Sugestão de leitura: confira os artigos publicados pelos membros do GDMA (Dez/2019 a Mar/2020)
Postado em 02/abr/2020
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Artigo 1: Sex Determination Using RNA-Sequencing Analyses in Early Prenatal Pig Development
Autores:
Revista: Genes (Dez/2019)
Abstract: Sexual dimorphism is a relevant factor in animal science, since it can affect the gene expression of economically important traits. Eventually, the interest in the prenatal phase in a transcriptome study may not comprise the period of development in which male and female conceptuses are phenotypically divergent. Therefore, it would be interesting if sex differentiation could be performed using transcriptome data, with no need for extra techniques. In this study, the sex of pig conceptuses (embryos at 25 days-old and fetuses at 35 days-old) was determined by reads counts per million (CPM) of Y chromosome-linked genes that were discrepant among samples. Thus, ten genes were used: DDX3Y, KDM5D, ZFY, EIF2S3Y, EIF1AY, LOC110255320, LOC110257894, LOC396706, LOC100625207, and LOC110255257. Conceptuses that presented reads CPM sum for these genes (ΣCPMchrY) greater than 400 were classified as males and those with ΣCPMchrY below 2 were classified as females. It was demonstrated that the sex identification can be performed at early stages of pig development from RNA-sequencing analysis of genes mapped on Y chromosome. Additionally, these results reinforce that sex determination is a mechanism conserved across mammals, highlighting the importance of using pigs as an animal model to study sex determination during human prenatal development.
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Artigo 2: Autoregressive and random regression test-day models for multiple lactations in genetic evaluation of Brazilian Holstein cattle.
Autores: Delvan Alves Silva, Claudio Nápolis Costa, Alessandra Alves Silva, Hugo Teixeira Silva, Paulo Sávio Lopes, Fabyano Fonseca Silva, Renata Veroneze, Gertrude Thompson, Ignacio Aguilar, Júlio Carvalheira
Revista: Journal of animal breeding and genetics (Dez/2019)
Abstract: Autoregressive (AR) and random regression (RR) models were fitted to test‐day records from the first three lactations of Brazilian Holstein cattle with the objective of comparing their efficiency for national genetic evaluations. The data comprised 4,142,740 records of milk yield (MY) and somatic cell score (SCS) from 274,335 cows belonging to 2,322 herds. Although heritabilities were similar between models and traits, additive genetic variance estimates using AR were 7.0 (MY) and 22.2% (SCS) higher than those obtained from RR model. On the other hand, residual variances were lower in both traits when estimated through AR model. The rank correlation between EBV obtained from AR and RR models was 0.96 and 0.94 (MY) and 0.97 and 0.95 (SCS), respectively, for bulls (with 10 or more daughters) and cows. Estimated annual genetic gains for bulls (cows) obtained using AR were 46.11 (49.50) kg for MY and −0.019 (−0.025) score for SCS; whereas using RR these values were 47.70 (55.56) kg and −0.022 (−0.028) score. Akaike information criterion was lower for AR in both traits. Although AR model is more parsimonious, RR model assumes genetic correlations different from the unity within and across lactations. Thus, when these correlations are relatively high, these models tend to yield to similar predictions; otherwise, they will differ more and RR model would be theoretically sounder.
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Artigo 3: Genomic evaluation for novel stayability traits in Nellore cattle
Autores: Pedro Vital Brasil Ramos, Fabyano Fonseca e Silva, Luiz Otávio Campos da Silva, Gustavo Garcia Santiago, Gilberto Romeiro de Oliveira Menezes, José Marcelo Soriano Viana, Roberto A. A. Torres Júnior, Andrea Gondo, Luiz F. Brito
Revista: Reproduction in Domestic Animals (Dez/2019)
Abstract: Cow stayability plays a major role on the overall profitability of the beef cattle industry, as it is directly related to reproductive efficiency and cow’s longevity. Stayability (STAY63) is usually defined as the ability of the cow to calve at least three times until 76 months of age. This is a late‐measured and lowly heritable trait, which consequently constrains genetic progress per time unit. Thus, the use of genomic information associated with novel stayability traits measured earlier in life will likely result in higher prediction accuracy and faster genetic progress for cow longevity. In this study, we aimed to compare pedigree‐based and single‐step GBLUP (ssGBLUP) methods as well as to estimate genetic correlations between the proposed stayability traits: STAY42, STAY53 and STAY64, which are measured at 52, 64 and 76 months of cow’s age, considering at least 2, 3 and 4 calving, respectively. ssGBLUP yielded the highest prediction accuracy for all traits. The heritability estimates for STAY42, STAY53, STAY63 and STAY64 were 0.090, 0.151, 0.152 and 0.143, respectively. The genetic correlations between traits ranged from 0.899 (STAY42 and STAY53) to 0.985 (STAY53 and STAY63). The high genetic correlation between STAY42 and STAY53 suggests that besides being related to cow longevity, STAY53 is also associated with the early‐stage reproductive efficiency. Thus, STAY53 is recommended as a suitable selection criterion for reproductive efficiency due to its higher heritability, favourable genetic correlation with other traits, and measured earlier in life, compared with the conventional stayability trait, that is STAY63.
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Artigo 4: Autoregressive repeatability model for genetic evaluation of longitudinal reproductive traits in dairy cattle
Autores: Hugo T. Silva, Paulo S. Lopes, Claudio N. Costa, Fabyano F. SilvaDelvan A. SilvaAlessandra A. SilvaGertrude Thompson,Júlio Carvalheira
Revista: Journal of Dairy Research (Fev/2020)
Abstract: We investigated the efficiency of the autoregressive repeatability model (AR) for genetic evaluation of longitudinal reproductive traits in Portuguese Holstein cattle and compared the results with those from the conventional repeatability model (REP). The data set comprised records taken during the first four calving orders, corresponding to a total of 416, 766, 872 and 766 thousand records for interval between calving to first service, days open, calving interval and daughter pregnancy rate, respectively. Both models included fixed (month and age classes associated to each calving order) and random (herd-year-season, animal and permanent environmental) effects. For AR model, a first-order autoregressive (co)variance structure was fitted for the herd-year-season and permanent environmental effects. The AR outperformed the REP model, with lower Akaike Information Criteria, lower Mean Square Error and Akaike Weights close to unity. Rank correlations between estimated breeding values (EBV) with AR and REP models ranged from 0.95 to 0.97 for all studied reproductive traits, when the total bulls were considered. When considering only the top-100 selected bulls, the rank correlation ranged from 0.72 to 0.88. These results indicate that the re-ranking observed at the top level will provide more opportunities for selecting the best bulls. The EBV reliabilities provided by AR model was larger for all traits, but the magnitudes of the annual genetic progress were similar between two models. Overall, the proposed AR model was suitable for genetic evaluations of longitudinal reproductive traits in dairy cattle, outperforming the REP model.
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Artigo 5: Estimated genetic associations among reproductive traits in Nellore cattle using Bayesian analysis
Autores: Edson V.Costa, Henrique T.Ventura, RenataVeroneze, Fabyano F.Silva, Mariana A.Pereira,Paulo S.Lopes
Revista: Animal Reproduction Science (Mar/2020)
Abstract: Scrotal circumference of bulls is correlated with pubertal age of female offspring. Hormonal control of reproductive function is similar in males and females, which may result in genetic correlation among different reproductive traits measured in the two sexes. The estimation of heritability and genetic correlations allows for the computation of direct and correlated genetic gains which are important for predicting of outcomes as a result of genetic-based selection. The aim of this study was to estimate genetic parameters and relative efficiency of indirect selection for age at first calving (AFC), stayability (STAY) and scrotal circumference at 365 days of age (SC365) in Nellore cattle. The STAY variable can be defined as the probability of a cow remain in the herd enough time to raise a certain number of calves that pay for her development and maintenance costs. A bivariate Bayesian analysis was used to estimate variance components using a linear-animal model for SC365 and AFC and threshold-linear model for SC365 and STAY and for AFC and STAY. For STAY, the value of 1 was assigned to cows that calved at least three times by 76 months of age; otherwise, the value 0 was assigned. The posteriori means of heritability estimates were 0.29, 0.08 and 0.09 for SC365, AFC and STAY, respectively. Genetic correlations were favorable from a cow productivity perspective between SC365 and AFC, and SC365 and STAY (-0.45 and 0.12, respectively). Indirect selection approaches were more efficient than direct selection for AFC (ERS = 1.87) when animals were selected for SC365.
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Artigo 6: Genetic parameters for milk, growth, and reproductive traits in Guzerá cattle under tropical conditions
Autores: Laís Costa Brito, Maria Gabriela Campolina Diniz Peixoto, Eula Regina Carrara, Fabyano Fonseca e Silva, Henrique Torres Ventura, Frank Angelo Tomita Bruneli, Paulo Sávio Lopes
Revista: Tropical Animal Health and Production (Mar/2020)
Abstract: This study aimed to estimate the genetic parameters of milk (305-day milk yield (MY305)), growth (weaning weight (WW), yearling weight (YW), and weight at 550 days (W550)), and reproductive (age at first calving (AFC)) traits in Guzerá cattle by using Bayesian multiple-trait models. Systematic effects included sex and age at calving for the growth and milk traits, respectively. The additive genetic and contemporary groups (herd and year and season of birth) were included as random effects. Additionally, maternal genetic and permanent effects were also included as random effects for the WW. The heritability estimates were 0.29 (MY305), 0.42 (WW), 0.49 (YW), 0.56 (W550), and 0.25 (AFC). The genetic correlations among the growth traits were higher than 0.83; between the MY305 and WW, MY305 and YW, and MY305 and W550, the genetic correlations were 0.25, 0.32, and 0.36, respectively. The AFC was negatively correlated with the milk and growth traits. These results suggest the viability and potential of the joint selection for milk, beef, and reproductive traits in Guzerá cattle.