Browsing by Author "Baldi, Fernando"

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    An assessment of genomic connectedness measures in Nellore cattle
    Amorim, Sabrina T.; Yu, Haipeng; Momen, Mehdi; de Albuquerque, Lucia Galvao; Cravo Pereira, Angelica S.; Baldi, Fernando; Morota, Gota (2020-11)
    An important criterion to consider in genetic evaluations is the extent of genetic connectedness across management units (MU), especially if they differ in their genetic mean. Reliable comparisons of genetic values across MU depend on the degree of connectedness: the higher the connectedness, the more reliable the comparison. Traditionally, genetic connectedness was calculated through pedigree-based methods; however, in the era of genomic selection, this can be better estimated utilizing new approaches based on genomics. Most procedures consider only additive genetic effects, which may not accurately reflect the underlying gene action of the evaluated trait, and little is known about the impact of non-additive gene action on connectedness measures. The objective of this study was to investigate the extent of genomic connectedness measures, for the first time, in Brazilian field data by applying additive and non-additive relationship matrices using a fatty acid profile data set from seven farms located in the three regions of Brazil, which are part of the three breeding programs. Myristic acid (C14:0) was used due to its importance for human health and reported presence of non-additive gene action. The pedigree included 427,740 animals and 925 of them were genotyped using the Bovine high-density genotyping chip. Six relationship matrices were constructed, parametrically and non-parametrically capturing additive and non-additive genetic effects from both pedigree and genomic data. We assessed genome-based connectedness across MU using the prediction error variance of difference (PEVD) and the coefficient of determination (CD). PEVD values ranged from 0.540 to 1.707, and CD from 0.146 to 0.456. Genomic information consistently enhanced the measures of connectedness compared to the numerator relationship matrix by at least 63%. Combining additive and non-additive genomic kernel relationship matrices or a non-parametric relationship matrix increased the capture of connectedness. Overall, the Gaussian kernel yielded the largest measure of connectedness. Our findings showed that connectedness metrics can be extended to incorporate genomic information and non-additive genetic variation using field data. We propose that different genomic relationship matrices can be designed to capture additive and non-additive genetic effects, increase the measures of connectedness, and to more accurately estimate the true state of connectedness in herds.
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    Effect of Different Selection Criteria on Performance, Carcass and Meat Quality of Nellore Young Bulls
    Silva, Juliana; Cônsolo, Nara Regina Brandão; Buarque, Vicente Luiz Macedo; Beline, Mariane; da Silva Martins, Taiane; Lobo, Annelise Aila Gomes; Gómez, Juan Fernando Morales; Eler, Joanir Pereira; Leme, Paulo Roberto; Netto, Arlindo Saran; Gerrard, David E.; Baldi, Fernando; Silva, Saulo Luz (MDPI, 2021-03-29)
    This study was carried out to evaluate the effects of selection criteria for post-weaning daily gain (PWDG) and early sexual heifer precocity (PP14) on the performance, carcass traits and meat quality of Nellore bulls. In year one, 50 animals were selected according to their expected progeny differences (EPDs) for PWDG and grouped as high (HG) or low (LG) groups. In year two, 50 animals were selected according to EPD for PP14 and also grouped as high (HP) or low (LP). After slaughter, samples of the longissimus muscle area (LMA) were used to evaluate meat quality. Most of performance traits were not affected by the selection criteria. However, the HG group had higher dressing percentage (p = 0.028), LMA (p = 0.02) and fat trim in the forequarter (p = 0.04) compared to the LG group. The HP group tended to have greater dry matter intake (p = 0.08), LMA (p = 0.05), rump fat (p = 0.04), heavier striploins (p = 0.07), tenderloins (p = 0.09) and briskets (p = 0.08) compared with LP group. In conclusion, the selection based on divergent groups PWDG or PP14 has a small impact on performance, carcass and meat quality traits.
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    Genotype-by-environment interactions for feed efficiency traits in Nellore cattle based on bi-trait reaction norm models
    Silva Neto, João B.; Mota, Lucio F. M.; Amorim, Sabrina T.; Peripolli, Elisa; Brito, Luiz F.; Magnabosco, Claudio U.; Baldi, Fernando (2023-12-14)
    Background: Selecting animals for feed efficiency directly impacts the profitability of the beef cattle industry, which contributes to minimizing the environmental footprint of beef production. Genetic and environmental factors influence animal feed efficiency, leading to phenotypic variability when exposed to different environmental conditions (i.e., temperature and nutritional level). Thus, our aim was to assess potential genotype-by-environment (G × E) interactions for dry matter intake (DMI) and residual feed intake (RFI) in Nellore cattle (Bos taurus indicus) based on bi-trait reaction norm models (RN) and evaluate the genetic association between RFI and DMI across different environmental gradient (EG) levels. For this, we used phenotypic information on 12,958 animals (young bulls and heifers) for DMI and RFI recorded during 158 feed efficiency trials. Results: The heritability estimates for DMI and RFI across EG ranged from 0.26 to 0.54 and from 0.07 to 0.41, respectively. The average genetic correlations (± standard deviation) across EG for DMI and RFI were 0.83 ± 0.19 and 0.81 ± 0.21, respectively, with the lowest genetic correlation estimates observed between extreme EG levels (low vs. high) i.e. 0.22 for RFI and 0.26 for DMI, indicating the presence of G × E interactions. The genetic correlation between RFI and DMI across EG levels decreased as the EG became more favorable and ranged from 0.79 (lowest EG) to 0.52 (highest EG). Based on the estimated breeding values from extreme EG levels (low vs. high), we observed a moderate Spearman correlation of 0.61 (RFI) and 0.55 (DMI) and a selection coincidence of 53.3% and 40.0% for RFI and DMI, respectively. Conclusions: Our results show evidence of G × E interactions on feed efficiency traits in Nellore cattle, especially in feeding trials with an average daily gain (ADG) that is far from the expected of 1 kg/day, thus increasing reranking of animals.