Identifying candidate genes for discrimination of ulcerative colitis and Crohn’s disease

In this study we aimed to screen effective biomarkers for differential diagnosis of ulcerative colitis (UC) and Crohn’s disease (CD). By using the gene expression profile dataset GSE24287 including 47 ileal CD, 27 UC and 25 non-inflammatory bowel diseases control downloaded from Gene Expression Omnibus database, we identified the differentially expressed genes (DEGs) between UC patients and controls as well as between CD patients and controls (|log₂FC(fold change)| > 1 and p < 0.05). Then Gene Ontology (GO) functional enrichment analyses were performed for these DEGs in two groups, followed by the construction of weight PPI (protein–protein interaction) networks. Subnets enriched for the PPIs and differentially expressed genes were constructed based on the weight PPI networks. The overlapping genes between the genes in the top 10 subnets with smallest p value and the DEGs were selected as the candidate genes of disease. A total of 75 DEGs were identified in UC group and 87 ones in CD group. There were 69 and 57 specific DEGs in CD group and UC group, respectively. The DEGs in CD group were mainly enriched in “inflammatory response” and “defense response”, while the most significantly enriched GO terms in UC group were “anion transport” and “chemotaxis”. FOS and SOCS3 were identified as candidate genes for CD and other three genes HELB, ZBTB16 and FAM107A were candidate genes for UC. In conclusion, there were distinct genetic alterations between UC and CD. The candidate genes identified in current study may be used as biomarkers for differential diagnosis of CD and UC.     

High-abundance mRNAs in Apis mellifera: comparison between nurses and foragers

A large volume of honey bee (Apis mellifera) tag-seq was obtained to identify differential gene expression via Solexa/lllumina Digital Gene Expression tag profiling (DGE) based on next generation sequencing. In total, 4,286,250 (foragers) and 3,422,327 (nurses) clean tags were sequenced, 24,568 (foragers) and 13,134 (nurses) distinct clean tags could not be match to the reference database, and 7508 and 6875 mapped genes were detected in foragers and nurses respectively. 7045 genes were found differentially expressed between foragers and nurses. Of those genes, 1621genes had significantly different expression, that is, they showed an expression ratio (foragers/nurses) of more than 2 and FDR (False Discovery Rate) of less than 0.001. We identified 101 genes that were uniquely expressed in foragers, and 9 genes that were only expressed in nurses. We performed the Gene Ontology (GO) category and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, and found 415 genes with annotation terms linked to the GO cellular component category. 200 components of KEGG pathways were obtained, including 21 signaling pathways. The PPAR signaling pathway was the most highly enriched, with the lowest Q-value.     

In silico identification and computational characterization of endogenous small interfering RNAs from diverse grapevine tissues and stages

Small interfering RNAs (siRNAs) are effectors of regulatory pathways underlying plant development, metabolism, and stress- and nutrient-signaling regulatory networks. The endogenous siRNAs are generally not conserved between plants; consequently, it is necessary and important to identify and characterize siRNAs from various plants. To address the nature and functions of siRNAs, and understand the biological roles of the huge siRNA population in grapevine (Vitis vinifera L.). The high-throughput sequencing technology was used to identify a large set of putative endogenous siRNAs from six grapevine tissues/organs. Subsequently, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis was performed to classify the target genes of siRNA. In total, 520,519 candidate siRNAs were identified and their expression profiles exhibited typical temporal characters during grapevine development. In addition, we identified two grapevine trans-acting siRNA (TAS) gene homologs (VvTAS3 and VvTAS4) and the derived trans-acting siRNAs (tasiRNAs) that could target grapevine auxin response factor (ARF) and myeloblastosis (MYB) genes. Furthermore, the GO and KEGG analysis of target genes showed that most of them covered a broad range of functional categories, especially involving in disease-resistance process. The large-scale and completely genome-wide level identification and characterization of grapevine endogenous siRNAs from the diverse tissues by high throughput technology revealed the nature and functions of siRNAs in grapevine.     

Chemical Components of Aqueous Extracts of Melia azedarach Fruits and Their Effects on The Transcriptome of Staphylococcus aureus

Staphylococcus aureus is the causative agent of numerous and varied clinical infections. Crude aqueous extracts of Melia azedarach fruits inhibit the planktonic growth and initial biofilm formation of S. aureus in a dose-dependent manner. Moreover, the biofilm topologies became sparse and decreased as the concentration of the aqueous extracts increased. RNA-Seq analyses revealed 532 differentially expressed genes (DEGs) after S. aureus exposure to 0.25 g/ml extracts; 319 of them were upregulated, and 213 were downregulated. The majority of DEGs were categorized into abundant sub-groups in the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. Finally, untargeted UHPLC-MS/MS analyses of the aqueous extracts of M. azedarach fruits demonstrated a highly complex profile in positive and negative electrospray ionization modes. The extracts primarily consisted of lipids and lipid-like molecules, organic acids and their derivatives, phenylpropanoids, polyketides, organoheterocyclic compounds, and benzenoids annotated by abundant lipid maps and KEGG pathways. Overall, this study provides evidences that the aqueous extracts of M. azedarach fruits can control S. aureus infections and sought to understand the mode of action of these extracts on S. aureus.