Heritability of rectal temperature and genetic correlations with production and reproduction traits in dairy cattle

Genetic selection for body temperature during heat stress might be a useful approach to reduce the magnitude of heat stress effects on production and reproduction. Objectives of the study were to estimate the genetic parameters of rectal temperature (RT) in dairy cows in freestall barns under heat stress conditions and to determine the genetic and phenotypic correlations of rectal temperature with other traits. Afternoon RT were measured in a total of 1,695 lactating Holstein cows sired by 509 bulls during the summer in North Florida. Genetic parameters were estimated with Gibbs sampling, and best linear unbiased predictions of breeding values were predicted using an animal model. The heritability of RT was estimated to be 0.17 ± 0.13. Predicted transmitting abilities for rectal temperature changed 0.0068 ± 0.0020°C/yr from (birth year) 2002 to 2008. Approximate genetic correlations between RT and 305-d milk, fat, and protein yields, productive life, and net merit were significant and positive, whereas approximate genetic correlations between RT and somatic cell count score and daughter pregnancy rate were significant and negative. Rectal temperature during heat stress has moderate heritability, but genetic correlations with economically important traits mean that selection for RT could lead to lower productivity unless methods are used to identify genes affecting RT that do not adversely affect other traits of economic importance.     

Hormones, metabolites, and reproduction in Holsteins, Jerseys, and their crosses

Holsteins (HH), Jerseys (JJ), and their crosses in first (n=157) and second (n=107) lactation were used to determine if reproduction, progesterone (P4), insulin-like growth factor 1 (IGF-1), insulin, nonesterified fatty acids (NEFA), and milk production differed between genetic groups. Thirty-four cows were Holstein-Jersey (HJ) crosses, 46 were Jersey-Holstein (JH) crosses, 48 were purebred Holsteins (HH), and 29 were purebred Jerseys (JJ) in first lactation, whereas the second-lactation animals included 23 HJ, 35 JH, 35 HH, and 14 JJ. Blood samples were collected weekly for the first 10 wk postpartum. Analyses were conducted using the MIXED, chi-square, and GLIMMIX procedures (SAS Institute Inc., Cary, NC). Seasons of calving were cold (November to May) and hot (June to October) and were combined with year to form 8 year-seasons. Days open and number of services were affected by genetic group. The HH were open 169±8 d, which was greater than HJ (143±9 d), JJ (132±10 d), and JH (127±8 d). The HH had 2.4±0.1 services per pregnancy, which was greater than JH (1.9±0.1), but not different from HJ (2.1±0.2) or JJ (2.1±0.2). Concentrations of NEFA were greater in lactation 2 (0.52±0.02 mEq/L) than in lactation 1 (0.45±0.02 mEq/L) and decreased over the 10-wk period. Concentrations of NEFA were greater in the cold season except in yr 3. Insulin in lactation 1 (0.81±0.03 ng/mL) was greater than in lactation 2 (0.72±0.03 ng/mL); insulin decreased to wk 2 then gradually increased. The HJ had the greatest insulin concentrations (0.87±0.04 ng/mL) and the JJ had the lowest (0.66±0.04 ng/mL), and IGF-1 gradually increased over the 10-wk period. Milk production (actual yield in the first 305 d, not adjusted for fat and protein) was affected by genetic group, lactation number, year-season, and wk 1 insulin. The HH produced 10,348±207 kg of milk, which was greater than the HJ (9,129±230 kg), the JH (9,384±190 kg), and the JJ (7,080±240 kg). Milk production in lactation 2 (9,676±163 kg) was greater than that in lactation 1 (8,294±160 kg). The JJ (10.3±4.7%) had the highest frequency of mastitis. The chance of getting mastitis for HH (1.1±0.9%) differed from that for HJ (9.4±4.1%), JH (8.1±3.4%), and JJ (10.3±4.7%). Genetic group affected hormones and metabolites, which may partially explain differences in reproductive measures and milk yield.     

Genetic and phenotypic correlations between milk coagulation properties, milk production traits, somatic cell count, casein content, and pH of milk

Genetic and phenotypic correlations between milk coagulation properties (MCP: coagulation time and curd firmness), milk yield, fat content, protein content, ln(somatic cell count) (SCS), casein content, and pH of milk and heritability of these traits were estimated from data consisting of milk samples of 4664 Finnish Ayrshire cows sired by 91 bulls. In addition, differences in average estimated breeding values (EBV) for the above traits between the cows with noncoagulating (NC) milk and those with milk that coagulated (CO samples) were examined. The estimations were carried out to study the possibilities of indirect genetic improvement of MCP by use of the above characteristics. The genetic and phenotypic correlations between MCP and the milk production traits were low or negligible. The genetic associations between desirable MCP and low SCS were rather strong (-0.45 to 0.29). Desirable MCP correlated both genetically and phenotypically with low pH of milk (-0.51 to 0.50). The rather high heritability estimates for curd firmness in different forms (0.22 to 0.39), and the wide variation in the proportion of daughters producing NC milk between the sires (0 to 47%) suggested that noncoagulation of milk is partly caused by additive genetic factors. Based on the genetic correlations between curd firmness and SCS and the high EBV for SCS obtained for the cows with NC-milk, it is possible that the loci causing noncoagulation of milk and increasing somatic cell count of milk are closely linked or partly the same. One means to genetically improve MCP and to reduce the occurrence of NC milk could thus be selection for low somatic cell count of milk.     

Estimation of genetic and phenotypic parameters for clinical mastitis, somatic cell production deviance, and protein yield in dairy cattle using Gibbs sampling.

When including clinical mastitis in the breeding goal, it is useful to know what measure of the trait is most appropriate and its relationship to the primary production traits and indicator traits in the relevant population. In this paper, genetic and phenotypic parameters for clinical mastitis, somatic cell production deviance, and protein yield were estimated for the dairy breed Danish Red. In preliminary analyses, the heritability for clinical mastitis was found to be highest in early lactation, and its genetic correlation to clinical mastitis at other stages of lactation were high. Therefore, clinical mastitis defined in early lactation was the measure of clinical mastitis used in subsequent analyses. Two bivariate analyses were performed. Each analysis fitted clinical mastitis and either somatic cell production deviance or protein yield as a continuous trait. The bivariate model was composed of a Gaussian model for the continuous trait and a threshold model for mastitis. The analyses were performed in a Bayesian setting, using the Gibbs sampler. Point estimates (mean of marginal posterior densities) of heritability for mastitis on the underlying scale were estimated to be 0.10 and 0.12 in the two analyses. The genetic correlation between mastitis and protein yield was 0.43 and between mastitis and somatic cell production deviance was 0.80. These results make clear the importance of including clinical mastitis in the breeding goal and the usefulness of somatic cell production deviance as the indicator trait for clinical mastitis. The best measure of clinical mastitis was to consider only cases in early lactation.     

Heritabilities and genetic and phenotypic correlations for milk production and fertility traits of spring-calved once-daily or twice-daily milking cows in New Zealand

The objectives of this study were to estimate the genetic and phenotypic correlations and heritabilities for milk production and fertility traits in spring-calved once-daily (OAD) milking cows for the whole season in New Zealand and compare those estimates with twice-daily (TAD) milking cows. Data used in the study consisted of 69,252 first parity cows from the calving seasons 2015–2016 to 2017–2018 in 113 OAD and 531 TAD milking herds. Heritability estimates for production and fertility traits were obtained through single-trait animal models, and estimates of genetic and phenotypic correlations were obtained through bivariate animal models. Heritability estimates of production traits varied from 0.26 to 0.61 in OAD and from 0.13 to 0.63 in TAD. Heritability estimates for fertility traits were low in both OAD and TAD milking cow populations, and estimates were consistent (OAD: 0.01 to 0.10 and TAD: 0.01 to 0.08) across milking regimens. Estimates of phenotypic and genetic correlations among production traits were consistent across populations. In both populations, phenotypic correlations between milk production and fertility traits were close to zero, and most of the genetic correlations were antagonistic. In OAD milking cows, genetic correlations of milk and lactose yields with the start of mating to conception, 6-wk in-calf, not-in-calf, and 6-wk calving rate were close to zero. Interval from first service to conception was negatively genetically correlated with milk and lactose yields in OAD milking cows. Protein percentage was positively genetically correlated with 3-wk and 6-wk submission, 3-wk in-calf, 6-wk in-calf, first service to conception, 3-wk calving, and 6-wk calving rate in the TAD milking cow population, but these correlations were low in the OAD milking cow population. Further studies are needed to understand the relationship of protein percentage and fertility traits in the OAD milking system. The phenotypic correlations between fertility traits were similar in OAD and TAD milking populations. Genetic correlations between fertility traits were strong (≥0.70) in cows milked TAD, but genetic correlations varied from weak to strong in cows milked OAD. Further research is required to evaluate the interaction between genotype by milking regimen for fertility traits in terms of sire selection in the OAD milking cow population.     

Estimation of genetic parameters for production and reproduction in Finnish Ayrshire cattle

Records of AI-sired cows born between 1978 and 1982 were used to form two composite production and reproduction data sets. First (second) consisted of 35,568 (26,443) first lactations of daughters of 270 (237) sires. Traits were FCM, heifer, and first parity nonreturn rates, days between calving and first insemination, and days open, with means 5075 (5280) kg, .62 (.62), .44 (.49), 81 (81) d and 110 (111) d. (Co)variance components were estimated by REML with an expectation maximization algorithm. Sire model included age, month, herd-year effects, and relationships among sires. Records on animals with observations missing on some traits were included. Estimates of heritabilities, averaged over data sets, were nonreturn rates for heifers and for cows, .02; FCM, .32; days to first insemination, .19; and days open, .10. Genetic correlations between first parity fertility and yield were unfavorable; the highest, .43, was between FCM and days open. Heifer nonreturn rate had a .09 correlation with production and a .26 correlation with cow nonreturn rate. Phenotypic correlations were in the same direction as genetic correlations but were smaller in magnitude. Results suggest that selection only for production would cause deterioration in level of fertility. When economical, AI sires should be evaluated for daughter fertility. A multi-trait model including milk production, days open and relationships among bulls is recommended for genetic evaluation.     

Effects of inbreeding on production and survival in Jerseys

Responses of registered Jersey cows to various levels of inbreeding were examined with pedigree data supplied by the American Jersey Cattle Association and test-day production data from 1970 through 1998 obtained from the Animal Breeding Center at Cornell University. Rate of increase in level of inbreeding is accelerating with time, making it more difficult for producers to make matings that avoid the potentially deleterious effects of inbreeding. Production losses caused by inbreeding were significant and curvilinear for all traits studied except somatic cell linear score, with the greatest losses at higher levels of inbreeding. Inbreeding was found to have the greatest effect on production at early ages and early in lactation. Early onset of the deleterious effects of inbreeding resulted in larger net present value losses than if effects of inbreeding occurred later in the life of an animal. Losses were probably enhanced because of the need to freshen animals as early as possible to maximize net present value returns. Survival decreased as level of inbreeding increased and was likely to have a greater negative impact on the financial health of the dairy enterprise than production losses.     

Method R estimates of additive genetic, dominance genetic, and permanent environmental fraction of variance for yield and health traits of Holsteins

Fractions of variance accounted for by additive genetic, dominance genetic, and permanent environmental effects for milk, fat, and protein yields; somatic cell score; and productive life were estimated from Holstein data used for national genetic evaluations. Contemporary group assignments were determined using the national procedure. Data included 1,973,317 milk and fat records for 812,659 cows, 1,019,421 protein records for 462,067 cows, 468,374 lactation average somatic cell score (SCS) records for 232,909 cows, and 735,256 cows with productive-life records. Variance components were estimated with the JAADOM program, which uses iteration on data and second-order Jacobi iteration for obtaining solutions to the mixed-model equations and Method R for estimation of variance components. Ten different random data subsets were used to estimate parameters for each trait. Estimated additive genetic, dominance genetic, and permanent environmental fractions of variance were 0.34, 0.05, and 0.10 for milk yield; 0.34, 0.05, and 0.11 for fat yield; 0.31, 0.05, and 0.10 for protein yield; and 0.17, 0.01, and 0.16 for lactation average SCS. Estimated additive genetic and dominance genetic fractions of variance were 0.12 and 0.06 for productive life. Mean empirical standard errors of additive genetic, dominance genetic, and permanent environmental variance fractions were 0.003, 0.006, and 0.006.     

Heritability estimates associated with alternative definitions of mastitis and correlations with somatic cell score and yield

The objectives of this study were to compare alternative mastitis definitions and to estimate genetic correlations of producer-recorded mastitis with somatic cell score (SCS) and yield. Cow health events and lactation records from June 2002 through October 2007 were provided by Dairy Records Management Systems (Raleigh, NC). First- through fifth-lactation records from cows calving between 20 and 120 mo of age and that calved in a herd-year with at least 1% of cows with a clinical mastitis event were retained. The edited data contained 118,516 lactation records and 1,072,741 test-day records of 64,893 cows. Mastitis occurrence (1 = at least one mastitis event during lactation or test-day interval, 0 = no mastitis events), number of mastitis events during lactation, SCS, and yield were analyzed with animal models (single trait) or sire-maternal grandsire models (multiple trait) in ASREML. Comparisons were made among models assuming a normal distribution, a binary distribution, or Poisson distribution (for total episodes). The overall incidence of clinical mastitis was 15.4%; and heritability estimates ranged from 0.73% (test-day interval mastitis with a linear model) to 11.07% (number of mastitis episodes with a Poisson model). Increased mastitis incidence was genetically correlated with higher SCS (range 0.66 to 0.88) and was generally correlated with higher yield (range −0.03 to 0.40), particularly during first lactation (0.04 to 0.40). Significant genetic variation exists for clinical mastitis; and health events recorded by producers could be used to generate genetic evaluations for cow health. Sires ranked similarly for daughter mastitis susceptibility regardless of how mastitis was defined; however, test-day interval mastitis and a total count of mastitis episodes per lactation allow a higher proportion of mastitis treatments to be included in the genetic analysis.     

Genotype by environment interaction and genetic correlations among parities for somatic cell count and milk yield

Lactation measures of somatic cell concentration and total SCC production were developed. Data were separated into three parity groups. Within parity, five data sets were created: four subsets by herd-year average SCC, and one with all records. Records on lactation SCC, total SCC production, and 305-d milk were analyzed by a sire model separately in each subset within parity. Variance components estimates were by REML. For SCC and total SCC production, heritability estimates averaged .12 and were lowest in the highest level of herd-year average SCC. Estimates of genetic correlation between SCC and total SCC production were over .95; between SCC and 305-d milk were around .25 in first and -.15 in later parities; between total SCC and 305-d milk were around .50 in first and .15 in later parities. Product-moment correlations between sire effects in different levels of herd-year average SCC were obtained. Ratios of product-moment correlations to their expected value were above .80 for all traits in all parities. High ratios indicated little genotype by environment interaction. A sire by herd interaction was fitted in the model and accounted for less than 2% of total phenotypic variance for SCC and total SCC production, and 4% for 305-d milk. Estimates of genetic correlation of first with later parities were .71 to .86 for all traits. Between second and third parity genetic correlation estimates were around unity for all traits. Records from all parities should be used for sire evaluation.     

Estimation of environmental sensitivity of genetic merit for milk production traits using a random regression model

The objective of this study was to estimate effects of environmental sensitivity of milk production traits for several environmental parameters and to investigate the impact of combining traits with different environmental sensitivity in an economic index. Variance components and breeding values were estimated for milk, fat, and protein yield, and fat and protein percentage by applying a random regression on values of an environmental parameter for each sire. Fourteen environmental parameters were defined and fitted to data consisting of 151,696 heifers in 6780 herds in The Netherlands with first-lactation records for milk production, somatic cell count, body condition score, and number of inseminations. Milk, fat, and protein yield showed environmental sensitivity in combination with 12 environmental parameters. Herd-year averages of protein, body condition score, age at calving, calving interval, and peak date of calving explained most genotype by environment interaction, mainly resulting from scaling effects. Almost all genetic correlations across environments were 0.99 or higher. Although heterogeneity of genetic variances was considerable, heterogeneity of heritabilities was limited. Scaling had a large effect on the weights of the economic index, but environmental sensitivities of milk, fat, and protein yields were approximately of equal magnitude. Consequently, very little reranking occurred based on the economic index.     

Sequential estimation of genetic and phenotypic parameters in multitrait mixed model analysis

Single-trait and multitrait (2-, 3-, 4-, and 5-trait) restricted maximum likelihood methods were applied to the same set of data with complete information on all traits. Results suggest that parameter estimates from a data set vary depending upon the type of analysis (single- or multitrait model) and upon the other traits included in multitrait analysis. The choice of parameter estimation method for a breeding design should be based on the breeding goal. In parameter estimation or sire evaluation, traits included in a multitrait analysis should correspond to the traits of interest in the breeding goal. Multitrait analysis explores all intercorrelations simultaneously in parameter estimation and thus provides a complete picture of all interrelationships among traits. In contrast, single-trait analysis produces pairwise (simple) correlations and ignores the possible contribution of other related traits under study to the pairwise correlation. The 5-trait model analysis through canonical transformation was about 300% more efficient in terms of computer time than single-trait model analysis of the same 5 traits. In this study, parameter estimates converged faster under multitrait analysis through canonical transformation than under single-trait analysis.     

Heritability and genetic correlations of test day milk yield and composition,individual laboratory cheese yield,and somatic cell count for dairy ewes

Genetic parameters for milk yield, contents of fat, total protein, casein and serum protein, individual laboratory cheese yield, and somatic cell counts (SCC) were estimated from 7492 monthly test-day records of 1119 Churra ewes. Estimates were from multivariate REML using analytical gradients (AG-REML) procedures. Except for fat content, estimates for the other routinely recorded traits (milk yield, protein content, and SCC) agreed with those previously obtained in this and other dairy sheep populations. Protein content and composition had the highest heritabilities and repeatabilities. Heritabilities for protein and casein contents were very similar (0.23 and 0.21, respectively), and genetic correlation between the traits was close to unity (0.99). Accordingly, casein content is not advisable as an alternative to protein content as a selection criterion in dairy ewes; it does not have any compelling advantages and costs more to measure. Individual laboratory cheese yield (ILCY) obtained with Churra ewes had a low heritability (0.08), suggesting that potential for selection for this parameter would be possible but is not recommended. All correlations with ILCY were high and positive except for milk yield. A high SCC was accompanied by an increase in serum protein content and involved a loss in milk yield.     

Breed differences over time and heritability estimates for production and reproduction traits of dairy goats in the United States

To aid in improvement of breeding programs for production and reproduction traits of US dairy goats, breed differences over time were documented and genetic parameters were estimated. Data were from herds with ≥2 breeds (Alpine, LaMancha, Nubian, Oberhasli, Saanen, or Toggenburg), but only purebred data were analyzed. Three kidding periods were examined: 1976 through 1984, 1985 through 1994, and 1995 through 2005. Univariate repeatability mixed models were used to estimate least squares means by kidding period-breed and genetic parameters for milk, fat, and protein yields, combined fat and protein yield, fat and protein percentages, protein:fat ratio, age at first kidding, and kidding interval. Trends across kidding periods were favorable for most yield traits for all breeds but generally unfavorable for reproduction traits. Saanens had the highest milk (1,063 to 1,125 kg) and protein yields (31 to 33 kg). Nubians had the highest fat yields (37 to 40 kg) and lowest milk yields (791 to 851 kg). Oberhaslis had the lowest fat (31 to 33 kg) and protein (23 to 27 kg) yields. Alpines had the largest increase in milk yield (7.4%); Oberhaslis had the largest increase in protein (17.4%) and combined fat and protein (13.2%) yields. Combined fat and protein yield was higher for Nubians, Saanens, and Alpines (65 to 72 kg) than for LaManchas, Toggenburgs, and Oberhaslis (53 to 67 kg). Nubians had the highest fat (4.7 to 4.8%) and protein (3.6 to 3.8%) percentages. Only Nubians increased in fat percentage (2.1%); protein percentage increased most for Toggenburgs (7.4%) and Alpines (7.1%). Protein:fat ratio was highest for Toggenburgs (0.84 to 0.89) and lowest for Nubians (0.76 to 0.81), but Nubians had the largest increase in protein:fat ratio (6.6%). Saanens were oldest at first kidding (509 to 589 d), and Toggenburgs and LaManchas generally were youngest (435 to 545 d); age at first kidding increased most for Alpines (21.8%) and LaManchas (21.6%). Kidding intervals generally were shorter for Oberhaslis, LaManchas, and Nubians (350 to 377 d) than for Toggenburgs, Alpines, and Saanens (373 to 387 d). Kidding interval increased most for Nubians (3.9%) and Saanens (3.8%) and decreased only for Oberhaslis (5.4%). Heritability estimates across breeds were 0.35 for milk and fat yields, 0.37 for protein yield and protein:fat ratio, 0.36 for combined fat and protein yield, 0.52 for fat percentage, 0.54 for protein percentage, 0.23 for age at first kidding, and 0.05 for kidding interval. Genetic selection within breed is feasible for production and reproduction traits of US dairy goats.     

Effect of herd environment on the genetic and phenotypic relationships among milk yield, conception rate, and somatic cell score in Holstein cattle

A total of 248,230 primiparous records of Holstein cows calving from 1987 to 1994 (daughters of 588 sires in 3042 herds) was used to evaluate potential genotype by environment interactions among mature equivalent milk yield, lactation mean somatic cell score, and conception rate at first service. Herds were classified into low and high environmental groups using three different criteria: standard deviation of herd mature equivalent milk yield, a combination of herd mature equivalent milk yield mean and standard deviation, and the herd mean of body weight at first calving divided by age at first calving. Genetic parameters were modeled by using multiple-trait linear mixed models and were fitted using the multiple-trait derivative-free software. Heritabilities for mature equivalent milk yield, lactation mean somatic cell score, and conception rate at first service were 0.221, 0.106, and 0.015 in low environment herds and 0.300, 0.093, and 0.009 in high environment herds, respectively. Genetic (and phenotypic) correlations between mature equivalent milk yield and lactation mean somatic cell score, mature equivalent milk yield and conception rate at first service, and lactation mean somatic cell score and conception rate at first service were 0.277, -0.417, and -0.209, (-0.049, -0.180, and -0.040) and 0.173, -0.318, and -0.144, (-0.087, -0.166, and -0.035) in low and high environment herds, respectively. The genetic correlations between pairs of traits were consistently smaller in high environment herds, suggesting that differences in management between the two environment levels lessened the antagonistic genetic association between the traits studied. A long-range plan for low environment herds should focus on improving the level of management, which would greatly reduce the unfavorable correlated changes in lactation mean somatic cell score and conception rate at first service associated with the genetic improvement of mature equivalent milk yield.     

Heritabilities, genetic correlations, and genetic change for female fertility and protein yield in Norwegian Dairy Cattle

Data from 1,815,581 first insemination records from daughters of 2697 Norwegian Dairy Cattle (NRF) sires were analyzed. A multitrait model was used to estimate genetic parameters and genetic change for 56-d nonreturn rate in virgin heifers (NR56D0), for 56-d nonreturn rate in first lactation cows (NR56D1L), for interval from calving to first insemination (CFI1L), and for protein yield (PY(305)1L). The heritabilities for NR56D0, NR56D1L, CFI1L, and PY(305)1L were 1.08, 0.99, 3.01, and 20.80%, respectively. Genetic correlation between heifer and cow fertility was high and favorable between NR56D0 and NR56D1L (0.54) and moderate and unfavorable between NR56D0 and CFI1L (0.24). The genetic correlations between NR56D1L and CFI1L and between NR56D0 and PY(305)1L were 0.08 and 0.04, respectively. A small, unfavorable genetic correlation between NR56D1L and PY(305)1L (-0.18) was found, while the genetic correlation between PY(305)1L and CFI1L was strongly unfavorable (0.47). Since 1972, NRF sires have been selected for NR56D0 using breeding values estimated from large progeny groups and with considerable weight in the total merit index. A linear regression analysis of sire PTA on year of first insemination of daughters showed an annual genetic change of 0.14% units for NR56D0. Selection was able to stabilize the genetic change of NR56D1L (0.03%/yr) but an undesirable change for CFI1L (0.11 d/yr) was found. The change of sire PTA for PY(305)1L was 0.63 kg/yr.     

Optical oxygen microrespirometry as a platform for environmental toxicology and animal model studies

We present a new methodology for testing physiological responses of small organisms (size 70-500 microm) via changes in their oxygen respiration monitored by quenched-phosphorescence oxygen sensing on a scale of a single organism. The method is demonstrated using three different formats of respirometric assays, Artemia salina and mouse embryos as model animals, and various effectors including compounds that induce and prevent superoxide-mediated and heavy metal ion toxicity. These assays, which employ soluble oxygen probes, standard fluorescent readers, and accessorytools, provide sensitive, noninvasive, real-time monitoring of animal respiration, and rapid assessment of EC50, sublethal effects, and metabolic alterations. Applications include screening for acute toxicity of compound libraries and environmental samples, and the study of animal physiology and metabolism.     

Short communication: estimates of genetic parameters of body condition score in the first 3 lactations using a random regression animal model

The objective of this research was to estimate the genetic parameters of body condition score (BCS) in the first 3 lactations in Canadian Holstein dairy cattle using a multiple-lactation random regression animal model. Field staff from Valacta milk recording agency (Sainte-Anne-de-Bellevue, QC, Canada) collected BCS from Québec herds several times throughout each lactation. Approximately 32,000, 20,000, and 11,000 first-, second-, and third-parity BCS were analyzed, respectively, from a total of 75 herds. Body condition score was a moderately heritable trait over the lactation for parity 1, 2, and 3, with average daily heritabilities of 0.22, 0.26, and 0.30, respectively. Daily heritability ranged between 0.14 and 0.26, 0.19 and 0.28, and 0.24 and 0.33 for parity 1, 2, and 3, respectively. Genetic variance of BCS increased with days in milk within lactations. The low genetic variance in early lactation suggests that the evolution of the ability to mobilize tissue reserves in early lactation provided cattle with a major advantage, and is, therefore, somewhat conserved. The increasing genetic variance suggests that more genetic differences were related to how well cows recovered from the negative energy balance state. More specifically, increasing genetic variation as lactation progressed could be a reflection of genetic differences in the ability of cows to efficiently control the rate of mobilization of tissue reserves, which would not be crucial in early lactation. The shape of BCS curves was similar across parities. From first to third parity, differences included the progressively deeper nadir and faster rate of recovery of condition. Daily genetic correlations between parities were calculated from 5 to 305 DIM, and were summed and divided by 301 to obtain average daily genetic correlations. The average daily genetic correlations were 0.84 between parity 1 and 2, 0.83 between parity 1 and 3, and 0.86 between parity 2 and 3. Although not 1, these genetic correlations are still strong, so much of the variation observed in BCS was controlled by the same genes for each of the first 3 lactations. If a genetic evaluation for BCS is developed, regular collection of first-lactation BCS records should be sufficient for genetic evaluation.     

Growth, reproduction, and lactation in somatic cell cloned cows with short telomeres

We previously showed that telomere lengths of 10 somatic cell cloned cows were significantly shorter than normal. In this study, we investigated growth, reproduction, and lactation in these animals to determine if shortened telomeres have any effect on these characteristics. Six Holstein and 4 Jersey cloned cows, derived from oviduct cells, were reared under general group feeding. Body weights were recorded from birth to 48 mo of age. A number of reproductive characteristics were screened during the prepubertal, postpubertal, and postpartum periods. After parturition, milk yields were recorded daily and percentages of milk fat, proteins, and solids-not-fat were measured at monthly intervals. These data were used to estimate production of milk components over a 305-d period. Overall, the cloned heifers exceeded standard growth rates for each breed. The cows were inseminated at the first estrus after they reached 450 d of age, and delivered normal calves except for one stillbirth in the Holstein group. They were inseminated at postpartum estrus to provide second and third parturitions and, again, these pregnancies were normal. Gestational periods and birth weights of the calves were both within the normal range. The average total milk yield per cow in Holstein group clones was less than that of the original cow, whereas Jersey group clones showed a higher average milk yield than the original cow. In both groups of cloned cows, inter-individual variation in milk production was relatively large; however, the coefficient of variation was less than 10%. Our results suggest that the cloned cows have normal growth, reproductive, and lactation characteristics, and thus normal productivity, despite having reduced telomere lengths.