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. 2019 Feb:123:33-40.
doi: 10.1016/j.fgb.2018.11.005. Epub 2018 Dec 5.

Reference genes for accurate normalization of gene expression in wood-decomposing fungi

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Reference genes for accurate normalization of gene expression in wood-decomposing fungi

Jiwei Zhang et al. Fungal Genet Biol. 2019 Feb.

Abstract

Wood-decomposing fungi efficiently decompose plant lignocellulose, and there is increasing interest in characterizing and perhaps harnessing the fungal gene regulation strategies that enable wood decomposition. Proper interpretation of these fungal mechanisms relies on accurate quantification of gene expression, demanding reliable internal control genes (ICGs) as references. Commonly used ICGs such as actin, however, fluctuate among wood-decomposing fungi under defined conditions. In this study, by mining RNA-seq data in silico and validating ICGs in vitro using qRT-PCR, we targeted more reliable ICGs for studying transcriptional responses in wood-decomposing fungi, particularly responses to changing environments (e.g., carbon sources, decomposition stages) in various culture conditions. Using the model brown rot fungus Postia placenta in a first-pass study, our mining efforts yielded 15 constitutively-expressed genes robust in variable carbon sources (e.g., no carbon, glucose, cellobiose, aspen) and cultivation stages (e.g., 15 h, 72 h) in submerged cultures. Of these, we found 7 genes as most suitable ICGs. Expression stabilities of these newly selected ICGs were better than commonly used ICGs, analyzed by NormFinder algorithm and qRT-PCR. In a second-pass, multi-species study in solid wood, our RNA-seq mining efforts revealed hundreds of highly constitutively expressed genes among four wood-decomposing fungi with varying nutritional modes (brown rot, white rot), including a shared core set of ICGs numbering 11 genes. Together, the newly selected ICGs highlighted here will increase reliability when studying gene regulatory mechanisms of wood-decomposing fungi.

Keywords: Basidiomycete; Fungi; Gene expression quantification; Reference gene; Wood decomposition.

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