Identification of nitrogen starvation-responsive microRNAs in Chrysanthemum nankingense.
Identification of nitrogen starvation-responsive microRNAs in Chrysanthemum nankingense.
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DOI：
10.1016/j.plaphy.2015.04.003
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发表时间：
2015-06
期刊：
影响因子：
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通讯作者：
A. Song;Linxiao Wang;Sumei Chen;Jiafu Jiang;Z. Guan;Pei-ling Li;Fadi Chen
中科院分区：
文献类型：
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作者：
A. Song;Linxiao Wang;Sumei Chen;Jiafu Jiang;Z. Guan;Pei-ling Li;Fadi Chen
MicroRNA（miRNA）参与植物的许多发育过程和各种非生物胁迫反应。由于氮是植物生长的限制因素，比较分析响应低氮胁迫的miRNA对于提高氮利用效率（NUE）非常重要。我们采用高通量测序技术检测了菊花根和叶中miRNAs对低氮胁迫的响应。与对照相比，根中差异表达的miRNAs有81个，叶中差异表达的miRNAs有101个。鉴定出的miRNA对根和叶中的硝酸盐限制表现出重叠或独特的反应，包括具有低氮胁迫反应的已知miRNA家族的几个成员，例如miR 156、miR 169和miR 393。这些miRNAs的潜在靶基因也被确定。预测的靶基因总数为219个，根中对应的匹配miRNAs数量为37个，叶中为44个。此外，我们还利用5′ RLM-RACE对4个预测的靶基因进行了切割位点的定位。通过实时定量聚合酶链反应（qRT-PCR）验证miRNAs和靶基因的差异表达水平。根据预测的靶基因的功能特点，将其分为转录因子、激酶和代谢三大类。
MicroRNA (miRNA) is involved in many developmental processes and various abiotic stress responses in plants. As nitrogen is a limited element for plant growth, comparative analyses of miRNAs responding to low nitrogen stress is important for improving the nitrogen use efficiency (NUE). We used high-throughput sequencing to detect the response of miRNAs to low nitrogen stress in the roots and leaves ofChrysanthemum nankingense. Compared with the control, the differential expression was more than 2-fold in 81 miRNAs in roots and 101 miRNAs in leaves. The identified miRNAs showed overlapping or unique response to nitrate limitation in roots and leaves, including several members of known miRNA families with low nitrogen stress response, such as miR156, miR169, and miR393. The potential target genes of these miRNAs were also identified. The total amount of predicted target genes was 219, and the corresponding amount of matched miRNAs was 37 in roots and 44 in leaves. Moreover, we used 5′ RLM-RACE to map the cleavage sites in four predicted target genes. The differential expression level of miRNAs and target genes was verified by quantitative real-time polymerase chain reaction (qRT-PCR). According to the functional characteristics of the predicted target genes, they were divided into three main categories: transcription factors, kinases, and metabolism.