High‐throughput SNPs for all: genotyping‐in‐thousands

Understanding the genetic structure of species is essential for conservation. It is only with this information that managers, academics, user groups and land‐use planners can understand the spatial scale of migration and local adaptation, source‐sink dynamics and effective population size. Such information is essential for a multitude of applications including delineating management units, balancing management priorities, discovering cryptic species and implementing captive breeding programmes. Species can range from locally adapted by hundreds of metres (Pavey et al. 2010 ) to complete species panmixia (Côté et al. 2013 ). Even more remarkable is that this essential information can be obtained without fully sequenced or annotated genomes, but from mere (putatively) nonfunctional variants. First with allozymes, then microsatellites and now SNPs, this neutral genetic variation carries a wealth of information about migration and drift. For many of us, it may be somewhat difficult to remember our understanding of species conservation before the widespread usage of these useful tools. However most species on earth have yet to give us that ‘peek under the curtain’. With the current diversity on earth estimated to be nearly 9 million species (Mora et al. 2011 ), we have a long way to go for a comprehensive meta‐phylogeographic understanding. A method presented in this issue by Campbell and colleagues (Campbell et al. 2015 ) is a tool that will accelerate the pace in this area. Genotyping‐in‐thousands (GT‐seq) leverages recent advancements in sequencing technology to save many hours and dollars over previous methods to generate this important neutral genetic information.     

Evaluating methods to visualize patterns of genetic differentiation on a landscape

With advances in sequencing technology, research in the field of landscape genetics can now be conducted at unprecedented spatial and genomic scales. This has been especially evident when using sequence data to visualize patterns of genetic differentiation across a landscape due to demographic history, including changes in migration. Two recent model‐based visualization methods that can highlight unusual patterns of genetic differentiation across a landscape, SpaceMix and EEMS, are increasingly used. While SpaceMix's model can infer long‐distance migration, EEMS’ model is more sensitive to short‐distance changes in genetic differentiation, and it is unclear how these differences may affect their results in various situations. Here, we compare SpaceMix and EEMS side by side using landscape genetics simulations representing different migration scenarios. While both methods excel when patterns of simulated migration closely match their underlying models, they can produce either un‐intuitive or misleading results when the simulated migration patterns match their models less well, and this may be difficult to assess in empirical data sets. We also introduce unbundled principal components (un‐PC), a fast, model‐free method to visualize patterns of genetic differentiation by combining principal components analysis (PCA), which is already used in many landscape genetics studies, with the locations of sampled individuals. Un‐PC has characteristics of both SpaceMix and EEMS and works well with simulated and empirical data. Finally, we introduce msLandscape, a collection of tools that streamline the creation of customizable landscape‐scale simulations using the popular coalescent simulator ms and conversion of the simulated data for use with un‐PC, SpaceMix and EEMS.     

The role of genetic structure in the adaptive divergence of populations experiencing saltwater intrusion due to relative sea‐level rise

Saltwater intrusion into estuaries creates stressful conditions for nektonic species. Previous studies have shown that Gambusia affinis populations with exposure to saline environments develop genetic adaptations for increased survival during salinity stress. Here, we evaluate the genetic structure of G. affinis populations, previously shown to have adaptations for increased salinity tolerance, and determine the impact of selection and gene flow on structure of these populations. We found that gene flow was higher between populations experiencing different salinity regimes within an estuary than between similar marsh types in different estuaries, suggesting the development of saline‐tolerant phenotypes due to local adaptation. There was limited evidence of genetic structure along a salinity gradient, and only some of the genetic variation among sites was correlated with salinity. Our results suggest limited structure, combined with selection to saltwater intrusion, results in phenotypic divergence in spite of a lack of physical barriers to gene flow.     

Development and characterization of 29 microsatellite markers for Ligumia nasuta (Bivalvia: Unionidae) using an Illumina sequencing approach

Ligumia nasuta (Say, 1817; Eastern Pondmussel) is an imperiled freshwater mussel (Unionidae) in eastern North America. Population declines in the Laurentian Great Lakes resulting from the introduction of dreissenid mussels and habitat destruction in the 20th Century have greatly reduced and limited its distribution. To properly inform restoration and management efforts for L. nasuta, fine-scale genetic analyses must be performed on the remnant populations. This study used Illumina paired-end shotgun sequencing to identify potential microsatellite loci for L. nasuta, utilizing two samples to develop the Illumina paired-end shotgun library. Forty-eight primer pairs were tested on the remaining 24 samples. Twenty-nine of the 48 microsatellite primer sets screened were successfully amplified using 24 L. nasuta samples collected from the Great Lakes watershed. The estimated fragment size ranged from 167 to 445 base-pairs (bp) and the number of alleles per locus varied between 5 and 16 (mean = 9.7). Only five of the loci deviated significantly from Hardy–Weinberg expectations after Bonferroni corrections. The development of these new microsatellite loci will greatly facilitate future genetic studies on L. nasuta.     

A C++ Template Library for Efficient Forward-Time Population Genetic Simulation of Large Populations

fwdpp is a C++ library of routines intended to facilitate the development of forward-time simulations under arbitrary mutation and fitness models. The library design provides a combination of speed, low memory overhead, and modeling flexibility not currently available from other forward simulation tools. The library is particularly useful when the simulation of large populations is required, as programs implemented using the library are much more efficient than other available forward simulation programs.     

Size differentiation in Finnish house sparrows follows Bergmann's rule with evidence of local adaptation

Bergmann's rule predicts that individuals are larger in more poleward populations and that this size gradient has an adaptive basis. Hence, phenotypic divergence in size traits between populations (P_ST) is expected to exceed the level of divergence by drift alone (F_ST). We measured 16 skeletal traits, body mass and wing length in 409 male and 296 female house sparrows Passer domesticus sampled in 12 populations throughout Finland, where the species has its northernmost European distributional margin. Morphometric differentiation across populations (P_ST) was compared with differentiation in 13 microsatellites (F_ST). We find that twelve traits phenotypically diverged more than F_ST in both sexes, and an additional two traits diverged in males. The phenotypic divergence exceeded F_ST in several traits to such a degree that findings were robust also to strong between‐population environmental effects. Divergence was particularly strong in dimensions of the bill, making it a strong candidate for the study of adaptive molecular genetic divergence. Divergent traits increased in size in more northern populations. We conclude that house sparrows show evidence of an adaptive latitudinal size gradient consistent with Bergmann's rule on the modest spatial scale of ca. 600 km.     

Genes,environment and responsibility for violent behavior: “Whatever genes one has it is preferable that you are prevented from going around stabbing people”

For the legal system to function effectively people are generally viewed as autonomous actors able to exercise choice and responsible for their actions. It is conceivable that genetic traits associated with violent and antisocial behavior could call into question an affected individual's responsibility for acts of criminal violence. Evidence concerning genes associated with violent and antisocial behavior has been introduced in criminal courts in the USA and Italy, either alone or with associated environmental factors. One example of a “genetic defense” is based on low levels of monoamine oxidase A (MAOA) activity, with a prevalence of around 30% in Caucasian males. In countries with trial by jury it is particularly relevant to consider the views of publics on criminal liability and the significance they assign to evidence citing genetic influences on behavior. This article draws on largely qualitative research looking at participants' explanations of, and assigning of responsibility for, violent and antisocial behavior where environmental or genetic influences are claimed. Genetic factors were not viewed deterministically by participants but were considered by most to be irrelevant to personal responsibility. Notions of human agency, free will and choice were crucial to explanations of problem behaviors and ensured that offenders could be held responsible despite evidence on environmental and genetic factors.     

Is there such a thing as landscape genetics?

For a scientific discipline to be interdisciplinary, it must satisfy two conditions; it must consist of contributions from at least two existing disciplines, and it must be able to provide insights, through this interaction, that neither progenitor discipline could address. In this study, I examine the complete body of peer‐reviewed literature self‐identified as landscape genetics (LG) using the statistical approaches of text mining and natural language processing. The goal here was to quantify the kinds of questions being addressed in LG studies, the ways in which questions are evaluated mechanistically, and how they are differentiated from the progenitor disciplines of landscape ecology and population genetics. I then circumscribe the main factions within published LG studies examining the extent to which emergent questions are being addressed and highlighting a deep bifurcation between existing individual‐ and population‐based approaches. I close by providing some suggestions on where theoretical and analytical work is needed if LGs is to serve as a real bridge connecting evolution and ecology sensu lato.     

Amylase activity is associated with AMY2B copy numbers in dog: implications for dog domestication,diet and diabetes

High amylase activity in dogs is associated with a drastic increase in copy numbers of the gene coding for pancreatic amylase, AMY2B, that likely allowed dogs to thrive on a relatively starch‐rich diet during early dog domestication. Although most dogs thus probably digest starch more efficiently than do wolves, AMY2B copy numbers vary widely within the dog population, and it is not clear how this variation affects the individual ability to handle starch nor how it affects dog health. In humans, copy numbers of the gene coding for salivary amylase, AMY1, correlate with both salivary amylase levels and enzyme activity, and high amylase activity is related to improved glycemic homeostasis and lower frequencies of metabolic syndrome. Here, we investigate the relationship between AMY2B copy numbers and serum amylase activity in dogs and show that amylase activity correlates with AMY2B copy numbers. We then describe how AMY2B copy numbers vary in individuals from 20 dog breeds and find strong breed‐dependent patterns, indicating that the ability to digest starch varies both at the breed and individual level. Finally, to test whether AMY2B copy number is strongly associated with the risk of developing diabetes mellitus, we compare copy numbers in cases and controls as well as in breeds with varying diabetes susceptibility. Although we see no such association here, future studies using larger cohorts are needed before excluding a possible link between AMY2B and diabetes mellitus.     

Landscape models for nuclear genetic diversity and genetic structure in white-footed mice (Peromyscus leucopus)

Dramatic changes in the North American landscape over the last 12 000 years have shaped the genomes of the small mammals, such as the white-footed mouse (Peromyscus leucopus), which currently inhabit the region. However, very recent interactions of populations with each other and the environment are expected to leave the most pronounced signature on rapidly evolving nuclear microsatellite loci. We analyzed landscape characteristics and microsatellite markers of P. leucopus populations along a transect from southern Ohio to northern Michigan, in order to evaluate hypotheses about the spatial distribution of genetic heterogeneity. Genetic diversity increased to the north and was best approximated by a single-variable model based on habitat availability within a 0.5-km radius of trapping sites. Interpopulation differentiation measured by clustering analysis was highly variable and not significantly related to latitude or habitat availability. Interpopulation differentiation measured as F_ST values and chord distance was correlated with the proportion of habitat intervening, but was best explained by agricultural distance and by latitude. The observed gradients in diversity and interpopulation differentiation were consistent with recent habitat availability being the major constraint on effective population size in this system, and contradicted the predictions of both the postglacial expansion and core-periphery hypotheses.     

Fine-scale genetic population structure in a mobile marine mammal: inshore bottlenose dolphins in Moreton Bay, Australia

Highly mobile marine species in areas with no obvious geographic barriers are expected to show low levels of genetic differentiation. However, small‐scale variation in habitat may lead to resource polymorphisms and drive local differentiation by adaptive divergence. Using nuclear microsatellite genotyping at 20 loci, and mitochondrial control region sequencing, we investigated fine‐scale population structuring of inshore bottlenose dolphins (Tursiops aduncus) inhabiting a range of habitats in and around Moreton Bay, Australia. Bayesian structure analysis identified two genetic clusters within Moreton Bay, with evidence of admixture between them (F_ST = 0.05, P = 0.001). There was only weak isolation by distance but one cluster of dolphins was more likely to be found in shallow southern areas and the other in the deeper waters of the central northern bay. In further analysis removing admixed individuals, southern dolphins appeared genetically restricted with lower levels of variation (AR = 3.252, π = 0.003) and high mean relatedness (r = 0.239) between individuals. In contrast, northern dolphins were more diverse (AR = 4.850, π = 0.009) and were mixing with a group of dolphins outside the bay (microsatellite‐based STRUCTURE analysis), which appears to have historically been distinct from the bay dolphins (mtDNA Φ_ST = 0.272, P < 0.001). This study demonstrates the ability of genetic techniques to expose fine‐scale patterns of population structure and explore their origins and mechanisms. A complex variety of inter‐related factors including local habitat variation, differential resource use, social behaviour and learning, and anthropogenic disturbances are likely to have played a role in driving fine‐scale population structure among bottlenose dolphins in Moreton Bay.     

Making the connection: expanding the role of restoration genetics in restoring and evaluating connectivity

The success of restoration activities is affected by connectivity with the surrounding landscape. From a genetic perspective, landscape connectivity can influence gene flow, effective size, and genetic diversity of populations, which in turn have impacts on the fitness and adaptive potential of species in restored areas. Researchers and practitioners are increasingly using genetic data to incorporate elements of connectivity into restoration planning and evaluation. We show that genetic studies of connectivity can improve restoration planning in three main ways. First, by comparing genetic estimates of contemporary and historical gene flow and population size, practitioners can establish historical baselines that may provide targets for restoration of connectivity. Second, empirical estimates of dispersal, landscape resistance to movement, and adaptive genetic variance can be derived from genetic data and used to parameterize existing restoration planning tools. Finally, restoration actions can also be targeted to remove barriers to gene flow or mitigate pinch‐points in corridors. We also discuss appropriate methods for evaluating the restoration of gene flow over timescales required by practitioners. Collaboration between restoration geneticists, ecologists, and practitioners is needed to develop practical and innovative ways to further incorporate connectivity into restoration practice.     

Rotifer genetics: integration of classic and modern techniques

Rotifer genetics has a long but sporadic history. There have been 4 major periods of research activity: (1) determining the environmental control of sexuality with inferences regarding genetics — early 1900's; (2) exploring the relationship between chromosome numbers and the rotifer life cycle — 1920's; (3) physiological and developmental genetics — 1960's; and (4) theoretical and experimental population genetics late 1970's. With newly developed molecular techniques, in conjunction with more traditional approaches, integration of these fields is beginning. Examples include investigation of gene expression involved in sexual reproduction by isolating glycoproteins responsible for mate recognition. Improvement of techniques for chromosome analysis has made it possible to verify haploidy in males and led to the discovery of polyploidy. The role of specialized proteins in the stress response is being elaborated with an accompanying search for the genetic elements which control them. Most recently the polymerase chain reaction (PCR) has been used to amplify ribosomal genes, and is a first step in using DNA sequences to define evolutionary relationships among the Rotifera.     

HETEROZYGOSITY‐FITNESS CORRELATIONS: A TIME FOR REAPPRAISAL

Owing to the remarkable progress of molecular techniques, heterozygosity‐fitness correlations (HFCs) have become a popular tool to study the impact of inbreeding in natural populations. However, their underlying mechanisms are often hotly debated. Here we argue that these “debates” rely on verbal arguments with no basis in existing theory and inappropriate statistical testing, and that it is time to reconcile HFC with its historical and theoretical fundaments. We show that available data are quantitatively and qualitatively consistent with inbreeding‐based theory. HFC can be used to estimate the impact of inbreeding in populations, although such estimates are bound to be imprecise, especially when inbreeding is weak. Contrary to common belief, linkage disequilibrium is not an alternative to inbreeding, but rather comes with some forms of inbreeding, and is not restricted to closely linked loci. Finally, the contribution of local chromosomal effects to HFC, while predicted by inbreeding theory, is expected to be small, and has rarely if ever proven statistically significant using adequate tests. We provide guidelines to safely interpret and quantify HFCs, and present how HFCs can be used to quantify inbreeding load and unravel the structure of natural populations.     

The European sea bass: a key marine fish model in the wild and in aquaculture

The European sea bass (Dicentrarchus labrax L.) is a marine fish of key economic and cultural importance in Europe. It is now more an aquaculture than a fisheries species (>96% of the production in 2016), although modern rearing techniques date back only from the late 1980s. It also has high interest for evolutionary studies, as it is composed of two semispecies (Atlantic and Mediterranean lineages) that have come into secondary contact following the last glaciation. Based on quantitative genetics studies of most traits of interest over the past 10–15 years, selective breeding programs are now applied to this species, which is at the beginning of its domestication process. The availability of a good quality reference genome has accelerated the development of new genomic resources, including SNP arrays that will enable genomic selection to improve genetic gain. There is a need to improve feed efficiency, both for economic and environmental reasons, but this will require novel phenotyping approaches. Further developments will likely focus on the understanding of genotype‐by‐environment interactions, which will be important both for efficient breeding of farmed stocks and for improving knowledge of the evolution of natural populations. At the interface between both, the domestication process must be better understood to improve production and also to fully evaluate the possible impact of aquaculture escapees on wild populations. The latter is an important question for all large‐scale aquaculture productions.     

Understanding and using quantitative genetic variation

Quantitative genetics, or the genetics of complex traits, is the study of those characters which are not affected by the action of just a few major genes. Its basis is in statistical models and methodology, albeit based on many strong assumptions. While these are formally unrealistic, methods work. Analyses using dense molecular markers are greatly increasing information about the architecture of these traits, but while some genes of large effect are found, even many dozens of genes do not explain all the variation. Hence, new methods of prediction of merit in breeding programmes are again based on essentially numerical methods, but incorporating genomic information. Long-term selection responses are revealed in laboratory selection experiments, and prospects for continued genetic improvement are high. There is extensive genetic variation in natural populations, but better estimates of covariances among multiple traits and their relation to fitness are needed. Methods based on summary statistics and predictions rather than at the individual gene level seem likely to prevail for some time yet.     

Evolutionary potential in the wild: more than meets the eye

The genus Aquilegia consists of 60–70 perennial plant species widely distributed throughout the northern hemisphere. Its flowers have a delicate and ornamental appearance that makes them a favourite of gardeners. In this genus, adaptive radiations for both floral and vegetative traits have occurred. These adaptive radiations, and the key phylogenetic placement of Aquilegia between Arabidopsis and rice, make this genus a ‘model system’ for plant evolution ( Kramer 2009 ). In this issue, Castellanos et al. (2011) use a marker‐based method to infer heritability for floral and vegetative traits in two Aquilegia species. Layered on top of this are estimates of the strength of natural selection. This novel joint estimation of heritability and selection in the wild showed that vegetative traits, compared to floral traits, have the highest evolutionarily potential. Evolutionary potential is the most important quantity to measure in wild populations. It combines inheritance and strength of selection and predicts the potential for populations to adapt to changing environments. The combination of molecular techniques with species in natural environments makes this work a model for molecular ecological investigations.     

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.     

Landscape drivers of genomic diversity and divergence in woodland Eucalyptus

Spatial genetic patterns are influenced by numerous factors, and they can vary even among coexisting, closely related species due to differences in dispersal and selection. Eucalyptus (L'Héritier 1789; the “eucalypts”) are foundation tree species that provide essential habitat and modulate ecosystem services throughout Australia. Here we present a study of landscape genomic variation in two woodland eucalypt species, using whole‐genome sequencing of 388 individuals of Eucalyptus albens and Eucalyptus sideroxylon. We found exceptionally high genetic diversity (π ≈ 0.05) and low genome‐wide, interspecific differentiation (F_ST = 0.15) and intraspecific differentiation between localities (F_ST ≈ 0.01–0.02). We found no support for strong, discrete population structure, but found substantial support for isolation by geographic distance (IBD) in both species. Using generalized dissimilarity modelling, we identified additional isolation by environment (IBE). Eucalyptus albens showed moderate IBD, and environmental variables have a small but significant amount of additional predictive power (i.e. IBE). Eucalyptus sideroxylon showed much stronger IBD and moderate IBE. These results highlight the vast adaptive potential of these species and set the stage for testing evolutionary hypotheses of interspecific adaptive differentiation across environments.     

遗传学双语教学探讨

遗传学双语教学是一个全新的教学研究领域。介绍了几种国外英语原版遗传学教材和教学参考书,并对遗传学双语教学方法进行了探讨。 Abstract:Bilingual teaching of genetics is a new teaching research area.This papper introduces a number of texts of genetics in English,and outlines principles of bilingual teaching of genetics.