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Rice Science, 2011, 18(3): 187−195 Copyright © 2011, China National Rice Research Institute Published by Elsevier BV. All rights reserved
Identification of QTL Affecting Protein and Amino Acid Contents in Rice
ZHONG Ming1, *, WANG Ling-qiang1, *, YUAN De-jun1, LUO Li-jun2, XU Cai-guo1, HE Yu-qing1 (1National Key Laboratory of Crop Genetic Improvement, National Center of Plant Gene Research (Wuhan) and National Center of
Crop Molecular Breeding, Huazhong Agricultural University, Wuhan 430070, China; 2Shanghai Agrobiological Gene Center,
Shanghai 201106, China; *The authors contributed equally to this paper )
Abstract: The phenotypes of protein and amino acid contents were measured in an F9 recombinant inbred line population
derived from a cross between Zhenshan 97B and Delong 208. A total of 48 and 64 QTLs were identified in 2004 and 2005,
respectively. The contribution of each QTL to the phenotypic variation ranged from 4.0% to 43.7%. Most QTLs co-localized,
forming 29 QTL clusters on the chromosomes with three major ones detected in both years, which were mapped on
chromosomes 1, 7 and 9, respectively. The two QTL clusters for amino acid content, qAa1 and qAa7, influenced almost all
the traits with the allele from Zhenshan 97B, and the third QTL cluster for amino acid content, qAa9, increased the lysine
content with the allele from Delong 208. A wide coincidence was found between the QTL detected under this study and the
loci involved in amino acid metabolism pathways in nitrogen assimilation and transport, or protein biosynthesis. The results
would facilitate the identification of candidate genes and could be used in marker-assisted selection for the favorable allele
in rice quality improvement.
Key words: amino acid content; protein content; quantitative trait locus; grain quality; Oryza sativa
As one of the two major food cereals, rice
provides a large proportion of the total nourishment of
the world population (Juliano, 1985). However,
studies on rice chemistry and technology have lagged
behind as compared to those on wheat. Protein is the
second most abundant constituent of milled rice,
following starch. As a staple food, rice is one of the
most important protein sources for people. Attempts
to improve the nutritional value of rice have been
concentrated on protein content and quality. Breeding
efforts have yielded very limited success so far
because of the complex inheritance and the large
effect of environment on protein content (Coffman
and Juliano, 1985).
The recent advances in molecular marker
technology and the development of high-density
molecular marker linkage maps in rice have provided
a powerful tool for elucidating the genetic basis of
quantitatively inherited traits, including most of
important agronomy traits (Tanksley 1993; Harushima
et al, 1998). Many important traits have been genetically
dissected through identification of quantitative trait
loci (QTL) (Anh et al, 1993b; Tan et al, 1999, 2000
and 2001; Fan et al, 2005; Tian et al, 2005). Many
QTL genes have been cloned to date including those
affecting fruit shape, grain shape, heading date and
grain protein content (Joppa et al, 1997; Yano et al,
1997; Yamamoto et al, 1998 and 2000; Ku et al, 1999;
Liu et al, 2002; Lin et al, 2003; Distelfeld et al, 2004;
Fan et al, 2006). In many cases, QTL mapping
positions have a good agreement with the tagged or
cloned genes, indicating that the mapped QTLs are
accurate (Adam, 2006). Therefore, some scientists
suggested that the results of rough QTL mapping or
fine mapping could be applied in breeding immediately
without costly gene cloning (Salvi and Tuberosa,
2005). Such an approach is particularly useful for
traits that are difficult to measure such as protein
content, amino acid content and fat content.
Quite a few chromosomal regions have been
identified to affect protein content in brown rice using
various rice populations (Tan et al, 2001; Yoshida et al,
2002; Wu et al, 2003; Aluko et al, 2004; Hu et al,
2004; Li et al, 2004; Li et al, 2006; Yu et al, 2006),
and only four have been reported in milled rice (Weng
et al, 2006). The likely reason is that the protein
content is low and not as easy to determine in milled
rice. Protein content is usually calculated from Kjedahl Received: 28 November 2010; Accepted: 21 February 2011 Corresponding author: HE Yu-qing (yqhe@mail.hzau.edu.cn)
Rice Science, Vol. 18, No. 3, 2011 188
nitrogen, multiplied by the factor 5.95 (Sotelo et al,
1990), and this method can be used to determine
protein content but not protein quality (i.e. amino acid
content). In fact, there is only one report on QTL
analysis of amino acid content in rice grain to date
(Wang et al, 2008).
In this study, QTLs for 19 traits including protein,
17 amino acids, and total amino acid contents were
investigated simultaneously in a recombinant inbred
line (RIL) population using data from two years. This
study aimed to comprehensively characterize the
genetic basis of protein quality of rice, in order to
facilitate breeding of high-quality rice varieties.
MATERIALS AND METHODS
Rice materials and field arrangements
An RIL population consisting of 188 lines derived
from the cross of two indica varieties, Zhenshan 97B
and Delong 208, were used. Zhenshan 97B is an elite
maternal parent of hybrid Shanyou 63, which is
planted extensively throughout China, and Delong 208
is a local variety from Yunnan Province of Southwest
China with a number of characteristics desirable for
cooked rice quality.
The field experiments were conducted in the rice-
growing seasons of 2004 and 2005 at the experimental
farm of Huazhong Agricultural University, Wuhan,
China. The sowing dates were 25 May in both years.
Ten plants per line were transplanted in a single row
with 16.5 cm between plants and 26.4 cm between
rows. Field management essentially followed normal
agricultural practice with fertilizer applied (per hectare)
as follows: 48.8 kg N, 58.5 kg P and 93.8 kg K as the
basal fertilizer; 86.3 kg N at the tillering stage; 27.6
kg N at the booting stage. The lines were harvested
individually at maturity.
Preparation of milled rice flour
Ten plants in each row were threshed in bulk and
rough rice was air-dried and stored at room temperature
for three months and then stored at 4 ºC. Hulls were
removed from 50 g of rough rice from each line using
a huller (Houston, TX, USA) to yield brown rice. The
embryo and the bran layer were removed from the
brown rice by passing the grains through a miller.
Then the milled rice was further ground into flour
with a Udy Cyclone Sample Mill (Udy Corporation,
Co., USA), passed through a 0.5 mm sieve and stored
at -20 ºC until analysis.
Determination of protein content
Crude protein content was measured using the
Kjeldahl method. The chemical composition was
determined by standard methods (Cunniff, 1995):
Removing moisture by drying in an oven at 105 ºC for
1 h until constant weight; about 0.1 g of sample was
subjected to carbonization with 2 mL of H2SO4 and 1
mL of ddH2O for 12 h, then assimilation at 380 ºC by
an infrared ray digestion equipment (SCP science)
until the digestion solution is limpid. The content of
NH4 in the digestion solution was diluted to 1−10
mg/L. About 5 mL of the dilution was placed into an
auto-sampler cannulation and analyzed using a
segmented continuous flow analyzer (Futura Ⅱ
Alliance). The amount of total N present in each
sample (mg/L) was calculated using a standard sample.
Grain protein content was calculated from the
percentage of total N multiplied by a conversion
factor of 5.95 (Sotelo et al, 1990). The assay for each
line was conducted with three replicates.
Determination of amino acid content
About 100 mg of each sample was hydrolyzed
with 6 mL of 6 mol/L HCl in a sealed air-evacuated
tube at 110 ºC for 22 h. The hydrolysate was diluted to
50 mL, and then 1 mL of the diluted hydrolysate was
transferred to a centrifuge tube and put into a rotary
evaporator to remove HCl and water. The residue was
completely dissolved with vigorous shaking in 1 mL
of 0.02 mol/L HCl, followed by centrifugation at 14 000
r/min for 15 min. About 0.8 mL of supernatant was
put into an auto-sampler bottle and analyzed using an
amino acid auto-analyzer (Model L-8800 Hitachi).
The amount of each amino acid present in the sample
(mg/g) was calculated using a standard sample. The
assay for each line was conducted with three replicates.
Data analysis
The estimation of mean and variance for each
trait was based on the RIL families. The molecular
ZHONG Ming, et al. Identification of QTL Affecting Protein and Amino Acid Contents in Rice 189
linkage map was constructed using Mapmaker/EXP
3.0 (Lincoln et al, 1992). The average of the
measurements for each line in each year was used for
QTL analysis. The means of the traits were used to
identify QTL with QTLMapper 1.6 based on a mixed
linear model approach (Zhu and Weir, 1998). The
likelihood ratio (LR) value corresponding to P=0.005
was used as the threshold for claiming the presence of
putative main QTLs. The significance of QTL effects,
including additive effect, was further tested by
running the sub-menu of the Bayesian test (P<0.005).
The peak points of the LR in the linkage map were
taken as the putative positions of the effects, and
additive effects were taken from the points showing
the largest effect. The relative contribution of a
genetic component was calculated as the proportion of
phenotypic variance explained by that component in
the selected model.
RESULTS
Phenotypic variation in parents and population
Significant phenotypic differences were detected
between the parents using a t-test at the 0.01 probability
level for protein content, 17 amino acid contents and
total amino acid content. Zhenshan 97B had higher
values for protein content, all of the 17 amino acid
contents and total amino acid content than those of
Delong 208 (Table 1). The RIL population showed
transgressive segregation in both directions for all
amino acid contents and total amino acid content. This
might indicate that the protein content and each amino
acid content are quantitative traits, and the positive
alleles could come from either parent.
Correlation analysis
Significantly positive correlations were found
between 2004 and 2005 for the same trait (Table 2).
The correlation of the protein content was the least,
followed by tyrosine, glysine, total amino acid,
threonine, alanine and glutamic acid. The relatively
lower heritability of protein content in milled rice
implied that the heritability of protein content was
more sensitive to environmental change than those of
amino acid contents. Addtionally, significantly
positive correlations were found between all amino
acid contents and protein content.
Linkage map
A linkage map was constructed with 180 SSR
markers, spanning a total of 1 817.2 cM, with an
average interval of 11.8 cM between adjacent markers
(Fig. 1). The marker orders in the map agreed well
with those of Temnykh et al (2000 and 2001).
QTL for protein content
QTLs for protein content (P=0.005) in milled rice
are presented in Table 3. Four QTLs were detected for
protein content in 2004 and 2005, accounting for
Table 1. Means of protein and amino acid contents of milled rice of mapping population in 2004 and 2005. %
2004 2005 Trait
Population range Mean±σ Zhenshan 97B Delong 208 Population range Mean±σ Zhenshan 97B Delong 208Protein 56.90–97.56 78.58±7.62 85.25±2.20 65.62±0.86 43.91–93.29 69.39±10.19 74.29±1.73 65.34±1.90Total amino acid 102.39–161.03 125.95±11.29 135.20±0.87 118.93±0.95 83.92–123.80 104.05±9.35 112.15±1.91 98.09±1.63Lysine 3.54–5.80 4.52±0.40 5.09±0.04 4.28±0.04 3.18–4.48 3.79±0.28 4.38±0.06 3.61±0.06Isoleucine 4.18–6.81 5.23±0.49 6.17±0.13 5.45±0.03 3.31–5.13 4.26±0.40 4.57±0.09 4.02±0.06Leucine 8.71–16.34 11.10±1.14 11.76±0.10 10.51±0.05 6.63–10.90 8.96±0.88 9.85±0.16 8.57±0.17Methionine 1.02–3.55 2.41±0.39 2.26±0.07 2.20±0.03 1.83–2.94 2.37±0.24 2.37±0.04 2.44±0.10Phenylalanine 5.10–9.24 7.14±0.69 8.11±0.06 7.09±0.02 4.53–7.10 5.86±0.57 6.52±0.12 5.50±0.09Threonine 3.68–5.80 4.59±0.38 4.77±0.05 4.30±0.03 3.00–4.52 3.84±0.33 4.17±0.08 3.71±0.05Valine 5.88–9.47 7.39±0.69 8.19±0.16 7.36±0.03 4.69–7.31 6.06±0.55 6.66±0.14 5.82±0.09Aspartic acid 9.22–15.09 11.57±1.07 12.81±0.15 10.73±0.07 7.62–11.29 9.31±0.87 11.02±0.13 8.76±0.13Alanine 5.70–9.23 7.23±0.65 7.61±0.06 6.82±0.05 4.11–7.39 5.74±0.61 6.64±0.11 5.69±0.10Tyrosine 2.92–8.56 5.27±0.80 5.15±0.12 4.38±0.26 3.22–5.35 4.31±0.44 4.17±0.12 4.09±0.33Serine 5.10–9.10 6.44±0.66 6.48±0.05 5.79±0.01 4.05–6.31 5.24±0.47 5.50±0.09 4.83±0.06Glycine 4.54–7.26 5.63±0.51 6.12±0.05 5.33±0.04 3.73–6.03 4.91±0.47 5.25±0.07 4.40±0.07Cystine 2.21–3.86 2.74±0.25 2.87±0.29 2.35±0.08 2.41–3.50 2.94±0.22 1.19±0.77 2.81±0.07Glutamic acid 20.26–32.48 25.57±2.43 27.21±0.24 24.42±0.14 14.98–25.42 20.80±2.14 22.65±0.38 19.47±0.32Histidine 2.55–4.45 3.23±0.36 3.86±0.03 3.47±0.04 2.10–3.19 2.61±0.22 2.80±0.05 2.40±0.05Arginine 8.24–13.80 10.30±1.03 11.00±0.12 9.31±0.20 6.61–10.17 8.40±0.83 9.62±0.11 7.74±0.21Proline 4.37–6.85 5.43±0.51 5.73±0.05 5.13±0.06 3.34–5.48 4.51±0.43 4.80±0.07 4.23±0.07
Rice Science, Vol. 18, No. 3, 2011 190
49.2% and 27.0% of the phenotypic variation in each
year, respectively (Table 3, Fig. 1). Two QTLs, qPr1
and qPr7, were detected in both years. qPr1 is located
at the RM493−RM562 interval on chromosome 1 and
qPr7 at the RM445−RM418 interval. The allele of
qPr1 from Zhenshan 97B decreased the protein
content whereas qPr7 increased the protein content of
milled rice.
QTLs for amino acid content
A total of 48 and 64 QTLs were detected for amino
acid content in 2004 and 2005, respectively (Table 4,
Fig. 1). Most QTLs co-localized, forming 12 QTL
clusters on the chromosomes, and three QTL clusters
were detected in both years. qAa1 located at RM493−
RM562 on chromosome 1, qAa7 located at MRG186−
MRG4499 on chromosome 7, and qAa9 located at
RM328−RM107 on chromosome 9. The Zhenshan
97B alleles of qAa1 and qAa9 decreased the amino
acid content whereas the Zhenshan 97B allele of qAa7
increased the amino acid content of milled rice.
Table 2. Coefficients of pairwise correlations of rice grain protein and amino acid contents in Zhenshan 97B/Delong 208 population between 2004 and 2005 (r0.05=0.2050, r 0.01=0.2673).
Trait Asp Lys Thr Ile Met Val Leu Ala Tyr Phe Ser Gly Cys Glu His Arg Pro Total Protein
Asp 0.436 a Lys 0.934 b 0.453 0.870 c Thr 0.920 0.853 0.490 0.958 0.879 Ile 0.943 0.880 0.926 0.485 0.942 0.844 0.958 Met 0.541 0.514 0.612 0.629 0.446 0.717 0.636 0.759 0.784 Val 0.917 0.844 0.912 0.975 0.667 0.464 0.913 0.816 0.939 0.984 0.757 Leu 0.878 0.826 0.865 0.884 0.551 0.855 0.442 0.949 0.828 0.970 0.978 0.750 0.969 Ala 0.966 0.875 0.928 0.953 0.551 0.922 0.894 0.498 0.901 0.831 0.907 0.899 0.680 0.849 0.906 Tyr 0.441 0.402 0.531 0.562 0.605 0.647 0.422 0.427 0.248 0.771 0.642 0.786 0.783 0.708 0.779 0.783 0.677 Phe 0.912 0.810 0.899 0.937 0.582 0.928 0.747 0.928 0.597 0.472 0.957 0.834 0.977 0.982 0.764 0.971 0.993 0.903 0.797 Ser 0.835 0.735 0.764 0.832 0.578 0.816 0.734 0.835 0.521 0.835 0.471 0.940 0.841 0.976 0.916 0.709 0.895 0.947 0.868 0.800 0.953 Gly 0.978 0.920 0.927 0.953 0.560 0.924 0.887 0.985 0.408 0.915 0.830 0.283 0.823 0.732 0.868 0.867 0.685 0.905 0.886 0.639 0.703 0.888 0.849 Cys 0.682 0.566 0.758 0.724 0.711 0.718 0.663 0.736 0.604 0.680 0.688 0.738 0.366 0.646 0.582 0.738 0.699 0.666 0.733 0.691 0.539 0.842 0.716 0.741 0.718 Glu 0.934 0.781 0.909 0.926 0.580 0.908 0.818 0.955 0.473 0.938 0.894 0.936 0.765 0.532 0.963 0.827 0.980 0.972 0.756 0.961 0.993 0.901 0.785 0.991 0.961 0.887 0.704 His 0.537 0.490 0.638 0.649 0.586 0.666 0.511 0.517 0.725 0.654 0.635 0.523 0.688 0.607 0.320 0.912 0.925 0.935 0.915 0.679 0.908 0.925 0.861 0.737 0.919 0.902 0.831 0.675 0.921 Arg 0.960 0.900 0.900 0.938 0.622 0.936 0.874 0.949 0.505 0.893 0.811 0.968 0.735 0.906 0.513 0.421 0.956 0.874 0.975 0.971 0.770 0.962 0.976 0.899 0.828 0.981 0.950 0.883 0.729 0.976 0.939 Pro 0.935 0.815 0.881 0.898 0.517 0.855 0.854 0.940 0.340 0.851 0.879 0.935 0.771 0.942 0.476 0.909 0.483 0.954 0.856 0.984 0.955 0.768 0.922 0.967 0.934 0.763 0.970 0.956 0.825 0.689 0.973 0.915 0.961 Total 0.962 0.874 0.947 0.976 0.666 0.969 0.888 0.965 0.600 0.950 0.890 0.962 0.773 0.964 0.676 0.955 0.926 0.490 0.969 0.862 0.987 0.981 0.776 0.967 0.990 0.905 0.819 0.993 0.963 0.883 0.730 0.993 0.937 0.991 0.977 Protein 0.792 0.749 0.804 0.783 0.470 0.791 0.754 0.790 0.466 0.784 0.660 0.791 0.559 0.760 0.442 0.816 0.750 0.808 0.207
0.646 0.530 0.659 0.701 0.564 0.726 0.711 0.552 0.522 0.712 0.643 0.720 0.482 0.705 0.643 0.682 0.633 0.687 a The diagonal indicates trait correlation coefficient between two years; b Coefficient in 2004; c Coefficient in 2005.
Table 3. Putative QTLs identified for protein content of milled rice from 2004 and 2005.
QTL Flanking marker a LOD A b Var (%) c
2004 qPr1 RM493–RM562 4.5 -3.77 9.2 qPr2 RM154–RM233A 1.9 2.47 4.0 qPr7 RM445–RM418 7.6 6.31 25.9 qPr8 RM149–RM433 3.5 -3.95 10.1
2005 qPr1 RM493–RM562 4.1 -5.26 9.6 qPr4 RM349–MRG113 2.2 3.85 5.1 qPr7 RM445–RM418 3.0 4.57 7.2 qPr9 RM460–RM257 2.7 -3.85 5.1
a The bold format means the QTL were detected in two years; b Positive values of additive effects indicate the alleles from Zhenshan 97B with increasing effects; c Percentage of variation explained.
ZHONG Ming, et al. Identification of QTL Affecting Protein and Amino Acid Contents in Rice 191
In 2004, the number of QTLs for each amino acid
ranged from 1 to 4, and the phenotypic variance
explained by each QTL ranged from 5.3% (Thr) to
43.7% (Cys). Of the four QTLs identified for lysine
content, the QTLs at the intervals of MRG141−
MRG6383 and RM443−RM297 on chromosome 1
controlled lysine only, whereas the other two QTLs
controlled the content of other amino acids as well.
Most QTLs co-localized, forming 12 QTL clusters on
the chromosomes, with six controlling only one trait,
and the other six controlling multiple traits. The QTL
clusters at the intervals of MRG186−MRG4499 and
RM493−RM562 included 14 and 11 members,
respectively. At most loci, the alleles from Zhenshan
97B increased the amino acid content, which might
explain a high phenotypic value of Zhenshan 97B.
In 2005, the number of QTLs detected for each
trait ranged from 2 to 5, and the phenotypic variance
explained by each QTL ranged from 4.2% (Lys) to
36.1% (Asp). Of four QTLs identified for lysine
content, two at the intervals of MRG2180−RM16 and
RM328−RM107 controlled lysine only, whereas the
others affected the contents of additional amino acids.
Most QTLs co-localized, forming 17 QTL clusters on
the chromosomes with nine affecting only one amino
acid content and eight affecting the contents of
multiple amino acid. The QTL clusters at the intervals
of MRG186−MRG4499 and RM493−RM562 included
Fig. 1. Putative QTL identified for protein and amino acid contents of milled rice. The bold format means the QTLs were detected in both 2004 and 2005, and the normal and italic format mean the QTLs were detected in 2004
and 2005, respectively. Positive values of additive effects indicate the alleles from Zhenshan 97B with increasing effects while negative values indicate the alleles from Delong 208 with increasing effects.
Rice Science, Vol. 18, No. 3, 2011 192
Zhenshan 97B at most loci contributed to an increase
of the amino acid content.
DISCUSSION
The quantity and quality of protein are the main
attributes that determine the nutritional quality of rice
grains. Protein quality is largely specified by the ratio
of essential amino acid content to protein content. The
present study has characterized the genetic basis of
protein content, 17 amino acid contents and total
amino acid content using a mapping population from
the cross between Zhenshan 97B and Delong 208. In
this study, 48 and 64 QTLs were identified in 2004
and 2005, respectively, for the phenotypes of protein,
17 amino acid and total amino acid contents. Most
QTLs co-localized, forming 29 QTL clusters on the
chromosomes, with three major ones detected in both
years and mapped on chromosomes 1, 7 and 9.
Interestingly, the major QTLs for protein and 17
amino acid contents are located in the same genomic
region, so that the chromosomal segment from Zhenshan
97B increases protein content and at the same time
greatly increases the amino acid content. Free amino
Table 4. Putative QTLs identified for amino acid content of milled rice from 2004 and 2005.
Chr-I a Flanking marker b QTL Trait LOD Additive effect c Var (%) d
2004 1-3 MRG141–MRG6383 Lys 4.1 0.12 9.1 1-12* RM493–RM562 qAa1 Asp/Thr/Glu/Gly/
Ala/Val/Leu/Phe/ Arg/Pro/Taa
9.6/5.3/6.6/5.0/ 6.6/8.6/7.3/8.1/ 6.1/6.9/12.3
-0.49/-0.14/-0.96/-0.17/ -0.24/-0.28/-0.50/-0.23/ -0.32/-0.21/-4.97
21.7/11.3/15.3/12.4/ 16.0/18.1/20.7/17.3/ 13.0/18.1/24.2
1-13 RM562–MRG4638 Ser/Ile/Lys 5.2/10.9/7.5 0.24/0.19/0.17 12.9/22.9/17.5 1-14 MRG4638–RM150A Thr/His 2.7/3.8 -0.09/-0.12 5.3/9.7 1-21 RM443–RM297 Lys 3.0 -0.10 6.3 2-1 RM154–RM233A Arg 3.3 0.25 7.5 7-5 MRG7006–MRG186 Leu 2.9 0.39 13.1 7-6* MRG186–MRG4499 qAa7 Asp/Thr/Ser/Glu/Gly/
Ala/Cys/Val/Met/ Ile/Phe/Arg/Pro/Taa
3.3/6.2/4.6/4.0/3.7/ 3.0/3.4/8.4/3.2/ 5.2/3.7/6.4/4.3/7.6
0.28/0.15/0.23/0.82/0.15/ 0.16/0.07/0.28/0.13/ 0.14/0.18/0.36/0.17/3.83
7.2/13.7/12.4/10.8/9.4/ 7.2/7.4/18.7/10.8/ 11.9/10.0/16.4/12.4/14.4
7-7 MRG4499–RM445 His 3.2 0.16 19.6 9-12 RM553–RM201 Glu/Ala/Cys 3.3/3.0/11.2 -0.71/-0.16/-0.16 7.9/6.9/43.7 9-14* RM328–RM107 qAa9 Asp/Thr/Ser/Gly/Val/
Ile/Phe/Lys/Taa 5.6/4.8/3.8/3.4/4.6/ 4.4/4.0/6/8.1
-0.34/-0.12/-0.19/-0.13/-0.18/ -0.11/-0.16/-0.13/-3.70
10.8/8.4/8.5/7.4/7.6/ 8.0/8.0/10.3/13.2
11-5 RM536–RM287 Tyr 3.2 -0.21 10.1 2005
1-8 RM243–RM577 Val/Ile/Arg 6.3/3.4/3.8 0.19/0.10/0.22 15.7/8.0/7.9 1-9 RM577–RM312 Asp/Thr/Glu/Ala/
Leu/Phe/Pro/Taa 4.8/5.3/4.3/1.8/ 4.4/5.2/3.5/5.7
0.26/0.09/0.56/0.12/ 0.26/0.18/0.10/2.75
10.3/9.8/9.4/4.6/ 11.6/12.2/6.8/9.5
1-11 MRG2412–RM493 Gly/Cys/Met/ Tyr/Lys
2.8/3.8/3.5/ 2.2/2.2
-0.14/-0.06/-0.05/ -0.11/-0.07
7.5/8.6/10.7 6.2/4.9
1-12* RM493–RM562 qAa1 Asp/Thr/Ser/Glu/ Ala/Val/Ile/Leu/Phe/ His/Arg/Pro/Taa
15.2/12.4/2.8/12.4/ 6.4/12.2/9.0/9.8/12.8/3.9/13..8/12.2/16.5
-0.48/-0.16/-0.09/-1.00/ -0.22/-0.27/-0.17-0.40/ -0.31/-0.07/-0.41/-0.19/-5.26
36.1/26.6/5.6/30.1/ 16.4/32.0/22.4/28.1/ 33.5/9.8/28.1/25.9/31.7
2-7 RM475–RM183 Thr 6.6 -0.11 11.4 3-7 MRG2180–RM16 Lys 3.2 0.09 8.0 4-5 MRG388B–RM241 Asp/Thr/Cys/
Arg/Pro 4.4/5.4/5.0/ 4.7/6.4
0.23/0.09/0.07/ 0.23/0.13
8.1/9.1/12.5/ 9.0/11.5
4-6 RM241–RM303 Taa 6.1 2.86 10.3 4-7 RM303–RM349 Ser/Gly 6.0/2.8 0.13/0.13 11.4/6.2 4-8 RM349–MRG113 His 2.3 0.05 5.1/5.2 6-2 RM586–MX21 Ser 2.3 -0.09 5.0 6-6 RM584–RM314 Ala 3.4 -0.15 7.8 7-5 MRG7006–MRG186 Gly/Lys/His 4.3/4.9/5.3 0.24/0.16/0.13 21.9/26.6/28.3 7-6* MRG186–MRG4499 qAa7 Asp/Thr/Ser/Glu/Ala/
Cys/Val/Ile/Leu/Tyr/ Phe/Arg/Pro/Taa
7.7/10.1/7.8/10.3/6.6/7.1/9.6/7.7/7.7/4.3/ 10.7/12.3/10.9/14.7
0.31/0.12/0.18/0.91/0.22/ 0.09/0.21/0.15/0.32/0.16/ 0.25/0.37/0.17/4.68
14.6/16.8/20.5/24.6/16.3/19.7/19.8/17.8/18.0/12.4/22.0/23.6/22.3/27.5
9-7 RM105–RM460 Met 3.4 -0.05 10.4 9-14* RM328–RM107 qAa9 Lys 2.0 -0.06 4.2 11-3 RM4B–RM202 Ile 2.3 -0.08 4.5
a Chr-I, The interval (I) on the chromosome (Chr) where QTL located; *, Detected in both years; b Flanking marker means the interval of QTL;c Positive values of additive effects indicate the alleles from Zhenshan 97B with increasing effects whereas negative values indicate the alleles from Delong 208 with increasing effects; d The percentage of the phenotypic variation explained by QTL.
ZHONG Ming, et al. Identification of QTL Affecting Protein and Amino Acid Contents in Rice 193
acid contents were also contributed to the total protein
content in the rice endosperm, but the content of free
amino acid is very low. It is about 0.69% in the brown
rice and 0.1%−0.2% in the milled rice of total protein
(Juliano, 1985; Wang et al, 2008). Our results showed
that both the mapping of protein and amino acids
contents were validated by each other.
Compared with the results of previous studies, it
is likely that qAa1 for protein and amino acid contents
on chromosome 1 detected in our study is the same
locus as the one reported by Aluko et al (2004).
Likewise, qAa7 might be the same as previously
reported locus (Wu et al, 2003; Hu et al, 2004; Wang
et al, 2008). However, the QTL for protein content
located near the Wx locus on chromosome 6 (Tan et al,
2001; Weng et al, 2006; Yu et al, 2006) was not
detected in our study.
Research has shown that cooking and eating
quality is largely controlled by the Wx locus on
chromosome 6 (Tan et al, 1999; Septiningsih et al,
2003; Tian et al, 2005; Fan et al, 2006; Wang et al,
2007), whereas some research suggests that proteins
in rice grains influence cooking properties (Martin and
Fitzgerald, 2002). Wang et al (2007) used the same
population to analyze the genetic basis of the cooking
and eating quality of rice as reflected by 17 traits.
They found that two major clusters, which
corresponded to the Wx and Alk loci on chromosome 6,
controlled the traits. However, in our research, only a
very small effective QTL of serine content in milled
rice is located in the Wx region. With respect to grain
quality improvement, it is clear that grain eating
quality and nutritional quality of hybrid rice can be
independently modified, since the major QTLs for
these two traits are located on different chromosomes.
Wang et al (2001a) identified four significant loci
that accounted for about 46% of the phenotypic
variance of free amino acid (FAA) content in the
endosperm. According to their QTL mapping, one of
these loci on the long arm of chromosome 2 was
coincident with the location of genes encoding a
mono-functional aspartate kinase 2 and a bi-functional
aspartate kinase-homo-serine dehydrogenase-2. They
suggested that an alteration of amino acid and carbon
metabolism led to overproduction and accumulation
of FAA in opaque-2 mutants and that aspartate kinase
2 was a candidate gene for the QTL influencing FAA
content in maize endosperm (Wang et al, 2001b).
They also characterized the mono-functional aspartate
kinase genes in maize and showed that these genes
related to FAA content in the endosperm (Wang et al,
2007). Based on those results, we examined whether
some genes encoding storage proteins or controlling
amino acid biosynthesis, assimilation and transport
were located in QTL regions identified in our study.
According to the BLAST search for all genes known
to encode storage proteins or proteins controlling
amino acid biosynthesis, assimilation or transport,
many of them were located in the QTL regions in our
research (Table 5, Fig 1). A wide coincidence was
Table 5. Coincidence of the loci (genes) involved in amino acid metabolism with the QTL for protein and amino acid profiles.
Chr-I Code Description of the gene function Genomic cloneLocation
(Mb) Marker
Amino acid assimilation and transfer 2-1 Asp AT Aspartate aminotransferase, putative, expressed AC105731 4.90 RM154, RM2420 1-3 CGS1 Oryza sativa cystathionine gamma-synthase (CGS1) mRNA AP004869 5.63 MRG141, RM12671
Amino acid biosynthesis 1-19 Thr synthase Threonine synthase, chloroplast precursor, putative AP003248 29.00 RM297, RM1244 1-19 Glu synthetase Glutamate synthase, chloroplast precursor, putative AP004363 28.40 RM443, RM5625 4-7 Gln synthetase Glutamine synthetase, chloroplast precursor, putative AP004087 33.40 RM349, RM8218 4-7 Shikimate kinase Shikimate kinase, chloroplast precursor, putative AL606649 32.40 RM349, RM17532 3-7 GluA-3 GluA-3 gene for glutelin AC1333982 17.80 RM16, RM2420 1-8 DHDS Oryza sativa dihydrodipicolinate synthase gene AL662952 29.70 RM243, RM3474 7-4 Putative AK Aspartate kinase family protein AP006343 11.87 MRG2224, RM214
Storage protein 1-3 RP5 Prolamin AP004943 5.73 MRG141, RM180 1-3 RP6 Prolamin AP003943 5.72 MRG141, RM180 7-7 LMW globulin Low molecular weight globulin AP004002 6.26 RM445, RM3917 7-7 RA5 Albumin AP003963 6.33 RM445, RM5673 7-7 RA14 Albumin AP004002 6.26 RM445, RM5672 7-7 RAG2(RA17) Albumin AP004002 6.25 RM445, RM3917
Chr-I, The interval (I) on the chromosome (Chr) where QTL located.
Rice Science, Vol. 18, No. 3, 2011 194
found between the QTL detected in our study and the
loci involved in amino acid metabolism pathways for
N assimilation and transport, or protein biosynthesis. For
example, in the interval of seven QTL clusters of our
results, 15 genes including two genes for N
assimilation and transfer, seven genes for amino acid
metabolism, and six genes for protein biosynthesis
were found. There were several genes corresponding
to one QTL. Interestingly, there were lots of genes in
the region of qAa7, such as the gene encoding putative
aspartate kinase, low molecular weight globulin and
albumin. The results might be helpful for gene cloning
by the candidate gene method.
In summary, the results from this study can be
useful to improve nutritional quality of rice grain by
molecular marker-assisted selection. The closely
linked markers that flank the identified QTLs can be
used to aid quality selection in breeding programs.
And the results of the coincidence between the QTL
detected in our study and the loci involved in amino
acid metabolism pathways in N assimilation, transfer,
or protein biosynthesis might be helpful for gene
cloning by the candidate gene method.
ACKNOWLEDGEMENTS
This work was supported by grants from the
National Program on the Development of Basic
Research (Grant No. 2011CB100200), the National
Program of High Technology Development (Grant No.
2010AA101801), the National Program of Plant
Transgenic Breeding (Grant No. 2008ZX08009-003)
and the National Natural Science Foundation of China
(Grant No. 30671114).
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