Data Structure for QTL Analysis

A data set used in QTL analysis will consist of a set of molecular marker scores and a set of phenotypic traits for each individual or line of the mapping population. Typically, a QTL data set will consist of 100 or more markers and five or more traits. A partial view of a data set for the Oregon Wolfe Barley population is shown in Table 1.

	Marker Scores	Trait Values
Line	ABG704	Wx	MWG089	CDO475	plant height	days to heading
1	A	A	A	A	73.34	39.3
2	B	B	A	A	40.01	23.7
4	A	A	A	A	59.37	41.0
5	B	A	.	B	81.92	46.3
6	B	B	A	A	37.47	28.0
7	B	B	B	B	71.12	43.0
8	A	A	B	B	39.69	30.4
9	A	B	B	B	78.42	60.8
10	A	A	A	A	48.90	32.0

Table 1. A subset of marker scores and phenotypic traits for 10 lines of the Oregon Wolfe Barley population, http://barleyworld.org/oregonwolfe. A and B scores refer to the parental alleles at a marker locus, and a period indicates missing data.

In addition to the marker and trait data, a marker linkage map is usually developed for each mapping population. A linkage map is required for simple and composite interval mapping, and is very useful, but not essential, for single-factor analysis of variance. Note the linkage map example (Fig. 7).

**Fig. 7. An example of a marker linkage map in wheat (after Gupta et al., 2002).**

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