Speed Index in the Racing Quarter Horse: A Genome-wide Association Study

Using Different Combinations of Body-Mounted IMU Sensors to Estimate Speed of Horses-A Machine Learning Approach

Speed is an essential parameter in biomechanical analysis and general locomotion research. It is possible to estimate the speed using global positioning systems (GPS) or inertial measurement units (IMUs). However, GPS requires a consistent signal connection to satellites, and errors accumulate during IMU signals integration. In an attempt to overcome these issues, we have investigated the possibility of estimating the horse speed by developing machine learning (ML) models using the signals from seven body-mounted IMUs. Since motion patterns extracted from IMU signals are different between breeds and gaits, we trained the models based on data from 40 Icelandic and Franches-Montagnes horses during walk, trot, tölt, pace, and canter. In addition, we studied the estimation accuracy between IMU locations on the body (sacrum, withers, head, and limbs). The models were evaluated per gait and were compared between ML algorithms and IMU location. The model yielded the highest estimation accuracy of speed (RMSE = 0.25 m/s) within equine and most of human speed estimation literature. In conclusion, highly accurate horse speed estimation models, independent of IMU(s) location on-body and gait, were developed using ML.

Identification and Functional Annotation of Genes Related to Horses' Performance: From GWAS to Post-GWAS

Simple Summary

It is assumed that the athletic performance of horses is influenced by a large number of genes; however, to date, not many genomic studies have been performed to identify candidate genes. In this study we performed a systematic review of genome-wide association studies followed by functional analyses aiming to identify the most candidate genes for horse performance. We were successful in identifying 669 candidate genes, from which we built biological process networks. Regulatory elements (transcription factors, TFs) of these genes were identified and used to build a gene–TF network. Genes and TFs presented in this study are suggested to play a role in the studied traits through biological processes related with exercise performance, for example, positive regulation of glucose metabolism, regulation of vascular endothelial growth factor production, skeletal system development, cellular response to fatty acids and cellular response to lipids. In general, this study may provide insights into the genetic architecture underlying horse performance in different breeds around the world.

Abstract

Integration of genomic data with gene network analysis can be a relevant strategy for unraveling genetic mechanisms. It can be used to explore shared biological processes between genes, as well as highlighting transcription factors (TFs) related to phenotypes of interest. Unlike other species, gene–TF network analyses have not yet been well applied to horse traits. We aimed to (1) identify candidate genes associated with horse performance via systematic review, and (2) build biological processes and gene–TF networks from the identified genes aiming to highlight the most candidate genes for horse performance. Our systematic review considered peer-reviewed articles using 20 combinations of keywords. Nine articles were selected and placed into groups for functional analysis via gene networks. A total of 669 candidate genes were identified. From that, gene networks of biological processes from each group were constructed, highlighting processes associated with horse performance (e.g., regulation of systemic arterial blood pressure by vasopressin and regulation of actin polymerization and depolymerization). Transcription factors associated with candidate genes were also identified. Based on their biological processes and evidence from the literature, we identified the main TFs related to horse performance traits, which allowed us to construct a gene–TF network highlighting TFs and the most candidate genes for horse performance.

Ten years of the horse reference genome: insights into equine biology, domestication and population dynamics in the post-genome era

The horse reference genome from the Thoroughbred mare Twilight has been available for a decade and, together with advances in genomics technologies, has led to unparalleled developments in equine genomics. At the core of this progress is the continuing improvement of the quality, contiguity and completeness of the reference genome, and its functional annotation. Recent achievements include the release of the next version of the reference genome (EquCab3.0) and generation of a reference sequence for the Y chromosome. Horse satellite‐free centromeres provide unique models for mammalian centromere research. Despite extremely low genetic diversity of the Y chromosome, it has been possible to trace patrilines of breeds and pedigrees and show that Y variation was lost in the past approximately 2300 years owing to selective breeding. The high‐quality reference genome has led to the development of three different SNP arrays and WGSs of almost 2000 modern individual horses. The collection of WGS of hundreds of ancient horses is unique and not available for any other domestic species. These tools and resources have led to global population studies dissecting the natural history of the species and genetic makeup and ancestry of modern breeds. Most importantly, the available tools and resources, together with the discovery of functional elements, are dissecting molecular causes of a growing number of Mendelian and complex traits. The improved understanding of molecular underpinnings of various traits continues to benefit the health and performance of the horse whereas also serving as a model for complex disease across species.

A genome-wide association study for harness racing success in the Norwegian-Swedish coldblooded trotter reveals genes for learning and energy metabolism

Background

Although harness racing is of high economic importance to the global equine industry, significant genomic resources have yet to be applied to mapping harness racing success. To identify genomic regions associated with harness racing success, the current study performs genome-wide association analyses with three racing performance traits in the Norwegian-Swedish Coldblooded Trotter using the 670 K Axiom Equine Genotyping Array.

Results

Following quality control, 613 horses and 359,635 SNPs were retained for further analysis. After strict Bonferroni correction, nine genome-wide significant SNPs were identified for career earnings. No genome-wide significant SNPs were identified for number of gallops or best km time. However, four suggestive genome-wide significant SNPs were identified for number of gallops, while 19 were identified for best km time. Multiple genes related to intelligence, energy metabolism, and immune function were identified as potential candidate genes for harness racing success.

Conclusions

Apart from the physiological requirements needed for a harness racing horse to be successful, the results of the current study also advocate learning ability and memory as important elements for harness racing success. Further exploration into the mental capacity required for a horse to achieve racing success is likely warranted.

Electronic supplementary material

The online version of this article (10.1186/s12863-018-0670-3) contains supplementary material, which is available to authorized users.

Identification on novel locus of dairy traits of Kazakh horse in Xinjiang

The utility of high-density single nucleotide polymorphism (SNP) data help to accurately identify genomic regions that have undergone positive selection. In this study, the Affymetrix Equine 670 K high-density SNP array was used to genotype Kazakh and Yili horse population. After quality control, 370,227 autosomal SNPs were used to detect selection signatures by using global fixation index (F_ST) and cross-population extended haplotype homozygosity (XP-EHH). The database of Ensemble, Genecards, and NCBI were used to make gene annotation and functional analysis. The results showed that there were 134 candidate SNPs overlapped between F_ST and XP-EHH in Kazakh horse. We also discovered some potential selective sweep regions associated with milk trait, including NUMB, LGALS2, ADCY8, SLC25A30, and CA8 genes. New findings from this research have potential value for milk traits selecting in horse.

Quantitative analysis of short- and long-distance racing performance in young and adult horses and association analysis with functional candidate genes in Spanish Trotter horses

The association of five candidate genes with sporting performance in young and adult Spanish Trotter horses (STHs) was performed according to a previous selection based on quantitative analysis of the trait time per kilometre (TPK). A total of 334 516 records of TPK from 5958 STHs were used to estimate the estimated breeding values (EBVs) at different age groups (young and adults horses) throughout the range of distances (1600-2700 m) using a bicharacter random regression model. The heritability estimated by distance ranged from 0.16 to 0.40, with a different range for the two age groups. Considering the animals with the best and the worst deregressed EBV, 321 STHs were selected for SNP genotyping in MSTN, COX4I2, PDK4, DMRT3 and CKM genes. An association analysis based on ridge and logistic regression revealed that the young trotters with genotype GG in PDK4 (p < 0.05) and AA of DMRT3 (p < 0.001) SNPs show the best potential in short-distance races, while those carrying the genotype AA in DMRT3 (p < 0.001) and CC in CKM (p < 0.05) genes seem to be the best in long-distance races. Adult trotters with genotype AA in DMRT3 also display greater speed (p < 0.05) and endurance (p < 0.001).