Cross-Species Network Analysis Uncovers Conserved Nitrogen-Regulated Network Modules in Rice

In this study, we used a cross-species network approach to uncover nitrogen-regulated network modules conserved across a model and a crop species. By translating gene “network knowledge” from the data-rich model Arabidopsis (Arabidopsis thaliana) to a crop (Oryza sativa), we identified evolutionarily conserved N-regulatory modules as targets for translational studies to improve N-use efficiency in transgenic plants. To uncover such conserved N-regulatory network modules, we first generated a N-regulatory network based solely on rice (O. sativa) transcriptome and gene interaction data. Next, we enhanced the “network knowledge” in the rice N-regulatory network using transcriptome and gene interaction data from Arabidopsis and new data from Arabidopsis and rice plants exposed to the same N-treatment conditions. This cross-species network analysis uncovered a set of N-regulated transcription factors (TFs) predicted to target the same genes and network modules in both species. Supernode analysis of the TFs and their targets in these conserved network modules uncovered genes directly related to nitrogen use (e.g. N-assimilation) and to other shared biological processes indirectly related to nitrogen. This cross-species network approach was validated with members of two TF families in the supernode network, bZIP-TGA and HRS1/HHO family, have recently been experimentally validated to mediate the N-response in Arabidopsis.Fil: Obertello, Mariana. University of New York; Estados Unidos. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Investigaciones en Ingeniería Genética y Biología Molecular ; ArgentinaFil: Shrivastava, Stuti. University of New York; Estados UnidosFil: Katari, Manpreet S.. University of New York; Estados UnidosFil: Coruzzi, Gloria M.. University of New York; Estados Unido

GObar: a gene ontology based analysis and visualization tool for gene sets

BACKGROUND: Microarray experiments, as well as other genomic analyses, often result in large gene sets containing up to several hundred genes. The biological significance of such sets of genes is, usually, not readily apparent.Identification of the functions of the genes in the set can help highlight features of interest. The Gene Ontology Consortium 1 has annotated genes in several model organisms using a controlled vocabulary of terms and placed the terms on a Gene Ontology (GO), which comprises three disjoint hierarchies for Molecular functions, Biological processes and Cellular locations. The annotations can be used to identify functions that are enriched in the set, but this analysis can be misleading since the underlying distribution of genes among various functions is not uniform. For example, a large number of genes in a set might be kinases just because the genome contains many kinases. RESULTS: We use the Gene Ontology hierarchy and the annotations to pick significant functions and pathways by comparing the distribution of functions in a given gene list against the distribution of all the genes in the genome, using the hypergeometric distribution to assign probabilities. GObar is a web-based visualizer that implements this algorithm.The public website for GObar 2 can analyse gene lists from the yeast (S. cervisiae), fly (D. Melanogaster), mouse (M. musculus) and human (H. sapiens) genomes. It also allows visualization of the GO tree, as well as placement of a single gene on the GO hierarchy. We analyse a gene list from a genomic study of pre-mRNA splicing to demonstrate the utility of GObar. CONCLUSION: GObar is freely available as a web-based tool at http://katahdin.cshl.org:9331/GO2 and can help analyze and visualize gene lists from genomic analyses

Molecular basis of disease resistance in banana progenitor Musa Balbisiana against Xanthomonas Campestris pv. Musacearum

Open Access JournalBanana Xanthomonas wilt disease, caused by Xanthomonas campestris pv. musacearum (Xcm), is a major threat to banana production in east Africa. All cultivated varieties of banana are susceptible to Xcm and only the progenitor species Musa balbisiana was found to be resistant. The molecular basis of susceptibility and resistance of banana genotypes to Xcm is currently unknown. Transcriptome analysis of disease resistant genotype Musa balbisiana and highly susceptible banana cultivar Pisang Awak challenged with Xcm was performed to understand the disease response. The number of differentially expressed genes (DEGs) was higher in Musa balbisiana in comparison to Pisang Awak. Genes associated with response to biotic stress were up-regulated in Musa balbisiana. The DEGs were further mapped to the biotic stress pathways. Our results suggested activation of both PAMP-triggered basal defense and disease resistance (R) protein-mediated defense in Musa balbisiana as early response to Xcm infection. This study reports the first comparative transcriptome profile of the susceptible and resistant genotype of banana during early infection with Xcm and provide insights on the defense mechanism in Musa balbisiana, which can be used for genetic improvement of commonly cultivated banana varieties

Serum leptin and its relation to anthropometric measures of obesity in pre-diabetic Saudis

Background: Little information is available on leptin concentrations in individuals with IGT. This study aims to determine and correlate leptin levels to anthropometric measures of obesity in prediabetic, (IFG and IGT), type 2 diabetic and normoglycaemic Saudis. Methods: 308 adult Saudis (healthy controls n = 80; pre-diabetes n = 86; Type 2 diabetes n = 142) participated. Anthropometric parameters were measured and fasting blood samples taken. Serum insulin was analysed, using a solid phase enzyme amplified sensitivity immunoassay and also leptin concentrations, using radio-immunoassay. The remaining blood parameters were determined using standard laboratory procedures. Results: Leptin levels of diabetic and pre-diabetic men were higher than in normoglycaemic men (12.4 [3.2–72] vs 3.9 [0.8–20.0] ng/mL, (median [interquartile range], p = 0.0001). In females, leptin levels were significantly higher in pre-diabetic subjects (14.09 [2.8–44.4] ng/mL) than in normoglycaemic subjects (10.2 [0.25–34.8] ng/mL) (p = 0.046). After adjustment for BMI and gender, hip circumference was associated with log leptin (p = 0.006 with R2 = 0.086) among all subjects. Conclusion: Leptin is associated with measures of adiposity, hip circumference in particular, in the non-diabetic state among Saudi subjects. The higher leptin level among diabetics and pre-diabetics is not related to differences in anthropometric measures of obesity

In Silico Evaluation of Predicted Regulatory Interactions in Arabidopsis thaliana

<p>Abstract</p> <p>Background</p> <p>Prediction of transcriptional regulatory mechanisms in <it>Arabidopsis </it>has become increasingly critical with the explosion of genomic data now available for both gene expression and gene sequence composition. We have shown in previous work <abbrgrp><abbr bid="B1">1</abbr></abbrgrp>, that a combination of correlation measurements and <it>cis</it>-regulatory element (CRE) detection methods are effective in predicting targets for candidate transcription factors for specific case studies which were validated. However, to date there has been no quantitative assessment as to which correlation measures or CRE detection methods used alone or in combination are most effective in predicting TF→target relationships on a genome-wide scale.</p> <p>Results</p> <p>We tested several widely used methods, based on correlation (Pearson and Spearman Rank correlation) and <it>cis-</it>regulatory element (CRE) detection (≥1 CRE or CRE over-representation), to determine which of these methods individually or in combination is the most effective by various measures for making regulatory predictions. To predict the regulatory targets of a transcription factor (TF) of interest, we applied these methods to microarray expression data for genes that were regulated over treatment and control conditions in wild type (WT) plants. Because the chosen data sets included identical experimental conditions used on TF over-expressor or T-DNA knockout plants, we were able to test the TF→target predictions made using microarray data from WT plants, with microarray data from mutant/transgenic plants. For each method, or combination of methods, we computed sensitivity, specificity, positive and negative predictive value and the F-measure of balance between sensitivity and positive predictive value (precision). This analysis revealed that the ≥1 CRE and Spearman correlation (used alone or in combination) were the most balanced CRE detection and correlation methods, respectively with regard to their power to accurately predict regulatory-target interactions.</p> <p>Conclusion</p> <p>These findings provide an approach and guidance for researchers interested in predicting transcriptional regulatory mechanisms using microarray data that they generate (or microarray data that is publically available) combined with CRE detection in promoter sequence data.</p

Modeling the global effect of the basic-leucine zipper transcription factor 1 (bZIP1) on nitrogen and light regulation in Arabidopsis

Background: Nitrogen and light are two major regulators of plant metabolism and development. While genes involved in the control of each of these signals have begun to be identified, regulators that integrate gene responses to nitrogen and light signals have yet to be determined. Here, we evaluate the role of bZIP1, a transcription factor involved in light and nitrogen sensing, by exposing wild-type (WT) and bZIP1 T-DNA null mutant plants to a combinatorial space of nitrogen (N) and light (L) treatment conditions and performing transcriptome analysis. We use ANOVA analysis combined with clustering and Boolean modeling, to evaluate the role of bZIP1 in mediating L and N signaling genome-wide. Results: This transcriptome analysis demonstrates that a mutation in the bZIP1 gene can alter the L and/or N-regulation of several gene clusters. More surprisingly, the bZIP1 mutation can also trigger N and/or L regulation of genes that are not normally controlled by these signals in WT plants. This analysis also reveals that bZIP1 can, to a large extent, invert gene regulation (e. g., several genes induced by N in WT plants are repressed by N in the bZIP1 mutant). Conclusion: These findings demonstrate that the bZIP1 mutation triggers a genome-wide de-regulation in response to L and/or N signals that range from i) a reduction of the L signal effect, to ii) unlocking gene regulation in response to L and N combinations. This systems biology approach demonstrates that bZIP1 tunes L and N signaling relationships genome-wide, and can suppress regulatory mechanisms hypothesized to be needed at different developmental stages and/or environmental conditions

Integrated RNA-seq and sRNA-seq analysis identifies novel nitrate-responsive genes in Arabidopsis thaliana roots

Background:Nitrate and other nitrogen metabolites can act as signals that regulate global gene expression in plants. Adaptive changes in plant morphology and physiology triggered by changes in nitrate availability are partly explained by these changes in gene expression. Despite several genome-wide efforts to identify nitrate-regulated genes, no comprehensive study of the Arabidopsis root transcriptome under contrasting nitrate conditions has been carried out. Results:In this work, we employed the Illumina high throughput sequencing technology to perform an integrated analysis of the poly-A + enriched and the small RNA fractions of the Arabidopsis thaliana root transcriptome in response to nitrate treatments. Our sequencing strategy identified new nitrate-regulated genes including 40 genes not represented in the ATH1 Affymetrix GeneChip, a novel nitrate-responsive antisense transcript and a new nitrate responsive miRNA/TARGET module consisting of a novel microRNA, miR5640 and its target, AtPPC3. Conclusions:Sequencing of small RNAs and mRNAs uncovered new genes, and enabled us to develop new hypotheses for nitrate regulation and coordination of carbon and nitrogen metabolism

Clinical features of acute reversible tacrolimus (FK 506) nephrotoxicity in kidney transplant recipients

This study was designed to (a) estimate the contribution of tacrolimus nephrotoxicity to episodes of renal allograft dysfunction investigated by needle biopsy, (b) describe the temporal evolution of nephrotoxicity and its response to therapy, and (c) ascertain how often renal dysfunction is associated with concurrent extra-renal toxicity. Patients were selected based on a rising serum creatinine, normal ultrasound, and biopsy findings leading to a reduction in the dose of tacrolimus and a fall in serum creatinine. Twenty two (17%) cases of nephrotoxicity were identified amongst 128 consecutive kidney transplant biopsies with sufficient clinical data for analysis. There were 13 males and 9 females, 17-75 yr in age. Tacrolimus was administered initially as a 0.075-0.1 mg/kg/d IV continuous infusion followed by an oral dose of 0.15 mg/kg twice daily. The onset of nephrotoxicity in this study occurred 1-156 wk post-operatively. The mean baseline creatinine was 212.2 ± 168.0 μmol/l (range 88.4-875.2) and rose 40.6% ± 14.2% (range 11-66) during episodes of nephrotoxicity (p 5.0 mequiv./l was recorded in 9/22 (41%) cases. Three or more elevations in blood glucose > 7.7 mmol/l (140 mg/dl) were recorded in 4/11 (36%) non-diabetic patients. Hand tremors were seen in two (9%) cases and elevated diastolic blood pressure > 90 mmHg in seven (32%) patients. In conclusion, tacrolimus nephrotoxicity accounted for 17% of graft dysfunction episodes investigated by biopsy. Concurrent hyperglycemia, hyperkalemia, or tremors were noted in several patients. Nephrotoxicity responded well to reduction in the drug dosage