遗 传 学 报
ISSN 0379-4172
Acta Genetica Sinica, August 2006, 33 (8)：724–732
QTL Analysis of Popping Fold and the Consistency of QTLs
Under Two Environments in Popcorn
LI Yu-Ling①, DONG Yong-Bin, NIU Su-Zhen
College of Agronomy, Henan Agricultural University, Zhengzhou 450002, China
Abstract: Popping fold (PF) is the most important quality trait in popcorn. In this study, a total of 259 F2:3 families, derived from
the cross between a dent corn inbred Dan232 and a popcorn inbred N04, were evaluated for their popping folds in replicated experiments under two environments. Of 613 simple sequence repeat (SSR) primer pairs screened, 183 pairs were selected to construct a genetic linkage map with the genetic distance of 1 762.2 cM (centimorgan) and on average 9.63 cM every marker.
Quantative trait loci (QTL) were identified, and their genetic effects were estimated using CIM (composite interval mapping)
method. The interactions among QTLs detected were calculated using MIM (multiple interval mapping) method. In all, 22 QTLs
were detected, and only 5 of them were common under two environments. Contribution to phenotypic variation of a single QTL
varied from 3.07% to 12.84%, and total contributions of all QTLs under two environments were 66.46% and 51.90%, respectively.
Three QTLs (qPF-6-1, qPF-8-1 and qPF-1-3) with more than 10% contributions were observed. The additive effects were larger
than dominant effects for most QTLs. The amount of QTLs showing additive, partially dominant, dominant and over-dominant
effects were 4, 5, 0, 2 in spring sowing and 2, 5, 2, 2 in summer sowing, respectively. There were only 2.60% pairs of QTLs or
maker intervals expressing AA, DA or DD interactions.
Key words: popcorn; popping fold; QTL; genetic effects; SSR marker
Popping fold (PF) is the most important quality
trait in popcorn[1]. Results from classical quantitative
genetics and traditional statistical analysis indicated
that PF is quantitative in nature, controlled by multiple genes [1-3]. Using normal maize (Zea mays L.)
germplasm is one of the effective ways to broad
popcorn germplasm and to improve popcorn inbred
lines [1,4-7]. With rapid advancement of molecular
technology, it is now possible to use molecular markers to construct high-density genetic maps for any
crop species, which can be used for detecting and
mapping major quantitative trait loci (QTL). In normal maize, many quantitative traits have been investigated, and their molecular genetic mechanisms have
been disclosed [8-16]. However, the PF in popcorn has
not been fully investigated. Only Lu et al.[17] studied
PF through 160 BC1S1 families developed from a
popcorn×dent corn cross, using 83 SSR markers and
interval mapping method.
Previous researches have shown that the amount
of QTLs detected, contribution and effect of individual QTL, interaction among different QTLs and their
fine mapping are all influenced by population size,
marker density, mapping methods and other influential
factors [18-21]. The effective utilization of marker assisted
selection (MAS) depends on the consistency of major
QTLs detected among different populations, generations
and environments. F2:3 population, which can be
quickly developed, harbors all possible combinations
of parental alleles, is the proper population for preliminary mapping to obtain as much information as
possible. Using codominant markers, three kinds of
genotypes according to Mendel’s law can be distinguished, and additive and dominant effects can be
estimated accurately through such populations.
Simulation results have shown that composite interval
Received: 2005-07-12; Accepted: 2005-12-15
This work was supported by the Major Programs for Science and Technology Development of Henan Province (No. 0122011700).
①
Corresponding author. E-mail: [email protected]; Tel: +86-371-6355 5540
LI Yu-Ling et al.: QTL Analysis of Popping Fold and the Consistency of QTLs Under Two Environments in Popcorn
mapping (CIM) method has high resolution and detection power, which has overcome the problems with
single marker analysis (SMA) and interval mapping
(IM) method [22].
In this study, 259 F2:3 families developed from a
cross between a dent corn inbred Dan232 and a popcorn inbred N04 were used. Popping fold was investigated under two environments, and mapped using
183 SSR markers and CIM mapping method. The
objectives of this study were to detect and map QTLs
for PF, to find some markers useful for further MAS
or marker-based selection in improvement of popcorn
using normal corn inbreds, and to provide reliable
theoretical basis for further fine mapping and cloning
of detected major QTLs.
1
1. 1
Materials and Methods
Materials
The population was developed from a cross between a dent corn inbred Dan232 and a popcorn inbred N04. The Dan232 × N04 cross was made at
Changge Agricultural Research Station, Xuchang,
Henan Province, China, in 2002. The F1 was selfed at
Sanya winter nursery, Hainan Province, China, in
winter 2002. The 259 F2:3 families were derived from
the unselected F2 plants at the Scientific Research and
Education Center of Henan Agricultural University
near Zhengzhou, Henan Province, China, in 2003.
Leaf samples were collected from each F2 plants,
F1 and the two parents at seedling stage, and stored at
–80℃ in a low-temperature refrigerator.
1. 2
Field experiments and PF measurement
The 259 F2:3 families, F1 and two parents were
evaluated in a completely randomized design of single
row plots 4 m long and 0.67 m apart with two replications under two environments (Spring and Summer
sowing) at the Scientific Research and Education Center
of Henan Agricultural University, Zhengzhou, Henan
Province, China, in 2004. Plots were planted by hand at
a density of 60 000 plants/ha. Standard cultural management practices were used at each environment.
All plants were self-pollinated or sister-pollinated
725
within each plot when more than 80% silks appeared.
After maturity, ears were harvested, naturally dried,
shelled, and bulked. Prior to popping with BZ-99 popping machine (Shanghai Duoli Food machine building
company, Shanghai, China), 2 × 100 randomly selected
perfect kernels were weighed with electron balance to
measure 100-kernel weight. The popping volume (PV,
mL) was measured with a 500 mL graduated glass, and
PF was calculated as PV/100KW (mL/g).
1. 3
Genotype analysis and molecular linkage
map construction
DNA was extracted and purified using a CTAB
procedure [23]. A total of 613 SSR primer pairs, chosen from Maize GDB（http://www.maizegdb.org）for
their distribution throughout all the ten maize chromosomes were initially screened for their polymorphism between the two parents. The primer pairs that
amplified polymorphic bands between parents and
generated co-dominant bands in their F1 were subsequently used to genotype each F2 plant. SSR analysis
was conducted as reported by Saghai Maroof et al [23].
The genetic map was constructed with Mapmaker/Exp 3.0 [24]. The critical LOD score for the test
of independence of markers pairs was set at 3.0. With
the Kosambi mapping function, the recombination
frequency between linked loci was transformed into
centimorgan (cM). A chi-square (χ2) test was then
applied to identify any distorted segregation of markers (P < 0.01) from the expected ratios.
1. 4
Data analysis and QTL mapping
CIM method [22] was used to map QTL and estimate their effects. For each chromosome, empirical
threshold levels for detecting QTL significance were
determined as 0.05 by 1 000 permutations according
to Churchill and Doerge [25]. A LOD score above 2.5
was considered as significant based on the study of
Lander and Botstein [26]. Average levels of dominance
were calculated as the ratio D/A with the dominance
effects estimated for the F2:3 populations. Gene action
was determined on the basis of the average level of
dominance by using the criteria used by Stuber et
al.[27]: additive (A) = 0–0.2; partial dominance (PD) =
726
遗传学报
Acta Genetica Sinica
Vol.33 No.8 2006
Table 1 shows the phenotypic variation of PF for
0.21–0.80; dominance (D) = 0.81–1.20; and overdominance (OD) > 1.20.
the F2:3 families, the parents and F1 in two environ-
1. 5
ments. PF differed between environments for F2:3
Interactions among detected QTLs
According to the result of QTL mapping based
on CIM, interactions among detected QTLs were analyzed using the multiple interval mapping (MIM)
method in WinQTLCart[28,29].
2
sowing, while for the F1 and the average of F2:3 families, PF was higher in Summer sowing. PF for the F1
was intermediate between the two parents. There
environments. The absolute values of skewness and
Trait performance of parents, F1 and F2:3
population
Table 1
was slightly higher in Spring sowing than in Summer
were wide variations among F2:3 families under both
Results
2. 1
families, two parents and F1. For the two parents, PF
kurtosis were all less than 1, showing normal distributions.
Performance of popping fold in both parents, F1 and F2:3 populations
Environments
Parents
F1
F2:3 population
Dan232
N04
Means
Range
CV (%)
Skewness
Kurtosis
Spring sowing
2.16
20.69
3.23
7.56±2.79
2.38–17.39
36.90
0.55
0.26
Summer sowing
2.14
19.21
3.81
9.95±3.28
2.04–20.97
32.96
0.29
0.23
2. 2
Genetic linkage map construction
One-hundred and ninety three SSR markers (ac-
counting for 31.48%), showing polymorphism between the two parents, were selected from 613 SSR
markers. Chi-square test reveled that 166 markers
accorded with the expected ratio of 1:2:1, and 27
markers (accounting for 13.99%) showed distortion
from the expected ratio. Ultimately, 183 markers
clearly showing co-dominant segregation were used
to construct the linkage map. Those markers covered
10 maize chromosomes with a total length of 1 762.2
cM and an average interval of 9.63 cM (Fig. 1). Most
of the markers located in regions similar to those in
maize GDB maps except for umc1841 (7.03),
bnlg2233 (7.02), bnlg292 (9.06) and bnlg1911
(10.04), which were located on chromosome 2 (2.07),
6 (6.04), 4 (4.08) and 9 (9.07), respectively.
2. 3
QTL analysis
A total of 22 QTLs significantly associated with
PF were detected under two environments (Table 2).
The QTLs were located at all maize chromosomes
except for chromosome 7. Five QTLs, qPF-1-1, qPF-1-4,
qPF-6-1, qPF-8-1 and qPF-9-1, were common under
both environments, which were located on the same
confidence interval or between the same marker intervals phi097–umc1269–umc1948, bnlg1643–umc1885,
phi299852–umc2165, umc1360–bnlg1863 (umc2147–
bnlg2082) and umc2371–bnlg1911, respectively.
In Spring sowing, 11 QTLs were detected, which
were located on chromosomes 1, 3, 4, 5, 6, 8, 9 and
10, with four on chromosome 1 and one on all others.
The contribution to phenotypic variation for an individual QTL varied between 3.07% and 12.84%, with
the total contribution of 66.46%. Eleven QTLs detected in Summer sowing were located on chromosomes 1, 2, 4, 6, 8, 9 and 10, with three on chromosome 1, two on chromosomes 2 and 6, and one on all
others. The contribution to phenotypic variation for
individual QTL varied between 3.83% and 12.15%,
with the total contribution of 51.90%.
There were three QTLs with contributions more
than 10% each: qPF-1-3 (12.84%, the highest in
Spring sowing), qPF-6-1 (10.38% in Spring sowing
and 12.15% in Summer sowing) and qPF-8-1 (4.59%
in Spring sowing and 10.43% in Summer sowing).
These QTLs could be considered as major QTLs.
LI Yu-Ling et al.: QTL Analysis of Popping Fold and the Consistency of QTLs Under Two Environments in Popcorn
Fig.1 Molecular marker map of 259 F2:3 families derived from cross Dan232 × N04
: popping fold in Spring sowing,
: popping fold in Summer sowing.
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Acta Genetica Sinica
Vol.33 No.8 2006
LI Yu-Ling et al.: QTL Analysis of Popping Fold and the Consistency of QTLs Under Two Environments in Popcorn
In most cases, additive effects were greater than
dominant effects. Only three QTLs had dominant
effects that were greater than the additive effects,
suggesting that additive effects were more important
than dominant effects for PF. This is consistent with
the results of the experiment through 15 generations
of successive selection using modified mixture selection by Weaver et al [30]. On the other hand, the numbers of QTLs expressing additive, partially dominant,
dominant, and over-dominant effects were 4, 5, 0, and
2 in Spring sowing and 2, 5, 2, and 2 in Summer
sowing. This indicates that partially dominant effects
might play the most important role in PF in popcorn,
followed by additive effects. As expected, the popTable 3
corn parent N04 contributed almost all of the positive
alleles. Interestingly, the normal corn parent Dan232
contributed the positive alleles of qPF-3-1.
2. 4
Digenic interactions among detected QTLs
Six pairs of digenic interactions among 22 QTLs
under two environments were detected using MIM
method in WinQTLCart (Table 3), which accounted for
only 2.60% of the possible 231 pairs of digenic interactions, suggesting their less importance. Three types of
digenic interactions existed, among which the pairs of
AA, AD and DD were 1, 4 and 1. The values of LOD
(0.60–1.58) and interaction effect of each pair of interactions (0.40%–3.70%) were all small.
Interactions among QTL detected for PF under two environments
Environments
QTL1/marker interval
QTL2
Interaction mode
LOD
Effects
R2 (%)
Spring sowing
qPF-1-2
qPF-4-1
DD
0.82
–1.350
0.90
qPF-1-3
qPF-1-4
DA
0.60
–0.960
0.40
qPF-1-4
qPF-6-1
DA
0.85
1.13
2.30
qPF-1-4
qPF-10-1
DA
0.71
1.22
2.00
qPF-6-1
qPF-9-1
DA
1.55
–1.45
3.30
umc1139-umc1075
qPF-10-2
AA
1.58
–1.06
1.80
Summer sowing
3
729
Discussion
Results from classical genetic research and practical breeding have proved that PF is quantitative in
nature, controlled by multiple genes [1,2]. Its broad
heritability is 0.62–0.96 [5, 30]. Additive genetic effect
plays the most important role in its inheritance, the
importance of dominant genetic effect varies with
different crosses, and no epistatic effect exists [3].
Twenty-two QTLs for PF were detected under two
environments in this study. The contributions to phenotypic variations for individual QTL varied between
3.07% and 12.84%. Only three QTLs, qPF-1-3,
qPF-6-1 and qPF-8-1, had contributions higher than
10% of the phenotypic variation, accounting for
13.64%. The numbers of QTLs expressing additive,
partially dominant, dominant, and over-dominant effects were 4, 5, 0, and 2 and 2, 5, 2, and 2, respectively, under two environments. Only 2.6% pairs of
digenic interactions among 22 QTLs were detected,
with small LOD values and contributions. In conclusion, PF was controlled by multiple genes with different effects. The number of major QTLs was small.
Additive and partially dominant effects might play an
important role, but dominant and over-dominant effects and three types of digenic interactions also existed. Therefore, more favorable additive gene loci
should be assembled through inter-crossing and successive selection in popcorn breeding, and then the
favorable partially dominant, dominant and
over-dominant effects be used through proper
cross-making among different inbreds.
Previous studies have indicated that the consistency in QTL detection among environments is different. Guffy et al. [31], Stuber et al. [15], Zehr et al. [32],
Schön et al. [16] and Melchinger et al. [19] have reported that QTL expression is influenced by different
environments. Nevertheless, detection of QTLs in the
730
same genomic regions across environments has been
reported by Austin et al. [33,34] and Veldboom et al [11].
Stuber et al. [15], Tanksley [35] and Goldman et al. [36]
stated that major QTLs with great effects have good
consistency in general. In present study, five QTLs
were detected under both the environments, accounting for 22.73% of all the 22 QTLs for PF. Among the
three major QTLs, only qPF-6-1 had contributions
higher than 10% under both environments. The QTL
qPF-1-3, with the greatest contribution (12.84%), was
only detected in Spring sowing. The contributions of
qPF-8-1 under two environments differed greatly,
with 4.59% and 10.43%, respectively. This reflected
that the expression of QTLs for PF was greatly influenced by environments, but some major QTLs had
good stability across environments, which was favorable to MAS.
The linkage degree between QTLs and its interval markers is the key factor in determining MAS
result. In this study, three major QTLs were detected
in three marker intervals on chromosomes 1, 6 and 8,
respectively. The QTL qPF-6-1 was 6.01 and 5.59 cM
apart from its two interval markers in Spring sowing,
and 4.01 and 7.59 cM in Summer sowing, which was
located in phi299852–umc2165 on chromosome 6,
with the best stability between environments, great
positive additive effects (1.35 and 1.69 mL/g) and
small negative dominant effects (–0.38 and –0.41
mL/g). The QTL qPF-8-1 was 0.01 and 0.59 cM apart
from its two interval markers under both the environments, which was located in two marker intervals
0.6 cM apart under two environments on chromosome 8, umc1360–bnlg1863 in Spring sowing and
umc2147–bnlg2082 in Summer sowing, with positive
additive effects (0.46 and 0.77 mL/g) and dominant
effects (0.56 and 1.04 mL/g). The QTL qPF-1-3 was
18.01 and 9.69 cM apart from its two interval markers in Spring sowing, which was located in
umc2227–bnlg1811 on chromosome 1, with the
greatest positive additive effect (1.76 mL/g) and the
greatest negative dominant effect (–1.04 mL/g).
Therefore, the QTL qPF-6-1 could be selected with
phi299852 and umc2165 simultaneously, qPF-8-1
with umc1360, bnlg1863, umc2147 and bnlg2082,
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Acta Genetica Sinica
Vol.33 No.8 2006
and qPF-1-3 with umc2227 and bnlg1811. However,
the selection results should be studied further. Zhu et
al.[37] suggested that MAS efforts may be better targeted at determining optimum combinations of QTL
alleles rather than pyramiding alleles detected in a
reference mapping population for traits such as grain
yield. Study on seeding emergence in sweet corn by
Yousef [38] showed that a combination of two QTLs
linked to umc139 and php200689 markers resulted in
the highest seeding emergence compared to other
combinations including all three of the beneficial
marker-QTL alleles together.
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爆裂玉米膨化倍数 QTL 分析及其环境稳定性
李玉玲，董永彬，牛素贞
河南农业大学农学院，郑州 450002
摘 要：膨化倍数是爆裂玉米最重要的品质指标。以普通玉米自交系丹 232 和爆裂玉米自交系 N04 杂交构建的 259 个 F2:3
家系为定位群体,采用完全随机区组设计在郑州春播和夏播条件下测定了膨化倍数。利用覆盖玉米 10 条染色体的 183 对多
态性分子标记构建连锁图，采用复合区间作图法（CIM）进行 QTL 定位分析，采用多区间作图法（MIM）分析定位 QTL
间的互作效应。共检测出 22 个 QTLs，单个 QTL 的贡献率为 3.07%～12.84%，累计贡献率为 66.46% 和 51.90%。其中 5
个 QTLs 在两种环境条件下均检测到，3 个 QTLs （qPF-6-1、qPF-8-1 和 qPF-1-3）的贡献率大于 10%。大多数 QTLs 的加
性效应值大于显性效应，表现为加性、部分显性、显性和超显性基因作用方式的 QTLs 数目在两种环境下分别为 4、5、0、
2 和 2、5、2、2。仅 6 对（占 2.60%）QTLs 或标记区间存在显著互作效应，表现为 AA、DA 或 DD 互作方式。
关键词：爆裂玉米；膨化倍数；QTL；遗传效应；SSR 标记
作者简介：李玉玲（1962-），女，博士，教授，博士生导师，研究方向：玉米遗传育种