Plant sugar metabolism, transport and signalling in challenging environments

Uncovering waterlogging-responsive genes in cucumber through machine learning and differential gene correlation analysis

As climate change intensifies, the frequency and severity of waterlogging are expected to increase, necessitating a deeper understanding of the cucumber response to this stress. In this study, three public RNA-seq datasets (PRJNA799460, PRJNA844418, and PRJNA678740) comprising 36 samples were analyzed. Various feature selection algorithms including Uncertainty, Relief, SVM (Support Vector Machine), Correlation, and logistic least absolute shrinkage, and selection operator (LASSO) were performed to identify the most significant genes related to the waterlogging stress response. These feature selection techniques, which have different characteristics, were used to reduce the complexity of the data and thereby identify the most significant genes related to the waterlogging stress response. Uncertainty, Relief, SVM, Correlation, and LASSO identified 4, 4, 10, 21, and 13 genes, respectively. Differential gene correlation analysis (DGCA) focusing on the 36 selected genes identified changes in correlation patterns between the selected genes under waterlogged versus control conditions, providing deeper insights into the regulatory networks and interactions among the selected genes. DGCA revealed significant changes in the correlation of 13 genes between control and waterlogging conditions. Finally, we validated 13 genes using the Random Forest (RF) classifier, which achieved 100% accuracy and a 1.0 Area Under the Curve (AUC) score. The SHapley Additive exPlanations (SHAP) values clearly showed the significant impact of LOC101209599, LOC101217277, and LOC101216320 on the model's predictive power. In addition, we employed the Boruta as a wrapper feature selection method to further validate our gene selection strategy. Eight of the 13 genes were common across the four feature weighting algorithms, LASSO, DGCA, and Boruta, underscoring the robustness and reliability of our gene selection strategy. Notably, the genes LOC101209599, LOC101217277, and LOC101216320 were among genes identified by multiple feature selection methods from different categories (filtering, wrapper, and embedded). Pathways associated with these specific genes play a pivotal role in regulating stress tolerance, root development, nutrient absorption, sugar metabolism, gene expression, protein degradation, and calcium signaling. These intricate regulatory mechanisms are crucial for cucumbers to adapt effectively to waterlogging conditions. These findings provide valuable insights for uncovering targets in breeding new cucumber varieties with enhanced stress tolerance.

Auxin regulates bulbil initiation by mediating sucrose metabolism in Lilium lancifolium

Lily bulbils, which serve as advantageous axillary organs for vegetative propagation, have not been extensively studied in terms of the mechanism of bulbil initiation. The functions of auxin and sucrose metabolism have been implicated in axillary organ development, but their relationship in regulating bulbil initiation remains unclear. In this study, exogenous indole-3-acetic acid (IAA) treatment increased the endogenous auxin levels at leaf axils and significantly decreased bulbil number, whereas treatment with the auxin polar transport inhibitor N-1-naphthylphthalamic acid (NPA), which resulted in a low auxin concentration at leaf axils, stimulated bulbil initiation and increased bulbil number. A low level of auxin caused by NPA spraying or silencing of auxin biosynthesis genes YUCCA FLAVIN MONOOXYGENASE-LIKE 6 (LlYUC6) and TRYPTOPHAN AMINOTRANSFERASERELATED 1 (LlTAR1) facilitated sucrose metabolism by activating the expression of SUCROSE SYNTHASES 1 (LlSusy1) and CELL WALL INVERTASE 2 (LlCWIN2), resulting in enhanced bulbil initiation. Silencing LlSusy1 or LlCWIN2 hindered bulbil initiation. Moreover, the transcription factor BASIC HELIX-LOOP-HELIX 35 (LlbHLH35) directly bound the promoter of LlSusy1, but not the promoter of LlCWIN2, and activated its transcription in response to the auxin content, bridging the gap between auxin and sucrose metabolism. In conclusion, our results reveal that an LlbHLH35-LlSusy1 module mediates auxin-regulated sucrose metabolism during bulbil initiation.

Unveiling the mechanism of source-sink rebalancing in cucumber-pumpkin heterografts: the buffering roles of rootstock cotyledon

Grafting onto pumpkin rootstock is widely applied in cucumber production to improve growth and yield, as well as to overcome soil-borne diseases and enhance resistance to abiotic stresses. In this study, we constructed the cucumber-pumpkin heterografts with the one-cotyledon grafting method, and examined the effects of heterografting on biomass allocation and sugar partitioning, with cucumber and pumpkin self-grafts used as control. Compared with cucumber self-grafts, heterografting onto pumpkin rootstock promoted photosynthesis in cucumber scion, and led to higher sucrose contents in the 1st true leaf (source) and newly emerged leaf (sink). Thereby, the scion part of heterografts accumulated more biomass than cucumber self-grafts. In contrast, when compared to pumpkin self-grafts, grafting with cucumber scion reduced root vigor and biomass but promoted cotyledon growth in pumpkin rootstock. The roots (sink) of heterografts contained less sucrose and hexoses, and showed reduced sucrose synthase (SuSy) and hexokinase (HXK) activities. However, the rootstock cotyledon (source) contained more sucrose and starch, and showed higher activities of HXK, cell-wall invertase (CWIN), and enzymes for starch synthesis and degradation. Furthermore, removal or shade of rootstock cotyledon led to reduced growth of root and scion. Silencing of CmoMEX1a gene in rootstock cotyledon inhibited maltose export and reduced root growth of heterografts. These results indicated that rootstock cotyledon, especially its starch content, played a buffering role in the growth regulation of cucumber-pumpkin heterografts. Taken together, our results provided a major contribution to our understanding of source-sink sugar partitioning and scion-rootstock growth balancing in cucumber-pumpkin heterografts.

Comparison of the transcriptome and metabolome of wheat (Triticum aestivum L.) proteins content during grain formation provides insight

Introduction

Wheat is a food crop with a large global cultivation area, and the content and quality of wheat glutenin accumulation are important indicators of the quality of wheat flour.

Methods

To elucidate the gene expression regulation and metabolic characteristics related to the gluten content during wheat grain formation, transcriptomic and metabolomic analyses were performed for the high gluten content of the Xinchun 26 cultivar and the low proteins content of the Xinchun 34 cultivar at three periods (7 d, 14 d and 21 d) after flowering.

Results

Transcriptomic analysis revealed that 5573 unique differentially expressed genes (DEGs) were divided into two categories according to their expression patterns during the three periods. The metabolites detected were mainly divided into 12 classes. Lipid and lipid-like molecule levels and phenylpropanoid and polyketide levels were the highest, and the difference analysis revealed a total of 10 differentially regulated metabolites (DRMs) over the three periods. Joint analysis revealed that the DEGs and DRMs were significantly enriched in starch and sucrose metabolism; the citrate cycle; carbon fixation in photosynthetic organisms; and alanine, aspartate and glutamate metabolism pathways. The genes and contents of the sucrose and gluten synthesis pathways were analysed, and the correlation between gluten content and its related genes was calculated. Based on weighted correlation network analysis (WGCNA), by constructing a coexpression network, a total of 5 specific modules and 8 candidate genes that were strongly correlated with the three developmental stages of wheat grain were identified.

Discussion

This study provides new insights into the role of glutenin content in wheat grain formation and reveals potential regulatory pathways and candidate genes involved in this developmental process.