Sample Collection Protocol Effects on Quantification of Gene Expression in Potato Leaf Tissue
文献类型： 外文期刊
作者： Luo, Sainan 3 ; Tai, Helen 1 ; Zebarth, Bernie 1 ; Li, Xiu-Qing 1 ; Millard, Pete 2 ; De Koeyer, David 1 ; Xiong, Xing 1 ;
作者机构： 1.Agr & Agri Food Canada, Potato Res Ctr, Fredericton, NB E3B 4Z7, Canada
2.Macaulay Inst, Aberdeen AB15 8QH, Scotland
3.Hunan Acad Agr Sci, Inst Hort, Changsha 410125, Hunan, Peoples R China
关键词： RNA;liquid nitrogen;genes: expression;field temperature
期刊名称：PLANT MOLECULAR BIOLOGY REPORTER （ 影响因子：1.595； 五年影响因子：2.042 ）
ISSN：
年卷期：
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收录情况： SCI
摘要： New platforms allow quantification of gene expression from large, replicated experiments but current sampling protocols for plant tissue using immediate flash freezing in liquid nitrogen are a barrier to these high-throughput studies. In this study, we compared four sampling methods for RNA extraction for gene expression analysis: (1) the standard sampling method of flash freezing whole leaves in liquid nitrogen immediately upon removal from the plant; (2) incubation of excised leaf disks for 2 min at field temperature followed by flash freezing; (3) incubation of excised leaf disks for 1 h on ice followed by flash freezing; and (4) incubation of excised leaf disks for 1 h at field temperature followed by flash freezing. Gene expression analysis was done for 23 genes using nCounter, and normalization of the data was done using the geometric mean of five housekeeping genes. Quality of RNA was highest for protocol A and lowest for protocol D. Despite some differences in RNA quality, gene expression was not significantly different among protocols A, B, and C for any of the 23 genes. Expression of some genes was significantly different between protocol D and the other protocols. This study demonstrates that when sampling leaf disks for gene expression analysis, the time between tissue removal from the plant and flash freezing in liquid nitrogen can be extended. This increase in time allowable during sampling provides greater flexibility in sampling large replicated field experiments for statistical analysis of gene expression data.
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