Abstract
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, that contains gene sequences from both the tobacco gene space sequence and the tobacco gene index 4 (NTGI4) collection of ESTs. The generated data set 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.
Highlights
Plants, being sessile organisms, must react and acclimatize to abiotic stresses to survive in various environmental conditions
This is a key tool for the identification of novel target genes for functional genomics [3]
Studies using microarrays to characterize abiotic stress responses have been reported for model species such as the moss Physcomitrella patens [4], Arabidopsis thaliana [5, 6], Medicago truncatula [7, 8], and rice [9], as well as nonmodel species such as soybean [10] and Musa [11]
Summary
Plants, being sessile organisms, must react and acclimatize to abiotic stresses to survive in various environmental conditions. 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]. These tools were developed for microbial and animal systems and, secondly, flexibility is limited in terms of the display of family members (e.g., class of enzymes) [13] This limitation had been addressed by MapMan software [13], which relied on its own ontology to classify genes and metabolites and visualize the pathways and processes in pictorial diagrams in a modular system [15]. The dataset we have generated from this study will be a tool for scientists working on tobacco as their model plant by providing a MapMan ontology mapping file for tobacco and homology comparisons between tobacco coding sequences and those of potato and Arabidopsis. The code and data package can be downloaded from http://maurice.vodien.com/datasets/MapMan-Tobacco.rar
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