Back

The long non-coding RNA LINDA restrains cellular collapse following DNA damage in Arabidopsis thaliana

Herbst, J.; Nagy, S. H.; Vercauteren, I.; De Veylder, L.; Kunze, R.

2023-06-29 plant biology
10.1101/2023.06.28.546876 bioRxiv
Show abstract

The genomic integrity of every organism is endangered by various intrinsic and extrinsic stresses. To maintain the genomic integrity, a sophisticated DNA damage response (DDR) network is activated rapidly after DNA damage. Notably, the fundamental DDR mechanisms are conserved in eukaryotes. However, knowledge about many regulatory aspects of the plant DDR is still limited. Important, yet little understood, regulatory factors of the DDR are the long non-coding RNAs (lncRNAs). In humans, 13 lncRNAs functioning in DDR have been characterized to date, whereas no such lncRNAs have been characterized in plants yet. By meta-analysis, we identified the long intergenic non-coding RNA induced by DNA damage (LINDA) that responds strongly to various DNA double-strand break-inducing treatments, but not to replication stress induced by mitomycin C. After DNA damage, LINDA is rapidly induced in an ATM- and SOG1-dependent manner. Intriguingly, the transcriptional response of LINDA to DNA damage is similar to that of its flanking hypothetical protein-encoding gene. Phylogenetic analysis of putative Brassicales and Malvales LINDA homologs indicates that LINDA lncRNAs originate from duplication of a flanking small protein-encoding gene followed by pseudogenization. We demonstrate that LINDA is not only needed for the regulation of this flanking gene, but also for fine-tuning of the DDR after the occurrence of DNA double-strand breaks. Moreover, {Delta}linda mutant root stem cells are unable to recover from DNA damage, most likely due to hyper-induced cell death. SIGNIFICANT STATEMENTWe unraveled the functional relevance of the first lncRNA within the DNA damage response network of Arabidopsis thaliana. This lncRNA, termed LINDA, is an important part of the DNA damage response network, as it is needed for accurate regulation of cell death and cell cycle progression.

Matching journals

The top 5 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.