10.5061/DRYAD.HMGQNK9F9
Schneemann, Hilde
0000-0002-7295-9734
University of Cambridge
De Sanctis, Bianca
University of Cambridge
Roze, Denis
Evolutionary Biology and Ecology of Algae
Bierne, Nicolas
University of Montpellier
Welch, John
University of Cambridge
The Geometry and Genetics of Hybridization
Dryad
dataset
2020
Fisher's geometric model
hybrid fitness
line crosses
Wellcome Trust
https://ror.org/029chgv08
PFHZ/157
Wellcome Trust
https://ror.org/029chgv08
PCGG.GAAB
Erasmus Mundus (MEME)*
Erasmus Mundus (MEME)
2020-10-21T00:00:00Z
2020-10-21T00:00:00Z
en
https://github.com/hildeschneemann/Fisher_divergence_simulation/blob/main/allopatry/MersenneTwister.h
931849944 bytes
5
CC0 1.0 Universal (CC0 1.0) Public Domain Dedication
When divergent populations form hybrids, hybrid fitness can vary with
genome composition, current environmental conditions, and the divergence
history of the populations. We develop analytical predictions for hybrid
fitness, which incorporate all three factors. The predictions are based on
Fisher's geometric model, and apply to a wide range of population
genetic parameter regimes and divergence conditions, including allopatry
and parapatry, local adaptation and drift. Results show that hybrid
fitness can be decomposed into intrinsic effects of admixture and
heterozygosity, and extrinsic effects of the (local) adaptedness of the
parental lines. Effect sizes are determined by a handful of geometric
distances, which have a simple biological interpretation. These distances
also reflect the mode and amount of divergence, such that there is
convergence towards a characteristic pattern of intrinsic isolation. We
next connect our results to the quantitative genetics of line crosses in
variable or patchy environments. This means that the geometrical distances
can be estimated from cross data, and provides a simple interpretation of
the ``composite effects''. Finally, we develop extensions to the
model, involving selectively-induced disequilibria, and variable
phenotypic dominance. The geometry of fitness landscapes provides a
unifying framework for understanding speciation, and wider patterns of
hybrid fitness.
Simulated data was generated from individual-based simulations as in the
code provided.
Readme file for simulation code provided. In addition, you need to
download the following header file and place it in the allopatry and
parapatry folders before compilation:
https://github.com/hildeschneemann/Fisher_divergence_simulation/blob/main/allopatry/MersenneTwister.h