BIBI: Bayesian inference of breed composition.

The aim of this paper was to develop statistical models to estimate individual breed composition based on the previously proposed idea of regressing discrete random variables corresponding to counts of reference alleles of biallelic molecular markers located across the genome on the allele frequencies of each marker in the pure (base) breeds. Some of the existing regression-based methods do not guarantee that estimators of breed composition will lie in the appropriate parameter space, and none of them account for uncertainty about allele frequencies in the pure breeds, that is, uncertainty about the design matrix. To overcome these limitations, we proposed two Bayesian generalized linear models. For each individual, both models assume that the counts of the reference allele at each marker locus follow independent Binomial distributions, use the logit link and pose a Dirichlet prior over the vector of regression coefficients (which corresponds to breed composition). This prior guarantees that point estimators of breed composition such as the posterior mean pertain to the appropriate space. The difference between these models is that model termed BIBI does not account for uncertainty about the design matrix, while model termed BIBI2 accounts for such an uncertainty by assigning independent Beta priors to the entries of this matrix. We implemented these models in a data set from the University of Florida's multibreed Angus-Brahman population. Posterior means were used as point estimators of breed composition. In addition, the ordinary least squares estimator proposed by Kuehn et al. () (OLSK) was also computed. BIBI and BIBI2 estimated breed composition more accurately than OLSK, and BIBI2 had a 7.69% improvement in accuracy as compared to BIBI.

Gaussian covariance graph models accounting for correlated marker effects in genome-wide prediction.

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.

Effect of Brahman genetics on myofibrillar protein degradation, collagen crosslinking, and tenderness of the longissimus lumborum.

The objective of this study was to examine the effect of percent Brahman genetics on Warner-Bratzler shear force (WBSF), desmin and troponin-T (TnT) degradation, hydroxylysyl pyridinoline (HP) crosslink content, and perimysial collagen melting temperature. Steers ( = 131) produced in 2012 and 2013 were harvested at 1.27 cm of visual s.c. back fat thickness. Steers were divided into 4 genetic categories consisting of steers that contained 6/32 or less Brahman genetics, 12/32 Brahman genetics, 14/32 to 18/32 Brahman genetics, and 23/32 to 32/32 Brahman genetics. Twenty-four hours after harvest, a 7.62-cm piece of the longissimus lumborum beginning at the 13th rib was collected and aged for 14 d. Following aging, three 2.54-cm steaks were cut for WBSF, trained sensory panel, and laboratory analyses. Laboratory analyses steaks were used to determine protein degradation, HP crosslink analysis, and perimysial collagen melting temperature. Data were analyzed using a polynomial regression for unequally spaced treatments. As the percent Brahman genetics increased, WBSF increased (linear, = 0.01). As percent Brahman genetics increased, tenderness score decreased (less tender) and connective tissue score increased (more connective tissue; linear, = 0.01). As the percentage of Brahman genetics increased, the amount of degraded desmin (38 kDa) and TnT (34 and 30 kDa) decreased (linear, < 0.03) whereas the amount of immunoreactive 36 kDa TnT increased (linear, = 0.04). Percent Brahman genetics had no effect ( = 0.14) on HP crosslink content but did tend to increase ( = 0.07) perimysial collagen melting temperature as the percent Brahman increased. The percentage of Brahman genetic influence was positively correlated to WBSF ( = 0.25), 36 kDa immunoreactive TnT ( = 0.26), and perimysial collagen melting temperature ( = 0.25, = 0.01). Sensory panel tenderness ( = -0.44), juiciness ( = -0.26), and connective tissue scores ( = -0.63); 38 kDa degraded desmin ( = -0.34), 34 ( = -0.36) and 30 kDa degraded TnT ( = -0.29); and HP collagen crosslinks ( = -0.20) were negatively correlated to percent Brahman genetic influence ( < 0.03). Increasing Brahman genetic influence in steers negatively affects tenderness, partially through a reduction in degradation of desmin and TnT. Although HP collagen crosslinks are unaffected by Brahman genetics, a tendency for increased perimysium melting temperature indicates that other collagen-stabilizing crosslinks may be affected.

Stochastic dynamic simulation modeling including multitrait genetics to estimate genetic, technical, and financial consequences of dairy farm reproduction and selection strategies.

The objective of this study was to develop a daily stochastic dynamic dairy simulation model that included multitrait genetics and to evaluate the effects of reduced genetic models and various reproduction and selection strategies on the genetic, technical, and financial performance of a dairy herd. The 12 correlated genetic traits included in the 2014 lifetime net merit (NM$) index were modeled for each animal. For each animal, a true breeding value (TBV) for each trait was calculated as the average of the sire's and dam's TBV, plus a fraction of the inbreeding and Mendelian sampling variability. Similarly, an environmental component for each trait was calculated and was partitioned into a permanent and a daily (temporary) effect. The combined TBV and environmental effects were converted into the phenotypic performance of each animal. Hence, genetics and phenotypic performances were associated. Estimated breeding values (EBV) were also simulated. Genetic trends for each trait for the service sire were based on expected trends in US Holsteins. Surplus heifers were culled based on various ranking criteria to maintain a herd size of 1,000 milking cows. In the first 8 scenarios, culling of surplus heifers was either random or based on the EBV of NM$. Four different genetic models, depending on the presence or absence of genetic trends or genetic and environmental correlations, or both, were evaluated to measure the effect of excluding multitrait genetics on animal performance. In the last 5 scenarios, the full genetic model was used and culling of surplus heifers was either random or based on the EBV of NM$ or the EBV of milk. Sexed semen use and reliability of the EBV were also varied. Each scenario was simulated for 15yr into the future. Results showed that genetic models without all 12 genetic trends and genetic and environmental correlations provided biased estimates of the genetic, technical, and financial performance of the dairy herd. Average TBV of NM$ of all cows in the herd was $263 greater in yr 15 in a scenario that combined sexed semen use in heifers and culling of surplus heifers with the lowest EBV of NM$, compared with a scenario that used only conventional semen and surplus heifers were culled randomly. The average TBV of daughter pregnancy rate of all cows in the herd was 1.25 percentage points greater in yr 15 in a scenario that combined using sexed semen in heifers as well as culling of surplus heifers ranked by EBV of NM$, compared with a scenario using conventional semen only as well as culling surplus heifers ranked by EBV of milk. In conclusion, the multitrait genetics model resulted in improved estimates of genetic, technical, and financial effects and appears useful to evaluate consequences of various reproduction and selection strategies within a dairy farm.

Single nucleotide polymorphisms associated with carcass traits in a population of Brahman and Brahman-influenced steers.

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.

Effect of Brahman genetic influence on collagen enzymatic crosslinking gene expression and meat tenderness.

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 (P<0.05) WBS values and tended to receive decreased (P < 0.06) 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 (P < 0.07). Crosslinking gene expression data revealed that at weaning Half-Blood steers had more (P < 0.05) mRNA expression of CYS and LOX than Angus and Brangus steers. At weaning and harvest, all genetic groups had similar mRNA expression of BMP1 (P > 0.10). At harvest, Brangus and Angus steers had greater LOX mRNA expression than Brahman cattle (P < 0.05). Pearson's correlation coefficients indicated that only weaning CYS mRNA expression was correlated to WBS, panel tenderness and connective tissue scores (P < 0.05). Expression of LOX was only correlated to these measures at harvest, and BMP1 was correlated to these traits at both time periods (P < 0.05). 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.

Subspecies differences in early fetal development and plasma pregnancy-associated glycoprotein concentrations in cattle.

Inclusion of Bos indicus genetics improves production traits of cattle maintained in hot climates. Limited information exists detailing pregnancy-specific events as influenced by variable amounts of Bos indicus genetics. Three experiments were completed to examine the effect of Bos taurus and Bos indicus genotypes on fetal size and plasma pregnancy-associated glycoprotein (PAG) concentrations. In all experiments, cows were bred by AI after synchronization of ovulation. Fetal measurements were completed by transrectal ultrasonography and plasma PAG concentrations 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 pregnancy 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 compared with cows containing <80% Angus influence (3.40 ± 0.28 vs. 2.86 ± 0.28 cm crown-rump length; P < 0.01). Plasma PAG concentrations were reduced (P < 0.01) in 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.

Genomic-polygenic evaluation of Angus-Brahman multibreed cattle for feed efficiency and postweaning growth using the Illumina 3K chip.

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.

Carcass and meat palatability breed differences and heterosis effects in an Angus-Brahman multibreed population.

Additive genetic Angus-Brahman differences, heterosis effects, and least squares means for six carcass and six meat palatability traits were estimated using data from 1367 steers from the Angus-Brahman multibreed herd of the University of Florida collected from 1989 to 2009. Brahman carcasses had higher dressing percent (P<0.0001), lower marbling (P<0.0001), smaller ribeye area (P<0.0001), and less fat over the ribeye (P<0.0001) than Angus carcasses. Brahman beef was less tender (P<0.0001), had more connective tissue (P<0.0001), and it was less juicy (P<0.001) than Angus beef. Heterosis increased hot carcass weight (P<0.0001), dressing percent (P<0.017), ribeye area (P<0.0001), fat over the ribeye (P<0.0001), and kidney, pelvic, and heart fat (P<0.01) in Angus-Brahman crossbred steers. Results indicated that crossbred animals with up to 50% Brahman showed limited negative impact on meat quality while maximizing meat yield due to heterosis.

Somatic Cells Count and Its Genetic Association with Milk Yield in Dairy Cattle Raised under Thai Tropical Environmental Conditions.

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<0.01). Heritability estimates for lnSCC and MY and their low but positive genetic correlation suggested that selection for low SCC may be feasible in this population as it is in other populations of dairy cows. Thus, selection for high MY and low SCC should be encouraged in Thai dairy improvement programs to increase profitability by improving both cow health and milk yield.

Estimation of genetic parameters for mature weight in Angus cattle.

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.

Effect of breed composition on phenotypic residual feed intake and growth in Angus, Brahman, and Angus x Brahman crossbred cattle.

The influence of additive and nonadditive genetic effects and temperament on 4 postweaning feed intake and growth traits was evaluated in a group of 581 bull, heifer, and steer calves born in 3 Florida herds in 2006 and 2007. Calves had breed compositions ranging from 100% Angus (A) to 100% Brahman (B). They were randomly allocated to 24 pens each year by herd (Brooksville, Gainesville, Marianna, FL), sire group (A, 3/4 A 1/4 B, Brangus, 1/2 A 1/2 B, 1/4 A 3/4 B, and B), and sex (bull, heifer, and steer) in a GrowSafe automated feeding facility at Marianna. Calves were fed a concentrate diet during the 21-d adjustment and the 70-d trial periods. Individual feed intakes were recorded daily, and BW, chute scores, and exit velocities were recorded every 2 wk. Traits were phenotypic daily residual feed intake (RFI), mean daily feed intake (DFI), mean daily feed conversion ratio (FCR), and postweaning BW gain. Phenotypic RFI was computed as the difference between actual and expected feed intakes. Calves were assigned to 3 RFI groups: high (RFI greater than 0.9 kg of DM/d), low (RFI less than -0.9 kg of DM/d), and medium (RFI between mean +/- 0.9 kg of DM/d; SD = 1.8 kg of DM/d). The mixed model included the fixed effects of contemporary group (herd-year-pen), RFI group (except when trait was RFI), age of dam, sex of calf, age of calf, B fraction of calf, heterozygosity of calf, mean chute score, and mean exit velocity. Brahman fraction and heterozygosity of calf were nested within sex of calf for RFI and within RFI group for DFI, FCR, and postweaning BW gain. Random effects were sire and residual. Feed efficiency tended to improve (decreased RFI) as the B fraction increased. However, calves required larger amounts of feed per kilogram of BW gain (larger FCR) as the B fraction increased. Postweaning BW gain tended to decrease as the B fraction increased. Temperament traits were unimportant for all traits except exit velocity for DFI, suggesting perhaps a lack of variation for temperament traits in this herd, or that calves became accustomed to the level of handling pre- and postweaning, thus decreasing behavioral differences among them.

Association between cow reproduction and calf growth traits and ELISA scores for paratuberculosis in a multibreed herd of beef cattle.

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.

Record keeping, genetic selection, educational experience and farm management effects on average milk yield per cow, milk fat percentage, bacterial score and bulk tank somatic cell count of dairy farms in the Central region of Thailand.

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.

Promoter region of the bovine growth hormone receptor gene: single nucleotide polymorphism discovery in cattle and association with performance in Brangus bulls.

Expression of the GH receptor (GHR) gene and its binding with GH is essential for growth and fat metabolism. A GT microsatellite exists in the promoter of bovine GHR segregating short (11 bp) and long (16 to 20 bp) allele sequences. To detect SNP and complete an association study of genotype to phenotype, we resequenced a 1,195-bp fragment of DNA including the GT microsatellite and exon 1A. Resequencing was completed in 48 familialy unrelated Holstein, Jersey, Brown Swiss, Simmental, Angus, Brahman, and Brangus cattle. Nine SNP were identified. Phylogeny analyses revealed minor distance (i.e., <5%) in DNA sequence among the 5 Bos taurus breeds; however, sequence from Brahman cattle averaged 27.4 +/- 0.07% divergence from the Bos taurus breeds, whereas divergence of Brangus was intermediate. An association study of genotype to phenotype was completed with data from growing Brangus bulls (n = 553 from 96 sires) and data from 4 of the SNP flanking the GT microsatellite. These SNP were found to be in Hardy-Weinberg equilibrium and in phase based on linkage disequilibrium analyses (r(2) = 0.84 and D'= 0.92). An A/G tag SNP was identified (ss86273136) and was located in exon 1A, which began 88 bp downstream from the GT microsatellite. Minor allele frequency of the tag SNP was greater than 10%, and Mendelian segregation was verified in 3 generation pedigrees. The A allele was derived from Brahman, and the G allele was derived from Angus. This tag SNP genotype was a significant effect in analyses of rib fat data collected with ultrasound when bulls were ~365 d of age. Specifically, bulls of the GG genotype had 6.1% more (P = 0.0204) rib fat than bulls of the AA and AG genotypes, respectively. Tag SNP (ss86273136), located in the promoter of GHR, appears to be associated with a measure of corporal fat in Bos taurus x Bos indicus composite cattle.

A survey of decision making practices, educational experiences, and economic performance of two dairy farm populations in Central Thailand.

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.

Comparison of two milk pricing systems and their effect on milk price and milk revenue of dairy farms in the Central region of 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.

Factors affecting milk yield, milk fat, bacterial score, and bulk tank somatic cell count of dairy farms in the central region of Thailand.

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<0.05) in winter and lower in the summer and rainy seasons. In addition, the majority of small size farms had higher (p<0.05) AYC and milk fat values, and lower bacterial score and BTSCC values than medium and large size farms.

Factors associated with ELISA scores for paratuberculosis in an Angus-Brahman multibreed herd of beef cattle.

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.

Genetic parameters and trends in the Chilean multibreed dairy cattle population.

Estimates of additive and nonadditive multibreed co-variance components, genetic parameters, and predicted genetic values for first lactation 305-d mature equivalent (ME) milk yield, fat yield, and protein yield were computed using data from a sample of 3316 cows from the Chilean Holstein-other breeds multibreed population. Variances and covariances were estimated by 2-trait REML analyses using a Generalized Expectation-Maximization algorithm applied to multibreed populations. Multiple estimates of additive genetic, nonadditive genetic, and environmental variances from 2-trait analyses were averaged to yield a single variance estimate for each trait and effect. Heritabilities were moderate for all traits in Holstein, other, and Holstein x other crossbred groups. Interbreed interactibilities (ratio of nonadditive genetic to phenotypic variances) were all near zero. Multibreed additive, nonadditive, and total genetic trends were estimated using the complete dataset (56,277 cows). Upward trends between 1990 and 2000 existed for all traits, genetic effects, and breed groups, except for 305-d ME protein yield in 1/4 Holstein, indicating that Chilean dairy producers were successful in choosing progressively better semen and sires from imported and local sources over time.