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Identification and validation of miRNA reference genes in poplar under pathogen stress.

Lichun ZhangXiaoqian YangYiyi YinJinxing WangYanwei Wang
Published in: Molecular biology reports (2021)
Quantitative real time polymerase chain reaction (qRT-PCR) is a common method to analyze gene expression. Due to differences in RNA quantity, quality, and reverse transcription efficiency between qRT-PCR samples, reference genes are used as internal standards to normalize gene expression. However, few universal genes, especially miRNAs, have been identified as reference so far. Therefore, it is essential to identify reference genes that can be used across various experimental conditions, stress treatments, or tissues. In this study, 14 microRNAs (miRNAs) and 5.8S rRNA were assessed for expression stability in poplar trees infected with canker pathogen. Using geNorm, NormFinder and Bestkeeper reference gene analysis programs, we found that miR156g and miR156a exhibited stable expression throughout the infection process. miR156g, miR156a and 5.8S rRNA were then tested as internal standards to measure the expression of miR1447 and miR171c, and the results were compared to small RNA sequencing (RNA-seq) data. We found that when miR156a and 5.8S rRNA were used as the reference gene, the expression of miR1447 and miR171c were consistent with the small RNA-seq expression profiles. Therefore, miR156a was the most stable miRNAs examined in this study, and could be used as a reference gene in poplar under canker pathogen stress, which should enable comprehensive comparisons of miRNAs expression and avoid the bias caused by different length between detected miRNAs and traditional reference genes. The present study has expanded the miRNA reference genes available for gene expression studies in trees under biotic stress.
Keyphrases
  • long non coding rna
  • cell proliferation
  • poor prognosis
  • gene expression
  • long noncoding rna
  • rna seq
  • genome wide
  • single cell
  • genome wide identification
  • bioinformatics analysis
  • copy number
  • mass spectrometry
  • big data