SGCP: a spectral self-learning method for clustering genes in co-expression networks.

BACKGROUND: A widely used approach for extracting information from gene expression data employs the construction of a gene co-expression network and the subsequent computational detection of gene clusters, called modules. WGCNA and related methods are the de facto standard for module detection. The purpose of this work is to investigate the applicability of more sophisticated algorithms toward the design of an alternative method with enhanced potential for extracting biologically meaningful modules. RESULTS: We present self-learning gene clustering pipeline (SGCP), a spectral method for detecting modules in gene co-expression networks. SGCP incorporates multiple features that differentiate it from previous work, including a novel step that leverages gene ontology (GO) information in a self-leaning step. Compared with widely used existing frameworks on 12 real gene expression datasets, we show that SGCP yields modules with higher GO enrichment. Moreover, SGCP assigns highest statistical importance to GO terms that are mostly different from those reported by the baselines. CONCLUSION: Existing frameworks for discovering clusters of genes in gene co-expression networks are based on relatively simple algorithmic components. SGCP relies on newer algorithmic techniques that enable the computation of highly enriched modules with distinctive characteristics, thus contributing a novel alternative tool for gene co-expression analysis.

Transcriptomic meta-analysis to identify potential antifungal targets in Candida albicans.

BACKGROUND: Candida albicans is a fungal pathogen causing human infections. Here we investigated differential gene expression patterns and functional enrichment in C. albicans strains grown under different conditions. METHODS: A systematic GEO database search identified 239 "Candida albicans" datasets, of which 14 were selected after rigorous criteria application. Retrieval of raw sequencing data from the ENA database was accompanied by essential metadata extraction from dataset descriptions and original articles. Pre-processing via the tailored nf-core pipeline for C. albicans involved alignment, gene/transcript quantification, and diverse quality control measures. Quality assessment via PCA and DESeq2 identified significant genes (FDR < = 0.05, log2-fold change > = 1 or <= -1), while topGO conducted GO term enrichment analysis. Exclusions were made based on data quality and strain relevance, resulting in the selection of seven datasets from the SC5314 strain background for in-depth investigation. RESULTS: The meta-analysis of seven selected studies unveiled a substantial number of genes exhibiting significant up-regulation (24,689) and down-regulation (18,074). These differentially expressed genes were further categorized into 2,497 significantly up-regulated and 2,573 significantly down-regulated Gene Ontology (GO) IDs. GO term enrichment analysis clustered these terms into distinct groups, providing insights into the functional implications. Three target gene lists were compiled based on previous studies, focusing on central metabolism, ion homeostasis, and pathogenicity. Frequency analysis revealed genes with higher occurrence within the identified GO clusters, suggesting their potential as antifungal targets. Notably, the genes TPS2, TPS1, RIM21, PRA1, SAP4, and SAP6 exhibited higher frequencies within the clusters. Through frequency analysis within the GO clusters, several key genes emerged as potential targets for antifungal therapies. These include RSP5, GLC7, SOD2, SOD5, SOD1, SOD6, SOD4, SOD3, and RIM101 which exhibited higher occurrence within the identified clusters. CONCLUSION: This comprehensive study significantly advances our understanding of the dynamic nature of gene expression in C. albicans. The identification of genes with enhanced potential as antifungal drug targets underpins their value for future interventions. The highlighted genes, including TPS2, TPS1, RIM21, PRA1, SAP4, SAP6, RSP5, GLC7, SOD2, SOD5, SOD1, SOD6, SOD4, SOD3, and RIM101, hold promise for the development of targeted antifungal therapies.

Network Pharmacological Analysis of a New Herbal Combination Targeting Hyperlipidemia and Efficacy Validation In Vitro.

The network pharmacology (NP) approach is a valuable novel methodology for understanding the complex pharmacological mechanisms of medicinal herbs. In addition, various in silico analysis techniques combined with the NP can improve the understanding of various issues used in natural product research. This study assessed the therapeutic effects of Arum ternata (AT), Poria cocos (PC), and Zingiber officinale (ZO) on hyperlipidemia after network pharmacologic analysis. A protein-protein interaction (PPI) network of forty-one key targets was analyzed to discover core functional clusters of the herbal compounds. The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and gene ontology (GO) term enrichment analysis identified significant categories of hypolipidemic mechanisms. The STITCH database indicated a high connection with several statin drugs, deduced by the similarity in targets. AT, PC, and ZO regulated the genes related to the energy metabolism and lipogenesis in HepG2 cells loaded with free fatty acids (FFAs). Furthermore, the mixture of three herbs had a combinational effect. The herbal combination exerted superior efficacy compared to a single herb, particularly in regulating acetyl-CoA carboxylase (ACC) and carnitine palmitoyltransferase 1 (CPT-1). In conclusion, the network pharmacologic approach was used to assess potential targets of the herbal combination for treatment. Experimental data from FFA-induced HepG2 cells suggested that the combination of AT, PC, and ZO might attenuate hyperlipidemia and its associated hepatic steatosis.

Alternative Splicing during Fiber Development in G. hirsutum.

Cotton is a valuable cash crop in many countries. Cotton fiber is a trichome that develops from a single epidermal cell and serves as an excellent model for understanding cell differentiation and other life processes. Alternative splicing (AS) of genes is a common post-transcriptional regulatory process in plants that is essential for plant growth and development. The process of AS during cotton fiber formation, on the other hand, is mainly unknown. A substantial number of multi-exon genes were discovered to be alternatively spliced during cotton fiber formation in this study, accounting for 23.31% of the total number of genes in Gossypium hirsutum. Retention intron (RI) is not necessarily the most common AS type, indicating that AS genes and processes during fiber development are very temporal and tissue-specific. When compared to fiber samples, AS is more prevalent at the fiber initiation stages and in the ovule, indicating that development stages and tissues use different AS strategies. Genes involved in fiber development have gone through stage-specific AS, demonstrating that AS regulates cotton fiber development. Furthermore, AS can be regulated by trans-regulation elements such as splicing factor and cis-regulation elements such as gene length, exon numbers, and GC content, particularly at exon-intron junction sites. Our findings also suggest that increased DNA methylation may aid in the efficiency of AS, and that gene body methylation is key in AS control. Finally, our research will provide useful information about the roles of AS during the cotton fiber development process.

G-Protein-Coupled Receptors Mediate Modulations of Cell Viability and Drug Sensitivity by Aberrantly Expressed Recoverin 3 within A549 Cells.

To elucidate the currently unknown molecular mechanisms responsible for the aberrant expression of recoverin (Rec) within cancerous cells, we examined two-dimensional (2D) and three-dimensional (3D) cultures of Rec-negative lung adenocarcinoma A549 cells which had been transfected with a plasmid containing human recoverin cDNA (A549 Rec) or an empty plasmid as a mock control (A549 MOCK). Using these cells, we measured cytotoxicity by several anti-tumor agents (2D), cellular metabolism including mitochondrial and glycolytic functions by a Seahorse bio-analyzer (2D), the physical properties, size and stiffness of the 3D spheroids, trypsin sensitivities (2D and 3D), and RNA sequencing analysis (2D). Compared with the A549 MOCK, the A549 Rec cells showed (1) more sensitivity toward anti-tumor agents (2D) and a 0.25% solution of trypsin (3D); (2) a metabolic shift from glycolysis to oxidative phosphorylation; and (3) the formation of larger and stiffer 3D spheroids. RNA sequencing analysis and bioinformatic analyses of the differentially expressed genes (DEGs) using Gene Ontology (GO) enrichment analysis suggested that aberrantly expressed Rec is most likely associated with several canonical pathways including G-protein-coupled receptor (GPCR)-mediated signaling and signaling by the cAMP response element binding protein (CREB). The findings reported here indicate that the aberrantly expressed Rec-induced modulation of the cell viability and drug sensitivity may be GPCR mediated.

ALGAEFUN with MARACAS, microALGAE FUNctional enrichment tool for MicroAlgae RnA-seq and Chip-seq AnalysiS.

BACKGROUND: Microalgae are emerging as promising sustainable sources for biofuels, biostimulants in agriculture, soil bioremediation, feed and human nutrients. Nonetheless, the molecular mechanisms underpinning microalgae physiology and the biosynthesis of compounds of biotechnological interest are largely uncharacterized. This hinders the development of microalgae full potential as cell-factories. The recent application of omics technologies into microalgae research aims at unraveling these systems. Nevertheless, the lack of specific tools for analysing omics raw data generated from microalgae to provide biological meaningful information are hampering the impact of these technologies. The purpose of ALGAEFUN with MARACAS consists in providing researchers in microalgae with an enabling tool that will allow them to exploit transcriptomic and cistromic high-throughput sequencing data. RESULTS: ALGAEFUN with MARACAS consists of two different tools. First, MARACAS (MicroAlgae RnA-seq and Chip-seq AnalysiS) implements a fully automatic computational pipeline receiving as input RNA-seq (RNA sequencing) or ChIP-seq (chromatin immunoprecipitation sequencing) raw data from microalgae studies. MARACAS generates sets of differentially expressed genes or lists of genomic loci for RNA-seq and ChIP-seq analysis respectively. Second, ALGAEFUN (microALGAE FUNctional enrichment tool) is a web-based application where gene sets generated from RNA-seq analysis as well as lists of genomic loci from ChIP-seq analysis can be used as input. On the one hand, it can be used to perform Gene Ontology and biological pathways enrichment analysis over gene sets. On the other hand, using the results of ChIP-seq data analysis, it identifies a set of potential target genes and analyses the distribution of the loci over gene features. Graphical representation of the results as well as tables with gene annotations are generated and can be downloaded for further analysis. CONCLUSIONS: ALGAEFUN with MARACAS provides an integrated environment for the microalgae research community that facilitates the process of obtaining relevant biological information from raw RNA-seq and ChIP-seq data. These applications are designed to assist researchers in the interpretation of gene lists and genomic loci based on functional enrichment analysis. ALGAEFUN with MARACAS is publicly available on https://greennetwork.us.es/AlgaeFUN/ .

MonaGO: a novel gene ontology enrichment analysis visualisation system.

BACKGROUND: Gene ontology (GO) enrichment analysis is frequently undertaken during exploration of various -omics data sets. Despite the wide array of tools available to biologists to perform this analysis, meaningful visualisation of the overrepresented GO in a manner which is easy to interpret is still lacking. RESULTS: Monash Gene Ontology (MonaGO) is a novel web-based visualisation system that provides an intuitive, interactive and responsive interface for performing GO enrichment analysis and visualising the results. MonaGO supports gene lists as well as GO terms as inputs. Visualisation results can be exported as high-resolution images or restored in new sessions, allowing reproducibility of the analysis. An extensive comparison between MonaGO and 11 state-of-the-art GO enrichment visualisation tools based on 9 features revealed that MonaGO is a unique platform that simultaneously allows interactive visualisation within one single output page, directly accessible through a web browser with customisable display options. CONCLUSION: MonaGO combines dynamic clustering and interactive visualisation as well as customisation options to assist biologists in obtaining meaningful representation of overrepresented GO terms, producing simplified outputs in an unbiased manner. MonaGO will facilitate the interpretation of GO analysis and will assist the biologists into the representation of the results.

Molecular variation among virulent and avirulent strains of the quarantine nematode Bursaphelenchus xylophilus.

Bursaphelenchus xylophilus is an emerging pathogenic nematode that is responsible for a devastating epidemic of pine wilt disease worldwide, causing severe ecological damage and economic losses to forestry. Two forms of this nematode have been reported, i.e., with strong and weak virulence, commonly referred as virulent and avirulent strains. However, the pathogenicity-related genes of B. xylophilus are not sufficiently characterized. In this study, to find pathogenesis related genes we re-sequenced and compared genomes of two virulent and two avirulent populations. We identified genes affected by genomic variation, and functional annotation of those genes indicated that some of them might play potential roles in pathogenesis. The performed analysis showed that both avirulent populations differed from the virulent ones by 1576 genes with high impact variants. Demonstration of genetic differences between virulent and avirulent strains will provide effective methods to distinguish these two nematode virulence forms at the molecular level. The reported results provide basic information that can facilitate development of a better diagnosis for B. xylophilus isolates/strains which present different levels of virulence and better understanding of the molecular mechanism involved in the development of the PWD.

Identification of foam cell biomarkers by microarray analysis.

BACKGROUND: Lipid infiltration and inflammatory response run through the occurrence of atherosclerosis. Differentiation into macrophages and foam cell formation are the key steps of AS. Aim of this study was that the differential gene expression between foam cells and macrophages was analyzed to search the key links of foam cell generation, so as to explore the pathogenesis of atherosclerosis and provide targets for the early screening and prevention of coronary artery disease (CAD). METHODS: The gene expression profiles of GSE9874 were downloaded from Gene Expression Omnibus (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE9874) on GPL96 [HG-U133A] Affymetrix Human Genome U133. A total of 22,383 genes were analyzed for differentially expression genes (DEGs) by Bayes package. GO enrichment analysis and KEGG pathway analysis for DEGs were performed using KOBAS 3.0 software (Peking University, Beijing, China). STRING software (STRING 10.0; European Molecular Biology Laboratory, Heidelberg, Germany) was used to analyze the protein-protein interaction (PPI) of DEGs. RESULTS: A total of 167 DEGs between macrophages and foam cells were identified. Compared with macrophages, 102 genes were significantly upregulated and 65 genes were significantly downregulated (P < 0.01, fold-change > 1) in foam cells. DEGs were mainly enrich in 'sterol biosynthetic and metabolic process', 'cholesterol metabolic and biosynthetic process' by GO enrichment analysis. The results of KEGG pathway analysis showed all differential genes are involved in biological processes through 143 KEGG pathways. A PPI network of the DEGs was constructed and 10 outstanding genes of the PPI network was identified by using Cytoscape, which include HMGCR, SREBF2, LDLR, HMGCS1, FDFT1, LPL, DHCR24, SQLE, ABCA1 and FDPS. CONCLUSION: Lipid metabolism related genes and molecular pathways were the key to the transformation of macrophages into foam cells. Therefore, lipid metabolism disorder is the key to turn macrophages into foam cells, which plays a major role in CAD.

Transcriptome analysis of leg muscles in fast and slow growth Bian chickens.

Chicken is popular among consumers in the market, but the mechanism for regulating its growth is still unclear. In this experiment, two groups of Bian chickens of different body weights at 16 weeks of age were studied. The leg muscles were taken for transcriptome sequencing after slaughter. In the differential gene screening, all the genes obtained by sequencing the fast and slow growth groups were screened by Fold Change ≥2 and False Discovery Rate (FDR) <0.05, and 108 differentially expressed genes were obtained. The slow growth group has 17 up-regulated genes and 91 down-regulated genes compared with the fast growing group. Significance analysis of differentially expressed genes in gene ontology (GO) enrichment indicates that there are 65, 16 and 6 significantly enriched entries in the three main categories of biological processes, cellular components and molecular functions (P-value <0.05), respectively. Pathway enrichment analysis yielded three significantly enriched signal pathways: Adrenergic signaling in cardiomyocytes, Cardiac muscle contraction and Tight junction. The experiment would contribute to reveal the molecular mechanism of chicken growth and provide a theoretical basis for improving the performance of Bian chicken.

Transcriptome profile of rat genes in bone marrow-derived macrophages at different activation statuses by RNA-sequencing.

The underlying mechanisms of macrophage polarization have been detected by genome-wide transcriptome analysis in a variety of mammals. However, the transcriptome profile of rat genes in bone marrow-derived macrophages (BMM) at different activation statuses has not been reported. Therefore, we performed RNA-Sequencing to identify gene expression signatures of rat BMM polarized in vitro with different stimuli. The differentially expressed genes (DEGs) among unactivated (M0), classically activated pro-inflammatory (M1), and alternatively activated anti-inflammatory macrophages (M2) were analyzed by using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analysis. In this study, not only we have identified the changes of global gene expression in rat M0, M1 and M2, but we have also made clear systematically the key genes and signaling pathways in the differentiation process of M0 to M1 and M2. These will provide a foundation for future researches of macrophage polarization.

Comparative Transcriptome Analysis of Two Contrasting Soybean Varieties in Response to Aluminum Toxicity.

: Aluminum (Al) toxicity is a major factor limiting crop productivity on acid soils. Soybean (Glycine max) is an important oil crop and there is great variation in Al tolerance in soybean germplasms. However, only a few Al-tolerance genes have been reported in soybean. Therefore, the purpose of this study was to identify candidate Al tolerance genes by comparative transcriptome analysis of two contrasting soybean varieties in response to Al stress. Two soybean varieties, M90-24 (M) and Pella (P), which showed significant difference in Al tolerance, were used for RNA-seq analysis. We identified a total of 354 Al-tolerance related genes, which showed up-regulated expression by Al in the Al-tolerant soybean variety M and higher transcript levels in M than P under Al stress. These genes were enriched in the Gene Ontology (GO) terms of cellular glucan metabolic process and regulation of transcription. Five out of 11 genes in the enriched GO term of cellular glucan metabolic process encode cellulose synthases, and one cellulose synthase gene (Glyma.02G205800) was identified as the key hub gene by co-expression network analysis. Furthermore, treatment of soybean roots with a cellulose biosynthesis inhibitor decreased the Al tolerance, indicating an important role of cellulose production in soybean tolerance to Al toxicity. This study provides a list of candidate genes for further investigation on Al tolerance mechanisms in soybean.

Identification and Characterization of circRNAs Responsive to Methyl Jasmonate in Arabidopsis thaliana.

Circular RNAs (circRNAs) are endogenous noncoding RNAs with covalently closed continuous loop structures that are formed by 3'-5' ligation during splicing. These molecules are involved in diverse physiological and developmental processes in eukaryotic cells. Jasmonic acid (JA) is a critical hormonal regulator of plant growth and defense. However, the roles of circRNAs in the JA regulatory network are unclear. In this study, we performed high-throughput sequencing of Arabidopsis thaliana at 24 h, 48 h, and 96 h after methyl JA (MeJA) treatment. A total of 8588 circRNAs, which were distributed on almost all chromosomes, were identified, and the majority of circRNAs had lengths between 200 and 800 bp. We identified 385 differentially expressed circRNAs (DEcircRNAs) by comparing data between MeJA-treated and untreated samples. Gene Ontology (GO) enrichment analysis of the host genes that produced the DEcircRNAs showed that the DEcircRNAs are mainly involved in response to stimulation and metabolism. Additionally, some DEcircRNAs were predicted to act as miRNA decoys. Eight DEcircRNAs were validated by qRT-PCR with divergent primers, and the junction sites of five DEcircRNAs were validated by PCR analysis and Sanger sequencing. Our results provide insight into the potential roles of circRNAs in the MeJA regulation network.

A Comparative Transcriptome Analysis, Conserved Regulatory Elements and Associated Transcription Factors Related to Accumulation of Fusariotoxins in Grain of Rye (Secale cereale L.) Hybrids.

Detoxification of fusariotoxin is a type V Fusarium head blight (FHB) resistance and is considered a component of type II resistance, which is related to the spread of infection within spikes. Understanding this type of resistance is vital for FHB resistance, but to date, nothing is known about candidate genes that confer this resistance in rye due to scarce genomic resources. In this study, we generated a transcriptomic resource. The molecular response was mined through a comprehensive transcriptomic analysis of two rye hybrids differing in the build-up of fusariotoxin contents in grain upon pathogen infection. Gene mining identified candidate genes and pathways contributing to the detoxification of fusariotoxins in rye. Moreover, we found cis regulatory elements in the promoters of identified genes and linked them to transcription factors. In the fusariotoxin analysis, we found that grain from the Nordic seed rye hybrid "Helltop" accumulated 4 times higher concentrations of deoxynivalenol (DON), 9 times higher nivalenol (NIV), and 28 times higher of zearalenone (ZEN) than that of the hybrid "DH372" after artificial inoculation under field conditions. In the transcriptome analysis, we identified 6675 and 5151 differentially expressed genes (DEGs) in DH372 and Helltop, respectively, compared to non-inoculated control plants. A Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis revealed that DEGs were associated with glycolysis and the mechanistic target of rapamycin (mTOR) signaling pathway in Helltop, whereas carbon fixation in photosynthesis organisms were represented in DH372. The gene ontology (GO) enrichment and gene set enrichment analysis (GSEA) of DEGs lead to identification of the metabolic and biosynthetic processes of peptides and amides in DH372, whereas photosynthesis, negative regulation of catalytic activity, and protein-chromophore linkage were the significant pathways in Helltop. In the process of gene mining, we found four genes that were known to be involved in FHB resistance in wheat and that were differentially expressed after infection only in DH372 but not in Helltop. Based on our results, we assume that DH372 employed a specific response to pathogen infection that led to detoxification of fusariotoxin and prevented their accumulation in grain. Our results indicate that DH372 might resist the accumulation of fusariotoxin through activation of the glycolysis and drug metabolism via cytochrome P450. The identified genes in DH372 might be regulated by the WRKY family transcription factors as associated cis regulatory elements found in the in silico analysis. The results of this study will help rye breeders to develop strategies against type V FHB.

Detailed prediction of protein sub-nuclear localization.

BACKGROUND: Sub-nuclear structures or locations are associated with various nuclear processes. Proteins localized in these substructures are important to understand the interior nuclear mechanisms. Despite advances in high-throughput methods, experimental protein annotations remain limited. Predictions of cellular compartments have become very accurate, largely at the expense of leaving out substructures inside the nucleus making a fine-grained analysis impossible. RESULTS: Here, we present a new method (LocNuclei) that predicts nuclear substructures from sequence alone. LocNuclei used a string-based Profile Kernel with Support Vector Machines (SVMs). It distinguishes sub-nuclear localization in 13 distinct substructures and distinguishes between nuclear proteins confined to the nucleus and those that are also native to other compartments (traveler proteins). High performance was achieved by implicitly leveraging a large biological knowledge-base in creating predictions by homology-based inference through BLAST. Using this approach, the performance reached AUC = 0.70-0.74 and Q13 = 59-65%. Travelling proteins (nucleus and other) were identified at Q2 = 70-74%. A Gene Ontology (GO) analysis of the enrichment of biological processes revealed that the predicted sub-nuclear compartments matched the expected functionality. Analysis of protein-protein interactions (PPI) show that formation of compartments and functionality of proteins in these compartments highly rely on interactions between proteins. This suggested that the LocNuclei predictions carry important information about function. The source code and data sets are available through GitHub: https://github.com/Rostlab/LocNuclei . CONCLUSIONS: LocNuclei predicts subnuclear compartments and traveler proteins accurately. These predictions carry important information about functionality and PPIs.

Differential gene expression profile in monocytic myeloid-derived suppressor cells at maternal-fetal interface in a mouse model of spontaneous abortion.

ABSTRACTBACKGROUND: Monocytic myeloid-derived suppressor cells (MO-MDSCs) play an important role in maintaining normal pregnancy. However, it is still not clear what kind of changes in MO-MDSCs may lead to miscarriage, and which gene expression changes take place when MO-MDSCs migrate to the uterus as bone marrow-derived cells. METHODS: We used flow sorting technology to obtain MO-MDSCs from the maternal-fetal interface and bone marrow, respectively. Affymetrix 3'IVT expression profiling chip technology was used to detect the differential gene expression profiles in MO-MDSCs at the maternal-fetal interface in a mouse model of spontaneous abortion compared with the normal fertility control mice. We also compared the differential gene expression of MO-MDSCs at the maternal-fetal interface compared with bone marrow in the normal fertility control mice. RESULTS: We found that 3,409 genes in MO-MDSCs were upregulated and 1,539 genes were downregulated at the maternal-fetal interface in the spontaneous abortion mice compared with the normal fertility mice. These genes are enriched in cellular components, biological processes, molecular functions, and protein binding, tumor signaling pathway, the PI3K-Akt signaling pathway, intratumoral proteoglycans, and extracellular matrix receptor interactions. Furthermore, we found that 270 genes in MO-MDSCs were upregulated and 383 genes were downregulated at the maternal-fetal interface in the normal fertility mice compared with those in the bone marrow. These genes are enriched in cellular components, biological processes, molecular functions, cell cycle, tumor transcriptional disorder, and cell adhesion molecules. CONCLUSION: Differential gene expression in MO-MDSCs likely contributes to a successful pregnancy in fetal-maternal immunotolerance.

Genome-wide analysis of Homo sapiens, Arabidopsis thaliana, and Saccharomyces cerevisiae reveals novel attributes of tail-anchored membrane proteins.

BACKGROUND: Tail-anchored membrane proteins (TAMPs) differ from other integral membrane proteins, because they contain a single transmembrane domain at the extreme carboxyl-terminus and are therefore obliged to target to membranes post-translationally. Although 3-5% of all transmembrane proteins are predicted to be TAMPs only a small number are well characterized. RESULTS: To identify novel putative TAMPs across different species, we used TAMPfinder software to identify 859, 657 and 119 putative TAMPs in human (Homo sapiens), plant (Arabidopsis thaliana), and yeast (Saccharomyces cerevisiae), respectively. Bioinformatics analyses of these putative TAMP sequences suggest that the list is highly enriched for authentic TAMPs. To experimentally validate the software predictions several human and plant proteins identified by TAMPfinder that were previously uncharacterized were expressed in cells and visualized at subcellular membranes by fluorescence microscopy and further analyzed by carbonate extraction or by bimolecular fluorescence complementation. With the exception of the pro-apoptotic protein harakiri, which is, peripherally bound to the membrane this subset of novel proteins behave like genuine TAMPs. Comprehensive bioinformatics analysis of the generated TAMP datasets revealed previously unappreciated common and species-specific features such as the unusual size distribution of and the propensity of TAMP proteins to be part of larger complexes. Additionally, novel features of the amino acid sequences that anchor TAMPs to membranes were also revealed. CONCLUSIONS: The findings in this study more than double the number of predicted annotated TAMPs and provide new insights into the common and species-specific features of TAMPs. Furthermore, the list of TAMPs and annotations provide a resource for further investigation.

Identification of cucumber circular RNAs responsive to salt stress.

BACKGROUND: Circular RNAs (circRNAs) are 3'-5' head-to-tail covalently closed non-coding RNA that have been proved to play essential roles in many cellular and developmental processes. However, no information relate to cucumber circRNAs is available currently, especially under salt stress condition. RESULTS: In this study, we sequenced circRNAs in cucumber and a total of 2787 were identified, with 1934 in root and 44 in leaf being differentially regulated under salt stress. Characteristics analysis of these circRNAs revealed following features: most of them are exon circRNAs (79.51%) and they prefer to arise from middle exon(s) of parent genes (2035/2516); moreover, most of circularization events (88.3%) use non-canonical-GT/AG splicing signals; last but not least, pairing-driven circularization is not the major way to generate cucumber circRNAs since very few circRNAs (18) contain sufficient flanking complementary sequences. Annotation and enrichment analysis of both parental genes and target mRNAs were launched to uncover the functions of differentially expressed circRNAs induced by salt stress. The results showed that circRNAs may be paly roles in salt stress response by mediating transcription, signal transcription, cell cycle, metabolism adaptation, and ion homeostasis related pathways. Moreover, circRNAs may function to regulate proline metabolisms through regulating associated biosynthesis and degradation genes. CONCLUSIONS: The present study identified large number of cucumber circRNAs and function annotation revealed their possible biological roles in response to salt stress. Our findings will lay a solid foundation for further structure and function studies of cucumber circRNAs.

Protein-protein interaction network analysis of insecticide resistance molecular mechanism in Drosophila melanogaster.

The problem of resistance has not been solved fundamentally at present, because the development speed of new insecticides can not keep pace with the development speed of resistance, and the lack of understanding of molecular mechanism of resistance. Here we collected seed genes and their interacting proteins involved in insecticide resistance molecular mechanism in Drosophila melanogaster by literature mining and the String database. We identified a total of 528 proteins and 13514 protein-protein interactions. The protein interaction network was constructed by String and Pajek, and we analyzed the topological properties, such as degree centrality and eigenvector centrality. Proteasome complexes and drug metabolism-cytochrome P450 were an enrichment by Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. This is the first time to explore the insecticide resistance molecular mechanism of D. melanogaster by the methods and tools of network biology, it can provide the bioinformatic foundation for further understanding the mechanisms of insecticide resistance.

Protein chip and bioinformatic analyses of differentially expressed proteins involved in the effect of hydrogen-rich water on myocardial ischemia-reperfusion injury.

Background: The differentially expressed proteins (DEPs) involved in the effect of hydrogen-rich water on myocardial ischemia reperfusion injury (MIRI) and their biological processes and signaling pathway were analyzed. Methods: 20 Wistar rats were randomly and equally divided into a control and a hydrogen-rich group. Hearts were removed and fixed in a Langendorff device. The control group was perfused with K-R solution, and the hydrogen-rich water group was perfused with K-R solution + hydrogen-rich water. Protein was extracted from the ventricular tissues, and GSR-CAA-67 was used to identify the DEPs between two groups. DEPs were analyzed through bioinformatic methods. Results: Compared with the control group, in the treatment group, the expression of 25 proteins was obviously decreased (P<0.05). For the DEPs, 359 biological processes, including the regulation of signaling pathways, immune reaction and formation of cardiovascular endothelial cells, were selected by GO enrichment analysis. Five signaling pathways were selected by KEGG pathway enrichment analysis. Conclusions: 25 proteins that are involved in hydrogen-water reducing MIRI were selected by high-throughput GSR-CAA-67. The biological processes and metabolic pathways involved in the DEPs were summarized, providing theoretical evidence for the clinical application of hydrogen-rich water.