Prediction and Investigation of Novel Proteins in DNA Double Stranded Break Repair
Bibliographic record
Abstract
DNA double stranded breaks (DSBs) are the most genotoxic forms of DNA lesions, causing fragmentation of the DNA strands.Mis-repaired and unrepaired DSBs lead to chromosomal rearrangement and genomic instability promoting tumorigenesis or cell death.DSBs are primarily repaired by two independent and highly conserved pathways: homologous recombination (HR) and non-homologous end joining (NHEJ).HR requires a homologous sequence to repair DNA breaks, whereas NHEJ repair is achieved through direct ligation of the broken ends of DNA.The process of NHEJ involves three main protein complexes: Yku70/Yku80 initiates and stabilizes the DNA ends, Mre11/Rad50/Xrs2 brings broken ends to close proximity and Dnl4/Lif1/Nej1 ligates the DNA ends.Protein-protein interaction (PPI) has been utilized in functional genomics studies to identify novel proteins involved in different pathways based on their PPI profiles.In this study we aim to screen for novel proteins involved in NHEJ using PPI predictions.We use a computational tool to predict novel PPIs between DNA repair proteins and human proteome.Using this method, we predicted 271 novel PPIs, expanding the reported human DNA repair interactome by 75%.Yeast homologs of the novel human gene candidates were subjected to a plasmid-based repair assay, in which deletion of eight of 12 yeast genes showed reduction in the repair efficiency.We further investigated the roles of Tpk1, Arp6 and Psk1/Psk2 in NHEJ repair.Deletion of any one of TPK1, ARP6, PSK1 and PSK2 reduced efficiency of repair in chromosomal and plasmid based assays and showed sensitivity to different DNA damaging agents.We suggest that Tpk1, catalytic subunit of protein kinase A, is involved in recruitment of Nej1 to the site of damage and its role in NHEJ is dependent on Nej1.We propose that the involvement of actin related protein 6, Arp6, in NHEJ is linked to Rsc2 and First and foremost, I would like to thank Dr. Golshani for giving me the opportunity to work in his lab.I would like to express my gratitude for his support, guidance and mentorship.But mostly thanks for your patience and believing in me, and for helping me to reach goals that would've not been possible without your supervision, inspiration and encouragement.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.003 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".