Molecular and Phytochemical Characteristics of Flower Color and Scent Compounds in Dog Rose (Rosa canina L.).

This study delves into the chemical and genetic determinants of petal color and fragrance in Rosa canina L., a wild rose species prized for its pharmacological and cosmetic uses. Comparative analysis of white and dark pink R. canina flowers revealed that the former harbors significantly higher levels of total phenolics (TPC) and flavonoids (TFC), while the latter is distinguished by elevated total anthocyanins (TAC). Essential oils in the petals were predominantly composed of aliphatic hydrocarbons, with phenolic content chiefly constituted by flavonols and anthocyanins. Notably, gene expression analysis showed an upregulation in most genes associated with petal color and scent biosynthesis in white buds compared to dark pink open flowers. However, anthocyanin synthase (ANS) and its regulatory gene RhMYB1 exhibited comparable expression levels across both flower hues. LC-MS profiling identified Rutin, kaempferol, quercetin, and their derivatives as key flavonoid constituents, alongside cyanidin and delphinidin as the primary anthocyanin compounds. The findings suggest a potential feedback inhibition of anthocyanin biosynthesis in white flowers. These insights pave the way for the targeted enhancement of R. canina floral traits through metabolic and genetic engineering strategies.

Characterization of key genes in anthocyanin and flavonoid biosynthesis during floral development in Rosa canina L.

This study investigates the transition of Rosa canina L. petals from pink to white, driven by genetic and biochemical factors. It characterizes the expression of ten key genes involved in anthocyanin and flavonoid biosynthesis across five developmental stages, correlating gene expression with flavonoid and anthocyanin concentrations and colorimetric changes. Initially, the petals exhibit a rich flavonoid profile, dominated by Rutin and Kaempferol derivatives. The peak anthocyanin concentration, corresponding to the deepest color saturation, occurs in the subsequent stage. Advanced chromatographic analyses identify key flavonoids persisting into the final white petal stage. Notably, the ANS gene shows a dramatic 137.82-fold increase in expression at the final stage, indicating its crucial role in petal color maturation despite the absence of visible pigmentation. The study provides a comprehensive characterization of the genetic and biochemical mechanisms underlying petal pigmentation, suggesting that reduced anthocyanin synthesis and increased flavonol concentration led to white petals. It also highlights the roles of other genes such as PAL, CCD1, FLS, CHI, CHS, UFGT, F3H, DFR, and RhMYB1, indicating that post-translational modifications and other regulatory mechanisms may influence anthocyanin stability and degradation.

Normalized Workflow to Optimize Hybrid De Novo Transcriptome Assembly for Non-Model Species: A Case Study in Lilium ledebourii (Baker) Boiss.

A high-quality transcriptome is required to advance numerous bioinformatics workflows. Nevertheless, the effectuality of tools for de novo assembly and real precision assembled transcriptomes looks somewhat unexplored, particularly for non-model organisms with complicated (very long, heterozygous, polyploid) genomes. To disclose the performance of various transcriptome assembly programs, this study built 11 single assemblies and analyzed their performance on some significant reference-free and reference-based criteria. As well as to reconfirm the outputs of benchmarks, 55 BLAST were performed and compared using 11 constructed transcriptomes. Concisely, normalized benchmarking demonstrated that Velvet-Oases suffer from the worst results, while the EvidentialGene strategy can provide the most comprehensive and accurate transcriptome of Lilium ledebourii (Baker) Boiss. The BLAST results also confirmed the superiority of EvidentialGene, so it could capture even up to 59% more (than Velvet-Oases) unique gene hits. To promote assembly optimization, with the help of normalized benchmarking, PCA and AHC, it is emphasized that each metric can only provide part of the transcriptome status, and one should never settle for just a few evaluation criteria. This study supplies a framework for benchmarking and optimizing the efficiency of assembly approaches to analyze RNA-Seq data and reveals that selecting an inefficient assembly strategy might result in less identification of unique gene hits.

Complete chloroplast genome of Lilium ledebourii (Baker) Boiss and its comparative analysis: lights into selective pressure and adaptive evolution.

Lilium ledebourii (Baker) Boiss is a rare species, which exhibits valuable traits. However, before its genetic diversity and evolutionary were uncovered, its wild resources were jeopardized. Moreover, some ambiguities in phylogenetic relationships of this genus remain unresolved. Therefore, obtaining the whole chloroplast sequences of L. ledebourii and its comparative analysis along with other Lilium species is crucial and pivotal to understanding the evolution of this genus as well as the genetic populations. A multi-scale genome-level analysis, especially selection pressure, was conducted. Detailed third­generation sequencing and analysis revealed a whole chloroplast genome of 151,884 bp, with an ordinary quadripartite and protected structure comprising 37.0% GC. Overall, 113 different genes were recognized in the chloroplast genome, consisting of 30 distinct tRNA genes, four distinct ribosomal RNAs genes, and 79 unique protein-encoding genes. Here, 3234 SSRs and 2053 complex repeats were identified, and a comprehensive analysis was performed for IR expansion and contraction, and codon usage bias. Moreover, genome-wide sliding window analysis revealed the variability of rpl32-trnL-ccsA, petD-rpoA, ycf1, psbI-trnS-trnG, rps15-ycf1, trnR, trnT-trnL, and trnP-psaJ-rpl33 were higher among the 48 Lilium cp genomes, displaying higher variability of nucleotide in SC regions. Following 1128 pairwise comparisons, ndhB, psbJ, psbZ, and ycf2 exhibit zero synonymous substitution, revealing divergence or genetic restriction. Furthermore, out of 78 protein-coding genes, we found that accD and rpl36 under positive selection: however, at the entire-chloroplast protein scale, the Lilium species have gone through a purifying selection. Also, a new phylogenetic tree for Lilium was rebuilt, and we believe that the Lilium classification is clearer than before. The genetic resources provided here will aid future studies in species identification, population genetics, and Lilium conservation.

Computational screening of miRNAs and their targets in saffron (Crocus sativus L.) by transcriptome mining.

MAIN CONCLUSION: A robust workflow for the identification of miRNAs and their targets in saffron was developed. MicroRNA-mediated gene regulation in saffron is potentially involved in several biological processes, including the biosynthesis of highly valuable apocarotenoids. Saffron (Crocus sativus L.) is the most expensive spice in the world and a major source of apocarotenoids. Even though miRNAs (20-24 nt non-coding small RNAs) are important regulators of gene expression at transcriptional and post-transcriptional levels, their role in saffron has not been thoroughly investigated. As a result, a workflow for computational identification of miRNAs and their targets can be useful to uncover the regulatory networks underlying biological processes in this valuable plant. The efficiency of several assembly tools such as Trans-ABySS, Trinity, Bridger, rnaSPAdes, and EvidentialGene was evaluated based on both reference-based and reference-free metrics using transcriptome data. A reliable workflow for computational identification of miRNAs and their targets in saffron was described. The EvidentialGene was found to be the most efficient de novo transcriptome assembler for saffron as a complex triploid model, followed by the Trinity. In total, 66 miRNAs from 19 different families that target 2880 genes, including several transcription factors involved in the flowering transition, were identified. Three of the identified targets were involved in the terpenoids backbone biosynthesis. CsCCD and CsUGT genes involved in the apocarotenoids biosynthetic pathway were targeted by csa-miR156g and csa-miR156b-3p, revealing a unique post-transcriptional regulation dynamic in saffron. The identified miRNAs and their targets add to our understanding of the many biological roles of miRNAs in saffron and shed new light on the control of the apocarotenoid biosynthetic pathway in this valuable plant.

Introducing a hybrid artificial intelligence method for high-throughput modeling and optimizing plant tissue culture processes: the establishment of a new embryogenesis medium for chrysanthemum, as a case study.

Data-driven models in a combination of optimization algorithms could be beneficial methods for predicting and optimizing in vitro culture processes. This study was aimed at modeling and optimizing a new embryogenesis medium for chrysanthemum. Three individual data-driven models, including multi-layer perceptron (MLP), adaptive neuro-fuzzy inference system (ANFIS), and support vector regression (SVR), were developed for callogenesis rate (CR), embryogenesis rate (ER), and somatic embryo number (SEN). Consequently, the best obtained results were used in the fusion process by a bagging method. For medium reformulation, effects of eight ionic macronutrients on CR, ER, and SEN and effects of four vitamins on SEN were evaluated using data fusion (DF)-non-dominated sorting genetic algorithm-II (NSGA-II) and DF-genetic algorithm (GA), respectively. Results showed that DF models with the highest R2 had superb performance in comparison with all other individual models. According to DF-NSGAII, the highest ER and SEN can be obtained from the medium containing 14.27 mM NH4+, 38.92 mM NO3-, 22.79 mM K+, 5.08 mM Cl-, 3.34 mM Ca2+, 1.67 mM Mg2+, 2.17 mM SO42-, and 1.44 mM H2PO4-. Based on the DF-GA model, the maximum SEN can be obtained from a medium containing 0.61 µM thiamine, 5.93 µM nicotinic acid, 0.25 µM biotin, and 0.26 µM riboflavin. The efficiency of the established-optimized medium was experimentally compared to Murashige and Skoog medium (MS) for embryogenesis of five chrysanthemum cultivars, and results indicated the efficiency of optimized medium over MS medium.Key points• MLP, SVR, and ANFIS were fused by a bagging method to develop a data fusion model.• NSGA-II and GA were linked to the data fusion model for establishing and optimizing a new embryogenesis medium.• The new culture medium (HNT) had better efficiency than MS medium.

Forecasting and optimizing Agrobacterium-mediated genetic transformation via ensemble model- fruit fly optimization algorithm: A data mining approach using chrysanthemum databases.

Optimizing the gene transformation factors can be considered as the first and foremost step in successful genetic engineering and genome editing studies. However, it is usually difficult to achieve an optimized gene transformation protocol due to the cost and time-consuming as well as the complexity of this process. Therefore, it is necessary to use a novel computational approach such as machine learning models for analyzing gene transformation data. In the current study, three individual machine learning models including Multi-Layer Perceptron (MLP), Adaptive Neuro-Fuzzy Inference System (ANFIS), and Radial Basis Function (RBF) were developed for forecasting Agrobacterium-mediated gene transformation in chrysanthemum based on eleven input variables including Agrobacterium strain, optical density (OD), co-culture period (CCP), and different antibiotics including kanamycin (K), vancomycin (VA), cefotaxime (CF), hygromycin (H), carbenicillin (CA), geneticin (G), ticarcillin (TI), and paromomycin (P). Consequently, best-obtained results were used in the fusion process by bagging method. Results showed that ensemble model with the highest R2 (0.83) had superb performance in comparison with all other individual models (MLP:063, RBF:0.69, and ANFIS: 0.74) in the validation set. Also, ensemble model was linked to Fruit fly optimization algorithm (FOA) for optimizing gene transformation, and the results showed that the maximum gene transformation efficiency (37.54%) can be achieved from EHA105 strain with 0.9 OD600, for 3.8 days CCP, 46.43 mg/l P, 9.54 mg/l K, 18.62 mg/l H, and 4.79 mg/l G as selection antibiotics and 109.74 µg/ml VA, 287.63 µg/ml CF, 334.07 µg/ml CA and 87.36 µg/ml TI as antibiotics in the selection medium. Moreover, sensitivity analysis demonstrated that input variables have a different degree of importance in gene transformation system in the order of Agrobacterium strain > CCP > K > CF > VA > P > OD > CA > H > TI > G. Generally, the developed hybrid model in this study (ensemble model-FOA) can be employed as an accurate and reliable approach in future genetic engineering and genome editing studies.

Development of support vector machine-based model and comparative analysis with artificial neural network for modeling the plant tissue culture procedures: effect of plant growth regulators on somatic embryogenesis of chrysanthemum, as a case study.

BACKGROUND: Optimizing the somatic embryogenesis protocol can be considered as the first and foremost step in successful gene transformation studies. However, it is usually difficult to achieve an optimized embryogenesis protocol due to the cost and time-consuming as well as the complexity of this process. Therefore, it is necessary to use a novel computational approach, such as machine learning algorithms for this aim. In the present study, two machine learning algorithms, including Multilayer Perceptron (MLP) as an artificial neural network (ANN) and support vector regression (SVR), were employed to model somatic embryogenesis of chrysanthemum, as a case study, and compare their prediction accuracy. RESULTS: The results showed that SVR (R2 > 0.92) had better performance accuracy than MLP (R2 > 0.82). Moreover, the Non-dominated Sorting Genetic Algorithm-II (NSGA-II) was also applied for the optimization of the somatic embryogenesis and the results showed that the highest embryogenesis rate (99.09%) and the maximum number of somatic embryos per explant (56.24) can be obtained from a medium containing 9.10 µM 2,4-dichlorophenoxyacetic acid (2,4-D), 4.70 µM kinetin (KIN), and 18.73 µM sodium nitroprusside (SNP). According to our results, SVR-NSGA-II was able to optimize the chrysanthemum's somatic embryogenesis accurately. CONCLUSIONS: SVR-NSGA-II can be employed as a reliable and applicable computational methodology in future plant tissue culture studies.

A robust workflow for indirect somatic embryogenesis and cormlet production in saffron (Crocus sativus L.) and its wild allies; C. caspius and C. speciosus.

Saffron (Crocus sativus L.) and its wild relatives, Crocus caspius and Crocus speciosus are of considerable significance in the pharmaceutical, nutraceutical, and ornamental bulbs industry. Towards the ultimate goal of the conservation of wild Crocus species and establishment of an efficient workflow for in vitro production of Crocuses, efficient protocols were developed for disinfection and in vitro production of cormlets in C. sativus and its wild allies C. caspius and C. speciosus. Moreover, the differential expression of the Somatic Embryogenesis Receptor-like Kinase (SERK) gene was evaluated as a potential molecular marker during embryogenesis between embryogenic and non-embryogenic calli. A highly efficient disinfection recipe and a low-cost TDZ-free protocol have been successfully developed for in vitro cormlet production in three Crocus species. MS medium containing 10.18 µM 2, 4-D + 4.44 µM BAP was most efficiently induced callus and somatic embryo formation. The highest conversion frequency and maximum cormlet weight were achieved in MS containing 5.37 µM NAA + 8.88 µM BAP. The SERK expression was significantly much higher in embryogenic calli than non-embryogenic in all Crocus species. The current low-cost and easy-to-use recipe suggests a promising in vitro propagation workflow for mass production of uniform pathogen-free cormlets of Crocus species, as well as a platform to better conservation of wild Crocus species and effective gene and genome editing using CRISPR-Cas9 in future studies.

Modeling and Optimizing Medium Composition for Shoot Regeneration of Chrysanthemum via Radial Basis Function-Non-dominated Sorting Genetic Algorithm-II (RBF-NSGAII).

The aim of the current study was modeling and optimizing medium compositions for shoot proliferation of chrysanthemum, as a case study, through radial basis function- non-dominated sorting genetic algorithm-II (RBF-NSGAII). RBF as one of the artificial neural networks (ANNs) was used for modeling four outputs including proliferation rate (PR), shoot number (SN), shoot length (SL), and basal callus weight (BCW) based on four variables including 6-benzylaminopurine (BAP), indole-3-butyric acid (IBA), phloroglucinol (PG), and sucrose. Afterward, models were linked to the optimization algorithm. Also, sensitivity analysis was applied for evaluating the importance of each input. The R2 correlation values of 0.88, 0.91, 0.97, and 0.76 between observed and predicted data were obtained for PR, SN, SL, and BCW, respectively. According to RBF-NSGAII, optimal PR (98.85%), SN (13.32), SL (4.83 cm), and BCW (0.08 g) can be obtained from a medium containing 2.16 µM BAP, 0.14 µM IBA, 0.29 mM PG, and 87.63 mM sucrose. The results of sensitivity analysis indicated that PR, SN, and SL were more sensitive to BAP, followed by sucrose, PG, and IBA. Finally, the performance of predicted and optimized medium compositions were tested, and results showed that the difference between the validation data and RBF-NSGAII predicted and optimized data were negligible. Generally, RBF-NSGAII can be considered as an efficient computational strategy for modeling and optimizing in vitro organogenesis.

Application of Adaptive Neuro-Fuzzy Inference System-Non-dominated Sorting Genetic Algorithm-II (ANFIS-NSGAII) for Modeling and Optimizing Somatic Embryogenesis of Chrysanthemum.

A hybrid artificial intelligence model and optimization algorithm could be a powerful approach for modeling and optimizing plant tissue culture procedures. The aim of this study was introducing an Adaptive Neuro-Fuzzy Inference System- Non-dominated Sorting Genetic Algorithm-II (ANFIS-NSGAII) as a powerful computational methodology for somatic embryogenesis of chrysanthemum, as a case study. ANFIS was used for modeling three outputs including callogenesis frequency (CF), embryogenesis frequency (EF), and the number of somatic embryo (NSE) based on different variables including 2,4-dichlorophenoxyacetic acid (2,4-D), 6-benzylaminopurine (BAP), sucrose, glucose, fructose, and light quality. Subsequently, models were linked to NSGAII for optimizing the process, and the importance of each input was evaluated by sensitivity analysis. Results showed that all of the R2 of training and testing sets were over 92%, indicating the efficiency and accuracy of ANFIS on the modeling of the embryogenesis. Also, according to ANFIS-NSGAII, optimal EF (99.1%), and NSE (13.1) can be obtained from a medium containing 1.53 mg/L 2,4-D, 1.67 mg/L BAP, 13.74 g/L sucrose, 57.20 g/L glucose, and 0.39 g/L fructose under red light. The results of the sensitivity analysis showed that embryogenesis was more sensitive to 2,4-D, and less sensitive to fructose. Generally, the hybrid ANFIS-NSGAII can be recognized as a powerful computational tool for modeling and optimizing in plant tissue culture.

Modeling and Optimizing in vitro Sterilization of Chrysanthemum via Multilayer Perceptron-Non-dominated Sorting Genetic Algorithm-II (MLP-NSGAII).

In vitro sterilization is a primary step of plant tissue culture which the ultimate results of in vitro culture are directly depended on the efficiency of the sterilization. Artificial intelligence models in a combination of optimization algorithms could be beneficial computational approaches for modeling and optimizing in vitro culture. The aim of this study was modeling and optimizing in vitro sterilization of chrysanthemum, as a case study, through Multilayer Perceptron- Non-dominated Sorting Genetic Algorithm-II (MLP-NSGAII). MLP was used for modeling two outputs including contamination frequency (CF), and explant viability (EV) based on seven variables including HgCl2, Ca(ClO)2, Nano-silver, H2O2, NaOCl, AgNO3, and immersion times. Subsequently, models were linked to NSGAII for optimizing the process, and the importance of each input was evaluated by sensitivity analysis. Results showed all of the R2 of training and testing data were over 94%. According to MLP-NSGAII, optimal CF (0%), and EV (99.98%) can be obtained from 1.62% NaOCl at 13.96 min immersion time. The results of sensitivity analysis showed that CF and EV were more sensitive to immersion time and less sensitive to AgNO3. Subsequently, the performance of predicted and optimized sterilants × immersion times combination were tested, and results indicated that the differences between the MLP predicted and validation data were negligible. Generally, MLP-NSGAII as a powerful methodology may pave the way for establishing new computational strategies in plant tissue culture.

Impact of exogenous GABA treatments on endogenous GABA metabolism in anthurium cut flowers in response to postharvest chilling temperature.

Anthurium flowers are susceptible to chilling injury, and the optimum storage temperature is 12.5-20 °C. The γ-aminobutyric acid (GABA) shunt pathway may alleviate chilling stress in horticultural commodities by providing energy (ATP), reducing molecules (NADH), and minimizing accumulation of reactive oxygen species (ROS). In this experiment, the impact of a preharvest spray treatment with 1 mM GABA and postharvest treatment of 5 mM GABA stem-end dipping on GABA shunt pathway activity of anthurium cut flowers (cv. Sirion) in response to cold storage (4 °C for 21 days) was investigated. GABA treatments resulted in lower glutamate decarboxylase (GAD) and higher GABA transaminase (GABA-T) activities in flowers during cold storage, which was associated with lower GABA content and coincided with higher ATP content. GABA treatments also enhanced accumulation of endogenous glycine betaine (GB) in flowers during cold storage, as well as higher spathe relative water content (RWC). These findings suggest that GABA treatments may alleviate chilling injury of anthurium cut flowers by enhancing GABA shunt pathway activity leading to provide sufficient ATP and promoting endogenous GB accumulation.

Capsule formation and asymbiotic seed germination in some hybrids of Phalaenopsis, influenced by pollination season and capsule maturity.

We explored the influence of pollination season and maturity of capsule on post-pollination capsule formation and in vitro asymbiotic seed germination, respectively. Three Phalaenopsis orchid hybrids, namely, 'Athens', 'Moscow' and 'Lusaka' flowers were artificially self-pollinated during winter, spring, summer and fall seasons and the impact of the pollination seasons was evident during capsule formation. It was observed that winter was the most suitable season for pollination of all the three Phalanaeopsis hybrids resulting in 80-88 % capsule formation. During summer, the pollination success rate was 24-28 %, but resulted in successful capsule formation. Season of pollination further delimited the germination efficiency of seeds harvested from capsules of variable maturity levels. Invariably, seeds collected from winter-pollinated capsules performed best in germination compared to other seasons, for instance, 'Moscow' seeds took less than 14 days to germinate from capsules developed following winter-pollination. Regarding the influence of capsule maturity on seed germination, we observed that seeds derived from 5-month mature capsules, invariably took least time to germinate than that of the 3-month or 7-month in all three hybrids, e.g., for 'Moscow' it was 13.9 days with a maximum of 90.3 % germination.

Indirect somatic embryogenesis from petal explant of endangered wild population of Fritillaria imperialis.

Fritillaria imperialis is an endangered bulbous plant and therefore in vitro micropropagation of this plant will have a great importance for germplasm conservation and commercial production. Petal explants, for the first time, were cultured on media containing various concentrations of plant growth regulators. In addition, the effects of cold pretreatment and light on induction and regeneration of somatic embryogenesis trough callus were studied in detail. Cold pretreatment had inhibitory effects on somatic embryogenesis pathway. Among the different combinations of 6-Bnzylaminopurine (BAP), alpha-naphthaleneacetic acid (NAA) and indole-3-aceticacid (IAA) tested, B5 medium supplemented with 0.1 mg L(-1) BAP + 0.6 mg L(-1) NAA + 0.4 mg L(-1) IAA was the best treatment for bulblet production (6 bulblets per somatic embryogenesis callus). This research presents petal as a reliable material for micropropagation and germplasm conservation of Fritillaria imperialis.