@article{286,
abstract = {Pedigree and sibship reconstruction are important methods in quantifying relationships and fitness of individuals in natural populations. Current methods employ a Markov chain-based algorithm to explore plausible possible pedigrees iteratively. This provides accurate results, but is time-consuming. Here, we develop a method to infer sibship and paternity relationships from half-sibling arrays of known maternity using hierarchical clustering. Given 50 or more unlinked SNP markers and empirically derived error rates, the method performs as well as the widely used package Colony, but is faster by two orders of magnitude. Using simulations, we show that the method performs well across contrasting mating scenarios, even when samples are large. We then apply the method to open-pollinated arrays of the snapdragon Antirrhinum majus and find evidence for a high degree of multiple mating. Although we focus on diploid SNP data, the method does not depend on marker type and as such has broad applications in nonmodel systems. },
author = {Ellis, Thomas and Field, David and Barton, Nicholas H},
journal = {Molecular Ecology Resources},
number = {5},
pages = {988 -- 999},
publisher = {Wiley},
title = {{Efficient inference of paternity and sibship inference given known maternity via hierarchical clustering}},
doi = {10.1111/1755-0998.12782},
volume = {18},
year = {2018},
}
@article{423,
abstract = {Herd immunity, a process in which resistant individuals limit the spread of a pathogen among susceptible hosts has been extensively studied in eukaryotes. Even though bacteria have evolved multiple immune systems against their phage pathogens, herd immunity in bacteria remains unexplored. Here we experimentally demonstrate that herd immunity arises during phage epidemics in structured and unstructured Escherichia coli populations consisting of differing frequencies of susceptible and resistant cells harboring CRISPR immunity. In addition, we develop a mathematical model that quantifies how herd immunity is affected by spatial population structure, bacterial growth rate, and phage replication rate. Using our model we infer a general epidemiological rule describing the relative speed of an epidemic in partially resistant spatially structured populations. Our experimental and theoretical findings indicate that herd immunity may be important in bacterial communities, allowing for stable coexistence of bacteria and their phages and the maintenance of polymorphism in bacterial immunity.},
author = {Payne, Pavel and Geyrhofer, Lukas and Barton, Nicholas H and Bollback, Jonathan P},
journal = {eLife},
publisher = {eLife Sciences Publications},
title = {{CRISPR-based herd immunity can limit phage epidemics in bacterial populations}},
doi = {10.7554/eLife.32035},
volume = {7},
year = {2018},
}
@article{430,
abstract = {In this issue of GENETICS, a new method for detecting natural selection on polygenic traits is developed and applied to sev- eral human examples ( Racimo et al. 2018 ). By de fi nition, many loci contribute to variation in polygenic traits, and a challenge for evolutionary ge neticists has been that these traits can evolve by small, nearly undetectable shifts in allele frequencies across each of many, typically unknown, loci. Recently, a helpful remedy has arisen. Genome-wide associ- ation studies (GWAS) have been illuminating sets of loci that can be interrogated jointly for c hanges in allele frequencies. By aggregating small signal s of change across many such loci, directional natural selection is now in principle detect- able using genetic data, even for highly polygenic traits. This is an exciting arena of progress – with these methods, tests can be made for selection associated with traits, and we can now study selection in what may be its most prevalent mode. The continuing fast pace of GWAS publications suggest there will be many more polygenic tests of selection in the near future, as every new GWAS is an opportunity for an accom- panying test of polygenic selection. However, it is important to be aware of complications th at arise in interpretation, especially given that these studies may easily be misinter- preted both in and outside the evolutionary genetics commu- nity. Here, we provide context for understanding polygenic tests and urge caution regarding how these results are inter- preted and reported upon more broadly.},
author = {Novembre, John and Barton, Nicholas H},
journal = {Genetics},
number = {4},
pages = {1351 -- 1355},
publisher = {Genetics Society of America},
title = {{Tread lightly interpreting polygenic tests of selection}},
doi = {10.1534/genetics.118.300786 },
volume = {208},
year = {2018},
}
@misc{5583,
abstract = {Data and scripts are provided in support of the manuscript "Efficient inference of paternity and sibship inference given known maternity via hierarchical clustering", and the associated Python package FAPS, available from www.github.com/ellisztamas/faps.
Simulation scripts cover:
1. Performance under different mating scenarios.
2. Comparison with Colony2.
3. Effect of changing the number of Monte Carlo draws
The final script covers the analysis of half-sib arrays from wild-pollinated seed in an Antirrhinum majus hybrid zone.},
author = {Ellis, Thomas},
publisher = {IST Austria},
title = {{Data and Python scripts supporting Python package FAPS}},
doi = {10.15479/AT:ISTA:95},
year = {2018},
}
@article{563,
abstract = {In continuous populations with local migration, nearby pairs of individuals have on average more similar genotypes
than geographically well separated pairs. A barrier to gene flow distorts this classical pattern of isolation by distance. Genetic similarity is decreased for sample pairs on different sides of the barrier and increased for pairs on the same side near the barrier. Here, we introduce an inference scheme that utilizes this signal to detect and estimate the strength of a linear barrier to gene flow in two-dimensions. We use a diffusion approximation to model the effects of a barrier on the geographical spread of ancestry backwards in time. This approach allows us to calculate the chance of recent coalescence and probability of identity by descent. We introduce an inference scheme that fits these theoretical results to the geographical covariance structure of bialleleic genetic markers. It can estimate the strength of the barrier as well as several demographic parameters. We investigate the power of our inference scheme to detect barriers by applying it to a wide range of simulated data. We also showcase an example application to a Antirrhinum majus (snapdragon) flower color hybrid zone, where we do not detect any signal of a strong genome wide barrier to gene flow.},
author = {Ringbauer, Harald and Kolesnikov, Alexander and Field, David and Barton, Nicholas H},
journal = {Genetics},
number = {3},
pages = {1231--1245},
publisher = {Genetics Society of America},
title = {{Estimating barriers to gene flow from distorted isolation-by-distance patterns}},
doi = {10.1534/genetics.117.300638 },
volume = {208},
year = {2018},
}
@article{564,
abstract = {Maladapted individuals can only colonise a new habitat if they can evolve a
positive growth rate fast enough to avoid extinction, a process known as evolutionary
rescue. We treat log fitness at low density in the new habitat as a
single polygenic trait and thus use the infinitesimal model to follow the evolution
of the growth rate; this assumes that the trait values of offspring of a
sexual union are normally distributed around the mean of the parents’ trait
values, with variance that depends only on the parents’ relatedness. The
probability that a single migrant can establish depends on just two parameters:
the mean and genetic variance of the trait in the source population.
The chance of success becomes small if migrants come from a population
with mean growth rate in the new habitat more than a few standard deviations
below zero; this chance depends roughly equally on the probability
that the initial founder is unusually fit, and on the subsequent increase in
growth rate of its offspring as a result of selection. The loss of genetic variation
during the founding event is substantial, but highly variable. With
continued migration at rate M, establishment is inevitable; when migration
is rare, the expected time to establishment decreases inversely with M.
However, above a threshold migration rate, the population may be trapped
in a ‘sink’ state, in which adaptation is held back by gene flow; above this
threshold, the expected time to establishment increases exponentially with M. This threshold behaviour is captured by a deterministic approximation,
which assumes a Gaussian distribution of the trait in the founder population
with mean and variance evolving deterministically. By assuming a constant
genetic variance, we also develop a diffusion approximation for the joint distribution
of population size and trait mean, which extends to include stabilising
selection and density regulation. Divergence of the population from its
ancestors causes partial reproductive isolation, which we measure through
the reproductive value of migrants into the newly established population.},
author = {Barton, Nicholas H and Etheridge, Alison},
journal = {Theoretical Population Biology},
number = {7},
pages = {110--127},
publisher = {Academic Press},
title = {{Establishment in a new habitat by polygenic adaptation}},
doi = {10.1016/j.tpb.2017.11.007},
volume = {122},
year = {2018},
}
@article{565,
abstract = {We re-examine the model of Kirkpatrick and Barton for the spread of an inversion into a local population. This model assumes that local selection maintains alleles at two or more loci, despite immigration of alternative alleles at these loci from another population. We show that an inversion is favored because it prevents the breakdown of linkage disequilibrium generated by migration; the selective advantage of an inversion is proportional to the amount of recombination between the loci involved, as in other cases where inversions are selected for. We derive expressions for the rate of spread of an inversion; when the loci covered by the inversion are tightly linked, these conditions deviate substantially from those proposed previously, and imply that an inversion can then have only a small advantage. },
author = {Charlesworth, Brian and Barton, Nicholas H},
journal = {Genetics},
number = {1},
pages = {377 -- 382},
publisher = {Genetics },
title = {{The spread of an inversion with migration and selection}},
doi = {10.1534/genetics.117.300426},
volume = {208},
year = {2018},
}
@misc{5757,
abstract = {File S1. Variant Calling Format file of the ingroup: 197 haploid sequences of D. melanogaster from Zambia (Africa) aligned to the D. melanogaster 5.57 reference genome.
File S2. Variant Calling Format file of the outgroup: 1 haploid sequence of D. simulans aligned to the D. melanogaster 5.57 reference genome.
File S3. Annotations of each transcript in coding regions with SNPeff: Ps (# of synonymous polymorphic sites); Pn (# of non-synonymous polymorphic sites); Ds (# of synonymous divergent sites); Dn (# of non-synonymous divergent sites); DoS; ⍺ MK . All variants were included.
File S4. Annotations of each transcript in non-coding regions with SNPeff: Ps (# of synonymous polymorphic sites); Pu (# of UTR polymorphic sites); Ds (# of synonymous divergent sites); Du (# of UTR divergent sites); DoS; ⍺ MK . All variants were included.
File S5. Annotations of each transcript in coding regions with SNPGenie: Ps (# of synonymous polymorphic sites); πs (synonymous diversity); Ss_p (total # of synonymous sites in the polymorphism data); Pn (# of non-synonymous polymorphic sites); πn (non-synonymous diversity); Sn_p (total # of non-synonymous sites in the polymorphism data); Ds (# of synonymous divergent sites); ks (synonymous evolutionary rate); Ss_d (total # of synonymous sites in the divergence data); Dn (# of non-synonymous divergent sites); kn (non-synonymous evolutionary rate); Sn_d (total # of non-
synonymous sites in the divergence data); DoS; ⍺ MK . All variants were included.
File S6. Gene expression values (RPKM summed over all transcripts) for each sample. Values were quantile-normalized across all samples.
File S7. Final dataset with all covariates, ⍺ MK , ωA MK and DoS for coding sites, excluding variants below 5% frequency.
File S8. Final dataset with all covariates, ⍺ MK , ωA MK and DoS for non-coding sites, excluding variants below 5%
frequency.
File S9. Final dataset with all covariates, ⍺ EWK , ωA EWK and deleterious SFS for coding sites obtained with the Eyre-Walker and Keightley method on binned data and using all variants.},
author = {Fraisse, Christelle},
keywords = {(mal)adaptation, pleiotropy, selective constraint, evo-devo, gene expression, Drosophila melanogaster},
publisher = {IST Austria},
title = {{Supplementary Files for "Pleiotropy modulates the efficacy of selection in Drosophila melanogaster"}},
doi = {10.15479/at:ista:/5757},
year = {2018},
}
@article{607,
abstract = {We study the Fokker-Planck equation derived in the large system limit of the Markovian process describing the dynamics of quantitative traits. The Fokker-Planck equation is posed on a bounded domain and its transport and diffusion coefficients vanish on the domain's boundary. We first argue that, despite this degeneracy, the standard no-flux boundary condition is valid. We derive the weak formulation of the problem and prove the existence and uniqueness of its solutions by constructing the corresponding contraction semigroup on a suitable function space. Then, we prove that for the parameter regime with high enough mutation rate the problem exhibits a positive spectral gap, which implies exponential convergence to equilibrium.Next, we provide a simple derivation of the so-called Dynamic Maximum Entropy (DynMaxEnt) method for approximation of observables (moments) of the Fokker-Planck solution, which can be interpreted as a nonlinear Galerkin approximation. The limited applicability of the DynMaxEnt method inspires us to introduce its modified version that is valid for the whole range of admissible parameters. Finally, we present several numerical experiments to demonstrate the performance of both the original and modified DynMaxEnt methods. We observe that in the parameter regimes where both methods are valid, the modified one exhibits slightly better approximation properties compared to the original one.},
author = {Bodova, Katarina and Haskovec, Jan and Markowich, Peter},
journal = {Physica D: Nonlinear Phenomena},
pages = {108--120},
publisher = {Elsevier},
title = {{Well posedness and maximum entropy approximation for the dynamics of quantitative traits}},
doi = {10.1016/j.physd.2017.10.015},
volume = {376-377},
year = {2018},
}
@article{315,
abstract = {More than 100 years after Grigg’s influential analysis of species’ borders, the causes of limits to species’ ranges still represent a puzzle that has never been understood with clarity. The topic has become especially important recently as many scientists have become interested in the potential for species’ ranges to shift in response to climate change—and yet nearly all of those studies fail to recognise or incorporate evolutionary genetics in a way that relates to theoretical developments. I show that range margins can be understood based on just two measurable parameters: (i) the fitness cost of dispersal—a measure of environmental heterogeneity—and (ii) the strength of genetic drift, which reduces genetic diversity. Together, these two parameters define an ‘expansion threshold’: adaptation fails when genetic drift reduces genetic diversity below that required for adaptation to a heterogeneous environment. When the key parameters drop below this expansion threshold locally, a sharp range margin forms. When they drop below this threshold throughout the species’ range, adaptation collapses everywhere, resulting in either extinction or formation of a fragmented metapopulation. Because the effects of dispersal differ fundamentally with dimension, the second parameter—the strength of genetic drift—is qualitatively different compared to a linear habitat. In two-dimensional habitats, genetic drift becomes effectively independent of selection. It decreases with ‘neighbourhood size’—the number of individuals accessible by dispersal within one generation. Moreover, in contrast to earlier predictions, which neglected evolution of genetic variance and/or stochasticity in two dimensions, dispersal into small marginal populations aids adaptation. This is because the reduction of both genetic and demographic stochasticity has a stronger effect than the cost of dispersal through increased maladaptation. The expansion threshold thus provides a novel, theoretically justified, and testable prediction for formation of the range margin and collapse of the species’ range.},
author = {Polechova, Jitka},
issn = {15449173},
journal = {PLoS Biology},
number = {6},
publisher = {Public Library of Science},
title = {{Is the sky the limit? On the expansion threshold of a species’ range}},
doi = {10.1371/journal.pbio.2005372},
volume = {16},
year = {2018},
}