Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Document Type

Article

Publication Date

2019

Abstract

As one of the major organs, the liver plays vital roles in the homeostasis of an individual. Being able to identify master regulator genes, genes whose product can affect the activation or deactivation of other genes, will enrich our understanding of hepatic function and liver disease. Previously, our lab used genome-wide microarray data to identify several transcription factors that may play a key role in liver expression. Here we ask whether overexpression of these transcription factors in a non-liver cell would result in liver phenotype activation or general disruption of gene regulation. To this end, we stably introduced seven transcription factors that we identified as being liver-specific into a non-liver cell line, followed by whole-genome expression analysis. As controls, we introduced a neo-plasmid to monitor general plasmid effects, as well as the HNF1α gene, previously shown to rescue liver-specific gene expression. Results show that introduction of the neo-plasmid alone resulted in 9 genes activated and 58 genes repressed by ≥2.5 fold. Overexpression of transcription factors resulted in between 320 and 664 genes activated, and 158 and 348 genes repressed by ≥2.5 fold even after controlling for the neo-plasmid data. In some cases, we observed much overlap. For example, 41 genes were activated by 4 of the 4 transcription factors (HHEX, CREG, CREB, and HNF6), with CREG and CREB sharing activation of an additional 94 genes. Focusing on only hepatic genes, each of the transcription factors activated between 13 and 35 liver-specific genes. However, there was little overlap between which genes that were activated in each case. These results suggest that while over-expression of transcription factors may activate tissue-specific genes, there is also a general dysregulation of gene expression that must be considered when interpreting data.

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