The traditional approach to mapping genes, which we have learned in this chapter, is to examine progeny phenotypes in genetic crosses or among individuals in a pedigree, looking for associations between the inheritance of a particular phenotype and the inheritance of alleles at other loci. This type of gene mapping is called linkage analysis because it is based on the detection of physical linkage between genes, as measured by the rate of recombination, in progeny from a cross. Linkage analysis has been a powerful tool in the genetic analysis of many different types of organisms, including fruit flies, corn, mice, and humans.

Another alternative approach to mapping genes is to conduct genome-wide association studies, looking for nonrandom associations between the presence of a trait and alleles at many different loci scattered across the genome. Unlike linkage analysis, this approach does not trace the inheritance of genetic markers and a trait in a genetic cross or family. Rather, it looks for associations between traits and particular suites of alleles in a population.

139

Imagine that we are interested in finding genes that contribute to bipolar disorder, a psychiatric illness characterized by severe depression and mania. When a mutation that predisposes a person to bipolar disorder first arises in a population, it will occur on a particular chromosome and will be associated with a specific set of alleles on that chromosome. In the example illustrated in Figure 5.17, the D⁻ mutation first arises on a chromosome that has alleles A², B², and C⁴, and therefore the D⁻ mutation is initially linked to the A², B², and C⁴ alleles. A specific set of linked alleles such as this is called a haplotype, and the nonrandom association between alleles in a haplotype is called linkage disequilibrium. Because of the physical linkage between the bipolar mutation and the other alleles of the haplotype, bipolar disorder and the haplotype will tend to be inherited together. Crossing over, however, breaks up the association between the alleles of the haplotype (see Figure 5.17), reducing the linkage disequilibrium between them. How long the linkage disequilibrium persists over evolutionary time depends on the amount of recombination between alleles at different loci. When the loci are far apart, linkage disequilibrium breaks down quickly; when the loci are close together, crossing over is less common, and linkage disequilibrium will persist longer. The important point is that linkage disequilibrium provides information about the distance between genes. A strong association between a trait such as bipolar disorder and a set of linked genetic markers indicates that one or more genes contributing to bipolar disorder are likely to be near the genetic markers.

In recent years, geneticists have mapped millions of single-nucleotide polymorphisms (SNPs), which are positions in the genome at which people vary in a single nucleotide base (see Chapter 15). Recall that SNPs were used in a linkage analysis that located the gene responsible for pattern baldness, as discussed in the introduction to this chapter. It is now possible to quickly and inexpensively genotype people for hundreds of thousands or millions of SNPs. This genotyping has provided the genetic markers needed for conducting genome-wide association studies, in which SNP haplotypes of people who have a particular disease, such as bipolar disorder, are compared with the haplotypes of healthy people. Nonrandom associations between SNPs and the disease suggest that one or more genes that contribute to the disease are closely linked to the SNPs. Genome-wide association studies do not usually locate specific genes; rather, they associate the inheritance of a trait or disease with a specific chromosomal region. After such an association has been established, geneticists can examine the chromosomal region for genes that might be responsible for the trait. Genome-wide association studies have been instrumental in the discovery of genes or chromosomal regions that influence a number of genetic diseases and important human traits, including bipolar disorder, height, skin pigmentation, eye color, body weight, coronary artery disease, blood lipid concentrations, diabetes, heart attacks, bone density, and glaucoma, among others.