Genomic signatures of adaptation in native lizards exposed to human-introduced fire ants
Bibliographic record
Abstract
Abstract Understanding the process of genetic adaptation in response to human-mediated ecological change will help elucidate the eco-evolutionary impacts of human activity. Red fire ants ( Solenopsis invicta ) spread across Southeastern USA since their accidental introduction via Port Mobile, Alabama in the 1930s, serving today as both novel venomous predator and novel toxic prey to native eastern fence lizards ( Sceloporus undulatus ). To identify potential signatures of genetic adaptation in lizards to invasive fire ants, we generated whole genome sequencing data from 420 native fence lizards sampled across three populations, two of which had not been invaded by fire ants (in Tennessee and Arkansas) and one which had been invaded for ∼70 years (Alabama). We detected signatures of positive selection exclusive to the exposed Alabama population for genetic variants overlapping genes related to the membrane attack complex of the complement immune system, growth factor pathways, and morphological development. Prior work identified a relationship between increased lizard survival of fire ant attack and longer hind limbs, which lizards use to remove ants from their bodies. Furthermore, we conducted a genome-wide association study with 381 Alabama lizards to identify 24 hind limb length-associated genetic loci. For two loci, positive-effect alleles occur in high frequency and overlap genomic regions that are highly differentiated from the populations naïve to fire ants. Collectively, these findings represent plausible genetic adaptations in response to fire ant invasion, whereby morphological differentiation may increase survival against swarming ants and altered immune responses may allow the exploitation of a novel, toxic food resource. Significance statement Human activity can force interactions between species from distinct ecological backgrounds. These interactions can consequently impose novel selective pressures on endemic populations via predation or disruption of ecological niches through community-wide effects. While some endemic taxa have been able to adapt biologically to these disruptions, we do not have a full understanding of the underlying genetic processes that may allow it. Here we identify genomic signatures of recent adaptation nearby genes involved in morphological and immunological processes in native fence lizards that are consistent with pressures imposed by the venomous, predatory fire ants introduced by humans. These signatures are largely absent from lizard populations that are naïve to fire ants.
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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 | 0.000 |
| 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".