Ancestral population genomics

The full genomes of several closely related species are now available, opening an emerging field of investigation borrowing both from population genetics and phylogenetics. Providing we can properly model sequence evolution within populations undergoing speciation events, this resource enables us to estimate key population genetics parameters, such as ancestral population sizes and split times. Furthermore, we can enhance our understanding of the recombination process and investigate various selective forces. We discuss the basic speciation models for closely related species, including the isolation and isolation-with-migration models. A major point in our discussion is that only a few complete genomes contain much information about the whole population. The reason being that recombination unlinks genomic regions, and therefore a few genomes contain many segments with distinct histories. The challenge of population genomics is to decode this mosaic of histories in order to infer scenarios of demography and selection. We survey different approaches for understanding ancestral species from analyses of genomic data from closely related species. In particular, we emphasize core assumptions and working hypothesis. Finally, we discuss computational and statistical challenges that arise in the analysis of population genomics data sets

Simulation from endpoint-conditioned, continuous-time Markov chains on a finite state space, with applications to molecular evolution

Analyses of serially-sampled data often begin with the assumption that the observations represent discrete samples from a latent continuous-time stochastic process. The continuous-time Markov chain (CTMC) is one such generative model whose popularity extends to a variety of disciplines ranging from computational finance to human genetics and genomics. A common theme among these diverse applications is the need to simulate sample paths of a CTMC conditional on realized data that is discretely observed. Here we present a general solution to this sampling problem when the CTMC is defined on a discrete and finite state space. Specifically, we consider the generation of sample paths, including intermediate states and times of transition, from a CTMC whose beginning and ending states are known across a time interval of length $T$. We first unify the literature through a discussion of the three predominant approaches: (1) modified rejection sampling, (2) direct sampling, and (3) uniformization. We then give analytical results for the complexity and efficiency of each method in terms of the instantaneous transition rate matrix $Q$ of the CTMC, its beginning and ending states, and the length of sampling time $T$. In doing so, we show that no method dominates the others across all model specifications, and we give explicit proof of which method prevails for any given $Q,T,$ and endpoints. Finally, we introduce and compare three applications of CTMCs to demonstrate the pitfalls of choosing an inefficient sampler.Comment: Published in at http://dx.doi.org/10.1214/09-AOAS247 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

Extreme selective sweeps independently targeted the X chromosomes of the great apes

The unique inheritance pattern of the X chromosome exposes it to natural selection in a way that is different from that of the autosomes, potentially resulting in accelerated evolution. We perform a comparative analysis of X chromosome polymorphism in 10 great ape species, including humans. In most species, we identify striking megabase-wide regions, where nucleotide diversity is less than 20% of the chromosomal average. Such regions are found exclusively on the X chromosome. The regions overlap partially among species, suggesting that the underlying targets are partly shared among species. The regions have higher proportions of singleton SNPs, higher levels of population differentiation, and a higher nonsynonymous-to-synonymous substitution ratio than the rest of the X chromosome. We show that the extent to which diversity is reduced is incompatible with direct selection or the action of background selection and soft selective sweeps alone, and therefore, we suggest that very strong selective sweeps have independently targeted these specific regions in several species. The only genomic feature that we can identify as strongly associated with loss of diversity is the location of testis-expressed ampliconic genes, which also have reduced diversity around them. We hypothesize that these genes may be responsible for selective sweeps in the form of meiotic drive caused by an intragenomic conflict in male meiosis

Blood ties: ABO is a trans-species polymorphism in primates

The ABO histo-blood group, the critical determinant of transfusion incompatibility, was the first genetic polymorphism discovered in humans. Remarkably, ABO antigens are also polymorphic in many other primates, with the same two amino acid changes responsible for A and B specificity in all species sequenced to date. Whether this recurrence of A and B antigens is the result of an ancient polymorphism maintained across species or due to numerous, more recent instances of convergent evolution has been debated for decades, with a current consensus in support of convergent evolution. We show instead that genetic variation data in humans and gibbons as well as in Old World Monkeys are inconsistent with a model of convergent evolution and support the hypothesis of an ancient, multi-allelic polymorphism of which some alleles are shared by descent among species. These results demonstrate that the ABO polymorphism is a trans-species polymorphism among distantly related species and has remained under balancing selection for tens of millions of years, to date, the only such example in Hominoids and Old World Monkeys outside of the Major Histocompatibility Complex.Comment: 45 pages, 4 Figures, 4 Supplementary Figures, 5 Supplementary Table

Ancestral population genomics

Borrowing both from population genetics and phylogenetics, the field of population genomics emerged as full genomes of several closely related species were available. Providing we can properly model sequence evolution within populations undergoing speciation events, this resource enables us to estimate key population genetics parameters such as ancestral population sizes and split times. Furthermore we can enhance our understanding of the recombination process and investigate various selective forces. With the advent of resequencing technologies, genome-wide patterns of diversity in extant populations have now come to complement this picture, offering an increasing power to study more recent genetic history

Different paths to the modern state in Europe: the interaction between domestic political economy and interstate competition

Theoretical work on state formation and capacity has focused mostly on early modern Europe and on the experience of western European states during this period. While a number of European states monopolized domestic tax collection and achieved gains in state capacity during the early modern era, for others revenues stagnated or even declined, and these variations motivated alternative hypotheses for determinants of fiscal and state capacity. In this study we test the basic hypotheses in the existing literature making use of the large date set we have compiled for all of the leading states across the continent. We find strong empirical support for two prevailing threads in the literature, arguing respectively that interstate wars and changes in economic structure towards an urbanized economy had positive fiscal impact. Regarding the main point of contention in the theoretical literature, whether it was representative or authoritarian political regimes that facilitated the gains in fiscal capacity, we do not find conclusive evidence that one performed better than the other. Instead, the empirical evidence we have gathered lends supports to the hypothesis that when under pressure of war, the fiscal performance of representative regimes was better in the more urbanized-commercial economies and the fiscal performance of authoritarian regimes was better in rural-agrarian economie

Fast and Robust Characterization of Time-Heterogeneous Sequence Evolutionary Processes Using Substitution Mapping

Genes and genomes do not evolve similarly in all branches of the tree of life. Detecting and characterizing the heterogeneity in time, and between lineages, of the nucleotide (or amino acid) substitution process is an important goal of current molecular evolutionary research. This task is typically achieved through the use of non-homogeneous models of sequence evolution, which being highly parametrized and computationally-demanding are not appropriate for large-scale analyses. Here we investigate an alternative methodological option based on probabilistic substitution mapping. The idea is to first reconstruct the substitutional history of each site of an alignment under a homogeneous model of sequence evolution, then to characterize variations in the substitution process across lineages based on substitution counts. Using simulated and published datasets, we demonstrate that probabilistic substitution mapping is robust in that it typically provides accurate reconstruction of sequence ancestry even when the true process is heterogeneous, but a homogeneous model is adopted. Consequently, we show that the new approach is essentially as efficient as and extremely faster than (up to 25 000 times) existing methods, thus paving the way for a systematic survey of substitution process heterogeneity across genes and lineages

Skewed Exposure to Environmental Antigens Complements Hygiene Hypothesis in Explaining the Rise of Allergy

The Hygiene Hypothesis has been recognized as an important cornerstone to explain the sudden increase in the prevalence of asthma and allergic diseases in modernized culture. The recent epidemic of allergic diseases is in contrast with the gradual implementation of Homo sapiens sapiens to the present-day forms of civilization. This civilization forms a gradual process with cumulative effects on the human immune system, which co-developed with parasitic and commensal Helminths. The clinical manifestation of this epidemic, however, became only visible in the second half of the twentieth century. In order to explain these clinical effects in terms of the underlying IgE-mediated reactions to innocuous environmental antigens, the low biodiversity of antigens in the domestic environment plays a pivotal role. The skewing of antigen exposure as a cumulative effect of reducing biodiversity in the immediate human environment as well as in changing food habits, provides a sufficient and parsimonious explanation for the rise in allergic diseases in a highly developed and helminth-free modernized culture. Socio-economic tendencies that incline towards a further reduction of environmental biodiversity may provide serious concern for future health. This article explains that the “Hygiene Hypothesis”, the “Old Friends Hypothesis”, and the “Skewed Antigen Exposure Hypothesis” are required to more fully explain the rise of allergy in modern societies

Auxiliary variables for Bayesian inference in multi-class queueing networks

Queueing networks describe complex stochastic systems of both theoretical and practical interest. They provide the means to assess alterations, diagnose poor performance and evaluate robustness across sets of interconnected resources. In the present paper, we focus on the underlying continuous-time Markov chains induced by these networks, and we present a flexible method for drawing parameter inference in multi-class Markovian cases with switching and different service disciplines. The approach is directed towards the inferential problem with missing data, where transition paths of individual tasks among the queues are often unknown. The paper introduces a slice sampling technique with mappings to the measurable space of task transitions between the service stations. This can address time and tractability issues in computational procedures, handle prior system knowledge and overcome common restrictions on service rates across existing inferential frameworks. Finally, the proposed algorithm is validated on synthetic data and applied to a real data set, obtained from a service delivery tasking tool implemented in two university hospitals