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Legume Genomics and Genetics 2012, Vol.3, No.1, 1
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Table 2 The results of plant height QTL by CIM
Year
QTLs
LG
Interval
Marker interval
QTL pos.
LOD R
2
(%)
Additive affect
2006
QphD1a-1
D1a 198.9~206.3
Sat_062~Sat_106
202.9
3.76
10.00
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10.53
2007
QphG-1
G
0.4~16.6
Satt199~Sat_094
6.5
4.11
11.00
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7.57
2008
QphB1-1
B1
192.9~254.8
Satt509~Satt229
202.8
4.97
39.00
9.69
QphG-2
G
0.2~17.8
Satt505~Satt288
14.3
4.86
13.00
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4.98
Table 3 The results of plant height QTL by MIM
Year QTLs
LG
Interval
Marker interval
QTL pos.
LOD
R
2
(%)
Additive affect
2006
QphD1a-2
D1a 198.4~207.7
Sat_062~Sat_106
203.2
4
9.10
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13.18
2007
QphG-3
G
0.0~15.7
Satt199~Sat_094
4.41
4.25
13.80
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7.16
2008
QphI-1
I
68.7~74.4
Sct_189~Satt292
73.6
3.04
7.00
5.77
QphA1-1
A1
204.3~223.5
Satt390~Satt218
212.81
4.99
7.40
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4
QphA1-2
A1
145.2~151.0
Satt276~Sat_119
148.5
3.2
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5.28
QphB1-2
B1
192.6~261.5
Satt251~Satt229
210.2
10.1
59.70
12.2
QphB1-3
B1
261.5~329
Satt251~Satt229
278.4
8.3
59.70
12.2
QphB1-4
B1
83.0~121.6
Satt509~Satt197
107.1
7.53
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12.2
QphB1-5
B1
135.0~185.9
Satt197~Satt251
169.3
8.76
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12.2
QphB1-6
B1
356.5~422.2
Sat_099~Sat_113
403.9
5.6
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12.2
QphD1a-3
D1a 140.9~170.0
Satt220~Sat_062
155.41
4.81
4.00
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4.53
variation with an additive effect of
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13.18;
QphD1a
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was mapped between Satt220 and Sat_062, its CI was
140.9~170.0 cM, explaining about 4.00% of the
variation with an additive effect of
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4.53, three QTLs
were detected overlap of the confidence interval and
QTL of soybean height maybe exist on LG D1a. On
LG G,
QphG
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1
was mapped between Satt199 and
Sat_094, its CI was 0.4~6.6 cM, explaining about
11.00% of the variation with an additive effect of
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7.57;
QphG
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2
was mapped between Satt505 and
Satt288, its CI was 0.2~17.8 cM, explaining about
13.00% of the variation with an additive effect of
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4.98;
QphG
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3
was mapped between Satt199 and
Sat_094, its CI was 0~15.7 cM, explaining about
13.80% of the variation with an additive effect of
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7.16. The major QTLs of height maybe exist on LGG,
the additive effect was between
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4.98 and 7.57,
explaining from 11.0% to 13.80% of the variation.
Based on the data of height in three years, for
minimizing the error, we selected the QTLs which
were identified twice or more times, the QTL on LG
B1, LG D1a and LG G were the major QTL of soybean
height which were less affected by environment.
1.3 Collection of soybean height QTLs and Meta-
analysis
We collected the information of 78 QTLs, including
parents, population size, analysis method and popula-
tion type from previous studies (Table 4), integrated
including 36 marker intervals and 20 marker loci. With
the method of meta-analysis, 12 consensus QTLs of
soybean height were obtained and located on LG B1,
LG C2, LG D1a, LG F, LG G, LG K, and LG M
(Table 5). As Figure 2 showed, QTLs were integrated
on LG B1, three consensus QTLs were analyzed from
three, two, three original QTLs, respectively, the
minimum CI could reach 0.24 cM.
2 Discussion
In recent years, many studies on QTL mapping of
soybean height used one-year phenotypic data, but
little based on the multiple years and sites with different
methods. From a statistical point of view, the accuracy
of QTL position and affect could be detected if the
database were analyzed in different locations and years
(Jansen et al., 1995). In this research, the phenotype of
Charleston has a distant genetic relationship and
obvious differences result from different environment
and the selected randomness of phenotype measuring.
The phenotypic data of parents didn’t change the
result of QTL mapping, which based on the linkage
map drawn by Zhang (2004) and phenotypic data
were measured from 149 individuals. It is better to
try and replenish different mapping method, different
environments of the same material QTL mapping,