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High-throughput sequencing reveals microRNAs in response to heat stress in the head kidney of rainbow trout (Oncorhynchus mykiss)

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Abstract

Recently, the research of animal microRNAs (miRNAs) has attracted wide attention for its regulatory effect in the development process and the response to abiotic stresses. Rainbow trout is a commercially and cold water fish species, and usually encounters heat stress, which affects its growth and leads to a huge economic loss. But there were few investigations about the roles of miRNAs in heat stress in rainbow trout. In this study, miRNAs of rainbow trout which were involved in heat stress were identified by high-throughput sequencing of six small RNA libraries from head kidney tissues under control (18 °C) and heat-treated (24 °C) conditions. A total of 392 conserved miRNAs and 989 novel miRNAs were identified, of which 78 miRNAs were expressed in different response to heat stress. Ten of these miRNAs were further validated by quantitative real–time PCR. In addition to, including 393 negative correlation miRNA-target gene pairs, several important regulatory pathways were involved in heat stress of the potential target genes, including protein processing in endoplasmic reticulum, NOD-like receptor signaling pathway, and phagosome. Our data significantly advance understanding of heat stress regulatory mechanism of miRNA in the head kidney of rainbow trout, which provide a useful resource for the cultivation of rainbow trout.

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This work was supported by the National Natural Science Foundation of China (Grant no. 31660735).

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Correspondence to Zhe Liu.

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All the methods used in this study were carried out according to the guiding principles of the Chinese Legislation on the Use and Care of Laboratory Animals. Protocol was approved by the Institutional Ethic Committee of Gansu Agricultural University (GSAU).

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Ma, F., Liu, Z., Huang, J. et al. High-throughput sequencing reveals microRNAs in response to heat stress in the head kidney of rainbow trout (Oncorhynchus mykiss). Funct Integr Genomics 19, 775–786 (2019). https://doi.org/10.1007/s10142-019-00682-3

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