Molecular Plant Breeding 2016, Vol.7, No.12, 1
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19
8
Continued Table 4
Traits
Chromosomes
QTLs
Intervals
LOD
PVE(%)
a
Add
b
9
qGL-9
RM566-9M10.51
2.59
5.57
0.1167
GW
2
qGW-2
M018-RM1211
2.50
4.81
0.0809
3
qGW-3
RM14391-M023
3.35
8.16
-0.0908
5
qGW-5a
M06502-M040
9.40
21.33
0.1634
5
qGW-5b
M13153-05M26.62
3.84
8.65
0.0917
LWR
2
qLWR-2
M018-RM1211
5.08
11.06
-0.1602
3
qLWR-3a
03M24.29-RM5488
4.43
8.60
-0.1524
3
qLWR-3b
RM14391-M023
3.91
10.91
0.1673
5
qLWR-5
M06502-M040
7.51
16.86
-0.2005
12
qLWR-12
M110-12M27.47
3.14
14.34
-0.1995
TGW
5
qTGW-5
M040-M09668
4.04
13.26
2.042
6
qTGW-6
06M17.5-6M13.5
3.57
9.04
1.4532
Note:
a
The percentage of phenotypic variation of QTL explained;
b
The additive effects of QTL. Positive
Add
indicates the alleles
derived from NYZ increasing the effect on that trait, and, whereas, negative
Add
indicates the alleles derived from NYZ decreasing
the effect on that trait.
Among four grain length QTLs,
qGL-3
, flanked by markers 03M36.3 and 03M33.1, was mapped at the end of the
short arm of chromosome 3 with 27.60% phenotypic contribution (Table 4). It should be mapped at the same locus
as
qGL3c
, another QTL for grain length, which was identified in a mapping population also using NYZ as
favorable grain size parent (Bai et al., 2010). It has been reported that QTL for grain size and shape traits mainly
controlled by cloned loci,
such as
GS3
,
GS5
,
GW2
,
GW5
, and
GW8
, with major effect on grain length, grain width,
and/or grain weight (Fan et al., 2006, 2009; Mao et al., 2010; Song et al., 2007; Shomura et al., 2008; Li et al.,
2011; Wang et al., 2012). In our results, two major QTLs
qGW-5a
and
qLWR-5
, were detected clustered at the
interval M06502-M09668 on chromosome 5 with
qTGW-5
. This locus is syntenic with the one that harbored
cloned
GW5
gene (Li et al., 2011; Huang et al., 2013). The other two clustered QTLs
qGW-3
and
qLWR-3b
, were
mapped at the interval RM14391-M023 on chromosome 3. Interestingly, cloned locus
GS3
and several
fine-mapped loci
GW3
,
GW3.1
,
qGL3a
, and
qGL-3
in previous reports, were located in this region (Huang et al.,
2013; Lou et al., 2009). These suggest that the hotspot identified in different research reports might be harbored a
pleiotropic QTL for grain length, width and grain weight (Figure 4; Table 4; Supplement Figure 3). However, in
this study, no QTL was identified syntenic with
GS5
,
GW2
, and
GW8
loci or located at their vicinity (Song et al.,
2007; Wang et al., 2012). Such phenomenon also observed in the other two study cases (Lou et al., 2009; Bai et al.,
2010). This indicates that different genetic background, different mapping population, and different methods for
QTL analysis may result in such discrepancy observed among different reports. In addition, no QTL for GT was
identified in this study. The reasonable interpretation might be the complex genetic basis of GT. It has been
suggested that GT is influenced by several distinct factors, such as, polygene controls with additive effects,
maternal effect, and, to some certain extent, affected by environmental conditions (Yang et al., 2001; Huang et al.,
2013).
Epistasis plays an important role in the genetic basis of rice flowering time and heterosis (Yamamoto et al., 2000).
In this study, all grain size related traits were influenced by epistatic interaction. The contributions of digenic
interactions to phenotypic variation were higher than those of their single QTLs. The effect of digenic interactions
to phenotypic variation of GL ranged from 12.42% to 46.17%. The effect to GW ranged from 16.41% to 41.88%,
and to GT ranged from 18.73% to 33.84%. The effect of digenic interactions for LWR ranged from 19.69% to
40.41%. Moreover, the digenic interactions to phenotypic variation of TGW had the largest effect (25.18% to
64.09%) by comparison with those of GL, GW, and GT (Supplement Table 2). The observation of the large
number of digenic interactions and a large proportion of phenotypic contribution involving in regulating the
variation of grain related traits also have been previously reported in rice (Lou et al., 2009) and in other crop
plants, such as maize (Ma et al., 2007), wheat (Wu et al., 2012). These results showed that digenic interaction
