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Inheritance of the stay-green trait in tropical maize
Pedro Radi Belıcuas • Aurelio Mendes Aguiar •
Dyeme Antonio Vieira Bento • Tassiano Marinho Maxwell Camara •
Claudio Lopes de Souza Junior
Received: 2 October 2013 / Accepted: 5 December 2013 / Published online: 25 March 2014
� Springer Science+Business Media Dordrecht 2014
Abstract Stay-green maize genotypes have been
associated with tolerance to biotic and abiotic stresses,
including tolerance to drought, and to stalk and root
lodging, but there is limited information on its
inheritance. Thus, this research was conducted to
study the inheritance of the stay-green trait using both
conventional analysis and QTL mapping of the Design
III in a tropical maize population developed from two
inbred lines genetically divergent for this trait. Two-
hundred and fifty F2 plants were genotyped with 177
microsatellite markers, and their backcrossed proge-
nies to both parental inbreds were evaluated at three
locations. Ten plants per plot were assessed 120 days
after sowing and the plot means scores for stay-green,
adjusted for days to silking emergence, were used for
analysis. The additive variance was larger than the
dominance variance, the genetic by location interac-
tion variance presented a high magnitude, and the
heritability coefficient on a plant-basis a low magni-
tude. Seventeen QTL were mapped, most of them
were clustered on four chromosomes and accounted
for by 73.08 % of the genetic variance. About half of
the QTL interacted with location, and the average
level of dominance was partial dominance. The
additive effects were larger than the dominance
effects; the latter were not unidirectional, so that
heterosis could not be exploited in crosses. Procedures
for marker-assisted selection to increase the level of
P. R. Belıcuas � A. M. Aguiar � D. A. V. Bento �T. M. M. Camara � C. L. de Souza Junior (&)
Department of Genetics, Agriculture College ‘‘Luiz de
Queiroz’’, University of Sao Paulo, P.O. Box 83,
13400-970 Piracicaba, Sao Paulo, Brazil
e-mail: [email protected]
Present Address:
P. R. Belıcuas
Syngenta Seeds Ltda., P.O. Box 585, 38406-270
Uberlandia, MG, Brazil
e-mail: [email protected]
Present Address:
A. M. Aguiar
Fibria Celulose, Rodovia Gen., Euryale de Jesus Zerbini,
Km 84, 12340-010 Jacareı, SP, Brazil
e-mail: [email protected]
Present Address:
D. A. V. Bento
Nunhes do Brasil Comercio de Sementes Ltda., P.O. Box
2081, 59611-970 Mossoro, RN, Brazil
e-mail: [email protected]
Present Address:
T. M. M. Camara
Embrapa/Tabuleiros Costeiros, P.O.Box 2013, 57100-000
Rio Largo, AL, Brazil
e-mail: [email protected]
123
Euphytica (2014) 198:163–173
DOI 10.1007/s10681-014-1106-4
stay-green are discussed and an approach is suggested
for using both stable and non-stable QTL in a marker-
assisted backcross program.
Keywords Stay-green �Microsatellite markers �QTL � Design III � Genetic variances � Tropical
maize
Introduction
The trait delayed leaf and stalk senescence has been
termed as stay-green in several crop species including
maize (Zea mays L.). The leaves and stalks of stay-
green genotypes remain green for longer than for non
stay-green genotypes, increasing the period over which
photosynthetic activity supplies carbohydrates to the
stalks, leaves and roots (Thomas and Howarth 2000).
Several reports have shown that maize breeding
programs aimed at increasing grain yield have also
increased the stay-green across the selection cycles.
Thus, newer hybrids (Duvick et al. 2004) and popu-
lations (Crosbie and Mock 1981) are more stay-green
than older ones; that is, to some extent, the higher
productivity of newer hybrids can be accounted for by
their increased level of delayed senescence (Valenti-
nuz and Tolenaar 2004). Moreover, stay-green maize
genotypes present higher tolerances to biotic (pests)
and abiotic stresses (such as drought and high popu-
lation density), and reduced stalk and root lodging than
non stay-green genotypes (Chapman and Edmeades
1999; Tollenaar and Wu 1999; Kamara et al. 2005).
In Brazil, maize is cultivated with two planting-
harvesting cycles each year: normal-season (planting
in the spring-September/October and harvesting in the
summer-March/April), and off-season (planting in the
summer-February/March and harvesting in the winter-
June/July). Off-season maize has been increasing in
recent years, and now accounts for about 50 % of the
total annual production of maize (Conab 2013).
Rainfall patterns in Brazil vary considerably from
year to year, with the result that normal-season maize
occasionally experiences short periods of drought
stress, while for the off-season crop long periods of
drought stress are common. This irregularity in the
distribution of rainfall during the crop cycle has been
linked to the variability between years to the maize
grain yield across the country, particularly for
off-season maize (Soler et al. 2007). Furthermore,
the anticipated increase in temperature resulting from
global climate change will increase evapotranspiration
and, consequently, water deficit in maize growing
areas (Andrioli and Sentelhas 2009). Thus, besides
grain yield and other traits of agronomic/economic
importance, the stay-green trait should be considered
in maize breeding programs since, to some extent, it
could account for important related traits, as afore-
mentioned, particularly drought tolerance for the off-
season crop in tropical regions.
However, there is limited information on the
inheritance of the stay-green trait in maize. Gentinetta
et al. (1986) reported that it is controlled by only one
locus with two alleles, presenting complete domi-
nance; however some outliers from this model were
observed and while these were attributed to the
segregation of modifying loci, they could be inter-
preted as an indication that the inheritance of the stay-
green trait is quantitative. Indeed, other studies have
reported that stay-green is a quantitatively inherited
trait with additive effects more important than non-
additive effects (dominance and epistasis) (Guei and
Wasson 1996; Banziger et al. 2000; Lee et al. 2005;
Costa et al. 2008). To our knowledge, only four studies
have been conducted to map the quantitative trait loci
(QTL) for stay-green in maize. In temperate maize
germplasm, Beavis et al. (1994) mapped three and five
QTL in F4 progenies and their testcrosses, respectively,
Zheng et al. (2009) mapped 14 QTL in F2:3 progenies,
and Wang et al. (2012) mapped 14 QTL in F2 plants,
while in tropical germplasm, Camara (2006) mapped
20 and 33 QTL in two populations using F2:3 progenies.
Comstock and Robinson (1952) developed the
Design III to estimate the components of the genetic
variance and the average level of dominance, and this
design has been widely used to study the inheritance of
several traits in maize (Hallauer and Miranda Filho
1988). Lu et al. (2003) and Frascaroli et al. (2007)
presented a procedure to map QTL using the Design
III, and coupled with classical analysis it is a powerful
framework for inheritance studies. To develop stay-
green maize cultivars a thorough understanding of the
inheritance of the stay-green trait is required, but as
mentioned earlier, there is only limited information on
164 Euphytica (2014) 198:163–173
123
this subject, especially for tropical germplasm. Thus,
the objective of this research was to use the Design III
coupled with molecular markers to study the inheri-
tance of the stay-green trait in a tropical maize
population.
Materials and methods
Genetic material
Parental inbred lines L-14-04B and L-08-05F that
present low and high stay-green phenotypes, respec-
tively, and similar flowering dates, were used to
develop a reference F2 population. Both inbreds were
developed by the Maize Breeding Program in the
Department of Genetics, at the Agriculture College
‘‘Luiz de Queiroz’’, University of Sao Paulo, Brazil.
Inbred L-14-04B, with yellow dent kernels, was
developed from the BR-106 population, and inbred
L-08-05F, with orange flint kernels, was developed
from the IG-1 population, and both populations were
derived from tropical germplasm (Sibov et al. 2003).
The parental inbreds were crossed and three F1 plants,
previously tested against the parental inbreds to check
their genetic identity with microsatellite markers,
were selfed to develop the F2 population. Two-
hundred and fifty plants were randomly taken and
selfed to develop F2:3 progenies, which were then
backcrossed to the parental inbreds in isolation blocks.
The F2:3 progenies were used as females and the
parental inbreds as males; the males were sown at each
set of four progenies and each plot consisted of 30
plants. Each plot was harvested separately and their
seeds bulked. Thus, from each F2 plant two back-
crossed progenies were developed, for a total of 500
backcrossed progenies (BC), 250 backcrossed to L-14-
04B (BC1) and 250 to L-08-05F (BC2).
Experimental evaluation
The 500 backcrossed progenies and their parental
inbreds were evaluated during the 202/203 growing
season on three locations near Piracicaba, Sao Paulo
State, Brazil: Areao, Caterpillar, and Departamento de
Genetica experimental stations of University of Sao
Paulo. The experimental design was 10 9 10 lattices,
with two replications per location. Each lattice con-
sisted of 50 pairs of progenies backcrossed to the two
parental inbreds; then there were five lattices (exper-
iments) per location. In all locations the experiments
and their replications were randomized within the area
they were installed. The parental inbreds were allo-
cated at the beginning of each replication. Plots were
one row 4.0 meters long, spaced 0.8 m between rows,
and 0.2 m between plants within rows; plots were
overplanted and thinned to 20 plants per plot (62,500
plants ha-1). Near the experiments, a mixture of seeds
of all progenies was sown as a border around the
experiments to allow the assessment of the physio-
logical maturity of the kernels of the F2 reference
population. Black layer development of the kernels
was assessed at three- day intervals, beginning
110 days after sowing, in a set of 50 ears taken from
plants in the borders. On the 119th day, in all
experiments, the vast majority (*90 %) of the ears
analyzed showed full development of the black layer.
The stay-green trait was recorded on the 120th day
after the experiments were sown, which corresponded
to 55 days after the average silking date for the
population.
Ten competitive plants per plot were visually rated
given a score from 1 (highest) to 5 (lowest) to record
their degree of stay-green. Score 1 was assigned to
plants with all leaves above the ear, at least two leaves
below the ear, and the stalks green; 2 to plants with all
leaves above the ear and the stalks green; 3 to plants with
two leaves above the ear senescent and the others green
regardless of the color of the stalks; 4 to plants with two
green leaves above the ear and senescent stalks; and 5
the plants with all leaves and stalks senescent. Thus, a
score of 1 means that the plant was fully stay-green,
retaining the green leaf area and photosynthetic activity
beyond maturity, while a score of 5 means that the plant
did not retain the green leaf area until the end of maturity
and, consequently, photosynthetic activity during the
grain filling period decreased. A similar rating scale has
been used in other studies on the inheritance of the stay-
green trait in maize (Guei and Wasson 1996; Duvick
et al. 2004; Camara et al. 2007; Costa et al. 2008).
Although the parental inbreds have similar flowering
dates, the backcrossed progenies presented variability in
their flowering dates. The progeny silking date, recorded
as the number of days from sowing to 50 % of the plants
in the plot showing silk emergence, was used to adjust
the stay-green trait for average silking date for each plot
by covariance analysis. The plot means were used for
analyses.
Euphytica (2014) 198:163–173 165
123
Analysis of variance
Analyses of variance were computed for each lattice,
pooled over lattices for each location, and combined
across locations following the Design III. Before the
analyses were conducted, the error variances were
tested for homogeneity using the Bartlett’s test
(P B 0.05) (Sokal and Rohlf 1995), and no significance
was found. All analyses were performed using PROC
GLM from the SAS software (SAS Institute Inc 2001).
From the combined analysis of variance, estimates of
the additive ðr2AÞ and dominance ðr2
DÞvariances, and
their respective interactions with location ðr2AL and
r2DLÞ, and the average level of dominance ð �d ¼ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi
2r2D=r
2AÞ
p
were computed following the procedures
devised by Comstock and Robinson (1952) for Design
III. Also, the genetic variance ðr2G ¼ r2
A þ r2DÞ, the
genetic by location interaction variance ðr2GL ¼
r2AL þ r2
DLÞ, the phenotypic variance on a progeny
mean-basis ½r2Ph ¼ r2
G þ ðr2GL=LÞ þ ðre=RLÞ� and on a
plant-basis ðr2PhP ¼ r2
G þ r2GL þ r2
eÞ, and the herita-
bility coefficients on a broad-sense progeny mean-
basis (hb ¼ r2G=r
2PhÞ and strict-sense ðh2
s ¼ r2A=r
2PhPÞ
were computed. re, R, and L stand for the error
variance, number of replications, and number of
locations, respectively. Confidence intervals at the
95 % probability level for the estimates of the genetic
and phenotypic variances, for the level of dominance,
and for the heritability coefficients were computed
following the procedures of Burdick and Graybill
(1992).
Genetic map
The genetic map used, and the procedures used to
develop it, was previously described by Sibov et al.
(2003). Briefly, the F2 plants that gave rise to the F2:3
progenies were genotyped with microsatellite mark-
ers. The genetic map was developed using MAP-
MAKER/EXP version 3.0b (Lincoln et al. 1992) with
a LOD threshold of 3.0 and a maximum distance
between adjacent markers of 50 cM; i.e., 0.38 as the
maximum recombination frequency, to establish the
linkage groups, and the Kosambi’s (1944) mapping
function was used to convert recombination frequen-
cies into map distances. Sixty new microsatellite
markers were added to the map of Sibov et al. (2003),
for a total of 177 markers distributed along the 10
linkage groups. The genetic map spanned 2,052 cM in
length with an average interval of 11.60 cM between
adjacent markers.
QTL mapping
The composite interval mapping method (CIM)
extended to perform a joint analysis of multiple
locations (mCIM) was used to map QTL, since it is
more powerful than the CIM procedure. The least
square means of stay-green scores from each location
were used to perform the analysis. The underlying
mixture model for QTL mapping is (Jiang and Zeng
1995):
Yjk ¼ b0k þ a�kx�j þ d�k z�j þX
t
l
ðalkxjl þ dlkzjlÞ þ ejk
where Yjk is the phenotypic mean of the jth progeny at
the kth location; b0k is the mean effect of the model for
location k; a�k is the additive effect of the putative QTL
for location k; x�j counts the number of alleles from
parental inbred L-08-05F at the putative QTL taking
values of 2, 1, and 0 for genotypes QQ, Qq, and qq,
respectively, with probabilities depending on the
genotypes of the markers flanking the putative QTL
and the recombination frequencies between the QTL
and the markers; d�k is the dominance effect of the
putative QTL for location k; z�j is an indicator variable
taking values of 1 for genotype Qq and 0 for genotypes
QQ and qq of the putative QTL, with probabilities
depending on the genotypes of the markers flanking
the putative QTL and the recombination frequencies
between the QTL and the markers; xjl and zjl are
corresponding variables for marker l, with t markers
selected as cofactors for controlling residual variation;
alk and dlk are the partial regression coefficients of Yjk
on xjl and on zjl, respectively; and ejk is the residual of
the model. The cofactors were selected using the
stepwise regression procedure (P B 0.05) for each
location and combined for the joint QTL analysis.
QTL mapping was performed for each set of the
backcrossed progeny, and then two analyses were
performed: one for the progenies backcrossed to the
parental inbred L-14-04B (BC1), and one for those
backcrossed to the parental inbred L-08-05F (BC2).
The likelihood-ratio (LR) threshold used to declare the
presence of a QTL was computed following the
166 Euphytica (2014) 198:163–173
123
procedure described by Vieira et al. (2000), which is
based on the number of independent tests and the
window size used (10 cM). The number of indepen-
dent tests was 74 and the genome-wide probability
level used was a = 0.05, so that for each test the
probability level was a0 = 0.05/74 = 0.00067. The
threshold for the QTL mapping was then LR = 19.33
(LOD = 4.20) and for the interaction QTL by location
(QTL 9 L) the threshold was LR = 14.6
(LOD = 3.17). The LOD score used for the QTL
mapping was greater than that used in other studies for
this trait in maize (Beavis et al. 1994; Zheng et al.
2009). The QTL mapping was performed with the
software Windows QTL Cartographer, version 2.5,
JZmap procedure (Wang et al. 2005), using a window
size of 10 cM and a walking speed of 1 cM.
Since the QTL analyses were performed separately
for each of the backcrossed progenies, the mCIM
model did not return directly the values of the additive
and dominance effects, but they can be computed from
the pseudo-additive values (‘‘a’’) estimated from the
individual analyses as follows: the ‘‘a’’ value for a
QTL mapped in the BC1 progenies is actually
‘‘a1’’ = (a - d)/2, and for a QTL mapped in the
BC2 progenies ‘‘a2’’ = (a ? d)/2, so that the additive
and dominance effects for each mapped QTL could be
computed as: a = (‘‘a1’’ ? ‘‘a2’’) and d = (‘‘a1’’ -
‘‘a2’’), respectively (Lu et al. 2003, Frascaroli et al.
2007). The phenotypic variances explained by each
QTL and by the set of all mapped QTL (R2Ph) were also
computed in Windows QTL Cartographer. All the QTL
previously mapped using the mCIM procedure were
fitted in a single model with multiple QTL, and then, the
software uses the EM algorithm to evaluate the likeli-
hood of this mixture model with multiple QTL. Once the
model had been fitted, the coefficients of phenotypic
determination of each QTL and of all QTL were
automatically computed by the software. The genotypic
coefficients of determination for each QTL and for the
set of all QTL mapped were computed by dividing the
respective phenotypic coefficients of determination
(R2Ph) by the coefficient of heritability, i.e.
R2G ¼ R2
Ph=h2. Parental inbred L-08-05F has slower
leaf senescence than the parental inbred L-14-04B.
Since the rating scale ranged from 1 for the highest
level of stay-green to 5 for no stay-green plants, a
negative sign for the additive effect of a QTL indicated
that the favorable allele (allele that increase stay-
green) was from the L-08-05F, while a positive sign
indicated that a favorable allele was from L-14-04B.
The level of dominance of a QTL was computed as the
ratio LD ¼ dj j= aj j, and the average level of dominance
(ALD) was computed as a sum of LD ratios, each
weighted by R2G value of its respective QTL. The QTL
action for each QTL and for the set of all mapped QTL
were characterized as additive (A) for 0.00 B LD
B 0.20, partial dominance (PD) for 0.21 B LD B
0.80, dominance (D) for 0.81 B LD B 1.20, and
overdominance for LD C 1.21 (Lima et al. 2006).
Results
Means and variances
The W tests performed for the distribution histograms of
the stay-green data and of the standardized residuals
showed that both histograms did not differ significantly
from the normal distributions. The overall means of the
parental inbreds differed significantly (P B 0.05) (L-
14-04B = 4.20 vs. L-08-05F = 2.20), their mean
(3.20) did not differ from the mean of the two
backcrosses (2.88), which in turn did not differ signif-
icantly between themselves (BC1 = 3.05 vs.
BC2 = 2.71). The means of the progenies assessed
ranged from 1.38 to 4.95 for BC1 and from 1.31 to 4.58
for BC2, showing the presence of transgressive proge-
nies, with lower and higher stay-green means than
parental inbreds, for both backcrosses. The experimen-
tal coefficient of variation (CV %) was 18.01 %, which
is similar to other reported values (Costa et al. 2008;
Camara et al. 2007), showing that the data recorded
presented good experimental precision (Table 1).
Highly significant differences (P B 0.01) were
detected in the combined analysis of variance of the
Design III (not shown) for progeny and for progeny by
parent interaction, indicating that both additive and
dominance effects were present in the variation for the
stay-green trait. Also, significant (P B 0.05) progeny
by location interaction was detected, but the progeny
by parent by location interaction was not found to be
significant, and therefore, the mean values of the
progenies from both backcrosses varied across loca-
tions whereas for the progeny by parent interaction did
not; then additive effects presented differential values
across locations but the dominance effects did not.
Euphytica (2014) 198:163–173 167
123
The estimate of the genetic variance (r2GÞ, and its
components the additive ðr2AÞ and the dominance ðr2
DÞvariances, the broad-sense ðh2
bÞ on a progeny mean-
basis and strict-senseðh2s Þ heritability coefficients, and
the average level of dominance, all differed signifi-
cantly from zero. In addition, additive variance was
significantly much larger than the dominance vari-
ance, and the level of dominance was 0.55 (Table 2).
QTL Mapping
Seventeen QTL were mapped on chromosomes 1, 2, 3,
4, 6 and 9; i.e., QTL were not mapped on chromo-
somes 5, 7, 8 and 10. The number of QTL mapped on
each chromosome varied greatly, being clustered on
chromosomes 1 (four QTL), 2 (five QTL), 3 (three
QTL), and 4 (three QTL); one QTL was mapped on
chromosome 6 and one on chromosome 9. The
additive effects (a) of the QTL ranged from -2.80 to
1.82, and the dominance effects (d) ranged from -1.33
to 1.93. The actions of four of the QTL mapped were
characterized as additive, seven QTL displayed partial
dominance, and six overdominance, so the mapped
QTL presented all types of gene action, except
dominance. The average level of dominance (ALD)
was 0.65, characterizing partial dominance. Of the
seventeen mapped QTL, 11 (64.70 %) with favorable
alleles (alleles increasing stay-green) were from the
parental inbred L-08-05F and six (35.30 %) from the
parental inbred L-14-04B. The percentage of the
phenotypic (genotypic) variance accounted for by a
single QTL ranged from 0.47 % (0.74 %) to 24.32 %
(38.67 %), and collectively 46.04 % (73.08 %) was
accounted for by the set of mapped QTL. There is one
major QTL on chromosome 1 (Stg1b) that alone
accounted for 24.32 and 38.67 % of the phenotypic
and genotypic variances, respectively. Nine out of the
17 mapped QTL (52.94 %) interacted significantly
with location as expected since the interaction progeny
by location in the combined analysis of variance was
highly significant (Table 3).
Discussion
Means and variances
The difference between the stay-green means for the
parental inbred lines L-08-05F (2.20) and L-14-04B
(4.20) was highly significant, evidencing their genetic
divergence for this trait. The mean for the progenies
backcrossed to L-08-05F (BC2 = 2.71) was lower
than for the progenies backcrossed to L-14-04B
(BC1 = 3.05); however, the difference was not
Table 1 Mean values and confidence intervals of the parental
inbreds (L-08-05F and L-14-04B), of the backcrossed proge-
nies to the parental inbreds (BC1 and BC2), of the averages of
the parental inbreds and of the backcrossed progenies, ranges
of BC1 and BC2, and coefficient of experimental variation
(CV %) for stay-green in a maize population
Entriesa Means Confidence intervalsb
L-08-05F 2.20 [1.92; 2.48]
L-14-04B 4.20 [3.39; 5.00]
(L-08-05F?L-14-04B)/2 3.20 [2.71; 3.72]
BC1 (L-14-04B) 3.05 [1.98; 3.97]
BC2 (L-08-05F) 2.71 [2.04; 3.70]
(BC1 ? BC2)/2 2.88 [2.55; 3.40]
Range BC1 1.38; 4.95 –
Range BC2 1.31; 4.58 –
CV % 18.01 % –
a L-08-05F: high stay-green, L-14-04B: low stay-green, BC1:
backcross to parental inbred L-14-04B, BC2: backcross to
parental inbred L-08-05Fb Confidence intervals at the 95 % probability level
Table 2 Estimates of additive ðr2AÞ, dominance ðr2
DÞ, genetic
ðr2G ¼ r2
A þ r2DÞ variances and their respective interaction with
location ðr2AL; r
2DL;r
2GLÞvariances, heritability coefficients on a
strict-sense ðh2s Þ and on a progeny-mean basis ðh2
bÞ, average
level of dominance ð�dÞ and their confidence intervals for stay-
green in a maize population
Parameters Estimatesa Confidence intervalsa,b
r2A
10.84 [7.61; 16.67]
r2D
1.69 [0.89; 4.38]
r2G
12.53 [8.82; 18.26]
r2AL
7.45 [4.25; 16.29]
r2DL
1.23 [-0.40; 17.34]
r2GL
8.68 [5.43; 16.78]
h2s
0.23 [0.18; 0.30]
h2b
0.63 [0.55; 0.71]
�d 0.55 [0.34; 0.82]
a Estimates of variances and their respective confidence
intervals multiplied by 102
b Confidence intervals at the 95 % probability level
168 Euphytica (2014) 198:163–173
123
statistically significant. Nevertheless, the genetic
divergence of the parental inbreds allowed the devel-
opment of a population with high genetic variability
for the trait assessed, and the presence of transgressive
progenies for both backcrosses indicates that both
parental inbreds have loci with alleles to increase and
to decrease stay-green.
Both the additive and dominance variances were
significant, with the additive variance exceeding the
dominance variance by a factor of 6.41. The additive
by location interaction variance was also significant,
with a similar value to the additive variance, whereas
the dominance by location interaction variance was
not found to be different from zero. The average level
of dominance was classified as partial dominance.
Since the type of population used in this study presents
a high-level of linkage disequilibrium, the estimates of
the additive and dominance variances are biased.
Regardless of the phase of the linkage disequilibrium,
the dominance variance is always biased upward while
the additive variance is biased upward when the
linkage disequilibrium is in the association-phase and
downward for the repulsion-phase (Comstock and
Robinson 1952). The expectation is that the estimate
of the level of dominance will be biased upward, so
that the additive effects are probably even more
important compared to the dominance effects than
suggested by the estimate of the level of dominance.
The estimate of the broad-sense heritability coefficient
(0.63) was slightly lower than the estimates reported
by Bekavac et al. (2007) and Camara et al. (2007),
which ranged from 0.67 to 0.81, but the strict-sense
Table 3 Genomic positions, likelihood-ratio (LR) values, gene actions and average level of dominance (ALD), direction, and
phenotypic ðR2PhÞ and genotypic ðR2
GÞ coefficients of determination for the QTL mapped for stay-green in a maize population
QTLa QTL positionsb LRc Genetic effectd Gene actione DirectionfR2
Ph% R2G%
Bin cM Flanking intervals a d LD Type
Stg1a 1.02/1.03 51.05 bnlg1083/umc1073 22.08 -1.29 0.71 0.55 PD L08-05 4.83 7.68
Stg1b 1.05/1.06 124.63 umc1601/bnlg2057 37.47 -2.80 1.93 0.69 PD L08-05 24.32 38.67
Stg1c 1.06/1.06 150.27 bnlg2057/umc1508 44.47 -1.52 -1.33 0.88 PD L08-05 8.00 12.72
Stg1d 1.10/1.11 274.12 umc1431/phi0120 21.76 0.59 0.38 0.64 PD L14-04 1.04 1.65
Stg2a 2.01/2.02 5.81 bnlg1338/umc1227 24.07 0.44 0.69 1.58 OD L14-04 1.08 1.72
Stg2b 2.02/2.02 12.72 bnlg1017/umc1265 19.58 0.27 0.51 1.91 OD L14-04 0.50 0.79
Stg2c 2.07/2.07 175.97 umc2129/umc1560 19.77 -0.84 1.29 1.53 OD L08-05 3.84 6.10
Stg2d 2.08/2.08 201.98 umc1464/umc1633 21.89 -0.86 1.05 1.22 OD L08-05 3.23 5.13
Stg2e 2.09/2.09 217.94 umc1230/bnlg1520 24.25 -1.14 0.71 0.62 PD L08-05 3.87 6.15
Stg3a 3.01/3.02 0.01 umc1394/bnlg1144 22.78 0.50 0.70 1.40 OD L14-04 1.23 1.95
Stg3b 3.07/3.08 147.40 umc1659/umc1320 22.27 -1.13 0.06 0.05 A L08-05 3.21 5.10
Stg3c 3.09/3.09 193.98 bnlg1754/bnlg1098 25.06 -0.25 -0.49 1.95 OD L08-05 0.47 0.74
Stg4a 4.01/4.01 0.01 umc1276/umc1757 25.49 -0.45 -0.32 0.71 PD L08-05 0.63 1.00
Stg4b 4.04/4.05 44.93 umc1652/phi0026 24.27 0.93 0.55 0.59 PD L14-04 2.56 4.07
Stg4c 4.05/4.06 56.85 bnlg0252/bnlg2291 23.72 1.82 0.15 0.08 A L14-04 8.36 13.29
Stg6 6.00/6.01 8.03 phi0126/bnlg1371 20.15 -1.22 -0.15 0.12 A L08-05 3.76 5.99
Stg9 9.03/9.04 67.67 bnlg0430/umc1107 27.13 -1.23 -0.09 0.07 A L08-05 3.80 6.04
ALD 0.65 PD Total 46.04 73.08
a QTL names are indicated as Stg (stay-green) followed by the chromosome number and by a letter for more than one QTL on the
same chromosomeb Position of QTL refers to the distance in centimorgans (cM) from the first marker on the chromosome to the mapped QTLc Underlined LR (likelihood-ratio) values indicate that the QTL interacted significantly with locationd Additive and dominance effects were multiplied by 10e Gene action-type: A additive, PD partial dominance, OD overdominance, ALD average level of dominancef Direction indicates the parental inbred that increases the trait: negative and positive a values indicates that favorable alleles were
from L-08-05F and L-14-04B, respectively
Euphytica (2014) 198:163–173 169
123
heritability coefficient on a plant-basis (0.23) was
slightly greater than those reported by Guei and
Wasson (1996) (0.12 and 0.15) for two tropical maize
populations.
QTL mapping
Fifteen out of the seventeen mapped QTL (88.23 %)
were found on just four chromosomes, and since the
set of mapped QTL accounted for a large portion of the
genetic variance (73.08 %) the results indicated that
the QTL underlying the stay-green trait were not
evenly distributed on the genome, but clustered in a
few chromosomes. Note that one of the QTL on
chromosome 1 (Stg1b) had a major effect accounting
for 38.67 % of the genetic variance.
The number of QTL mapped in the four previous
reported studies of the stay-green trait in maize varies
greatly, i.e., from eight (Beavis et al. 1994) to 33
(Camara 2006); and both Zheng et al. (2009) and
Wang et al. (2012) mapped 14 QTL for this trait.
Camara (2006) reported QTL mapping for two
tropical maize populations, and in one of these
populations the 20 QTL mapped were distributed
over the ten chromosomes, but in the other population
23 (76.67 %) of the 33 QTL mapped were clustered on
chromosomes 1, 2 and 5. Beavis et al. (1994) reported
that three out of their eight mapped QTL were on
chromosomes 1 and 2, in the study of Zheng et al.
(2009) the QTL were largely clustered on chromo-
somes 1, 2, and 5, and in the report of Wang et al.
(2012) they were largely clustered on chromosomes 1,
4, and 5. In our study no QTL were mapped on
chromosome 5; they were largely clustered on chro-
mosomes 1 and 2, and the major QTL (Stg1b) was on
chromosome 1. Thus, based on our results and on the
previously reported studies, it is likely that most of the
QTL underlying the stay-green trait are clustered on
chromosomes 1, 2, and 5.
Comparing our results with those of Beavis et al.
(1994), Zheng et al. (2009), and Wang et al. (2012), we
found only two (Stg2b and Stg2d), three (Stg1b, Stg1c,
and Stg3b), and three QTL (Stg1a, Stg1b, and Stg4b),
respectively, mapped in the same genomic regions.
However, 11 of the 17 QTL mapped in our study and
all the QTL reported by Beavis et al. (1994), Zheng
et al. (2009), and by Wang et al. (2012) were on the
same genomic regions of the QTL reported by Camara
(2006). Thus, six unreported QTL for stay-green were
mapped in this study, adding information on the
genetic architecture of this trait.
Of the QTL mapped, 11 displayed negative and six
displayed positive additive effects (a). Therefore,
alleles that increase stay-green, i.e., favorable alleles,
were present in both parental inbreds. As expected,
most of the QTL with favorable alleles (64.70 %) were
from the parental inbred L-08-05F. The presence of
QTL with favorable and unfavorable alleles in both
parental inbreds allowed the observed occurrence of
transgressive progenies as aforementioned. The dom-
inance effects ðdÞ of the QTL were not unidirectional,
since they displayed positive and negative signs. The
average level of dominance was partial dominance
(ALD = 0.65), which is close to that computed from
the variance components ( �d ¼ 0:55), and it was within
the confidence interval of the latter. In module, the
additive effects were greater than the dominance
effects of the QTL, showing that the additive effects
were more important than the dominance effects for
the expression of the stay-green trait. Six QTL
presented overdominance, but since true overdomi-
nance is not expected, this might be due to repulsion-
phase linkages of sets of QTL with dominance and/or
partial dominance effects mimicking overdominance
(Lu et al. 2003). The average level of dominance
reported in other studies varied from partial domi-
nance (Beavis et al. 1994; ALD = 0.77) to overdom-
inance (Camara 2006; ALD = 1.69 and ALD = 1.88).
Zheng et al. (2009) and Wang et al. (2012) did not
report the ALD values. Our result agreed with that
reported by Beavis et al. (1994), but did not agree with
those reported by Camara (2006). Results from other
types of study have also indicated that the additive
effects are more likely to be important than the
dominance effects for the stay-green trait. For
instance, Guei and Wasson (1996) reported that the
additive variance was greater than the dominance
variance in two tropical maize populations, while
Costa et al. (2008) and Lee et al. (2005) have reported
from diallel studies that general combining ability
accounted for the major portion (70 and 90 %) of the
phenotypic variance of the crosses.
Implications for breeding
The results of our study coupled with the vast majority
of previously reported studies (Beavis et al. 1994;
170 Euphytica (2014) 198:163–173
123
Guei and Wasson 1996; Banziger et al. 2000; Lee et al.
2005; Costa et al. 2008) indicate that additive effects
are more important than dominance effects in the
inheritance of the stay-green trait. Since the domi-
nance effects were not unidirectional, it is likely that
both inbreeding depression and heterosis will present
low magnitudes, indicating that heterosis cannot be
exploited in crosses. Also, the heritability coefficients
on a plant-basis presented low magnitudes in both this
study and in the study reported by Guei and Wasson
(1996), showing that the expression of the stay-green
trait is highly dependent on the environmental effects.
These results indicate that, for selection to be effective
in increasing the stay-green level, genotypes (families,
inbreds and hybrids) should be assessed in replicated
experiments across locations to increase the heritabil-
ity coefficient on a progeny-mean basis, as computed
in this study, and also reported by Bekavac et al.
(2007) and Camara et al. (2007).
The use of marker-assisted selection (MAS) using
the mapped QTL could be a useful tool to increase the
stay-green level of inbreds and their hybrids. However,
the high proportion of the mapped QTL that interacted
significantly with location (&53 %) could impose
additional challenges for MAS. Two approaches have
been suggested through which the problems posed to
MAS from QTL by environment interaction
(QTL 9 E) can be circumvented: (i) partition the
environments into subsets with either low or non-
crossover genotype by environment interaction
(G 9 E), and conduct MAS only with the QTL mapped
in each one of these subsets, or (ii) use only QTL which
are stable across all environments (Moreau et al. 2004;
Lima et al. 2006). However, for maize breeding
programs, environment partition is carried out for grain
yield, not for traits such as stay-green. Although the
second approach could be deemed more appealing it
cannot be as effective since any QTL that interacts with
the environment will not be used. We suggest the joint
use of both approaches, i.e., MAS using the QTL that
are stable across all environments plus those QTL
mapped in each subset of environments partitioned for
grain yield. The number of QTL used for MAS will then
be larger than the number of stable QTL, which will
increase the effectiveness of the MAS. The QTL with
both high additive effects and high R2G could be
transferred by marker-assisted backcross selection,
pyramiding these QTL in elite inbreds, which would
have enhanced levels of stay-green. This procedure,
i.e., marker-assisted backcross selection has been
successfully used in maize for grain yield, as well as
in other crops for other traits (Stuber and Sisco 1992;
Toojinda et al. 1998; Benchimol et al. 2005; Neereja
et al. 2007; Garzon et al. 2008). In our study, eight
QTL were stable across the locations, six out of these
eight QTL had favorable alleles in the parental inbred
L-08-05F and, therefore, this inbred line is an impor-
tant source of QTL that could be used to increase the
level of stay-green in tropical maize inbreds. The fact
that most of the QTL mapped in this study were
clustered on four chromosomes, could facilitate future
research on fine mapping these genomic regions to
clone the QTL underlying this trait.
Concluding remarks
The tropical maize growing areas of the world are
prone to moisture deficits because of the irregular
distribution of rainfall during the crop cycle. Specif-
ically in Brazil, the off-season maize crop has
increased steadily over the years and will continue to
increase in the coming years, and therefore, hybrids
with high levels of stay-green should be developed to
supply the increased demand for drought tolerant
cultivars. Thus, this study has contributed to increase
knowledge on the inheritance of the stay-green trait in
tropical maize and its implications for maize breeding.
In addition, procedures using both phenotypic and
molecular markers to implement breeding programs
aimed to develop cultivars with enhanced levels of
stay-green have been suggested.
Acknowledgments This research was supported by the
Brazilian Conselho Nacional de Desenvolvimento Cientıfico e
Tecnologico (CNPq-308499/2006-9 and CNPq-301717/2009-
5), and by the Department of Genetics at the Agriculture College
‘‘Luiz de Queiroz’’/University of Sao Paulo. C. L. Souza Jr. is
recipient of a research fellowship from CNPq. The authors are
grateful to Dr. Anete Pereira de Souza, from the University of
Campinas, for the genetic mapping of the population; and to A.
J. Desiderio, A. S. Oliveira, A. O. Gil, C. R. Segatelli, and A.
Silva for their assistance with the field experiments.
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