Comparison of information content for microsatellites and SNPs in poultry and cattle

The role of agro-ecological factors and transboundary transhumance in shaping the genetic diversity in four indigenous cattle populations of Benin

The indigenous cattle population of Benin is a diverse mix of taurine and hybrid breeds shaped by diverse ecological and climatic conditions with eight agro-ecological zones (AEZ). Presumably, the taurine breeds face current endangerment due to ongoing indicine introgression following climate change and transboundary transhumance. The aim of the study was to investigate the genetic diversity and population structure of the indigenous breeds Lagune, Somba, Pabli and Borgou considering spatial agro-ecological and socio-economic factors (transhumance) based on 50k SNP and microsatellite data. Among the four sampled breeds, six genetic clusters were identified using model-free (discriminant analysis of principal components) and model-based (TESS and ADMIXTURE) methods separating taurine from hybrid breeds. Results based on an extension with publicly available historic SNP data sets from taurine and indicine West African cattle and additional outgroups provided additional insight into changes of genetic structure in the sampled breeds over time. Both taurine breeds, Somba and Lagune, showed a stable foundation but also spatially limited partial indicine introgression associated with transhumance leading to high genetic diversity. In addition, we found evidence for spatial diversity and changes in genetic structure over time in the Borgou breed in comparison of our samples with the historic samples which could be explained by potential continuous indicine introgression into the Borgou breed in two sample regions. Results for the Pabli breed do not conclusively point to full absorbance by the Borgou in comparison with all available Borgou samples. Further research is needed in this regard.

Applying genomic data in wildlife monitoring: Development guidelines for genotyping degraded samples with reduced single nucleotide polymorphism panels

The genomic era has led to an unprecedented increase in the availability of genome-wide data for a broad range of taxa. Wildlife management strives to make use of these vast resources to enable refined genetic assessments that enhance biodiversity conservation. However, as new genomic platforms emerge, problems remain in adapting the usually complex approaches for genotyping of noninvasively collected wildlife samples. Here, we provide practical guidelines for the standardized development of reduced single nucleotide polymorphism (SNP) panels applicable for microfluidic genotyping of degraded DNA samples, such as faeces or hairs. We demonstrate how microfluidic SNP panels can be optimized to efficiently monitor European wildcat (Felis silvestris S.) populations. We show how panels can be set up in a modular fashion to accommodate informative markers for relevant population genetics questions, such as individual identification, hybridization assessment and the detection of population structure. We discuss various aspects regarding the implementation of reduced SNP panels and provide a framework that will allow both molecular ecologists and practitioners to help bridge the gap between genomics and applied wildlife conservation.

Applying genomic data in wildlife monitoring: Development guidelines for genotyping degraded samples with reduced single nucleotide polymorphism panels

The genomic era has led to an unprecedented increase in the availability of genome-wide data for a broad range of taxa. Wildlife management strives to make use of these vast resources to enable refined genetic assessments that enhance biodiversity conservation. However, as new genomic platforms emerge, problems remain in adapting the usually complex approaches for genotyping of noninvasively collected wildlife samples. Here, we provide practical guidelines for the standardized development of reduced single nucleotide polymorphism (SNP) panels applicable for microfluidic genotyping of degraded DNA samples, such as faeces or hairs. We demonstrate how microfluidic SNP panels can be optimized to efficiently monitor European wildcat (Felis silvestris S.) populations. We show how panels can be set up in a modular fashion to accommodate informative markers for relevant population genetics questions, such as individual identification, hybridization assessment and the detection of population structure. We discuss various aspects regarding the implementation of reduced SNP panels and provide a framework that will allow both molecular ecologists and practitioners to help bridge the gap between genomics and applied wildlife conservation.

The Value of Reference Genomes in the Conservation of Threatened Species

Conservation initiatives are now more crucial than ever-over a million plant and animal species are at risk of extinction over the coming decades. The genetic management of threatened species held in insurance programs is recommended; however, few are taking advantage of the full range of genomic technologies available today. Less than 1% of the 13505 species currently listed as threated by the International Union for Conservation of Nature (IUCN) have a published genome. While there has been much discussion in the literature about the importance of genomics for conservation, there are limited examples of how having a reference genome has changed conservation management practice. The Tasmanian devil (Sarcophilus harrisii), is an endangered Australian marsupial, threatened by an infectious clonal cancer devil facial tumor disease (DFTD). Populations have declined by 80% since the disease was first recorded in 1996. A reference genome for this species was published in 2012 and has been crucial for understanding DFTD and the management of the species in the wild. Here we use the Tasmanian devil as an example of how a reference genome has influenced management actions in the conservation of a species.

Application of a SSR-GBS marker system on investigation of European Hedgehog species and their hybrid zone dynamics

By applying second-generation sequencing technologies to microsatellite genotyping, sequence information is produced which can result in high-resolution population genetics analysis populations and increased replicability between runs and laboratories. In the present study, we establish an approach to study the genetic structure patterns of two European hedgehog species Erinaceaus europaeus and E. roumanicus. These species are usually associated with human settlements and are good models to study anthropogenic impacts on the genetic diversity of wild populations. The short sequence repeats genotyping by sequence (SSR-GBS) method presented uses amplicon sequences to determine genotypes for which allelic variants can be defined according to both length and single nucleotide polymorphisms (SNPs). To evaluate whether complete sequence information improved genetic structure definition, we compared this information with datasets based solely on length information. We identified a total of 42 markers which were successfully amplified in both species. Overall, genotyping based on complete sequence information resulted in a higher number of alleles, as well as greater genetic diversity and differentiation between species. Additionally, the structure patterns were slightly clearer with a division between both species and some potential hybrids. There was some degree of genetic structure within species, although only in E. roumanicus was this related to geographical distance. The statistically significant results obtained by SSR-GBS demonstrate that it is superior to electrophoresis-based methods for SSR genotyping. Moreover, the greater reproducibility and throughput with lower effort which can be obtained with SSR-GBS and the possibility to include degraded DNA into the analysis, allow for continued relevance of SSR markers during the genomic era.

DNA-based Determination of Ancestry in Cynomolgus Macaques (Macaca fascicularis)

Interest in the genetic composition of cynomolgus macaques (Macaca fascicularis) has increased due to the rising demand for NHP models in human biomedical research. Significant genetic differences among regional populations of cynomolgus macaques can confound interpretations of research results because they do not solely reflect differences in experimental treatment effects. Therefore, the common origin of cynomolgus macaques used as research subjects should be verified by using region-specific genetic markers to minimize the influence of underlying genetic variation among animals selected as research subjects on phenotypes under study. We compared the effectiveness of 18 short tandem repeat (STR) markers with that of 83 single-nucleotide polymorphism (SNP) markers to differentiate the ancestry of cynomolgus macaques from 6 different populations (Cambodia, Sumatra, Mauritius, Singapore, and the islands of Luzon and Zamboanga in the Philippines). Genetic diversity indices such as allele numbers and expected heterozygosity based on SNP were lower and exhibited lower standard errors than those provided by STR, probably because, unlike STR, most SNP are biallelic and consequently exhibit maximal expected heterozygosity values of 0.50. However, the standard error of estimates of observed heterozygosity based on SNP was higher than that for STR, perhaps reflecting sampling errors. Only 27 SNP were required to match the resolving power of 17 STR to detect population structure, that is, 1.6 SNP:1 STR. Whereas STR only differentiated the Mauritian population from all other populations, SNP detected 4 genetically distinct groups (Cambodia, Singapore-Sumatra, Mauritius, and Zamboanga). SNP are poised to become as valuable as STR for understanding and detecting genetic structure among cynomolgus macaques. Although STR will remain an important tool for cynomolgus macaque population studies, SNP have the potential to become the mainstream marker type.

Whole-genome SNP analysis elucidates the genetic structure of Russian cattle and its relationship with Eurasian taurine breeds

BACKGROUND

The origin of native and locally developed Russian cattle breeds is linked to the historical, social, cultural, and climatic features of the diverse geographical regions of Russia. In the present study, we investigated the population structure of nine Russian cattle breeds and their relations to the cattle breeds from around the world to elucidate their origin. Genotyping of single nucleotide polymorphisms (SNPs) in Bestuzhev (n = 26), Russian Black-and-White (n = 21), Kalmyk (n = 14), Kholmogor (n = 25), Kostromsky (n = 20), Red Gorbatov (n = 23), Suksun (n = 20), Yakut (n = 25), and Yaroslavl cattle breeds (n = 21) was done using the Bovine SNP50 BeadChip. SNP profiles from an additional 70 breeds were included in the analysis as references.

RESULTS

The observed heterozygosity levels were quite similar in eight of the nine studied breeds (H_O = 0.337-0.363) except for Yakut (Ho = 0.279). The inbreeding coefficients F_IS ranged from -0.028 for Kalmyk to 0.036 for Russian Black-and-White and were comparable to those of the European breeds. The nine studied Russian breeds exhibited taurine ancestry along the C1 axis of the multidimensional scaling (MDS)-plot, but Yakut was clearly separated from the European taurine breeds on the C2 axis. Neighbor-Net and admixture analyses, discriminated three groups among the studied Russian breeds. Yakut and Kalmyk were assigned to a separate group because of their Turano-Mongolian origin. Russian Black-and-White, Kostromsky and Suksun showed transboundary European ancestry, which originated from the Holstein, Brown Swiss, and Danish Red breeds, respectively. The lowest level of introgression of transboundary breeds was recorded for the Kholmogor, Yaroslavl, Red Gorbatov and Bestuzhev breeds, which can be considered as an authentic genetic resource.

CONCLUSIONS

Whole-genome SNP analysis revealed that Russian native and locally developed breeds have conserved authentic genetic patterns in spite of the considerable influence of Eurasian taurine cattle. In this paper, we provide fundamental genomic information that will contribute to the development of more accurate breed conservation programs and genetic improvement strategies.

Origins and wanderings of the Finnish hunting spitzes

Deducing the evolutionary histories of dog breeds can be challenging due to convergent traits and frequent admixture. In this report, we have explored the relationships of indigenous Finnish hunting spitz breeds among other northern Eurasian hunting breeds using commercially available SNP analysis (the MyDogDNA panel test). We find that Nordic hunting breeds Finnish Spitz, Nordic Spitz and the Karelian Bear Dog, as well as the reindeer herding Lapphund and Lapponian herder are all closely related and have common origins with the northeastern Eurasian Laika breeds, rather than with other Scandinavian Spitz breeds, such as Elkhounds and Swedish Vallhund. By tracing admixture events and direction of gene flow, we also elucidate the complex interactions between the breeds and provide new insight into the history of Swedish Elkhound and Russian-European Laika. The findings, together with an analysis of genetic differentiation between the populations, not only help to understand the origins of the breeds but also provide interesting possibilities to revive genetic diversity, lost during the breeding history, by backcrossing breeds to their hypothetical ancestry.

Adding loci improves phylogeographic resolution in red mangroves despite increased missing data: comparing microsatellites and RAD-Seq and investigating loci filtering

The widespread adoption of RAD-Seq data in phylogeography means genealogical relationships previously evaluated using relatively few genetic markers can now be addressed with thousands of loci. One challenge, however, is that RAD-Seq generates complete genotypes for only a small subset of loci or individuals. Simulations indicate that loci with missing data can produce biased estimates of key population genetic parameters, although the influence of such biases in empirical studies is not well understood. Here we compare microsatellite data (8 loci) and RAD-Seq data (six datasets ranging from 239 to 25,198 loci) from red mangroves (Rhizophora mangle) in Florida to evaluate how different levels of data filtering influence phylogeographic inferences. For all datasets, we calculated population genetic statistics and evaluated population structure, and for RAD-Seq datasets, we additionally examined population structure using coalescence. We found higher F_ST using microsatellites, but that RAD-Seq-based estimates approached those based on microsatellites as more loci with more missing data were included. Analyses of RAD-Seq datasets resolved the classic Gulf-Atlantic coastal phylogeographic break, which was not significant in the microsatellite analyses. Applying multiple levels of filtering to RAD-Seq datasets can provide a more complete picture of potential biases in the data and elucidate subtle phylogeographic patterns.

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.

SNPs selected by information content outperform randomly selected microsatellite loci for delineating genetic identification and introgression in the endangered dark European honeybee (Apis mellifera mellifera)

The honeybee (Apis mellifera) has been threatened by multiple factors including pests and pathogens, pesticides and loss of locally adapted gene complexes due to replacement and introgression. In western Europe, the genetic integrity of the native A. m. mellifera (M-lineage) is endangered due to trading and intensive queen breeding with commercial subspecies of eastern European ancestry (C-lineage). Effective conservation actions require reliable molecular tools to identify pure-bred A. m. mellifera colonies. Microsatellites have been preferred for identification of A. m. mellifera stocks across conservation centres. However, owing to high throughput, easy transferability between laboratories and low genotyping error, SNPs promise to become popular. Here, we compared the resolving power of a widely utilized microsatellite set to detect structure and introgression with that of different sets that combine a variable number of SNPs selected for their information content and genomic proximity to the microsatellite loci. Contrary to every SNP data set, microsatellites did not discriminate between the two lineages in the PCA space. Mean introgression proportions were identical across the two marker types, although at the individual level, microsatellites' performance was relatively poor at the upper range of Q-values, a result reflected by their lower precision. Our results suggest that SNPs are more accurate and powerful than microsatellites for identification of A. m. mellifera colonies, especially when they are selected by information content.

A Study of Applicability of SNP Chips Developed for Bovine and Ovine Species to Whole-Genome Analysis of Reindeer Rangifer tarandus

Two sets of commercially available single nucleotide polymorphisms (SNPs) developed for cattle (BovineSNP50 BeadChip) and sheep (OvineSNP50 BeadChip) have been trialed for whole-genome analysis of 4 female samples of Rangifer tarandus inhabiting Russia. We found out that 43.0% of bovine and 47.0% of Ovine SNPs could be genotyped, while only 5.3% and 2.03% of them were respectively polymorphic. The scored and the polymorphic SNPs were identified on each bovine and each ovine chromosome, but their distribution was not unique. The maximal value of runs of homozygosity (ROH) was 30.93Mb (for SNPs corresponding to bovine chromosome 8) and 80.32Mb (for SNPs corresponding to ovine chromosome 7). Thus, the SNP chips developed for bovine and ovine species can be used as a powerful tool for genome analysis in reindeer R. tarandus.

Trypanosomosis: potential driver of selection in African cattle

Trypanosomosis is a serious cause of reduction in productivity of cattle in tsetse-fly infested areas. Baoule and other local Taurine cattle breeds in Burkina Faso are trypanotolerant. Zebuine cattle, which are also kept there are susceptible to trypanosomosis but bigger in body size. Farmers have continuously been intercrossing Baoule and Zebu animals to increase production and disease tolerance. The aim of this study was to compare levels of zebuine and taurine admixture in genomic regions potentially involved in trypanotolerance with background admixture of composites to identify differences in allelic frequencies of tolerant and non-tolerant animals. The study was conducted on 214 animals (90 Baoule, 90 Zebu, and 34 composites), genotyped with 25 microsatellites across the genome and with 155 SNPs in 23 candidate regions. Degrees of admixture of composites were analyzed for microsatellite and SNP data separately. Average Baoule admixture based on microsatellites across the genomes of the Baoule- Zebu composites was 0.31, which was smaller than the average Baoule admixture in the trypanosomosis candidate regions of 0.37 (P = 0.15). Fixation index F_ST measured in the overall genome based on microsatellites or with SNPs from candidate regions indicates strong differentiation between breeds. Nine out of 23 regions had F_ST ≥ 0.20 calculated from haplotypes or individual SNPs. The levels of admixture were significantly different from background admixture, as revealed by microsatellite data, for six out of the nine regions. Five out of the six regions showed an excess of Baoule ancestry. Information about best levels of breed composition would be useful for future breeding ctivities, aiming at trypanotolerant animals with higher productive capacity.

Challenges in analysis and interpretation of microsatellite data for population genetic studies

Advancing technologies have facilitated the ever-widening application of genetic markers such as microsatellites into new systems and research questions in biology. In light of the data and experience accumulated from several years of using microsatellites, we present here a literature review that synthesizes the limitations of microsatellites in population genetic studies. With a focus on population structure, we review the widely used fixation (F ST) statistics and Bayesian clustering algorithms and find that the former can be confusing and problematic for microsatellites and that the latter may be confounded by complex population models and lack power in certain cases. Clustering, multivariate analyses, and diversity-based statistics are increasingly being applied to infer population structure, but in some instances these methods lack formalization with microsatellites. Migration-specific methods perform well only under narrow constraints. We also examine the use of microsatellites for inferring effective population size, changes in population size, and deeper demographic history, and find that these methods are untested and/or highly context-dependent. Overall, each method possesses important weaknesses for use with microsatellites, and there are significant constraints on inferences commonly made using microsatellite markers in the areas of population structure, admixture, and effective population size. To ameliorate and better understand these constraints, researchers are encouraged to analyze simulated datasets both prior to and following data collection and analysis, the latter of which is formalized within the approximate Bayesian computation framework. We also examine trends in the literature and show that microsatellites continue to be widely used, especially in non-human subject areas. This review assists with study design and molecular marker selection, facilitates sound interpretation of microsatellite data while fostering respect for their practical limitations, and identifies lessons that could be applied toward emerging markers and high-throughput technologies in population genetics.

Reintroductions and genetic introgression from domestic pigs have shaped the genetic population structure of Northwest European wild boar

BACKGROUND

Population genetic studies focus on natural dispersal and isolation by landscape barriers as the main drivers of genetic population structure. However, anthropogenic factors such as reintroductions, translocations and wild x domestic hybridization may also have strong effects on genetic population structure. In this study we genotyped 351 Single Nucleotide Polymorphism markers evenly spread across the genome in 645 wild boar (Sus scrofa) from Northwest Europe to evaluate determinants of genetic population structure.

RESULTS

We show that wild boar genetic population structure is influenced by historical reintroductions and by genetic introgression from domestic pigs. Six genetically distinct and geographically coherent wild boar clusters were identified in the Netherlands and Western Germany. The Dutch Veluwe cluster is known to be reintroduced, and three adjacent Dutch and German clusters are suspected to be a result of reintroduction, based on clustering results, low levels of heterozygosity and relatively high genetic distances to nearby populations. Recent wild x domestic hybrids were found geographically widespread across clusters and at low frequencies (average 3.9%). The relationship between pairwise kinship coefficients and geographic distance showed male-biased dispersal at the population genetic level.

CONCLUSIONS

Our results demonstrate that wildlife and landscape management by humans are shaping the genetic diversity of an iconic wildlife species. Historical reintroductions, translocation and recent restocking activities with farmed wild boar have all influenced wild boar genetic population structure. The current trend of wild boar population growth and range expansion has recently led to a number of contact zones between clusters, and further admixture between the different wild boar clusters is to be expected.