Title: Weighted Gene Correlation Network Analysis (WGCNA) Reveals Novel Transcription Factors Associated With Bisphenol A Dose-Response.

Authors: Maertens, Alexandra; Tran, Vy; Kleensang, Andre; Hartung, Thomas

Published In Front Genet, (2018)

Abstract: Despite Bisphenol-A (BPA) being subject to extensive study, a thorough understanding of molecular mechanism remains elusive. Here we show that using weighted gene correlation network analysis (WGCNA), which takes advantage of a graph theoretical approach to understanding correlations amongst genes and grouping genes into modules that typically have co-ordinated biological functions and regulatory mechanisms, that despite some commonality in altered genes, there is minimal overlap between BPA and estrogen in terms of network topology. We confirmed previous findings that ZNF217 and TFAP2C are involved in the estrogen pathway, and are implicated in BPA as well, although for BPA they appear to be active in the absence of canonical estrogen-receptor driven gene expression. Furthermore, our study suggested that PADI4 and RACK7/ZMYNDB8 may be involved in the overlap in gene expression between estradiol and BPA. Lastly, we demonstrated that even at low doses there are unique transcription factors that appear to be driving the biology of BPA, such as SREBF1. Overall, our data is consistent with other reports that BPA leads to subtle gene changes rather than profound aberrations of a conserved estrogen signaling (or other) pathways.

PubMed ID: 30483308

MeSH Terms: No MeSH terms associated with this publication