scholarly journals Genomic Correlations Between the Gaits of Young Horses Measured by Accelerometry and Functional Longevity in Jumping Competition

2021 ◽  
Vol 12 ◽  
Author(s):  
Manon Dugué ◽  
Bernard Dumont Saint Priest ◽  
Harmony Crichan ◽  
Sophie Danvy ◽  
Anne Ricard
Keyword(s):  
Principal Components ◽  
Genomic Data ◽  
Principal Component ◽  
Well Being ◽  
Relationship Matrix ◽  
Significant Qtls ◽  
Breeding Values ◽  
A Genome ◽  
Young Horses ◽  
Show Jumping

Functional longevity is essential for the well-being of horses and the satisfaction of riders. Conventional selection using longevity breeding values calculated from competition results is not efficient because it takes too long to obtain reliable information. Therefore, the objective was to identify early criteria for selection. We assessed two types of early criteria: gait traits of young horses and QTLs. Thus, our aim was to estimate the genetic correlation between gait traits and longevity and to perform a genome-wide association study (GWAS) for longevity. Measurements of gaits by accelerometry were recorded on 1,477 show jumping horses that were 4 to 5 years old. Gait analysis provided 9 principal components describing trot, canter, and walk. Longevity estimated breeding values (EBVs) for stallions were calculated using a survival analysis of more than 900,000 years of performances by 179,448 show jumping horses born from 1981 onwards. Longevity was measured as the number of years spent in competition. Model included region and month of birth, age at first competition, year, and performance level. Longevity EBVs were deregressed to obtain weighted pseudo-performances for 1,968 stallions. Genomic data were available for 3,658 jumping horses. Seventy-eight percent of the horses measured for gaits and twenty-five percent of those measured for longevity were genotyped. A GWAS of longevity revealed no significant QTLs. Genetic parameters between each of the 9 principal components of the gait variables and longevity were evaluated with a bi-trait animal linear mixed model using single-step GBLUP analysis with the relationship matrix constructed from genomic data and genealogy (24,448 ancestors over four generations). The heritability of the gait traits varied from 0.11 to 0.44. The third principal component for trot (high lateral activity) and the first principal component for canter (high dorsoventral activity and low stride frequency) were moderately genetically correlated with higher longevity: rg = 0.38 (0.15) and 0.28 (0.13), respectively. Our study revealed that functional longevity is a polygenic trait with no major genes. We found new correlations between longevity and gait traits. Before using gait characteristics in a selection plan, these correlations need to be understood better at the biomechanical level.

Genome-wide association and genomic selection in animal breedingThis article is one of a selection of papers from the conference “Exploiting Genome-wide Association in Oilseed Brassicas: a model for genetic improvement of major OECD crops for sustainable farming”.

Genome ◽  
2010 ◽  
Vol 53 (11) ◽  
pp. 876-883 ◽  
Author(s):  
Ben Hayes ◽  
Mike Goddard
Keyword(s):  
Genomic Selection ◽  
Complex Traits ◽  
Association Studies ◽  
Genome Wide Association ◽  
Relationship Matrix ◽  
Genome Wide Association Studies ◽  
Simple Method ◽  
Breeding Values ◽  
Genome Wide ◽  
A Genome

Results from genome-wide association studies in livestock, and humans, has lead to the conclusion that the effect of individual quantitative trait loci (QTL) on complex traits, such as yield, are likely to be small; therefore, a large number of QTL are necessary to explain genetic variation in these traits. Given this genetic architecture, gains from marker-assisted selection (MAS) programs using only a small number of DNA markers to trace a limited number of QTL is likely to be small. This has lead to the development of alternative technology for using the available dense single nucleotide polymorphism (SNP) information, called genomic selection. Genomic selection uses a genome-wide panel of dense markers so that all QTL are likely to be in linkage disequilibrium with at least one SNP. The genomic breeding values are predicted to be the sum of the effect of these SNPs across the entire genome. In dairy cattle breeding, the accuracy of genomic estimated breeding values (GEBV) that can be achieved and the fact that these are available early in life have lead to rapid adoption of the technology. Here, we discuss the design of experiments necessary to achieve accurate prediction of GEBV in future generations in terms of the number of markers necessary and the size of the reference population where marker effects are estimated. We also present a simple method for implementing genomic selection using a genomic relationship matrix. Future challenges discussed include using whole genome sequence data to improve the accuracy of genomic selection and management of inbreeding through genomic relationships.

scholarly journals Evaluation of Breeding Value Based on Scores Achieved in the Polish Championships for Young Horses

2015 ◽  
Vol 15 (4) ◽  
pp. 879-887
Author(s):  
Tomasz Próchniak ◽  
Iwona Rozempolska-Rucińska ◽  
Grzegorz Zięba ◽  
Marek Łukaszewicz
Keyword(s):  
Genetic Improvement ◽  
Genetic Parameters ◽  
Performance Test ◽  
Breeding Value ◽  
Genetic Trend ◽  
Breeding Values ◽  
Physical Traits ◽  
Young Horses ◽  
Show Jumping ◽  
Detailed Picture

Abstract Genetic improvement of show jumping horses is problematic, given the multitude of physical traits that determine sport usability and the specific mental predispositions required during training and competitions. The Polish Championships for Young Horses (PCYH) provide an opportunity to evaluate usability traits in Polish horses, which, however, is not a basis for evaluation of the breeding value. The aim of the study was to propose a model for evaluation of the breeding value of horses taking part in the Championships. In total, 1232 starts of 894 4-, 5-, 6-, and 7-year-old horses were analysed. Indices of BLUP breeding values were calculated based on 7 traits with known genetic parameters (ranking in the championship, style rating on days 1, 2, and 3, and penalty points on days 1, 2, and 3). A low and irregular genetic trend, significant only in the case of penalties scored on days 1 and 2 of the championships, was shown. Compatibility of the evaluation of the breeding value estimated on the basis of scores achieved in the Polish Championships for Young Horses with the scores of the performance test carried out in Training Centres was shown. It was also demonstrated that the “sum penalty” and “sum style” measured during the three days of the Championships is sufficient for evaluation of the BLUP breeding value. It was suggested that the evaluation combined with the results achieved at the PCYH (in four age categories) would provide a more detailed picture of the genetic predispositions of jumping horses.

The structure of a cattle stud determined using a medium density single nucleotide polymorphism array

2012 ◽  
Vol 52 (10) ◽  
pp. 890 ◽  
Author(s):  
Blair E. Harrison ◽  
Rowan J. Bunch ◽  
Russell McCulloch ◽  
Paul Williams ◽  
Warren Sim ◽  
...  
Keyword(s):  
Single Nucleotide Polymorphism Array ◽  
Genetic Difference ◽  
Principal Component ◽  
Relationship Matrix ◽  
Nucleotide Polymorphisms ◽  
Genetic Progress ◽  
Individual Property ◽  
Single Nucleotide ◽  
A Genome ◽  
Tick Burden

Genetic progress depends on accurate knowledge of the genetic composition of a population or herd including level of inbreeding and parentage. However, in many circumstances, such as at an individual property level, the relationships between animals may be unknown, or at best, only partly known. In this study, we used DNA from 938 animals and genotypes from ~54 000 single nucleotide polymorphisms (SNP) to determine the genetic structure of a stud from Central Queensland. Animals on the study were bred using multi-sire mating in mobs of composite tropically adapted cattle of the Senepol, Belmont and Bonsmara breeds. Following genotyping using an array of 54 000 SNP, we were able to separate animals into breed groups using principal components and show that ~400 SNP were sufficient to separate animals into stable groups if the sample was genetically diverse. However, precise principal component values were only achieved when a few thousand SNP were used. We characterised the pedigree relationships between individuals using a genome relationship matrix. At least 3000 SNP were required to calculate accurate relationship coefficients between individuals. Around 19% of paired comparisons between animals showed similarity equivalent to sharing a great-grandparent or 1/64 shared ancestry. Approximately 8% of the individuals showed more than 10% inbreeding. To demonstrate the utility of calculating the relationship coefficients, we counted the tick burden on each animal at more than one time and then calculated the heritability of tick burden of h2 = 0.46 (±0.08). There was no significant genetic difference in tick burden between Belmont and Bonsmara cattle compared with Senepol on this property once a genetic relationship matrix was included to account for co-ancestry of individuals.

scholarly journals Principal Component Analysis of the Well-Being at Work and Respect for Human Rights Questionnaire (WWRRR) in the Mediterranean Region

2020 ◽  
Vol 16 (1) ◽  
pp. 115-124
Author(s):  
Mathilde Husky ◽  
Yosra Zgueb ◽  
Uta Ouali ◽  
Cesar I. A. Gonzalez ◽  
Martina Piras ◽  
...  
Keyword(s):  
Human Rights ◽  
Health Care Providers ◽  
Principal Components ◽  
Essential Element ◽  
Principal Component ◽  
Well Being ◽  
Strongly Correlated ◽  
Care Providers ◽  
Single Factor ◽  
Eigen Value

Background: The Well-Being at Work and Respect for human Rights Questionnaire (WWRR) was conceived based on the hypothesis that the perception of respect for users' rights is an essential element of well-being in the workplace in healthcare. The objective of the study is to examine the principal components of the WWRR. Methods: A random sample representative of a set of professionals working in three different healthcare networks in Tunisia, North-Macedonia, and Italy was enrolled (n=426). Each professional completed a questionnaire on sociodemographic data and the WWRR. The WWRR consists of six items on beliefs about: satisfaction at work, users’ satisfaction, organization at work, respect of users’ and staff human rights, adequacy of resources. A seventh item assesses the perceived needs of personnel. Correlation between the items was evaluated by analysing the principal components with Varimax rotation and Kaiser normalization (which included all components with an Eigen value> 1). Results: A single factor covered over 50% of the variance, all the items of the questionnaire were closely related and compose a single factor. Tunisia presented some differences regarding the item about the human rights of staff. Conclusion: Satisfaction with the respect for the rights of users is strongly correlated with the other factors that are part of the concept of the organizational well-being of health care providers. The WWRR provides a means of measuring this important and often neglected dimension.

scholarly journals Genetic and genomic characterization followed by single-step genomic evaluation of withers height in German Warmblood horses

2022 ◽  
Author(s):  
Sarah Vosgerau ◽  
Nina Krattenmacher ◽  
Clemens Falker-Gieske ◽  
Anita Seidel ◽  
Jens Tetens ◽  
...  
Keyword(s):  
Genome Wide Association Study ◽  
Reference Population ◽  
Single Step ◽  
Relationship Matrix ◽  
Nucleotide Polymorphisms ◽  
Step Method ◽  
Genomic Breeding ◽  
Breeding Values ◽  
A Genome ◽  
Estimation System

Abstract  Reliability of genomic predictions is influenced by the size and genetic composition of the reference population. For German Warmblood horses, compilation of a reference population has been enabled through the cooperation of five German breeding associations. In this study, preliminary data from this joint reference population were used to genetically and genomically characterize withers height and to apply single-step methodology for estimating genomic breeding values for withers height. Using data on 2113 mares and their genomic information considering about 62,000 single nucleotide polymorphisms (SNPs), analysis of the genomic relationship revealed substructures reflecting breed origin and different breeding goals of the contributing breeding associations. A genome-wide association study confirmed a known quantitative trait locus (QTL) for withers height on equine chromosome (ECA) 3 close to LCORL and identified a further significant peak on ECA 1. Using a single-step approach with a combined relationship matrix, the estimated heritability for withers height was 0.31 (SE = 0.08) and the corresponding genomic breeding values ranged from − 2.94 to 2.96 cm. A mean reliability of 0.38 was realized for these breeding values. The analyses of withers height showed that compiling a reference population across breeds is a suitable strategy for German Warmblood horses. The single-step method is an appealing approach for practical genomic prediction in horses, because not many genotypes are available yet and animals without genotypes can by this way directly contribute to the estimation system.

scholarly journals Genomic and phenotypic characterization of finger millet indicates a complex diversification history

2021 ◽  
Author(s):  
Jon Bančič ◽  
Damaris A. Odeny ◽  
Henry F. Ojulong ◽  
Samuel M. Josiah ◽  
Jaap Buntjer ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Finger Millet ◽  
Agronomic Traits ◽  
Genomic Data ◽  
Principal Component ◽  
Component Analysis ◽  
Phenotypic Characterization ◽  
List Type ◽  
A Genome ◽  
New Knowledge

ABSTRACTAdvances in sequencing technologies mean that insights into crop diversification aiding future breeding can now be explored in crops beyond major staples. For the first time, we use a genome assembly of finger millet, an allotetraploid orphan crop, to analyze DArTseq single nucleotide polymorphisms (SNPs) at the sub-genome level. A set of 8,778 SNPs and 13 agronomic traits characterizing a broad panel of 423 landrace accessions from Africa and Asia suggested the crop has undergone complex, context-specific diversification consistent with a long domestication history. Both Principal Component Analysis and Discriminant Analysis of Principal Components of SNPs indicated four groups of accessions that coincided with the principal geographic areas of finger millet cultivation. East Africa, the considered origin of the crop, appeared the least genetically diverse. A Principal Component Analysis of phenotypic data also indicated clear geographic differentiation, but different relationships among geographic areas than genomic data. Neighbour-joining trees of sub-genomes A and B showed different features which further supported the crop’s complex evolutionary history. Our genome-wide association study indicated only a small number of significant marker-trait associations. We applied then clustering to marker effects from a ridge regression model for each trait which revealed two clusters of different trait complexity, with days to flowering and threshing percentage among simple traits, and finger length and grain yield among more complex traits. Our study provides comprehensive new knowledge on the distribution of genomic and phenotypic variation in finger millet, supporting future breeding intra- and inter-regionally across its major cultivation range.Core ideas8,778 SNPs and 13 agronomic traits characterized a panel of 423 finger millet landraces.4 clusters of accessions coincided with major geographic areas of finger millet cultivation.A comparison of phenotypic and genomic data indicated a complex diversification history.This was confirmed by the analysis of allotetraploid finger millet’s separate sub-genomes.Comprehensive new knowledge for intra- and inter-regional breeding is provided.

scholarly journals The impact of QTL allele frequency distribution on the accuracy of genomic prediction

2018 ◽  
Vol 61 (2) ◽  
pp. 207-213 ◽  
Author(s):  
Pourya Davoudi ◽  
Rostam Abdollahi-Arpanahi ◽  
Ardeshir Nejati-Javaremi
Keyword(s):  
Allele Frequency ◽  
Frequency Distribution ◽  
Genomic Prediction ◽  
Prediction Accuracy ◽  
Snp Markers ◽  
Relationship Matrix ◽  
Allele Frequency Distribution ◽  
Breeding Values ◽  
A Genome ◽  
The Impact

Abstract. The accuracy of genomic prediction of quantitative traits based on single nucleotide polymorphism (SNP) markers depends among other factors on the allele frequency distribution of quantitative trait loci (QTL). Therefore, the aim of this study was to investigate different QTL allele frequency distributions and their effect on the accuracy of genomic estimated breeding values (GEBVs) using best linear unbiased genomic prediction (GBLUP) in simulated data. A population of 1000 individuals composed of 500 males and 500 females as well as a genome of 1000 cM consisting of 10 chromosomes and with a mutation rate of 2.5 × 10−5 per locus was simulated. QTL frequencies were derived from five distributions of allele frequency including constant, uniform, U-shaped, L-shaped and minor allele frequency (MAF) less than 0.01 (lowMAF). QTL effects were generated from a standard normal distribution. The number of QTL was assumed to be 500, and the simulation was done in 10 replications. The genomic prediction accuracy in the first-validation generation in constant, and the uniform allele frequency distribution was 0.59 and 0.57, respectively. Results showed that the highest accuracy of GEBVs was obtained with constant and uniform distributions followed by L-shaped, U-shaped and lowMAF QTL allele frequency distribution. The regression of true breeding values on predicted breeding values in the first-validation generation was 0.94, 0.92, 0.88, 0.85 and 0.75 for constant, uniform, L-shaped, U-shaped and lowMAF distributions, respectively. Depite different values of regression coefficients, in all scenarios GEBVs are biased downward. Overall, results showed that when QTL had a lower MAF relative to SNP markers, a low linkage disequilibrium (LD) was observed, which had a negative effect on the accuracy of GEBVs. Hence, the effect of the QTL allele frequency distribution on prediction accuracy can be alleviated through using a genomic relationship weighted by MAF or an LD-adjusted relationship matrix.

Structuring Assessments of Psychopathology

2006 ◽  
Vol 27 (2) ◽  
pp. 87-92 ◽  
Author(s):  
Willem K.B. Hofstee ◽  
Dick P.H. Barelds ◽  
Jos M.F. Ten Berge
Keyword(s):  
Principal Components ◽  
Personality Assessment ◽  
Clinical Sample ◽  
Principal Component ◽  
Normal Sample ◽  
Normative Sample ◽  
Assessment Data ◽  
Obsessive Compulsive ◽  
Oblique Rotation ◽  
Two Samples

Hofstee and Ten Berge (2004a) have proposed a new look at personality assessment data, based on a bipolar proportional (-1, .. . 0, .. . +1) scale, a corresponding coefficient of raw-scores likeness L = ΢XY/N, and raw-scores principal component analysis. In a normal sample, the approach resulted in a structure dominated by a first principal component, according to which most people are faintly to mildly socially desirable. We hypothesized that a more differentiated structure would arise in a clinical sample. We analyzed the scores of 775 psychiatric clients on the 132 items of the Dutch Personality Questionnaire (NPV). In comparison to a normative sample (N = 3140), the eigenvalue for the first principal component appeared to be 1.7 times as small, indicating that such clients have less personality (social desirability) in common. Still, the match between the structures in the two samples was excellent after oblique rotation of the loadings. We applied the abridged m-dimensional circumplex design, by which persons are typed by their two highest scores on the principal components, to the scores on the first four principal components. We identified five types: Indignant (1-), Resilient (1-2+), Nervous (1-2-), Obsessive-Compulsive (1-3-), and Introverted (1-4-), covering 40% of the psychiatric sample. Some 26% of the individuals had negligible scores on all type vectors. We discuss the potential and the limitations of our approach in a clinical context.

Customer-Related Social Stressors

2015 ◽  
Vol 14 (4) ◽  
pp. 165-181 ◽  
Author(s):  
Sarah Dudenhöffer ◽  
Christian Dormann
Keyword(s):  
Service Providers ◽  
Principal Component ◽  
Well Being ◽  
Emotional Dissonance ◽  
Social Stressors ◽  
Data Set ◽  
Confirmatory Factor Analyses ◽  
Confirmatory Factor ◽  
Service Jobs ◽  
Single Data

Abstract. The purpose of this study was to replicate the dimensions of the customer-related social stressors (CSS) concept across service jobs, to investigate their consequences for service providers’ well-being, and to examine emotional dissonance as mediator. Data of 20 studies comprising of different service jobs (N = 4,199) were integrated into a single data set and meta-analyzed. Confirmatory factor analyses and explorative principal component analysis confirmed four CSS scales: disproportionate expectations, verbal aggression, ambiguous expectations, disliked customers. These CSS scales were associated with burnout and job satisfaction. Most of the effects were partially mediated by emotional dissonance. Further analyses revealed that differences among jobs exist with regard to the factor solution. However, associations between CSS and outcomes are mainly invariant across service jobs.

Comparison of Principal Component Solutions in Two Populations

Methodology ◽  
2016 ◽  
Vol 12 (1) ◽  
pp. 11-20 ◽  
Author(s):  
Gregor Sočan
Keyword(s):  
Simulation Study ◽  
Principal Components ◽  
Common Factor ◽  
Principal Component ◽  
Component Model ◽  
Bootstrap Procedure ◽  
Factor Loadings ◽  
Component Loadings ◽  
Principal Component Model ◽  
Two Populations

Abstract. When principal component solutions are compared across two groups, a question arises whether the extracted components have the same interpretation in both populations. The problem can be approached by testing null hypotheses stating that the congruence coefficients between pairs of vectors of component loadings are equal to 1. Chan, Leung, Chan, Ho, and Yung (1999) proposed a bootstrap procedure for testing the hypothesis of perfect congruence between vectors of common factor loadings. We demonstrate that the procedure by Chan et al. is both theoretically and empirically inadequate for the application on principal components. We propose a modification of their procedure, which constructs the resampling space according to the characteristics of the principal component model. The results of a simulation study show satisfactory empirical properties of the modified procedure.

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