Relationships between milk yield and fertility in dairy cattle

In three studies of 51,618 Holstein, 6,630 Jersey, and 1,524 Guernsey records, correlation was .07 between 120-day milk yield and number of services required for probable conception, independent of days postpartum. The partial regression coefficient for Holsteins was .014 +/- .001 more services for each additional 100 kg of 120-day milk. For Jerseys and Guernseys, .028 +/- .008 more services were required for each additional 100 kg of 120-day milk.     

Estimated genetic correlations between disease and yield traits in dairy cattle.

Data included observations on more than 200,000 first lactations of Norwegian cattle. Milk yield, fat and protein percentages, and observations on mastitis, ketosis, and presence of disease (binary coding of 0 or 1) were analyzed. Following Bayesian principles and applying the threshold concept, dispersion parameters for the binary traits (on the underlying scale) with continuous production traits were estimated. Heritabilities were .27, .34, and .43 for milk yield, fat percentage, and protein percentage, respectively. Heritabilities for the disease traits were .05 to .13 but may be inconsistent because of methodology problems with small sire by herd-year-season subclass size. Genetic correlations between milk yield and all three disease traits were above .5, indicating an undesirable relationship. Genetic correlations between ketosis and the content traits were -.38 to -.65; low component percentages were associated with high ketosis frequencies. Ignoring diseases in breeding programs may lead to undesirable correlated selection responses when selecting on milk yield.     

Relationships between milk culture results and milk yield in Norwegian dairy cattle

Associations between test-day milk yield and positive milk cultures for Staphylococcus aureus, Streptococcus spp., and other mastitis pathogens or a negative milk culture for mastitis pathogens were assessed in quarter milk samples from randomly sampled cows selected without regard to current or previous udder health status. Staphylococcus aureus was dichotomized according to sparse (≤1,500 cfu/mL of milk) or rich (>1,500 cfu/mL of milk) growth of the bacteria. Quarter milk samples were obtained on 1 to 4 occasions from 2,740 cows in 354 Norwegian dairy herds, resulting in a total of 3,430 samplings. Measures of test-day milk yield were obtained monthly and related to 3,547 microbiological diagnoses at the cow level. Mixed model linear regression models incorporating an autoregressive covariance structure accounting for repeated test-day milk yields within cow and random effects at the herd and sample level were used to quantify the effect of positive milk cultures on test-day milk yields. Identical models were run separately for first-parity, second-parity, and third-parity or older cows. Fixed effects were days in milk, the natural logarithm of days in milk, sparse and rich growth of Staph. aureus (1/0), Streptococcus spp. (1/0), other mastitis pathogens (1/0), calving season, time of test-day milk yields relative to time of microbiological diagnosis (test day relative to time of diagnosis), and the interaction terms between microbiological diagnosis and test day relative to time of diagnosis. The models were run with the logarithmically transformed composite milk somatic cell count excluded and included. Rich growth of Staph. aureus was associated with decreased production levels in first-parity cows. An interaction between rich growth of Staph. aureus and test day relative to time of diagnosis also predicted a decline in milk production in third-parity or older cows. Interaction between sparse growth of Staph. aureus and test day relative to time of diagnosis predicted declining test-day milk yields in first-parity cows. Sparse growth of Staph. aureus was associated with high milk yields in third-parity or older cows after including the logarithmically transformed composite milk somatic cell count in the model, which illustrates that lower production levels are related to elevated somatic cell counts in high-producing cows. The same association with test-day milk yield was found among Streptococcus spp.-positive pluriparous cows.     

Selecting for lactation curve and milk yield in dairy cattle

Knowledge of genetic relationships between characteristics of lactation curves and lactation yields is essential for joint selection for both. An equation, yt = atbexp(-ct), was chosen to depict individual lactation curves for 5,927 first lactations by Holsteins in 557 herds in Michigan Dairy Herd Improvement where yt is daily milk yield at day t in lactation, a is yield at time zero, b is ascent to peak, and c is decline after peak. Genetic correlations for 305-day milk yield with initial production (a), ascent to peak (b), descent after peak (c), and peak yield were -.37, .40, 0, and .91. From empirical results from applied selection indexes, selecting for both increase of ascent to peak and peak yield did not decrease 305-day milk substantially. Rankings of sires on these indexes were similar to their rankings on milk yield alone. Attempts to decrease peak yield and increase persistency decreased milk yield greatly.     

Effect of mobility score on milk yield and activity in dairy cattle

Previous studies have indicated that lame cows have reduced milk yield both before and after they are treated for lameness. One explanation for the reduction in yield before treatment is delay to treatment; that is, cows have impaired mobility for some time before they are treated. The aim of this study was to test this hypothesis by investigating temporal associations between change in milk yield and change in mobility score. Mobility score (MS, on a scale from 0 to 3), milk yield, treatments for lameness, and cow activity were recorded on 312 cows in a dairy herd in Somerset, UK, for 1 yr. The MS was scored every 2 wk and compared with daily yield and activity (mean log steps/h) averaged over the previous 16 d. Approximately 52% of MS changed within 14 d, usually by 1 unit. Overall, milk yields of cows with MS 1 were greater than those of cows with other scores. Cows with MS 2 and 3 produced 0.7 (95% confidence interval: 0.35–0.97) and 1.6 (0.98–2.23) kg less milk/d, respectively, compared with cows with MS 1. In addition, cows with MS 1 were significantly more active than cows with MS 0, 2, or 3. Cows with MS 2 and 3 were 0.02 (0.01–0.03) and 0.03 (0.01–0.05) mean log steps less active than cows with MS 1. Six to 8 wk before nonlame cows became MS 2 or 3, their daily milk yield decreased by a mean (95% CI) of 0.5 kg (0.12–0.47) and 0.9 kg (0.16–1.65) respectively. Daily yield remained lower by 0.42 kg (0.09–0.75) for 4 wk after cows with MS 2 had recovered. The activity of cows was significantly less (0.01 mean log steps) with increasing MS; the associations between activity and parity (means 0.03–0.11) and month of lactation (means 0.03–0.36) were quantitatively larger. Results from a multistate model indicated that once cows were lame they remained lame or became lame again despite treatment. In conclusion, cows’ milk production started to decline before their mobility was visibly impaired.     

Effect of quantitative trait loci for milk protein percentage on milk protein yield and milk yield in Israeli Holstein dairy cattle

Although numerous quantitative trait loci (QTL) mapping studies involving milk protein percent (PP), milk yield (MY), and protein yield (PY) have been carried out, there has not been any systematic evaluation of the effects of individual QTL on these 3 interrelated traits. Consequently, the aim of the present study was to investigate the effects on MY and PY of QTL for PP previously mapped in various laboratories. The study, based on selective DNA pooling of milk samples, included 10 Israeli Holstein artificial insemination bulls, each the sire of 1,800 or more milk-recorded daughters. For each sire-trait combination across the 10 sires, milk samples of the highest and lowest daughters with respect to estimated breeding values for PP, PY, and MY were collected for pooling. A total of 134 dinucleotide microsatellites distributed over 25 bovine autosomes were used. An empirical standard error for marker-QTL linkage testing was calculated based on the variation among split samples within the same tail. Threshold comparison-wise error rate P-values were set to control proportion of false positives at P = 0.10 level for declaring significant effects at the marker-trait level. Estimates of the number of true null hypotheses for each trait were obtained from the histogram of marker comparison-wise error rate P-values. Based on these estimates, effective power of the experiment at the marker-trait level was estimated as 0.75, 0.41, and 0.73 for PP, PY, and MY. The proportion of heterozygosity at the QTL was estimated as 0.46, 0.39, and 0.40, respectively. After correcting for incomplete power and proportion of false positives, it was estimated that 38.7 and 37.5% of the markers affecting PP and MY, respectively, also affected PY. Of the markers affecting PY, 68.9 and 76.5%, respectively, also affected PP and MY. Apparently, none of the significant markers affected PY exclusively, and only 6.5 and 16.0%, respectively, affected PP or MY exclusively. Thus, almost all significant markers, and by inference almost all QTL, had effects on at least 2 of the 3 traits.     

Statistical modeling of candidate gene effects on milk production traits in dairy cattle

A major objective of dairy cattle genomic research is to identify genes underlying the variability of milk production traits that could be useful in breeding programs. The candidate gene approach provides tools for searching for causative polymorphisms affecting quantitative traits. Genes with a possible effect on milk traits in cattle can be involved in different physiological pathways, such as triglyceride synthesis [acyl-CoA:diacylglycerol acyltransferase 1 gene (DGAT1)], fat secretion from the mammary epithelial tissue (butyrophilin), or entire-body energy homeostasis regulation (leptin and leptin receptor). In this study, based on data from 252 Black and White bulls from the active Polish dairy population, effects and potential interactions of 9 single nucleotide polymorphisms in the butyrophilin, DGAT1, leptin, and leptin receptor genes were investigated. Additionally, the effect of the number of additive, dominance, and epistatic genetic effects fitted into the model on the estimates of model parameters and model selection was illustrated. Phenotypic records were daughter yield deviations for milk, fat, and protein yields, obtained from a routine national genetic evaluation. Out of all the analyzed polymorphisms, DGAT1 K232A had a much larger effect on milk traits than the other single nucleotide polymorphisms considered. Estimates of the additive genetic effect of K232A expressed as half of the difference between Lys- and Ala-encoding variants were −107.4 kg of milk, 5.4 kg of fat, and −1.6 kg of protein at first parity, as well as −120 kg of milk and 6.8 kg of fat at second parity. In terms of model selection, it was demonstrated that the modified version of Bayesian information criterion selects models with the parameterization reflecting the genetic background of the analyzed trait, while the Bayesian information criterion chooses models that are too highly parameterized.     

Effects of the osteopontin gene variants on milk production traits in dairy cattle

Osteopontin (OPN) is a highly phosphorylated glycoprotein whose gene has been cloned and sequenced in different species. Several whole genome scans have identified quantitative trait loci (QTL) affecting milk production traits on bovine chromosome 6 close to the osteopontin gene (OPN) location. The presence of OPN in milk and its elevated expression in mammary gland epithelial cells together with previous QTL studies have prompted us to investigate the effects of OPN variants on milk production traits in the Holstein dairy cattle population. A single nucleotide polymorphism in intron 4 (C/T) was detected and primers were designed to amplify genomic DNA from 1362 bulls obtained from Cooperative Dairy DNA Repository and from 214 cows from the University of Wisconsin herd. For the Repository population, the C allele was associated with an increase in milk protein percentage and milk fat percentage. Correlation between milk protein percentage and milk fat percentage was about 0.57. For the University of Wisconsin herd, the estimates of the effects of allele C were in the same direction as for the Repository population, although these estimates did not reach statistical significance. Our results are consistent with other studies that showed a significant association of the microsatellite markers in the region of OPN with milk protein percentage and other correlated traits.     

Indirect genomic predictions for milk yield in crossbred Holstein-Jersey dairy cattle

The objective of this study was to predict genomic breeding values for milk yield of crossbred dairy cattle under different scenarios using single-step genomic BLUP (ssGBLUP). The data set included 13,880,217 milk yield measurements on 6,830,415 cows. Genotypes of 89,558 Holstein, 40,769 Jersey, and 22,373 Holstein-Jersey crossbred animals were used, of which all Holstein, 9,313 Jersey, and 1,667 crossbred animals had phenotypic records. Genotypes were imputed to 45K SNP markers. The SNP effects were estimated from single-breed evaluations for Jersey (JE), Holstein (HO) and crossbreds (CROSS), and multibreed evaluations including all Jersey and Holstein (JE_HO) or approximately equal proportions of Jersey, Holstein, and crossbred animals (MIX). Indirect predictions (IP) of the validation animals (358 crossbred animals with phenotypes excluded from evaluations) were calculated using the resulting SNP effects. Additionally, breed proportions (BP) of crossbred animals were applied as a weight when IP were estimated based on each pure breed. The predictive ability of IP was calculated as the Pearson correlation between IP and phenotypes of the validation animals adjusted for fixed effects in the model. Regression of adjusted phenotypes on IP was used to assess the inflation of IP. The predictive ability of IP for CROSS, JE, HO, JE_HO, and MIX scenario was 0.50, 0.50, 0.47, 0.50, and 0.46, respectively. Using BP was the least successful, with a predictive ability of 0.32. The inflation of the IP for crossbred animals using CROSS, JE, HO, JE_HO, MIX, and BP scenarios were 1.17, 0.65, 0.55, 0.78, 1.00, and 0.85, respectively. The IP of crossbred animals can be predicted using single-step GBLUP under a scenario that includes purebred genotypes.     

Dietary choline effects on milk yield and duodenal choline flow in dairy cattle

In Experiment 1, the effect, in early lactation, of 0 or 3 g of supplemental choline/kg of total diet DM on milk yield and composition was tested in 20 first lactation and older Holstein cows. In Experiment 2, 30 first lactation and older Holstein cows between 45 and 200 d postpartum were assigned to treatments of 0, 2.5, and 5.0 g of supplemental choline/kg of total diet DM to test the effect of dietary choline with diets based on corn and soybean meal. In Experiments 1 and 2, added choline had no effect on either milk yield or fat-corrected milk yield. In both experiments, fat yield and fat percentage tended to increase with choline supplementation, but protein yield and protein percentage were unaffected. In Experiment 1, choline had no effect on serum lipids. Ruminal dosing of steers with 27 g/d supplemental choline in Experiment 3 increased duodenal choline flow by only 3 g/d. The apparent rumen degradability of choline tended to be higher (77.1 vs. 70.6%) in the supplemented steers. Choline concentration in rumen fluid and duodenal chyme were higher in the supplemented steers. Choline supplementation in Experiments 1 and 3 had no effect on rumen VFA or rumen pH. Dietary choline supplementation apparently is ineffective because of rapid degradation of choline in the rumen.     

Quantitative trait loci affecting milk production traits in Finnish Ayrshire dairy cattle

A whole genome scan of Finnish Ayrshire was conducted to map quantitative trait loci (QTL) affecting milk production. The analysis included 12 half-sib families containing a total of 494 bulls in a granddaughter design. The families were genotyped with 150 markers to construct a 2764 cM (Haldane) male linkage map. In this study interval mapping with multiple-marker regression approach was extended to analyse multiple chromosomes simultaneously. The method uses identified QTL on other chromosomes as cofactors to increase mapping power. The existence of multiple QTL on the same linkage group was also analyzed by fitting a two-QTL model to the analysis. Empirical values for chromosome-wise significance thresholds were determined using a permutation test. Two genome-wise significant QTL were identified when chromosomes were analyzed individually, one affecting fat percentage on chromosome (BTA) 14 and another affecting fat yield on BTA12. The cofactor analysis revealed in total 31 genome-wise significant QTL. The result of two-QTL analysis suggests the existence of two QTL for fat percentage on BTA3. In general, most of the identified QTL confirm results from previous studies of Holstein-Friesian cattle. A new QTL for all yield components was identified on BTA12 in Finnish Ayrshire.     

Lack of evidence of cytoplasmic inheritance in milk production traits of dairy cattle

Heritability estimates, by year of freshening of daughter, were obtained from daughter-dam and granddaughter-granddam regressions using 61,482 triply matched first lactations of artificially sired Holstein cows obtained from the Northeast Dairy Records Processing Laboratory. After adjusting for herd-year-season effects, residual effects may include additive and other genetic effects of the animal, maternal effects, cytoplasmic effects, and other environmental effects. Analysis of residuals showed that cytoplasmic effects accounted for no variation in milk and fat yield and fat percent. Weighted yearly heritability estimates and standard errors from daughter on dam regressions were .35 +/- .01 for milk yield, .30 +/- .01 for milk fat yield, and .63 +/- .01 for milk fat percent and from daughter on granddam regressions were .34 +/- .03 for milk production, .28 +/- .03 for milk fat production, and .55 +/- .03 for milk fat percent. The differences between daughter-dam and daughter-granddam heritability estimates, which estimate twice the fraction of variance due to cytoplasmic effects, were negative and not statistically significant for milk fat yield and also were negative but highly significant for milk fat percent.     

Validation of single nucleotide polymorphisms associated with milk production traits in dairy cattle

Single nucleotide polymorphism (SNP) associations with milk production traits found to be significant in different screening experiments, including SNP in genes hypothesized to be in gene pathways affecting milk production, were tested in a validation population to confirm their association. In total, 423 SNP were genotyped across 411 Holstein bulls, and their association with 6 milk production traits--Australian Selection Index (indicating the profitability of an animal's milk production), protein, fat, and milk yields, and protein and fat composition--were tested using single SNP regressions. Seventy-two SNP were significantly associated with one or more of the traits; their effects were in the same direction as in the screening experiment and therefore their association was considered validated. An over-representation of SNP (43 of the 423) on chromosome 20 was observed, including a SNP in the growth hormone receptor gene previously published as having an association with protein composition and protein and milk yields. The association with protein composition was confirmed in this experiment, but not the association with protein and milk yields. A multiple SNP regression analysis for all SNP on chromosome 20 was performed for all 6 traits, which revealed that this mutation was not significantly associated with any of the milk production traits and that at least 2 other quantitative trait loci were present on chromosome 20.     

Effects of supplementation of dairy cattle with fish oil on silage intake, milk yield and milk composition

The effects of level of fish oil inclusion in the diet on grass silage intake, and milk yield and composition of dairy cows offered either 5 or 10 kg concentrates/d were evaluated in a ten treatment, partly balanced, changeover design experiment involving 50 cows in early lactation. Concentrates were prepared to provide 0, 150, 300 or 450 g fish oil/cow per d or 300 g fish oil/cow per d from a premix when each animal was offered 5 kg/d. The fish oil was predominantly from herring and mackerel caught in the North Atlantic while the fish oil premix was obtained from a commercial source and used palm kernel expeller as a carrier. Increasing fish oil supplementation decreased silage dry matter intake and the concentrations of milk fat and protein, and increased milk yield and diet digestibility. There were significant interactions between concentrate feed level and level of fish oil for silage intake and milk yield. Other than for the concentrations of milk fat and protein, and 20:4n-6 fatty acids, the source of fish oil did not affect forage intake or animal performance. Fish oil supplementation also decreased the concentrations of milk protein by 0.9 g/kg for each 100 g increase in fish oil supplementation, the depression being similar at each level of concentrate feeding. Supplementing the feed of dairy cows with 450 g fish oil/cow per d decreased the concentration of milk fat by 15 g/kg. This study also showed that feeding dairy cattle with fish oil is an efficient method of increasing eicosapentaenoic acid in the human diet through transfer into milk.     

Association between milk protein gene variants and protein composition traits in dairy cattle

The objective of this study was to identify DNA markers in the 4 casein genes (CSN1S1, CSN1S2, CSN2, and CSN3) and the 2 major whey protein genes (LALBA and LGB) that show associations with milk protein profile measured by reverse-phase HPLC. Fifty-three single nucleotide polymorphisms (SNP) were genotyped for cows in a unique resource population consisting of purebred Holstein and (Holstein × Jersey) × Holstein crossbred animals. Seven traits were analyzed, including concentrations of α(S)-casein (CN), β-CN, κ-CN, α-lactalbumin, β-lactoglobulin, and 2 additional secondary traits, the total concentration of the above 5 milk proteins and the α(S)-CN to β-CN ratio. A substantial fraction of phenotypic variation could be explained by the additive genetic component for the 7 milk protein composition traits studied. Moreover, several SNP were significantly associated with all examined traits at an experiment-wise error rate of 0.05, except for α-lactalbumin. Importantly, the significant SNP explained a large proportion of the phenotypic variation of milk protein composition. Our findings could be used for selecting animals that produce milk with desired composition or desired processing and manufacturing properties.     

Effect of maternal age on milk production traits, fertility, and longevity in cattle

Longevity is the economically most important functional trait in cattle populations. However, with an increased productive lifespan, the number of offspring born by older dams increases. A higher maternal age might have negative effects on the performance of offspring. The objective of this study was to investigate the effect of maternal age on production (energy-corrected milk yield [ECM]) and functional traits (fertility; somatic cell score, and functional longevity) in Austrian dual-purpose Simmental cows. Age of dam had a significant effect on ECM yield and longevity. The ECM yield of daughters decreased with age of dam. Although the risk of culling slightly increased with age of dam, it was lowest for daughters of oldest dams. Results for fertility were non-significant, and results for somatic cell scores were inconsistent across parities.     

Phenotypic and genetic effects of season on milk production traits in dairy cattle in the Netherlands

Milk production systems in several countries show considerable differences between seasons. For example, in the Netherlands, cows are kept inside and fed silage in winter, whereas they are on pasture in summer. The differences between seasons affect milk yield and composition and might influence the genetic background of milk production traits. The objective of this study was to estimate phenotypic and genetic effects of season on milk production traits. For this purpose, 19,286 test-day milk production records of 1,800 first-parity Dutch Holstein-Frisian cows were available, and these cows were genotyped using a 50K SNP panel. Phenotypic effects of season were significant for all milk production traits. Effects of season were large for milk fat yield, fat content, and protein content. Genetic correlations between milk production traits in different seasons showed that genotype by season interaction effects were relatively small for most milk production traits. The genetic background of protein content and lactose content seems to be sensitive to seasonal effects. Furthermore, the genetic correlations between spring and autumn differed significantly from unity for almost all milk production traits. A genome-wide association study for genotype by season interaction identified chromosomal regions on BTA3, BTA14, BTA20, and BTA25 that showed genotype by season interaction effects, including a region containing DGAT1, which showed interaction effects for fat content and protein content.     

Associations among milk yield, yield persistency, conception, and culling of Israeli Holstein dairy cattle

Genetic correlations among Predicted Differences for milk yield corrected for economic value of fat content, annualized yield, yield persistency, conception rate, and culling rate were estimated. Correlations were .43 between yield persistency and annualized yield, .42 between yield persistency and conception rate, and .1 between annualized yield and conception rate. For Predicted Differences for these traits computed separately for each of first three parities, correlations between pairs were highest for annualized yield and lowest for culling rate. Regression coefficients for conception rate from cow insemination records on daily yield preceding insemination and on absolute change of yield during month of insemination were significantly negative for the first three parities. A positive pleiotropic effect for yield, yield persistency, and conception rate was suggested; therefore, progeny testing for yield persistency may improve yield and conception rate. High yields and large changes of yield during month of insemination adversely affected conception rate of cows within herds.     

Milk protein polymorphism in Danish dairy cattle and the influence of genetic variants on milk yield

In milk samples from 549 cows of the breeds Danish Jersey, Red Danish Dairy Cattle (RDM), and Black and White Danish Dairy Cattle (SDM) the genetic polymorphisms of the alpha-s1, beta and k-casein and beta=lactoglobulin (beta-Lg) loci were determined by isoelectric focusing in agarose gels. The results of the screening were compared with results obtained by Larsen and Thymann. In addition, the genetic linkage of the three casein loci was studied , and the association between milk protein genotypes and yields in first and second lactations of milk, fat and protein were investigated. The distribution of genotypes of all four milk protein systems was different from breed to breed. For Jersey cows, significant differences in the gene frequencies from the results of the 1966 investigation were found for alpha-s1 and k-casein and beta-Lg. For SDM cows a change in the k-casein frequency had occurred whereas for RDM cows no changes were found. Linkage between some of the casein loci was found within all three breeds. For the RDM breed the possible linkage between alpha-s1-casein and the other caseins could not be tested because nearly all the cows were homozygous for the alpha-s1-casein-B genotypes. beta-Casein genotypes were associated with yield parameters in all breeds. The A2A2 genotype of this protein gave higher yields of milk, fat, and protein in the second lactation than the A1A1 genotype.     

Negative influence of high maternal milk production before and after conception on offspring survival and milk production in dairy cattle

There is a paucity of studies on the effect of intrauterine conditions on subsequent progeny performance in dairy cows. Using a large national data set on Irish Holstein-Friesian dairy cows, the objective of this study was to determine if intrauterine conditions, quantified by a maternal genetic variance component, significantly affected milk production, age at first calving, calving interval, somatic cell score (natural logarithm of somatic cell count) and survival in first-, second-, and third-parity female offspring. Maternal genetic variance for each trait in each parity was estimated in a linear mixed model which included, other than fixed effects, direct additive genetic, maternal genetic, cytoplasmic and permanent environmental effect of the dam, and residual component. A covariance was also estimated between the direct additive and maternal genetic components where possible. Because calves in Irish dairy herds are separated from dams at birth, a significant maternal genetic variance (with all other random effects in the model) indicates a prepartum maternal effect. A significant maternal genetic variance was estimated for 305-d milk yield in first and third lactation, somatic cell score in first lactation, and survival to second lactation from 188,144 lactations on 80,881 animals. Where estimated, a negative correlation existed between the direct additive and maternal genetic components. Regression of maternal mixed model solutions on dam milk production at different stages relative to conception revealed that greater milk yield preconception and during gestation was associated with reduced survival and milk yield and greater somatic cell count in the progeny. This study suggests that offspring survival and performance are affected by prepartum conditions that offspring experience as an oocyte, embryo, or fetus, one of which is mediated through milk production (or factors related to milk production) of the dam.