SNPs in ecological and conservation studies: a test in the Scandinavian wolf population

Genome-wide identification and characterization of microsatellite markers in Bactrian Camel

Simple sequence repeats (SSRs) have been widely used for parentage testing, marker-assisted selection, and evolutionary studies. The insufficient availability of SSR markers in Bactrian camels partially accounts for the lack of systematic breeding. Therefore, we aimed to establish a comprehensive SSR dataset for the Bactrian camel. Our approach involved genome searching to locate every SSR in the genome, SSR-enriched sequencing to acquire polymorphism information, and literature research to collect published data. The resulting dataset contains 213,711 SSRs and details their characteristics, including genome coordinates, motifs, lengths, annotations, PCR primers, and polymorphism information. The dataset reveals a biased distribution of SSRs in the Bactrian camel genome, reflecting the mutation mechanism and complex evolution of SSRs. In practice, we successfully demonstrated the utility of the dataset through parentage testing using 15 randomly selected SSRs. This comprehensive dataset can facilitate systematic breeding and enable QTL mapping and GWAS of the Bactrian camel.

African wild dogs (Lycaon pictus) from the Kruger National Park, South Africa are currently not inbred but have low genomic diversity

African wild dogs (Lycaon pictus) have undergone severe population reductions and are listed as endangered on the International Union for Conservation of Nature Red List. Small, isolated populations have the potential to suffer from threats to their genetic diversity that may impact species viability and future survival. This study provides the first set of population-wide genomic data to address conservation concerns for this endangered species. Whole genome sequencing data were generated for 71 free-ranging African wild dogs from the Kruger National Park (KNP), South Africa, and used to estimate important population genomic parameters. Genomic diversity metrics revealed that variation levels were low; however, this African wild dog population showed low levels of inbreeding. Very few first- and second-order relationships were observed in this cohort, with most relationships falling into the third-order or distant category. Patterns of homozygosity could have resulted from historical inbreeding or a loss in genome variation due to a population bottleneck. Although the results suggest that this stronghold African wild dog population maintains low levels of inbreeding, likely due to their cooperative breeding system, it may lead to a continuous population decline when a reduced number of suitable mates are available. Consequently, the low genomic variation may influence species viability over time. This study highlights the importance of assessing population genomic parameters to set conservation priorities. Future studies should include the investigation of the potential of this endangered species to adapt to environmental changes considering the low genomic diversity in this population.

Waste not, want not: Microsatellites remain an economical and informative technology for conservation genetics

Comparisons of microsatellites and single-nucleotide polymorphisms (SNPs) have found that SNPs outperform microsatellites in population genetic analyses, questioning the continued utility of microsatellites in population and landscape genetics. Yet, highly polymorphic markers may be of value in species that have reduced genetic variation. This study repeated previous analyses that used microsatellites with SNPs developed from ddRAD sequencing in the black-capped vireo source-sink system. SNPs provided greater resolution of genetic diversity, population differentiation, and migrant detection but could not reconstruct parentage relationships due to insufficient heterozygosities. The biological inferences made by both sets of markers were similar: asymmetrical gene flow from source sites to the remaining sink sites. With the landscape genetic analyses, we found different results between the two molecular markers, but associations of the top environmental features (riparian, open habitat, agriculture, and human development) with dispersal estimates were shared between marker types. Despite the higher precision of SNPs, we find that microsatellites effectively uncover population processes and patterns and are superior for parentage analyses in this species with reduced genetic diversity. This study illustrates the continued applicability and relevance of microsatellites in population genetic research.

Achievements and Challenges of Genomics-Assisted Breeding in Forest Trees: From Marker-Assisted Selection to Genome Editing

Forest tree breeding efforts have focused mainly on improving traits of economic importance, selecting trees suited to new environments or generating trees that are more resilient to biotic and abiotic stressors. This review describes various methods of forest tree selection assisted by genomics and the main technological challenges and achievements in research at the genomic level. Due to the long rotation time of a forest plantation and the resulting long generation times necessary to complete a breeding cycle, the use of advanced techniques with traditional breeding have been necessary, allowing the use of more precise methods for determining the genetic architecture of traits of interest, such as genome-wide association studies (GWASs) and genomic selection (GS). In this sense, main factors that determine the accuracy of genomic prediction models are also addressed. In turn, the introduction of genome editing opens the door to new possibilities in forest trees and especially clustered regularly interspaced short palindromic repeats and CRISPR-associated protein 9 (CRISPR/Cas9). It is a highly efficient and effective genome editing technique that has been used to effectively implement targetable changes at specific places in the genome of a forest tree. In this sense, forest trees still lack a transformation method and an inefficient number of genotypes for CRISPR/Cas9. This challenge could be addressed with the use of the newly developing technique GRF-GIF with speed breeding.

Low cost, low tech SNP genotyping tools for resource-limited areas: Plague in Madagascar as a model

BACKGROUND

Genetic analysis of pathogenic organisms is a useful tool for linking human cases together and/or to potential environmental sources. The resulting data can also provide information on evolutionary patterns within a targeted species and phenotypic traits. However, the instruments often used to generate genotyping data, such as single nucleotide polymorphisms (SNPs), can be expensive and sometimes require advanced technologies to implement. This places many genotyping tools out of reach for laboratories that do not specialize in genetic studies and/or lack the requisite financial and technological resources. To address this issue, we developed a low cost and low tech genotyping system, termed agarose-MAMA, which combines traditional PCR and agarose gel electrophoresis to target phylogenetically informative SNPs.

METHODOLOGY/PRINCIPAL FINDINGS

To demonstrate the utility of this approach for generating genotype data in a resource-constrained area (Madagascar), we designed an agarose-MAMA system targeting previously characterized SNPs within Yersinia pestis, the causative agent of plague. We then used this system to genetically type pathogenic strains of Y. pestis in a Malagasy laboratory not specialized in genetic studies, the Institut Pasteur de Madagascar (IPM). We conducted rigorous assay performance validations to assess potential variation introduced by differing research facilities, reagents, and personnel and found no difference in SNP genotyping results. These agarose-MAMA PCR assays are currently employed as an investigative tool at IPM, providing Malagasy researchers a means to improve the value of their plague epidemiological investigations by linking outbreaks to potential sources through genetic characterization of isolates and to improve understanding of disease ecology that may contribute to a long-term control effort.

CONCLUSIONS

The success of our study demonstrates that the SNP-based genotyping capacity of laboratories in developing countries can be expanded with manageable financial cost for resource constraint laboratories. This is a practical formula that reduces resource-driven limitations to genetic research and promises to advance global collective knowledge of infectious diseases emanating from resource limited regions of the world.

Fast and cost-effective single nucleotide polymorphism (SNP) detection in the absence of a reference genome using semideep next-generation Random Amplicon Sequencing (RAMseq)

Biodiversity has suffered a dramatic global decline during the past decades, and monitoring tools are urgently needed providing data for the development and evaluation of conservation efforts both on a species and on a genetic level. However, in wild species, the assessment of genetic diversity is often hampered by the lack of suitable genetic markers. In this article, we present Random Amplicon Sequencing (RAMseq), a novel approach for fast and cost-effective detection of single nucleotide polymorphisms (SNPs) in nonmodel species by semideep sequencing of random amplicons. By applying RAMseq to the Eurasian otter (Lutra lutra), we identified 238 putative SNPs after quality filtering of all candidate loci and were able to validate 32 of 77 loci tested. In a second step, we evaluated the genotyping performance of these SNP loci in noninvasive samples, one of the most challenging genotyping applications, by comparing it with genotyping results of the same faecal samples at microsatellite markers. We compared (i) polymerase chain reaction (PCR) success rate, (ii) genotyping errors and (iii) Mendelian inheritance (population parameters). SNPs produced a significantly higher PCR success rate (75.5% vs. 65.1%) and lower mean allelic error rate (8.8% vs. 13.3%) than microsatellites, but showed a higher allelic dropout rate (29.7% vs. 19.8%). Genotyping results showed no deviations from Mendelian inheritance in any of the SNP loci. Hence, RAMseq appears to be a valuable tool for the detection of genetic markers in nonmodel species, which is a common challenge in conservation genetic studies.

Assessing SNP genotyping of noninvasively collected wildlife samples using microfluidic arrays

Noninvasively collected samples are a common source of DNA in wildlife genetic studies. Currently, single nucleotide polymorphism (SNP) genotyping using microfluidic arrays is emerging as an easy-to-use and cost-effective methodology. Here we assessed the performance of microfluidic SNP arrays in genotyping noninvasive samples from grey wolves, European wildcats and brown bears, and we compared results with traditional microsatellite genotyping. We successfully SNP-genotyped 87%, 80% and 97% of the wolf, cat and bear samples, respectively. Genotype recovery was higher based on SNPs, while both marker types identified the same individuals and provided almost identical estimates of pairwise differentiation. We found that samples for which all SNP loci were scored had no disagreements across the three replicates (except one locus in a wolf sample). Thus, we argue that call rate (amplification success) can be used as a proxy for genotype quality, allowing the reduction of replication effort when call rate is high. Furthermore, we used cycle threshold values of real-time PCR to guide the choice of protocols for SNP amplification. Finally, we provide general guidelines for successful SNP genotyping of degraded DNA using microfluidic technology.

Novel efficient genome-wide SNP panels for the conservation of the highly endangered Iberian lynx

BACKGROUND

The Iberian lynx (Lynx pardinus) has been acknowledged as the most endangered felid species in the world. An intense contraction and fragmentation during the twentieth century left less than 100 individuals split in two isolated and genetically eroded populations by 2002. Genetic monitoring and management so far have been based on 36 STRs, but their limited variability and the more complex situation of current populations demand more efficient molecular markers. The recent characterization of the Iberian lynx genome identified more than 1.6 million SNPs, of which 1536 were selected and genotyped in an extended Iberian lynx sample.

METHODS

We validated 1492 SNPs and analysed their heterozygosity, Hardy-Weinberg equilibrium, and linkage disequilibrium. We then selected a panel of 343 minimally linked autosomal SNPs from which we extracted subsets optimized for four different typical tasks in conservation applications: individual identification, parentage assignment, relatedness estimation, and admixture classification, and compared their power to currently used STR panels.

RESULTS

We ascribed 21 SNPs to chromosome X based on their segregation patterns, and identified one additional marker that showed significant differentiation between sexes. For all applications considered, panels of autosomal SNPs showed higher power than the currently used STR set with only a very modest increase in the number of markers.

CONCLUSIONS

These novel panels of highly informative genome-wide SNPs provide more powerful, efficient, and flexible tools for the genetic management and non-invasive monitoring of Iberian lynx populations. This example highlights an important outcome of whole-genome studies in genetically threatened species.

Assessing polar bear (Ursus maritimus) population structure in the Hudson Bay region using SNPs

Defining subpopulations using genetics has traditionally used data from microsatellite markers to investigate population structure; however, single‐nucleotide polymorphisms (SNPs) have emerged as a tool for detection of fine‐scale structure. In Hudson Bay, Canada, three polar bear (Ursus maritimus) subpopulations (Foxe Basin (FB), Southern Hudson Bay (SH), and Western Hudson Bay (WH)) have been delineated based on mark–recapture studies, radiotelemetry and satellite telemetry, return of marked animals in the subsistence harvest, and population genetics using microsatellites. We used SNPs to detect fine‐scale population structure in polar bears from the Hudson Bay region and compared our results to the current designations using 414 individuals genotyped at 2,603 SNPs. Analyses based on discriminant analysis of principal components (DAPC) and STRUCTURE support the presence of four genetic clusters: (i) Western—including individuals sampled in WH, SH (excluding Akimiski Island in James Bay), and southern FB (south of Southampton Island); (ii) Northern—individuals sampled in northern FB (Baffin Island) and Davis Strait (DS) (Labrador coast); (iii) Southeast—individuals from SH (Akimiski Island in James Bay); and (iv) Northeast—individuals from DS (Baffin Island). Population structure differed from microsatellite studies and current management designations demonstrating the value of using SNPs for fine‐scale population delineation in polar bears.

Wolf population genetics in Europe: a systematic review, meta-analysis and suggestions for conservation and management

The grey wolf (Canis lupus) is an iconic large carnivore that has increasingly been recognized as an apex predator with intrinsic value and a keystone species. However, wolves have also long represented a primary source of human-carnivore conflict, which has led to long-term persecution of wolves, resulting in a significant decrease in their numbers, genetic diversity and gene flow between populations. For more effective protection and management of wolf populations in Europe, robust scientific evidence is crucial. This review serves as an analytical summary of the main findings from wolf population genetic studies in Europe, covering major studies from the 'pre-genomic era' and the first insights of the 'genomics era'. We analyse, summarize and discuss findings derived from analyses of three compartments of the mammalian genome with different inheritance modes: maternal (mitochondrial DNA), paternal (Y chromosome) and biparental [autosomal microsatellites and single nucleotide polymorphisms (SNPs)]. To describe large-scale trends and patterns of genetic variation in European wolf populations, we conducted a meta-analysis based on the results of previous microsatellite studies and also included new data, covering all 19 European countries for which wolf genetic information is available: Norway, Sweden, Finland, Estonia, Latvia, Lithuania, Poland, Czech Republic, Slovakia, Germany, Belarus, Russia, Italy, Croatia, Bulgaria, Bosnia and Herzegovina, Greece, Spain and Portugal. We compared different indices of genetic diversity in wolf populations and found a significant spatial trend in heterozygosity across Europe from south-west (lowest genetic diversity) to north-east (highest). The range of spatial autocorrelation calculated on the basis of three characteristics of genetic diversity was 650-850 km, suggesting that the genetic diversity of a given wolf population can be influenced by populations up to 850 km away. As an important outcome of this synthesis, we discuss the most pressing issues threatening wolf populations in Europe, highlight important gaps in current knowledge, suggest solutions to overcome these limitations, and provide recommendations for science-based wolf conservation and management at regional and Europe-wide scales.

A New Panel of SNP Markers for the Individual Identification of North American Pumas

Pumas Puma concolor are one of the most studied terrestrial carnivores because of their widespread distribution, substantial ecological impacts, and conflicts with humans. Over the past decade, managing pumas has involved extensive efforts including the use of genetic methods. Microsatellites have been the most commonly used genetic markers; however, technical artifacts and little overlap of frequently used loci render large-scale comparison of puma genetic data across studies challenging. Therefore, a panel of genetic markers that can produce consistent genotypes across studies without the need for extensive calibrations is essential for range-wide genetic management of puma populations. Here, we describe the development of PumaPlex, a high-throughput assay to genotype 25 single nucleotide polymorphisms in pumas. We validated PumaPlex in 748 North American pumas Puma concolor couguar, and demonstrated its ability to generate reproducible genotypes and accurately identify individuals. Furthermore, in a test using fecal deoxyribonucleic acid (DNA) samples, we found that PumaPlex produced significantly more genotypes with fewer errors than 12 microsatellite loci, 8 of which are commonly used. Our results demonstrate that PumaPlex is a valuable tool for the genetic monitoring and management of North American puma populations. Given the analytical simplicity, reproducibility, and high-throughput capability of single nucleotide polymorphisms, PumaPlex provides a standard panel of markers that promotes the comparison of genotypes across studies and independent of the genotyping technology used.

Toward a genome-wide approach for detecting hybrids: informative SNPs to detect introgression between domestic cats and European wildcats (Felis silvestris)

Endemic gene pools have been severely endangered by human-mediated hybridization, which is posing new challenges in the conservation of several vertebrate species. The endangered European wildcat is an example of this problem, as several natural populations are suffering introgression of genes from the domestic cat. The implementation of molecular methods for detecting hybridization is crucial for supporting appropriate conservation programs on the wildcat. In this study, genetic variation at 158 single-nucleotide polymorphisms (SNPs) was analyzed in 139 domestic cats, 130 putative European wildcats and 5 captive-bred hybrids (N=274). These SNPs were variable both in wild (HE=0.107) and domestic cats (HE=0.340). Although we did not find any SNP that was private in any population, 22 SNPs were monomorphic in wildcats and pairwise FCT values revealed marked differences between domestic and wildcats, with the most divergent 35 loci providing an average FCT>0.74. The power of all the loci to accurately identify admixture events and discriminate the different hybrid categories was evaluated. Results from simulated and real genotypes show that the 158 SNPs provide successful estimates of admixture, with 100% hybrid individuals (two to three generations in the past) being correctly identified in STRUCTURE and over 92% using the NEWHYBRIDS' algorithm. None of the unclassified cats were wrongly allocated to another hybrid class. Thirty-five SNPs, showing the highest FCT values, provided the most parsimonious panel for robust inferences of parental and first generations of admixed ancestries. This approach may be used to further reconstruct the evolution of wildcat populations and, hopefully, to develop sound conservation guidelines for its legal protection in Europe.

The genetic basis of population fecundity prediction across multiple field populations of Nilaparvata lugens

Identifying the molecular markers for complex quantitative traits in natural populations promises to provide novel insight into genetic mechanisms of adaptation and to aid in forecasting population dynamics. In this study, we investigated single nucleotide polymorphisms (SNPs) using candidate gene approach from high- and low-fecundity populations of the brown planthopper (BPH) Nilaparvata lugens Stål (Hemiptera: Delphacidae) divergently selected for fecundity. We also tested whether the population fecundity can be predicted by a few SNPs. Seven genes (ACE, fizzy, HMGCR, LpR, Sxl, Vg and VgR) were inspected for SNPs in N. lugens, which is a serious insect pest of rice. By direct sequencing of the complementary DNA and promoter sequences of these candidate genes, 1033 SNPs were discovered within high- and low-fecundity BPH populations. A panel of 121 candidate SNPs were selected and genotyped in 215 individuals from 2 laboratory populations (HFP and LFP) and 3 field populations (GZP, SGP and ZSP). Prior to association tests, population structure and linkage disequilibrium (LD) among the 3 field populations were analysed. The association results showed that 7 SNPs were significantly associated with population fecundity in BPH. These significant SNPs were used for constructing general liner models with stepwise regression. The best predictive model was composed of 2 SNPs (ACE-862 and VgR-816 ) with very good fitting degree. We found that 29% of the phenotypic variation in fecundity could be accounted for by only two markers. Using two laboratory populations and a complete independent field population, the predictive accuracy was 84.35-92.39%. The predictive model provides an efficient molecular method to predict BPH fecundity of field populations and provides novel insights for insect population management.

First regional evaluation of nuclear genetic diversity and population structure in northeastern coyotes ( Canis latrans)

Previous genetic studies of eastern coyotes ( Canis latrans) are based on one of two strategies: sampling many individuals using one or very few molecular markers, or sampling very few individuals using many genomic markers. Thus, a regional analysis of genetic diversity and population structure in eastern coyotes using many samples and several molecular markers is lacking. I evaluated genetic diversity and population structure in 385 northeastern coyotes using 16 common single nucleotide polymorphisms (SNPs). A region-wide analysis of population structure revealed three primary genetic populations, but these do not correspond to the same three subdivisions inferred in a previous analysis of mitochondrial DNA sequences. More focused geographic analyses of population structure indicated that ample genetic structure occurs in coyotes from an intermediate contact zone where two range expansion fronts meet. These results demonstrate that genotyping several highly heterozygous SNPs in a large, geographically dense sample is an effective way to detect cryptic population genetic structure. The importance of SNPs in studies of population and wildlife genomics is rapidly increasing; this study adds to the growing body of recent literature that demonstrates the utility of SNPs ascertained from a model organism for evolutionary inference in closely related species.

Assessment of coyote-wolf-dog admixture using ancestry-informative diagnostic SNPs

The evolutionary importance of hybridization as a source of new adaptive genetic variation is rapidly gaining recognition. Hybridization between coyotes and wolves may have introduced adaptive alleles into the coyote gene pool that facilitated an expansion in their geographic range and dietary niche. Furthermore, hybridization between coyotes and domestic dogs may facilitate adaptation to human-dominated environments. We genotyped 63 ancestry-informative single-nucleotide polymorphisms in 427 canids to examine the prevalence, spatial distribution and the ecology of admixture in eastern coyotes. Using multivariate methods and Bayesian clustering analyses, we estimated the relative contributions of western coyotes, western and eastern wolves, and domestic dogs to the admixed ancestry of Ohio and eastern coyotes. We found that eastern coyotes form an extensive hybrid swarm, with all our samples having varying levels of admixture. Ohio coyotes, previously thought to be free of admixture, are also highly admixed with wolves and dogs. Coyotes in areas of high deer density are genetically more wolf-like, suggesting that natural selection for wolf-like traits may result in local adaptation at a fine geographic scale. Our results, in light of other previously published studies of admixture in Canis, revealed a pattern of sex-biased hybridization, presumably generated by male wolves and dogs mating with female coyotes. This study is the most comprehensive genetic survey of admixture in eastern coyotes and demonstrates that the frequency and scope of hybridization can be quantified with relatively few ancestry-informative markers.

Application of single nucleotide polymorphisms to non-model species: a technical review

Single nucleotide polymorphisms (SNPs) have gained wide use in humans and model species and are becoming the marker of choice for applications in other species. Technology that was developed for work in model species may provide useful tools for SNP discovery and genotyping in non-model organisms. However, SNP discovery can be expensive, labour intensive, and introduce ascertainment bias. In addition, the most efficient approaches to SNP discovery will depend on the research questions that the markers are to resolve as well as the focal species. We discuss advantages and disadvantages of several past and recent technologies for SNP discovery and genotyping and summarize a variety of SNP discovery and genotyping studies in ecology and evolution.

Genome-wide SNP and population divergence of finless porpoises

Single nucleotide polymorphisms (SNPs) are rapidly becoming the population genomic markers in addressing ecology, evolution, and conservation issues for their high capacity to access variability across the genome. We isolated a total of 140 ideal SNPs from the finless porpoise and used 78 (under Hardy–Weinberg equilibrium) of them to conduct those issues especially for addressing population genetic differentiation. Bayesian clustering and principal component analyses all suggested that finless porpoises in Chinese waters could be divided into three distinct genetic groupings. Low levels of within-population genetic variation (mean H_E = 0.3405, standard deviation = 0.1188) and significant differentiation among populations (F_ST = 0.1050–0.1628, P < 0.01) were confirmed. Limited gene flow was found especially between the freshwater Yangtze River porpoise and the oceanic Yellow Sea and South China Sea populations, which strongly suggested that some barriers might have restricted their genetic exchange. These evidences not only support a recent subdivision of the finless porpoise into two species but also suggest a full species status for the Yangtze finless porpoise, especially considering the significant genetic divergence between freshwater and marine porpoises, in combination with the unique distribution of Yangtze finless porpoises in freshwater and their distinctness in physiological and morphological features.

Two different high throughput sequencing approaches identify thousands of de novo genomic markers for the genetically depleted Bornean elephant

High throughput sequencing technologies are being applied to an increasing number of model species with a high-quality reference genome. The application and analyses of whole-genome sequence data in non-model species with no prior genomic information are currently under way. Recent sequencing technologies provide new opportunities for gathering genomic data in natural populations, laying the empirical foundation for future research in the field of conservation and population genomics. Here we present the case study of the Bornean elephant, which is the most endangered subspecies of Asian elephant and exhibits very low genetic diversity. We used two different sequencing platforms, the Roche 454 FLX (shotgun) and Illumina, GAIIx (Restriction site associated DNA, RAD) to evaluate the feasibility of the two methodologies for the discovery of de novo markers (single nucleotide polymorphism, SNPs and microsatellites) using low coverage data. Approximately, 6,683 (shotgun) and 14,724 (RAD) SNPs were detected within our elephant sequence dataset. Genotyping of a representative sample of 194 SNPs resulted in a SNP validation rate of ∼ 83 to 94% and 17% of the loci were polymorphic with a low diversity (H_o = 0.057). Different numbers of microsatellites were identified through shotgun (27,226) and RAD (868) techniques. Out of all di-, tri-, and tetra-microsatellite loci, 1,706 loci had sufficient flanking regions (shotgun) while only 7 were found with RAD. All microsatellites were monomorphic in the Bornean but polymorphic in another elephant subspecies. Despite using different sample sizes, and the well known differences in the two platforms used regarding sequence length and throughput, the two approaches showed high validation rate. The approaches used here for marker development in a threatened species demonstrate the utility of high throughput sequencing technologies as a starting point for the development of genomic tools in a non-model species and in particular for a species with low genetic diversity.

Estimates of genetic differentiation measured by F(ST) do not necessarily require large sample sizes when using many SNP markers

Population genetic studies provide insights into the evolutionary processes that influence the distribution of sequence variants within and among wild populations. F_ST is among the most widely used measures for genetic differentiation and plays a central role in ecological and evolutionary genetic studies. It is commonly thought that large sample sizes are required in order to precisely infer F_ST and that small sample sizes lead to overestimation of genetic differentiation. Until recently, studies in ecological model organisms incorporated a limited number of genetic markers, but since the emergence of next generation sequencing, the panel size of genetic markers available even in non-reference organisms has rapidly increased. In this study we examine whether a large number of genetic markers can substitute for small sample sizes when estimating F_ST. We tested the behavior of three different estimators that infer F_ST and that are commonly used in population genetic studies. By simulating populations, we assessed the effects of sample size and the number of markers on the various estimates of genetic differentiation. Furthermore, we tested the effect of ascertainment bias on these estimates. We show that the population sample size can be significantly reduced (as small as n = 4–6) when using an appropriate estimator and a large number of bi-allelic genetic markers (k>1,000). Therefore, conservation genetic studies can now obtain almost the same statistical power as studies performed on model organisms using markers developed with next-generation sequencing.

Rates of assay success and genotyping error when single nucleotide polymorphism genotyping in non-model organisms: a case study in the Antarctic fur seal

Although single nucleotide polymorphisms (SNPs) are increasingly being recognized as powerful molecular markers, their application to non-model organisms can bring significant challenges. Among these are imperfect conversion rates of assays designed from in silico resources and the enhanced potential for genotyping error relative to pre-validated, highly optimized human SNPs. To explore these issues, we used Illumina's GoldenGate assay to genotype 480 Antarctic fur seal (Arctocephalus gazella) individuals at 144 putative SNPs derived from a 454 transcriptome assembly. One hundred and thirty-five polymorphic SNPs (93.8%) were automatically validated by the program GenomeStudio, and the initial genotyping error rate, estimated from nine replicate samples, was 0.004 per reaction. However, an almost tenfold further reduction in the error rate was achieved by excluding 31 loci (21.5%) that exhibited unclear clustering patterns, manually editing clusters to allow rescoring of ambiguous or incorrect genotypes, and excluding 18 samples (3.8%) with unreliable genotypes. After stringent quality filtering, we also found a counter-intuitive negative relationship between in silico minor allele frequency and the conversion rate, suggesting that some of our assays may have been designed from paralogous loci. Nevertheless, we obtained over 45 000 individual SNP genotypes with a final error rate of 0.0005, indicating that the GoldenGate assay is eminently capable of generating large, high-quality data sets for non-model organisms. This has positive implications for future studies of the evolutionary, behavioural and conservation genetics of natural populations.

SNP Discovery through Next-Generation Sequencing and Its Applications

The decreasing cost along with rapid progress in next-generation sequencing and related bioinformatics computing resources has facilitated large-scale discovery of SNPs in various model and nonmodel plant species. Large numbers and genome-wide availability of SNPs make them the marker of choice in partially or completely sequenced genomes. Although excellent reviews have been published on next-generation sequencing, its associated bioinformatics challenges, and the applications of SNPs in genetic studies, a comprehensive review connecting these three intertwined research areas is needed. This paper touches upon various aspects of SNP discovery, highlighting key points in availability and selection of appropriate sequencing platforms, bioinformatics pipelines, SNP filtering criteria, and applications of SNPs in genetic analyses. The use of next-generation sequencing methodologies in many non-model crops leading to discovery and implementation of SNPs in various genetic studies is discussed. Development and improvement of bioinformatics software that are open source and freely available have accelerated the SNP discovery while reducing the associated cost. Key considerations for SNP filtering and associated pipelines are discussed in specific topics. A list of commonly used software and their sources is compiled for easy access and reference.

Analysis of >1000 single nucleotide polymorphisms in geographically matched samples of landrace and wild barley indicates secondary contact and chromosome-level differences in diversity around domestication genes

Barley is a model species for the investigation of the evolution, adaptation and spread of the world's important crops. In this article, we describe the first application of an oligonucleotide pool assay single nucleotide polymorphism (SNP) platform to assess the evolution of barley in a portion of the Fertile Crescent, a key region in the development of farming. A large collection of >1000 genetically mapped, genome-wide SNPs was assayed in geographically matched landrace and wild barley accessions (N=448) from Jordan and Syria. Landrace and wild barley categories were clearly genetically differentiated, but a limited degree of secondary contact was evident. Significant chromosome-level differences in diversity between barley types were observed around genes known to be involved in the evolution of cultivars. The region of Jordan and southern Syria, compared with the north of Syria, was supported by SNP data as a more likely domestication origin. Our data provide evidence for hybridization as a possible mechanism for the continued adaptation of landrace barley under cultivation, indicate regions of the genome that may be subject to selection processes and suggest limited origins for the development of the cultivated crop.

PolyAna: analyzing synonymous and nonsynonymous polymorphic sites

PolyAna (available at http://www.biol.sc.edu/~austin/) aids in the analysis of natural selection on protein-coding sequences by estimating sample gene diversity at individual polymorphic nucleotide sites, which are classified as synonymous, non-synonymous, or ambiguous.

Outlier SNPs show more genetic structure between two Bay of Fundy metapopulations of Atlantic salmon than do neutral SNPs

Atlantic salmon of Eastern Canada were once of considerable importance to aboriginal, recreational, and commercial fisheries, yet many populations are now in decline, particularly those of the inner Bay of Fundy (iBoF), which were recently listed as endangered. We investigated whether nonneutral SNPs could be used to assign individual Atlantic salmon accurately to either the iBoF or the outer Bay of Fundy (oBoF) metapopulations because this has been difficult with existing neutral markers. We first searched for markers under diversifying selection by genotyping eight captively bred Bay of Fundy (BoF) populations for 320 SNP loci with the Sequenom MassARRAY™ system and then analysed the data set with four different F(ST) outlier detection programs. Three outlier loci were identified by both BayesFST and BayeScan whereas seven outlier loci, including the three previously mentioned, were identified by both Fdist and Arlequin. A subset of 14 nonneutral SNPs was more accurate (85% accuracy) than a subset of 67 neutral SNPs (75% accuracy) at assigning individual salmon back to their metapopulation. We then chose a subset of nine outlier SNP markers and used them to inexpensively genotype archived DNA samples from seven wild BoF populations using Invader™ chemistry. Hierarchical AMOVA of these independent wild samples corroborated our previous findings of significant genetic differentiation between iBoF and oBoF salmon metapopulations. Our research shows that identifying and using outlier loci is an important step towards achieving the goal of consistently and accurately distinguishing iBoF from oBoF Atlantic salmon, which will aid in their conservation.

Current trends in microsatellite genotyping

Microsatellites have been popular molecular markers ever since their advent in the late eighties. Despite growing competition from new genotyping and sequencing techniques, the use of these versatile and cost-effective markers continues to increase, boosted by successive technical advances. First, methods for multiplexing PCR have considerably improved over the last years, thereby decreasing genotyping costs and increasing throughput. Second, next-generation sequencing technologies allow the identification of large numbers of microsatellite loci at reduced cost in non-model species. As a consequence, more stringent selection of loci is possible, thereby further enhancing multiplex quality and efficiency. However, current practices are lagging behind. By surveying recently published population genetic studies relying on simple sequence repeats, we show that more than half of the studies lack appropriate quality controls and do not make use of multiplex PCR. To make the most of the latest technical developments, we outline the need for a well-established strategy including standardized high-throughput bench protocols and specific bioinformatic tools, from primer design to allele calling.

Dog leukocyte antigen class II-associated genetic risk testing for immune disorders of dogs: simplified approaches using Pug dog necrotizing meningoencephalitis as a model

A significantly increased risk for a number of autoimmune and infectious diseases in purebred and mixed-breed dogs has been associated with certain alleles or allele combinations of the dog leukocyte antigen (DLA) class II complex containing the DRB1, DQA1, and DQB1 genes. The exact level of risk depends on the specific disease, the alleles in question, and whether alleles exist in a homozygous or heterozygous state. The gold standard for identifying high-risk alleles and their zygosity has involved direct sequencing of the exon 2 regions of each of the 3 genes. However, sequencing and identification of specific alleles at each of the 3 loci are relatively expensive and sequencing techniques are not ideal for additional parentage or identity determination. However, it is often possible to get the same information from sequencing only 1 gene given the small number of possible alleles at each locus in purebred dogs, extensive homozygosity, and tendency for disease-causing alleles at each of the 3 loci to be strongly linked to each other into haplotypes. Therefore, genetic testing in purebred dogs with immune diseases can be often simplified by sequencing alleles at 1 rather than 3 loci. Further simplification of genetic tests for canine immune diseases can be achieved by the use of alternative genetic markers in the DLA class II region that are also strongly linked with the disease genotype. These markers consist of either simple tandem repeats or single nucleotide polymorphisms that are also in strong linkage with specific DLA class II genotypes and/or haplotypes. The current study uses necrotizing meningoencephalitis of Pug dogs as a paradigm to assess simple alternative genetic tests for disease risk. It was possible to attain identical necrotizing meningoencephalitis risk assessments to 3-locus DLA class II sequencing by sequencing only the DQB1 gene, using 3 DLA class II-linked simple tandem repeat markers, or with a small single nucleotide polymorphism array designed to identify breed-specific DQB1 alleles.

Microsatellite standardization and evaluation of genotyping error in a large multi-partner research programme for conservation of Atlantic salmon (Salmo salar L.)

Microsatellite genotyping is a common DNA characterization technique in population, ecological and evolutionary genetics research. Since different alleles are sized relative to internal size-standards, different laboratories must calibrate and standardize allelic designations when exchanging data. This interchange of microsatellite data can often prove problematic. Here, 16 microsatellite loci were calibrated and standardized for the Atlantic salmon, Salmo salar, across 12 laboratories. Although inconsistencies were observed, particularly due to differences between migration of DNA fragments and actual allelic size (‘size shifts’), inter-laboratory calibration was successful. Standardization also allowed an assessment of the degree and partitioning of genotyping error. Notably, the global allelic error rate was reduced from 0.05 ± 0.01 prior to calibration to 0.01 ± 0.002 post-calibration. Most errors were found to occur during analysis (i.e. when size-calling alleles; the mean proportion of all errors that were analytical errors across loci was 0.58 after calibration). No evidence was found of an association between the degree of error and allelic size range of a locus, number of alleles, nor repeat type, nor was there evidence that genotyping errors were more prevalent when a laboratory analyzed samples outside of the usual geographic area they encounter. The microsatellite calibration between laboratories presented here will be especially important for genetic assignment of marine-caught Atlantic salmon, enabling analysis of marine mortality, a major factor in the observed declines of this highly valued species.