MHC evolutionary ecology in European barn owls (Tyto alba)

Details

Ressource 1Download: Thèse_A.Gaigher-OK.pdf (7829.88 [Ko])
State: Serval
Version: After imprimatur
Serval ID
serval:BIB_CA1408269A7C
Type
PhD thesis: a PhD thesis.
Collection
Publications
Title
MHC evolutionary ecology in European barn owls (Tyto alba)
Author(s)
Gaigher Arnaud
Director(s)
Fumagalli Luca
Codirector(s)
Roulin Alexandre
Institution
Université de Lausanne, Faculté de biologie et médecine
Publication state
Accepted
Issued date
2017
Language
english
Abstract
Elucidating the mechanisms promoting and maintaining adaptive genetic diversity (i.e., variation at loci with a direct effect on fitness) is a central issue in evolutionary and conservation biology. Due to their essential role in pathogen resistance and extraordinary levels of polymorphism, genes of the major histocompatibility complex (MHC) constitute perfect candidates for studying adaptive genetic variability. However, despite the accumulation of empirical data, estimating the relative contribution of adaptive against non-adaptive processes that drive the MHC evolution in natural populations is still challenging, and consequently requires further investigation.
In this thesis, my general aim was to understand the pattern of MHC evolution by using the European populations of barn owl (Tyto alba) as model species. We adopted a sampling strategy including individuals from family data, for which fitness-related trait information from experimental data were available, as well as an extensive number of individuals from many localities in Europe. This sampling resulted in a total of 1'300 barn owls that were sequenced for both MHC class Iα exon3 (MHC-I) and MHC class IIβ exon 2 (MHC-IIB) using a high-throughput sequencing technology. Our strategy allowed us to address some of the important topics in the MHC field, i.e. MHC genotyping, molecular evolution of MHC genes, the link between MHC diversity and individual fitness-related traits, and the spatial pattern of MHC diversity.
I first characterized the diversity at the two MHC classes (MHC-I and MHC-IIB), and revealed only two duplicated genes in each class. All four genes displayed the characteristics of functional MHC genes, i.e. footprints of historical positive selection, high genetic diversity, and footprints of recombination and gene conversion. Additionally, I highlighted a remarkable discrepancy in the evolutionary dynamic between the two MHC classes, where alleles between MHC-I genes were extremely homogenized, while the ones at MHC-IIB genes were strongly divergent. These findings suggest that the different evolutionary histories at the two MHC classes may constrain or promote the evolution for an optimal MHC-mediated pathogen defence. Taking advantage of this detailed characterization, in a follow-up study, I investigated whether specific aspects of MHC diversity (i.e. high diversity or specific alleles) confer higher immunocompetence. Overall I found low support in this sense, but most importantly these results highlighted that if an effect exists, it is of small to moderate effect size, which is important for future studies in order to achieve enough power to detect small-effects associations. Finally, I took a global view and investigated the pattern of MHC diversity across Europe. I found that MHC diversity has been mainly driven by the species colonization history, even if certain localities show intriguing patterns that may allow me to think that selection has also contributed to shape MHC diversity. This study revealed the complexity of distinguishing the relative contribution of evolutionary forces shaping the spatial MHC diversity and requires pathogen community information to properly discern the forces in action.
The findings of this PhD, using a multilevel approach coupled with high throughput sequencing technologies, have permitted to bring new insights into the MHC evolutionary ecology, but have also opened new challenging perspectives, such as the importance of using genomic scans and sampling strategy efforts, in order to overcome the general difficulty of fully understanding the outcomes of host-pathogen interactions.
Create date
28/11/2017 19:18
Last modification date
03/03/2018 21:24
Usage data