Identification of microRNAs and their targets in tomato infected with Cucumber mosaic virus based on deep sequencing
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MicroRNAs (miRNAs) play important regulatory roles in plant development and stress responses. Tomato is an economically important vegetable crop in the world with publicly available genomic information database, but only a limited number of tomato miRNAs have been identified. In this study, two independent small RNA libraries from mock and Cucumber mosaic virus (CMV)-infected tomatoes were constructed, respectively, and sequenced with a high-throughput Illumina Solexa system. Based on sequence analysis and hairpin structure prediction, a total of 50 plant miRNAs and 273 potentially candidate miRNAs (PC-miRNAs) were firstly identified in tomato, with 12 plant miRNAs and 82 PC-miRNAs supported by both the 3p and 5p strands. Comparative analysis revealed that 79 miRNAs (including 15 new tomato miRNAs) and 40 PC-miRNAs were differentially expressed between the two libraries, and the expression patterns of some new tomato miRNAs and PC-miRNAs were further validated by qRT-PCR. Moreover, potential targets for some of the known and new tomato miRNAs were identified by the recently developed degradome sequencing approach, and target annotation indicated that they were involved in multiple biological processes, including transcriptional regulation and virus resistance. Gene ontology analysis of these target transcripts demonstrated that defense response- and photosynthesis-related genes were most affected in CMV-Fny-infected tomatoes. Because tomato is not only an important crop but also is a genetic model for basic biology research, our study contributes to the understanding of miRNAs in response to virus infection.
KeywordsCucumber mosaic virus Degradome analysis High-throughput sequencing MicroRNA
Cucumber mosaic virus
Small interfering RNA
RNA-induced silencing complex
Minimal folding free energy index
Potential candidate miRNA
Reverse transcription-quantitative polymerase chain reaction
This work was supported by the grants from the National Natural Science Foundation of China (30800716) and the Science Foundation of Zhejiang Sci-Tech University (ZSTU) under Grant No. 1016816-Y.