12,577 research outputs found
Dynamics of transcription factor binding site evolution
Evolution of gene regulation is crucial for our understanding of the
phenotypic differences between species, populations and individuals.
Sequence-specific binding of transcription factors to the regulatory regions on
the DNA is a key regulatory mechanism that determines gene expression and hence
heritable phenotypic variation. We use a biophysical model for directional
selection on gene expression to estimate the rates of gain and loss of
transcription factor binding sites (TFBS) in finite populations under both
point and insertion/deletion mutations. Our results show that these rates are
typically slow for a single TFBS in an isolated DNA region, unless the
selection is extremely strong. These rates decrease drastically with increasing
TFBS length or increasingly specific protein-DNA interactions, making the
evolution of sites longer than ~10 bp unlikely on typical eukaryotic speciation
timescales. Similarly, evolution converges to the stationary distribution of
binding sequences very slowly, making the equilibrium assumption questionable.
The availability of longer regulatory sequences in which multiple binding sites
can evolve simultaneously, the presence of "pre-sites" or partially decayed old
sites in the initial sequence, and biophysical cooperativity between
transcription factors, can all facilitate gain of TFBS and reconcile
theoretical calculations with timescales inferred from comparative genetics.Comment: 28 pages, 15 figure
High genetic diversity at the extreme range edge: nucleotide variation at nuclear loci in Scots pine (Pinus sylvestris L.) in Scotland
Nucleotide polymorphism at 12 nuclear loci was studied in Scots pine populations across an environmental gradient in Scotland, to evaluate the impacts of demographic history and selection on genetic diversity. At eight loci, diversity patterns were compared between Scottish and continental European populations. At these loci, a similar level of diversity (Ξsil=~0.01) was found in Scottish vs mainland European populations, contrary to expectations for recent colonization, however, less rapid decay of linkage disequilibrium was observed in the former (Ï=0.0086±0.0009, Ï=0.0245±0.0022, respectively). Scottish populations also showed a deficit of rare nucleotide variants (multi-locus Tajima's D=0.316 vs D=â0.379) and differed significantly from mainland populations in allelic frequency and/or haplotype structure at several loci. Within Scotland, western populations showed slightly reduced nucleotide diversity (Ïtot=0.0068) compared with those from the south and east (0.0079 and 0.0083, respectively) and about three times higher recombination to diversity ratio (Ï/Ξ=0.71 vs 0.15 and 0.18, respectively). By comparison with results from coalescent simulations, the observed allelic frequency spectrum in the western populations was compatible with a relatively recent bottleneck (0.00175 Ă 4Ne generations) that reduced the population to about 2% of the present size. However, heterogeneity in the allelic frequency distribution among geographical regions in Scotland suggests that subsequent admixture of populations with different demographic histories may also have played a role
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Polygenic Adaptation to an Environmental Shift: Temporal Dynamics of Variation Under Gaussian Stabilizing Selection and Additive Effects on a Single Trait.
Predictions about the effect of natural selection on patterns of linked neutral variation are largely based on models involving the rapid fixation of unconditionally beneficial mutations. However, when phenotypes adapt to a new optimum trait value, the strength of selection on individual mutations decreases as the population adapts. Here, I use explicit forward simulations of a single trait with additive-effect mutations adapting to an "optimum shift." Detectable "hitchhiking" patterns are only apparent if (i) the optimum shifts are large with respect to equilibrium variation for the trait, (ii) mutation rates to large-effect mutations are low, and (iii) large-effect mutations rapidly increase in frequency and eventually reach fixation, which typically occurs after the population reaches the new optimum. For the parameters simulated here, partial sweeps do not appreciably affect patterns of linked variation, even when the mutations are strongly selected. The contribution of new mutations vs. standing variation to fixation depends on the mutation rate affecting trait values. Given the fixation of a strongly selected variant, patterns of hitchhiking are similar on average for the two classes of sweeps because sweeps from standing variation involving large-effect mutations are rare when the optimum shifts. The distribution of effect sizes of new mutations has little effect on the time to reach the new optimum, but reducing the mutational variance increases the magnitude of hitchhiking patterns. In general, populations reach the new optimum prior to the completion of any sweeps, and the times to fixation are longer for this model than for standard models of directional selection. The long fixation times are due to a combination of declining selection pressures during adaptation and the possibility of interference among weakly selected sites for traits with high mutation rates
Rate and cost of adaptation in the Drosophila Genome
Recent studies have consistently inferred high rates of adaptive molecular
evolution between Drosophila species. At the same time, the Drosophila genome
evolves under different rates of recombination, which results in partial
genetic linkage between alleles at neighboring genomic loci. Here we analyze
how linkage correlations affect adaptive evolution. We develop a new inference
method for adaptation that takes into account the effect on an allele at a
focal site caused by neighboring deleterious alleles (background selection) and
by neighboring adaptive substitutions (hitchhiking). Using complete genome
sequence data and fine-scale recombination maps, we infer a highly
heterogeneous scenario of adaptation in Drosophila. In high-recombining
regions, about 50% of all amino acid substitutions are adaptive, together with
about 20% of all substitutions in proximal intergenic regions. In
low-recombining regions, only a small fraction of the amino acid substitutions
are adaptive, while hitchhiking accounts for the majority of these changes.
Hitchhiking of deleterious alleles generates a substantial collateral cost of
adaptation, leading to a fitness decline of about 30/2N per gene and per
million years in the lowest-recombining regions. Our results show how
recombination shapes rate and efficacy of the adaptive dynamics in eukaryotic
genomes
Historical contingency and entrenchment in protein evolution under purifying selection
The fitness contribution of an allele at one genetic site may depend on
alleles at other sites, a phenomenon known as epistasis. Epistasis can
profoundly influence the process of evolution in populations under selection,
and can shape the course of protein evolution across divergent species. Whereas
epistasis between adaptive substitutions has been the subject of extensive
study, relatively little is known about epistasis under purifying selection.
Here we use mechanistic models of thermodynamic stability in a ligand-binding
protein to explore the structure of epistatic interactions between
substitutions that fix in protein sequences under purifying selection. We find
that the selection coefficients of mutations that are nearly-neutral when they
fix are highly contingent on the presence of preceding mutations. Conversely,
mutations that are nearly-neutral when they fix are subsequently entrenched due
to epistasis with later substitutions. Our evolutionary model includes
insertions and deletions, as well as point mutations, and so it allows us to
quantify epistasis within each of these classes of mutations, and also to study
the evolution of protein length. We find that protein length remains largely
constant over time, because indels are more deleterious than point mutations.
Our results imply that, even under purifying selection, protein sequence
evolution is highly contingent on history and so it cannot be predicted by the
phenotypic effects of mutations assayed in the wild-type sequence.Comment: 42 pages, 13 figure
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