Your browser doesn't support javascript.
loading
Adaptive divergence and the evolution of hybrid trait mismatch in threespine stickleback.
Chhina, Avneet K; Thompson, Ken A; Schluter, Dolph.
Afiliação
  • Chhina AK; Department of Zoology & Biodiversity Research Centre University of British Columbia Vancouver BC V6T 1Z4 Canada.
  • Thompson KA; Department of Zoology & Biodiversity Research Centre University of British Columbia Vancouver BC V6T 1Z4 Canada.
  • Schluter D; Department of Zoology & Biodiversity Research Centre University of British Columbia Vancouver BC V6T 1Z4 Canada.
Evol Lett ; 6(1): 34-45, 2022 Feb.
Article em En | MEDLINE | ID: mdl-35127136
Selection against mismatched traits in hybrids is the phenotypic analogue of intrinsic hybrid incompatibilities. Mismatch occurs when hybrids resemble one parent population for some phenotypic traits and the other parent population for other traits, and is caused by dominance in opposing directions or from segregation of alleles in recombinant hybrids. In this study, we used threespine stickleback fish (Gasterosteus aculeatus L.) to test the theoretical prediction that trait mismatch in hybrids should increase with the magnitude of phenotypic divergence between parent populations. We measured morphological traits in parents and hybrids in crosses between a marine population representing the ancestral form and twelve freshwater populations that have diverged from this ancestral state to varying degrees according to their environments. We found that trait mismatch was greater in more divergent crosses for both F1 and F2 hybrids. In the F1, the divergence-mismatch relationship was caused by traits having dominance in different directions, whereas it was caused by increasing segregating phenotypic variation in the F2. Our results imply that extrinsic hybrid incompatibilities accumulate as phenotypic divergence proceeds.
Palavras-chave

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2022 Tipo de documento: Article