Selection and use of SNP markers for animal identification and paternity analysis in U.S. beef cattle

An overview of recent technological developments in bovine genomics

Cattle are regarded as highly valuable animals because of their milk, beef, dung, fur, and ability to draft. The scientific community has tried a number of strategies to improve the genetic makeup of bovine germplasm. To ensure higher returns for the dairy and beef industries, researchers face their greatest challenge in improving commercially important traits. One of the biggest developments in the last few decades in the creation of instruments for cattle genetic improvement is the discovery of the genome. Breeding livestock is being revolutionized by genomic selection made possible by the availability of medium- and high-density single nucleotide polymorphism (SNP) arrays coupled with sophisticated statistical techniques. It is becoming easier to access high-dimensional genomic data in cattle. Continuously declining genotyping costs and an increase in services that use genomic data to increase return on investment have both made a significant contribution to this. The field of genomics has come a long way thanks to groundbreaking discoveries such as radiation-hybrid mapping, in situ hybridization, synteny analysis, somatic cell genetics, cytogenetic maps, molecular markers, association studies for quantitative trait loci, high-throughput SNP genotyping, whole-genome shotgun sequencing to whole-genome mapping, and genome editing. These advancements have had a significant positive impact on the field of cattle genomics. This manuscript aimed to review recent advances in genomic technologies for cattle breeding and future prospects in this field.

PMSeeker: A Scheme Based on the Greedy Algorithm and the Exhaustive Algorithm to Screen Low-Redundancy Marker Sets for Large-Scale Parentage Assignment with Full Parental Genotyping

Parentage assignment is a genetic test that utilizes genetic characteristics, such as molecular markers, to identify the parental relationships within populations, which, in commercial fish farming, are almost always large and where full information on potential parents is known. To accurately find the true parents, the genotypes of all loci in the parentage marker set (PMS) are required for each individual being tested. With the same accuracy, a PMS containing a smaller number of markers will undoubtedly save experimental costs. Thus, this study established a scheme to screen low-redundancy PMSs using the exhaustive algorithm and greedy algorithm. When screening PMSs, the greedy algorithm selects markers based on the parental dispersity index (PDI), a uniquely defined metric that outperforms the probability of exclusion (PE). With the conjunctive use of the two algorithms, non-redundant PMSs were found for more than 99.7% of solvable cases in three groups of random sample experiments in this study. Then, a low-redundancy PMS can be composed using two or more of these non-redundant PMSs. This scheme effectively reduces the number of markers in PMSs, thus conserving human and experimental resources and laying the groundwork for the widespread implementation of parentage assignment technology in economic species breeding.

Single nucleotide polymorphisms cumulating to genetic variation for fertility in crossbred (Bos taurus × Bos indicus) bull spermatozoa

Spermatozoa from high-fertile (HF) and low-fertile (LF) breeding bulls were subjected to high-throughput next-generation sequencing to identify important Single nucleotide polymorphisms (SNPs) and novel variants associated with fertility. A total of 77,038 genome-wide SNPs were identified, among which, 10,788 were novel variants. A total of 42,290 and 34,748 variants were recorded with 6115 and 4673 novel variants in in HF and LF bulls, respectively. Higher number of SNPs were identified in HF compared to LF bulls. GO analysis of filtered genes with significant variations in HF bulls indicated their involvement in oxidative phosphorylation and metabolic pathways. GO analysis of filtered genes with significant variation in LF bulls revealed their involvement in Ca2++ ion binding, structural constituent of ribosome, and biological processes like translation and ribosomal small subunit assembly. The study identified SNPs in candidate genes including TPT1, BOLA-DRA, CD74, RPS17, RPS28, RPS29, RPL14, RPL13, and RPS27A, which are linked to sperm functionality, survival, oxidative stress, and bull fertility. The identified SNPs could be used in selection of bulls for high fertility and the variation in these genes could be established as an explanation for the fertility differences in bulls upon validation in large number of bulls.

High resolution melt curve analysis identifies a novel SNP (G21A) in butyrophilin gene having significant association with milk production traits in Holstein Friesian crossbreds of Kerala

Butyrophilin (BTN1A1) gene is located in the neighborhood of a quantitative trait loci for milk production in bovine autosome 23. We verified the genetic variability of exon-3 in BTN1A1 and its association with milk production traits in Holstein Friesian crossbreds of Kerala. Genomic DNA was isolated and 94 bp fragment enclosing exon-3 was amplified by primers designed using PRIMER 3 based on reference sequence (GenBank NC_037350). Pooled amplicons were sequenced by Sanger's method and a novel single nucleotide polymorphism due to a transversion of guanine to adenine at position 21 of amplicon (G21A) leading to amino acid change arginine to glutamine was detected. The study population was genotyped by high-resolution melt curve analysis and revealed two genotypes with frequencies GG/0.84 and GA/0.14. The allele G was found to be the major one (G/0.93 and A/0.07). Moreover, association analysis of G21A with milk production traits was done using the General linear model-Analysis of Variance considering herd, season, and parity as non-genetic factors and milk production trait as a dependent variable. In analysis, animals with GA genotype were found to be having significantly higher (p ≤ 0.01) 305 day milk (GG:2720.74 ± 122.92 kg; GA:3250.20 ± 183.24 kg), fat (GG:106.55 ± 4.32 kg; GA:126.30 ± 13.35 kg), and SNF yield (GG: 211.52 ± 9.20 kg; GA: 246.90 ± 13.70 kg). However, GG (7.80 ± 0.04) genotype has significantly higher (p ≤ 0.05) SNF percent than GA (7.65 ± 0.07). Butyrophilin gene polymorphism G21A can be suggested as a molecular marker for future breeding programmes of cattle.

Single nucleotide polymorphism marker combinations for classifying Yeonsan Ogye chicken using a machine learning approach

Genetic analysis has great potential as a tool to differentiate between different species and breeds of livestock. In this study, the optimal combinations of single nucleotide polymorphism (SNP) markers for discriminating the Yeonsan Ogye chicken (Gallus gallus domesticus) breed were identified using high-density 600K SNP array data. In 3,904 individuals from 198 chicken breeds, SNP markers specific to the target population were discovered through a case-control genome-wide association study (GWAS) and filtered out based on the linkage disequilibrium blocks. Significant SNP markers were selected by feature selection applying two machine learning algorithms: Random Forest (RF) and AdaBoost (AB). Using a machine learning approach, the 38 (RF) and 43 (AB) optimal SNP marker combinations for the Yeonsan Ogye chicken population demonstrated 100% accuracy. Hence, the GWAS and machine learning models used in this study can be efficiently utilized to identify the optimal combination of markers for discriminating target populations using multiple SNP markers.

Genome-Wide Selection Signatures and Human-Mediated Introgression Events in Bos taurus indicus-influenced Composite Beef Cattle

Genetic introgression from interbreeding hybridization of European Bos taurus taurus (EBT) and Indian Bos taurus indicus (IBI) cattle breeds have been widely used to combine the climatic resilience of the IBI cattle and the higher productivity of EBT when forming new composite beef cattle (CB) populations. The subsequent breeding strategies have shifted their initial genomic compositions. To uncover population structure, signatures of selection, and potential introgression events in CB populations, high-density genotypes [containing 492,954 single nucleotide polymorphisms (SNPs) after the quality control] of 486 individuals from 15 cattle breeds, including EBT, IBI, and CB populations, along with two Bos grunniens genotypes as outgroup were used in this study. Then, in-depth population genetics analyses were performed for three CB breeds of Beefmaster, Brangus, and Santa Gertrudis. Neighbor-joining, principal components, and admixture analyses confirmed the historical introgression of EBT and IBI haplotypes into CB breeds. The f_dM statistics revealed that only 12.9% of CB populations' genetic components are of IBI origin. The results of signatures of selection analysis indicated different patterns of selection signals in the three CB breeds with primary pressure on pathways involved in protein processing and stress response in Beefmaster, cell proliferation regulation and immune response in Brangus, and amino acids and glucose metabolisms in Santa Gertrudis. An average of >90% of genomic regions underlying selection signatures were of EBT origin in the studied CB populations. Investigating the CB breeds' genome allows the estimation of EBT and IBI ancestral proportions and the locations within the genome where either taurine or indicine origin alleles are under selective pressure. Such findings highlight various opportunities to control the selection process more efficiently and explore complementarity at the genomic level in CB populations.

Unraveling genetic admixture in the Indian crossbred cattle by different approaches using Bovine 50K BeadChip

With the upsurge of crossbreeding in India, the admixture levels are highly unpredictable in the composite breeds. Hence, in the present study, 72 Vrindavani animals were assessed for the level of admixture from their known ancestors that are Holstein-Friesian, Jersey, Brown Swiss, and Hariana, through three different software, namely, STRUCTURE, ADMIXTURE, and frappe. The genotype data for ancestral breeds were obtained from a public repository, i.e., DRYAD. The Frieswal crossbred cattle along with ancestral breeds like Holstein-Friesian and Sahiwal were also investigated for the level of admixture with the help of the above-mentioned software. The Frieswal population was found to comprise an average of 62.49, 61.12, and 61.21% of Holstein-Friesian and 37.50, 38.88, and 38.80% of Sahiwal estimated through STRUCTURE, ADMIXTURE, and frappe, respectively. The Vrindavani population was found to consist of on average 39.5, 42.4, and 42.3% of Holstein-Friesian; 22.9, 22.3, and 21.7% of Jersey; 10.7, 10.6, and 11.9% of Brown Swiss; and 26.9, 24.7, and 24.1% of Hariana blood estimated through STRUCTURE, ADMIXTURE, and frappe, respectively. A greater degree of variation was noted in the results from STRUCTURE vs. frappe, STRUCTURE vs. ADMIXTURE than in ADMIXTURE vs. frappe. From this study, we conclude that the admixture analysis based on a single software should be validated through the use of many different approaches for better prediction of admixture levels.

Standardization of a SNP panel for parentage verification and identification in the domestic cat (Felis silvestris catus)

The domestic cat (Felis silvestris catus) is a valued companion animal throughout the world. Over 60 different cat breeds are accepted for competition by the cat fancy registries in different countries. Genetic markers, including short tandem repeats and SNPs, are available to evaluate and manage levels of inbreeding and genetic diversity, population and breed structure relationships, and individual identification for forensic and registration purposes. The International Society of Animal Genetics (ISAG) hosts the Applied Genetics in Companion Animals Workshop, which supports the standardization of genetic marker panels and genotyping for the identification of cats via comparison testing. SNP panels have been in development for many species, including the domestic cat. An ISAG approved core panel of SNPs for use in cat identification and parentage analyses is presented. SNPs (n = 121) were evaluated by different university-based and commercial laboratories using 20 DNA samples as part of the ISAG comparison testing procedures. Different SNP genotyping technologies were examined, including DNA arrays, genotyping-by-sequencing and mass spectroscopy, to select a robust and efficient panel of 101 SNPs as the ISAG core panel for cats. The SNPs are distributed across all chromosomes including two on the X chromosome and an XY pseudo-autosomal sexing marker (zinc-finger XY; ZFXY). A population study demonstrated that the markers have an average polymorphic information content of 0.354 and a power of exclusion greater than 0.9999. The SNP panel should keep testing affordable while also allowing for the development of additional panels to monitor health, phenotypic traits, hybrid cats and highly inbred cats.

Ultra-small SNP panels to uniquely identify individuals in thousands of samples

Context Genomic profiles are the only information source that can uniquely identify an individual but have not yet been strongly considered in the context of paddock to plate traceability due to the lack of value proposition. Aim The aim of this study was to define the minimum number of single nucleotide polymorphisms (SNP) required to distinguish a unique genotype profile for each individual sample within a large given population. At the same time, ad hoc approaches were explored to reduce SNP density, and therefore, the size of the dataset to improve computing efficiency and storage requirements while maintaining informativeness to distinguish individuals. Methods Data for this study included two datasets. One included 78 411 high-density SNP genotypes from commercial Angus cattle and the other 2107 from a research data (1000-bull genome data). In a stepwise approach, different-size SNP panels were explored, with the last step being a successive removal resulting in the smallest set of SNPs that still produced the maximum number of unique genotypes. Key results First study that has demonstrated for large datasets, that ultra-small SNP panels with 20–23 SNPs can generate unique genotypes for up to ~80 000 individuals, allowing for 100% matching accuracy. Conclusions Ultra-small SNP panels could provide an efficient method to approach the large-scale task of the traceability of beef products through the beef supply chain. Implications Genomic tools could enhance supply-chain traceability.

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.

Evaluation of the International Society for Animal Genetics bovine single nucleotide polymorphism parentage panel in South African Bonsmara and Drakensberger cattle

A panel of 200 single nucleotide polymorphisms (SNPs) have been recommended by the International Society for Animal Genetics (ISAG) for use in parentage verification of cattle. While the SNPs included on the ISAG panel are segregating in European Bos taurus and Bos indicus breeds, their applicability in South African (SA) Sanga cattle has never been evaluated. This study, therefore, assessed the usefulness of the ISAG panel in SA Bonsmara (BON) and Drakensberger (DRB) cattle. Genotypes of 185 ISAG SNPs from 64 BON and 97 DRB sire-offspring pairs were available, all of which were validated with 119,375 SNPs. Of the 185 ISAG SNPs, 14 and 18 in the BON and DRB, respectively (9 in common to both breeds), were either monomorphic, exhibited at least one discordance between validated sire-offspring pairs, or had poor call rate or clustering issue. The mean minor allele frequency of the 185 ISAG SNPs was 0.331 in the BON and 0.359 in the DRB. The combined probability of parentage exclusion (P_E) was the same (99.46%) for both breeds, while the probability of identity varied from 1.61 × 10^-48 (BON) to 1.11 × 10^-54 (DRB). Fifteen (23.4%) and 32 (33%) of the already validated sire-offspring pairs for the BON and DRB, respectively, were determined by the ISAG panel to be false-negatives based on a threshold of having at least two discordant SNPs. In comparison to sire discovery using the 119,375 SNPs, sire discovery using only the ISAG panel identified correctly 44 (out of 64 identified using the 119,375 SNPs) unique sire-offspring BON pairs and 62 (out of 97 identified using the 119,375 SNPs) unique sire-offspring DRB when all sires were masked. Five BON and three DRB offspring had > 1 sire nominated. This study demonstrated that the use of the ISAG panel may result in incorrect exclusions and multiple candidate sires for a given animal. Selection of more informative SNPs is, therefore, necessary in the pursuit of a low-cost and effective SNP panel for indigenous cattle breeds in SA.

Using triallelic SNPs for determining parentage in North American yak ( Bos grunniens) and estimating cattle ( B. taurus) introgression

Background: Genetic testing for pedigree accuracy is critical for managing genetic diversity in North American (NA) yak ( Bos grunniens), a population expanded mostly from imported zoological park specimens.  DNA testing also enhances species conservation by identifying recent B. taurus F1 hybrid ancestors (within three generations).  Biallelic single nucleotide polymorphisms (SNPs) can accomplish either task, but increases the marker count and costs necessary to achieve both.  Our aim was to identify novel, multifunctional, triallelic yak SNPs (tySNPs), with each having two alleles for yak parentage testing, and a third allele for identifying recent cattle introgression.  Methods:  Genome sequences were aligned to the cattle UMD3.1 assembly and SNPs were screened for 1) heterozygosity in a NA and a Chinese yak, 2) a third allele at high frequency in cattle, and 3) flanking sequences conserved in both species.  Subsequently, tySNPs were filtered for unique alignment to the haplotype-resolved F1 yak assembly.  Allele frequencies were estimated in a subset of 87 tySNPs by genotyping 170 NA yak. Results:  We identified 610 autosomal tySNPs, distributed in 441 clusters with 5 Mb average genome spacing.  The average NA yak minor allele frequency was high (0.296), while average introgressed cattle alleles were low (0.004).  In simulations with tySNPs, 28 were sufficient for globally-unique animal identification (P _I=5.81x10 ^-12), 87 were able to exclude 19 random bulls from parentage at the 99% level without using the dam's genotype (P _E=5.3x10 ^-4), and 87 were able to detect F1 hybridization events after three generations of yak backcrosses (1/16th B. taurus germplasm). Conclusions:  Identifying animals, determining parentage and detecting recent hybridization events was efficient with as few as 87 tySNPs.  A similar triallelic approach could be used with other bottlenecked Bos species that hybridize with cattle, such as NA plains bison ( B. bison).

Symposium review: Advances in sequencing technology herald a new frontier in cattle genomics and genome-enabled selection

The cattle reference genome assembly has underpinned major innovations in beef and dairy genetics through genome-enabled selection, including removal of deleterious recessive variants and selection for favorable alleles affecting quantitative production traits. The initial reference assemblies, up to and including UMD3.1 and Btau4.1, were based on a combination of clone-by-clone sequencing of bacterial artificial chromosome clones generated from blood DNA of a Hereford bull and whole-genome shotgun sequencing of blood DNA from his inbred daughter/granddaughter named L1 Dominette 01449 (Dominette). The approach introduced assembly gaps, misassemblies, and errors, and it limited the ability to assemble regions that undergo rearrangement in blood cells, such as immune gene clusters. Nonetheless, the reference supported the creation of genotyping tools and provided a basis for many studies of gene expression. Recently, long-read sequencing technologies have emerged that facilitated a re-assembly of the reference genome, using lung tissue from Dominette to resolve many of the problems and providing a bridge to place historical studies in common context. The new reference, ARS-UCD1.2, successfully assembled germline immune gene clusters and improved overall continuity (i.e., reduction of gaps and inversions) by over 250-fold. This reference properly places nearly all of the legacy genetic markers used for over a decade in the industry. In this review, we discuss the improvements made to the cattle reference; remaining issues present in the assembly; tools developed to support genome-based studies in beef and dairy cattle; and the emergence of newer genome assembly methods that are producing even higher-quality assemblies for other breeds of cattle at a fraction of the cost. The new frontier for cattle genomics research will likely include a transition from the individual Hereford reference genome, to a "pan-genome" reference, representing all the DNA segments existing in commonly used cattle breeds, bringing the cattle reference into line with the current direction of human genome research.

Comparative analysis of microsatellite and SNP markers for parentage testing in the golden snub-nosed monkey (Rhinopithecus roxellana)

Microsatellite markers are popular for assigning parentage, but single-nucleotide polymorphisms (SNPs) have only been applied in this area recently. To evaluate these two markers which have been previously studied in golden snub-nosed monkeys, we genotyped 12 individuals using 37 microsatellite loci and 37 SNP markers. The data showed that 32 of 37 microsatellite loci were polymorphic, and most microsatellite loci were high informative (mean PIC = 0.599). Meanwhile, 24 of 37 SNP markers were polymorphic and most were low informative (mean PIC = 0.244). For microsatellites, the combined exclusion probability with one-parent-unknown/known (CE-1P/CE-2P) nearly reached 1, while for the SNP markers, CE-2P only reached 0.9582. Under the condition of one parent known/unknown, the CE-2P and CE-1P could meet the international human parental standard (0.9973) by using five or nine microsatellite loci respectively. For SNP markers, we doubled the loci (n = 48) and simulated parentage testing, and the data showed that the CE-2P was 0.998 while the CE-1P was still low. This result indicated that the SNP loci which we used here had low polymorphism and that more loci need to be developed in the future. In addition, we corrected one case of failed identification by excluding siblings and reducing the range of candidate paternities.

Genetic characterization of White Fulani cattle in Nigeria: A comparative study

Objective

The objective of the present study was to evaluate heterozygosis in cattle population, and to characterize White Fulani breed by identifying DNA markers considering microsatellites.

Materials and Methods

A total of 41 cattle were randomly selected and used for sample (wool) collection for the characterization and identification of phenotypic traits of cattle in Nigeria. The DNA samples from the samples were prepared. Twelve microsatellite primers were used for the microsatellite analysis in the genomic DNA of cattle. The reinforced products were analyzed to determine polymorphic alleles and their frequencies.

Results

White Fulani is characterized by a high degree of genetic diversity. The microsatellites have multiple alleles and may show heterozygosity frequencies of at least 70%. White Fulani cows and their F1 descendants form a common cluster, to which the bulls of the Kuru and Red Boro breeds are adjacent. There is a clear differentiation of purebred populations of Tajik zebu-like cattle (Q = 98.7%) and a significant proportion of white Fulani (Q = 81.8%) from Nigeria. The microsatellite analysis of zebu of Nigeria allowed identifying a total of 80 alleles. In the KURU and PAX-KR-BOR rocks, 17 and 19 alleles were identified, respectively. In F1, 51 alleles were detected.

Conclusion

White Fulani cattle are characterized by a high degree of genetic diversities. This makes it a highly informative source in genetic analysis. The results can be applied in dealing with the conservation and sustainable applications of genetic resources in the Nigerian cattle population.

The PLAG1 mRNA expression analysis among genetic variants and relevance to growth traits in Chinese cattle

Pleomorphic adenoma gene 1 (PLAG1) encodes a developmentally regulated zinc finger protein, locating in growth-related QTNs. The mRNA expression of this gene was investigated in different tissues and from two different developmental periods, whilst to explore the functions of PLAG1 in growth traits of cattle. The results showed that PLAG1 was expressed in all examined tissues. However, PLAG1 expression levels in all examined tissues were significantly different between the 5-month fetus and 36-month adult cattle. Our juvenile results indicated PLAG1 is primarily expressed in embryonic tissues of Chinese cattle. Furthermore, two variations were identified. Association analysis revealed that the two variations were associated with growth traits (p < 0.05 or p < 0.01). These new findings provide a comprehensive overview of the critical roles of PLAG1 in growth traits modulation and can be highlighted as candidate molecular markers in cattle breeding.

Pedigree verification and parentage assignment using genomic information in the Mexican Holstein population

Genealogical information is an essential tool for carrying out any genetic improvement program. The objective of this study was to determine the accuracy of pedigree information in the Mexican registered Holstein population using genomic data available in Mexico and for the US Holstein population. The study included 7,508 animals (158 sires and 7,350 cows) that were born from 2002 through 2014, registered with Holstein de México, and genotyped with single nucleotide polymorphism arrays of different densities. Parentage could not be validated for 17% of sires of cows and 12% of sires of bulls. Most (79%) of the dams of cows and the dams of bulls had no genotype available and could not be validated. A parentage test was possible for only 6,104 sires of cows, 139 sires of bulls, 1,519 dams of cows, and 33 dams of bulls. Of the animals with a parentage test, parent assignment was confirmed for 89% of sires of cows, 92% of dams of cows, 95% of sires of bulls, and 97% of dams of bulls. Parent discovery was possible for some animals without confirmed parents: 17% for sires of cows, 2.5% for dams of cows, 43% for sires of bulls, and 0% for dams of bulls. Of the 7,795 progeny tests, 777 had parent conflicts, which is an error rate of 9.97% for parental recording in the population, a rate that is similar to those recently reported for other populations. True parents for some progeny conflicts (15%) were discovered for the Mexican population, and the remaining parents were assigned as unknown. Expected effects of misidentification on rate of genetic gain could be decreased by half if genealogical errors were decreased to 5%. This study indicates that genotyping and genealogy recovery may help in increasing rates of genetic improvement in the Mexican registered Holstein population.

Functional SNP panel for parentage assessment and assignment in worldwide goat breeds

BACKGROUND

International standard panels of single nucleotide polymorphisms (SNPs) have replaced microsatellites in several species for parentage assessment and assignment (PA) purposes. However, such a resource is still lacking in goats. The application of a cheap tool for PA would help the management of goat populations by improving the reliability of pedigree registration and, consequently, allow a better implementation of breeding schemes or conservation programs.

RESULTS

Using data from the current GoatSNP50 chip, starting from a worldwide dataset of more than 4000 animals belonging to more than 140 breeds and populations from the AdaptMap initiative, we selected a panel of 195 SNPs. The assignment rate of this panel was up to 100% on an additional dataset that included 2000 Alpine and Saanen animals and highly related candidate sires.

CONCLUSIONS

In this study, we defined a highly informative SNP panel, which will be publicly available to worldwide breeders and laboratories. Its development on such a large number of breeds and populations, together with validation on a second set of cosmopolitan breeds, makes it a promising and important genomic tool for the goat species.

Selection and effectiveness of informative SNPs for paternity in Chinese Simmental cattle based on a high-density SNP array

Incorrect paternity assignment in cattle can significantly influence the accuracy of genetic evaluation. Recent advances in high-throughput technology have facilitated the identification of single nucleotide polymorphism (SNP) markers and their applications for filiation and individual identification. We genotyped 1074 bulls from a reference population of Chinese Simmental cattle for genomic selection using a BovineSNP770K BeadChip. Among them, a total of 136 bulls were randomly selected to design a suitable low-density SNP panel for paternity testing in Simmental cattle. Our results showed that 50 SNPs were determined to be the most informative markers in parental testing, with an accuracy of 99.89% for CPE (cumulative probability of exclusion) in the unknown female parent case. The 50 highly informative SNP markers were distributed across 25 chromosomes, and the mean intermarker distance per chromosome was 26.72 Mb. The average minor allele frequency (MAF), expected heterozygosity (HE), and polymorphic information content (PIC) values were 0.3748, 0.4998, and 0.4818, respectively. Finally, the 50 identified SNPs were used to estimate paternity for the remaining 938 of 1074 bulls from 23 farms. Our results revealed that 76.75% of the 938 bulls were assigned parentage to the pedigree sires with 95% confidence, and the rate of pedigree record mistakes ranged from 9.52%-39.29% in different herds. Our study is the first attempt to provide valuable insights into the extraction of informative markers through the application of high-density SNP chips for paternity testing in Chinese Simmental cattle.

Discovery of SNPs for individual identification by reduced representation sequencing of moose (Alces alces)

Monitoring of wild animal populations is challenging, yet reliable information about population processes is important for both management and conservation efforts. Access to molecular markers, such as SNPs, enables population monitoring through genotyping of various DNA sources. We have developed 96 high quality SNP markers for individual identification of moose (Alces alces), an economically and ecologically important top-herbivore in boreal regions. Reduced representation libraries constructed from 34 moose were high-throughput de novo sequenced, generating nearly 50 million read pairs. About 50 000 stacks of aligned reads containing one or more SNPs were discovered with the Stacks pipeline. Several quality criteria were applied on the candidate SNPs to find markers informative on the individual level and well representative for the population. An empirical validation by genotyping of sequenced individuals and additional moose, resulted in the selection of a final panel of 86 high quality autosomal SNPs. Additionally, five sex-specific SNPs and five SNPs for sympatric species diagnostics are included in the panel. The genotyping error rate was 0.002 for the total panel and probability of identities were low enough to separate individuals with high confidence. Moreover, the autosomal SNPs were highly informative also for population level analyses. The potential applications of this SNP panel are thus many including investigations of population size, sex ratios, relatedness, reproductive success and population structure. Ideally, SNP-based studies could improve today’s population monitoring and increase our knowledge about moose population dynamics.

SNP Data Quality Control in a National Beef and Dairy Cattle System and Highly Accurate SNP Based Parentage Verification and Identification

A major use of genetic data is parentage verification and identification as inaccurate pedigrees negatively affect genetic gain. Since 2012 the international standard for single nucleotide polymorphism (SNP) verification in Bos taurus cattle has been the ISAG SNP panels. While these ISAG panels provide an increased level of parentage accuracy over microsatellite markers (MS), they can validate the wrong parent at ≤1% misconcordance rate levels, indicating that more SNP are needed if a more accurate pedigree is required. With rapidly increasing numbers of cattle being genotyped in Ireland that represent 61 B. taurus breeds from a wide range of farm types: beef/dairy, AI/pedigree/commercial, purebred/crossbred, and large to small herd size the Irish Cattle Breeding Federation (ICBF) analyzed different SNP densities to determine that at a minimum ≥500 SNP are needed to consistently predict only one set of parents at a ≤1% misconcordance rate. For parentage validation and prediction ICBF uses 800 SNP (ICBF800) selected based on SNP clustering quality, ISAG200 inclusion, call rate (CR), and minor allele frequency (MAF) in the Irish cattle population. Large datasets require sample and SNP quality control (QC). Most publications only deal with SNP QC via CR, MAF, parent-progeny conflicts, and Hardy-Weinberg deviation, but not sample QC. We report here parentage, SNP QC, and a genomic sample QC pipelines to deal with the unique challenges of >1 million genotypes from a national herd such as SNP genotype errors from mis-tagging of animals, lab errors, farm errors, and multiple other issues that can arise. We divide the pipeline into two parts: a Genotype QC and an Animal QC pipeline. The Genotype QC identifies samples with low call rate, missing or mixed genotype classes (no BB genotype or ABTG alleles present), and low genotype frequencies. The Animal QC handles situations where the genotype might not belong to the listed individual by identifying: >1 non-matching genotypes per animal, SNP duplicates, sex and breed prediction mismatches, parentage and progeny validation results, and other situations. The Animal QC pipeline make use of ICBF800 SNP set where appropriate to identify errors in a computationally efficient yet still highly accurate method.

Comparison of beef traceability in serial and parallel fabrication systems using RFID and two-dimensional barcodes

Traceability of beef attributes from small- and mid-sized farms through supply chains is a market barrier. The objective of this trial was to determine the influence of fabrication method on beef traceability system requirements. Individual identities of 54 animals were maintained through harvest, processing, packaging, and distribution. At harvest, each animal’s unique radio frequency identification (RFID) animal identification number was transferred to a harvest label on each carcass quarter. Following transportation to a processor, nine carcasses were processed on alternating days by one of the two methods. Carcasses were fabricated, using a serial fabrication method (SFM), into wholesale cuts one at a time or fabricated using a parallel fabrication method (PFM), by processing multiple hindquarters or forequarters simultaneously into wholesale cuts. In-process labels were generated by scanning the two-dimensional (2D) barcode on the harvest label with a handheld mobile computer and printed from a wireless mobile printer. Tracking of SFM and PFM carcass quarters was accomplished by creating in-process labels for lugs and individual wholesale cuts, respectively. The process was recorded and the data was captured from video analysis. The mean number of in-process labels generated per carcass for SFM was 3.7 and for PFM was 30.9 (P < 0.01). The amount of time required for generating in-process labels for SFM (2 min 16 s) was less than PFM (8 min 45 s) (P = 0.01). The amount of time required to label each carcass was less (P < 0.01) for SFM (18 s) than for PFM (3 min 10 s) with in-process labels. Total cost of traceability, including fixed and consumable cost per carcass, was nearly twice as much for PFM ($17.98) than SFM ($9.02). Traceability, within both processing methods, was found to have 100% fidelity, as verified using DNA marker genotyping. Overall, the number of labels generated for traceability was less for SFM than that for PFM. The overall time spent on generating, applying, and removing labels was less for SFM than that for PFM. The total cost of traceability was approximately half for SFM compared with that for PFM; however both methods were able to track product accurately. Tracking of beef from individual animals, using RFID ear tags and 2D barcodes, appears to be feasible for the fabrication methods used in this study.

A single nucleotide polymorphism genotyping platform for the authentication of patient derived xenografts

Patient derived xenografts (PDXs) have become a vital, frequently used, component of anti-cancer drug development. PDXs can be serially passaged in vivo for years, and shared across laboratories. As a consequence, the potential for mis-identification and cross-contamination is possible, yet authentication of PDXs appears limited. We present a PDX Authentication System (PAS), by combining a commercially available OpenArray assay of single nucleotide polymorphisms (SNPs) with in-house R studio programs, to validate PDXs established in individual mice from acute lymphoblastic leukemia biopsies. The PAS is sufficiently robust to identify contamination at levels as low as 3%, similar to the gold standard of short tandem repeat (STR) profiling. We have surveyed a panel of PDXs established from 73 individual leukemia patients, and found that the PAS provided sufficient discriminatory power to identify each xenograft. The identified SNP-discrepant PDXs demonstrated distinct gene expression profiles, indicating a risk of contamination for PDXs at high passage number. The PAS also allows for the authentication of tumor cells with complex karyotypes from solid tumors including prostate cancer and Ewing's sarcoma. This study highlights the demands of authenticating PDXs for cancer research, and evaluates a reliable authentication platform that utilizes a commercially available and cost-effective system.

Forensic genetics and genomics: Much more than just a human affair

While traditional forensic genetics has been oriented towards using human DNA in criminal investigation and civil court cases, it currently presents a much wider application range, including not only legal situations sensu stricto but also and, increasingly often, to preemptively avoid judicial processes. Despite some difficulties, current forensic genetics is progressively incorporating the analysis of nonhuman genetic material to a greater extent. The analysis of this material-including other animal species, plants, or microorganisms-is now broadly used, providing ancillary evidence in criminalistics in cases such as animal attacks, trafficking of species, bioterrorism and biocrimes, and identification of fraudulent food composition, among many others. Here, we explore how nonhuman forensic genetics is being revolutionized by the increasing variety of genetic markers, the establishment of faster, less error-burdened and cheaper sequencing technologies, and the emergence and improvement of models, methods, and bioinformatics facilities.

Development of a SNP panel dedicated to parentage assignment in French sheep populations

BACKGROUND

The efficiency of breeding programs partly relies on the accuracy of the estimated breeding values which decreases when pedigrees are incomplete. Two reproduction techniques are mainly used by sheep breeders to identify the sires of lambs: animal insemination and natural matings with a single ram per group of ewes. Both methods have major drawbacks, notably time-consuming tasks for breeders, and are thus used at varying levels in breeding programs. As a consequence, the percentage of known sires can be very low in some breeds and results in less accurate estimated breeding values.

RESULTS

In order to address this issue and offer an alternative strategy for obtaining parentage information, we designed a set of 249 SNPs for parentage assignment in French sheep breeds and tested its efficiency in one breed. The set was derived from the 54 K SNP chip that was used to genotype the thirty main French sheep populations. Only SNPs in Hardy-Weinberg equilibrium, displaying the highest Minor Allele Frequency across all the thirty populations and not associated with Mendelian errors in verified family trios were selected. The panel of 249 SNPs was successfully used in an on-farm test in the BMC breed and resulted in more than 95% of lambs being assigned to a unique sire.

CONCLUSION

In this study we developed a SNP panel for assignment that achieved good results in the on-farm testing. We also raised some conditions for optimal use of this panel: at least 180 SNPs should be used and a minute preparation of the list of candidate sires. Our panel also displays high levels of MAF in the SheepHapMap breeds, particularly in the South West European breeds.

A Genetic Method To Evaluate the Prevalence of Unique DNA Profiles between Sequential Ground Beef Batches

The delineation of ground beef batches has implications for the management of product disposition policies in the event of Shiga toxin-producing Escherichia coli contamination. Analysis of individual contributor animal-specific DNA profiles can provide valuable empirical data for understanding the dynamics of ground meat production processes and can act as a surrogate for cross-contamination. A genetic method was developed for characterizing the source raw material flow and carryover between discrete batches of ground beef in a large-scale commercial beef grinding operation. The application developed involves the introduction of a genetically distinct source raw material batch into the grinding system and comprehensive sampling of that index batch and subsequent batches followed by single nucleotide polymorphism genotyping of random subsamples. Capture-mark-recapture statistical techniques were used to estimate (i) the number of carcass contributors and (ii) the associated level of carryover between batches. Carryover, expressed as a percentage of the total weight of the batch material (in pounds), was observed between the genetically distinct index batch and the next sequential batch at approximately 1%. The nondetection of additional carryover to subsequent batches, with a detection level of approximately 0.2%, supports a serial dilution model of same source raw material carryover, consistent with the recorded weight of beef trimmings used in each batch. For ground beef manufacturers, this method is a simple approach for validating the independence of finished batches of beef in their grind systems in support of product disposition policies.

The Importance of Endophenotypes to Evaluate the Relationship between Genotype and External Phenotype

With the exception of a few Mendelian traits, almost all phenotypes (traits) in livestock science are quantitative or complex traits regulated by the expression of many genes. For most of the complex traits, differential expression of genes, rather than genomic variation in the gene coding sequences, is associated with the genotype of a trait. The expression profiles of the animal's transcriptome, proteome and metabolome represent endophenotypes that influence/regulate the externally-observed phenotype. These expression profiles are generated by interactions between the animal's genome and its environment that range from the cellular, up to the husbandry environment. Thus, understanding complex traits requires knowledge about not only genomic variation, but also environmental effects that affect genome expression. Gene products act together in physiological pathways and interaction networks (of pathways). Due to the lack of annotation of the functional genome and ontologies of genes, our knowledge about the various biological systems that contribute to the development of external phenotypes is sparse. Furthermore, interaction with the animals' microbiome, especially in the gut, greatly influences the external phenotype. We conclude that a detailed understanding of complex traits requires not only understanding of variation in the genome, but also its expression at all functional levels.

Genomic prediction for tick resistance in Braford and Hereford cattle

One of the main animal health problems in tropical and subtropical cattle production is the bovine tick, which causes decreased performance, hide devaluation, increased production costs with acaricide treatments, and transmission of infectious diseases. This study investigated the utility of genomic prediction as a tool to select Braford (BO) and Hereford (HH) cattle resistant to ticks. The accuracy and bias of different methods for direct and blended genomic prediction was assessed using 10,673 tick counts obtained from 3,435 BO and 928 HH cattle belonging to the Delta G Connection breeding program. A subset of 2,803 BO and 652 HH samples were genotyped and 41,045 markers remained after quality control. Log transformed records were adjusted by a pedigree repeatability model to estimate variance components, genetic parameters, and breeding values (EBV) and subsequently used to obtain deregressed EBV. Estimated heritability and repeatability for tick counts were 0.19 ± 0.03 and 0.29 ± 0.01, respectively. Data were split into 5 subsets using k-means and random clustering for cross-validation of genomic predictions. Depending on the method, direct genomic value (DGV) prediction accuracies ranged from 0.35 with Bayes least absolute shrinkage and selection operator (LASSO) to 0.39 with BayesB for k-means clustering and between 0.42 with BayesLASSO and 0.45 with BayesC for random clustering. All genomic methods were superior to pedigree BLUP (PBLUP) accuracies of 0.26 for k-means and 0.29 for random groups, with highest accuracy gains obtained with BayesB (39%) for k-means and BayesC (55%) for random groups. Blending of historical phenotypic and pedigree information by different methods further increased DGV accuracies by values between 0.03 and 0.05 for direct prediction methods. However, highest accuracy was observed with single-step genomic BLUP with values of 0.48 for -means and 0.56, which represent, respectively, 84 and 93% improvement over PBLUP. Observed random clustering cross-validation breed-specific accuracies ranged between 0.29 and 0.36 for HH and between 0.55 and 0.61 for BO, depending on the blending method. These moderately high values for BO demonstrate that genomic predictions could be used as a practical tool to improve genetic resistance to ticks and in the development of resistant lines of this breed. For HH, accuracies are still in the low to moderate side and this breed training population needs to be increased before genomic selection could be reliably applied to improve tick resistance.

A method for single nucleotide polymorphism selection for parentage assessment in goats

Accurate pedigrees are essential to optimize genetic improvement and conservation of animal genetic resources. In goats, the use of mating groups and kidding management procedures hamper the identification of parentage. Small panels of single nucleotide polymorphisms (SNP) have been proposed in other species to substitute microsatellites for parentage assessment. Using data from the current GoatSNP50 chip, we developed a new 3-step procedure to identify a low-density SNP panel for highly accurate parentage assessment. Methodologies for SNP selection used in other species are less suitable in the goat because of uncertainties in the genome assembly. The procedure developed in this study is based on parent-offspring identification and on estimation of Mendelian errors, followed by canonical discriminant analysis identification and stepwise regression reduction. Starting from a reference sample of 109 Alpine goats with known pedigree relationships, we first identified a panel of 200 SNP that was further reduced to 2 final panels of 130 and 114 SNP with random coincidental match inclusion of 1.51×10(-57) and 2.94×10(-34), respectively. In our reference data set, all panels correctly identified all parent-offspring combinations, revealing a 40% pedigree error rate in the information provided by breeders. All reference trios were confirmed by official tests based on microsatellites. Panels were also tested on Saanen and Teramana breeds. Although the testing on a larger set of breeds in the reference population is still needed to validate these results, our findings suggest that our procedure could identify SNP panels for accurate parentage assessment in goats or in other species with unreliable marker positioning.

Limitations of GCTA as a solution to the missing heritability problem

Genome-wide association studies (GWASs) seek to understand the relationship between complex phenotype(s) (e.g., height) and up to millions of single-nucleotide polymorphisms (SNPs). Early analyses of GWASs are commonly believed to have "missed" much of the additive genetic variance estimated from correlations between relatives. A more recent method, genome-wide complex trait analysis (GCTA), obtains much higher estimates of heritability using a model of random SNP effects correlated between genotypically similar individuals. GCTA has now been applied to many phenotypes from schizophrenia to scholastic achievement. However, recent studies question GCTA's estimates of heritability. Here, we show that GCTA applied to current SNP data cannot produce reliable or stable estimates of heritability. We show first that GCTA depends sensitively on all singular values of a high-dimensional genetic relatedness matrix (GRM). When the assumptions in GCTA are satisfied exactly, we show that the heritability estimates produced by GCTA will be biased and the standard errors will likely be inaccurate. When the population is stratified, we find that GRMs typically have highly skewed singular values, and we prove that the many small singular values cannot be estimated reliably. Hence, GWAS data are necessarily overfit by GCTA which, as a result, produces high estimates of heritability. We also show that GCTA's heritability estimates are sensitive to the chosen sample and to measurement errors in the phenotype. We illustrate our results using the Framingham dataset. Our analysis suggests that results obtained using GCTA, and the results' qualitative interpretations, should be interpreted with great caution.

How many markers are enough? Factors influencing parentage testing in different livestock populations

Reliability of parentage test panels is usually based on its power to exclude wrong parentage assignments based on allele frequencies. We evaluated the rates of false exclusions and inclusions in parentage assignments, and how these results are affected by allele frequencies, panel sizes and the number of allowed mismatches. We also evaluated the reliability of parentage testing by comparing populations with distinct genetic backgrounds using pure and composite families of cattle and sheep. Allowing for 1% genotype mismatches in true parent-offspring relations provided the best compromise between false-positive and false-negative assignments. Pure breeds needed at least 200-210 single-nucleotide polymorphism (SNP) markers to correctly assign relations, but between 700 and 890 markers to avoid assigning incorrect relationships. Composite breeds needed between 220 (sheep) and 500 (cattle) markers for correct assignment; 680 (cattle) to 4400 (sheep) SNPs were needed to eliminate false-positive assignments. Allowing 0% genotype mismatches decreased false-positive but increased false-negative assignments, whilst a higher threshold of 2% showed the opposite effects. Panels with high minor allele frequencies (0.35-0.45) provided the best chance for correct parentage resolutions requiring fewer markers. Further, we propose that a dynamic threshold would allow adapting to population specific error rates. A comparison to the performance of the official International Society for Animal Genetics SNP panel for cattle and a recently published SNP panel for sheep showed that randomly selected markers performed only slightly worse for the applied parentage test based on opposing homozygotes. This suggests that even with carefully selected panels, only marginal assignment improvements are obtainable for a particular number of SNPs. The main point for improvement is the number of markers used. We recommend using at least 200 SNP markers for parentage testing if the aim is to reduce false-negative results. To fully exclude false positives at least 700 markers are required.

Characterization of the bovine gene LIPE and possible influence on fatty acid composition of meat

LIPE is an intracellular neutral lipase, which is capable of hydrolyzing a variety of esters and plays a key role in the mobilization of fatty acids from diacylglycerols. The objectives of this study were to characterize the genetic polymorphism of bovine LIPE gene and to evaluate the possible association between three SNPs in the coding regions of this gene with the fatty acid composition of meat in a cattle population. Forty-three unrelated animals from different cattle breeds were re-sequenced and 21 SNPs were detected over approximately 2600 bp, five of these SNPs were novel. Three SNPs were selected, on the basis of evolutionary conservation, to perform validation and association studies in a crossbred cattle population. Our results may suggest a possible association of SNP1 with contents of oleic acid and total monounsaturated fatty acids (p < 0.01), and SNP2 and SNP3 with Heneicosylic acid content (p < 0.01), may be helpful to improve the quality of meat and improve health.

Effectiveness of single-nucleotide polymorphisms to investigate cattle rustling

Short tandem repeats (STR)s have been the eligible markers for forensic animal genetics, despite single-nucleotide polymorphisms (SNP)s became acceptable. The technology, the type, and amount of markers could limit the investigation in degraded forensic samples. The performance of a 32-SNP panel genotyped through OpenArrays(TM) (real-time PCR based) was evaluated to resolve cattle-specific forensic cases. DNA from different biological sources was used, including samples from an alleged instance of cattle rustling. SNPs and STRs performance and repeatability were compared. SNP call rate was variable among sample type (average = 80.18%), while forensic samples showed the lowest value (70.94%). The repeatability obtained (98.7%) supports the used technology. SNPs had better call rates than STRs in 12 of 20 casework samples, while forensic index values were similar for both panels. In conclusion, the 32-SNPs used are as informative as the standard bovine STR battery and hence are suitable to resolve cattle rustling investigations.

Prediction of expected genetic variation within groups of offspring for innovative mating schemes

Background

Experience from progeny-testing indicates that the mating of popular bull sires that have high estimated breeding values with excellent dams does not guarantee the production of offspring with superior breeding values. This is explained partly by differences in the standard deviation of gamete breeding values (SDGBV) between animals at the haplotype level. The SDGBV depends on the variance of the true effects of single nucleotide polymorphisms (SNPs) and the degree of heterozygosity. Haplotypes of 58 035 Holstein animals were used to predict and investigate expected SDGBV for fat yield, protein yield, somatic cell score and the direct genetic effect for stillbirth.

Results

Differences in SDGBV between animals were detected, which means that the groups of offspring of parents with low SDGBV will be more homogeneous than those of parents with high SDGBV, although the expected mean breeding values of the progeny will be the same. SDGBV was negatively correlated with genomic and pedigree inbreeding coefficients and a small loss of SDGBV over time was observed. Sires that had relatively low mean gamete breeding values but high SDGBV had a higher probability of producing extremely positive offspring than sires that had a high mean gamete breeding value and low SDGBV.

Conclusions

An animal’s SDGBV can be estimated based on genomic information and used to design specific genomic mating plans. Estimated SDGBV are an additional tool for mating programs, which allows breeders to identify and match mating partners using specific haplotype information.

SNPs for parentage testing and traceability in globally diverse breeds of sheep

DNA-based parentage determination accelerates genetic improvement in sheep by increasing pedigree accuracy. Single nucleotide polymorphism (SNP) markers can be used for determining parentage and to provide unique molecular identifiers for tracing sheep products to their source. However, the utility of a particular "parentage SNP" varies by breed depending on its minor allele frequency (MAF) and its sequence context. Our aims were to identify parentage SNPs with exceptional qualities for use in globally diverse breeds and to develop a subset for use in North American sheep. Starting with genotypes from 2,915 sheep and 74 breed groups provided by the International Sheep Genomics Consortium (ISGC), we analyzed 47,693 autosomal SNPs by multiple criteria and selected 163 with desirable properties for parentage testing. On average, each of the 163 SNPs was highly informative (MAF≥0.3) in 48±5 breed groups. Nearby polymorphisms that could otherwise confound genetic testing were identified by whole genome and Sanger sequencing of 166 sheep from 54 breed groups. A genetic test with 109 of the 163 parentage SNPs was developed for matrix-assisted laser desorption/ionization-time-of-flight mass spectrometry. The scoring rates and accuracies for these 109 SNPs were greater than 99% in a panel of North American sheep. In a blinded set of 96 families (sire, dam, and non-identical twin lambs), each parent of every lamb was identified without using the other parent's genotype. In 74 ISGC breed groups, the median estimates for probability of a coincidental match between two animals (PI), and the fraction of potential adults excluded from parentage (PE) were 1.1×10(-39) and 0.999987, respectively, for the 109 SNPs combined. The availability of a well-characterized set of 163 parentage SNPs facilitates the development of high-throughput genetic technologies for implementing accurate and economical parentage testing and traceability in many of the world's sheep breeds.

A high throughput single nucleotide polymorphism multiplex assay for parentage assignment in New Zealand sheep

Accurate pedigree information is critical to animal breeding systems to ensure the highest rate of genetic gain and management of inbreeding. The abundance of available genomic data, together with development of high throughput genotyping platforms, means that single nucleotide polymorphisms (SNPs) are now the DNA marker of choice for genomic selection studies. Furthermore the superior qualities of SNPs compared to microsatellite markers allows for standardization between laboratories; a property that is crucial for developing an international set of markers for traceability studies. The objective of this study was to develop a high throughput SNP assay for use in the New Zealand sheep industry that gives accurate pedigree assignment and will allow a reduction in breeder input over lambing. This required two phases of development- firstly, a method of extracting quality DNA from ear-punch tissue performed in a high throughput cost efficient manner and secondly a SNP assay that has the ability to assign paternity to progeny resulting from mob mating. A likelihood based approach to infer paternity was used where sires with the highest LOD score (log of the ratio of the likelihood given parentage to likelihood given non-parentage) are assigned. An 84 “parentage SNP panel” was developed that assigned, on average, 99% of progeny to a sire in a problem where there were 3,000 progeny from 120 mob mated sires that included numerous half sib sires. In only 6% of those cases was there another sire with at least a 0.02 probability of paternity. Furthermore dam information (either recorded, or by genotyping possible dams) was absent, highlighting the SNP test’s suitability for paternity testing. Utilization of this parentage SNP assay will allow implementation of progeny testing into large commercial farms where the improved accuracy of sire assignment and genetic evaluations will increase genetic gain in the sheep industry.