Deciphering the sex bias in housekeeping gene expression in adipose tissue: a comprehensive meta-analysis of transcriptomic studies

Biol Sex Differ. 2023 Apr 18;14(1):20. doi: 10.1186/s13293-023-00506-x.

Abstract

Background: As the housekeeping genes (HKG) generally involved in maintaining essential cell functions are typically assumed to exhibit constant expression levels across cell types, they are commonly employed as internal controls in gene expression studies. Nevertheless, HKG may vary gene expression profile according to different variables introducing systematic errors into experimental results. Sex bias can indeed affect expression display, however, up to date, sex has not been typically considered as a biological variable.

Methods: In this study, we evaluate the expression profiles of six classical housekeeping genes (four metabolic: GAPDH, HPRT, PPIA, and UBC, and two ribosomal: 18S and RPL19) to determine expression stability in adipose tissues (AT) of Homo sapiens and Mus musculus and check sex bias and their overall suitability as internal controls. We also assess the expression stability of all genes included in distinct whole-transcriptome microarrays available from the Gene Expression Omnibus database to identify sex-unbiased housekeeping genes (suHKG) suitable for use as internal controls. We perform a novel computational strategy based on meta-analysis techniques to identify any sexual dimorphisms in mRNA expression stability in AT and to properly validate potential candidates.

Results: Just above half of the considered studies informed properly about the sex of the human samples, however, not enough female mouse samples were found to be included in this analysis. We found differences in the HKG expression stability in humans between female and male samples, with females presenting greater instability. We propose a suHKG signature including experimentally validated classical HKG like PPIA and RPL19 and novel potential markers for human AT and discarding others like the extensively used 18S gene due to a sex-based variability display in adipose tissue. Orthologs have also been assayed and proposed for mouse WAT suHKG signature. All results generated during this study are readily available by accessing an open web resource ( https://bioinfo.cipf.es/metafun-HKG ) for consultation and reuse in further studies.

Conclusions: This sex-based research proves that certain classical housekeeping genes fail to function adequately as controls when analyzing human adipose tissue considering sex as a variable. We confirm RPL19 and PPIA suitability as sex-unbiased human and mouse housekeeping genes derived from sex-specific expression profiles, and propose new ones such as RPS8 and UBB.

Keywords: Adipose tissue; Housekeeping genes; Meta-analysis; Sex bias; Transcriptomics.

Plain language summary

Housekeeping genes (HKG) are involved in the maintenance of essential cellular functions. They usually present constant expression levels and are relevant because of their usefulness as internal controls in gene expression studies. However, HKG can vary the gene expression profile depending on different variables such as sex, introducing errors in the experimental results. In this study, we have performed an exhaustive systematic review and applied a massive analysis of expression data to check which HKG presents this bias and which do not. The results confirm that certain classical HKG do not perform adequately as controls when analyzing human adipose tissue considering sex as a variable. We further confirm the suitability of RPL19 and PPIA as human and mouse HKG without sex bias derived from sex-specific expression profiles, and propose new ones such as RPS8 and UBB. These results will be of great use in upcoming studies where expression data need to be normalized without the inclusion of sex bias.

Publication types

  • Meta-Analysis
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animals
  • Female
  • Gene Expression Profiling / methods
  • Genes, Essential*
  • Humans
  • Male
  • Mice
  • Microarray Analysis
  • Sexism
  • Transcriptome*