Genetic parameters of growth, feed intake, feed conversion and carcass composition of dual-purpose bulls in performance testing

Genomic Prediction in Local Breeds: The Rendena Cattle as a Case Study

Simple Summary

Although genomic selection is being used in many livestock species, it has not yet been considered in local breeds due to the lower population size and the potential less effective impact on the genetic evaluation of these breeds. The current research aims to investigate how genomic data can impact the accuracy of genetic predictions for beef traits in Rendena, a small local cattle breed of the North-East of Italy selected for a dual purpose. Classical animal models using only phenotypic information were compared with two models that integrated genomic data with pedigree information. The genomic models presented better accuracy in estimated breeding values of the animals than the ‘classical’ animal model, especially the ‘simpler’ one assuming homogeneous variances of single nucleotide polymorphisms. Our results show that the inclusion of genomic information can be successfully applied to breeding selection scenarios even in small local cattle breeds such as Rendena.

Abstract

The maintenance of local cattle breeds is key to selecting for efficient food production, landscape protection, and conservation of biodiversity and local cultural heritage. Rendena is an indigenous cattle breed from the alpine North-East of Italy, selected for dual purpose, but with lesser emphasis given to beef traits. In this situation, increasing accuracy for beef traits could prevent detrimental effects due to the antagonism with milk production. Our study assessed the impact of genomic information on estimated breeding values (EBVs) in Rendena performance-tested bulls. Traits considered were average daily gain, in vivo EUROP score, and in vivo estimate of dressing percentage. The final dataset contained 1691 individuals with phenotypes and 8372 animals in pedigree, 1743 of which were genotyped. Using the cross-validation method, three models were compared: (i) Pedigree-BLUP (PBLUP); (ii) single-step GBLUP (ssGBLUP), and (iii) weighted single-step GBLUP (WssGBLUP). Models including genomic information presented higher accuracy, especially WssGBLUP. However, the model with the best overall properties was the ssGBLUP, showing higher accuracy than PBLUP and optimal values of bias and dispersion parameters. Our study demonstrated that integrating phenotypes for beef traits with genomic data can be helpful to estimate EBVs, even in a small local breed.

Selection Response Due to Different Combination of Antagonistic Milk, Beef, and Morphological Traits in the Alpine Grey Cattle Breed

Selection in local dual-purpose breeds requires great carefulness because of the need to preserve peculiar traits and also guarantee the positive genetic progress for milk and beef production to maintain economic competitiveness. A specific breeding plan accounting for milk, beef, and functional traits is required by breeders of the Alpine Grey cattle (AG), a local dual-purpose breed of the Italian Alps. Hereditability and genetic correlations among all traits have been analyzed for this purpose. After that, different selection indexes were proposed to identify the most suitable for this breed. Firstly, a genetic parameters analysis was carried out with different datasets. The milk dataset contained 406,918 test day records of milk, protein, and fat yields and somatic cells (expressed as SCS). The beef dataset included performance test data conducted on 749 young bulls. Average daily gain, in vivo estimated carcass yields, and carcass conformation (SEUROP) were the phenotypes obtained from the performance tests. The morphological dataset included 21 linear type evaluations of 11,320 first party cows. Linear type traits were aggregated through factor analysis and three factors were retained, while head typicality (HT) and rear muscularity (RM) were analyzed as single traits. Heritability estimates (h2) for milk traits ranged from 0.125 to 0.219. Analysis of beef traits showed h2 greater than milk traits, ranging from 0.282 to 0.501. Type traits showed a medium value of h2 ranging from 0.238 to 0.374. Regarding genetic correlation, SCS and milk traits were strongly positively correlated. Milk traits had a negative genetic correlation with the factor accounting for udder conformations (-0.40) and with all performance test traits and RM. These latter traits showed also a negative genetic correlation with udder volume (-0.28). The HT and the factor accounting for rear legs traits were not correlated with milk traits, but negatively correlated with beef traits (-0.32 with RM). We argue that the consequence of these results is that the use of the current selection index, which is mainly focused on milk attitude, will lead to a deterioration of all other traits. In this study, we propose more appropriate selection indexes that account for genetic relationships among traits, including functional traits.

Genetic correlations among milk yield, morphology, performance test traits and somatic cells in dual-purpose Rendena breed

Selection in native local breeds needs great carefulness due to the small population size and the risk of inbreeding. Furthermore, most breeds are dual-purpose, and milk and beef attitudes are antagonistic. For preservation purposes functional traits need to be considered. Focusing on the small local Rendena cattle, this study aimed to analyse the genetic correlations among milk, beef and udder health traits and the response to selection predicted under different scenarios. The study considered milk, fat and protein yields (MY), factor scores for udder volume (UV), conformation (UC) and muscularity obtained from type traits scored on primiparous cows, and performance test traits (PT) measured on young bulls at test station: average daily gain, in vivo SEUROP fleshiness, in vivo dressing percentage. Somatic cell score (SCS) was considered as a functional trait, with a possibility of restricting its genetic gain to zero. The study considered 281 497 MY test-day data collected on 16 974 cows, and data from linear type evaluation on 11 992 primiparous cows for factor scores. The PT data were recorded on 1428 young bulls, and SCS obtained from cell counts at milk recording. Bi-trait restricted maximum likelihood animal model analyses were performed to assess genetic parameters. Heritability varied from 0.157 (fat) to 0.442 (dressing percentage). Udder volume and MY resulted positively genetically correlated (average correlation 0.427), whereas the low-negative genetic correlation between MY and UC (-0.141) suggested a negative impact of milk gain on udder form. Beef traits of factor muscularity and PT showed medium-high favourable genetic correlations (from 0.357 to 0.984), excluding a null correlation between daily gain and muscularity. The genetic correlation MY v. muscularity was unfavourable (-0.328 on average), whereas null correlations were found in MY v. PT, apart from fat v. dressing percentage (-0.151). Somatic cell score showed low unfavourable correlations with protein (0.111) and UV (0.092), and favourable correlations with UC (-0.193). Response to selection in different scenarios indicated a good balanced gain for milk and beef when standardized economic weights of 0.66 and 0.34 are given to the two attitudes, and SCS genetic gain is restricted. Current genetic trends (MY and PT increasing, but muscularity lessening) reflect a stronger selection for milk, suggesting a slight progressive change towards a milk conformation. Aiming to preserve the dual-purpose characteristics of a breed, proper breeding policies taking into account the genetic relationships among traits and including functional traits should be applied in local dual-purpose populations.