Diving into the amphibian genomegenetic architecture of larval life history traits

  1. Palomar García, Gemma
Dirigida por:
  1. Alfredo González Nicieza Director

Universidad de defensa: Universidad de Oviedo

Fecha de defensa: 27 de julio de 2017

Tribunal:
  1. Iván Gómez Mestre Presidente/a
  2. Jose Luis Martinez Fernandez Secretario/a
  3. Germán Orizaola Vocal
Departamento:
  1. Biología de Organismos y Sistemas

Tipo: Tesis

Teseo: 493188 DIALNET

Resumen

Knowing the genetic basis of adaptive traits is essential to predict the magnitude and the pace of evolutionary change. However, little is known about the detailed genetic architecture of evolutionary important traits in natural populations. At the current rate of climate change, many species and populations cannot cope with the new environmental conditions. Thus, it is critical to know whether threatened populations have enough adaptive potential to face this rate of change and to have the tools available to monitor vulnerable populations at the species range. These are, indeed, the transversal topics of this thesis. Using as model vulnerable amphibian populations (i.e. high-altitude populations with reduced population size and high degree of isolation, and populations affected by an emergent fungal disease), this thesis estimates the heritable component of several early life fitness-related traits, fungal infection rate and their genetic correlations. We provide the first estimation of the genetic component of Batrachochytrium dendrobatidis load in an amphibian host and identify associated genetic polymorphisms. Furthermore, we present the densest linkage map for Rana temporaria to date, which was used to locate specific genomic regions related to larval life history traits. Overall, this thesis detailed the genetic architecture of several amphibian important traits revealing that the studied populations harbour significant adaptive potential. In addition, our mapping efforts usher in the development of markers related to ecologically important traits. These tools are invaluable to understand evolutionary processes at large scale and to monitor relevant functional variation for conservation purposes.