Epidemiological investigation of insulin dysregulation in Shetland and Welsh ponies in Australia.

BACKGROUND: Insulin dysregulation (ID) is central to equine metabolic syndrome. There are limited epidemiological studies investigating dynamic testing of ID in ponies. OBJECTIVES: To evaluate prevalence and risk factors for ID through dynamic testing of hyperinsulinaemia (DHI) and insulin resistance (IR). STUDY DESIGN: Cross-sectional. METHODS: Sex, age, breed, height, cresty neck score (CNS), body condition score (BCS), laminitis, HMGA2:c.83G>A genotype and pituitary pars intermedia dysfunction (PPID) status were documented. Dynamic hyperinsulinaemia was diagnosed with an oral sugar test (OST) and IR with an insulin tolerance test (ITT). Owners completed surveys reporting activity, laminitis history and perception of body condition using a (1-9) visual analogue scale (VASo). Ordinal scores were converted to binary outcomes for CNS (≤2/5 or ≥3/5), BCS and VASo (≤6/9 or ≥7/9). Variables associated with insulin concentrations, glucose reduction after the ITT and laminitis were evaluated with mixed effects regression models accounting for random effects of farms. RESULTS: Among 167 ponies tested, median (range) age was 9 (4-21) years and BCS was 6 (4-8). Prevalence (95% confidence interval [CI]) of ID was 61 (53-68)%. Factors associated with insulin concentrations (estimate [95% CI]; µIU/mL) 60 min post-OST were: age (1.07 [1.02-1.11]), CNS (≥3/5, 1.52 [1.04-2.23]) and VASo (≥7/9, 1.75 [1.09-2.79]); and 90 min post-OST were: age (1.08 [1.03-1.12]), CNS (≥3/5, 1.80 [1.22-2.64]), VASo (≥7/9, 2.49 [1.52-4.08]) and sex (male, 0.64 [0.45-0.91]). Factors associated with glucose reduction after the ITT (estimate [95% CI]; %) were: age (-1.34 [-2.01 to -0.67]), sex (female, -6.21 [-11.68 to -0.74]) and VASo (≥7/9, -1.74 [-18.89 to -4.78]). Factors associated with laminitis (odds ratio [95% CI]) were DHI (4.60 [1.68-12.58]), IR (3.66 [1.26-10.61]) and PPID (11.75 [1.54-89.40]). MAIN LIMITATIONS: Single time-point sampling, laminitis definition and diet analysis. CONCLUSIONS: Ageing, being female and owner-perceived obesity were associated with ID.

Evaluation of an HMGA2 variant contribution to height and basal insulin concentrations in ponies.

BACKGROUND: The HMGA2:c.83G>A variant was identified in Welsh ponies having pleiotropic effects on height and insulin concentration. OBJECTIVE: Determine whether the HMGA2:c.83G>A variant is associated with decreased height and higher basal insulin concentrations across pony breeds. ANIMALS: Two hundred thirty-six ponies across 6 breeds. METHODS: Cross-sectional study. Ponies were genotyped for the HMGA2:c.83G>A variant and phenotyped for height and basal insulin concentrations. Stepwise regression was performed for model analysis using a linear regression model for height and mixed linear model for insulin with farm as a random effect. Coefficient of determination, pairwise comparison of the estimated marginal means and partial correlation coefficients (parcor) were calculated to assess the relationship between HMGA2 genotype and height or insulin. RESULTS: Breed and genotype accounted for 90.5% of the variation in height across breeds, and genotype explained 21% to 44% of the variation within breeds. Breed, genotype, cresty neck score, sex, age, and farm accounted for 45.5% of the variation in insulin, with genotype accounting for 7.1%. The HMGA2 A allele frequency was 62% and correlated with both height (parcor = -0.39; P < .001) and insulin (parcor = 0.22; P = .02). Pairwise comparisons found A/A ponies were >10 cm shorter than other genotypes. Compared with G/G individuals, A/A and G/A individuals had 4.3 µIU/mL (95% confidence interval [CI]: 1.8-10.5) and 2.7 µIU/mL (95% CI: 1.4-5.3) higher basal insulin concentrations, respectively. CONCLUSIONS AND CLINICAL IMPORTANCE: These data demonstrate the pleiotropic effects of the HMGA2:c.83G>A variant and its role in identifying ponies at increased risk for insulin dysregulation.

Heritability and Genomic Architecture of Episodic Exercise-Induced Collapse in Border Collies.

An episodic nervous system disorder triggered by strenuous exercise, termed border collie collapse (BCC), exists in border collies and related breeds. The genetic basis of BCC is unknown but is believed to be a complex genetic disorder. Our goal was to estimate the heritability (h2SNP) of BCC, define its underlying genetic architecture, and identify associated genomic loci using dense whole-genome single-nucleotide polymorphism (SNP) genotyping data. Genotype data were obtained for ~440,000 SNPs from 343 border collies (168 BCC cases and 175 controls). h2SNP was calculated to be 49-61% depending on the estimated BCC prevalence. A total of 2407 SNPs across the genome accounted for nearly all the h2SNP of BCC, with an estimated 2003 SNPs of small effect, 349 SNPs of moderate effect, and 56 SNPs of large effect. Genome-wide association analyses identified significantly associated loci on chromosomes 1, 6, 11, 20, and 28, which accounted for ~5% of the total BCC h2SNP. We conclude that BCC is a moderately- to highly-heritable complex polygenetic disease resulting from contributions from hundreds to thousands of genetic variants with variable effect sizes. Understanding how much the BCC phenotype is determined by genetics and whether major gene mutations are likely to exist inform veterinarians and working/stock dog communities of the true nature of this condition.

Genetics of Equine Endocrine and Metabolic Disease.

A role for a genetic contribution to equine metabolic syndrome (EMS) and pars pituitary intermedia dysfunction (PPID) has been hypothesized. Heritability estimates of EMS biochemical measurements were consistent with moderately to highly heritable traits. Further, genome-wide association analyses have identified hundreds of regions of the genome contributing to EMS and candidate variants have been identified. The genetics of PPID has not yet been proven. Continued research for the specific genetic risk factors for both EMS and PPID is crucial for gaining a better understanding of the pathophysiology of both conditions and allowing development of genetic tests.

Equine Genotyping Arrays.

High-quality genomic tools have been integral in understanding genomic architecture and function in the modern-day horse. The equine genetics community has a long tradition of pooling resources to develop genomic tools. Since the equine genome was sequenced in 2006, several iterations of high throughput genotyping arrays have been developed and released, enabling rapid and cost-effective genotyping. This review highlights the design considerations of each iteration, focusing on data available during development and outlining considerations in selecting the genetic variants included on each array. Additionally, we outline recent applications of equine genotyping arrays as well as future prospects and applications.

Erratum: Author Correction: Improved reference genome for the domestic horse increases assembly contiguity and composition.

[This corrects the article DOI: 10.1038/s42003-018-0199-z.].

Differential Gene Expression in Articular Cartilage and Subchondral Bone of Neonatal and Adult Horses.

Skeletogenesis is complex and incompletely understood. Derangement of this process likely underlies developmental skeletal pathologies. Examination of tissue-specific gene expression may help elucidate novel skeletal developmental pathways that could contribute to disease risk. Our aim was to identify and functionally annotate differentially expressed genes in equine neonatal and adult articular cartilage (AC) and subchondral bone (SCB). RNA was sequenced from healthy AC and SCB from the fetlock, hock, and stifle joints of 6 foals (≤4 weeks of age) and six adults (8-12 years of age). There was distinct clustering by age and tissue type. After differential expression analysis, functional annotation and pathway analysis were performed using PANTHER and Reactome. Approximately 1115 and 3574 genes were differentially expressed between age groups in AC and SCB, respectively, falling within dozens of overrepresented gene ontology terms and enriched pathways reflecting a state of growth, high metabolic activity, and tissue turnover in the foals. Enriched pathways were dominated by those related to extracellular matrix organization and turnover, and cell cycle and signal transduction. Additionally, we identified enriched pathways related to neural development and neurotransmission in AC and innate immunity in SCB. These represent novel potential mechanisms for disease that can be explored in future work.

Exploration of fine-scale recombination rate variation in the domestic horse.

Total genetic map length and local recombination landscapes typically vary within and across populations. As a first step to understanding the recombination landscape in the domestic horse, we calculated population recombination rates and identified likely recombination hotspots using approximately 1.8 million SNP genotypes for 485 horses from 32 distinct breeds. The resulting breed-averaged recombination map spans 2.36 Gb and accounts for 2939.07 cM. Recombination hotspots occur once per 23.8 Mb on average and account for ∼9% of the physical map length. Regions with elevated recombination rates in the entire cohort were enriched for genes in pathways involving interaction with the environment: immune system processes (specifically, MHC class I and class II genes), responses to stimuli, and serotonin receptor pathways. We found significant correlations between differences in local recombination rates and population differentiation quantified by F ST Analysis of breed-specific maps revealed thousands of hotspot regions unique to particular breeds, as well as unique "coldspots," regions where a particular breed showed below-average recombination, whereas all other breeds had evidence of a hotspot. Finally, we identified relative enrichment (P = 5.88 × 10-27) for the in silico-predicted recognition motif for equine PR/SET domain 9 (PRDM9) in recombination hotspots. These results indicate that selective pressures and PRDM9 function contribute to variation in recombination rates across the domestic horse genome.

Estimation of Actual and Ideal Bodyweight Using Morphometric Measurements of Miniature, Saddle-Type, and Thoroughbred Horses.

Adding breed type, height, and neck circumference to body length and girth circumference improves bodyweight (BW) estimation in different breeds of horses; however, equations have not been developed for all breed types. The objectives were to develop BW estimation equations for Miniature, saddle-type, and Thoroughbred horses using morphometric measurements. Measurements were collected on adult (≥3 years, nonpregnant) saddle-type (n = 209), adult (n = 249) and juvenile (<3 years, n = 61) Miniatures, and adult Thoroughbreds (n = 100). Personnel determined body condition score (BCS), measured withers height and girth circumference at the third thoracic vertebra, body length from the point of the shoulder to the point of the buttock and to a line perpendicular to the point of the buttock, and neck circumference at the midway point between the poll and withers. Each horse was weighed using a livestock scale. Bodyweight estimations equations were developed using linear regression modeling and log transformation. Mean (±standard deviation) BCS was 6.1 (±0.8), 5.4 (±0.6), 6.0 (±1.0), and 5.0 (±0.6) for adult and juvenile Miniatures, saddle-type, and Thoroughbreds, respectively. Bodyweight estimation equations developed through the current research were within 4% of the scale BW and offered improvements over previous BW estimation equations and weight tapes, which were off by 5%-25%. Owner-estimated BW was within 8%-15% of scale BW. Morphometric measurements were successfully used to develop BW equations for Miniature, saddle-type, and Thoroughbred horses. The equations will assist owners and professionals with managing horse BW and will be added to the Healthy Horse application.

Identification and validation of genetic variants predictive of gait in standardbred horses.

Several horse breeds have been specifically selected for the ability to exhibit alternative patterns of locomotion, or gaits. A premature stop codon in the gene DMRT3 is permissive for "gaitedness" across breeds. However, this mutation is nearly fixed in both American Standardbred trotters and pacers, which perform a diagonal and lateral gait, respectively, during harness racing. This suggests that modifying alleles must influence the preferred gait at racing speeds in these populations. A genome-wide association analysis for the ability to pace was performed in 542 Standardbred horses (n = 176 pacers, n = 366 trotters) with genotype data imputed to ~74,000 single nucleotide polymorphisms (SNPs). Nineteen SNPs on nine chromosomes (ECA1, 2, 6, 9, 17, 19, 23, 25, 31) reached genome-wide significance (p < 1.44 x 10-6). Variant discovery in regions of interest was carried out via whole-genome sequencing. A set of 303 variants from 22 chromosomes with putative modifying effects on gait was genotyped in 659 Standardbreds (n = 231 pacers, n = 428 trotters) using a high-throughput assay. Random forest classification analysis resulted in an out-of-box error rate of 0.61%. A conditional inference tree algorithm containing seven SNPs predicted status as a pacer or trotter with 99.1% accuracy and subsequently performed with 99.4% accuracy in an independently sampled population of 166 Standardbreds (n = 83 pacers, n = 83 trotters). This highly accurate algorithm could be used by owners/trainers to identify Standardbred horses with the potential to race as pacers or as trotters, according to the genotype identified, prior to initiating training and would enable fine-tuning of breeding programs with designed matings. Additional work is needed to determine both the algorithm's utility in other gaited breeds and whether any of the predictive SNPs play a physiologically functional role in the tendency to pace or tag true functional alleles.

Evaluation of an HMGA2 variant for pleiotropic effects on height and metabolic traits in ponies.

BACKGROUND: Ponies are highly susceptible to metabolic derangements including hyperinsulinemia, insulin resistance, and adiposity. HYPOTHESIS/OBJECTIVES: Genetic loci affecting height in ponies have pleiotropic effects on metabolic pathways and increase the susceptibility to equine metabolic syndrome (EMS). ANIMALS: Two hundred ninety-four Welsh ponies and 529 horses. METHODS: Retrospective study of horses phenotyped for metabolic traits. Correlations between height and metabolic traits were assessed by Pearson's correlation coefficients. Complementary genome-wide analysis methods were used to identify a region of interest (ROI) for height and metabolic traits, determine the fraction of heritability contributed by the ROI, and identify candidate genes. RESULTS: There was an inverse relationship between height and baseline insulin (-0.26) in ponies. Genomic signature of selection and association analyses for both height and insulin identified the same ~1.3 megabase region on chromosome 6 that contained a shared ancestral haplotype between these traits. The ROI contributed ~40% of the heritability for height and ~20% of the heritability for insulin. High-mobility group AT-hook 2 was identified as a candidate gene, and Sanger sequencing detected a c.83G>A (p.G28E) variant associated with height in Shetland ponies. In our cohort of ponies, the A allele had a frequency of 0.76, was strongly correlated with height (-0.75), and was low to moderately correlated with metabolic traits including: insulin (0.32), insulin after an oral sugar test (0.25), non-esterified fatty acids (0.19), and triglyceride (0.22) concentrations. CONCLUSIONS AND CLINICAL IMPORTANCE: These data have important implications for identifying individuals at risk for EMS.

A Vision for Development and Utilization of High-Throughput Phenotyping and Big Data Analytics in Livestock.

Automated high-throughput phenotyping with sensors, imaging, and other on-farm technologies has resulted in a flood of data that are largely under-utilized. Drastic cost reductions in sequencing and other omics technology have also facilitated the ability for deep phenotyping of livestock at the molecular level. These advances have brought the animal sciences to a cross-roads in data science where increased training is needed to manage, record, and analyze data to generate knowledge and advances in Agriscience related disciplines. This paper describes the opportunities and challenges in using high-throughput phenotyping, "big data," analytics, and related technologies in the livestock industry based on discussions at the Livestock High-Throughput Phenotyping and Big Data Analytics meeting, held in November 2017 (see: https://www.animalgenome.org/bioinfo/community/workshops/2017/). Critical needs for investments in infrastructure for people (e.g., "big data" training), data (e.g., data transfer, management, and analytics), and technology (e.g., development of low cost sensors) were defined by this group. Though some subgroups of animal science have extensive experience in predictive modeling, cross-training in computer science, statistics, and related disciplines are needed to use big data for diverse applications in the field. Extensive opportunities exist for public and private entities to harness big data to develop valuable research knowledge and products to the benefit of society under the increased demands for food in a rapidly growing population.

Improved reference genome for the domestic horse increases assembly contiguity and composition.

Recent advances in genomic sequencing technology and computational assembly methods have allowed scientists to improve reference genome assemblies in terms of contiguity and composition. EquCab2, a reference genome for the domestic horse, was released in 2007. Although of equal or better quality compared to other first-generation Sanger assemblies, it had many of the shortcomings common to them. In 2014, the equine genomics research community began a project to improve the reference sequence for the horse, building upon the solid foundation of EquCab2 and incorporating new short-read data, long-read data, and proximity ligation data. Here, we present EquCab3. The count of non-N bases in the incorporated chromosomes is improved from 2.33 Gb in EquCab2 to 2.41 Gb in EquCab3. Contiguity has also been improved nearly 40-fold with a contig N50 of 4.5 Mb and scaffold contiguity enhanced to where all but one of the 32 chromosomes is comprised of a single scaffold.

eQTL discovery and their association with severe equine asthma in European Warmblood horses.

BACKGROUND: Severe equine asthma, also known as recurrent airway obstruction (RAO), is a debilitating, performance limiting, obstructive respiratory condition in horses that is phenotypically similar to human asthma. Past genome wide association studies (GWAS) have not discovered coding variants associated with RAO, leading to the hypothesis that causative variant(s) underlying the signals are likely non-coding, regulatory variant(s). Regions of the genome containing variants that influence the number of expressed RNA molecules are expression quantitative trait loci (eQTLs). Variation associated with RAO that also regulates a gene's expression in a disease relevant tissue could help identify candidate genes that influence RAO if that gene's expression is also associated with RAO disease status. RESULTS: We searched for eQTLs by analyzing peripheral blood mononuclear cells (PBMCs) from two half-sib families and one unrelated cohort of 82 European Warmblood horses that were previously treated in vitro with: no stimulation (MCK), lipopolysaccharides (LPS), recombinant cyathostomin antigen (RCA), and hay-dust extract (HDE). We identified high confidence eQTLs that did not violate linear modeling assumptions and were not significant due to single outlier individuals. We identified a mean of 4347 high confidence eQTLs in four treatments of PBMCs, and discovered two trans regulatory hotspots regulating genes involved in related biological pathways. We corroborated previous RAO associated single nucleotide polymorphisms (SNPs), and increased the resolution of past GWAS by analyzing 1,056,195 SNPs in 361 individuals. We identified four RAO-associated SNPs that only regulate gene expression of dexamethasone-induced protein (DEXI), however we found no significant association between DEXI gene expression and presence of RAO. CONCLUSIONS: Thousands of genetic variants regulate gene expression in PBMCs of European Warmblood horses in cis and trans. Most high confidence eSNPs are significantly enriched near the transcription start sites of their target genes. Two trans regulatory hotspots on chromosome 11 and 13 regulate many genes involved in transmembrane cell signaling and neurological development respectively when PBMCs are treated with HDE. None of the top fifteen RAO associated SNPs strongly influence disease status through gene expression regulation.

Genome-Wide Signatures of Selection Reveal Genes Associated With Performance in American Quarter Horse Subpopulations.

Selective breeding for athletic performance in various disciplines has resulted in population stratification within the American Quarter Horse (QH) breed. The goals of this study were to utilize high density genotype data to: (1) identify genomic regions undergoing positive selection within and among QH subpopulations; (2) investigate haplotype structure within each QH subpopulation; and (3) identify candidate genes within genomic regions of interest (ROI), as well as biological pathways, predicted to play a role in elite performance in each group. For that, 65K SNP genotyping data on 143 elite individuals from 6 QH subpopulations (cutting, halter, racing, reining, western pleasure, and working cow) were imputed to 2M SNPs. Signatures of selection were identified using FST-based (di ) and haplotype-based (hapFLK) analyses, accompanied by identification of local haplotype structure and sharing within subpopulations (hapQTL). Regions undergoing positive selection were identified on all 31 autosomes, and ROI on 2 chromosomes were identified by all 3 methods combined. Genes within each ROI were retrieved and used to identify pathways and genes that might contribute to performance in each subpopulation. These included, among others, candidate genes associated with skeletal muscle development, metabolism, and central nervous system development. This work improves our understanding of equine breed development, and provides breeders with a better understanding of how selective breeding impacts the performance of QH populations.

Case-control study of risk factors for pasture-and endocrinopathy-associated laminitis in North American horses.

OBJECTIVE To investigate risk factors for the development of pasture- and endocrinopathy-associated laminitis (PEAL) in horses and ponies in North America. DESIGN Case-control study. ANIMALS 199 horses with incident cases of PEAL and 351 horses from 2 control populations (healthy horses [n = 198] and horses with lameness not caused by laminitis [153]) that were evaluated in North America between January 2012 and December 2015 by veterinarian members of the American Association of Equine Practitioners. PROCEDURES North American members of the American Association of Equine Practitioners were contacted to participate in the study, and participating veterinarians provided historical data on incident cases of PEAL, each matched with a healthy control and a lameness control. Conditional logistic regression analysis was used to compare data on PEAL-affected horses with data on horses from each set of controls. RESULTS Horses with an obese body condition (ie, body condition score ≥ 7), generalized or regional adiposity (alone or in combination), preexisting endocrinopathy, or recent (within 30 days) glucocorticoid administration had increased odds of developing PEAL, compared with horses that did not have these findings. CONCLUSIONS AND CLINICAL RELEVANCE The present study identified several risk factors for PEAL that may assist not only in managing and preventing this form of laminitis, but also in guiding future research into its pathogenesis.

Metabolic perturbations in Welsh Ponies with insulin dysregulation, obesity, and laminitis.

BACKGROUND: Metabolomics, the study of small-molecule metabolites, has increased understanding of human metabolic diseases, but has not been used to study equine metabolic syndrome (EMS). OBJECTIVES: (1) To examine the serum metabolome of Welsh Ponies with and without insulin dysregulation before and during an oral sugar test (OST). (2) To identify differences in metabolites in ponies with insulin dysregulation, obesity, or history of laminitis. ANIMALS: Twenty Welsh Ponies (mean ± SD; 13.8 ± 9.0 years) classified as non-insulin dysregulated [CON] (n = 10, insulin < 30 mU/L) or insulin dysregulated [ID] (n = 10, insulin > 60 mU/L) at 75 minutes after administration of Karo syrup, obese (n = 6) or nonobese (n = 14), and history of laminitis (n = 9) or no history of laminitis (n = 11). METHODS: Case-control study. Metabolomic analysis was performed on serum obtained at 0 minutes (baseline) and 75 minutes during the OST. Data were analyzed with multivariable mixed linear models with significance set at P ≤ .05. RESULTS: Metabolomic analysis of 646 metabolites (506 known) detected significant metabolite differences. At baseline, 55 metabolites (insulin response), 91 metabolites (obesity status), and 136 metabolites (laminitis history) were different. At 75 minutes, 51 metabolites (insulin response), 102 metabolites (obesity status), and 124 metabolites (laminitis history) were different. CONCLUSIONS AND CLINICAL IMPORTANCE: Use of metabolomics could have diagnostic utility for early detection of EMS and provide new knowledge regarding the pathophysiology of metabolic perturbations associated with this condition that might lead to improved clinical management.

The Scope of Big Data in One Medicine: Unprecedented Opportunities and Challenges.

Advances in high-throughput molecular biology and electronic health records (EHR), coupled with increasing computer capabilities have resulted in an increased interest in the use of big data in health care. Big data require collection and analysis of data at an unprecedented scale and represents a paradigm shift in health care, offering (1) the capacity to generate new knowledge more quickly than traditional scientific approaches; (2) unbiased collection and analysis of data; and (3) a holistic understanding of biology and pathophysiology. Big data promises more personalized and precision medicine for patients with improved accuracy and earlier diagnosis, and therapy tailored to an individual's unique combination of genes, environmental risk, and precise disease phenotype. This promise comes from data collected from numerous sources, ranging from molecules to cells, to tissues, to individuals and populations-and the integration of these data into networks that improve understanding of heath and disease. Big data-driven science should play a role in propelling comparative medicine and "one medicine" (i.e., the shared physiology, pathophysiology, and disease risk factors across species) forward. Merging of data from EHR across institutions will give access to patient data on a scale previously unimaginable, allowing for precise phenotype definition and objective evaluation of risk factors and response to therapy. High-throughput molecular data will give insight into previously unexplored molecular pathophysiology and disease etiology. Investigation and integration of big data from a variety of sources will result in stronger parallels drawn at the molecular level between human and animal disease, allow for predictive modeling of infectious disease and identification of key areas of intervention, and facilitate step-changes in our understanding of disease that can make a substantial impact on animal and human health. However, the use of big data comes with significant challenges. Here we explore the scope of "big data," including its opportunities, its limitations, and what is needed capitalize on big data in one medicine.

Developing a 670k genotyping array to tag ~2M SNPs across 24 horse breeds.

BACKGROUND: To date, genome-scale analyses in the domestic horse have been limited by suboptimal single nucleotide polymorphism (SNP) density and uneven genomic coverage of the current SNP genotyping arrays. The recent availability of whole genome sequences has created the opportunity to develop a next generation, high-density equine SNP array. RESULTS: Using whole genome sequence from 153 individuals representing 24 distinct breeds collated by the equine genomics community, we cataloged over 23 million de novo discovered genetic variants. Leveraging genotype data from individuals with both whole genome sequence, and genotypes from lower-density, legacy SNP arrays, a subset of ~5 million high-quality, high-density array candidate SNPs were selected based on breed representation and uniform spacing across the genome. Considering probe design recommendations from a commercial vendor (Affymetrix, now Thermo Fisher Scientific) a set of ~2 million SNPs were selected for a next-generation high-density SNP chip (MNEc2M). Genotype data were generated using the MNEc2M array from a cohort of 332 horses from 20 breeds and a lower-density array, consisting of ~670 thousand SNPs (MNEc670k), was designed for genotype imputation. CONCLUSIONS: Here, we document the steps taken to design both the MNEc2M and MNEc670k arrays, report genomic and technical properties of these genotyping platforms, and demonstrate the imputation capabilities of these tools for the domestic horse.