Scientific ReportsGenomicsPeer-reviewed journal article
Transcriptional targets of senataxin and E2 promoter binding factors are associated with neuro-degenerative pathways during increased autophagic flux
Aaron CaseyiD, Wenjun LiuiD, Leanne K. HeiniD, Timothy J. SargeantiD, Stephen PedersoniD, Ville‐Petteri MäkineniD
Abstract
Autophagy is an intracellular recycling process that degrades harmful molecules, maintains optimal composition of cellular organelles and enables survival during starvation. Previous studies have demonstrated how transcription factors (TFs) can increase autophagy with therapeutic potential (impaired autophagy in the ageing brain, in particular, may be an important risk factor for dementia). To investigate the transcriptional regulation of autophagy from a systems perspective, we induced autophagy by amino acid starvation and mTOR inhibition in HeLa, HEK 293 and SH-SY5Y cells and used RNA-seq to measure gene expression at three time points. We observed 453 differentially expressed (DE) genes due to starvation and 284 genes due to mTOR inhibition (PFDR < 0.05 in every cell line). Pathway analyses confirmed enrichment of genes implicated in Alzheimers (PFDR < 0.001 in SH-SY5Y and HeLa) and Parkinsons (PFDR [≤] 0.024 in SH-SY5Y and HeLa) diseases and amyotrophic lateral sclerosis (ALS, PFDR < 0.05 in 4 of 6 experiments). We then integrated Signaling Pathway Impact Analysis and TF target enrichment testing to predict which TF target genes were contributing to pathway perturbation. Differential expression of the Senataxin (SETX) target gene set was predicted to activate multiple neurodegenerative pathways (PFDR [≤] 0.04). Notably, SETX is a causal gene for a rare form of ALS. In the SH-SY5Y cells of neuronal origin, the E2F transcription family was predicted to activate Alzheimers disease pathway (PFDR [≤] 0.0065). SETX and E2F may be important mediators of transcriptional regulation of autophagy and may provide new therapeutic opportunities for neuro-degenerative conditions.
- organism: human
- assay: bulk RNA-seq
- research focus: differential expression
- approach: statistical model
- Citations
- 5
- FWCI
- 0.54
- Field percentile
- top 36%
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