Resolving the genetic paradox of invasions: Preadapted genomes and postintroduction hybridization of bigheaded carps in the Mississippi River Basin
Bibliographic record
Abstract
Abstract The genetic paradox of biological invasions is complex and multifaceted. In particular, the relative role of disparate propagule sources and genetic adaptation through postintroduction hybridization has remained largely unexplored. To add resolution to this paradox, we investigate the genetic architecture responsible for the invasion of two invasive Asian carp species, bighead carp ( Hypophthalmichthys nobilis ) and silver carp ( H. molitrix ) (bigheaded carps) that experience extensive hybridization in the Mississippi River Basin (MRB). We sequenced the genomes of bighead and silver carps (~1.08G bp and ~1.15G bp, respectively) and their hybrids collected from the MRB. We found moderate‐to‐high heterozygosity in bighead (0.0021) and silver (0.0036) carps, detected significantly higher dN/dS ratios of single‐copy orthologous genes in bigheaded carps versus 10 other species of fish, and identified genes in both species potentially associated with environmental adaptation and other invasion‐related traits. Additionally, we observed a high genomic similarity (96.3% in all syntenic blocks) between bighead and silver carps and over 90% embryonic viability in their experimentally induced hybrids. Our results suggest intrinsic genomic features of bigheaded carps, likely associated with life history traits that presumably evolved within their native ranges, might have facilitated their initial establishment of invasion, whereas ex-situ interspecific hybridization between the carps might have promoted their range expansion. This study reveals an alternative mechanism that could resolve one of the genetic paradoxes in biological invasions and provides invaluable genomic resources for applied research involving bigheaded carps.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".