THE EVOLUTION OF GENOMIC BASE COMPOSITION IN BACTERIA
Bibliographic record
Abstract
Guanine plus cytosine (GC) content ranges broadly among bacterial genomes. In this study, we explore the use of a Brownian-motion model for the evolution of GC content over time. This model assumes that GC content varies over time in a continuous and homogeneous manner. Using this model and a maximum-likelihood approach, we analyzed the evolution of GC content across several bacterial phylogenies. Using three independent tests, we found that the observed divergence in GC content was consistent with a homogeneous Brownian-motion model. For example, similar rates of GC content evolution were inferred in several different bacterial subclades, indicating that there is relatively little rate heterogeneity in GC content evolution over broad evolutionary time scales. We thus argue that the homogeneous Brownian-motion model provides a good working model for GC content evolution. We then use this model to determine the overall rate of GC content evolution among eubacteria. We also determine the time frame over which GC content remains similar in related taxa, using a flexible definition for "similarity" in GC content so that, depending on the context, more or less stringent criteria may be applied. Our results have implications for models of sequence evolution, including those used for phylogenetic reconstruction and for inferring unusual changes in GC content.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".