Search

The objective of this study was to identify genomic regions and candidate genes associated with feed efficiency in lactating Holstein cows. In total, 4,916 cows with actual or imputed genotypes for 60,671 single nucleotide polymorphisms having individual feed intake, milk yield, milk composition, and body weight records were used in this study. Cows were from research herds located in the United States, Canada, the Netherlands, and the United Kingdom. Feed efficiency, defined as residual feed intake (RFI), was calculated within location as the residual of the regression of dry matter intake (DMI) on milk energy (MilkE), metabolic body weight (MBW), change in body weight, and systematic effects. For RFI, DMI, MilkE, and MBW, bivariate analyses were performed considering each trait as a separate trait within parity group to estimate variance components and genetic correlations between them. Animal relationships were established using a genomic relationship matrix. Genome-wide association studies were performed separately by parity group for RFI, DMI, MilkE, and MBW using the Bayes B method with a prior assumption that 1% of single nucleotide polymorphisms have a nonzero effect. One-megabase windows with greatest percentage of the total genetic variation explained by the markers (TGVM) were identified, and adjacent windows with large proportion of the TGVM were combined and reanalyzed. Heritability estimates for RFI were 0.14 (±0.03; ±SE) in primiparous cows and 0.13 (±0.03) in multiparous cows. Genetic correlations between primiparous and multiparous cows were 0.76 for RFI, 0.78 for DMI, 0.92 for MBW, and 0.61 for MilkE. No single 1-Mb window explained a significant proportion of the TGVM for RFI; however, after combining windows, significance was met on Bos taurus autosome 27 in primiparous cows, and nearly reached on Bos taurus autosome 4 in multiparous cows. Among other genes, these regions contain β-3 adrenergic receptor and the physiological candidate gene, leptin, respectively. Between the 2 parity groups, 3 of the 10 windows with the largest effects on DMI neighbored windows affecting RFI, but were not in the top 10 regions for MilkE or MBW. This result suggests a genetic basis for feed intake that is unrelated to energy consumption required for milk production or expected maintenance as determined by MBW. In conclusion, feed efficiency measured as RFI is a polygenic trait exhibiting a dynamic genetic basis and genetic variation distinct from that underlying expected maintenance requirements and milk energy output.

Proper regulation of lipid metabolism is critical for preventing the development of metabolic diseases. It is clear that leptin plays a critical role in the regulation of energy homeostasis by regulating energy intake. However, leptin can also regulate energy homeostasis by inducing lipolysis in adipocytes, but it is unclear how the major lipases are involved in leptin-stimulated lipolysis. Therefore, the objectives of this study were to determine if (1) leptin acts directly to induce lipolysis in bovine adipocytes, (2) the potential lipases involved in leptin-induced lipolysis in bovine adipocytes, and (3) increases translocation of adipose triglyceride lipase (ATGL) and hormone sensitive lipase (HSL) during leptin-stimulated lipolysis in bovine stromal vascular cell-derived adipocytes. As hypothesized, leptin induced a lipolytic response (P = 0.02) in isolated adipocytes which was accompanied by an increase in phosphorylation of signal transducer and activator of transcription (STAT)3 (P = 0.03), a well-documented secondary messenger of leptin, and ATGL protein abundance (P0.01). Protein abundance of STAT3, perilipin, HSL, and phosphorylation of HSL by PKA and AMPK were not altered during leptin-stimulated lipolysis (P0.05). Immunostaining techniques were employed to determine the location of HSL and ATGL. Both lipases translocated to the lipid droplet after 2 h of exposure to isoproterenol (P0.02). However, only ATGL was translocated to the lipid droplet during leptin-stimulated lipolysis (P = 0.04), indicating ATGL may be the active lipase in leptin-stimulated lipolysis. In summary, leptin stimulates lipolysis in bovine adipocytes. The lack of phosphorylated HSL and translocation of HSL to the lipid droplet during leptin-stimulated lipolysis suggest minimal activity by PKA. Interestingly, leptin-stimulated lipolysis is accompanied by an increase in ATGL protein abundance and translocation to the lipid droplet, indicating its involvement in leptin-stimulated lipolysis either due to an increase in protein abundance or through a novel lipolytic cascade.

Feed efficiency (FE), characterized as the fraction of feed nutrients converted into salable milk or meat, is of increasing economic importance in the dairy industry. We conjecture that FE is a complex trait whose variation and relationships or partial efficiencies (PE) involving the conversion of dry matter intake to milk energy and metabolic body weight may be highly heterogeneous across environments or management scenarios. In this study, a hierarchical Bayesian multivariate mixed model was proposed to jointly infer upon such heterogeneity at both genetic and nongenetic levels on PE and variance components (VC). The heterogeneity was modeled by embedding mixed effects specifications on PE and VC in addition to those directly specified on the component traits. We validated the model by simulation and applied it to a joint analysis of a dairy FE consortium data set with 5,088 Holstein cows from 13 research stations in Canada, the Netherlands, the United Kingdom, and the United States. Although no differences were detected among research stations for PE at the genetic level, some evidence was found of heterogeneity in residual PE. Furthermore, substantial heterogeneity in VC across stations, parities, and ration was observed with heritability estimates of FE ranging from 0.16 to 0.46 across stations.

Feed efficiency, as defined by the fraction of feed energy or dry matter captured in products, has more than doubled for the US dairy industry in the past 100 yr. This increased feed efficiency was the result of increased milk production per cow achieved through genetic selection, nutrition, and management with the desired goal being greater profitability. With increased milk production per cow, more feed is consumed per cow, but a greater portion of the feed is partitioned toward milk instead of maintenance and body growth. This dilution of maintenance has been the overwhelming driver of enhanced feed efficiency in the past, but its effect diminishes with each successive increment in production relative to body size and therefore will be less important in the future. Instead, we must also focus on new ways to enhance digestive and metabolic efficiency. One way to examine variation in efficiency among animals is residual feed intake (RFI), a measure of efficiency that is independent of the dilution of maintenance. Cows that convert feed gross energy to net energy more efficiently or have lower maintenance requirements than expected based on body weight use less feed than expected and thus have negative RFI. Cows with low RFI likely digest and metabolize nutrients more efficiently and should have overall greater efficiency and profitability if they are also healthy, fertile, and produce at a high multiple of maintenance. Genomic technologies will help to identify these animals for selection programs. Nutrition and management also will continue to play a major role in farm-level feed efficiency. Management practices such as grouping and total mixed ration feeding have improved rumen function and therefore efficiency, but they have also decreased our attention on individual cow needs. Nutritional grouping is key to helping each cow reach its genetic potential. Perhaps new computer-driven technologies, combined with genomics, will enable us to optimize management for each individual cow within a herd, or to optimize animal selection to match management environments. In the future, availability of feed resources may shift as competition for land increases. New approaches combining genetic, nutrition, and other management practices will help optimize feed efficiency, profitability, and environmental sustainability.

To include feed-intake-related traits in the breeding goal, accurate estimates of genetic parameters of feed intake, and its correlations with other related traits (i.e., production, conformation) are required to compare different options. However, the correlations between feed intake and conformation traits can vary depending on the population. Therefore, the objective was to estimate genetic correlations between 6 feed-intake-related traits and 7 conformation traits within dairy cattle from 2 countries, the Netherlands (NL) and the United States (US). The feed-intake-related traits were dry matter intake (DMI), residual feed intake (RFI), milk energy output (MilkE), milk yield (MY), body weight (BW), and metabolic body weight (MBW). The conformation traits were stature (ST), chest width (CW), body depth (BD), angularity (ANG), rump angle (RA), rump width (RW), and body condition score (BCS). Feed intake data were available for 1,665 cows in NL and for 1,920 cows in US, from 83 nutritional experiments (48 in NL and 35 in US) conducted between 1991 and 2011 in NL and between 2007 and 2013 in US. Additional conformation records from relatives of the animals with DMI records were added to the database, giving a total of 37,241 cows in NL and 28,809 in US with conformation trait information. Genetic parameters were estimated using bivariate animal model analyses. The model included the following fixed effects for feed-intake-related traits: location by experiment-ration, age of cow at calving modeled with a second order polynomial by parity class, location by year-season, and days in milk, and these fixed effects for the conformation traits: herd by classification date, age of cow at classification, and lactation stage at classification. Both models included additive genetic and residual random effects. The highest estimated genetic correlations involving DMI were with CW in both countries (NL = 0.45 and US = 0.61), followed by ST (NL = 0.33 and US = 0.57), BD (NL = 0.26 and US = 0.49), and BCS (NL = 0.24 and US = 0.46). The MilkE and MY were moderately correlated with ANG in both countries (0.33 and 0.47 in NL, and 0.36 and 0.48 in US). Finally, BW was highly correlated with CW (0.77 in NL and 0.84 in US) and with BCS (0.83 in NL and 0.85 in US). Feed-intake-related traits were moderately to highly genetically correlated with conformation traits (ST, CW, BD, and BCS) in both countries, making them potentially useful as predictors of DMI.

Heat stress (HS) affects numerous physiological processes including nutrient partitioning and lipid metabolism. Objectives of this study were to evaluate how acute HS affects lipid metabolism in subcutaneous adipose tissue of dairy cattle. Adipose tissue biopsies were performed on Holstein cows for bovine primary adipocyte isolation and cultured at either 42°C (HS) or 37°C (thermal neutral, TN). Adipocytes were incubated with increasing isoproterenol (ISO), and with increasing concentrations of insulin in the presence of ISO to evaluate changes in lipolysis. Incorporation of radioactive acetate into lipids was measured as an indicator of lipogenesis. Abundance and phosphorylation of several lipolytic and lipogenic proteins were also measured. Adipocytes exposed to HS had an elevated maximal response to ISO and were more sensitive to lipolytic stimulation by ISO compared with cells cultured at TN. Thermal treatment did not affect the antilipolytic effects of insulin in the presence of ISO. Lipogenesis measured as acetate incorporation was not altered by HS, but a temperature by insulin interaction was observed for the regulation of acetyl CoA carboxylase, such that the presence of insulin resulted in a reduction in phosphorylation of acetyl CoA carboxylase in adipocytes cultured at TN but not HS conditions. Results of this study demonstrate that acute HS has a direct effect on the regulation of lipolysis and the rate-limiting enzyme of lipogenesis in isolated bovine adipocytes.

Genome-wide association (GWA) of feed efficiency (FE) could help target important genomic regions influencing FE. Data provided by an international dairy FE research consortium consisted of phenotypic records on dry matter intakes (DMI), milk energy (MILKE), and metabolic body weight (MBW) on 6,937 cows from 16 stations in 4 counties. Of these cows, 4,916 had genotypes on 57,347 single nucleotide polymorphism (SNP) markers. We compared a GWA analysis based on the more classical residual feed intake (RFI) model with one based on a previously proposed multiple trait (MT) approach for modeling FE using an alternative measure (DMI|MILKE,MBW). Both models were based on a single-step genomic BLUP procedure that allowed the use of phenotypes from both genotyped and nongenotyped cows. Estimated effects for single SNP markers were small and not statistically important but virtually identical for either FE measure (RFI vs. DMI|MILKE,MBW). However, upon further refining this analysis to develop joint tests within nonoverlapping 1-Mb windows, significant associations were detected between either measure of FE with a window on each of Bos taurus autosomes BTA12 and BTA26. There was, as expected, no overlap between detected genomic regions for DMI|MILKE,MBW and genomic regions influencing the energy sink traits (i.e., MILKE and MBW) because of orthogonal relationships clearly defined between the various traits. Conversely, GWA inferences on DMI can be demonstrated to be partly driven by genetic associations between DMI with these same energy sink traits, thereby having clear implications when comparing GWA studies on DMI to GWA studies on FE-like measures such as RFI.

Feed efficiency is an economically important trait in the beef and dairy cattle industries. Residual feed intake (RFI) is a measure of partial efficiency that is independent of production level per unit of body weight. The objective of this study was to identify significant associations between single nucleotide polymorphism (SNP) markers and RFI in dairy cattle using the Random Forests (RF) algorithm. Genomic data included 42,275 SNP genotypes for 395 Holstein cows, whereas phenotypic measurements were daily RFI from 50 to 150 d postpartum. Residual feed intake was defined as the difference between an animal's feed intake and the average intake of its cohort, after adjustment for year and season of calving, year and season of measurement, age at calving nested within parity, days in milk, milk yield, body weight, and body weight change. Random Forests is a widely used machine-learning algorithm that has been applied to classification and regression problems. By analyzing the tree structures produced within RF, the 25 most frequent pairwise SNP interactions were reported as possible epistatic interactions. The importance scores that are generated by RF take into account both main effects of variables and interactions between variables, and the most negative value of all importance scores can be used as the cutoff level for declaring SNP effects as significant. Ranking by importance scores, 188 SNP surpassed the threshold, among which 38 SNP were mapped to RFI quantitative trait loci (QTL) regions reported in a previous study in beef cattle, and 2 SNP were also detected by a genome-wide association study in beef cattle. The ratio of number of SNP located in RFI QTL to the total number of SNP in the top 188 SNP chosen by RF was significantly higher than in all 42,275 whole-genome markers. Pathway analysis indicated that many of the top 188 SNP are in genomic regions that contain annotated genes with biological functions that may influence RFI. Frequently occurring ancestor-descendant SNP pairs can be explored as possible epistatic effects for further study. The importance scores generated by RF can be used effectively to identify large additive or epistatic SNP and informative QTL. The consistency in results of our study and previous studies in beef cattle indicates that the genetic architecture of RFI in dairy cattle might be similar to that of beef cattle.

Feed efficiency in dairy cattle has gained much attention recently. Due to the cost-prohibitive measurement of individual feed intakes, combining data from multiple countries is often necessary to ensure an adequate reference population. It may then be essential to model genetic heterogeneity when making inferences about feed efficiency or selecting efficient cattle using genomic information. In this study, we constructed a marker x environment interaction model that decomposed marker effects into main effects and interaction components that were specific to each environment. We compared environment-specific variance component estimates and prediction accuracies from the interaction model analyses, an across-environment analyses ignoring population stratification, and a within-environment analyses using an international feed efficiency data set. Phenotypes included residual feed intake, dry matter intake, net energy in milk, and metabolic body weight from 3,656 cows measured in 3 broadly defined environments: North America (NAM), the Netherlands (NLD), and Scotland (SAC). Genotypic data included 57,574 single nucleotide polymorphisms per animal. The interaction model gave the highest prediction accuracy for metabolic body weight, which had the largest estimated heritabilities ranging from 0.37 to 0.55. The within environment model performed the best when predicting residual feed intake, which had the lowest estimated heritabilities ranging from 0.13 to 0.41. For traits (dry matter intake and net energy in milk) with intermediate estimated heritabilities (0.21 to 0.50 and 0.17 to 0.53, respectively), performance of the 3 models was comparable. Genomic correlations between environments also were computed using variance component estimates from the interaction model. Averaged across all traits, genomic correlations were highest between NAM and NLD, and lowest between NAM and SAC. In conclusion, the interaction model provided a novel way to evaluate traits measured in multiple environments in which genetic heterogeneity may exist. This model allowed estimation of environment-specific parameters and provided genomic predictions that approached or exceeded the accuracy of competing within- or across environment models. Agriculture and Food Research Initiative Competitive Grants from the USDA National Institute of Food and Agriculture (Washington, DC) [2008-35205-18711, 2011-68004-30340]; Hatch grant from the Wisconsin Agricultural Experiment Station (Madison, WI) [MSN139239]; National Association of Animal Breeders (Columbia, MO) This project was supported by Agriculture and Food Research Initiative Competitive Grants no. 2008-35205-18711 and 2011-68004-30340 from the USDA National Institute of Food and Agriculture (Washington, DC). Support from Hatch grant no. MSN139239 from the Wisconsin Agricultural Experiment Station (Madison, WI) is acknowledged, and K. A. Weigel acknowledges partial financial support from the National Association of Animal Breeders (Columbia, MO). Public domain – authored by a U.S. government employee

Dairy cows often experience negative energy balance with the onset of lactation, and severe or prolonged negative energy balance can contribute to declines in overall fitness. Energy stores, in the form of adipose tissue triacylglycerides, are mobilized during times of energy deficit, and recent research has implicated several proteins associated with the lipid droplet as lipolytic regulators. The objective of this study was to determine if these novel proteins associated with lipolytic regulation are altered with the changing metabolic demands of lactation. Weekly blood samples were collected from 26 Holstein cows from 21 d before expected parturition through 28 d postpartum, and again at 150 d postpartum. Serum nonesterified fatty acids, glycerol, and β-hydroxybutyrate were measured. Energy balance was calculated from daily feed intake and milk yield, weekly body weight, and monthly milk component measurements. Adipose tissue biopsies were taken 21 d before expected parturition (-21 d) and at 5, 21, and 150 d postpartum. Semiquantitative Western blotting was used to measure abundance of hormone-sensitive lipase (HSL), phosphorylated HSL, perilipin, phosphorylated perilipin (PPLIN), adipose triglyceride lipase (ATGL), and comparative gene identity-58 (CGI-58). Abundance of ATGL was less at 5 and 21 d in milk (DIM) compared with -21 and 150 DIM, even though cows were in negative energy balance and experiencing increased rates of lipolysis in early lactation. In contrast, phosphorylated HSL and PPLIN increased with increasing lipolysis immediately after parturition. Additionally, PPLIN was negatively correlated with milk yield at 5, 21, and 150 d postpartum, and negatively correlated with feed intake and energy balance at 21 d postpartum. This result is consistent with the hypothesis that phosphorylation of perilipin is responsive to signals for increased triaclyglyceride mobilization. Finally, a consistent negative correlation between abundance of perilipin and CGI-58 proteins was observed throughout the transition period. These results confirm that novel lipolytic proteins in adipose tissue are regulated at the level of protein abundance and phosphorylation during the periparturient period and into mid lactation.

Pyruvate carboxylase (PC) catalyzes a pivotal reaction in gluconeogenesis and lipid metabolism in liver. In bovine the PC gene is expressed as six 5' untranslated region (UTR) mRNA variants. The objectives for this study were to clone and sequence the bovine PC gene, determine the intron and exon organization and identify PC promoter region(s). Oligonucleotide sequences that corresponded to the 5' UTR mRNA variants and coding sequence of bovine PC were used to isolate 2 clones from the RPCI-42 bovine bacterial artificial chromosome (BAC) library. Sequencing data confirmed the presence of regions for the 5' UTR for bovine PC mRNA. The exon arrangement from 5' to 3' is 48 (exon I), 41 (exon II), 178 (exon IIIA and IIIB), and 185 (exon IV) bp. Three promoter regions, P3, P2, and P1, adjacent to exon I, II, and IIIA, respectively, were identified based on computer analysis of sequence data. Putative promoters were cloned into a firefly luciferase vector and transiently transfected into H4IIE rat hepatoma cells. All PC promoters demonstrated luciferase activity comparable with the minimal promoter luciferase vector and higher than the promoterless luciferase vector. In addition, PC promoter 1 exhibited greater luciferase activity compared with PC promoter 2 or 3. These data provide information about the arrangement of the 4 bovine PC 5' UTR exons, the identity of the promoter regions for the bovine PC gene, and indicate differences in relative basal activity of the promoter regions.

Genetic improvement of feed efficiency (FE) in dairy cattle requires greater attention given increasingly important resource constraint issues. A widely accepted yet occasionally contested measure of FE in dairy cattle is residual feed intake (RFI). The use of RFI is limiting for several reasons, including interpretation, differences in recording frequencies between the various component traits that define RFI, and potential differences in genetic versus nongenetic relationships between dry matter intake (DMI) and FE component traits. Hence, analyses focusing on DMI as the response are often preferred. We propose an alternative multiple-trait (MT) modeling strategy that exploits the Cholesky decomposition to provide a potentially more robust measure of FE. We demonstrate that our proposed FE measure is identical to RFI provided that genetic and nongenetic relationships between DMI and component traits of FE are identical. We assessed both approaches (MT and RFI) by simulation as well as by application to 26,383 weekly records from 50 to 200 d in milk on 2,470 cows from a dairy FE consortium study involving 7 institutions. Although the proposed MT model fared better than the RFI model when simulated genetic and nongenetic associations between DMI and FE component traits were substantially different from each other, no meaningful differences were found in predictive performance between the 2 models when applied to the consortium data.

Prior to genomic selection on a trait, a reference population needs to be established to link marker genotypes with phenotypes. For costly and difficult-to-measure traits, international collaboration and sharing of data between disciplines may be necessary. Our aim was to characterize the combining of data from nutrition studies carried out under similar climate and management conditions to estimate genetic parameters for feed efficiency. Furthermore, we postulated that data from the experimental cohorts within these studies can be used to estimate the net energy of lactation (NE L ) densities of diets, which can provide estimates of energy intakes for use in the calculation of the feed efficiency metric, residual feed intake (RFI), and potentially reduce the effect of variation in energy density of diets. Individual feed intakes and corresponding production and body measurements were obtained from 13 Midwestern nutrition experiments. Two measures of RFI were considered, RFI Mcal and RFI kg , which involved the regression of NE L intake (Mcal/d) or dry matter intake (DMI; kg/d) on 3 expenditures: milk energy, energy gained or lost in body weight change, and energy for maintenance. In total, 677 records from 600 lactating cows between 50 and 275 d in milk were used. Cows were divided into 46 cohorts based on dietary or nondietary treatments as dictated by the nutrition experiments. The realized NE L densities of the diets (Mcal/kg of DMI) were estimated for each cohort by totaling the average daily energy used in the 3 expenditures for cohort members and dividing by the cohort's total average daily DMI. The NE L intake for each cow was then calculated by multiplying her DMI by her cohort's realized energy density. Mean energy density was 1.58 Mcal/kg. Heritability estimates for RFI kg , and RFI Mcal in a single-trait animal model did not differ at 0.04 for both measures. Information about realized energy density could be useful in standardizing intake data from different climate conditions or management systems, as well as investigating potential genotype by diet interactions.

Our long-term objective is to develop breeding strategies for improving feed efficiency in dairy cattle. In this study, phenotypic data were pooled across multiple research stations to facilitate investigation of the genetic and nongenetic components of feed efficiency in Holstein cattle. Specifically, the heritability of residual feed intake (RFI) was estimated and heterogeneous relationships between RFI and traits relating to energy utilization were characterized across research stations. Milk, fat, protein, and lactose production converted to megacalories (milk energy; MilkE), dry matter intakes (DMI), and body weights (BW) were collected on 6,824 lactations from 4,893 Holstein cows from research stations in Scotland, the Netherlands, and the United States. Weekly DMI, recorded between 50 to 200 d in milk, was fitted as a linear function of MilkE, BW0.75, and change in BW (ΔBW), along with parity, a fifth-order polynomial on days in milk (DIM), and the interaction between this polynomial and parity in a first-stage model. The residuals from this analysis were considered to be a phenotypic measure of RFI. Estimated partial regression coefficients of DMI on MilkE and on BW0.75 ranged from 0.29 to 0.47 kg/Mcal for MilkE across research stations, whereas estimated partial regression coefficients on BW0.75 ranged from 0.06 to 0.16 kg/kg0.75. Estimated partial regression coefficients on ΔBW ranged from 0.06 to 0.39 across stations. Heritabilities for country-specific RFI were based on fitting second-stage random regression models and ranged from 0.06 to 0.24 depending on DIM. The overall heritability estimate across all research stations and all DIM was 0.15±0.02, whereas an alternative analysis based on combining the first- and second-stage model as 1 model led to an overall heritability estimate of 0.18±0.02. Hence future genomic selection programs on feed efficiency appear to be promising; nevertheless, care should be taken to allow for potentially heterogeneous variance components and partial relationships between DMI and other energy sink traits across environments when determining RFI.

Dehorning in cattle has been associated with behavioral, physiological, and neuroendocrine responses indicative of pain. Unaddressed, the pain associated with a routine production procedure could contribute to a negative public perception of livestock production practices. Alternative considerations of dehorning include the selection of polled cattle within herds, thereby avoiding pain and production loss. As polledness results from an autosomal dominant pattern of inheritance, genetic selection for polled cattle could reduce the prevalence of the horned trait. Herein we discuss 3 strategies to incorporate polled genetics into a cow herd and the estimated impact on the overall genetic merit of the herd. Furthermore, the availability and genetic merit of polled artificial insemination bulls in the United States is summarized. Both Holstein and Jersey dairy bulls registered with the National Association of Animal Breeders from December 2010 through April 2013 were queried. Polled bulls were identified as either being homozygous (PP) or heterozygous (Pp) and the average net merit (NM) predicted transmitting ability (PTA) of each sire group was calculated. The percentage of polled calves born each year over a 10-yr period was calculated for the following 3 scenarios: (A) various percentages of horned cows were randomly mated to Pp bulls, (B) various percentages of horned cows were preferentially mated to Pp bulls, and (C) horned cows were selectively mated to PP bulls, heterozygous cows to Pp bulls, and homozygous polled cows to horned bulls. Additionally, the change in NM PTA of the cow herd was calculated over the same period. The highest percentage of polled animals (87%) was achieved in scenario C. An evaluation of the herd NM PTA highlights the trade-offs associated with increasing polled genetics. Given the current genetic merit of horned and polled bulls, increasing the percentage of polled calves will decrease the NM PTA in Holstein, but may have minimal impact in Jersey herds. Decisions regarding selective breeding to increase polled genetics will need to be evaluated in the context of production objectives, cost of dehorning, and impact on overall genetic merit.

Lipid metabolism plays a crucial role in the adaptation of dairy cows to periods of energy insufficiency. The objective of the current study was to determine if lipolytic proteins are consistently regulated when energy mobilization is stimulated by different factors. We evaluated 2 models of altered energy balance in mid-lactation Holstein cows, including feed restriction (FR) and administration of bovine growth hormone (GH), by quantifying the abundance and (or) phosphorylation of hormone-sensitive lipase (HSL), perilipin (PLIN), and adipose triglyceride lipase (ATGL). For GH administration, adipose tissue and blood samples were collected 4d before and 3 and 7d after administration of GH (n=20 cows). Similarly, adipose and blood samples were obtained 6d before and 1 and 4d after initiation of FR (n=18 cows). Estimated net energy balance decreased and nonesterified fatty acid concentration increased in both experimental models. Decreased ATGL and PLIN protein abundance was observed with GH administration and FR. Additionally, the abundance of phosphorylated HSL Ser565 decreased in both models. Decreased abundance of phosphorylated PLIN was observed with GH administration, but not FR. Decreased ATGL protein abundance appears to be a consistent response to energy insufficiency in lactating cows, as this response was also described with negative energy balance at the onset of lactation. In contrast, the abundance of PLIN protein and phosphorylation of HSL using antibodies targeting serine residue 565 of HSL (HSL Ser565 ) were altered in the current research, but not at the onset of lactation. Our findings demonstrate that lipolysis is altered through the regulation of multiple proteins, and that this regulation differs according to physiological state in lactating cows.

Objectives of the current study were to estimate genetic parameters in Holstein cows for energy balance (EB) and related traits including dry matter intake (DMI), body weight (BW), body condition score (BCS), energy-corrected milk (ECM) production, and gross feed efficiency (GFE), defined as the ratio of total ECM yield to total DMI over the first 150d of lactation. Data were recorded for the first half of lactation on 227 and 175 cows in their first or later lactation, respectively. Random regression models were fitted to longitudinal data. Also, each trait was averaged over monthly intervals and analyzed by single and multivariate animal models. Heritability estimates ranged from 0.27 to 0.63, 0.12 to 0.62, 0.12 to 0.49, 0.63 to 0.72, and 0.49 to 0.53 for DMI, ECM yield, EB, BW, and BCS, respectively, averaged over monthly intervals. Daily heritability estimates ranged from 0.18 to 0.30, 0.10 to 0.26, 0.07 to 0.22, 0.43 to 0.67, and 0.25 to 0.38 for DMI, ECM yield, EB, BW, and BCS, respectively. Estimated heritability for GFE was 0.32. The genetic correlation of EB at 10d in milk (DIM) with EB at 150 DIM was −0.19, suggesting the genetic regulation of this trait differs by stage of lactation. Positive genetic correlations were found among DMI, ECM yield, and BW averaged over monthly intervals, whereas correlations of these traits with BCS depended upon stage of lactation. Total ECM yield for the lactation was positively correlated with DMI, but a negative genetic correlation between total ECM yield and EB was found. However, the genetic correlation between total ECM yield and EB in the first month of lactation was −0.02, indicating that total production is not genetically correlated with EB during the first month of lactation, when negative EB is most closely associated with diminished fitness. The genetic correlation between GFE and EB ranged from −0.73 to −0.99, indicating that selection for more efficient cows would favor a lower energy status. However, the genetic correlation between EB in the first month of lactation and GFE calculated from 75 to 150 DIM was not significant, indicating that the unfavorable correlation between GFE and EB in early lactation may be minimized with alternative definitions of efficiency. Thus, EB, GFE and related traits will likely respond to genetic selection in Holstein cows. However, the impact of selection for improved feed efficiency on EB must be carefully considered to avoid potential negative consequences of further reductions in EB at the onset of lactation.

To understand the biology and evolution of ruminants, the cattle genome was sequenced to about sevenfold coverage. The cattle genome contains a minimum of 22,000 genes, with a core set of 14,345 orthologs shared among seven mammalian species of which 1217 are absent or undetected in noneutherian (marsupial or monotreme) genomes. Cattle-specific evolutionary breakpoint regions in chromosomes have a higher density of segmental duplications, enrichment of repetitive elements, and species-specific variations in genes associated with lactation and immune responsiveness. Genes involved in metabolism are generally highly conserved, although five metabolic genes are deleted or extensively diverged from their human orthologs. The cattle genome sequence thus provides a resource for understanding mammalian evolution and accelerating livestock genetic improvement for milk and meat production. Fil: Bovine Genome Sequencing and Analysis Consortium. Bovine Genome Sequencing And Analysis Consortium; Estados Unidos Fil: Amadio, Ariel Fernando. Instituto Nacional de Tecnología Agropecuaria. Centro Regional Santa Fe. Estación Experimental Agropecuaria Rafaela; Argentina Fil: Poli, Mario Andres. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación en Ciencias Veterinarias y Agronómicas. Instituto de Genética; Argentina

Genetic diversity in candidate genes for fitness and production traits was explored in three populations of dairy cattle. The study focused on adipokines, including leptin (LEP), tumor necrosis factor alpha (TNF), interleukin-8 (IL8) and interleukin-10 (IL10) as candidate genes. The three populations of interest included young Jersey and Holstein (modern Holstein) sires, and Holstein sires born prior to 1970 (traditional Holstein). Pools of DNA representing each sire group were used as template to generate PCR products for sequencing and identification of single nucleotide polymorphisms (SNP). Sequences of PCR products were assembled and SNPs identified using Sequencher 4.5 software. One SNP representing each gene and a previously reported SNP in LEP were selected for genotyping across all bulls. A multiplexed genotyping assay was developed using the ABI PRISM SNaPshot Multiplex Kit. Allele and genotypic frequencies were determined for each sire group, and genotypic frequencies were in agreement with Hardy-Weinberg equilibrium. Allele frequencies were compared among sire groups using the chi-square test. A significant difference between Jersey and Holstein was observed for all genes, and modern and traditional Holstein groups differed for the previously described LEP and IL10 SNP. Although allele frequency differences between modern and traditional Holsteins may reflect the effect of selection pressure for production traits on these genomic regions, random genetic drift or sampling bias could also have contributed to the observed differences. Keywords : Fitness traits; genetic markers; adipokines; dairy cattle South African Journal of Animal Science Vol. 37 (3) 2007: pp.154-157

Background Beta-adrenergic receptor agonists (BA) induce skeletal muscle hypertrophy, yet specific mechanisms that lead to this effect are not well understood. The objective of this research was to identify novel genes and physiological pathways that potentially facilitate BA induced skeletal muscle growth. The Affymetrix platform was utilized to identify gene expression changes in mouse skeletal muscle 24 hours and 10 days after administration of the BA clenbuterol. Results Administration of clenbuterol stimulated anabolic activity, as indicated by decreased blood urea nitrogen (BUN; P < 0.01) and increased body weight gain (P < 0.05) 24 hours or 10 days, respectively, after initiation of clenbuterol treatment. A total of 22,605 probesets were evaluated with 52 probesets defined as differentially expressed based on a false discovery rate of 10%. Differential mRNA abundance of four of these genes was validated in an independent experiment by quantitative PCR. Functional characterization of differentially expressed genes revealed several categories that participate in biological processes important to skeletal muscle growth, including regulators of transcription and translation, mediators of cell-signalling pathways, and genes involved in polyamine metabolism. Conclusion Global evaluation of gene expression after administration of clenbuterol identified changes in gene expression and overrepresented functional categories of genes that may regulate BA-induced muscle hypertrophy. Changes in mRNA abundance of multiple genes associated with myogenic differentiation may indicate an important effect of BA on proliferation, differentiation, and/or recruitment of satellite cells into muscle fibers to promote muscle hypertrophy. Increased mRNA abundance of genes involved in the initiation of translation suggests that increased levels of protein synthesis often associated with BA administration may result from a general up-regulation of translational initiators. Additionally, numerous other genes and physiological pathways were identified that will be important targets for further investigations of the hypertrophic effect of BA on skeletal muscle.