<abstract xmlns="http://www.w3.org/1999/xhtml">
<p>In Romania, the livestock is very scattered on the diverse environmental conditions. Due to difficulties regarding data collection, with the help of genomic selection, the paradigm of genetic improvement of economical traits in Romanian cattle breeds can be changed. Population studied in this paper consist in animals genotyped using 60k SNP panel. Association studies were performed for estimate the effect of SNP polymorphism on milk yield at 305 days. Genetic evaluation was compared under four statistical methodologies were compared under six scenarios 5k, 10k, 15k, 20k, 25k and 37k SNP panels. High association with phenotypes were displayed by 38 SNP’s. Generally, accuracy of the studied models, tend to increase with complexity (informational input). The model with the lowest accuracy was Sire-Model (36.6% accuracy). Adding information in Animal Model increase accuracy of estimation and finally, adding genomic information the accuracy was maximized to 69.9%. For each lactation all the statistical models return highly correlated breeding values. The highest (97.2%) and the lowest (79.2%) rank correlation are registered between Test-Day and Animal Model for the first and second lactation. Genomic evaluation is a more feasible methodology than classical breeding value estimation, in term of accuracy of selection and the quality of the parentage information.</p>
</abstract>

In Romania, the livestock is very scattered on the diverse environmental conditions. Due to difficulties regarding data collection, with the help of genomic selection, the paradigm of genetic improvement of economical traits in Romanian cattle breeds can be changed. Population studied in this paper consist in animals genotyped using 60k SNP panel. Association studies were performed for estimate the effect of SNP polymorphism on milk yield at 305 days. Genetic evaluation was compared under four statistical methodologies were compared under six scenarios 5k, 10k, 15k, 20k, 25k and 37k SNP panels. High association with phenotypes were displayed by 38 SNP’s. Generally, accuracy of the studied models, tend to increase with complexity (informational input). The model with the lowest accuracy was Sire-Model (36.6% accuracy). Adding information in Animal Model increase accuracy of estimation and finally, adding genomic information the accuracy was maximized to 69.9%. For each lactation all the statistical models return highly correlated breeding values. The highest (97.2%) and the lowest (79.2%) rank correlation are registered between Test-Day and Animal Model for the first and second lactation. Genomic evaluation is a more feasible methodology than classical breeding value estimation, in term of accuracy of selection and the quality of the parentage information.

Preliminary study regarding use of genomic selection in Romanian cattle breeds evaluation

National Research and Development Institute for Animal Biology and Nutrition

Archiva Zootechnica

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

In Romania, the livestock is very scattered on the diverse environmental conditions. Due to difficulties regarding data collection, with the help of genomic...

Preliminary study regarding use of genomic selection in Romanian cattle breeds evaluation

Online veröffentlicht: 21. Okt. 2023

Seitenbereich: 52 - 68

DOI: https://doi.org/10.2478/azibna-2023-0014

Schlüsselwörter
Single Nucleotide Polymorphism, Best Linear Unbiased Prediction, Genome-Wide Association Study, models comparison, Genomic Selection

© 2023 Mihail Alexandru Gras et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Preliminary study regarding use of genomic selection in Romanian cattle breeds evaluation

Online veröffentlicht: 21. Okt. 2023

Seitenbereich: 52 - 68

DOI: https://doi.org/10.2478/azibna-2023-0014

SchlüsselwörterSingle Nucleotide Polymorphism, Best Linear Unbiased Prediction, Genome-Wide Association Study, models comparison, Genomic Selection

© 2023 Mihail Alexandru Gras et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Schlüsselwörter
Single Nucleotide Polymorphism, Best Linear Unbiased Prediction, Genome-Wide Association Study, models comparison, Genomic Selection