Applying landscape genetics to the microbial world

Landscape genetics, which explicitly quantifies landscape effects on gene flow and adaptation, has largely focused on macroorganisms, with little attention given to microorganisms. This is despite overwhelming evidence that microorganisms exhibit spatial genetic structuring in relation to environmental variables. The increasing accessibility of genomic data has opened up the opportunity for landscape genetics to embrace the world of microorganisms, which may be thought of as ‘the invisible regulators’ of the macroecological world. Recent developments in bioinformatics and increased data accessibility have accelerated our ability to identify microbial taxa and characterize their genetic diversity. However, the influence of the landscape matrix and dynamic environmental factors on microorganism genetic dispersal and adaptation has been little explored. Also, because many microorganisms coinhabit or codisperse with macroorganisms, landscape genomic approaches may improve insights into how micro‐ and macroorganisms reciprocally interact to create spatial genetic structure. Conducting landscape genetic analyses on microorganisms requires that we accommodate shifts in spatial and temporal scales, presenting new conceptual and methodological challenges not yet explored in ‘macro’‐landscape genetics. We argue that there is much value to be gained for microbial ecologists from embracing landscape genetic approaches. We provide a case for integrating landscape genetic methods into microecological studies and discuss specific considerations associated with the novel challenges this brings. We anticipate that microorganism landscape genetic studies will provide new insights into both micro‐ and macroecological processes and expand our knowledge of species’ distributions, adaptive mechanisms and species’ interactions in changing environments.     

A hot topic: the genetics of adaptation to geothermal vents in Mimulus guttatus

Identifying the individual loci and mutations that underlie adaptation to extreme environments has long been a goal of evolutionary biology. However, finding the genes that underlie adaptive traits is difficult for several reasons. First, because many traits and genes evolve simultaneously as populations diverge, it is difficult to disentangle adaptation from neutral demographic processes. Second, finding the individual loci involved in any trait is challenging given the respective limitations of quantitative and population genetic methods. In this issue of Molecular Ecology, Hendrick et al. (2016) overcome these difficulties and determine the genetic basis of microgeographic adaptation between geothermal vent and nonthermal populations of Mimulus guttatus in Yellowstone National Park. The authors accomplish this by combining population and quantitative genetic techniques, a powerful, but labour‐intensive, strategy for identifying individual causative adaptive loci that few studies have used (Stinchcombe & Hoekstra 2008 ). In a previous common garden experiment (Lekberg et al. 2012), thermal M. guttatus populations were found to differ from their closely related nonthermal neighbours in various adaptive phenotypes including trichome density. Hendrick et al. (2016) combine quantitative trait loci (QTL) mapping, population genomic scans for selection and admixture mapping to identify a single genetic locus underlying differences in trichome density between thermal and nonthermal M. guttatus. The candidate gene, R2R3 MYB, is homologous to genes involved in trichome development across flowering plants. The major trichome QTL, Tr14, is also involved in trichome density differences in an independent M. guttatus population comparison (Holeski et al. 2010) making this an example of parallel genetic evolution.     

Perspectives and challenges in landscape genetics

A recent workshop held at the University of Grenoble gathered the leading experts in the field of landscape genetics and spatial statistics. Landscape genetics was only recently defined as an independent research field. It aims to understand the processes of gene flow and local adaptation by studying the interactions between genetic and spatial or environmental variation. This workshop discussed the perspectives and challenges of combining emerging molecular, spatial and statistical tools to unravel how landscape and environmental variables affect genetic variation.     

Genomics and museum specimens

Nearly 25 years ago, Allan Wilson and colleagues isolated DNA sequences from museum specimens of kangaroo rats (Dipodomys panamintinus) and compared these sequences with those from freshly collected animals (Thomas et al. 1990 ). The museum specimens had been collected up to 78 years earlier, so the two samples provided a direct temporal comparison of patterns of genetic variation. This was not the first time DNA sequences had been isolated from preserved material, but it was the first time it had been carried out with a population sample. Population geneticists often try to make inferences about the influence of historical processes such as selection, drift, mutation and migration on patterns of genetic variation in the present. The work of Wilson and colleagues was important in part because it suggested a way in which population geneticists could actually study genetic change in natural populations through time, much the same way that experimentalists can do with artificial populations in the laboratory. Indeed, the work of Thomas et al. ( 1990 ) spawned dozens of studies in which museum specimens were used to compare historical and present‐day genetic diversity (reviewed in Wandeler et al. 2007 ). All of these studies, however, were limited by the same fundamental problem: old DNA is degraded into short fragments. As a consequence, these studies mostly involved PCR amplification of short templates, usually short stretches of mitochondrial DNA or microsatellites. In this issue, Bi et al. ( 2013 ) report a breakthrough that should open the door to studies of genomic variation in museum specimens. They used target enrichment (exon capture) and next‐generation (Illumina) sequencing to compare patterns of genetic variation in historic and present‐day population samples of alpine chipmunks (Tamias alpinus) (Fig. 1). The historic samples came from specimens collected in 1915, so the temporal span of this comparison is nearly 100 years.     

Parallel introgression and selection on introduced alleles in a native species

As humans cause the redistribution of species ranges, hybridization between previously allopatric species is on the rise. Such hybridization can have complex effects on overall fitness of native species as new allelic combinations are tested. Widespread species introductions provide a unique opportunity to study selection on introgressed alleles in independent, replicated populations. We examined selection on alleles that repeatedly introgressed from introduced rainbow trout (Oncorhynchus mykiss) into native westslope cutthroat trout (Oncorhynchus clarkii lewisi) populations in western Canada. We found that the degree of introgression of individual single nucleotide polymorphisms from the invasive species into the native is correlated between independent watersheds. A number of rainbow trout alleles have repeatedly swept to high frequency in native populations, suggesting parallel adaptive advantages. Using simulations, we estimated large selection coefficients up to 0.05 favoring several rainbow trout alleles in the native background. Although previous studies have found reduced hybrid fitness and genome‐wide resistance to introgression in westslope cutthroat trout, our results suggest that some introduced genomic regions are strongly favored by selection. Our study demonstrates the utility of replicated introductions as case studies for understanding parallel adaptation and the interactions between selection and introgression across the genome. We suggest that understanding this variation, including consideration of beneficial alleles, can inform management strategies for hybridizing species.     

Putting the genes into community genetics

As part of the long‐term fusion of evolutionary biology and ecology (Ford, 1964), the field of community genetics has made tremendous progress in describing the impacts of plant genetic variation on community and ecosystem processes. In the “genes‐to‐ecosystems” framework (Whitham et al., 2003), genetically based traits of plant species have ecological consequences, but previous studies have not identified specific plant genes responsible for community phenotypes. The study by Barker et al. (2019) in this issue of Molecular Ecology uses an impressive common garden experiment of trembling aspen (Figure 1) to test for the genetic basis of tree traits that shape the insect community composition. Using a Genome‐Wide Association Study (GWAS), they found that genomic regions associated with phytochemical traits best explain variation in herbivore community composition, and identified specific genes associated with different types of leaf‐modifying herbivores and ants. This is one of the first studies to identify candidate genes underlying the heritable plant traits that explain patterns of insect biodiversity.     

Population genetic structure and adaptation of malaria parasites on the edge of endemic distribution

To determine whether the major human malaria parasite Plasmodium falciparum exhibits fragmented population structure or local adaptation at the northern limit of its African distribution where the dry Sahel zone meets the Sahara, samples were collected from diverse locations within Mauritania over a range of ~1000 km. Microsatellite genotypes were obtained for 203 clinical infection samples from eight locations, and Illumina paired‐end sequences were obtained to yield high coverage genomewide single nucleotide polymorphism (SNP) data for 65 clinical infection samples from four locations. Most infections contained single parasite genotypes, reflecting low rates of transmission and superinfection locally, in contrast to the situation seen in population samples from countries further south. A minority of infections shared related or identical genotypes locally, indicating some repeated transmission of parasite clones without recombination. This caused some multilocus linkage disequilibrium and local divergence, but aside from the effect of repeated genotypes there was minimal differentiation between locations. Several chromosomal regions had elevated integrated haplotype scores (|iHS|) indicating recent selection, including those containing drug resistance genes. A genomewide F_ST scan comparison with previous sequence data from an area in West Africa with higher infection endemicity indicates that regional gene flow prevents genetic isolation, but revealed allele frequency differentiation at three drug resistance loci and an erythrocyte invasion ligand gene. Contrast of extended haplotype signatures revealed none to be unique to Mauritania. Discrete foci of infection on the edge of the Sahara are genetically highly connected to the wider continental parasite population, and local elimination would be difficult to achieve without very substantial reduction in malaria throughout the region.     

Navigating the pitfalls and promise of landscape genetics

The field of landscape genetics has been evolving rapidly since its emergence in the early 2000s. New applications, techniques and criticisms of techniques appear like clockwork with each new journal issue. The developments are an encouraging, and at times bewildering, sign of progress in an exciting new field of study. However, we suggest that the rapid expansion of landscape genetics has belied important flaws in the development of the field, and we add an air of caution to this breakneck pace of expansion. Specifically, landscape genetic studies often lose sight of the fundamental principles and complex consequences of gene flow, instead favouring simplistic interpretations and broad inferences not necessarily warranted by the data. Here, we describe common pitfalls that characterize such studies, and provide practical guidance to improve landscape genetic investigation, with careful consideration of inferential limits, scale, replication, and the ecological and evolutionary context of spatial genetic patterns. Ultimately, the utility of landscape genetics will depend on translating the relationship between gene flow and landscape features into an understanding of long‐term population outcomes. We hope the perspective presented here will steer landscape genetics down a more scientifically sound and productive path, garnering a field that is as informative in the future as it is popular now.     

景观遗传学：概念与方法

全球变化下的物种栖息地丧失和破碎化给生物多样性保护带来了新的问题和挑战,生物多样性保护必须由单纯的物种保护上升到栖息地景观的保护。景观遗传学是定量确定栖息地景观特征对种群遗传结构影响的一门交叉学科,在生物保护及自然保护区管理方面有巨大的潜力。从生物多样性保护的角度评述了景观结构与遗传多样性的关系,介绍了景观遗传学的基本概念,研究尺度和方法,并对景观遗传学当前的研究焦点及面临的挑战做了总结。     

Adaptive landscape genetics and malaria across divergent island bird populations

Environmental conditions play a major role in shaping the spatial distributions of pathogens, which in turn can drive local adaptation and divergence in host genetic diversity. Haemosporidians, such as Plasmodium (malaria), are a strong selective force, impacting survival and fitness of hosts, with geographic distributions largely determined by habitat suitability for their insect vectors. Here, we have tested whether patterns of fine‐scale local adaptation to malaria are replicated across discrete, ecologically differing island populations of Berthelot's pipits Anthus berthelotii. We sequenced TLR4, an innate immunity gene that is potentially under positive selection in Berthelot's pipits, and two SNPs previously identified as being associated with malaria infection in a genome‐wide association study (GWAS) in Berthelot's pipits in the Canary Islands. We determined the environmental predictors of malaria infection, using these to estimate variation in malaria risk on Porto Santo, and found some congruence with previously identified environmental risk factors on Tenerife. We also found a negative association between malaria infection and a TLR4 variant in Tenerife. In contrast, one of the GWAS SNPs showed an association with malaria risk in Porto Santo, but in the opposite direction to that found in the Canary Islands GWAS. Together, these findings suggest that disease‐driven local adaptation may be an important factor in shaping variation among island populations.     

Geneland: a computer package for landscape genetics

Geneland is a computer package that allows to make use of georeferenced individual multilocus genotypes for the inference of the number of populations and of the spatial location of genetic discontinuities between those populations. Main assumptions of the method are: (i) the number of populations is unknown and all values are considered a priori equally likely, (ii) populations are spread over areas given by a union of some polygons of unknown location in the spatial domain, (iii) Hardy–Weinberg equilibrium is assumed within each population and (iv) allele frequencies in each population are unknown and treated as random variable either following the so‐called Dirichlet model or Falush model. Different algorithms implemented in Geneland to perform inferences are first briefly presented. Then major running steps and outputs (i.e. histogram of number of populations and map of posterior probabilities of population membership) are illustrated from the analysis of a simulated data set, which was also produced by Geneland.     

Climate variables explain neutral and adaptive variation within salmonid metapopulations: the importance of replication in landscape genetics

Understanding how environmental variation influences population genetic structure is important for conservation management because it can reveal how human stressors influence population connectivity, genetic diversity and persistence. We used riverscape genetics modelling to assess whether climatic and habitat variables were related to neutral and adaptive patterns of genetic differentiation (population‐specific and pairwise F_ST) within five metapopulations (79 populations, 4583 individuals) of steelhead trout (Oncorhynchus mykiss) in the Columbia River Basin, USA. Using 151 putatively neutral and 29 candidate adaptive SNP loci, we found that climate‐related variables (winter precipitation, summer maximum temperature, winter highest 5% flow events and summer mean flow) best explained neutral and adaptive patterns of genetic differentiation within metapopulations, suggesting that climatic variation likely influences both demography (neutral variation) and local adaptation (adaptive variation). However, we did not observe consistent relationships between climate variables and F_ST across all metapopulations, underscoring the need for replication when extrapolating results from one scale to another (e.g. basin‐wide to the metapopulation scale). Sensitivity analysis (leave‐one‐population‐out) revealed consistent relationships between climate variables and F_ST within three metapopulations; however, these patterns were not consistent in two metapopulations likely due to small sample sizes (N = 10). These results provide correlative evidence that climatic variation has shaped the genetic structure of steelhead populations and highlight the need for replication and sensitivity analyses in land and riverscape genetics.     

Integrative conservation genetics: Prioritizing populations using climate predictions,adaptive potential and habitat connectivity

Conservation decisions often involve allocation of scarce resources among many areas of need. Various approaches exist to help prioritize species and populations for conservation. Past efforts have often used relatively narrow, one‐dimensional criteria, such as genetic resource value or exposure to threats. What is lacking is a refined, comprehensive prioritization approach including ecological and evolutionary aspects, informed by rich and reliable data. In this issue of Molecular Ecology Resources, Razgour et al. ( 2017 ) present a new prioritization framework that coherently integrates three dimensions of population vulnerability: exposure to change, sensitivity to change and range shift potential. They measure these dimensions for 10 populations of a European bat using a suite of advanced analysis methods that leverage genomic, environmental and occurrence data. Explicitly recognizing and quantifying the multidimensional nature of conservation priorities is a key advance because it enables a nuanced assessment of each population and identification of populations of high concern along all three dimensions. With some caveats and modifications, this framework could be a major step for conservation prioritization and intervention that is proactive and informed by evolutionary principles.     

Recognizing the temporal distinctions between landscape genetics and phylogeography

The steadily advancing fields of landscape genetics and phylogeography share many goals. However, there are some very distinct differences between these two disciplines, including the kinds of data and analyses commonly used, the timescale over which these data are informative, and the hypotheses the data are used to examine. Recently, a number of studies appear to have confused or synonymized phylogeography and landscape genetics. The difference is not merely semantic; understanding the distinctions between these fields is important for ensuring that researchers are aware of the temporal scale over which their data are informative.     

Genetics of host–parasite interactions: towards a comprehensive dissection of Drosophila resistance to viral infection

One of the major challenges in evolutionary biology is to unravel the genetic basis of adaptation. This issue has been gaining momentum in recent years with the accelerated development of novel genetic and genomic techniques and resources. In this issue of Molecular Ecology, Cogni et al. (2016) address the genetic basis of resistance to two viruses in Drosophila melanogaster using a panel of recombinant inbred lines with unprecedented resolution allowing detection of rare alleles and/or alleles of small effect. The study confirms the role of previously identified genes of major effect and adds novel regions with minor effect to the genetic basis of Drosophila resistance to the Drosophila C virus or the sigma virus. Additional analyses reveal the absence of cross‐resistance and of epistasis between the various genomic regions. This detailed information on the genetic architecture of host resistance constitutes an important step towards the understanding of both the physiology of antiviral immunity and the evolution of host–parasite interactions.     

A robust sequencing assay of a thousand amplicons for the high-throughput population monitoring of Alpine ibex immunogenetics

Polymorphism for immune functions can explain significant variation in health and reproductive success within species. Drastic loss in genetic diversity at such loci constitutes an extinction risk and should be monitored in species of conservation concern. However, effective implementations of genome-wide immune polymorphism sets into high-throughput genotyping assays are scarce. Here, we report the design and validation of a microfluidics-based amplicon sequencing assay to comprehensively capture genetic variation in Alpine ibex (Capra ibex). This species represents one of the most successful large mammal restorations recovering from a severely depressed census size and a massive loss in diversity at the major histocompatibility complex (MHC). We analysed 65 whole-genome sequencing sets of the Alpine ibex and related species to select the most representative markers and to prevent primer binding failures. In total, we designed ~1,000 amplicons densely covering the MHC, further immunity-related genes as well as randomly selected genome-wide markers for the assessment of neutral population structure. Our analysis of 158 individuals shows that the genome-wide markers perform equally well at resolving population structure as RAD-sequencing or low-coverage genome sequencing data sets. Immunity-related loci show unexpectedly high degrees of genetic differentiation within the species. Such information can now be used to define highly targeted individual translocations. Our design strategy can be realistically implemented into genetic surveys of a large range of species. In conclusion, leveraging whole-genome sequencing data sets to design targeted amplicon assays allows the simultaneous monitoring of multiple genetic risk factors and can be translated into species conservation recommendations.     

Advances in ecological genomics in forest trees and applications to genetic resources conservation and breeding

Forest trees are an unparalleled group of organisms in their combined ecological, economic and societal importance. With widespread distributions, predominantly random mating systems and large population sizes, most tree species harbour extensive genetic variation both within and among populations. At the same time, demographic processes associated with Pleistocene climate oscillations and land‐use change have affected contemporary range‐wide diversity and may impinge on the potential for future adaptation. Understanding how these adaptive and neutral processes have shaped the genomes of trees species is therefore central to their management and conservation. As for many other taxa, the advent of high‐throughput sequencing methods is expected to yield an understanding of the interplay between the genome and environment at a level of detail and depth not possible only a few years ago. An international conference entitled ‘Genomics and Forest Tree Genetics’ was held in May 2016, in Arcachon (France), and brought together forest geneticists with a wide range of research interests to disseminate recent efforts that leverage contemporary genomic tools to probe the population, quantitative and evolutionary genomics of trees. An important goal of the conference was to discuss how such data can be applied to both genome‐enabled breeding and the conservation of forest genetic resources under land use and climate change. Here, we report discoveries presented at the meeting and discuss how the ecological genomic toolkit can be used to address both basic and applied questions in tree biology.