Exploring the silent fitness landscape
Auf einen Blick
- Projektleiter/in : Dr. Maria Anisimova
- Projektteam : Dr. Victor Garcia
- Projektvolumen : CHF 202'170
- Projektstatus : abgeschlossen
- Drittmittelgeber : SNF (SystemsX.ch)
- Kontaktperson : Maria Anisimova
Beschreibung
Since Darwin, natural selection has been recognized as one of
major biological forces
shaping genetic patterns in molecular data. Detecting selection on
proteins has
become an indispensible part of genome studies. Remarkably
selection can act not
only on proteins, but also on synonymous codons translating into
the same amino
acid. This manifests itself as codon bias, with no influence on the
protein sequence,
but with potentially strong impact on the protein product and
associated cellular
processes. In addition, mechanisms such as biased gene conversion
may result in an
excess of synonymous changes with mild deleterious effect. The role
of selection on
synonymous changes is often studied by measuring codon usage on the
entire gene.
This approach however lacks power: it ignores evolutionary
information and the impact
of site-specific synonymous rate variation, found in >1/3 of
proteins. For instance, the
use of rare codons at certain sites may slow down translation
producing a ribosomal
pause for ubiquitin modification or for co-translational protein
folding. Codon choice at
such sites may affect protein synthesis or product’s properties.
Synonymous changes
at sites of miRNA or siRNA binding may have impact on protein
abundance in a
process known as RNA interference (RNAi). Recently single
synonymous mutations
have been shown to contribute to human diseases such as cancers and
diabetes. Such
sites often use rare codons or exhibit high synonymous
variability.
Here we focus on site-specific synonymous codon bias due to
selection or
biased gene conversion. We develop statistical methods to identify
candidate
sites in genome-wide scans of species orthologs. A deeper insight
into evolutionary
dynamics at synonymous sites will come from contrasting fixed
differences between
species and polymorphisms within populations. To test predictions
of the neutral
theory about macro- and microevolutionary forces acting on genomes,
we develop a
statistical framework for analyzing mixed population/species data,
thereby bridging
the existing methodological gap between molecular evolution and
population genetics
models.
Weiterführende Informationen
Publikationen
-
Cadosch, Dominique; Garcia, Victor; Jensen, Jørgen S.; Low, Nicola; Althaus, Christian L.,
2020.
Understanding the spread of de novo and transmitted macrolide-resistance in Mycoplasma genitalium.
PeerJ.
8.
Verfügbar unter: https://doi.org/10.7717/peerj.8913
-
Garcia, Victor; Bonhoeffer, Sebastian; Fu, Feng,
2020.
Journal of Theoretical Biology.
492(110185).
Verfügbar unter: https://doi.org/10.1016/j.jtbi.2020.110185