@article{3290,
abstract = {Analysis of genomic data requires an efficient way to calculate likelihoods across very large numbers of loci. We describe a general method for finding the distribution of genealogies: we allow migration between demes, splitting of demes [as in the isolation-with-migration (IM) model], and recombination between linked loci. These processes are described by a set of linear recursions for the generating function of branch lengths. Under the infinite-sites model, the probability of any configuration of mutations can be found by differentiating this generating function. Such calculations are feasible for small numbers of sampled genomes: as an example, we show how the generating function can be derived explicitly for three genes under the two-deme IM model. This derivation is done automatically, using Mathematica. Given data from a large number of unlinked and nonrecombining blocks of sequence, these results can be used to find maximum-likelihood estimates of model parameters by tabulating the probabilities of all relevant mutational configurations and then multiplying across loci. The feasibility of the method is demonstrated by applying it to simulated data and to a data set previously analyzed by Wang and Hey (2010) consisting of 26,141 loci sampled from Drosophila simulans and D. melanogaster. Our results suggest that such likelihood calculations are scalable to genomic data as long as the numbers of sampled individuals and mutations per sequence block are small.},
author = {Lohse, Konrad and Harrison, Richard and Barton, Nicholas H},
journal = {Genetics},
number = {3},
pages = {977 -- 987},
publisher = {Genetics Society of America},
title = {{A general method for calculating likelihoods under the coalescent process}},
doi = {10.1534/genetics.111.129569},
volume = {189},
year = {2011},
}
@article{3372,
abstract = {Nowak et al.1 argue that inclusive fitness theory has been of little value in explaining the natural world, and that it has led to negligible progress in explaining the evolution of eusociality. However, we believe that their arguments are based upon a misunderstanding of evolutionary theory and a misrepresentation of the empirical literature. We will focus our comments on three general issues.},
author = {Abbot, Patrick and Abe, Jun and Alcock, John and Alizon, Samuel and Alpedrinha, Joao and Andersson, Malte and Andre, Jean and Van Baalen, Minus and Balloux, Francois and Balshine, Sigal and Barton, Nicholas H and Beukeboom, Leo and Biernaskie, Jay and Bilde, Trine and Borgia, Gerald and Breed, Michael and Brown, Sam and Bshary, Redouan and Buckling, Angus and Burley, Nancy and Burton Chellew, Max and Cant, Michael and Chapuisat, Michel and Charnov, Eric and Clutton Brock, Tim and Cockburn, Andrew and Cole, Blaine and Colegrave, Nick and Cosmides, Leda and Couzin, Iain and Coyne, Jerry and Creel, Scott and Crespi, Bernard and Curry, Robert and Dall, Sasha and Day, Troy and Dickinson, Janis and Dugatkin, Lee and El Mouden, Claire and Emlen, Stephen and Evans, Jay and Ferriere, Regis and Field, Jeremy and Foitzik, Susanne and Foster, Kevin and Foster, William and Fox, Charles and Gadau, Juergen and Gandon, Sylvain and Gardner, Andy and Gardner, Michael and Getty, Thomas and Goodisman, Michael and Grafen, Alan and Grosberg, Rick and Grozinger, Christina and Gouyon, Pierre and Gwynne, Darryl and Harvey, Paul and Hatchwell, Ben and Heinze, Jürgen and Helantera, Heikki and Helms, Ken and Hill, Kim and Jiricny, Natalie and Johnstone, Rufus and Kacelnik, Alex and Kiers, E Toby and Kokko, Hanna and Komdeur, Jan and Korb, Judith and Kronauer, Daniel and Kümmerli, Rolf and Lehmann, Laurent and Linksvayer, Timothy and Lion, Sébastien and Lyon, Bruce and Marshall, James and Mcelreath, Richard and Michalakis, Yannis and Michod, Richard and Mock, Douglas and Monnin, Thibaud and Montgomerie, Robert and Moore, Allen and Mueller, Ulrich and Noë, Ronald and Okasha, Samir and Pamilo, Pekka and Parker, Geoff and Pedersen, Jes and Pen, Ido and Pfennig, David and Queller, David and Rankin, Daniel and Reece, Sarah and Reeve, Hudson and Reuter, Max and Roberts, Gilbert and Robson, Simon and Roze, Denis and Rousset, Francois and Rueppell, Olav and Sachs, Joel and Santorelli, Lorenzo and Schmid Hempel, Paul and Schwarz, Michael and Scott Phillips, Tom and Shellmann Sherman, Janet and Sherman, Paul and Shuker, David and Smith, Jeff and Spagna, Joseph and Strassmann, Beverly and Suarez, Andrew and Sundström, Liselotte and Taborsky, Michael and Taylor, Peter and Thompson, Graham and Tooby, John and Tsutsui, Neil and Tsuji, Kazuki and Turillazzi, Stefano and Úbeda, Francisco and Vargo, Edward and Voelkl, Bernard and Wenseleers, Tom and West, Stuart and West Eberhard, Mary and Westneat, David and Wiernasz, Diane and Wild, Geoff and Wrangham, Richard and Young, Andrew and Zeh, David and Zeh, Jeanne and Zink, Andrew},
journal = {Nature},
number = {7339},
pages = {E1 -- E4},
publisher = {Nature Publishing Group},
title = {{Inclusive fitness theory and eusociality}},
doi = {10.1038/nature09831},
volume = {471},
year = {2011},
}
@article{3375,
abstract = {By exploiting an analogy between population genetics and statistical mechanics, we study the evolution of a polygenic trait under stabilizing selection, mutation and genetic drift. This requires us to track only four macroscopic variables, instead of the distribution of all the allele frequencies that influence the trait. These macroscopic variables are the expectations of: the trait mean and its square, the genetic variance, and of a measure of heterozygosity, and are derived from a generating function that is in turn derived by maximizing an entropy measure. These four macroscopics are enough to accurately describe the dynamics of the trait mean and of its genetic variance (and in principle of any other quantity). Unlike previous approaches that were based on an infinite series of moments or cumulants, which had to be truncated arbitrarily, our calculations provide a well-defined approximation procedure. We apply the framework to abrupt and gradual changes in the optimum, as well as to changes in the strength of stabilizing selection. Our approximations are surprisingly accurate, even for systems with as few as five loci. We find that when the effects of drift are included, the expected genetic variance is hardly altered by directional selection, even though it fluctuates in any particular instance. We also find hysteresis, showing that even after averaging over the microscopic variables, the macroscopic trajectories retain a memory of the underlying genetic states.},
author = {de Vladar, Harold and Barton, Nicholas H},
journal = {Journal of the Royal Society Interface},
number = {58},
pages = {720 -- 739},
publisher = {Royal Society of London},
title = {{The statistical mechanics of a polygenic character under stabilizing selection mutation and drift}},
doi = {10.1098/rsif.2010.0438},
volume = {8},
year = {2011},
}
@article{3380,
abstract = {Linkage between markers and genes that affect a phenotype of interest may be determined by examining differences in marker allele frequency in the extreme progeny of a cross between two inbred lines. This strategy is usually employed when pooling is used to reduce genotyping costs. When the cross progeny are asexual, the extreme progeny may be selected by multiple generations of asexual reproduction and selection. We analyse this method of measuring phenotype in asexual progeny and examine the changes in marker allele frequency due to selection over many generations. Stochasticity in marker frequency in the selected population arises due to the finite initial population size. We derive the distribution of marker frequency as a result of selection at a single major locus, and show that in order to avoid spurious changes in marker allele frequency in the selected population, the initial population size should be in the low to mid hundreds.},
author = {Logeswaran, Sayanthan and Barton, Nicholas H},
journal = {Genetical Research},
number = {3},
pages = {221 -- 232},
publisher = {Cambridge University Press},
title = {{Mapping Mendelian traits in asexual progeny using changes in marker allele frequency}},
doi = {10.1017/S0016672311000115},
volume = {93},
year = {2011},
}
@article{3390,
abstract = {What determines the genetic contribution that an individual makes to future generations? With biparental reproduction, each individual leaves a 'pedigree' of descendants, determined by the biparental relationships in the population. The pedigree of an individual constrains the lines of descent of each of its genes. An individual's reproductive value is the expected number of copies of each of its genes that is passed on to distant generations conditional on its pedigree. For the simplest model of biparental reproduction analogous to the Wright-Fisher model, an individual's reproductive value is determined within ~10 generations, independent of population size. Partial selfing and subdivision do not greatly slow this convergence. Our central result is that the probability that a gene will survive is proportional to the reproductive value of the individual that carries it, and that conditional on survival, after a few tens of generations, the distribution of the number of surviving copies is the same for all individuals, whatever their reproductive value. These results can be generalized to the joint distribution of surviving blocks of ancestral genome. Selection on unlinked loci in the genetic background may greatly increase the variance in reproductive value, but the above results nevertheless still hold. The almost linear relationship between survival probability and reproductive value also holds for weakly favored alleles. Thus, the influence of the complex pedigree of descendants on an individual's genetic contribution to the population can be summarized through a single number: its reproductive value.},
author = {Barton, Nicholas H and Etheridge, Alison},
journal = {Genetics},
number = {4},
pages = {953 -- 973},
publisher = {Genetics Society of America},
title = {{The relation between reproductive value and genetic contribution}},
doi = {10.1534/genetics.111.127555},
volume = {188},
year = {2011},
}
@article{3391,
abstract = {Evolutionary biology shares many concepts with statistical physics: both deal with populations, whether of molecules or organisms, and both seek to simplify evolution in very many dimensions. Often, methodologies have undergone parallel and independent development, as with stochastic methods in population genetics. Here, we discuss aspects of population genetics that have embraced methods from physics: non-equilibrium statistical mechanics, travelling waves and Monte-Carlo methods, among others, have been used to study polygenic evolution, rates of adaptation and range expansions. These applications indicate that evolutionary biology can further benefit from interactions with other areas of statistical physics; for example, by following the distribution of paths taken by a population through time},
author = {de Vladar, Harold and Barton, Nicholas H},
journal = {Trends in Ecology and Evolution},
number = {8},
pages = {424 -- 432},
publisher = {Cell Press},
title = {{The contribution of statistical physics to evolutionary biology}},
doi = {10.1016/j.tree.2011.04.002},
volume = {26},
year = {2011},
}
@article{3393,
abstract = {Unlike unconditionally advantageous “Fisherian” variants that tend to spread throughout a species range once introduced anywhere, “bistable” variants, such as chromosome translocations, have two alternative stable frequencies, absence and (near) fixation. Analogous to populations with Allee effects, bistable variants tend to increase locally only once they become sufficiently common, and their spread depends on their rate of increase averaged over all frequencies. Several proposed manipulations of insect populations, such as using Wolbachia or “engineered underdominance” to suppress vector-borne diseases, produce bistable rather than Fisherian dynamics. We synthesize and extend theoretical analyses concerning three features of their spatial behavior: rate of spread, conditions to initiate spread from a localized introduction, and wave stopping caused by variation in population densities or dispersal rates. Unlike Fisherian variants, bistable variants tend to spread spatially only for particular parameter combinations and initial conditions. Wave initiation requires introduction over an extended region, while subsequent spatial spread is slower than for Fisherian waves and can easily be halted by local spatial inhomogeneities. We present several new results, including robust sufficient conditions to initiate (and stop) spread, using a one-parameter cubic approximation applicable to several models. The results have both basic and applied implications.},
author = {Barton, Nicholas H and Turelli, Michael},
journal = {American Naturalist},
number = {3},
pages = {E48 -- E75},
publisher = {University of Chicago Press},
title = {{Spatial waves of advance with bistable dynamics: Cytoplasmic and genetic analogues of Allee effects}},
doi = {10.1086/661246},
volume = {178},
year = {2011},
}
@article{3394,
abstract = {Random genetic drift shifts clines in space, alters their width, and distorts their shape. Such random fluctuations complicate inferences from cline width and position. Notably, the effect of genetic drift on the expected shape of the cline is opposite to the naive (but quite common) misinterpretation of classic results on the expected cline. While random drift on average broadens the overall cline in expected allele frequency, it narrows the width of any particular cline. The opposing effects arise because locally, drift drives alleles to fixation—but fluctuations in position widen the expected cline. The effect of genetic drift can be predicted from standardized variance in allele frequencies, averaged across the habitat: 〈F〉. A cline maintained by spatially varying selection (step change) is expected to be narrower by a factor of relative to the cline in the absence of drift. The expected cline is broader by the inverse of this factor. In a tension zone maintained by underdominance, the expected cline width is narrower by about 1 – 〈F〉relative to the width in the absence of drift. Individual clines can differ substantially from the expectation, and we give quantitative predictions for the variance in cline position and width. The predictions apply to clines in almost one-dimensional circumstances such as hybrid zones in rivers, deep valleys, or along a coast line and give a guide to what patterns to expect in two dimensions.},
author = {Polechova, Jitka and Barton, Nicholas H},
journal = {Genetics},
number = {1},
pages = {227 -- 235},
publisher = {Genetics Society of America},
title = {{Genetic drift widens the expected cline but narrows the expected cline width}},
doi = {10.1534/genetics.111.129817},
volume = {189},
year = {2011},
}
@article{3395,
abstract = {Defining population structure and genetic diversity levels is of the utmost importance for developing efficient conservation strategies. Overfishing has caused mean annual catches of the European spiny lobster (Palinurus elephas) to decrease alarmingly along its distribution area. In this context, there is a need for comprehensive studies aiming to evaluate the genetic health of the exploited populations. The present study is based on a set of ten nuclear markers amplified in 331 individuals from ten different localities covering most of P. elephas distribution area. Samples from Atlantic and Mediterranean basins showed small but significant differences, indicating that P. elephas populations do not behave as a single panmictic unit but form two partially-overlapping groups. Despite intense overfishing, our dataset did not recover a recent bottleneck signal, and instead showed a large and stable historical effective size. This result could be accounted for by specific life-history traits (reproduction and longevity) and the limitations of molecular markers in covering recent timescales for nontemporal samples. The findings of the present study emphasize the need to integrate information on effective population sizes and life-history parameters when evaluating population connectivity levels from genetic data.},
author = {Palero, Ferran and Abello, Pere and Macpherson, Enrique and Beaumont, Mark and Pascual, Marta},
journal = {Biological Journal of the Linnean Society},
number = {2},
pages = {407 -- 418},
publisher = {Wiley-Blackwell},
title = {{Effect of oceanographic barriers and overfishing on the population genetic structure of the European spiny lobster Palinurus elephas }},
doi = {10.1111/j.1095-8312.2011.01728.x},
volume = {104},
year = {2011},
}
@article{3778,
author = {Barton, Nicholas H},
journal = {Heredity},
number = {2},
pages = {205 -- 206},
publisher = {Nature Publishing Group},
title = {{Estimating linkage disequilibria}},
doi = {10.1038/hdy.2010.67},
volume = {106},
year = {2011},
}