A Java-based tool for the design of classification microarrays

A roadmap to multifactor dimensionality reduction methods

Complex diseases are defined to be determined by multiple genetic and environmental factors alone as well as in interactions. To analyze interactions in genetic data, many statistical methods have been suggested, with most of them relying on statistical regression models. Given the known limitations of classical methods, approaches from the machine-learning community have also become attractive. From this latter family, a fast-growing collection of methods emerged that are based on the Multifactor Dimensionality Reduction (MDR) approach. Since its first introduction, MDR has enjoyed great popularity in applications and has been extended and modified multiple times. Based on a literature search, we here provide a systematic and comprehensive overview of these suggested methods. The methods are described in detail, and the availability of implementations is listed. Most recent approaches offer to deal with large-scale data sets and rare variants, which is why we expect these methods to even gain in popularity.

Neurite outgrowth resistance to rho kinase inhibitors in PC12 Adh cell

Rho kinase (ROCK) inhibitor is a promising agent for neural injury disorders, which mechanism is associated with neurite outgrowth. However, neurite outgrowth resistance occurred when PC12 Adh cell was treated with ROCK inhibitors for a longer time. PC12 Adh cells were treated with ROCK inhibitor Y27632 or NGF for different durations. Neurite outgrowth resistance occurred when PC12 Adh cell exposed to Y27632 (33 µM) for 3 or more days, but not happen when exposed to nerve growth factor (NGF, 100 ng/mL). The gene expression in the PC12 Adh cells treated with Y27632 (33 µM) or NGF (100 ng/mL) for 2 or 4 days was assayed by gene microarray, and the reliability of the results were confirmed by real-time RT-PCR. Cluster analysis proved that the gene expression profile of PC12 Adh cell treated with Y27632 for 4 days was different from that treated with Y27632 for 2 days and those treated with NGF for 2 and 4 days, respectively. Pathway analysis hinted that the neurite outgrowth resistance could be associated with up-regulation of inflammatory pathways, especially rno04610 (complement and coagulation cascades), and down-regulation of cell cycle pathways, especially rno04110.

Global gene expression of Poncirus trifoliata, Citrus sunki and their hybrids under infection of Phytophthora parasitica

Background

Gummosis and root rot caused by Phytophthora are among the most economically important diseases in citrus. Four F₁ resistant hybrids (Pool R), and four F₁ susceptible hybrids (Pool S) to P. parasitica, were selected from a cross between susceptible Citrus sunki and resistant Poncirus trifoliata cv. Rubidoux. We investigated gene expression in pools of four resistant and four susceptible hybrids in comparison with their parents 48 hours after P. parasitica inoculation. We proposed that genes differentially expressed between resistant and susceptible parents and between their resistant and susceptible hybrids provide promising candidates for identifying transcripts involved in disease resistance. A microarray containing 62,876 UniGene transcripts selected from the CitEST database and prepared by NimbleGen Systems was used for analyzing global gene expression 48 hours after infection with P. parasitica.

Results

Three pairs of data comparisons (P. trifoliata/C. sunki, Pool R/C. sunki and Pool R/Pool S) were performed. With a filter of false-discovery rate less than 0.05 and fold change greater than 3.0, 21 UniGene transcripts common to the three pairwise comparative were found to be up-regulated, and 3 UniGene transcripts were down-regulated. Among them, our results indicated that the selected transcripts were probably involved in the whole process of plant defense responses to pathogen attack, including transcriptional regulation, signaling, activation of defense genes participating in HR, single dominant genes (R gene) such as TIR-NBS-LRR and RPS4 and switch of defense-related metabolism pathway. Differentially expressed genes were validated by RT-qPCR in susceptible and resistant plants and between inoculated and uninoculated control plants

Conclusions

Twenty four UniGene transcripts were identified as candidate genes for Citrus response to P. parasitica. UniGene transcripts were likely to be involved in disease resistance, such as genes potentially involved in secondary metabolite synthesis, intracellular osmotic adjustment, signal transduction pathways of cell death, oxidative burst and defense gene expression. Furthermore, our microarray data suggest another type of resistance in Citrus-Phytophthora interaction conferred by single dominant genes (R gene) since we encountered two previously reported R genes (TIR-NBS-LRR and RPS4) upregulated in the resistant genotypes relative to susceptible. We identified 7 transcripts with homology in other plants but yet unclear functional characterization which are an interesting pool for further analyses and 3 transcripts where no significant similarity was found. This is the first microarray study addressing an evaluation of transcriptional changes in response to P. parasitica in Citrus.