Measuring individual inbreeding in the age of genomics: marker-based measures are better than pedigrees.

Inbreeding (mating between relatives) can dramatically reduce the fitness of offspring by causing parts of the genome to be identical by descent. Thus, measuring individual inbreeding is crucial for ecology, evolution and conservation biology. We used computer simulations to test whether the realized proportion of the genome that is identical by descent (IBDG) is predicted better by the pedigree inbreeding coefficient (FP) or by genomic (marker-based) measures of inbreeding. Genomic estimators of IBDG included the increase in individual homozygosity relative to mean Hardy-Weinberg expected homozygosity (FH), and two measures (FROH and FE) that use mapped genetic markers to estimate IBDG. IBDG was more strongly correlated with FH, FE and FROH than with FP across a broad range of simulated scenarios when thousands of SNPs were used. For example, IBDG was more strongly correlated with FROH, FH and FE (estimated with ⩾10 000 SNPs) than with FP (estimated with 20 generations of complete pedigree) in populations with a recent reduction in the effective populations size (from Ne=500 to Ne=75). FROH, FH and FE generally explained >90% of the variance in IBDG (among individuals) when 35 K or more SNPs were used. FP explained <80% of the variation in IBDG on average in all simulated scenarios, even when pedigrees included 20 generations. Our results demonstrate that IBDG can be more precisely estimated with large numbers of genetic markers than with pedigrees. We encourage researchers to adopt genomic marker-based measures of IBDG as thousands of loci can now be genotyped in any species.

Combining demographic and genetic factors to assess population vulnerability in stream species.

Accelerating climate change and other cumulative stressors create an urgent need to understand the influence of environmental variation and landscape features on the connectivity and vulnerability of freshwater species. Here, we introduce a novel modeling framework for aquatic systems that integrates spatially explicit, individual-based, demographic and genetic (demogenetic) assessments with environmental variables. To show its potential utility, we simulated a hypothetical network of 19 migratory riverine populations (e.g., salmonids) using a riverscape connectivity and demogenetic model (CDFISH). We assessed how stream resistance to movement (a function of water temperature, fluvial distance, and physical barriers) might influence demogenetic connectivity, and hence, population vulnerability. We present demographic metrics (abundance, immigration, and change in abundance) and genetic metrics (diversity, differentiation, and change in differentiation), and combine them into a single vulnerability index for identifying populations at risk of extirpation. We considered four realistic scenarios that illustrate the relative sensitivity of these metrics for early detection of reduced connectivity: (1) maximum resistance due to high water temperatures throughout the network, (2) minimum resistance due to low water temperatures throughout the network, (3) increased resistance at a tributary junction caused by a partial barrier, and (4) complete isolation of a tributary, leaving resident individuals only. We then applied this demogenetic framework using empirical data for a bull trout (Salvelinus confluentus) metapopulation in the upper Flathead River system, Canada and USA, to assess how current and predicted future stream warming may influence population vulnerability. Results suggest that warmer water temperatures and associated barriers to movement (e.g., low flows, dewatering) are predicted to fragment suitable habitat for migratory salmonids, resulting in the loss of genetic diversity and reduced numbers in certain vulnerable populations. This demogenetic simulation framework, which is illustrated in a web-based interactive mapping prototype, should be useful for evaluating population vulnerability in a wide variety of dendritic and fragmented riverscapes, helping to guide conservation and management efforts for freshwater species.

An ecological perspective on Brucella abortus in the western United States.

After a hiatus during the 1990s, outbreaks of Brucella abortus in cattle are occurring more frequently in some of the western states of the United States, namely, Montana, Wyoming and Idaho. This increase is coincidentwith increasing brucellosis seroprevalence in elk (Cervus elaphus), which is correlated with elk density. Vaccines are a seductive solution, but their use in wildlife systems remains limited by logistical, financial, and scientific constraints. Cattle vaccination is ongoing in the region. Livestock regulations, however, tend to be based on serological tests that test for previous exposure and available vaccines do not protect against seroconversion. The authors review recent ecological studies of brucellosis, with particular emphasis on the Greater Yellowstone Area, and highlight the management options and implications of this work, including the potential utility of habitat modifications and targeted hunts, as well as scavengers and predators. Finally, the authors discuss future research directions that will help us to understand and manage brucellosis in wildlife.

Why replication is important in landscape genetics: American black bear in the Rocky Mountains.

We investigated how landscape features influence gene flow of black bears by testing the relative support for 36 alternative landscape resistance hypotheses, including isolation by distance (IBD) in each of 12 study areas in the north central U.S. Rocky Mountains. The study areas all contained the same basic elements, but differed in extent of forest fragmentation, altitude, variation in elevation and road coverage. In all but one of the study areas, isolation by landscape resistance was more supported than IBD suggesting gene flow is likely influenced by elevation, forest cover, and roads. However, the landscape features influencing gene flow varied among study areas. Using subsets of loci usually gave models with the very similar landscape features influencing gene flow as with all loci, suggesting the landscape features influencing gene flow were correctly identified. To test if the cause of the variability of supported landscape features in study areas resulted from landscape differences among study areas, we conducted a limiting factor analysis. We found that features were supported in landscape models only when the features were highly variable. This is perhaps not surprising but suggests an important cautionary note - that if landscape features are not found to influence gene flow, researchers should not automatically conclude that the features are unimportant to the species' movement and gene flow. Failure to investigate multiple study areas that have a range of variability in landscape features could cause misleading inferences about which landscape features generally limit gene flow. This could lead to potentially erroneous identification of corridors and barriers if models are transferred between areas with different landscape characteristics.

Testing a Generalizable Machine Learning Workflow for Aquatic Invasive Species on Rainbow Trout (Oncorhynchus mykiss) in Northwest Montana.

Biological invasions are accelerating worldwide, causing major ecological and economic impacts in aquatic ecosystems. The urgent decision-making needs of invasive species managers can be better met by the integration of biodiversity big data with large-domain models and data-driven products. Remotely sensed data products can be combined with existing invasive species occurrence data via machine learning models to provide the proactive spatial risk analysis necessary for implementing coordinated and agile management paradigms across large scales. We present a workflow that generates rapid spatial risk assessments on aquatic invasive species using occurrence data, spatially explicit environmental data, and an ensemble approach to species distribution modeling using five machine learning algorithms. For proof of concept and validation, we tested this workflow using extensive spatial and temporal hybridization and occurrence data from a well-studied, ongoing, and climate-driven species invasion in the upper Flathead River system in northwestern Montana, USA. Rainbow Trout (RBT; Oncorhynchus mykiss), an introduced species in the Flathead River basin, compete and readily hybridize with native Westslope Cutthroat Trout (WCT; O. clarkii lewisii), and the spread of RBT individuals and their alleles has been tracked for decades. We used remotely sensed and other geospatial data as key environmental predictors for projecting resultant habitat suitability to geographic space. The ensemble modeling technique yielded high accuracy predictions relative to 30-fold cross-validated datasets (87% 30-fold cross-validated accuracy score). Both top predictors and model performance relative to these predictors matched current understanding of the drivers of RBT invasion and habitat suitability, indicating that temperature is a major factor influencing the spread of invasive RBT and hybridization with native WCT. The congruence between more time-consuming modeling approaches and our rapid machine-learning approach suggest that this workflow could be applied more broadly to provide data-driven management information for early detection of potential invaders.

Quantifying the lag time to detect barriers in landscape genetics.

Understanding how spatial genetic patterns respond to landscape change is crucial for advancing the emerging field of landscape genetics. We quantified the number of generations for new landscape barrier signatures to become detectable and for old signatures to disappear after barrier removal. We used spatially explicit, individual-based simulations to examine the ability of an individual-based statistic [Mantel's r using the proportion of shared alleles' statistic (Dps)] and population-based statistic (FST ) to detect barriers. We simulated a range of movement strategies including nearest neighbour dispersal, long-distance dispersal and panmixia. The lag time for the signal of a new barrier to become established is short using Mantel's r (1-15 generations). FST required approximately 200 generations to reach 50% of its equilibrium maximum, although G'ST performed much like Mantel's r. In strong contrast, FST and Mantel's r perform similarly following the removal of a barrier formerly dividing a population. Also, given neighbour mating and very short-distance dispersal strategies, historical discontinuities from more than 100 generations ago might still be detectable with either method. This suggests that historical events and landscapes could have long-term effects that confound inferences about the impacts of current landscape features on gene flow for species with very little long-distance dispersal. Nonetheless, populations of organisms with relatively large dispersal distances will lose the signal of a former barrier within less than 15 generations, suggesting that individual-based landscape genetic approaches can improve our ability to measure effects of existing landscape features on genetic structure and connectivity.

Probable causes of increasing brucellosis in free-ranging elk of the Greater Yellowstone Ecosystem.

While many wildlife species are threatened, some populations have recovered from previous overexploitation, and data linking these population increases with disease dynamics are limited. We present data suggesting that free-ranging elk (Cervus elaphus) are a maintenance host for Brucella abortus in new areas of the Greater Yellowstone Ecosystem (GYE). Brucellosis seroprevalence in free-ranging elk increased from 0-7% in 1991-1992 to 8-20% in 2006-2007 in four of six herd units around the GYE. These levels of brucellosis are comparable to some herd units where elk are artificially aggregated on supplemental feeding grounds. There are several possible mechanisms for this increase that we evaluated using statistical and population modeling approaches. Simulations of an age-structured population model suggest that the observed levels of seroprevalence are unlikely to be sustained by dispersal from supplemental feeding areas with relatively high seroprevalence or an older age structure. Increases in brucellosis seroprevalence and the total elk population size in areas with feeding grounds have not been statistically detectable. Meanwhile, the rate of seroprevalence increase outside the feeding grounds was related to the population size and density of each herd unit. Therefore, the data suggest that enhanced elk-to-elk transmission in free-ranging populations may be occurring due to larger winter elk aggregations. Elk populations inside and outside of the GYE that traditionally did not maintain brucellosis may now be at risk due to recent population increases. In particular, some neighboring populations of Montana elk were 5-9 times larger in 2007 than in the 1970s, with some aggregations comparable to the Wyoming feeding-ground populations. Addressing the unintended consequences of these increasing populations is complicated by limited hunter access to private lands, which places many ungulate populations out of administrative control. Agency-landowner hunting access partnerships and the protection of large predators are two management strategies that may be used to target high ungulate densities in private refuges and reduce the current and future burden of disease.

MODELER4SIMCOAL2: a user-friendly, extensible modeler of demography and linked loci for coalescent simulations.

UNLABELLED: MODELER4SIMCOAL2 (M4S2) is an extensible graphical tool to model linked loci and population demographies. M4S2 is easy to use, allowing for the modeling of complicated scenarios, making coalescent simulation modeling accessible to biologists with limited computer skills. The software includes an extension system allowing for new models to be created, published and downloaded from the Internet. AVAILABILITY: M4S2 is available from http://popgen.eu/soft/m4s2 under a GPL license. The web site also contains guides, screen shots and tutorials.

Short communication: new alleles of the bovine kappa-casein gene revealed by resequencing and haplotype inference analysis.

We tested the hypothesis that extensive undiscovered genetic diversity exists in important functional genes from domestic and wild cattle species (Bos spp.). We resequenced 483 bp of a key exon (exon IV) from the kappa (kappa)-casein gene (CSN3) for a panel of samples of domestic cattle from 8 countries and a close relative species, the gayal (Bos frontalis). Six single nucleotide polymorphisms were identified. Haplotype inference revealed 12 haplotypes, of which 8 were newly discovered. Among these 8 new haplotypes, 5 differed by one nonsynonymous mutation and 3 differed by one silent mutation from previously well-characterized CSN3 alleles. From those, one was shared by the gayal and Zebu, was different from CSN3*B at position Ile136Thr, and showed a close phylogenetic relationship with the banteng, gaur, and yak. The other 7 new haplotypes were detected in our panel of worldwide local cattle breeds but were absent from previously reported commercial breeds. These results support the hypothesis that genetic diversity at the coding region of CSN3 has been underestimated. This study also highlights how important it is to resequence functionally important genes in worldwide local cattle breeds, many of which are threatened by extinction or replacement by commercial breeds.

Assessment of population structure by single nucleotide polymorphisms (SNPs) in goat breeds.

Single nucleotide polymorphisms (SNPs) may be used in biodiversity studies and commercial tasks like traceability, paternity testing and selection for suitable genotypes. Twenty-seven SNPs were characterized and genotyped on 250 individuals belonging to eight Italian goat breeds. Multilocus genotype data were used to infer population structure and assign individuals to populations. To estimate the number of groups (K) to test in population structure analysis we used likelihood values and variance of the bootstrap samples, deriving optimal K from a drop in the likelihood and a rise in the variance plots against K.

Estimating the effective number of breeders from heterozygote excess in progeny.

The heterozygote-excess method is a recently published method for estimating the effective population size (Ne). It is based on the following principle: When the effective number of breeders (Neb) in a population is small, the allele frequencies will (by chance) be different in males and females, which causes an excess of heterozygotes in the progeny with respect to Hardy-Weinberg equilibrium expectations. We evaluate the accuracy and precision of the heterozygote-excess method using empirical and simulated data sets from polygamous, polygynous, and monogamous mating systems and by using realistic sample sizes of individuals (15-120) and loci (5-30) with varying levels of polymorphism. The method gave nearly unbiased estimates of Neb under all three mating systems. However, the confidence intervals on the point estimates of Neb were sufficiently small (and hence the heterozygote-excess method useful) only in polygamous and polygynous populations that were produced by <10 effective breeders, unless samples included > approximately 60 individuals and 20 multiallelic loci.

Description and power analysis of two tests for detecting recent population bottlenecks from allele frequency data.

When a population experiences a reduction of its effective size, it generally develops a heterozygosity excess at selectively neutral loci, i.e., the heterozygosity computed from a sample of genes is larger than the heterozygosity expected from the number of alleles found in the sample if the population were at mutation drift equilibrium. The heterozygosity excess persists only a certain number of generations until a new equilibrium is established. Two statistical tests for detecting a heterozygosity excess are described. They require measurements of the number of alleles and heterozygosity at each of several loci from a population sample. The first test determines if the proportion of loci with heterozygosity excess is significantly larger than expected at equilibrium. The second test establishes if the average of standardized differences between observed and expected heterozygosities is significantly different from zero. Type I and II errors have been evaluated by computer simulations, varying sample size, number of loci, bottleneck size, time elapsed since the beginning of the bottleneck and level of variability of loci. These analyses show that the most useful markers for bottleneck detection are those evolving under the infinite allele model (IAM) and they provide guidelines for selecting sample sizes of individuals and loci. The usefulness of these tests for conservation biology is discussed.

New methods employing multilocus genotypes to select or exclude populations as origins of individuals.

A new method for assigning individuals of unknown origin to populations, based on the genetic distance between individuals and populations, was compared to two existing methods based on the likelihood of multilocus genotypes. The distribution of the assignment criterion (genetic distance or genotype likelihood) for individuals of a given population was used to define the probability that an individual belongs to the population. Using this definition, it becomes possible to exclude a population as the origin of an individual, a useful extension of the currently available assignment methods. Using simulated data based on the coalescent process, the different methods were evaluated, varying the time of divergence of populations, the mutation model, the sample size, and the number of loci. Likelihood-based methods (especially the Bayesian method) always performed better than distance methods. Other things being equal, genetic markers were always more efficient when evolving under the infinite allele model than under the stepwise mutation model, even for equal values of the differentiation parameter F(st). Using the Bayesian method, a 100% correct assignment rate can be achieved by scoring ca. 10 microsatellite loci (H approximately 0.6) on 30-50 individuals from each of 10 populations when the F(st) is near 0.1.

Genetic diversity and assignment tests among seven French cattle breeds based on microsatellite DNA analysis.

Genetic variability and relationships among six native French cattle breeds (Abondance, Tarentaise, Villard de Lans, Montbéliarde, Limousin, and Charolais) and one foreign breed (Holstein) were investigated using 23 microsatellite markers. These breeds were also compared with four Swiss breeds genotyped in a previously published study. Interestingly, the French alpine breeds have smaller population sizes but showed higher genetic variability than the larger Holstein breed. Neighbor-joining trees and PCA (principal components analysis) showed that alpine breeds tend to cluster together. Abondance and Tarentaise breeds were closely related, whereas the Holstein was highly differentiated from all breeds analyzed. Two different assignment tests for determining the breed of origin of individuals were compared: "direct" and "exclusion-simulation" approaches. The exclusion-simulation significance test correctly assigns fewer individuals than the direct approach but provides a confidence level (e.g., P < 0.01) for each individual being assigned. Accurate assignment with high statistical confidence is required for animal traceability. Unfortunately, the accuracy of assignment greatly decreases as the threshold level of confidence of assignment increases (e.g., from P < 0.05 to P < 0.001). Assignment accuracy also greatly declines as the level of population differentiation decreases below the level often found between related breeds (e.g., F(ST) < 0.1).

Development and evaluation of 200 novel SNP assays for population genetic studies of westslope cutthroat trout and genetic identification of related taxa.

DNA sequence data were collected and screened for single nucleotide polymorphisms (SNPs) in westslope cutthroat trout (Oncorhynchus clarki lewisi) and also for substitutions that could be used to genetically discriminate rainbow trout (O. mykiss) and cutthroat trout, as well as several cutthroat trout subspecies. In total, 260 expressed sequence tag-derived loci were sequenced and allelic discrimination genotyping assays developed from 217 of the variable sites. Another 50 putative SNPs in westslope cutthroat trout were identified by restriction-site-associated DNA sequencing, and seven of these were developed into assays. Twelve O. mykiss SNP assays that were variable within westslope cutthroat trout and 12 previously published SNP assays were also included in downstream testing. A total of 241 assays were tested on six westslope cutthroat trout populations (N = 32 per population), as well as collections of four other cutthroat trout subspecies and a population of rainbow trout. All assays were evaluated for reliability and deviation from Hardy-Weinberg and linkage equilibria. Poorly performing and duplicate assays were removed from the data set, and the remaining 200 assays were used in tests of population differentiation. The remaining markers easily distinguished the various subspecies tested, as evidenced by mean G(ST) of 0.74. A smaller subset of the markers (N = 86; average G(ST) = 0.40) was useful for distinguishing the six populations of westslope cutthroat trout. This study increases by an order of magnitude the number of genetic markers available for the study of westslope cutthroat trout and closely related taxa and includes many markers in genes (developed from ESTs).

Relationships between migration rates and landscape resistance assessed using individual-based simulations.

Linking landscape effects on gene flow to processes such as dispersal and mating is essential to provide a conceptual foundation for landscape genetics. It is particularly important to determine how classical population genetic models relate to recent individual-based landscape genetic models when assessing individual movement and its influence on population genetic structure. We used classical Wright-Fisher models and spatially explicit, individual-based, landscape genetic models to simulate gene flow via dispersal and mating in a series of landscapes representing two patches of habitat separated by a barrier. We developed a mathematical formula that predicts the relationship between barrier strength (i.e., permeability) and the migration rate (m) across the barrier, thereby linking spatially explicit landscape genetics to classical population genetics theory. We then assessed the reliability of the function by obtaining population genetics parameters (m, F(ST) ) using simulations for both spatially explicit and Wright-Fisher simulation models for a range of gene flow rates. Next, we show that relaxing some of the assumptions of the Wright-Fisher model can substantially change population substructure (i.e., F(ST) ). For example, isolation by distance among individuals on each side of a barrier maintains an F(ST) of ∼0.20 regardless of migration rate across the barrier, whereas panmixia on each side of the barrier results in an F(ST) that changes with m as predicted by classical population genetics theory. We suggest that individual-based, spatially explicit modelling provides a general framework to investigate how interactions between movement and landscape resistance drive population genetic patterns and connectivity across complex landscapes.

A new individual-based spatial approach for identifying genetic discontinuities in natural populations.

The population concept is central in evolutionary and conservation biology, but identifying the boundaries of natural populations is often challenging. Here, we present a new approach for assessing spatial genetic structure without the a priori assumptions on the locations of populations made by adopting an individual-centred approach. Our method is based on assignment tests applied in a moving window over an extensively sampled study area. For each individual, a spatially explicit probability surface is constructed, showing the estimated probability of finding its multilocus genotype across the landscape, and identifying putative migrants. Population boundaries are localized by estimating the mean slope of these probability surfaces over all individuals to identify areas with genetic discontinuities. The significance of the genetic discontinuities is assessed by permutation tests. This new approach has the potential to reveal cryptic population structure and to improve our ability to understand gene flow dynamics across landscapes. We illustrate our approach by simulations and by analysing two empirical datasets: microsatellite data of Ursus arctos in Scandinavia, and amplified fragment length polymorphism (AFLP) data of Rhododendron ferrugineum in the Alps.

Estimating the probability of identity among genotypes in natural populations: cautions and guidelines.

Individual identification using DNA fingerprinting methods is emerging as a critical tool in conservation genetics and molecular ecology. Statistical methods that estimate the probability of sampling identical genotypes using theoretical equations generally assume random associations between alleles within and among loci. These calculations are probably inaccurate for many animal and plant populations due to population substructure. We evaluated the accuracy of a probability of identity (P(ID)) estimation by comparing the observed and expected P(ID), using large nuclear DNA microsatellite data sets from three endangered species: the grey wolf (Canis lupus), the brown bear (Ursus arctos), and the Australian northern hairy-nosed wombat (Lasiorinyus krefftii). The theoretical estimates of P(ID) were consistently lower than the observed P(ID), and can differ by as much as three orders of magnitude. To help researchers and managers avoid potential problems associated with this bias, we introduce an equation for P(ID) between sibs. This equation provides an estimator that can be used as a conservative upper bound for the probability of observing identical multilocus genotypes between two individuals sampled from a population. We suggest computing the actual observed P(ID) when possible and give general guidelines for the number of codominant and dominant marker loci required to achieve a reasonably low P(ID) (e.g. 0.01-0.0001).

Noninvasive genetic sampling: look before you leap.

Noninvasive sampling allows genetic studies of free-ranging animals without the need to capture or even observe them, and thus allows questions to be addressed that cannot be answered using conventional methods. Initially, this sampling strategy promised to exploit fully the existing DNA-based technology for studies in ethology, conservation biology and population genetics. However, recent work now indicates the need for a more cautious approach, which includes quantifying the genotyping error rate. Despite this, many of the difficulties of noninvasive sampling will probably be overcome with improved methodology.

Power of 22 microsatellite markers in fluorescent multiplexes for parentage testing in goats (Capra hircus).

Two multiplex systems, each containing 11 microsatellite loci, were developed for semiautomated parentage testing in goats. Eight of the loci originate from goats, nine from cattle and five from sheep. Eighteen of the loci have been mapped to 16 different autosomes (in goats and cattle). Parentage exclusion probabilities were computed from allele frequencies in approximately 30 unrelated individuals from each of four economically important breeds: Mongolian Native Cashmere, Turkish Angora, Swiss Saanen, and Spanish Murciana-Grenadina. In cases where genotypes are known for one parent and an offspring, the 22 markers will exclude an (erroneously) alleged parent with a probability of > 0.999999 in the cashmere breed, > 0.99999 in Angora and Murciana-Grenadina, and > 0.9999 in Saanen. The multiplexes provide very high power for individual identification as the probability of finding two identical genotypes for the 22 loci is < 1 in 1.10(15) in each of the four breeds. The multiplexes will also be useful for studies of population structure, history, and diversity in goats and also in wild Capra species that represent important resources for genetic improvement of domestic breeds.