Genomic compartmentalization of gene families encoding core components of metazoan signaling systems
Bibliographic record
Abstract
To investigate the role of gene localization and genome organization in cell-cell signalling and regulation, we mapped the distribution pattern of gene families that comprise core components of intercellular communication networks. Our study is centered on the distinct evolutionarily conserved metazoan signalling pathways that employ proteins in the receptor tyrosine kinase, WNT, hedgehog, NOTCH, Janus kinase/STAT, transforming growth factor beta, and nuclear hormone receptor protein families. Aberrant activity of these signalling pathways is closely associated with the promotion and maintenance of human cancers. The cataloguing and mapping of genes encoding these signalling proteins and comparisons across species has led us to propose that the genome can be subdivided into six genome-wide primary linkage groups (PLGs). PLGs are composed of assemblages of gene families that are often mutually exclusive, raising the possibility of unique functional identities for each group. Examination of the localization patterns of genes with distinct functions in signal transduction demonstrates dichotomous segregation patterns. For example, gene families of cell-surface receptors localize to genomic compartments that are distinct from the locations of their cognate ligand gene families. Additionally, genes encoding negative-acting components of signalling pathways (inhibitors and antagonists) are topologically separated from their positive regulators and other signal transducer genes. We, therefore, propose the existence of conserved genomic territories that encode key proteins required for the proper activity of metazoan signaling and regulatory systems. Disruption in this pattern of topologic genomic organization may contribute to aberrant regulation in hereditary or acquired diseases such as cancer. We further propose that long-range looping genomic regulatory interactions may provide a mechanism favouring the remarkable retention of these conserved gene clusters during chordate evolution.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".