Optimizing gene expression analysis under hypoxia: identification and validation of novel reference genes in steroidogenic tissues and cell lines

Context: Signaling pathways that regulate steroidogenesis are known to be modulated by varying oxygen levels. Thus, appropriate internal controls unaffected by hypoxia are essential for accurate assessement of oxygen-dependent regulatory mechanisms in steroidogenic cells. Aims: To identify and validate novel reference genes (RG) for use in hypoxia-related studies with mouse steroidogenic cell lines. Methods: RNA-sequencing datasets from mouse steroidogenic cell lines (MA-10, MLTC-1, KK-1 and Y-1) cultured under varying oxygen levels were used to identify potential RGs, applying different assessment tools to evaluate their stability in mouse steroidogenic tissues and cell lines. Top-ranked RGs were evaluated in the normalization of selected target genes. Key results: Five potential RGs (Ap3d1, Cap1, Med15, Prpf8 and Sec62) and two commonly used RGs (Actb and Gapdh) were evaluated. Ap3d1, Med15 and Sec62 were identified as optimal RGs for normalizing target gene expression in steroidogenic cell lines. Well-established factors affected by hypoxia (Vegfa and Slc2a1) and steroidogenesis (Star) were normalized with the novel suggested RGs, and resulted in more reliable expression patterns in steroidogenic cells. Conclusions: The results of our study show there is no benchmark RG that can be widely used for gene expression normalization in hypoxia experiments with different steroidogenic samples and recommend Ap3d1, Med15 and Sec62 for steroidogenic cell lines. Implications: This study underscores the importance of carefully selecting stable RGs for accurate gene expression analysis in hypoxia-related steroidogenesis research. It provides a set of RGs to be used in studies aimed at understanding how oxygen availability influences hormone production.

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Publication Details

Journal
Universität Zürich, ZORA
Published
2025-11-24
DOI
https://doi.org/10.5167/uzh-283554
Primary Topic
Cancer, Hypoxia, and Metabolism
Type
article
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article

Optimizing gene expression analysis under hypoxia: identification and validation of novel reference genes in steroidogenic tissues and cell lines

Mariusz P. Kowalewski, Olivia Eilers Smith, Luiz Antonio Berto Gomes
Universität Zürich, ZORA
Cancer, Hypoxia, and Metabolism
article

Optimizing gene expression analysis under hypoxia: identification and validation of novel reference genes in steroidogenic tissues and cell lines

Mariusz P. Kowalewski, Olivia Eilers Smith, Luiz Antonio Berto Gomes
article en

Abstract

Context: Signaling pathways that regulate steroidogenesis are known to be modulated by varying oxygen levels. Thus, appropriate internal controls unaffected by hypoxia are essential for accurate assessement of oxygen-dependent regulatory mechanisms in steroidogenic cells. Aims: To identify and validate novel reference genes (RG) for use in hypoxia-related studies with mouse steroidogenic cell lines. Methods: RNA-sequencing datasets from mouse steroidogenic cell lines (MA-10, MLTC-1, KK-1 and Y-1) cultured under varying oxygen levels were used to identify potential RGs, applying different assessment tools to evaluate their stability in mouse steroidogenic tissues and cell lines. Top-ranked RGs were evaluated in the normalization of selected target genes. Key results: Five potential RGs (Ap3d1, Cap1, Med15, Prpf8 and Sec62) and two commonly used RGs (Actb and Gapdh) were evaluated. Ap3d1, Med15 and Sec62 were identified as optimal RGs for normalizing target gene expression in steroidogenic cell lines. Well-established factors affected by hypoxia (Vegfa and Slc2a1) and steroidogenesis (Star) were normalized with the novel suggested RGs, and resulted in more reliable expression patterns in steroidogenic cells. Conclusions: The results of our study show there is no benchmark RG that can be widely used for gene expression normalization in hypoxia experiments with different steroidogenic samples and recommend Ap3d1, Med15 and Sec62 for steroidogenic cell lines. Implications: This study underscores the importance of carefully selecting stable RGs for accurate gene expression analysis in hypoxia-related steroidogenesis research. It provides a set of RGs to be used in studies aimed at understanding how oxygen availability influences hormone production.

Universität Zürich, ZORA
Openalex Percentile: Top 31%
Cancer, Hypoxia, and Metabolism
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