Extending phylogeography to account for lineage fusion

Secondary contact between long isolated populations has several possible outcomes. These include the strengthening of preexisting reproductive isolating mechanisms via reinforcement, the emergence of a hybrid lineage that is distinct from its extant parental lineages and which occupies a spatially restricted zone between them, or complete merging of two populations such that parental lineages are no longer extant (“lineage fusion” herein). The latter scenario has rarely been explicitly considered in single‐species and comparative phylogeographic studies, yet it has the potential to impact inferences about population history and levels of congruence. In this paper, we explore the idea that insights into past lineage fusion may now be possible, owing to the advent of next‐generation sequencing. Using simulated DNA sequence haplotype datasets (i.e., loci with alleles comprised of a set of linked nucleotide polymorphisms), we examined basic requirements (number of loci and individuals sampled) for identifying cases when a present‐day panmictic population is the product of lineage fusion, using an exemplar statistical framework—approximate Bayesian computation. We found that with approximately 100 phased haplotype loci (each 400 bp long) and modest sample sizes of individuals (10 per population), lineage fusion can be detected under rather challenging scenarios. This included some scenarios where reticulation was fully contained within a Last Glacial Maximum timeframe, provided that mixing was symmetrical, ancestral gene pools were moderately to deeply diverged, and the lag time between the fusion event and gene pool sampling was relatively short. However, the more realistic case of asymmetrical mixing is not prohibitive if additional genetic data (e.g., 400 loci) are available. Notwithstanding some simplifying assumptions of our simulations and the knowledge gaps that remain about the circumstances under which lineage fusion is potentially detectable, we suggest that the recent release from data limitation allows phylogeographers to expand the scope of inferences about long‐term population history.     

Post-GWAS: where next? More samples,more SNPs or more biology?

The power of genome-wide association studies (GWAS) rests on several foundations: (i) there is a significant amount of additive genetic variation, (ii) individual causal polymorphisms often have sizable effects and (iii) they segregate at moderate-to-intermediate frequencies, or will be effectively ‘tagged'' by polymorphisms that do. Each of these assumptions has recently been questioned. (i) Why should genetic variation appear additive given that the underlying molecular networks are highly nonlinear? (ii) A new generation of relatedness-based analyses directs us back to the nearly infinitesimal model for effect sizes that quantitative genetics was long based upon. (iii) Larger effect causal polymorphisms are often low frequency, as selection might lead us to expect. Here, we review these issues and other findings that appear to question many of the foundations of the optimism GWAS prompted. We then present a roadmap emerging as one possible future for quantitative genetics. We argue that in future GWAS should move beyond purely statistical grounds. One promising approach is to build upon the combination of population genetic models and molecular biological knowledge. This combined treatment, however, requires fitting experimental data to models that are very complex, as well as accurate capturing of the uncertainty of resulting inference. This problem can be resolved through Bayesian analysis and tools such as approximate Bayesian computation—a method growing in popularity in population genetic analysis. We show a case example of anterior–posterior segmentation in Drosophila, and argue that similar approaches will be helpful as a GWAS augmentation, in human and agricultural research.     

Multiple introductions,admixture and bridgehead invasion characterize the introduction history of Ambrosia artemisiifolia in Europe and Australia

Admixture between differentiated populations is considered to be a powerful mechanism stimulating the invasive success of some introduced species. It is generally facilitated through multiple introductions; however, the importance of admixture prior to introduction has rarely been considered. We assess the likelihood that the invasive Ambrosia artemisiifolia populations of Europe and Australia developed through multiple introductions or were sourced from a historical admixture zone within native North America. To do this, we combine large genomic and sampling data sets analysed with approximate Bayesian computation and random forest scenario evaluation to compare single and multiple invasion scenarios with pre‐ and postintroduction admixture simultaneously. We show the historical admixture zone within native North America originated before global invasion of this weed and could act as a potential source of introduced populations. We provide evidence supporting the hypothesis that the invasive populations established through multiple introductions from the native range into Europe and subsequent bridgehead invasion into Australia. We discuss the evolutionary mechanisms that could promote invasiveness and evolutionary potential of alien species from bridgehead invasions and admixed source populations.     

Crystal Structural Framework of Lithium Super‐Ionic Conductors

As technologically important materials for solid‐state batteries, Li super‐ionic conductors are a class of materials exhibiting exceptionally high ionic conductivity at room temperature. These materials have unique crystal structural frameworks hosting a highly conductive Li sublattice. However, it is not understood why certain crystal structures of the super‐ionic conductors lead to high conductivity in the Li sublattice. In this study, using topological analysis and ab initio molecular dynamics simulations, the crystal structures of all Li‐conducting oxides and sulfides are studied systematically and the key features pertaining to fast‐ion conduction are quantified. In particular, a unique feature of enlarged Li sites caused by large local spaces in the crystal structural framework is identified, promoting fast conduction in the Li‐ion sublattice. Based on these quantified features, the high‐throughput screening identifies many new structures as fast Li‐ion conductors, which are further confirmed by ab initio molecular dynamics simulations. This study provides new insights and a systematic quantitative understanding of the crystal structural frameworks of fast ion‐conductor materials and motivates future experimental and computational studies on new fast‐ion conductors.     

Echoes of a distant time: effects of historical processes on contemporary genetic patterns in Galaxias platei in Patagonia

Interpreting the genetic structure of a metapopulation as the outcome of gene flow over a variety of timescales is essential for the proper understanding of how changes in landscape affect biological connectivity. Here we contrast historical and contemporary connectivity in two metapopulations of the freshwater fish Galaxias platei in northern and southernmost Patagonia where paleolakes existed during the Holocene and Pleistocene, respectively. Contemporary gene flow was mostly high and asymmetrical in the northern system while extremely reduced in the southernmost system. Historical migration patterns were high and symmetric in the northern system and high and largely asymmetric in the southern system. Both systems showed a moderate structure with a clear pattern of isolation by distance (IBD). Effective population sizes were smaller in populations with low contemporary gene flow. An approximate Bayesian computation (ABC) approach suggests a late Holocene colonization of the lakes in the northern system and recent divergence of the populations from refugial populations from east and west of the Andes. For the southern system, the ABC approach reveals that some of the extant G. platei populations most likely derive from an ancestral population inhabiting a large Pleistocene paleolake while the rest derive from a higher‐altitude lake. Our results suggest that neither historical nor contemporary processes individually fully explain the observed structure and geneflow patterns and both are necessary for a proper understanding of the factors that affect diversity and its distribution. Our study highlights the importance of a temporal perspective on connectivity to analyse the diversity of spatially complex metapopulations.     

Generalized causal mediation analysis

The goal of mediation analysis is to assess direct and indirect effects of a treatment or exposure on an outcome. More generally, we may be interested in the context of a causal model as characterized by a directed acyclic graph (DAG), where mediation via a specific path from exposure to outcome may involve an arbitrary number of links (or "stages"). Methods for estimating mediation (or pathway) effects are available for a continuous outcome and a continuous mediator related via a linear model, while for a categorical outcome or categorical mediator, methods are usually limited to two-stage mediation. We present a method applicable to multiple stages of mediation and mixed variable types using generalized linear models. We define pathway effects using a potential outcomes framework and present a general formula that provides the effect of exposure through any specified pathway. Some pathway effects are nonidentifiable and their estimation requires an assumption regarding the correlation between counterfactuals. We provide a sensitivity analysis to assess the impact of this assumption. Confidence intervals for pathway effect estimates are obtained via a bootstrap method. The method is applied to a cohort study of dental caries in very low birth weight adolescents. A simulation study demonstrates low bias of pathway effect estimators and close-to-nominal coverage rates of confidence intervals. We also find low sensitivity to the counterfactual correlation in most scenarios.     

Leveraging whole genome sequencing data for demographic inference with approximate Bayesian computation

Accounting for historical demographic features, such as the strength and timing of gene flow and divergence times between closely related lineages, is vital for many inferences in evolutionary biology. Approximate Bayesian computation (ABC) is one method commonly used to estimate demographic parameters. However, the DNA sequences used as input for this method, often microsatellites or RADseq loci, usually represent a small fraction of the genome. Whole genome sequencing (WGS) data, on the other hand, have been used less often with ABC, and questions remain about the potential benefit of, and how to best implement, this type of data; we used pseudo‐observed data sets to explore such questions. Specifically, we addressed the potential improvements in parameter estimation accuracy that could be associated with WGS data in multiple contexts; namely, we quantified the effects of (a) more data, (b) haplotype‐based summary statistics, and (c) locus length. Compared with a hypothetical RADseq data set with 2.5 Mbp of data, using a 1 Gbp data set consisting of 100 Kbp sequences led to substantial gains in the accuracy of parameter estimates, which was mostly due to haplotype statistics and increased data. We also quantified the effects of including (a) locus‐specific recombination rates, and (b) background selection information in ABC analyses. Importantly, assuming uniform recombination or ignoring background selection had a negative effect on accuracy in many cases. Software and results from this method validation study should be useful for future demographic history analyses.     

Speciation with gene flow in whiptail lizards from a Neotropical xeric biome

Two main hypotheses have been proposed to explain the diversification of the Caatinga biota. The riverine barrier hypothesis (RBH) claims that the São Francisco River (SFR) is a major biogeographic barrier to gene flow. The Pleistocene climatic fluctuation hypothesis (PCH) states that gene flow, geographic genetic structure and demographic signatures on endemic Caatinga taxa were influenced by Quaternary climate fluctuation cycles. Herein, we analyse genetic diversity and structure, phylogeographic history, and diversification of a widespread Caatinga lizard (Cnemidophorus ocellifer) based on large geographical sampling for multiple loci to test the predictions derived from the RBH and PCH. We inferred two well‐delimited lineages (Northeast and Southwest) that have diverged along the Cerrado–Caatinga border during the Mid‐Late Miocene (6–14 Ma) despite the presence of gene flow. We reject both major hypotheses proposed to explain diversification in the Caatinga. Surprisingly, our results revealed a striking complex diversification pattern where the Northeast lineage originated as a founder effect from a few individuals located along the edge of the Southwest lineage that eventually expanded throughout the Caatinga. The Southwest lineage is more diverse, older and associated with the Cerrado–Caatinga boundaries. Finally, we suggest that C. ocellifer from the Caatinga is composed of two distinct species. Our data support speciation in the presence of gene flow and highlight the role of environmental gradients in the diversification process.     

Estimation of Parameters for Macroparasite Population Evolution Using Approximate Bayesian Computation

Summary We estimate the parameters of a stochastic process model for a macroparasite population within a host using approximate Bayesian computation (ABC). The immunity of the host is an unobserved model variable and only mature macroparasites at sacrifice of the host are counted. With very limited data, process rates are inferred reasonably precisely. Modeling involves a three variable Markov process for which the observed data likelihood is computationally intractable. ABC methods are particularly useful when the likelihood is analytically or computationally intractable. The ABC algorithm we present is based on sequential Monte Carlo, is adaptive in nature, and overcomes some drawbacks of previous approaches to ABC. The algorithm is validated on a test example involving simulated data from an autologistic model before being used to infer parameters of the Markov process model for experimental data. The fitted model explains the observed extra‐binomial variation in terms of a zero‐one immunity variable, which has a short‐lived presence in the host.     

Information contents and dinucleotide compositions of plant intron sequences vary with evolutionary origin

The DNA sequence composition of 526 dicot and 345 monocot intron sequences have been characterized using computational methods. Splice site information content and bulk intron and exon dinucleotide composition were determined. Positions 4 and 5 of 5 splice sites contain different statistically significant levels of information in the two groups. Basal levels of information in introns are higher in dicots than in monocots. Two dinucleotide groups, WW (AA, AU, UA, UU) and SS (CC, CG, GC, GG) have significantly different frequencies in exons and introns of the two plant groups. These results suggest that the mechanisms of splice-site recognition and binding may differ between dicot and monocot plants.