At present, many bacterial species are validly known as etiological agents of dairy cattle metritis, yet the vast uncultured fraction has received no attention so far. The purpose of this study was to use culture-independent methods to describe and compare the uterine bacterial composition in healthy and metritic postpartum Holstein dairy cows. Both group-specific 16S ribosomal DNA PCR-denaturing gradient gel electrophoresis (DGGE) and clone library sequencing of broad-range 16S ribosomal DNA PCR revealed differences in the bacterial communities comparing healthy and metritic cows. Bacterial diversity in healthy and metritic uteri was greater and more complex than described previously by traditional culture methods. Sequences were assigned to 5 major groups (Gammaproteobacteria, Firmicutes, Fusobacteria, Bacteroidetes, and Tenericutes) and to uncultured bacteria. Additionally, DGGE suggested the presence of Actinobacteria. Most clone sequences in the metritic status libraries were affiliated with the phylum Fusobacteria. Many components, especially from other phyla, have not previously been isolated from cases of metritis. In the clone libraries from the healthy status dairy cows, Gammaproteobacteria was the most prominent group and most sequences showed high identity with Mannheimia varigena, Pasteurella hemolytica, and members of the phylum Tenericutes. Our data showed that the uterine bacterial community in postpartum dairy cows differed considerably between healthy and metritic cows and described the occurrence of a previously unrecognized extent of this diversity in the bovine intrauterine microbiota.

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The objective was to compare the reproductive efficacy of Ultrasynch, a synchronization program based on functionality of the corpus luteum as determined by ultrasonography, with an Ovsynch protocol. A randomized field trial was conducted on a commercial dairy in Cayuga County, New York, during scheduled weekly pregnancy examinations. Cows (n=745) determined nonpregnant 28 to 34 d after artificial insemination (AI) were randomly assigned to Ultrasynch or Ovsynch protocols. Cows assigned to the Ultrasynch management program (n=366) were treated based on corpus luteum (CL) diameter: cows with a CL > 23 mm received an injection of PGF(2alpha) and were bred via AI following detection of estrus (Ultra-PGF), whereas cows with a CL < or = 23 mm received injections and were bred on an Ovsynch protocol. Cows assigned to the Ovsynch management program (n=379) were placed on an Ovsynch protocol regardless of CL diameter. Pregnancy status was rechecked 28 to 34 d after AI; cows determined nonpregnant after initial enrollment were maintained in their assigned management group and received treatments based on CL diameter if in the Ultrasynch group and Ovsynch treatments if in the Ovsynch group. Hazard of pregnancy was similar between Ultrasynch and Ovsynch (hazard ratio=1.10, 95% confidence interval=0.88-1.36). Median days to conception were 98 and 87 for Ultrasynch and Ovsynch, respectively. The detection of estrus rate of cows in the Ultra-PGF group was 49%; better performance of an Ultrasynch management program may be achievable in a herd with a higher rate of estrus detection.

Summary The objective of this study was to compare accuracies of different Bayesian regression models in predicting molecular breeding values for health traits in Holstein cattle. The dataset was composed of 2505 records reporting the occurrence of retained fetal membranes (RFM), metritis (MET), mastitis (MAST), displaced abomasum (DA), lameness (LS), clinical endometritis (CE), respiratory disease (RD), dystocia (DYST) and subclinical ketosis (SCK) in Holstein cows, collected between 2012 and 2014 in 16 dairies located across the US. Cows were genotyped with the Illumina BovineHD (HD, 777K). The quality controls for SNP genotypes were HWE P‐value of at least 1 × 10−10; MAF greater than 0.01 and call rate greater than 0.95. The FImpute program was used for imputation of missing SNP markers. The effect of each SNP was estimated using the Bayesian Ridge Regression (BRR), Bayes A, Bayes B and Bayes Cπ methods. The prediction quality was assessed by the area under the curve, the prediction mean square error and the correlation between genomic breeding value and the observed phenotype, using a leave‐one‐out cross‐validation technique that avoids iterative cross‐validation. The highest accuracies of predictions achieved were: RFM [Bayes B (0.34)], MET [BRR (0.36)], MAST [Bayes B (0.55), DA [Bayes Cπ (0.26)], LS [Bayes A (0.12)], CE [Bayes A (0.32)], RD [Bayes Cπ (0.23)], DYST [Bayes A (0.35)] and SCK [Bayes Cπ (0.38)] models. Except for DA, LS and RD, the predictive abilities were similar between the methods. A strong relationship between the predictive ability and the heritability of the trait was observed, where traits with higher heritability achieved higher accuracy and lower bias when compared with those with low heritability. Overall, it has been shown that a high‐density SNP panel can be used successfully to predict genomic breeding values of health traits in Holstein cattle and that the model of choice will depend mostly on the genetic architecture of the trait.

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A modified technique for the resection of the distal interphalangeal joint and the proximal resection of the deep digital flexor tendon in cows is described. Septic arthritis of the joint was diagnosed in eight Holstein cows and treated in the field. Four of the cows were diagnosed with ascending tendonitis during the resection of the joint and their tendons were also resected. All the animals remained moderately to severely lame for two weeks postoperatively but quickly recovered and were sound within five months. Eight months after the last surgery only one cow had been culled, 321 days after its surgery, for reproductive failure. The other seven cows had survived for a mean period of 308 days, with a range from 235 to 392 days.

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