A degenerative skeletal muscle disease with vascular, neurologic, and renal lesions and a probable familial distribution was identified in 4-20-month-old purebred Gelbvieh cattle. Thirteen affected animals were confirmed from 6 separate beef herds, with a mortality rate of 100%. Clinical signs in affected animals consisted of ataxia, weakness, and terminal recumbency. Gross and histologic muscle lesions were indicative of nutritional myopathy of ruminants, with a lack of myocardial lesions in most cases and only rare myocardial changes in a few animals. Acute to chronic lesions in most large skeletal muscle groups consisted of degeneration, necrosis, regeneration, fibrosis, and atrophy. Fibrinoid necrosis of arterioles was a common feature in multiple tissues. Lesions in the spinal cord white matter and peripheral nerves consisted of degeneration of the dorsal columns and axons, respectively. Changes in the kidneys consisted of chronic interstitial nephritis with fibrosis, hyaline droplet change and tubular epithelial vacuolar change and were most severe in the older calves. Intracytoplasmic myoglobin and iron were demonstrated within the hyaline droplets in degenerate renal cortical tubular epithelial cells. Vitamin E levels were deficient in most (6/7) of the animals tested. Investigation of the pedigree of affected animals revealed a common ancestry for all but 1 of the animals whose parentage could be traced. This investigation suggests that a hereditary metabolic defect, possibly involving antioxidant metabolism, could be responsible for this condition. Renal disease, possibly secondary to myoglobinuria, may be unique to this bovine condition.
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http://dx.doi.org/10.1177/104063870201400208 | DOI Listing |
BMC Genomics
April 2024
Department of Animal Science, University of Nebraska-Lincoln, Lincoln, NE, USA.
J Anim Sci
February 2022
Department of Animal Science, University of Nebraska, Lincoln, NE 68583, USA.
Understanding the genetic relationship between mature cow weight (MWT) and body condition score (BCS) is useful to implement selection programs focused on cow efficiency. The objectives of this study were to estimate genetic parameters, heterosis, and breed effects for MWT and BCS. In total, 25,035 and 24,522 overlapping records were available for MWT and BCS on 6,138 and 6,131 cows, respectively, from the Germplasm Evaluation program, a crossbred beef population at the U.
View Article and Find Full Text PDFJ Anim Sci
August 2021
Department of Animal Science, University of Nebraska-Lincoln, Lincoln, NE 68583, USA.
Cow mature weight (MWT) is heritable and affects the costs and efficiency of a breeding operation. Cow weight is also influenced by the environment, and the relationship between the size and profitability of a cow varies depending on production system. Producers, therefore, need tools to incorporate MWT in their selection of cattle breeds and herd replacements.
View Article and Find Full Text PDFBMC Genomics
December 2019
Department of Veterinary Pathobiology, Texas A&M University, College Station, 77843, USA.
Background: Single nucleotide polymorphism (SNP) arrays have facilitated discovery of genetic markers associated with complex traits in domestic cattle; thereby enabling modern breeding and selection programs. Genome-wide association analyses (GWAA) for growth traits were conducted on 10,837 geographically diverse U.S.
View Article and Find Full Text PDFAnim Genet
April 2017
USDA, ARS, U.S. Meat Animal Research Center, Clay Center, NE, 68933, USA.
Copy number variations (CNVs) are large insertions, deletions or duplications in the genome that vary between members of a species and are known to affect a wide variety of phenotypic traits. In this study, we identified CNVs in a population of bulls using low coverage next-generation sequence data. First, in order to determine a suitable strategy for CNV detection in our data, we compared the performance of three distinct CNV detection algorithms on benchmark CNV datasets and concluded that using the multiple sample read depth approach was the best method for identifying CNVs in our sequences.
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