Global identification and analysis of long non-coding RNAs in diploid strawberry Fragaria vesca during flower and fruit development

Length distribution of small RNAs derived from lncRNAs. Figure S2. Characterization of strawberry lncRNAs. Figure S3. Heatmaps showing tissue-specific expression patterns of lncRNAs. Figure S4. Expression correlations between lncRNAs and the adjacent PC genes. Figure S5. Negative correlations of lncRNA expression with PC genes across the genome. (PDF 12315 kb

SGR: an online genomic resource for the woodland strawberry

Fragaria vesca, a diploid strawberry species commonly known as the alpine or woodland strawberry, is a versatile experimental plant system and an emerging model for the Rosaceae family. An ancestral F. vesca genome contributed to the genome of the octoploid dessert strawberry (F. ×ananassa), and the extant genome exhibits synteny with other commercially important members of the Rosaceae family such as apple and peach. To provide a molecular description of floral organ and fruit development at the resolution of specific tissues and cell types, RNAs from flowers and early developmental stage fruit tissues of the inbred F. vesca line YW5AF7 were extracted and the resulting cDNA libraries sequenced using an Illumina HiSeq2000. To enable easy access as well as mining of this two-dimensional (stage and tissue) transcriptome dataset, a web-based database, the Strawberry Genomic Resource (SGR), was developed. SGR is a web accessible database that contains sample description, sample statistics, gene annotation, and gene expression analysis. This information can be accessed publicly from a web-based interface at http://bioinformatics.towson.edu/strawberry/Default.aspx . The SGR website provides user friendly search and browse capabilities for all the data stored in the database. Users are able to search for genes using a gene ID or description or obtain differentially expressed genes by entering different comparison parameters. Search results can be downloaded in a tabular format compatible with Microsoft excel application. Aligned reads to individual genes and exon/intron structures are displayed using the genome browser, facilitating gene re-annotation by individual users. The SGR database was developed to facilitate dissemination and data mining of extensive floral and fruit transcriptome data in the woodland strawberry. It enables users to mine the data in different ways to study different pathways or biological processes during reproductive development.https://doi.org/10.1186/1471-2229-13-22

Thioflavin T fluorescence and NMR spectroscopy 1 suggesting a non-G-quadruplex structure for a 2 sodium binding aptamer embedded in DNAzymes

Recently, a Na+-binding aptamer was reported to be embedded in a few RNA-cleaving DNAzymes including NaA43, Ce13d and NaH1. These DNAzymes require Na+ for activity but show no activity in the presence of K+ or other metal ions. Given that DNA can selectively bind K+ by forming a G-quadruplex structure, this work aims to answer whether this Na+ aptamer also uses a G-quadruplex to bind Na+. The Na+ aptamer embedded in Ce13d consists of multiple GG sequences, which is also a pre-requisite for the formation of G4 structures. To delineate the structural differences and similarities between Ce13d and G-quadruplex in terms of metal binding, thioflavin T (ThT) fluorescence spectroscopy, NMR spectroscopy and CD spectroscopy were used. Through comparative ThT fluorescence spectrometry studies, we deciphered that while a control G-quadruplex DNA exhibited notable fluorescence enhancement up to 5 mM K+ with a Kd of 0.52 mM, the Ce13d DNAzyme fluorescence was negligibly perturbed with similar concentrations of K+. Opposed to this, Ce13d displayed specific remarkable fluorescence decrease with low millimolar concentrations of Na+. NMR experiments at two different pH values suggest that Ce13d adopts a significantly different conformation or equilibrium of conformations in the presence of Na+ versus K+ and has a more stable structure in the presence of Na+. Additionally, absence of characteristic peaks expected for a G-quadruplex structure in 1D 1H NMR suggest that G4 is not responsible for the Na+ binding. This theory is confirmed by absence of characteristic peaks in the CD spectra of this sequence. Therefore, we concluded that the aptamer must be selective for Na+ and binds using a structural element that does not contain G4.Natural Sciences and Engineering Research Council of Canada, Discovery Grant 303454

Advanced Glycation End Products-Induced Activation of Keratinocytes: A Mechanism Underlying Cutaneous Immune Response in Psoriasis

Psoriasis is a common inflammatory skin disease, in which epidermal keratinocytes play a vital role in its pathogenesis by acting both as the responder and as the accelerator to the cutaneous psoriatic immune response. Advanced glycation end products (AGEs) are a class of proinflammatory metabolites that are commonly accumulating in cardiometabolic disorders. Recent studies have also observed the increased level of AGEs in the serum and skin of psoriasis patients, but the role of AGEs in psoriatic inflammation has not been well investigated. In the present study, we initially detected abnormal accumulation of AGEs in epidermal keratinocytes of psoriatic lesions collected from psoriasis patients. Furthermore, AGEs promoted the proliferation of keratinocytes via upregulated Keratin 17 (K17)-mediated p27KIP1 inhibition followed by accelerated cell cycle progression. More importantly, AGEs facilitated the production of interleukin-36 alpha (IL-36α) in keratinocytes, which could enhance T helper 17 (Th17) immune response. In addition, the induction of both K17 and IL-36α by AGEs in keratinocytes was dependent on the activation of signal transducer and activator of transcription 1/3 (STAT1/3) signaling pathways. At last, the effects of AGEs on keratinocytes were mediated by the receptor for AGEs (RAGE). Taken together, these findings support that AGEs potentiate the innate immune function of keratinocytes, which contributes to the formation of psoriatic inflammation. Our study implicates AGEs as a potential pathogenic link between psoriasis and cardiometabolic comorbidities

Development and Validation of an Effective CRISPR/Cas9 Vector for Efficiently Isolating Positive Transformants and Transgene-Free Mutants in a Wide Range of Plant Species

The CRISPR/Cas9 technique is a highly valuable tool in creating new materials for both basic and applied researches. Previously, we succeeded in effectively generating mutations in Brassica napus using an available CRISPR/Cas9 vector pKSE401, while isolation of Cas9-free mutants is laborious and inefficient. Here, we inserted a fluorescence tag (sGFP) driven by the constitutive 35S promoter into pKSE401 to facilitate a visual screen of mutants. This modified vector was named pKSE401G and tested in several dicot plant species, including Arabidopsis, B. napus, Fragaria vesca (strawberry), and Glycine max (soybean). Consequently, GFP-positive plants were readily identified through fluorescence screening in all of these species. Among these GFP-positive plants, the average mutation frequency ranged from 20.4 to 52.5% in Arabidopsis and B. napus with stable transformation, and was 90.0% in strawberry and 75.0% in soybean with transient transformation, indicating that the editing efficiency resembles that of the original vector. Moreover, transgene-free mutants were sufficiently identified in Arabidopsis in the T2 generation and B. napus in the T1 generation based on the absence of GFP fluorescence, and these mutants were stably transmissible to next generation without newly induced mutations. Collectively, pKSE401G provides us an effective tool to readily identify positive primary transformants and transgene-free mutants in later generations in a wide range of dicot plant species

Research on Network Security Situation Awareness Based on the LSTM-DT Model

To better understand the behavior of attackers and describe the network state, we construct an LSTM-DT model for network security situation awareness, which provides risk assessment indicators and quantitative methods. This paper introduces the concept of attack probability, making prediction results more consistent with the actual network situation. The model is focused on the problem of the time sequence of network security situation assessment by using the decision tree algorithm (DT) and long short-term memory(LSTM) network. The biggest innovation of this paper is to change the description of the network situation in the original dataset. The original label only has attack and normal. We put forward a new idea which regards attack as a possibility, obtaining the probability of each attack, and describing the network situation by combining the occurrence probability and attack impact. Firstly, we determine the network risk assessment indicators through the dataset feature distribution, and we give the network risk assessment index a corresponding weight based on the analytic hierarchy process (AHP). Then, the stack sparse auto-encoder (SSAE) is used to learn the characteristics of the original dataset. The attack probability can be predicted by the processed dataset by using the LSTM network. At the same time, the DT algorithm is applied to identify attack types. Finally, we draw the corresponding curve according to the network security situation value at each time. Experiments show that the accuracy of the network situation awareness method proposed in this paper can reach 95%, and the accuracy of attack recognition can reach 87%. Compared with the former research results, the effect is better in describing complex network environment problems