Maximizing Use of an Extension Beef Cattle Data Set: Part 2—Reproductive Rates

Previously, we described CHAPS20Y, a historical data set, and trends in CHAPS20Y calving distributions. In this article, we describe reproductive rates, including total females exposed to bull(s), pregnancy, pregnancy loss, calving, calf death loss, weaning, culling, and replacement percentages. Yearly mean exposed females increased from 1994 through 2013, consistent with a greater replacement percentage versus culling percentage. Yearly mean reproductive percentages varied over time. Factors such as weather, body condition, temperament, nutrition, and health likely contributed to this variation. CHAPS20Y is a tool Extension professionals can use to understand beef reproductive rates and help producers set and achieve their herd management goals

Maximizing Use of Extension Beef Cattle Benchmarks Data Derived from Cow Herd Appraisal Performance Software

One goal of Extension is to provide practical information that makes a difference to producers. Cow Herd Appraisal Performance Software (CHAPS) has provided beef producers with production benchmarks for 30 years, creating a large historical data set. Many such large data sets contain useful information but are underutilized. Our goal was to create a 20-year data set (CHAPS20Y) to examine trends in beef production from 1994 to 2013. In this article, we describe the CHAPS program and the process used to select herds for CHAPS20Y. We hope to publish additional related articles that will examine trends in calving distributions, reproduction, and growth and discuss implications for producers and Extension

Identification of a major locus interacting with MC1R and modifying black coat color in an F2 Nellore-Angus population

BACKGROUND: In cattle, base color is assumed to depend on the enzymatic activity specified by the MC1R locus, i.e. the extension locus, with alleles coding for black (E( D )), red (e), and wild-type (E( + )). In most mammals, these alleles are presumed to follow the dominance model of E( D ) > E( + ) > e, although exceptions are found. In Bos indicus x Bos taurus F(2) cattle, some E( D )E( + ) heterozygotes are discordant with the dominance series for MC1R and display various degrees of red pigmentation on an otherwise predicted black background. The objective of this study was to identify loci that modify black coat color in these individuals. RESULTS: Reddening was classified with a subjective scoring system. Interval analyses identified chromosome-wide suggestive (P < 0.05) and significant (P < 0.01) QTL on bovine chromosomes (BTA) 4 and 5, although these were not confirmed using single-marker association or Bayesian methods. Evidence of a major locus (F = 114.61) that affects reddening was detected between 60 and 73 Mb on BTA 6 (Btau4.0 build), and at 72 Mb by single-marker association and Bayesian methods. The posterior mean of the genetic variance for this region accounted for 43.75% of the genetic variation in reddening. This region coincided with a cluster of tyrosine kinase receptor genes (PDGFRA, KIT and KDR). Fitting SNP haplotypes for a 1 Mb interval that contained all three genes and centered on KIT accounted for the majority of the variation attributed to this major locus, which suggests that one of these genes or associated regulatory elements, is responsible for the majority of variation in degree of reddening. CONCLUSIONS: Recombinants in a 5 Mb region surrounding the cluster of tyrosine kinase receptor genes implicated PDGFRA as the strongest positional candidate gene. A higher density marker panel and functional analyses will be required to validate the role of PDGFRA or other regulatory variants and their interaction with MC1R for the modification of black coat color in Bos indicus influenced cattle

Open Access

Identification of a major locus interacting with MC1R and modifying black coat color in an F2 Nellore-Angus populatio

Glycoprotein B Cleavage Is Important for Murid Herpesvirus 4 To

Glycoprotein B (gB) is a conserved herpesvirus virion component implicated in membrane fusion. As with many — but not all— herpesviruses, the gB of murid herpesvirus 4 (MuHV-4) is cleaved into disulfide-linked subunits, apparently by furin. Preventing gB cleavage for some herpesviruses causes minor infection deficits in vitro, but what the cleavage contributes to host coloniza-tion has been unclear. To address this, we mutated the furin cleavage site (R-R-K-R) of the MuHV-4 gB. Abolishing gB cleavage did not affect its expression levels, glycosylation, or antigenic conformation. In vitro, mutant viruses entered fibroblasts and epithelial cells normally but had a significant entry deficit in myeloid cells such as macrophages and bone marrow-derived den-dritic cells. The deficit in myeloid cells was not due to reduced virion binding or endocytosis, suggesting that gB cleavage pro-motes infection at a postendocytic entry step, presumably viral membrane fusion. In vivo, viruses lacking gB cleavage showed reduced lytic spread in the lungs. Alveolar epithelial cell infection was normal, but alveolar macrophage infection was signifi-cantly reduced. Normal long-term latency in lymphoid tissue was established nonetheless. Glycoprotein B (gB) is a conserved herpesvirus virion com-ponent involved in cell binding and viral membrane fu-sion (1). It and the structurally homologous vesicular stomati-tis virus (VSV) G protein and baculovirus gp64 are considered to be class III fusion proteins (2–7). Most herpesvirus gBs con-tain an R-X-K/R-R recognition motif for the ubiquitously ex

Genetic Distinctness and Diversity of American Aberdeen Cattle Compared to Common Beef Breeds in the United States

American Aberdeen (AD) cattle in the USA descend from an Aberdeen Angus herd originally brought to the Trangie Agricultural Research Centre, New South Wales, AUS. Although put under specific selection pressure for yearling growth rate, AD remain genomically uncharacterized. The objective was to characterize the genetic diversity and structure of purebred and crossbred AD cattle relative to seven common USA beef breeds using available whole-genome SNP data. A total of 1140 animals consisting of 404 purebred (n = 8 types) and 736 admixed individuals (n = 10 types) was used. Genetic diversity metrics, an analysis of molecular variance, and a discriminant analysis of principal components were employed. When linkage disequilibrium was not accounted for, markers influenced basic diversity parameter estimates, especially for AD cattle. Even so, intrapopulation and interpopulation estimates separate AD cattle from other purebred types (e.g., Latter’s pairwise FST ranged from 0.1129 to 0.2209), where AD cattle were less heterozygous and had lower allelic richness than other purebred types. The admixed AD-influenced cattle were intermediate to other admixed types for similar parameters. The diversity metrics separation and differences support strong artificial selection pressures during and after AD breed development, shaping the evolution of the breed and making them genomically distinct from similar breeds

Comparison of breeding value prediction for two traits in a Nellore-Angus crossbred population using different Bayesian modeling methodologies

The objectives of this study were to 1) compare four models for breeding value prediction using genomic or pedigree information and 2) evaluate the impact of fixed effects that account for family structure. Comparisons were made in a Nellore-Angus population comprising F2, F3 and half-siblings to embryo transfer F2 calves with records for overall temperament at weaning (TEMP; n = 769) and Warner-Bratzler shear force (WBSF; n = 387). After quality control, there were 34,913 whole genome SNP markers remaining. Bayesian methods employed were BayesB ( π = 0.995 or 0.997 for WBSF or TEMP, respectively) and BayesC (π = 0 and π), where π is the ideal proportion of markers not included. Direct genomic values (DGV) from single trait Bayesian analyses were compared to conventional pedigree-based animal model breeding values. Numerically, BayesC procedures (using π) had the highest accuracy of all models for WBSF and TEMP ( ρgg = 0.843 and 0.923, respectively), but BayesB had the least bias (regression of performance on prediction closest to 1, βy,x = 2.886 and 1.755, respectively). Accounting for family structure decreased accuracy and increased bias in prediction of DGV indicating a detrimental impact when used in these prediction methods that simultaneously fit many markers