@article{11640,
  abstract     = {Spatially explicit population genetic models have long been developed, yet have rarely been used to test hypotheses about the spatial distribution of genetic diversity or the genetic divergence between populations. Here, we use spatially explicit coalescence simulations to explore the properties of the island and the two-dimensional stepping stone models under a wide range of scenarios with spatio-temporal variation in deme size. We avoid the simulation of genetic data, using the fact that under the studied models, summary statistics of genetic diversity and divergence can be approximated from coalescence times. We perform the simulations using gridCoal, a flexible spatial wrapper for the software msprime (Kelleher et al., 2016, Theoretical Population Biology, 95, 13) developed herein. In gridCoal, deme sizes can change arbitrarily across space and time, as well as migration rates between individual demes. We identify different factors that can cause a deviation from theoretical expectations, such as the simulation time in comparison to the effective deme size and the spatio-temporal autocorrelation across the grid. Our results highlight that FST, a measure of the strength of population structure, principally depends on recent demography, which makes it robust to temporal variation in deme size. In contrast, the amount of genetic diversity is dependent on the distant past when Ne is large, therefore longer run times are needed to estimate Ne than FST. Finally, we illustrate the use of gridCoal on a real-world example, the range expansion of silver fir (Abies alba Mill.) since the last glacial maximum, using different degrees of spatio-temporal variation in deme size.},
  author       = {Szep, Eniko and Trubenova, Barbora and Csilléry, Katalin},
  issn         = {1755-0998},
  journal      = {Molecular Ecology Resources},
  number       = {8},
  pages        = {2941--2955},
  publisher    = {Wiley},
  title        = {{Using gridCoal to assess whether standard population genetic theory holds in the presence of spatio-temporal heterogeneity in population size}},
  doi          = {10.1111/1755-0998.13676},
  volume       = {22},
  year         = {2022},
}

@article{9119,
  abstract     = {We present DILS, a deployable statistical analysis platform for conducting demographic inferences with linked selection from population genomic data using an Approximate Bayesian Computation framework. DILS takes as input single‐population or two‐population data sets (multilocus fasta sequences) and performs three types of analyses in a hierarchical manner, identifying: (a) the best demographic model to study the importance of gene flow and population size change on the genetic patterns of polymorphism and divergence, (b) the best genomic model to determine whether the effective size Ne and migration rate N, m are heterogeneously distributed along the genome (implying linked selection) and (c) loci in genomic regions most associated with barriers to gene flow. Also available via a Web interface, an objective of DILS is to facilitate collaborative research in speciation genomics. Here, we show the performance and limitations of DILS by using simulations and finally apply the method to published data on a divergence continuum composed by 28 pairs of Mytilus mussel populations/species.},
  author       = {Fraisse, Christelle and Popovic, Iva and Mazoyer, Clément and Spataro, Bruno and Delmotte, Stéphane and Romiguier, Jonathan and Loire, Étienne and Simon, Alexis and Galtier, Nicolas and Duret, Laurent and Bierne, Nicolas and Vekemans, Xavier and Roux, Camille},
  issn         = {1755-0998},
  journal      = {Molecular Ecology Resources},
  pages        = {2629--2644},
  publisher    = {Wiley},
  title        = {{DILS: Demographic inferences with linked selection by using ABC}},
  doi          = {10.1111/1755-0998.13323},
  volume       = {21},
  year         = {2021},
}

@article{8099,
  abstract     = {Sewall Wright developed FST for describing population differentiation and it has since been extended to many novel applications, including the detection of homomorphic sex chromosomes. However, there has been confusion regarding the expected estimate of FST for a fixed difference between the X‐ and Y‐chromosome when comparing males and females. Here, we attempt to resolve this confusion by contrasting two common FST estimators and explain why they yield different estimates when applied to the case of sex chromosomes. We show that this difference is true for many allele frequencies, but the situation characterized by fixed differences between the X‐ and Y‐chromosome is among the most extreme. To avoid additional confusion, we recommend that all authors using FST clearly state which estimator of FST their work uses.},
  author       = {Gammerdinger, William J and Toups, Melissa A and Vicoso, Beatriz},
  issn         = {1755-0998},
  journal      = {Molecular Ecology Resources},
  number       = {6},
  pages        = {1517--1525},
  publisher    = {Wiley},
  title        = {{Disagreement in FST estimators: A case study from  sex chromosomes}},
  doi          = {10.1111/1755-0998.13210},
  volume       = {20},
  year         = {2020},
}