Linkage disequilibrium (LD) between molecular markers
reflects the correlation between genotypes of two markers
or the degree of non-random association between their
alleles. Previous studies that used single nucleotide polymorphisms
(SNPs) to describe patterns of LD in cattle at
the whole-genome level [1-6] have suggested that 30 000
to 300 000 SNPs are necessary to perform a genome-wide
association study (GWAS), depending on the trait studied
and the statistical power desired [1,2]. Today, the availability
of high-density SNP platforms that can assay more
than 0.5 million loci offers the required marker density.
The extent of LD has implications for both GWAS and
the delivery of accurate genomic predictions. However, its importance is often neglected despite the fact that it is
known that it can introduce bias. Collecting and using
SNP genotyping data have exploded for cattle in the last
few years due in part to decreasing genotyping cost and
to efforts to improve cattle breeding through genomic
selection. Despite this, few studies have documented the
behaviour of LD using the expanded set of 777 000 SNPs
available on the BovineHD platform (Illumina Inc, San
Diego). One of the significant advances of this denser chip
is that it allows for an accurate estimation of LD over
short physical distances as it contains many more marker
pairs separated by 10 kb or less.
Here, we present the LD decay curves for SNPs on bovine
autosomes and the X chromosome for three genetic
groups of cattle breeds: Bos taurus (taurine), Bos indicus
(indicine) and a composite beef cattle group. The results
were compared to an independent population to confirm