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Several statistical models used in genome-wide prediction assume uncorrelated marker allele substitution effects, but it is known that these effects may be correlated. In statistics, graphical models have been identified as a useful tool for covariance estimation in high-dimensional problems and it is an area that has recently experienced a great expansion. In Gaussian covariance graph models (GCovGM), the joint distribution of a set of random variables is assumed to be Gaussian and the pattern of zeros of the covariance matrix is encoded in terms of an undirected graph G. In this study, methods adapting the theory of GCovGM to genome-wide prediction were developed (Bayes GCov, Bayes GCov-KR and Bayes GCov-H). In simulated data sets, improvements in correlation between phenotypes and predicted breeding values and accuracies of predicted breeding values were found. Our models account for correlation of marker effects and permit to accommodate general structures as opposed to models proposed in previous studies, which consider spatial correlation only. In addition, they allow incorporation of biological information in the prediction process through its use when constructing graph G, and their extension to the multi-allelic loci case is straightforward.

The objective of this research was to estimate (co) variance functions and genetic parameters for body weight in Colombian buffalo populations using random regression models with Legendre polynomials. Data consisted of 34,738 weight records from birth to 900 days of age from 7815 buffaloes. Fixed effects in the model were contemporary group and parity order of the mother. Random effects were direct and maternal additive genetic, as well as animal and maternal permanent environmental effects. A cubic orthogonal Legendre polynomial was used to model the mean curve of the population. Eleven models with first to sixth order polynomials were used to describe additive genetic direct and maternal effects, and animal and maternal permanent environmental effects. The residual was modeled considering five variance classes. The best model included fourth and sixth order polynomials for direct additive genetic and animal permanent environmental effects, respectively, and third-order polynomials for maternal genetic and maternal permanent environmental effects. The direct heritability increased from birth until 120 days of age (0.32±0.05), decreasing thereafter until one year of age (0.18±0.04) and increased again, reaching 0.39±0.09, at the end of the evaluated period. The highest maternal heritability estimates (0.11±0.05), were obtained for weights around weaning age (weaning age range is between 8 and 9.5 months). Maternal genetic and maternal permanent environmental variances increased from birth until about one year of age, decreasing at later ages. Direct genetic correlations ranged from moderate (0.60±0.060) to high (0.99±0.001), maternal genetic correlations showed a similar range (0.41±0.401 and 0.99±0.003), and all of them decreased as time between weighings increased. Direct genetic correlations suggested that selecting buffalos for heavier weights at any age would increase weights from birth through 900 days of age. However, higher heritabilities for direct genetic weights effects after 600 days of age suggested that selection for these effects would be more effective if done during this age period. A greater response to selection for maternal ability would be expected if selection used maternal genetic predictions for weights near weaning.

Inclusion of Bos indicus genetics improves production traits of cattle maintained in hot climates. Limited information exists detailing pregnan- cy-specific events as influenced by variable amounts of Bos indicus genetics. Three experiments were complet- ed to examine the effect of Bos taurus and Bos indicus genotypes on fetal size and plasma pregnancy-associ- ated glycoprotein (PAG) concentrations. In all experi- ments, cows were bred by AI after synchronization of ovulation. Fetal measurements were completed by transrectal ultrasonography and plasma PAG concentra- tions were quantified from plasma harvested the day of each fetal measurement. In Exp. 1, fetal size and plasma PAG concentrations were measured at d 53 of preg- nancy in cows composed of various fractions of Angus and Brahman (n = 9 to 21 cows/group). Fetus size was greater in cows containing >80% Angus genetics com- pared with cows containing 80% Angus genetics when compared with their contemporaries (6.0 ± 1.5 ng/mL vs. 9.4 ± 1.5 ng/mL). In Exp. 2, fetal measurements and plasma PAG concentrations were determined at d 35 and 62 of pregnancy in Angus and Brangus cows. Breed did not affect fetus size at d 35, but Angus cows contained larger fetuses than Brangus cows at d 62 (3.0 ± 0.03 vs. 2.8 ± 0.03 cm crown-nose length (CNL; P > 0.01)). Plasma PAG concentrations were not different between breed at d 35 and 62 (P > 0.1). In Exp. 3, fetal measurements and plasma samples were collected at d 33/34, 40/41, 47/48, and 54/55 post-AI in Angus and Brangus cows. Fetus size was not different (P > 0.05) between genotypes on d 33/34, 40/41, and 47/48. Angus fetuses were larger than Brangus fetuses at d 54/55 (2.1 ± 0.03 vs. 1.9 ± 0.03 cm CNL; P = 0.001). Plasma PAG concentrations were less in Angus than Brangus cows at each time point (average 4.9 ± 0.9 vs. 8.2 ± 0.9 ng/ mL; P = 0.005). In conclusion, these studies determined that the Bos taurus × Bos indicus genotype impacts fetal size and rate of fetal development by 7 wk of gestation. Plasma PAG concentrations were increased in cattle with Bos indicus genetics in 2 of 3 studies, suggesting that genotype is one of several determinants of PAG production and secretion in cattle.

The objectives of this study were to estimate the proportion of additive genetic and phenotypic variances explained by the SNP markers in the Illumina3K chip for 4 postweaning ultrasound carcass and weight traits, to compare rankings of calf predicted additive genetic values with 3 models, and to evaluate trends of calf predictions as Brahman fraction increased from 0 to 1. Traits were postweaning ultrasound measures of ribeye area (UREA), backfat thickness (UFAT), intramuscular fat (UPIMF), and body weight at time of ultrasound (UW). Models were genomic-polygenic, genomic, and polygenic. Phenotypes and genotypes were from 623 bulls, heifers, and steers ranging in breed composition from 100% Angus to 100% Brahman fed for 90 d at a GrowSafe automated feeding facility from 2006 to 2010. Variance components were estimated with Markov Chain Monte Carlo procedures (option VCE, program GS3) using a single-trait genomic-polygenic model. Fixed effects were contemporary group (year-pen), age of dam, sex of calf, age of calf, Brahman fraction of calf, and heterozygosity of calf. Random effects were additive SNP, animal polygenic, and residual effects. Models without polygenic effects were used for genomic predictions, and without additive SNP effects for polygenic predictions. Fractions of additive genetic variances explained by the SNP in the Illumina3K chip were 9% for UREA, 38% for UBF, 6% for UPIMF, and 8% for UW. Phenotypic variance fractions explained by Illumina3K SNP were 3.7% for UREA, 9.7% for UBF, 3.2% for UPIMF, and 4.6% for UW. Substantially higher rank correlations existed between genomic-polygenic and polygenic models (0.89 to 0.99) than between genomic-polygenic and genomic (0.64 to 0.79), and genomic and polygenic (0.51 to 0.65) models. Genomic-polygenic, genomic, and polygenic predicted values tended to decrease as Brahman fraction of calf increased suggesting that calves with higher percentage Brahman grew more slowly and had less desirable ultrasound carcass traits. However, there were calves with high, medium, and low predicted genetic values across the Angus–Brahman spectrum, suggesting that selection of animals with desirable postweaning ultrasound carcass and growth traits using a genomic-polygenic strategy would be effective in this multibreed population. Insofar as this multibreed herd represents commercial operations in Florida and the Southern region of the US, selection of commercial calves for these postweaning traits would likely increase their rate of improvement in Brahman and Brahman crossbred populations.

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

Objective: the objective of this study was to compare growth traits in buffaloes reared in farms using a pre-weaning management system with no milking (NM), or a dual-purpose system (DP: meat and milk production). Methods: performance tests were conducted at the Experimental Station of the University of Antioquia, located in Barbosa (Antioquia, Colombia). Buffaloes were confined and fed with fresh Maralfalfa grass (Pennisetum sp.) ad libitum, plus two kilograms of mixed plus two 2 kilograms of concentrate supplement per day. Weight, ultrasound, and bovinometric measurements were taken every 14 d. Bovinometric measurements were chest girth (CG), height at withers (HW), and height at sacrum (HS). Ultrasound measurements were Longissimus muscle area (REA) and rump fat thickness (RFT). Traits were analyzed using a linear regression and second order polynomial model using unstructured variance-covariance matrices and accounting for relationships among animals. Results: all the traits in DP animals, as well as RFT, HW, and HS in NM animals fit well with a second-order regression mixed model. Weight, CG, and REA in NM animals fit well with a first-order regression mixed model. The rate of increase for HW and HS declined at the end of the test in NM animals, while weight, CG, RFT, and REA did not. The DP buffaloes displayed an accelerated rate of increase for all traits towards the end of the evaluation. The non-zero estimates of genetic variances for random regression effects suggests that these characteristics may be improved genetically in Colombia. Environmental and genetic differences among farms may have influenced the high variability among individuals for the intercept. Conclusions: the linear regression variances were small for all traits, suggesting that although selection of animals within these performance tests is possible, expected changes in the buffalo population will be small.Objetivo: el objetivo de este estudio fue comparar características de crecimiento de búfalos sometidos a pruebas de desempeño, pertenecientes a dos sistemas de producción: cría sin ordeño (CSO) y doble propósito (DP). Métodos: las pruebas se realizaron en la Estación Experimental de la Universidad de Antioquia, ubicada en Barbosa, Colombia. Los animales fueron confinados y alimentados con pasto Maralfalfa (Pennisetum sp.) y dos kilogramos de un suplemento concentrado por día. El peso, las medidas de ultrasonido y bovinométricas fueron tomadas cada 14 días. Las medidas bovinométricas fueron perímetro torácico (PT), altura a la cruz (AC) y altura al sacro (AS). Las medidas por ultrasonido fueron área del músculo Longissimus (AOL) y espesor de grasa de la cadera (EGC). Las características fueron analizadas utilizando un modelo de regresión lineal mixto de primer orden y polinomial de segundo orden, con matrices de varianzas y covarianzas sin estructura, teniendo en cuenta la matriz de parentesco entre los animales. Resultados: todas las características en los animales provenientes del sistema DP y las caracteristicas EGC, AC y AS en animales de CSO, presentaron un mejor ajuste al modelo de regresión de segundo orden. El peso, PT y AOL en animales de CSO ajustaron mejor con un modelo de regresión de primer orden. La tasa de incremento de AC y AS en los búfalos de CSO declinó al final de la prueba, mientras que las otras características no presentaron disminución. Los búfalos del sistema DP aceleraron la tasa de incremento para todas las características al final de la evaluación. Las varianzas genéticas estimadas para los coeficientes de regresión fueron diferentes de cero, sugiriendo que estas características pueden ser mejoradas genéticamente en Colombia. Diferencias ambientales y genéticas entre fincas pueden haber influido en la alta variabilidad del intercepto entre los individuos. Conclusiones: las varianzas de los coeficientes de la regresión lineal fueron pequeñas para todas las características, sugiriendo que, aunque la selección de animales en pruebas de desempeño es posible, los cambios esperados en la población de búfalos serán pequeños.Objetivo: o objetivo deste estudo foi comparar as características de crescimento de búfalos submetidos em testes de desempenho. Estes búfalos foram provenientes de fazendas de gado de corte (CSO) ou dupla aptidão (DP). Métodos: as provas foram conduzidas na Estação Experimental da Universidade de Antioquia, localizada no município de Barbosa, na Colômbia. Os animais foram confinados e alimentados com capim Maralfalfa (Pennisetum sp.) e dois kg de suplemento por dia. Medidas morfométricas, de pesagem e ultrassom foram realizadas a cada 14 dias. As medidas morfométricas foram: perímetro torácico (PT), altura de cernelha (AC) e altura da garupa (AS). As mensurações de ultrassom foram: área do olho do lombo (AOL) e espessura de gordura na anca (EGA). As características foram analisadas utilizando um modelo de regressão linear misto de primeira ordem e polinomial de segunda ordem, com uma matriz de variância e covariância não estruturada, tendo em conta a matriz de parentesco entre os animais. Resultados: todas as características em búfalos provenientes do sistema DP e as características EGA, AC e AS em búfalos do sistema CSO, apresentaram um melhor ajuste em regressões de segunda ordem. O Peso, PT e AOL em animais provenientes do sistema CSO, ajustaram se melhor em regressões de primeira ordem. Em animais do sistema CSO a taxa de incremento da AC e AS diminuiu no final do período, as outras características não apresentaram diminuição. Os búfalos do sistema DP apresentaram um aumento considerável de todas as características ao final da avaliação. A variância genética estimada para os coeficientes de regressão foram diferentes de zero, o que sugere que estas características podem ser melhoradas geneticamente na Colômbia. Diferenças ambientais e genéticas entre as fazendas podem ter influenciado na alta variabilidade do intercepto entre os indivíduos. Conclusões: as variâncias do coeficiente de regressão linear foram pequenas para todas as características, sugerindo que, embora a seleção de animais em testes de desempenho seja possível, as mudanças esperadas na população de búfalos serão pequenas.

Objective: the objective of this research was to estimate genetic parameters and to predict breeding values for live weight in a Colombian Bos taurus-Bos indicus multibreed beef cattle population using random regression models (RRM). Methods: the population included 352 offspring from 37 sires of nine breeds mated to Gray Brahman females. The sire breeds were Gray Brahman, Red Brahman, Guzerat, Blanco Orejinegro, Romosinuano, Simmental, Braunvieh, Normand and Limousin. A longitudinal structured data set comprising 1,090 records was used. First (LP1) and second (LP2) order Legendre polynomials were used to estimate the coefficients of covariance functions. The animal model used included animal age, parity, contemporary group (herd * year * season * sex), breed group, additive genetic and heterosis as fixed effects. Random effects were the direct and maternal additive genetic, and the maternal permanent environment. Residual variances were assumed to be constant along the trajectory (HOM) or to change trough different stages of the growth trajectory (HET). Thus, four RRM (i.e: LP1HOM, LP1HET, LP2HOM, and LP2HET) were compared via Schwartz's Bayesian information and Corrected Akaike's Information criteria. Results: the best RRM model was LP2HET. This model was used to obtain direct and maternal heritabilities (Dh and Mh), correlations, and breeding values. The estimated direct additive covariance function showed that additive genetic covariances increased with age. The Dh was 0.24 at birth, decreased to 0.02 at 132 days, then increased to 0.18 at 492 d. The Mh was negligible throughout the growth period. Direct additive correlation values were moderate (0.43) to high (0.99) and tended to decrease as difference between ages increased. Maternal permanent environmental correlations (MPEC) followed a similar trend. Conclusions: these results suggest that selection for additive direct genetic effects based on weight at an early age would be effective in obtaining heavier animals at advanced growth stages under Colombia's tropical pasture conditions.Objetivo: el objetivo de esta investigación fue estimar parámetros genéticos y predecir valores genéticos para peso vivo en una población bovina multirracial Bos taurus-Bos indicus empleando modelos de regresión aleatoria (RRM). Métodos: la población estuvo compuesta por 352 descendencias de 37 toros de nueve razas apareados con hembras Brahman gris. Las razas de los toros fueron: Brahman gris, Brahman rojo, Guzerat, Blanco Orejinegro, Romosinuano, Simmental, Braunvieh, Normando y Limousin. Se empleó una base de datos con estructura longitudinal de 1,090 registros. Para estimar los coeficientes de las funciones de covarianza se usaron Polinomios de Legendre de primero (LP1) y segundo orden (LP2). El modelo animal empleado consideró como efectos fijos la edad del animal, número de partos de la madre, grupo contemporáneo (hacienda * año * época * sexo), grupo racial genético aditivo, y heterosis. Los efectos aleatorios fueron genético aditivo directo y materno y ambiente permanente materno. Las varianzas residuales se asumieron constantes (HOM) o cambiantes a través de diferentes etapas de la trayectoria de crecimiento (HET). Así, se compararon cuatro modelos: LP1HOM, LP1HET, LP2HOM, LP2HET mediante los criterios de información Bayesiano de Schwartz y de Akaike corregido. Resultados: el mejor RRM fue LP2HET. Este modelo fue empleado para obtener heredabilidades directa (Dh) y materna (Mh), correlaciones, y valores genéticos. La función de covarianza aditiva directa estimada mostró que la covarianza aditiva directa aumentó conforme los animales crecieron. La Dh fue 0.24 al nacimiento, disminuyó a 0.02 a los 132 días y luego aumentó hasta 0.18 a los 492 días. La Mh fue despreciable a través del periodo de crecimiento. Los valores de correlación genética directa fueron moderados (0.43) a altos (0.99). Las correlaciones de ambiente permanente materno siguieron una tendencia similar. Conclusiones: estos resultados sugieren que la selección para efectos genéticos aditivos directos basada en el peso a edades tempranas sería efectiva para obtener animales más pesados en estadios de crecimiento posteriores bajo las condiciones tropicales de pastoreo en Colombia.Objetivo: o objetivo deste trabalho foi à estimação de parâmetros genéticos e a predição dos valores genéticos para peso vivo em bovinos mestiços (Bos taurus-Bos indicus) utilizando modelos de regressão aleatória (RRM). Métodos: foram analisadas 1090 informações de 352 animais, filhos de 37 touros de nove raças diferentes, acasalados com fêmeas Brahman. As raças dos touros foram Brahman, Brahman Vermelho, Guzerá, Blanco Orejinegro, Romosinuano, Simental, Braunvieh, Normanda e Limousin. Para a estimação dos coeficientes das funções de covariância foram utilizados Polinômios de Legendre de primeiro (LP1) e segundo orden (LP2). O modelo animal empregado considerou como efeitos fixos a idade do animal, o numero de partos da vaca, o grupo contemporâneo (fazenda * ano * época * sexo da cria), a genética aditiva do grupo racial e a heterose. E como efeitos aleatórios: o efeito genético aditivo e materno e o ambiente permanente materno. As variâncias residuais assumiram se constantes ao longo da trajetória (HOM) ou com mudanças através das diferentes etapas do crescimento (HET). Assim, compararam se quatro modelos: LP1HOM, LP1HET, LP2HOM, LP2HET por médio de critérios de informação Bayesiano de Schwartz e pelo critério de informação Akaike corrigido. Resultados: o melhor modelo de RRM foi LP2HET. Este modelo foi usado para obter as herdabilidade direta e materna (Dh e Mh), e as correlações genéticas e os valores genéticos. A função de covariância aditiva direta mostrou que as covariâncias genéticas aditivas aumentaram com o crescimento do animal. A Dh foi de 0,24 ao nascimento, diminuiu até 0,02 aos 132 dias e após aumento até 0,18 aos 492 dias. A Mh foi insignificante durante todo o período de crescimento. Os valores de correlação direta aditiva foram de moderados (0,43) a altos (0,99) e tenderam a diminuir quando a idade aumentou. As correlações de ambiente permanente materno seguiram uma tendência similar. Conclusões: estes resultados sugerem que a seleção para os efeitos genéticos aditivos diretos nas idades iniciais seria eficiente na obtenção de animais com maiores pesos na idade adulta sob condições tropicais na Colômbia.

In genome-wide prediction, independence of marker allele substitution effects is typically assumed; however, since early stages in the evolution of this technology it has been known that nature points to correlated effects. In statistics, graphical models have been identified as a useful and powerful tool for covariance estimation in high dimensional problems and it is an area that has recently experienced a great expansion. In particular, Gaussian concentration graph models (GCGM) have been widely studied. These are models in which the distribution of a set of random variables, the marker effects in this case, is assumed to be Markov with respect to an undirected graph G. In this paper, Bayesian (Bayes G and Bayes G-D) and frequentist (GML-BLUP) methods adapting the theory of GCGM to genome-wide prediction were developed. Different approaches to define the graph G based on domain-specific knowledge were proposed, and two propositions and a corollary establishing conditions to find decomposable graphs were proven. These methods were implemented in small simulated and real datasets. In our simulations, scenarios where correlations among allelic substitution effects were expected to arise due to various causes were considered, and graphs were defined on the basis of physical marker positions. Results showed improvements in correlation between phenotypes and predicted additive genetic values and accuracies of predicted additive genetic values when accounting for partially correlated allele substitution effects. Extensions to the multiallelic loci case were described and some possible refinements incorporating more flexible priors in the Bayesian setting were discussed. Our models are promising because they allow incorporation of biological information in the prediction process, and because they are more flexible and general than other models accounting for correlated marker effects that have been proposed previously.

The aim of this study was to determine the effects of daily ranges and maximum ambient temperatures, and other risk factors on reproductive failure of Landrace (L) and Yorkshire (Y) sows under an open-house system in Thailand. Daily ambient temperatures were added to information on 35,579 litters from 5929 L sows and 1057 Y sows from three commercial herds. The average daily temperature ranges (ADT) and the average daily maximum temperatures (PEAK) in three gestation periods from the 35th day of gestation to parturition were classified. The considered reproductive failure traits were the occurrences of mummified fetuses (MM), stillborn piglets (STB), and piglet death losses (PDL) and an indicator trait for number of piglets born alive below the population mean (LBA). A multiple logistic regression model included farrowing herd-year-season (HYS), breed group of sow (BG), parity group (PAR), number of total piglets born (NTB), ADT1, ADT2, ADT3, PEAK1, PEAK2, and PEAK3 as fixed effects, while random effects were animal, repeated observations, and residual. Yorkshire sows had a higher occurrence of LBA than L sows (P = 0.01). The second to fifth parities sows had lower reproductive failures than other parities. The NTB regression coefficients of log-odds were positive (P

Objective The objective of this research was to estimate genetic correlations between number of piglets born alive in the first parity (NBA1), litter birth weight in the first parity (LTBW1), number of piglets weaned in the first parity (NPW1), litter weaning weight in the first parity (LTWW1), number of piglets born alive from second to last parity (NBA2+), litter birth weight from second to last parity (LTBW2+), number of piglets weaned from second to last parity (NPW2+) and litter weaning weight from second to last parity (LTWW2+), and to identify the percentages of animals (the top 10%, 25%, and 50%) for first parity and sums of second and later parity traits. Methods The 9,830 records consisted of 2,124 Landrace (L), 724 Yorkshire (Y), 2,650 LY, and 4,332 YL that had their first farrowing between July 1989 and December 2013. The 8-trait animal model included the fixed effects of first farrowing year-season, additive genetic group, heterosis of the sow and the litter, age at first farrowing, and days to weaning (NPW1, LTWW1, NPW2+, and LTWW2+). Random effects were animal and residual. Results Heritability estimates ranged from 0.08±0.02 (NBA1 and NPW1) to 0.29±0.02 (NPW2+). Genetic correlations between reproduction traits in the first parity and from second to last parity ranged from 0.17±0.08 (LTBW1 and LTBW2+) to 0.67±0.06 (LTWW1 and LTWW2+). Phenotypic correlations between reproduction traits in the first parity and from second to last parity were close to zero. Rank correlations between LTWW1 and LTWW2+ estimated breeding value tended to be higher than for other pairs of traits across all replacement percentages. Conclusion These rank correlations indicated that selecting boars and sows using genetic predictions for first parity reproduction traits would help improve reproduction traits in the second and later parities as well as lifetime productivity in this swine population.

Each year Shiga toxin-producing Escherichia coli (STEC) are responsible for 2.8 million acute illnesses around the world and > 250,000 cases in the US. Lowering the prevalence of this pathogen in animal reservoirs has the potential to reduce STEC outbreaks in humans by controlling its entrance into the food chain. However, factors that modulate the colonization and persistence of STEC in beef cattle remain largely unidentified. This study evaluated if animal physiological factors such as age, breed, sex, and weight gain influenced the shedding of STEC in beef cattle. A cohort of beef calves (n = 260) from a multi-breed beef calf population was sampled every three months after birth to measure prevalence and concentration of STEC during the first year of life. Metagenomic analysis was also used to understand the association between the STEC colonization and the composition of gut microflora. This study identified that beef calves were more likely to shed STEC during the first 6 months and that STEC shedding decreased as the animal matured. Animal breed group, sex of the calf, and average weight gain were not significantly associated with STEC colonization. The metagenomic analysis revealed for the first time that STEC colonization was correlated with a lower diversity of gut microflora, which increases as the cattle matured. Given these findings, intervention strategies that segregate younger animals, more likely to be colonized by STEC from older animals that are ready to be harvested, could be investigated as a method to reduce zoonotic transmission of STEC from cattle to humans.

Insulin-like growth factor II (IGF-II) is one of the members of the somatotropic axis which controls the growth and development of animals. This study was conducted to identify single-nucleotide polymorphisms in the IGF2 gene and study their associations with two production traits in a Chinese indigenous chicken (Langshan chicken) population. Genetic variants within the IGF2 gene were screened through PCR-SSCP and DNA sequencing methods. A C6707G mutation (Chromosome 5 position 13,161,038 build 4) was identified. Associations between the mutations of the gene with two production traits were analysed. The results showed that individuals within the GG genotype had significantly higher 16-week-old body weight than those within the CG genotype. In addition, the GG individuals also had significantly higher 300 days egg numbers than individuals within CC or CG genotype. Ratios of dominance effects to absolute values of additive effects were less than 0 for both traits implying that Langshan chickens with homozygous genotypes for this locus had higher performance than individuals with heterozygous genotypes.

Brahman cattle are important in tropical regions due to their ability to tolerate excessive heat and parasites. However, Brahman cattle exhibit lower carcass quality characteristics when compared to Bos taurus breeds. The objective of this study was to evaluate potential associations between single nucleotide polymorphisms (SNPs) in six candidate genes for carcass quality and composition traits in a population of Brahman and Brahman-influenced steers. Steers were evaluated through the American Brahman Breeders Association carcass evaluation project in Gonzales, Texas. Carcass traits measured included hot carcass weight, ribeye area, marbling score, yield grade, quality grade, dressing percent, and Warner-Bratzler shear force score. Six previously described candidate genes were chosen for SNP analysis based on their previous association with growth and carcass traits. Candidate genes utilized in the current study included calpastatin (CAST), calpain (CAPN3), thyroglobulin (TG), growth hormone, insulin growth factor 1, and adiponectin. Six unique SNPs from three candidate genes (TG, CAST, and CAPN3) were significantly associated (P < 0.001) with carcass quality traits (marbling score and quality grade). A genotypic effect was observed for all significant SNPs, with differing levels of performance observed for animals inheriting different genotypes. Although multiple SNPs in the current study were significantly (P < 0.001) associated with growth and carcass traits, they should be validated in larger populations prior to implementation in selection strategies.

Objetivo: dada la necesidad de evaluar varias razas bovinas en Colombia para caracteres de crecimiento y composición corporal, el objetivo de este estudio fue obtener mejores estimadores lineales insesgados para efectos de heterosis y grupo racial para tales caracteres. Métodos: las características de crecimiento evaluadas fueron el peso a diferentes edades: nacimiento (PN), y aproximadamente a los 4 meses (P4), destete (PD), año (PA), y 15 meses (P15). Las caracteristicas de composición corporal fueron área de ojo del lomo (AOL) y grasa dorsal (GD) medidas a las mismas edades que el peso, excepto al nacimiento: AOL4 y GD4, AOLD y GDD, AOLA y GDA, AOL15 y GD15. La población estuvo conformada por 352 progenies de 37 toros representando 9 razas (Brahman Gris, Brahman Rojo, Guzerat, Blanco Orejinegro, Romosinuano, Normando, Braunvieh, Limousin y Simmental) y hembras Brahman Gris. Se emplearon modelos animales uni-varidos con los efectos de: grupo contemporáneo, número de partos de la madre, edad del animal, fracción esperada de grupo racial en el animal, y proporción de heterocigosis como efectos fijos y aditivos directo y materno como aleatorios. Resultados: los mayores valores genéticos aditivos para PN, P4, PD, PA y P15 se encontraron en animales de la raza Guzerat (6.31 kg), Normando (12.67 kg), Normando (8.28 kg), Braunvieh (24.80 kg) y Normando (42.20 kg), respectivamente. Para AOL4, AOLD, AOLA y AOL15 se encontraron en animales de la raza Limousin (20.87 cm²), Limousin (12.60 cm²), Simmental (10.94 cm²) y Limousin (16.09 cm²), respectivamente. Y para GD4, GDD, GDA y GD15 se encontraron en animales de la raza Limousin (0.27 mm), Guzerat (0.21 mm), Blanco Orejinegro (1.05 mm) y Romosinuano (0.71 mm). Los valores de heterosis para peso variaron entre -3.22 kg (PA) y 7.43 kg (P15), para AOL entre 0.12 cm² (AOL4) y 4.39 cm² (AOLA) y para GD entre 0.01 (GDD y GD15) y 0.09 mm (GDA). Conclusiones: los resultados indicaron que en general Normando fue superior para peso vivo, y Limousin para AOL entre los animales de cada raza en el estudio.Objetivo: em virtude da necessidade de avaliar diversas raças de bovinos na Colômbia para características de crescimento e composição corporal, o objetivo deste estudo foi determinar o melhor estimador linear não-viciado para obter os efeitos de heterose e grupo racial para essas características. Métodos: as características de crescimento foram os pesos a diferentes idades: nascimento (PN), y aproximadamente aos quatro meses (P4), desmame (PD), ano (PA) e 15 meses (P15). Características de composição corporal como a área de olho de lombo (AOL) e espessura de gordura subcutânea (GD) foram mensuradas nas mesmas idades, exceto ao peso ao nascimento (AOL4 e GD4; AOLD e GDD; AOLA e GDA; AOL15 e GD15). A população estava conformada por 352 progênies de 37 touros pertencentes a nove raças (Brahman Cinza, Brahman Vermelho, Guzerá, Blanco Orejinegro, Romosinuano, Normando, Braunvieh, Limuosin e Simental) acasalados com fêmeas da raça Brahman Cinza. Foram empregados modelos animais univariados considerando: efeito de grupo de contemporâneos, número de partos da mãe, idade do animal, fração esperada do grupo racial no animal e proporção da heterozigose como efeitos fixos, e como aleatórios o efeito aditivo direto e o efeito materno. Resultados: os maiores valores genéticos aditivos para PN, P4, PD, PA e P15 foram encontrados em animais da raça Guzerá (6.31 kg), Normando (12.67 kg), Normando (8.28 kg), Braunvieh (24.80 kg) e Normando (42.20 kg) respectivamente. Para AOL4, AOLD, AOLA e AOL15 os maiores valores foram encontrados em animais da raça Limousin (20.87 cm²), Limousin (12.60 cm²), Simental (10.94 cm²) e Limousin (16.09 cm²), respectivamente. E para GD4, GDD, GDA e GD15 os maiores valores foram encontrados na raça Limousin (0.27 mm), Guzerá (0.21 mm), Blanco Orejinegro (1.05 mm) e Romosinuano (0.71 mm). Os valores de heterose para peso variaram de -3.22 kg (PA) ate 7.43 kg (P15), para AOL entre 0.12 cm² (AOL4) e 4.39 cm² (AOLA) e para GD entre 0.01 mm (GDD e GD15) e 0.09 mm (GDA). Conclusões: os resultados indicam que em geral animais da raça Normando foram superiores para peso vivo quando se compararam com as outras raças, e para a AOL animais da raça Limousin apresentaram os maiores valores.Objective: given the need to evaluate several cattle breeds for growth and body composition traits in Colombia, the objective of this study was to obtain the best linear unbiased estimators of heterosis and breed group effects for these traits. Methods: live weight was evaluated at birth (PN), and aproximately at 4 months (P4), weaning (PD), first year (PA), and 15 months of age (P15). Body composition traits evaluated were rib eye area (AOL) and back fat thickness (GD) measured at the same ages as live weight, except at birth: AOL4 and GD4, AOLD and GDD, AOLA and GDA, AOL15 and GD15. The evaluated population consisted of 352 offspring from 37 bulls representing 9 breeds (Gray Brahman, Red Brahman, Guzerat, Blanco Orejinegro, Romosinuano, Normando, Braunvieh, Limousin, and Simmental), and Gray Brahman females. The farms were located in southern Cesar, Colombia. Univariate animal models were used. Models included contemporary group, dam parity, age of the animal, expected fraction of breed group in the animal, and proportion of heterozygosis as fixed effects, with direct additive and maternal as random effects. Results: the highest additive genetic values for PN, P4, PD, PA, P15 were found in Guzerat (6.31 kg), Normando (12.67 kg), Normando (8.28 kg), Braunvieh (24.80 kg) and Normando (42.20 kg), respectively. Those for AOL4, AOLD, AOLA and AOL15 in Limousin (20.87 cm²), Limousin (12.60 cm²), Simmental (10.94 cm²) and Limousin (16.09 cm²). And those for GD4, GDD, GDA and GD15 in Limousin (0.27 mm), Guzerat (0.21 mm), Blanco Orejinegro (1.05 mm) and Romosinuano (0.71 mm), respectively. The heterosis values for live weight ranged from -3.22 (PA) to 7.43 kg (P15), for AOL from 0.12 (AOL4) to 4.39 mm² (AOLA) and for GD from 0.01 (GDD and GD15) to 0.09 mm (GDA). Conclusion: results indicated that Normando was generally superior for live weight and Limousin was superior for AOL among the animals sampled from each breed in the study.

The objectives of this study were to determine the fraction of additive genetic variance explained by the SNP from the Illumina Bovine3K chip; to compare the ranking of animals evaluated with genomic-polygenic, genomic, and polygenic models; and to assess trends in predicted values from these 3 models for residual feed intake (RFI), daily feed intake (DFI), feed conversion ratio (FCR), and postweaning BW gain (PWG) in a multibreed Angus-Brahman cattle population under subtropical conditions. Data consisted of phenotypes and genotypes from 620 bulls, steers, and heifers ranging from 100% Angus to 100% Brahman. Phenotypes were collected in a GrowSafe automated feeding facility (GrowSafe Systems, Ltd., Airdrie, Alberta, Canada) from 2006 to 2010. Variance components were estimated using single-trait genomic-polygenic mixed models with option VCE (Markov chain Monte Carlo) of the program GS3. Fixed effects were contemporary group (year-pen), age of dam, sex of calf, age of calf, Brahman fraction of calf, and heterozygosity of calf. Random effects were additive SNP, animal polygenic, and residual effects. Genomic predictions were computed using a model without polygenic effects and polygenic predictions with a model that excluded additive SNP effects. Heritabilities were 0.20 for RFI, 0.31 for DFI, 0.21 for FCR, and 0.36 for PWG. The fraction of the additive genetic variance explained by SNP in the Illumina 3K chip was 15% for RFI, 11% for DFI, 25% for FCR, and 15% for PWG. These fractions will likely differ in other multibreed populations. Rank correlations between genomic-polygenic and polygenic predictions were high (0.95 to 0.99; P < 0.0001), whereas those between genomic-polygenic and genomic predictions were low (0.65 to 0.74; P < 0.0001). Genomic-polygenic, genomic, and polygenic predictions for all traits tended to decrease as Brahman fraction increased, indicating that calves with greater Brahman fraction were more efficient but grew more slowly than calves with greater Angus fraction. Predicted SNP values were small for all traits, and those above and below 0.2 SNP SD were in multiple chromosomes, supporting the contention that quantitative traits are determined by large numbers of alleles with small effects located throughout the genome.

La metodología de modelos mixtos ha sido la principal herramienta estadística para la evaluación y la selección de animales domésticos tales como el vacuno durante más de 30 años. Desde que se propuso el uso de modelos lineales mixtos para obtener los mejores predictores lineales insesgados de los valores genéticos de los individuos en una población se han dado avances científicos a nivel estadístico y computacional que han permitido implementar modelos más complejos, los cuales describen diferentes situaciones biológicas y estructuras de datos. En el presente trabajo se hace una breve revisión de la historia de las evaluaciones genéticas en vacunos haciendo énfasis en la metodología de modelos mixtos en la cual se han basado dichas evaluaciones. Los siguientes tópicos son descritos en este documento: El modelo animal unirracial, la derivación de las ecuaciones de modelos mixtos, algunas extensiones del modelo animal unirracial (efectos aditivos directos y maternos, efectos ambientales aleatorios, modelo para múltiples caracteres), el modelo animal multirracial, modelos para la evaluación genética de datos longitudinales y finalmente una breve descripción de la evaluación genómica.A metodologia dos modelos mistos tem sido a principal ferramenta estatística para a avaliação e seleção de animais domésticos, como ocorreu em bovinos há mais de trinta anos. Desde sua proposta, o uso de modelos lineares mistos, para obter os melhores preditores lineares imparciais dos valores genéticos de indivíduos de uma população, têm sofrendo avanços científicos a nível estatístico e computacional, tornando-se possível implementar modelos mais complexos que descrevem diferentes situações biológicas e estruturas de dados. No presente trabalho, é feita uma breve revisão histórica sobre as avaliações genéticas em bovinos, com ênfase na metodologia de modelos mistos, na qual estas avaliações são baseadas. Os seguintes tópicos são descritos neste documento: o modelo animal unirracial, a derivação das equações de modelos mistos, algumas extensões do modelo animal unirracial (efeitos aditivos direto e materno, efeitos aleatórios ambientais, modelos multicaracterísticas), o modelo animal multirracial, modelos para a avaliação genética de dados longitudinais e, finalmente, uma breve descrição da avaliação genômica.Mixed model methodology has been the main statistical tool for unbiased genetic animal evaluation and selection of domestic animals, such as bovines, for over thirty years. Since the use of linear mixed models to obtain the best linear unbiased prediction of the breeding value of the individuals in a population was proposed, there have been scientific advances at the statistical and computational level that have led to implement more complex models describing different biological situations and data structures. This work briefly reviews the history of genetic evaluation in cattle emphasizing on the mixed model methodology in which these evaluations are based. The following topics are discussed in this paper: The unibreed animal model, the derivation of the mixed model equations, some extensions of the unibreed animal model (additive direct and maternal effects, random environmental effects, multiple traits model), the mutibreed animal model, models for the genetic evaluation of longitudinal data and, finally, a brief description of genomic evaluation.

The aim of this study was to estimate genetic parameters for BW of Angus cattle up to 5 yr of age and to discuss options for including mature weight (MW) in their genetic evaluation. Data were obtained from the American Angus Association. Only records from herds with at least 500 animals and with >10% of animals with BW at ≥ 2 yr of age were considered. Traits were weaning weight (WW, n = 81,525), yearling weight (YW, n = 62,721), and BW measured from 2 to 5 yr of age (MW2, n = 15,927; MW3, n = 12,404; MW4, n = 9,805; MW5, n = 7,546). Genetic parameters were estimated using an AIREML algorithm with a multiple-trait animal model. Fixed effects were contemporary group and departure of the actual age from standard age (205, 365, 730, 1,095, 1,460, and 1,825 d of age for WW, YW, MW2, MW3, MW4, and MW5, respectively). Random effects were animal direct additive genetic, maternal additive genetic, maternal permanent environment, and residual. Estimates of direct genetic variances (kg(2)) were 298 ± 71.8, 563 ± 15.1, 925 ± 52.1, 1,221 ± 65.8, 1,406 ± 80.4, and 1,402 ± 66.9; maternal genetic variances were 167 ± 4.8, 153 ± 6.1, 123 ± 9.1, 136 ± 12.25, 167 ± 18.0, and 110 ± 14.0; maternal permanent environment variances were 124 ± 2.9, 120 ± 4.3, 61 ± 7.5, 69 ± 11.9, 103 ± 15.9, and 134 ± 35.2; and residual variances were 258 ± 3.8, 608 ± 8.6, 829 ± 34.2, 1,016 ± 38.8, 1,017 ± 52.1, and 1,202 ± 63.22 for WW, YW, MW2, MW3, MW4, and MW5, respectively. The direct genetic correlation between WW and YW was 0.84 ± 0.14 and between WW and MW ranged from 0.66 ± 0.06 (WW and MW4) to 0.72 ± 0.11 (WW and MW2). Direct genetic correlations ranged from 0.77 ± 0.08 (YW and MW5) to 0.85 ± 0.07 (YW and MW2) between YW and MW, and they were ≥ 0.95 among MW2, MW3, MW4, and MW5. Maternal genetic correlations between WW and YW and MW ranged from 0.52 ± 0.05 (WW and MW4) to 0.95 ± 0.07 (WW and YW), and among MW they ranged from 0.54 ± 0.14 (MW4 and MW5) to 0.94 ± 0.07 (MW2 and MW3). Genetic correlations suggest that a genetic evaluation for MW may be MW2-based and that including BW from older ages could be accomplished by adjusting records to the scale of MW2.

The objective of this research was to estimate the relative magnitude of effects included in contemporary groups (CG) and their interactions with adjusted and actual 120 d and 210 d weights in 72, 731 male and female Nelore calves born from 1985 to 2005 in 40 herds from PMGRN (Genetic Improvement Program of Nelore). Ten models with different CG structures were compared. The analyses were done using the general linear models (GLM) procedure run in SAS software. All of the effects included in the CG for each model were significant (p < 0.001) for the four traits analyzed. Inclusion of semester or trimester of birth as part of a CG was more appropriate than its use as an independent effect in the model because it accounted for interactions with the other effects in the CG. Calf sex (CS) and dam age at calving (DAC) had similar effects across the models, which suggested independence from other effects in these models. The corresponding age deviation effect had a larger impact on actual weight at 120 d than any other effect in all of the models tested. The use of actual weights in models with no CS effect in CG provides an alternative that would allow better genetic connectedness among CGs and greater accuracy in genetic evaluations.

The objective of this study was to characterize factors influencing genetic improvement of dairy cattle for milk production at farm level. Data were accumulated from 305-day milk yields and pedigree information from 1,921 first-lactation dairy cows that calved from 1990 to 2007 on 161 farms in Central Thailand. Variance components were estimated using average information restricted maximum likelihood procedures. Animal breeding values were predicted by an animal model that contained herd-year-season, calving age, and regression additive genetic group as fixed effects, and cow and residual as random effects. Estimated breeding values from cows that calved in a particular month were used to estimate genetic trends for each individual farm. Within-farm genetic trends (b, regression coefficient of farm milk production per month) were used to classify farms into 3 groups: i) farms with negative genetic trend (b kg/mo), and iii) farms with positive genetic trend (b>0.5 kg/mo). Questionnaires were used to gather information from individual farmers on educational background, herd characteristics, farm management, decision making practices, and opinion on dairy farming. Farmer's responses to the questionnaire were used to test the association between these factors and farm groups using Fisher's exact test. Estimated genetic trend for the complete population was kg/year for cows. At farm level, most farms (40%) had positive genetic trend ( to kg/mo) followed by farms with negative genetic trend (35%; to kg/mo) and those with no genetic trend (25%; to kg/mo). Except for educational background (p

The objective of this research was to assess the effect of experience, education, record keeping, labor, and decision making on monthly milk yield per farm (MYF), monthly milk yield per cow (MYC), monthly milk revenue per farm (MRF), and monthly revenue per cow (MRC) of dairy farms supported by a private organization in Central Thailand. The dataset contained 34,082 monthly milk yield and revenue records collected from January 2004 to December 2008 on 497 farms, and information on individual farmer experience and education, record keeping, and decision making obtained with a questionnaire. Farmer experience categories were i) no experience, ii) one year, iii) two to five years, iv) six to ten years, v) eleven to fifteen years, vi) sixteen to twenty years, and vii) more than twenty years. Farmer education categories were i) no education or primary school, ii) high school, and iii) bachelor or higher degree. Record keeping categories were: i) no records and ii) kept records. Labor categories were: i) family, ii) hired people, and iii) family and hired people. Decision making categories were: i) decisions made by farmers themselves, ii) decisions made with help from government officials, and iii) decisions made with help from organization staff. The mixed linear model contained the fixed effects of year-season, farm location-farm size subclass, experience, education, record keeping, labor, and decision making on sire selection, and the random effects of farm and residual. Results showed that longer experience increased (p

The objectives of this research were the estimation of genetic parameters and trends for weaning-to-first service interval (WSI), and litter traits in a commercial swine population composed of Landrace (L), Large White (T), LT, and TL animals in Chiang Mai, Northern Thailand. The dataset contained 4,399 records of WSI, number of piglets born alive (NBA), litter weight of live piglets at birth (LBW), number of piglets at weaning (NPW), and litter weight at weaning (LWW). Variance and covariance components were estimated with REML using 2-trait analyses. An animal model was used for WSI and a sire-dam model for litter traits. Fixed effects were farrowing year-season, breed group of sow, breed group of boar (litter traits), parity, heterosis (litter traits), sow age, and lactation length (NPW and LWW). Random effects were boar (litter traits), sow, permanent environment, and residual. Heritabilities for direct genetic effects were low for WSI (0.04±0.02) and litter traits (0.05±0.02 to 0.06±0.02). Most heritabilities for maternal litter trait effects were 20% to 50% lower than their direct counterparts. Repeatability for WSI was similar to its heritability. Repeatabilities for litter traits ranged from 0.15±0.02 to 0.18±0.02. Direct genetic, permanent environment, and phenotypic correlations between WSI and litter traits were near zero. Direct genetic correlations among litter traits ranged from 0.56±0.20 to 0.95±0.05, except for near zero estimates between NBA and LWW, and LBW and LWW. Maternal, permanent environment, and phenotypic correlations among litter traits had similar patterns of values to direct genetic correlations. Boar genetic trends were small and significant only for NBA (-0.015±0.005 piglets/yr, p

Genetic parameters and genetic trends for age at first calving (AFC), interval between first and second calving (CI1), and interval between second and third calving (CI2) were estimated in a Colombian beef cattle population composed of Angus, Blanco Orejinegro, and Zebu straightbred and crossbred animals. Data were analyzed using a multiple trait mixed model procedures. Estimates of variance components and genetic parameters were obtained by Restricted Maximum Likelihood. The 3-trait model included the fixed effects of contemporary group (year-season of calving-sex of calf; sex of calf for CI1 and CI2 only), age at calving (CI1 and CI2 only), breed genetic effects (as a function of breed fractions of cows), and individual heterosis (as a function of cow heterozygosity). Random effects for AFC, CI1, and CI2 were cow and residual. Program AIREMLF90 was used to perform computations. Estimates of heritabilities for additive genetic effects were 0.15 ± 0.13 for AFC, 0.11 ± 0.06 for CI1, and 0.18 ± 0.11 for CI2. Low heritabilities suggested that nutrition and reproductive management should be improved to allow fuller expressions of these traits. The correlations between additive genetic effects for AFC and CI1 (0.33 ± 0.41) and for AFC and CI2 (0.40 ± 0.36) were moderate and favorable, suggesting that selection of heifers for AFC would also improve calving interval. Trends were negative for predicted cow yearly means for AFC, CI1, and CI2 from 1989 to 2004. The steepest negative trend was for cow AFC means likely due to the introduction of Angus and Blanco Orejinegro cattle into this population.

Genetic parameters and genetic trends for weaning weight adjusted to 240 d of age (WW240), and weight gain from weaning to 24 mo of age (GW730) were estimated in a Colombian beef cattle population composed of Blanco Orejinegro, Romosinuano, Angus, and Zebu straightbred and crossbred animals. Calves were born and weaned in a single farm, and moved to 14 farms postweaning. Data were analyzed using a multiple trait mixed model procedures. Estimates of variance components and genetic parameters were obtained by Restricted Maximum Likelihood. The 2-trait model included the fixed effects of contemporary group (herd–year–season–sex), age of dam (WW240 only), breed direct genetic effects (as a function of breed fractions of calves), breed maternal genetic effects (as a function of breed fractions of dams; WW240 only), individual heterosis (as a function of calf heterozygosity), and maternal heterosis (as a function of dam heterozygosity; WW240 only). Random effects for WW240 were calf direct genetic, dam maternal genetic, permanent environmental maternal, and residual. Random effects for GW730 were calf direct genetic and residual. All relationships among animals were accounted for. Program AIREML was used to perform computations. Estimates of heritabilities for additive direct genetic effects were 0.20 ± 0.003 for WW240, and 0.32 ± 0.004 for GW730. Maternal heritability was 0.14 ± 0.002 for WW240. Estimates of heritability suggest that selection for preweaning and postweaning growth in this population is feasible. Low direct and maternal preweaning heritabilities suggest that nutrition and management should be improved to allow fuller expressions of calf direct growth and cow maternal ability. The genetic correlation between direct additive and maternal additive effects for WW240 was − 0.42 ± 0.009, indicating an antagonistic relationship between these effects. The correlation between additive direct genetic effects for WW240 and GW730 was almost zero (− 0.04 ± 0.009), suggesting that genes affecting growth preweaning may differ from those influencing growth postweaning. Trends were negative for direct WW240 and GW730 weighted yearly means of calves, sires, and dams from 1995 to 2006. Maternal WW240 showed near zero trends during these years. Trends for calf direct WW240 and GW730 followed sire trends closely, suggesting that more emphasis was placed on choosing sires than on dam replacements.

Genetic variability and genetic trends for 305-day milk yield (MY), 305-day fat yield (FY), and average 305-day fat percent (FP) were evaluated using monthly test-day records from first-lactation cows collected from 1991 to 2005 in 92 farms located in Central Thailand. Estimates of variance and covariance components and breeding values (EBV) were obtained using a multiple-trait animal model. Fixed effects were contemporary group (herd–year–season), calving age, additive genetic group as a function of Holstein fraction, and non-additive genetic group as function of heterosis effect. Random effects were animal and residual. Program ASREML was used to perform computations. Estimates of heritabilities were 0.38 ± 0.10 for MY, 0.25 ± 0.11 for FY, and 0.22 ± 0.11 for FP. Although the difference between the mean MY for cows in 1991 and 2005 was 324.1 kg, the regression of mean cow EBV for MY on year was 6.5 kg/year. Differences between mean cow EBV for FY and FP in 1991 and 2005 and their corresponding regressions of mean FY and FP on year were all near zero. Similarly, mean EBV for sires and dams of cows also showed near zero trends during these years. A factor contributing to the near complete absence of genetic trends was likely the variety of criteria used by producers to choose sires and to keep dams in addition to EBV (e.g., availability of semen, reproductive ability, adaptation to hot and humid conditions). It also appears that high percent Holstein cows failed to reach their production potential under the management, nutrition, and hot and humid climatic conditions in this tropical region. Changes in nutrition and management would be needed for high percent Holstein cows to show an upward trend in Central Thailand.

The objective of this research was to assess the association between 4 cow reproductive and weight traits, and 2 preweaning calf traits and ELISA scores for paratuberculosis (0 = negative, 1 = suspect, 2 = weak-positive, and 3 = positive) in a multibreed herd of cows ranging from 100% Angus (A) to 100% Brahman (B). Cow data were 624 gestation lengths (GL), 358 records of time open (TO), 605 calving intervals (CI), and 1240 weight changes from November to weaning in September (WC) from 502 purebred and crossbred cows. Calf data consisted of 956 birth weights (BWT), and 923 weaning weights adjusted to 205 d of age (WW205) from 956 purebred and crossbred calves. Traits were analyzed individually using multibreed mixed models that assumed homogeneity of variances across breed groups. Covariances among random effects were assumed to be zero. Fixed effects were year, age of cow, sex of calf, year x age of cow interaction (except WC), age of cow x sex of calf interaction (only for WC), and covariates for B fraction of sire and cow, heterosis of cow and calf, and ELISA score. Random effects were sire (except for TO and CI), dam, and residual. Regression estimates of cow and calf traits on ELISA scores indicated that lower cow fertility (longer TO), lower ability of cows to maintain weight (negative WC), lower calf BWT, and lower calf WW205 were associated with higher cow ELISA scores. Further research on the effects of subclinical paratuberculosis in beef cattle at regional and national levels seems advisable considering the large potential economic cost of this disease.

A study was conducted to estimate the record keeping, genetic selection, educational, and farm management effects on average milk yield per cow (AYC), milk fat percentage, bacterial score, and bulk tank somatic cell count (BTSCC) of dairy farms in the central region of Thailand. Farms were located in the provinces of Saraburi and Nakhon Ratchisima and were members of the Muaklek dairy cooperative. Records from individual animals were unavailable. Thus, farm records of milk yield, milk fat percentage, bacterial score, and BTCCC were collected from July 1, 2003 through June 30, 2006. Additional record keeping, genetic selection, education, and farm management information was collected through a questionnaire in May of 2006. Data from the Muaklek dairy cooperative and the questionnaire were then merged by a farm identification number. A single trait mixed model was used to analyze AYC, milk fat percentage, and BTSCC, while a log linear model was used to analyze bacterial score. Results showed that farms that kept records on individual animals had higher (P < 0.05) milk fat percentages and lower bacterial scores than farms that did not. Farms that used genetic information (EBV) and phenotypes when selecting sires were higher (P < 0.05) for milk fat percentage than farms that used only phenotypes and personal opinion. Farms milking cows with a single unit milking machine and by hand, had higher (P < 0.05) bacterial scores and BTSCC than farms using only a single or multi unit machine. Overall farms that kept individual animal records, used EBV when selecting sires, used a single method for collecting milk, and used family labor achieved higher performance from their herds than farms that did not.

A survey was performed to characterize the dairy production, educational experiences, decision making practices, and income and expenses of dairy farms and to determine any differences of these practices among two dairy farm populations. Farm groups were identified as farms from the Muaklek dairy cooperative (Muaklek farms) and farms from other dairy cooperatives (Non-Muaklek farms). In April, 2006 questionnaires were distributed to 500 dairy farms located in Lopburi, Nakhon Ratchisima, and Saraburi provinces. A total of 85 farms completed and returned questionnaires. Means and frequencies were calculated for questions across categories and Chi-square tests were performed to determine differences among Muaklek and Non-Muaklek farms. Results showed that most farms from both groups had a primary or high school educational level, used a combination confinement and pasture production system, gave a mineral supplement, raised their own replacement females, milked approximately 16 cows/day, used crossbred Holstein cows (75% Holstein or more), and mated purebred Holstein sires to their cows. More Non-Muaklek farms (P < 0.05; 80%) used a combination of genetic and phenotypic information when selecting sires than Muaklek farms (54%). Monthly profit per lactating cow, were 1,641 and 1,029 baht for Muaklek and Non-Muaklek farms, respectively. Overall, information from the study should be useful for dairy cooperatives and other dairy organizations when training farmers in the future and furthering dairy production research in Thailand.

A study was conducted to investigate determinates of how milk pricing system, farm location, farm size, and month and year affected farm milk price (FMP), farm milk revenue (FMR) and loss in FMR of dairy farms in the Central region of Thailand. A total of 58,575 milk price and 813,636 milk yield records from 1034 farms were collected from November of 2004 to June of 2006. Farms were located in the districts of Muaklek, Pak Chong, Wang Muang, and Kaeng Khoi. A fixed linear model was used to analyze milk price of farms. Two pricing systems were defined as 1 = base price plus additions/deductions for milk fat percentage, solids-non-fat, and bacterial score, and 2 = same as 1 plus bulk tank somatic cell count (BTSCC). Farm size (small, medium, and large) was based on the number of cows milked per day of farms. Results showed that FMP were lower (P < 0.05) in pricing system 1 than pricing system 2. Most small farms had higher (P < 0.05) milk prices than medium and large farms across both pricing systems. Large farms lost more milk revenue due to deductions from bacterial score and BTSCC than small and medium farms.

A study was conducted to determine the effects of season, farm location, and farm size on farm milk yield (FMY), average milk yield per cow (AYC), milk fat, bacterial score, and bulk tank somatic cell count (BTSCC) of dairy farms in the central region of Thailand. Farms were located in the districts of Kaeng Khoi, Muaklek, Pak Chong, and Wang Muang. Collection of data was at the farm level; individual animal records were unavailable. A total of 967,110 daily farm milk yield, 58,575 milk fat and bacterial score, and 24,109 BTSCC records from 1,034 farms were collected from July of 2003 to June of 2006. There were three seasons: rainy, summer and winter. Farms were categorized into small, medium, and large according to the number of cows milked per day. Results showed that FMY and AYC were higher (p

Genetic parameters and trends for length of productive life (LPL), lifetime number of piglets born alive per year (LBAY), lifetime number of piglets weaned per year (LPWY), lifetime litter birth weight per year (LBWY) and lifetime litter weaning weight per year (LWWY) were estimated using phenotypic records of 3085 sows collected from 1989 to 2013 in a commercial swine farm in Northern Thailand. The five-trait animal model included the fixed effects of first farrowing year-season, breed group and age at first farrowing. Random effects were animal and residual. Heritability estimates ranged from 0.04 ± 0.02 for LBWY to 0.17 ± 0.04 for LPL. Genetic correlations ranged from 0.66 ± 0.14 between LPL and LBAY to 0.95 ± 0.02 between LPWY and LWWY. Spearman rank correlations among estimated breeding values for LPL and lifetime production efficiency traits tended to be higher for boars than for sows. Sire genetic trends were negative and significant for all traits, except for LPWY. Dam genetic trends were positive and significant for all traits. Sow genetic trends were mostly positive and significant only for LPWY and LBWY. Improvement of LPL and lifetime production efficiency traits will require these traits to be included in the selection indexes used to choose replacement boars and gilts in this population.

The objective of this research was to estimate genetic parameters and trends for length of productive life (LPL), lifetime number of piglets born alive (LBA), lifetime number of piglets weaned (LPW), lifetime litter birth weight (LBW), and lifetime litter weaning weight (LWW) in a commercial swine farm in Northern Thailand. Data were gathered during a 24-year period from July 1989 to August 2013. A total of 3,109 phenotypic records from 2,271 Landrace (L) and 838 Yorkshire sows (Y) were analyzed. Variance and covariance components, heritabilities and correlations were estimated using an Average Information Restricted Maximum Likelihood (AIREML) procedure. The 5-trait animal model contained the fixed effects of first farrowing year-season, breed group, and age at first farrowing. Random effects were sow and residual. Estimates of heritabilities were medium for all five traits (0.17±0.04 for LPL and LBA to 0.20±0.04 for LPW). Genetic correlations among these traits were high, positive, and favorable (p

In this paper, decision theory was used to derive Bayes and minimax decision rules to estimate allelic frequencies and to explore their admissibility. Decision rules with uniformly smallest risk usually do not exist and one approach to solve this problem is to use the Bayes principle and the minimax principle to find decision rules satisfying some general optimality criterion based on their risk functions. Two cases were considered, the simpler case of biallelic loci and the more complex case of multiallelic loci. For each locus, the sampling model was a multinomial distribution and the prior was a Beta (biallelic case) or a Dirichlet (multiallelic case) distribution. Three loss functions were considered: squared error loss (SEL), Kulback-Leibler loss (KLL) and quadratic error loss (QEL). Bayes estimators were derived under these three loss functions and were subsequently used to find minimax estimators using results from decision theory. The Bayes estimators obtained from SEL and KLL turned out to be the same. Under certain conditions, the Bayes estimator derived from QEL led to an admissible minimax estimator (which was also equal to the maximum likelihood estimator). The SEL also allowed finding admissible minimax estimators. Some estimators had uniformly smaller variance than the MLE and under suitable conditions the remaining estimators also satisfied this property. In addition to their statistical properties, the estimators derived here allow variation in allelic frequencies, which is closer to the reality of finite populations exposed to evolutionary forces., Comment: 36 pages, 3 figures

Cow and calf genetic and environmental factors were evaluated for their association with ELISA scores for paratuberculosis in a multibreed population of beef cattle. The ELISA scores are a measure of the presence or absence of antibodies against Mycobacterium avium subsp. paratuberculosis in bovine serum. The linear mixed-model analysis used 352 ELISA scores from 238 cows: 51 Angus (A); 34 Brahman (B); 41 (3/4 A 1/4 B); 45 (1/2 A 1/2 B); 34 (1/4 A 3/4 B); and 33 Brangus (5/8 A 3/8 B). Cows were assumed to be unrelated. Year affected (P < 0.001) ELISA scores, but age of cow did not, which was expected to be significant because of the chronic progressive nature of this disease. Important regressions on fixed effects associated with cows were 1) a positive estimate of cow B breed effect (0.59 +/- 0.24; P < 0.017), indicating an upward trend of ELISA scores toward 100% B cows; 2) a negative estimate for weight change from before calving (late November) to the date of the blood sample in May (-0.0062 +/- 0.0019 score/kg; P < 0.002), indicating that poorer maintenance of cow weights was associated with higher ELISA scores; and 3) a positive estimate for days in lactation of cow on the date of the blood sample (0.0086 +/- 0.0034 score/d; P < 0.021), indicating the production of larger amounts of antibodies against Mycobacterium avium subsp. paratuberculosis as lactation progressed. Relevant regressions on fixed effects associated with calves were 1) calf birth weight (-0.022 +/- 0.010 score/kg; P < 0.035), and 2) calf gain from birth to the date of the cow blood sample (-0.0092 +/- 0.0027 score/kg; P < 0.001). These estimates indicate that cows that produced lighter calves at birth and/or calves with slower preweaning growth tended to have greater ELISA scores. Although the sensitivity (percentage of infected animals detected) of ELISA was only 50%, these results suggest that subclinical paratuberculosis may be negatively affecting cows and their offspring. Factors identified as associated with ELISA scores could help producers with culling decisions related to paratuberculosis control and eradication in beef cattle.

The objective of the study was to examine the effect of Brahman genetics on collagen enzymatic crosslinking gene expression and meat tenderness. Steers were randomly selected to represent a high percentage Brahman genetics (n = 13), Half-Blood genetics (n = 13), Brangus genetics (n = 13), and a high percentage Angus genetics (n = 13). Muscle samples from the Longissimus lumborum muscle were collected at weaning and harvest and reverse transcription quantitative PCR (qPCR) analysis was conducted to measure the mRNA expression of lysyl oxidase (LOX), bone morphogenetic protein 1 (BMP1), and cystatin C (CYS). Steaks from subject animals were collected at harvest, aged for 14 d and subjected to collagen analysis, Warner-Bratzler Shear Force (WBS) and trained sensory panel analysis (tenderness, juiciness, and connective tissue). Data indicated that Half-Blood and Brahman steers had greater (P0.05) WBS values and tended to receive decreased (P0.06) panel tenderness scores than Angus and Brangus steers. Panelists tended to detect more connective tissue in Brahman and Half-Blood steaks when compared to Angus and Brangus steaks (P0.07). Crosslinking gene expression data revealed that at weaning Half-Blood steers had more (P0.05) mRNA expression of CYS and LOX than Angus and Brangus steers. At weaning and harvest, all genetic groups had similar mRNA expression of BMP1 (P0.10). At harvest, Brangus and Angus steers had greater LOX mRNA expression than Brahman cattle (P0.05). Pearson's correlation coefficients indicated that only weaning CYS mRNA expression was correlated to WBS, panel tenderness and connective tissue scores (P0.05). Expression of LOX was only correlated to these measures at harvest, and BMP1 was correlated to these traits at both time periods (P0.05). These results indicate that collagen crosslinking enzyme activity, as indicated by mRNA levels, early in an animal's life may account for some of the variation seen in steak tenderness due to Brahman genetic influence.

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 (interactibi-lidades) 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 enlre r97ty 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 período postdestete. Estos resultados indican que animales Sanmartinero fueron competitivos con animales Cebú para caracteres de crecimiento y demostraron excelente habilidad combinatoria interracial bajo Ias condiciones de nutrición y manejo del Centro de Investigación La Libertad.

Se obtuvieron predicciones de efectos genéticos aditivos y no aditivos para peso al destete en un rebaño Angus x Brahman usando un procedimiento de evaluación animal multirracial incluyendo un macromineral en la evaluación. Se encontraron cambios en las predicciones de efectos genéticos cuando se incluyó calcio, fósforo o magnesio sérico. La exactitud en las predicciones de los efectos genéticos aditivos y no aditivos fue mayor o igual a la reportada cuando se realizó el análisis de peso solamente. Las correlaciones entre las predicciones de valores genéticos aditivos basados en un análisis simple, y aquellos obtenidos cuando se incluyó un macromineral fueron altas (P >.96). Para los efectos genéticos no aditivos, las correlaciones fluctuaron entre .65 y .99. Por lo tanto, el uso de caracteres genéticamente relacionados con el crecimiento que pueden ser medidos al mismo tiempo que los pesos, pueden mejorar la exactitud de las predicciones genéticas del peso.

Colombia posee siete razas de bovinos criollos adaptadas a las condiciones tropicales; el número total de animales puros es menor de 18.000, aunque si se consideran los animales criollos cruzados, dicho censo asciende a 50.000 animales aproximadamente. El Proyecto de Desarrollo Ganadero de 1986 sugirió aumentar su número y desarrollar planes de mejoramiento a nivel de finca. Estos objetivos se pueden lograr mediante un programa de evaluación genética nacional que incluya todas las razas criollas y sus cruces. El presente artículo presenta las estructuras básicas de las poblaciones y de los datos, a partir de los cuales es posible realizar una evaluación genética nacional, la cual se analiza en términos de la actual situación colombiana. Se discuten además, métodos lineales y procedimientos computacionales unirraciales y multirraciales para su manejo, y se sugiere el uso de programas de computación. Así mismo, se plantea una estrategia general para desarrollar dicho Programa Nacional de Evaluación Genética, enfatizando en algunos aspectos específicos desde el punto de vista colombiano. La implementación de dicho programa beneficiaría la conservación y el desarrollo de las razas criollas y de sus cruces, además de servir como modelo para desarrollar de manera sistemática la evaluación genética de los bovinos colombianos.

We used actual and adjusted weights to 120 d and 210 d of age of 72,731 male and female Nellore calves born in 40 PMGRN - Nellore Brazil herds from 1985 to 2005 aiming to compare the effect of different definitions of contemporary groups on estimates of (co)variance and genetic parameters. Four models, each one with a different structure of contemporary group ( CG ), were compared using the Akaike Information Criterion (AIC), the Bayesian Information Criterion (BIC), and the Consistent Akaike Information Criterion (CAIC). (Co)variance estimates were obtained using a derivative-free restricted maximum likelihood procedure. Estimates of (co)variances and genetic parameters were similar for the four models considered. However, the BIC and CAIC indicated that the most appropriate model for this Nellore population was the one that considered CG to be random, and sex of calf to be fixed and separate from CG , in which CG was defined as the group of calves born in the same herd, year, season of birth (trimester), and undergone the same management. KEYWORDS: beef cattle; contemporary groups; information criteria.

Controlling the prevalence of Escherichia coli O157 in cattle at the pre-harvest level is critical to reduce outbreaks of this pathogen in humans. Multilayers of factors including the environmental and bacterial factors modulate the colonization and persistence of E. coli O157 in cattle that serve as a reservoir of this pathogen. Here, we report animal factors contributing to the prevalence of E. coli O157 in cattle. We observe the lowest number of E. coli O157 in Brahman breed when compared with other crosses in an Angus-Brahman multibreed herd, and bulls excrete more E. coli O157 than steers in the pens where cattle were housed together. The presence of super-shedders, cattle excreting >10(5) CFU/rectal anal swab, increases the concentration of E. coli O157 in the pens; thereby super-shedders enhance transmission of this pathogen among cattle. Molecular subtyping analysis reveal only one subtype of E. coli O157 in the multibreed herd, indicating the variance in the levels of E. coli O157 in cattle is influenced by animal factors. Furthermore, strain tracking after relocation of the cattle to a commercial feedlot reveals farm-to-farm transmission of E. coli O157, likely via super-shedders. Our results reveal high risk factors in the prevalence of E. coli O157 in cattle whereby animal genetic and physiological factors influence whether this pathogen can persist in cattle at high concentration, providing insights to intervene this pathogen at the pre-harvest level.

Somatic cells count (SCC), milk yield (MY) and pedigree information of 2,791 first lactation cows that calved between 1990 and 2010 on 259 Thai farms were used to estimate genetic parameters and trends for SCC and its genetic association with MY. The SCC were log-transformed (lnSCC) to make them normally distributed. An average information-restricted maximum likelihood procedure was used to estimate variance components. A bivariate animal model that considered herd-yr-season, calving age, and regression additive genetic group as fixed effects, and animal and residual as random effects was used for genetic evaluation. Heritability estimates were 0.12 (SE = 0.19) for lnSCC, and 0.31 (SE = 0.06) for MY. The genetic correlation estimate between lnSCC and MY was 0.26 (SE = 0.59). Mean yearly estimated breeding values during the last 20 years increased for SCC (49.02 cells/ml/yr, SE = 26.81 cells/ml/yr; p = 0.08), but not for MY (0.37 kg/yr, SE = 0.87 kg/yr; p = 0.68). Sire average breeding values for SCC and MY were higher than those of cows and dams (p