Integrated Transcriptomic and Metabolomics Analyses Reveal Molecular Responses to Cold Stress in Coconut (Cocos nucifera L.) Seedlings.

Coconut is an important tropical and subtropical fruit and oil crop severely affected by cold temperature, limiting its distribution and application. Thus, studying its low-temperature reaction mechanism is required to expand its cultivation range. We used growth morphology and physiological analyses to characterize the response of coconuts to 10, 20, and 30 d of low temperatures, combined with transcriptome and metabolome analysis. Low-temperature treatment significantly reduced the plant height and dry weight of coconut seedlings. The contents of soil and plant analyzer development (SPAD), soluble sugar (SS), soluble protein (SP), proline (Pro), and malondialdehyde (MDA) in leaves were significantly increased, along with the activities of superoxide dismutase (SOD), peroxidase (POD), and catalase (CAT), and the endogenous hormones abscisic acid (ABA), auxin (IAA), zeatin (ZR), and gibberellin (GA) contents. A large number of differentially expressed genes (DEGs) (9968) were detected under low-temperature conditions. Most DEGs were involved in mitogen-activated protein kinase (MAPK) signaling pathway-plant, plant hormone signal transduction, plant-pathogen interaction, biosynthesis of amino acids, amino sugar and nucleotide sugar metabolism, carbon metabolism, starch and sucrose metabolism, purine metabolism, and phenylpropanoid biosynthesis pathways. Transcription factors (TFs), including WRKY, AP2/ERF, HSF, bZIP, MYB, and bHLH families, were induced to significantly differentially express under cold stress. In addition, most genes associated with major cold-tolerance pathways, such as the ICE-CBF-COR, MAPK signaling, and endogenous hormones and their signaling pathways, were significantly up-regulated. Under low temperatures, a total of 205 differentially accumulated metabolites (DAMs) were enriched; 206 DAMs were in positive-ion mode and 97 in negative-ion mode, mainly including phenylpropanoids and polyketides, lipids and lipid-like molecules, benzenoids, organoheterocyclic compounds, organic oxygen compounds, organic acids and derivatives, nucleosides, nucleotides, and analogues. Comprehensive metabolome and transcriptome analysis revealed that the related genes and metabolites were mainly enriched in amino acid, flavonoid, carbohydrate, lipid, and nucleotide metabolism pathways under cold stress. Together, the results of this study provide important insights into the response of coconuts to cold stress, which will reveal the underlying molecular mechanisms and help in coconut screening and breeding.

Identification and expression analysis of histone modification gene (HM) family during somatic embryogenesis of oil palm.

BACKGROUND: Oil palm (Elaeis guineensis, Jacq.) is an important vegetable oil-yielding plant. Somatic embryogenesis is a promising method to produce large-scale elite clones to meet the demand for palm oil. The epigenetic mechanisms such as histone modifications have emerged as critical factors during somatic embryogenesis. These histone modifications are associated with the regulation of various genes controlling somatic embryogenesis. To date, none of the information is available on the histone modification gene (HM) family in oil palm. RESULTS: We reported the identification of 109 HM gene family members including 48 HMTs, 27 HDMs, 13 HATs, and 21 HDACs in the oil palm genome. Gene structural and motif analysis of EgHMs showed varied exon-intron organization and with conserved motifs among them. The identified 109 EgHMs were distributed unevenly across 16 chromosomes and displayed tandem duplication in oil palm genome. Furthermore, relative expression analysis showed the differential expressional pattern of 99 candidate EgHM genes at different stages (non-embryogenic, embryogenic, somatic embryo) of somatic embryogenesis process in oil palm, suggesting the EgHMs play vital roles in somatic embryogenesis. Our study laid a foundation to understand the regulatory roles of several EgHM genes during somatic embryogenesis. CONCLUSIONS: A total of 109 histone modification gene family members were identified in the oil palm genome via genome-wide analysis. The present study provides insightful information regarding HM gene's structure, their distribution, duplication in oil palm genome, and also their evolutionary relationship with other HM gene family members in Arabidopsis and rice. Finally, our study provided an essential role of oil palm HM genes during somatic embryogenesis process.

The oil palm R2R3-MYB subfamily genes EgMYB111 and EgMYB157 improve multiple abiotic stress tolerance in transgenic Arabidopsis plants.

KEY MESSAGE: We found that overexpression of EgMYB111 and EgMYB157 genes positively regulate the abiotic stress tolerance. MYB family genes are well-known regulators in modulating the abiotic stress-responsive mechanisms in plants. However, lesser is known about the functional roles of oil palm MYB genes. Previously, we found that oil palm MYB genes such as EgMYB111 and EgMYB157 were significantly up-regulated under salinity, cold, and drought stress conditions. In this study, we over-expressed EgMYB111 and EgMYB157 genes separately in Arabidopsis plants. The transgenic Arabidopsis plants expressing EgMYB111 have shown improved tolerance to salinity, cold and drought stress conditions, whereas transgenic Arabidopsis plants expressing EgMYB157 dispalyed improved tolerance to cold and drought stress conditions only. Various biochemical analyses also revealed significant improvement of antioxidant enzyme activities, photosynthetic pigments, net photosynthetic rate, stomatal conductance, and intercellular CO2 concentration in transgenic plants compared to wild-type plants under cold, drought, and salinity stress conditions. Significant up-regulation of various known stress marker genes such as RD22, RD29A, RAB18, COR47, ABA1, ABI1, HAB1 was also noticed in EgMYB111 and EgMYB157 expressing transgenic plants compared to wild-type plants under cold, drought, and salinity stress conditions. Taken together, over-expression of EgMYB111 and/or EgMYB157 significantly improve abiotic tolerance in transgenic Arabidopsis plants, indicating that EgMYB111 and EgMYB157 are the potential candidates for developing abiotic stress-tolerant crops in near future.

Integrative Omics Analysis of Three Oil Palm Varieties Reveals (Tanzania × Ekona) TE as a Cold-Resistant Variety in Response to Low-Temperature Stress.

Oil palm (Elaeis guineensis Jacq.) is an economically important tropical oil crop widely cultivated in tropical zones worldwide. Being a tropical crop, low-temperature stress adversely affects the oil palm. However, integrative leaf transcriptomic and proteomic analyses have not yet been conducted on an oil palm crop under cold stress. In this study, integrative omics transcriptomic and iTRAQ-based proteomic approaches were employed for three oil palm varieties, i.e., B × E (Bamenda × Ekona), O × G (E. oleifera × Elaeis guineensis), and T × E (Tanzania × Ekona), in response to low-temperature stress. In response to low-temperature stress at (8 °C) for 5 days, a total of 5175 up- and 2941 downregulated DEGs in BE-0_VS_BE-5, and a total of 3468 up- and 2443 downregulated DEGs for OG-0_VS_OG-5, and 3667 up- and 2151 downregulated DEGs for TE-0_VS_TE-5 were identified. iTRAQ-based proteomic analysis showed 349 up- and 657 downregulated DEPs for BE-0_VS_BE-5, 372 up- and 264 downregulated DEPs for OG-0_VS_OG-5, and 500 up- and 321 downregulated DEPs for TE-0_VS_TE-5 compared to control samples treated at 28 °C and 8 °C, respectively. The KEGG pathway correlation of oil palm has shown that the metabolic synthesis and biosynthesis of secondary metabolites pathways were significantly enriched in the transcriptome and proteome of the oil palm varieties. The correlation expression pattern revealed that TE-0_VS_TE-5 is highly expressed and BE-0_VS_BE-5 is suppressed in both the transcriptome and proteome in response to low temperature. Furthermore, numerous transcription factors (TFs) were found that may regulate cold acclimation in three oil palm varieties at low temperatures. Moreover, this study identified proteins involved in stresses (abiotic, biotic, oxidative, and heat shock), photosynthesis, and respiration in iTRAQ-based proteomic analysis of three oil palm varieties. The increased abundance of stress-responsive proteins and decreased abundance of photosynthesis-related proteins suggest that the TE variety may become cold-resistant in response to low-temperature stress. This study may provide a basis for understanding the molecular mechanism for the adaptation of oil palm varieties in response to low-temperature stress in China.

Genome-Wide Identification of the DOF Gene Family Involved in Fruitlet Abscission in Areca catechu L.

Fruitlet abscission frequently occurs in Areca catechu L. and causes considerable production loss. However, the inducement mechanism of fruitlet abscission remains mysterious. In this study, we observed that the cell architecture in the abscission zone (AZ) was distinct with surrounding tissues, and varied obviously before and after abscission. Transcriptome analysis of the "about-to-abscise" and "non-abscised" AZs were performed in A. catechu, and the genes encoding the plant-specific DOF (DNA-binding with one finger) transcription factors showed a uniform up-regulation in AZ, suggesting a role of the DOF transcription in A. catechu fruitlet abscission. In total, 36 members of the DOF gene family distributed in 13 chromosomes were identified from the A. catechu genome. The 36 AcDOF genes were classified into nine subgroups based on phylogenic analysis. Six of them showed an AZ-specific expression pattern, and their expression levels varied according to the abscission process. In total, nine types of phytohormone response cis-elements and five types of abiotic stress related cis-elements were identified in the promoter regions of the AcDOF genes. In addition, histochemical staining showed that lignin accumulation of vascular bundles in AZ was significantly lower than that in pedicel and mesocarp, indicating the specific characteristics of the cell architecture in AZ. Our data suggests that the DOF transcription factors might play a role in fruitlet abscission regulation in A. catechu.

Combining sequence and network information to enhance protein-protein interaction prediction.

BACKGROUND: Protein-protein interactions (PPIs) are of great importance in cellular systems of organisms, since they are the basis of cellular structure and function and many essential cellular processes are related to that. Most proteins perform their functions by interacting with other proteins, so predicting PPIs accurately is crucial for understanding cell physiology. RESULTS: Recently, graph convolutional networks (GCNs) have been proposed to capture the graph structure information and generate representations for nodes in the graph. In our paper, we use GCNs to learn the position information of proteins in the PPIs networks graph, which can reflect the properties of proteins to some extent. Combining amino acid sequence information and position information makes a stronger representation for protein, which improves the accuracy of PPIs prediction. CONCLUSION: In previous research methods, most of them only used protein amino acid sequence as input information to make predictions, without considering the structural information of PPIs networks graph. We first time combine amino acid sequence information and position information to make representations for proteins. The experimental results indicate that our method has strong competitiveness compared with several sequence-based methods.

Background-free upconversion-encoded microspheres for mycotoxin detection based on a rapid visualization method.

Methods for detecting mycotoxins are very important because of the great health hazards of mycotoxins. However, there is a high background and low signal-to-noise ratio in real-time sensing, and therefore it is difficult to meet the fast, accurate, and convenient requirements for control of food quality. Here we constructed a quantitative fluorescence image analysis based on multicolor upconversion nanocrystal (UCN)-encoded microspheres for detection of ochratoxin A and zearalenone. The background-free encoding image signal of UCN-doped microspheres was captured by fluorescence microscopy under near-infrared excitation, whereas the detection image signal of phycoerythrin-labeled secondary antibodies conjugated to the microspheres was captured under blue light excitation. We custom-wrote an algorithm to analyze the two images for the same sample in 10 s, and only the gray value in the red channel of the secondary probe confirmed the quantity. The results showed that this novel detection platform performed feasible and reliable fluorescence image measurements by this method. Additionally, the limit of detection of was 0.34721 ng/mL for ochratoxin A and 0.41162 ng/mL for zearalenone. We envision that this UCN encoding strategy will be usefully applied for fast, accurate, and convenient testing of multiple food contaminants to ensure the safety of the food.

Using deep reinforcement learning to speed up collective cell migration.

BACKGROUND: Collective cell migration is a significant and complex phenomenon that affects many basic biological processes. The coordination between leader cell and follower cell affects the rate of collective cell migration. However, there are still very few papers on the impacts of the stimulus signal released by the leader on the follower. Tracking cell movement using 3D time-lapse microscopy images provides an unprecedented opportunity to systematically study and analyze collective cell migration. RESULTS: Recently, deep reinforcement learning algorithms have become very popular. In our paper, we also use this method to train the number of cells and control signals. By experimenting with single-follower cell and multi-follower cells, it is concluded that the number of stimulation signals is proportional to the rate of collective movement of the cells. Such research provides a more diverse approach and approach to studying biological problems. CONCLUSION: Traditional research methods are always based on real-life scenarios, but as the number of cells grows exponentially, the research process is too time consuming. Agent-based modeling is a robust framework that approximates cells to isotropic, elastic, and sticky objects. In this paper, an agent-based modeling framework is used to establish a simulation platform for simulating collective cell migration. The goal of the platform is to build a biomimetic environment to demonstrate the importance of stimuli between the leading and following cells.

Attention-based recurrent neural network for influenza epidemic prediction.

BACKGROUND: Influenza is an infectious respiratory disease that can cause serious public health hazard. Due to its huge threat to the society, precise real-time forecasting of influenza outbreaks is of great value to our public. RESULTS: In this paper, we propose a new deep neural network structure that forecasts a real-time influenza-like illness rate (ILI%) in Guangzhou, China. Long short-term memory (LSTM) neural networks is applied to precisely forecast accurateness due to the long-term attribute and diversity of influenza epidemic data. We devise a multi-channel LSTM neural network that can draw multiple information from different types of inputs. We also add attention mechanism to improve forecasting accuracy. By using this structure, we are able to deal with relationships between multiple inputs more appropriately. Our model fully consider the information in the data set, targetedly solving practical problems of the Guangzhou influenza epidemic forecasting. CONCLUSION: We assess the performance of our model by comparing it with different neural network structures and other state-of-the-art methods. The experimental results indicate that our model has strong competitiveness and can provide effective real-time influenza epidemic forecasting.

Enhanced photocatalytic activity of perovskite NaNbO3 by oxygen vacancy engineering.

NaNbO3 with oxygen vacancies has been successfully synthesized through a well controllable solid-state reaction, whose photocatalytic performances have been prominently enhanced by almost 2.4 times compared with just annealed NaNbO3 (the control sample). When oxygen vacancies were introduced into the perovskite, the color of NaNbO3 turned black and the band gap was decreased, resulting in its remarkable absorption under visible light, and its higher symmetry also favors the electron transfer. More importantly, oxygen vacancies lead to larger specific surface area and higher charge density, which play non-negligible roles in improving the visible-light-activities. These encouraging findings prove that oxygen vacancy engineering is a feasible and general strategy to improve the photocatalytic performances of perovskite oxides, which will promote many related applications.

Nano-Ferroelectric for High Efficiency Overall Water Splitting under Ultrasonic Vibration.

Piezocatalysis, converting mechanical vibration into chemical energy, has emerged as a promising candidate for water-splitting technology. However, the efficiency of the hydrogen production is quite limited. We herein report well-defined 10 nm BaTiO3 nanoparticles (NPs) characterized by a large electro-mechanical coefficient which induces a high piezoelectric effect. Atomic-resolution high angle annular dark field scanning transmission electron microscopy (HAADF-STEM) and scanning probe microscopy (SPM) suggests that piezoelectric BaTiO3 NPs display a coexistence of multiple phases with low energy barriers and polarization anisotropy which results in a high electro-mechanical coefficient. Landau free energy modeling also confirms that the greatly reduced polarization anisotropy facilitates polarization rotation. Employing the high piezoelectric properties of BaTiO3 NPs, we demonstrate an overall water-splitting process with the highest hydrogen production efficiency hitherto reported, with a H2 production rate of 655 µmol g-1 h-1 , which could rival excellent photocatalysis system. This study highlights the potential of piezoelectric catalysis for overall water splitting.

Collagen intrafibrillar mineralization as a result of the balance between osmotic equilibrium and electroneutrality.

Mineralization of fibrillar collagen with biomimetic process-directing agents has enabled scientists to gain insight into the potential mechanisms involved in intrafibrillar mineralization. Here, by using polycation- and polyanion-directed intrafibrillar mineralization, we challenge the popular paradigm that electrostatic attraction is solely responsible for polyelectrolyte-directed intrafibrillar mineralization. As there is no difference when a polycationic or a polyanionic electrolyte is used to direct collagen mineralization, we argue that additional types of long-range non-electrostatic interaction are responsible for intrafibrillar mineralization. Molecular dynamics simulations of collagen structures in the presence of extrafibrillar polyelectrolytes show that the outward movement of ions and intrafibrillar water through the collagen surface occurs irrespective of the charges of polyelectrolytes, resulting in the experimentally verifiable contraction of the collagen structures. The need to balance electroneutrality and osmotic equilibrium simultaneously to establish Gibbs-Donnan equilibrium in a polyelectrolyte-directed mineralization system establishes a new model for collagen intrafibrillar mineralization that supplements existing collagen mineralization mechanisms.

Novel lead-free ferroelectric film by ultra-small Ba0.8Sr0.2TiO3 nanocubes assembled for a large electrocaloric effect.

A giant electrocaloric effect (ECE) can be achieved in ferroelectric thin films, which demonstrates the applications of thin films in alternative cooling. However, electrocaloric thin films fabricated by conventional techniques, such as the pulsed laser deposition or sol-gel methods, may be limited by high costs, low yield and their dependence on substrates. In this study, we present a new bottom-up strategy to construct electrocaloric Ba0.8Sr0.2TiO3 thin films by assembling precisely designed building blocks of ferroelectric nanocubes, which is supported by detailed structural characterization. Moreover, it is found that our assembled Ba0.8Sr0.2TiO3 films differ remarkably from both individual Ba0.8Sr0.2TiO3 NPs and bulk Ba0.8Sr0.2TiO3 ceramics in terms of new collective ferroelectric properties, including superior and diffused permittivity constants and polarization-electric field loops. Benefiting from these unique ferroelectric properties, a giant ECE (9.1 K) over a broad temperature range (20 °C to 60 °C) is achieved, which is very large in the lead-free oxide film. Clearly, this bottom-up strategy provides a promising pathway for developing high electrocaloric effect devices.

Silver-modified nanosized ferroelectrics as a novel photocatalyst.

Monodispersed ferroelectric BaTiO3 nanoparticles are synthesized as a model system to investigate the effect of ferroelectricity on a photocatalytic process. The results demonstrate that ferroelectricity can directly affect the photocatalytic activity due to promotion of the separation of photo-excited carriers by spontaneous polarization in ferroelectric materials. Moreover, Ag nanoparticles are attached on these BaTiO3 to further improve the photocatalytic property.

AUX/LAX genes encode a family of auxin influx transporters that perform distinct functions during Arabidopsis development.

Auxin transport, which is mediated by specialized influx and efflux carriers, plays a major role in many aspects of plant growth and development. AUXIN1 (AUX1) has been demonstrated to encode a high-affinity auxin influx carrier. In Arabidopsis thaliana, AUX1 belongs to a small multigene family comprising four highly conserved genes (i.e., AUX1 and LIKE AUX1 [LAX] genes LAX1, LAX2, and LAX3). We report that all four members of this AUX/LAX family display auxin uptake functions. Despite the conservation of their biochemical function, AUX1, LAX1, and LAX3 have been described to regulate distinct auxin-dependent developmental processes. Here, we report that LAX2 regulates vascular patterning in cotyledons. We also describe how regulatory and coding sequences of AUX/LAX genes have undergone subfunctionalization based on their distinct patterns of spatial expression and the inability of LAX sequences to rescue aux1 mutant phenotypes, respectively. Despite their high sequence similarity at the protein level, transgenic studies reveal that LAX proteins are not correctly targeted in the AUX1 expression domain. Domain swapping studies suggest that the N-terminal half of AUX1 is essential for correct LAX localization. We conclude that Arabidopsis AUX/LAX genes encode a family of auxin influx transporters that perform distinct developmental functions and have evolved distinct regulatory mechanisms.

Exploiting transcriptome data for the development and characterization of gene-based SSR markers related to cold tolerance in oil palm (Elaeis guineensis).

BACKGROUND: The oil palm (Elaeis guineensis, 2n = 32) has the highest oil yield of any crop species, as well as comprising the richest dietary source of provitamin A. For the tropical species, the best mean growth temperature is about 27°C, with a minimal growth temperature of 15°C. Hence, the plantation area is limited into the geographical ranges of 10°N to 10°S. Enhancing cold tolerance capability will increase the total cultivation area and subsequently oil productivity of this tropical species. Developing molecular markers related to cold tolerance would be helpful for molecular breeding of cold tolerant Elaeis guineensis. RESULTS: In total, 5791 gene-based SSRs were identified in 51,452 expressed sequences from Elaeis guineensis transcriptome data: approximately one SSR was detected per 10 expressed sequences. Of these 5791 gene-based SSRs, 916 were derived from expressed sequences up- or down-regulated at least two-fold in response to cold stress. A total of 182 polymorphic markers were developed and characterized from 442 primer pairs flanking these cold-responsive SSR repeats. The polymorphic information content (PIC) of these polymorphic SSR markers across 24 lines of Elaeis guineensis varied from 0.08 to 0.65 (mean = 0.31 ± 0.12). Using in-silico mapping, 137 (75.3%) of the 182 polymorphic SSR markers were located onto the 16 Elaeis guineensis chromosomes. Total coverage of 473 Mbp was achieved, with an average physical distance of 3.4 Mbp between adjacent markers (range 96 bp - 20.8 Mbp). Meanwhile, Comparative analysis of transcriptome under cold stress revealed that one ICE1 putative ortholog, five CBF putative orthologs, 19 NAC transcription factors and four cold-induced orhologs were up-regulated at least two fold in response to cold stress. Interestingly, 5' untranslated region of both Unigene21287 (ICE1) and CL2628.Contig1 (NAC) both contained an SSR markers. CONCLUSIONS: In the present study, a series of SSR markers were developed based on sequences differentially expressed in response to cold stress. These EST-SSR markers would be particularly useful for gene mapping and population structure analysis in Elaeis guineensis. Meanwhile, the EST-SSR loci were inducible expressed in response to low temperature, which may have potential application in identifying trait-associated markers in oil palm in the future.

ASP: Learn a Universal Neural Solver!

Applying machine learning to combinatorial optimization problems has the potential to improve both efficiency and accuracy. However, existing learning-based solvers often struggle with generalization when faced with changes in problem distributions and scales. In this paper, we propose a new approach called ASP: Adaptive Staircase Policy Space Response Oracle to address these generalization issues and learn a universal neural solver. ASP consists of two components: Distributional Exploration, which enhances the solver's ability to handle unknown distributions using Policy Space Response Oracles, and Persistent Scale Adaption, which improves scalability through curriculum learning. We have tested ASP on several challenging COPs, including the traveling salesman problem, the vehicle routing problem, and the prize collecting TSP, as well as the real-world instances from TSPLib and CVRPLib. Our results show that even with the same model size and weak training signal, ASP can help neural solvers explore and adapt to unseen distributions and varying scales, achieving superior performance. In particular, compared with the same neural solvers under a standard training pipeline, ASP produces a remarkable decrease in terms of the optimality gap with 90.9% and 47.43% on generated instances and real-world instances for TSP, and a decrease of 19% and 45.57% for CVRP.

Bi-DexHands: Towards Human-Level Bimanual Dexterous Manipulation.

Achieving human-level dexterity in robotics remains a critical open problem. Even simple dexterous manipulation tasks pose significant difficulties due to the high number of degrees of freedom and the need for cooperation among heterogeneous agents (e.g., finger joints). While some researchers have utilized reinforcement learning (RL) to control a single hand in manipulating objects, tasks that require coordinated bimanual cooperation are still under-explored due to the fewer suitable environments, which can result in difficulties and sub-optimal performance. To address these challenges, we introduce Bi-DexHands, a simulator with two dexterous hands featuring 20 bimanual manipulation tasks and thousands of target objects, designed to match various levels of human motor skills based on cognitive science research. We developed Bi-DexHands in Issac Gym, enabling highly efficient RL training at over 30,000 frames per second using a single NVIDIA RTX 3090. Based on Bi-DexHands, we present a comprehensive evaluation of popular RL algorithms in different settings, including single-agent/multi-agent RL, offline RL, multi-task RL, and meta RL. Our findings show that on-policy algorithms, such as PPO, can master simple manipulation tasks that correspond to those of 48-month-old babies, such as catching a flying object or opening a bottle. Furthermore, multi-agent RL can improve the ability to perform manipulations that require skilled bimanual cooperation, such as lifting a pot or stacking blocks. Despite achieving success in individual tasks, current RL algorithms struggle to learn multiple manipulation skills in most multi-task and few-shot learning scenarios. This highlights the need for further research and development within the RL community.

Widely targeted metabolomics combined with E-tongue and E-nose reveal dynamic changes of tender coconut water in responses to the infection of Ceratocystis paradoxa.

Ceratocystis paradoxa is a major cause of postharvest disease in tender coconuts worldwide. We conducted a comprehensive study using widely targeted metabolomics, electronic tongue (E-tongue), and electronic nose (E-nose) analyses to investigate the impacts of C. paradoxa invasion on the quality of tender coconut water (TCW) from fresh control (FC), uninoculated (UN), skin-inoculated (SI), and deep-inoculated (DI) nuts. DI exhibited significantly higher taste indicators associated with bitterness, saltiness, astringency aftertaste, and bitter aftertaste, as well as odor sensor values related to various compounds such as long-chain alkanes, hydrides, methane, organic sulfides, etc. Invasion of C. paradoxa into the endosperm altered the flavor characteristics of TCW mainly through the modulation of carbohydrate and secondary metabolite pathways. Furthermore, significant correlations were observed between the differentially expressed flavorful metabolites and the sensor indicators of the E-nose and E-tongue. These findings offer valuable insights into understanding the impact of C. paradoxa infection on coconuts.

Combined transcriptome and metabolome analysis of sugar and fatty acid of aromatic coconut and non-aromatic coconut in China.

Sugar and fatty acid content are among the important factors that contribute to the intensity of flavor in aromatic coconut. Gaining a comprehensive understanding of the sugar and fatty acid metabolites in the flesh of aromatic coconuts, along with identifying the key synthetic genes, is of significant importance for improving the development of desirable character traits in these coconuts. However, the related conjoint analysis of metabolic targets and molecular synthesis mechanisms has not been carried out in aromatic coconut until now. UPLC-MS/MS combined with RNA-Seq were performed in aromatic coconut (AC) and non-aromatic coconut (NAC) meat at 7, 9 and 11 months. The results showed that D-fructose in AC coconut meat was 3.48, 2.56 and 3.45 fold higher than that in NAC coconut meat. Similarly, D-glucose in AC coconut meat was 2.48, 2.25 and 3.91 fold higher than that in NAC coconut meat. The NAC coconut meat showed a 1.22-fold rise in the content of lauric acid compared to the AC coconut meat when it reached 11 months of age. Myristic acid content in NAC coconut meat was 1.47, 1.44 and 1.13 fold higher than that in AC coconut meat. The palmitic acid content in NAC coconut meat was 1.62 and 1.34 fold higher than that in AC coconut meat. The genes SPS, GAE, GALE, GLCAK, UGE, UGDH, FBP, GMLS, PFK, GPI, RHM, ACC, FabF, FatA, FabG, and FabI exhibited a negative correlation with D-fructose (r = -0.81) and D-glucose (r = -0.99) contents, while showing a positive correlation (r = 0.85-0.96) with lauric acid and myristic acid. Furthermore, GALE, GLCAK, FBP, GMLS, and ACC displayed a positive correlation (r = 0.83-0.94) with palmitic acid content. The sugar/organic acid ratio exhibited a positive correlation with SPS, GAE, UGE, FabF, FabZ and FabI.