@article{6858,
author = {Barton, Nicholas H},
issn = {2095-5138},
journal = {National Science Review},
number = {2},
pages = {291--292},
publisher = {Oxford University Press},
title = {{Is speciation driven by cycles of mixing and isolation?}},
doi = {10.1093/nsr/nwy113},
volume = {6},
year = {2019},
}
@phdthesis{200,
abstract = {This thesis is concerned with the inference of current population structure based on geo-referenced genetic data. The underlying idea is that population structure affects its spatial genetic structure. Therefore, genotype information can be utilized to estimate important demographic parameters such as migration rates. These indirect estimates of population structure have become very attractive, as genotype data is now widely available. However, there also has been much concern about these approaches. Importantly, genetic structure can be influenced by many complex patterns, which often cannot be disentangled. Moreover, many methods merely fit heuristic patterns of genetic structure, and do not build upon population genetics theory. Here, I describe two novel inference methods that address these shortcomings. In Chapter 2, I introduce an inference scheme based on a new type of signal, identity by descent (IBD) blocks. Recently, it has become feasible to detect such long blocks of genome shared between pairs of samples. These blocks are direct traces of recent coalescence events. As such, they contain ample signal for inferring recent demography. I examine sharing of IBD blocks in two-dimensional populations with local migration. Using a diffusion approximation, I derive formulas for an isolation by distance pattern of long IBD blocks and show that sharing of long IBD blocks approaches rapid exponential decay for growing sample distance. I describe an inference scheme based on these results. It can robustly estimate the dispersal rate and population density, which is demonstrated on simulated data. I also show an application to estimate mean migration and the rate of recent population growth within Eastern Europe. Chapter 3 is about a novel method to estimate barriers to gene flow in a two dimensional population. This inference scheme utilizes geographically localized allele frequency fluctuations - a classical isolation by distance signal. The strength of these local fluctuations increases on average next to a barrier, and there is less correlation across it. I again use a framework of diffusion of ancestral lineages to model this effect, and provide an efficient numerical implementation to fit the results to geo-referenced biallelic SNP data. This inference scheme is able to robustly estimate strong barriers to gene flow, as tests on simulated data confirm.},
author = {Ringbauer, Harald},
pages = {146},
publisher = {IST Austria},
title = {{Inferring recent demography from spatial genetic structure}},
doi = {10.15479/AT:ISTA:th_963},
year = {2018},
}
@article{723,
abstract = {Escaping local optima is one of the major obstacles to function optimisation. Using the metaphor of a fitness landscape, local optima correspond to hills separated by fitness valleys that have to be overcome. We define a class of fitness valleys of tunable difficulty by considering their length, representing the Hamming path between the two optima and their depth, the drop in fitness. For this function class we present a runtime comparison between stochastic search algorithms using different search strategies. The (1+1) EA is a simple and well-studied evolutionary algorithm that has to jump across the valley to a point of higher fitness because it does not accept worsening moves (elitism). In contrast, the Metropolis algorithm and the Strong Selection Weak Mutation (SSWM) algorithm, a famous process in population genetics, are both able to cross the fitness valley by accepting worsening moves. We show that the runtime of the (1+1) EA depends critically on the length of the valley while the runtimes of the non-elitist algorithms depend crucially on the depth of the valley. Moreover, we show that both SSWM and Metropolis can also efficiently optimise a rugged function consisting of consecutive valleys.},
author = {Oliveto, Pietro and Paixao, Tiago and Pérez Heredia, Jorge and Sudholt, Dirk and Trubenova, Barbora},
journal = {Algorithmica},
number = {5},
pages = {1604 -- 1633},
publisher = {Springer},
title = {{How to escape local optima in black box optimisation when non elitism outperforms elitism}},
doi = {10.1007/s00453-017-0369-2},
volume = {80},
year = {2018},
}
@article{40,
abstract = {Hanemaaijer et al. (Molecular Ecology, 27, 2018) describe the genetic consequences of the introgression of an insecticide resistance allele into a mosquito population. Linked alleles initially increased, but many of these later declined. It is hard to determine whether this decline was due to counter‐selection, rather than simply to chance.},
author = {Barton, Nicholas H},
issn = {1365294X},
journal = {Molecular Ecology},
number = {24},
pages = {4973--4975},
publisher = {Wiley-Blackwell},
title = {{The consequences of an introgression event}},
doi = {10.1111/mec.14950},
volume = {27},
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},
}