Dataset Information

Genetic parameters for first lactation dairy traits in the Alpine and Saanen goat breeds using a random regression test-day model.

ABSTRACT: BACKGROUND:Random regression models (RRM) are widely used to analyze longitudinal data in genetic evaluation systems because they can better account for time-course changes in environmental effects and additive genetic values of animals by fitting the test-day (TD) specific effects. Our objective was to implement a random regression model for the evaluation of dairy production traits in French goats. RESULTS:The data consisted of milk TD records from 30,186 and 32,256 first lactations of Saanen and Alpine goats. Milk yield, fat yield, protein yield, fat content and protein content were considered. Splines were used to model the environmental factors. The genetic and permanent environmental effects were modeled by the same Legendre polynomials. The goodness-of-fit and the genetic parameters derived from functions of the polynomials of orders 0 to 4 were tested. Results were also compared to those from a lactation model with total milk yield calculated over 250 days and to those of a multiple-trait model that considers performance in six periods throughout lactation as different traits. Genetic parameters were consistent between models. Models with fourth-order Legendre polynomials led to the best fit of the data. In order to reduce complexity, computing time, and interpretation, a rank reduction of the variance covariance matrix was performed using eigenvalue decomposition. With a reduction to rank 2, the first two principal components correctly summarized the genetic variability of milk yield level and persistency, with a correlation close to 0 between them. CONCLUSIONS:A random regression model was implemented in France to evaluate and select goats for yield traits and persistency, which are independent i.e. no genetic correlation between them, in first lactation.

SUBMITTER: Arnal M

PROVIDER: S-EPMC6693143 | biostudies-literature | 2019 Aug

REPOSITORIES: biostudies-literature

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Genetic parameters for first lactation dairy traits in the Alpine and Saanen goat breeds using a random regression test-day model.

Arnal Mathieu M Larroque Hélène H Leclerc Hélène H Ducrocq Vincent V Robert-Granié Christèle C

Genetics, selection, evolution : GSE 20190813 1

<h4>Background</h4>Random regression models (RRM) are widely used to analyze longitudinal data in genetic evaluation systems because they can better account for time-course changes in environmental effects and additive genetic values of animals by fitting the test-day (TD) specific effects. Our objective was to implement a random regression model for the evaluation of dairy production traits in French goats.<h4>Results</h4>The data consisted of milk TD records from 30,186 and 32,256 first lactat ...[more]

PMID: 31409294

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Project description:BackgroundLocal breeds retained unique genetic variability important for adaptive potential especially in light of challenges related to climate change. Our first objective was to perform, for the first time, a genome-wide diversity characterization using Illumina GoatSNP50 BeadChip of autochthonous Drežnica goat breed from Slovenia, and five and one local breeds from neighboring Austria and Italy, respectively. For optimal conservation and breeding programs of endangered local breeds, it is important to detect past admixture events and strive for preservation of purebred representatives of each breed with low or without admixture. In the second objective, we hence investigated the effect of inclusion or exclusion of outliers from datasets on genetic diversity and population structure parameters.ResultsDistinct genetic origin of the Drežnica goat was demonstrated as having closest nodes to Austrian and Italian breeds. A phylogenetic study of these breeds with other goat breeds having SNP data available in the DRYAD repository positioned them in the alpine, European and global context. Swiss breeds clustered with cosmopolitan alpine breeds and were closer to French and Spanish breeds. On the other hand, the Drežnica goat, Austrian and Italian breeds were closer to Turkish breeds. Datasets where outliers were excluded affected estimates of genetic diversity parameters within the breed and increased the pairwise genetic distances between most of the breeds. Alpine breeds, including Drežnica, Austrian and Italian goats analyzed here, still exhibit relatively high levels of genetic variability, homogeneous genetic structure and strong geographical partitioning.ConclusionsGenetic diversity analyses revealed that the Slovenian Drežnica goat has a distinct genetic identity and is closely related to the neighboring Austrian and Italian alpine breeds. These results expand our knowledge on phylogeny of goat breeds from easternmost part of the European Alps. The here employed outlier test and datasets optimization approaches provided an objective and statistically powerful tool for removal of admixed outliers. Importance of this test in selecting the representatives of each breed is warranted to obtain more objective diversity parameters and phylogenetic analysis. Such parameters are often the basis of breeding and management programs and are therefore important for preserving genetic variability and uniqueness of local rare breeds.

Dataset Information

Genetic parameters for first lactation dairy traits in the Alpine and Saanen goat breeds using a random regression test-day model.

Publications

Genetic parameters for first lactation dairy traits in the Alpine and Saanen goat breeds using a random regression test-day model.

Similar Datasets

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