摘要：
Rice blast is a globally devastating fungal disease that affects the production of rice (Oryza sativa), and the screening of excellent biocontrol strains is an important direction for the biological control of the fungus that causes rice blast disease (Magnaporthe oryzae). The objectives were to obtain strains that were highly antagonistic to rice blast, analyze the genetic information of the antagonistic bacterium YN-917, and explore the resources of its antagonistic gene cluster. The antagonistic bacteria were isolated and identified by the plate confrontation method, morphological observation, physiological and biochemical identification, and molecular biology methods. In addition, the strains were subjected to whole-genome sequencing, and their sequences were analyzed. Strain YN-917 was screened from healthy rice plants of the variety Xiangzaoxian 24, which is susceptible to rice blast, and it inhibited M. oryzae by 72.63% +/- 1.30%. Additionally, the strain had different degrees of inhibitory effects on various plant pathogenic fungi and was highly resistant to stress. The morphological observation, analysis of physiological and biochemical features, 16S rRNA homology analysis, and wholegenome sequencing analysis revealed that the strain YN-917 was Bacillus cereus (GenBank No.: PRJNA687285). The total length of its whole genome was 5326162 bp, and its average G + C content was 35.37%. It was composed of one circular chromosome and one endoplasmic plasmid. There were 5483 genes encoded on average. They included 105 tRNA genes, 42 self-replicating RNA (sRNA), 178 tandem repeat sequences, three prophages, and nine genomic islands. The prediction of antagonistic gene cluster demonstrated that the genome sequence of YN-917 had six secondary metabolic gene biosynthetic clusters, including those for bacteriocins, siderophores, non-ribosomal peptide synthetases (NRPs), and terpene. This study provides a theoretical basis to further explore microbial resources and their metabolic gene clusters for agricultural biological control.
通讯机构：
[Yineng Chen; Guanghui Chen] C;College of Information Science & Engineering, Hunan Women’s University, Changsha, P. R. China<&wdkj&>College of Agronomy, Hunan Agricultural University, Changsha, P. R. China
摘要：
Rice variety identification is important for genetic breeding classification and crop yield estimation. Traditional identification methods are time-consuming and inaccurate. This paper proposes a method for rice variety identification based on the hyperspectral characteristics of leaves. Hyperspectral data of rice leaves were collected using a geophysical spectrometer imaging system. To reduce the redundance among the hyperspectral data and save the identification cost, locality preserving projections (LPP) is first applied to extract low-dimensional representative features from the leaf hyperspectral data. Then, support vector machine (SVM) is combined for conducting the identification of rice varieties. The experimental results show that the identification rate of 10 varieties of early rice was found to be 91.67% and the identification rate of 10 varieties of late rice was 97.33%.
期刊：
International Journal of Molecular Sciences,2023年24(3):2255- ISSN：1422-0067
通讯作者：
Jianhua Zhang<&wdkj&>Nenghui Ye
作者机构：
[Chen, Yinke; Teng, Zhenning; Duan, Meijuan; Meng, Shuan; Ye, Nenghui] Hunan Agr Univ, Coll Agr, Changsha 410128, Peoples R China.;[Teng, Zhenning] Chinese Univ Hong Kong, Shenzhen Res Inst, Shenzhen 518057, Peoples R China.;[Duan, Meijuan; Ye, Nenghui] Hunan Agr Univ, Hunan Prov Key Lab Rice Stress Biol, Changsha 410128, Peoples R China.;[Zhang, Jianhua] Hong Kong Baptist Univ, Dept Biol, Hong Kong 999077, Peoples R China.
通讯机构：
[Jianhua Zhang; Nenghui Ye] A;Authors to whom correspondence should be addressed.<&wdkj&>Department of Biology, Hong Kong Baptist University, Hong Kong 999077, China<&wdkj&>Authors to whom correspondence should be addressed.<&wdkj&>College of Agriculture, Hunan Agricultural University, Changsha 410128, China<&wdkj&>Hunan Provincial Key Laboratory of Rice Stress Biology, Hunan Agricultural University, Changsha 410128, China
摘要：
Light, temperature, water, and fertilizer are arguably the most important environmental factors regulating crop growth and productivity. Environmental stimuli, including low light, extreme temperatures, and water stresses caused by climate change, affect crop growth and production and pose a growing threat to sustainable agriculture. Furthermore, soil salinity is another major environmental constraint affecting crop growth and threatening global food security. The grain filling stage is the final stage of growth and is also the most important stage in cereals, directly determining the grain weight and final yield. However, the grain filling process is extremely vulnerable to different environmental stimuli, especially for inferior spikelets. Given the importance of grain filling in cereals and the deterioration of environmental problems, understanding environmental stimuli and their effects on grain filling constitutes a major focus of crop research. In recent years, significant advances made in this field have led to a good description of the intricate mechanisms by which different environmental stimuli regulate grain filling, as well as approaches to adapt cereals to changing climate conditions and to give them better grain filling. In this review, the current environmental stimuli, their dose-response effect on grain filling, and the physiological and molecular mechanisms involved are discussed. Furthermore, what we can do to help cereal crops adapt to environmental stimuli is elaborated. Overall, we call for future research to delve deeper into the gene function-related research and the commercialization of gene-edited crops. Meanwhile, smart agriculture is the development trend of the future agriculture under environmental stimuli.
摘要：
Gibberellin regulates plant growth, development, and metabolic processes. However, the underlying mechanism of the substantial effect of gibberellin on stem height and secondary metabolites in forage ramie is unclear. Therefore, this study combined transcriptomic and metabolomics analyses to identify the mechanisms regulating growth and secondary metabolite contents in forage ramie following exogenous gibberellin application. Exogenous gibberellin application significantly reduced the lignin content in the leaves but not in the stems. At the same time, gibberellin significantly increased the total flavonoid and chlorogenic acid contents in both the stems and leaves. In addition, 293 differentially expressed genes (DEGs) and 68 differentially expressed metabolites (DEMs) were identified in the leaves. In the stems, 128 DEGs and 41 DEMs were identified. The DEGs PER42, FLS, CYP75A, and PNC1 were up-regulated in the leaves, affecting phenylpropane metabolism. The joint analysis of the DEMs and DEGs revealed that the changes in the DEGs and DEMs in the leaves and stems improved the substrate efficiency in the phenol propane pathway and inhibited lignin synthesis in plants, thus shifting to flavonoid pathway synthesis. In conclusion, gibberellin treatment effectively reduces the lignin content in forage ramie while increasing the flavonoid and chlorogenic acid contents. These findings provide empirical and practical guidance for breeding for forage quality in ramie and the improvement and cultivation control of forage ramie.
作者机构：
[Wu, Ya; Zeng, Zaohai; Xia, Rui; Liu, Yuanlong; He, Yehua; Chen, Chengjie; Xu, Jing; Chen, CJ] South China Agr Univ, Coll Hort, State Key Lab Conservat & Utilizat Subtrop Agrobio, Guangzhou 510640, Guangdong, Peoples R China.;[Zeng, Zaohai; Xia, Rui; Liu, Yuanlong; Chen, Chengjie; Xu, Jing; Chen, CJ] South China Agr Univ, Key Lab Biol & Germplasm Enhancement Hort Crops So, Minist Agr & Rural Affair, Guangzhou 510640, Guangdong, Peoples R China.;[Zeng, Zaohai; Xia, Rui; Liu, Yuanlong; Chen, Chengjie; Xu, Jing; Chen, CJ] South China Agr Univ, Guangdong Lab Lingnan Modern Agr, Guangzhou 510640, Guangdong, Peoples R China.;[Li, Jiawei] Jinan Univ, Guangdong Hongkong Macau Inst CNS Regenerat, Guangdong Key Lab Nonhuman Primate Res, Guangzhou 510632, Guangdong, Peoples R China.;[Wang, Xiao] Henan Univ, Sch Life Sci, State Key Lab Crop Stress Adaptat & Improvement, Henan Joint Int Lab Crop MultiOm Res, Kaifeng 475004, Peoples R China.
通讯机构：
[Chen, CJ; Xia, R ] S;South China Agr Univ, Coll Hort, State Key Lab Conservat & Utilizat Subtrop Agrobio, Guangzhou 510640, Guangdong, Peoples R China.;South China Agr Univ, Key Lab Biol & Germplasm Enhancement Hort Crops So, Minist Agr & Rural Affair, Guangzhou 510640, Guangdong, Peoples R China.;South China Agr Univ, Guangdong Lab Lingnan Modern Agr, Guangzhou 510640, Guangdong, Peoples R China.
关键词：
BSA-seq;TBtools-II;biological big data;plugin
摘要：
Since the official release of the stand-alone bioinformatics toolkit TBtools in 2020, its superior functionality in data analysis has been demonstrated by its widespread adoption by many thousands of users and references in more than 5000 academic articles. Now, TBtools is a commonly used tool in biological laboratories. Over the past 3 years, thanks to invaluable feedback and suggestions from numerous users, we have optimized and expanded the functionality of the toolkit, leading to the development of an upgraded version-TBtools-II. In this upgrade, we have incorporated over 100 new features, such as those for comparative genomics analysis, phylogenetic analysis, and data visualization. Meanwhile, to better meet the increasing needs of personalized data analysis, we have launched the plugin mode, which enables users to develop their own plugins and manage their selection, installation, and removal according to individual needs. To date, the plugin store has amassed over 50 plugins, with more than half of them being independently developed and contributed by TBtools users. These plugins offer a range of data analysis options including co-expression network analysis, single-cell data analysis, and bulked segregant analysis sequencing data analysis. Overall, TBtools is now transforming from a stand-alone software to a comprehensive bioinformatics platform of a vibrant and cooperative community in which users are also developers and contributors. By promoting the theme"one for all, all for one", we believe that TBtools-II will greatly benefit more biological researchers in this big-data era.
通讯机构：
[Huang, H ] H;Hunan Agr Univ, Coll Agron, Changsha 410128, Peoples R China.;Hunan Engn Res Ctr Rice Field Ecol Planting & Bree, Changsha 410128, Peoples R China.
关键词：
Rice;Earthworm;Cadmium contamination;Symbiosis system
摘要：
Currently, the effects of earthworm inoculation on cadmium-contaminated rice field remain unclear. In this study, four treatments were tested, including rice monoculture (CK), earthworm inoculation with low density (L, 30 g/m(2)), middle density (M, 60 g/m(2)), and high density (H, 90 g/m(2)). The pot and field experiment were conducted in Hunan Province, China. In the pot experiment, the H treatment significantly decreased the available cadmium concentration in 0 similar to 20 cm soil by 5.21% similar to 16.51%, and the M treatment significantly decreased in 0 similar to 10 cm soil by 7.29% similar to 8.96%. The H treatment significantly decreased the total cadmium concentration in 0 similar to 5 cm soil by 10.36%. Moreover, the earthworm inoculation treatments significantly reduced cadmium accumulation in rice organs. In the field experiment, the M and H treatment decreased the available cadmium concentration in 0 similar to 20 cm soil by 14.05% similar to 47.52% and the H treatment decreased the total cadmium concentration in 0 similar to 20 cm soil by 0.78% similar to 5.75% although there was no significant difference. Furthermore, the earthworm inoculation treatments significantly decreased cadmium accumulation in part of rice organs. In conclusion, this study recommends that earthworm inoculation is an effective method of controlling cadmium contamination for rice production.
摘要：
High oleic acid oilseed rape is a hot research area in the development of functional oilseed rape. At present, the model of predicting the oleic acid content in rapeseed at the early growth stage based on hyperspectral technology lacks a mechanistic explanation. In this study, based on the data collected at the 5-6 leaf stage of oilseed rape, a one-dimensional linear regression prediction model of the oleic acid content in leaves (x) and the oleic acid content in rapeseed (y) was constructed with the regression equation y = 1.83x + 75.26, and the R-2, RMSE, and RPD of the testing set were 0.96, 0.23%, and 4.86, respectively. Then, a support vector regression prediction model of the spectral standard normal transformed feature parameters and the oleic acid content in leaves was constructed, and the R-2, RMSE, and RPD of the testing set were 0.74, 0.21%, and 2.01, respectively. Finally, the sensitive parameter transfer model for the prediction of "spectral standard normal transform feature-oleic acid content in leaves-oleic acid content in rapeseed" was validated, and the R-2, RMSE, and RPD of the full sample test were 0.71, 0.54%, and 0.54, respectively. The results show that although the accuracy of the prediction model after the introduction of the agronomic parameters was reduced compared with the performance of direct prediction by using spectra, the oleic acid content in oilseed rape leaves, as an important intermediate variable, could better explain the relationship between the reflection spectrum of the leaf and the oleic acid content in rapeseed. This study provides a theoretical basis and technical support for hyperspectral remote sensing technology in the quality prediction of rapeseed.
通讯机构：
[Chunyun Guan; Mei Guan] A;Authors to whom correspondence should be addressed.<&wdkj&>College of Agriculture, Hunan Agricultural University, Hunan Branch of National Oilseed Crops Improvement Center, Southern Regional Collaborative Innovation Center for Grain and Oil Crops in China, Changsha 410128, China
关键词：
high-oleic-acid rapeseed;lncRNA–mRNA;lipid metabolism;seed development
摘要：
A high oleic acid content is considered an essential characteristic in the breeding of high-quality rapeseed in China. Long-chain non-coding RNA (lncRNA) molecules play an important role in the plant’s growth and its response to stress. To better understand the role of lncRNAs in regulating plant reproductive development, we analyzed whole-transcriptome and physiological data to characterize the dynamic changes in lncRNA expression during the four representative times of seed development of high- and low-oleic-acid rapeseed in three regions. We identified 21 and 14 lncRNA and mRNA modules, respectively. These modules were divided into three types related to region, development stages, and material. Next, we analyzed the key modules related to the oil content and the oleic acid, linoleic acid, and linolenic acid contents with physiological data and constructed the key functional network analysis on this basis. Genes related to lipid metabolism, such as 3-ketoacyl-CoA synthase 16 (KCS16) and acyl-CoA:diacylglycerol acyltransferase 1 (DGAT1), were present in the co-expression network, suggesting that the effect of these genes on lipid metabolism might be embodied by the expression of these lncRNAs. Our results provide a fresh insight into region-, development-stage-, and material-biased changes in lncRNA expression in the seeds of Brassica napus. Some of these lncRNAs may participate in the regulatory network of lipid accumulation and metabolism, together with regulated genes. These results may help elucidate the regulatory system of lncRNAs in the lipid metabolism of high-oleic-acid rapeseed seeds.
