Associations Among Descriptors of Herd Management and Phenotypic and Genetic Levels of Health and Fertility

Direct genetic effects, maternal genetic effects, and maternal genetic sensitivity on prenatal heat stress for calf diseases and corresponding genomic loci in German Holsteins

The aim of this study was to infer the effects of heat stress (HS) of dams during late gestation on direct and maternal genetic parameters for pneumonia (PNEU, 112,563 observations), diarrhea (DIAR, 176,904 observations), and omphalitis (OMPH, 176,872 observations) in Holstein calves kept in large-scale co-operator herds. The genotype dataset included 41,135 SNPs from 19,247 male and female cattle. Temperature-humidity indices (THI) during the last 8 wk of pregnancy were calculated, using the climate data from the nearest public weather station for each herd. Heat load effects were considered for average weekly THI larger than 60. Phenotypically, regression coefficients of calf diseases on prenatal THI during the last 8 wk of gestation were estimated in 8 consecutive runs. The strongest detrimental effects of prenatal HS on PNEU and DIAR were identified for the last week of pregnancy (wk 1). Thus, only wk 1 was considered in ongoing genetic and genomic analyses. In an advanced model considering prenatal HS, random regression coefficients on THI in wk 1 nested within maternal genetic effects (maternal slope effects for heat load) were considered as parameters to infer maternal sensitivity in response to prenatal THI alterations. Direct heritabilities from the advanced model ranged from 0.10 (THI 60) to 0.08 (THI 74) for PNEU and were close to 0.16 for DIAR. Maternal heritabilities for PNEU increased from 0.03 to 0.10 along the THI gradient. For DIAR, the maternal heritability was largest (0.07) at the minimum THI (THI = 60) and decreased to 0.05 at THI 74. Genetic correlations smaller than 0.80 for PNEU and DIAR recorded at THI 60 with corresponding diseases at THI 74 indicated genotype by climate interactions for maternal genetic effects. Genome-wide associations studies were performed using de-regressed proofs of genotyped sires for direct genetic, maternal genetic, and maternal slope effects. Thirty suggestive and 2 significant SNPs were identified from the GWAS. Forty-three genes located close to the suggestive SNPs (±100 kb) were annotated as potential candidate genes. Three biological processes were inferred on the basis of the these genes, addressing the negative regulation of the viral life cycle, innate immune response, and protein ubiquitination. Hence, the genetics of prenatal heat stress mechanisms are associated with immune physiology and disease resistance mechanisms.

Multistep analysis reveals the relationship between blood indices at the time of ovum pick-up and in vitro embryo production in heifers

The inflammatory factors of complete blood count (CBC) are associated with a decrease in the in vitro embryo production (IVP) outcome in women. The relation between the blood indices and in vitro fertilization (IVF) outcomes in bovines remains to be elucidated. Using ovum pick-up (OPU), oocytes were retrieved from heifers (n = 60) and inseminated separately with sperm. The blastocyst formation was recorded on day 7 after insemination for each animal and the blood indices were evaluated at the time of OPU. Then, heifers were classified on the basis of (1) blastocyst formation, cleaved vs. failed, or (2) inflammation, low-grade inflammation (lymphocyte counts > 5.6 × 10⁹/L) vs. no inflammation (lymphocyte counts < 5.6 × 10⁹/L). Oocytes derived from heifers with higher lymphocytes, red blood cells (RBC), platelets, hematocrit, red cell distribution width (RDW-SD) and plateletcrit values and lower monocytes, eosinophils, mean corpuscular hemoglobin (MCH) and MCH concentration (MCHC) successfully developed to the blastocyst stage. Heifers with low-grade inflammation numerically had a higher percentage of blastocyst formation than normal heifers. The principle component analysis (PCA) showed that blastocyst formation had the strongest positive association with RDW-cv and RDW-SD, while having a strong negative association with mean corpuscular volume (MCV), hemoglobin, MCHC and MCH. The PCA determined that the number of grade A COCs and the percentage of COCs reached the cleavage stage had a negative association with white blood cells (WBC), lymphocytes, basophils and monocytes, and a positive correlation with platelet to lymphocyte ratio, platelet distribution width (PDW) and plateletcrit. Network mapping detected close similarities between BFR and RDW-SD, MPV, and lymphocytes. The area under the receiver operating characteristic curve (AUC) identified that, eosinophils (AUC 0.80), RDW-SD (AUC 0.76), monocytes (AUC 0.76) and lymphocytes (AUC 0.76) had a good predictive ability to detect heifers with high OPU-IVP outcome (≥60%). In conclusion, these findings suggest that CBC indices at the time of OPU were associated with the IVF outcome and may be incorporated into protocols for the identification of heifers with high potential for blastocyst formation.

Genetic parameters for conception rate and milk production traits within and across Holstein herds with different housing types and feeding systems during the first 3 lactations

The housing types (HST) in which dairy cows are kept and the feeding systems (FDS) used differ among farmers in Japan. Here, we investigated the genetic relationships among conception rate at first insemination (CR) and milk production traits (PROD) during the first 3 lactations of Holstein cows by using a multiple-trait model that considered the trait values of herds with different HST [tiestall (TSL) barn, freestall (FS) barn, or grazing (GZ)] and FDS as separate traits. Milk production and conception records of Holstein cows in the Hokkaido region of Japan (283,611 records for first lactation, 253,902 for second, and 181,197 for third) were analyzed. We categorized herds with TSL or FS into 2 types of FDS for cows: separate feeding (SF) of roughage plus concentrate or feeding of total mixed ration, in which roughage and concentrates were mixed before feeding. The PROD analyzed were cumulative milk, fat, and protein yields within 305 d and lactation persistency, which we defined as the difference between milk yields at 240 and 60 d in milk. We estimated the heritabilities for CR or PROD within each HST or HST × FDS group and the genetic correlations between these traits within each group or across different groups within each lactation by using a 3-HST (TSL, FS, and GZ) × 2-trait (CR and each PROD) or 2-HST (TSL and FS) × 2-FDS × 2-trait animal model. Heritability estimates for CR in GZ were higher than those in TSL or FS, and genetic correlations for CR between GZ and TSL or FS barns were weaker than those between TSL and FS barns. In addition, genetic correlations between CR and PROD in GZ were weaker than those in TSL and FS barns. In the comparison among the 4 HST × FDS except GZ, heritability estimates for CR in FS × SF were higher than those in the others, and genetic correlations for CR between FS × SF and the other systems were relatively weak. These results indicated that differences in the production system for Holstein cows influence genotypic effects in terms of the cows' ability to conceive and the genetic relationships between fertility traits and milk production traits.

Genotype by environment interaction for female fertility traits under conventional and organic production systems in Danish Holsteins

Conventional and organic production systems mainly differ in feeding strategies, outdoor and pasture access, and the use of antibiotic treatments. These environmental differences could lead to a genotype by environment interaction (G × E) and a requirement for including G × E in breeding decisions. The objectives of this study were to estimate variance components and heritabilities for conventional and organic production systems and investigate G × E under these 2 production systems for female fertility traits in Danish Holsteins. The analyzed traits included the interval from calving to first insemination (ICF), the interval from first to last insemination, number of inseminations per conception (NINS), and non-return rate within 56 d after the first insemination. Records of female fertility in heifers and the first 3 lactations in cows as well as grass ratio of feed at herd level were collected during the period from 2011 to 2016. The performances of a trait in heifers and cows (lactation 1 to 3) were considered as different traits. The (co)variance components and the resulting heritabilities and genetic correlations were estimated using 2 models. One was a bivariate model treating performances of a trait under organic and conventional production systems as 2 different traits using a reduced data set, and the other was a reaction norm model with random regression on the production system and the grass ratio of feed using a full data set. The full data set comprised records of 37,836 females from 112 organic herds and 513,599 females from 1,224 conventional herds, whereas the reduced data set comprised records from all these 112 organic herds and 92,696 females from 185 convention herds extracted from the full data set with grass ratio of feed lower than 0.20. All female fertility performances of the organic production system were superior to those of the conventional production system. Besides, heterogeneities in additive genetic variances and heritabilities were observed between conventional and organic production systems for all traits. Furthermore, genetic correlations between these 2 production systems ranged from 0.607 to 1.000 estimated from bivariate models and from 0.848 to 0.999 estimated from reaction norm models. Statistically significant G × E were observed for NINS in heifers, non-return rate within 56 d after the first insemination in heifers, and ICF from the bivariate model, and for ICF and NINS in cows from the reaction norm model.

Plasma metabolomic profiles differ at the time of artificial insemination based on pregnancy outcome, in Bos taurus beef heifers

Infertility remains the most prevalent reason for cattle being removed from production environments. We utilized metabolomic profiling to identify metabolites in the blood plasma that may be useful in identifying infertile heifers at the time of artificial insemination (AI). Prior to AI, phenotypic parameters including body condition, weight, and reproductive organ measurements were collected. These were determined not effective at differentiating between fertile and infertile heifers. Analysis of the resulting metabolomic profiles revealed 15 metabolites at significantly different levels (T-test P ≤ 0.05), with seven metabolites having a greater than 2-fold difference (T-test P ≤ 0.05, fold change ≥2, ROC-AUC ≥ 0.80) between infertile and fertile heifers. We further characterized the utility of using the levels of these metabolites in the blood plasma to discriminate between fertile and infertile heifers. Finally, we investigated the potential role inflammation may play by comparing the expression of inflammatory cytokines in the white blood cells of infertile heifers to that of fertile heifers. We found significantly higher expression in infertile heifers of the proinflammatory markers tumor necrosis factor alpha (TNFα), interleukin 6 (IL6), and the C-X-C motif chemokine 5 (CXCL5). Our work offers potentially valuable information regarding the diagnosis of fertility problems in heifers undergoing AI.

Genotype by environment interaction for activity-based estrus traits in relation to production level for Danish Holstein

The objective of this study was to investigate whether genotype by environment interaction exists for female fertility traits and production of energy-corrected milk at 70d in milk (ECM70). Fertility traits considered were the activity-based estrus traits interval from calving to first high activity (CFHA), duration of high activity episode (DHA), as an indicator for first estrus duration, and strength of high activity episode (SHA), as an indicator for first estrus strength. The physical activity traits were derived from electronic activity tags for 11,522 first-parity cows housed in 125 commercial dairy herds. Data were analyzed using a univariate random regression animal model (URRM), by regressing the phenotypic performance on the average herd ECM70 as an environmental gradient. Furthermore, the genetic correlations between CFHA and ECM70 as a function of production level were estimated using a bivariate random regression animal model (BRRM). For all traits, heterogeneity of additive genetic variances and heritability estimates was observed. The heritability estimate for CFHA decreased from 0.25 to 0.10 with increasing production level and the heritability estimate for ECM70 decreased from 0.35 to 0.15 with increasing production level using URRM. The genetic correlation of the same trait in low and high production levels was around 0.74 for CFHA and 0.80 for ECM70 using URRM, but when data were analyzed using the multiple-trait analysis (MT), genetic correlation estimates between low and high production levels were not significantly different from unity. Furthermore, the genetic correlation of SHA between low and high production level was 0.22 using URRM, but the corresponding correlation estimate had large standard error when data were analyzed using MT. The genetic correlation between CFHA and ECM70 as a function of production environment was weak but unfavorable and decreased slightly from 0.09 to 0.04 with increasing production level using BRRM. Moreover, the same trend was observed when the data were analyzed using MT where the genetic correlation between CFHA and ECM70 in the low production environment was 0.29 compared with -0.13 in the high production environment, but these estimates had large standard errors. In conclusion, regardless of the trait used, in relation to average herd ECM70 production, the results indicated no clear evidence of strong genotype by environment interaction that would cause significant re-ranking of sires between low and high production environments.

Effects of different five-day progesterone-based synchronization protocols on the estrous response and follicular/luteal dynamics in dairy cows

This study compared the responses shown by lactating dairy cows to four different P4-based protocols for AI at estrus. Cows with no estrous signs 96 h after progesterone intravaginal device (PRID) removal were subjected to fixed-time AI (FTAI), and their data were also included in the study. In Experiment I, follicular/luteal and endometrial dynamics were assessed every 12 h from the beginning of treatment until AI. The estrous response was examined in Experiment II, and fertility was assessed in both experiments. The protocols consisted of a PRID fitted for five days, along with the administration of different combinations of gonadotropin releasing hormone (GnRH), equine chorionic gonadotropin and a single or double dose (24 h apart) of prostaglandin F2α. In Experiment I (40 cows), animals receiving GnRH at the start of treatment showed a significantly higher ovulation rate during the PRID insertion period while estrus was delayed. In Experiment II (351 cows), according to the odds ratios, cows showing luteal activity at the time of treatment were less likely to show estrus than cows with no signs of luteal activity. Treatment affected the estrous response and the interval from PRID removal to estrus but did not affect conception rates 28-34 days post AI. Primiparous cows displayed a better estrous response than multiparous cows. Our findings reveal acceptable results of 5-day P4-based protocols for AI at estrus in high-producing dairy cows. Time from treatment to estrus emerged as a good guide for FTAI after a 5-day P4-based synchronization protocol.

Genotype by environment interaction for livability of dairy calves from first parity cows

Death of calves around parturition is a matter of concern for dairy farmers. Relatively high stillbirth rates and unfavourable trends have been reported for Holstein heifers in the Netherlands and several other countries. In our study, we investigated herd differences, genetic parameters and genotype by environment interaction for heifer calf livability. A large dataset with data from calvings between 1993 and 2012 of Dutch dairy farms was used. There were considerable differences between herds in livability of calves from heifers, with averages ranging from 74% to 95%. Both herds with relatively high and low averages showed the same negative trend between 1993 and 2012, with largest declines in herds with the lowest averages. We found that heritability and genetic variation of first parity livability were substantially larger in herd environments where the likelihood of stillbirth was high v. environments where stillbirth was at a low level. The genetic correlations between herd environment levels were all very close to unity, indicating that ranking of sires was similar for all environments. However, for herds with a relatively high stillbirth incidence selecting sires with favourable breeding values is expected to be twice as profitable as in herds with a relatively low stillbirth incidence.

Genetic parameters for energy balance, fat /protein ratio, body condition score and disease traits in German Holstein cows

Various health problems in dairy cows have been related to the magnitude and duration of the energy deficit post partum. Energy balance indicator traits like fat/protein ratio in milk and body condition score could be used in selection programmes to help predicting breeding values for health traits, but currently there is a lack of appropriate genetic parameters. Therefore, genetic correlations among energy balance, fat/protein ratio, and body condition score, and mastitis, claw and leg diseases, and metabolic disorders were estimated using linear and threshold models on data from 1693 primiparous cows recorded within the first 180 days in milk. Average daily energy balance, milk fat/protein ratio and body condition score were 8 MJ NEL, 1.13 and 2.94, respectively. Disease frequencies (% cows with at least one case) were 24.6% for mastitis, 9.7% for metabolic disorders and 28.2% for claw and leg diseases. Heritability estimates were 0.06, 0.30 and 0.34 for energy balance, fat/protein ratio and body condition score, respectively. For the disease traits, heritabilities ranged between 0.04 and 0.15. The genetic correlations were, in general, associated with large standard errors, but, although not significant, the results suggest that an improvement of overall health can be expected if energy balance traits are included into future breeding programmes. A low fat/protein ratio might serve as an indicator for metabolic stability and health of claw and legs. Between body condition and mastitis, a significant negative correlation of -0.40 was estimated. The study provides a new insight into the role energy balance traits can play as auxiliary traits for robustness of dairy cows. It was concluded that both, fat/protein ratio and body condition score, are potential variables to describe how well cows can adapt to the challenge of early lactation. However, the genetic parameters should be re-estimated on a more comprehensive data set.

Simultaneous estimation of genotype by environment interaction accounting for discrete and continuous environmental descriptors in Irish dairy cattle

Genotype by environment interaction can be analyzed by using a multi-trait model in which a trait measured in different environments is considered as separate traits. Alternatively, it can be analyzed by using a reaction norm model, in which the trait is considered a function of an environmental descriptor. Here, a model is developed where the 2 approaches are combined such that the effect of a continuous environmental descriptor can be analyzed in 2 or more discrete environments. The model is applied to somatic cell score (SCS) in relation to average herd milk production in 2 production environments: spring calving and year-round calving in Ireland. Heritabilities and additive genetic variances for SCS increased somewhat with increasing milk production and were higher in year-round calving. Under the combined model, the genetic correlation between spring and year-round calving was estimated at 0.82 to 0.84, clearly lower than obtained in a bivariate analysis ignoring effects of herd milk production. Thus, when estimating the genetic correlation between environments, effects of one environmental descriptor may be obscured by another, but can be disentangled in an analysis combining the reaction norm and the multi-trait approach. Such models will be especially useful for analyzing questions such as whether the effect of increasing production or temperature is more severe in different production systems or geographic regions.

Genetic evaluation of lactation persistency for five breeds of dairy cattle

Cows with high lactation persistency tend to produce less milk than expected at the beginning of lactation and more than expected at the end. Best prediction of lactation persistency is calculated as a function of trait-specific standard lactation curves and linear regressions of test-day deviations on days in milk. Because regression coefficients are deviations from a tipping point selected to make yield and lactation persistency phenotypically uncorrelated it should be possible to use 305-d actual yield and lactation persistency to predict yield for lactations with later endpoints. The objectives of this study were to calculate (co)variance components and breeding values for best predictions of lactation persistency of milk (PM), fat (PF), protein (PP), and somatic cell score (PSCS) in breeds other than Holstein, and to demonstrate the calculation of prediction equations for 400-d actual milk yield. Data included lactations from Ayrshire, Brown Swiss, Guernsey (GU), Jersey (JE), and Milking Shorthorn (MS) cows calving since 1997. The number of sires evaluated ranged from 86 (MS) to 3,192 (JE), and mean sire estimated breeding value for PM ranged from 0.001 (Ayrshire) to 0.10 (Brown Swiss); mean estimated breeding value for PSCS ranged from -0.01 (MS) to -0.043 (JE). Heritabilities were generally highest for PM (0.09 to 0.15) and lowest for PSCS (0.03 to 0.06), with PF and PP having intermediate values (0.07 to 0.13). Repeatabilities varied considerably between breeds, ranging from 0.08 (PSCS in GU, JE, and MS) to 0.28 (PM in GU). Genetic correlations of PM, PF, and PP with PSCS were moderate and favorable (negative), indicating that increasing lactation persistency of yield traits is associated with decreases in lactation persistency of SCS, as expected. Genetic correlations among yield and lactation persistency were low to moderate and ranged from -0.55 (PP in GU) to 0.40 (PP in MS). Prediction equations for 400-d milk yield were calculated for each breed by regression of both 305-d yield and 305-d yield and lactation persistency on 400-d yield. Goodness-of-fit was very good for both models, but the addition of lactation persistency to the model significantly improved fit in all cases. Routine genetic evaluations for lactation persistency, as well as the development of prediction equations for several lactation end-points, may provide producers with tools to better manage their herds.

The use of data from sampling for bacteriology for genetic selection against clinical mastitis

One breeding objective of Dutch cattle breeders is to improve genetic resistance against clinical and subclinical mastitis. Because of a lack of direct mastitis information, udder health breeding values are based on indirect traits. Inclusion of direct information on clinical mastitis could improve reliability of breeding values. The aim of this study was to investigate whether data from milk samples sent in for bacteriology are potential sources of information for the occurrence of mastitis, which may be used in animal breeding, and if so how this data can be used. Although there are 2 separate flows of milk samples for bacteriology in the Netherlands, it was not considered necessary to account for the origin of the samples. In both flows, the majority of the samples are visually normal and flow-specific traits are highly correlated. Therefore, information from these flows is combined for genetic analysis. Nearly two-thirds of the bacteriology data could be linked to milk recording and pedigree records. Relatively few farmers (<3%) took 5 or more samples for bacteriology between January 1, 2003, and March 31, 2006. Their herds had, on average, greater milk production and lower cell counts than herds for which no samples were taken. However, the range and variation within both groups of herds for these variables was similar and there was a large overlap in sires used within both groups. Whether or not samples were taken for bacteriology turned out to be a potentially useful indicator for clinical mastitis at the cow level, because this trait had a strong positive genetic correlation with clinical mastitis registered by farmers (0.84 or 0.89, depending on the data set) and similar heritability (2%) and genetic variation. Also, genetic correlations of bacteriology with SCC traits were similar to those for farmer-registered clinical mastitis. An important advantage of these bacteriology data is that they are already collected routinely and stored in a central database in the Netherlands; this is not the case for registration of clinical cases. Thus, data from bacteriological culturing can be used for genetic improvement of udder health.

A genome scan for quantitative trait locus by environment interactions for production traits

Genotype by environment interactions between milk production traits and production level have often been observed. To increase the power of quantitative trait loci (QTL) detection, QTL by environment interaction was included in QTL analyses for the milk, protein, and fat yields. The aim of the study was to detect QTL with interaction effects with the production environment. The QTL effects were modeled through random regression models for within-herd production level. All autosomes except Bos taurus autosome 6 were included in the analysis. A more detailed study of chromosome 6 is planned. For milk yield, 5 QTL were observed, 2 of which had interaction effects with production level (suggestive linkage). For protein yield, 5 QTL were observed, 3 of which had interaction effects (suggestive linkage). For fat yield, 3 QTL were observed, none of which had interaction effects with the environment (suggestive linkage). Thus, some QTL with interaction effects seemingly exist for milk yield and protein yield. For such QTL, estimated correlations between slope and intercept of the effect (close to 1 or -1) indicated that only 2 alleles were segregating. The study indicates that QTL by environment interactions exist, and that random regression models that describe the environment as herd production level can detect this interaction.

Short Communication: Changes in the Association Between Milk Yield and Age at First Calving in Holstein Cows with Herd Environment Level for Milk Yield

The aim of this study was to evaluate the effect of herd environment class on the genetic and phenotypic relationships of mature equivalent milk yield (MY) on age at first calving (AFC). Data analyzed were 248,230 first parity records of Holstein cows, daughters of 588 sires in 3,042 herds in the United States. Heritability for AFC was 0.33 +/- 0.01 and 0.20 +/- 0.01 in high and low environment herds, respectively, and 0.47 +/- 0.01 in the complete data set. The correlation between AFC sires' predicted breeding values of low and high classes was 0.69. Genetic correlations between MY and AFC were -0.52 +/- 0.02 and -0.31 +/- 0.03 in high and low environment herds, respectively, and -0.44 +/- 0.02 in the complete data set representing intermediate environments. If selection is based on the whole data set, expected correlated responses for AFC estimated as a result of 1,000 kg of genetic gain in MY, for high and low herd environment herds were -26.1 and -15.3 d, respectively, and -32.6 for the complete data set; hence the highest reduction in AFC occurs in intermediate environment herds. Different estimates of the heritability of AFC, the correlation between AFC breeding values of low and high classes as well as changes in the genetic correlation between MY and AFC across environments indicate genotype x environment interaction. Caution in interpretation is warranted because genetic relationships are dynamic, especially in populations undergoing selection. Current relationships may differ from those during the time period of the present study (1987-1994). Notwithstanding this possibility, methods and findings from the present study provide insight about the complexity of genetic association and genotype x environment interactions between AFC and MY.

Factors affecting the fertility of high producing dairy herds in northeastern Spain

Infertility has been often correlated to a rising milk yield in high producing dairy cattle. The aim of the present study was to evaluate, using logistic regression procedures, the effects of several management indicators on the fertility of four dairy herds in northeastern Spain. Data derived from 10,965 artificial insemination (AI). The factors examined were: herd, milking frequency (three versus two milkings per day), lactation number, previous twinning and disorders such as placenta retention and pyometra, milk production at AI, the inseminating bull, season (warm versus cool period) and year effects, AI technician and repeat breeding syndrome (cows undergoing four or more AI). Our findings indicated no effects on fertility of the herd, year of AI, previous twining, placenta retention and pyometra and milk production at AI. Based on the odds ratios, the likelihood of pregnancy decreased: in cows milked three times per day (by a factor of 0.62); for each one unit increase in lactation number (by a factor of 0.92); for inseminations performed during the warm period (by a factor of 0.67); in repeat breeder cows (by a factor of 0.73); and when 3 of the 45 inseminating bulls included in the study were used (by factors of 0.35, 0.43 and 0.44, respectively). Of the 13 AI technicians participating in the study, 3 were related to a fertility rate improved by odds ratios of 1.86, 1.84 and 1.30, respectively, whereas 2 technicians gave rise to fertility rates reduced by odds ratios of 0.64 and 0.49, respectively. Under our study conditions, management practices were able to compensate for the effects of previous twining and reproductive disorders such as placenta retention and pyometra. However, fertility was significantly affected by the factors milking frequency, AI technician, inseminating bull, repeat breeding syndrome, lactation number and AI season.

Genotype by Environment Interaction for Somatic Cell Score Across Bulk Milk Somatic Cell Count and Days in Milk

The objective of this paper was to investigate the importance of a genotype x environment interaction (G x E) for somatic cell score (SCS) across levels of bulk milk somatic cell count (BMSCC), number of days in milk (DIM), and their interaction. Variance components were estimated with a model including random regressions for each sire on herd test-day BMSCC, DIM, and the interaction of BMSCC and DIM. The analyzed data set contained 344,029 test-day records of 24,125 cows, sired by 182 bulls, in 461 herds comprising 13,563 herd test-days. In early lactation, considerable G x E effects were detected for SCS, indicated by 3-fold higher genetic variance for SCS at high BMSCC compared with SCS at low BMSCC, and a genetic correlation of 0.72 between SCS at low and at high BMSCC. Estimated G x E effects were smaller during late lactation. Genetic correlations between SCS at the same level of BMSCC, across DIM, were between 0.43 and 0.89. The lowest genetic correlation between SCS measures on any 2 possible combinations of BMSCC and DIM was 0.42. Correlated responses in SCS across BMSCC and DIM were, on some occasions, less than half the direct response to selection in the response environment. Responses to selection were reasonably high among environments in the second half of the lactation, whereas responses to selection between environments early and late in lactation tended to be low. Selection for reduced SCS yielded the highest direct response early in lactation at high BMSCC.

Genetic correlations between milk production and health and fertility depending on herd environment

High milk production in dairy cattle can have negative side effects on health and fertility traits. This paper explores the genetic relationship of milk yield with health and fertility depending on herd environment. A total of 71,720 lactations from heifers calving in 1997 to 1999 in the Netherlands were analyzed. Herd environment was described by 4 principal components: intensity, average fertility, farm size, and relative performance indicating whether herds had good (poor) health and fertility despite a high (low) production. Fertility was evaluated by days to first service and number of inseminations (NINS); somatic cell score was used as a measure of udder health. Data were analyzed with a multitrait reaction norm model. Genetic correlation within traits across environments ranged from 0.84 to unity. Genetic correlations of the 3 traits with milk yield were antagonistic but varied over environments. Genetic correlation of milk yield with days to first service varied from 0.30 in small herds to 0.48 in herds with low average fertility. Correlations with NINS varied from 0.18 in large herds to 0.64 in high fertility herds, and with somatic cell score from 0.25 in herds with a high fertility relative to production to 0.47 in herds with a relative low fertility. Selection in environments of average value resulted in different predicted responses over environments. For example, selection for a decrease of NINS of 0.1 in an average production environment decreased milk yield by 35 kg in low production herds, but by 178 kg in high production herds.