Identification of SNPs and Candidate Genes Associated With Salt Tolerance at the Seedling Stage in Cotton (Gossypium hirsutum L.)

Salt tolerance in cotton is highly imperative for improvement in the response to decreasing farmland and soil salinization. However, little is known about the genetic basis underlying salt tolerance in cotton, especially the seedling stage. In this study, we evaluated two salt-tolerance-related traits of a natural population comprising 713 upland cotton (Gossypium hirsutum L.) accessions worldwide at the seedling stage and performed a genome-wide association study (GWAS) to identify marker-trait associations under salt stress using the Illumina Infinium CottonSNP63K array. A total of 23 single nucleotide polymorphisms (SNPs) that represented seven genomic regions on chromosomes A01, A10, D02, D08, D09, D10, and D11 were significantly associated with the two salt-tolerance-related traits, relative survival rate (RSR) and salt tolerance level (STL). Of these, the two SNPs i46598Gh and i47388Gh on D09 were simultaneously associated with the two traits. Based on all loci, we screened 280 possible candidate genes showing different expression levels under salt stress. Most of these genes were involved in transcription factors, transporters and enzymes and were previously reported as being involved in plant salt tolerance, such as NAC, MYB, NXH, WD40, CDPK, LEA, and CIPK. We further validated six putative candidate genes by qRT-PCR and found a differential expression level between salt-tolerant and salt-sensitive varieties. Our findings provide valuable information for enhancing the understanding of complicated mechanisms of salt tolerance in G. hirsutum seedlings and cotton salt tolerance breeding by molecular marker-assisted selection

Identification of a cellular senescence-related-lncRNA (SRlncRNA) signature to predict the overall survival of glioma patients and the tumor immune microenvironment

Background: Gliomas are brain tumors that arise from glial cells, and they are the most common primary intracranial tumors with a poor prognosis. Cellular senescence plays a critical role in cancer, especially in glioma. In this study, we constructed a senescence-related lncRNA (SRlncRNA) signature to assess the prognosis of glioma.Methods: The Cancer Genome Atlas was used to collect SRlncRNA transcriptome profiles and clinical data about glioma. Patients were randomized to training, testing, and whole cohorts. LASSO and Cox regression analyses were employed to construct the SRlncRNA signature, and Kaplan–Meier (K-M) analysis was performed to determine each cohort’s survival. Receiver operating characteristic (ROC) curves were applied to verify the accuracy of this signature. Gene set enrichment analysis was used to visualize functional enrichment (GSEA). The CIBERSORT algorithm, ESTIMATE and TIMER databases were utilized to evaluate the differences in the infiltration of 22 types of immune cells and their association with the signature. RT–qPCR and IHC were used to identify the consistency of the signature in tumor tissue.Results: An SRlncRNA signature consisting of six long non-coding RNAs (lncRNAs) was constructed, and patients were divided into high-risk and low-risk groups by the median of their riskscore. The KM analysis showed that the high-risk group had worse overall survival, and the ROC curve confirmed that the riskscore had more accurate predictive power. A multivariate Cox analysis and its scatter plot with clinical characteristics confirmed the riskscore as an independent risk factor for overall survival. GSEA showed that the GO and KEGG pathways were mainly enriched in the immune response to tumor cells, p53 signaling pathway, mTOR signaling pathway, and Wnt signaling pathway. Further validation also yielded significant differences in the risk signature in terms of immune cell infiltration, which may be closely related to prognostic differences, and qRT–PCR and IHC confirmed the consistency of the expression differences in the major lncRNAs with those in the prediction model.Conclusion Our findings indicated that the SRlncRNA signature might be used as a predictive biomarker and that there is a link between it and immune infiltration. This discovery is consistent with the present categorization system and may open new avenues for research and personalized therapy

Genome sequence of the cultivated cotton <i>Gossypium arboreum</i>

The complex allotetraploid nature of the cotton genome (AADD; 2n = 52) makes genetic, genomic and functional analyses extremely challenging. Here we sequenced and assembled the Gossypium arboreum (AA; 2n = 26) genome, a putative contributor of the A subgenome. A total of 193.6 Gb of clean sequence covering the genome by 112.6-fold was obtained by paired-end sequencing. We further anchored and oriented 90.4% of the assembly on 13 pseudochromosomes and found that 68.5% of the genome is occupied by repetitive DNA sequences. We predicted 41,330 protein-coding genes in G. arboreum. Two whole-genome duplications were shared by G. arboreum and Gossypium raimondii before speciation. Insertions of long terminal repeats in the past 5 million years are responsible for the twofold difference in the sizes of these genomes. Comparative transcriptome studies showed the key role of the nucleotide binding site (NBS)-encoding gene family in resistance to Verticillium dahliae and the involvement of ethylene in the development of cotton fiber cells.Genetics &amp; HereditySCI(E)[email protected]; [email protected]; [email protected]

Conversion Discriminative Analysis on Mild Cognitive Impairment Using Multiple Cortical Features from MR Images

Neuroimaging measurements derived from magnetic resonance imaging provide important information required for detecting changes related to the progression of mild cognitive impairment (MCI). Cortical features and changes play a crucial role in revealing unique anatomical patterns of brain regions, and further differentiate MCI patients from normal states. Four cortical features, namely, gray matter volume, cortical thickness, surface area, and mean curvature, were explored for discriminative analysis among three groups including the stable MCI (sMCI), the converted MCI (cMCI), and the normal control (NC) groups. In this study, 158 subjects (72 NC, 46 sMCI, and 40 cMCI) were selected from the Alzheimer's Disease Neuroimaging Initiative. A sparse-constrained regression model based on the l2-1-norm was introduced to reduce the feature dimensionality and retrieve essential features for the discrimination of the three groups by using a support vector machine (SVM). An optimized strategy of feature addition based on the weight of each feature was adopted for the SVM classifier in order to achieve the best classification performance. The baseline cortical features combined with the longitudinal measurements for 2 years of follow-up data yielded prominent classification results. In particular, the cortical thickness produced a classification with 98.84% accuracy, 97.5% sensitivity, and 100% specificity for the sMCI–cMCI comparison; 92.37% accuracy, 84.78% sensitivity, and 97.22% specificity for the cMCI–NC comparison; and 93.75% accuracy, 92.5% sensitivity, and 94.44% specificity for the sMCI–NC comparison. The best performances obtained by the SVM classifier using the essential features were 5–40% more than those using all of the retained features. The feasibility of the cortical features for the recognition of anatomical patterns was certified; thus, the proposed method has the potential to improve the clinical diagnosis of sub-types of MCI and predict the risk of its conversion to Alzheimer's disease

An Efficient Electrochemical Biosensor to Determine 1,5-Anhydroglucitol with Persimmon-Tannin-Reduced Graphene Oxide-PtPd Nanocomposites

1,5-Anhydroglucitol (1,5-AG) is a sensitive biomarker for real-time detection of diabetes mellitus. In this study, an electrochemical biosensor to specifically detect 1,5-AG levels based on persimmon-tannin-reduced graphene oxide-PtPd nanocomposites (PT-rGO-PtPd NCs), which were modified onto the surface of a screen-printed carbon electrode (SPCE), was designed. The PT-rGO-PtPd NCs were prepared by using PT as the film-forming material and ascorbic acid as the reducing agent. Scanning electron microscopy (SEM), transmission electron microscopy (TEM), ultraviolet–visible spectroscopy (UV–vis), and X-ray diffraction (XRD) spectroscopy analysis were used to characterise the newly synthesised materials. PT-rGO-PtPd NCs present a synergistic effect not only to increase the active surface area to bio-capture more targets, but also to exhibit electrocatalytic efficiency to catalyze the decomposition of hydrogen peroxide (H2O2). A sensitive layer is formed by pyranose oxidase (PROD) attached to the surface of PT-rGO-PtPd NC/SPCE. In the presence of 1,5-AG, PROD catalyzes the oxidization of 1,5-AG to generate 1,5-anhydrofuctose (1,5-AF) and H2O2 which can be decomposed into H2O under the synergistic catalysis of PT-rGO-PtPd NCs. The redox reaction between PT and its oxidative product (quinones, PTox) can be enhanced simultaneously by PT-rGO-PtPd NCs, and the current signal was recorded by the differential pulse voltammetry (DPV) method. Under optimal conditions, our biosensor shows a wide range (0.1–2.0 mg/mL) for 1,5-AG detection with a detection limit of 30 μg/mL (S/N = 3). Moreover, our electrochemical biosensor exhibits acceptable applicability with recoveries from 99.80 to 106.80%. In summary, our study provides an electrochemical method for the determination of 1,5-AG with simple procedures, lower costs, good reproducibility, and acceptable stability

The Effects of Oxidation Temperature on the Microstructure and Photocatalytic Activity of the TiO2 Coating

Titanium coatings were prepared on the surface of 1mm ZrO2 balls by mechanical ball mill, then the coatings were oxidized to photocatalytic TiO2 films at 400 ~ 600 °C. X-Ray Diffraction, Scanning Electron Microscope, Energy Dispersive Spectroscopy and Optical Microscope were used to analyze the microstructure and crystal form of the films. The photocatalytic activity of the samples was also evaluated. After that, the effects of oxidation temperature on the microstructure and photocatalytic activity of the films were discussed. The results show that the fabricated coatings are uneven, with average thickness of 60 μm. In the process of oxidation, oxygen is imported into the inner coatings by the gaps existed in the Ti coatings, which makes the Ti particles oxidize from surface to core, finally the films with TiO2 + Ti composite microstructure are obtained. The films oxidized at 500 °C have the best photocatalytic performance with the degradation rate of methyl orange solution 79.08 %, this owing to the existence of anatase and the TiO2+Ti composite microstructure. The result will provide theoretical basis for the fabrication of efficient photocatalytic film