Genomic signatures of local adaptation across parasitised cricket populations
Rayner, J. G.; Yusuf, L.; Zhang, R.; Zhang, S.; Gaggiotti, O. E.; Bailey, N. W.
Show abstract
Novel species interactions provide an opportunity to assess the earliest stages of genetic adaptation in wild populations. We explored the genomic and geographic landscape of adaptation in small, fragmented Hawaiian cricket populations, which are parasitised by larvae of an introduced fly that targets singing males. Multiple protective male-silencing cricket morphs have recently spread despite songs role in mate attraction. Combining population genomics and field selection experiments, we found sharp declines in the crickets effective population size after the flys introduction. Nevertheless, geographical variation in selection influences the distribution of male-silencing alleles, consistent with local adaptation. Populations showing the strongest evidence of recovery retain large numbers of singing-capable males, suggesting that initially adaptive responses to the fly created an evolutionary trap via loss of sexual signalling.
Matching journals
The top 3 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- A genetic switch for male UV-iridescence in an incipient species pair of sulphur butterflies 97%
- Early life-stage thermal resilience is determined by climate-linked regulatory variation 96%
- Standing genetic variation and chromosome differences drove rapid ecotype formation in a major malaria vector 96%
Similar papers in this journal
- Post-meiotic mechanism of facultative parthenogenesis in gonochoristic whiptail lizard species. 96%
- Dynamic molecular evolution of a supergene with suppressed recombination in white-throated sparrows 96%
- Hybridization alters the shape of the genotypic fitness landscape, increasing access to novel fitness peaks during adaptive radiation 95%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.