Genetic signatures of lineage fusion closely resemble population decline

Accurate interpretation of the genetic signatures of past demographic events is crucial for reconstructing evolutionary history. Lineage fusion (complete merging, resulting in a single panmictic population) is a special case of secondary contact that is seldom considered. Here, the circumstances under which lineage fusion can be distinguished from population size constancy, growth, bottleneck, and decline were investigated. Multi-locus haplotype data were simulated under models of lineage fusion with different divergence versus sampling lag times (D:L ratios). These pseudo-observed datasets also differed in their allocation of a fixed amount of sequencing resources (number of sampled alleles, haplotype length, number of loci). Distinguishability of lineage fusion versus each of 10 untrue non-fusion scenarios was quantified based on six summary statistics (neutrality tests). Some datasets were also analyzed using extended Bayesian skyline plots. Results showed that signatures of lineage fusion very closely resemble those of decline-high distinguishability was generally limited to the most favorable scenario (D:L = 9), using the most sensitive summary statistics (F S and Z nS), coupled with the optimal sequencing resource allocation (maximizing number of loci). Also, extended Bayesian skyline plots often erroneously inferred population decline. Awareness of the potential for lineage fusion to carry the hallmarks of population decline is critical.

Exome Resequencing Reveals Evolutionary History, Genomic Diversity, and Targets of Selection in the Conifers Pinus taeda and Pinus elliottii

Loblolly pine (Pinus taeda) and slash pine (Pinus elliottii) are ecologically and economically important pine species that dominate many forest ecosystems in the southern United States, but like all conifers, the study of their genetic diversity and demographic history has been hampered by their large genome size. A small number of studies mainly based on candidate-gene sequencing have been reported for P. taeda to date, whereas none are available for P. elliottii. Targeted exome resequencing has recently enabled population genomics studies for conifers, approach used here to assess genomic diversity, signatures of selection, population structure, and demographic history of P. elliottii and P. taeda. Extensive similarities were revealed between these species: both species feature rapid linkage disequilibrium decay and high levels of genetic diversity. Moreover, genome-wide positive correlations for measures of genetic diversity between the species were also observed, likely due to shared structural genomic constraints. Also, positive selection appears to be targeting a common set of genes in both pines. Demographic history differs between both species, with only P. taeda being affected by a dramatic bottleneck during the last glacial period. The ability of P. taeda to recover from a dramatic reduction in population size while still retaining high levels of genetic diversity shows promise for other pines facing environmental stressors associated with climate change, indicating that these too may be able to adapt successfully to new future conditions even after a drastic population size contraction.

SimBac: simulation of whole bacterial genomes with homologous recombination

Bacteria can exchange genetic material, or acquire genes found in the environment. This process, generally known as bacterial recombination, can have a strong impact on the evolution and phenotype of bacteria, for example causing the spread of antibiotic resistance across clades and species, but can also disrupt phylogenetic and transmission inferences. With the increasing affordability of whole genome sequencing, the need has emerged for an efficient simulator of bacterial evolution to test and compare methods for phylogenetic and population genetic inference, and for simulation-based estimation. We present SimBac, a whole-genome bacterial evolution simulator that is roughly two orders of magnitude faster than previous software and includes a more general model of bacterial evolution, allowing both within- and between-species homologous recombination. Since methods modelling bacterial recombination generally focus on only one of these two modes of recombination, the possibility to simulate both allows for a general and fair benchmarking. SimBac is available from https://github.com/tbrown91/SimBac and is distributed as open source under the terms of the GNU General Public Licence.

A Review on Methods for Detecting SNP Interactions in High-Dimensional Genomic Data

In this era of genome-wide association studies (GWAS), the quest for understanding the genetic architecture of complex diseases is rapidly increasing more than ever before. The development of high throughput genotyping and next generation sequencing technologies enables genetic epidemiological analysis of large scale data. These advances have led to the identification of a number of single nucleotide polymorphisms (SNPs) responsible for disease susceptibility. The interactions between SNPs associated with complex diseases are increasingly being explored in the current literature. These interaction studies are mathematically challenging and computationally complex. These challenges have been addressed by a number of data mining and machine learning approaches. This paper reviews the current methods and the related software packages to detect the SNP interactions that contribute to diseases. The issues that need to be considered when developing these models are addressed in this review. The paper also reviews the achievements in data simulation to evaluate the performance of these models. Further, it discusses the future of SNP interaction analysis.

Hybridization between previously isolated ancestors may explain the persistence of exactly two ancient lineages in the genome of the oyster parasite Perkinsus marinus

Theory predicts that neutral genetic variation accumulates within populations to a level determined by gains through mutation and losses by genetic drift. This balance results in a characteristic distribution of allelic variation with the maximum allelic difference determined by effective population size. Here, we report a striking departure from these expectations in the form of allelic dimorphism, observed at the majority of seven loci examined in Perkinsus marinus, an important oyster parasite that causes Dermo disease. DNA sequences were collected from five loci flanking microsatellite repeats and two loci coding for superoxide dismutase enzymes that may mediate the parasite's interaction with its host. Based on 474 sequences, sampled across 5000 km of the eastern United States coastline, no more than two alleles were observed at each locus (discounting singletons). Depending on the locus, the common allele ranged in overall frequency from 72% to 92%. At each locus the two alleles differed substantially (3.8% sequence difference, on average), and the among-locus variance in divergences was not sufficient to reject a simultaneous origin for all dimorphisms using approximate Bayesian methods. Dimorphic alleles were estimated to have diverged from a common ancestral allele at least 0.9 million years ago. Across these seven loci, only five other alleles were ever observed, always as singletons and differing from the dimorphic alleles by no more than two nucleotides. Free recombination could potentially have shuffled these dimorphisms into as many as 243 multilocus combinations, but the existence of only ten combinations among all samples strongly supports low recombination frequencies and is consistent with the observed absence of intragenic recombination. We consider several demographic and evolutionary hypotheses to explain these patterns. Few can be conclusively rejected with the present data, but we advance a recent hybridization of ancient divergent lineages scenario as the most parsimonious.

Porcine colonization of the Americas: a 60k SNP story

The pig, Sus scrofa, is a foreign species to the American continent. Although pigs originally introduced in the Americas should be related to those from the Iberian Peninsula and Canary islands, the phylogeny of current creole pigs that now populate the continent is likely to be very complex. Because of the extreme climates that America harbors, these populations also provide a unique example of a fast evolutionary phenomenon of adaptation. Here, we provide a genome wide study of these issues by genotyping, with a 60k SNP chip, 206 village pigs sampled across 14 countries and 183 pigs from outgroup breeds that are potential founders of the American populations, including wild boar, Iberian, international and Chinese breeds. Results show that American village pigs are primarily of European ancestry, although the observed genetic landscape is that of a complex conglomerate. There was no correlation between genetic and geographical distances, neither continent wide nor when analyzing specific areas. Most populations showed a clear admixed structure where the Iberian pig was not necessarily the main component, illustrating how international breeds, but also Chinese pigs, have contributed to extant genetic composition of American village pigs. We also observe that many genes related to the cardiovascular system show an increased differentiation between altiplano and genetically related pigs living near sea level.

An overview of population genetic data simulation

Simulation studies in population genetics play an important role in helping to better understand the impact of various evolutionary and demographic scenarios on sequence variation and sequence patterns, and they also permit investigators to better assess and design analytical methods in the study of disease-associated genetic factors. To facilitate these studies, it is imperative to develop simulators with the capability to accurately generate complex genomic data under various genetic models. Currently, a number of efficient simulation software packages for large-scale genomic data are available, and new simulation programs with more sophisticated capabilities and features continue to emerge. In this article, we review the three basic simulation frameworks--coalescent, forward, and resampling--and some of the existing simulators that fall under these frameworks, comparing them with respect to their evolutionary and demographic scenarios, their computational complexity, and their specific applications. Additionally, we address some limitations in current simulation algorithms and discuss future challenges in the development of more powerful simulation tools.

Evolutionary study of a potential selection target region in the pig

Domestication, modern breeding and artificial selection have shaped dramatically the genomic variability of domestic animals. In livestock, the so-called FAT1 quantitative trait locus (QTL) in porcine chromosome 4 was the first QTL uncovered although, to date, its precise molecular nature has remained elusive. Here, we characterize the nucleotide variability of 13 fragments of ∼500 bp equally spaced in a 2 Mb region in the vicinity of the FAT1 region in a wide-diversity panel of 32 pigs. Asian and European animals, including local Mediterranean and international pig breeds, were sequenced. Patterns of genetic variability were very complex and varied largely across loci and populations; they did not reveal overall a clear signal of a selective sweep in any breed, although FABP4 fragment showed a significantly higher diversity. We used an approximate Bayesian computation approach to infer the evolutionary history of this SSC4 region. Notably, we found that European pig populations have a much lower effective size than their Asian counterparts: in the order of hundreds vs hundreds of thousands. We show also an important part of extant European variability is actually due to introgression of Asian germplasm into Europe. This study shows how a potential loss in diversity caused by bottlenecks and possible selective sweeps associated with domestication and artificial selection can be counterbalanced by migration, making it much more difficult the identification of selection footprints based on naive demographic assumptions. Given the small fragment analyzed here, it remains to be studied how these conclusions apply to the rest of the genome.