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Gene expression changes in phosphorus deficient potato (Solanum tuberosum L.) leaves and the potential for diagnostic gene expression markers
- Source :
- PLoS ONE, Vol 6, Iss 9, p e24606 (2011), PLoS ONE
- Publication Year :
- 2011
- Publisher :
- Public Library of Science (PLoS), 2011.
-
Abstract
- Background: There are compelling economic and environmental reasons to reduce our reliance on inorganic phosphate (Pi)\ud fertilisers. Better management of Pi fertiliser applications is one option to improve the efficiency of Pi fertiliser use, whilst\ud maintaining crop yields. Application rates of Pi fertilisers are traditionally determined from analyses of soil or plant tissues.\ud Alternatively, diagnostic genes with altered expression under Pi limiting conditions that suggest a physiological\ud requirement for Pi fertilisation, could be used to manage Pifertiliser applications, and might be more precise than indirect\ud measurements of soil or tissue samples.\ud Results: We grew potato (Solanum tuberosum L.) plants hydroponically, under glasshouse conditions, to control their\ud nutrient status accurately. Samples of total leaf RNA taken periodically after Pi was removed from the nutrient solution were\ud labelled and hybridised to potato oligonucleotide arrays. A total of 1,659 genes were significantly differentially expressed\ud following Pi withdrawal. These included genes that encode proteins involved in lipid, protein, and carbohydrate\ud metabolism, characteristic of Pi deficient leaves and included potential novel roles for genes encoding patatin like proteins\ud in potatoes. The array data were analysed using a support vector machine algorithm to identify groups of genes that could\ud predict the Pi status of the crop. These groups of diagnostic genes were tested using field grown potatoes that had either\ud been fertilised or unfertilised. A group of 200 genes could correctly predict the Pi status of field grown potatoes.\ud Conclusions: This paper provides a proof-of-concept demonstration for using microarrays and class prediction tools to\ud predict the Pi status of a field grown potato crop. There is potential to develop this technology for other biotic and abiotic\ud stresses in field grown crops. Ultimately, a better understanding of crop stresses may improve our management of the crop,\ud improving the sustainability of agriculture.
- Subjects :
- Support Vector Machine
Gene Expression
lcsh:Medicine
Crops
Plant Science
Biology
Plant Genetics
Crop
Agricultural Production
Gene Expression Regulation, Plant
Gene expression
Genetics
Arabidopsis thaliana
Fertilizers
lcsh:Science
Gene
SB
Plant Proteins
Solanum tuberosum
Crop Genetics
Plant Growth and Development
Multidisciplinary
Gene Expression Profiling
Crop yield
fungi
lcsh:R
food and beverages
Agriculture
Phosphorus
biology.organism_classification
Crop Management
Plant Leaves
Gene expression profiling
Agronomy
Plant Physiology
lcsh:Q
Patatin
Agrochemicals
High-Input Farming
Research Article
Subjects
Details
- Language :
- English
- ISSN :
- 19326203
- Volume :
- 6
- Issue :
- 9
- Database :
- OpenAIRE
- Journal :
- PLoS ONE
- Accession number :
- edsair.doi.dedup.....610a4b968fe301c25425d85ea7f8ef9d