qtl analysis for flag leaf characteristics and their relationships with yield and yield traits in...

遗传学报 Acta Genetica Sinica, September 2006, 33 (9)：824–832 ISSN 0379-4172

QTL Analysis for Flag Leaf Characteristics and Their Rela-tionships with Yield and Yield Traits in Rice

YUE Bing1, XUE Wei-Ya1, LUO Li-Jun2, XING Yong-Zhong1,①

1. National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan 430070, China;

2. Shanghai Agrobiological Gene Center, Shanghai 201106, China

Abstract: Photosynthesis of carbohydrate is the primary source of grain yield in rice (Oryza sativa L.). It is important to genetically

analyze the morphological and the physiological characteristics of functional leaves, especially flag leaf, in rice improvement. In

this study, a recombinant inbred population derived from a cross between an indica (O. sativa L. ssp. indica) cultivar and a japon-

ica (O. sativa L. ssp. japonica) cultivar was employed to map quantitative traits loci (QTLs) for the morphological (i.e., leaf length,

width, and area) and physiological (i.e., leaf color rating and stay-green) characteristics of flag leaf and their relationships with

yield and yield traits in 2003 and 2004. A total of 17 QTLs for morphological traits (flag leaf length, width, and area), 6 QTLs for

degree of greenness and 14 QTLs for stay-green-related traits (retention-degrees of greenness, relative retention of greenness, and

retention of the green area) were resolved, and 10 QTLs were commonly detected in both the years. Correlation analysis revealed

that flag leaf area increased grain yield by increasing spikelet number per panicle. However, the physiological traits including de-

gree of greenness and stay-green traits were not or negatively correlated to grain yield and yield traits, which may arise from the

negative relation between degree of greenness and flag leaf size and the partial sterility occurred in a fraction of the lines in this

population. The region RM255-RM349 on chromosome 4 controlled the three leaf morphological traits simultaneously and ex-

plained a large part of variation, which was very useful for genetic improvement of grain yield. The region RM422-RM565 on

chromosome 3 was associated with the three stay-green traits simultaneously, and the use of this region in genetic improvement of

grain yield needs to be assessed by constructing near-isogenic lines.

Key words: Oryza sativa L.; QTL mapping; flag leaf size; stage-green; grain yield

Received: 2005-08-11; Accepted: 2005-09-08

This work was supported by the National Program on the Development of Basic Research (No.G1998010204) and the Rockefeller

Foundation.

① Corresponding author. E-mail: [email protected] ; Tel: +86-27-8728 1715, Fax: +86-27-8728 7092

Grain yield is one of the important aims in con-

ventional crop breeding. However, grain yield, as well

as yield components, is an extremely complex trait,

and genetic control of grain yield is realized through

the control of a series of complex biochemical and

physiological processes [1]. Photosynthesis is the pri-

mary source of grain yield in rice (Oryza sativa L.) [2].

The top three leaves on a stem, particularly the flag

leaf, are the primary source of the carbohydrates pro-

duction [3-5]. Some morphological traits, such as size

and shape of the leaves, have been considered to be a

major source of capacity-related traits in cereals [6, 7],

and a number of physiological traits, such as chloro-

phyll content, photosynthesis capacity, and stay-green,

were also considered as important determinants of

grain yield [2, 8]. Previous studies have mainly focused

on few morphological traits, such as the size of leaves

in rice, and the quantitative traits loci (QTLs) for these

traits were co-located with some sink-related traits [9, 10].

Recently, the genetic basis of photosynthesis rate,

chlorophyll content, and stomatal resistance has been

studied in rice [8]. However, the relationships between

these traits and grain yield are still unknown. Although

the contribution of stay-green to maintain high and

stable yield production under drought-prone conditions

has been reported in sorghum [11], the genetic correla-

tion between stay-green and yield has not been de-

tected yet in rice [12,13].

YUE Bing et al.: QTL Analysis for Flag Leaf Characteristics and Their Relationships with Yield and Yield Traits in Rice 825

In this study, QTLs for some morphological and

physiological traits of flag leaf and their relationships

with yield and yield components were analyzed in

rice. The aim of this study was to understand the ge-

netic basis of these traits and their possible role in

genetic improvement of grain yield in rice.

1 Materials and Methods

1. 1 Plant materials and growing conditions

A population consisting of 180 recombinant inbred

lines (RILs at F9/F10 generation) was developed from the

cross between a paddy rice (O. sativa L. ssp. indica) cul-

tivar Zhenshan 97, and an upland rice (O. sativa L. ssp.

japonica) cultivar IRAT109. Zhenshan 97 is the main-

tainer line for a number of elite hybrids widely grown in

China, and IRAT 109 was introduced from Cote d’Ivoire.

The RIL population, together with its parents, was

directly planted in polyvinyl chloride (PVC) pipes with

one plant per pipe in the experimental farm of

Huazhong Agricultural University, Wuhan, China in

the rice-growing season. The pipe was 20 cm in di-

ameter and 1 m in length. The pipes were laid out in

three blocks following a randomized complete block

design with three replicates, two pipes per replicate for

each genotype in May 2003, and one pipe per replicate

for each genotype in May 2004. Each pipe was loaded

with a plastic bag filled with 38 kg of thoroughly

mixed soil that composed of two parts of clay and one

part of river sand, to which 25 g fertilizers (including 4

g each of N, P2O5, and K2O) were added. Three to five

germinated seeds were sown in each pipe and then

thinned to single healthy plant 30 days after sowing. At

the beginning of tillering stage, 1 g of urea (dissolved

in water) was applied to each pipe. Plants were fully

irrigated by watering every day till maturating.

1. 2 Traits and measurements

Three morphological traits, four physiological

traits, and five yield traits were investigated for all

plants that headed within 2 weeks, considering that

these traits are sensitive to environments.

The flag leaf length (FLL, cm) and flag leaf width

(FLW, cm) were measured on the largest two tillers of

all plants at maturing stage. One derived trait, the flag

leaf area (FLA) = FLL × FLW, was calculated. The

degree of greenness (DG) and some stay-green traits

were also investigated for all plants following a

method described by Jiang et al [13]. Using a Minolta

Chlorophyll Meter SPAD-502 (Minolta Camera Co.,

Japan), the degrees of greenness of the flag leaves

from the biggest two tillers were measured on the day

of heading and again after 15 days. To ensure that the

measurements were taken on the right day for the right

tiller, tillers were tagged at the day of heading. The

SPAD readings of the flag leaves measured on the day

of heading were designated DG, and the SPAD values

15 days after heading were used as measurements for

the retention-degrees of greenness, designated RDG.

The ratios of RDG to DG were used as indexes for the

relative retention of greenness, designated RRG. An-

other measurement of stay-green was an independent

visual estimation of the retention of the green-area

(RGA) for leaves 15 days after heading on a 1-5 scale,

where 1 represents complete or nearly complete leaf

death and 5 corresponds to a complete green leaves.

Yield and its component traits were also exam-

ined for all plants, including grain yield per plant (Y,

g), panicle number per plant (PN), number of

spikelets per panicle (SN), 1000-grain-weight (GW,

g), and spikelet fertility (SF, %). Spikelet fertility was

measured as the number of grains divided by the total

number of spikelets of a plant.

1. 3 QTL analysis

The genetic linkage map was constructed using a

total of 245 SSR markers as described previously [14].

The means of each trait were used to identify QTL by

the method of composite interval mapping (CIM) by

using QTL Cartographer 2.0 software [15] with a

threshold of LOD score 2.4 (selected by permutation

test based on 1 000 runs, P=0.05).

2 Results

2. 1 Phenotypic variation of the parents and RILs

The phenotypic differences between parents as

well as the variation in the RIL population are sum-

826 遗传学报 Acta Genetica Sinica Vol.33 No.9 2006

marized in Table 1. Transgressive segregations were

observed in the RIL population for all the traits in-

vestigated. ANOVA revealed that the difference from

from genotypes for these traits was significant,

whereas for the most of the cases the difference from

replicates was not significant (Table 1).

For traits FLL, FLW, and FLA, IRAT109 had

higher values than Zhenshan 97 in both the years, and

the differences of FLA between the parents in both

the years and FLW in 2004 were significant. However,

the values of DG and RDG of Zhenshan 97 were sig-

nificantly higher than that of IRAT109 in 2003. For

other traits, the difference between two parents was

not significant in both the years.

When data collected from the two years were

compared, the mean values of RILs for traits RDG,

RRG, and RGA were higher in 2003 than in 2004

(Table 1). This was caused by high temperature at

flowering stage in 2003 resulting in reduction of seed

setting rate.

2. 2 Correlations of the traits

The correlations among the flag leaf characteristics

are shown in Table 2. Three traits related to flag leaf

area (FLL, FLW, and FLA) were highly intercorrelated,

and so were the three stay-green-related traits, RDG,

RRG, and RGA. Strong correlations were also de-

tected between DG and RDG in both the years. Nega-

tive or small correlations were identified between flag

leaf area and stay-green-related traits.

Table 1 Measurements and ANOVA of the traits relative to flag leaf in the RIL population and the parents in 2003 and 2004

ANOVA significant c) Traitsa) Zhenshan 97 IRAT109 Mean of RILs Range of RILs

Genotype Replication

FLL 25.7/27.2b) 28.8/29.7 28.8/28.1 (16.2-50.2)/(18.7-43.0) **/** Ns/Ns

FLW 1.3/1.4 1.4/1.5** 1.5/1.4 (1.0-2.2)/(0.9-3.8) **/** Ns/Ns

FLA 33.4/38.1 40.3*/44.6* 41.9/40.7 (19.0-108.7)/(17.1-97.7) **/** Ns/Ns

DG 39.8*/40.5 36.8/39.4 39.5/40.2 (29.2-48.1)/(30.3-51.1) **/** **/Ns

RDG 33.8*/30.2 30.4/28.7 31.2/23.0 (17.2-43.9)/(10.7-35.4) **/** **/Ns

RRG 82.2/70.2 82.7/71.7 78.9/56.4 (51.1-98.4)/(29.8-75.0) **/** */Ns

RGA 2.6/2.6 2.7/2.8 2.6/2.4 (1.0-4.7)/(1.0-3.6) **/** **/Ns

a) FLL: flag leaf length; FLW: flag leaf width; FLA: flag leaf area; DG: degree of greenness; RDG: retention-degrees of green-

ness; RRG: relative retention of greenness; RGA: retention of the green area; b) The data on the left- and right-side of slash in each cell were the results obtained in 2003 and 2004, respectively. Data following

the marks * or ** are significantly higher than the other parent at the 0.05 and 0.01 probability levels based on t-test; c) “*”, “**”, and “Ns” represent significant at P<0.05, P<0.01 level and no significant, respectively.

Table 2 Coefficients of pairwise correlations of the traits related to flag leaf investigated in 2003 and 2004

Traits a) FLL FLW FLA DG RDG RRG

FLW 0.42/0.22 b)

FLA 0.87/0.76 0.80/0.80

DG -0.36/-0.54 -0.43/-0.43 -0.43/-0.61

RDG -0.40/-0.19 -0.30/-0.13 -0.39/-0.19 0.59/0.60

RRG -0.27/0.02 -0.07/0.08 -0.20/0.07 0.02/0.16 0.82/0.86

RGA -0.21/0.21 -0.06/0.16 -0.16/0.20 0.05/0.00 0.72/0.66 0.86/0.86

See the footnote a), b) of Table 1 for explanation, the values in bold face are significantly at P<0.05.


Correlations between yield, yield components,

and the traits related to flag leaf characteristics are

given in Table 3. In general, potential yield and SN

were positively correlated with FLL, FLW, and FLA,

and negatively correlated with DG, RDG, RRG, and

RGA in both the years. Furthermore, the differences

were significant in at least one year. PN and GW had

small or negative correlation with the traits related to

flag leaf characters. It was interesting to note that

stay-green traits were significantly and negatively

correlated with SF in 2003, but they were positively

associated with SF in 2004.

2. 3 QTL mapping

Seven QTLs were resolved for flag leaf length in

the two years; only one was detected in both the years,

and individual QTL explained 5.3%–21.7% of phe-

notypic variation (Table 4). Four QTLs for flag leaf

width were identified in 2003 and 2004 with individ-

ual QTL explained 4.4%–35.8% of phenotypic varia-

tion. However, only QFlw4 was detected in both

years and had the largest additive effects. Alleles

from IRAT109 at eight of the QTLs (72.7%) for FLL

and FLW had positive effects, which was also coin-

cided to the performance of both the parents for these

traits. Six QTLs for FLA were detected, two of them

were identified in both the years, and individual QTL

explained 4.7%–26.8% of phenotypic variation.

For the trait of DG, six QTLs were resolved in

2003 and 2004; two of them were detected in both the

years, and individual QTL explained 4.5%–28.1% of

phenotypic variation. Six QTLs for RDG were identi-

fied in 2003 and 2004 with individual QTL explained

6.8%–19.5% of phenotypic variation, and two of

them were detected in both the years. Five QTLs for

RGA were detected, only one of them was common

in both the years, and individual QTL explained

10.0%–14.2% of phenotypic variation. For the trait of

RRG, three QTLs were identified, whereas only one

of them was detected in both the years. Individual

QTL explained 7.9%–23.8% of phenotypic variation.

In summary, a total of 17 QTL were resolved for

the flag leaf size related traits (i.e., FLL, FLW, and

FLA) including four commonly detected in both the

years and 13 observed in one year. The region

RM255-RM349 on chromosome 4 controlled the three

traits simultaneously and detected in both years. For

the stay-green-related traits (i.e., RDG, RGA, and

RRG), 14 QTLs were resolved including four detected

in both years and 10 identified only in one year. The

region RM422-RM565 on chromosome 3 controlled

the three traits simultaneously (Table 4, Fig. 1).

2. 4 Congruence of QTL

There were three regions congregated more than

three QTLs and eight regions clustered two QTLs.

For examples, the region RM422-RM565 on chro-

mosome 3 clustered QTLs for the three stay-green

traits, and the region RM255-RM349 on chromosome

4 overlapped the QTLs for FLL, FLW, FLA, and

RGA (Fig. 1). Among them, five regions were associ-

ated with FLL, FLW, or FLA simultaneously, four

Table 3 Coefficients of pairwise correlations between yield related traits and other traits investigated in 2003 and 2004

Traits a) Y PN SN SF GW

FLL 0.41/0.31 b) -0.14/-0.03 0.54/0.51 0.09/-0.13 0.03/-0.21

FLW 0.30/0.10 -0.26/0.01 0.44/0.18 0.13/-0.13 0.13/0.16

FLA 0.43/0.26 -0.22/-0.02 0.60/0.44 0.11/-0.16 0.07/-0.03

DG -0.22/-0.26 -0.08/-0.14 -0.14/-0.35 -0.03/0.18 -0.11/0.17

RDG -0.36/-0.16 -0.11/-0.23 -0.21/-0.07 -0.16/0.15 -0.08/-0.01

RRG -0.31/-0.06 -0.08/-0.19 -0.19/0.06 -0.18/0.10 -0.02/-0.04

RGA -0.37/-0.02 -0.08/-0.23 -0.13/0.16 -0.31/0.08 -0.10/-0.08

See the footnote a),b) of Table 1 for explanation, the values in bold face are significantly at P<0.05. Y: yield; PN: panicle number

per plant; SN: spikelet number per panicle; SF: spikelet fertility; GW: 1000 grain weight.


regions clustered stay-green traits, three regions over-

lapped with the QTL for DG and RDG. These results coin-

cide with the correlations among these traits (Table 2).

3 Discussion

Grain yield was positively and strongly correlated

with FLL and FLA in the present study, and the correla-

tions between flag leaf characteristics and yield compo-

nents revealed that large leaf length, leaf width, and leaf

area contributed to increased spikelet number per pani-

cle. Li et al. [9] concluded that leaf area was positively

related to grain yield, and QTL-influencing-related

Table 4 QTL for the traits related to flag leaf resolved using composite interval mapping in the RIL population of Zhen-

shan 97/IRAT109

2003 2004 Traits

Chra QTL Intervalb LOD Addc Var%d Chra QTL Intervalb LOD Addc Var%d

FLL 3 QFll3 RM523-RM231 4.0 -1.72 7.69 2 QFll2 RM262-MRG0303 5.5 2.52 19.69

4 QFll4 RM255-RM349 3.7 1.74 7.75 4 QFll4 RM255-RM349 3.0 1.93 11.98

5 QFll5 RM480-RM334 2.5 1.53 5.32 6 QFll6 RM588-RM589 6.2 2.89 21.68

7 QFll7 RM274-RM480 4.9 1.80 8.41

10 QFll10 RM596-RM271 3.1 -1.57 5.95

FLW 4 QFlw4 RM255-RM349 20.5 0.15 35.81 4 QFlw4 RM255-RM349 3.9 0.14 16.50

5 QFlw4 RM421-RM274 7.9 0.09 13.40 5 QFlw5 RM274-RM480 3.1 0.11 10.08

6 QFlw6 RM539-RM527 3.3 -0.05 4.41

FLA 3 QFla3 RM523-RM231 5.9 -4.65 10.60 2 QFla2 RM262-MRG0303 3.0 4.51 10.47

4 Qfla4 RM255-RM349 12.8 7.45 26.83 4 QFla4 RM255-RM349 5.2 5.92 17.68

5 QFla5 RM274-RM480 4.1 4.43 9.22 6 QFla6 RM111-RM276 3.6 -5.70 11.80

6 Qfla6 RM111-RM276 2.5 -3.11 4.66

10 QFla10 RM596-RM271 3.2 -3.45 5.68

DG 1 QDg1 RM302-RM472 5.8 -1.29 12.86 2 QDg2 RM29-RM341 3.0 -1.46 8.25

2 QDg2 RM29-RM341 8.9 -1.49 16.45 4 QDg4b MRG4503-RM255 6.9 -2.33 18.92

4 QDg4a RM471-RM142 3.6 0.94 6.66 9 QDg9 RM434-RM257 5.6 2.04 16.68

4 QDg4b MRG4503-RM255 14.1 -1.92 28.09

5 QDg5 RM161-RM421 3.0 0.77 4.46

RDG 1 QRdg1 RM302-RM472 2.5 -1.37 7.24 2 QRdg2 RM29-RM341 4.0 -2.53 19.51

3 QRdg3 RM422-RM565 5.4 1.88 13.60 3 QRdg3 RM422-RM565 3.1 1.94 11.12

4 QRdg4 MRG4503-RM255 4.1 -1.49 8.58 9 QRdg9 RM215-RM245 4.2 2.09 13.28

8 QRdg8 RM350-RM284 2.4 -1.34 6.76

9 QRdg9 RM215-RM245 2.5 1.16 5.15

RGA 3 Qrga3 RM422-RM565 5.4 0.29 13.18 2 Qrga2 MRG2762-RM526 2.9 -0.23 10.80

7 Qrga7 RM295-RM481 2.9 0.25 10.44 4 Qrga4 MRG4503-RM255 3.0 0.24 11.68

8 Qrga8 RM350-RM284 6.3 -0.35 14.24 8 Qrga8 RM350-RM284 2.7 -0.22 9.96

RRG 2 QRrg2b RM497-RM240 2.7 3.06 7.92 2 QRrg2a MRG2762-RM526 4.3 -5.74 23.79

3 QRrg3 RM422-RM565 4.9 4.23 14.91 3 QRrg3 RM422-RM565 2.5 3.49 9.76

a,b Chromosome number and marker intervals, the bold format means the QTLs were detected in two years; c Additive effects, the positive values of additive effects indicate the alleles from IRAT109 with increasing effects; d Phenotype variation rate explained by detected QTLs.


Fig. 1 Chromosomal locations of the QTLs for the flag leaf related traits

The QTLs for all traits are shown on the left of the chromosomes. The QTLs in bold were detected in both years. The italic QTLs

indicate that the alleles for increasing trait values were from Zhenshan 97. Distances are given in Kosambi centiMorgans.


source-sink traits were mapped to similar genomic

locations and showed consistent gene actions. There-

fore it is possible to improve grain yield by genetic

improvement of FLL, FLW, and FLA with the aid of

using molecular markers. Comparison with the QTL

detected in another population with one common

parent, Zhenshan 97, the QTL for FLA (QFla6) on

chromosome 6 in the present study corresponded to

the QTL for flag leaf area reported by Cui et al [10].

Moreover, the region RM255-RM349 on chromo-

some 4 was responsible for the three leaf morpho-

logical traits simultaneously and was detected in both

years with large additive effects. This region is poten-

tial for genetic improvement of grain yield, and its

contribution to grain yield could be assessed in field

tests using near-isogenic lines.

High chlorophyll content and delaying senes-

cence of the leaves have been considered to be a fa-

vorable characteristic in crop production [2,8,11].

However, degree of greenness (corresponding to leaf

chlorophyll content) and stay-green traits had no cor-

relation or negatively associated with potential yield

and yield components in this study. Negative correla-

tion between degree of greenness and grain yield can

be explained by the fact that degree of greenness was

significantly and negatively associated with flag leaf

size (Table 2), which was positively correlated with

yield and yield parameters. The lack of correlation

between stay-green and yield was also found in maize

and rice [13, 16]. A possible explanation for the lack of,

or negative, correlation between stay-green traits and

grain yield is that the experimental population was

derived from an inter-subspecific cross and the partial

sterility occurred in a fraction of the lines. Partial ste-

rility would result in less portion of nutrient transport

from leaves to the developing seeds, which causes

lower seed-setting rate accompanied by greener

leaves with higher chlorophyll content. In addition,

the extremely high temperature (above 38℃ for 1

week) at reproductive stage in 2003 resulted in higher

degree of spikelet fertility (data not shown); and the

correlations between spikelet fertility and the physio-

logical traits were negative in 2003 but slightly posi-

tive in 2004 (Table 3). This result also explained that

partial sterility affected the correlation between grain

yield and stay-green traits. Cha et al. [12] identified a

stay-green gene (sgr) on chromosome 9 correspond-

ing to the QTL for retention of degree of greenness

(QRdg9) in this study, which delays the progress of

yellowing but not functionally keeping the photosyn-

thetic capability. This kind of genes may also have

partly contribution to the negative correlation be-

tween grain yield and stay-green as observed in this

population.

It is widely believed that yield gains are most

likely to be achieved by simultaneously increasing

both source (photosynthetic rate) and sink (partition-

ing to grain) strengths. Flag leaf area is an important

factor which determines yield potential through af-

fecting photosynthetic rate. Thus, it is very reason-

able that flag leaf area is highly associated with yield

and yield traits in this study. While partial sterility of

some lines in the population could limit the transpor-

tation of assimilates from stem and leaves to grain.

This case could be a noise to discover the real rela-

tionship between leaf stay-green duration and yield.

After removal of the partial sterility lines, the correla-

tion (data not shown) between flag leaf traits and

yield traits is reanalyzed, and the relationship keeps

highly similar. At the QTL mapping level, some

QTLs for flag leaf area are located to the similar re-

gions where QTL for yield and yield traits are de-

tected, whereas no QTL for stay-green are located in

the yield QTL regions (data not shown). This situa-

tion also supports the relationships between flag leaf

associated traits and yield traits in this study.

Some of the QTLs for stay-green detected in the

present study appear to match the stay-green QTLs ob-

tained from other populations. These include the genomic

regions RM29-RM341 and RM497-RM240 on chromo-

some 2, and RM293-RM571 on chromosome 3 [13, 17].

The use of the stay-green traits to delay leaf senescence as

a means to increase crop production has remained an at-

tractive strategy. These common stay-green QTLs and the

QTL region (RM422-RM565 on chromosome 3 control-

ling the three stay-green traits may be used as targets for


construction near isogenic lines, and the contribution of

QTLs and domains to grain yield necessitates to be as-

sessed in field conditions.

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水稻剑叶部分形态生理特性 QTL分析以及它们与产量、产量

性状的关系

岳兵 1，薛为亚 1，罗利军 2，邢永忠 1

1. 华中农业大学作物遗传改良国家重点实验室，武汉 430070；

2. 上海市农业基因中心，上海 201106

摘要：光合产物是水稻产量的主要来源，因此对水稻后期功能叶片尤其是剑叶形态生理性状的遗传分析对水稻高产育种

很重要。利用来源于籼/粳交后代的重组自交系群体为材料对水稻剑叶形态（叶片长、宽、面积）和生理性状（叶绿度、持

绿性）进行了 QTL定位，并对这些性状与产量、产量性状的相关性进行了分析。两年分别定位了 17、6和 14个与剑叶形

态性状、叶绿度和持绿性有关的 QTL，其中 10个 QTL在两年中共同检测到。相关分析表明，较大的剑叶可以增加穗粒数

并显著增加产量，然而叶绿度和持绿性与产量、产量性状无关或呈显著负相关。叶绿度与剑叶大小呈显著负相关以及籼/

粳交群体后代半不育是叶绿度和持绿性与产量、产量性状无关或呈显著负相关的可能原因。染色体 4 上的 RM255-RM349

区域同时控制 3 个剑叶形态性状并且解释的变异也较大，该区域可用于遗传改良以提高水稻产量。染色体 3 上的

RM422-RM565区域重叠了 3个与持绿性有关的 QTL，它们对产量的贡献有待于通过构建近等基因系进行深入研究。

关键词：水稻；QTL定位；剑叶大小；持绿性；产量

作者简介：岳兵，男（1972-），博士，研究方向：水稻分子遗传，现工作单位：湖北省农业科学研究院粮食作物研究所。

E-mail: [email protected]

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