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Keywords = breed proportions of US Brown Swiss

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23 pages, 4068 KiB  
Article
Analyzing Runs of Homozygosity Reveals Patterns of Selection in German Brown Cattle
by Anna Wirth, Jürgen Duda, Reiner Emmerling, Kay-Uwe Götz, Franz Birkenmaier and Ottmar Distl
Genes 2024, 15(8), 1051; https://doi.org/10.3390/genes15081051 - 9 Aug 2024
Cited by 4 | Viewed by 1861
Abstract
An increasing trend in ancestral and classical inbreeding coefficients as well as inbreeding depression for longevity were found in the German Brown population. In addition, the proportion of US Brown Swiss genes is steadily increasing in German Browns. Therefore, the aim of the [...] Read more.
An increasing trend in ancestral and classical inbreeding coefficients as well as inbreeding depression for longevity were found in the German Brown population. In addition, the proportion of US Brown Swiss genes is steadily increasing in German Browns. Therefore, the aim of the present study was to analyze the presence and genomic localization of runs of homozygosity (ROH) in order to evaluate their associations with the proportion of US Brown Swiss genes and survival rates of cows to higher lactations. Genotype data were sampled in 2364 German Browns from 258 herds. The final data set included 49,693 autosomal SNPs. We identified on average 35.996 ± 7.498 ROH per individual with a mean length of 8.323 ± 1.181 Mb. The genomic inbreeding coefficient FROH was 0.122 ± 0.032 and it decreased to 0.074, 0.031 and 0.006, when genomic homozygous segments > 8 Mb (FROH>8), >16 Mb (FROH>16) and >32 Mb (FROH>32) were considered. New inbreeding showed the highest correlation with FROH>32, whereas ancestral inbreeding coefficients had the lowest correlations with FROH>32. The correlation between the classical inbreeding coefficient and FROH was 0.572. We found significantly lower FROH, FROH>4, FROH>8 and FIS for US Brown Swiss proportions <60% compared to >80%. Cows surviving to the 2nd, 4th, 6th, 8th, and 10th lactation had lower genomic inbreeding for FROH and up to FROH>32, which was due to a lower number of ROH and a shorter average length of ROH. The strongest ROH island and consensus ROH shared by 50% of the animals was found on BTA 6 at 85–88 Mb. The genes located in this genomic region were associated with longevity (NPFFR2 and ADAMTS3), udder health and morphology (SLC4A4, NPFFR2, GC and RASSF6), milk production, milk protein percentage, coagulation properties of milk and milking speed (CSN3). On BTA 2, a ROH island was detected only in animals with <60% US Brown Swiss genes. Genes within this region are predominantly important for dual-purpose cattle breeds including Original Browns. For cows reaching more than 9 lactations, an exclusive ROH island was identified on BTA 7 with genes assumed to be associated with longevity. The analysis indicated that genomic homozygous regions important for Original Browns are still present and also ROH containing genes affecting longevity may have been identified. The breeding of German Browns should prevent any further increase in genomic inbreeding and run a breeding program with balanced weights on production, robustness and longevity. Full article
(This article belongs to the Special Issue Advances in Cattle, Sheep, and Goats Molecular Genetics and Breeding)
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14 pages, 1288 KiB  
Article
Comparison of Single-Breed and Multi-Breed Training Populations for Infrared Predictions of Novel Phenotypes in Holstein Cows
by Lucio Flavio Macedo Mota, Sara Pegolo, Toshimi Baba, Gota Morota, Francisco Peñagaricano, Giovanni Bittante and Alessio Cecchinato
Animals 2021, 11(7), 1993; https://doi.org/10.3390/ani11071993 - 2 Jul 2021
Cited by 6 | Viewed by 3807
Abstract
In general, Fourier-transform infrared (FTIR) predictions are developed using a single-breed population split into a training and a validation set. However, using populations formed of different breeds is an attractive way to design cross-validation scenarios aimed at increasing prediction for difficult-to-measure traits in [...] Read more.
In general, Fourier-transform infrared (FTIR) predictions are developed using a single-breed population split into a training and a validation set. However, using populations formed of different breeds is an attractive way to design cross-validation scenarios aimed at increasing prediction for difficult-to-measure traits in the dairy industry. This study aimed to evaluate the potential of FTIR prediction using training set combining specialized and dual-purpose dairy breeds to predict different phenotypes divergent in terms of biological meaning, variability, and heritability, such as body condition score (BCS), serum β-hydroxybutyrate (BHB), and kappa casein (k-CN) in the major cattle breed, i.e., Holstein-Friesian. Data were obtained from specialized dairy breeds: Holstein (468 cows) and Brown Swiss (657 cows), and dual-purpose breeds: Simmental (157 cows), Alpine Grey (75 cows), and Rendena (104 cows), giving a total of 1461 cows from 41 multi-breed dairy herds. The FTIR prediction model was developed using a gradient boosting machine (GBM), and predictive ability for the target phenotype in Holstein cows was assessed using different cross-validation (CV) strategies: a within-breed scenario using 10-fold cross-validation, for which the Holstein population was randomly split into 10 folds, one for validation and the remaining nine for training (10-fold_HO); an across-breed scenario (BS_HO) where the Brown Swiss cows were used as the training set and the Holstein cows as the validation set; a specialized multi-breed scenario (BS+HO_10-fold), where the entire Brown Swiss and Holstein populations were combined then split into 10 folds, and a multi-breed scenario (Multi-breed), where the training set comprised specialized (Holstein and Brown Swiss) and dual-purpose (Simmental, Alpine Grey, and Rendena) dairy cows, combined with nine folds of the Holstein cows. Lastly a Multi-breed CV2 scenario was implemented, assuming the same number of records as the reference scenario and using the same proportions as the multi-breed. Within-Holstein, FTIR predictions had a predictive ability of 0.63 for BCS, 0.81 for BHB, and 0.80 for k-CN. Using a specific breed (Brown Swiss) as the training set for prediction in the Holstein population reduced the prediction accuracy by 10% for BCS, 7% for BHB, and 11% for k-CN. Notably, the combination of Holstein and Brown Swiss cows in the training set increased the predictive ability of the model by 6%, which was 0.66 for BCS, 0.85 for BHB, and 0.87 for k-CN. Using multiple specialized and dual-purpose animals in the training set outperforms the 10-fold_HO (standard) approach, with an increase in predictive ability of 8% for BCS, 7% for BHB, and 10% for k-CN. When the Multi-breed CV2 was implemented, no improvement was observed. Our findings suggest that FTIR prediction of different phenotypes in the Holstein breed can be improved by including different specialized and dual-purpose breeds in the training population. Our study also shows that predictive ability is enhanced when the size of the training population and the phenotypic variability are increased. Full article
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13 pages, 1556 KiB  
Article
Genetic Diversity and the Impact of the Breed Proportions of US Brown Swiss in German Brown Cattle
by Anna Wirth, Jürgen Duda and Ottmar Distl
Animals 2021, 11(1), 152; https://doi.org/10.3390/ani11010152 - 11 Jan 2021
Cited by 12 | Viewed by 3206
Abstract
Increase of inbreeding and loss of genetic diversity have large impact on farm animal genetic resources. Therefore, the aims of the present study were to analyse measures of genetic diversity as well as recent and ancestral inbreeding using pedigree data of the German [...] Read more.
Increase of inbreeding and loss of genetic diversity have large impact on farm animal genetic resources. Therefore, the aims of the present study were to analyse measures of genetic diversity as well as recent and ancestral inbreeding using pedigree data of the German Brown population, and to identify causes for loss of genetic diversity. The reference population included 922,333 German Brown animals born from 1990 to 2014. Pedigree depth and completeness reached an average number of complete equivalent generations of 6.24. Estimated effective population size for the German Brown reference population was about 112 with a declining trend from 141 to 95 for the birth years. Individual inbreeding coefficients increased from 0.013 to 0.036. Effective number of founders, ancestors and founder genomes of 63.6, 36.23 and 20.34 indicated unequal contributions to the reference population. Thirteen ancestors explained 50% of the genetic diversity. Higher breed proportions of US Brown Swiss were associated with higher levels of individual inbreeding. Ancestral inbreeding coefficients, which are indicative for exposure of ancestors to identical-by-descent alleles, increased with birth years but recent individual inbreeding was higher than ancestral inbreeding. Given the increase of inbreeding and decline of effective population size, measures to decrease rate of inbreeding and increase effective population size through employment of a larger number of sires are advisable. Full article
(This article belongs to the Section Animal Genetics and Genomics)
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