High throughput analysis of MHC class I and class II diversity of Zambian indigenous cattle populations

Isaac Silwamba, Deepali Vasoya, Martin Simuunza, Thomas Tzelos, King S Nalubamba, Edgar Simulundu, Christina Vrettou, Geoffrey Mainda, Mick Watson, John Bwalya Muma, Timothy Connelley

Research output: Contribution to journalArticlepeer-review

Abstract / Description of output

The classical MHC class I and class II molecules play key roles in determining the antigenic-specificity of CD8+ and CD4+ T-cell responses-as such characterisation of the repertoire of MHCI and MHCII allelic diversity is fundamental to our ability to understand, and potentially, exploit how genetic diversity influences the outcome of immune responses. Cattle remain one of the most economically livestock species, with particular importance to many small-holder farmers in low-and-middle income countries (LMICs). However, our knowledge of MHC (BoLA) diversity in the indigenous breeds that form the mainstay of cattle populations in many LMICs remains very limited. In this study we develop a MiSeq-based platform to enable the rapid analysis of BoLA-DQA and BoLA-DQB, and combine this with similar platforms to analyse BoLA-I and BoLA-DRB repertoires, to study a large cohort of cattle (~800 animals) representing the 3 major indigenous breeds (Angoni, Barotse, Tonga) in Zambia. The data presented confirms the capacity of this high-throughput and high-resolution approach to provide a full characterisation of the MHCI-MHCII genotypes of cattle for which little previous MHC sequence data has been obtained. The cattle in Zambia were found to express a diverse range of MHCI, MHCII and extended MHCI-MHCII haplotypes. The combined MHCI-MHCII genotyping now possible opens new opportunities to rapidly expand our knowledge of MHC diversity in cattle that could find applications in a related translational disciplines such as vaccine development.

Original languageEnglish
Pages (from-to)458-483
JournalHLA: Immune Response Genetics
Volume101
Issue number5
Early online date21 Jan 2023
DOIs
Publication statusPublished - May 2023

Keywords / Materials (for Non-textual outputs)

  • MHC
  • cattle
  • high-throughput sequencing

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