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

Genomic association using principal components of morphometric traits in horses: identification of genes related to bone growth

The measurement of morphometric traits in horses is important for determining breed qualification and is one of the main selection criteria for the species. The development of an index (HPC) that consists of principal components weighted by additive genetic values allows to explore the most relevant relationships using a reduced number of variables that explain the greatest amount of variation in the data. Genome-wide association studies (GWAS) using HPC are a relatively new approach that permits to identify regions related to a set of traits. The aim of this study was to perform GWAS using HPC for 15 linear measurements as the explanatory variable in order to identify associated genomic regions and to elucidate the biological mechanisms linked to this index in Campolina horses. For GWAS, weighted single-step GBLUP was applied to HPC. The eight genomic windows that explained the highest proportion of additive genetic variance were identified. The sum of the additive variance explained by the eight windows was 95.89%. Genes involved in bone and cartilage development were identified (SPRY2, COL9A2, MIR30C, HEYL, BMP8B, LTBP1, FAM98A, and CRIM1). They represent potential positional candidates for the HPC of the linear measurements evaluated. The HPC is an efficient alternative to reduce the 15 usually measured traits in Campolina horses. Moreover, candidate genes inserted in region that explained high additive variance of the HPC were identified and might be fine-mapped for searching putative mutation/markers.

Cardiac ion channel expression in the equine model - In-silico prediction utilising RNA sequencing data from mixed tissue samples

Understanding cardiomyocyte ion channel expression is crucial to understanding normal cardiac electrophysiology and underlying mechanisms of cardiac pathologies particularly arrhythmias. Hitherto, equine cardiac ion channel expression has rarely been investigated. Therefore, we aim to predict equine cardiac ion channel gene expression. Raw RNAseq data from normal horses from 9 datasets was retrieved from ArrayExpress and European Nucleotide Archive and reanalysed. The normalised (FPKM) read counts for a gene in a mix of tissue were hypothesised to be the average of the expected expression in each tissue weighted by the proportion of the tissue in the mix. The cardiac-specific expression was predicted by estimating the mean expression in each other tissues. To evaluate the performance of the model, predicted gene expression values were compared to the human cardiac gene expression. Cardiac-specific expression could be predicted for 91 ion channels including most expressed Na+ channels, K+ channels and Ca2+ -handling proteins. These revealed interesting differences from what would be expected based on human studies. These differences included predominance of NaV 1.4 rather than NaV 1.5 channel, and RYR1, SERCA1 and CASQ1 rather than RYR2, SERCA2, CASQ2 Ca2+ -handling proteins. Differences in channel expression not only implicate potentially different regulatory mechanisms but also pathological mechanisms of arrhythmogenesis.

Genetics of Equine Orthopedic Disease

Orthopedic diseases are a common cause for limited exercise capacity in the horse. They often underlie genetic risk factors, which can affect bone, articular cartilage, tendons, ligaments, and adnexal structures among others. The genetic effects can directly interfere with tissue development and skeletal growth or can trigger degenerative or inflammatory processes. Many of these diseases of the locomotor system like osteochondrosis are complex and can be affected by multifactorial influences. For this reason, it is important for those performing diagnostic procedures to have a comprehensive knowledge of orthopedic diseases, their prevalence within breeds, and genetic background.