LC3B drives transcription-associated homologous recombination via direct interaction with R-loops.
Junghyun YoonYiseul HwangHansol YunJee Min ChungSoyeon KimGyeongmin KimYeji LeeByoung Dae LeeHo Chul KangPublished in: Nucleic acids research (2024)
Exploring the connection between ubiquitin-like modifiers (ULMs) and the DNA damage response (DDR), we employed several advanced DNA damage and repair assay techniques and identified a crucial role for LC3B. Notably, its RNA recognition motif (RRM) plays a pivotal role in the context of transcription-associated homologous recombination (HR) repair (TA-HRR), a particular subset of HRR pathways. Surprisingly, independent of autophagy flux, LC3B interacts directly with R-loops at DNA lesions within transcriptionally active sites via its RRM, promoting TA-HRR. Using native RNA immunoprecipitation (nRIP) coupled with high-throughput sequencing (nRIP-seq), we discovered that LC3B also directly interacts with the 3'UTR AU-rich elements (AREs) of BRCA1 via its RRM, influencing its stability. This suggests that LC3B regulates TA-HRR both proximal to and distal from DNA lesions. Data from our LC3B depletion experiments showed that LC3B knockdown disrupts end-resection for TA-HRR, redirecting it towards the non-homologous end joining (NHEJ) pathway and leading to chromosomal instability, as evidenced by alterations in sister chromatid exchange (SCE) and interchromosomal fusion (ICF). Thus, our findings unveil autophagy-independent functions of LC3B in DNA damage and repair pathways, highlighting its importance. This could reshape our understanding of TA-HRR and the interaction between autophagy and DDR.
Keyphrases
- dna damage
- dna repair
- simultaneous determination
- oxidative stress
- dna damage response
- cell death
- mass spectrometry
- liquid chromatography
- endoplasmic reticulum stress
- signaling pathway
- high throughput sequencing
- solid phase extraction
- small molecule
- single molecule
- circulating tumor
- cell free
- high resolution mass spectrometry
- rna seq
- deep learning
- single cell
- electronic health record