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ORIGINAL PAPER
Identification of QTLs associated with tissue culture responsethrough sequencing-based genotyping of RILs derivedfrom 93-11 3 Nipponbare in rice (Oryza sativa)
Sujuan Li • Song Yan • A-hong Wang •
Guihua Zou • Xuehui Huang • Bin Han •
Qian Qian • Yuezhi Tao
Received: 19 June 2012 / Revised: 21 August 2012 / Accepted: 11 September 2012
� Springer-Verlag 2012
Abstract
Key message The performance of callus induction and
callus differentiation was evaluated by 9 indices for 140
RILs; 2 major QTLs associated with plant regeneration
were identified.
Abstract In order to investigate the genetic mechanisms
of tissue culture response, 140 recombinant inbred lines
(RILs) derived from 93-11 (Oryza sativa ssp.
indica) 9 Nipponbare (Oryza sativa ssp. japonica) and a
high quality genetic map based on the SNPs generated
from deep sequencing of the RIL genomes, were used to
identify the quantitative trait loci (QTLs) associated with
in vitro tissue culture response (TCR) from mature seed in
rice. The performance of callus induction was evaluated by
indices of induced-callus color (ICC), induced-callus size
(ICS), induced-callus friability (ICF) and callus induction
rate (CIR), respectively, and the performance of callus
differentiation was evaluated by indices of callus prolifer-
ation ability (CPA), callus browning tendency (CBT),
callus greening ability (CGA), the average number of
regenerated shoots per callus (NRS) and regeneration rate
(%, RR), respectively. A total of 25 QTLs, 2 each for ICC,
ICS, ICF, CIR and CBA, 3 for CPA, 4 each for CGA, NRS
and RR, respectively, were detected and located on 8 rice
chromosomes. Significant correlations were observed
among the traits of CGA, NRS and RR, and QTLs iden-
tified for these three indices were co-located on chromo-
somes 3 and 7, and the additive effects came from both
Nipponbare and 93-11, respectively. The results obtained
from this study provide guidance for further fine mapping
and gene cloning of the major QTL of TCR and the
knowledge of the genes underlying the traits investigated
would be very helpful for revealing the molecular bases of
tissue culture response.Communicated by P. Ozias-Akins.
Electronic supplementary material The online version of thisarticle (doi:10.1007/s00299-012-1345-6) contains supplementarymaterial, which is available to authorized users.
S. Li � Q. Qian
The College of Agriculture and Biotechnology, Zhejiang
University, 388 Yuhangtang Road, Hangzhou 310058, China
e-mail: [email protected]
S. Li � S. Yan � G. Zou � Y. Tao (&)
State Key Laboratory Breeding Base for Zhejiang Sustainable
Pest and Disease Control, The Institute of Crop and Nuclear
Technology Utilization, Zhejiang Academy of Agricultural
Sciences, 198 Shiqiao Road, Hangzhou 310021, China
e-mail: [email protected]
S. Yan
e-mail: [email protected]
G. Zou
e-mail: [email protected]
A.-hong Wang � X. Huang � B. Han
National Centre for Gene Research, Chinese Academy
of Sciences, 500 Caobao Road, Shanghai 200233, China
e-mail: [email protected]
X. Huang
e-mail: [email protected]
B. Han
e-mail: [email protected]
Q. Qian (&)
State Key Lab of Rice Biology, China National Rice Research
Institute, Chinese Academy of Agricultural Sciences,
359 Tiyuchang Road, Hangzhou 310006, China
e-mail: [email protected]
123
Plant Cell Rep
DOI 10.1007/s00299-012-1345-6
Keywords Rice � QTL mapping � RIL � SNPs �Tissue culture response
Abbreviations
ICC Induced-callus color
ICS Induced-callus size
ICF Induced-callus friability
CIR Callus induction rate
CPA Callus proliferation ability
CBT Callus browning tendency
CGA Callus greening ability
NRS The average number of regenerated shoots per
callus
RR Regeneration rate (%)
Introduction
Understanding the genetic basis of tissue culture response
(TCR) has great importance for many aspects of funda-
mental studies and genetic improvements in plants since
tissue culture and genetic transformation are not only the
basic procedures currently employed in plant biotechnol-
ogy research, but also the prerequisites for the practical use
of genetic engineering (Lee et al. 2002; Rao et al. 2009;
Zhao et al. 2009). Numerous transformation methods have
been developed and Agrobacterium-mediated transforma-
tion has become one of the most widely applied methods in
plants, particularly for many dicot species. In the case of
rice, transformation has been satisfactorily realized in
various cultivars of japonica rice after the establishment of
a high efficiency Agrobacterium-mediated transformation
system (Hiei et al. 1994; Yang et al. 1999; Lee et al. 2002;
Bajaj and Mohanty 2005; Toki et al. 2006; Nishimura et al.
2007; Hiei and Komari 2008), but only a few successes
have been reported in indica rice (Aldemita and Hodges
1996; Rashid et al. 1996; Nayak et al. 1997; Zhang et al.
1997; Khanna and Raina 1999, 2002; Mohanty et al. 2002;
Kumar et al. 2005; Lin and Zhang 2005; Saika and Toki
2010).
Establishment of a highly efficient transformation sys-
tem is limited by a number of factors. The availability of
efficient embryogenic cultures has proved to be the prin-
cipal element because the regeneration of transgenic plants
relies on the formation of somatic embryos in many
important crops (Rao et al. 2009). Low regeneration ability
of somatic embryos has always been considered as the
main constraint for poor transformation efficiency.
Recently, a great effort has been made to improve the
medium ingredients and transformation procedures in cal-
lus of indica rice (Lee et al. 2002; Lin and Zhang 2005; Ge
et al. 2006; Zaidi et al. 2006). A highly efficient system for
Agrobacterium-mediated transformation was established
for indica rice based on two new media for callus sub-
culture and differentiation, and the two major steps in the
tissue culture process (Lin and Zhang 2005). But positive
effects of the media were subsequently proved to be limited
to some genotypes and not generally applicable across a
wide range of indica rice (Ge et al. 2006; Zaidi et al. 2006).
The donor genotype is, therefore, still confirmed as the
most important factor influencing the plant tissue culture
ability since no culture conditions have been reported
suitable for all genotypes (Bolibok and Rakoczy-Tro-
janowska 2006; Ge et al. 2006). Recently, callus micro-
array analysis of transient and stable transformation after
Agrobacterium-mediated infection showed that some
genes, which may be essential for the transformation pro-
cess, were down-regulated in the indica cultivar Zhenshan
97, a cultivar which is very difficult to realize transfor-
mation (Tie et al. 2012).
Many studies have provided evidence that genetic con-
trol of plant regeneration ability can be either qualitative
(Reisch and Bingham 1980) or quantitative (Zhang and
Hattori 1998; Schiantarelli et al. 2001; Taguchi-Shiobara
et al. 2006). Using quantitative trait loci (QTL) mapping
technology, it has become possible to estimate the number
of loci controlling genetic variation of complex traits and
map their location on the genome (Paterson 1995; Price
2006). The QTL analysis for TCR traits has been reported
on maize (Armstrong et al. 1992; Wan et al. 1992; Mu-
rigneux et al. 1994), barley (Komatsuda et al. 1993; Mano
et al. 1996; Manninen 2000; Bregitzer and Campbell 2001;
Mano and Komatsuda 2002), wheat (Ben Amer et al. 1997;
Torp et al. 2001; Jia et al. 2007), rye (Grosse et al. 1996;
Bolibok et al. 2007), triticale (Gonzalez et al. 2005) and
rice (Taguchi-Shiobara et al. 1997a, 2006; Takeuchi et al.
2000; Kwon et al. 2000; Nishimura et al. 2005; Zhao et al.
2009).
In the past decades, various traditional molecular
markers were extensively applied to detect the genes or
QTL controlling the tissue culturability, such as restriction
fragment length polymorphisms (RFLPs) (Taguchi-Shio-
bara et al. 1997a, 2006), amplified fragment length poly-
morphism (AFLP) (Kwon et al. 2000) and simple sequence
repeat (SSR) (Zhao et al. 2009). The development of the
next-generation sequencing technology (NGST) has pro-
vided a powerful high-throughput genotyping approach and
has been implemented for crop genetics and breeding
(Ansorge 2009; Varshney et al. 2009; Delseny et al. 2010).
A high density genetic map based on recombination bins
defined by SNPs (single nucleotide polymorphisms)
detected from re-sequencing of the entire population with
150 recombination inbred lines (RILs) derived from a cross
between 93-11 and Nipponbare (the two indica and
japonica rice reference genomes), was generated and used
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for QTL mapping and gene discovery (Huang et al. 2009;
Wang et al. 2010). Similar re-sequencing studies were also
conducted for a population with 128 CSSLs (chromosome
segment substitution lines) from 93-11 9 Nipponbare of
rice (Xu et al. 2010) and 241 RILs derived from the cross
between two elite rice lines of indica subspecies, Zhenshan
97 and Minghui 63 (Yu et al. 2011). These studies have
testified that SNP maps hold the huge advantage of an
ultra-high quality and ultra-high density physical map in
comparison to QTL mapping based on RFLPs/SSRs, and
would not only contribute to gene discovery involved in
various complex traits on the whole-genome scale but also
promote the development of superior rice varieties.
Since Nipponbare, a representative of the typical easily
transformed japonica rice genotype, has shown very dif-
ferent tissue culture response from 93-11, which has been
reported as one of the indica rice genotypes difficult for
transformation, the population derived from these two lines
was predicted to be an ideal segregating population for
evaluating and mapping the traits associated with tissue
culture response. Also, the establishment of the high den-
sity genetic map would facilitate to identify QTLs associ-
ated with tissue culture response in rice.
Materials and methods
Plant materials and linkage map construction
The population consisting of 150 F11 recombinant inbred
lines (RILs) was developed from a cross between Oryza
sativa ssp. indica cv. 93-11 and ssp. japonica cv. Nip-
ponbare followed by self-fertilization at Hangzhou and
Hainan, respectively, in China. By using a high-throughput
genotyping method, whole-genome re-sequencing for 150
RILs and their parents was carried out, large numbers of
polymorphic SNP markers were generated, recombination
maps for each line were obtained, and a linkage map based
on the recombination bins was then constructed through
aligning the recombination map of the whole population
with the minimum bin length of 100 kb, as previously
reported (Huang et al. 2009). A total of 140 F14:15 RILs
among this population and the sequencing-based genetic
map were used for QTL mapping associated with tissue
culture ability in this study. The tissue culture performance
of two parents and their hybrid F1 was also tested.
Culture procedures
Callus induction
Mature healthy dehusked seeds of RILs, two parents and
their F1 were sterilized by immersion in 70 % ethanol for
30 s, followed by 0.1 % (w/v) mercuric chloride solution
for 10 min with shaking, and rinsed five times with sterile
water. NBm medium, a modified Nippon Barre medium
with N6 macronutrient components (Chu et al. 1975),
B5 micronutrient components and organic components
(Gamborg et al. 1968), supplemented with 2.5 mg/l of
2,4-D, 0.3 g/l of casein hydrolysate (CH), 0.5 g/l of gluta-
mine, 2.8 g/l of proline, 30 g/l of sucrose, was used for the
induction of embryogenic calluses. The pH of the medium
was adjusted to 5.8, and 3.6 g/l Phytagel was added before
autoclaving. About 60 seeds of each line, with even dis-
tribution between 3 dishes, were placed on the induction
medium and incubated for 15 days at 28 �C under 16 h
light/8 h darkness.
Callus differentiation and plant regeneration
After 15 days on callus induction medium, the scutellum-
derived calluses were transferred onto the regeneration
medium, the NBm medium supplemented with 0.3 g/l of
casein hydrolysate (CH), 0.5 g/l of glutamine, 0.5 g/l of
proline, 3 mg/l 6-BA, 0.5 mg/l NAA and 30 g/l of sucrose.
The medium was also adjusted to pH 5.8 and solidified by
adding 7 g/l agar before autoclaving. Three to five plant
tissue culture bottles, containing six calluses each, were
used for regeneration culture for each line. The regenera-
tion culture was performed in the light (16 h light/8 h dark)
at 28 ± 2 �C for 40 days.
The performance of callus induction from seed, callus
differentiation and plant regeneration was evaluated for
both parents, F1 and all 140 RILs in 2 replicated experi-
ments. In each replicate, the whole population was divided
into 7 subgroups with 20 RILs each and the tissue culture
process of each subgroup was conducted by a single person
and completed in an exact time span. All phenotypic
evaluation was also done by the same person in order to
keep the consistency of the tissue culture experiments and
phenotypic evaluation, and to minimize the artificial errors
caused by different operating behaviors from different
hands. The images showing the different status of tissue
culture responses of different genotypes were recorded
accordingly with a digital camera during the different
periods of tissue culture experiment.
Phenotypic evaluation
Callus induction
Four indices were used to evaluate callus induction from
seed: callus induction rate (CIR), the proportion of callus-
forming seeds to the total number of cultured seeds as
described by Kwon et al. (2000); induced-callus color
(ICC) as described by Taguchi-Shiobara et al. (2006) with
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slight alteration; induced-callus size (ICS) and induced-
callus friability (ICF).
ICC was categorized into five types from 1 to 5: brown,
brownish-yellow, yellow, yellowish and yellowish-white.
The ICS after 15 days’ culture, was sorted into five scales
from 1 to 5 based on the average diameter of callus
(0–0.25, 0.25–0.40, 0.40–0.55, 0.55–0.70 and [0.70 cm),
respectively. For ICF, calluses were classed into four
groups from 1 to 4: solid, moderately disperse, friable and
very friable, respectively.
Callus differentiation and plant regeneration
After 20 days’ growth on the regeneration medium, the
status of callus differentiation was evaluated by three
indices: callus proliferation ability (CPA), the ratio of the
area occupied by proliferated calluses to the whole tissue
culture bottle bottom area; callus browning tendency
(CBT), the proportion of browning calluses to the whole
produced calluses; callus greening ability (CGA), the
proportion of greening calluses to all produced calluses.
After another 20 days, plant regeneration ability was
assessed by two indices: the average number of regenerated
shoots per callus (NRS) and regeneration rate (%, RR), the
percentage of calluses that produced regenerated shoots to
the total number of calluses, respectively, as described by
Peng and Hodges (1989).
The CPA, the extent of proliferation during callus dif-
ferentiation, was classified into five scales from 1 to 5
(0–20 %, 21–40 %, 41–60 %, 61–80 % and 81–100 %) to
distinguish the different levels of callus proliferation,
respectively. The similar classifications were also applied
in the determinations of various degrees for CBT and CGA,
respectively. Explanations about the classification of five
traits (ICC, ICS, CPA, CBT and CGA) are presented in
Online Resource 1 and 2.
Statistical and QTL analysis
All the phenotypic data were analyzed with the application
of the SPSS V 13.0 statistics software, including correla-
tion analysis between the indices, analysis of variance
(ANOVA) and the drawing of frequency distribution.
Composite interval mapping (CIM) analysis, imple-
mented in the software package Window QTL Cartogra-
pher V2.5 (http://statgen.ncsu.edu/qtlcart/WQTLCart.htm),
was performed using Model 6 with forward and backward
stepwise regression (Wang et al. 2007). A 10-cM scan
window was employed, and the likelihood ratio statistic
was computed every 1 cM. A permutation test was con-
ducted 1,000 times to determine the experiment-wide sig-
nificance (P \ 0.05) thresholds for QTL detection
(Churchill and Doerge 1994). The location of a QTL was
determined according to its LOD peak location and the
surrounding region with 95 % confidence interval calcu-
lated using WinQTLCart. The QTL were identified through
their LOD scores compared with the threshold by permu-
tation test and the ones with LOD values larger than
threshold of 3 were calculated as QTLs for the particular
traits based on the procedure as previously reported (Wang
et al. 2010).
Results
Phenotypic variations for tissue culture responses
of the parents, F1 and RILs
The tissue culture response was dissected into nine rela-
tively easy-scoring indices and evaluated in the standard-
ized system for both parents, F1 and all 140 RILs in two
replicated experiments. The two sets of phenotypic evalu-
ation data generated from two replicates are closely cor-
related to each other, giving correlation coefficients of
0.775 for CIR and CPA, 0.632 for CGA, 0.709 for CBT
and 0.740 for RR. Since the phenotypic data generated
from two duplicated experiments are reproducible, the
mean values for each index were, therefore, calculated for
each genotype and used for all of the following analyses in
this study.
After 15 days of inoculation on callus induction medium,
embryogenic calluses were induced from the scutellar
region of 93-11, Nipponbare and F1 seeds, respectively,
showing a dry, compact, yellow or light yellowish and
nodular appearance (Fig. 1a). A high frequency of callus
induction was observed for all three genotypes. The callus
induction rate (CIR) of 93-11 was lower than that of Nip-
ponbare and F1 and, CIR of F1 was slightly higher than
Nipponbare (Fig. 2d). The CIR varied significantly among
lines in the RI population, ranging from 3.56 to 100 %
(Fig. 2d). Phenotypic variation showing callus morpho-
logical status as represented by ICC, ICS and the degree of
ICF, were observed in both parents, F1 and RILs, and dis-
continuous phenotype variations were detected in the RI
populations (Fig. 2a–c). Huge differences were found in the
aspects of callus color (from brown to yellowish-white),
callus size (from\0.25 cm to[0.70 cm), as well as callus
friability (from solid to very friable) (Fig. 2a–c; Online
Resource 1 and 3).
With regard to callus differentiation, represented by CPA,
CBT, CGA, and plant regeneration ability, dramatic
phenotypic variations were discovered among all lines in the
population, (Fig. 2e–i; Online Resource 1 and 4). After
being transferred to regeneration medium, the calluses
induced from Nipponbare proliferated rapidly and produced
abundant secondary embryogenic calluses spreading over
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the medium surface in the tissue culture bottle. About
7–10 days later, a large proportion of calluses started turning
to green and the regenerated plantlets emerged gradually
during the course of regeneration. The majority of calluses
induced from 93-11, on the other hand, changed from green
to brown and eventually turned blackish in color, and no
proliferation or green plantlets appeared on the regeneration
medium (Fig. 1b). It was very clear, as shown from the
images of cultures in Fig. 1, that F1 showed almost the same
performance as Nipponbare under the plant regeneration
phase. Throughout the survey of the whole population during
the regeneration period, all kinds of phenotypic variation
were discovered for CPA, CBT, CGA, NRS and RR,
respectively (Fig. 2; Online Resource 1 and 4). Similar fre-
quency distributions were observed for CGA, NRS and RR.
The number of RILs decreased at each ranking from the very
top at the lowest rank on the scale to the bottom at the highest
rank, but the opposite trend emerged for CBT (Fig. 2f–i).
Transgressive segregations were detected remarkably for all
traits investigated in the RI population (Fig. 2).
Correlation among the nine indices associated
with performance of tissue culture
Correlations among the nine indices associated with per-
formance of tissue culture were revealed by calculating the
correlation coefficients (r) (Table 1). ICC had the positive
correlation with ICF (r = 0.213). ICS was positively cor-
related with CIR (r = 0.431) and CBT (r = 0.259), but
negatively with CGA (r = -0.270), NRS (r = -0.269)
and RR (r = -0.284), respectively. The positive correla-
tions were also found in ICF and CPA (r = 0.372), CIR
and CPA (r = 0.232), respectively. For the indices asso-
ciated with callus differentiation and regeneration, signifi-
cant positive correlations were strikingly observed among
the four indices CPA, CGA, NRS and RR. The correlation
coefficients between these indices were varied from 0.216
to 0.903. The high and positive correlations were observed
between each other among CGA, NRS and RR, and CBT
was marked negatively correlated with CPA, CGA, NRS
and RR, respectively (Table 1).
Fig. 1 Callus induction (a) and plant regeneration (b) from seed callus derived from Nipponbare and 93-11 parental varieties and their F1
progeny
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QTL identifications for culturability
Twenty QTLs were initially detected for nine indices based
on the LOD thresholds ranging from 3.22 (for CIR) to 3.47
(for ICF) after permutation tests, and five additional QTLs
for which LOD values were lower than their corresponding
permutation thresholds but higher than 3.0 were also
included. Consequently a total of 25 QTLs were identified
and distributed on all chromosomes except chromosome 1,
4, 8 and 11, and each QTL was named according to rice
Fig. 2 Frequency distribution of nine indices for mature seed culturability in rice RIL population
Table 1 Correlation coefficient (r) between the indices described for tissue culture response
ICC ICS ICF CIR CPA CBT CGA NRS
ICS 0.074
ICF 0.213* 0.046
CIR -0.126 0.431** 0.132
CPA -0.004 -0.139 0.372** 0.232**
CBT -0.012 0.259* 0.014 -0.106 -0.605**
CGA -0.060 -0.270** -0.127 0.000 0.355** -0.740**
NRS -0.002 -0.269** -0.144 -0.086 0.216* -0.674** 0.839**
RR -0.041 -0.284** -0.117 0.024 0.373** -0.752** 0.903** 0.847**
ICC induced-callus color, ICS induced-callus size, ICF induced-callus friability, CIR callus induction rate, CPA callus proliferation ability, CBTcallus browning tendency, CGA callus greening ability, NRS the average number of regenerated shoots per callus, RR regeneration rate (%)
* Correlation is significant at the 0.05 level (two-tailed)
** Correlation is significant at the 0.01 level (two-tailed)
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QTL nomenclature rules (McCouch and CGSNL 2008)
(Table 2; Fig. 3).
Eight putative QTLs that are closely related with the
ability of callus induction were identified, two each for ICC
(qICC-6 and qICC-12), ICS (qICS-5 and qICS-9), ICF
(qICF-5 and qICF-6) and CIR (qCIR-10 and qCIR-12).
These QTLs were located on chromosomes 5, 6, 9, 10 and
12, and the co-location of QTLs occurred in the cases of
qICC-6 and qICF-6, qICC-12 and qCIR-12 when the
overlap of 95 % confidence region was investigated.
Seventeen QTLs for the five indices associated with
callus differentiation and plant regeneration ability were
detected: three for CPA (qCPA-2a, qCPA-2b, and qCPA-
10), two for CBT (qCBT-2a and qCBT-2b), and four each
for CGA (qCGA-2, qCGA-3a, qCGA-3b and qCGA-7),
NRS (qNRS-3a, qNRS-3b, qNRS-7 and qNRS-12) and
RR (qRR-2, qRR-3, qRR-7 and qRR-12), located on
chromosomes 2, 3, 7, 10 and 12. Co-location of QTLs
defined by the overlap of 95 % confidence intervals also
occurred in six cases: (1) qCPA-2a and qCGA-2, (2) qCBT-
2b and qRR-2, (3) qCGA-3a and qNRS-3a, (4) qCGA-3b,
qNRS-3b and qRR-3, (5) qCGA-7, qNRS-7 and qRR-7, and
(6) qNRS-12 and qRR-12, respectively.
Through a general survey of all QTLs in this study,
phenotypic effect (R2) variance explained by these QTLs
ranged between 5.99 % (qCPA-10) and 21.91 % (qCGA-
7), and more than 10 % of phenotypic variation explained
by a single QTL was found for 13 QTLs identified for all
indices (Table 2). qCGA-7 had the highest LOD score
(9.09), and the largest phenotypic variation explained
(21.91 %), followed by qNRS-3b (LOD 6.67 and R2
14.87 %). Phenotypic effects contributed from Nipponbare
were observed for seven indices (ICC, ICF, CIR, CPA,
CGA, NRS and RR), showing negative additive effects
Table 2 QTLs identified from the analysis of the rice recombinant inbred lines
Trait LOD
thresholdaQTL Chr. Marker LOD LOD peak
position (cM)
Additive effectb R2 (%)c 95 % CI (cM)d QTL
region (Mb)e
ICC 3.32 qICC-6 6 bin 1299 3.78 100.71 -0.40 10.60 98.0–101.4 26.8–27.2
qICC-12 12 bin 2247 3.43 62.91 0.37 9.58 58.3–67.1 12.9–16.0
ICS 3.43 qICS-5 5 bin 1020 3.28 42.51 0.32 7.61 41.1–45.2 6.8–8.9
qICS-9 9 bin 1710 5.93 11.91 0.50 14.51 11.0–13.7 6.4–7.2
ICF 3.47 qICF-5 5 bin 1137 4.26 117.11 -0.36 8.96 116.8–119.9 28.7–29.2
qICF-6 6 bin 1303 5.68 103.41 -0.42 12.32 100.4–106.6 27–28.4
CIR 3.22 qCIR-10 10 bin 1956 3.86 74.61 -8.61 10.31 73.3–78.0 22.1–22.6
qCIR-12 12 bin 2248 4.31 65.41 -8.53 10.59 62.9–67.7 15.4–16.8
CPA 3.29 qCPA-2a 2 bin 0317 3.87 19.21 -0.37 6.75 14.8–22.0 3.3–4.6
qCPA-2b 2 bin 0491 6.95 131.61 -0.50 12.71 129.3–133.6 32.0–33.2
qCPA-10 10 bin 1966 3.48 84.61 0.32 5.99 81.3–84.9 23.1–23.6
CBT 3.39 qCBT-2a 2 bin 0513 3.93 146.61 0.37 9.03 146.5–149.8 35.4–35.6
qCBT-2b 2 bin 0523 4.68 160.11 0.40 10.61 157.7–160.4 36.2–36.6
CGA 3.33 qCGA-2 2 bin 0313 3.14 17.31 -0.31 6.17 13.5–18.4 3.0–3.7
qCGA-3a 3 bin 0546 3.64 16.31 -0.36 7.12 14.2–17.3 2.6–3.0
qCGA-3b 3 bin 0569 3.15 30.41 0.34 6.90 28.5–32.4 5.5–6.5
qCGA-7 7 bin 1462 9.09 80.41 -0.55 21.91 77.3–84.2 24.6–26.0
NRS 3.38 qNRS-3a 3 bin 0546 4.85 16.31 -0.82 10.35 11.9–17.6 2.3–3.3
qNRS-3b 3 bin 0567 6.67 29.81 1.07 14.87 28.7–30.1 5.5–6.0
qNRS-7 7 bin 1461 4.99 79.71 -0.73 10.77 75.5–81.4 24.5–25.3
qNRS-12 12 bin 2279 3.12 82.11 0.56 6.61 78.1–84.3 20.9–22.2
RR 3.38 qRR-2 2 bin 0522 3.15 159.71 -0.30 6.46 153.1–160.4 35.9–36.6
qRR-3 3 bin 0567 6.61 29.81 0.48 14.20 28.5–33.3 5.5–6.9
qRR-7 7 bin 1461 6.30 79.71 -0.44 13.37 72.7–81.4 24.2–25.3
qRR-12 12 bin 2279 3.29 81.11 0.31 6.60 77.8–84.3 20.8–22.2
a Thresholds determined by 1,000 permutationsb Positive and negative values indicated additive effects contributed by the alleles of 93-11 and Nipponbare, respectivelyc Percentage of phenotypic variation explainedd Chromosome regions corresponding to the 95 % confidence interval for the detected QTLe Regions between flanking bins of identified QTLs using high-throughput genotyping method (re-sequencing) by their physical locations
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ranging from -0.30 to -8.61, while phenotypic effects
derived from 93-11 were observed for seven indices (ICC,
ICS, CPA, CGA, CBT, NRS and RR), showing positive
additive effects ranging from 0.31 to 1.07. For ICF and
CIR, all phenotypic variances explained by two respective
QTLs were contributed from Nipponbare alleles only. For
Fig. 3 Chromosomal locations
of the QTLs detected for rice
mature seed culturability
Twelve rice chromosomes are
numbered, with centromeres
indicated by ellipses. Positions
of recombinant bins used as
genetic markers are indicated by
horizontal lines spaced
proportionally according to their
genetic distance on the linkage
map. Rhombus heads indicated
LOD peak locations of QTL and
different color represents
different traits. Rhombus with
vertical bar inside heads QTL
with LOD values above 3.0 but
below the permutation threshold
Plant Cell Rep
123
ICS and CBT, phenotypic variances explained by two
QTLs, respectively, were all contributed from 93-11
alleles. For the remaining indices (ICC, CPA, CGA, NRS
and RR), contributions for total phenotypic variance came
from both Nipponbare and 93-11.
Discussion
Reproducibility of phenotypic evaluations
Tissue culture response could be influenced by many fac-
tors including the genotype and the explant organ of donor
plants, the physiological status of the explant, the medium
composition, the culture procedure, and the interactions
between them (Henry et al. 1994; Lee et al. 2002; Bolibok
and Rakoczy-Trojanowska 2006; Ge et al. 2006). It is not
surprising that the outcomes from tissue culture are very
different between different laboratories and different per-
sons even for the same genotype and the same procedure.
Having highly reproducible, reliable and accurate pheno-
typic evaluation is, therefore, the most difficult task in a
QTL mapping study for a complicated trait, particularly
tissue culture response as examined in this study. A stan-
dardized system was implemented to retain a consistency
of the tissue culture experiments and phenotypic evaluation
through the following approaches: (1) dissecting the target
trait into several easily scored indices, (2) dividing the
whole experiment into several sub-experiments each with
an easily manageable scale, and (3) conducting the
experiment in a one-person operating system to minimize
the artificial errors caused by different operating behaviors
from different persons. Reproducibility of phenotypic
evaluations was satisfactorily achieved in this study, which
is evidenced by the correlations between the data generated
from replicates, and also the correlations between different
indices and co-locations of corresponding QTLs.
Determination of the most suitable tissue
culture procedure
Seed-derived calluses from the scutellum of the mature
embryo is the most frequently used explant in rice trans-
formation because of its advantages of no seasonal
restrictions, efficient regeneration and easier transforma-
tion than other tissues. Rice seed-derived calluses have
normally been categorized into two types: (1) embryogenic
callus showing dry and compact texture, yellow or yel-
lowish color and knobby appearance, and (2) non-
embryogenic callus presenting the characteristic of watery,
translucent and non-compact texture, white color (Kamiya
et al. 1988; Lee et al. 2002; Ge et al. 2006; Khaleda et al.
2007). An additional simple classification based on the
length of culture time for mature seed-derived callus in rice
has also been suggested recently as primary callus (\10-
day-old callus induced from scutellum) and secondary
callus ([2-week-old callus proliferated from primary cal-
lus) and tremendous differences for callus friability and
rigidity also existed between primary callus and secondary
callus (Saika and Toki 2010). Though regeneration ability
of the primary calluses is comparable with embryogenic
calluses for the majority of rice genotypes, the regeneration
capability of the secondary calluses are not always con-
sistent with their primary callus through a course of sub-
culture because of the alteration of callus texture,
especially for indica rice. Up to now, successful regener-
ation could be achieved from 2- to 3-week-old rice callus
(Hiei et al. 1994; Dabul et al. 2009), callus within a month
of the start of the aseptic culture of mature rice seeds after a
1-day preculture (Toki et al. 2006), and also the callus after
1–2 subcultures (Taguchi-Shiobara et al. 1997a, b, 2006;
Lin and Zhang 2005; Ge et al. 2006; Zhao et al. 2009), but
the decreasing regeneration ability of calluses going
through long-term subculture has also been found. There
are many factors that influence callus subculture and the
subsequent regeneration process, for example medium
composition, culture process and genotype. Plant regener-
ation efficiency in secondary calluses of rice variety Super
basmati was increased dramatically by means of partial
physical desiccation and chemical desiccation (Ikram-ul-
Haq et al. 2009).
For the purpose to observe the maximum phenotypic
variations for tissue culture performance from the segre-
gating population, a series of pilot experiments was con-
ducted and the critical criteria were determined and applied
for this study. The texture of 93-11 callus converting from
an embryogenic to non-embryogenic state was determined
with the extension of subculture time in the pilot experi-
ments, showing a close relationship with the plant regen-
eration ability. DL3, an optimal differentiation medium
succeeding in four different kinds of indica rice as previ-
ously reported (Lin and Zhang 2005), was used to test the
callus regeneration ability of 93-11 in this study. It was
found that the medium could vastly improve the regener-
ation ability of 15–30 days old callus but not older than
30-days, compared with other regeneration media tested in
the pilot experiment in this study (data not shown).
Finding the optimal time-point to transfer the cultures
onto new regeneration medium is always a critical deter-
minant for a favorable performance of callus differentiation
and plant regeneration for many genotypes in rice. The
callus culture time of 15-days, the time required for neither
primary calluses (defined as \10-day-old) nor secondary
calluses (defined as [2-week-old), was shown to be the
transition time suitable for all lines investigated in this
study since a remarkable difference among different lines
Plant Cell Rep
123
was detected during the callus induction and plant regen-
eration and also, some major-effect QTLs associated with
plant regeneration ability were identified successfully
through observing the course of callus differentiation.
Additionally, the important information about early callus
culturability in rice was obtained from regeneration
research on early callus in a shorter experimental period
with less labor cost for in vitro culture.
Evaluation of tissue culture response
In previous reports, a number of indices such as induction
of callus, callus growth, callus morphology and plant
regeneration (qualitatively or quantitatively) were used to
estimate various characteristics for plant tissue culture
ability (Bolibok and Rakoczy-Trojanowska 2006). In rice
callus induction rate, callus color, volume and weight,
callus subculture ability, the NRS and RR had been used as
the important parameters to evaluate the performance of
callus tissue culture (Taguchi-Shiobara et al. 1997a, b,
2006; Takeuchi et al. 2000; Kwon et al. 2000; Ge et al.
2006; Zaidi et al. 2006; Raveendar et al. 2008; Dabul et al.
2009; Zhao et al. 2009). In this study, tissue culture
response including induced-callus morphology was elabo-
rately dissected as well as callus differentiation. Apart from
ICC, CIR, NRS and RR, several new concepts such as ICF,
CPA, CBT and CGA were introduced and two to four
QTLs related to these corresponding traits were identified.
The differences of friability (ICF) for individual lines in
this study is very likely a consequence of the different
growth times for the transition from primary callus to
secondary callus for each line while secondary callus is
even more friable due to exuberant growth. The growth of
the calluses, after inoculation on the regeneration medium,
could follow two different developmental paths, one is
embryogenic with continuing healthy callus growth, and
producing more friable embryogenic calluses with the great
potential to develop into regeneration plantlets, and the
other is non-embryonic, becoming softer, watery, or ceas-
ing proliferation and turning necrotic. Dabul et al. (2009)
had used the frequency of callus greening at 15 or 30 days
on regeneration medium as an index to screen the high-
frequency regeneration rice germplasm for in vitro tissue
culture. This character had similarity with the CGA, pre-
sented in this study. Callus browning is an important lim-
iting factor to the normal regeneration process, but the
genetic mechanism leading to callus browning during the
regeneration process in rice is still poorly understood.
Although in a previous study the single locus correlated to
callus browning had been located on chromosome 1 (Li
et al. 2007), it is very different from the QTL regions for
CBT on chromosome 2 detected in this study because the
investigation targets involved in the two studies are
actually two different indices. The former occurred in the
initial stage of callus induction and presented as a quali-
tative trait, but the latter (CBT), representing a trend to turn
brown, happened in the course of plant regeneration and
behaved as a quantitative trait. In conclusion, proposal of
these new concepts (ICF, CPA, CGA and CBT) may offer
us a new insight to decompose the whole tissue culture
process.
Transgressive segregation, which is interpreted as an
indicator of polygenic inheritance, has become a com-
monly observed phenomenon in QTL detection for TCR
(Taguchi-Shiobara et al. 1997a; He et al. 1998; Bregitzer
and Campbell 2001; Flores Berrios et al. 2000; Schian-
tarelli et al. 2001; Mano and Komatsuda 2002), and dis-
continuous and skewed distributions have also been
reported in many cases for tissue culture capability (Zhang
and Hattori 1998; Kwon et al. 2000; Torp et al. 2001;
Taguchi-Shiobara et al. 2006). Transgressive segregation
and segregation distortion were observed for nine indices
in this study (Fig. 2), implying the existence of major
genes for tissue culture response in this population, but the
genetic mechanism underlying these phenomena still
remains unclear.
Identification of QTLs for culturability
A number of QTL mapping studies concerning plant
regeneration capability in rice have been conducted using
mature seed as explants in the past two decades (Table 3).
The density and quality of markers played very important
roles in QTL mapping. However, the markers used in
previous reports about QTL mapping for tissue culture
ability in rice all belonged to traditional molecular marker
types. The high resolution bin map based on SNP poly-
morphisms used in this study boosted the accuracy for QTL
identification, as it revealed more precise recombination
breakpoints compared with the traditional molecular mar-
ker-based map (Huang et al. 2009; Wang et al. 2010; Xu
et al. 2010; Yu et al. 2011). Moreover, various evaluation
criteria and different culture systems, such as medium
composition, age of the callus and callus culture procedure,
as well as parental genotypes selected greatly affect QTL
mapping results for tissue culture response.
Based on investigation of four indices (frequency of
callus induction, callus subculture capability, frequency of
plant regeneration and the mean plantlet number per
regenerated callus), 29 QTLs controlling rice mature seed
culturability, under two medium systems for indica or
japonica varieties, had been identified using CSSLs
derived from Zhenshan 97B (indica) 9 Nipponbare
(japonica) (Zhao et al. 2009). Among these, 12 QTLs were
found under the culture system for japonica rice, while the
other 17 QTLs were in culture context for indica rice, and
Plant Cell Rep
123
Ta
ble
3C
om
par
iso
no
fQ
TL
iden
tifi
edfr
om
this
and
pre
vio
us
stu
die
so
fin
dic
aan
dja
po
nic
acu
ltiv
ars
Tra
its
QT
Lo
fth
isst
ud
yP
rev
iou
sst
ud
ies
QT
L
nu
mb
er
Ch
r.co
de
inv
olv
ed
QT
L
nu
mb
er
Ch
r.co
de
Inv
olv
ed
Po
pu
lati
on
typ
eP
op
ula
tio
n
size
Mar
ker
typ
e(n
um
ber
)M
app
ing
par
ents
Ref
eren
ces
ICC
26
,1
22
4,
9B
C1F
31
83
RF
LP
(11
6)
Ko
shih
ikar
i(J
),
Kas
alat
h(I
)
Tag
uch
i-S
hio
bar
a
etal
.(2
00
6)
CIR
21
0,
12
62
,3
,8
,1
1C
SS
L1
39
SS
R(1
17
)N
ipp
on
bar
e(J
),
Zh
ensh
an9
7B
(I)
Zh
aoet
al.
(20
09
)
21
,2
RI
(F13:F
14)
16
4R
FL
P,
AF
LP
,S
SL
P,
Iso
zym
e
mo
rph
olo
gic
al(5
36
)
Mil
yan
g2
3(t
on
gil
),
Gih
ob
yeo
(J)
Kw
on
etal
.(2
00
0)
NR
S4
3,
7,
12
51
,2
,4
BC
1F
59
8R
FL
P(2
45
)N
ipp
on
bar
e(J
),
Kas
alat
h(I
)
Tag
uch
i-S
hio
bar
a
etal
.(1
99
7a)
RR
42
,3
,7
,1
24
2,
4B
C1F
59
8R
FL
P(2
45
)N
ipp
on
bar
e(J
),
Kas
alat
h(I
)
Tag
uch
i-S
hio
bar
a
etal
.(1
99
7a)
61
,4
,6
,8
,1
0,
12
CS
SL
13
9S
SR
(11
7)
Nip
po
nb
are
(J),
Zh
ensh
an9
7B
(I)
Zh
aoet
al.
(20
09
)
42
,3
,1
1R
I(F
13:F
14)
16
4R
FL
P,
AF
LP
,S
SL
P,
Iso
zym
e
mo
rph
olo
gic
al(5
36
)
Mil
yan
g2
3(t
on
gil
),
Gih
ob
yeo
(J)
Kw
on
etal
.(2
00
0)
41
,2
,3
,6
BC
1F
2(f
rom
99
BC
1F
1)
18
0P
CR
mar
ker
s(2
62
)N
ipp
on
bar
e(J
),
Kas
alat
h(I
)
Nis
him
ura
etal
.(2
00
5)
22
,4
F2
79
RF
LP
(10
3)
No
rin
1(J
),T
adu
kan
(I)
Tak
euch
iet
al.
(20
00
)
Plant Cell Rep
123
as for the same indices only 4 QTLs were identified under
both medium systems.
In this study, 25 QTLs were discovered under only one
culture system for japonica rice. Through comparison of
QTLs controlling the same trait (ICC, CIR, NRS and RR)
identified from this and previous studies of indica and
japonica cultivars, locations of QTLs in this study were
significantly different from the ones presented in Table 3.
These discrepancies were due partly to the difference of
two parental genotypes, population type and culture con-
dition particularly the choice of only one regeneration-
medium system.
Co-localizations of QTLs
A total of 8 groups of co-localized QTL were found among
25 QTLs, 8 indices and 18 QTLs were involved (Table 2;
Fig. 3). Every pair of indices involved in QTL co-locali-
zation possessed significant correlation, except the pair of
ICC and CIR. It was very interesting to notice that co-
localizations occurred among three QTLs in two cases:
qCGA-3b, qNRS-3b and qRR-3 were located on the same
region on chromosome 3, shared the same direction of
phenotypic variance contributed from 93-11, and similarly,
qCGA-7, qNRS-7 and qRR-7 were all located on the same
region on chromosome 7 and shared the same direction
of phenotypic variance contributed from Nipponbare
(Table 2; Fig. 3). Given the fact that three different indices
were involved in the identification of these QTLs, CGA,
NRS and RR were all closely correlated to each other, it
implicated the existence of a single gene with pleiotropic
effects or a very close linkage between the genes. Another
possibility is that these three indices owned coherence on
description of plant regeneration but from different aspects.
The results presented here have, therefore, demonstrated
the feasibility of new produced concepts, especially CGA,
for evaluating phenotypic variation on TCR with an
advantage of high efficiency and accuracy.
Although several methods have been presented toward
cloning of QTLs, cloning of major-effect QTL has been
rarely achieved. The gene encoding ferredoxin-nitrite
reductase (NiR) isolated from a main QTL has been
reported for determining regeneration ability in rice
(Nishimura et al. 2005), but many more genes involved are
neither revealed nor cloned so far, and hence a clear picture
could not be drawn on tissue culture responses in plants.
Taking advantage of the successful identification of major
QTLs and the availability of sequence information pro-
vided by the physical map based on whole-genome
re-sequencing, the populations segregating for individual
major-QTL have been created, and further fine mapping
and gene cloning of these major QTLs are currently
underway.
In conclusion, phenotypic variations for nine indices
associated with tissue culture responses were evaluated by
a standardized system, and combined with a high quality
sequence-based genetic map, a total of 25 QTLs were
identified in a RI population derived from 93-11 (Oryza
sativa ssp. indica) 9 Nipponbare (Oryza sativa ssp.
japonica). At least two major QTLs associated with plant
regeneration, confirmed by three different indices of CGA,
NRS and RR, were identified and located one each on
chromosome 3 and chromosome 7 with the additive effects
contributed from both Nipponbare and 93-11. The results
obtained from this study have paved a solid foundation for
fine mapping and gene cloning of major QTLs for TCR in
further studies. The knowledge of the genes underlying the
tissue culture response would be very helpful not only for
better understanding of the molecular basis for tissue cul-
ture response, but also for setting up an optimized trans-
formation system suitable for the genotypes useful in rice
breeding.
Acknowledgments The authors would like to thank Ms. Jixiang
Huang and Dr. Hua Jiang for their assistance with data analysis, and
Mr. Guoxing Mi for taking care of rice plants in the experiment. This
study is financially supported by the 863 project from MOST
(2012AA10A302-6), China and the fundamental research project
from ZAAS.
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