Department of Plant and Microbial Biology, University of Minnesota, Saint Paul, MN, United States.
Earth and Biological Sciences Divisions, Pacific Northwest National Laboratory, Richland, WA 99354, United States.
Fungal Genet Biol. 2019 Feb;123:33-40. doi: 10.1016/j.fgb.2018.11.005. Epub 2018 Dec 5.
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.
木质素分解真菌能够有效地分解植物木质纤维素，因此人们越来越感兴趣于对这些真菌的基因调控策略进行研究和利用，以促进木质素分解。这些真菌机制的正确解释依赖于基因表达的准确量化，这就要求使用可靠的内参基因（ICG）作为参考。然而，在特定条件下，常用的 ICG，如肌动蛋白，在木质素分解真菌中会发生波动。在本研究中，我们通过计算机挖掘 RNA-seq 数据，并使用 qRT-PCR 在体外验证 ICG，旨在为研究木质素分解真菌的转录响应寻找更可靠的 ICG，特别是在各种培养条件下对环境变化（如碳源、分解阶段）的响应。在第一个研究中，我们以模式褐腐菌 Postia placenta 为模型，通过挖掘努力，得到了 15 个在可变碳源（如无碳、葡萄糖、纤维二糖、白杨）和培养阶段（如 15 h、72 h）下在液体培养中稳定表达的组成型基因。其中，我们发现 7 个基因是最合适的 ICG。通过 NormFinder 算法和 qRT-PCR 分析，这些新选择的 ICG 的表达稳定性优于常用的 ICG。在第二个固体木材的多物种研究中，我们的 RNA-seq 挖掘工作揭示了四种木质素分解真菌（褐腐菌、白腐菌）在不同营养模式下具有数百个高度组成型表达的基因，包括一个数量为 11 个的共享核心 ICG 集。总之，这里新选择的 ICG 将提高研究木质素分解真菌基因调控机制的可靠性。
