RKN Lethal DB: A database for the identification of Root Knot Nematode (Meloidogyne spp.) candidate lethal genes

Root Knot nematode (RKN; Meloidogyne spp.) is one of the most devastating parasites that infect the roots of hundreds of plant species. RKN cannot live independently from their hosts and are the biggest contributors to the loss of the world''s primary foods. RNAi gene silencing studies have demonstrated that there are fewer galls and galls are smaller when RNAi constructs targeted to silence certain RKN genes are expressed in plant roots. We conducted a comparative genomics analysis, comparing RKN genes of six species: Meloidogyne Arenaria, Meloidogyne Chitwoodi, Meloidogyne Hapla, Meloidogyne Incognita, Meloidogyne Javanica, and Meloidogyne Paranaensis to that of the free living nematode Caenorhabditis elegans, to identify candidate genes that will be lethal to RKN when silenced or mutated. Our analysis yielded a number of such candidate lethal genes in RKN, some of which have been tested and proven to be effective in soybean roots. A web based database was built to house and allow scientists to search the data. This database will be useful to scientists seeking to identify candidate genes as targets for gene silencing to confer resistance in plants to RKN.

Availability

The database can be accessed from http://bioinformatics.towson.edu/RKN/     

Transcriptome Analysis of the Hippocampus in Novel Rat Model of Febrile Seizures

Febrile seizures (FS) are the most common type of convulsive events in infants and young children, but the precise underlying genetic mechanism remains to be explored. To investigate the underlying pathogenic factors in FS and subsequent epilepsy, alterations in gene expression between the two new strains of rats (hyperthermia-prone [HP] vs hyperthermia-resistant [HR]), were investigated by using the Whole Rat Genome Oligo Microarray. This process identified 1,140 differentially expressed genes (DEGs; 602 upregulated and 538 downregulated), which were analyzed to determine significant Gene Ontology (GO) categories, signaling pathways and gene networks. Based on the GO analyses, the modified genes are closely related to various FS pathogenesis factors, including immune and inflammatory responses and ion transport. Certain DEGs identified have not been previously examined in relation to FS pathogenesis. Among these genes is dipeptidyl peptidase 4 (DPP4), a gene closely linked to interleukin 6 (IL-6), which played a key role in the gene network analysis. Furthermore, sitagliptin, a DPP4 inhibitor significantly decreased epileptic discharge in rats, observed via electroencephalogram, suggesting an important role for DPP4 in FS. The effectiveness of sitagliptin in reducing seizure activity may occur through a mechanism that stabilizes cellular Ca²⁺ homeostasis. In addition, DPP4 expression may be regulated by DNA methylation. The hippocampal gene expression profiles in novel rat models of FS provides a large database of candidate genes and pathways, which will be useful for researchers interested in disorders of neuronal excitability.     

MicroRNA-target gene responses to root knot nematode (Meloidogyne incognita) infection in cotton (Gossypium hirsutum L.)

MicroRNAs (miRNAs) are a large class of small regulatory RNA molecules, however no study has been performed to elucidate the role of miRNAs in cotton (Gossypium hirsutum) response to the root knot nematode (RKN, Meloidogyne incognita) infection. We selected 28 miRNAs and 8 miRNA target genes to investigate the miRNA-target gene response to M. incognita infection. Our results show that RKN infection significantly affected the expression of several miRNAs and their targeted genes. After 10 days of RKN infection, expression fold changes on miRNA expressions ranged from down-regulated by 33% to upregulated by 406%; meanwhile the expression levels of miRNA target genes were 45.8% to 231%. Three miRNA-target pairs, miR159-MYB, miR319-TCP4 and miR167-ARF8, showed inverse expression patterns between gene targets and their corresponded miRNAs, suggesting miRNA-mediated gene regulation in cotton roots in response to RKN infection.     

Comprehensive gene expression analysis reveals multiple signal pathways associated with prostate cancer

Prostate cancer (PC) depends on androgenic signaling for growth and survival. To data, the exact molecular mechanism of hormone controlling proliferation and tumorigenesis in the PC remains unclear. Therefore, in this study, we explored the differentially expressed genes (DEGs) and identified featured genes related to hormone stimulus from PC. Two sets of gene expression data, including PC and normal control sample, were downloaded from Gene Expression Omnibus (GEO) database. The t-test was used to identify DEGs between PC and controls. Gene ontology (GO) functional annotation was applied to analyze the function of DEGs and screen hormone-related DEGs. Then these hormone-related DEGs were further analyzed in constructed cancer network and Human Protein Reference Database to screen important signaling pathways they participated in. A total of 912 DEGs were obtained which included 326 up-regulated genes and 586 down-regulated genes. GO functional enrichment analysis identified 50 hormone-related DEGs associated with PC. After pathway and PPI network analysis, we found these hormone-related DEGs participated in several important signaling pathways including TGF-β (TGFB2, TGFB3 and TGFBR2), MAPK (TGFB2, TGFB3 and TGFBR2), insulin (PIK3R3, SHC1 and EIF4EBP1), and p53 signaling pathways (CCND2 and CDKN1A). In addition, a total of five hormone-related DEGs (SHC1, CAV1, RXRA, CDKN1A and SRF) were located in the center of PPI network and 12 hormone-related DEGs formed six protein modules. These important signal pathways and hormone-related DEGs may provide potential therapeutic targets for PC.     

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.     

RNA sequencing analysis provides new insights into dynamic molecular responses to <Emphasis Type="Italic">Valsa mali</Emphasis> pathogenicity in apple ‘Changfu No. 2’

Valsa canker caused by the necrotrophic pathogen Valsa mali (Vm) severely affects apple production in Eastern Asia. The molecular basis underlying the apple response to Vm infection is poorly understood. Hence, we performed RNA sequencing (RNA-seq) to investigate the dynamic gene expression profiles of a major apple cultivar, ‘Changfu No.2’, during Vm infection. Compared with the control (C), 104, 313, and 1059 differentially expressed genes (DEGs) were detected from the phloem tissue within the range of 0.9–1.3 cm (T1), 0.5–0.9 cm (T2), and 0.1–0.5 cm (T3) beyond the lesion periphery, respectively. Gene ontology (GO) enrichment analysis revealed that the DEGs associated with plant growth and development were down-regulated, whereas those related to defense responses were up-regulated. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis showed that hormonal and Ca²⁺ signaling and phenylpropanoid biosynthesis were involved in the defense responses. In conclusion, multiple defense responses associated with ABA, JA, ET, Ca²⁺, and cell wall signals contributed to the defense against Vm infection in ‘Changfu No.2’. In contrast, the DEGs with inhibited expression were involved in plant growth and development; auxin signaling and several resistance genes might weaken the resistance of ‘Changfu No.2’ to pathogens. Our results offer a new insight into plant responses against necrotrophs and could benefit programs aimed at breeding for Vm resistance.     

A Study of Gene Expression in the Nematode Resistant Wild Peanut Relative, Arachis stenosperma, in Response to Challenge with Meloidogyne arenaria

Peanut (Arachis hypogaea) is amongst the most important legume crops in the world. One of its main yield constraints is the root-knot nematode Meloidogyne arenaria. A number of wild Arachis species, including A. stenosperma, are resistant to nematodes, and are a potential source of new resistance alleles for cultivated peanut. Using in silico subtraction of ESTs and macroarray analysis, we identified genes differentially expressed in A. stenosperma roots during its resistance response to M. arenaria. The three most differentially expressed genes [Auxin Repressed Protein (AsARP), Cytokinin Oxidase (AsCKX) and Metallothionein Type 2 (AsMET2)] were further analyzed using northern-blot and showed distinct expression profiles in the resistant A. stenosperma and susceptible A. hypogaea, both after, and sometimes even before, challenge with nematodes. Of the three most differentially expressed genes, AsARP and AsCKX are potentially involved in plant hormonal balance, and AsMET2 may be related to the reactive oxygen reaction triggered by the hypersensitive response (HR).