Author response: A direct experimental test of Ohno’s hypothesis
Bibliographic record
Abstract
Inside all living things, genes carry instructions to make and maintain the body. Individuals carefully maintain their set of genes, known as the genome, to pass their appearance and other traits on to the next generation. Sometimes a particular gene may be duplicated so that cells end up with an extra copy in their genome. Typically, around 50% of genes are duplicated in genomes and these duplicates may then accumulate changes (or “mutations”) that enable them to adopt new roles in the body. Some mutations may be harmful to the body and lead to the mutated gene being inactivated. In 1970, the researcher Susumu Ohno proposed that when two copies of the same gene are present, they can accumulate more mutations than a single copy would while maintaining function. As a result, duplicated genes may thus evolve new properties and roles in the body more rapidly than single-copy genes. However, it has been difficult to design experiments to test this hypothesis. A protein known as GFP emits green light when it absorbs certain colors of light, a phenomenon known as fluorescence. To test Ohno’s hypothesis, Mihajlovic et al. developed an experimental system to place one or two copies of the gene that encodes GFP into bacteria known as Escherichia coli. The team then introduced mutations into these genes and simulated evolution by selecting bacteria on their ability to emit green, blue or both lights. The experiments found that part of Ohno’s hypothesis is correct. Bacteria with two gene copies were more likely to retain their ability to emit green light after mutations than bacteria with one copy. However, gene duplication did not accelerate the evolution of more fluorescent GFPs or of new functions of the protein, such as emitting blue light. Instead, one copy of the gene often became inactivated by harmful mutations. This suggests that there may be other reasons beyond those proposed by Ohno to explain why gene duplications are so common in nature – for instance, by enhancing protein production. The experimental system developed in this work serves as a platform for further investigations into Ohno’s hypothesis, which may help us better understand the origins of genetic diversity in bacteria and other forms of life.
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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 | 0.013 | 0.079 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.015 | 0.012 |
| Insufficient payload (model declined to judge) | 0.079 | 0.024 |
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".