Forward-in-Time, Spatially Explicit Modeling Software to Simulate Genetic Lineages Under Selection

SELECTOR is a software package for studying the evolution of multiallelic genes under balancing or positive selection while simulating complex evolutionary scenarios that integrate demographic growth and migration in a spatially explicit population framework. Parameters can be varied both in space and time to account for geographical, environmental, and cultural heterogeneity. SELECTOR can be used within an approximate Bayesian computation estimation framework. We first describe the principles of SELECTOR and validate the algorithms by comparing its outputs for simple models with theoretical expectations. Then, we show how it can be used to investigate genetic differentiation of loci under balancing selection in interconnected demes with spatially heterogeneous gene flow. We identify situations in which balancing selection reduces genetic differentiation between population groups compared with neutrality and explain conflicting outcomes observed for human leukocyte antigen loci. These results and three previously published applications demonstrate that SELECTOR is efficient and robust for building insight into human settlement history and evolution

Genetic Demixing and Evolutionary Forces in the One-Dimensional Stepping Stone Model

We review and extend results for mutation, selection, genetic drift, and migration in a one-dimensional continuous population. The population is described by a continuous limit of the stepping stone model, which leads to the stochastic Fisher-Kolmogorov-Petrovsky-Piscounov equation with additional terms describing mutations. Although the stepping stone model was first proposed for population genetics, it is closely related to "voter models" of interest in nonequilibrium statistical mechanics. The stepping stone model can also be regarded as an approximation to the dynamics of a thin layer of actively growing pioneers at the frontier of a colony of microorganisms undergoing a range expansion on a Petri dish. We find that the population tends to segregate into monoallelic domains. This segregation slows down genetic drift and selection because these two evolutionary forces can only act at the boundaries between the domains; the effects of mutation, however, are not significantly affected by the segregation. Although fixation in the neutral well-mixed (or "zero dimensional") model occurs exponentially in time, it occurs only algebraically fast in the one-dimensional model. If selection is weak, selective sweeps occur exponentially fast in both well-mixed and one-dimensional populations, but the time constants are different. We also find an unusual sublinear increase in the variance of the spatially averaged allele frequency with time. Although we focus on two alleles or variants, q-allele Potts-like models of gene segregation are considered as well. We also investigate the effects of geometry at the frontier by considering growth of circular colonies. Our analytical results are checked with simulations, and could be tested against recent spatial experiments on range expansions off linear inoculations of Escherichia coli and Saccharomyces cerevisiae.Comment: 29 pages, 20 figures; Reviews of Modern Physics, Volume 82, April-June 201

Selecting for useful properties of plants and fungi – Novel approaches, opportunities, and challenges

Humans use plants and fungi for a wide range of purposes and, over millennia, have improved wild species by selecting for and combining genetic variation. Improvements in DNA sequencing technologies have enhanced our capacity to identify and manipulate genetic diversity, increasing the range of variation that can be utilized, and accelerating the breeding cycle to reduce the time taken to develop and put new varieties to use. Most recently, the CRISPR/Cas9 gene editing technology has greatly increased our capacity to directly introduce novel genetic variants without unwanted associated material. Moreover, increased knowledge of metabolic pathways resulting from genomic analysis can be used to design new varieties with desired properties with increased precision. Selecting for, or engineering, desirable variants has increased the usefulness of plants and fungi to humans, but at the cost of reducing their genetic diversity, decreasing their resilience and reducing the stock of variation available for future use. Conservation of genetic biodiversity is thus an essential counterpart of crop improvement and is essential to ensure that crop species retain resilience to emerging threats. Conservation efforts are focused on orphan crops, wild relatives of crop species, and landraces; in and exsitu efforts are complementary. Informatic approaches can inform use of these materials in breeding programmes even in the absence of genomic information. The application of some of these approaches may be restricted by ethical, legal, or organizational obstacles. If these can be overcome, there is great potential to unlock previously untapped reservoirs of biodiversity for human benefit

Assessing population genetic structure via the maximisation of genetic distance

<p>Abstract</p> <p>Background</p> <p>The inference of the hidden structure of a population is an essential issue in population genetics. Recently, several methods have been proposed to infer population structure in population genetics.</p> <p>Methods</p> <p>In this study, a new method to infer the number of clusters and to assign individuals to the inferred populations is proposed. This approach does not make any assumption on Hardy-Weinberg and linkage equilibrium. The implemented criterion is the maximisation (via a <it>simulated annealing </it>algorithm) of the averaged genetic distance between a predefined number of clusters. The performance of this method is compared with two Bayesian approaches: STRUCTURE and BAPS, using simulated data and also a real human data set.</p> <p>Results</p> <p>The simulations show that with a reduced number of markers, BAPS overestimates the number of clusters and presents a reduced proportion of correct groupings. The accuracy of the new method is approximately the same as for STRUCTURE. Also, in Hardy-Weinberg and linkage disequilibrium cases, BAPS performs incorrectly. In these situations, STRUCTURE and the new method show an equivalent behaviour with respect to the number of inferred clusters, although the proportion of correct groupings is slightly better with the new method. Re-establishing equilibrium with the randomisation procedures improves the precision of the Bayesian approaches. All methods have a good precision for <it>F</it>_{<it>ST </it>}≥ 0.03, but only STRUCTURE estimates the correct number of clusters for <it>F</it>_{<it>ST </it>}as low as 0.01. In situations with a high number of clusters or a more complex population structure, MGD performs better than STRUCTURE and BAPS. The results for a human data set analysed with the new method are congruent with the geographical regions previously found.</p> <p>Conclusion</p> <p>This new method used to infer the hidden structure in a population, based on the maximisation of the genetic distance and not taking into consideration any assumption about Hardy-Weinberg and linkage equilibrium, performs well under different simulated scenarios and with real data. Therefore, it could be a useful tool to determine genetically homogeneous groups, especially in those situations where the number of clusters is high, with complex population structure and where Hardy-Weinberg and/or linkage equilibrium are present.</p

A Quantitative Test of Hamilton's Rule for the Evolution of Altruism

A study of experimental evolution in simulated groups of foraging robots demonstrates that their propensity to behave altruistically depends on their genetic relatedness (similarity), and the costs and benefits associated with altruistic behavior

Population structure and genetic diversity in a commercial maize breeding program assessed with SSR and SNP markers

Information about the genetic diversity and population structure in elite breeding material is of fundamental importance for the improvement of crops. The objectives of our study were to (a) examine the population structure and the genetic diversity in elite maize germplasm based on simple sequence repeat (SSR) markers, (b) compare these results with those obtained from single nucleotide polymorphism (SNP) markers, and (c) compare the coancestry coefficient calculated from pedigree records with genetic distance estimates calculated from SSR and SNP markers. Our study was based on 1,537 elite maize inbred lines genotyped with 359 SSR and 8,244 SNP markers. The average number of alleles per locus, of group specific alleles, and the gene diversity (D) were higher for SSRs than for SNPs. Modified Roger’s distance (MRD) estimates and membership probabilities of the STRUCTURE matrices were higher for SSR than for SNP markers but the germplasm organization in four heterotic pools was consistent with STRUCTURE results based on SSRs and SNPs. MRD estimates calculated for the two marker systems were highly correlated (0.87). Our results suggested that the same conclusions regarding the structure and the diversity of heterotic pools could be drawn from both markers types. Furthermore, although our results suggested that the ratio of the number of SSRs and SNPs required to obtain MRD or D estimates with similar precision is not constant across the various precision levels, we propose that between 7 and 11 times more SNPs than SSRs should be used for analyzing population structure and genetic diversity

Impact of Selection and Demography on the Diffusion of Lactase Persistence

BACKGROUND: The lactase enzyme allows lactose digestion in fresh milk. Its activity strongly decreases after the weaning phase in most humans, but persists at a high frequency in Europe and some nomadic populations. Two hypotheses are usually proposed to explain the particular distribution of the lactase persistence phenotype. The gene-culture coevolution hypothesis supposes a nutritional advantage of lactose digestion in pastoral populations. The calcium assimilation hypothesis suggests that carriers of the lactase persistence allele(s) (LCT*P) are favoured in high-latitude regions, where sunshine is insufficient to allow accurate vitamin-D synthesis. In this work, we test the validity of these two hypotheses on a large worldwide dataset of lactase persistence frequencies by using several complementary approaches. METHODOLOGY: We first analyse the distribution of lactase persistence in various continents in relation to geographic variation, pastoralism levels, and the genetic patterns observed for other independent polymorphisms. Then we use computer simulations and a large database of archaeological dates for the introduction of domestication to explore the evolution of these frequencies in Europe according to different demographic scenarios and selection intensities. CONCLUSIONS: Our results show that gene-culture coevolution is a likely hypothesis in Africa as high LCT*P frequencies are preferentially found in pastoral populations. In Europe, we show that population history played an important role in the diffusion of lactase persistence over the continent. Moreover, selection pressure on lactase persistence has been very high in the North-western part of the continent, by contrast to the South-eastern part where genetic drift alone can explain the observed frequencies. This selection pressure increasing with latitude is highly compatible with the calcium assimilation hypothesis while the gene-culture coevolution hypothesis cannot be ruled out if a positively selected lactase gene was carried at the front of the expansion wave during the Neolithic transition in Europe

Rate accelerations in nuclear 18S rDNA of mycoheterotrophic and parasitic angiosperms

Rate variation in genes from all three genomes has been observed frequently in plant lineages with a parasitic and mycoheterotrophic mode of life. While the loss of photosynthetic ability leads to a relaxation of evolutionary constraints in genes involved in the photosynthetic apparatus, it remains to be determined how prevalent increased substitution rates are in nuclear DNA of non-photosynthetic angiosperms. In this study we infer rates of molecular evolution of 18S rDNA of all parasitic and mycoheterotorphic plant families (except Lauraceae and Polygalaceae) using relative rate tests. In several holoparasitic and mycoheterotrophic plant lineages extremely high substitution rates are observed compared to other photosynthetic angiosperms. The position and frequency of these substitutions have been identified to understand the mutation dynamics of 18S rRNA in achlorophyllous plants. Despite the presence of significantly elevated substitution rates, very few mutations occur in major functional and structural regions of the small ribosomal molecule, providing evidence that the efficiency of the translational apparatus in non-photosynthetic plants has not been affected

Evidence for a heritable predisposition to Chronic Fatigue Syndrome

<p>Abstract</p> <p>Background</p> <p>Chronic Fatigue Syndrome (CFS) came to attention in the 1980s, but initial investigations did not find organic causes. Now decades later, the etiology of CFS has yet to be understood, and the role of genetic predisposition in CFS remains controversial. Recent reports of CFS association with the retrovirus xenotropic murine leukemic virus-related virus (XMRV) or other murine leukemia related retroviruses (MLV) might also suggest underlying genetic implications within the host immune system.</p> <p>Methods</p> <p>We present analyses of familial clustering of CFS in a computerized genealogical resource linking multiple generations of genealogy data with medical diagnosis data of a large Utah health care system. We compare pair-wise relatedness among cases to expected relatedness in the Utah population, and we estimate risk for CFS for first, second, and third degree relatives of CFS cases.</p> <p>Results</p> <p>We observed significant excess relatedness of CFS cases compared to that expected in this population. Significant excess relatedness was observed for both close (p <0.001) and distant relationships (p = 0.010). We also observed significant excess CFS relative risk among first (2.70, 95% CI: 1.56-4.66), second (2.34, 95% CI: 1.31-4.19), and third degree relatives (1.93, 95% CI: 1.21-3.07).</p> <p>Conclusions</p> <p>These analyses provide strong support for a heritable contribution to predisposition to Chronic Fatigue Syndrome. A population of high-risk CFS pedigrees has been identified, the study of which may provide additional understanding.</p