Biomedical subjects

D Laloë

Publications and source records attributed to D Laloë.

6 recordsLinked to original sources

PubMed2004

Use of structured antedependence models for the genetic analysis of growth curves.

Growth curve analysis is an important issue for many agricultural and laboratory species, for both phenotypic and genetic studies. The aim of this paper is to present the use of a novel statistical approach, namely the structured antedependence (SAD) models, to deal with this issue. The basic idea of these models is that an observation at time t can be explained by the previous observations. These models are especially appropriate to deal with cumulative traits such as growth, as BW at age t clearly depends on BW measures at ages (t -1), (t -2), etc. These models were applied on an INRA experimental Charolais herd data set. The data comprised BW records for 560 cows born over an 11-yr period (from 1988 to 1998) from 60 sires and 369 dams. The proposed SAD models were compared with the well-known random regression (RR) models that are already widely used in various areas of longitudinal data analysis. It was found that the SAD models fit the growth process better with far fewer parameters than the RR models (9 instead of 16 covariance parameters for the phenotypic analysis, and 14 instead of 21 for the genetic analysis). Despite this smaller number of covariance parameters, the likelihood value was found to be much higher with the SAD vs. the RR models, with a difference of 262.9 for the phenotypic analysis with a quartic polynomial for the RR and 751.5 for the genetic analysis with a cubic polynomial for both the genetic and environmental parts of the RR model. The SAD models also proved to be better able to interpolate missing values. Heritability, genetic, and environmental correlation coefficients were estimated for weights from birth to adulthood. The structured antedependence models proved, in this study, to be very appropriate to model growth data in a parsimonious and flexible way.

Aging↗

PubMed2003

Evaluation models and genetic parameters for calving difficulty in beef cattle.

Calving difficulty was analyzed under threshold and linear models considering either a fixed or random herd-year effect. The aim of the study was to compare models for predicting breeding values according to the size of herd-year groups. When simulating data sets with small herds, in order to obtain an unbiased evaluation under a nonrandom and negative association of sire and herd effects, the best model for a practical evaluation was the fixed linear model. Field data included 246,576 records of the largest Charolais herds in France. Models were compared using the correlations of estimated breeding values between the different models. Although the best model from a theoretical point of view was a threshold model with a fixed herd-year effect, a linear model with a fixed herd-year effect was the best choice from a practical point of view for predicting direct effects for calving difficulty in beef cattle and was a sufficient choice for predicting the associated maternal effects for data set with large herds. Correlations between direct estimated breeding values under the reference model and the fixed linear model and the random threshold model were 0.94 and 0.91, respectively. Correlations between the corresponding maternal estimated breeding values were 0.94 and 0.98. Heritabilities of direct effects were 0.27 and 0.14 under fixed threshold and fixed linear models, respectively. The corresponding heritabilities of maternal effects were 0.18 and 0.13, and the genetic correlation between direct and maternal effects were -0.36 and -0.34, respectively.

Animal Husbandry↗

PubMed2002

Is a multivariate consensus representation of genetic relationships among populations always meaningful?

To determine the relationships among closely related populations or species, two methods are commonly used in the literature: phylogenetic reconstruction or multivariate analysis. The aim of this article is to assess the reliability of multivariate analysis. We describe a method that is based on principal component analysis and Mantel correlations, using a two-step process: The first step consists of a single-marker analysis and the second step tests if each marker reveals the same typology concerning population differentiation. We conclude that if single markers are not congruent, the compromise structure is not meaningful. Our model is not based on any particular mutation process and it can be applied to most of the commonly used genetic markers. This method is also useful to determine the contribution of each marker to the typology of populations. We test whether our method is efficient with two real data sets based on microsatellite markers. Our analysis suggests that for closely related populations, it is not always possible to accept the hypothesis that an increase in the number of markers will increase the reliability of the typology analysis.

Animals↗

PubMed1997

Analysis of genetic relationships between 10 cattle breeds with 17 microsatellites.

To guide genetic conservation programmes with objective criteria, general genetic variability has to be taken into account. This study was conducted to determine the genetic variation between 10 cattle breeds by using 17 microsatellite loci and 13 biochemical markers (11 blood groups, the transferrin and beta-casein loci). Microsatellite loci were amplified in 31-50 unrelated individuals from 10 cattle breeds: Charolais, Limousin, Breton Black Pied, Parthenais, Montbéliard, Vosgien, Maine-Anjou, Normande, Jersey and Holstein. Neighbor-joining trees were calculated from genetic distance estimates. The robustness of tree topology was obtained by bootstrap resampling of loci. A total of 210 alleles of the 17 microsatellites were detected in this study and average heterozygosities ranged from 0.53 in the Jersey breed to 0.66 in the Parthenais breed. In general, low bootstrap values were obtained: with the 17 microsatellites, the highest bootstrap values concerned the Holstein/Maine-Anjou grouping with an occurrence of 74%; with the biochemical markers, this node had an occurrence of 79% and the Charolais/Limousin grouping appeared with an occurrence of 74%; when microsatellites and biochemical polymorphism were analysed together, the occurrence of the Holstein/Maine-Anjou grouping was 90% and that of the Charolais/Limousin grouping was 42%. These results suggest that 30 microsatellites, a number currently considered as sufficient to distinguish closely related breeds is, in fact, probably insufficient.

Alleles↗

PubMedDate not supplied

Genetic diversity measures of local European beef cattle breeds for conservation purposes.

This study was undertaken to determine the genetic structure, evolutionary relationships, and the genetic diversity among 18 local cattle breeds from Spain, Portugal, and France using 16 microsatellites. Heterozygosities, estimates of Fst, genetic distances, multivariate and diversity analyses, and assignment tests were performed. Heterozygosities ranged from 0.54 in the Pirenaica breed to 0.72 in the Barrosã breed. Seven percent of the total genetic variability can be attributed to differences among breeds (mean F(st) = 0.07; P<0.01). Five different genetic distances were computed and compared with no correlation found to be significantly different from 0 between distances based on the effective size of the population and those which use the size of the alleles. The Weitzman recursive approach and a multivariate analysis were used to measure the contribution of the breeds diversity. The Weitzman approach suggests that the most important breeds to be preserved are those grouped into two clusters: the cluster formed by the Mirandesa and Alistana breeds and that of the Sayaguesa and Tudanca breeds. The hypothetical extinction of one of those clusters represents a 17% loss of diversity. A correspondence analysis not only distinguished four breed groups but also confirmed results of previous studies classifying the important breeds contributing to diversity. In addition, the variation between breeds was sufficiently high so as to allow individuals to be assigned to their breed of origin with a probability of 99% for simulated samples.

Algorithms↗

PubMedDate not supplied

A sampling method for estimating the accuracy of predicted breeding values in genetic evaluation.

A sampling-based method for estimating the accuracy of estimated breeding values using an animal model is presented. Empirical variances of true and estimated breeding values were estimated from a simulated n-sample. The method was validated using a small data set from the Parthenaise breed with the estimated coefficient of determination converging to the true values. It was applied to the French Salers data file used for the 2000 on-farm evaluation (IBOVAL) of muscle development score. A drawback of the method is its computational demand. Consequently, convergence can not be achieved in a reasonable time for very large data files. Two advantages of the method are that a) it is applicable to any model (animal, sire, multivariate, maternal effects...) and b) it supplies off-diagonal coefficients of the inverse of the mixed model equations and can therefore be the basis of connectedness studies.

Algorithms↗