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Functional genomics for improved disease resistance in dairy cattle

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Kjetil Aune

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kjetil.aune@nofima.no

40th Biochemical Contact Meeting, NBS 2004; Hafjell, Norway, 2004-01-15–2004-01-18

Nilsen, Heidi; Opsal, Monica Aasland; Roseth, Arne; Sundvold, Hilde; Våge, Dag Inge; Lien, Sigbjørn

Norwegian agriculture faces new demands from consumers asking for less expensive and high quality food. As a result intensive focus on improving food safety through increased knowledge of disease resistance, immune- and gene function has emerged. Mastitis is the most frequent and costly disease in dairy production. It is a complex inflammatory disease caused by introduction and multiplication of pathogenic microorganisms in the mammary gland. Our aim is to improve the understanding of the bovine immune system in general, and on clinical mastitis in particular, using a quite broad functional genomics strategy involving two main components: A positional cloning approach involving genome scan for chromosome regions affecting clinical mastitis, and a candidate gene approach focused on genes involved in the innate immune response. An initial genome scan for Quantitative Trait Loci (QTL) was completed a few years ago (Klungland et al., 2001). Here, we present a strategy for following up on fine mapping QTL and comparative positional cloning of the causative mutation(s), focusing particularly on bovine chromosome 6 (BTA6). Secondly, TLR-genes involved in immune response pathways are mapped and characterised according to the candidate gene approach. Toll-like receptors (TLR) are cell-surface signalling molecules that recognise pathogen-associated molecular patterns (PAMP). Binding between TLR and PAMPs initiates a signalling pathway that stimulates the host defence system. Knowledge of these genes will improve the immunological basis for protection against animal disease. In both approaches we take great advantage of the unique national wide recording system for diseases in Norwegian Cattle (The Norwegian Cattle Biobank, BoviBank AS) and the resources and competence established at Centre for Integrative Genetics (CIGENE) (www.cigene.no). High-throughput processing levels for SNPs, microsatellites, sequencing and gene expression analysis are performed using MassARRAY (http://www.sequenom.com). Moreover, we are developing key competence concerning identification and methodological integration of experimental and theoretical approaches for making a causal connection between genomic and phenotypic data on complex traits.