Transgene-mediated skeletal phenotypic variation in zebrafish
Bibliographic record
Abstract
Abstract When considering relationships between genotype and phenotype we frequently ignore the fact that the genome of a typical animal, notably including that of a fish and a human, harbors a huge amount of foreign DNA. Some of it, including the DNA of “autonomous” transposable elements, can spontaneously mobilize to occupy new chromosomal sites and take on new functions, presenting a challenge to the host organism and also possibly introducing new fuel for evolutionary change. Transposable elements are useful for introducing transgenes, integrating them into host genomes with high efficiency. Transgenesis has become very widespread in biological research, and in our society at large. This year the governments of both Canada and the United States have approved the first use of ‘genetically engineered’ animals in food production, Atlantic salmon, Salmo salar . With the recent advent of amazing gene-editing technology, there is no doubt that the transgene industry will grow explosively in the coming years. The biology of transgenes needs to be included in our understanding of the genome. It is in this spirit that we have investigated an unexpected and novel phenotypic effect of the chromosomally integrated transgene fli1a-F-hsp70l:Gal4VP16 . We examine larval fras1 mutant zebrafish ( Danio rerio ). Gal4VP16 is a potent transcriptional activator, and already well known for toxicity and mediating unusual transcriptional effects. In the presence of the transgene, phenotypes in the neural crest-derived craniofacial skeleton, notably fusions and shape changes associated with loss of function fras1 mutations, are made more severe, as we quantify by scoring phenotypic penetrance, the fraction of mutants expressing the trait. A very interesting feature is that the enhancements are highly specific for fras1 mutant phenotypes – occurring in the apparent absence of more wide-spread changes. Except for the features due to the fras1 mutation, the transgene-bearing larvae appear generally healthy and to be developing normally. The transgene behaves as a genetic partial dominant: A single copy is sufficient for the enhancements, yet, for some traits, two copies may exert a stronger effect. We made new strains bearing independent insertions of the fli1a-F-hsp70l:Gal4VP16 transgene in new locations in the genome, and observed increased severities of the same phenotypes as observed for the original insertion. This finding suggests that sequences within the transgene, e.g. Gal4VP16, are responsible for the enhancements, rather than effect on neighboring host sequences (such as an insertional mutation). The specificity, and biological action underlying the traits, are subjects of considerable interest for further investigation, as we discuss. Our findings show that work with transgenes needs to be undertaken with caution and attention to detail.
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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 | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".