Whole-transcriptome RNA sequencing reveals the global molecular responses and ceRNA regulatory network of mRNAs, lncRNAs, miRNAs and circRNAs in response to copper toxicity in Ziyang Xiangcheng (Citrus junos Sieb. Ex Tanaka)

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Abstract
Background: Copper (Cu) toxicity has become a potential threat for citrus production, but little is known about related mechanisms. This study aims to uncover the global landscape of mRNAs, long non-coding RNAs (lncRNAs), circular RNAs (circRNAs) and microRNAs (miRNAs) in response to Cu toxicity so as to construct a regulatory network of competing endogenous RNAs (ceRNAs) and to provide valuable knowledge pertinent to Cu response in citrus. Results: Tolerance of four commonly used rootstocks to Cu toxicity was evaluated, and ‘Ziyang Xiangcheng’ (Citrus junos) was found to be the most tolerant genotype. Then the roots and leaves sampled from ‘Ziyang Xiangcheng’ with or without Cu treatment were used for whole-transcriptome sequencing. In total, 5734 and 222 mRNAs, 164 and 5 lncRNAs, 45 and 17 circRNAs, and 147 and 130 miRNAs were identified to be differentially expressed (DE) in Cu-treated roots and leaves, respectively, in comparison with the control. Gene ontology enrichment analysis showed that most of the DEmRNAs and targets of DElncRNAs and DEmiRNAs were annotated to the categories of ‘oxidation-reduction’, ‘phosphorylation’, ‘membrane’, and ‘ion binding’. The ceRNA network was then constructed with the predicted pairs of DEmRNAs-DEmiRNAs and DElncRNAs-DEmiRNAs, which further revealed regulatory roles of these DERNAs in Cu toxicity. Conclusions: A large number of mRNAs, lncRNAs, circRNAs, and miRNAs in ‘Ziyang Xiangcheng’ were altered in response to Cu toxicity, which may play crucial roles in mitigation of Cu toxicity through the ceRNA regulatory network in this Cu-tolerant rootstock.
Funding Information
  • National Key Research and Development Program of China (2018YFD1000300, 2017YFD0202000)
  • National Natural Science Foundation of China (31772280)
  • National Citrus Engineering Research Center (NCERC2019001)

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