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Background The trading of individual animal genotype information often involves only the exchange of the called genotypes and not necessarily the additional information required to effectively call structural variants. The main aim here was to determine if it is possible to impute copy number variants (CNVs) using the flanking single nucleotide polymorphism (SNP) haplotype structure in cattle. While this objective was achieved using high-density genotype panels (i.e., 713,162 SNPs), a secondary objective investigated the concordance of CNVs called with this high-density genotype panel compared to CNVs called from a medium-density panel (i.e., 45,677 SNPs in the present study). This is the first study to compare CNVs called from high-density and medium-density SNP genotypes from the same animals. High (and medium-density) genotypes were available on 991 Holstein-Friesian, 1015 Charolais, and 1394 Limousin bulls. The concordance between CNVs called from the medium-density and high-density genotypes were calculated separately for each animal. A subset of CNVs which were called from the high-density genotypes was selected for imputation. Imputation was carried out separately for each breed using a set of high-density SNPs flanking the midpoint of each CNV. A CNV was deemed to be imputed correctly when the called copy number matched the imputed copy number. Results For 97.0% of CNVs called from the high-density genotypes, the corresponding genomic position on the medium-density of the animal did not contain a called CNV. The average accuracy of imputation for CNV deletions was 0.281, with a standard deviation of 0.286. The average accuracy of imputation of the CNV normal state, i.e. the absence of a CNV, was 0.982 with a standard deviation of 0.022. Two CNV duplications were imputed in the Charolais, a single CNV duplication in the Limousins, and a single CNV duplication in the Holstein-Friesians; in all cases the CNV duplications were incorrectly imputed. Conclusion The vast majority of CNVs called from the high-density genotypes were not detected using the medium-density genotypes. Furthermore, CNVs cannot be accurately predicted from flanking SNP haplotypes, at least based on the imputation algorithms routinely used in cattle, and using the SNPs currently available on the high-density genotype panel.

The objective of this study was to develop, using alternative algorithms, low-density SNP genotyping panels (384 to 12,000 SNP), which can be accurately imputed to higher-density panels across independent cattle populations. Single nucleotide polymorphisms were selected based on genomic characteristics (i.e., linkage disequilibrium [LD], minor allele frequency [MAF], and genomic distance) in a population of 1,267 Holstein-Friesian animals genotyped on the Illumina Bovine50 Beadchip (54,001 SNP). Single nucleotide polymorphism selection methods included 1) random; 2) equidistant location; 3) combination of SNP MAF and LD structure while maintaining relatively equal genomic distance between adjacent SNP; 4) a combination of high MAF, genomic distance between selected and candidate SNP, and correlation between genotypes of selected and candidate SNP; and 5) a machine learning algorithm. The panels were validated separately in 1) a population of 750 Holstein-Friesian animals with masked genotypes to reflect the lower-density SNP densities under investigation (1,249 animals with complete genotypes included in reference population) and 2) a population of 359 Limousin and Charolais cattle with high (777,962 SNP)-density genotypes (1,918 animals with complete genotypes included in the reference population). Irrespective of SNP selection method, imputation accuracy in both populations improved at a diminishing rate as the number of SNP included in the lower-density genotype panel increased. Additionally, the variability in mean imputation accuracy per individual decreased as the panel density increased. The SNP selection method had a major impact on the mean allele concordance rate, although its impact diminished as the panel density increased. Imputation accuracy for SNP selected using a combination of high SNP MAF, LD structure, and relatively equal genomic distance between SNP outperformed all other selection methods in densities12,000 SNP. Using this method of SNP selection, the correlation between the imputed and actual genotypes for the 3,000 SNP panel was 0.90 and 0.96 when applied to the beef and dairy populations, respectively; the respective correlations for the 6,000 SNP panel were 0.95 and 0.98. It is necessary to include between 3,000 and 6,000 SNP in a low-density panel to achieve adequate imputation accuracy to either medium density (approximately 50,000 SNP in the dairy population) or high density (approximately 700,000 SNP in the beef population) across diverse and independent populations.

In this study the effect of artificial selection on BLUP EBV for production traits on the allele frequencies of a pleiotropic QTL affecting both production and disease susceptibility was investigated. Stochastic simulations were used to model artificial selection on a production trait that is controlled, in part, by a biallelic QTL that also controls susceptibility to disease. The QTL allele increasing production also increased susceptibility to disease. Different modes of action and proportions of variation accounted for by the QTL were assessed for the production trait. The main results indicated that alleles that confer susceptibility to the disease could be maintained in the population over a long period, depending on the mode of action of the QTL. In addition, the results of the study indicate that, under various conditions, it is possible to find pleiotropic QTL that control 2 traits despite these traits appearing to be uncorrelated. Therefore, in practice, an estimate of the genetic correlation between 2 traits may be misleading when the presence of such a QTL exists. The results of this study have implications for breeding programs. For example, if a pleiotropic QTL exists that favors heterozygotes for a production trait, it would be very difficult to remove disease susceptibility alleles via traditional selection methods.

The objective of this study was to determine the effect of inbreeding on milk production, somatic cell count, fertility, survival, calving performance, and cow conformation in Irish Holstein-Friesian pluriparous dairy cows. Inbreeding was included in a linear mixed model as either a class variable or a continuous variable, where higher order polynomials of the latter were also tested in the model as an indicator of nonlinear inbreeding depression. The effects of dam inbreeding and calf inbreeding on calving-related traits were analyzed separately. Inbreeding had a deleterious effect on most of the traits analyzed, although inbreeding depression was sometimes nonlinear or differed significantly across parities. A primiparous animal, 12.5% inbred (i.e., following the mating of noninbred half-sibs), had milk, fat, and protein yields reduced by 61.8, 5.3, and 1.2 kg, respectively; fat and protein concentrations reduced by 0.05 and 0.01%, respectively; and somatic cell scores (i.e., natural log of somatic cell count divided by 1,000) increased by 0.03. The 12.5% inbred animal was also expected to have a 2% greater incidence of dystocia, a 1% greater incidence of stillbirth, a 0.7% greater incidence of male calves, an increase in calving interval of 8.8 d, an increase in age at first calving of 2.5 d, and a reduced survival to second lactation of 4 percentage units. Inbred animals were also taller, narrower, and more angular. Although the effects of inbreeding were statistically significant, they were small and are unlikely to cause great financial loss on Irish dairy farms.

Human CD7 is a 40 kDa protein expressed on thymocytes, early T, B, NK and myeloid lineage cells in bone marrow, and on mature T and NK cells. Previous studies suggested human CD7 may be involved in T and NK cell activation and/or adhesion, and that CD7-mediated cell activation may be transduced via the lipid kinase phosphatidylinositol 3-kinase (Pi3-kinase), a heterodimeric cytosolic protein consisting of an 85 kDa adaptor subunit that is coupled to a 110 kDa catalytic subunit. It has recently been shown that a sequence motif present in the cytoplasmic tall of both human and mouse CD7 bound with high affinity to recombinant SH2 domains present in the p85 subunit of Pi3-kinase. In this work, we used co-precipitation with anti-CD7 mAb 3A1 and recombinant p85 SH2-GST fusion proteins and peptide competition analysis to demonstrate that the cytoplasmic tail of CD7 interacts with a functional Pi3-kinase via the pTyr-X-X-Met motif. Furthermore, we show that cross-linking of CD7 markedly increased the amount of Pi3-kinase activity associated with CD7. The interaction of CD7 with the Pi3-kinase signal transduction pathway provides a mechanism for the previously observed functional responses attributed to CD7-mediated T and NK cell activation.