Genomic and genealogical investigation of the French Canadian founder population structure

Characterizing the genetic structure of worldwide populations is important for understanding human history and is essential to the design and analysis of genetic epidemiological studies. In this study, we examined genetic structure and distant relatedness and their effect on the extent of linkage disequilibrium (LD) and homozygosity in the founder population of Quebec (Canada). In the French Canadian founder population, such analysis can be performed using both genomic and genealogical data. We investigated genetic differences, extent of LD, and homozygosity in 140 individuals from seven sub-populations of Quebec characterized by different demographic histories reflecting complex founder events. Genetic findings from genome-wide single nucleotide polymorphism data were correlated with genealogical information on each of these sub-populations. Our genomic data showed significant population structure and relatedness present in the contemporary Quebec population, also reflected in LD and homozygosity levels. Our extended genealogical data corroborated these findings and indicated that this structure is consistent with the settlement patterns involving several founder events. This provides an independent and complementary validation of genomic-based studies of population structure. Combined genomic and genealogical data in the Quebec founder population provide insights into the effects of the interplay of two important sources of bias in genetic epidemiological studies, unrecognized genetic structure and cryptic relatedness.     

Recombination and clonality in natural populations of Escherichia coli

Bacteria such as Escherichia coli have been commonly viewed as being primarily clonal organisms. As such, the genetic variation within clones was thought to be almost exclusively the result of the mutational process. This conclusion has recently been challenged by data from DNA sequencing studies of natural isolates that are incompatible with a primarily clonal structure. Molecular population genetic analyses of these data, including gene genealogical comparisons, have raised the possibility of a much more complex population structure that may encompass relatively frequent recombination, recurrent selective sweeps and extensive ecological population subdivision.     

The utility of indels in population genetics: the Tpi intron for host race genealogy of Acrocercops transecta (Insecta: Lepidoptera)

We investigated the utility of indel data for genealogical and population genetic analyses using the Tpi intron of the leaf mining moth Acrocercops transecta (Insecta: Lepidoptera). Genealogical analyses revealed that indel data were less homoplasious than DNA sequence data and that indel data contained a sufficient signal to provide a high resolution tree that was highly congruent with the tree estimated from DNA sequences. Although some conflicts were identified in the distributions of multi-residue indels, such conflicts were especially useful for the unambiguous detection of recombinations. For the first time, we adopted a Bayesian clustering method for indel characters to infer genetic structure of the moth. We concluded that indel characters have the potential to be a powerful tool in the analysis of population genetics and population structure as well as in the detection of gene flow.     

Nuclear DNA analyses in genetic studies of populations: practice,problems and prospects

Population-genetic studies have been remarkably productive and successful in the last decade following the invention of PCR technology and the introduction of mitochondrial and microsatellite DNA markers. While mitochondrial DNA has proven powerful for genealogical and evolutionary studies of animal populations, and microsatellite sequences are the most revealing DNA markers available so far for inferring population structure and dynamics, they both have important and unavoidable limitations. To obtain a fuller picture of the history and evolutionary potential of populations, genealogical data from nuclear loci are essential, and the inclusion of other nuclear markers, i.e. single copy nuclear polymorphic (scnp) sequences, is clearly needed. Four major uncertainties for nuclear DNA analyses of populations have been facing us, i.e. the availability of scnp markers for carrying out such analysis, technical laboratory hurdles for resolving haplotypes, difficulty in data analysis because of recombination, low divergence levels and intraspecific multifurcation evolution, and the utility of scnp markers for addressing population-genetic questions. In this review, we discuss the availability of highly polymorphic single copy DNA in the nuclear genome, describe patterns and rate of evolution of nuclear sequences, summarize past empirical and theoretical efforts to recover and analyse data from scnp markers, and examine the difficulties, challenges and opportunities faced in such studies. We show that although challenges still exist, the above-mentioned obstacles are now being removed. Recent advances in technology and increases in statistical power provide the prospect of nuclear DNA analyses becoming routine practice, allowing allele-discriminating characterization of scnp loci and microsatellite loci. This certainly will increase our ability to address more complex questions, and thereby the sophistication of genetic analyses of populations.     

Model-free Estimation of Recent Genetic Relatedness

Genealogical inference from genetic data is essential for a variety of applications in human genetics. In genome-wide and sequencing association studies, for example, accurate inference on both recent genetic relatedness, such as family structure, and more distant genetic relatedness, such as population structure, is necessary for protection against spurious associations. Distinguishing familial relatedness from population structure with genotype data, however, is difficult because both manifest as genetic similarity through the sharing of alleles. Existing approaches for inference on recent genetic relatedness have limitations in the presence of population structure, where they either (1) make strong and simplifying assumptions about population structure, which are often untenable, or (2) require correct specification of and appropriate reference population panels for the ancestries in the sample, which might be unknown or not well defined. Here, we propose PC-Relate, a model-free approach for estimating commonly used measures of recent genetic relatedness, such as kinship coefficients and IBD sharing probabilities, in the presence of unspecified structure. PC-Relate uses principal components calculated from genome-screen data to partition genetic correlations among sampled individuals due to the sharing of recent ancestors and more distant common ancestry into two separate components, without requiring specification of the ancestral populations or reference population panels. In simulation studies with population structure, including admixture, we demonstrate that PC-Relate provides accurate estimates of genetic relatedness and improved relationship classification over widely used approaches. We further demonstrate the utility of PC-Relate in applications to three ancestrally diverse samples that vary in both size and genealogical complexity.     

New methods for inference of local tree topologies with recombinant SNP sequences in populations

Large amount of population-scale genetic variation data are being collected in populations. One potentially important biological problem is to infer the population genealogical history from these genetic variation data. Partly due to recombination, genealogical history of a set of DNA sequences in a population usually cannot be represented by a single tree. Instead, genealogy is better represented by a genealogical network, which is a compact representation of a set of correlated local genealogical trees, each for a short region of genome and possibly with different topology. Inference of genealogical history for a set of DNA sequences under recombination has many potential applications, including association mapping of complex diseases. In this paper, we present two new methods for reconstructing local tree topologies with the presence of recombination, which extend and improve the previous work in. We first show that the "tree scan" method can be converted to a probabilistic inference method based on a hidden Markov model. We then focus on developing a novel local tree inference method called RENT that is both accurate and scalable to larger data. Through simulation, we demonstrate the usefulness of our methods by showing that the hidden-Markov-model-based method is comparable with the original method in terms of accuracy. We also show that RENT is competitive with other methods in terms of inference accuracy, and its inference error rate is often lower and can handle large data.     

High Y-chromosomal diversity and low relatedness between paternal lineages on a communal scale in the Western European Low Countries during the surname establishment

There is limited knowledge on the biological relatedness between citizens and on the demographical dynamics within villages, towns and cities in pre-17th century Western Europe. By combining Y-chromosomal genotypes, in-depth genealogies and surname data in a strict genetic genealogical approach, it is possible to provide insights into the genetic diversity and the relatedness between indigenous paternal lineages within a particular community at the time of the surname adoption. To obtain these insights, six Flemish communities were selected in this study based on the differences in geography and historical development. After rigorous selection of appropriate DNA donors, low relatedness between Y chromosomes of different surnames was found within each community, although there is co-occurrence of these surnames in each community since the start of the surname adoption between the 14th and 15th century. Next, the high communal diversity in Y-chromosomal lineages was comparable with the regional diversity across Flanders at that time. Moreover, clinal distributions of particular Y-chromosomal lineages between the communities were observed according to the clinal distributions earlier observed across the Flemish regions and Western Europe. No significant indication for genetic differences between communities with distinct historical development was found in the analysis. These genetic results provide relevant information for studies in historical sciences, archaeology, forensic genetics and genealogy.     

The mapping of epistatic effects onto a genealogical tree in haploid populations

In this paper we present a model that maps epistatic effects onto a genealogical tree for a haploid population. Prior work has demonstrated that genealogical structure causes the genotypic values of individuals to covary. Our results indicate that epistasis can reduce genotypic covariance that is caused by genealogical structure. Genotypic effects (both additive and epistatic) occur along the branches of a genealogical tree, from the base of the tree to its tips. Epistasis reduces genotypic covariance because there is a reweighting of the contribution of branches to the states of genotypes compared to the additive case. Branches near the tips of a genealogical tree contribute proportionally more genetic effects with epistasis than without epistasis. Epistatic effects are most numerous at basal positions in a genealogical tree when a population is constant in size and experiencing no selection, optimizing selection, diversifying selection or directional selection, indicating that epistatic effects are typically old. For a population that is growing in size, epistatic effects are most numerous at midpoints in a genealogical tree, indicating epistatic effects are of moderate age. Our results are important in that they suggest epistatic effects may typically explain deep (old) divergences and broad patterns of divergence that exist in populations, except in growing populations. In a growing population, epistatic effects may cause more within group divergence higher up in a tree and less between group divergence that is deep in a tree. The distribution of the number of epistatic effects and the expected variance and covariance in the number of epistatic effects is also provided assuming neutrality.     

Mitochondrial DNA phylogeography of Caiman crocodilus in Mesoamerica and South America

The Neotropical crocodylian species, Caiman crocodilus, is widely distributed through Mesoamerica, northern South America, and the Amazon basin. Four subspecies are recognized within C. crocodilus, suggesting some geographic variation in morphology. In this study, we utilized mitochondrial DNA (mtDNA) sequence data from 45 individuals of C. crocodilus throughout its range to infer its evolutionary history and population structure, as well as to evaluate genealogical support for subspecies and their geographic distributions. Our molecular phylogenetic results identified five mtDNA haplotype clades with a mean sequence divergence of 3.4%, indicating considerable evolutionary independence among phylogeographic lineages. Our results were also broadly consistent with current subspecific taxonomy, with some important additional findings. First, we found substantial genetic structuring within C. c. fuscus from southern Mesoamerica. Second, though we confirmed the existence of a widespread Amazonian clade, we also discovered a cryptic and divergent mtDNA lineage that was indistinguishable from C. c. crocodilus based on external morphology. Third, we confirm the status of C. c. chiapasius as a distinct evolutionary lineage, and provide evidence that C. c. fuscus may be moving northward and hybridizing with C. c. chiapasius in northern Mesoamerica. Finally, our results parallel previous phylogeographic studies of other organisms that have demonstrated significant genetic structure over shorter geographic distances in Mesoamerica compared with Amazonia. We support conservation efforts for all five independent lineages within C. crocodilus, and highlight the subspecies C. c. chiapasius as a unit of particular conservation concern.     

Canadian polar bear population structure using genome‐wide markers

Predicting the consequences of environmental changes, including human‐mediated climate change on species, requires that we quantify range‐wide patterns of genetic diversity and identify the ecological, environmental, and historical factors that have contributed to it. Here, we generate baseline data on polar bear population structure across most Canadian subpopulations (n = 358) using 13,488 genome‐wide single nucleotide polymorphisms (SNPs) identified with double‐digest restriction site‐associated DNA sequencing (ddRAD). Our ddRAD dataset showed three genetic clusters in the sampled Canadian range, congruent with previous studies based on microsatellites across the same regions; however, due to a lack of sampling in Norwegian Bay, we were unable to confirm the existence of a unique cluster in that subpopulation. These data on the genetic structure of polar bears using SNPs provide a detailed baseline against which future shifts in population structure can be assessed, and opportunities to develop new noninvasive tools for monitoring polar bears across their range.     

Sampling related individuals within ponds biases estimates of population structure in a pond‐breeding amphibian

Effective conservation and management of pond‐breeding amphibians depends on the accurate estimation of population structure, demographic parameters, and the influence of landscape features on breeding‐site connectivity. Population‐level studies of pond‐breeding amphibians typically sample larval life stages because they are easily captured and can be sampled nondestructively. These studies often identify high levels of relatedness between individuals from the same pond, which can be exacerbated by sampling the larval stage. Yet, the effect of these related individuals on population genetic studies using genomic data is not yet fully understood. Here, we assess the effect of within‐pond relatedness on population and landscape genetic analyses by focusing on the barred tiger salamanders (Ambystoma mavortium) from the Nebraska Sandhills. Utilizing genome‐wide SNPs generated using a double‐digest RADseq approach, we conducted standard population and landscape genetic analyses using datasets with and without siblings. We found that reduced sample sizes influenced parameter estimates more than the inclusion of siblings, but that within‐pond relatedness led to the inference of spurious population structure when analyses depended on allele frequencies. Our landscape genetic analyses also supported different models across datasets depending on the spatial resolution analyzed. We recommend that future studies not only test for relatedness among larval samples but also remove siblings before conducting population or landscape genetic analyses. We also recommend alternative sampling strategies to reduce sampling siblings before sequencing takes place. Biases introduced by unknowingly including siblings can have significant implications for population and landscape genetic analyses, and in turn, for species conservation strategies and outcomes.     

Conservation genetics: beyond the maintenance of marker diversity

One of the major problems faced by conservation biologists is the allocation of scarce resources to an overwhelmingly large number of species in need of preservation efforts. Both demographic and genetic information have been brought to bear on this problem; however, the role of information obtained from genetic markers has largely been limited to the characterization of gene frequencies and patterns of diversity. While the genetic consequences of rarity may be a contributing factor to endangerment, it is widely recognized that demographic factors often may be more important. Because patterns of genetic marker variation are influenced by the same demographic factors of interest to the conservation biologist, it is possible to extract useful demographic information from genetic marker data. Such an approach may be productive for determining plant mating systems, inbreeding depression, effective population size, and metapopulation structure. In many cases, however, data consisting only of marker frequencies are inadequate for these purposes. Development of genealogical based analytical methods coupled with studies of DNA sequence variation within and among populations is likely to yield the most information on demographic processes from genetic marker data. Indeed, in some cases it may be the only means of obtaining information on the long-term demographic properties that may be most useful for determining the future prospects of a species of interest.     

Congruent population structure across paralogous and nonparalogous loci in Salish Sea chum salmon (Oncorhynchus keta)

Whole‐genome duplications are major evolutionary events with a lasting impact on genome structure. Duplication events complicate genetic analyses as paralogous sequences are difficult to distinguish; consequently, paralogs are often excluded from studies. The effects of an ancient whole‐genome duplication (approximately 88 MYA) are still evident in salmonids through the persistence of numerous paralogous gene sequences and partial tetrasomic inheritance. We use restriction site‐associated DNA sequencing on 10 collections of chum salmon from the Salish Sea in the USA and Canada to investigate genetic diversity and population structure in both tetrasomic and rediploidized regions of the genome. We use a pedigree and high‐density linkage map to identify paralogous loci and to investigate genetic variation across the genome. By applying multivariate statistical methods, we show that it is possible to characterize paralogous loci and that they display similar patterns of population structure as the diploidized portion of the genome. We find genetic associations with the adaptively important trait of run‐timing in both sets of loci. By including paralogous loci in genome scans, we can observe evolutionary signals in genomic regions that have routinely been excluded from population genetic studies in other polyploid‐derived species.     

Population structure,landscape genomics,and genetic signatures of adaptation to exotic disease pressure in Cornus florida L.—Insights from GWAS and GBS data

Understanding the consequences of exotic diseases on native forests is important to evolutionary ecology and conservation biology because exotic pathogens have drastically altered US eastern deciduous forests. Cornus florida L. (flowering dogwood tree) is one such species facing heavy mortality. Characterizing the genetic structure of C. florida populations and identifying the genetic signature of adaptation to dogwood anthracnose (an exotic pathogen responsible for high mortality) remain vital for conservation efforts. By integrating genetic data from genotype by sequencing (GBS) of 289 trees across the host species range and distribution of disease, we evaluated the spatial patterns of genetic variation and population genetic structure of C. florida and compared the pattern to the distribution of dogwood anthracnose. Using genome‐wide association study and gradient forest analysis, we identified genetic loci under selection and associated with ecological and diseased regions. The results revealed signals of weak genetic differentiation of three or more subgroups nested within two clusters—explaining up to 2%–6% of genetic variation. The groups largely corresponded to the regions within and outside the eastern Hot‐Continental ecoregion, which also overlapped with areas within and outside the main distribution of dogwood anthracnose. The fungal sequences contained in the GBS data of sampled trees bolstered visual records of disease at sampled locations and were congruent with the reported range of Discula destructiva, suggesting that fungal sequences within‐host genomic data were informative for detecting or predicting disease. The genetic diversity between populations at diseased vs. disease‐free sites across the range of C. florida showed no significant difference. We identified 72 single‐nucleotide polymorphisms (SNPs) from 68 loci putatively under selection, some of which exhibited abrupt turnover in allele frequencies along the borders of the Hot‐Continental ecoregion and the range of dogwood anthracnose. One such candidate SNP was independently identified in two prior studies as a possible L‐type lectin‐domain containing receptor kinase. Although diseased and disease‐free areas do not significantly differ in genetic diversity, overall there are slight trends to indicate marginally smaller amounts of genetic diversity in disease‐affected areas. Our results were congruent with previous studies that were based on a limited number of genetic markers in revealing high genetic variation and weak population structure in C. florida.     

Local genetic structure in the critically endangered,cave‐associated perennial herb Primulina tabacum (Gesneriaceae)

The local spatial genetic structures of cave‐associated plants are seldom studied. Given that these plants are mainly confined to small areas in and around the entrances of caves, we hypothesized that they might lack genetic structures at local scales. To test this hypothesis, we sampled two large populations (named D and T) of a critically endangered perennial herb, Primulina tabacum, which is endemic to karst caves in southern China. We analysed nine microsatellite loci and sequenced four chloroplast DNA (cpDNA) intergenic spacer regions to study the genetic diversity and structure within and between both populations. Both populations have distinct genetic characteristics. Samples from two subpopulations in population D showed considerable genetic divergence. This is not consistent with the hypothesis that P. tabacum has a weak genetic structure at a local scale. However, 94% of the individuals in population T shared the same multilocus genotype, which indicates little genetic structure within this population. The contributions of seed flow, pollen flow and (sub)population history to the genetic diversity and structure in each and both populations are discussed. Our study is the first to investigate local genetic diversity and structure in a cave‐associated plant, and provides valuable information for the sustainable conservation of such species. © 2013 The Linnean Society of London, Biological Journal of the Linnean Society, 2013, 109 , 747–756.     

Molecular phylogenetics at the population/species interface in cave spiders of the southern Appalachians (Araneae:Nesticidae:Nesticus)

This paper focuses on the relationship between population genetic structure and speciation mechanisms in a monophyletic species group of Appalachian cave spiders (Nesticus). Using mtDNA sequence data gathered from 256 individuals, I analyzed patterns of genetic variation within and between populations for three pairs of closely related sister species. Each sister-pair comparison involves taxa with differing distributional and ecological attributes; if these ecological attributes are reflected in basic demographic differences, then speciation might proceed differently across these sister taxa comparisons. Both frequency-based and gene tree analyses reveal that the genetic structure of the Nesticus species studied is characterized by similar and essentially complete population subdivision, regardless of differences in general ecology. These findings contrast with results of prior genetic studies of cave-dwelling arthropods that have typically revealed variation in population structure corresponding to differences in general ecology. Species fragmentation through both extrinsic and intrinsic evolutionary forces has resulted in discrete, perhaps independent, populations within morphologically defined species. Large sequence divergence values observed between populations suggest that this independence may extend well into the past. These patterns of mtDNA genealogical structure and divergence imply that species as morphological lineages are currently more inclusive than basal evolutionary or phylogenetic units, a suggestion that has important implications for the study of speciation mechanisms.      

Detecting selection along environmental gradients: analysis of eight methods and their effectiveness for outbreeding and selfing populations

Thanks to genome‐scale diversity data, present‐day studies can provide a detailed view of how natural and cultivated species adapt to their environment and particularly to environmental gradients. However, due to their sensitivity, up‐to‐date studies might be more sensitive to undocumented demographic effects such as the pattern of migration and the reproduction regime. In this study, we provide guidelines for the use of popular or recently developed statistical methods to detect footprints of selection. We simulated 100 populations along a selective gradient and explored different migration models, sampling schemes and rates of self‐fertilization. We investigated the power and robustness of eight methods to detect loci potentially under selection: three designed to detect genotype–environment correlations and five designed to detect adaptive differentiation (based on F_ST or similar measures). We show that genotype–environment correlation methods have substantially more power to detect selection than differentiation‐based methods but that they generally suffer from high rates of false positives. This effect is exacerbated whenever allele frequencies are correlated, either between populations or within populations. Our results suggest that, when the underlying genetic structure of the data is unknown, a number of robust methods are preferable. Moreover, in the simulated scenario we used, sampling many populations led to better results than sampling many individuals per population. Finally, care should be taken when using methods to identify genotype–environment correlations without correcting for allele frequency autocorrelation because of the risk of spurious signals due to allele frequency correlations between populations.     

The genetic population structure of northern Sweden and its implications for mapping genetic diseases

The northern Swedish population has a history of admixture of three ethnic groups and a dramatic population growth from a relatively small founder population. This has resulted in founder effects that together with unique resources for genealogical analyses provide excellent conditions for genetic mapping of monogenic diseases. Several recent examples of successful mapping of genetic factors underlying susceptibility to complex diseases have suggested that the population of northern Sweden may also be an important tool for efficient mapping of more complex phenotypes. A potential factor contributing to these effects may be population sub-isolates within the large river valleys, constituting a central geographic characteristic of this region. We here provide evidence that marriage patterns as well as the distribution of gene frequencies in a set of marker loci are compatible with this notion. The possible implications of this population structure on linkage- and association based strategies for identifying genes contributing risk to complex diseases are discussed.     

Local adaptation along smooth ecological gradients causes phylogeographic breaks and phenotypic clustering

Coalescent theory has provided a basis for evolutionary biologists to build sophisticated methods for inferring population history from variation in genetic markers, but these methods leave out a major conceptual cornerstone of modern evolutionary theory: natural selection. I provide the first quantitative analysis of the effects of selection on genealogical patterns in a continuously distributed population in which the selective optimum for a trait linked to the marker varies gradually and continuously across the landscape. Simulations show that relatively weak selection for local adaptation can lead to strong phylogeographic structure, in which highly divergent genealogical groups (i.e., clades) are geographically localized and differentially adapted, and dramatically increased standing variation (e.g., coalescence time) compared to neutral expectations. This pattern becomes more likely with increasing population size and with decreasing dispersal distances, mutation rates, and mutation sizes. Under some conditions, the system alternates between a nearly neutral behavior and a behavior in which highly divergent clades are locally adapted. Natural selection on markers commonly used in phylogeographic studies (such as mitochondrial DNA) presents a major challenge to the inference of biogeographic history but also provides exciting opportunities to study how selection affects both between- and within-species biodiversity.