Development and application of microsatellite markers in Hippophae rhamnoides subsp. sinensis Rousi (Hippophae rhamnoides L.) based on transcriptome sequencing

Hippophae rhamnoides subsp. sinensis Rousi is a cold- and drought-tolerant pioneer species with significant economic and ecological value. Evaluating its genetic diversity and population structure is of great importance for guiding the development and utilization of resources. In this study, a total of 41,804 SSRs were generated by transcriptome sequencing of Hippophae rhamnoides subsp. sinensis Rousi. Among the different SSR motif types, mononucleotide repeats (26,972) were the most abundant, followed by trinucleotides, tetranucleotides, and pentanucleotides. 200 pairs of SSR primers were selected to detect polymorphisms, of which 15 pairs primers were selected as validated polymorphic SSRs used for genetic diversity and population structure analysis. A total of 63 alleles were identified with 15 pairs primers, with Nei’s genetic diversity index ranged from 0.27 to 0.83 (average: 0.54), and the expected heterozygosity ranged from 0.16 to 0.73 (average: 0.46). The polymorphism information content ranged from 0.23 to 0.81 (average: 0.48). Genetic structure analyses showed that the 10 populations could be broadly categorized into two groups. AMOVA denoted that genetic variations primarily originated from within the populations, with minimal differences observed between the groups, accounting for only 7% of the total genetic variation. This implies that mutation in H. rhamnoides subsp. sinensis Rousi mainly occurred within the populations. The results showed that the 10 populations of H. rhamnoides subsp. sinensis Rousi are rich in genetic diversity, with low levels of population differentiation and a high degree of gene exchange, which should be taken into consideration for the future work of germplasm resource preservation and seedling breeding

Effects of three different probiotics of Tibetan sheep origin and their complex probiotics on intestinal damage, immunity, and immune signaling pathways of mice infected with Clostridium perfringens type C

Tibetan sheep have unique intestinal microorganisms in their intestines that are adapted to the highland alpine and anoxic environment. To further clarify the probiotic properties of Tibetan sheep-derived probiotics, we selected three Tibetan sheep-derived probiotic isolates (Enterococcus faecalis EF1-mh, Bacillus subtilis BS1-ql, and Lactobacillus sakei LS-ql) to investigate the protective mechanisms of monocultures and their complex strains against Clostridium perfringens type C infection in mice. We established a model of C. perfringens type C infection and used histology and molecular biology to analyze the effects and mechanisms of different probiotic treatments on mice after C. perfringens type C infection. After supplementation with either probiotics or complex probiotics, mice were improved in terms of weight reduction and reduced the levels of cytokines in serum and increased the levels of intestinal sIgA, and supplementation with complex probiotics was effective. In addition, both probiotic and complex probiotic supplementation effectively improved the damage of intestinal mucosa and spleen tissue. The relative expressions of Muc 2, Claudin-1, and Occludin genes were increased in the ileum. The three probiotics and the compound probiotics treatment significantly reduced the relative mRNA expression of toll-like/MyD88/NF-κB/MAPK. The effect of probiotic treatment was similar to the results of engramycin treatment, but the effect of engramycin treatment on intestinal sIgA was not significant. Our results clarify the immunomodulatory effects of the three probiotic isolates and the complex probiotics on C. perfringens infection, and the repair of the intestinal mucosal barrier

Nuclear Receptor SHP Activates miR-206 Expression via a Cascade Dual Inhibitory Mechanism

MicroRNAs play a critical role in many essential cellular functions in the mammalian species. However, limited information is available regarding the regulation of miRNAs gene transcription. Microarray profiling and real-time PCR analysis revealed a marked down-regulation of miR-206 in nuclear receptor SHP−/− mice. To understand the regulatory function of SHP with regard to miR-206 gene expression, we determined the putative transcriptional initiation site of miR-206 and also its full length primary transcript using a database mining approach and RACE. We identified the transcription factor AP1 binding sites on the miR-206 promoter and further showed that AP1 (c-Jun and c-Fos) induced miR-206 promoter transactivity and expression which was repressed by YY1. ChIP analysis confirmed the physical association of AP1 (c-Jun) and YY1 with the endogenous miR-206 promoter. In addition, we also identified nuclear receptor ERRγ (NR3B3) binding site on the YY1 promoter and showed that YY1 promoter was transactivated by ERRγ, which was inhibited by SHP (NROB2). ChIP analysis confirmed the ERRγ binding to the YY1 promoter. Forced expression of SHP and AP1 induced miR-206 expression while overexpression of ERRγ and YY1 reduced its expression. The effects of AP1, ERRγ, and YY1 on miR-206 expression were reversed by siRNA knockdown of each gene, respectively. Thus, we propose a novel cascade “dual inhibitory” mechanism governing miR-206 gene transcription by SHP: SHP inhibition of ERRγ led to decreased YY1 expression and the de-repression of YY1 on AP1 activity, ultimately leading to the activation of miR-206. This is the first report to elucidate a cascade regulatory mechanism governing miRNAs gene transcription

Project Gradient Descent Adversarial Attack against Multisource Remote Sensing Image Scene Classification

Deep learning technology (a deeper and optimized network structure) and remote sensing imaging (i.e., the more multisource and the more multicategory remote sensing data) have developed rapidly. Although the deep convolutional neural network (CNN) has achieved state-of-the-art performance on remote sensing image (RSI) scene classification, the existence of adversarial attacks poses a potential security threat to the RSI scene classification task based on CNN. The corresponding adversarial samples can be generated by adding a small perturbation to the original images. Feeding the CNN-based classifier with the adversarial samples leads to the classifier misclassify with high confidence. To achieve a higher attack success rate against scene classification based on CNN, we introduce the projected gradient descent method to generate adversarial remote sensing images. Then, we select several mainstream CNN-based classifiers as the attacked models to demonstrate the effectiveness of our method. The experimental results show that our proposed method can dramatically reduce the classification accuracy under untargeted and targeted attacks. Furthermore, we also evaluate the quality of the generated adversarial images by visual and quantitative comparisons. The results show that our method can generate the imperceptible adversarial samples and has a stronger attack ability for the RSI scene classification

Transcriptomic analysis of drought stress responses of sea buckthorn (Hippophae rhamnoidessubsp. sinensis) by RNA-Seq.

Sea buckthorn is one of the most important eco-economic tree species in China due to its ability to grow and produce acceptable yields under limited water and fertilizer availability. In this study, the differentially expressed genes under drought stress (DS) of sea buckthorn were identified and compared with control (CK) by RNA-Seq. A total of 122,803 unigenes were identified in sea buckthorn, and 70,025 unigenes significantly matched a sequence in at least one of the seven databases. A total of 24,060 (19.59%) unigenes can be assigned to 19 KEGG pathways, and 1,644 unigenes were differentially expressed between DS and CK, of which 519 unigenes were up-regulated and 1,125 unigenes down-regulated. Of the 47 significantly enriched GO terms, 14, 7 and 26 items were related to BP, CC and MF, respectively. KEGG enrichment analysis showed 398 DEGs involved in 97 different pathways, of which 119 DEGs were up-regulated and 279 DEGs were down-regulated under drought stress. In addition, we found 4438 transcriptor factors (TFs) in sea buckthorn, of which 100 were differentially expressed between DS and CK. These results lay a first foundation for further investigations of the very specific functions of these unigenes in sea buckthorn in response to drought stress

The characteristics of intestinal flora of Tibetan sheep in different regions at high altitude were revealed based on metagenomic technique

Tibetan sheep play a vital role in the livelihoods of herders and are an important part of the ecosystem of the Tibetan Plateau. In order to study the characteristics of the gut microorganisms of Tibetan sheep at high altitude, this study employed macrogenomic techniques to analyse the diversity and differences in the gut flora of Tibetan sheep in different regions of high altitude and high cold. The results demonstrated that at the phylum level, the dominant phylum in the ileo-cecum segment of Tibetan sheep in Qilian, Henan and Gonghe counties was identical, namely Euryarchaeota, Firmicutes and Ascomycota. At the level of the archaebacterial genus, the dominant bacteria of the ileocecal segment of Tibetan sheep in Qilian County, Henan County and Gonghe County were Methanobrevibacter. At the level of bacterial genus, the dominant bacteria of Tibetan sheep ileocecal in Qilian County and Henan County were Bacteroides, while in Gonghe County, the dominant bacteria were Bifidobacterium. At the level of fungal genus, there were notable differences in the abundance of Tibetan sheep ileocecal genus across different regions. However, the abundance of cecum genus exhibited a more consistent trend across regions. From the perspective of functional prediction, the metabolic pathways enriched in the intestinal segments of Tibetan sheep in different regions were found to be identical, with the relative abundance of each functional gene also being essentially uniform. This result will provide a foundation for further research on the mechanism of action of gut microbes in ruminants at high altitude and alpine regions

Correlation of HrANR genes and flavonoid accumulation with drought resistance in sea buckthorn (Hippophaerhamnoides subsp. sinensis)

Anthocyanidin reductase is one of the key enzyme involved in the synthesis of flavonoids. In order to explore the structure of ANR gene, ANR enzyme expression pattern and flavonoid content under drought stress and their correlation, a HrANR gene identified from RNA-seq data of sea buckthorn was screened and analyzed by bioinformatics soft, the expression patterns of HrANR gene in different tissues and of flavonoid contents in leaves were performed. The results were as follows: (1) The ORF of HrANR gene was 1 017 bp, which encoded 338 amino acids. It was a stable hydrophilic protein, and the homologous protein had significant family and genus characteristics. (2) HrANR gene was expressed in roots, stems and leaves of sea buckthorn under drought stress, but the expression trends were different, with an increase followed by a decrease and then an increase in roots, a continuous decrease in stems, and an increase followed by a continuous decrease in leaves. (3) The flavonoid contents in leaves of sea buckthorn under different levels of stress showed a trend that first increased continuously and then decreased slightly, increased to the highest point after rehydration. The above results indicated that the expression of HrANR gene and the changes of flavonoid content were closely related to the drought resistance of sea buckthorn. The flavonoid content in leaves was positively correlated with drought stress at the beginning of drought stress and negatively correlated with drought stress under severe stress. (4) Leaf expression, stem expression and flavonoid content of HrANR gene were negatively correlated (Pleaf= -0.751, Pstem= -0.934) and root expression was positively correlated with flavonoid content (Proot= 0.444). The above results indicate that the expression of HrANR genes and changes of flavonoid content in sea buckthorn are closely related to drought resistance, and it provides a reference for elucidating the drought resistance mechanism of sea buckthorn

Multi-Block Mixed Sample Semi-Supervised Learning for SAR Target Recognition

In recent years, synthetic aperture radar (SAR) automatic target recognition has played a crucial role in multiple fields and has received widespread attention. Compared with optical image recognition with massive annotation data, lacking sufficient labeled images limits the performance of the SAR automatic target recognition (ATR) method based on deep learning. It is expensive and time-consuming to annotate the targets for SAR images, while it is difficult for unsupervised SAR target recognition to meet the actual needs. In this situation, we propose a semi-supervised sample mixing method for SAR target recognition, named multi-block mixed (MBM), which can effectively utilize the unlabeled samples. During the data preprocessing stage, a multi-block mixed method is used to interpolate a small part of the training image to generate new samples. Then, the new samples are used to improve the recognition accuracy of the model. To verify the effectiveness of the proposed method, experiments are carried out on the moving and stationary target acquisition and recognition (MSTAR) data set. The experimental results fully demonstrate that the proposed MBM semi-supervised learning method can effectively address the problem of annotation insufficiency in SAR data sets and can learn valuable information from unlabeled samples, thereby improving the recognition performance