Transcriptomic changes induced by acute ozone in resistant and sensitive Medicago truncatula accessions

Background: Tropospheric ozone, the most abundant air pollutant is detrimental to plant and animal health including humans. In sensitive plant species even a few hours of exposure to this potent oxidant (200-300 nL. L-1) leads to severe oxidative stress that manifests as visible cell death. In resistant plants usually no visible symptoms are observed on exposure to similar ozone concentrations. Naturally occurring variability to acute ozone in plants provides a valuable resource for examining molecular basis of the differences in responses to ozone. From our earlier study in Medicago truncatula, we have identified cultivar Jemalong is ozone sensitive and PI 464815 (JE154) is an ozone-resistant accession. Analyses of transcriptome changes in ozone-sensitive and resistant accession will provide important clues for understanding the molecular changes governing the plant responses to ozone.Results: Acute ozone treatment (300 nL L-1 for six hours) led to a reactive oxygen species (ROS) burst in sensitive Jemalong six hours post-fumigation. In resistant JE154 increase in ROS levels was much reduced compared to Jemalong. Based on the results of ROS profiling, time points for microarray analysis were one hour into the ozone treatment, end of treatment and onset of an ozone-induced ROS burst at 12 hours. Replicated temporal transcriptome analysis in these two accessions using 17 K oligonucleotide arrays revealed more than 2000 genes were differentially expressed. Significantly enriched gene ontologies (GOs) were identified using the Cluster Enrichment analysis program. A striking finding was the alacrity of JE154 in altering its gene expression patterns in response to ozone, in stark contrast to delayed transcriptional response of Jemalong. GOs involved in signaling, hormonal pathways, antioxidants and secondary metabolism were altered in both accessions. However, the repertoire of genes responding in each of these categories was different between the two accessions. Real-time PCR analysis confirmed the differential expression patterns of a subset of these genes.Conclusion: This study provided a cogent view of the unique and shared transcriptional responses in an ozone-resistant and sensitive accession that exemplifies the complexity of oxidative signaling in plants. Based on this study, and supporting literature in Arabidopsis we speculate that plants sensitive to acute ozone are impaired in perception of the initial signals generated by the action of this oxidant. This in turn leads to a delayed transcriptional response in the ozone sensitive plants. In resistant plants rapid and sustained activation of several signaling pathways enables the deployment of multiple mechanisms for minimizing the toxicity effect of this reactive molecule.Peer reviewedBiochemistry and Molecular Biolog

Statistical monitoring of weak spots for improvement of normalization and ratio estimates in microarrays

BACKGROUND: Several aspects of microarray data analysis are dependent on identification of genes expressed at or near the limits of detection. For example, regression-based normalization methods rely on the premise that most genes in compared samples are expressed at similar levels and therefore require accurate identification of nonexpressed genes (additive noise) so that they can be excluded from the normalization procedure. Moreover, key regulatory genes can maintain stringent control of a given response at low expression levels. If arbitrary cutoffs are used for distinguishing expressed from nonexpressed genes, some of these key regulatory genes may be unnecessarily excluded from the analysis. Unfortunately, no accurate method for differentiating additive noise from genes expressed at low levels is currently available. RESULTS: We developed a multistep procedure for analysis of mRNA expression data that robustly identifies the additive noise in a microarray experiment. This analysis is predicated on the fact that additive noise signals can be accurately identified by both distribution and statistical analysis. CONCLUSIONS: Identification of additive noise in this manner allows exclusion of noncorrelated weak signals from regression-based normalization of compared profiles thus maximizing the accuracy of these methods. Moreover, genes expressed at very low levels can be clearly identified due to the fact that their expression distribution is stable and distinguishable from the random pattern of additive noise

Modulation of redox homeostasis under suboptimal conditions by Arabidopsis nudix hydrolase 7

<p>Abstract</p> <p>Background</p> <p>Nudix hydrolases play a key role in maintaining cellular homeostasis by hydrolyzing various nuceloside diphosphate derivatives and capped mRNAs. Several independent studies have demonstrated that <it>Arabidopsis nudix hydrolase 7 </it>(AtNUDT7) hydrolyzes NADH and ADP-ribose. Loss of function <it>Atnudt7-1 </it>mutant plants (SALK_046441) exhibit stunted growth, higher levels of reactive oxygen species, enhanced resistance to pathogens. However, using the same T-DNA line, two other groups reported that mutant plants do not exhibit any visible phenotypes. In this study we analyze plausible factors that account for differences in the observed phenotypes in <it>Atnudt7</it>. Secondly, we evaluate the biochemical and molecular consequences of increased NADH levels due to loss of function of AtNUDT7 in Arabidopsis.</p> <p>Results</p> <p>We identified a novel conditional phenotype of <it>Atnudt7-1 </it>knockout plants that was contingent upon nutrient composition of potting mix. In nutrient-rich Metro-Mix, there were no phenotypic differences between mutant and wild-type (WT) plants. In the nutrient-poor mix (12 parts vermiculite: 3 parts Redi-earth and 1 part sand), mutant plants showed the characteristic stunted phenotype. Compared with WT plants, levels of glutathione, NAD⁺, NADH, and in turn NADH:NAD⁺ratio were higher in <it>Atnudt7-1 </it>plants growing in 12:3:1 potting mix. Infiltrating NADH and ADP-ribose into WT leaves was sufficient to induce AtNUDT7 protein. Constitutive over-expression of <it>AtNudt7 </it>did not alter NADH levels or resistance to pathogens. Transcriptome analysis identified nearly 700 genes differentially expressed in the <it>Atnudt7-1 </it>mutant compared to WT plants grown in 12:3:1 potting mix. In the <it>Atnudt7-</it>1 mutant, genes associated with defense response, proteolytic activities, and systemic acquired resistance were upregulated, while gene ontologies for transcription and phytohormone signaling were downregulated.</p> <p>Conclusions</p> <p>Based on these observations, we conclude that the differences observed in growth phenotypes of the <it>Atnudt7-1 </it>knockout mutants can be due to differences in the nutrient composition of potting mix. Our data suggests AtNUDT7 plays an important role in maintaining redox homeostasis, particularly for maintaining NADH:NAD⁺balance for normal growth and development. During stress conditions, rapid induction of AtNUDT7 is important for regulating the activation of stress/defense signaling and cell death pathways.</p

Analytical vectorial structure of non-paraxial four-petal Gaussian beams in the far field

The analytical vectorial structure of non-paraxial four-petal Gaussian beams(FPGBs) in the far field has been studied based on vector angular spectrum method and stationary phase method. In terms of analytical electromagnetic representations of the TE and TM terms, the energy flux distributions of the TE term, the TM term, and the whole beam are derived in the far field, respectively. According to our investigation, the FPGBs can evolve into a number of small petals in the far field. The number of the petals is determined by the order of input beam. The physical pictures of the FPGBs are well illustrated from the vectorial structure, which is beneficial to strengthen the understanding of vectorial properties of the FPGBs

Domain Adaptation with Incomplete Target Domains

Domain adaptation, as a task of reducing the annotation cost in a target domain by exploiting the existing labeled data in an auxiliary source domain, has received a lot of attention in the research community. However, the standard domain adaptation has assumed perfectly observed data in both domains, while in real world applications the existence of missing data can be prevalent. In this paper, we tackle a more challenging domain adaptation scenario where one has an incomplete target domain with partially observed data. We propose an Incomplete Data Imputation based Adversarial Network (IDIAN) model to address this new domain adaptation challenge. In the proposed model, we design a data imputation module to fill the missing feature values based on the partial observations in the target domain, while aligning the two domains via deep adversarial adaption. We conduct experiments on both cross-domain benchmark tasks and a real world adaptation task with imperfect target domains. The experimental results demonstrate the effectiveness of the proposed method