Contextual diversity of the human cell-essential proteome
Bibliographic record
Abstract
Abstract Essential genes define central biological functions required for cell growth, proliferation and survival, but the nature of gene essentiality across human cell types is not well understood. We assessed essential gene function in a Cas9-inducible human B-cell lymphoma cell line using an extended knockout (EKO) library of 278,754 sgRNAs that targeted 19,084 RefSeq genes, 20,852 alternatively-spliced exons and 3,872 hypothetical genes. A new statistical analysis tool called RANKS identified 2,280 essential genes, 234 of which had not been reported previously. Essential genes exhibited a bimodal distribution across 10 cell lines screened in different studies, consistent with a continuous variation in essentiality as a function of cell type. Genes essential in more lines were associated with more severe fitness defects and encoded the evolutionarily conserved structural cores of protein complexes. Genes essential in fewer lines tended to form context-specific modules and encode subunits at the periphery of essential complexes. The essentiality of individual protein residues across the proteome correlated with evolutionary conservation, structural burial, modular domains, and protein interaction interfaces. Many alternatively-spliced exons in essential genes were dispensable and tended to encode disordered regions. We also detected a significant fitness defect for 44 newly evolved hypothetical reading frames. These results illuminate the nature and evolution of essential gene functions in human cells.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".