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有机种植和常规种植马铃薯块茎转录组差异的鉴定和解读。

The identification and interpretation of differences in the transcriptomes of organically and conventionally grown potato tubers.

机构信息

RIKILT-Institute of Food Safety (Wageningen UR), Wageningen, The Netherlands.

出版信息

J Agric Food Chem. 2012 Mar 7;60(9):2090-101. doi: 10.1021/jf204696w. Epub 2012 Feb 22.

Abstract

In the European integrated research project SAFEFOODS, one of the aims was to further establish the potential of transcriptomics for the assessment of differences between plant varieties grown under different environmental conditions. Making use of the knowledge of cellular processes and interactions is one of the ways to obtain a better understanding of the differences found with transcriptomics. For the present study the potato genotype Santé was grown under both organic and conventional fertilizer, and each combined with either organic or conventional crop protection, giving four different treatments. Samples were derived from the European project QualityLowInputFood (QLIF). Microarray data were analyzed using different statistical tools (multivariate, principal components analysis (PCA); univariate, analysis of variance (ANOVA)) and with pathway analysis (hypergeometric distribution (HGD) and gene set enrichment analysis (GSEA)). Several biological processes were implicated as a result of the different treatments of the plants. Most obvious were the lipoxygenase pathway, with higher expression in organic fertilizer and lower expression in organic crop protection; the starch synthase pathway, with higher expression in both organic crop protection and fertilizer; and the biotic stress pathway, with higher expression in organic fertilizer. This study confirmed that gene expression profiling in combination with pathway analysis can identify and characterize differences between plants grown under different environmental conditions.

摘要

在欧洲综合研究项目 SAFEFOODS 中,其目标之一是进一步确定转录组学在评估不同环境条件下生长的植物品种差异方面的潜力。利用细胞过程和相互作用的知识是更好地理解转录组学发现的差异的方法之一。本研究以马铃薯基因型 Santé 为材料,在有机和常规肥料下生长,并分别与有机或常规作物保护相结合,共得到四种不同的处理。样品来自欧洲项目 QualityLowInputFood (QLIF)。使用不同的统计工具(多元分析、主成分分析 (PCA);单变量分析、方差分析 (ANOVA))和途径分析(超几何分布 (HGD) 和基因集富集分析 (GSEA))对微阵列数据进行了分析。由于植物的不同处理,涉及到几个生物学过程。最明显的是脂氧合酶途径,在有机肥料中表达较高,在有机作物保护中表达较低;淀粉合酶途径,在有机作物保护和肥料中表达较高;以及生物胁迫途径,在有机肥料中表达较高。本研究证实,基因表达谱分析结合途径分析可以识别和描述不同环境条件下生长的植物之间的差异。

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