Allelic association under map error and recombinational heterogeneity: A tale of two sites

Abstract

Recombination acts on the genetic map, not on the physical map. On the other hand, the physical map is usually more accurate. Choice of the genetic or physical map for positional cloning by allelic association depends on the goodness of fit of data to each map under an established model. Huntington disease illustrates the usual case in which the greater reliability of physical data outweighs recombinational heterogeneity. Hemochromatosis represents an exceptional case in which unrecognized recombinational heterogeneity retarded positional cloning for a decade. The Malecot model performs well for major genes, but no approach assuming either equilibrium or disequilibrium has been validated for oligogenes contributing to common disease. In this case of greatest interest, the power of allelic association relative to linkage is less clear than for major genes.Linkage is measured by sex-specific recombination between two loci, without regard to genotype. Allelic association is measured by dependence of allelic frequencies at two loci, without regard to sex-specific recombination. We are interested in the case in which one locus is a polymorphic marker and the other locus has alleles that affect susceptibility to a particular disease but have not yet been characterized. In a dense marker map, the distance between the disease gene and the closest marker can approach zero. Then under simple assumptions, maximal association is expected to occur at the same location as minimal recombination. These two independent sources of information may be efficiently combined to identify a small candidate region for the disease gene preparatory to positional cloning and sequencing (1, 2). The relative efficiency of linkage and allelic association depends on map accuracy and density, sample composition, evolutionary history of disease genes, and their frequencies and effects. Map error and recombinational heterogeneity pose problems for allelic association that are addressed here.

The first linkage disequilibrium (LD) maps: Delineation of hot and cold blocks by diplotype analysis

“…Older oligogenes must be less sensitive to inflexions in the LD map, which may mirror recombination more accurately than the few families on which the linkage map is currently based. LD maps will certainly increase the efficiency of positional cloning, for which the physical map is an unreliable measure of distance (31). For the HLA region male meiosis shows tight clustering of recombinants in hot spots with an SD of 300 bp (15).…”

Mapping quantitative effects of oligogenes by allelic association

“…The candidate region may be narrowed by recombination and refined by merging associated microsatellite marker alleles, calculating for each marker locus an appropriate measure of association ρ, and estimating the location of a disease locus in a high-resolution marker map Lonjou et al 1998). In contrast, oligogenes are usually common enough so that their allelic associations are more efficiently estimated in cohort or case-control studies , and their effects small enough that no reliance can be placed on merging alleles by a significance test.…”

“…Since 0 ρ 1 , we adopt the convention that 0 β b G and so 0 T b G . The Malecot equation for isolation by distance has been used to describe the decline of association with distance Lonjou et al 1998) and therefore gives a location for a causal site within a candidate region. If we express ρ in terms of β, R and T, the equation for the ith associated polymorphism becomes…”

“…M is the proportion of disease alleles transmitted from a unique founder haplotype (and so is 1 if disease alleles are monophyletic and less than 1 if they are polyphyletic). The distance d i between marker i and the causal locus should be measured in centimorgans (cM) if the genetic map is accurate, or on the physical map (kb) otherwise (Lonjou et al 1998). When available, a linkage disequilibrium map will give more reliable localization than either cM or kb (Maniatis et al 2002).…”

Fifty years of genetic epidemiology, with special reference to Japan

“…Better results were obtained by Collins and Morton (1998), who placed DF508 within 50 kb of its physical location using an evolutionary model provided by Malecot (1948) and including composite likelihood to allow for autocorrelation. Subsequent papers proved the appropriateness of the Malecot model ) and compared assignments from the physical and linkage maps, both at that time subject to considerable error (Lonjou et al 1998). Most of the markers used then were RFLPs that cannot be identified in later maps, and their locations in the linkage map are subject to substantial error.…”