7.1 Abstract
A functional conformation is crucial for any elite equine performance. The conformational traits that are considered for population genetic analyses of Hanoverian warmbloods are grouped under two topics, riding horse points (RHP) and limbs (LIMBS). RHP include all traits that are constitutive for the quality of a riding horse (head, neck, saddle position, frame, type and development), whereas LIMBS comprises all thus traits describe the quality of limb conformation (front legs, hind legs and correctness of gaits). Employing the Ilumina equine SNP50 Beadchip, we performed genome wide association (GWA) analyses to map quantitative trait loci (QTL) for RHP and LIMBS. We genotyped 115 stallions of the National state stud of Lower Saxony. To control spurious associations based on population stratification, two different mixed linear animal model (MLM) approaches were employed besides three general linear models with adaptive permutations for correcting multiple testing.
Population stratification was taken into account best by employing a MLM, including the proportion of genes of Hanoverian, Thoroughbred, Trakehner and Holsteiner, and a marker identity by state (IBS) based kinship. We revealed four QTL for RHP on ECA3, 15, 19 and 20 and two QTL for LIMBS on ECA5 and 18 (-log10 P-value >5).
Further putative QTL with -log10 P-values >3 <5 were detected for RHP on ECA3, 6, 17, 18, 19, 21 and 27 and for LIMBS on ECA1, 3, 5, 8, 10, 11, 14, 17, 18, 19, 20, 25, 26 and 31. Within the QTL regions for RHP on ECA3 we identified PPARGC1A and LCORL as candidate genes. Inside the further putative QTL regions CYP27B1 on ECA6, MYO7B on ECA18, SOHX2 on ECA19 and FST on ECA21 could be identified as functional candidate genes for RHP. For LIMBS we detected PRG4 on ECA5 and MYO7B on ECA18 as functional candidate genes. Within the further putative QTL regions SHOX2 on ECA19, COL15A1 and RAD23B on ECA25, RNF160 on ECA26 and PLAGL1 on ECA31 could be identified as candidate genes for LIMBS.
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7.2 Introduction
Any elite physical performance in horses is based on a preferable functional conformation. Positive genetic correlations between conformation traits and performance in equestrian sports have been shown in several, although not all genetic studies [1], [2]. In addition, a favourable conformation can represent a possible sale benefit in particular at young ages. Hence, the Hanoverian studbook society (HSS) aims at selecting animals with best conformation values for the next generation. A modern and noble sport horse of varying calibre; big framed, with a well defined outline, lean texture, and well-muscled with a clear sex type is recommended by the HSS. Hence, horses intent for breeding under the HSS are previously scored by a judging commission for conformation and correctness of gaits.
To simplify conformation orientated breeding, breeding values (BVs) for conformational traits of the Hanoverian warmblood are composed to total a BV for riding horse points (RHP) and a BV for LIMBS. RHP is a composed trait resulting from scores for conformation of the head, the neck and the saddle position, the type, the frame and the general impression and development. BV LIMBS is also a composed trait resulting from scores for frontlegs, hindlegs and correctness of gaits.
Heritability estimates in Hanoverian warmbloods range from 0.19 to 0.50 for conformational traits included in RHP, and 0.09 to 0.12 for traits included in LIMBS [3].
Genetic improvement in horses is greatly reduced by the long generation interval, so the application of genetic markers in selection schemes to improve body conformation could be highly desirable. However, even population genetic analyses are performed routinely nowadays, studies on QTL and candidate genes contributing to equine body conformation are still at the beginning.
For human, dairy cattle, and dogs genotyping arrays containing SNP markers were successfully used for mapping QTL for quantitative traits. With the completion of the equine genome assembly, SNP assays spanning the whole equine genome and research work on large scale identification, validation and analysis of genotypic variation in horses has become possible but no such study on equine conformation is published jet.
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The objective of this study was a whole genome-wide association (GWA) analysis using the equine SNP50 BeadChip (Illumina, San Diego, CA, USA) for RHP and LIMBS in Hanoverian warmblood horses.
7. 3 Results
The GWA analysis could identify four QTL for RHP on ECA3, 15, 19 and 20 (Table1). Peak values were at 101.3-109.0 Mb on ECA3 and at 84.4–87.9 Mb on ECA15. Only one SNP at 2.3 Mb was supporting the QTL on ECA19. On ECA20 – log10 P-value were highest at 19.3–24.1 Mb. Further putative QTL for RHP were detected on ECA2, 3, 6, 15, 17, 18, 20, 21 and 27 (Table S1). Their locations were at 11.5-14.5 Mb and 43.9–46.9 Mb on ECA2, at 81.4-85.6 Mb on ECA3, at 75.5–78.7 Mb on ECA6, at 102.2 Mb on ECA17, at 2.3 Mb on ECA18, at 15.4 Mb on ECA20, at 18.8 Mb on ECA21 and at 13.2 Mb on ECA27 (Table S1).
For LIMBS we were able to detect 2 QTL on ECA5 and 18 (Table 2). On ECA5 we revealed a QTL at 20.5–23.5 Mb. Only one SNP was supporting the QTL on ECA18 at 2.3 MB. Further putative QTL for LIMBS were located on ECA1, 3, 5, 8, 11, 14, 17, 19, 20, 25, 26 and 31 (Table S2). Peak values were at 123.8 Mb on ECA1, at 59.2–
61.3 Mb and at 69.2 Mb on ECA3. On ECA5 –log10 P-values were highest at 87.8-91.1 Mb. On ECA8 -log P-values were highest at 9.4 and 24.9 Mb, on ECA11 at 6.4 Mb, and on ECA14 at 65.7-65.9 Mb. On ECA17 peak values were highest at 35.3–
39.5 Mb, at 2.3 Mb on ECA19 and on ECA20 at 17.3 Mb. We detected two QTL on ECA 25, one at 4.8 Mb and one at 11.5–11.7 Mb. Further QTL were detected at 26.1 Mb on ECA26 and at 20.8 Mb on ECA31.
The additive effect of BIEC2-808466 (ECA3) was highly significant for RHP.
BIEC2-325253 (ECA15) had a highly significant additive effect as well as a highly significant dominance effect on the BV for RHP. A highly significant dominance effect was observed for BIEC2-524152 on ECA20. For BIEC2-422566 on ECA19 the additive and the dominance effect were not estimable, because none of the investigated horses was homozygote for the minor allele (Table 3). For LIMBS, BIEC2-897799 (ECA5) and BIEC2-391005 (ECA18) had both highly significant additive effects (Table 4). The correlation coefficient estimated between the gBV for
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RHP and the BV for RHP was 0.40 and between the gBV for LIMBS and the BV for LIMBS was 0.33. Table 3 shows the distribution of SNP genotypes per proportions of Hanoverian, Thoroughbred, Trakehner and Holsteiner genes.
Within the identified QTL region for RHP on ECA3 we identified the peroxisome proliferator-activated receptor gamma, coactivator 1 alpha gene (PPARGC1A) and the ligand dependent nuclear receptor corepressor-like gene (LCORL) as candidate genes. Within the putative QTL regions, the cytochrome P450, family 27, subfamily B, polypeptide 1 gene (CYP27B1) on ECA6, the myosin VIIB gene (MYO7B) on ECA18, and the short stature homeobox 2 gene (SHOX2) on ECA19, and the follistatin gene (FST) on ECA21 could be identified as functional candidate genes for RHP.
Among the two QTL regions for LIMBS we detected the proteoglycan gene (PRG4) on ECA5 and MYO7B on ECA18 as a functional candidate gene. Within putative QTL regions we revealed SHOX2 on ECA19, the collagen, type XV, alpha 1 gene (COL15A1) and the RAD23 homolog B gene (RAD23B) on ECA25, the ring finger protein 160 (RNF160) on ECA26 and the pleiomorphic adenoma gene-like 1 gene (PLAGL1) on ECA31 as candidate genes for BV LIMBS.
7.4 Discussion
The aim of this study was to detect QTL associated with conformation in Hanoverian warmblood horses. The number of QTL on different chromosomes found for RHP and LIMBS in this study suggest that several genes are possibly involved in growth and developmental processes.
Potential QTL for RHP and LIMBS were defined as genomic region with minimum one SNP marker estimated as highly significant using Tassel1 or Tassel2, but at least estimated as significant using both models, and -log10 (P) >1 using any of the other models employed. Further putative QTL were defined as genomic regions harbouring at least one SNP marker estimated as significant using Tassel1 and Tassel2 and -log10 (P) >1 using any other model. According to the Q-Q-plots, omitting the effects of kinship and the proportion of genes would result in an overestimation of SNP effects caused by stratification within the investigated
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population. The differences between the -log10 P-values observed for the same SNP using different models for association analyses are due to data inflation. Considering the Q-Q plot for Tassel2, expected and observed -log10 Pvalues are in line up to -log10 (P) <3. At the same expected -log10 P-value (3) using any of the other implemented models, observed P-values are larger, representing data inflation, depending on the model used.
With exception of the QTL on ECA18 and 19, a coincidence of QTL positions among the two traits RHP and LIMBS could not be observed. We suppose that thus analogies are due to the genetic correlations between RHP and LIMBS (0.74). Both, RHP and LIMBS are composed traits and the individual traits included show variable genetic correlations among each other. Strongest correlations between traits included in RHP and traits included in LIMBS were observed between the conformation of front legs and the frame, and between the correctness of gaits and the development and general impression of the individual horse. It is likely that QTL analogous between RHP and LIMBS are harbouring genes that have impact on one trait and hence on the other, too.
We compared the identified QTL to positively selected regions in Thoroughbreds found by Gu et al. (2009) [4]. The putative QTL for RHP on ECA17 was also found to be subjected to positive selection in Thoroughbreds. For LIMBS we found analogy in QTL on ECA5, and putative QTL on ECA8, 11 and 17. However, none of the other potential QTL coincided with those regions. Those analogies could be due to the common usage of Thoroughbred stallions in Hanoverian breeding to make future progenies nobler. However, in the Hanoverian horse population analyzed here, possible breed-related marker associations have been on purpose sufficiently accounted for in the models used, to reveal within-breed-variation for RHP and LIMBS. In contrast, Gu et al. (2009) [4] were searching for across-breed-variations to reveal genomic regions distinctive primary for Thoroughbreds.
We detected six functional candidate genes within the defined and putative QTL for RHP and seven functional candidate genes within the QTL and putative QTL for LIMBS. On ECA3 we revealed PPARGC1A and LCORL as promising candidate genes for RHP in proximity to BIEC2-808466, one of seven neighbouring SNPs
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estimated as highly significant using any of the applied models. PPARGC1A transcriptionally activates a complex pathway of lipid and glucose metabolism and is expressed primarily in tissues of high metabolic activity such as liver, heart and exercising oxidative skeletal muscle fibers. The PPARGC1A is a coactivator of the subset of oxidative phosphorylation genes that control glucose and lipid transportation and oxidation, skeletal muscle fiber type formation and mitochondrial biosynthesis [5]. Studies in Brangus steers revealed associations of SNPs in the bovine PPARGC1A with growth and meat quality traits [6]. A SNP marker within the human PPARGC1A shows strong association with endurance capacity. Trained individuals show in general increased PPARGC1A mRNA levels and increased resistance to muscle fatigue [7]. Recently, Eivers et al. (2009) [8] found in Thoroughbreds a significant association with post-exercise PPARCG1A expression in equine skeletal muscle and post-exercise plasma lactate concentration. Thus PPARGC1A is a candidate gene that might influence RHP through an athletic and muscular phenotype.
On the same chromosome we identified LCORL as a functional candidate gene.
Polymorphisms in LCORL are significantly associated with measures of skeletal frame size (trunk length) and adult height in human and mice [9], [10]. In horses, trunk length and height at withers strongly affect the conformation of the saddle position, the frame, and general impression and development, three of the traits included in RHP.
CYP27B1 is a cytochrome P450 enzyme in the proximal tubule of the kidney that catalyzes the hydroxylation of calcidiol to calcitriol, the bioactive form of Vitamin D3, which binds to the vitamin D receptor (VDR) and regulates calcium metabolism.
Thus, this enzyme regulates the level of biologically active vitamin D and plays an important role in calcium homeostasis. Panda et al. 2003 [11] found that mice deficient for CYP27B1 developed features similar to those of human rickets:
hypocalcemia, secondary hyperparathyroidism, retarded growth, and skeletal abnormalities. The orthologous equine gene is localized on ECA6 next to BIEC2-1187571 that has a significant additive effect (P<0.01) on RHP.
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On ECA18 next to BIEC2-391005, and on ECA19 in proximity to BIEC2-422566 we found MYO7B and SHOX2 as functional candidate genes within QTL for RHP as well as for LIMBS. Myosins are the fundamental functional units of straight muscles, by being molecular motors that, upon interaction with actin filaments, utilize energy from ATP hydrolysis to generate mechanical force. Dall'Olio et al. (2009) [12] found SNPs in the myosin heavy chain 7 gene varying among horse breeds that differ in performance and morphology traits. That indicates that genes involved in the myosin formation play central roles for conformational traits and physical performance. Most conformational traits included in RHP are positively affected from a well defined, muscular outline. Scores for front and hindlegs benefit if they are lean, well muscled and defined. Hence, we suppose MYO7B represents a suitable candidate gene for RHP as well as for LIMBS.
Mutations in the human SHOX2 lead to growth retardation associated with Turner, Leri-Weill dyschondrosteosis, and Langer mesomelic dysplasia syndromes, which marked the shortening of the forearms and lower legs [13]. Same results could be observed in mice with inactivated SHOX2 in the developing limbs [14]. Some traits included in RHP, in particular saddle position and frame, are influenced by the conformation of front legs. In this context, genes like SHOX2 are suitable candidate genes for RHP as well as for LIMBS.
On ECA21 localized next to BIEC2-554900, which is found highly associated with RHP using any of the implemented models, FST represents another potential candidate gene for RHP. Follistatin is an autocrine glycoprotein that is expressed in nearly all tissues of higher animals. It is being studied for its role in regulation of muscle growth in mice, as an antagonist to myostatin (MSTN) which inhibits excessive muscle growth. Lee and McPherron (2001) [15] demonstrated that inhibition of MSTN, either by genetic elimination (knockout mice) or by increasing the amount of follistatin, resulted in greatly increased muscle mass.
For LIMBS we detected a highly significant SNP (BIEC2-898157) intragentic in PRG4 on ECA5. The protein encoded by PRG4 is a large proteoglycan specifically synthesized by chondrocytes located at the surface of articular cartilage, and also by some synovial lining cells. It functions as a boundary lubricant at the cartilage surface
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and contributes to the elastic absorption and energy dissipation of synovial fluid.
Mutations in this gene result in camptodactyly-arthropathy-coxa vara-pericarditis syndromean, an arthritis-like autosomal recessive disorder [16]. PRG4 has multiple functions in articulating joints and tendons that include the protection of surfaces and control of synovial cell growth [17]. We suppose, PRG4 could have an influence on LIMBS through its function as a lubricant in joints and tendons [18]. In additions, it represents is highlighted through BIEC2-898157 as a positional candidate gene.
On ECA25 COL15A1 in proximity to 655148 and RAD23B next to BIEC2-659406 are functional candidate genes. Both SNP markers had highly significant (P
<0.01) additive effects on LIMBS. Collagen is a protein that strengthens and supports many tissues in the body, including cartilage, bone, tendon, skin and sclera. Type XV collagen has a wide tissue distribution but the strongest expression is localized to basement membrane zones so it may function to adhere basement membranes to underlying connective tissue stroma. Mouse studies have shown that collagen XV deficiency is associated with muscle and microvessel deterioration [19]. In human, the collagen, type I, alpha 1, and the collagen, type V, alpha 1 genes are highly associated with tendon injuries, indicating genes coding for collagens as suspicious candidate genes for LIMBS.
The protein encoded by RAD23B is one of two mammal homologs of Saccharomyces cerevisiae Rad23, a protein involved in the nucleotide excision repair. Ng et al. (2002) [20] created a RAD23B knockout mouse model and observed a high rate of intrauterine or neonatal death in RAD23B deficient animals. However, surviving animals displayed a variety of abnormalities, including retarded growth.
Further analyses are required to investigate whether RAD23B has impact on equine limb growth.
RNF160 on ECA26 next to BIEC2-691812, which has highly significant additive (P<0.01) and dominance effects (P<0.01) on RHP, represents another promising candidate gene. Like most RING finger proteins, RNF160 function as an ubiquitin ligase. Chu et al. (2009) [21] identified a recessive mutation in the mouse RNF160 that manifested as a progressive movement disorder. Affected mice exhibited
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dependent and often asymmetrical progressive weakness of the hind limbs, bradykinesia, and eventually loss of locomotion.
On ECA31 next to a SNP (BIEC2-841254) that has a highly significant (P<0.01) additive effect on LIMBS, we identified PLAGL1 as another functional candidate gene. PLAGL1 encodes a C2H2 zinc finger protein with transactivation and DNA-binding activity and is a member of a network of co-regulated genes comprising other imprinted genes involved in the control of embryonic growth. Varrault et al. (2006) [22] could show that PLAGL1 insufficient mice had intrauterine growth restriction, altered bone formation, and neonatal lethality. Whether PLAGL1 influences equine limb growth remains open and further analyses are required for verification.
In doges several QTL harbouring candidate genes appropriate to regulation of size are described [23]. For the stallion population investigated in this study we could not detect one of the genes significantly associated with size in dog breeds. Aim of the present study was to reveal QTL for within breed variation for RHP and LIMBS in the Hanoverian population investigated. In contrast, Jones et al. (2008) [23] were searching for QTL associated to across-breed-variation for conformation.
Accordingly, genes involved in major conformational variation observed across-breeds are probably not the same responsible for the minor variations observed within a breed.
We can conclude that first of all genes coding for muscular processes, growth, limb development and embryonic development might be constitutive for both, RHP and LIMBS. Hence, our findings are in line with most previous population genetic analyses that found positive genetic correlations between conformation and performance traits. Our findings indicate that genes that influence conformation might also have an impact on physical performance. Further analyses including larger population and denser SNP marker sets are required to verify the potential QTL for RHP and LIMBS. Our approach appeared useful as a starting point to identify QTL for RHP and LIMBS within a breed.
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7.5 Materials and Methods 7.5.1 Animals and phenotypic data
Blood samples were collected from 115 Hanoverian warmblood stallions of the National State stud of Lower Saxony. These stallions were born between 1972 and 2000 and represent a random sample from all Hanoverian stallions born in last 20-30 years. Pedigree data were made available by the Hanoverian studbook society (HSS) through the national unified animal ownership database (Vereinigte Informationssysteme Tierhaltung w.V., VIT). Pedigree records of these stallions allowed us to assign the 115 stallions into 16 families which included a total of 798 stallions (Table S3). We employed the latest BVs RHP and LIMBS (Mai 2009) provided by the HSS. BVs for RHP were estimated based on results of studbook inspection (SBI) since 1979 including 85,598 animals.
RHP is a composed trait resulting from scores for conformation of the head, the neck, the saddle position, the type, the frame and the general impression and
RHP is a composed trait resulting from scores for conformation of the head, the neck, the saddle position, the type, the frame and the general impression and