The Population Genetic Signature of Polygenic Local Adaptation

Adaptation in response to selection on polygenic phenotypes may occur via subtle allele frequencies shifts at many loci. Current population genomic techniques are not well posed to identify such signals. In the past decade, detailed knowledge about the specific loci underlying polygenic traits has begun to emerge from genome-wide association studies (GWAS). Here we combine this knowledge from GWAS with robust population genetic modeling to identify traits that may have been influenced by local adaptation. We exploit the fact that GWAS provide an estimate of the additive effect size of many loci to estimate the mean additive genetic value for a given phenotype across many populations as simple weighted sums of allele frequencies. We first describe a general model of neutral genetic value drift for an arbitrary number of populations with an arbitrary relatedness structure. Based on this model we develop methods for detecting unusually strong correlations between genetic values and specific environmental variables, as well as a generalization of $Q_{ST}/F_{ST}$ comparisons to test for over-dispersion of genetic values among populations. Finally we lay out a framework to identify the individual populations or groups of populations that contribute to the signal of overdispersion. These tests have considerably greater power than their single locus equivalents due to the fact that they look for positive covariance between like effect alleles, and also significantly outperform methods that do not account for population structure. We apply our tests to the Human Genome Diversity Panel (HGDP) dataset using GWAS data for height, skin pigmentation, type 2 diabetes, body mass index, and two inflammatory bowel disease datasets. This analysis uncovers a number of putative signals of local adaptation, and we discuss the biological interpretation and caveats of these results.Comment: 42 pages including 8 figures and 3 tables; supplementary figures and tables not included on this upload, but are mostly unchanged from v

Comparison of Bayesian Clustering and Edge Detection Methods for Inferring Boundaries in Landscape Genetics

Recently, techniques available for identifying clusters of individuals or boundaries between clusters using genetic data from natural populations have expanded rapidly. Consequently, there is a need to evaluate these different techniques. We used spatially-explicit simulation models to compare three spatial Bayesian clustering programs and two edge detection methods. Spatially-structured populations were simulated where a continuous population was subdivided by barriers. We evaluated the ability of each method to correctly identify boundary locations while varying: (i) time after divergence, (ii) strength of isolation by distance, (iii) level of genetic diversity, and (iv) amount of gene flow across barriers. To further evaluate the methods’ effectiveness to detect genetic clusters in natural populations, we used previously published data on North American pumas and a European shrub. Our results show that with simulated and empirical data, the Bayesian spatial clustering algorithms outperformed direct edge detection methods. All methods incorrectly detected boundaries in the presence of strong patterns of isolation by distance. Based on this finding, we support the application of Bayesian spatial clustering algorithms for boundary detection in empirical datasets, with necessary tests for the influence of isolation by distance

Conservation genetic assessment of savannah elephants (Loxodonta africana) in the Greater Kruger Biosphere, South Africa

Savannah elephant populations have been severely reduced and fragmented throughout its remaining range. In general, however, there is limited information regarding their genetic status, which is essential knowledge for conservation. We investigated patterns of genetic variation in savannah elephants from the Greater Kruger Biosphere, with a focus on those in previously unstudied nature reserves adjacent to Kruger National Park, using dung samples from 294 individuals and 18 microsatellites. The results of genetic structure analyses using several different methods of ordination and Bayesian clustering strongly suggest that elephants throughout the Greater Kruger National Park (GKNP) constitute a single population. No evidence of a recent genetic bottleneck was detected using three moment-based approaches and two coalescent likelihood methods. The apparent absence of a recent genetic bottleneck associated with the known early 1900s demographic bottleneck may result from a combination of rapid post-bottleneck population growth, immigration and long generation time. Point estimates of contemporary effective population size (Ne) for the GKNP were ~ 500–700, that is, at the low end of the range of Ne values that have been proposed for maintaining evolutionary potential and the current ratio of Ne to census population size (Nc) may be quite low (<0.1). This study illustrates the difficulties in assessing the impacts on Ne in populations that have suffered demographic crashes but have recovered rapidly and received gene flow, particularly in species with long generation times in which genetic time lags are longer. This work provides a starting point and baseline information for genetic monitoring of the GKNP elephants

Assessing genetic structure in common but ecologically distinct carnivores: the stone marten and red fox

The identification of populations and spatial genetic patterns is important for ecological and conservation research, and spatially explicit individual-based methods have been recognised as powerful tools in this context. Mammalian carnivores are intrinsically vulnerable to habitat fragmentation but not much is known about the genetic consequences of fragmentation in common species. Stone martens (Martes foina) and red foxes (Vulpes vulpes) share a widespread Palearctic distribution and are considered habitat generalists, but in the Iberian Peninsula stone martens tend to occur in higher quality habitats. We compared their genetic structure in Portugal to see if they are consistent with their differences in ecological plasticity, and also to illustrate an approach to explicitly delineate the spatial boundaries of consistently identified genetic units. We analysed microsatellite data using spatial Bayesian clustering methods (implemented in the software BAPS, GENELAND and TESS), a progressive partitioning approach and a multivariate technique (Spatial Principal Components Analysis-sPCA). Three consensus Bayesian clusters were identified for the stone marten. No consensus was achieved for the red fox, but one cluster was the most probable clustering solution. Progressive partitioning and sPCA suggested additional clusters in the stone marten but they were not consistent among methods and were geographically incoherent. The contrasting results between the two species are consistent with the literature reporting stricter ecological requirements of the stone marten in the Iberian Peninsula. The observed genetic structure in the stone marten may have been influenced by landscape features, particularly rivers, and fragmentation. We suggest that an approach based on a consensus clustering solution of multiple different algorithms may provide an objective and effective means to delineate potential boundaries of inferred subpopulations. sPCA and progressive partitioning offer further verification of possible population structure and may be useful for revealing cryptic spatial genetic patterns worth further investigation

Conservation genetic assessment of savannah elephants (Loxodonta africana) in the Greater Kruger Biosphere, South Africa

Savannah elephant populations have been severely reduced and fragmented throughout its remaining range. In general, however, there is limited information regarding their genetic status, which is essential knowledge for conservation. We investigated patterns of genetic variation in savannah elephants from the Greater Kruger Biosphere, with a focus on those in previously unstudied nature reserves adjacent to Kruger National Park, using dung samples from 294 individuals and 18 microsatellites. The results of genetic structure analyses using several different methods of ordination and Bayesian clustering strongly suggest that elephants throughout the Greater Kruger National Park (GKNP) constitute a single population. No evidence of a recent genetic bottleneck was detected using three moment-based approaches and two coalescent likelihood methods. The apparent absence of a recent genetic bottleneck associated with the known early 1900s demographic bottleneck may result from a combination of rapid post-bottleneck population growth, immigration and long generation time. Point estimates of contemporary effective population size (Ne) for the GKNP were ~ 500–700, that is, at the low end of the range of Ne values that have been proposed for maintaining evolutionary potential and the current ratio of Ne to census population size (Nc) may be quite low (<0.1). This study illustrates the difficulties in assessing the impacts on Ne in populations that have suffered demographic crashes but have recovered rapidly and received gene flow, particularly in species with long generation times in which genetic time lags are longer. This work provides a starting point and baseline information for genetic monitoring of the GKNP elephants

Using genome scans of DNA polymorphism to infer adaptive population divergence

Elucidating the genetic basis of adaptive population divergence is a goal of central importance in evolutionary biology. In principle, it should be possible to identify chromosomal regions involved in adaptive divergence by screening genome-wide patterns of DNA polymorphism to detect the locus-specific signature of positive directional selection. In the case of spatially separated populations that inhabit different environments or sympatric populations that exploit different ecological niches, it is possible to identify loci that underlie divergently selected traits by comparing relative levels of differentiation among large numbers of unlinked markers. In this review I first address the question of whether diversifying selection on polygenic traits can be expected to produce predictable patterns of allelic variation at the underlying quantitative trait loci (QTL), and whether the locus-specific effects of selection can be reliably detected against the genome-wide backdrop of stochastic variability. I then review different approaches that have been developed to identify loci involved in adaptive population divergence and I discuss the relative merits of model-based approaches that rely on assumptions about population structure vs. model-free approaches that are based on empirical distributions of summary statistics. Finally, I consider the evolutionary and functional insights that might be gained by conducting genome scans for loci involved in adaptive population divergence

Pronounced Fixation, Strong Population Differentiation and Complex Population History in the Canary Islands Blue Tit Subspecies Complex

Evolutionary molecular studies of island radiations may lead to insights in the role of vicariance, founder events, population size and drift in the processes of population differentiation. We evaluate the degree of population genetic differentiation and fixation of the Canary Islands blue tit subspecies complex using microsatellite markers and aim to get insights in the population history using coalescence based methods. The Canary Island populations were strongly genetically differentiated and had reduced diversity with pronounced fixation including many private alleles. In population structure models, the relationship between the central island populations (La Gomera, Tenerife and Gran Canaria) and El Hierro was difficult to disentangle whereas the two European populations showed consistent clustering, the two eastern islands (Fuerteventura and Lanzarote) and Morocco weak clustering, and La Palma a consistent unique lineage. Coalescence based models suggested that the European mainland forms an outgroup to the Afrocanarian population, a split between the western island group (La Palma and El Hierro) and the central island group, and recent splits between the three central islands, and between the two eastern islands and Morocco, respectively. It is clear that strong genetic drift and low level of concurrent gene flow among populations have shaped complex allelic patterns of fixation and skewed frequencies over the archipelago. However, understanding the population history remains challenging; in particular, the pattern of extreme divergence with low genetic diversity and yet unique genetic material in the Canary Island system requires an explanation. A potential scenario is population contractions of a historically large and genetically variable Afrocanarian population, with vicariance and drift following in the wake. The suggestion from sequence-based analyses of a Pleistocene extinction of a substantial part of North Africa and a Pleistocene/Holocene eastward re-colonisation of western North Africa from the Canaries remains possible

Empirical approaches to detecting the action of natural selection in Drosophila

This dissertation examines two aspects of how natural selection shapes the amount and pattern of genetic variation within and between species: (1) the role of positively selected alleles in shaping the variation within and between subpopulations of a subdivided species and (2) the influence of epistatic selection operating on RNA secondary structures. First, the role of natural selection in shaping the pattern of variation within and between populations of the subdivided species Drosophila ananassae is investigated. To delimit the spread of positively selected alleles and characterize the role of natural selection in genetic differentiation, sequence data was collected from a locus in a region of low recombination for 13 populations, spanning a majority of the species range of D. ananassae. The migration behavior of this selected locus is compared to that of 10 independent neutrally evolving loci and tested against alternative models of natural selection. Second, nucleotide variation at the D. melanogaster bicoid locus is examined. The presence of a large, conserved secondary structure in the 3’ untranslated region enables the relationship between RNA secondary structure and patterns of standing variation in natural populations to be explored. Variation within this structure is analyzed with respect to models of compensatory evolution and recent improvements of these models. Evidence suggests that bicoid may be the result of a relatively recent gene duplication in the Dipteran lineage, thus, variation in the bicoid coding region is also analyzed with respect to the evolutionary processes that may be ongoing if this gene is still undergoing diversification and/or refining of its function. Finally, long-range compensatory interactions between the two ends of Drosophila alcohol dehydrogenase (Adh) mRNA are investigated by experimental manipulation. Site-directed mutations were introduced in the D. melanogaster Adh gene in an effort to explain why previous mutational analysis failed to fit Kimura’s classical model of compensatory evolution. The results of the mutational analysis indicate that a classical result was not observed due to the pleiotropic effect of changing a nucleotide involved in both long-range base pairing and the negative regulation of gene expression

A Unifying Model for the Analysis of Phenotypic, Genetic, and Geographic Data

Recognition of evolutionary units (species, populations) requires integrating several kinds of data, such as genetic or phenotypic markers or spatial information in order to get a comprehensive view concerning the differentiation of the units. We propose a statistical model with a double original advantage: (i) it incorporates information about the spatial distribution of the samples, with the aim to increase inference power and to relate more explicitly observed patterns to geography and (ii) it allows one to analyze genetic and phenotypic data within a unified model and inference framework, thus opening the way to robust comparisons between markers and possibly combined analyses. We show from simulated data as well as real data that our method estimates parameters accurately and is an improvement over alternative approaches in many situations. The power of this method is exemplified using an intricate case of inter- and intraspecies differentiation based on an original data set of georeferenced genetic and morphometric markers obtained on Myodes voles from Sweden. A computer program is made available as an extension of the R package Genelan

Guidelines for genetic data analysis

The IWC Scientific Committee recently adopted guidelines for quality control of DNA data. Once data have been collected, the next step is to analyse the data and make inferences that are useful for addressing practical problems in conservation and management of cetaceans. This is a complex exercise, as numerous analyses are possible and users have a wide range of choices of software programs for implementing the analyses. This paper reviews the underlying issues, illustrates application of different types of genetic data analysis to two complex management problems (involving common minke whales and humpback whales), and concludes with a number of recommendations for best practices in the analysis of population genetic data. An extensive Appendix provides a detailed review and critique of most types of analyses that are used with population genetic data for cetaceans.Publisher PDFPeer reviewe