Identification of putative fungal reference genes with stable expression from large RNA-seq datasets

Abstract

RNA-sequencing (RNA-seq) is the dominant technology for genome-wide transcript quantification in various biological studies. The wide applications of RNA-seq have played an essential role in elucidating complex molecular mechanisms of fungal physiology, and have generated large volumes of related data that are valuable for further bioinformatic mining. In this study, we focus on identifying fungal reference genes from large available transcriptome datasets. In total, 44 candidate reference genes from Aspergillus niger were identified through strict statistical analysis of 332 transcriptomic samples. These candidates cover both newly identified genes and previously reported housekeeping genes and were enriched in several basic cellular pathways, such as genes encoding ubiquitin-conjugating enzyme, 26S proteasome regulatory subunits, vacuolar H⁺-ATPase subunits, mitochondrial import protein and Ras-related GTPase. Moreover, 26 of the newly identified reference genes with a single ortholog in four other fungi showed stable expression patterns across these fungi. Additionally, these new candidates showed more stable expression than the traditionally used reference genes in the tested datasets, such as gapdh, highlighting their potential to improve normalization of RT-qPCR and transcriptome data.