Moderately Elevated Temperature Offsets the Adverse Effects of Waterlogging Stress on Tomato.

Global warming and waterlogging stress due to climate change are expected to continue influencing agricultural production worldwide. In the field, two or more environmental stresses usually happen simultaneously, inducing more complex responses in plants compared with individual stresses. Our aim was to clarify how the two key factors (temperature and water) interacted and influenced physiological response and plant growth in tomatoes under ambient temperature, moderately elevated temperature, waterlogging stress, and moderately elevated temperature and waterlogging stress. The results showed that leaf photosynthesis was inhibited by waterlogging stress but enhanced by elevated temperature, as shown by both the light- and temperature-response curves. The elevated temperature decreased leaf water-use efficiency, but enhanced plant growth and fresh and dry weights of plants under both normal water supply and waterlogging stress conditions. Elevated temperature generally decreased the anthocyanin and flavonol index in tomato leaves compared with the control temperature, regardless of water status. The increase in the optimal temperature was more pronounced in plants under normal irrigation than under waterlogging stress. Waterlogging stress significantly inhibited the root length, and leaf number and area, while the moderately elevated temperature significantly enhanced the leaf number and area. Overall, the moderately elevated temperature offset the effects of waterlogging stress on tomato plants, as shown by leaf gas exchange, plant size, and dry matter accumulation. Our study will improve the understanding of how tomatoes respond to increasing temperature and excess water.

Potential Suitable Habitats of Chili Pepper in China under Climate Change.

Chili pepper (Capsicum annuum L.) is extensively cultivated in China, with its production highly reliant on regional environmental conditions. Given ongoing climate change, it is imperative to assess its impact on chili pepper cultivation and identify suitable habitats for future cultivation. In this study, the MaxEnt model was optimized and utilized to predict suitable habitats for open-field chili pepper cultivation, and changes in these habitats were analyzed using ArcGIS v10.8. Our results showed that the parameter settings of the optimal model were FC = LQPTH and RM = 2.7, and the critical environmental variables influencing chili pepper distribution were annual mean temperature, isothermality, maximum temperature of the warmest month, and precipitation of the warmest quarter. Under current climate conditions, suitable habitats were distributed across all provinces in China, with moderately- and highly-suitable habitats concentrated in the east of the Qinghai-Tibetan Plateau and south of the Inner Mongolia Plateau. Under future climate scenarios, the area of suitable habitats was expected to be larger than the current ones, except for SSP126-2050s, and reached the maximum under SSP126-2090s. The overlapping suitable habitats were concentrated in the east of the Qinghai-Tibetan Plateau and south of the Inner Mongolia Plateau under various climate scenarios. In the 2050s, the centroids of suitable habitats were predicted to shift towards the southwest, except for SSP126, whereas this trend was reversed in the 2090s. Our results suggest that climate warming is conductive to the cultivation of chili pepper, and provide scientific guidance for the introduction and cultivation of chili pepper in the face of climate warming.

Cloning and Analysis of Expression of Genes Related to Carotenoid Metabolism in Different Fruit Color Mutants of Pepper (Capsicum annuum L.).

The formation of fruit color in pepper is closely related to the processes of carotenoid metabolism. In this study, red wild-type pepper XHB, SP01, PC01 and their corresponding mutants H0809 (orange), SP02 (yellow), and PC02 (orange) were used as research materials. The Ggps, Psy, Lcyb, Crtz, Zep, and Ccs genes involved in carotenoid biosynthesis were cloned, and bioinformatics and expression analyses were carried out. The results showed that the full lengths of the six genes were 1110 bp, 2844 bp, 1497 bp, 2025 bp, 510 bp, and 1497 bp, and they encoded 369, 419, 498, 315, 169, and 498 amino acids, respectively. Except for the full-length Ccs gene, which could not be amplified in the yellow mutant SP02 and the orange mutant PC02, the complete full-length sequences of the other genes could be amplified in different materials, indicating that the formation of fruit color in the SP02 and PC02 mutants could be closely related to the deletion or mutation of the Ccs gene. The analytical results of real-time quantitative reverse transcription PCR (qRT-PCR) showed that the Ggps, Psy, Lcyb, Crtz, and Zep genes were expressed at different developmental stages of three pairs of mature-fruit-colored materials, but their patterns of expression were not consistent. The orange mutant H0809 could be amplified to the full Ccs gene sequence, but its expression was maintained at a lower level. It showed a significant difference in expression compared with the wild-type XHB, indicating that the formation of orange mutant H0809 fruit color could be closely related to the different regulatory pattern of Ccs expression. The results provide a theoretical basis for in-depth understanding of the molecular regulatory mechanism of the formation of color in pepper fruit.

The influence of low-temperature resistant lactic acid bacteria on the enhancement of quality and the microbial community in winter Jerusalem Artichoke (Helianthus tuberosus L.) silage on the Qinghai-Tibet Plateau.

Jerusalem Artichoke (Helianthus tuberosus L.), an emerging "food and fodder" economic crop on the Qinghai-Tibet Plateau. To tackle problems such as incomplete fermentation and nutrient loss occurring during the low-temperature ensilage of Jerusalem Artichokes in the plateau's winter, this study inoculated two strains of low-temperature resistant lactic acid bacteria, Lactobacillus plantarum (GN02) and Lactobacillus brevis (XN25), along with their mixed components, into Jerusalem Artichoke silage material. We investigated how low-temperature resistant lactic acid bacteria enhance the quality of low-temperature silage fermentation for Jerusalem Artichokes and clarify its mutual feedback effect with microorganisms. Results indicated that inoculating low-temperature resistant lactic acid bacteria significantly reduces the potential of hydrogen and water-soluble carbohydrates content of silage, while increasing lactic acid and acetic acid levels, reducing propionic acid, and preserving additional dry matter. Inoculating the L. plantarum group during fermentation lowers pH and propionic acid levels, increases lactic acid content, and maintains a dry matter content similar to the original material. Bacterial community diversity exhibited more pronounced changes than fungal diversity, with inoculation having a minor effect on fungal community diversity. Within the bacteria, Lactobacillus remains consistently abundant (>85%) in the inoculated L. plantarum group. At the fungal phylum and genus levels, no significant changes were observed following fermentation, and dominant fungal genera in all groups did not differ significantly from those in the raw material. L. plantarum exhibited a positive correlation with lactic acid and negative correlations with pH and propionic acid. In summary, the inoculation of L. plantarum GN02 facilitated the fermentation process, preserved an acidic silage environment, and ensured high fermentation quality; it is a suitable inoculant for low-temperature silage in the Qinghai-Tibet Plateau.

Development and Validation of Contrast-Enhanced CT-Based Deep Transfer Learning and Combined Clinical-Radiomics Model to Discriminate Thymomas and Thymic Cysts: A Multicenter Study.

RATIONALE AND OBJECTIVES: This study aims to evaluate the feasibility and effectiveness of deep transfer learning (DTL) and clinical-radiomics in differentiating thymoma from thymic cysts. MATERIALS AND METHODS: Clinical and imaging data of 196 patients pathologically diagnosed with thymoma and thymic cysts were retrospectively collected from center 1. (training cohort: n = 137; internal validation cohort: n = 59). An independent external validation cohort comprised 68 thymoma and thymic cyst patients from center 2. Region of interest (ROI) delineation was performed on contrast-enhanced chest computed tomography (CT) images, and eight DTL models including Densenet 169, Mobilenet V2, Resnet 101, Resnet 18, Resnet 34, Resnet 50, Vgg 13, Vgg 16 were constructed. Radiomics features were extracted from the ROI on the CT images of thymoma and thymic cyst patients, and feature selection was performed using intra-observer correlation coefficient (ICC), Spearman correlation analysis, and least absolute shrinkage and selection operator (LASSO) algorithm. Univariate analysis and multivariable logistic regression (LR) were used to select clinical-radiological features. Six machine learning classifiers, including LR, support vector machine (SVM), k-nearest neighbors (KNN), Light Gradient Boosting Machine (LightGBM), Adaptive Boosting (AdaBoost), and Multilayer Perceptron (MLP), were used to construct Radiomics and Clinico-radiologic models. The selected features from the Radiomics and Clinico-radiologic models were fused to build a Combined model. Receiver operating characteristic curve (ROC), calibration curve, and decision curve analysis (DCA) were used to evaluate the discrimination, calibration, and clinical utility of the models, respectively. The Delong test was used to compare the AUC between different models. K-means clustering was used to subdivide the lesions of thymomas or thymic cysts into subregions, and traditional radiomics methods were used to extract features and compare the ability of Radiomics and DTL models to reflect intratumoral heterogeneity using correlation analysis. RESULTS: The Densenet 169 based on DTL performed the best, with AUC of 0.933 (95% CI: 0.875-0.991) in the internal validation cohort and 0.962 (95% CI: 0.923-1.000) in the external validation cohort. The AdaBoost classifier achieved AUC of 0.965 (95% CI: 0.923-1.000) and 0.959 (95% CI: 0.919-1.000) in the internal and external validation cohorts, respectively, for the Radiomics model. The LightGBM classifier achieved AUC of 0.805 (95% CI: 0.690-0.920) and 0.839 (95% CI: 0.736-0.943) in the Clinico-radiologic model. The AUC of the Combined model in the internal and external validation cohorts was 0.933 (95% CI: 0.866-1.000) and 0.945 (95% CI: 0.897-0.994), respectively. The results of the Delong test showed that the Radiomics model, DTL model, and Combined model outperformed the Clinico-radiologic model in both internal and external validation cohorts (p-values were 0.002, 0.004, and 0.033 in the internal validation cohort, while in the external validation cohort, the p-values were 0.014, 0.006, and 0.015, respectively). But there was no statistical difference in performance among the three models (all p-values <0.05). Correlation analysis showed that radiomics performed better than DTL in quantifying intratumoral heterogeneity differences between thymoma and thymic cysts. CONCLUSION: The developed DTL model and the Combined model based on radiomics and clinical-radiologic features achieved excellent diagnostic performance in differentiating thymic cysts from thymoma. They can serve as potential tools to assist clinical decision-making, particularly when endoscopic biopsy carries a high risk.

Metabolomics analysis of quality components metabolism during the growth process of pepino (Solanum muricatum) fruit.

Pepino (Solanum muricatum), a horticultural crop that has experienced significant growth in the highlands of China over the past two decades, is widely embraced by consumers due to its distinctive taste and nutritional advantages. This study focused on the cultivar 'Qingcanxiang' of pepino grown on the Qinghai-Tibetan Plateau was analyzed using UPLC-QTOF-MS and RNA-seq transcriptome sequencing. Fruit samples were collected at three distinct stages of development, and the results of the metabolomics and transcriptomics were compared and correlated. The study's findings indicate that the 'Qingcanxiang' fruit contained a total of 187 metabolites, comprising 12 distinct categories of compounds, including amino acids and their derivatives, organic acids, sugars and alcohols, phenols and phenolic acids. Of these metabolites, 94 were identified as differential. Significant variations in nutrient composition were observed across the three growth stages of the fruit. Specifically, the stage spanning from the growth to the maturation was identified as the critical stages for nutrient accumulation and flavor development. Transcriptome sequencing analysis revealed a set of highly associated genes between aspartate and quinic acid, namely SIR2, IRAK4, RP-L29, and CCNH. These genes are potentially involved in the regulation of both amino acid and phenolic acid synthesis. Through the application of metabolomics and transcriptomics, this investigation elucidates the alterations in metabolites and the underlying molecular regulatory mechanisms of pepino fruits during three growth stages. The findings furnish a theoretical foundation for the evaluation of nutritional quality and the enhancement of breeding strategies for pepino.

Assessment of suitable cultivation region for Pepino (Solanum muricatum) under different climatic conditions using the MaxEnt model and adaptability in the Qinghai-Tibet plateau.

Pepino (Solanum muricatum), a member of the Solanaceae family originating from South America, is cultivated globally. However, the cultivation range and suitable habitat of Pepino have not been extensively studied, which hampers the further development of its cultivation industry. Therefore, we aimed at enrich and expand the planting scope of Pepino. Currently, the main cultivation areas of Pepino in China are the Yunnan-Guizhou Plateau and the Loess Plateau, where the altitude is above 1000 m. In this study, ArcGIS combined with the MaxEnt model was used for prediction, whose area under curve value was 0.949. The main climatic factors affecting the distribution of Pepino are temperature seasonality, annual means temperature, mean temperature of the coldest quarter, elevation, isothermality, and the climate factors, and their cumulative contribution rate of 87.6%. Pepino's main potential distribution areas are located in Yunnan-Guizhou Plateau, Yunnan Province, Hexi Corridor of Loess Plateau, and low altitude areas of Qinghai-Tibet Plateau. The main distribution ranges from 1000 to 2000 m above sea level, and the total suitable area accounts for 20.09% of China's total land area. The prediction results reveal an expanded potential area for Pepino, with no significant migration in the central region of the main potential distribution area by 2050 and 2070. No studies have been conducted on the open-area cultivation of Pepino in northern China. Our findings revealed that the yield and quality in the four experimental sites and final actual cultivation conditions were consistent with the predicted results of MaxEnt. The yiel d per plant in Xunhua and Minhe was significantly different from that in Xining, which was low, and that in Minhe was the highest. Overall, the fruit quality in the Xining region was the lowest among the three regions, which was related to the climatic differences in each region. These results align with the predicted outcomes, indicating that Xining is the least suitable area. Further, these data verify the accuracy of the prediction results. The climate data of the four regions were analyzed simultaneously to elucidate the influence of different climate conditions on the growth of Pepino. Our findings are of considerable significance for introducing characteristic horticultural crops in the Qinghai-Tibet Plateau and using the MaxEnt model to predict the cultivation range of crops.

Systematic Investigation of TCP Gene Family: Genome-Wide Identification and Light-Regulated Gene Expression Analysis in Pepino (Solanum Muricatum).

Plant-specific transcription factors such as the TCP family play crucial roles in light responses and lateral branching. The commercial development of S. muricatum has been influenced by the ease with which its lateral branches can be germinated, especially under greenhouse cultivation during the winter with supplemented LED light. The present study examined the TCP family genes in S. muricatum using bioinformatics analysis (whole-genome sequencing and RNA-seq) to explore the response of this family to different light treatments. Forty-one TCP genes were identified through a genome-wide search; phylogenetic analysis revealed that the CYC/TB1, CIN and Class I subclusters contained 16 SmTCP, 11 SmTCP and 14 SmTCP proteins, respectively. Structural and conserved sequence analysis of SmTCPs indicated that the motifs in the same subcluster were highly similar in structure and the gene structure of SmTCPs was simpler than that in Arabidopsis thaliana; 40 of the 41 SmTCPs were localized to 12 chromosomes. In S. muricatum, 17 tandem repeat sequences and 17 pairs of SmTCP genes were found. We identified eight TCPs that were significantly differentially expressed (DETCPs) under blue light (B) and red light (R), using RNA-seq. The regulatory network of eight DETCPs was preliminarily constructed. All three subclusters responded to red and blue light treatment. To explore the implications of regulatory TCPs in different light treatments for each species, the TCP regulatory gene networks and GO annotations for A. thaliana and S. muricatum were compared. The regulatory mechanisms suggest that the signaling pathways downstream of the TCPs may be partially conserved between the two species. In addition to the response to light, functional regulation was mostly enriched with auxin response, hypocotyl elongation, and lateral branch genesis. In summary, our findings provide a basis for further analysis of the TCP gene family in other crops and broaden the functional insights into TCP genes regarding light responses.

Screening and Verification of Reference Genes for Analysis of Gene Expression in Garlic (Allium sativum L.) under Cold and Drought Stress.

The principal objective of this study was to screen and verify reference genes appropriate for gene expression evaluation during plant growth and development under distinct growth conditions. Nine candidate reference genes were screened based on garlic transcriptome sequence data. RT-qPCR was used to detect the expression levels of the aforementioned reference genes in specific tissues under drought and cold stress. Then, geNorm, NormFinder, BestKeeper, and ReFinder were used to consider the consistency of the expression levels of candidate reference genes. Finally, the stress-responsive gene expression of ascorbate peroxidase (APX) was quantitatively evaluated to confirm the chosen reference genes. Our results indicated that there were variations in the abundance and stability of nine reference gene transcripts underneath cold and drought stress, among which ACT and UBC-E2 had the highest transcript abundance, and 18S rRNA and HIS3 had the lowest transcript abundance. UBC and UBC-E2 were the most stably expressed genes throughout all samples; UBC and UBC-E2 were the most stably expressed genes during cold stress, and ACT and UBC were the most stably expressed genes under drought stress. The most stably expressed genes in roots, pseudostems, leaves, and cloves were EF1, ACT, HIS3, UBC, and UBC-E2, respectively, while GAPDH was the most unstable gene during drought and cold stress conditions and in exclusive tissues. Taking the steady reference genes UBC-E2, UBC, and ACT as references during drought and cold stress, the reliability of the expression levels was further demonstrated by detecting the expression of AsAPX. Our work thereby offers a theoretical reference for the evaluation of gene expression in garlic in various tissues and under stress conditions.

Identification of the key metabolites and related genes network modules highly associated with the nutrients and taste components among different Pepino (Solanum muricatum) cultivars.

There is considerable knowledge about plant compounds that produce flavor, scent, and aroma. Aside from the similarities, however, groups of plant-produced nutrients and taste components have little in common with each other. Network analysis holds promise for metabolic gene discovery, which is especially important in plant systems where metabolic networks are not yet fully resolved. To bridge this gap, we propose a joint model of gene regulation and metabolic reactions in two different pepino varieties. Differential metabolomics analysis is carried out for detection of eventual interaction of compound. We adopted a multi-omics approach to profile the transcriptome and metabolome analyze differences in phenolic acids, flavonoids, organic acids, lipids, alkaloids, and sugars between LOF and SRF. The two most predominant classes of metabolites are phenolic acids and lipids in pepino. Overall results show enrichment in most DEGs was carbohydrate and biosynthesis of secondary metabolites pathway. Results of DEMs predominantly comprised N-p-coumaroyl agmatine and tryptamine, and significant differences were observed in their expression between LOF and SRF. Integrated DEMs and DEGs specific networks were constructed by combining two types of networks: transcriptional regulatory networks composed of interactions between DEMs and the regulated genes, and pepino metabolite-metabolite interaction networks. Newly discovered features, such as DEGs (USPA, UBE2 and DELLA) involved in the production of secondary metabolites are found in coregulated gene clusters. Moreover, lipid metabolites were most involved in DEMs correlations by OPLS-DA while identifying a significant number of DEGs co-regulated by SENP1, HMGCS et al. These results further that the metabolite discrepancies result from characterized the nutrients and taste components between two pepino genotype. Among the possible causes of the differences between species in pepino metabolite concentrations is co-regulated by these DEGs, continue to suggest that novel features of metabolite biosynthetic pathway remain to be uncovered. Finally, the integrated metabolome and transcriptome analyses have revealed that many important metabolic pathways are regulated at the transcriptional level. The metabolites content differences observed among varieties of the same species mainly originates from different regulated genes and enzymes expression. Overall, this study provides new insights into the underlying causes of differences in the plant metabolites and suggests that genetic data can be used to improve its nutrients and taste components.

Effects of light spectrum on the morphophysiology and gene expression of lateral branching in Pepino (Solanum muricatum).

In the present study, we determined the morphological and physiological indicators of Pepino to elucidate its lateral branching responses to different light qualities using a full-spectrum lamp (F) as the control and eight different light ratios using blue light (B) and red light (R). In addition, correlation analysis revealed that the gene expression patterns correlated with lateral branching under various light treatments. Compared with the F treatment, the R treatment increased the plant height and inhibited the elongation of lateral branches, in contrast with the B treatment. The number of lateral branches did not change significantly under different light quality treatments. Moreover, correlation analysis showed that the ratio of blue light was significantly positively correlated with the length of lateral branches and significantly negatively correlated with plant height, aboveground dry weight, and other indicators. We conducted transcriptome sequencing of the sites of lateral branching at three periods under different light quality treatments. The gene related to photodynamic response, cryptochrome (CRY), was the most highly expressed under B treatment, negatively regulated lateral branch length, and positively correlated with plant height. Branched 1, a lateral branch regulation gene, was upregulated under R treatment and inhibited branching. Overall, the red light facilitated internode elongation, leaf area expansion, plant dry weight increase, and inhibition of lateral branching. Soluble sugar content increased, and the lateral branches elongated under blue light. Different light qualities regulated lateral branching by mediating different pathways involving strigolactones and CRY. Our findings laid a foundation for further clarifying the response mechanism of Pepino seedlings to light and provided a theoretical reference for elucidating the regulation of different light qualities on the lateral branching of Pepino.

Diversity of bacterial community in Jerusalem artichoke (Helianthus tuberosus L.) during storage is associated with the genotype and carbohydrates.

Jerusalem artichoke (JA) is a fructan-accumulating crop that has gained popularity in recent years. The objective of the present study was to determine the dynamics of the JA-microbiome during storage. The microbial population on the surface of the JA tuber was determined by next-generation sequencing of 16S rRNA amplicons. Subsequently, the changes in carbohydrate and degree of polymerization of fructan in tubers during storage were measured. Among different genotypes of JA varieties, intergeneric differences were observed in the diversity and abundance of bacterial communities distributed on the surface of tubers. Additionally, bacterial diversity was significantly higher in storage-tolerant varieties relative to the storage-intolerant varieties. Redundancy analysis (RDA) and the correlation matrix indicated a relationship between changes in the carbohydrates and microbial community succession during tuber storage. The tuber decay rate correlated positively with the degree of polymerization of fructan. Moreover, Dysgonomonas and Acinetobacter in perishable varieties correlated significantly with the decay rate. Therefore, the bacteria associated with the decay rate may be involved in the degradation of the degree of polymerization of fructan. Furthermore, Serratia showed a significant positive correlation with inulin during storage but a negative correlation with the decay rate, suggesting its antagonistic role against pathogenic bacteria on the surface of JA tubers. However, the above correlation was not observed in the storage-tolerant varieties. Functional annotation analysis revealed that storage-tolerant JA varieties maintain tuber quality through enrichment of biocontrol bacteria, including Flavobacterium, Sphingobacterium, and Staphylococcus to resist pathogens. These results suggested that crop genotype and the structural composition of carbohydrates may result in differential selective enrichment effects of microbial communities on the surface of JA varieties. In this study, the relationship between microbial community succession and changes in tuber carbohydrates during JA storage was revealed for the first time through the combination of high-throughput sequencing, high-performance liquid chromatography (HPLC), and high-performance ion-exchange chromatography (HPIC). Overall, the findings of this study are expected to provide new insights into the dynamics of microbial-crop interactions during storage.

Mining the Roles of Cucumber DUF966 Genes in Fruit Development and Stress Response.

DUF966 genes are widely found in monocotyledons, dicotyledons, mosses, and other species. Current evidence strongly suggests that they are involved in growth regulation and stress tolerance in crops. However, their functions in cucumbers remain unexplored. Here, cucumber CsDUF966 was systemically identified and characterized using bioinformatics. Eight CsDUF966 genes were identified in the cucumber genome. These were phylogenetically separated into three groups. All CsDUF966 proteins were hydrophilic and localized to the nucleus. Moreover, three acidic and five basic proteins were identified. Evolutionary analysis of DUF966 between cucumber and 33 other Cucurbitaceae species/cultivars revealed that most CsDUF966 genes were conserved, whereas CsDUF966_4.c and CsDUF966_7.c were positively selected among the five cucumber cultivars. Expression profiling analysis showed that CsDUF966 had variable expression patterns, and that miRNA164, miRNA166, and Csa-novel-35 were involved in the post-transcriptional regulation of CsDUF966_4.c and CsDUF966_7.c. The expression of CsDUF966_4.c and CsDUF966_7.c, which were under strong neofunctionalization selection, was strictly regulated in fruit and tissues, including seeds, pericarps, peels, and spines, suggesting that these genes are fruit growth regulators and were strongly selected during the cucumber breeding program. In conclusion, the results reveal the roles of CsDUF966s in regulating cucumber fruit development and lay the foundation for further functional studies.

Pepino (Solanum muricatum) Metabolic Profiles and Soil Nutrient Association Analysis in Three Growing Sites on the Loess Plateau of Northwestern China.

Different soil nutrients affect the accumulation characteristics of plant metabolites. To investigate the differences among the metabolites of pepino grown in greenhouses on the Loess Plateau in northwest China, we investigated the main soil nutrients and their correlation with metabolites. A total of 269 pepino metabolites were identified using UPLC-QTOF-MS to detect metabolites in fruits from three major pepino growing regions and analyze their differential distribution characteristics. A total of 99 of these substances differed among pepino fruits from the three areas, and the main classes of the differential metabolites were, in order of number: amino acids and derivatives, nucleotides and derivatives, organic acids, alkaloids, vitamins, saccharides and alcohols, phenolic acids, lipids and others. An environmental factor analysis identified soil nutrients as the most significant differentiator. Five soil nutrient indicators: TN (total nitrogen), TP (total phosphorus), AP (available phosphorus), AK (available potassium), and OM (organic matter), exhibited significant differences in three growing sites. Metabolite and soil nutrient association analysis using redundancy analysis (RDA) and the Mantel test indicated that TN and OM contributed to the accumulation of amino acids and derivatives, nucleotides and derivatives, and alkaloids while inhibiting organic acids, vitamins coagulation biosynthesis. Moreover, AP and TP were associated with the highest accumulation of saccharides and, alcohols, phenolic acids. Consequently, differences in soil nutrients were reflected in pepino metabolite variability. This study clarified the metabolite variability and the relationship between pepino and soil nutrients in the main planting areas of northwest China. It provides a theoretical basis for the subsequent development of Pepino's nutritional value and cultivation management.

Transcriptomics Integrated with Metabolomics Unveil Carotenoids Accumulation and Correlated Gene Regulation in White and Yellow-Fleshed Turnip (Brassica rapa ssp. rapa).

Turnip (Brassica rapa ssp. rapa) is considered to be a highly nutritious and health-promoting vegetable crop, whose flesh color can be divided into yellow and white. It is widely accepted that yellow-fleshed turnips have higher nutritional value. However, reports about flesh color formation is lacking. Here, the white-fleshed inbred line, W21, and yellow-fleshed inbred line, W25, were profiled from the swollen root of the turnip at three developmental periods to elucidate the yellow color formation. Transcriptomics integrated with metabolomics analysis showed that the PSY gene was the key gene affecting the carotenoids formation in W25. The coding sequence of BrrPSY-W25 was 1278 bp and that of BrrPSY-W21 was 1275 bp, and BrrPSY was more highly expressed in swollen roots in W25 than in W21. Transient transgenic tobacco leaf over-expressing BrrPSY-W and BrrPSY-Y showed higher transcript levels and carotenoids contents. Results revealed that yellow turnip formation is due to high expression of the PSY gene rather than mutations in the PSY gene, indicating that a post-transcriptional regulatory mechanism may affect carotenoids formation. Results obtained in this study will be helpful for explaining the carotenoids accumulation of turnips.

Electrochemical Synthesis of ß-Functionalized Ketones via Ring-Opening of Cycloalkanols.

The electrochemical deconstructive functionalization of cycloalkanols with nucleophiles has been studied, which allows functionalization to occur exclusively at the ß-position of ketones. The substrate scope includes a wide range of cycloalkanols as well as diverse N, O, C, and P-centered nucleophiles, providing ready access to ß-functionalized ketones as products. Mechanistic studies support the generation of α,ß-unsaturated ketones as key intermediates followed by Michael addition with nucleophiles.

An Exploration of Pepino (Solanum muricatum) Flavor Compounds Using Machine Learning Combined with Metabolomics and Sensory Evaluation.

Flavor is one of the most important characteristics that directly determines the popularity of a food. Moreover, the flavor of fruits is determined by the interaction of multiple metabolic components. Pepino, an emerging horticultural crop, is popular for its unique melon-like flavor. We analyzed metabolomics data from three different pepino growing regions in Haidong, Wuwei, and Jiuquan and counted the status of sweetness, acidity, flavor, and overall liking ratings of pepino fruit in these three regions by sensory panels. The metabolomics and flavor ratings were also integrated and analyzed using statistical and machine learning models, which in turn predicted the sensory panel ratings of consumers based on the chemical composition of the fruit. The results showed that pepino fruit produced in the Jiuquan region received the highest ratings in sweetness, flavor intensity, and liking, and the results with the highest contribution based on sensory evaluation showed that nucleotides and derivatives, phenolic acids, amino acids and derivatives, saccharides, and alcohols were rated in sweetness (74.40%), acidity (51.57%), flavor (56.41%), and likability (33.73%) dominated. We employed 14 machine learning strategies trained on the discovery samples to accurately predict the outcome of sweetness, sourness, flavor, and liking in the replication samples. The Radial Sigma SVM model predicted with better accuracy than the other machine learning models. Then we used the machine learning models to determine which metabolites influenced both pepino flavor and consumer preference. A total of 27 metabolites most important for pepino flavor attributes to distinguish pepino originating from three regions were screened. Substances such as N-acetylhistamine, arginine, and caffeic acid can enhance pepino's flavor intensity, and metabolites such as glycerol 3-phosphate, aconitic acid, and sucrose all acted as important variables in explaining the liking preference. While glycolic acid and orthophosphate inhibit sweetness and enhance sourness, sucrose has the opposite effect. Machine learning can identify the types of metabolites that influence fruit flavor by linking metabolomics of fruit with sensory evaluation among consumers, which conduces breeders to incorporate fruit flavor as a trait earlier in the breeding process, making it possible to select and release fruit with more flavor.

Transcriptome-wide and expression analysis of the NAC gene family in pepino (Solanum muricatum) during drought stress.

Solanum muricatum (Pepino) is an increasingly popular solanaceous crop and is tolerant of drought conditions. In this study, 71 NAC transcription factor family genes of S. muricatum were selected to provide a theoretical basis for subsequent in-depth study of their regulatory roles in the response to biological and abiotic stresses, and were subjected to whole-genome analysis. The NAC sequences obtained by transcriptome sequencing were subjected to bioinformatics prediction and analysis. Three concentration gradient drought stresses were applied to the plants, and the target gene sequences were analyzed by qPCR to determine their expression under drought stress. The results showed that the S. muricatum NAC family contains 71 genes, 47 of which have conserved domains. The protein sequence length, molecular weight, hydrophilicity, aliphatic index and isoelectric point of these transcription factors were predicted and analyzed. Phylogenetic analysis showed that the S. muricatum NAC gene family is divided into seven subfamilies. Some NAC genes of S. muricatum are closely related to the NAC genes of Solanaceae crops such as tomato, pepper and potato. The seedlings of S. muricatum were grown under different gradients of drought stress conditions and qPCR was used to analyze the NAC expression in roots, stems, leaves and flowers. The results showed that 13 genes did not respond to drought stress while 58 NAC genes of S. muricatum that responded to drought stress had obvious tissue expression specificity. The overall expression levels in the root were found to be high. The number of genes at extremely significant expression levels was very large, with significant polarization. Seven NAC genes with significant responses were selected to analyze their expression trend in the different drought stress gradients. It was found that genes with the same expression trend also had the same or part of the same conserved domain. Seven SmNACs that may play an important role in drought stress were selected for NAC amino acid sequence alignment of Solanaceae crops. Four had strong similarity to other Solanaceae NAC amino acid sequences, and SmNAC has high homology with the Solanum pennellii. The NAC transcription factor family genes of S. muricatum showed strong structural conservation. Under drought stress, the expression of NAC transcription factor family genes of S. muricatum changed significantly, which actively responded to and participated in the regulation process of drought stress, thereby laying foundations for subsequent in-depth research of the specific functions of NAC transcription factor family genes of S. muricatum.

Metabolite Analysis of Jerusalem Artichoke (Helianthus tuberosus L.) Seedlings in Response to Polyethylene Glycol-Simulated Drought Stress.

Jerusalem artichokes are a perennial crop with high drought tolerance and high value as a raw material to produce biofuels, functional feed, and food. However, there are few comprehensive metabolomic studies on Jerusalem artichokes under drought conditions. METHODS: Ultra-performance liquid chromatography and tandem mass spectrometry were used to identify differential metabolites in Jerusalem artichoke seedling leaves under polyethylene glycol (PEG) 6000-simulated drought stress at 0, 18, 24, and 36 h. RESULTS: A total of 661 metabolites and 236 differential metabolites were identified at 0 vs. 18, 18 vs. 24, and 24 vs. 36 h. 146 differential metabolites and 56 common were identified and at 0 vs. 18, 24, and 36 h. Kyoto Encyclopedia of Genes and Genomes enrichment identified 236 differential metabolites involved in the biosynthesis of secondary metabolites and amino acids. Metabolites involved in glycolysis, phenolic metabolism, tricarboxylic cycle, glutamate-mediated proline biosynthesis, urea cycle, amino acid metabolism, unsaturated fatty acid biosynthesis, and the met salvage pathway responded to drought stress. CONCLUSION: A metabolic network in the leaves of Jerusalem artichokes under drought stress is proposed. These results will improve understanding of the metabolite response to drought stress in Jerusalem artichokes and develop a foundation for breeding drought-resistant varieties.