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Knowledge of the genetic architecture of key growth and beef traits in livestock species has greatly improved worldwide thanks to genome-wide association studies (GWAS), which allow to link target phenotypes to Single Nucleotide Polymorphisms (SNPs) across the genome. Local dual-purpose breeds have rarely been the focus of such studies; recently, however, their value as a possible alternative to intensively farmed breeds has become clear, especially for their greater adaptability to environmental change and potential for survival in less productive areas. We performed single-step GWAS and post-GWAS analysis for body weight (BW), average daily gain (ADG), carcass fleshiness (CF) and dressing percentage (DP) in 1,690 individuals of local alpine cattle breed, Rendena. This breed is typical of alpine pastures, with a marked dual-purpose attitude and good genetic diversity. Moreover, we considered two of the target phenotypes (BW and ADG) at different times in the individuals' life, a potentially important aspect in the study of the traits' genetic architecture. We identified 8 significant and 47 suggestively associated SNPs, located in 14 autosomal chromosomes (BTA). Among the strongest signals, 3 significant and 16 suggestive SNPs were associated with ADG and were located on BTA10 (50–60 Mb), while the hotspot associated with CF and DP was on BTA18 (55–62 MB). Among the significant SNPs some were mapped within genes, such as SLC12A1 , CGNL1 , PRTG (ADG), LOC513941 (CF), NLRP2 (CF and DP), CDC155 (DP). Pathway analysis showed great diversity in the biological pathways linked to the different traits; several were associated with neurogenesis and synaptic transmission, but actin-related and transmembrane transport pathways were also represented. Time-stratification highlighted how the genetic architectures of the same traits were markedly different between different ages. The results from our GWAS of beef traits in Rendena led to the detection of a variety of genes both well-known and novel. We argue that our results show that expanding genomic research to local breeds can reveal hitherto undetected genetic architectures in livestock worldwide. This could greatly help efforts to map genomic complexity of the traits of interest and to make appropriate breeding decisions. [ABSTRACT FROM AUTHOR]

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. 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. [ABSTRACT FROM AUTHOR]

Simple Summary: A selection index considering milk, beef, and functional traits is required by breeders of the local dual-purpose Alpine Grey breed because of the worsening of beef and other functional characteristics of the breed not yet accounted for in the present selection scheme. The present study has examined genetic correlations among different traits to investigate the possible breeding scenarios for this breed. Results indicate the need to shift selection toward a greater economic weight for beef and functional traits to improve the dual-purpose attitude and maintain the breed's peculiar characteristics. 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. [ABSTRACT FROM AUTHOR]