Gene expression changes in phosphorus deficient potato (Solanum tuberosum L.) leaves and the potential for diagnostic gene expression markers.
Gene expression changes in phosphorus deficient potato (Solanum tuberosum L.) leaves and the potential for diagnostic gene expression markers.
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DOI：
10.1371/journal.pone.0024606
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发表时间：
2011
期刊：
影响因子：
3.7
通讯作者：
White PJ
中科院分区：
文献类型：
--
作者：
Hammond JP;Broadley MR;Bowen HC;Spracklen WP;Hayden RM;White PJ
有令人信服的经济和环境原因来减少我们对无机磷酸盐（Pi）肥料的依赖。更好地管理磷肥施用是提高磷肥使用效率，同时保持作物产量的一种选择。传统上，磷肥的施用量是通过分析土壤或植物组织来确定的。或者，在Pi限制条件下具有改变的表达的诊断基因表明Pi施肥的生理要求，可用于管理Pi施肥应用，并且可能比土壤或组织样品的间接测量更精确。我们种植马铃薯（Solanum tuberosum L.）植物水培，在温室条件下，以控制其营养状况准确。将Pi从营养液中除去后定期采集的总叶RNA样品标记并与马铃薯寡核苷酸阵列杂交。总共有1，659个基因在Pi停药后显著差异表达。这些包括编码参与脂质、蛋白质和碳水化合物代谢的蛋白质的基因，这些蛋白质是缺磷叶片的特征，还包括编码马铃薯糖蛋白样蛋白的基因在马铃薯中的潜在新作用。使用支持向量机算法分析阵列数据，以识别可以预测作物Pi状态的基因组。这些诊断基因组是用田间种植的土豆进行测试的，这些土豆要么施肥，要么不施肥。一组200个基因可以正确预测田间种植的土豆的Pi状态。本文提供了一个概念验证的演示，使用微阵列和类预测工具来预测田间种植的马铃薯作物的Pi状态。有潜力开发这种技术用于其他生物和非生物胁迫在田间生长的作物。最终，更好地了解作物压力可能会改善我们对作物的管理，提高农业的可持续性。
There are compelling economic and environmental reasons to reduce our reliance on inorganic phosphate (Pi) fertilisers. Better management of Pi fertiliser applications is one option to improve the efficiency of Pi fertiliser use, whilst maintaining crop yields. Application rates of Pi fertilisers are traditionally determined from analyses of soil or plant tissues. Alternatively, diagnostic genes with altered expression under Pi limiting conditions that suggest a physiological requirement for Pi fertilisation, could be used to manage Pifertiliser applications, and might be more precise than indirect measurements of soil or tissue samples. We grew potato (Solanum tuberosum L.) plants hydroponically, under glasshouse conditions, to control their nutrient status accurately. Samples of total leaf RNA taken periodically after Pi was removed from the nutrient solution were labelled and hybridised to potato oligonucleotide arrays. A total of 1,659 genes were significantly differentially expressed following Pi withdrawal. These included genes that encode proteins involved in lipid, protein, and carbohydrate metabolism, characteristic of Pi deficient leaves and included potential novel roles for genes encoding patatin like proteins in potatoes. The array data were analysed using a support vector machine algorithm to identify groups of genes that could predict the Pi status of the crop. These groups of diagnostic genes were tested using field grown potatoes that had either been fertilised or unfertilised. A group of 200 genes could correctly predict the Pi status of field grown potatoes. This paper provides a proof-of-concept demonstration for using microarrays and class prediction tools to predict the Pi status of a field grown potato crop. There is potential to develop this technology for other biotic and abiotic stresses in field grown crops. Ultimately, a better understanding of crop stresses may improve our management of the crop, improving the sustainability of agriculture.
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影响因子：
6.9
作者：
Broadley, MR;Bowen, HC;White, PJ
通讯作者：
White, PJ
DOI：
10.1073/pnas.95.4.1950
发表时间：
1998-02-17
影响因子：
11.1
作者：
Essigmann, B;Güler, S;Benning, C
通讯作者：
Benning, C
影响因子：
7.2
作者：
Gaude, Nicole;Nakamura, Yuki;Doermann, Peter
通讯作者：
Doermann, Peter
影响因子：
6.9
作者：
Hammond, John P.;Broadley, Martin R.;Greenwood, Duncan J.
通讯作者：
Greenwood, Duncan J.
影响因子：
6.9
作者：
Calderon-Vazquez, Carlos;Ibarra-Laclette, Enrique;Herrera-Estrella, Luis
通讯作者：
Herrera-Estrella, Luis