ABSTRACT
Karl Sax was a pioneer in the field of quantitative trait loci (QTL) mapping. In his ground breaking 1923 paper (Sax, 1923), Sax identified a quantitative trait locus (QTL) for seed weight by associating the trait with seed color (a “marker” for which genotype information could be inferred). The next 60 years saw only a handful of similar studies, due mainly to limitations imposed by the difficulty in arranging crosses with a large number of genetic markers. This changed in the 1980s following the discovery that abundant, highly polymorphic variation could be used to derive molecular markers densely spaced throughout the genome (Botstein et al., 1980). This advance, combined with statistical methods for QTL mapping (Lander and Botstein, 1989), led to hundreds of QTL mapping studies. A recent advance of comparable significance has been made in the area of phenotyping. With high throughput technologies now widely available, investigators today can easily measure thousands of traits for QTL mapping. Gene expression abundances measured via microarrays (see Section 1.4) are particularly amenable to QTL mapping, and most scientists agree that the mapping of gene expression has the potential to impact a broad range of biological endeavors (Cox, 2004; Broman, 2005). The optimism is based largely on the first expression trait loci (ETL) studies, which have demonstrated utility: in identifying candidate genes (Schadt et al., 2003; Hubner et al., 2005; Bystrykh et al., 2005), in inferring not only correlative but also causal relationships between modulator and modulated genes (Brem et al., 2002; Schadt et al., 2003; Yvert et al., 2003), in elucidating subclasses of clinical phenotypes (Schadt et al., 2003; Bystrykh et al., 2005; Chesler et al., 2005; Hubner et al., 2005), and perhaps most importantly, in identifying “hot spot” regions, genomic regions where multiple transcripts map (Schadt et al., 2003; Brem et al., 2002; Morley et al., 2004; Bystrykh et al., 2005; Chesler et al., 2005; Hubner et al., 2005). Hot spot regions are attractive for follow up studies as they putatively contain master regulators that
affect transcripts of common function. The identification of master regulators could give critical information on mechanisms of regulation that remain poorly characterized, ultimately leading to targets of gene therapies (Cox, 2004; Schadt et al., 2003). As a result of these successes, a number of efforts are now underway to localize the genetic basis of gene expression.
