An alternative experimental case-control design for genetic association studies on bovine mastitis

The possibility of using genetic control strategies to increase disease resistance to infectious diseases relies on the identification of markers to include in the breeding plans. Possible incomplete exposure of mastitis-free (control) animals, however, is a major issue to find relevant markers in genetic association studies for infectious diseases. Usually, designs based on elite dairy sires are used in association studies, but an epidemiological case-control strategy, based on cows repeatedly field-tested could be an alternative for disease traits. To test this hypothesis, genetic association results obtained in the present work from a cohort of Italian Holstein cows tested for mastitis over time were compared with those from a previous genome-wide scan on Italian Holstein sires genotyped with 50k single nucleotide polymorphisms for de-regressed estimated breeding values for somatic cell counts (SCCs) on Bos taurus autosome (BTA6) and BTA14. A total of 1121 cows were selected for the case-control approach (cases=550, controls=571), on a combination of herd level of SCC incidence and of within herd individual level of SCC. The association study was conducted on nine previously identified markers, six on BTA6 and four on BTA14, using the R statistical environment with the 'qtscore' function of the GenABEL package, on high/low adjusted linear score as a binomial trait. The results obtained in the cow cohort selected on epidemiological information were in agreement with those obtained from the previous sire genome-wide association study (GWAS). Six out of the nine markers showed significant association, four on BTA14 (rs109146371, rs109234250, rs109421300, rs109162116) and two on BTA6 (rs110527224 and rs42766480). Most importantly, using mastitis as a case study, the current work further validated the alternative use of historical field disease data in case-control designs for genetic analysis of infectious diseases in livestock.

S. Biffani, M. Del Corvo, R. Capoferri, A. Pedretti, M. Luini, J. L. Williams, G. Pagnacco, F. Minvielle and G. Minozzi