Uses of Microsatellites

Microsatellites are ideal for genetic mapping for several reasons. In humans they are highly informative and most exhibit heterozygosities over 70% (Weber, 1990; Gyapay et ai, 1994). As most of the mouse crosses are interspecific or intrasubspecific, more than 90% of microsatellites can be mapped by segregation analysis. The phenotypes can be determined through amplification of minute quantities of DNA, a process that can be scaled up through adaptation of multiplexing procedures and automation (e.g. Reed et ai, 1994; Weissenbach et ai, 1992). The mutation rate, estimated to be in the order of 10'^ in humans (Kwiatkowski et a i, 1992) and about 5x10*^ for laboratory mice (Dallas, 1992; Montaguelli et a i, 1991), would be expected to be negligible in the context of genetic mapping, provided that it remains relatively constant across the genome. The mutation rate in

the mouse was estimated for a few loci in recombinant inbred strains but as microsatellites become more widely used more accurate estimates should emerge, provided that sensitive electrophoretic analysis is used to detect mutant alleles.

Microsatellites have been used to generate genetic maps for a number of species, including domestic animals such as dogs and pigs (Ostrander et al., 1993; Wilke et al., 1994), plants such as Arabidopsis (Bell and Ecker, 1994) and mosquitoes (Zheng et al., 1993). In general, determining the phenotypes at a microsatellite locus involves size comparisons of the alleles. A number of approaches have been adopted for analysing the products from microsatellite amplification (e.g. Weber and May, 1989; Love et al., 1990; Reed et al., 1994; Dietrich et al., 1992). Each approach was adapted to maximise the efficiency of the project involved. During the amplification of mononucleotide and dinucletodite microsatellites, products are generated which are usually shorter or longer than the size of the amplified allele. The underlying mechanism that generates these ‘shadow bands’ is thought to involve slipped-strand mispairing, the same mechanism postulated to be responsible for the generation of new alleles in vivo (Hauge and Litt, 1993; Levinson and Gutman, 1987).

About 10% of microsatellites isolated from Mus musculus subspecies fail to amplify Mus spretus DNA (Dietrich et al., 1992 and 1994). The segregation of these ‘null’ alleles could still be followed in backcrosses where the interspecific hybrids are backcrossed to the Mus spretus parent. In human segregation analysis, null alleles were observed at a relatively high level and can potentially cause anomalies in the data (Weissenbach, 1993). Seven out of 23 loci surveyed in the CEPH (Centre d’Etude du Polymorphisme Humaine) families showed null alleles recognised by the apparent non-inheritance of parental alleles in some offspring and for three of these loci, nearly half of the families surveyed segregated a null allele (Callen et al., 1993).

3.3.5.1 Tackling Multifactorlal Diseases

The high degree of variation observed at microsatellites, the existence of mouse phenotypic variants that resemble complex human diseases like diabetes and epilepsy and the ability to set up breeding strategies to identify these regions, have made critical contributions in identifying loci implicated in traits caused by more than one gene. A complex trait is one that does not exhibit classic Mendelian inheritance attributable to a single gene locus (Lander and Schork, 1994).

The development of congenic strains led to the realisation that the genetic background affects the manifestation of a particular trait. It is now possible to dissect the mouse genome and identify specific regions and ultimately genes that exert these effects. For example, the NOD (non-obese diabetic) strain of mouse spontaneously develops insulin-dependent (type 1) diabetes mellitus (ldd-1) and

Eisenbarth, 1990). IDDM-1 is a metabolic disease resulting from an autoimmune destruction of insulin-producing p cells of the pancreas. So far, ten loci that contribute to the NOD phenotype have been identified (Todd et al., 1991; Cornall et al., 1991; Ghosh et al., 1993). This was achieved by analysing a first generation backcross progeny between NOD and a non-diabetic strain, the latter being the backcross parent. The candidate regions were those for which the mice were homozygous for NOD alleles which were then tested for association of the disease status and certain chromosomal regions. By advancing the number of backcross generations based on the same principle, Dietrich et al (1993) have identified a gene that resides on distal mouse chromosome 4 which affects the expression at the Min locus. The mouse mutant Min (for multiple intestinal neoplasia) shares many phenotypic features seen in patients with colonic polyposis syndromes, which include familial adenomatous polyposis (Moser et al., 1990). The effect of the min mutation can be modulated by the genetic background. The gene responsible for this phenotype, ape, is the mouse homologue of APC gene (adenomatous polyposis coli); the causative mutation has been characterised (Su et al., 1992).

The introduction of recombinant congenic strains (RCS), specifically designed for fine genetic mapping of loci involved in tumourigenesis, provide a novel genetic tool to dissect this multifactorial process (Groot et al., 1992; Moen et al., 1991). RCS are produced by inbreeding mice of the second backcross (N3 generation) for approximately 20 generations. The progeny theoretically carries 12.5% genes from the donor strain and the remaining 87.5% from the background strain. The backcross parent is the ‘normal’ line and the donor strain the ‘disease’ one. Inbreeding individual lines for 20 generations fixes this 12.5% fraction of the donor genome in different lines. As the set of donor-strain genes in each RC is different, the non­ linked genes in the donor strain controlling a multigenic trait such as tumour susceptibility become distributed in each RCS where they can be analysed one by one. Again, microsatellites are the only loci that can be used efficiently to map out the composition of the each RCS in terms of donor- and background-genome content. A genome-wide characterisation has been completed for three sets of RCS and four tumour susceptibility loci, on chromosomes 2, 7, 10 and 11 , have so far been identified (Moen et al., 1992; Groot et al., 1992). Individual susceptibility loci can be propagated in congenic strains for finer genetic mapping and eventual identificaition of the gene responsible (Ghosh et ai, 1993).

The genes responsible for multifactorial and monogenic diseases can be localised by linkage disequilibrium studies. When a disease mutation arises on a single chromosome, the combination of alleles that are tightly linked to the mutation remain in association through time because of their proximity. Tracking down these alleles in population studies can pinpoint the position of the disease locus at a much higher resolution than conventional linkage studies. The most important requirement

for linkage disequililbrium studies is the presence of polymorphic markers. Microsatellites again fit the bill, provided the mutation rate remains relatively low. In American blacks for example, a microsatellite allele at the glucokinase locus on human chromosome 7p is associated with susceptibility to non-insulin dependent diabetes mellitus (NIDDM) (Chiu, et ai, 1992). This observation was confirmed by the discovery that a rare autosomal dominant form of NIDDM is caused by mutations in the glucokinase gene (Froguel et ai, 1992; Vionnet et a i, 1992).