Spectrum®/Spectrum OR™ Service Manual 00-02 v Foreword Introduction Foreword The Spectrum®/Spectrum OR™ Service Manual is intended as a guide for technically qualified personnel during repair and calibration procedures. This publication may have been updated to reflect product design changes and/or manual improvements.

These abstracts are presented here as prepared by the authors. The accuracy and content of each abstract remain the responsibility of the authors. In the identification number above each abstract, OPO designates an Orthopaedic Section poster presentation.

J Orthop Sports Phys Ther 2018;48(1):A67–A202. doi:10.2519/jospt.2018.48.1.A67

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Zebu animals ( Bos indicus) are known to take longer to reach puberty compared with taurine animals ( Bos taurus), limiting the supply of animals for harvest or breeding and impacting profitability. Genomic information can be a helpful tool to better understand complex traits and improve genetic gains. In this study, we performed a genomewide association study (GWAS) to identify genetic variants associated with reproductive traits in Nelore beef cattle. Heifer pregnancy (HP) was recorded for 1,267 genotyped animals distributed in 12 contemporary groups (CG) with an average pregnancy rate of 0.35 (±0.01).

Disregarding one of these CG, the number of antral follicles (NF) was also collected for 937 of these animals, with an average of 11.53 (±4.43). The animals were organized in CG: 12 and 11 for HP and NF, respectively.

Genes in linkage disequilibrium (LD) with the associated variants can be considered in a functional enrichment analysis to identify biological mechanisms involved in fertility. Medical Subject Headings (MeSH) were detected using the MESHR package, allowing the extraction of broad meanings from the gene lists provided by the GWAS. The estimated heritability for HP was 0.28 ± 0.07 and for NF was 0.49 ± 0.09, with the genomic correlation being −0.21 ± 0.29. The average LD between adjacent markers was 0.23 ± 0.01, and GWAS identified genomic windows that accounted for 1% of total genetic variance on chromosomes 5, 14, and 18 for HP and on chromosomes 2, 8, 11, 14, 15, 16, and 22 for NF.

The MeSH enrichment analyses revealed significant ( P. INTRODUCTIONReproductive traits are economically important in beef cattle production, especially for zebu animals ( Bos indicus), where heifers often take longer to reach puberty (; ) compared with taurine animals ( Bos taurus). Reduced heifer fertility impacts the profitability of a given size herd in the production system by decreasing the number of weaned calves and increasing the lifetime costs of herd replacements.The inclusion of genomic information in genetic evaluations can be a helpful tool to analyze polygenic traits, such as those for reproduction, shortening the time it takes to obtain reliable breeding value estimates, which can lead to reduced generation intervals and improving genetic gains. It positively affects accuracies by including a more precise measure of genetic similarity between individuals compared with traditional pedigree-based evaluations (; ). Bee gees greatest hits download. Genomic markers such as SNP can be used in genomewide association studies ( GWAS), a well-established strategy that has identified thousands of markers spread across the cattle genome related to important economic traits. Genomewide association study relies on linkage disequilibrium ( LD) between at least 1 marker and the causal mutation or quantitative trait nucleotides responsible for the observed phenotypic variation.Female fertility can be measured in a number of different ways.

Heifer pregnancy ( HP), defined by the determination of whether or not a heifer exposed to breeding has become pregnant, is a directly measured trait for which data collection is an easy and inexpensive process. This allows its implementation as a selection criterion in large herds.Because reproductive technologies, such as ovum pick up and in vitro fertilization ( IVF), are widely adopted in zebu herds, the numbers of antral follicles ( NF) has become a relevant trait, due to its association with female performance for ovum pick up and IVF.A better understanding of genetic factors that affect reproduction could lead to substantial improvement in genetic selection to improve reproductive rates. Identification of genomic regions associated with reproductive traits could expand our understanding of reproductive processes and be used to improve reproductive efficiency in cattle, especially in zebu animals.Medical Subject Headings ( MeSH) is a collection of comprehensive life sciences terms organized by the U.S. National Library of Medicine (Bethesda, MD); it is the annotation used for PubMed documents. These terms are clustered into 16 categories, and the size of MeSh's vocabulary library is approximately twice as large as that of Gene Ontology.

They have been recently used in overrepresentation analysis , permitting the extraction of broad meaning from the gene lists provided by GWAS.In this study, phenotypic information for HP and NF were collected from Nelore heifers on commercial farms in Brazil. Following whole-genome genotyping, GWAS was performed to identify genomic regions associated with these traits followed by MeSH enrichment analyses of these regions, aiming to increase knowledge about the genetic influence and biological role of genes related to HP. This is the first study in Nelore cattle introducing the concept of MeSH analysis. Heifer PregnancyThe diagnosis of pregnancy was performed using ultrasound (Chison 8200VET with 7.5 MHz transducer; Kylumax, Wuxi, China) or transrectal palpation 40 d after AI. Phenotypic records were treated as categorical, assigning the value of 1 (success) to heifers that were diagnosed pregnant and 0 (failure) to those that were not pregnant at the time of diagnosis.In tropical countries, calving is normally spread from July to November, with heifers entering the October breeding season at between 12 (born in November) and 16 mo old (born in July). So challenging animals around 15 mo old is a strategy to select for sexual precocity that fits in with the routine management of the farms.

Genotypic DataHair samples of 1,267 young heifers (about 16 mo old) from 2,283 available animals were collected for genomic DNA extraction and subsequent genotyping analysis using the GeneSeek GGP Bos indicus HD array (Neogen, Lincoln, NE) with 74,677 SNP, specially developed for B. Indicus cattle. All 1,267 animals had phenotypic records for HP and, of those, 938 also had NF records.Quality control procedures were performed using PREGSF90 version 1.10 software to reduce spurious associations and, consequently, increase the accuracy of the genomic analyses. The quality control parameters used herein to delete loci were minor allele frequency 15%. Samples with call rate. In which y is the vector of the dependent variable (observed phenotypes) for genotyped and nongenotyped animals; b is the vector of fixed effects, including the CG and linear covariate for heifer age at pregnancy diagnosis; a is the vector of random additive genetic effects; X and Z are incidence matrices relating b and a with the dependent variable y; and e is a vector of random residual errors.

Variance components for HP were estimated using a threshold model, which related the observed trait on a categorical scale to an underlying continuous normal scale, whereas NF was modeled as a continuous variable.The covariance matrix of a and e assumed. In which M is a transformed incidence matrix of marker alleles whose elements in the ith column are 0 − 2 p i, 1 − 2 p i, and 2 − 2 p i for genotypes AA, AB, and BB, respectively; M′ is the transpose of M; and p i is the frequency of allele B in the ith marker.A total of 2,200,000 chains were generated for this variance component analysis using THRGIBBS1F90 , discarding the first 200,000 iterations (burn-in). The convergence of Markov chain Monte Carlo ( MCMC) chains was verified by Geweke's convergence test and visual inspection of trace plots using the boa (Bayesian output analysis) package in R software. The genetic and residual variance estimates were used as prior values in the subsequent Bayesian analysis. In which A, a, B, and b are the frequencies of each allele in the studied population. The analyses were conducted with PLINK version 1.9.The associations between SNP markers and the phenotypic information were performed using BayesB methodology, which simultaneously analyzes all SNP data and assumes a different genetic variance for each SNP locus with scaled inverse χ 2 prior distributions and that a fraction (1 − π) of the markers have nonzero effects (; ).

The traits were analyzed separately using GenSel software , and the posterior distribution of marker effects was predicted under the statistical model. In which π was assumed to be 0.999, which results in about 0.1% of the SNP fitted in the model at each iteration. The marker genetic prior for χ 2 and the random residual prior with ν β = 4 and ν e = 10 df, and scale parameters estimated as and, respectively, in which n is the number of individuals.A total of 90,000 iterations was considered, where the first 2,000 were discarded (burn-in) and the following 88,000 were used to predict the posterior mean effect of each SNP marker. Rather than using effects of individual markers, the proportion of variance explained by nonoverlapping 1-Mb genomic windows comprising all the SNP effects in that region were used for inference in the genomewide association.

This proportion was sampled. Gene Search and Functional EnrichmentThe important regions identified by the GWAS were extended on either side (±500 kb) for the functional enrichment analyses and gene search. Annotated genes in these regions were retrieved from the Ensembl Genes 87 database using Biomart software.Medical Subject Headings terms were detected using the MESHR package for enrichment analyses considering the genes that were associated with HP (127) and NF (91). Medical subject headings identification associated with each Entrez Gene Identifications were obtained from the MESH.BTA.EG.DB annotation package , assuming a universe of all annotated genes with a unique corresponding Entrez Gene identifications (17,093). The R package uses a hypergeometric test to assess the significance of the enrichment as described. The terms with a P-value. RESULTS AND DISCUSSIONThe genomic estimates of heritability on the liability scale by the single-step method were 0.28 (SD 0.07) for HP and 0.49 (SD 0.09) for NF.

The estimated genomic correlation was −0.21 (SD 0.29). This high SD makes the confidence interval straddle 0, suggesting weak or no genetic association between the traits. The highest posterior density (0.025–0.975%) interval estimated for the genomic correlation between HP and NF was remarkably wide, varying between −0.781 and 0.329. As the proposed convergence criteria were well met, the width of this interval may be attributed to the limited number of observations included in the present study.

Genomewide Association StudyThe average LD between adjacent markers was 0.23 ± 0.01, ranging from 0.20 on chromosome 27 to 0.25 on chromosome 5 , and the overall LD on the same chromosome varied from 0.09 on chromosome 27 to 0.13 on chromosome 6, with an average of 0.11 (SD 0.01; Supplemental Fig. S1 see the online version of the article at ). Reported an r 2 averaging 0.17 for overall SNP in a population of 795 Nelore bulls with approximately 447,000 markers. This observed difference is expected because LD is inversely proportional to the distance between markers, with denser genotypes generally having high overall LD. Found average r2 of 0.21 ± 0.27 and 0.16 ± 0.20 in 391 Hereford and 2,019 Braford animals, respectively, with approximately 41,000 SNP. As noted by those authors, LD can be influenced by several factors and is, therefore, population specific. Mean values (±SD) of linkage disequilibrium ( r 2) of adjacent markers by chromosomes in the studied population of Nelore heifers.A total of 2,673 genomic windows were constructed for 30 chromosomes (29 autosomes and the X chromosome) including, on average, 25.5 SNP distributed between flanking SNP that were 934 kb apart.

The results identified significant regions on chromosomes 5, 14, and 18 for HP and 2, 8, 11, 14, 15, 16, and 22 for NF that each explained 1% of the total genetic variance ( and ). These genomic regions were used to locate candidate genes and are presented on and for HP and NF, respectively. Other genomic regions on chromosomes 1, 2, 3, 5, 14, 24, 29, and X demonstrated an important influence on HP and genomic regions on chromosomes 2, 12, 15, 19, 24, 25, and 29 demonstrated an important influence on NF , explaining 0.5% of the total additive genetic variance. Nonetheless, these regions were not considered in the further analyses.

CHR 1Position (UMD 3.1 bovine assembly 2)GenesVar, 3%No. CHR 1Position (UMD 3.1bovine assembly 2)GenesVar, 3%No. CHR 1SNPstart 2SNPend 3Posstart, 4 bpPosend, 5 bpSize, 6 bpNo. CHR 1SNPstart 2SNPend 3Posstart, 4 bpPosend, 5 bpSize, 6 bpNo. Of SNP 7%Var 824rs133021126rs2,008,41762,594,740.9129rs42183484rs3,000,05233,914,330.9012rs109641299rs0,015,62760,994,480.812rs42321794rs6,028,20256,979,910.7919rs109030622rs1,000,10961,990,850.7519rs136160175rs,008,92256,945,750.7519rs137834616rs6,010,13126,962,490.6725rs134031092rs6,006,91316,986,610.6012rs110539435rs0,015,79130,992,700.5815rs137836273rs1,018,17681,864,820.5812rs137815663rs9,019,12679,976,470.56Xrs133820946rs44,008,894144,988,850.50. 8%Var = percentage of the additive genetic variance explained by the window.Six and 7 genomic windows explained at least 1% each of the additive genetic variance for HP and NF, respectively. The cumulative genetic variance explained by these windows was 12.73% for HP and 20.12% for NF.

The highest proportion of genetic variance explained by a window for HP was 3.90% in a window located at 73 Mb in chromosome 5, whereas for NF, the most relevant window explained 5.56% of the genetic variance; this window is located at 15 Mb in chromosome 22. Half of the genetic variance was explained by 237 windows for HP and 116 windows for NF, whereas to achieve 90% of explained variance, it would be a similar function of 1,704 windows for HP and 2,673 windows for NF. Medical Subject Headings Enrichment AnalysesThe MeSH enrichment analyses revealed 74 terms related to HP (Supplemental Table S1; see the online version of the article at ) and 48 terms related to NF (Supplemental Table S2; see the online version of the article at ).

After the Benjamini and Hochberg correction, the terms that were significantly ( P. Chromosome 5Twenty-four genes in 3 genomic windows on chromosome 5 had large effects on HP. A study by found a significant peak on this chromosome (approximately 40 cM) for ovulation rate and suggested that this chromosome may harbor important genes for this trait in cattle.

The results of found highest meta-GWAS scores on chromosome 1, 5, 13, and 16 for fertility traits.The genes TOM1 and HO-1 are associated with pregnancy in humans. Noted that TOM1 downregulates the transcription factor AP1, which is involved in the LH pathway in preovulatory bovine granulosa cells. They also confirmed that TOM1 is a negative biomarker of oocyte competence. Heme-oxygenase 1 ( HO-1) is an oxidative stress-related gene, and high levels of expression in cumulus cells is associated with reduced oocyte fertilization in humans. These results support the hypothesis that this genomic region (72–74 Mb) is involved with HP outcomes.In a study by, chromosome 5 harbored the most important markers associated with reproductive traits, such as age at puberty, in Tropical Composite cattle. The most significant SNP was located at around 96 Mb, which is close to the regions reported in this study (72–83 Mb).

Other studies (;;;; ) also related this chromosome to reproductive traits. Insulin-like growth factor 1 ( IGF1) is located at 66 Mb and is frequently associated with reproductive traits in cattle. The average LD of adjacent markers between the locations of the middle of this gene (66,564,289 bp) and the middle of the closest genomic window reported in this study (73,494,204 bp) was 0.34 (95% confidence interval 0.30–0.39), suggesting a possible linkage between these markers. Chromosome 14Eighteen genes were associated with both HP and NF in a window (22–24 Mb) on chromosome 14. Associated multiple clusters of SNP related to reproductive traits in 843 Brahman and 866 Tropical Composites beef heifers, with the most significant markers located between 22 and 25 Mb. A meta-GWAS study found the highest score on chromosome 14 for sexual maturity in cattle.These same regions had large effects in the current study for both HP and NF, emphasizing their importance in reproductive traits and suggesting a possible pleiotropic effect. This hypothesis was reinforced by comparing the correlation of the genomewide estimated genomic values of HP and NF with the estimated genomic values when considering only the markers present in referenced genomic window.

The estimates were −0.14 (95% confidence interval −0.21 to −0.08) when considering all SNP and −0.30 (95% confidence interval −0.36 to −0.24) considering only SNP in the referened window. A Fisher r-to-Z transformation test was performed to assess significant differences between the estimates, and the obtained result ( P. Chromosome 18The genomic window (54–56 Mb) on chromosome 18 included 83 different genes. The galactoside 2-α- L- fucosyltransferase ( FUT2) gene appears to be stimulated by estrogen, and the correlated expression of fucosylated H-typed-1 carbohydrate epitope in the endometrial epithelia may be involved with embryo implantation. The FUT1 gene was associated with daughter pregnancy rate as well as total number of piglets born (; ), and also found significant associations between this gene and cow conception rate and daughter pregnancy rate in Holstein cattle.The proapoptotic Bcl-2 associated X protein ( BAX) gene accelerates programmed cell death, and it has been shown that the absence of this gene results in infertility in males.

However, in females, Bcl-2 knockout mice exhibit increased oocytes and follicle numbers , although found that upregulation of this gene resulted in enhanced follicle damage and premature ovarian failure in mice.Luteinizing hormone β polypeptide ( LHB) is known to promote ovulation by stimulating the ovaries to synthesize steroids. Luteinizing hormone is secreted by the pituitary gland and plays an important role in gonadal functions. Associated a homozygous mutation in the LHB gene with delayed puberty in humans. Normal pulsatile release of this hormone is crucial for successful induction of LH receptors on the granulosa cells of the developing dominant follicle. Reported a positive correlation between feed intake and LH concentration, with both high and low values being harmful to embryo development.The genes SLC17A7, SLC6A16, and SLC8A2 are part of the solute carrier family. SLC17A7 is regulated by estrogen and encodes the vesicular glutamate transporter 1 (Vglut1) protein, which is expressed in cells of the hippocampus and may be associated with estrogen regulation.

SLC6 specifically transports neurotransmitters (e.g., dopamine and serotonin), AA (e.g., gamma 1-aminobutyric acid GABA), and osmolytes (e.g., betaine, taurine, and creatine; ). SLC8A2 mediates the electrogenic exchange of Ca 2+ against Na+ ions across the cell membrane. Reported that SLC8A is expressed in the uterine endometrium of pregnant pigs and concluded that calcium extrusion molecules may be associated with the establishment and maintenance of pregnancy.The sphingosine kinase (SPHK) gene family is part of the sphingolipid metabolic pathway, which is highly activated in decidua during pregnancy. The isoform genes SPHK1 and SPHK2 participate in the pathway of the bioactive lipid sphingosine 1-phosphate ( S1P) and have been associated with vasoconstriction in human uterine arteries during pregnancy.

Found that mutant mice for SPHK1 and SPHK2 produced infertile females, with reduced production of S1P. Chromosome 2The associated genomic window on chromosome 2 (122–124 Mb) harbored 12 genes. The intracellular fatty acid–binding proteins (FBP) are associated with metabolism and transport of long-chain fatty acids that have import roles in oocyte meiotic maturation prior to ovulation. The small nuclear ribonucleoproteins have been related to oocyte maturation, fertilization, and early embryogenesis in mouse.associated the Pumilio 1 ( PUM1) gene in Drosophila with embryogenesis, primordial germ cell proliferation, germline stem cell division, and the oogenic process. PUM1 is also involved in oocyte maturation in Xenopus. The presence of anti-Pum antibody, or the overexpression of Pum1, has significant impacts on oocyte maturation. Reported that this gene plays a critical role in the establishment of primordial folliculogenesis, meiosis, and female fertility in mice.

Chromosome 11Eleven genes were reported in the genomic window at chromosome 11 (69–71 Mb). SPDYA is a protein-coding gene expressed in pathways related to oocyte meiosis. Additionally, it was also associated with oocyte maturation in humans and Xenopus. Concluded that this class of genes is an essential component of cell proliferation pathways.FOS-like antigen 2 ( FOSL2) participates in the regulation of steroidogenesis, which includes the estrogen hormone. This gene encodes components of activator protein 1 ( AP-1), which participates in the terminal differentiation of granulosa cells to luteal cells.

Suggested that elements from the FOS gene family are activated in porcine corpora lutea with acquired luteolytic sensibility, playing an important role in structural luteolysis in pigs.The protein yippee-like 5 ( YPEL5) is part of the yippee like (YPEL) gene family involved with cell cycle progression and growth, with high expression in oocytes (; ). Reported significant upregulation of this gene in large follicles (10 mm) compared with small follicles (. Chromosome 15Only 2 genes were present in the associated genomic window on chromosome 15 (8–10 Mb). The protein-coding gene Rho GTPase activating protein 42 ( ARHGAP42) influences blood pressure in vascular smooth muscle. ARHGAP42 also is involved in biological processes related to the regulation of Rho protein, which is part of a family of proteins involved in regulation and timing of cell division. Associated this gene with age at menarche and age at natural menopause in African American women.

Chromosome 16The associated genomic window on chromosome 16 (70–72 Mb) harbored 13 genes. Discussed the association of the G protein-coupled receptor 37 ( GPR37) with gonadal differentiation in mice. Mutant animals (GPR37-null) had impaired testis development, affecting postnatal Sertoli cell proliferation and maturation, resulting in significant reduction of sperm count. This gene may have similar functions in females, affecting granulosa cell proliferation and animal fertility.Although the precise function of leucine-rich repeat-containing G protein coupled receptor 6 ( LGR6) is still unknown, other leucine-rich repeat-containing G-protein coupled receptor (LGR) genes have been characterized as part of the insulin gene family, which also includes important reproductive genes including LH, FSH, and TSH. LGR7 and LGR8 are receptors for relaxin hormone, which is primarily produced by the corpus luteum. LGR4 knockout mice were infertile and exhibited abnormal development of the reproductive tract.Protein phosphatase 1 regulatory subunit 12B ( PPP1R12B) may be involved with insulin signaling.

This gene is associated with smooth muscle contractibility and regulation of uterine cell hypertrophy in the early stages of gestation. Found that PPP1R12B participates in protein phosphorylation, which may influence reproduction in humans.Protein tyrosine phosphatases ( PTP) regulate many cellular processes, such as metabolism, cell–cell adhesion, cell migration, cell growth, and the expression of transformation growth factor beta, which is a key regulator of follicle development in mammals (; ). Reported that 48 PTP genes are expressed in zebra fish embryos, with the majority of them being maternally derived. Chromosome 22Twenty genes were reported in the associated genomic window on chromosome 22 (14–16 Mb). Showed that testis and ovary-specific PAZ domain gene 1 ( TOPAZ1) is expressed in the gonads of sheep and mice, particularly in pregnant females during fetal gonad development.

They concluded that the gene has an important function in germ cell meiosis. Supporting these findings, found that this gene also plays an important role in the progression of meiosis in oocytes and spermatogenesis in mice.Lysozyme-like ( LYZL) genes belong to the class of c-type lysozymes, which are widely distributed in the animal species and which have protective bacteriolytic functions in host defense. LYZL4 is expressed in the epithelium of the human epididymis, and it has also been observed on the surface of human embryonic stem cells. When mouse spermatozoa were incubated with anti- LYZL4 antibodies, there was a concomitant loss of fertilizing ability. Some studies (; ) have suggested that this gene could be used as a biomarker for male fertility. The LYZL genes may have similar functions in females, participating in the process of germ cell developmentIn summary, this study provides evidence of the genomic complexity involved in reproductive traits.

Genomic regions on chromosomes 5, 14, and 18 showed important associations (that explained 1% of the total additive genetic variance) with HP, whereas regions on chromosomes 2, 8, 11, 14, 15, 16, and 22 had large associations with NF. Although the same genomic window on chromosome 14 was associated with both traits, their genetic correlation was not relevant, suggesting that the selection for one trait has no interference in the other trait. The MeSH terms “Munc18 Proteins,” “Fucose,” and “Hemoglobins” were significantly related to HP, and the MeSH terms “Cathepsin B,” “Receptors, Neuropeptide,” and “Palmitic Acid” were related to NF. Increasing the knowledge about associated genomic regions and genes may be useful for enhancing genomic selection, increasing evaluation accuracy, and making better selection decisions. ConclusionsGenomewide association studies allowed us to identify genomic regions associated with the reproductive traits heifer pregnancy and number of antral follicles. Medical Subject Headings enrichment analyses identified important biological processes that are related to the expression of the phenotypes, providing useful information about the genetic components of these traits. The gene search suggested that some genomic regions harbor important genes related to the traits studied, which could be used in genomic prediction to improve reproductive performance.