Can long-range microsatellite data be used to predict short-range linkage disequilibrium?

Abstract

The distribution of linkage disequilibrium (LD) across the genome is highly complex. Little is known about the relationship between long-range and short-range LD in a genomic region. We assessed whether a dense set of microsatellite data could be used to predict short-range LD in family samples. We analyzed intermarker LD in data derived from chromosomal regions 18q22 and 10q25-26, densely genotyped with microsatellite markers. The pattern of LD was highly heterogeneous within and between both chromosomal regions. On 10q25-26, very little LD was detected. On 18q22, where marker density was higher, many marker pairs were in LD. We modeled the decay of LD over distance in this region. A classical model accounted for most of the relationship between LD and distance (R2 = 63%). We used this model to predict the proportion of markers expected to show useful levels of LD at short distances. This prediction agreed with estimates based on single-nucleotide polymorphism (SNP) marker genotypes in the region. Both microsatellite and SNP data predict that about 80% of marker pairs would display levels of LD that are useful for association studies at distances of up to 15kb in this region. These projections also agree with levels of LD directly measured in a 10 kb set of SNP genotypes generated in a nearby region of finished sequence. Our results suggest that existing sets of microsatellite data, if sufficiently dense, may be used to develop good initial estimates of the density of additional markers needed to screen a region for disease alleles by association analysis.