Chontida did her thesis on a genome-wide association study

Thesis title

Genome-wide association study of health traits in Fleckvieh cattle

Summary

Genome-wide association study (GWAS) has become an important methodology to detect QTLs affecting phenotypic variations of traits, especially for traits with low heritability. Many health traits in cattle display low heritability and conventional genetic improvements often yield unsatisfying selection responses. In this study, single-SNP and multiple-SNP GWAS analyses were conducted to find SNPs for longevity, fertility and cystic ovaries in Fleckvieh cattle. The daughter yield deviations of progeny tested bulls were used as phenotypes and genotypes of each individual were scored for a total of 41008 SNPs distributed over the whole genome. Bonferroni correction and false discovery rate (FDR) for multiple testing were applied to adjust the significance threshold in the single-SNP analyses. Based on analyses of simulated data, Waldmann et al. (in prep) have shown that penalized multiple regression with the elastic net (penalty weight α = 0.05) expressed a very good trade-off between Type I and Type II error.

Therefore, the elastic net method (α = 0.05 and 1000-fold cross validation) was used in the multiple-SNP analyses. The Bonferroni correction resulted in 4 significant SNPs for longevity and 19 SNPs for fertility. With the FDR method, number of detected SNPs was 270 and 726 for longevity and fertility, respectively. 143 SNPs were identified for longevity in the multiple-SNP analyses and 183 SNPs were detected for fertility. No SNPs were found for cystic ovaries in neither single-SNP nor multiple-SNP analyses. Hence, we can conclude that the single SNP analyses either under- or over-estimate the number of associated SNPs, and that there seems to be a potential for using genomic selection of longevity and fertility in Fleckvieh cattle.