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Association of BoLA-DRB3.2 Alleles with Resistance and Susceptibility to Persistent Lymphocytosis in BLV Infected Cattle in Argentina


Article Information

Title: Association of BoLA-DRB3.2 Alleles with Resistance and Susceptibility to Persistent Lymphocytosis in BLV Infected Cattle in Argentina

Authors: C.J. Panei, K. Suzuki, M.G. Echeverria, M.S. Serena, G.E. Metz, E.T. Gonzalez

Journal: International Journal of Dairy Science

HEC Recognition History
Category From To
Y 2023-07-01 2024-09-30
Y 2022-07-01 2023-06-30
X 2021-07-01 2022-06-30
Y 2020-07-01 2021-06-30

Publisher: Asian Network for Scientific Information

Country: Pakistan

Year: 2009

Volume: 4

Issue: 3

Language: English

DOI: 10.3923/ijds.2009.123.128

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Abstract

ABSTRACT


The objective of this preliminary study was to describe alleles of bovine major histocompatibility complex class II BoLA-DRB3.2 gene associated with resistance and susceptibility to Persistent Lymphocytosis PL in Bovine leukaemia virus BLV infected cattle, to set a direction for the future studies. A total of 81 dairy cattle in Argentina were investigated for the distribution of BoLA-DRB3.2 alleles. The study cattle were categorized into 3 groups as follows Category PL BLV seropositive with PL Category PL BLV seropositive without PL and Category BLV BLV seronegative. The alleles were identified by polymerase chain reaction with subsequent analysis of restriction fragment length polymorphism. The association between the BoLA-DRB3.2 alleles and the PL and PL categories was determined as the odds ratio. Some alleles BoLA-DRB3.2 mediating 1 resistance and 2 susceptibility to PL were observed, respectively. A stochastic model including Shannon146s diversity index calculation was run based on Markov-Chain Monte Carlo simulation method. The Shannon146s diversity indices in each of the cattle categories indicated that the richness of gene diversity decreased as leading to a clinical stage of BLV. This relates to the existence of alleles mediating resistance and susceptibility to PL. The stochastic prediction with inclusion of uncertainty is important which can serve as a future study beacon.

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