@article{achaz_reproducibility_2014,
Author = {Achaz, Guillaume and Rodriguez-Verdugo, Alejandra and
Gaut, Brandon S. and Tenaillon, Olivier},
Title = {The reproducibility of adaptation in the light of
experimental evolution with whole genome sequencing},
Journal = {Advances in Experimental Medicine and Biology},
Volume = {781},
Pages = {211--231},
abstract = {A key question in evolutionary biology is the
reproducibility of adaptation. This question can now be
quantitatively analyzed using experimental evolution
coupled to whole genome sequencing (WGS). With complete
sequence data, one can assess convergence among
replicate populations. In turn, convergence reflects
the action of natural selection and also the breadth of
the field of possible adaptive solutions. That is, it
provides insight into how many genetic solutions or
adaptive paths may lead to adaptation in a given
environment. Convergence is both a property of an
adaptive landscape and, reciprocally, a tool to study
that landscape. In this chapter we present the links
between convergence and the properties of adaptive
landscapes with respect to two types of microbial
experimental evolution. The first tries to reconstruct
a full adaptive landscape using a handful of carefully
identified mutations (the reductionist approach), while
the second uses WGS of replicate experiments to infer
properties of the adaptive landscape. Reductionist
approaches have highlighted the importance of epistasis
in shaping the adaptive landscape, but have also
uncovered a wide diversity of landscape architectures.
The WGS approach has uncovered a very high diversity of
beneficial mutations that affect a limited set of genes
or functions and also suggests some shortcomings of the
reductionist approach. We conclude that convergence may
be better defined at an integrated level, such as the
genic level or even at a phenotypic level, and that
integrated mechanistic models derived from systems
biology may offer an interesting perspective for the
analysis of convergence at all levels.},
doi = {10.1007/978-94-007-7347-9_11},
issn = {0065-2598},
language = {eng},
pmid = {24277302},
year = 2014
}
Author = {Achaz, Guillaume and Rodriguez-Verdugo, Alejandra and
Gaut, Brandon S. and Tenaillon, Olivier},
Title = {The reproducibility of adaptation in the light of
experimental evolution with whole genome sequencing},
Journal = {Advances in Experimental Medicine and Biology},
Volume = {781},
Pages = {211--231},
abstract = {A key question in evolutionary biology is the
reproducibility of adaptation. This question can now be
quantitatively analyzed using experimental evolution
coupled to whole genome sequencing (WGS). With complete
sequence data, one can assess convergence among
replicate populations. In turn, convergence reflects
the action of natural selection and also the breadth of
the field of possible adaptive solutions. That is, it
provides insight into how many genetic solutions or
adaptive paths may lead to adaptation in a given
environment. Convergence is both a property of an
adaptive landscape and, reciprocally, a tool to study
that landscape. In this chapter we present the links
between convergence and the properties of adaptive
landscapes with respect to two types of microbial
experimental evolution. The first tries to reconstruct
a full adaptive landscape using a handful of carefully
identified mutations (the reductionist approach), while
the second uses WGS of replicate experiments to infer
properties of the adaptive landscape. Reductionist
approaches have highlighted the importance of epistasis
in shaping the adaptive landscape, but have also
uncovered a wide diversity of landscape architectures.
The WGS approach has uncovered a very high diversity of
beneficial mutations that affect a limited set of genes
or functions and also suggests some shortcomings of the
reductionist approach. We conclude that convergence may
be better defined at an integrated level, such as the
genic level or even at a phenotypic level, and that
integrated mechanistic models derived from systems
biology may offer an interesting perspective for the
analysis of convergence at all levels.},
doi = {10.1007/978-94-007-7347-9_11},
issn = {0065-2598},
language = {eng},
pmid = {24277302},
year = 2014
}