Abstract
The lack of reliable reference genes (RGs) in the genus Streptomyces hampers effort to obtain the precise data of transcript levels. To address this issue, we aimed to identify reliable RGs in the model organism Streptomyces coelicolor. A pool of potential RGs containing 1,471 genes was first identified by determining the intersection of genes with stable transcript levels from four time-series transcriptome microarray datasets of S. coelicolor M145 cultivated in different conditions. Then, following a strict rational selection scheme including homology analysis, disturbance analysis, function analysis and transcript abundance analysis, 13 candidates were selected from the 1,471 genes. Based on real-time quantitative reverse transcription PCR assays, SCO0710, SCO6185, SCO1544, SCO3183 and SCO4758 were identified as the top five genes with the most stable transcript levels among the 13 candidates. Further analyses showed these five genes also maintained stable transcript levels in different S. coelicolor strains, as well as in Streptomyces avermitilis MA-4680 and Streptomyces clavuligerus NRRL 3585, suggesting they could fulfill the requirements of accurate data normalization in streptomycetes. Moreover, the systematic strategy employed in this work could be used for reference in other microorganism to select reliable RGs.
Highlights
Represents the primary housekeeping regulator, which differs from the other sigma factors such as HrdA, SigB and WhiG3,4
To make sure of that, we accessed the major microarray databases, NCBI Gene Expression Omnibus (GEO) database and Stanford Microarray Database, and extracted three sets of time-series transcriptome microarray data of S. coelicolor M145: GSE1848918, GSE3056919 and GSE298320
To get reliable reference genes (RGs) as possible as we could, we carried out time-series transcriptome microarray experiments of S. coelicolor M145 in the liquid supplemented minimal medium (SMM), which is a widely used minimal medium in laboratory
Summary
Represents the primary housekeeping regulator, which differs from the other sigma factors such as HrdA, SigB and WhiG3,4. RGs were normally selected from a set of constitutively expressed genes obtained by qRT-PCR14,15 Compared to this technique, transcriptome microarray provides gene expression data at the genome scale and offers greater potential to mine credible RGs16,17. To provide reliable RGs for S. coelicolor strains, in this work, we applied statistical analysis to four different time-series microarray datasets of S. coelicolor and got the first pool containing genes with stable expression profiles. The top five genes with the most stable transcript levels showed the similar expression profiles in different S. coelicolor strains, indicating they are reliable as RGs for this species. These five genes possessed the constant transcript levels in other Streptomyces species, which implies their possibilities as RGs in the genus Streptomyces
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