A MYB-related transcription factor from sheepgrass, LcMYB2, promotes seed germination and root growth under drought stress.

BACKGROUND: Drought is one of the most serious factors limiting plant growth and production. Sheepgrass can adapt well to various adverse conditions, including drought. However, during germination, sheepgrass young seedlings are sensitive to these adverse conditions. Therefore, the adaptability of seedlings is very important for plant survival, especially in plants that inhabit grasslands or the construction of artificial grassland. RESULTS: In this study, we found a sheepgrass MYB-related transcription factor, LcMYB2 that is up-regulated by drought stress and returns to a basal level after rewatering. The expression of LcMYB2 was mainly induced by osmotic stress and was localized to the nucleus. Furthermore, we demonstrate that LcMYB2 promoted seed germination and root growth under drought and ABA treatments. Additionally, we confirmed that LcMYB2 can regulate LcDREB2 expression in sheepgrass by binding to its promoter, and it activates the expression of the osmotic stress marker genes AtDREB2A, AtLEA14 and AtP5CS1 by directly binding to their promoters in transgenic Arabidopsis. CONCLUSIONS: Based on these results, we propose that LcMYB2 improves plant drought stress tolerance by increasing the accumulation of osmoprotectants and promoting root growth. Therefore, LcMYB2 plays pivotal roles in plant responses to drought stress and is an important candidate for genetic manipulation to create drought-resistant crops, especially during seed germination.

Construction of a high-density genetic map using specific-locus amplified fragments in sorghum.

BACKGROUND: Sorghum is mainly used as a human food and beverage source, playing an important role in the production of ethanol and other bio-industrial products. Thus it is regarded as a model crop for energy plants. Genetic map construction is the foundation for marker-assisted selection and gene cloning. So far several sorghum linkage maps have been reported using different kinds of molecular markers. However marker numbers and chromosome coverage are limited. As a result, it is difficult to get consistent results and the maps are hard to unify. In the present study, the genomes of 130 individuals consisting an F2 population together with their parents were surveyed using a high-throughput sequencing technique. A high-density linkage map was constructed using specific-locus amplified fragments (SLAF) markers. This map can provide information and serve as a reference for effective gene exploration, and for marker assisted-breeding program. RESULTS: A high-throughput sequencing method was adopted to screen SLAF markers with 130 F2 individuals from a cross between a grain sorghum variety, J204, and a sweet sorghum variety, Keter. In the present study, 52,928 suitable SLAF markers out of 43,528,021 pair-end reads were chosen to conduct genetic map construction, 12.0% of which were polymorphic. Among the 6353 polymorphic SLAF markers, 5829 (91.8%) were successfully genotyped in the F2 mapping population. Finally 2246 SLAF markers were obtained to construct a high-density genetic linkage map. The total distance of linkage map covering all 10 chromosomes was 2158.1 cM. The largest gap on each chromosome was 10.2 cM on average. The proportion of gaps less than and/or equal to 5.0 cM was averagely 98.1%. The markers on each chromosome ranged from 123 (chromosome 9) to 315 (chromosome 4) with a mean value of 224.6, the distance between adjacent markers ranged from 0.6 (chromosome 10) to 1.3 cM (chromosome 9) with an average distance of only 0.98 cM. CONCLUSION: A high density sorghum genetic map was constructed in this study. The total length was 2158.1 cM covering all 10 chromosomes with a total number of 2246 SLAF markers. The construction of this map can provide detailed information for accurate gene localization and cloning and application of marker-assisted breeding.

LcSAIN1, a novel salt-induced gene from sheepgrass, confers salt stress tolerance in transgenic Arabidopsis and rice.

Previously, we identified >1,500 genes that were induced by high salt stress in sheepgrass (Leymus chinensis, Gramineae: Triticeae) when comparing the changes in their transcription levels in response to high salt stress by next-generation sequencing. Among the identified genes, a gene of unknown function (designated as Leymus chinensis salt-induced 1, LcSAIN1) showed a high sequence identity to its homologs from wheat, Hordeum vulgare and Oryza sativa, but LcSAIN1 and its homologs produce hypothetical proteins with no conserved functional domains. Transcription of the LcSAIN1 gene was up-regulated by various stresses. The overexpression of LcSAIN1 in Arabidopsis and rice increased the greening rate of cotyledons, the fresh weight, root elongation, plant height and the plant survival rate when compared with control plants and conferred a tolerance against salt stress. Subcellular localization analysis indicated that LcSAIN1 is localized predominantly in the nucleus. Our results show that the LcSAIN1 gene might play an important positive modulation role in increasing the expression of transcription factors (MYB2 and DREB2A) and functional genes (P5CS and RAB18) in transgenic plants under salt stress and that it augments stress tolerance through the accumulation of compatible solutes (proline and soluble sugar) and the alleviation of changes in reactive oxygen species. The LcSAIN1 gene could be a potential resource for engineering salinity tolerance in important crop species.

Drought resistance index screening and evaluation of lettuce under water deficit conditions on the basis of morphological and physiological differences.

Introduction: Water is one of the important factors affecting the yield of leafy vegetables. Lettuce, as a widely planted vegetable, requires frequent irrigation due to its shallow taproot and high leaf evaporation rate. Therefore, screening drought-resistant genotypes is of great significance for lettuce production. Methods: In the present study, significant variations were observed among 13 morphological and physiological traits of 42 lettuce genotypes under normal irrigation and water-deficient conditions. Results: Frequency analysis showed that soluble protein (SP) was evenly distributed across six intervals. Principal component analysis (PCA) was conducted to transform the 13 indexes into four independent comprehensive indicators with a cumulative contribution ratio of 94.83%. The stepwise regression analysis showed that root surface area (RSA), root volume (RV), belowground dry weight (BDW), soluble sugar (SS), SP, and leaf relative water content (RWC) could be used to evaluate and predict the drought resistance of lettuce genotypes. Furthermore, the drought resistance ranks of the genotypes were similar according to the drought resistance comprehensive evaluation value (D value), comprehensive drought resistance coefficient (CDC), and weight drought resistance coefficient (WDC). The cluster analysis enabled the division of the 42 genotypes into five drought resistance groups; among them, variety Yidali151 was divided into group I as a strongly drought-resistant variety, group II included 6 drought-resistant genotypes, group III included 16 moderately drought-resistant genotypes, group IV included 12 drought-sensitive genotypes, and group V included 7 highly drought-sensitive genotypes. Moreover, a representative lettuce variety was selected from each of the five groups to verify its water resistance ability under water deficit conditions. In the drought-resistant variety, it was observed that stomatal density, superoxide anion (O2.-wfi2) production rate, and malondialdehyde (MDA) content exhibited a low increase rate, while catalase (CAT), superoxide dismutase (SOD), and that peroxidase (POD) activity exhibited a higher increase than in the drought-sensitive variety. Discussion: In summary, the identified genotypes are important because their drought-resistant traits can be used in future drought-resistant lettuce breeding programs and water-efficient cultivation.

Genistein: Therapeutic and Preventive Effects, Mechanisms, and Clinical Application in Digestive Tract Tumor.

Genistein is one of the numerous recognized isoflavones that may be found in a variety of soybeans and soy products, including tofu and tofu products. The chemical name for genistein is 4', 5, 7-trihydroxyisoflavone, and it is found in plants. In recent years, the scientific world has become more interested in genistein because of its possible therapeutic effects on many forms of cancer. It has been widely investigated for its anticancer properties. The discovery of genistein's mechanism of action indicates its potential for apoptosis induction and cell cycle arrest in gastrointestinal cancer, especially gastric and colorectal cancer. Genistein's pharmacological activities as determined by the experimental studies presented in this review lend support to its use in the treatment of gastrointestinal cancer; however, additional research is needed in the future to determine its efficacy, safety, and the potential for using nanotechnology to increase bioavailability and therapeutic efficacy.

Multispectral Drone Imagery and SRGAN for Rapid Phenotypic Mapping of Individual Chinese Cabbage Plants.

The phenotypic parameters of crop plants can be evaluated accurately and quickly using an unmanned aerial vehicle (UAV) equipped with imaging equipment. In this study, hundreds of images of Chinese cabbage (Brassica rapa L. ssp. pekinensis) germplasm resources were collected with a low-cost UAV system and used to estimate cabbage width, length, and relative chlorophyll content (soil plant analysis development [SPAD] value). The super-resolution generative adversarial network (SRGAN) was used to improve the resolution of the original image, and the semantic segmentation network Unity Networking (UNet) was used to process images for the segmentation of each individual Chinese cabbage. Finally, the actual length and width were calculated on the basis of the pixel value of the individual cabbage and the ground sampling distance. The SPAD value of Chinese cabbage was also analyzed on the basis of an RGB image of a single cabbage after background removal. After comparison of various models, the model in which visible images were enhanced with SRGAN showed the best performance. With the validation set and the UNet model, the segmentation accuracy was 94.43%. For Chinese cabbage dimensions, the model was better at estimating length than width. The R2 of the visible-band model with images enhanced using SRGAN was greater than 0.84. For SPAD prediction, the R2 of the model with images enhanced with SRGAN was greater than 0.78. The root mean square errors of the 3 semantic segmentation network models were all less than 2.18. The results showed that the width, length, and SPAD value of Chinese cabbage predicted using UAV imaging were comparable to those obtained from manual measurements in the field. Overall, this research demonstrates not only that UAVs are useful for acquiring quantitative phenotypic data on Chinese cabbage but also that a regression model can provide reliable SPAD predictions. This approach offers a reliable and convenient phenotyping tool for the investigation of Chinese cabbage breeding traits.

Major energy plants and their potential for bioenergy development in China.

China is rich in energy plant resources. In this article, 64 plant species are identified as potential energy plants in China. The energy plant species include 38 oilseed crops, 5 starch-producing crops, 3 sugar-producing crops and 18 species for lignocellulosic biomass. The species were evaluated on the basis of their production capacity and their resistance to salt, drought, and/or low temperature stress. Ten plant species have high production and/or stress resistance and can be potentially developed as the candidate energy plants. Of these, four species could be the primary energy plants in China: Barbados nut (Jatropha curcas L.), Jerusalem artichoke (Helianthus tuberosus L.), sweet sorghum (Sorghum bicolor L.) and Chinese silvergrass (Miscanthus sinensis Anderss.). We discuss the use of biotechnological techniques such as genome sequencing, molecular markers, and genetic transformation to improve energy plants. These techniques are being used to develop new cultivars and to analyze and manipulate genetic variation to improve attributes of energy plants in China.

Fecal microbiota transplantation alters the susceptibility of obese rats to type 2 diabetes mellitus.

Obesity is one of the susceptibility factors for type 2 diabetes (T2DM), both of which could accelerate the aging of the body and bring many hazards. A causal relationship is present between intestinal microbiota and body metabolism, but how the microbiota play a role in the progression of obesity to T2DM has not been elucidated. In this study, we transplanted healthy or obese-T2DM intestinal microbiota to ZDF and LZ rats, and used 16S rRNA and targeted metabonomics to evaluate the directional effect of the microbiota on the susceptibility of obese rats to T2DM. The glycolipid metabolism phenotype could be changed bidirectionally in obese rats instead of in lean ones. One possible mechanism is that the microbiota and metabolites alter the structure of the intestinal tract, and improve insulin and leptin resistance through JAK2 / IRS / Akt pathway. It is worth noting that 7 genera, such as Lactobacillus, Clostridium and Roche, can regulate 15 metabolites, such as 3-indolpropionic acid, acetic acid and docosahexaenoic acid, and have a significant improvement on glycolipid metabolism phenotype. Attention to intestinal homeostasis may be the key to controlling obesity and preventing T2DM.

Combining Next Generation Sequencing with Bulked Segregant Analysis to Fine Map a Stem Moisture Locus in Sorghum (Sorghum bicolor L. Moench).

Sorghum is one of the most promising bioenergy crops. Stem juice yield, together with stem sugar concentration, determines sugar yield in sweet sorghum. Bulked segregant analysis (BSA) is a gene mapping technique for identifying genomic regions containing genetic loci affecting a trait of interest that when combined with deep sequencing could effectively accelerate the gene mapping process. In this study, a dry stem sorghum landrace was characterized and the stem water controlling locus, qSW6, was fine mapped using QTL analysis and the combined BSA and deep sequencing technologies. Results showed that: (i) In sorghum variety Jiliang 2, stem water content was around 80% before flowering stage. It dropped to 75% during grain filling with little difference between different internodes. In landrace G21, stem water content keeps dropping after the flag leaf stage. The drop from 71% at flowering time progressed to 60% at grain filling time. Large differences exist between different internodes with the lowest (51%) at the 7th and 8th internodes at dough stage. (ii) A quantitative trait locus (QTL) controlling stem water content mapped on chromosome 6 between SSR markers Ch6-2 and gpsb069 explained about 34.7-56.9% of the phenotypic variation for the 5th to 10th internodes, respectively. (iii) BSA and deep sequencing analysis narrowed the associated region to 339 kb containing 38 putative genes. The results could help reveal molecular mechanisms underlying juice yield of sorghum and thus to improve total sugar yield.