GENCODE: reference annotation for the human and mouse genomes in 2023.

GENCODE produces high quality gene and transcript annotation for the human and mouse genomes. All GENCODE annotation is supported by experimental data and serves as a reference for genome biology and clinical genomics. The GENCODE consortium generates targeted experimental data, develops bioinformatic tools and carries out analyses that, along with externally produced data and methods, support the identification and annotation of transcript structures and the determination of their function. Here, we present an update on the annotation of human and mouse genes, including developments in the tools, data, analyses and major collaborations which underpin this progress. For example, we report the creation of a set of non-canonical ORFs identified in GENCODE transcripts, the LRGASP collaboration to assess the use of long transcriptomic data to build transcript models, the progress in collaborations with RefSeq and UniProt to increase convergence in the annotation of human and mouse protein-coding genes, the propagation of GENCODE across the human pan-genome and the development of new tools to support annotation of regulatory features by GENCODE. Our annotation is accessible via Ensembl, the UCSC Genome Browser and https://www.gencodegenes.org.

Non-redundant functions of H2A.Z.1 and H2A.Z.2 in chromosome segregation and cell cycle progression.

H2A.Z is a H2A-type histone variant essential for many aspects of cell biology, ranging from gene expression to genome stability. From deuterostomes, H2A.Z evolved into two paralogues, H2A.Z.1 and H2A.Z.2, that differ by only three amino acids and are encoded by different genes (H2AFZ and H2AFV, respectively). Despite the importance of this histone variant in development and cellular homeostasis, very little is known about the individual functions of each paralogue in mammals. Here, we have investigated the distinct roles of the two paralogues in cell cycle regulation and unveiled non-redundant functions for H2A.Z.1 and H2A.Z.2 in cell division. Our findings show that H2A.Z.1 regulates the expression of cell cycle genes such as Myc and Ki-67 and its depletion leads to a G1 arrest and cellular senescence. On the contrary, H2A.Z.2, in a transcription-independent manner, is essential for centromere integrity and sister chromatid cohesion regulation, thus playing a key role in chromosome segregation.

GENCODE 2021.

The GENCODE project annotates human and mouse genes and transcripts supported by experimental data with high accuracy, providing a foundational resource that supports genome biology and clinical genomics. GENCODE annotation processes make use of primary data and bioinformatic tools and analysis generated both within the consortium and externally to support the creation of transcript structures and the determination of their function. Here, we present improvements to our annotation infrastructure, bioinformatics tools, and analysis, and the advances they support in the annotation of the human and mouse genomes including: the completion of first pass manual annotation for the mouse reference genome; targeted improvements to the annotation of genes associated with SARS-CoV-2 infection; collaborative projects to achieve convergence across reference annotation databases for the annotation of human and mouse protein-coding genes; and the first GENCODE manually supervised automated annotation of lncRNAs. Our annotation is accessible via Ensembl, the UCSC Genome Browser and https://www.gencodegenes.org.

Impact of Environmentally Relevant Concentrations of Bisphenol A (BPA) on the Gene Expression Profile in an In Vitro Model of the Normal Human Ovary.

Endocrine-disrupting chemicals (EDCs), including the xenoestrogen Bisphenol A (BPA), can interfere with hormonal signalling. Despite increasing reports of adverse health effects associated with exposure to EDCs, there are limited data on the effect of BPA in normal human ovaries. In this paper, we present a detailed analysis of the transcriptomic landscape in normal Human Epithelial Ovarian Cells (HOSEpiC) treated with BPA (10 and 100 nM). Gene expression profiles were determined using high-throughput RNA sequencing, followed by functional analyses using bioinformatics tools. In total, 272 and 454 differentially expressed genes (DEGs) were identified in 10 and 100 nM BPA-treated HOSEpiCs, respectively, compared to untreated controls. Biological pathways included mRNA surveillance pathways, oocyte meiosis, cellular senescence, and transcriptional misregulation in cancer. BPA exposure has a considerable impact on 10 genes: ANAPC2, AURKA, CDK1, CCNA2, CCNB1, PLK1, BUB1, KIF22, PDE3B, and CCNB3, which are also associated with progesterone-mediated oocyte maturation pathways. Future studies should further explore the effects of BPA and its metabolites in the ovaries in health and disease, making use of validated in vitro and in vivo models to generate data that will address existing knowledge gaps in basic biology, hazard characterisation, and risk assessment associated with the use of xenoestrogens such as BPA.

In Silico Study to Predict the Structural and Functional Consequences of SNPs on Biomarkers of Ovarian Cancer (OC) and BPA Exposure-Associated OC.

BACKGROUND: Recently, we have shown that seven genes, namely GBP5, IRS2, KRT4, LINCOO707, MRPL55, RRS1 and SLC4A11, have prognostic power for the overall survival in ovarian cancer (OC). METHODS: We present an analysis on the association of these genes with any phenotypes and mutations indicative of involvement in female cancers and predict the structural and functional consequences of those SNPS using in silico tools. RESULTS: These seven genes present with 976 SNPs/mutations that are associated with human cancers, out of which 284 related to female cancers. We have then analysed the mutation impact on amino acid polarity, charge and water affinity, leading to the identification of 30 mutations in gynaecological cancers where amino acid (aa) changes lead to opposite polarity, charges and water affinity. Out of these 30 mutations identified, only a missense mutation (i.e., R831C/R804C in uterine corpus endometrial carcinomas, UCEC) was suggestive of structural damage on the SLC4A11 protein. CONCLUSIONS: We demonstrate that the R831C/R804C mutation is deleterious and the predicted ΔΔG values suggest that the mutation reduces the stability of the protein. Future in vitro studies should provide further insight into the role of this transporter protein in UCEC.

Repeat associated mechanisms of genome evolution and function revealed by the Mus caroli and Mus pahari genomes.

Understanding the mechanisms driving lineage-specific evolution in both primates and rodents has been hindered by the lack of sister clades with a similar phylogenetic structure having high-quality genome assemblies. Here, we have created chromosome-level assemblies of the Mus caroli and Mus pahari genomes. Together with the Mus musculus and Rattus norvegicus genomes, this set of rodent genomes is similar in divergence times to the Hominidae (human-chimpanzee-gorilla-orangutan). By comparing the evolutionary dynamics between the Muridae and Hominidae, we identified punctate events of chromosome reshuffling that shaped the ancestral karyotype of Mus musculus and Mus caroli between 3 and 6 million yr ago, but that are absent in the Hominidae. Hominidae show between four- and sevenfold lower rates of nucleotide change and feature turnover in both neutral and functional sequences, suggesting an underlying coherence to the Muridae acceleration. Our system of matched, high-quality genome assemblies revealed how specific classes of repeats can play lineage-specific roles in related species. Recent LINE activity has remodeled protein-coding loci to a greater extent across the Muridae than the Hominidae, with functional consequences at the species level such as reproductive isolation. Furthermore, we charted a Muridae-specific retrotransposon expansion at unprecedented resolution, revealing how a single nucleotide mutation transformed a specific SINE element into an active CTCF binding site carrier specifically in Mus caroli, which resulted in thousands of novel, species-specific CTCF binding sites. Our results show that the comparison of matched phylogenetic sets of genomes will be an increasingly powerful strategy for understanding mammalian biology.

GENCODE reference annotation for the human and mouse genomes.

The accurate identification and description of the genes in the human and mouse genomes is a fundamental requirement for high quality analysis of data informing both genome biology and clinical genomics. Over the last 15 years, the GENCODE consortium has been producing reference quality gene annotations to provide this foundational resource. The GENCODE consortium includes both experimental and computational biology groups who work together to improve and extend the GENCODE gene annotation. Specifically, we generate primary data, create bioinformatics tools and provide analysis to support the work of expert manual gene annotators and automated gene annotation pipelines. In addition, manual and computational annotation workflows use any and all publicly available data and analysis, along with the research literature to identify and characterise gene loci to the highest standard. GENCODE gene annotations are accessible via the Ensembl and UCSC Genome Browsers, the Ensembl FTP site, Ensembl Biomart, Ensembl Perl and REST APIs as well as https://www.gencodegenes.org.

Comparative analysis of the transcriptome across distant species.

The transcriptome is the readout of the genome. Identifying common features in it across distant species can reveal fundamental principles. To this end, the ENCODE and modENCODE consortia have generated large amounts of matched RNA-sequencing data for human, worm and fly. Uniform processing and comprehensive annotation of these data allow comparison across metazoan phyla, extending beyond earlier within-phylum transcriptome comparisons and revealing ancient, conserved features. Specifically, we discover co-expression modules shared across animals, many of which are enriched in developmental genes. Moreover, we use expression patterns to align the stages in worm and fly development and find a novel pairing between worm embryo and fly pupae, in addition to the embryo-to-embryo and larvae-to-larvae pairings. Furthermore, we find that the extent of non-canonical, non-coding transcription is similar in each organism, per base pair. Finally, we find in all three organisms that the gene-expression levels, both coding and non-coding, can be quantitatively predicted from chromatin features at the promoter using a 'universal model' based on a single set of organism-independent parameters.

Comparative analysis of pseudogenes across three phyla.

Pseudogenes are degraded fossil copies of genes. Here, we report a comparison of pseudogenes spanning three phyla, leveraging the completed annotations of the human, worm, and fly genomes, which we make available as an online resource. We find that pseudogenes are lineage specific, much more so than protein-coding genes, reflecting the different remodeling processes marking each organism's genome evolution. The majority of human pseudogenes are processed, resulting from a retrotranspositional burst at the dawn of the primate lineage. This burst can be seen in the largely uniform distribution of pseudogenes across the genome, their preservation in areas with low recombination rates, and their preponderance in highly expressed gene families. In contrast, worm and fly pseudogenes tell a story of numerous duplication events. In worm, these duplications have been preserved through selective sweeps, so we see a large number of pseudogenes associated with highly duplicated families such as chemoreceptors. However, in fly, the large effective population size and high deletion rate resulted in a depletion of the pseudogene complement. Despite large variations between these species, we also find notable similarities. Overall, we identify a broad spectrum of biochemical activity for pseudogenes, with the majority in each organism exhibiting varying degrees of partial activity. In particular, we identify a consistent amount of transcription (∼15%) across all species, suggesting a uniform degradation process. Also, we see a uniform decay of pseudogene promoter activity relative to their coding counterparts and identify a number of pseudogenes with conserved upstream sequences and activity, hinting at potential regulatory roles.

Loregic: a method to characterize the cooperative logic of regulatory factors.

The topology of the gene-regulatory network has been extensively analyzed. Now, given the large amount of available functional genomic data, it is possible to go beyond this and systematically study regulatory circuits in terms of logic elements. To this end, we present Loregic, a computational method integrating gene expression and regulatory network data, to characterize the cooperativity of regulatory factors. Loregic uses all 16 possible two-input-one-output logic gates (e.g. AND or XOR) to describe triplets of two factors regulating a common target. We attempt to find the gate that best matches each triplet's observed gene expression pattern across many conditions. We make Loregic available as a general-purpose tool (github.com/gersteinlab/loregic). We validate it with known yeast transcription-factor knockout experiments. Next, using human ENCODE ChIP-Seq and TCGA RNA-Seq data, we are able to demonstrate how Loregic characterizes complex circuits involving both proximally and distally regulating transcription factors (TFs) and also miRNAs. Furthermore, we show that MYC, a well-known oncogenic driving TF, can be modeled as acting independently from other TFs (e.g., using OR gates) but antagonistically with repressing miRNAs. Finally, we inter-relate Loregic's gate logic with other aspects of regulation, such as indirect binding via protein-protein interactions, feed-forward loop motifs and global regulatory hierarchy.

Effect of MYC and PARP Inhibitors in Ovarian Cancer Using an In Vitro Model.

BACKGROUND/AIM: The 8q24 chromosomal region, which contains the MYC and PVT1 candidate oncogenes, is amplified in carcinomas. Both genes have been involved in the etiopathogenesis of ovarian cancer (OC). In this study, we used an in vitro OC model with a known 8q24 copy number increase and in silico tools to investigate the expression of MYC/PVT1 loci and copy number variation in OC. We also assessed the effects of rucaparib (a PARP inhibitor) in the presence or absence of 10058F4 (a MYC inhibitor) on the expression of MYC/linear PVT1/circular PVT1. MATERIALS AND METHODS: Tissue culture, chromosome preparation, RNA extraction, RT-qPCR, FISH, and wound healing assays were employed. OncoDB, cBioportal, UALKAN, and ROC Plotter in silico tools were also utilized. RESULTS: Although PVT1 and MYC expression levels remained unaltered in OC, putative copy number alterations across all cancers showed a marked difference between the two genes, particularly in gain and amplification for MYC. PVT1 expression demonstrated prognostic value for the treatment of patients with serous and endometrioid OC. Both genes correlated with PARP10, FAM83H, and DEPTOR. The use of rucaparib in the presence or absence of the MYC inhibitor (10058F4) in vitro, led to a significant down-regulation in the expression of MYC, linear, and circular PVT1. CONCLUSION: Our data provide a novel insight into the potential interactions of MYC and PVT1 with other genes. Moreover, we identified a new PARP inhibition mechanism down-regulating MYC, as well as the linear and circular PVT1 transcripts. Future work should expand on clinical studies to better understand the prognostic role of PVT1 in OC.

Transcriptional Landscape of 3D vs. 2D Ovarian Cancer Cell Models.

Three-dimensional (3D) cancer models are revolutionising research, allowing for the recapitulation of an in vivo-like response through the use of an in vitro system, which is more complex and physiologically relevant than traditional monolayer cultures. Cancers such as ovarian (OvCa) are prone to developing resistance, are often lethal, and stand to benefit greatly from the enhanced modelling emulated by 3D cultures. However, the current models often fall short of the predicted response, where reproducibility is limited owing to the lack of standardised methodology and established protocols. This meta-analysis aims to assess the current scope of 3D OvCa models and the differences in the genetic profiles presented by a vast array of 3D cultures. An analysis of the literature (Pubmed.gov) spanning 2012-2022 was used to identify studies with paired data of 3D and 2D monolayer counterparts in addition to RNA sequencing and microarray data. From the data, 19 cell lines were found to show differential regulation in their gene expression profiles depending on the bio-scaffold (i.e., agarose, collagen, or Matrigel) compared to 2D cell cultures. The top genes differentially expressed in 2D vs. 3D included C3, CXCL1, 2, and 8, IL1B, SLP1, FN1, IL6, DDIT4, PI3, LAMC2, CCL20, MMP1, IFI27, CFB, and ANGPTL4. The top enriched gene sets for 2D vs. 3D included IFN-α and IFN-γ response, TNF-α signalling, IL-6-JAK-STAT3 signalling, angiogenesis, hedgehog signalling, apoptosis, epithelial-mesenchymal transition, hypoxia, and inflammatory response. Our transversal comparison of numerous scaffolds allowed us to highlight the variability that can be induced by these scaffolds in the transcriptional landscape and identify key genes and biological processes that are hallmarks of cancer cells grown in 3D cultures. Future studies are needed to identify which is the most appropriate in vitro/preclinical model to study tumour microenvironments.

Pan-Cancer Analysis Identifies MNX1 and Associated Antisense Transcripts as Biomarkers for Cancer.

The identification of diagnostic and prognostic biomarkers is a major objective in improving clinical outcomes in cancer, which has been facilitated by the availability of high-throughput gene expression data. A growing interest in non-coding genomic regions has identified dysregulation of long non-coding RNAs (lncRNAs) in several malignancies, suggesting a potential use as biomarkers. In this study, we leveraged data from large-scale sequencing projects to uncover the expression patterns of the MNX1 gene and its associated lncRNAs MNX1-AS1 and MNX1-AS2 in solid tumours. Despite many reports describing MNX1 overexpression in several cancers, limited studies exist on MNX1-AS1 and MNX1-AS2 and their potential as biomarkers. By employing clustering methods to visualise multi-gene relationships, we identified a discriminative power of the three genes in distinguishing tumour vs. normal samples in several cancers of the gastrointestinal tract and reproductive systems, as well as in discerning oesophageal and testicular cancer histological subtypes. Notably, the expressions of MNX1 and its antisenses also correlated with clinical features and endpoints, uncovering previously unreported associations. This work highlights the advantages of using combinatory expression patterns of non-coding transcripts of differentially expressed genes as clinical evaluators and identifies MNX1, MNX1-AS1, and MNX1-AS2 expressions as robust candidate biomarkers for clinical applications.

Differential Regulation of Genes by the Glucogenic Hormone Asprosin in Ovarian Cancer.

Background: Ovarian cancer (OvCa) is one of the most lethal forms of gynaecological malignancy. Altered energy metabolism and increased aerobic glycolysis in OvCa are hallmarks that demand attention. The glucogenic hormone asprosin is often dysregulated in metabolic disorders such as insulin resistance, diabetes (type 2 and gestational), and preeclampsia. Despite association with metabolic disorders, its role in energy metabolism within the tumour microenvironment is yet to be explored. Here, we study the role of asprosin in OvCa using transcriptomics and expand on functional studies with clinical samples. Methods: RNA sequencing, functional gene enrichment analysis, Western blotting and ImageStream. Results: Following treatment with 100 nM of asprosin, the serous OvCa cell line, SKOV-3, displayed 160 and 173 gene regulatory changes, at 4 and 12 h respectively, when compared with control samples (p < 0.05 and Log2FC > 1). In addition to energy metabolism and glucose-related pathways, asprosin was shown to alter pathways associated with cell communication, TGF-ß signalling, and cell proliferation. Moreover, asprosin was shown to induce phosphorylation of ERK1/2 in the same in vitro model. Using liquid biopsies, we also report for novel expression of asprosin's predicted receptors OR4M1 and TLR4 in cancer-associated circulating cells; with significant reduction seen between pre-chemotherapy and end of first line chemotherapy, in addition to patients under maintenance with bevacizumab +/− olaparib for OR4M1. Conclusions: In relation to OvCa, asprosin appears to regulate numerous signalling pathways in-vitro. The prognostic potential of OR4M1 in liquid biopsies should also be explored further.

Engineered model of t(7;12)(q36;p13) AML recapitulates patient-specific features and gene expression profiles.

Acute myeloid leukaemia carrying the translocation t(7;12)(q36;p13) is an adverse-risk leukaemia uniquely observed in infants. Despite constituting up to 30% of cases in under 2-year-olds, it remains poorly understood. Known molecular features are ectopic overexpression of the MNX1 gene and generation of a fusion transcript in 50% of patients. Lack of research models has hindered understanding of t(7;12) biology, which has historically focused on MNX1 overexpression rather than the cytogenetic entity itself. Here, we employed CRISPR/Cas9 to generate t(7;12) in the human K562 cell line, and in healthy CD34+ haematopoietic progenitors where the translocation was not sustained in long-term cultures or through serial replating. In contrast, in K562 cells, t(7;12) was propagated in self-renewing clonogenic assays, with sustained myeloid bias in colony formation and baseline depletion of erythroid signatures. Nuclear localisation analysis revealed repositioning of the translocated MNX1 locus to the interior of t(7;12)-harbouring K562 nuclei - a known phenomenon in t(7;12) patients which associates with ectopic overexpression of MNX1. Crucially, the K562-t(7;12) model successfully recapitulated the transcriptional landscape of t(7;12) patient leukaemia. In summary, we engineered a clinically-relevant model of t(7;12) acute myeloid leukaemia with the potential to unravel targetable molecular mechanisms of disease.

Differential Expression of RAD51AP1 in Ovarian Cancer: Effects of siRNA In Vitro.

BACKGROUND: DNA double strand breaks can affect genome integrity potentially leading to cancer. RAD51-associated protein 1 (RAD51AP1), an accessory protein to RAD51, is critical for homologous recombination, a key DNA damage response pathway. Emerging studies indicate a novel role for RAD51AP1 in carcinogenesis. Here we provide additional insight into the role of RAD51AP1 in ovarian cancer (OvCa). METHODS: Gene expression and patient phenotype data were obtained from TCGA and GTEX project consortia for bioinformatics analysis. Immunohistochemistry of OvCa tissue microarray was undertaken. Functional analyses were performed in a SKOV3 OvCa cell line with down-regulation of RAD51AP1 using siRNA. RESULTS: RAD51AP1 is overexpressed at gene level in primary and recurrent OvCa compared to controls. At protein level, RAD51AP1 was up-regulated in low grade serous tumors compared to high grade OvCa. There was higher expression of RAD51AP1 in OvCa metastatic to lymph nodes compared to primary cancer samples. Gene enrichment analyses identified 12 differentially expressed genes (DEGs) related to OvCa, eight of which are also common in tissue from patients with type 2 diabetes mellitus (T2DM). CONCLUSIONS: RAD51AP1 is overexpressed in OvCa, Given the link between OvCa and T2DM, the eight-gene signature shows potential for predictive value.

GENCODE Pseudogenes.

Pseudogenes have long been considered nonfunctional elements. The influx of large-scale sequencing projects over the last decade have provided rich sources of evidence that pseudogenes can play key evolutionary and regulatory roles, highlighting the need for high quality annotation for both human and key model organisms. To date, GENCODE has completed the manual annotation of pseudogenes in human and has undertaken the task to curate and characterize pseudogenes in the mouse reference genome. Capitalizing on available high-quality annotations as well as on the functional-genomics, evolutionary, and phenotypical data, we were able to create a comprehensive picture of both the human and mouse pseudogene complements' creation, development, and activity. Thus, we found that while human pseudogenes were created through a single burst of retrotransposition events, the active transposable element content in mouse allows for a continuous renewal of the pseudogene pool. Despite their differences, the two organisms share a number of similarities in terms of pseudogene activity, with ~10% of pseudogenes being transcribed. Finally, we highlight a variety of resources developed based on the available GENCODE annotations that help shed light on pseudogene biology.

Pseudogenes as Biomarkers and Therapeutic Targets in Human Cancers.

Pseudogenes are commonly labeled as "junk DNA" given their perceived nonfunctional status. However, the advent of large-scale genomics projects prompted a revisit of pseudogene biology, highlighting their key functional and regulatory roles in numerous diseases, including cancers. Integrative analyses of cancer data have shown that pseudogenes can be transcribed and even translated, and that pseudogenic DNA, RNA, and proteins can interfere with the activity and function of key protein coding genes, acting as regulators of oncogenes and tumor suppressors. Capitalizing on the available clinical research, we are able to get an insight into the spread and variety of pseudogene biomarker and therapeutic potential. In this chapter, we describe pseudogenes that fulfill their role as diagnostic or prognostic biomarkers, both as unique elements and in collaboration with other genes or pseudogenes. We also report that the majority of prognostic pseudogenes are overexpressed and exert an oncogenic role in colorectal, liver, lung, and gastric cancers. Finally, we highlight a number of pseudogenes that can establish future therapeutic avenues.

Identification of Potential Bisphenol A (BPA) Exposure Biomarkers in Ovarian Cancer.

Endocrine-disrupting chemicals (EDCs) can exert multiple deleterious effects and have been implicated in carcinogenesis. The xenoestrogen Bisphenol A (BPA) that is found in various consumer products has been involved in the dysregulation of numerous signalling pathways. In this paper, we present the analysis of a set of 94 genes that have been shown to be dysregulated in presence of BPA in ovarian cancer cell lines since we hypothesised that these genes might be of biomarker potential. This study sought to identify biomarkers of disease and biomarkers of disease-associated exposure. In silico analyses took place using gene expression data extracted from The Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression (GTEx) databases. Differential expression was further validated at protein level using immunohistochemistry on an ovarian cancer tissue microarray. We found that 14 out of 94 genes are solely dysregulated in the presence of BPA, while the remaining 80 genes are already dysregulated (p-value < 0.05) in their expression pattern as a consequence of the disease. We also found that seven genes have prognostic power for the overall survival in OC in relation to their expression levels. Out of these seven genes, Keratin 4 (KRT4) appears to be a biomarker of exposure-associated ovarian cancer, whereas Guanylate Binding Protein 5 (GBP5), long intergenic non-protein coding RNA 707 (LINC00707) and Solute Carrier Family 4 Member 11 (SLC4A11) are biomarkers of disease. BPA can exert a plethora of effects that can be tissue- or cancer-specific. Our in silico findings generate a hypothesis around biomarkers of disease and exposure that could potentially inform regulation and policy making.

Is There a Link between Bisphenol A (BPA), a Key Endocrine Disruptor, and the Risk for SARS-CoV-2 Infection and Severe COVID-19?

Infection by the severe acute respiratory syndrome (SARS) coronavirus-2 (SARS-CoV-2) is the causative agent of a new disease (COVID-19). The risk of severe COVID-19 is increased by certain underlying comorbidities, including asthma, cancer, cardiovascular disease, hypertension, diabetes, and obesity. Notably, exposure to hormonally active chemicals called endocrine-disrupting chemicals (EDCs) can promote such cardio-metabolic diseases, endocrine-related cancers, and immune system dysregulation and thus, may also be linked to higher risk of severe COVID-19. Bisphenol A (BPA) is among the most common EDCs and exerts its effects via receptors which are widely distributed in human tissues, including nuclear oestrogen receptors (ERα and ERß), membrane-bound oestrogen receptor (G protein-coupled receptor 30; GPR30), and human nuclear receptor oestrogen-related receptor gamma. As such, this paper focuses on the potential role of BPA in promoting comorbidities associated with severe COVID-19, as well as on potential BPA-induced effects on key SARS-CoV-2 infection mediators, such as angiotensin-converting enzyme 2 (ACE2) and transmembrane serine protease 2 (TMPRSS2). Interestingly, GPR30 appears to exhibit greater co-localisation with TMPRSS2 in key tissues like lung and prostate, suggesting that BPA exposure may impact on the local expression of these SARS-CoV-2 infection mediators. Overall, the potential role of BPA on the risk and severity of COVID-19 merits further investigation.