Genetic evaluation of animals in multibreed cattle populations using linear models

This review discusses the use of lineal procedures to evaluate cattle in multibreed populations for traits of economic importance. First, a multibreed mixed linear model was presented in detail, and all their terms were defined. Then, computational algorithms to solve multibreed mixed model equations and to estimate additive and nonadditive variance and covariance components were discussed, and the types of multibreed predictions obtained in these analyses were explained. Finally, applications of multibreed procedures to experimental and field datasets were presented, and implementations of national multibreed systems in the United States were discussed

PERSPECTIVAS DA AVALIAÇÃO GENÉTICA MULTIRRACIAL EM BOVINOS NO BRASIL

A disponibilidade de grandes bases de dados em associações de diferentes raças e cruzamentos de bovinos,e a demanda crescente dos produtores por avaliações genéticas dos animais de raças puras e cruzados têm renovado o interesse na implementação de procedimentos de avaliação genética multirracial. Na maioria das associações de criadores dos Estados Unidos está sendo aplicada a avaliação genética de animais puros e cruzados.O Brasil, com sua enorme população bovina (167 milhões),composta amplamente por Zebu e seus cruzamentos (80%),e muitas grandes e bem estruturadas empresas (várias com dez mil animais ou mais), é provável que possua um expressivo número de bases de dados apropriadas para ser analisado por meio de procedimentos de avaliação genética multirracial. Comumente, no entanto, neste país são usados procedimentos de avaliação genética intra-racial independentemente da composição genética das populações bovinas. Os procedimentos intra-raciais ignoram os efeitos genéticos não-aditivos entre raças, e assumem que os parâmetros genéticos são os mesmos em todos os grupos raciais. Os procedimentos de avaliação genética multirracial incluem ambos os aspectos, assim, eles são preferíveis aos intra-raciais para avaliar geneticamente populações compostas por animais puros e cruzados. Os procedimentos de avaliação genética multirracial produzem predições genéticas aditivas mais acuradas, permitem a comparação direta de animais de diferente composição racial e viabilizam o melhoramento genético aditivo e não-aditivo em populações multirraciais. No entanto, esses procedimentos são computacionalmente mais complexos, requerem maior número de parâmetros genéticos e apresentam problemas de confundimento e multi colinearidade. Neste artigo, caracterizam-se as populações multirraciais, discutem-se modelos de avaliação genética, procedimentos e tarefas para sua implementação, e, quando relevante, apresentam-se comentários gerais sobre a situação multirracial no Brasil. PALAVRAS-CHAVE: Bovinos, cruzamento, avaliação genética, multirracial, predição

Variance Components and Genetic Parameters for Milk Production and Lactation Pattern in an Ethiopian Multibreed Dairy Cattle Population

The objective of this study was to estimate variance components and genetic parameters for lactation milk yield (LY), lactation length (LL), average milk yield per day (YD), initial milk yield (IY), peak milk yield (PY), days to peak (DP) and parameters (ln(a) and c) of the modified incomplete gamma function (MIG) in an Ethiopian multibreed dairy cattle population. The dataset was composed of 5,507 lactation records collected from 1,639 cows in three locations (Bako, Debre Zeit and Holetta) in Ethiopia from 1977 to 2010. Parameters for MIG were obtained from regression analysis of monthly test-day milk data on days in milk. The cows were purebred (Bos indicus) Boran (B) and Horro (H) and their crosses with different fractions of Friesian (F), Jersey (J) and Simmental (S). There were 23 breed groups (B, H, and their crossbreds with F, J, and S) in the population. Fixed and mixed models were used to analyse the data. The fixed model considered herd-year-season, parity and breed group as fixed effects, and residual as random. The single and two-traits mixed animal repeatability models, considered the fixed effects of herd-year-season and parity subclasses, breed as a function of cow H, F, J, and S breed fractions and general heterosis as a function of heterozygosity, and the random additive animal, permanent environment, and residual effects. For the analysis of LY, LL was added as a fixed covariate to all models. Variance components and genetic parameters were estimated using average information restricted maximum likelihood procedures. The results indicated that all traits were affected (p<0.001) by the considered fixed effects. High grade B×F cows (3/16B 13/16F) had the highest least squares means (LSM) for LY (2,490±178.9 kg), IY (10.5±0.8 kg), PY (12.7±0.9 kg), YD (7.6±0.55 kg) and LL (361.4±31.2 d), while B cows had the lowest LSM values for these traits. The LSM of LY, IY, YD, and PY tended to increase from the first to the fifth parity. Single-trait analyses yielded low heritability (0.03±0.03 and 0.08±0.02) and repeatability (0.14±0.01 to 0.24±0.02) estimates for LL, DP and parameter c. Medium heritability (0.21±0.03 to 0.33±0.04) and repeatability (0.27±0.02 to 0.53±0.01) estimates were obtained for LY, IY, PY, YD and ln(a). Genetic correlations between LY, IY, PY, YD, ln(a), and LL ranged from 0.59 to 0.99. Spearman’s rank correlations between sire estimated breeding values for LY, LL, IY, PY, YD, ln(a) and c were positive (0.67 to 0.99, p<0.001). These results suggested that selection for IY, PY, YD, or LY would genetically improve lactation milk yield in this Ethiopian dairy cattle population

Characterization of Akirin 2 gene in Langshan chicken

Akirin play an important role not only in innate immune response but also in skeletal myogenesis. The chicken’s Akirin gene family only has Akirin 2. We detected the coding sequences of the Akirin 2 gene in a Chinese indigenous chicken (Langshan chicken) population to investigate the possibility of using this gene for chicken marker-assisted selection. The results of PCR-SSCP and DNA sequence showed that there were no polymorphisms in the six amplified regions of the Akirin 2 gene. In addition, there was no SNP record about the chicken’s Akirin 2 gene by searching in NCBI. Thus, the Akirin 2 gene may not be suitable to be used in chicken as a gene marker for marker- assisted selection

Parámetros genéticos para producción de leche de ganado Holstein en dos modalidades de control de producción

Variance components and genetic parameters were estimated for total milk production at first lactation (MP1), milkyield adjusted to 305 d and adult equivalent at the first lactation (MP1std), total milk production of the first fivelactations (MP5) and milk yield adjusted to 305 d and mature equivalent of the first five lactations (MP5std). Thedatabases of the Mexican Holstein Association (MHA, n= 43,668) and of the National Bank of Dairy Information(NBDI, n= 120,217) were used. Variances were estimated by REML, using a simple animal model for MP1 and MP1stdand a repeatability animal model for MP5 and MP5std. Heritability estimates ranged from low to moderate for thefirst lactation (0.17 ± 0.009 to 0.49 ± 0.019) and for the first five lactations (0.16 ± 0.006 to 0.41 ± 0.004). Therepeatabilities for MP5 and MP5std ranged from 0.32 ± 0.002 to 0.41 ± 0.004. The inclusion of information of theNBDI on the national evaluations made possible the incorporation of production data that had not been taken intoconsideration before. This inclusion not only improved the accuracy of sire breeding values   for milk production, butalso allowed the prediction of breeding values of more foreign and domestic animals with progeny in Mexico.Se estimaron componentes de varianza y parámetros genéticos para producción de leche total a la primera lactancia (PL1), producción de leche ajustada a 305 días y a equivalente adulto de la primera lactancia (PL1std), producción de leche total de las cinco primeras lactancias (PL5) y producción de leche ajustada a 305 días y a equivalente adulto de las primeras 5 lactancias (PL5std). Se utilizaron las bases de datos de la Asociación Holstein de México (AHM; n= 43,668) y del Banco Nacional de Información Lechera (BNIL; n= 120,217). Las varianzas fueron estimadas mediante REML, utilizando un modelo animal simple para PL1 y PL1std y un modelo animal de repetibilidad para PL5 y PL5std. Las heredabilidades estimadas fueron desde bajas a moderadas para la primera lactancia (0.17 ± 0.009 a 0.49 ± 0.019) y para las primeras cinco lactancias (0.16 ± 0.006 a 0.41 ± 0.004). Las repetibilidades para PL5 y PL5std tuvieron un rango de 0.32 ± 0.002 a 0.41 ± 0.004. La inclusión de la información del BNIL en las evaluaciones genéticas permitió incorporar datos de producción que no se estaban tomando en cuenta. Esto no solamente mejoró la precisión de los valores genéticos de los sementales para producción de leche, sino que también permitió la predicción de los valores genéticos de animales nacionales y extranjeros con progenies en México

Parámetros genéticos para producción de leche de ganado Holstein en dos modalidades de control de producción

Variance components and genetic parameters were estimated for total milk production at first lactation (MP1), milkyield adjusted to 305 d and adult equivalent at the first lactation (MP1std), total milk production of the first fivelactations (MP5) and milk yield adjusted to 305 d and mature equivalent of the first five lactations (MP5std). Thedatabases of the Mexican Holstein Association (MHA, n= 43,668) and of the National Bank of Dairy Information(NBDI, n= 120,217) were used. Variances were estimated by REML, using a simple animal model for MP1 and MP1stdand a repeatability animal model for MP5 and MP5std. Heritability estimates ranged from low to moderate for thefirst lactation (0.17 ± 0.009 to 0.49 ± 0.019) and for the first five lactations (0.16 ± 0.006 to 0.41 ± 0.004). Therepeatabilities for MP5 and MP5std ranged from 0.32 ± 0.002 to 0.41 ± 0.004. The inclusion of information of theNBDI on the national evaluations made possible the incorporation of production data that had not been taken intoconsideration before. This inclusion not only improved the accuracy of sire breeding values   for milk production, butalso allowed the prediction of breeding values of more foreign and domestic animals with progeny in Mexico.Se estimaron componentes de varianza y parámetros genéticos para producción de leche total a la primera lactancia (PL1), producción de leche ajustada a 305 días y a equivalente adulto de la primera lactancia (PL1std), producción de leche total de las cinco primeras lactancias (PL5) y producción de leche ajustada a 305 días y a equivalente adulto de las primeras 5 lactancias (PL5std). Se utilizaron las bases de datos de la Asociación Holstein de México (AHM; n= 43,668) y del Banco Nacional de Información Lechera (BNIL; n= 120,217). Las varianzas fueron estimadas mediante REML, utilizando un modelo animal simple para PL1 y PL1std y un modelo animal de repetibilidad para PL5 y PL5std. Las heredabilidades estimadas fueron desde bajas a moderadas para la primera lactancia (0.17 ± 0.009 a 0.49 ± 0.019) y para las primeras cinco lactancias (0.16 ± 0.006 a 0.41 ± 0.004). Las repetibilidades para PL5 y PL5std tuvieron un rango de 0.32 ± 0.002 a 0.41 ± 0.004. La inclusión de la información del BNIL en las evaluaciones genéticas permitió incorporar datos de producción que no se estaban tomando en cuenta. Esto no solamente mejoró la precisión de los valores genéticos de los sementales para producción de leche, sino que también permitió la predicción de los valores genéticos de animales nacionales y extranjeros con progenies en México

Variabilidad y predicciones genéticas aditivas, no aditivas y totales para la producción de ganado de carne en el rebaño multirracial Sanmartinero-Cebú de La Libertad.

Se utilizaron datos de crecimiento de terneros del rebaño multirracial Sanmartinero-Cebú localizado en el Centro de Investigaciones La Libertad, con el objeto de obtener la estimación de razones genéticas aditivas (heredabilidades), no aditivas (interactibilidades) y correlaciones genético aditivas, no aditivas, directas y maternas para peso al nacimiento, peso al destete (240 d), y ganancia de peso postdestete (240 a 480 d). Se obtuvieron también predicciones de valores genéticos aditivos y no aditivos de los tres caracteres de crecimiento para todos los toros usados en el rebaño entre 1971 y 1996. La metodología utilizada, tanto para el cálculo de la estimación de componentes de varianza y covarianza, como para las predicciones genéticas de toros, fue de tipo multirracial. La estimación de heredabilidades en las razas Sanmartinero y Cebú fue: 0.26 y 0.30 para peso al nacimiento directo, 0.10 y 0.08 para peso al destete directo, 0.44 y 0.37 para ganancia postdestete directa, 0.29 y 0.36 para peso al nacimiento materno, 0.11 y 0.10 para peso al destete materno y 0.46 y 0.38 para ganancia postdeste materno, respectivamente. Las estimaciones de correlaciones genéticas aditivas y no aditivas entre todos los caracteres y efectos genéticos fueron bajas, la mayoría de ellas (38 de 45) menores de 0.10. Las predicciones genéticas aditivas y totales directas indican que los toros Sanmartinero tuvieron, en general, terneros más pequeños al nacimiento de menor peso al destete y de similar ganancia postdestete que en los terneros de toros Cebú. Las predicciones genéticas aditivas y totales maternas, por el contrario, sugieren que hijas de toros Sanmartinero tuvieron terneros más grandes al nacimiento, de mayor peso al destete y de mayor ganancia postdestete que terneros de hijas de toros Cebú. Las predicciones genéticas no aditivas directas fueron mayores que las no aditivas maternas para toros Sanmartinero y Cebú.;Por su parte, las predicciones aditivas y no aditivas pre y postdestete maternas sugieren que terneros de madres de menor habilidad materna (e.g., menor producción de leche) crecieron más en el periodo postdestete. Estos resultados indican que animales Sanmartinero fueron competitivos con animales Cebú para caracteres de crecimiento y demostraron excelente habilidad combinatoria interracial bajo las condiciones de nutrición y manejo del Centro de Investigación La Libertad.Ganado de carne-Ganadería carn

INTERAÇÃO PAI–AVÔ-MATERNO NA ESTIMATIVA DE CO)VARIÂNCIAS, E TENDÊNCIA GENÉTICA DO CRESCIMENTO PRÉ-DESMAMA EM GADO NELORE

Foram utilizados pesos padronizados aos 120 (P120) e 240 (P240) dias de idade, de 8.084 bezerros Nelore, de ambos os sexos, criados a pasto, nascidos entre 1987 e 1997 em 31 rebanhos, para estimar componentes de (co)variância e obter predições de valores genéticos. O modelo animal misto completo para cada caráter incluiu os efeitos fixos de grupo contemporâneo (rebanho-ano-época-sexo-grupo- manejo) e seis classes de idade da vaca ao parto em anos (2, 3, 4, 5, 6 a 9, 10 e mais), e os efeitos aleatórios genéticos aditivos do animal (direto e maternal), ambiental permanente maternal, interação pai –avô-materno (PAM) e residual. O efeito da interação PAM explicou entre 2,8% e 3,1 % da variância fenotípica, e determinou redução das variâncias direta e maternal e aumento da covariância entre efeitos direto e maternal. As herdabilidades diretas diminuíram de 0,24 a 0,20 (P120), e 0,24 a 0,19 (P240), e as correspondentes herdabilidades maternais de 0,17 a 0,13 e 0,20 a 0,16, respectivamente. As correlações entre efeitos genéticos direto e maternal aumentaram de 0,05 a 0,29 (P120), e -0,12 a 0,01 (P240), não indicando antagonismo. A evolução das médias anuais dos valores genéticos indicou escasso ou nenhum progresso no período analisado, especialmente na habilidade maternal. O uso intensivo e por vários anos de poucos touros aponta-se como causa importante desse resultado. O efeito da interação PAM e a evolução genética devem ser pesquisados com maior abrangência, incluindo dados mais recentes. PALAVRAS-CHAVE: (Co)variâncias maternais, interação pai–avô-materno, tendência genética

Structural Equation Modeling and Whole-Genome Scans Uncover Chromosome Regions and Enriched Pathways for Carcass and Meat Quality in Beef

Structural equation models involving latent variables are useful tools for formulating hypothesized models defined by theoretical variables and causal links between these variables. The objectives of this study were: (1) to identify latent variables underlying carcass and meat quality traits and (2) to perform whole-genome scans for these latent variables in order to identify genomic regions and individual genes with both direct and indirect effects. A total of 726 steers from an Angus-Brahman multibreed population with records for 22 phenotypes were used. A total of 480 animals were genotyped with the GGP Bovine F-250. The single-step genomic best linear unbiased prediction method was used to estimate the amount of genetic variance explained for each latent variable by chromosome regions of 20 adjacent SNP-windows across the genome. Three types of genetic effects were considered: (1) direct effects on a single latent phenotype; (2) direct effects on two latent phenotypes simultaneously; and (3) indirect effects. The final structural model included carcass quality as an independent latent variable and meat quality as a dependent latent variable. Carcass quality was defined by quality grade, fat over the ribeye and marbling, while the meat quality was described by juiciness, tenderness and connective tissue, all of them measured through a taste panel. From 571 associated genomic regions (643 genes), each one explaining at least 0.05% of the additive variance, 159 regions (179 genes) were associated with carcass quality, 106 regions (114 genes) were associated with both carcass and meat quality, 242 regions (266 genes) were associated with meat quality, and 64 regions (84 genes) were associated with carcass quality, having an indirect effect on meat quality. Three biological mechanisms emerged from these findings: postmortem proteolysis of structural proteins and cellular compartmentalization, cellular proliferation and differentiation of adipocytes, and fat deposition