Geoscience Reference
In-Depth Information
table 17.3
Single-marker analysis of markers associated
with qTLs using qGene
Chromosome or
linkage group
Marker
P value
R2
E
2
<0.0001
91
F
2
0.0001
58
G
2
0.023
26
H
2
0.5701
2
Source:
Nelson, J. 1997.
Molecular Breeding
, 3(3), 239-245.
Simple interval mapping
In order to mitigate the matter
related to single marker analysis, these techniques create
use of linkage maps and analyses intervals between adjacent
pairs of linked markers along chromosomes simultaneously
(Lander and Botstein 1989). This approach was considered
statistically more powerful compared to single-point analy-
sis because of the use of linked markers for recombination
between the markers and the QTL (Lander and Botstein
1989; Liu 1998). Several investigators have used Map Maker/
QTL (Lincoln et al. 1993) and Q Gene (Nelson 1997) to con-
duct SIM.
Composite interval mapping
Recently, this method has
become prevalent for mapping QTLs. This method com-
bines features of interval mapping with linear regression and
includes additional genetic markers in the statistical model
additionally to an adjacent pair of linked markers for inter-
val mapping (Jansen 1993; Jansen and Stam 1994; Zeng 1993,
1994). The main advantage associated with CIM is that it is
more precise and effective at mapping QTLs compared to
single-point analysis and interval mapping, especially when
linked QTLs are involved. Many researchers have used QTL
Cartographer (Basten et al. 1994, 2004), MapManager QTX
(Manly et al. 2001) and PLABQTL (Utz and Melchinger 1996)
to perform CIM.
Understanding interval mapping results
Interval mapping
strategies generate a profile of the sites for a QTL between adja-
cent linked markers. The result of the test statistic for interval
mapping is often conferred employing a LOD score or likeli-
hood ratio statistic (LRS). There is an immediate one-to-one
transformation between LOD scores and LRS scores (the
