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Legume Genomics and Genetics 2012, Vol.3, No.1, 1
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Table 4 Information of soybean height QTLs
No. of QTLs Parents
Population size Analysis methods Population type Reference
5
Zheng92116×Shang951099
105
IM
F
2
Guan, 2004
4
Kefeng1×Nannong1138
-
2
201
IM
RIL
Wu et al., 2001
19
Zhongdou29×Zhongdou32
255
CIM
RIL
Wang, 2008
5
Suinong14×Suinong20
94
CIM
F
2
Zhu, 2006
8
Kefeng1×Nannong1138
-
2
184
CIM
F
2
Zhang et al., 2004
1
G. max
‘7499’×
G. soja
PI 245331
295
CIM
RIL
Li et al., 2008
6
G. max
IA2008×PI 468916
468
CIM
RIL
Wang et al., 2004
1
Minsoy×Noir 1
-
IM
RIL
Mansur et al., 1993
11
BSR 101×LG82
-
8379
167
-
RIL
Kabelka et al., 2004
2
Essex×Williams
-
-
RIL
Chapman et al., 2003
8
Jindou23×Huibuzhiheidou
-
CIM
RIL
Wang, 2004
8
Charleston×Dongnong594
154
CIM
RIL
Chen et al., 2007
Total: 78
Note: IM: Interval Mapping; CIM: Composite Interval Mapping
Table 5 Meta-analysis of soybean height QTLs
Chr. AIC value MQTL pos.
(cM)
Interval (cM)
Map-Distance
(cM)
L-marker L-Marker
Coordinate (cM)
R-Marker R-Marker
Coordinate (cM)
B1 105.37
32.61
30.75~34.47
3.72
Satt426
28
Sat_156
35
B1 105.37
56.42
54.25~58.58
4.33
Sat_149
54
Satt298
65
B1 105.37
87.44
81.87~93.01
11.14
Sat_095
81
Satt665
96
C2 18.04
105.05
102.33~107.78 5.45
Satt665
102
Satt365
112
D1a 16.92
49.04
48.2~49.88
1.68
Satt342
48
Sat_159
50
F
27.28
111.34
105.7~116.98
11.28
Sat_197
104
Satt218
118
G
21.53
10.08
4.12~16.04
11.92
Sat_168
3.9
Satt217
18
K
19.3
38.93
36.99~40.86
3.87
Satt137
37
Satt178
41
K
19.3
41.65
40.89~42.41
1.52
Satt178
41
Satt555
43
K
19.3
46.32
46.2~46.44
0.24
Satt441
41
Satt552
46
M
32.35
18.58
11.08~26.08
15
Satt590
7.8
Satt567
33
M
32.35
42.47
37.06~47.88
10.82
Satt540
34
Sat_244
49
QTL×Environment (Q×E) interaction, to obtain the
real QTL with genetic stability and explaining high
phenotypic variation, to improve the traits and accelerate
the development of breeding (Guo et al., 2003).
Epistatic effects of QTLs and QE interaction effects
were considered on protein and oil content in soybean
by mixed linear approach (Shan et al., 2008; 2009).
Based on different model, CIM and MIM were
different mapping methods (Zeng, 1994; Kao, 1999).
In the present study, 15 QTLs of soybean height were
detected by CIM and MIM in different environments.
The objective of planting under different environments
is to minimize the error, QTLs were detected twice or
more times would be the major QTL.
Wang and Paigen (2002) found that 18 of the 22
human HDL-C QTLs were within the murine HDL-C
QTL for guiding future research on the genetic
regulation of HDL concentrations and for finding gene
targets for up regulating HDL levels in mice and
humans. 127 plant height QTLs of maize were refined
by means of “overview” analysis. At last, 40 “real”
QTLs were identified (Wang et al., 2006). CI of QTLs
was greatly narrowed down by the method of
Meta-analysis. The “real” QTLs with precise locations
were then compared with genes affecting plant height
in maize and rice, and a number of candidate genes for
plant height QTG were found. Based on data of
soybean height from different populations and mapping