Variation in MUTYH expression in Arabian horses with Cerebellar Abiotrophy.

Cerebellar Abiotrophy (CA) is a neurodegenerative disease in Arabian horses affecting the cerebellum, more specifically the Purkinje neurons. Although CA occurs in several domestic species, CA in Arabian horses is unique in that a single nucleotide polymorphism (SNP) has been associated with the disease. Total RNA sequencing (RNA-seq) was performed on CA-affected horses to address the molecular mechanism underlying the disease. This research expands upon the RNA-seq work by measuring the impact of the CA-associated SNP on the candidate gene MutY homolog (MUTYH) and its regulation, isoform-specific expression and protein localization. We hypothesized that the CA-associated SNP compromises the promoter region of MUTYH, leading to differential expression of its isoforms. Our research demonstrates that the CA-associated SNP introduces a new binding site for a novel transcription factor (Myelin Transcription Factor-1 Like protein, MYT1L). In addition, CA-affected horses show differential expression of a specific isoform of MUTYH as well as different localization in the Purkinje and granular neurons of the cerebellum.

Identification of long non-coding RNA in the horse transcriptome.

BACKGROUND: Efforts to resolve the transcribed sequences in the equine genome have focused on protein-coding RNA. The transcription of the intergenic regions, although detected via total RNA sequencing (RNA-seq), has yet to be characterized in the horse. The most recent equine transcriptome based on RNA-seq from several tissues was a prime opportunity to obtain a concurrent long non-coding RNA (lncRNA) database. RESULTS: This lncRNA database has a breadth of eight tissues and a depth of over 20 million reads for select tissues, providing the deepest and most expansive equine lncRNA database. Utilizing the intergenic reads and three categories of novel genes from a previously published equine transcriptome pipeline, we better describe these groups by annotating the lncRNA candidates. These lncRNA candidates were filtered using an approach adapted from human lncRNA annotation, which removes transcripts based on size, expression, protein-coding capability and distance to the start or stop of annotated protein-coding transcripts. CONCLUSION: Our equine lncRNA database has 20,800 transcripts that demonstrate characteristics unique to lncRNA including low expression, low exon diversity and low levels of sequence conservation. These candidate lncRNA will serve as a baseline lncRNA annotation and begin to describe the RNA-seq reads assigned to the intergenic space in the horse.

Tissue resolved, gene structure refined equine transcriptome.

BACKGROUND: Transcriptome interpretation relies on a good-quality reference transcriptome for accurate quantification of gene expression as well as functional analysis of genetic variants. The current annotation of the horse genome lacks the specificity and sensitivity necessary to assess gene expression especially at the isoform level, and suffers from insufficient annotation of untranslated regions (UTR) usage. We built an annotation pipeline for horse and used it to integrate 1.9 billion reads from multiple RNA-seq data sets into a new refined transcriptome. RESULTS: This equine transcriptome integrates eight different tissues from 59 individuals and improves gene structure and isoform resolution, while providing considerable tissue-specific information. We utilized four levels of transcript filtration in our pipeline, aimed at producing several transcriptome versions that are suitable for different downstream analyses. Our most refined transcriptome includes 36,876 genes and 76,125 isoforms, with 6474 candidate transcriptional loci novel to the equine transcriptome. CONCLUSIONS: We have employed a variety of descriptive statistics and figures that demonstrate the quality and content of the transcriptome. The equine transcriptomes that are provided by this pipeline show the best tissue-specific resolution of any equine transcriptome to date and are flexible for several downstream analyses. We encourage the integration of further equine transcriptomes with our annotation pipeline to continue and improve the equine transcriptome.

Defining Trends in Global Gene Expression in Arabian Horses with Cerebellar Abiotrophy.

Equine cerebellar abiotrophy (CA) is a hereditary neurodegenerative disease that affects the Purkinje neurons of the cerebellum and causes ataxia in Arabian foals. Signs of CA are typically first recognized either at birth to any time up to 6 months of age. CA is inherited as an autosomal recessive trait and is associated with a single nucleotide polymorphism (SNP) on equine chromosome 2 (13074277G>A), located in the fourth exon of TOE1 and in proximity to MUTYH on the antisense strand. We hypothesize that unraveling the functional consequences of the CA SNP using RNA-seq will elucidate the molecular pathways underlying the CA phenotype. RNA-seq (100 bp PE strand-specific) was performed in cerebellar tissue from four CA-affected and five age-matched unaffected horses. Three pipelines for differential gene expression (DE) analysis were used (Tophat2/Cuffdiff2, Kallisto/EdgeR, and Kallisto/Sleuth) with 151 significant DE genes identified by all three pipelines in CA-affected horses. TOE1 (Log2(foldchange) = 0.92, p = 0.66) and MUTYH (Log2(foldchange) = 1.13, p = 0.66) were not differentially expressed. Among the major pathways that were differentially expressed, genes associated with calcium homeostasis and specifically expressed in Purkinje neurons, CALB1 (Log2(foldchange) = -1.7, p < 0.01) and CA8 (Log2(foldchange) = -0.97, p < 0.01), were significantly down-regulated, confirming loss of Purkinje neurons. There was also a significant up-regulation of markers for microglial phagocytosis, TYROBP (Log2(foldchange) = 1.99, p < 0.01) and TREM2 (Log2(foldchange) = 2.02, p < 0.01). These findings reaffirm a loss of Purkinje neurons in CA-affected horses along with a potential secondary loss of granular neurons and activation of microglial cells.