Back

Large-scale RNA-seq mining reveals ciclopirox triggers TDP-43 cryptic exons

Sinha, I. R.; Sandal, P. S.; Burns, G. D.; Mallika, A. P.; Irwin, K. E.; Cruz, A. L. F.; Wang, V.; Rodriguez, J. L.; Wong, P. C.; Ling, J. P.

2024-03-30 neuroscience
10.1101/2024.03.27.587011 bioRxiv
Show abstract

Nuclear clearance and cytoplasmic aggregation of TDP-43 in neurons, initially identified in ALS-FTD, are hallmark pathological features observed across a spectrum of neurodegenerative diseases. We previously found that TDP-43 loss-of-function leads to the transcriptome-wide inclusion of deleterious cryptic exons in brains and biofluids post-mortem as well as during the presymptomatic stage of ALS-FTD, but upstream mechanisms that lead to TDP-43 dysregulation remain unclear. Here, we developed a web-based resource (SnapMine) to determine the levels of TDP-43 cryptic exon inclusion across hundreds of thousands of publicly available RNA sequencing datasets. We established cryptic exon inclusion across a variety of human cells and tissues to provide ground truth references for future studies on TDP-43 dysregulation. We then explored studies that were entirely unrelated to TDP-43 or neurodegeneration and found that ciclopirox olamine (CPX), an FDA-approved antifungal, can trigger the inclusion of TDP-43-associated cryptic exons in a variety of mouse and human primary cells. CPX induction of cryptic exon occurs via heavy metal toxicity and oxidative stress, suggesting that similar vulnerabilities could play a role in neurodegeneration. Our work demonstrates how diverse datasets can be linked through common biological features and underscores that public archives of sequencing data represent a vastly underutilized resource with tremendous potential for uncovering novel insights into complex biological mechanisms and diseases.

Matching journals

The top 10 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.