RESUMEN

BACKGROUND: Rice is a staple crop for over half of the global population, but soil salinization poses a significant threat to its production. As a type of polyamine, spermidine (Spd) has been shown to reduce stress-induced damage in plants, but its specific role and mechanism in protecting rice roots under salt stress require further investigation. RESULTS: This study suggested spermidine (Spd) mitigates salt stress on rice root growth by enhancing antioxidant enzyme activity and reducing peroxide levels. Transcriptomic analysis showed that salt stress caused 333 genes to be upregulated and 1,765 to be downregulated. However, adding Spd during salt treatment significantly altered this pattern: 2,298 genes were upregulated and 844 were downregulated, which indicated Spd reverses some transcriptional changes caused by salt stress. KEGG pathway analysis suggested that Spd influenced key signaling pathways, including MAPK signaling, plant hormone signal transduction, and phenylalanine metabolism. Additionally, the bZIP transcription factor OsbZIP73 was upregulated after Spd treatment, which is confirmed by Western blot. Further insights into the interaction between OsbZIP73 and Spd were gained through fluorescence polarization experiments, showing that Spd enhances protein OsbZIP73's affinity for RNA. Functional enrichment analyses revealed that OsPYL1, OsSPARK1, and various SAUR family genes involved in Spd-affected pathways. The presence of G/A/C-box elements in these genes suggests they are potential targets for OsbZIP73. CONCLUSIONS: Our findings suggest a strategy of using spermidine as a chemical alleviator for salt stress and provide insights into the regulatory function of OsbZIP73 in mitigating salt stress in rice roots.

Asunto(s)

RESUMEN

Soybean (Glycine max) and mung bean (Vigna radiata) are key legumes with global importance, but their mechanisms for coping with cold stress-a major challenge in agriculture-have not been thoroughly investigated, especially in a comparative study. This research aimed to fill this gap by examining how these two major legumes respond differently to cold stress and exploring the role of uniconazole, a potential stress mitigator. Our comprehensive approach involved transcriptomic and metabolomic analyses, revealing distinct responses between soybean and mung bean under cold stress conditions. Notably, uniconazole was found to significantly enhance cold tolerance in mung bean by upregulating genes associated with photosynthesis, while its impact on soybean was either negligible or adverse. To further understand the molecular interactions, we utilized advanced machine learning algorithms for protein structure prediction, focusing on photosynthetic pathways. This enabled us to identify LOC106780309 as a direct binding target for uniconazole, confirmed through isothermal titration calorimetry. This research establishes a new comparative approach to explore how soybean and mung bean adapt to cold stress, offers key insights to improve the hardiness of legumes against environmental challenges, and contributes to sustainable agricultural practices and food security.

RESUMEN

Cold stress poses a significant threat to the quality and productivity of lychee (Litchi chinensis Sonn.). While previous research has extensively explored the genomic and transcriptomic responses to cold stress in lychee, the translatome has not been thoroughly investigated. This study delves into the translatomic landscape of the 'Xiangjinfeng' cultivar under both control and low-temperature conditions using RNA sequencing and ribosome profiling. We uncovered a significant divergence between the transcriptomic and translatomic responses to cold exposure. Additionally, bioinformatics analyses underscored the crucial role of codon occupancy in lychee's cold tolerance mechanisms. Our findings reveal that the modulation of translation via codon occupancy is a vital strategy to abiotic stress. Specifically, the study identifies ribosome stalling, particularly at the E site AAU codon, as a key element of the translation machinery in lychee's response to cold stress. This work enhances our understanding of the molecular dynamics of lychee's reaction to cold stress and emphasizes the essential role of translational regulation in the plant's environmental adaptability.

Asunto(s)

RESUMEN

Genome size variation and evolutionary forces behind have been long pursued in flowering plants. The genus Oryza, consisting of approximately 25 wild species and two cultivated rice, harbors eleven extant genome types, six of which are diploid (AA, BB, CC, EE, FF, and GG) and five of which are tetraploid (BBCC, CCDD, HHJJ, HHKK, and KKLL). To obtain the most comprehensive knowledge of genome size variation in the genus Oryza, we performed flow cytometry experiments and estimated genome sizes of 166 accessions belonging to 16 non-AA genome Oryza species. k-mer analyses were followed to verify the experimental results of the two accessions for each species. Our results showed that genome sizes largely varied fourfold in the genus Oryza, ranging from 279 Mb in Oryza brachyantha (FF) to 1,203 Mb in Oryza ridleyi (HHJJ). There was a 2-fold variation (ranging from 570 to 1,203 Mb) in genome size among the tetraploid species, while the diploid species had 3-fold variation, ranging from 279 Mb in Oryza brachyantha (FF) to 905 Mb in Oryza australiensis (EE). The genome sizes of the tetraploid species were not always two times larger than those of the diploid species, and some diploid species even had larger genome sizes than those of tetraploids. Nevertheless, we found that genome sizes of newly formed allotetraploids (BBCC-) were almost equal to totaling genome sizes of their parental progenitors. Our results showed that the species belonging to the same genome types had similar genome sizes, while genome sizes exhibited a gradually decreased trend during the evolutionary process in the clade with AA, BB, CC, and EE genome types. Comparative genomic analyses further showed that the species with different rice genome types may had experienced dissimilar amplification histories of retrotransposons, resulting in remarkably different genome sizes. On the other hand, the closely related rice species may have experienced similar amplification history. We observed that the contents of transposable elements, long terminal repeats (LTR) retrotransposons, and particularly LTR/Gypsy retrotransposons varied largely but were significantly correlated with genome sizes. Therefore, this study demonstrated that LTR retrotransposons act as an active driver of genome size variation in the genus Oryza.

RESUMEN

Photoperiod sensitivity is a dominant determinant for the phase transition in cereal crops. CCT (CONSTANS, CO-like, and TOC1) transcription factors (TFs) are involved in many physiological functions including the regulation of the photoperiodic flowering. However, the functional roles of CCT TFs have not been elucidated in the wild progenitors of crops. In this study, we identified 41 CCT TFs, including 19 CMF, 17 COL, and five PRR TFs in Oryza rufipogon, the presumed wild ancestor of Asian cultivated rice. There are thirty-eight orthologous CCT genes in Oryza sativa, of which ten pairs of duplicated CCT TFs are shared with O. rufipogon. We investigated daily expression patterns, showing that 36 OrCCT genes exhibited circadian rhythmic expression. A total of thirteen OrCCT genes were identified as putative flowering suppressors in O. rufipogon based on rhythmic and developmental expression patterns and transgenic phenotypes. We propose that OrCCT08, OrCCT24, and OrCCT26 are the strong functional alleles of rice DTH2, Ghd7, and OsPRR37, respectively. The SD treatment at 80 DAG stimulated flowering of the LD-grown O. rufipogon plants. Our results further showed that the nine OrCCT genes were significantly downregulated under the treatment. Our findings would provide valuable information for the construction of photoperiodic flowering regulatory network and functional characterization of the CCT TFs in both O. rufipogon and O. sativa.

RESUMEN

PURPOSE: To develop and validate an MRI-based radiomics model in differentiation between sinonasal primary lymphomas and squamous cell carcinomas (SCCs). MATERIALS AND METHODS: One-hundred-and-fifty-four patients were enrolled (74 individuals with SCCs and 80 with lymphomas). After feature analysis and feature selection with variance threshold and least absolute shrinkage and selection operator (LASSO) methods, an MRI-based radiomics model with the support vector machine (SVM) classifier was constructed in differentiation between lymphomas and SCCs. Areas under the receiver operating characteristic curves (AUCs) of the MRI-based radiomics model were compared with those of radiologists using Delong test. RESULTS: Five features (T1 original shape Compactness2, T1 wavelet-HHH first-order Total Energy, T2 wavelet-HLH GLCM Informational Measure of Correlation1, T1 wavelet-LHL GLCM Inverse Variance and T1 square GLRLM Long Run Low Gray Level Emphasis) were finally selected in the radiomics model. The AUC values in differentiation between lymphomas and SCCs were 0.94 for the training dataset and 0.85 for the validation dataset, respectively. For all the patient datasets, the AUC values of radiomics model, readers 1, 2 and 3 were 0.92, 0.76, 0.77 and 0.80, respectively. For the validation datasets, no significant difference was found between the AUCs of the radiomics model and those of the three radiologist (P = 0.459, 0.469, 0.738 for radiologist 1, 2 and 3, respectively). CONCLUSION: An MRI-based radiomics model can help to differentiate sinonasal lymphomas from SCCs with high accuracy.

Asunto(s)

RESUMEN

BACKGROUND: Laryngeal and hypopharyngeal squamous cell carcinoma (LHSCC) with thyroid cartilage invasion are considered T4 and need total laryngectomy. However, the accuracy of preoperative diagnosis of thyroid cartilage invasion remains lower. Therefore, the purpose of this study was to assess the potential of computed tomography (CT)-based radiomics features in the prediction of thyroid cartilage invasion from LHSCC. METHODS: A total of 265 patients with pathologically proven LHSCC were enrolled in this retrospective study (86 with thyroid cartilage invasion and 179 without invasion). Two head and neck radiologists evaluated the thyroid cartilage invasion on CT images. Radiomics features were extracted from venous phase contrast-enhanced CT images. The least absolute shrinkage and selection operator (LASSO) and logistic regression (LR) method were used for dimension reduction and model construction. In addition, the support vector machine-based synthetic minority oversampling (SVMSMOTE) algorithm was adopted to balance the dataset and a new LR-SVMSMOTE model was constructed. The performance of the radiologist and the two models were evaluated with receiver operating characteristic (ROC) curves and compared using the DeLong test. RESULTS: The areas under the ROC curves (AUCs) in the prediction of thyroid cartilage invasion from LHSCC for the LR-SVMSMOTE model, LR model, and radiologist were 0.905 [95% confidence interval (CI): 0.863 to 0.937)], 0.876 (95%CI: 0.830 to 0.913), and 0.721 (95%CI: 0.663-0.774), respectively. The AUCs of both models were higher than that of the radiologist assessment (all P < 0.001). There was no significant difference in predictive performance between the LR-SVMSMOTE and LR models (P = 0.05). CONCLUSIONS: Models based on CT radiomic features can improve the accuracy of predicting thyroid cartilage invasion from LHSCC and provide a new potentially noninvasive method for preoperative prediction of thyroid cartilage invasion from LHSCC.

Asunto(s)