Genomics of natural history collections for understanding evolution in the wild

A long‐standing question in biology is how organisms change through time and space in response to their environment. This knowledge is of particular relevance to predicting how organisms might respond to future environmental changes caused by human‐induced global change. Usually researchers make inferences about past events based on an understanding of current static genetic patterns, but these are limited in their capacity to inform on underlying past processes. Natural history collections (NHCs) represent a unique and critical source of information to provide temporally deep and spatially broad time‐series of samples. By using NHC samples, researchers can directly observe genetic changes over time and space and link those changes with specific ecological/evolutionary events. Until recently, such genetic studies were hindered by the intrinsic challenges of NHC samples (i.e. low yield of highly fragmented DNA). However, recent methodological and technological developments have revolutionized the possibilities in the novel field of NHC genomics. In this Special Feature, we compile a range of studies spanning from methodological aspects to particular case studies which demonstrate the enormous potential of NHC samples for accessing large genomic data sets from the past to advance our knowledge on how populations and species respond to global change at multiple spatial–temporal scales. We also highlight possible limitations, recommendations and a few opportunities for future researchers aiming to study NHC genomics.     

No specimen left behind: industrial scale digitization of natural history collections

Traditional approaches for digitizing natural history collections, which include both imaging and metadata capture, are both labour- and time-intensive. Mass-digitization can only be completed if the resource-intensive steps, such as specimen selection and databasing of associated information, are minimized. Digitization of larger collections should employ an “industrial” approach, using the principles of automation and crowd sourcing, with minimal initial metadata collection including a mandatory persistent identifier. A new workflow for the mass-digitization of natural history museum collections based on these principles, and using SatScan® tray scanning system, is described.     

The development of a digitising service centre for natural history collections

Digitarium is a joint initiative of the Finnish Museum of Natural History and the University of Eastern Finland. It was established in 2010 as a dedicated shop for the large-scale digitisation of natural history collections. Digitarium offers service packages based on the digitisation process, including tagging, imaging, data entry, georeferencing, filtering, and validation. During the process, all specimens are imaged, and distance workers take care of the data entry from the images. The customer receives the data in Darwin Core Archive format, as well as images of the specimens and their labels. Digitarium also offers the option of publishing images through Morphbank, sharing data through GBIF, and archiving data for long-term storage. Service packages can also be designed on demand to respond to the specific needs of the customer. The paper also discusses logistics, costs, and intellectual property rights (IPR) issues related to the work that Digitarium undertakes.     

Likelihood‐based inference of population history from low‐coverage de novo genome assemblies

Short‐read sequencing technologies have in principle made it feasible to draw detailed inferences about the recent history of any organism. In practice, however, this remains challenging due to the difficulty of genome assembly in most organisms and the lack of statistical methods powerful enough to discriminate between recent, nonequilibrium histories. We address both the assembly and inference challenges. We develop a bioinformatic pipeline for generating outgroup‐rooted alignments of orthologous sequence blocks from de novo low‐coverage short‐read data for a small number of genomes, and show how such sequence blocks can be used to fit explicit models of population divergence and admixture in a likelihood framework. To illustrate our approach, we reconstruct the Pleistocene history of an oak‐feeding insect (the oak gallwasp Biorhiza pallida), which, in common with many other taxa, was restricted during Pleistocene ice ages to a longitudinal series of southern refugia spanning the Western Palaearctic. Our analysis of sequence blocks sampled from a single genome from each of three major glacial refugia reveals support for an unexpected history dominated by recent admixture. Despite the fact that 80% of the genome is affected by admixture during the last glacial cycle, we are able to infer the deeper divergence history of these populations. These inferences are robust to variation in block length, mutation model and the sampling location of individual genomes within refugia. This combination of de novo assembly and numerical likelihood calculation provides a powerful framework for estimating recent population history that can be applied to any organism without the need for prior genetic resources.     

Assessing the phylogeographic history of the montane caddisfly Thremma gallicum using mitochondrial and restriction‐site‐associated DNA (RAD) markers

Repeated Quaternary glaciations have significantly shaped the present distribution and diversity of several European species in aquatic and terrestrial habitats. To study the phylogeography of freshwater invertebrates, patterns of intraspecific variation have been examined primarily using mitochondrial DNA markers that may yield results unrepresentative of the true species history. Here, population genetic parameters were inferred for a montane aquatic caddisfly, Thremma gallicum, by sequencing a 658‐bp fragment of the mitochondrial CO1 gene, and 12,514 nuclear RAD loci. T. gallicum has a highly disjunct distribution in southern and central Europe, with known populations in the Cantabrian Mountains, Pyrenees, Massif Central, and Black Forest. Both datasets represented rangewide sampling of T. gallicum. For the CO1 dataset, this included 352 specimens from 26 populations, and for the RAD dataset, 17 specimens from eight populations. We tested 20 competing phylogeographic scenarios using approximate Bayesian computation (ABC) and estimated genetic diversity patterns. Support for phylogeographic scenarios and diversity estimates differed between datasets with the RAD data favouring a southern origin of extant populations and indicating the Cantabrian Mountains and Massif Central populations to represent highly diverse populations as compared with the Pyrenees and Black Forest populations. The CO1 data supported a vicariance scenario (north–south) and yielded inconsistent diversity estimates. Permutation tests suggest that a few hundred polymorphic RAD SNPs are necessary for reliable parameter estimates. Our results highlight the potential of RAD and ABC‐based hypothesis testing to complement phylogeographic studies on non‐model species.     

Combining genome‐wide association study and FST‐based approaches to identify targets of Borrelia‐mediated selection in natural rodent hosts

Recent advances in high‐throughput sequencing technologies provide opportunities to gain novel insights into the genetic basis of phenotypic trait variation. Yet to date, progress in our understanding of genotype–phenotype associations in nonmodel organisms in general and natural vertebrate populations in particular has been hampered by small sample sizes typically available for wildlife populations and a resulting lack of statistical power, as well as a limited ability to control for false‐positive signals. Here we propose to combine a genome‐wide association study (GWAS) and F_ST‐based approach with population‐level replication to partly overcome these limitations. We present a case study in which we used this approach in combination with genotyping‐by‐sequencing (GBS) single nucleotide polymorphism (SNP) data to identify genomic regions associated with Borrelia afzelii resistance or susceptibility in the natural rodent host of this Lyme disease‐causing spirochete, the bank vole (Myodes glareolus). Using this combined approach we identified four consensus SNPs located in exonic regions of the genes Slc26a4, Tns3, Wscd1 and Espnl, which were significantly associated with the voles’ Borrelia infectious status within and across populations. Functional links between host responses to bacterial infections and most of these genes have previously been demonstrated in other rodent systems, making them promising new candidates for the study of evolutionary host responses to Borrelia emergence. Our approach is applicable to other systems and may facilitate the identification of genetic variants underlying disease resistance or susceptibility, as well as other ecologically relevant traits, in wildlife populations.     

Phylogenomics using formalin‐fixed and 100+ year‐old intractable natural history specimens

Museum specimens provide a wealth of information to biologists, but obtaining genetic data from formalin‐fixed and fluid‐preserved specimens remains challenging. While DNA sequences have been recovered from such specimens, most approaches are time‐consuming and produce low data quality and quantity. Here, we use a modified DNA extraction protocol combined with high‐throughput sequencing to recover DNA from formalin‐fixed and fluid‐preserved snakes that were collected over a century ago and for which little or no modern genetic materials exist in public collections. We successfully extracted DNA and sequenced ultraconserved elements ( = 2318 loci) from 10 fluid‐preserved snakes and included them in a phylogeny with modern samples. This phylogeny demonstrates the general use of such specimens in phylogenomic studies and provides evidence for the placement of enigmatic snakes, such as the rare and never‐before sequenced Indian Xylophis stenorhynchus. Our study emphasizes the relevance of museum collections in modern research and simultaneously provides a protocol that may prove useful for specimens that have been previously intractable for DNA sequencing.     

Colonization history and genetic diversity: adaptive potential in early stage invasions

The introduction of Anolis cristatellus from the multiple species anole community of Puerto Rico in the Greater Antilles to the island of Dominica in the Lesser Antilles, with its solitary endemic anole, provides an example of a very recent, timed, single colonization. We investigate the geographic origin and adaptive potential of the Dominican population using a range of methods including mtDNA phylogeography, nuclear microsatellite variation and multiple paternity studies, as well as heritability estimates, common garden experiments and comparative geographic studies of quantitative scalation traits. Phylogeographic analysis of NADH2 and microsatellite studies suggests that the Dominican population arose from a set of individuals from the central west area of Puerto Rico within their endemic range. The multiple‐individual inoculation, together with sperm storage and evidence of multiple paternity indicate genetic variability and suggest the potential for adaptation by natural selection. Estimates of heritability, common garden experiments and broad sense Q_ST/F_ST ratios, linked to replicated comparisons along elevational transects go some way to suggesting that the invasive populations may be adapting by natural selection, in parallel with the endemic anole, in the brief period since their introduction.     

The power of allele frequency comparisons to detect the footprint of selection in natural and experimental situations

Recently, inter-population comparisons of allele frequencies to detect past selection haven gained popularity. Data from genome-wide scans are used to detect the number and position of genes that have responded to unknown selection pressures in natural populations, or known selection pressures in experimental lines. Yet, the limitations and possibilities of these methods have not been well studied. In this paper, the objectives were (1) to investigate the distance over which a signal of directional selection is detectable under various scenarios, and (2) to study the power of the method depending on the properties of the used markers, for both natural populations and experimental set-ups. A combination of recurrence equations and simulations was used. The results show that intermediate strength selection on new mutations can be detected with a marker spacing of about 0.5 cM in large natural populations, 200 to 400 generations after the divergence of subpopulations. In experimental situations, only strong selection will be detectable, while markers can be spaced a few cM apart. Adaptation from standing variation in the base population will be hard to detect, though some solutions are presented for experimental designs.     

Museum genomics: low-cost and high-accuracy genetic data from historical specimens

Natural history collections are unparalleled repositories of geographical and temporal variation in faunal conditions. Molecular studies offer an opportunity to uncover much of this variation; however, genetic studies of historical museum specimens typically rely on extracting highly degraded and chemically modified DNA samples from skins, skulls or other dried samples. Despite this limitation, obtaining short fragments of DNA sequences using traditional PCR amplification of DNA has been the primary method for genetic study of historical specimens. Few laboratories have succeeded in obtaining genome-scale sequences from historical specimens and then only with considerable effort and cost. Here, we describe a low-cost approach using high-throughput next-generation sequencing to obtain reliable genome-scale sequence data from a traditionally preserved mammal skin and skull using a simple extraction protocol. We show that single-nucleotide polymorphisms (SNPs) from the genome sequences obtained independently from the skin and from the skull are highly repeatable compared to a reference genome.     

Whole mitochondrial genome capture from faecal samples and museum‐preserved specimens

Population‐scale molecular studies of endangered and cryptic species are often limited by access to high‐quality samples. The use of noninvasively collected samples or museum‐preserved specimens reduces the pressure on modern populations by removing the need to capture and handle live animals. However, endogenous DNA content in such samples is low, making shotgun sequencing a financially prohibitive approach. Here, we apply a target enrichment method to retrieve mitochondrial genomes from 65 museum specimens and 56 noninvasively collected faecal samples of two endangered great ape species, Grauer's gorilla and the eastern chimpanzee. We show that the applied method is suitable for a wide range of sample types that differ in endogenous DNA content, increasing the proportion of target reads to over 300‐fold. By systematically evaluating biases introduced during target enrichment of pooled museum samples, we show that capture is less efficient for fragments shorter or longer than the baits, that the proportion of human contaminating reads increases postcapture although capture efficiency is lower for human compared to gorilla fragments with a gorilla‐generated bait, and that the rate of jumping PCR is considerable, but can be controlled for with a double‐barcoding approach. We succeed in capturing complete mitochondrial genomes from faecal samples, but observe reduced capture efficiency as sequence divergence increases between the bait and target species. As previously shown for museum specimens, we demonstrate here that mitochondrial genome capture from field‐collected faecal samples is a robust and reliable approach for population‐wide studies of nonmodel organisms.     

Genome‐wide analysis of allele frequency change in sunflower crop–wild hybrid populations evolving under natural conditions

Crop‐wild hybridization occurs in numerous plant species and could alter the genetic structure and evolutionary dynamics of wild populations. Studying crop‐derived alleles in wild populations is also relevant to assessing/mitigating the risks associated with transgene escape. To date, crop‐wild hybridization has generally been examined via short‐term studies, typically within a single generation, focusing on few traits or genetic markers. Little is known about patterns of selection on crop‐derived alleles over multiple generations, particularly at a genome‐wide scale. Here, we documented patterns of natural selection in an experimental crop × wild sunflower population that was allowed to evolve under natural conditions for two generations at two locations. Allele frequencies at a genome‐wide collection of SNPs were tracked across generations, and a common garden experiment was conducted to compare trait means between generations. These data allowed us to identify instances of selection on crop‐derived alleles/traits and, in concert with QTL mapping results, test for congruence between our genotypic and phenotypic results. We found that natural selection overwhelmingly favours wild alleles and phenotypes. However, crop alleles in certain genomic regions can be favoured, and these changes often occurred in parallel across locations. We did not, however, consistently observe close agreement between our genotypic and phenotypic results. For example, when a trait evolved towards the wild phenotype, wild QTL alleles associated with that trait did not consistently increase in frequency. We discuss these results in the context of crop allele introgression into wild populations and implications for the management of GM crops.     

Phylogenomics using low‐depth whole genome sequencing: A case study with the olive tribe

Species trees have traditionally been inferred from a few selected markers, and genome‐wide investigations remain largely restricted to model organisms or small groups of species for which sampling of fresh material is available, leaving out most of the existing and historical species diversity. The genomes of an increasing number of species, including specimens extracted from natural history collections, are being sequenced at low depth. While these data sets are widely used to analyse organelle genomes, the nuclear fraction is generally ignored. Here we evaluate different reference‐based methods to infer phylogenies of large taxonomic groups from such data sets. Using the example of the Oleeae tribe, a worldwide‐distributed group, we build phylogenies based on single nucleotide polymorphisms (SNPs) obtained using two reference genomes (the olive and ash trees). The inferred phylogenies are overall congruent, yet present differences that might reflect the effect of distance to the reference on the amount of missing data. To limit this issue, genome complexity was reduced by using pairs of orthologous coding sequences as the reference, thus allowing us to combine SNPs obtained using two distinct references. Concatenated and coalescence trees based on these combined SNPs suggest events of incomplete lineage sorting and/or hybridization during the diversification of this large phylogenetic group. Our results show that genome‐wide phylogenetic trees can be inferred from low‐depth sequence data sets for eukaryote groups with complex genomes, and histories of reticulate evolution. This opens new avenues for large‐scale phylogenomics and biogeographical analyses covering both the extant and the historical diversity stored in museum collections.     

Genotype‐free estimation of allele frequencies reduces bias and improves demographic inference from RADSeq data

Restriction‐site associated DNA sequencing (RADSeq) facilitates rapid generation of thousands of genetic markers at relatively low cost; however, several sources of error specific to RADSeq methods often lead to biased estimates of allele frequencies and thereby to erroneous population genetic inference. Estimating the distribution of sample allele frequencies without calling genotypes was shown to improve population inference from whole genome sequencing data, but the ability of this approach to account for RADSeq‐specific biases remains unexplored. Here we assess in how far genotype‐free methods of allele frequency estimation affect demographic inference from empirical RADSeq data. Using the well‐studied pied flycatcher (Ficedula hypoleuca) as a study system, we compare allele frequency estimation and demographic inference from whole genome sequencing data with that from RADSeq data matched for samples using both genotype‐based and genotype free methods. The demographic history of pied flycatchers as inferred from RADSeq data was highly congruent with that inferred from whole genome resequencing (WGS) data when allele frequencies were estimated directly from the read data. In contrast, when allele frequencies were derived from called genotypes, RADSeq‐based estimates of most model parameters fell outside the 95% confidence interval of estimates derived from WGS data. Notably, more stringent filtering of the genotype calls tended to increase the discrepancy between parameter estimates from WGS and RADSeq data, respectively. The results from this study demonstrate the ability of genotype‐free methods to improve allele frequency spectrum‐ (AFS‐) based demographic inference from empirical RADSeq data and highlight the need to account for uncertainty in NGS data regardless of sequencing method.     

Using phylogeographic approaches to analyse the dispersal history,velocity and direction of viral lineages — Application to rabies virus spread in Iran

Recent years have seen the extensive use of phylogeographic approaches to unveil the dispersal history of virus epidemics. Spatially explicit reconstructions of viral spread represent valuable sources of lineage movement data that can be exploited to investigate the impact of underlying environmental layers on the dispersal of pathogens. Here, we performed phylogeographic inference and applied different post hoc approaches to analyse a new and comprehensive data set of viral genomes to elucidate the dispersal history and dynamics of rabies virus (RABV) in Iran, which have remained largely unknown. We first analysed the association between environmental factors and variations in dispersal velocity among lineages. Second, we present, test and apply a new approach to study the link between environmental conditions and the dispersal direction of lineages. The statistical performance (power of detection, false‐positive rate) of this new method was assessed using simulations. We performed phylogeographic analyses of RABV genomes, allowing us to describe the large diversity of RABV in Iran and to confirm the cocirculation of several clades in the country. Overall, we estimate a relatively high lineage dispersal velocity, similar to previous estimates for dog rabies virus spread in northern Africa. Finally, we highlight a tendency for RABV lineages to spread in accessible areas associated with high human population density. Our analytical workflow illustrates how phylogeographic approaches can be used to investigate the impact of environmental factors on several aspects of viral dispersal dynamics.     

After the games are over: life‐history trade‐offs drive dispersal attenuation following range expansion

Increased dispersal propensity often evolves on expanding range edges due to the Olympic Village effect, which involves the fastest and fittest finding themselves together in the same place at the same time, mating, and giving rise to like individuals. But what happens after the range's leading edge has passed and the games are over? Although empirical studies indicate that dispersal propensity attenuates following range expansion, hypotheses about the mechanisms driving this attenuation have not been clearly articulated or tested. Here, we used a simple model of the spatiotemporal dynamics of two phenotypes, one fast and the other slow, to propose that dispersal attenuation beyond preexpansion levels is only possible in the presence of trade‐offs between dispersal and life‐history traits. The Olympic Village effect ensures that fast dispersers preempt locations far from the range's previous limits. When trade‐offs are absent, this preemptive spatial advantage has a lasting impact, with highly dispersive individuals attaining equilibrium frequencies that are strictly higher than their introduction frequencies. When trade‐offs are present, dispersal propensity decays rapidly at all locations. Our model's results about the postcolonization trajectory of dispersal evolution are clear and, in principle, should be observable in field studies. We conclude that empirical observations of postcolonization dispersal attenuation offer a novel way to detect the existence of otherwise elusive trade‐offs between dispersal and life‐history traits.     

Testing the role of ecology and life history in structuring genetic variation across a landscape: a trait‐based phylogeographic approach

Hypotheses to explain phylogeographic structure traditionally invoke geographic features, but often fail to provide a general explanation for spatial patterns of genetic variation. Organisms' intrinsic characteristics might play more important roles than landscape features in determining phylogeographic structure. We developed a novel comparative approach to explore the role of ecological and life‐history variables in determining spatial genetic variation and tested it on frog communities in Panama. We quantified spatial genetic variation within 31 anuran species based on mitochondrial DNA sequences, for which hierarchical approximate Bayesian computation analyses rejected simultaneous divergence over a common landscape. Regressing ecological variables, on genetic divergence allowed us to test the importance of individual variables revealing that body size, current landscape resistance, geographic range, biogeographic origin and reproductive mode were significant predictors of spatial genetic variation. Our results support the idea that phylogeographic structure represents the outcome of an interaction between organisms and their environment, and suggest a conceptual integration we refer to as trait‐based phylogeography.     

Enthesopathy formation in the humerus: Data from known age‐at‐death and known occupation skeletal collections

Enthesopathies, in the guise of musculoskeletal skeletal stress markers (MSM), have been widely used to reconstruct activity levels in human skeletal populations. In general, studies have focused on their presence in the upper limb, which is used in the majority of daily activities. The aim of this study was to use some of the attachment sites on the humerus to explore the relationship between enthesopathy formation, activity, and the ageing process. The skeletal sample used in this study comprised male adult skeletons with known age‐at‐death and known occupations from the late‐19th and early‐20th century cemeteries in Portugal. The enthesopathies were recorded as either present or absent. Statistical analysis using Fishers exact tests and logistic regression was undertaken to determine whether associations could be found between specific activities or socioeconomic status (manual or nonmanual workers), and age and enthesopathy presence. Left and right sides were analyzed separately. Fisher's exact tests were used to determine the relationship between activity and enthesopathy, and they demonstrated no association between activity and enthesopathies (P > 0.01). The results of the logistic regression established that age was the single most significant factor in enthesopathy formation (P > 0.05). This study found that, in these samples, age‐at‐death, and therefore age‐related degeneration rather than degeneration caused by activities, was the primary cause of enthesopathy formation. Considering the difficulties of reliably ageing adult human skeletal remains, this is a major issue for studies of activity using enthesopathies. Am J Phys Anthropol, 2010. © 2009 Wiley‐Liss, Inc.     

The predictability and magnitude of life‐history divergence to ecological agents of selection: a meta‐analysis in livebearing fishes

Environments causing variation in age‐specific mortality – ecological agents of selection – mediate the evolution of reproductive life‐history traits. However, the relative magnitude of life‐history divergence across selective agents, whether divergence in response to specific selective agents is consistent across taxa and whether it occurs as predicted by theory, remains largely unexplored. We evaluated divergence in offspring size, offspring number, and the trade‐off between these traits using a meta‐analysis in livebearing fishes (Poeciliidae). Life‐history divergence was consistent and predictable to some (predation, hydrogen sulphide) but not all (density, food limitation, salinity) selective agents. In contrast, magnitudes of divergence among selective agents were similar. Finally, there was a negative, asymmetric relationship between offspring‐number and offspring‐size divergence, suggesting greater costs of increasing offspring size than number. Ultimately, these results provide strong evidence for predictable and consistent patterns of reproductive life‐history divergence and highlight the importance of comparing phenotypic divergence across species and ecological selective agents.     

ABC inference of multi‐population divergence with admixture from unphased population genomic data

Rapidly developing sequencing technologies and declining costs have made it possible to collect genome‐scale data from population‐level samples in nonmodel systems. Inferential tools for historical demography given these data sets are, at present, underdeveloped. In particular, approximate Bayesian computation (ABC) has yet to be widely embraced by researchers generating these data. Here, we demonstrate the promise of ABC for analysis of the large data sets that are now attainable from nonmodel taxa through current genomic sequencing technologies. We develop and test an ABC framework for model selection and parameter estimation, given histories of three‐population divergence with admixture. We then explore different sampling regimes to illustrate how sampling more loci, longer loci or more individuals affects the quality of model selection and parameter estimation in this ABC framework. Our results show that inferences improved substantially with increases in the number and/or length of sequenced loci, while less benefit was gained by sampling large numbers of individuals. Optimal sampling strategies given our inferential models included at least 2000 loci, each approximately 2 kb in length, sampled from five diploid individuals per population, although specific strategies are model and question dependent. We tested our ABC approach through simulation‐based cross‐validations and illustrate its application using previously analysed data from the oak gall wasp, Biorhiza pallida.