Sean D. Schoville

Testing for Associations between Loci and Environmental Gradients Using Latent Factor Mixed Models

Adaptation to local environments often occurs through natural selection acting on a large number of loci, each having a weak phenotypic effect. One way to detect these loci is to identify genetic polymorphisms that exhibit high correlation with environmental variables used as proxies for ecological pressures. Here, we propose new algorithms based on population genetics, ecological modeling, and statistical learning techniques to screen genomes for signatures of local adaptation. Implemented in the computer program “latent factor mixed model” (LFMM), these algorithms employ an approach in which population structure is introduced using unobserved variables. These fast and computationally efficient algorithms detect correlations between environmental and genetic variation while simultaneously inferring background levels of population structure. Comparing these new algorithms with related methods provides evidence that LFMM can efficiently estimate random effects due to population history and isolation-by-distance patterns when computing gene-environment correlations, and decrease the number of false-positive associations in genome scans. We then apply these models to plant and human genetic data, identifying several genes with functions related to development that exhibit strong correlations with climatic gradients.

Is Chytridiomycosis an Emerging Infectious Disease in Asia

The disease chytridiomycosis, caused by the fungus Batrachochytrium dendrobatidis (Bd), has caused dramatic amphibian population declines and extinctions in Australia, Central and North America, and Europe. Bd is associated with >200 species extinctions of amphibians, but not all species that become infected are susceptible to the disease. Specifically, Bd has rapidly emerged in some areas of the world, such as in Australia, USA, and throughout Central and South America, causing population and species collapse. The mechanism behind the rapid global emergence of the disease is poorly understood, in part due to an incomplete picture of the global distribution of Bd. At present, there is a considerable amount of geographic bias in survey effort for Bd, with Asia being the most neglected continent. To date, Bd surveys have been published for few Asian countries, and infected amphibians have been reported only from Indonesia, South Korea, China and Japan. Thus far, there have been no substantiated reports of enigmatic or suspected disease-caused population declines of the kind that has been attributed to Bd in other areas. In order to gain a more detailed picture of the distribution of Bd in Asia, we undertook a widespread, opportunistic survey of over 3,000 amphibians for Bd throughout Asia and adjoining Papua New Guinea. Survey sites spanned 15 countries, approximately 36° latitude, 111° longitude, and over 2000 m in elevation. Bd prevalence was very low throughout our survey area (2.35% overall) and infected animals were not clumped as would be expected in epizootic events. This suggests that Bd is either newly emerging in Asia, endemic at low prevalence, or that some other ecological factor is preventing Bd from fully invading Asian amphibians. The current observed pattern in Asia differs from that in many other parts of the world.

Controlling false discoveries in genome scans for selection.

Population differentiation (PD) and ecological association (EA) tests have recently emerged as prominent statistical methods to investigate signatures of local adaptation using population genomic data. Based on statistical models, these genomewide testing procedures have attracted considerable attention as tools to identify loci potentially targeted by natural selection. An important issue with PD and EA tests is that incorrect model specification can generate large numbers of false‐positive associations. Spurious association may indeed arise when shared demographic history, patterns of isolation by distance, cryptic relatedness or genetic background are ignored. Recent works on PD and EA tests have widely focused on improvements of test corrections for those confounding effects. Despite significant algorithmic improvements, there is still a number of open questions on how to check that false discoveries are under control and implement test corrections, or how to combine statistical tests from multiple genome scan methods. This tutorial study provides a detailed answer to these questions. It clarifies the relationships between traditional methods based on allele frequency differentiation and EA methods and provides a unified framework for their underlying statistical tests. We demonstrate how techniques developed in the area of genomewide association studies, such as inflation factors and linear mixed models, benefit genome scan methods and provide guidelines for good practice while conducting statistical tests in landscape and population genomic applications. Finally, we highlight how the combination of several well‐calibrated statistical tests can increase the power to reject neutrality, improving our ability to infer patterns of local adaptation in large population genomic data sets.

Uncovering the genetic basis of adaptive change: on the intersection of landscape genomics and theoretical population genetics

A workshop recently held at the École Polytechnique Fédérale de Lausanne (EPFL, Switzerland) was dedicated to understanding the genetic basis of adaptive change, taking stock of the different approaches developed in theoretical population genetics and landscape genomics and bringing together knowledge accumulated in both research fields. Indeed, an important challenge in theoretical population genetics is to incorporate effects of demographic history and population structure. But important design problems (e.g. focus on populations as units, focus on hard selective sweeps, no hypothesis‐based framework in the design of the statistical tests) reduce their capability of detecting adaptive genetic variation. In parallel, landscape genomics offers a solution to several of these problems and provides a number of advantages (e.g. fast computation, landscape heterogeneity integration). But the approach makes several implicit assumptions that should be carefully considered (e.g. selection has had enough time to create a functional relationship between the allele distribution and the environmental variable, or this functional relationship is assumed to be constant). To address the respective strengths and weaknesses mentioned above, the workshop brought together a panel of experts from both disciplines to present their work and discuss the relevance of combining these approaches, possibly resulting in a joint software solution in the future.

Evolutionary diversification of cryophilic Grylloblatta species (Grylloblattodea: Grylloblattidae) in alpine habitats of California

BackgroundClimate in alpine habitats has undergone extreme variation during Pliocene and Pleistocene epochs, resulting in repeated expansion and contraction of alpine glaciers. Many cold-adapted alpine species have responded to these climatic changes with long-distance range shifts. These species typically exhibit shallow genetic differentiation over a large geographical area. In contrast, poorly dispersing organisms often form species complexes within mountain ranges, such as the California endemic ice-crawlers (Grylloblattodea: Grylloblattidae: Grylloblatta). The diversification pattern of poorly dispersing species might provide more information on the localized effects of historical climate change, the importance of particular climatic events, as well as the history of dispersal. Here we use multi-locus genetic data to examine the phylogenetic relationships and geographic pattern of diversification in California Grylloblatta.ResultsOur analysis reveals a pattern of deep genetic subdivision among geographically isolated populations of Grylloblatta in California. Alpine populations diverged from low elevation populations and subsequently diversified. Using a Bayesian relaxed clock model and both uncalibrated and calibrated measurements of time to most recent common ancestor, we reconstruct the temporal diversification of alpine Grylloblatta populations. Based on calibrated relaxed clock estimates, evolutionary diversification of Grylloblatta occurred during the Pliocene-Pleistocene epochs, with an initial dispersal into California during the Pliocene and species diversification in alpine clades during the middle Pleistocene epoch.ConclusionsGrylloblatta species exhibit a high degree of genetic subdivision in California with well defined geographic structure. Distinct glacial refugia can be inferred within the Sierra Nevada, corresponding to major, glaciated drainage basins. Low elevation populations are sister to alpine populations, suggesting alpine populations may track expanding glacial ice sheets and diversify as a result of multiple glacial advances. Based on relaxed-clock molecular dating, the temporal diversification of Grylloblatta provides evidence for the role of a climate-driven species pump in alpine species during the Pleistocene epoch.

Detecting adaptive evolution based on association with ecological gradients : orientation matters

Population genetic signatures of local adaptation are frequently investigated by identifying loci with allele frequencies that exhibit high correlation with ecological variables. One difficulty with this approach is that ecological associations might be confounded by geographic variation at selectively neutral loci. Here, we consider populations that underwent spatial expansion from their original range, and for which geographical variation of adaptive allele frequency coincides with habitat gradients. Using range expansion simulations, we asked whether our ability to detect genomic regions involved in adaptation could be impacted by the orientation of the ecological gradients. For three ecological association methods tested, we found, counter-intuitively, fewer false-positive associations when ecological gradients aligned along the main axis of expansion than when they aligned along any other direction. This result has important consequences for the analysis of genomic data under non-equilibrium population genetic models. Alignment of gradients with expansion axes is likely to be common in scenarios in which expanding species track their ecological niche during climate change while adapting to changing environments at their rear edge.

Alpine biogeography of Parnassian butterflies during Quaternary climate cycles in North America

Growth of alpine glaciers during the Pleistocene had profound effects on montane landscapes in North America and the organisms now inhabiting alpine ecosystems. Biogeography of this region has often been viewed as a system of sky islands despite the fact that species richness patterns deviate from a strict island biogeographic model. One explanation is that alpine species are not in equilibrium because of late Quaternary geographic range shifts. Genetic data can provide evidence of nonequilibrium dynamics and the distributional shifts that occur during glaciation events in alpine landscapes. Using mitochondrial and nuclear sequence data, we examine the evolutionary history of butterflies in the Parnassius phoebus complex. We test explicit, alternative models of the biogeographic history of Parnassius smintheus and Parnassius behrii, including an equilibrium island model, ancestral radiation and fragmentation, an expanding alpine archipelago and an alpine archipelago refuge model. Our results support the alpine archipelago refuge model, in which alpine butterflies undergo population contraction during glacial climates followed by population expansion during interglacial phases. While butterflies can disperse between distant mountain ranges during glacial periods, gene flow is rare. We find evidence of recent connectivity between California and Colorado, population expansion events following deglaciation ∼20 000 years B.P., and small population sizes during the last glacial period. An analysis of lineage splitting suggests that morphological differences in P. smintheus and P. behrii are the result of late Pleistocene divergence (∼48 000 years B.P.) with limited gene flow. Our results demonstrate that spatially complex and nonequilibrium population dynamics influence alpine diversity patterns.

Pleistocene origin and population history of a neoendemic alpine butterfly

Alpine environments underwent dramatic transformation during glacial–interglacial cycles, with the consequence that geographical, ecological and demographic changes of alpine populations provided the opportunity for formation of neoendemic species. Several biogeographical models have been proposed to account for the unique history of alpine populations, with different expectations of genetic divergence and speciation. The expanding alpine archipelago model proposes that alpine populations expand spatially and demographically during glacial events, dispersing between mountain ranges. Under this model, alpine populations are unlikely to diverge in isolation due to substantial interpopulation gene flow. In contrast, the alpine archipelago refuge model proposes that gene flow during glacial phases is limited and populations expand demographically during interglacial phases, increasing genetic isolation and the likelihood of speciation. We assess these models by reconstructing the evolutionary history of Colias behrii, a morphologically and ecologically distinct alpine butterfly restricted to the California Sierra Nevada. C. behrii exhibits very low genetic diversity at mitochondrial and nuclear loci, limited population structure and evidence of population expansion. C. behrii and Rocky Mountain C. meadii share identical mitochondrial haplotypes, while in contrast, nuclear data indicate common ancestry between C. behrii and Cascades Range Colias pelidne. The conflict in gene genealogies may be a result of recent expansion in North American Colias, but an isolation with migration analysis indicates that genetic patterns in C. behrii might result from differential introgression following hybridization. Based on the timing of population expansion and gene flow between mountain ranges, the expanding alpine archipelago model is supported in C. behrii.

Characterizing Molecular Mechanisms of Imidacloprid Resistance in Select Populations of Leptinotarsa decemlineata in the Central Sands Region of Wisconsin.

The Colorado potato beetle, Leptinotarsa decemlineata (Say), is a major agricultural pest in the Central Sands region of Wisconsin. Imidacloprid, a neonicotinoid insecticide, has commonly been used for control of L. decemlineata since its registration in 1995. In the last 10 years, many field populations of L. decemlineata have begun to show increasing imidacloprid resistance. We studied resistance phenotype as a phenomenon that reduces neonicotinoid efficacy and has practical consequences for potato pest management. Although we have not observed complete field failure following the use of these products, multiple studies have demonstrated that the lethal concentration to kill 50% of the test organisms (LC50) in different field populations of L. decemlineata varies greatly which may suggest that resistance of L. decemlineata is heritable and involves genetic changes. An important challenge in understanding resistance is assessing the genetic mechanisms associated with resistance and classifying up-regulated genes that may be involved in combating an insecticide insult. In this study we uncovered trends in imidacloprid phenotypic response that have developed in the region by estimating the LC50 values among different field populations against a range of imidacloprid doses. The LC50 values collected in 2008–2011, and more recently in 2013 and 2014, show that some field locations remain susceptible to imidacloprid, while nearby fields (<100km) have developed high levels of resistance. We also sought to uncover potential mechanisms of resistance at each field location. We compiled a transcriptome for populations, characterized as phenotypically ‘susceptible’ and ‘resistant’, by isolating mRNA from adult beetles and analyzing gene expression level differences. Strong differences were observed in constituently up and down-regulated genes among different field populations. Most significantly, the up-regulation of 3 cytochrome p450s and a glutathione synthetase related protein in multiple resistant populations provide a mechanistic explanation of resistance evolution in L. decemlineata.

Reverse genetics in the tide pool: knock‐down of target gene expression via RNA interference in the copepod Tigriopus californicus

Reverse genetic tools are essential for characterizing phenotypes of novel genes and testing functional hypotheses generated from next‐generation sequencing studies. RNA interference (RNAi) has been a widely used technique for describing or quantifying physiological, developmental or behavioural roles of target genes by suppressing their expression. The marine intertidal copepod Tigriopus californicus has become an emerging model for evolutionary and physiological studies, but this species is not amenable to most genetic manipulation approaches. As crustaceans are susceptible to RNAi‐mediated gene knock‐down, we developed a simple method for delivery of gene‐specific double‐stranded RNA that results in significant suppression of target gene transcription levels. The protocol was examined on five genes of interest, and for each, at least 50% knock‐down in expression was achieved. While knock‐down levels did not reach 100% in any trial, a well‐controlled experiment with one heat‐shock gene showed unambiguously that such partial gene suppression may cause dramatic changes in phenotype. Copepods with suppressed expression of heat‐shock protein beta 1 (hspb1) exhibited dramatically decreased tolerance to high temperatures, validating the importance of this gene during thermal stress, as proposed by a previous study. The application of this RNAi protocol in T. californicus will be invaluable for examining the role of genes putatively involved in reproductive isolation, mitochondrial function and local adaptation.