Partitioning among-animal variance of energy utilization in lactating Jersey cows.

Animals vary in the way in which they utilize energy due to diet, genetics, and management. Energy consumed by the animal supports milk production, but considerable variation among-animals in energy utilization is thought to exist. The study objective was to estimate the among-animal variance in energy utilization in data collected from Jersey cows using indirect calorimetry. Individual animal-period data from 15 studies (n = 560) were used. The data set included 115 animals from 44 to 410 DIM producing 11.5 to 39.1 kg/d of milk. On average, the 63 treatments in the data set ranged 14.8 to 19.5% CP, 21.4 to 43.0% NDF, 16.2 to 33.3% starch, and 2.21 to 6.44% crude fat. Data were analyzed with the Glimmix procedure of SAS (9.4) with random effects of cow, treatment nested within period, square, and experiment. The percentage of among-animal, dietary treatment, and experimental variance was calculated as the variance associated with each fraction divided by the sum of variance from animal, dietary treatment, experiment, and residual which was considered the total variance. The percentage of among-animal variance was characterized as high or low when the value was greater than or less than the mean value of 29.2%. Among-animal variance explained approximately 29.3 - 42.5% of the total variance in DM intake (DMI), gross energy (GE), digestible energy (DE), metabolizable energy (ME), and net energy of lactation (NEL) in Mcal/d. When energetic components of feces, urine, and heat in Mcal/d were expressed per unit of DMI the among-animal variance decreased by 20.4, 4.82, and 9.55% units, respectively. However, among-animal variance explained 4.80, 8.78, and 5.02% units more of the total variation for methane energy, lactation energy, and tissue energy in Mcal/d when expressed per unit of DMI. Variance in energetic efficiencies of DE/GE, ME/GE, and ME/DE were explained to a lesser extent by among-animal variance (averaging 17.8 ± 1.95%). The among-animal contribution to total variance in milk energy was 28.8%. Milk energy was a large proportion of the energy efficiency calculation which included milk energy plus corrected tissue energy over net energy intake which likely contributed to the 22.2% of total among-animal variance in energy efficiency. Results indicate that among-animal variance explains a large proportion of the total variation in DMI. This contributes to the variance observed for energy fractions as well as energy components when expressed in Mcal/d. Variation in energetic loss associated with methane was primarily explained by differences among-animals and was increased when expressed per unit of DMI highlighting the role of inherent animal differences in these losses.

Animal board invited review: Practical applications of genomic information in livestock.

Access to high-dimensional genomic information in many livestock species is accelerating. This has been greatly aided not only by continual reductions in genotyping costs but also an expansion in the services available that leverage genomic information to create a greater return-on-investment. Genomic information on individual animals has many uses including (1) parentage verification and discovery, (2) traceability, (3) karyotyping, (4) sex determination, (5) reporting and monitoring of mutations conferring major effects or congenital defects, (6) better estimating inbreeding of individuals and coancestry among individuals, (7) mating advice, (8) determining breed composition, (9) enabling precision management, and (10) genomic evaluations; genomic evaluations exploit genome-wide genotype information to improve the accuracy of predicting an animal's (and by extension its progeny's) genetic merit. Genomic data also provide a huge resource for research, albeit the outcome from this research, if successful, should eventually be realised through one of the ten applications already mentioned. The process for generating a genotype all the way from sample procurement to identifying erroneous genotypes is described, as are the steps that should be considered when developing a bespoke genotyping panel for practical application.

A genome-wide association study for gestation length in swine.

Selection for increased litter size in swine has potentially resulted in a correlated increase in preweaning mortality. Additional selection criteria should be considered when selecting for increased litter size to account for associated decreases in piglet quality, specifically piglet survival, initial weight and growth. Traits such as gestation length (GL), which have been associated with piglet performance, could be utilized to improve piglet development and survivability. The objective of this study was to conduct a genome-wide association study to identify genomic regions associated with GL in differing parities in swine (n = 831) from the University of Nebraska-Lincoln reproductive longevity project. Gestation length was calculated as the number of days between last insemination administered and farrowing. Sows were genotyped with the Illumina SNP60 BeadArray, and the data were analyzed using Bayesian mixture models for GL at parity 1, 2, 3 and 4 (GL1, GL2, GL3 and GL4 respectively). Means (SD) for GL1-GL4 were 113 (1.4), 114 (1.2), 114 (1.3) and 115 (1.2) respectively. Posterior mean heritability estimates (PSD) for GL1, GL2, GL3 and GL4 were 0.33 (0.06), 0.34 (0.07), 0.32 (0.08) and 0.20 (0.08) respectively. Rank correlations between genomic estimated breeding values between GL1 and GL2, GL3 and GL4 respectively were moderate: 0.67, 0.65 and 0.60. The top SNP (ASGA0017859, SSC4, 7.8 Mb), located in the top common genomic region associated with GL1, GL2 and GL3, was associated with a difference of 1.1 days in GL1 between homozygote genotypes (P < 0.0001). The results of this study suggest that GL is a largely polygenic trait with relatively minor contributions from multiple genomic regions.

Estimates of genomic heritability and genome-wide association study for fatty acids profile in Santa Inês sheep.

BACKGROUND: Despite the health concerns and nutritional importance of fatty acids, there is a relative paucity of studies in the literature that report genetic or genomic parameters, especially in the case of sheep populations. To investigate the genetic architecture of fatty acid composition of sheep, we conducted genome-wide association studies (GWAS) and estimated genomic heritabilities for fatty acid profile in Longissimus dorsi muscle of 216 male sheep. RESULTS: Genomic heritability estimates for fatty acid content ranged from 0.25 to 0.46, indicating that substantial genetic variation exists for the evaluated traits. Therefore, it is possible to alter fatty acid profiles through selection. Twenty-seven genomic regions of 10 adjacent SNPs associated with fatty acids composition were identified on chromosomes 1, 2, 3, 5, 8, 12, 14, 15, 16, 17, and 18, each explaining ≥0.30% of the additive genetic variance. Twenty-three genes supporting the understanding of genetic mechanisms of fat composition in sheep were identified in these regions, such as DGAT2, TRHDE, TPH2, ME1, C6, C7, UBE3D, PARP14, and MRPS30. CONCLUSIONS: Estimates of genomic heritabilities and elucidating important genomic regions can contribute to a better understanding of the genetic control of fatty acid deposition and improve the selection strategies to enhance meat quality and health attributes.

Genome-wide association study of Stayability and Heifer Pregnancy in Red Angus cattle.

Reproductive performance is the most important component of cattle production from the standpoint of economic sustainability of commercial beef enterprises. Heifer Pregnancy (HPG) and Stayability (STAY) genetic predictions are 2 selection tools published by the Red Angus Association of America (RAAA) to assist with improvements in reproductive performance. Given the importance of HPG and STAY to the profitability of commercial beef enterprises, the objective of this study was to identify QTL associated with both HPG and STAY in Red Angus cattle. A genome-wide association study (GWAS) was performed using deregressed HPG and STAY EBV, calculated using a single-trait animal model and a 3-generation pedigree with data from the Spring 2015 RAAA National Cattle Evaluation. Each individual animal possessed 74,659 SNP genotypes. Individual animals with a deregressed EBV reliability > 0.05 were merged with the genotype file and marker quality control was performed. Criteria for sifting genotypes consisted of removing those markers where any of the following were found: average call rate less than 0.85, minor allele frequency < 0.01, lack of Hardy-Weinberg equilibrium (P < 0.0001), or extreme linkage disequilibrium (r2 > 0.99). These criteria resulted in 2,664 animals with 62,807 SNP available for GWAS. Association studies were performed using a Bayes Cπ model in the BOLT software package. Marker significance was calculated as the posterior probability of inclusion (PPI), or the number of instances a specific marker was sampled divided by the total number of samples retained from the Markov chain Monte Carlo chains. Nine markers, with a PPI ≥ 3% were identified as QTL associated with HPG on BTA 1, 11, 13, 23, and 29. Twelve markers, with a PPI ≥ 75% were identified as QTL associated with STAY on BTA 6, 8, 9, 12, 15, 18, 22, and 23.

GENOMICS SYMPOSIUM: Using genomic approaches to uncover sources of variation in age at puberty and reproductive longevity in sows.

Genetic variants associated with traits such as age at puberty and litter size could provide insight into the underlying genetic sources of variation impacting sow reproductive longevity and productivity. Genomewide characterization and gene expression profiling were used using gilts from the University of Nebraska-Lincoln swine resource population ( = 1,644) to identify genetic variants associated with age at puberty and litter size traits. From all reproductive traits studied, the largest fraction of phenotypic variation explained by the Porcine SNP60 BeadArray was for age at puberty (27.3%). In an evaluation data set, the predictive ability of all SNP from high-ranked 1-Mb windows (1 to 50%), based on genetic variance explained in training, was greater (12.3 to 36.8%) compared with the most informative SNP from these windows (6.5 to 23.7%). In the integrated data set ( = 1,644), the top 1% of the 1-Mb windows explained 6.7% of the genetic variation of age at puberty. One of the high-ranked windows detected (SSC2, 12-12.9 Mb) showed pleiotropic features, affecting both age at puberty and litter size traits. The RNA sequencing of the hypothalami arcuate nucleus uncovered 17 differentially expressed genes (adjusted < 0.05) between gilts that became pubertal early (<155 d of age) and late (>180 d of age). Twelve of the differentially expressed genes are upregulated in the late pubertal gilts. One of these genes is involved in energy homeostasis (), a function in which the arcuate nucleus plays an important contribution, linking nutrition with reproductive development. Energy restriction during the gilt development period delayed age at puberty by 7 d but increased the probability of a sow to produce up to 3 parities ( < 0.05). Identification of pleotropic functional polymorphisms may improve accuracy of genomic prediction while facilitating a reduction in sow replacement rates and addressing welfare concerns.

The impact of training strategies on the accuracy of genomic predictors in United States Red Angus cattle.

Genomic selection (GS) has become an integral part of genetic evaluation methodology and has been applied to all major livestock species, including beef and dairy cattle, pigs, and chickens. Significant contributions in increased accuracy of selection decisions have been clearly illustrated in dairy cattle after practical application of GS. In the majority of U.S. beef cattle breeds, similar efforts have also been made to increase the accuracy of genetic merit estimates through the inclusion of genomic information into routine genetic evaluations using a variety of methods. However, prediction accuracies can vary relative to panel density, the number of folds used for folds cross-validation, and the choice of dependent variables (e.g., EBV, deregressed EBV, adjusted phenotypes). The aim of this study was to evaluate the accuracy of genomic predictors for Red Angus beef cattle with different strategies used in training and evaluation. The reference population consisted of 9,776 Red Angus animals whose genotypes were imputed to 2 medium-density panels consisting of over 50,000 (50K) and approximately 80,000 (80K) SNP. Using the imputed panels, we determined the influence of marker density, exclusion (deregressed EPD adjusting for parental information [DEPD-PA]) or inclusion (deregressed EPD without adjusting for parental information [DEPD]) of parental information in the deregressed EPD used as the dependent variable, and the number of clusters used to partition training animals (3, 5, or 10). A BayesC model with π set to 0.99 was used to predict molecular breeding values (MBV) for 13 traits for which EPD existed. The prediction accuracies were measured as genetic correlations between MBV and weighted deregressed EPD. The average accuracies across all traits were 0.540 and 0.552 when using the 50K and 80K SNP panels, respectively, and 0.538, 0.541, and 0.561 when using 3, 5, and 10 folds, respectively, for cross-validation. Using DEPD-PA as the response variable resulted in higher accuracies of MBV than those obtained by DEPD for growth and carcass traits. When DEPD were used as the response variable, accuracies were greater for threshold traits and those that are sex limited, likely due to the fact that these traits suffer from a lack of information content and excluding animals in training with only parental information substantially decreases the training population size. It is recommended that the contribution of parental average to deregressed EPD should be removed in the construction of genomic prediction equations. The difference in terms of prediction accuracies between the 2 SNP panels or the number of folds compared herein was negligible.

Economic selection index development for Beefmaster cattle II: General-purpose breeding objective.

An economic selection index was developed for Beefmaster cattle in a general-purpose production system in which bulls are mated to a combination of heifers and mature cows, with resulting progeny retained as replacements or sold at weaning. National average prices from 2010 to 2014 were used to establish income and expenses for the system. Genetic parameters were obtained from the literature. Economic values were estimated by simulating 100,000 animals and approximating the partial derivatives of the profit function by perturbing traits 1 at a time, by 1 unit, while holding the other traits constant at their respective means. Relative economic values for the objective traits calving difficultly direct (CDd), calving difficulty maternal (CDm), weaning weight direct (WWd), weaning weight maternal (WWm), mature cow weight (MW), and heifer pregnancy (HP) were -2.11, -1.53, 18.49, 11.28, -33.46, and 1.19, respectively. Consequently, under the scenario assumed herein, the greatest improvements in profitability could be made by decreasing maintenance energy costs associated with MW followed by improvements in weaning weight. The accuracy of the index lies between 0.218 (phenotypic-based index selection) and 0.428 (breeding values known without error). Implementation of this index would facilitate genetic improvement and increase profitability of Beefmaster cattle operations with a general-purpose breeding objective when replacement females are retained and with weaned calves as the sale end point.

Economic selection index development for Beefmaster cattle I: Terminal breeding objective.

The objective of this study was to develop an economic selection index for Beefmaster cattle in a terminal production system where bulls are mated to mature cows with all resulting progeny harvested. National average prices from 2010 to 2014 were used to establish income and expenses for the system. Phenotypic and genetic parameter values among the selection criteria and goal traits were obtained from literature. Economic values were estimated by simulating 100,000 animals and approximating the partial derivatives of the profit function by perturbing traits one at a time, by 1 unit, while holding the other traits constant at their respective means. Relative economic values (REV) for the terminal objective traits HCW, marbling score (MS), ribeye area (REA), 12th-rib fat (FAT), and feed intake (FI) were 91.29, 17.01, 8.38, -7.07, and -29.66, respectively. Consequently, improving the efficiency of beef production is expected to impact profitability greater than improving carcass merit alone. The accuracy of the index lies between 0.338 (phenotypic selection) and 0.503 (breeding values known without error). The application of this index would aid Beefmaster breeders in their sire selection decisions, facilitating genetic improvement for a terminal breeding objective.

Breed effects and genetic parameter estimates for calving difficulty and birth weight in a multibreed population.

Birth weight (BWT) and calving difficulty (CD) were recorded on 4,579 first-parity females from the Germplasm Evaluation Program at the U.S. Meat Animal Research Center (USMARC). Both traits were analyzed using a bivariate animal model with direct and maternal effects. Calving difficulty was transformed from the USMARC scores to corresponding -scores from the standard normal distribution based on the incidence rate of the USMARC scores. Breed fraction covariates were included to estimate breed differences. Heritability estimates (SE) for BWT direct, CD direct, BWT maternal, and CD maternal were 0.34 (0.10), 0.29 (0.10), 0.15 (0.08), and 0.13 (0.08), respectively. Calving difficulty direct breed effects deviated from Angus ranged from -0.13 to 0.77 and maternal breed effects deviated from Angus ranged from -0.27 to 0.36. Hereford-, Angus-, Gelbvieh-, and Brangus-sired calves would be the least likely to require assistance at birth, whereas Chiangus-, Charolais-, and Limousin-sired calves would be the most likely to require assistance at birth. Maternal breed effects for CD were least for Simmental and Charolais and greatest for Red Angus and Chiangus. Results showed that the diverse biological types of cattle have different effects on both BWT and CD. Furthermore, results provide a mechanism whereby beef cattle producers can compare EBV for CD direct and maternal arising from disjoined and breed-specific genetic evaluations.

Genetic parameters for docility, weaning weight, yearling weight, and intramuscular fat percentage in Hereford cattle.

Cattle behavior, including measures of docility, is important to beef cattle producers not only from a human safety perspective but also due to potential correlations to economically relevant traits. Field data from the American Hereford Association was used to estimate genetic parameters for chute score (CS; = 25,037), weaning weight (WW; = 24,908), yearling weight (YW; = 23,978), and intramuscular fat percentage (IMF; = 12,566). Single-trait and bivariate animal models were used to estimate heritabilities and genetic correlations. All models included fixed effects of sex and contemporary group, defined as herd-year-season, and direct genetic and residual components were included as random effects. For CS and WW, additional random effects of maternal genetic and maternal permanent environment were also fitted. For CS, WW, YW, and IMF, heritability estimates were 0.27 ± 0.02, 0.35 ± 0.03, 0.36 ± 0.02, and 0.27 ± 0.02, respectively. Genetic correlations between CS and WW, CS and YW, CS and IMF, WW and YW, WW and IMF, and YW and IMF were -0.12 ± 0.06, -0.10 ± 0.05, -0.08 ± 0.06, 0.47 ± 0.05, -0.19 ± 0.09, and -0.41 ± 0.05, respectively. Heritability estimates for all traits suggest that they would respond favorably to selection and that selection for increased WW or YW could decrease marbling. Genetic correlations between CS and WW, YW, and IMF were all favorable but weak, suggesting that selection for improved docility will not have negative consequences on growth or carcass quality. Furthermore, maternal additive and maternal permanent environmental variances for CS were near 0, suggesting that their inclusion in National Cattle Evaluations is not warranted.

Effects of shade and feeding zilpaterol hydrochloride to finishing steers on performance, carcass quality, heat stress, mobility, and body temperature.

Steers ( = 480; 22% with black hides and 78% with red hides) were used to study the effects of shade and feeding zilpaterol hydrochloride (ZH) on performance, carcass quality, heat stress, mobility, and body temperature (BT). A randomized block design with a 2 × 2 factorial treatment arrangement was used with 4 replicates per treatment. Factors included housing type (open or shaded pens) and the feeding of ZH (0 or 8.33 mg/kg DM) the last 21 d on feed with a 3-d withdrawal. Cattle were blocked by BW into a heavy or light block and randomly assigned to pen within each block. Rumen boluses to record BT were inserted before ZH feeding. Respiration rate and panting scores were recorded daily during the ZH feeding period. Mobility scores were collected at various time points from before ZH feeding through harvest. Interactions between ZH and housing type were not significant ( > 0.26) for animal performance, carcass characteristics, and respiration or panting score. No differences ( > 0.44) were observed for DMI, ADG, or G:F on a live basis due to ZH; however, cattle fed in open pens tended ( = 0.08) to have a greater ADG than cattle in shaded pens. Cattle fed ZH had 14 kg heavier carcasses with larger LM area ( < 0.01) than control cattle. Respiration rates for cattle fed ZH were greater ( = 0.05) with no differences ( = 0.88) due to housing. Time affected ( < 0.01) mobility scores, with observations on the morning of harvest at the abattoir being the worst for all groups of cattle. An interaction ( < 0.01) was observed between ZH and housing type for BT. Cattle fed ZH, in both shaded and open pens, had lower ( < 0.05) average, maximum, and area under the curve BT than control cattle fed in the same housing type. However, the observed reduction in BT due to ZH was greater for cattle fed ZH in open pens than for cattle fed ZH in shaded pens. From these results, we conclude that ZH improved HCW with little impact on heat stress or mobility, suggesting that animal welfare was not affected by feeding ZH for 21 d at the end of the feeding period.

Evaluation of reduced subsets of single nucleotide polymorphisms for the prediction of age at puberty in sows.

Genomic information could be used efficiently to improve traits that are expensive to measure, sex limited or expressed late in life. This study analyzed the phenotypic variation explained by major SNPs and windows for age at puberty in gilts, an indicator of reproductive longevity. A genome-wide association study using 56, 424 SNPs explained 25.2% of the phenotypic variation in age at puberty in a training set (n = 820). All SNPs from the top 10% of 1-Mb windows explained 33.5% of the phenotypic variance compared to 47.1% explained by the most informative markers (n = 261). In an evaluation population, consisting of subsequent batches (n = 412), the predictive ability of all SNPs from the major 1-Mb windows was higher compared to the variance captured by the most informative SNP from each of these windows. The phenotypic variance explained in the evaluation population varied from 12.3% to 36.8% when all SNPs from major windows were used compared to 6.5-23.7% explained by most informative SNPs. The correlation between phenotype and genomic prediction values based on SNP effects estimated in the training population was marginal compared to their effects retrained in the evaluation population for all (0.46-0.81) or most informative SNPs (0.30-0.65) from major windows. An increase in genetic gain of 20.5% could be obtained if genomic selection included both sexes compared to females alone. The pleiotropic role of major genes such as AVPR1A could be exploited in selection of both age at puberty and reproductive longevity.

Estimation of breed-specific heterosis effects for birth, weaning, and yearling weight in cattle.

Heterosis, assumed proportional to expected breed heterozygosity, was calculated for 6834 individuals with birth, weaning and yearling weight records from Cycle VII and advanced generations of the U.S. Meat Animal Research Center (USMARC) Germplasm Evaluation (GPE) project. Breeds represented in these data included: Angus, Hereford, Red Angus, Charolais, Gelbvieh, Simmental, Limousin and Composite MARC III. Heterosis was further estimated by proportions of British × British (B × B), British × Continental (B × C) and Continental × Continental (C × C) crosses and by breed-specific combinations. Model 1 fitted fixed covariates for heterosis within biological types while Model 2 fitted random breed-specific combinations nested within the fixed biological type covariates. Direct heritability estimates (SE) for birth, weaning ,and yearling weight for Model 1 were 0.42 (0.04), 0.22 (0.03), and 0.39 (0.05), respectively. The direct heritability estimates (SE) of birth, weaning, and yearling weight for Model 2 were the same as Model 1, except yearling weight heritability was 0.38 (0.05). The B × B, B × C, and C × C heterosis estimates for birth weight were 0.47 (0.37), 0.75 (0.32), and 0.73 (0.54) kg, respectively. The B × B, B × C, and C × C heterosis estimates for weaning weight were 6.43 (1.80), 8.65 (1.54), and 5.86 (2.57) kg, respectively. Yearling weight estimates for B × B, B × C, and C × C heterosis were 17.59(3.06), 13.88 (2.63), and 9.12 (4.34) kg, respectively. Differences did exist among estimates of breed-specific heterosis for weaning and yearling weight, although the variance component associated with breed-specific heterosis was not significant. These results illustrate that there are differences in breed-specific heterosis and exploiting these differences can lead to varying levels of heterosis among mating plans.

Genome wide association study of cholesterol and poly- and monounsaturated fatty acids, protein, and mineral content of beef from crossbred cattle.

The objectives were to determine the variation explained by the BovineSNP50v2 BeadChip for cholesterol (CH), polyunsaturated fatty acids (PUFA), monounsaturated fatty acids (MUFA), protein, and minerals in beef cattle, and to identify chromosomal regions that harbor major allelic variants underlying the variation of these traits. Crossbred steers and heifers (n=236) segregating at the inactive myostatin allele on BTA2 were harvested and steaks were sampled from the M. semitendinosus and the M. longissimus thoracis et lumborum for nutrient analysis. A Bayes C algorithm was employed in genome-wide association analysis. The resulting posterior heritability (SD) estimates ranged from 0.43 (0.10) to 0.71 (0.08) for lipid traits and 0.05 (0.08) to 0.75 (0.06) for mineral traits. Across cuts, correlations between genomic estimated breeding values (GEBV) were similar for CH, MUFA and PUFA. The top 0.5% 1-Mb windows for all traits explained up to 9.93% of the SNP variance. Slight differences did exist between cuts and between different measurement scales of fatty acids.

The effect of myostatin genotype on body temperature during extreme temperature events.

Extreme heat and cold events can create deleterious physiological changes in cattle as they attempt to cope. The genetic background of animals can influence their response to these events. The objective of the current study was to determine the impact of myostatin genotype (MG) on body temperature during periods of heat and cold stress. Two groups of crossbred steers and heifers of unknown pedigree and breed fraction with varying percentages of Angus, Simmental, and Piedmontese were placed in a feedlot over 2 summers and 2 winters. Before arrival, animals were genotyped for the Piedmontese-derived myostatin mutation (C313Y) to determine their MG as either homozygous normal (0 copy; n = 84), heterozygous (1 copy; n = 96), or homozygous for inactive myostatin (2 copy; n = 59). Hourly tympanic and vaginal temperature measurements were collected for steers and heifers, respectively, for 5 d during times of anticipated heat and cold stress. Mean (±SD) ambient temperature for summer and winter stress events were 24.4 (±4.64) and -1.80 (±11.71), respectively. A trigonometric function (sine + cosine) with periods of 12 and 24 h was used to describe the diurnal cyclical pattern. Hourly body temperature was analyzed within a season, and fixed effects included MG, group, trigonometric functions nested within group, and interaction of MG with trigonometric functions nested within group; random effects were animal and residual (Model [I]). A combined analysis of season and group was also investigated with the inclusion of season as a main effect and the nesting of effects within both group and season (Model [C]). In both models, the residual was fitted using an autoregressive covariance structure. A 3-way interaction of MG, season, and trigonometric function periodicities of 24 h (P < 0.001) and 12 h (P < 0.02) for Model [C] indicate that a genotype × environment interaction exists for MG. For MG during summer stress events the additive estimate was 0.10°C (P < 0.01) and dominance estimate was -0.12°C (P < 0.001). During winter stress events the additive estimate was 0.10°C (P < 0.001) and dominance estimate was 0.054°C (P > 0.05). The current study illustrated that a genotype × environment interaction exists for MG and 1-copy animals were more robust to environmental extremes in comparison with 0- or 2-copy animals.

Genome-wide prediction of age at puberty and reproductive longevity in sows.

Traditional selection for sow reproductive longevity is ineffective due to low heritability and late expression of the trait. Incorporation of DNA markers into selection programs is potentially a more practical approach for improving sow lifetime productivity. Using a resource population of crossbred gilts, we explored pleiotropic sources of variation that influence age at puberty and reproductive longevity. Of the traits recorded before breeding, only age at puberty significantly affected the probability that females would produce a first parity litter. The genetic variance explained by 1-Mb windows of the sow genome, compared across traits, uncovered regions that influence both age at puberty and lifetime number of parities. Allelic variants of SNPs located on SSC5 (27-28 Mb), SSC8 (36-37 Mb) and SSC12 (1.2-2 Mb) exhibited additive effects and were associated with both early expression of puberty and a greater than average number of lifetime parities. Combined analysis of these SNPs showed that an increase in the number of favorable alleles had positive impact on reproductive longevity, increasing number of parities by up to 1.36. The region located on SSC5 harbors non-synonymous alleles in the arginine vasopressin receptor 1A (AVPR1A) gene, a G-protein-coupled receptor associated with social and reproductive behaviors in voles and humans and a candidate for the observed effects. This region is characterized by high levels of linkage disequilibrium in different lines and could be exploited in marker-assisted selection programs across populations to increase sow reproductive longevity.

Ant colony optimization as a method for strategic genotype sampling.

A simulation study was carried out to develop an alternative method of selecting animals to be genotyped. Simulated pedigrees included 5000 animals, each assigned genotypes for a bi-allelic single nucleotide polymorphism (SNP) based on assumed allelic frequencies of 0.7/0.3 and 0.5/0.5. In addition to simulated pedigrees, two beef cattle pedigrees, one from field data and the other from a research population, were used to test selected methods using simulated genotypes. The proposed method of ant colony optimization (ACO) was evaluated based on the number of alleles correctly assigned to ungenotyped animals (AK(P)), the probability of assigning true alleles (AK(G)) and the probability of correctly assigning genotypes (APTG). The proposed animal selection method of ant colony optimization was compared to selection using the diagonal elements of the inverse of the relationship matrix (A(-1)). Comparisons of these two methods showed that ACO yielded an increase in AK(P) ranging from 4.98% to 5.16% and an increase in APTG from 1.6% to 1.8% using simulated pedigrees. Gains in field data and research pedigrees were slightly lower. These results suggest that ACO can provide a better genotyping strategy, when compared to A(-1), with different pedigree sizes and structures.

Different methods of selecting animals for genotyping to maximize the amount of genetic information known in the population.

It is possible to predict genotypes of some individuals based on genotypes of relatives. Different methods of sampling individuals to be genotyped from populations were evaluated using simulation. Simulated pedigrees included 5,000 animals and were assigned genotypes based on assumed allelic frequencies for a SNP (favorable/unfavorable) of 0.3/0.7, 0.5/0.5, and 0.8/0.2. A field data pedigree (29,101 animals) and a research pedigree (8,688 animals) were used to test selected methods using simulated genotypes with allelic frequencies of 0.3/0.7 and 0.5/0.5. For the simulated pedigrees, known and unknown allelic frequencies were assumed. The methods used included random sampling, selection of males, and selection of both sexes based on the diagonal element of the inverse of the relationship matrix (A(-1)) and absorption of either the A or A(-1) matrix. For random sampling, scenarios included selection of 5 and 15% of the animals, and all other methods presented concentrated on the selection of 5% of the animals for genotyping. The methods were evaluated based on the percentage of alleles correctly assigned after peeling (AK(P)), the probability of assigning true alleles (AK(G)), and the average probability of correctly assigning the true genotype. As expected, random sampling was the least desirable method. The most desirable method in the simulated pedigrees was selecting both males and females based on their diagonal element of A(-1). Increases in AK(P) and AK(G) ranged from 26.58 to 29.11% and 2.76 to 6.08%, respectively, when males and females (equal to 5% of all animals) were selected based on their diagonal element of A(-1) compared with selecting 15% of the animals at random. In the case of a real beef cattle pedigree, selection of males only or males and females yielded similar results and both selection methods were superior to random selection.

Combining genetic test information and correlated phenotypic records for breeding value estimation.

The use of marker assisted selection in the beef cattle industry to date has involved using traditional EPD in tandem with molecular test information. In the current study, a multiple-trait simulation was carried out to create a beef cattle data set using genetic parameter estimates from the literature to identify the best procedure for combining both sources of information and to assess the added benefit of the procedure. To reach these objectives, the following simulation/ analysis steps were implemented: (1) varying percentages (100, 5, or 0) of available records for the trait of interest, (2) varying percentages (100, 50, 25, or 0) of animals with molecular information, (3) scenarios where the favorable (F) or the unfavorable (U) allele was more frequent, and (4) analysis of the response due to selection over 5 generations. The data sets included 3 correlated traits in which 2 of them, birth weight and postweaning gain, had complete recording and the availability of records for the third trait (marbling score) varied. It was further assumed that molecular information was available for the third trait for a causative gene that explained 10% of the genetic variation. Estimates of Pearson correlations between true and predicted breeding values for marbling score declined as the amount of information declined, and instances in which the molecular information was recorded were always closer to the true values than in the case in which the molecular information was absent. When the U allele was more frequent, rank correlation estimates were increased among top sires, low accuracy sires, and high accuracy sires by approximately 24.9, 12.1, and 4.7% with limited marbling score records and complete genotyping compared with limited marbling score records and no genotyping. Similar results were seen when the F allele was more frequent. When there was a complete absence of recording for the trait of interest, the same trends in correlations were observed and were lower than when the trait of interest was recorded. Jointly considering molecular and phenotypic information showed a greater long-term response compared with tandem selection, showing that discrimination of candidates for selection based solely on molecular information is not optimal.