multi‐dice: r package for comparative population genomic inference under hierarchical co‐demographic models of independent single‐population size changes

Population genetic data from multiple taxa can address comparative phylogeographic questions about community‐scale response to environmental shifts, and a useful strategy to this end is to employ hierarchical co‐demographic models that directly test multi‐taxa hypotheses within a single, unified analysis. This approach has been applied to classical phylogeographic data sets such as mitochondrial barcodes as well as reduced‐genome polymorphism data sets that can yield 10,000s of SNPs, produced by emergent technologies such as RAD‐seq and GBS. A strategy for the latter had been accomplished by adapting the site frequency spectrum to a novel summarization of population genomic data across multiple taxa called the aggregate site frequency spectrum (aSFS), which potentially can be deployed under various inferential frameworks including approximate Bayesian computation, random forest and composite likelihood optimization. Here, we introduce the r package multi‐dice , a wrapper program that exploits existing simulation software for flexible execution of hierarchical model‐based inference using the aSFS, which is derived from reduced genome data, as well as mitochondrial data. We validate several novel software features such as applying alternative inferential frameworks, enforcing a minimal threshold of time surrounding co‐demographic pulses and specifying flexible hyperprior distributions. In sum, multi‐dice provides comparative analysis within the familiar R environment while allowing a high degree of user customization, and will thus serve as a tool for comparative phylogeography and population genomics.     

Exploring Approximate Bayesian Computation for inferring recent demographic history with genomic markers in nonmodel species

Approximate Bayesian computation (ABC) is widely used to infer demographic history of populations and species using DNA markers. Genomic markers can now be developed for nonmodel species using reduced representation library (RRL) sequencing methods that select a fraction of the genome using targeted sequence capture or restriction enzymes (genotyping‐by‐sequencing, GBS). We explored the influence of marker number and length, knowledge of gametic phase, and tradeoffs between sample size and sequencing depth on the quality of demographic inferences performed with ABC. We focused on two‐population models of recent spatial expansion with varying numbers of unknown parameters. Performing ABC on simulated data sets with known parameter values, we found that the timing of a recent spatial expansion event could be precisely estimated in a three‐parameter model. Taking into account uncertainty in parameters such as initial population size and migration rate collectively decreased the precision of inferences dramatically. Phasing haplotypes did not improve results, regardless of sequence length. Numerous short sequences were as valuable as fewer, longer sequences, and performed best when a large sample size was sequenced at low individual depth, even when sequencing errors were added. ABC results were similar to results obtained with an alternative method based on the site frequency spectrum (SFS) when performed with unphased GBS‐type markers. We conclude that unphased GBS‐type data sets can be sufficient to precisely infer simple demographic models, and discuss possible improvements for the use of ABC with genomic data.     

Comparative phylogeographic inference with genome-wide data from aggregated population pairs

Comparing divergences across multiple sister population pairs has been a focus in phylogeography since its inception. Initial approaches used organelle genetic data and involved qualitative comparisons of phylogenetic patterns to evaluate hypotheses of shared and variable evolutionary responses. This endeavor has progressed with coalescent model-based statistical techniques and advances in next-generation sequencing, yet there remains a need for methods that can exploit aggregated genomic-scale data within a unified analytical framework. To this end, we introduce the aggregate joint site frequency spectrum (ajSFS) by validating its use within a hierarchical Bayesian framework through several in silico experiments. Subsequently, we applied our method against two published restriction site–associated DNA marker datasets consisting of eight local replicates of a lamprey species pair and six co-distributed passerine taxon pairs, respectively, with the aim of inferring variability in co-divergence and co-migration histories. We found that the lamprey population pairs exhibited temporal synchrony in both co-divergence and collective secondary contact times, yet an idiosyncratic pattern in secondary migration intensities. In contrast, the bird population pairs displayed thoroughly asynchronous co-divergence histories. Our results demonstrate that the ajSFS can be exploited for complex and flexible co-demographic inference, opening up new possibilities for comparative phylogeography and population genomic studies.     

Germ banks affect the inference of past demographic events

Continuous progress in empirical population genetics based on the whole‐genome polymorphism data requires the theoretical analysis of refined models in order to interpret the evolutionary history of populations with adequate accuracy. Recent studies focus prevalently on the aspects of demography and adaptation, whereas age structure (for example, in plants via the maintenance of seed banks) has attracted less attention. Germ banking, that is, seed or egg dormancy, is a prevalent and important life‐history trait in plants and invertebrates, which buffers against environmental variability and modulates species extinction in fragmented habitats. Within this study, we investigate the combined effect of germ banking and time‐varying population size on the neutral coalescent and particularly derive the allele frequency spectrum under some simplifying assumptions. We then perform an ABC analysis using two simple demographic scenarios—a population expansion and an instantaneous decline. We demonstrate the appreciable influence of seed banks on the estimation of demographic parameters depending on the germination rate with biases scaled by the square of the germination rate. In the more complex case of a population bottleneck, which comprises an instantaneous decline and an expansion phase, ignoring information on the germination rate denies reliable estimates of the bottleneck parameters via the allelic spectrum. In particular, when seeds remain in the bank over several generations, recent expansions may remain invisible in the frequency spectrum, whereas ancient declines leave signatures much longer than in the absence of seed bank.     

ABC inference of multi‐population divergence with admixture from unphased population genomic data

Rapidly developing sequencing technologies and declining costs have made it possible to collect genome‐scale data from population‐level samples in nonmodel systems. Inferential tools for historical demography given these data sets are, at present, underdeveloped. In particular, approximate Bayesian computation (ABC) has yet to be widely embraced by researchers generating these data. Here, we demonstrate the promise of ABC for analysis of the large data sets that are now attainable from nonmodel taxa through current genomic sequencing technologies. We develop and test an ABC framework for model selection and parameter estimation, given histories of three‐population divergence with admixture. We then explore different sampling regimes to illustrate how sampling more loci, longer loci or more individuals affects the quality of model selection and parameter estimation in this ABC framework. Our results show that inferences improved substantially with increases in the number and/or length of sequenced loci, while less benefit was gained by sampling large numbers of individuals. Optimal sampling strategies given our inferential models included at least 2000 loci, each approximately 2 kb in length, sampled from five diploid individuals per population, although specific strategies are model and question dependent. We tested our ABC approach through simulation‐based cross‐validations and illustrate its application using previously analysed data from the oak gall wasp, Biorhiza pallida.     

McSwan: A joint site frequency spectrum method to detect and date selective sweeps across multiple population genomes

Inferring the mode and tempo of natural selection helps further our understanding of adaptation to past environmental changes. Here, we introduce McSwan, a method to detect and date past and recent natural selection events in the case of a hard sweep. The method is based on the comparison of site frequency spectra obtained under various demographic models that include selection. McSwan demonstrated high power (high sensitivity and specificity) in capturing hard selective sweep events without requiring haplotype phasing. It performed slightly better than SweeD when the recent effective population size was low and the genomic region was small. We then applied our method to a European (CEU) and an African (LWK) human re‐sequencing data set. Most hard sweeps were detected in the CEU population (96%). Moreover, hard sweeps in the African population were estimated to have occurred further back in time (mode: 43,625 years BP) compared to those of Europeans (mode: 24,850 years BP). Most of the estimated ages of hard sweeps in Europeans were associated with the Last Glacial Maximum and were enriched in immunity‐associated genes.     

High genomic diversity in the bank vole at the northern apex of a range expansion: The role of multiple colonizations and end‐glacial refugia

The history of repeated northern glacial cycling and southern climatic stability has long dominated explanations for how genetic diversity is distributed within temperate species in Eurasia and North America. However, growing evidence indicates the importance of cryptic refugia for northern colonization dynamics. An important geographic region to assess this is Fennoscandia, where recolonization at the end of the last glaciation was restricted to specific routes and temporal windows. We used genomic data to analyse genetic diversity and colonization history of the bank vole (Myodes glareolus) throughout Europe (>800 samples) with Fennoscandia as the northern apex. We inferred that bank voles colonized Fennoscandia multiple times by two different routes; with three separate colonizations via a southern land‐bridge route deriving from a “Carpathian” glacial refugium and one via a north‐eastern route from an “Eastern” glacial refugium near the Ural Mountains. Clustering of genome‐wide SNPs revealed high diversity in Fennoscandia, with eight genomic clusters: three of Carpathian origin and five Eastern. Time estimates revealed that the first of the Carpathian colonizations occurred before the Younger Dryas (YD), meaning that the first colonists survived the YD in Fennoscandia. Results also indicated that introgression between bank and northern red‐backed voles (Myodes rutilus) took place in Fennoscandia just after end‐glacial colonization. Therefore, multiple colonizations from the same and different cryptic refugia, temporal and spatial separations and interspecific introgression have shaped bank vole genetic variability in Fennoscandia. Together, these processes drive high genetic diversity at the apex of the northern expansion in this emerging model species.