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      Next generation sequencing gives an insight into the characteristics of highly selected breeds versus non-breed horses in the course of domestication

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          Abstract

          Background

          Domestication has shaped the horse and lead to a group of many different types. Some have been under strong human selection while others developed in close relationship with nature. The aim of our study was to perform next generation sequencing of breed and non-breed horses to provide an insight into genetic influences on selective forces.

          Results

          Whole genome sequencing of five horses of four different populations revealed 10,193,421 single nucleotide polymorphisms (SNPs) and 1,361,948 insertion/deletion polymorphisms (indels). In comparison to horse variant databases and previous reports, we were able to identify 3,394,883 novel SNPs and 868,525 novel indels. We analyzed the distribution of individual variants and found significant enrichment of private mutations in coding regions of genes involved in primary metabolic processes, anatomical structures, morphogenesis and cellular components in non-breed horses and in contrast to that private mutations in genes affecting cell communication, lipid metabolic process, neurological system process, muscle contraction, ion transport, developmental processes of the nervous system and ectoderm in breed horses.

          Conclusions

          Our next generation sequencing data constitute an important first step for the characterization of non-breed in comparison to breed horses and provide a large number of novel variants for future analyses. Functional annotations suggest specific variants that could play a role for the characterization of breed or non-breed horses.

          Electronic supplementary material

          The online version of this article (doi:10.1186/1471-2164-15-562) contains supplementary material, which is available to authorized users.

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          Most cited references42

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          Genome sequence, comparative analysis, and population genetics of the domestic horse.

          We report a high-quality draft sequence of the genome of the horse (Equus caballus). The genome is relatively repetitive but has little segmental duplication. Chromosomes appear to have undergone few historical rearrangements: 53% of equine chromosomes show conserved synteny to a single human chromosome. Equine chromosome 11 is shown to have an evolutionary new centromere devoid of centromeric satellite DNA, suggesting that centromeric function may arise before satellite repeat accumulation. Linkage disequilibrium, showing the influences of early domestication of large herds of female horses, is intermediate in length between dog and human, and there is long-range haplotype sharing among breeds.
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            Four Loci Explain 83% of Size Variation in the Horse

            Horse body size varies greatly due to intense selection within each breed. American Miniatures are less than one meter tall at the withers while Shires and Percherons can exceed two meters. The genetic basis for this variation is not known. We hypothesize that the breed population structure of the horse should simplify efforts to identify genes controlling size. In support of this, here we show with genome-wide association scans (GWAS) that genetic variation at just four loci can explain the great majority of horse size variation. Unlike humans, which are naturally reproducing and possess many genetic variants with weak effects on size, we show that horses, like other domestic mammals, carry just a small number of size loci with alleles of large effect. Furthermore, three of our horse size loci contain the LCORL, HMGA2 and ZFAT genes that have previously been found to control human height. The LCORL/NCAPG locus is also implicated in cattle growth and HMGA2 is associated with dog size. Extreme size diversification is a hallmark of domestication. Our results in the horse, complemented by the prior work in cattle and dog, serve to pinpoint those very few genes that have played major roles in the rapid evolution of size during domestication.
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              A genome-wide SNP-association study confirms a sequence variant (g.66493737C>T) in the equine myostatin (MSTN) gene as the most powerful predictor of optimum racing distance for Thoroughbred racehorses

              Background Thoroughbred horses have been selected for traits contributing to speed and stamina for centuries. It is widely recognized that inherited variation in physical and physiological characteristics is responsible for variation in individual aptitude for race distance, and that muscle phenotypes in particular are important. Results A genome-wide SNP-association study for optimum racing distance was performed using the EquineSNP50 Bead Chip genotyping array in a cohort of n = 118 elite Thoroughbred racehorses divergent for race distance aptitude. In a cohort-based association test we evaluated genotypic variation at 40,977 SNPs between horses suited to short distance (≤ 8 f) and middle-long distance (> 8 f) races. The most significant SNP was located on chromosome 18: BIEC2-417495 ~690 kb from the gene encoding myostatin (MSTN) [P unadj. = 6.96 × 10-6]. Considering best race distance as a quantitative phenotype, a peak of association on chromosome 18 (chr18:65809482-67545806) comprising eight SNPs encompassing a 1.7 Mb region was observed. Again, similar to the cohort-based analysis, the most significant SNP was BIEC2-417495 (P unadj. = 1.61 × 10-9; P Bonf. = 6.58 × 10-5). In a candidate gene study we have previously reported a SNP (g.66493737C>T) in MSTN associated with best race distance in Thoroughbreds; however, its functional and genome-wide relevance were uncertain. Additional re-sequencing in the flanking regions of the MSTN gene revealed four novel 3' UTR SNPs and a 227 bp SINE insertion polymorphism in the 5' UTR promoter sequence. Linkage disequilibrium was highest between g.66493737C>T and BIEC2-417495 (r 2 = 0.86). Conclusions Comparative association tests consistently demonstrated the g.66493737C>T SNP as the superior variant in the prediction of distance aptitude in racehorses (g.66493737C>T, P = 1.02 × 10-10; BIEC2-417495, P unadj. = 1.61 × 10-9). Functional investigations will be required to determine whether this polymorphism affects putative transcription-factor binding and gives rise to variation in gene and protein expression. Nonetheless, this study demonstrates that the g.66493737C>T SNP provides the most powerful genetic marker for prediction of race distance aptitude in Thoroughbreds.
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                Author and article information

                Contributors
                julia.metzger@tiho-hannover.de
                rtonda@pcb.ub.cat
                sbeltrana@pcb.ub.cat
                lagueda@pcb.ub.cat
                mgut@pcb.ub.cat
                ottmar.distl@tiho-hannover.de
                Journal
                BMC Genomics
                BMC Genomics
                BMC Genomics
                BioMed Central (London )
                1471-2164
                4 July 2014
                4 July 2014
                2014
                : 15
                : 1
                : 562
                Affiliations
                [ ]Institute for Animal Breeding and Genetics, University of Veterinary Medicine Hannover, Bünteweg 17p, 30559 Hannover, Germany
                [ ]Centro Nacional de Análisis Genómico, Parc Científic de Barcelona, Torre I Baldiri Reixac, 4, Barcelona, 08028 Spain
                Article
                6235
                10.1186/1471-2164-15-562
                4097168
                24996778
                e20508c4-045c-414b-bd50-3b3cd7e9bfb9
                © Metzger et al.; licensee BioMed Central Ltd. 2014

                This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 20 December 2013
                : 24 June 2014
                Categories
                Research Article
                Custom metadata
                © The Author(s) 2014

                Genetics
                Genetics

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