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The genomic sequence of the horse has been available since 2009, providing critical resources for discovering important genomic variants regarding both animal health and population structures. However, to fully understand the functional implications of these variants, detailed annotation of the horse genome is required. Due to the limited availability of functional data for the equine genome, as well as the technical limitations of short-read RNA-seq, existing annotation of the equine genome contains limited information about important aspects of gene regulation, such as alternate isoforms and regulatory elements, which are either not transcribed or transcribed at a very low level. To solve above problems, the Functional Annotation of the Animal Genomes (FAANG) project proposed a systemic approach to tissue collection, phenotyping, and data generation, adopting the blueprint laid out by the Encyclopedia of DNA Elements (ENCODE) project. Here we detail the first comprehensive overview of gene expression and regulation in the horse, presenting 39,625 novel transcripts, 84,613 candidate cis-regulatory elements (CRE) and their target genes, 332,115 open chromatin regions genome wide across a diverse set of tissues. We showed substantial concordance between chromatin accessibility, chromatin states in different genic features and gene expression. This comprehensive and expanded set of genomics resources will provide the equine research community ample opportunities for studies of complex traits in the horse.

Equine arteritis virus (EAV) is the causative agent of equine viral arteritis (EVA), a respiratory, systemic, and reproductive disease of horses and other equid species. Following natural infection, 10-70% of the infected stallions can become persistently infected and continue to shed EAV in their semen for periods ranging from several months to life. Recently, we reported that some stallions possess a subpopulation(s) of CD3+ T lymphocytes that are susceptible to in vitro EAV infection and that this phenotypic trait is associated with long-term carrier status following exposure to the virus. In contrast, stallions not possessing the CD3+ T lymphocyte susceptible phenotype are at less risk of becoming long-term virus carriers. A genome wide association study (GWAS) using the Illumina Equine SNP50 chip revealed that the ability of EAV to infect CD3+ T lymphocytes and establish long-term carrier status in stallions correlated with a region within equine chromosome 11. Here we identified the gene and mutations responsible for these phenotypes. Specifically, the work implicated three allelic variants of the equine orthologue of CXCL16 (EqCXCL16) that differ by four non-synonymous nucleotide substitutions (XM_00154756; c.715 A → T, c.801 G → C, c.804 T → A/G, c.810 G → A) within exon 1. This resulted in four amino acid changes with EqCXCL16S (XP_001504806.1) having Phe, His, Ile and Lys as compared to EqCXL16R having Tyr, Asp, Phe, and Glu at 40, 49, 50, and 52, respectively. Two alleles (EqCXCL16Sa, EqCXCL16Sb) encoded identical protein products that correlated strongly with long-term EAV persistence in stallions (P

The reference assembly for the domestic horse, EquCab2, published in 2009, was built using approximately 30 million Sanger reads from a Thoroughbred mare named Twilight. Contiguity in the assembly was facilitated using nearly 315 thousand BAC end sequences from Twilight's half brother Bravo. Since then, it has served as the foundation for many genome-wide analyses that include not only the modern horse, but ancient horses and other equid species as well. As data mapped to this reference has accumulated, consistent variation between mapped datasets and the reference, in terms of regions with no read coverage, single nucleotide variants, and small insertions/deletions have become apparent. In many cases, it is not clear whether these differences are the result of true sequence variation between the research subjects' and Twilight's genome or due to errors in the reference. EquCab2 is regarded as "The Twilight Assembly." The objective of this study was to identify inconsistencies between the EquCab2 assembly and the source Twilight Sanger data used to build it. To that end, the original Sanger and BAC end reads have been mapped back to this equine reference and assessed with the addition of approximately 40X coverage of new Illumina Paired-End sequence data. The resulting mapped datasets identify those regions with low Sanger read coverage, as well as variation in genomic content that is not consistent with either the original Twilight Sanger data or the new genomic sequence data generated from Twilight on the Illumina platform. As the haploid EquCab2 reference assembly was created using Sanger reads derived largely from a single individual, the vast majority of variation detected in a mapped dataset comprised of those same Sanger reads should be heterozygous. In contrast, homozygous variations would represent either errors in the reference or contributions from Bravo's BAC end sequences. Our analysis identifies 720,843 homozygous discrepancies between new, high throughput genomic sequence data generated for Twilight and the EquCab2 reference assembly. Most of these represent errors in the assembly, while approximately 10,000 are demonstrated to be contributions from another horse. Other results are presented that include the binary alignment map file of the mapped Sanger reads, a list of variants identified as discrepancies between the source data and resulting reference, and a BED annotation file that lists the regions of the genome whose consensus was likely derived from low coverage alignments.