Detection and characterization of SNPs useful for identity control and parentage testing in major European dairy breeds

We propose the use of single nucleotide polymorphisms (SNPs) instead of polymorphic microsatellite markers for individual identification and parentage control in cattle. To this end, we present an initial set of 37 SNP markers together with a gender-specific SNP for identity control and parentage testing in the Holstein, Fleckvieh and Braunvieh breeds. To obtain suitable SNPs, a total of 91.13 kb of random genomic DNA was screened yielding 531 SNPs. These, and 43 previously identified SNPs, were subjected to the following selection criteria: (1) the frequency of the minor allele must be larger than 0.1 in at least two of the three examined breeds, and (2) markers should not be linked closely. Allele frequencies were estimated by analysing sequencing traces of pooled DNA or by genotyping individual DNA samples. The selected SNP loci were physically mapped by radiation hybrid mapping or by fluorescence in situ hybridization, and tested against the neutral mutation hypothesis. The presented marker set theoretically allows probabilities of identity less than 10(-13) for individual verification and exclusion powers exceeding 99.99% for parentage testing.     

The future of parentage analysis: From microsatellites to SNPs and beyond

Parentage analysis is a cornerstone of molecular ecology that has delivered fundamental insights into behaviour, ecology and evolution. Microsatellite markers have long been the king of parentage, their hypervariable nature conferring sufficient power to correctly assign offspring to parents. However, microsatellite markers have seen a sharp decline in use with the rise of next‐generation sequencing technologies, especially in the study of population genetics and local adaptation. The time is ripe to review the current state of parentage analysis and see how it stands to be affected by the emergence of next‐generation sequencing approaches. We find that single nucleotide polymorphisms (SNPs), the typical next‐generation sequencing marker, remain underutilized in parentage analysis but are gaining momentum, with 58 SNP‐based parentage analyses published thus far. Many of these papers, particularly the earlier ones, compare the power of SNPs and microsatellites in a parentage context. In virtually every case, SNPs are at least as powerful as microsatellite markers. As few as 100–500 SNPs are sufficient to resolve parentage completely in most situations. We also provide an overview of the analytical programs that are commonly used and compatible with SNP data. As the next‐generation parentage enterprise grows, a reliance on likelihood and Bayesian approaches, as opposed to strict exclusion, will become increasingly important. We discuss some of the caveats surrounding the use of next‐generation sequencing data for parentage analysis and conclude that the future is bright for this important realm of molecular ecology.     

The evaluation of the usefulness of pedigree verification-dedicated SNPs for breed assignment in three polish cattle populations

The breed assignment in cattle is one of the issues of molecular genetics which needs further testing and development. Although several statistical approaches have been developed to enable such application, the obtained results strongly depend on specific populations differentiation and power of markers discrimination or their informativeness. Currently, all breeding animals are being tested for parentage with the use of panel of 12 microsatellite markers, which in near future probably will be replaced by about 100 single nucleotide polymorphisms (SNPs). Despite the fact that SNPs are mainly bi-allelic, the multilocus genotypes can reach the level of polymorphism of a panel of microsatellite markers. In this study we attempted to determine the breed of origin of 741 cattle by using 120 SNPs dedicated for parentage testing and included in the BovineSNP50 BeadChip genotyping assay (Illumina). The applied Bayesian and frequency-based methods allowed such differentiation, however, the reliability of the results was not completely satisfying, suggesting that the studied markers are not the best tool for breed assignment.     

Single nucleotide polymorphisms for DNA typing in the domestic horse

Genetic markers are important resources for individual identification and parentage assessment. Although short tandem repeats (STRs) have been the traditional DNA marker, technological advances have led to single nucleotide polymorphisms (SNPs) becoming an attractive alternative. SNPs can be highly multiplexed and automatically scored, which allows for easier standardization and sharing among laboratories. Equine parentage is currently assessed using STRs. We obtained a publicly available SNP dataset of 729 horses representing 32 diverse breeds. A proposed set of 101 SNPs was analyzed for DNA typing suitability. The overall minor allele frequency of the panel was 0.376 (range 0.304–0.419), with per breed probability of identities ranging from 5.6 × 10^?35 to 1.86 × 10^?42. When one parent was available, exclusion probabilities ranged from 0.9998 to 0.999996, although when both parents were available, all breeds had exclusion probabilities greater than 0.9999999. A set of 388 horses from 35 breeds was genotyped to evaluate marker performance on known families. The set included 107 parent–offspring pairs and 101 full trios. No horses shared identical genotypes across all markers, indicating that the selected set was sufficient for individual identification. All pairwise comparisons were classified using ISAG rules, with one or two excluding markers considered an accepted parent–offspring pair, two or three excluding markers considered doubtful and four or more excluding markers rejecting parentage. The panel had an overall accuracy of 99.9% for identifying true parent–offspring pairs. Our developed marker set is both present on current generation SNP chips and can be highly multiplexed in standalone panels and thus is a promising resource for SNP‐based DNA typing.     

From microsatellites to single nucleotide polymorphisms for the genetic monitoring of a critically endangered sturgeon

The use of genetic information is crucial in conservation programs for the establishment of breeding plans and for the evaluation of restocking success. Short tandem repeats (STRs) have been the most widely used molecular markers in such programs, but next‐generation sequencing approaches have prompted the transition to genome‐wide markers such as single nucleotide polymorphisms (SNPs). Until now, most sturgeon species have been monitored using STRs. The low diversity found in the critically endangered European sturgeon (Acipenser sturio), however, makes its future genetic monitoring challenging, and the current resolution needs to be increased. Here, we describe the discovery of a highly informative set of 79 SNPs using double‐digest restriction‐associated DNA (ddRAD) sequencing and its validation by genotyping using the MassARRAY system. Comparing with STRs, the SNP panel proved to be highly efficient and reproducible, allowing for more accurate parentage and kinship assignments' on 192 juveniles of known pedigree and 40 wild‐born adults. We explore the effectiveness of both markers to estimated relatedness and inbreeding, using simulated and empirical datasets. Interestingly, we found significant correlations between STRs and SNPs at individual heterozygosity and inbreeding that give support to a reasonable representation of whole genome diversity for both markers. These results are useful for the conservation program of A. sturio in building a comprehensive studbook, which will optimize conservation strategies. This approach also proves suitable for other case studies in which highly discriminatory genetic markers are needed to assess parentage and kinship.     

Effects of genotyping errors on parentage exclusion analysis

Genetic markers are widely used to determine the parentage of individuals in studies of mating systems, reproductive success, dispersals, quantitative genetic parameters and in the management of conservation populations. These markers are, however, imperfect for parentage analyses because of the presence of genotyping errors and undetectable alleles, which may cause incompatible genotypes (mismatches) between parents and offspring and thus result in false exclusions of true parentage. Highly polymorphic markers widely used in parentage analyses, such as microsatellites, are especially prone to genotyping errors. In this investigation, I derived the probabilities of excluding a random (related) individual from parentage and the probabilities of Mendelian-inconsistent errors (mismatches) and Mendelian-consistent errors (which do not cause mismatches) in parent-offspring dyads, when a marker having null alleles, allelic dropouts and false alleles is used in a parentage analysis. These probabilities are useful in evaluating the impact of various types of genotyping errors on the information content of a set of markers in and thus the power of a parentage analysis, in determining the threshold number of genetic mismatches that is appropriate for a parentage exclusion analysis and in estimating the rates of genotyping errors and frequencies of null alleles from observed mismatches between known parent-offspring dyads. These applications are demonstrated by numerical examples using both hypothetical and empirical data sets and discussed in the context of practical parentage exclusion analyses.     

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.     

Microsatellite variation in the equine MHC

Genes within the major histocompatibility complex (MHC) encode proteins involved in innate and adaptive immune responses. Genetic variation in this region can influence the immune response of an individual animal to challenges from a variety of pathogens; however, a complete documentation of genetic variation in the MHC is lacking for most domestic animals, including horses. To provide additional genetic markers for study of the horse MHC, or ELA (equine lymphocyte antigen), we identified 37 polymorphic microsatellite repeats in ELA and used these variations separately and together with published SNPs to investigate linkage disequilibrium (LD) and haplotype structure in a sample of Thoroughbred horses. ELA SNPs alone detected little LD, but microsatellites, either separately or combined with SNPs, revealed substantially more LD. A subset of markers in very high LD across the breadth of ELA may be predictive of structural polymorphisms or linked epistases that are important drivers of haplotype structure in Thoroughbreds.     

Characterization of single nucleotide polymorphism markers for eelgrass (Zostera marina)

We characterized 37 single nucleotide polymorphism (SNP) makers for eelgrass Zostera marina. SNP markers were developed using existing EST (expressed sequence tag)-libraries to locate polymorphic loci and develop primers from the functional expressed genes that are deposited in The ZOSTERA database (V1.2.1). SNP loci were genotyped using a single-base-extension approach which facilitated high-throughput genotyping with minimal optimization time. These markers show a wide range of variability among 25 eelgrass populations and will be useful for population genetic studies including evaluation of population structure, historical demography, and phylogeography. Potential applications include haplotype inference of physically linked SNPs and identification of genes under selection for temperature and desiccation stress.     

The impact of missing and erroneous genotypes on tagging SNP selection and power of subsequent association tests

OBJECTIVE: Single nucleotide polymorphisms (SNPs) serve as effective markers for localizing disease susceptibility genes, but current genotyping technologies are inadequate for genotyping all available SNP markers in a typical linkage/association study. Much attention has recently been paid to methods for selecting the minimal informative subset of SNPs in identifying haplotypes, but there has been little investigation of the effect of missing or erroneous genotypes on the performance of these SNP selection algorithms and subsequent association tests using the selected tagging SNPs. The purpose of this study is to explore the effect of missing genotype or genotyping error on tagging SNP selection and subsequent single marker and haplotype association tests using the selected tagging SNPs. METHODS: Through two sets of simulations, we evaluated the performance of three tagging SNP selection programs in the presence of missing or erroneous genotypes: Clayton's diversity based program htstep, Carlson's linkage disequilibrium (LD) based program ldSelect, and Stram's coefficient of determination based program tagsnp.exe. RESULTS: When randomly selected known loci were relabeled as 'missing', we found that the average number of tagging SNPs selected by all three algorithms changed very little and the power of subsequent single marker and haplotype association tests using the selected tagging SNPs remained close to the power of these tests in the absence of missing genotype. When random genotyping errors were introduced, we found that the average number of tagging SNPs selected by all three algorithms increased. In data sets simulated according to the haplotype frequecies in the CYP19 region, Stram's program had larger increase than Carlson's and Clayton's programs. In data sets simulated under the coalescent model, Carlson's program had the largest increase and Clayton's program had the smallest increase. In both sets of simulations, with the presence of genotyping errors, the power of the haplotype tests from all three programs decreased quickly, but there was not much reduction in power of the single marker tests. CONCLUSIONS: Missing genotypes do not seem to have much impact on tagging SNP selection and subsequent single marker and haplotype association tests. In contrast, genotyping errors could have severe impact on tagging SNP selection and haplotype tests, but not on single marker tests.     

Development of versatile gene-based SNP assays in maize (<Emphasis Type="Italic">Zea mays</Emphasis> L.)

A large number of maize single nucleotide polymorphism (SNP) candidate sequences have been generated and deposited in public databases. However, very little work has been done to date to comprehensively characterize those SNPs and identify a set of markers, which potentially would have high impact in molecular genetics research and breeding programs. Here we describe a multi-step process to identify highly polymorphic gene-based SNPs among ~130,000 public markers. A set of 695 highly polymorphic SNPs (minor allele frequency value >0.3), identified within exons, 5′ and 3′ untranslated regions of genes, were converted into four of the most popular high-throughput genotyping assays that include Illumina’s GoldenGate and Infinium chemistries, Life Technologies’ TaqMan assay and KBioSciences’ KASPar assay. The term “versatile” was applied to 162 gene-based SNPs that were successfully converted into all four chemistries and had perfect genotypic clustering patterns. This subset of discovered versatile SNP markers represents a universal tool for application in various molecular genetics and breeding projects in maize, where genotyping is based on one of the four above-mentioned chemistries. This study demonstrated that despite the availability of millions of discovered SNPs in maize, only a very small portion of those polymorphisms could be utilized for the development of robust, versatile assays, and has real practical value in marker-assisted selection.     

Development,inheritance and evaluation of 55 novel single nucleotide polymorphism markers for parentage assignment in the Pacific oyster (Crassostrea gigas)

Expressed sequence tags (ESTs) are essential to ascertain gene function, but also to identify polymorphic gene-associated single nucleotide polymorphisms (SNPs) (type I markers) suitable for map construction and population analysis in the Pacific oyster (Crassostrea gigas). In this study, a total of 48,769 putative SNPs were detected from 46,171 ESTs of the Pacific oyster. Fifty-five gene-derived SNPs were isolated and characterized by means of high resolution melting analysis. The observed and expected heterozygosities ranged from 0.063–0.563 and 0.091–0.448, with an average of 0.284 and 0.279, respectively. The SNPs were tested on 6 families of C. gigas for examination of inheritance mode of SNPs. One hundred and thirty-two tests of segregation ratios at 48 loci revealed 30 (22 %) significant departures from expected Mendelian ratios, but no null allele was detected. The power of these SNPs in parentage assignment was evaluated, and the real data demonstrated that 17 % of all real offspring were unambiguously assigned parents with 30 SNPs, and 100 % of the offspring were correctly allocated to their parents when 40 or more SNPs were used. The results obtained in this study suggest that gene-derived SNPs will complement the currently available microsatellite markers and may be useful for comparative mapping, marker-assisted selection and evolutionary studies.     

SNP development from RNA‐seq data in a nonmodel fish: how many individuals are needed for accurate allele frequency prediction?

Single nucleotide polymorphisms (SNPs) are rapidly becoming the marker of choice in population genetics due to a variety of advantages relative to other markers, including higher genomic density, data quality, reproducibility and genotyping efficiency, as well as ease of portability between laboratories. Advances in sequencing technology and methodologies to reduce genomic representation have made the isolation of SNPs feasible for nonmodel organisms. RNA‐seq is one such technique for the discovery of SNPs and development of markers for large‐scale genotyping. Here, we report the development of 192 validated SNP markers for parentage analysis in Tripterygion delaisi (the black‐faced blenny), a small rocky‐shore fish from the Mediterranean Sea. RNA‐seq data for 15 individual samples were used for SNP discovery by applying a series of selection criteria. Genotypes were then collected from 1599 individuals from the same population with the resulting loci. Differences in heterozygosity and allele frequencies were found between the two data sets. Heterozygosity was lower, on average, in the population sample, and the mean difference between the frequencies of particular alleles in the two data sets was 0.135 ± 0.100. We used bootstrap resampling of the sequence data to predict appropriate sample sizes for SNP discovery. As cDNA library production is time‐consuming and expensive, we suggest that using seven individuals for RNA sequencing reduces the probability of discarding highly informative SNP loci, due to lack of observed polymorphism, whereas use of more than 12 samples does not considerably improve prediction of true allele frequencies.     

Selection and implementation of single nucleotide polymorphism markers for parentage analysis in crossbred cattle population

Crossbreeding is an essential way of improving herd performance. However, frequent parentage record errors appear, which results in the lower accuracy of genetic parameter estimation and genetic evaluation. This study aims to build a single nucleotide polymorphism (SNP) panel with sufficient power for parentage testing in the crossbred population of Simmental and Holstein cattle. The direct sequencing technique in PCR products of pooling DNA along with matrix-assisted laser desorption/ionization time-of-flight MS method for genotyping the individuals was applied. A panel comprising 50 highly informative SNPs for parentage analysis was developed in the crossbred population. The average minor allele frequency for SNPs was 0.43, and the cumulative probability of exclusion for single-parent and both-parent inference met 0.99797 and 0.999999, respectively. The maker-set for parentage verification was then used in a group of 81 trios with aid of the likelihood-based parentage-assignment program of Cervus software. Reconfirmation with on-farm records showed that this 50-SNP system could provide sufficient and reliable information for parentage testing with the parental errors for mother–offspring and sire–offspring being 8.6 and 18.5%, respectively. In conclusion, a set of low-cost and efficient SNPs for the paternity testing in the Simmental and Holstein crossbred population are provided.     

Developing genomic resources for the common bottlenose dolphin (Tursiops truncatus): isolation and characterization of 153 single nucleotide polymorphisms and 53 genotyping assays

Although single nucleotide polymorphisms (SNPs) are commonly used in human genetics, they have only recently been incorporated into genetic studies of non‐model organisms, including cetaceans. SNPs have several advantages over other molecular markers for studies of population genetics: they are quicker and more straightforward to score, cross‐laboratory comparisons of data are less complicated, and they can be used successfully with low‐quality DNA. We screened portions of the genome of one of the most abundant cetaceans in U.S. waters, the common bottlenose dolphin (Tursiops truncatus), and identified 153 SNPs resulting in an overall average of one SNP every 463 base pairs. Custom TaqMan^® Assays were designed for 53 of these SNPs, and their performance was tested by genotyping a set of bottlenose dolphin samples, including some with low‐quality DNA. We found that in 19% of the loci examined, the minor allele frequency (MAF) estimated during initial SNP ascertainment using a DNA pool of 10 individuals differed significantly from the final MAF after genotyping over 100 individuals, suggesting caution when making inferences about MAF values based on small data sets. For two assays, we also characterized the basis for unusual clustering patterns to determine whether their data could still be utilized for further genetic studies. Overall results support the use of these SNPs for accurate analysis of both poor and good‐quality DNA. We report the first SNP markers and genotyping assays for use in population and conservation genetic studies of bottlenose dolphins.     

Development of a Genotyping Microarray for Studying the Role of Gene-Environment Interactions in Risk for Lung Cancer

A microarray (LungCaGxE), based on Illumina BeadChip technology, was developed for high-resolution genotyping of genes that are candidates for involvement in environmentally driven aspects of lung cancer oncogenesis and/or tumor growth. The iterative array design process illustrates techniques for managing large panels of candidate genes and optimizing marker selection, aided by a new bioinformatics pipeline component, Tagger Batch Assistant. The LungCaGxE platform targets 298 genes and the proximal genetic regions in which they are located, using ∼13,000 DNA single nucleotide polymorphisms (SNPs), which include haplotype linkage markers with a minimum allele frequency of 1% and additional specifically targeted SNPs, for which published reports have indicated functional consequences or associations with lung cancer or other smoking-related diseases. The overall assay conversion rate was 98.9%; 99.0% of markers with a minimum Illumina design score of 0.6 successfully generated allele calls using genomic DNA from a study population of 1873 lung-cancer patients and controls.