Fine-mapping the POLL locus in Brahman cattle yields the diagnostic marker CSAFG29
The POLL locus has been mapped to the centromeric region of bovine chromosome 1 (BTA1) in both taurine breeds and taurine–indicine crosses in an interval of approximately 1 Mb. It has not yet been mapped in pure-bred zebu cattle. Despite several efforts, neither causative mutations in candidate genes nor a singular diagnostic DNA marker has been identified. In this study, we genotyped a total of 68 Brahman cattle and 20 Hereford cattle informative for the POLL locus for 33 DNA micro satellites, 16 of which we identified de novo from the bovine genome sequence, mapping the POLL locus to the region of the genes IFNAR2 and SYNJ1. The 303-bp allele of the new micro satellite, CSAFG29, showed strong association with the POLL allele. We then genotyped 855 Brahman cattle for CSAFG29 and confirmed the association between the 303-bp allele and POLL. To determine whether the same association was found in taurine breeds, we genotyped 334 animals of the Angus, Hereford and Limousin breeds and 376 animals of the Brangus, Drought master and Santa Gertrudis composite taurine–zebu breeds. The association between the 303-bp allele and POLL was confirmed in these breeds; however, an additional allele (305 bp) was also associated but not fully predictive of POLL. Across the data, CSAFG29 was in sufficient linkage disequilibrium to the POLL allele in Australian Brahman cattle that it could potentially be used as a diagnostic marker in that breed, but this may not be the case in other breeds. Further, we provide confirmatory evidence that the scur phenotype generally occurs in animals that are heterozygous for the POLL allele.
Detection of quantitative trait loci in 'Bos indicus' and 'Bos taurus' cattle using genome-wide association studies
Background: The apparent effect of a single nucleotide polymorphism (SNP) on phenotype depends on the linkage disequilibrium (LD) between the SNP and a quantitative trait locus (QTL). However, the phase of LD between a SNP and a QTL may differ between 'Bos indicus' and 'Bos taurus' because they diverged at least one hundred thousand years ago. Here, we test the hypothesis that the apparent effect of a SNP on a quantitative trait depends on whether the SNP allele is inherited from a 'Bos taurus' or 'Bos indicus' ancestor. Methods: Phenotype data on one or more traits and SNP genotype data for 10 181 cattle from 'Bos taurus', 'Bos indicus' and composite breeds were used. All animals had genotypes for 729 068 SNPs (real or imputed). Chromosome segments were classified as originating from B. 'indicus' or B. 'taurus' on the basis of the haplotype of SNP alleles they contained. Consequently, SNP alleles were classified according to their sub-species origin. Three models were used for the association study: (1) conventional GWAS (genome-wide association study), fitting a single SNP effect regardless of subspecies origin, (2) interaction GWAS, fitting an interaction between SNP and subspecies-origin, and (3) best variable GWAS, fitting the most significant combination of SNP and sub-species origin. Results: Fitting an interaction between SNP and subspecies origin resulted in more significant SNPs (i.e. more power) than a conventional GWAS. Thus, the effect of a SNP depends on the subspecies that the allele originates from. Also, most QTL segregated in only one subspecies, suggesting that many mutations that affect the traits studied occurred after divergence of the subspecies or the mutation became fixed or was lost in one of the subspecies. Conclusions: The results imply that GWAS and genomic selection could gain power by distinguishing SNP alleles based on their subspecies origin, and that only few QTL segregate in both B. 'indicus' and B. 'taurus' cattle. Thus, the QTL that segregate in current populations likely resulted from mutations that occurred in one of the subspecies and can have both positive and negative effects on the traits. There was no evidence that selection has increased the frequency of alleles that increase body weight.
A Multi-Trait, Meta-analysis for Detecting Pleiotropic Polymorphisms for Stature, Fatness and Reproduction in Beef Cattle
Polymorphisms that affect complex traits or quantitative trait loci (QTL) often affect multiple traits. We describe two novel methods (1) for finding single nucleotide polymorphisms (SNPs) significantly associated with one or more traits using a multi-trait, meta-analysis, and (2) for distinguishing between a single pleiotropic QTL and multiple linked QTL. The metaanalysis uses the effect of each SNP on each of n traits, estimated in single trait genome wide association studies (GWAS). These effects are expressed as a vector of signed t-values (t) and the error covariance matrix of these t values is approximated by the correlation matrix of t-values among the traits calculated across the SNP (V). Consequently, t'V⁻¹t is approximately distributed as a chi-squared with n degrees of freedom. An attractive feature of the meta-analysis is that it uses estimated effects of SNPs from single trait GWAS, so it can be applied to published data where individual records are not available. We demonstrate that the multi-trait method can be used to increase the power (numbers of SNPs validated in an independent population) of GWAS in a beef cattle data set including 10,191 animals genotyped for 729,068 SNPs with 32 traits recorded, including growth and reproduction traits. We can distinguish between a single pleiotropic QTL and multiple linked QTL because multiple SNPs tagging the same QTL show the same pattern of effects across traits. We confirm this finding by demonstrating that when one SNP is included in the statistical model the other SNPs have a non-significant effect. In the beef cattle data set, cluster analysis yielded four groups of QTL with similar patterns of effects across traits within a group. A linear index was used to validate SNPs having effects on multiple traits and to identify additional SNPs belonging to these four groups.