%0 Journal Article
%T Extending MapMan Ontology to Tobacco for Visualization of Gene Expression
%A Maurice H. T. Ling
%A Roel C. Rabara
%A Prateek Tripathi
%A Paul J. Rushton
%A Xijin Ge
%J Dataset Papers in Science
%D 2013
%R 10.7167/2013/706465
%X Microarrays are a large-scale expression profiling method which has been used to study the transcriptome of plants under various environmental conditions. However, manual inspection of microarray data is difficult at the genome level because of the large number of genes (normally at least 30£¿000) and the many different processes that occur within any given plant. MapMan software, which was initially developed to visualize microarray data for Arabidopsis, has been adapted to other plant species by mapping other species onto MapMan ontology. This paper provides a detailed procedure and the relevant computing codes to generate a MapMan ontology mapping file for tobacco (Nicotiana tabacum L.) using potato and Arabidopsis as intermediates. The mapping file can be used directly with our custom-made NimbleGen oligoarray, which contains gene sequences from both the tobacco gene space sequence and the tobacco gene index 4 (NTGI4) collection of ESTs. The generated dataset will be informative for scientists working on tobacco as their model plant by providing a MapMan ontology mapping file to tobacco, homology between tobacco coding sequences and that of potato and Arabidopsis, as well as adapting our procedure and codes for other plant species where the complete genome is not yet available. 1. Introduction Plants, being sessile organisms, must react and acclimatize to abiotic stresses to survive in various environmental conditions. Plants have developed various stress tolerance mechanisms, such as physiological and biochemical alterations, that result in adaptive or morphological changes. In crop production, understanding how cultivated crops respond to abiotic stress is crucial in developing new varieties that could tolerate stress without affecting potential yield. With the rapid development of technologies for functional genomics research, comprehensive analyses at the mRNA, protein, and metabolites level have become possible. This is leading to increased understanding of the complex regulatory networks associated with stress adaptation and tolerance [1]. Currently, microarrays are one of the most popular technologies for large-scale expression profiling because they allow the simultaneous detection of tens of thousands of transcripts at a reasonable cost [2]. The development of gene chips for model plants like Arabidopsis and rice and other species that have a sequenced genome has led to genome-wide transcriptional profiling from diverse tissues. This is a key tool for the identification of novel target genes for functional genomics [3]. Studies using
%U http://www.hindawi.com/journals/dpis/2013/706465/