Silencing Agrobacterium oncogenes in transgenic grapevine results in strain-specific crown gall resistance

Key message

Grapevine rootstock transformed with an Agrobacterium oncogene-silencing transgene was resistant to certain Agrobacterium strains but sensitive to others. Thus, genetic diversity of Agrobacterium oncogenes may limit engineering crown gall resistance.

Abstract

Crown gall disease of grapevine induced by Agrobacterium vitis or Agrobacterium tumefaciens causes serious economic losses in viticulture. To establish crown gall-resistant lines, somatic proembryos of Vitis berlandieri × V. rupestris cv. ‘Richter 110’ rootstock were transformed with an oncogene-silencing transgene based on iaaM and ipt oncogene sequences from octopine-type, tumor-inducing (Ti) plasmid pTiA6. Twenty-one transgenic lines were selected, and their transgenic nature was confirmed by polymerase chain reaction (PCR). These lines were inoculated with two A. tumefaciens and three A. vitis strains. Eight lines showed resistance to octopine-type A. tumefaciens A348. Resistance correlated with the expression of the silencing genes. However, oncogene silencing was mostly sequence specific because these lines did not abolish tumorigenesis by A. vitis strains or nopaline-type A. tumefaciens C58.     

GOrilla: a tool for discovery and visualization of enriched GO terms in ranked gene lists

Background

Although expression microarrays have become a standard tool used by biologists, analysis of data produced by microarray experiments may still present challenges. Comparison of data from different platforms, organisms, and labs may involve complicated data processing, and inferring relationships between genes remains difficult.

Results

S TAR N ET 2 is a new web-based tool that allows post hoc visual analysis of correlations that are derived from expression microarray data. S TAR N ET 2 facilitates user discovery of putative gene regulatory networks in a variety of species (human, rat, mouse, chicken, zebrafish, Drosophila, C. elegans, S. cerevisiae, Arabidopsis and rice) by graphing networks of genes that are closely co-expressed across a large heterogeneous set of preselected microarray experiments. For each of the represented organisms, raw microarray data were retrieved from NCBI's Gene Expression Omnibus for a selected Affymetrix platform. All pairwise Pearson correlation coefficients were computed for expression profiles measured on each platform, respectively. These precompiled results were stored in a MySQL database, and supplemented by additional data retrieved from NCBI. A web-based tool allows user-specified queries of the database, centered at a gene of interest. The result of a query includes graphs of correlation networks, graphs of known interactions involving genes and gene products that are present in the correlation networks, and initial statistical analyses. Two analyses may be performed in parallel to compare networks, which is facilitated by the new H EAT S EEKER module.

Conclusion

S TAR N ET 2 is a useful tool for developing new hypotheses about regulatory relationships between genes and gene products, and has coverage for 10 species. Interpretation of the correlation networks is supported with a database of previously documented interactions, a test for enrichment of Gene Ontology terms, and heat maps of correlation distances that may be used to compare two networks. The list of genes in a S TAR N ET network may be useful in developing a list of candidate genes to use for the inference of causal networks. The tool is freely available at http://vanburenlab.medicine.tamhsc.edu/starnet2.html, and does not require user registration.     

Expression of hsp70, hsp100 and ubiquitin in Aloe barbadensis Miller under direct heat stress and under temperature acclimation conditions

Key message

The study determined the tolerance of Aloe vera to high temperature, focusing on the expression of hsp70 , hsp100 and ubiquitin genes. These were highly expressed in plants acclimated at 35 °C prior to a heat shock of 45 °C.

Abstract

Aloe barbadensis Miller (Aloe vera), a CAM plant, was introduced into Chile in the semiarid IV and III Regions, which has summer diurnal temperature fluctuations of 25 to 40 °C and annual precipitation of 40 mm (dry years) to 170 mm (rainy years). The aim of this study was to investigate how Aloe vera responds to water and heat stress, focusing on the expression of heat shock genes (hsp70, hsp100) and ubiquitin, which not studied before in Aloe vera. The LT₅₀ of Aloe vera was determined as 53.2 °C. To study gene expression by semi-quantitative RT-PCR, primers were designed against conserved regions of these genes. Sequencing the cDNA fragments for hsp70 and ubiquitin showed a high identity, over 95 %, with the genes from cereals. The protein sequence of hsp70 deduced from the sequence of the cDNA encloses partial domains for binding ATP and the substrate. The protein sequence of ubiquitin deduced from the cDNA encloses a domain for interaction with the enzymes E2, UCH and CUE. The expression increased with temperature and water deficit. Hsp70 expression at 40–45 °C increased 50 % over the controls, while the expression increased by 150 % over the controls under a water deficit of 50 % FC. The expression of all three genes was also studied under 2 h of acclimation at 35 or 40 °C prior to a heat shock at 45 °C. Under these conditions, the plants showed greater expression of all genes than when they were subjected to direct heat stress.     

Fitting hidden Markov models of protein domains to a target species: application to Plasmodium falciparum

Background

The identification of gene sets that are significantly impacted in a given condition based on microarray data is a crucial step in current life science research. Most gene set analysis methods treat genes equally, regardless how specific they are to a given gene set.

Results

In this work we propose a new gene set analysis method that computes a gene set score as the mean of absolute values of weighted moderated gene t-scores. The gene weights are designed to emphasize the genes appearing in few gene sets, versus genes that appear in many gene sets. We demonstrate the usefulness of the method when analyzing gene sets that correspond to the KEGG pathways, and hence we called our method P athway A nalysis with D own-weighting of O verlapping G enes (PADOG). Unlike most gene set analysis methods which are validated through the analysis of 2-3 data sets followed by a human interpretation of the results, the validation employed here uses 24 different data sets and a completely objective assessment scheme that makes minimal assumptions and eliminates the need for possibly biased human assessments of the analysis results.

Conclusions

PADOG significantly improves gene set ranking and boosts sensitivity of analysis using information already available in the gene expression profiles and the collection of gene sets to be analyzed. The advantages of PADOG over other existing approaches are shown to be stable to changes in the database of gene sets to be analyzed. PADOG was implemented as an R package available at: http://bioinformaticsprb.med.wayne.edu/PADOG/or http://www.bioconductor.org.