Comparative transcriptomics and co-expression networks reveal cultivar-specific molecular signatures associated with reproductive-stage cold stress in rice.

KEY MESSAGE: The resistance of Huaidao5 results from the high constitutive expression of tolerance genes, while that of Huaidao9 is due to the cold-induced resistance in flag leaves and panicles. The regulation mechanism of rice seedlings' cold tolerance is relatively clear, and knowledge of its underlying mechanisms at the reproductive stage is limited. We performed differential expression and co-expression network analyses to transcriptomes from panicle and flag leaf tissues of a cold-tolerant cultivar (Huaidao5), and a sensitive cultivar (Huaidao9), under reproductive-stage cold stress. The results revealed that the expression levels of genes in stress-related pathways such as MAPK signaling pathway, diterpenoid biosynthesis, glutathione metabolism, plant-pathogen interaction and plant hormone signal transduction were constitutively highly expressed in Huaidao5, especially in panicles. Moreover, the Hudaidao5's panicle sample-specific (under cold) module contained some genes related to rice yield, such as GW5L, GGC2, SG1 and CTPS1. However, the resistance of Huaidao9 was derived from the induced resistance to cold in flag leaves and panicles. In the flag leaves, the responses included a series of stress response and signal transduction, while in the panicles nitrogen metabolism was severely affected, especially 66 endosperm-specific genes. Through integrating differential expression with co-expression networks, we predicted 161 candidate genes (79 cold-responsive genes common to both cultivars and 82 cold-tolerance genes associated with differences in cold tolerance between cultivars) potentially affecting cold response/tolerance, among which 85 (52.80%) were known to be cold-related genes. Moreover, 52 (65.82%) cold-responsive genes (e.g., TIFY11C, LSK1 and LPA) could be confirmed by previous transcriptome studies and 72 (87.80%) cold-tolerance genes (e.g., APX5, OsFbox17 and OsSTA109) were located within QTLs associated with cold tolerance. This study provides an efficient strategy for further discovery of mechanisms of cold tolerance in rice.

NRT1.1B mediates rice plant growth and soil microbial diversity under different nitrogen conditions.

Interactions between microorganisms and plants can stimulate plant growth and promote nitrogen cycling. Nitrogen fertilizers are routinely used in agriculture to improve crop growth and yield; however, poor use efficiency impairs the optimal utilization of such fertilizers. Differences in the microbial diversity and plant growth of rice soil under different nitrogen application conditions and the expression of nitrogen-use efficiency-related genes have not been previously investigated. Therefore, this study investigates how nitrogen application and nitrogen-use efficiency-related gene NRT1.1B expression affect the soil microbial diversity and growth indices of two rice varieties, Huaidao 5 and Xinhuai 5. In total, 103,463 and 98,427 operational taxonomic units were detected in the soils of the Huaidao 5 and Xinhuai 5 rice varieties, respectively. The Shannon and Simpson indices initially increased and then decreased, whereas the Chao and abundance-based coverage estimator indices decreased after the application of nitrogen fertilizer. Nitrogen fertilization also reduced soil bacterial diversity and richness, as indicated by the reduced abundances of Azotobacter recorded in the soils of both rice varieties. Nitrogen application initially increased and then decreased the grain number per panicle, yield per plant, root, stem, and leaf nitrogen, total nitrogen content, glutamine synthetase, nitrate reductase, urease, and root activities of both varieties. Plant height showed positive linear trends in response to nitrogen application, whereas thousand-grain weights showed a negative trend. Our findings may be used to optimize nitrogen fertilizer use for rice cultivation and develop crop-variety-specific strategies for nitrogen fertilizer application.

Comparative transcriptome profiling reveals the key genes and molecular mechanisms involved in rice under blast infection.

The aim of this study was to analyze the resistance genes and molecular mechanisms involved in rice blast infection. The contents of seven hormones and eight biochemical indicators in the leaves and spikes were at dynamic levels after inoculation with rice blast strains over time. The mRNA and protein expression of the six genes were consistent with the transcriptome analysis results. In addition, KEGG enrichment analysis showed that Os03g0132000, Os06g0215600, and Os06g0215500 were significantly enriched in the alpha-linolenic acid metabolism KEGG pathway, whereas Os05g0311801 was significantly enriched in the zeatin biosynthesis KEGG pathway. Furthermore, Os03g0180900 and Os09g0439200 were significantly enriched in the plant hormone signal transduction KEGG pathways. Therefore, blast infection could alter the hormones, biochemical indicators, and traits of rice. Moreover, genes including Os03g0132000, Os03g0180900, and Os05g0311801 were identified as rice blast resistance genes, and the mechanism might involve alpha-linolenic acid metabolism, zeatin biosynthesis, and plant hormone signal transduction KEGG pathways.

Predicting in-hospital death in patients with type B acute aortic dissection.

The outcome of patients with acute type B aortic dissection (BAAD) is largely dictated by whether or not the case is "complicated." The purpose of this study was to investigate the risk factors leading to in-hospital death among patients with BAAD and then to develop a predictive model to estimate individual risk of in-hospital death.A total of 188 patients with BAAD were enrolled. Risk factors for in-hospital death were investigated with univariate and multivariable logistic regression analysis. Significant risk factors were used to develop a predictive model.The in-hospital mortality rate was 9% (17 of 188 patients). Univariate analysis revealed 7 risk factors to be statistically significant predictors of in-hospital death (P < .1). In multivariable analysis, the following variables at admission were independently associated with increased in-hospital mortality: hypotension (odds ratio [OR], 4.85; 95% confidence interval [CI], 1.12-18.90; P = .04), ischemic complications (OR, 8.24; 95% CI, 1.25-33.85; P < .001), renal dysfunction (OR, 12.32; 95% CI, 10.63-76.66; P < .001), and neutrophil percentage ≥80% (OR, 5.76; 95% CI, 2.58-12.56; P = .03). Based on these multivariable results, a reliable and simple prediction model was developed, a total score of 4 offered the best point value.Independent risk factors associated with in-hospital death can be predicted in BAAD patients. The prediction model could be used to identify the prognosis for BAAD patients and assist physicians in their choice of management.