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Garcia-Garcia, F.

Publications and source records attributed to Garcia-Garcia, F..

3 recordsLinked to original sources

Sex bias evaluation of classic and novel Housekeeping Genes in adipose tissue through the massive analysis of transcriptomics data

BackgroundAs 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. MethodsIn 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. ResultsJust 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. ConclusionsThis 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. HighlightsO_LIA computational strategy based on massive data analysis revealed that an accurate experimental design for adipose tissue requires the adequate selection of a sex-unbiased housekeeping genes (HKG). C_LIO_LIThe extensively used 18S gene displays sex-based variability in adipose tissue, although PPIA and RPL19 do not, and hence, represent robust HKG. C_LIO_LINew sex-unbiased human and mouse candidate HKG: RPS8 and UBB. C_LIO_LImetafun-HKG (https://bioinfo.cipf.es/metafun-HKG): a freely available web tool to allow users to review stable expression levels of candidate HKG along the large volume of FAIR data. C_LI

genomics↗

MetaFun: Unveiling sex differences in multiple omics studies through comprehensive functional meta-analysis

While sex-based differences in various health scenarios have been thoroughly acknowledged in the literature, we lack a deep analysis of sex as a variable in this context. To fill this knowledge gap, we created MetaFun as an easy-to-use web-based tool to meta-analyze multiple transcriptomic datasets with a sex-based perspective to gain major statistical power and biological soundness. Furthermore, MetaFun can be used to perform case-control meta-analyses, allowing researchers with basic programming skills to access this methodology. Availability and implementationMetaFun is freely available at http://bioinfo.cipf.es/metafun The back end was implemented in R and Java, and the front end was developed using Angular Contactfgarcia@cipf.es, mhidalgo@cipf.es Supplementary informationR code available at https://gitlab.com/ubb-cipf/metafunr

bioinformatics↗

Unveiling sex-based differences in the effects of alcohol abuse: a comprehensive functional meta-analysis of transcriptomic studies

The abuse of alcohol, one of the most popular psychoactive substances, can cause several pathological and psychological consequences, including alcohol use disorder (AUD). An impaired ability to stop or control alcohol intake despite adverse health or social consequences characterize AUD. While AUDs predominantly occur in men, growing evidence suggests the existence of distinct cognitive and biological consequences of alcohol dependence in women. The molecular and physiological mechanisms participating in these differential effects remain unknown. Transcriptomic technology permits the detection of the biological mechanisms responsible for such sex-based differences, which supports the subsequent development of novel personalized therapeutics to treat AUD. We conducted a systematic review and meta-analysis of transcriptomics studies regarding alcohol dependence in humans with representation from both sexes. For each study, we processed and analyzed transcriptomic data to obtain a functional profile of pathways and biological functions and then integrated the resulting data by meta-analysis to characterize any sex-based transcriptomic differences associated with AUD. Global results of the transcriptomic analysis revealed the association of decreased tissue regeneration, embryo malformations, altered intracellular transport, and increased rate of RNA and protein replacement with female AUD patients. Meanwhile, our analysis indicated that increased inflammatory response and blood pressure and a reduction in DNA repair capabilities associated with male AUD patients. In summary, our functional meta-analysis of transcriptomic studies provides evidence for differential biological mechanisms that AUD patients of differing sex. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=169 SRC="FIGDIR/small/254185v1_ufig1.gif" ALT="Figure 1"> View larger version (36K): org.highwire.dtl.DTLVardef@13c9becorg.highwire.dtl.DTLVardef@20aac4org.highwire.dtl.DTLVardef@ab5502org.highwire.dtl.DTLVardef@5a0d37_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioinformatics↗