Estimating additive and dominance variances for complex traits in pigs combining genomic and pedigree information

Knowledge of dominance effects should improve ge-netic evaluations, provide the accurate selection of purebred animals, and enable better breeding strategies, including the exploitation of het-erosis in crossbreeds. In this study, we combined genomic and pedi-gree data to study the relative importance of additive and dominance genetic variation in growth and carcass traits in an F2 pig population. Two GBLUP models were used, a model without a polygenic effect (ADM) and a model with a polygenic effect (ADMP). Additive effects played a greater role in the control of growth and carcass traits than did dominance effects. However, dominance effects were important for all traits, particularly in backfat thickness. The narrow-sense and broad-sense heritability estimates for growth (0.06 to 0.42, and 0.10 to 0.51, respectively) and carcass traits (0.07 to 0.37, and 0.10 to 0.76, respec-tively) exhibited a wide variation. The inclusion of a polygenic effect in the ADMP model changed the broad-sense heritability estimates only for birth weight and weight at 21 days of age

Censored Bayesian models for genetic evaluation of age at first calving in Brazilian Brahman cattle

We compared different Bayesian models to handle censored data for genetic parameters estimation of age at first calving (AFC) in Brazilian Brahman cattle. Data from females with AFC above 1825 days of age were assumed to have failed to calve and were considered as censored records. Data including information of 53, 703 cows were analyzed through the following methods: conventional linear model method (LM), which consider only uncensored records; simulation method (SM), in which the data were augmented by drawing random samples from positive truncated normal distributions; penalty method (PM), in which a constant of 21 days was added to censored records; and the bivariate threshold-linear method (TLcens). The LM was the most suited for genetic evaluation of AFC in Brazilian Brahman cattle based on the predictive ability evaluation through cross-validation analysis. The similar results for LM and PM regarding Spearman correlations, and the higher percentages of selected animals in common, indicated that there was not relevant reranking of animals when censored records were used. In summary, the heritability estimates for AFC ranged from 0.09 (TLcens) to 0.20 (LM). Given its poor predictive performance, the SM is not recommended for handling censored records for genetic evaluation of AFC

Comparing Alternative Single-Step GBLUP Approaches and Training Population Designs for Genomic Evaluation of Crossbred Animals

As crossbreeding is extensively used in some livestock species, we aimed to evaluate the performance of single-step GBLUP (ssGBLUP) and weighted ssGBLUP (WssGBLUP) methods to predict Genomic Estimated Breeding Values (GEBVs) of crossbred animals. Different training population scenarios were evaluated: (SC1) ssGBLUP based on a single-trait model considering purebred and crossbred animals in a joint training population; (SC2) ssGBLUP based on a multiple-trait model to enable considering phenotypes recorded in purebred and crossbred training animals as different traits; (SC3) WssGBLUP based on a single-trait model considering purebred and crossbred animals jointly in the training population (both populations were used for SNP weights\u27 estimation); (SC4) WssGBLUP based on a single-trait model considering only purebred animals in the training population (crossbred population only used for SNP weights\u27 estimation); (SC5) WssGBLUP based on a single-trait model and the training population characterized by purebred animals (purebred population used for SNP weights\u27 estimation). A complex trait was simulated assuming alternative genetic architectures. Different scaling factors to blend the inverse of the genomic (G−1) and pedigree ( A − 1 22 ) relationship matrices were also tested. The predictive performance of each scenario was evaluated based on the validation accuracy and regression coefficient. The genetic correlations across simulated populations in the different scenarios ranged from moderate to high (0.71–0.99). The scenario mimicking a completely polygenic trait ( h 2 Q T L = 0) yielded the lowest validation accuracy (0.12; for SC3 and SC4). The simulated scenarios assuming 4,500 QTLs affecting the trait and h 2 Q T L = h 2 resulted in the greatest GEBV accuracies (0.47; for SC1 and SC2). The regression coefficients ranged from 0.28 (for SC3 assuming polygenic effect) to 1.27 (for SC2 considering 4,500 QTLs). In general, SC3 and SC5 resulted in inflated GEBVs, whereas other scenarios yielded deflated GEBVs. The scaling factors used to combine G−1 and A − 1 22 had a small influence on the validation accuracies, but a greater effect on the regression coefficients. Due to the complexity of multiple-trait models and WssGBLUP analyses, and a similar predictive performance across the methods evaluated, SC1 is recommended for genomic evaluation in crossbred populations with similar genetic structures [moderate-to-high (0.71–0.99) genetic correlations between purebred and crossbred populations]

Genotype imputation strategies for Portuguese Holstein cattle using different SNP panels.

Abstract: Although several studies have investigated the factors affecting imputation accuracy, most of these studies involved a large number of genotyped animals. Thus, results from these studies cannot be directly applied to small populations, since the population structure affects imputation accuracy. In addition, factors affecting imputation accuracy may also be intensified in small populations. Therefore, we aimed to compare different imputation strate-gies for the Portuguese Holstein cattle population considering several commercially available single nucleotide poly-morphism (SNP) panels in a relatively small number of genotyped animals. Data from 1359 genotyped animals were used to evaluate imputation in 7 different scenarios. In the S1 to S6 scenarios, imputations were performed from LDv1, 50Kv1, 57K, 77K, HDv3 and Ax58K panels to 50Kv2 panel. In these scenarios, the bulls in 50Kv2 were divided into reference (352) and validation (101) populations based on the year of birth. In the S7 scenario, the validation population consisted of 566 cows genotyped with the Ax58K panel with theirgenotypes masked to LDv1. In general, all sample imputation accuracies were high with correlations ranging from 0.94 to 0.99 and concordance rate rang-ing from 92.59 to 98.18%. SNP-specific accuracy was consistent with that of sample imputation. S4 (40.32% of SNPs imputed) had higher accuracy than S2 and S3, both with less than 7.59% of SNPs imputed. Most probably, this was due to the high number of imputed SNPs with minor allele frequency (MAF) < 0.05 in S2 and S3 (by 18.43% and 16.06% higher than in S4, respectively). Therefore, for these two scenarios, MAF was more relevant than the panel density. These results suggest that genotype imputation using several commercially available SNP panels is feasible for the Portuguese national genomic evaluation

Genotype × environment interaction in milk traits of Guzerá cattle using reaction norm models

This study aimed to evaluate genotype × environment (G×E) interactions in Guzerá breed animals for 305-day first-lactation cumulative yields (kg) of milk (MY305), fat (FY305), and protein (PY305). We used 6823 records of MY305, 2466 records of FY305, and 1870 records of PY305. The contemporary groups (CG) were created considering herd and year of calving. The analyses were performed in two steps. In the first step, environmental effects on phenotypes were estimated by using a multi-trait model ignoring G×E interactions. In the second step, G×E interactions were evaluated by using single-trait analyses with the reaction norm model and considering heterogeneous residual variance divided into five classes. The CG solutions obtained in step 1 were used as an environmental gradient in step 2, representing low to high management environments. We observed increasing genetic variance estimates along the environmental gradient for all evaluated traits. Residual variance showed the same pattern, except with class 5 of FY305 and class 4 of PY305. Heritability estimates increased slightly as the management level increased. The correlation estimates between the intercept and the slope of the reaction norm curve were 0.998 for MY305, 0.989 for FY305, and 0.987 for PY305. The genetic correlation among the low (5% quantile), medium (55% quantile), and high (95% quantile) management level environments was high, with values higher than 0.99, 0.97, and 0.70 for MY305, FY305, and PY305, respectively. The breeding values of the animals changed along the environmental gradient, even those classified as robust. These results demonstrate a G×E interaction with scale effect for the evaluated traits that affects the breeding values

Estimating additive and dominance variances for complex traits in pigs combining genomic and pedigree information.

Knowledge of dominance effects should improve genetic evaluations, provide the accurate selection of purebred animals, and enable better breeding strategies, including the exploitation of heterosis in crossbreeds. In this study, we combined genomic and pedigree data to study the relative importance of additive and dominance genetic variation in growth and carcass traits in an F2 pig population. Two GBLUP models were used, a model without a polygenic effect (ADM) and a model with a polygenic effect (ADMP). Additive effects played a greater role in the control of growth and carcass traits than did dominance effects. However, dominance effects were important for all traits, particularly in backfat thickness. The narrow-sense and broad-sense heritability estimates for growth (0.06 to 0.42, and 0.10 to 0.51, respectively) and carcass traits (0.07 to 0.37, and 0.10 to 0.76, respectively) exhibited a wide variation. The inclusion of a polygenic effect in the ADMP model changed the broad-sense heritability estimates only for birth weight and weight at 21 days of age

Adotabilidade de sistemas de integração lavoura-pecuária-floresta no Mato Grosso do Sul.

O objetivo deste trabalho foi avaliar a adotabilidade de diferentes modalidades de sistemas de Integração Lavoura-Pecuária-Floresta (ILPF) entre pecuaristas do estado de Mato Grosso do Sul (MS). O trabalho foi conduzido em dois municípios inseridos em duas situações distintas: uma região com predominância na produção de grãos, no centro sul do estado, onde o sistema mais difundido é o de Integração Lavoura-Pecuária (ILP), sem o componente florestal, e outra região com predominância da pecuária na região central, onde o maior potencial de inovação é a Integração Pecuária-Floresta (IPF), pela introdução do componente florestal. Em cada município foi realizada uma oficina com especialistas, profissionais da assistência técnica, gestores de cooperativas, empresas do agronegócio e pesquisadores da região, para a coleta de informações e a aplicação da metodologia ADOPT. Os públicos-alvo e as tecnologias a serem avaliadas foram definidos previamente com o auxílio de representantes das instituições participantes das oficinas. Cada uma delas contou com a participação de aproximadamente 16 pessoas divididas em dois grupos, sendo que um grupo tratou de questões relativas ao perfil do público-alvo (produtores) e o outro das questões relativas à inovação tecnológica. Foram observadas taxas de adoção superiores a 90% em todas as simulações. Entretanto, alguns gargalos foram identificados: no sul do MS, dificuldades com assistência técnica especializada foram apontadas como desfavoráveis à adoção da ILP. A IPF, por sua vez, mostrou-se dependente de um modelo de fomento que assegure rentabilidade no curto prazo. Esta publicação vai ao encontro dos Objetivos do Desenvolvimento Sustentável (ODS) contidos na Agenda 2030, proposta pela Organização das Nações Unidas, da qual o Brasil é signatário, nos seguintes objetivos específicos: ODS 2 “Acabar com a fome, alcançar a segurança alimentar e melhoria da nutrição e promover a agricultura sustentável; ODS 12 “Assegurar padrões de produção e de consumo sustentáveis”; ODS 15 “Proteger, recuperar e promover o uso sustentável dos ecossistemas terrestres, gerir de forma sustentável as florestas, combater a desertificação, deter e reverter a degradação da terra e deter a perda de biodiversidade”.Selo ODS 2, Selo ODS 12, Selo ODS 15

Genetic study of quantitative traits supports the use of Guzerá as dual-purpose cattle.

Objective: The aim of this study was to estimate genetic parameters for 305-day cumulative milk yield and components, growth, and reproductive traits in Guzerá cattle. Methods: The evaluated traits were 305-day first-lactation cumulative yields (kg) of milk (MY305), fat (FY305), protein (PY305), lactose (LY305), and total solids (SY305); age at first calving (AFC) in days; adjusted scrotal perimeter (cm) at the ages of 365 (SP365) and 450 (SP450) days; and adjusted body weight (kg) at the ages of 210 (W210), 365 (W365) and 450 (W450) days. The (co)variance components were estimated using the restricted maximum likelihood method for single-trait, bi-trait and tri-trait analyses. Contemporary groups and additive genetic effects were included in the general mixed model. Maternal genetic and permanent environmental effects were also included for W210. Results: The direct heritability estimates ranged from 0.16 (W210) to 0.32 (MY305). The maternal heritability estimate for W210 was 0.03. Genetic correlation estimates among milk production traits and growth traits ranged from 0.92 to 0.99 and from 0.92 to 0.99, respectively. For milk production and growth traits, the genetic correlations ranged from 0.33 to 0.56. The genetic correlations among AFC and all other traits were negative ( 0.43 to 0.27). Scrotal perimeter traits and body weights showed genetic correlations ranging from 0.41 to 0.46, and scrotal perimeter and milk production traits showed genetic correlations ranging from 0.11 to 0.30. The phenotypic correlations were similar in direction (same sign) and lower than the corresponding genetic correlations. Conclusion: These results suggest the viability and potential of joint selection for dairy and beef traits in Guzerá cattle, taking into account reproductive traits.First online