Single-step genome-wide association for longitudinal traits of Canadian Ayrshire,Holstein, and Jersey dairy cattle

Estimating single nucleotide polymorphism (SNP) effects over time is essential to identify and validate candidate genes (or quantitative trait loci) associated with time-dependent variation of economically important traits and to better understand the underlying mechanisms of lactation biology. Therefore, in this study, we aimed to estimate time-dependent effects of SNP and identifying candidate genes associated with milk (MY), fat (FY), and protein (PY) yields, and somatic cell score (SCS) in the first 3 lactations of Canadian Ayrshire, Holstein, and Jersey breeds, as well as suggest their potential pattern of phenotypic effect over time. Random regression coefficients for the additive direct genetic effect were estimated for each animal using single-step genomic BLUP, based on 2 random regression models: one considering MY, FY, and PY in the first 3 lactations and the other considering SCS in the first 3 lactations. Thereafter, SNP solutions were obtained for random regression coefficients, which were used to estimate the SNP effects over time (from 5 to 305 d in lactation). The top 1% of SNP that showed a high magnitude of SNP effect in at least 1 d in lactation were selected as relevant SNP for further analyses of candidate genes, and clustered according to the trajectory of their SNP effects over time. The majority of SNP selected for MY, FY, and PY increased the magnitude of their effects over time, for all breeds. In contrast, for SCS, most selected SNP decreased the magnitude of their effects over time, especially for the Holstein and Jersey breeds. In general, we identified a different set of candidate genes for each breed, and similar genes were found across different lactations for the same trait in the same breed. For some of the candidate genes, the suggested pattern of phenotypic effect changed among lactations. Among the lactations, candidate genes (and their suggested phenotypic effect over time) identified for the second and third lactations were more similar to each other than for the first lactation. Well-known candidate genes with major effects on milk production traits presented different suggested patterns of phenotypic effect across breeds, traits, and lactations in which they were identified. The candidate genes identified in this study can be used as target genes in studies of gene expression.     

Genomic prediction of lactation curves for milk,fat, protein,and somatic cell score in Holstein cattle

Application of random regression models (RRM) in a 2-step genomic prediction might be a feasible way to select young animals based on the complete pattern of the lactation curve. In this context, the prediction reliability and bias of genomic estimated breeding value (GEBV) for milk, fat, and protein yields and somatic cell score over days in milk (DIM) using a 2-step genomic approach were investigated. In addition, the effect of including cows in the training and validation populations was investigated. Estimated breeding values for each DIM (from 5 to 305 d) from the first 3 lactations of Holstein animals were deregressed and used as pseudophenotypes in the second step. Individual additive genomic random regression coefficients for each trait were predicted using RRM and genomic best linear unbiased prediction and further used to derive GEBV for each DIM. Theoretical reliabilities of GEBV obtained by the RRM were slightly higher than theoretical reliabilities obtained by the accumulated yield up to 305 d (P305). However, validation reliabilities estimated for GEBV using P305 were higher than for GEBV using RRM. For all traits, higher theoretical and validation reliabilities were estimated when incorporating genomic information. Less biased GEBV estimates were found when using RRM compared with P305, and different validation reliability and bias patterns for GEBV over time were observed across traits and lactations. Including cows in the training population increased the theoretical reliabilities and bias of GEBV; nonetheless, the inclusion of cows in the validation population does not seem to affect the regression coefficients and the theoretical reliabilities. In summary, the use of RRM in 2-step genomic prediction produced fairly accurate GEBV over the entire lactation curve for all analyzed traits. Thus, selecting young animals based on the pattern of lactation curves seems to be a feasible alternative in genomic selection of Holstein cattle for milk production traits.     

Genome-wide association study for milk production traits in a Brazilian Holstein population

Advances in the molecular area of selection have expanded knowledge of the genetic architecture of complex traits through genome-wide association studies (GWAS). Several GWAS have been performed so far, but confirming these results is not always possible due to several factors, including environmental conditions. Thus, our objective was to identify genomic regions associated with traditional milk production traits, including milk yield, somatic cell score, fat, protein and lactose percentages, and fatty acid composition in a Holstein cattle population producing under tropical conditions. For this, 75,228 phenotypic records from 5,981 cows and genotypic data of 56,256 SNP from 1,067 cows were used in a weighted single-step GWAS. A total of 46 windows of 10 SNP explaining more than 1% of the genetic variance across 10 Bos taurus autosomes (BTA) harbored well-known and novel genes. The MGST1 (BTA5), ABCG2 (BTA6), DGAT1 (BTA14), and PAEP (BTA11) genes were confirmed within some of the regions identified in our study. Potential novel genes involved in tissue damage and repair of the mammary gland (COL18A1), immune response (LTTC19), glucose homeostasis (SLC37A1), synthesis of unsaturated fatty acids (LTBP1), and sugar transport (SLC37A1 and MFSD4A) were found for milk yield, somatic cell score, fat percentage, and fatty acid composition. Our findings may assist genomic selection by using these regions to design a customized SNP array to improve milk production traits on farms with similar environmental conditions.     

Estimation of quantitative trait loci parameters for milk production traits in German Holstein dairy cattle population

The main objective of this study was to estimate the proportion of total genetic variance attributed to a quantitative trait locus (QTL) on Bos taurus autosome 6 (BTA6) for milk production traits in the German Holstein dairy cattle population. The analyzed chromosomal region on BTA6 spanned approximately 70 cM, and contained 6 microsatellite markers. Milk production data were obtained from routine genetic evaluation for 4500 genotyped German Holstein bulls. Technical aspects related to the estimation of model parameters for a large data set from routine genotype recording were outlined. A fixed QTL model and a random QTL model were introduced to incorporate marker information into parameter estimation and genetic evaluation. Estimated QTL variances, expressed as the ratio of QTL to polygenic variances, were 0.04, 0.03, and 0.07 for milk yield; 0.06, 0.08, and 0.14 for fat yield; and 0.04, 0.04, and 0.11 for protein yield, in the first 3 parities, respectively. The estimated QTL positions, expressed as distances from the leftmost marker DIK82, were 18, 31, and 17 cM for milk yield; 25, 17, and 9 cM for fat yield; and 16, 30, and 17 cM for protein yield in the 3 respective parities. Because the data for the parameter estimation well represented the current population of active German Holstein bulls, the QTL parameter estimates have been used in routine marker-assisted genetic evaluation for German Holsteins.     

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.     

Parameters for milk somatic cell score and relationships with production traits in primiparous dairy sheep

A total of 13,066 first-lactation test-day records of 2,277 Valle del Belice ewes from 17 flocks were used to estimate genetic parameters for somatic cell scores (SCS) and milk production traits, using a repeatability test-day animal model. Heritability estimates were low and ranged from 0.09 to 0.14 for milk, fat, and protein yields, and contents. For SCS, the heritability of 0.14 was relatively high. The repeatabilities were moderate and ranged from 0.29 to 0.47 for milk production traits. The repeatability for SCS was 0.36. Flock-test-day explained a large proportion of the variation for milk production traits, but it did not have a big effect on SCS. The genetic correlations of fat and protein yields with fat and protein percentages were positive and high, indicating a strong association between these traits. The genetic correlations of milk production traits with SCS were positive and ranged from 0.16 to 0.31. The results showed that SCS is a heritable trait in Valle del Belice sheep and that single-trait selection for increased milk production will also increase SCS.     

Climatic effects on milk production traits and somatic cell score in lactating Holstein-Friesian cows in different housing systems

The objective of this study was to compare the effect of the temperature-humidity index (THI) on milk production traits and somatic cell score (SCS) of dairy cows raised in 4 different housing systems: (1) warm loose housing with access to grazing (WG), (2) warm loose housing without access to grazing (WI), (3) cold loose housing with access to grazing (CG), and (4) cold loose housing without access to grazing (CI). For each of the 4 housing systems, 5 farms with a herd size of 70 to 200 lactating cows in Lower Saxony, Germany, were studied. Ambient temperature and relative humidity were recorded hourly in each barn to calculate THI. Milk production data included 21,546 test-day records for milk, fat, and protein yield, and SCS. These data were associated with the average THI of the 3 d preceding the respective measurement, which was divided into 6 classes (<45, ≥45 to <50, ≥50 to <55, ≥55 to <60, ≥60 to <65, and ≥65). Furthermore, bulk milk samples including the fat and protein percentage, and SCS taken 4 to 6 times per month were associated with the average and maximum THI of the 3 d before sampling. Data were recorded from April 2010 to March 2011. In each of the housing systems, monthly THI values above 60, indicating heat stress, were recorded between June and September, with higher values in WI and WG. In all systems, fat-corrected milk, fat, and protein yields of the test-day records decreased in tendency from 60 ≤ THI < 65 to THI >65. In WI and CI, values for SCS were greater in the class THI >65 than in 60 ≤ THI < 65, whereas no difference between any of the THI classes was found in WG and CG. The fat and protein percentage of the bulk milk samples decreased with increasing 3-d maximum THI in all 4 systems, whereas the SCS increased with increasing 3-d average THI. In conclusion, negative effects of heat stress conditions under a temperate climate on milk production traits and SCS were found, although a housing system being superior to the other systems in altering heat stress effects was not identified.     

Effect of intramammary infection with non-aureus staphylococci in early lactation in dairy heifers on quarter somatic cell count and quarter milk yield during the first 4 months of lactation

A longitudinal study was conducted to assess to what extent intramammary infection (IMI) with non-aureus staphylococci (NAS) within the first 4 d after calving in dairy heifers affects quarter milk yield (qMY) and quarter milk somatic cell count (qSCC) during the first 4 mo of lactation. In total, 324 quarters from 82 Holstein Friesian heifers from 3 commercial dairy herds equipped with an automatic milking system were included and followed from calving up to 4 mo in lactation. The automatic milking system allowed us to precisely determine the daily qMY. A milk sample from each quarter was collected in early lactation (between 1 and 4 d in milk) for bacteriological culturing and measurement of the qSCC. Subsequently, milk samples were taken on a biweekly basis for measurement of the qSCC. The milk prolactin level in early lactation was measured, and the relation with NAS IMI was determined. Overall, NAS IMI in early lactation caused only a slight but significant increase in qSCC compared with milk from noninfected quarters during the first 4 mo in lactation, whereas no significant difference in daily qMY was present between NAS-infected and noninfected quarters. The milk prolactin level in early lactation did not differ between NAS-infected and noninfected quarters either. Our data suggest that IMI with NAS (as a group) present shortly after calving do not have an adverse effect on later production. The milk prolactin concentrations were not dissimilar between NAS-infected and noninfected quarters and thus cannot explain why NAS-infected quarters do not produce less than noninfected quarters.     

Multitrait quantitative trait Loci mapping for milk production traits in danish Holstein cattle

The aims of this study were (1) to confirm previously identified quantitative trait loci (QTL) on bovine chromosomes 6, 11, 14, and 23 in the Danish Holstein cattle population, (2) to assess the pleiotropic nature of each QTL on milk production traits by building multitrait and multi-QTL models, and (3) to include pedigree information on nongenotyped individuals to improve the estimation of genetic parameters underlying the random QTL model. Nineteen grandsire families were analyzed by single-trait (ST) and multitrait (MT) QTL mapping methods. The variance component-based QTL mapping model was implemented via restricted maximum likelihood (REML) to estimate QTL position and parameters. Segregation of the previously identified QTL was confirmed on bovine chromosomes 6, 11, and 14, but not on 23. A highly significant (1% chromosome-wise level) QTL was found on chromosome 6, between 37 and 73 cM. This QTL had a strong effect on protein percentage (PP) and fat percentage (FP) according to ST analyses, and effects on PP, FP, milk yield (MY), fat yield (FY), and protein yield (PY) in MT analyses. A QTL affecting PP was detected on chromosome 11 (at 70 cM) using ST analysis. The MT analysis revealed a second QTL (at 67 cM) approaching significance with an effect on MY. The ST analysis identified a QTL for MY and FP on chromosome 14, between 10 and 24 cM. The extended pedigree (nongenotyped animals) was included to estimate genetic parameters underlying the random QTL model; that is, additive polygenic and QTL variances. In general, the estimates of the QTL variance components were smaller but more precise when the extended pedigree was considered in the analysis.     

Detection of quantitative trait loci in Danish Holstein cattle affecting clinical mastitis, somatic cell score, udder conformation traits, and assessment of associated effects on milk yield

The aim of this study was to 1) detect QTL across the cattle genome that influence the incidence of clinical mastitis and somatic cell score (SCS) in Danish Holsteins, and 2) characterize these QTL for pleiotropy versus multiple linked quantitative trait loci (QTL) when chromosomal regions affecting clinical mastitis were also affecting other traits in the Danish udder health index or milk production traits. The chromosomes were scanned using a granddaughter design where markers were typed for 19 to 34 grandsire families and 1,373 to 2,042 sons. A total of 356 microsatellites covering all 29 autosomes were used in the scan. Among the across-family regression analyses, 16 showed chromosome-wide significance for the primary traits incidence of clinical mastitis in first (CM1), second (CM2), and third (CM3) lactations, and SCS. Regions of chromosomes 5, 6, 9, 11, 15, and 26 were found to affect CM and regions of chromosomes 5, 6, 8, 13, 22, 23, 24, and 25 affected SCS. Markers on chromosomes 6, 11, 15, and 26 can be used to perform marker-assisted selection on CM without a direct negative selection on milk yield, because no effects were detected on the milk traits. Comparing multi-trait models assuming either a pleiotropic QTL affecting 2 traits or 2 QTL each affecting 1 trait gave some evidence to distinguish between these models. For Bos taurus autosome 5, the most likely models were a pleiotropic QTL affecting CM2, CM3, and SCS, and a linked QTL affecting fat yield index. For Bos taurus autosome 9, the most likely model is a pleiotropic QTL affecting CM1 and CM2 at approximately 8 cM.     

Relationship of test-day somatic cell score with test-day and lactation milk yields

To determine the relationship of test-day (TD) somatic cell score (SCS) to TD and lactation milk yields, 1,320,590 records from Holstein first and second calvings from 1995 through 2002 were examined. All lactations had recorded yield and SCS for at least the first 4 TD. Least square analyses were conducted for yields on TD 2 through 10 within herd and cow. The model included regressions on current TD SCS and mean SCS of all previous TD with separate estimates by parity; effects for parity and calving year were included as well as regression on days in milk on TD 1. Corresponding analyses were conducted without regression on current SCS. An analysis of lactation yield was performed with a similar model and regression on all TD SCS. The SCS was highest most often on TD 1 for parity 1 (22.5%) and on TD 10 for parity 2 (18.5%). Regression of TD milk yield on mean of previous TD SCS was highest during the latter half of lactation (maximum of -0.346 kg/SCS unit on TD 9) for parity 1 and during TD through 7 (maximum of -0.366 kg/SCS unit on TD 4) for parity 2. Regression of TD yield on current TD SCS tended to be larger for later lactation. Regression of lactation yield on TD SCS was negative and important for TD 1 through 6 for parity 1 and for all TD for parity 2. To minimize milk loss, mastitis control is most important immediately pre- and postcalving for parity 1 and throughout lactation for parity 2.     

Genome-wide association study for calving traits in Danish and Swedish Holstein cattle

A total of 22 quantitative trait loci (QTL) were detected on 19 chromosomes for direct and maternal calving traits in cattle using a genome-wide association study. Calving performance is affected by the genotypes of both the calf (direct effect) and dam (maternal effect). To identify the QTL contributing these effects to calving characteristics, we performed a genome-wide association study using a mixed-model analysis in Danish and Swedish Holstein cattle. The analysis incorporated 2,062 progeny-tested bulls, and 36,387 single nucleotide polymorphism markers on 29 bovine autosomes were analyzed for association with 14 calving traits. Strong evidence for the presence of QTL that affect calving traits was observed on chromosomes 4, 6, 12, 18, 20, and 25. The QTL intervals were generally smaller than those described in earlier linkage studies. The identification of calving trait-associated single nucleotide polymorphisms and mapping of the corresponding QTL in small chromosomal regions will facilitate the search for candidate calving performance genes and polymorphisms.     

Detection of quantitative trait loci affecting milk production, health, and reproductive traits in Holstein cattle

We report putative quantitative trait loci affecting female fertility and milk production traits using the merged data from two research groups that conducted independent genome scans in Dairy Bull DNA Repository grandsire families to identify quantitative trait loci (QTL) affecting economically important traits. Six families used by both groups had been genotyped for 367 microsatellite markers covering 2713.5 cM of the cattle genome (90%), with an average spacing of 7.4 cM. Phenotypic traits included PTA for pregnancy rate and daughter deviations for milk, protein and fat yields, protein and fat percentages, somatic cell score, and productive life. Analysis of the merged dataset identified putative quantitative trait loci that were not detected in the separate studies, and the pregnancy rate PTA estimates that recently became available allowed detection of pregnancy rate QTL for the first time. Sixty-one putative significant marker effects were identified within families, and 13 were identified across families. Highly significant effects were found on chromosome 3 affecting fat percentage and protein yield, on chromosome 6 affecting protein and fat percentages, on chromosome 14 affecting fat percentage, on chromosome 18 affecting pregnancy rate, and on chromosome 20 affecting protein percentage. Within-family analysis detected putative QTL associated with pregnancy rate on six chromosomes, with the effect on chromosome 18 being the most significant statistically. These findings may help identify the most useful markers available for QTL detection and, eventually, for marker-assisted selection for improvement of these economically important traits.     

Association of candidate gene polymorphisms with milk technological traits,yield, composition,and somatic cell score in Italian Holstein-Friesian sires

Advances in DNA-based marker technology have enabled the identification of genomic regions underlying complex phenotypic traits in livestock species. The incorporation of detected quantitative trait loci into genetic evaluation provides great potential to enhance selection accuracies, hence expediting the genetic improvement of economically important traits. The objective of the present study was to investigate 96 single nucleotide polymorphisms (SNP) located in 53 candidate genes previously reported to have effects on milk production and quality traits in a population of highly selected Holstein-Friesian bulls. A total of 423 semen samples were used to genotype the bulls through a custom oligo pool assay. Forty-five SNP in 32 genes were found to be associated with at least 1 of the tested traits. Most significant and favorable SNP trait associations were observed for polymorphisms located in CCL3 and AGPAT6 genes for fat yield (0.037 and 0.033 kg/d, respectively), DGKG gene for milk yield (0.698 kg/d), PPARGC1A, CSN1S1, and AGPAT6 genes for fat percentage (0.127, 0.113, and 0.093%, respectively), GHR gene for protein (0.064%) and casein percentage (0.053%), and TLR4 gene for fat (0.090%), protein (0.066%), and casein percentage (0.050%). Somatic cell score was favorably affected by GHR (?0.095) and POU1F1 (?0.137), and interesting SNP-trait associations were observed for polymorphisms located in CSN2, POU1F1, and AGPAT6 genes for rennet coagulation time (?0.592, ?0.558, and ?0.462 min, respectively), and GHR and CSN2 genes for curd firmness 30 min after rennet addition (1.264 and 1.183 mm, respectively). In addition to the influence of individual SNP, the effects of composite genotypes constructed by grouping SNP according to their individual effects on traits considered in the analysis were also examined. Favorable and significant effects on milk traits were observed for 2 composite genotypes, one including 10 SNP and the other 4 SNP. The former was associated with an increase of milk (0.075 kg/d), fat (0.097 kg/d), protein (0.083 kg/d), and casein yields (0.065 kg/d), and the latter was associated with an increase of fat (0.244%), protein (0.071%), and casein percentage (0.047%). Although further research is required to validate the identified SNP loci in other populations and breeds, our results can be considered as a preliminary foundation for further replication studies on gene-assisted selection programs.     

Effect of kappa-casein and beta-lactoglobulin loci on milk production traits and reproductive performance of Holstein cows

The effects of kappa-casein (kappa-CN) and beta-lactoglobulin (beta-LG) loci on milk production traits (milk, fat, protein, and lactose yield, fat, protein, and lactose content) and reproductive performance (gestation length, calving interval, age at first and second calving, number of services per conception) was estimated for 278 Holstein cows in the first 2 lactations. Genotypes of kappa-CN and beta-LG were determined by alkaline and acidic polyacrylamide gel electrophoresis. Milk production was recorded daily. Single-trait, mixed, linear models were used for the statistical analysis of the data. Results indicated that kappa-CN genotypes affected significantly protein yield and content (genotype AB > genotype AA). A tendency for increased milk and fat yield of animals having AB kappa-CN genotype was also found. Fat content and lactose yield and content were not affected. In the beta-LG system, significant differences were detected for milk yield (AB > AA), fat yield (BB and AB > AA), fat content (BB > AA and AB), and lactose yield (AB > AA). A tendency for higher protein yield was also observed (AB > AA). The beta-LG locus had no significant effect on protein and lactose content. No associations between polymorphisms at the kappa-CN locus and reproductive performance were found. There was a tendency, however, for cows with AB genotype to have older age at first and second calving. In the beta-LG system, cows with AA genotype had significantly shorter gestation length than did those with AB or BB genotype. No differences were detected between beta-LG polymorphisms for the other reproductive traits.     

Genome-wide association study for lactation persistency,female fertility,longevity, and lifetime profit index traits in Holstein dairy cattle

Female fertility in Holstein cattle can decline when intense genetic selection is placed on milk production. One approach to improving fertility is to identify the genomic regions and variants affecting fertility traits and then incorporate this knowledge into selection decisions. The objectives of this study were to identify or refine the positions of the genomic regions associated with lactation persistency, female fertility traits (age at first service, cow first service to conception, heifer and cow nonreturn rates), longevity traits (herd life, indirect herd life, and direct herd life), and lifetime profit index in the North American Holstein dairy cattle population. A genome-wide association study was performed for each trait, using a single SNP (single nucleotide polymorphism) regression mixed linear model and imputed high-density panel (777k) genotypes. No associations were identified for fertility traits. Several peak regions were detected for lifetime profit index, lactation persistency, and longevity. The results overlap with previous findings and identify some novel regions for lactation persistency. Previously proposed causative and candidate genes supported by this work include DGAT1, GRINA, and CPSF1, whereas new candidate genes are SLC2A4RG and THRB. Thus, the chromosomal regions identified in this study not only confirm several previous findings but also highlight new regions that may contribute to genetic variation in lactation persistency and longevity-associated traits in dairy cattle.     

Genome-wide association study for milk production and conformation traits in Canadian Alpine and Saanen dairy goats

Increasing the productivity of Canadian dairy goats is critical to the competitiveness of the sector; however, little is known about the underlying genetic architecture of economically important traits in these populations. Consequently, the objectives of this study were as follows: (1) to perform a single-step GWAS for milk production traits (milk, protein, and fat yields, and protein and fat percentages in first and later lactations) and conformation traits (body capacity, dairy character, feet and legs, fore udder, general appearance, rear udder, suspensory ligament, and teats) in the Canadian Alpine and Saanen breeds; and (2) to identify positional and functional candidate genes related to these traits. The data available for analysis included 305-d milk production records for 6,409 Alpine and 3,434 Saanen does in first lactation and 5,827 Alpine and 2,632 Saanen does in later lactations; as well as linear type conformation records for 5,158 Alpine and 2,342 Saanen does. Genotypes were available for 833 Alpine and 874 Saanen animals. Both single-breed and multiple-breed GWAS were performed using single-trait animal models. Positional and functional candidate genes were then identified in downstream analyses. The GWAS identified 189 unique SNP that were significant at the chromosomal level, corresponding to 271 unique positional candidate genes within 50 kb up- and downstream, across breeds and traits. This study provides evidence for the economic importance of several candidate genes (e.g., CSN1S1, CSN2, CSN1S2, CSN3, DGAT1, and ZNF16) in the Canadian Alpine and Saanen populations that have been previously reported in other dairy goat populations. Moreover, several novel positional and functional candidate genes (e.g., RPL8, DCK, and MOB1B) were also identified. Overall, the results of this study have provided greater insight into the genetic architecture of milk production and conformation traits in the Canadian Alpine and Saanen populations. Greater understanding of these traits will help to improve dairy goat breeding programs.     

The association between milk urea nitrogen and DHI production variables in western commercial dairy herds

A retrospective observational study was conducted using data from Dairy Herd Improvement monthly tests to investigate the association between milk urea nitrogen (MUN) concentration and milk yield, milk protein, milk fat percentage, SCC, and parity for commercial Holstein and Jersey herds in Utah, Idaho, and Montana. Mean MUN for Holstein cows was 15.5 mg/ dl (5.5 mmol/L) MUN and 14.1 mg/dl (5.0 mmol/L) for Jersey cows. Mean MUN, categorized by 30-d increments of days in milk (DIM), paralleled changes in milk values and followed a curvilinear shape. For Holstein cows, concentrations of MUN were different among lactation groups 1, 2, and 3+ for the first 90 DIM for Holsteins. Overall, concentrations of MUN were lower during for the first 30 DIM compared with all other DIM categories for both Holstein and Jersey cows. Multivariate regression models of MUN by milk protein showed that as the milk protein percentage increased, MUN concentration decreased; however, models for Jersey cows showed that MUN did not decrease significantly until above 3.4% milk protein. Milk fat percentage also decreased as MUN increased, but by only 1 mg/dl MUN over the range of 2.2 to 5.8% milk fat. Somatic cell count showed a negative relationship with MUN. Holstein cows with milk protein percentage >3.2% had lower MUN compared with cows having milk protein <3.2% for milk yields from 27.3 to 54.5 kg/d and lower than cows having a milk protein <3.0% for milk yield of 54.5 to 63.6 kg/d. In Jersey cows, MUN concentrations were not different among milk protein percentage categorized by milk yield. This study found that MUN was inversely associated with milk protein percentage and paralleled change in milk yield over time.     

Effects of recombinant bovine interleukin-8 (rbIL-8) treatment on health,metabolism, and lactation performance in Holstein cattle II: Postpartum uterine health,ketosis, and milk production

To evaluate the effect of recombinant bovine interleukin-8 (rbIL-8) on uterine health and milk production, 2 separate studies were conducted. For study 1, postpartum Holstein cows (n = 213) were randomly allocated into 1 of 3 intrauterine treatment groups: control (CTR, 250 mL of saline solution), low dose (L-IL8, 11.25 µg of rbIL-8 diluted in 250 mL of saline solution), and high dose (H-IL8, 1,125 µg of rbIL-8 diluted in 250 mL of saline solution). Intrauterine delivery of treatments was performed within 12 h of parturition. Cows were evaluated for retained fetal membranes, puerperal metritis, and clinical endometritis. Blood samples were collected immediately before treatment and 1, 2, and 3 d in milk for assessment of IL-8, haptoglobin, fatty acids, and β-hydroxybutyrate concentrations. Treatment with rbIL-8 reduced the incidence of puerperal metritis in multiparous cows (CTR = 34.3, L-IL8 = 8.11, and H-IL8 = 6.35%). Both the L-IL8 and H-IL8 groups produced significantly more milk, fat-corrected milk, and energy-corrected milk yields when compared with placebo-treated controls. A second study was performed to confirm the effect of rbIL-8 on milk production. In study 2, 164 primiparous cows were randomly allocated into 1 of 4 treatment groups: control (CTR, 250 mL of saline solution), low dose (L-IL8, 0.14 µg of rbIL-8), medium dose (M-IL8, 14 µg of rbIL-8), and high dose (H-IL8, 1,400 µg of rbIL-8). Treatments were prepared and administered as described for study 1. Cows in the L-IL8, M-IL8, and H-IL8 groups produced significantly more milk, fat-corrected milk, and energy-corrected milk yields when compared with control cows. In conclusion, treatment with rbIL-8 decreased the incidence of puerperal metritis in multiparous cows. The administration of rbIL-8 was repeatedly associated with a dramatic and long-lasting improvement of lactation performance.