Identification and evaluation of suitable reference genes for RT-qPCR analyses in Trichoderma atroviride under varying light conditions

被引：4

作者：

Flatschacher D. ^{[1
]}

Eschlböck A. ^{[1
]}

Zeilinger S. ^{[1
]}

机构：

[1] Department of Microbiology, University of Innsbruck, Technikerstraße 25, Innsbruck

来源：

Fungal Biology and Biotechnology | / 10卷 / 1期

基金：

奥地利科学基金会;

关键词：

Photobiology; Reference genes; RT-qPCR; Trichoderma atroviride;

D O I：

10.1186/s40694-023-00167-w

中图分类号：

学科分类号：

摘要：

Background: Trichoderma atroviride is a competitive soil-borne mycoparasitic fungus with extensive applications as a biocontrol agent in plant protection. Despite its importance and application potential, reference genes for RT-qPCR analysis in T. atroviride have not been evaluated. Light exerts profound effects on physiology, such as growth, conidiation, secondary metabolism, and stress response in T. atroviride, as well as in other fungi. In this study, we aimed to address this gap by identifying stable reference genes for RT-qPCR experiments in T. atroviride under different light conditions, thereby enhancing accurate and reliable gene expression analysis in this model mycoparasite. We measured and compared candidate reference genes using commonly applied statistical algorithms. Results: Under cyclic light–dark cultivation conditions, tbp and rho were identified as the most stably expressed genes, while act1, fis1, btl, and sar1 were found to be the least stable. Similar stability rankings were obtained for cultures grown under complete darkness, with tef1 and vma1 emerging as the most stable genes and act1, rho, fis1, and btl as the least stable genes. Combining the data from both cultivation conditions, gapdh and vma1 were identified as the most stable reference genes, while sar1 and fis1 were the least stable. The selection of different reference genes had a significant impact on the calculation of relative gene expression, as demonstrated by the expression patterns of target genes pks4 and lox1. Conclusion: The data emphasize the importance of validating reference genes for different cultivation conditions in fungi to ensure accurate interpretation of gene expression data. © 2023, BioMed Central Ltd., part of Springer Nature.

引用

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