single cDNA library, it is required that the total RNA per sample ≥ 1 µg, OD\u003csub\u003e260/280\u003c/sub\u003e ≥1.8, and RIN value ≥ 6.5. The RNA-seq analysis was performed after the sample quality validation.\u003c/p\u003e\u003ch2\u003eSequencing data analysis\u003c/h2\u003e\u003cp\u003eTo obtain clean data, low-quality reads and reads containing adapters were discarded. Before data analysis, stringent quality control was applied to ensure that these reads possessed sufficient quality for the accuracy of subsequent analysis. Using the DESeq2 program (v1.6.3, open source, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.bioconductor.org/\u003c/span\u003e\u003cspan address=\"http://www.bioconductor.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), differential expression analysis across samples was conducted to obtain differentially expressed genes (DEGs). The parameters were FDR ≤ 0.05 and |log2FC| (FC, fold change) ≥ 1. The seashore paspalum reference genome (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://phytozome-next.jgi.doe.gov/info/Pvaginatum_v3_1\u003c/span\u003e\u003cspan address=\"https://phytozome-next.jgi.doe.gov/info/Pvaginatum_v3_1\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) was used as the reference genome. Three replicates of standardized sequencing data with repeatability were applied for analysis. Gene function was annotated using commonly utilized databases. GO-Term Finder (v0.86, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://search.cpan.org/dist/GO-TermFinder/\u003c/span\u003e\u003cspan address=\"http://search.cpan.org/dist/GO-TermFinder/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) provided descriptions for the GO terms of molecular function, biological process, and cellular component. GO terms with a p-value \u0026lt; 0.05 were considered significant. The Kyoto Encyclopedia of Genes and Genomes (KEGG) databases (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://en.wikipedia.org/wiki/KEGG\u003c/span\u003e\u003cspan address=\"http://en.wikipedia.org/wiki/KEGG\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) were used to determine which pathways were enriched. Significant metabolic pathways and functional categories were identified within differentially expressed genes, with FDR ≤ 0.05.\u003c/p\u003e\u003ch2\u003eQuantitative Real-Time PCR analysis\u003c/h2\u003e\u003cp\u003eQuantitative Real-Time PCR (RT-qPCR) was used to validate six genes that may have roles in callus regeneration in four stages that matched transcriptome sequencing. RT-qPCR was performed using the ACTIN gene as a reference. The forward and reverse primers listed in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e were designed using Primer 5.0. The amplification program was as follows: 10 min at 95°C, and then 10 s at 95°C, 10 s at 60°C, and 20 s at 72°C for 40 cycles. To ensure accurate and consistent results, three technical duplicates were carried out for both the test and reference genes in every sample. Relative transcript levels for each gene were calculated using the 2\u003csup\u003e−ΔΔCt\u003c/sup\u003e method. Duncan’s multiple range test and variance (ANOVA) analysis were conducted to determine the significant difference (p-values \u0026lt; 0.05) using SPSS 22.0 software (SPSS Inc., Chicago, IL, USA). Results were shown as mean ± standard error of biological replications.\u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePrimers used for qRT-PCR\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGene name\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePrimer\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSequence (5′–3′)\u003c/p\u003e \u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003ePv-Actin\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eForward\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCTTCTCTCAGCACTTTCCAACA\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(\u003cem\u003ePavag03G414200.1\u003c/em\u003e)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReverse\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAAACATAACCTGCAATCTCTCC\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003ePvGA2ox\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eForward\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGCAGATCATCTCCGTGCTCA\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(\u003cem\u003ePavagK145700.v3.1\u003c/em\u003e)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReverse\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCAGTACACCTGAGCCACCTG\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003ePvGID1\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eForward\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGTGATGTCCGTGGACTACCG\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(\u003cem\u003ePavag01G411900.v3.1\u003c/em\u003e)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReverse\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGTCTCCGAGATGCACACCAG\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003ePvDELLA\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eForward\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eATCCTGGAGTCGTTCCTCGA\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(\u003cem\u003ePavag02G332900.v3.1\u003c/em\u003e)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReverse\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTCCTCCAGCGAGTCCATGTA\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003ePvKAO\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eForward\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eACATGATGGACCGGCTGATC\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(\u003cem\u003ePavag10G007100.v3.1\u003c/em\u003e)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReverse\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGACGGAGATCTCGAGCTTGG\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003ePvCYP714B\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eForward\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTGAGAGCACAGCAGTCACAG\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(\u003cem\u003ePavag01G365100.v3.1\u003c/em\u003e)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReverse\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGCTCTGGCTCCACAATGAGT\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003ePvTF\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eForward\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCACCATGTCGCCGATGACTA\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(\u003cem\u003ePavag03G251100.v3.1\u003c/em\u003e)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReverse\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAAGTACTCGTCGGTTGCCTG\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003ePvSNRK2\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eForward\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eACAAGTACGAGCCAGTTCGG\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(\u003cem\u003ePavag09G156200.v3.1\u003c/em\u003e)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReverse\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGGGTAAGCTCCCACAAGCAT\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003c/div\u003e\u003ch2\u003eEndogenous hormone level identification\u003c/h2\u003e\u003cp\u003eHPLC grade acetonitrile (ACN) and methanol (MeOH) were acquired from Merck (Darmstadt, Germany). All experiments were conducted using MilliQ water (Millipore, Bradford, USA). All of the standards were purchased from isoReag (Shanghai, China) and Olchemim Ltd. (Olomouc, Czech Republic). The stock solutions of standards were prepared at the concentration of 1 mg/mL in MeOH and stored at -20°C. Before analysis, the stock solutions were diluted with MeOH to create working solutions.\u003c/p\u003e\u003cp\u003eSamples of callus tissues from four distinct states (CK, KT-D, KT-L, and KT-L-NR) were ground into powder (50 Hz, 60 s) in liquid nitrogen and then stored at -80°C. 50 mg of the material was weighed and then dissolved in 1 mL of methanol/water/formic acid (15:4:1, V/V/V). To serve as internal standards (IS) for the quantitation, 10 µL of an internal standard mixed solution (100 ng/mL) was added to the extract. The supernatant was transferred to plastic microtubules and evaporation to dryness, it was dissolved in 100 µ in 80% methanol (V/V); and filtered through a 0.22 µm membrane filter for LC-MS/MS analysis.\u003c/p\u003e\u003cp\u003eA UPLC-ESI-MS/MS system (UPLC, ExionLC™ AD, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://sciex.com.cn/\u003c/span\u003e\u003cspan address=\"https://sciex.com.cn/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e; MS, QTRAP® 6500+, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://sciex.com.cn/\u003c/span\u003e\u003cspan address=\"https://sciex.com.cn/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) was utilized to analyze the sample extracts. The following were the analytical conditions: LC: column, Waters ACQUITY UPLC HSS T3 C18 (100 mm×2.1 mm i.d., 1.8 µm); solvent system, water with 0.04% acetic acid (A), acetonitrile with 0.04% acetic acid (B); gradient program, started at 5% B (0–1 min), increased to 95% B (1–8 min), 95% B (8–9 min), and finally ramping back to 5% B (9.1–12 min); flow rate, 0.35 mL/min; temperature, 40°C; injection volume: 2 µL.\u003c/p\u003e\u003cp\u003eLinear ion trap (LIT) and triple quadrupole (QQQ) scans were acquired on a triple quadrupole-linear ion trap mass spectrometer (QTRAP), QTRAP® 6500 + LC-MS/MS System, equipped with an ESI Turbo Ion-Spray interface, operating in both positive and negative ion mode and controlled by Analyst 1.6.3 software (Sciex).\u003c/p\u003e\u003cp\u003eData from three replicates were analyzed by using one-way ANOVA. All statistical analysis was performed by Statistical Package for the Social Sciences (SPSS 17.0). Results are shown as mean ± standard error of biological replications. The means were separated using Duncan’s multiple range test (p \u0026lt; 0.05).\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eKT: Kinetin; DEGs: differentially expressed genes; FDR: false discovery rate; GO: Gene Ontology; KEGG: Kyoto Encyclopedia of Genes and Genomes; GA: gibberellin; CK: cytokinin; JA: jasmonic acid; SA: salicylic acid; ABA: abscisic acid, ETH: ethylene; MLT: melatonin; DCHs: differentially changed hormones; \u003cem\u003eCYP714B\u003c/em\u003e: gibberellin 13-oxidase, \u003cem\u003eGA20ox\u003c/em\u003e: gibberellin-44 dioxygenase; \u003cem\u003eGA2ox\u003c/em\u003e: gibberellin 2beta-dioxygenas; \u003cem\u003ePIF3\u003c/em\u003e: phytochrome-interacting factor 3; PP2C: protein phosphatase 2C; ABF: ABA responsive element binding factor; JAR1: jasmonic acid-amino synthetase; JAZ: jasmonate ZIM domain-containing protein; IAA: indole-3-acetic acid; IAA-Trp: indole-3-acetyl-L-tryptophan, IAA-Val-Me: indole-3-acetyl-L-valine methyl ester, TRA: tryptamine; KR: kinetin riboside; IP: N6-isopentenyladenine; tZR: trans-zeatin riboside; SE: somatic embryogenesis;\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe use of plant parts in the present study complies with international, national, and/or institutional guidelines. Our research team is affiliated with the Key Laboratory of the Yellow River Delta Grassland Resources and Ecology of the Chinese Forestry and Grassland Administration. We have obtained the permission to collect Seashore Paspalum.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated and/or analysed during the current study are available in the NCBI repository,\u0026nbsp;[https://www.ncbi.nlm.nih.gov/bioproject/PRJNA1128878].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the National Natural Science Foundation of China (32101423), the Foundation Project of Shandong Natural Science Foundation (ZR2021MC066), and Fundamental Research Funds for the Universities (6631120002). the Foundation Project of Shandong Natural Science Foundation\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eX. W. and K. J. conducted experiments; X.H., X. W., Z. Y., Q. S., W. W., and G. Y. gave advice and assistance in this research; Z.W. revised the manuscript; X. W. designed experiments and wrote the manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003ePessarakli M. Screening various cultivars of seashore paspalum (\u003cem\u003ePaspalum vagenitum Swartz\u003c/em\u003e) for salt tolerance for potential use as a cover plant in combatting desertification. \u003cem\u003eInt J Water Res Arid Environ\u003c/em\u003e. 2018;7(1): 36-43.\u003c/li\u003e\n\u003cli\u003eSpiekerman JJ, Devos KM. The halophyte seashore paspalum uses adaxial leaf papillae for sodium sequestration. \u003cem\u003ePlant Physiol\u003c/em\u003e. 2020;184(4):2107\u0026ndash;2119.\u003c/li\u003e\n\u003cli\u003eKarimi IYM, Kurup SS, Salem MAMA, Cheruth AJ, Purayil FT, Subramaniam S, Pessarakli M. 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In vitro growth and regeneration of brassica oleracea var. gongylodes: a decade of research. \u003cem\u003eHorticulturae\u003c/em\u003e. 2023;9(6):674.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"seashore paspalum, regeneration, light, genotype, endogenous hormones","lastPublishedDoi":"10.21203/rs.3.rs-4615496/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4615496/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground: \u003c/strong\u003eSeashore paspalum (\u003cem\u003ePaspalum vaginatum\u003c/em\u003e O. Swartz) is a halophyte known for its exceptional salt tolerance and ecological adaptability. It is an excellent candidate for studying salt tolerance mechanisms and screening salt tolerance genes. However, the difficulties with callus tissue regeneration and the influence of genotype during cultivation provide a significant obstacle to the process of molecular breeding employing genetic transformation and gene editing techniques in seashore paspalum.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo elucidate the molecular mechanism of callus regeneration in seashore paspalum, this study analyzed the content of endogenous hormones and investigated the effects of light, KT, and genotype on callus regeneration; Through transcriptome analysis between different treatments, the molecular mechanisms were explored. Under light conditions, almost all callus tissues of genotype I could produce regenerated green buds, but genotype II could not regenerate. A total of 106.2 Gb clean readings were obtained from 12 cDNA sample libraries in four regeneration states (CK, KT-D, KT-L, and KT-L-NR). The Pearson correlation coefficients, principal component analysis, and DEG hierarchical clustering heatmap analysis results indicated good intra-group repeatability and reliable data. The specific expression genes induced by different genotypes (KT-L-NR vs KT-L) (3083) were significantly higher than those in other groups by Venn plot analysis. A total of 73 endogenous hormone substances were quantitatively detected in all samples. KEGG enrichment analysis showed that all comparison groups significantly enriched differentially changed hormones (DCHs) in diterpenoid biosynthesis and plant hormone signal transduction pathways. In KT-L, GA\u003csub\u003e5\u003c/sub\u003e and GA\u003csub\u003e51\u003c/sub\u003e were significantly higher than those in other groups, while GA\u003csub\u003e20\u003c/sub\u003e and GA\u003csub\u003e29\u003c/sub\u003e were significantly lower. KT-L-NR showed noticeably higher levels of GA\u003csub\u003e3\u003c/sub\u003e, GA\u003csub\u003e20\u003c/sub\u003e, and GA\u003csub\u003e29\u003c/sub\u003e, which could be a contributing cause to the incapacity of callus regeneration. The expression level of \u003cem\u003eGA2ox\u003c/em\u003e (Pavag03G280900. v3.1) was very high, significantly negatively regulating GA\u003csub\u003e51\u003c/sub\u003e. In KT-L, the content of ABA and JA were the lowest and significantly lower than that in KT-L-NR. The content of indole-3-acetic acid (IAA) in KT-L and KT-L-NR were significantly higher than that in CK and KT-D, indicating that light played an important role in synthesizing of IAA, which was beneficial for the regeneration of callus tissue.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis is the first report on callus regeneration mechanisms of seashore paspalum by combined transcriptome and endogenous hormone profiling. The results will improve the understanding of molecular mechanisms and the effects of endogenous hormones, and provide new insights to address the issue of genotype dependence in callus regeneration.\u003c/p\u003e","manuscriptTitle":"Integrated transcriptomic and endogenous hormones analyses revealed the molecular mechanism of light and auxin for the regeneration of callus tissue in seashore paspalum","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-07-29 13:13:13","doi":"10.21203/rs.3.rs-4615496/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":"894f4d0b-4c99-4402-9ed1-627945a1d33d","owner":[],"postedDate":"July 29th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-02-06T22:53:56+00:00","versionOfRecord":[],"versionCreatedAt":"2024-07-29 13:13:13","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4615496","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4615496","identity":"rs-4615496","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}