BMC Plant Biology
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Molecular insights into how a deficiency of amylose affects carbon allocation -carbohydrate and oil analyses and gene expression profiling in the seeds of a
rice waxy mutant
BMC Plant Biology 2012, 12:230
doi:10.1186/1471-2229-12-230
Ming-Zhou Zhang (zmzzju@yahoo.com.cn)
Jie-Hong Fang (figo0726@163.com)
Xia Yan (Xia.Yan@slu.se)
Jun Liu (liujuncjlu@163.com)
Jin-Song Bao (jsbao@zju.edu.cn)
Gunnel Fransson (gunnel.fransson@slu.se)
Roger Andersson (Roger.Andersson@slu.se)
Christer Jansson (cgjansson@lbl.gov)
Per Åman (per.aman@slu.se)
Chuanxin Sun (chuanxin.sun@slu.se)
ISSN
1471-2229
Article type
Research article
Submission date
13 August 2012
Acceptance date
27 November 2012
Publication date
5 December 2012
Article URL
http://www.biomedcentral.com/1471-2229/12/230
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Molecular insights into how a deficiency of amylose
affects carbon allocation – carbohydrate and oil
analyses and gene expression profiling in the seeds of
a rice waxy mutant
Ming-Zhou Zhang1,†
Email: zmzzju@yahoo.com.cn
Jie-Hong Fang1,†
Email: figo0726@163.com
Xia Yan2,3
Email: Xia.Yan@slu.se
Jun Liu1
Email: liujuncjlu@163.com
Jin-Song Bao4
Email: jsbao@zju.edu.cn
Gunnel Fransson5
Email: gunnel.fransson@slu.se
Roger Andersson5
Email: Roger.Andersson@slu.se
Christer Jansson6
Email: cgjansson@lbl.gov
Per Åman5
Email: per.aman@slu.se
Chuanxin Sun2*
*
Corresponding author
Email: chuanxin.sun@slu.se
1
College of Life Science, China JiLiang University, Hangzhou 310018, China
2
Department of Plant Biology & Forest Genetics, Uppsala BioCenter, Swedish
University of Agricultural Sciences and Linnean Center for Plant Biology, P.O.
Box 7080, SE 75007 Uppsala, Sweden
3
Heihe Key Laboratory of Ecohydrology and Integrated River Basin Science,
Cold and Arid Regions Environmental and Engineering Institute, Chinese
Academy of Sciences, 260 Donggang West Road, Lanzhou 730000, China
4
Institute of Nuclear Agricultural Sciences, Zhejiang University, Hangzhou,
Zhejiang 310029, China
5
Department of Food Science, Uppsala BioCenter, Swedish University of
Agricultural Sciences, P.O. Box 7051, SE 75007 Uppsala, Sweden
6
Lawrence Berkeley National Laboratory, Earth Sciences Division, 1 Cyclotron
Road, Berkeley, CA 94720, U.S.A
†
Equal contributors.
Abstract
Background
Understanding carbon partitioning in cereal seeds is of critical importance to develop cereal
crops with enhanced starch yields for food security and for producing specified end-products
high in amylose, β-glucan, or fructan, such as functional foods or oils for biofuel applications.
Waxy mutants of cereals have a high content of amylopectin and have been well
characterized. However, the allocation of carbon to other components, such as β-glucan and
oils, and the regulation of the altered carbon distribution to amylopectin in a waxy mutant are
poorly understood. In this study, we used a rice mutant, GM077, with a low content of
amylose to gain molecular insight into how a deficiency of amylose affects carbon allocation
to other end products and to amylopectin. We used carbohydrate analysis, subtractive cDNA
libraries, and qPCR to identify candidate genes potentially responsible for the changes in
carbon allocation in GM077 seeds.
Results
Carbohydrate analysis indicated that the content of amylose in GM077 seeds was
significantly reduced, while that of amylopectin significantly rose as compared to the wild
type BP034. The content of glucose, sucrose, total starch, cell-wall polysaccharides and oil
were only slightly affected in the mutant as compared to the wild type. Suppression
subtractive hybridization (SSH) experiments generated 116 unigenes in the mutant on the
wild-type background. Among the 116 unigenes, three, AGP, ISA1 and SUSIBA2-like, were
found to be directly involved in amylopectin synthesis, indicating their possible roles in
redirecting carbon flux from amylose to amylopectin. A bioinformatics analysis of the
putative SUSIBA2-like binding elements in the promoter regions of the upregulated genes
indicated that the SUSIBA2-like transcription factor may be instrumental in promoting the
carbon reallocation from amylose to amylopectin.
Conclusion
Analyses of carbohydrate and oil fractions and gene expression profiling on a global scale in
the rice waxy mutant GM077 revealed several candidate genes implicated in the carbon
reallocation response to an amylose deficiency, including genes encoding AGPase and
SUSIBA2-like. We believe that AGP and SUSIBA2 are two promising targets for classical
breeding and/or transgenic plant improvement to control the carbon flux between starch and
other components in cereal seeds.
Keywords
Carbon allocation, Rice (Oryza sativa), Waxy seeds, Suppression subtractive hybridization
(SSH), Quantitative polymerase chain reaction (qPCR), Gene expression
Background
Cereal crops are of critical importance in agriculture. The top three cereals in global
production (2009) are maize, wheat, and rice, with 819, 686 and 685 M tonnes, respectively
(http://faostat.fao.org). Cereal crops constitute our largest primary food source and are also
highly used in food and non-food industrial applications. Contributing factors to the
importance of cereals are that they can be bred to be very high yielding, that cereal grains
lend themselves to long-term storage, and that the grain can accumulate different types of
carbohydrates and lipids. Major carbohydrates in cereal caryopses are the starch components
amylose and amylopectin, cell wall components, such as different types of arabinoxylan,
mixed-linkage β-glucan and cellulose, fructooligosaccharides, fructan, and sucrose [1,2].
Interestingly significant amounts of oil can also be stored in the endosperm, especially in oats
[3]. The composition of the cereal grain dictates the end use of the crop. For example, the
cereal endosperm is the most important source of starch worldwide [4,5] and is therefore of
tremendous value for food security. There is an ongoing search for genotypes with high
content of amylose, β-glucan and/or fructan for different applications within the functional
food sector [6-8]. At the other end of the spectrum are efforts to develop cereals that redirect
carbon flux from carbohydrates to oils for production of high-density biofuels [9-13]. A
thorough understanding of the mechanisms for the partitioning of photosynthates in cereals is
crucial for our ability to boost starch yield, to develop specialty crops for the functional food
industry, such as barley with enhanced ß-glucan levels, and to tailor cereal production for the
non-food industry.
Carbon partitioning in higher plants has been studied at the whole-plant level [14,15], for
certain types of plant tissues [16-18], and for plant cells [19]. However, many questions
remain unanswered. For example, we need to identify and map the actions of key elements
that determine carbon allocation between source and sink tissues and that govern carbon flux
along pathways for synthesis of different carbohydrate and oil sinks. It is also imperative that
we gain insight into how environmental factors influence carbon partitioning [4,20]. Several
proteins have been implicated as important players in carbon partitioning in plants. They
include proteins involved in sugar transport and metabolism, such as sucrose transporters
[21], sucrose invertases [22] and sucrose synthases [23,24], and in hexose metabolism and
transport, such as hexose kinases [25] and monosaccharide transporters [26]. Other examples
include proteins controlling the flux in polysaccharide biosynthesis, such as ADP-glucose
pyrophosphorylase [27], and UDP-glucose pyrophosphorylase [28,29], and regulatory
proteins, such as sucrose non-fermenting-1-related protein kinase [30], trehalose-6-phosphate
synthase [31], and transcription factors [12,32-35].
We are interested in identifying molecular switches in cereals that direct carbon flux to
different tissues and into the specific end products. We are particularly concerned with
carbon partitioning between amylose, amylopectin, oil, β-glucan and fructan in cereal seeds.
For the present study, we chose a rice waxy mutant, GM077, which is deficient in amylose
biosynthesis. We examined carbon partitioning between amylose, amylopectin, oil, β-glucan,
fructan and other dietary fibers in the GM077 background, a nearly isogenic waxy line. We
constructed a suppression subtractive hybridization (SSH) cDNA library between the mutant
and the corresponding wild type to identify potential candidates involved in carbon
partitioning. We used qPCR to verify results from the SSH experiments and to study how
gene regulation controls carbon allocation in the absence of amylose biosynthesis.
Results
The GM077 rice is a waxy mutant
Waxy rice has been drawing much attention in rice breeding in China as it has many
applications in traditional Chinese food and brewing. This has resulted in a large collection of
waxy rice in the Chinese rice germplasm repositories and also in a number of breeding
programs on the different qualities of waxy rice [36-38]. We selected one waxy rice cultivar,
GM077 (code No. GM077; Bao et al. unpublished), mainly based on the following factors: i)
It is a stable mutant with a nearly isogenic background; ii) It has a relatively low amylose
content (see also below) compared to other waxy mutants; iii) With the exception of its waxy
grain character, GM077 is phenotypically similar to its wild-type counterpart BP034 (code
No. BP034), an elite variety of Indica rice (also cultivated under the name Guangluai No. 4 in
Southern China) [38,Bao et al. unpublished] (Figure 1A-C; Additional file 1). When the
grains of GM077 were cut transversely and stained with an iodine solution, a typical reddish
color of waxy starch was revealed in the endosperm [39,40]. We have further characterized
the grain starch of GM077 by recording the light absorbance of the starch-iodine complex
between 200 nm and 1100 nm with a scanning spectrophotometer. We included internal
standards of starch with known contents of amylose. As seen in Additional file 2, the
absorbance value around 595 nm for the amylose-iodine complex was reduced proportionally
with the amylose content in the starch samples, including those from the wild type (BP034)
and mutant (GM077). Based on the absorbance, the estimated amylose content of BP034 and
GM077 is between standards 4 (26.5%) and 3 (16.2%), and standards 2 (10.4%) and 1
(1.5%), respectively. The estimations were confirmed with chemical analyses revealing a
significant difference (P = 0.0001) in amylose content of 23.0% and 6.9% in kernels of
BP034 and GMO077, respectively. The starch content was around 67% in both types of rice
grains (P > 0.05) (Figure 1B).
Figure 1 Demonstration of GM077 as a waxy mutant using the corresponding wild type
BP034 as a control. (A) Phenotypic traits of BP034 and GM077 grains. The grains, with and
without hull (A and B, respectively), are visualized. Transverse sections of the grains without
and with iodine-staining were photographed (C and D, respectively). Scale bars (=1.5 mm)
are indicated. (B) Content of total starch and amylose was determined as Sun et al. [35]. 1No
significant difference of total starch content between BP034 and GM077 (P = 0.425).
2
Significant difference of total amylose content between BP034 and GM077 (P = 0.0001).
(C) qPCR analysis of expression levels for GBSSI and GBSSII. DW (dry weight), GBSS
(granule-bound starch synthase). The statistical difference between BP034 and GM077 is
presented as “significantly decreased” (**P < 0.01) and “increased” (*P < 0.05), respectively
It is generally accepted that amylose synthesis is carried out by granule-bound starch
synthases (GBSS). Cereals have two forms of GBSS, GBSSI and GBSSII [41,42]. GBSSI is
responsible for amylose synthesis in storage tissues, such as endosperm, whereas GBSSII is
present in green tissues, including the pericarp of seeds. We used qPCR to analyze gene
expression for both GBSS genes in rice seeds with the ubiquitin gene, UBQ5, as an internal
standard. The qPCR results showed that, in GM077 seeds, gene expression of GBSSI was
significantly reduced (Figure 1C) and the expression of UBQ5 is about the same as in the
control BP034. Expression of GBSSII was significantly increased in GM077 as compared
with BP034.
We have shown that the GM077 rice is a waxy mutant caused by down-regulation of GBSSI.
Yield, kernel weight and starch content were similar between the waxy mutant and the
corresponding wild type (Figure 1B; Additional file 1).To gain insight into the redistribution
of carbon in the GM077 seed, we subjected the mutant and wild-type lines to carbohydrate
and oil analyses.
The major carbon from amylose is redistributed to amylopectin in the waxy
mutant
Carbohydrate analyses revealed that both GM077 and the parental BP034 lines contained
about 3% dietary fiber with similar compositions (Table 1; Additional file 3). Arabinoxylan
and cellulose were major dietary fiber components (about 1% of dry caryopsis each) while
mixed-linkage β-glucan and fructan were minor components. Consequently, no extra carbon
was distributed into the cell walls or to the β-glucan or fructan sink in the GMO77 mutant.
The starch content was slightly reduced in the waxy mutant (67.5% of dry caryopsis)
compared to the wild type (69.3% of dry caryopsis) (P < 0.05). The amylose content was
normal in the wild type (24% of the starch) but highly reduced in the waxy mutant (3.9% of
the starch) (P < 0.01). Thus the amylose content in the seed was reduced from 17% of the
caryopsis in the wild type to 2.6% in the waxy mutant (P < 0.01). The reduced content of
amylose was mainly compensated for by an increased content of amylopectin in the waxy
caryopsis, 65% in the waxy mutant compared to 53% in the wild type. The content of sucrose
and crude oils were the same in the two rice lines (P > 0.05). The glucose content in the
GM077 mutant (0.2%) was somewhat higher than the wild type (0.1%) (P < 0.05), but was
low in both lines.
Table 1 Content of carbohydrates, Klason lignin and oil in BP034 and GM077
GM077 (% of seed
Component
Composition
BP034 (% of seed
DW, n = 3*)
DW, n = 3*)
n.d. (not detected)
n.d.
Total dietary Rhamnose**
fiber
Fucose**
n.d.
n.d.
Arabinose**
0.45 ± 0.08
0.43 ± 0.04
Xylose**
0.52 ± 0.04
0.49 ± 0.07
Mannose**
0.23 ± 0.03
0.20 ± 0.04
Galactose**
0.13 ± 0.02
0.13 ± 0.03
Glucose**
1.03 ± 0.13
0.92 ± 0.05
Uronic acids**
0.26 ± 0.01
0.27 ± 0.01
Klason lignin
0.60 ± 0.50
0.56 ± 0.44
Fructan and
<0.10
<0.10
fructooligosaccharides
3.2 ± 0.50
3.0 ± 0.32
β-Glucan
<0.05
<0.05
Amylose
16.8 ± 0.70 (% of seed 2.6 ± 0.17 (% of seed
Total starch
DW)
DW)
Amylose
Amylopectin
24.2 (% of starch)
3.9 (% of starch)
52.5 (% of seed DW) 64.9 (% of seed DW)
69.3 ± 0.75
67.5 ± 0.59
1.5 ± 0.21
1.5 ± 0.21
Oil
0.1 ± 0.00
0.2 ± 0.00
Free Glc
0.7 ± 0.15
0.9 ± 0.15
Free Suc
*Mean value from three independent analytic experiments using randomly selected caryopses
from a pool of six plants (see table S3). **Sugar residue
The carbohydrate analysis thus indicated that a major fraction of carbon in the waxy mutant
GM077 was reallocated from amylose to amylopectin synthesis. This result prompted us to
try to identify the genes in GM077 responsible for this reallocation. To this end, we employed
the SSH strategy (see below).
Suppression subtractive hybridization identified 116 unigenes in the waxy
mutant
We used GM077 as the tester and BP034 as the driver to construct a cDNA library after PCR
amplification and SSH of cDNAs from total RNA isolated from plants at 12 days after
flowering (daf). The resulting SSH library of “GM077 vs BP034” contained 471 clones with
an average length of around 500 bp. All positive clones were applied to sequencing, which
returned the identification of 116 unigenes. These 116 unigenes were used for the clusters of
orthologous groups (COG) functional annotation analysis [43] after BLASTX and TBLASTX
against the NCBI protein databases. Among the 116 unigenes, 90 exhibited high similarity
(E-value < 10-5) to known protein sequences, and 26 showed no similarity to any reported
sequence. Within the 90 protein sequences, 26 lacked functional annotation. The rest of
sequences were categorized in four functional groups: “information storage and processing”,
“cellular processes and signaling”, “metabolism”, and “poorly characterized” (Figure 2;
Additional file 4). These four functional groups have 12, 21, 23 and 8 unigenes,
corresponding to 10.4%, 18.1%, 19.8% and 6.9% of the total unigenes, respectively (Figure
2). The details of the unigenes and their putative functions are shown in Table 2.
Interestingly, two unigenes (clone ID No. A74 and ID No. 2B03), similar to the genes for
ADP-glucose pyrophosphorylase small subunit (AGPS; GenBank accession No. ACJ86329.1
of the Indica group and GenBank accession No. AK103906 of the Japonica group) and
isoamylase (ISA; GenBank accession No. BAC75533.1 of the Japonica group), respectively,
were found in the carbohydrate transport and metabolism group. Notably, one clone (ID No.
D25) in the group of no related COGs showed a high similarity to WRKY transcription factor
34 (GenBank accession No. NP_001060116.1 of the Japonica group). Further sequence
analysis of the genes for isoamylase and WRKY transcription factor 34 revealed that they are
rice orthologs to barley ISA1 and SUSIBA2, respectively, previously described by Sun et al.
[34,42].
Figure 2 Functional classification of the 116 unigenes from the subtractive libray of
GM077 vs BP034. The classification was based on BLASTX and TBLASTX results (E-value
< 10-5) using the expressed sequence tags (ESTs) of the unigenes. Genes are categorized
using the NCBI KOGnitor COG classification [43]. The number of unigenes in each group is
indicated and their percentage in the total number of unigenes is denoted
Table 2 Functional categories (putative functions) of proteins deduced from the obtained cDNAs (116 unigenes) after subtraction of
waxy rice (GM077) with its wild-type (BP034)
Number of Top-matched molecule Top-matched molecule in
Protein name and/or putative function
e-Value COGs
Clone ID
clones
in Genbank on Blastx Genbank on Blastx (species)
(accession number)
INFORMATION STORAGE AND PROCESSING (13)
[J] Translation, ribosomal structure and biogenesis (3)
D06
1
P49608.1
Cucurbita maxima
Aconitate hydratase, cytoplasmic
7.00E-52 KOG0452
C46
6
ACM79935.1
Populus deltoides
Eukaryotic translation, initiation factor 5A
7.00E-14 KOG3271
2B05
1
NP_001148134.1
Zea mays
Arginyl-tRNA synthetase
7.00E-62 KOG4426
[A] RNA processing and modification (NONE)
[K] Transcription (5)
B34
6
ACG28870.1
Zea mays
Transcription factor BTF3
3.00E-40 KOG2240
E14
2
BAD08114.1
Oryza sativa
Putative SET domain protein SDG117
1.00E-34 KOG1082
A62
8
NP_001054968.1
Oryza sativa
RNA polymerase I-associated factor PAF67
1.00E-39 KOG3677
C11
1
NP_001060344.1
Oryza sativa
Myb-related protein B (B-Myb)
7.00E-86 KOG0048
B30
1
EEE62186.1
Oryza sativa
Hypothetical protein OsJ_16973
7.00E-50 KOG1878
A47
2
EEE62186.1
Oryza sativa
Hypothetical protein OsJ_16973
1.00E-59 KOG1878
[L] Replication, recombination and repair (1)
C54
5
EEE66658.1
Oryza sativa
Hypothetical protein OsJ_23285
3.00E-50 KOG4585
[B] Chromatin structure and dynamics (3)
C41
3
NP_569031.1
Arabidopsis thaliana
Transducin family protein / WD-40 repeat family 1.00E-59 KOG1446
protein
B86
2
NP_001047885.1
Oryza sativa
Nuclear protein SET domain containing protein
7.00E-121 KOG1082
A76
1
CAL54140.1
Ostreococcus tauri
Histones H3 and H4 (ISS)
3.00E-15 KOG1745
CELLULAR PROCESSES AND SIGNALING (21)
[D] Cell cycle control, cell division, chromosome partitioning (2)
D22
1
ABG65960.1
Oryza sativa
PAP/25A associated domain containing protein, 7.00E-17 KOG2277
expressed (Nucleotidyltransferase domain)
D27
1
AAY23369.1
[Y] Nuclear structure (NONE)
[V] Defense mechanisms (NONE)
[T] Signal
transduction
mechanisms (3)
B00
2
NP_194324.2
Oryza sativa
Retinoblastoma-related protein 2
Arabidopsis thaliana
D66
Oryza sativa
Epsin N-terminal homology (ENTH) domain1.00E-08 KOG0251
containing protein
Hypothetical protein(Two-component response
5.00E-35 COG0745
regulator ARR14)
CBL-interacting serine/threonine-protein kinase 15 1.00E-82 KOG0583
1
NP_001056986.1
E43
31
NP_001148041.1
[M] Cell wall/membrane/envelope biogenesis (3)
F70
1
AAO72599.1
Zea mays
E73
1
A21
5
[N] Cell motility (NONE)
[Z] Cytoskeleton (2)
B38
6
AAT80327.1
AAT80327.1
Hordeum vulgare
Hordeum vulgare
NP_563908.1
Arabidopsis thaliana
C80
NP_171697.3
Arabidopsis thaliana
11
Oryza sativa
[W] Extracellular structures (NONE)
[U] Intracellular trafficking, secretion, and vesicular transport (4)
F48
1
ABA95598.1
Oryza sativa
D80
1
ABF95668.1
Oryza sativa
F23
E39
1
1
ACG31280.1
NP_001150650.1
Zea mays
Zea mays
Putative 2-dehydro-3-deoxyphosphooctonate
aldolase
UDP-D-glucuronate decarboxylase
UDP-D-glucuronate decarboxylase
4.00E-35 KOG1010
9.00E-66 COG2877
2.00E-36 KOG1429
3.00E-17 KOG1429
ARK3(ARMADILLO REPEAT KINESIN 3);
1.00E-18 KOG0240
ATP binding/binding/microtubule motor
Armadillo/ß-catenin repeat family protein/kinesin 3.00E-86 KOG0240
motor family protein
Clathrin heavy chain, putative, expressed
Serologically defined breastcancer antigen NYBR-84, putative,expressed
ADP-ribosylation factor 1
Serologically defined breast cancer antigen NYBR-84
5.00E-08 KOG0985
2.00E-69 KOG2667
9.00E-18 KOG0070
6.00E-32 KOG2667
[O] Posttranslational modification, protein turnover, chaperones (7)
B28
1
AAK51086.1
Avicennia marina
A32
1
BAB78487.1
Oryza sativa
Mitochondrial processing peptidase
26S proteasome regulatory particle non-ATPase
subunit8
Polyubiquitin 4 UBQ4
Zn-finger, RING domain containing protein
Peptidyl-prolyl cis-trans isomerase NIMAinteracting 4
ATP-dependent Clp protease ATP-binding subunit
clpX
Pyrrolidone carboxyl peptidase
2.00E-50 KOG0960
1.00E-21 KOG1556
5.00E-61
8.00E-29
2.00E-29
7.00E-95
Zea mays
Aldehyde dehydrogenase
Hydroxypyruvate reductase
HPR; glycerate dehydrogenase/poly(U) binding
Electron transfer flavoprotein- ubiquinone
oxidoreductase, mitochondrial precursor, putative,
expressed
Vacuolar ATP synthase subunit F
Oryza sativa
Gossypium hirsutum
Oryza sativa
Zea mays
Oryza sativa
Hordeum vulgare
Hordeum vulgare
Oryza sativa
Glyceraldehyde-3-phosphate dehydrogenase
Glycosyl hydrolase (sugar binding domain)
Glycosyl hydrolases family 38 protein, expressed
Nucleotide-sugar transporter/ sugar porter
ADP-glucose pyrophosphorylase small subunit
UDP-D-glucuronate decarboxylase
UDP-D-glucuronate decarboxylase
Isoamylase
2.00E-48
6.00E-30
5.00E-48
2.00E-52
0.00E+00
2.00E-36
3.00E-17
7.00E-66
C67
B58
04C04
2
1
1
BAF00213.1
NP_001054802.1
ACG31834.1
Arabidopsis thaliana
Oryza sativa
Zea mays
D56
3
NP_001147507.1
Zea mays
D60
1
NP_001149461.1
METABOLISM (23)
[C] Energy production and conversion (5)
D01
10
AF162665_1
E05
3
BAB44155.1
C01
1
NP_176968.1
D14
25
ABB47885.1
Zea mays
D33
2
NP_001149476.1
[G] Carbohydrate transport and metabolism (8)
F66
1
AAA82047.1
A15
1
AAO27794.1
E47
22
ABG22500.1
A64
1
ACG45298.1
A74
1
ACJ86329.1
E73
1
AAT80327.1
A21
5
AAT80327.1
2B03
1
BAC75533.1
Oryza sativa
Bruguiera, gymnorhiza
Arabidopsis, thaliana
Oryza sativa
5.00E-31 KOG0001
5.00E-57 KOG0800
7.00E-38 KOG3258
8.00E-08 KOG0745
9.00E-44 KOG4755
KOG2450
KOG0069
KOG0069
KOG2415
2.00E-25 KOG3432
KOG0657
KOG2230
KOG1959
KOG2234
COG0448
KOG1429
KOG1429
GKOG0470
[E] Amino acid
transport and
metabolism (3)
E28
1
P37833.1
Oryza sativa
E42
5
ACG39804.1
Zea mays
F16
1
NP_001147070.1
Zea mays
[F] Nucleotide transport and metabolism (NONE)
[H] Coenzyme transport and metabolism (1)
F89
1
ACG34051.1
Zea mays
[I] Lipid transport and metabolism (NONE)
[P] Inorganic ion transport and metabolism (2)
F76
1
AAP31024.1
Oryza sativa
04F04
1
NP_001149686.1
Zea mays
[Q] Secondary metabolites biosynthesis, transport and catabolism (4)
D58
56
AAB19117.1
Oryza sativa
A41
1
NP_176471.1
Arabidopsis thaliana
E72
9
ACM17649.1
C77
4
BAE00046.1
POORLY CHARACTERIZED (9)
[R] General function prediction only (6)
C74
1
BAB69445.1
A46
2
BAD82577.1
D20
1
BAD11341.1
Oryza rufipogon
Oryza sativa
F31
C50
1
8
ABC94598.1
NP_001043287.1
Oryza sativa
Oryza sativa
D53
1
EEE55043.1
Oryza sativa
Oryza sativa
Oryza sativa
Oryza sativa
Aspartate aminotransferase, cytoplasmic
Histidinol-phosphate aminotransferase
Nicalin
4.00E-23 KOG1411
2.00E-76 KOG0633
4.00E-16 KOG2526
Farnesyl pyrophosphate synthetase
5.00E-07 KOG0711
Zinc transporter
Carbonic anhydrase
7.00E-31 KOG1482
3.00E-13 KOG1578
Class III ADH enzyme
LDL1 (LSD1-LIKE1); amine oxidase/ electron
carrier/oxidoreductase
Alcohol dehydrogenase family-2
Alcohol dehydrogenase
2.00E-98 KOG0022
1.00E-38 KOG0029
Hypothetical protein
PHD finger protein-like
BRI1-KD interacting protein 113 (RNA
recognition motif)
NBS-LRR type R protein, Nbs2-Pi2
Zn-finger-like, PHD finger domain containing
protein
Hypothetical protein OsJ_02730
4.00E-19 KOG1901
8.00E-13 KOG1246
1.00E-51 KOG0118
3.00E-25 KOG0022
4.00E-140 KOG0022
1.00E-80 KOG0619
4.00E-79 KOG1246
1.00E-114 KOG0431
D42
3
EEE55043.1
[S] Function unknown (2)
F54
1
NP_568713.1
C18
1
NP_001147117.1
NO RELATED COG (3 BeTs) (26)
A44
11
BAD11344.1
Oryza sativa
Hypothetical protein
8.00E-93 KOG0431
Arabidopsis thaliana
Zea mays
Emb1879 (embryo defective 1879)
Nucleotide binding protein (WD40 domain)
3.00E-47 KOG4249
8.00E-32 KOG0772
Oryza sativa
BRI1-KD interacting protein 116
C21
C27
F81
F15
2
1
1
1
ACN85167.1
ABA95230.1
Q01881.2
AAP54389.2
Oryza nivara
Oryza sativa
Oryza sativa
Oryza sativa
F32
A07
F39
A43
E29
C62
C35
B45
C48
D54
D79
D25
04C03
2B02
E36
B11
C25
1
2
1
1
21
3
9
1
1
2
1
1
2
1
2
10
1
NP_001052330.1
NP_001054936.1
NP_001058150.1
NP_001066171.1
EAZ06308.1
ABR25963.1
ACA04850.1
EEC77808.1
EEC81525.1
EEE68920.1
NP_001149805.1
NP_001060116.1
BAH91806.1
EAZ06308.1
CAA59142.1
AAK13589.1
CAA38212.1
Oryza sativa
Oryza sativa
Oryza sativa
Oryza sativa
Oryza sativa
Oryza sativa
Picea abies
Oryza sativa
Oryza sativa
Oryza sativa
Zea mays
Oryza sativa
Oryza sativa
Oryza sativa
Oryza sativa
Oryza sativa
Oryza sativa
3.00E-36 NO
RELATED
MYB-CC type transfactor
5.00E-66
Retrotransposon protein, putative
9.00E-17
Seed allergenic protein RA5
3.00E-08
Ulp1 protease family, C-terminal catalytic domain 7.00E-14
containing protein
Hypothetical protein
7.00E-10
Hypothetical protein
1.00E-07
Hypothetical protein
1.00E-41
Conserved hypothetical protein
4.00E-07
Hypothetical protein OsI_28542
8.00E-81
DnaJ heat shock protein
1.00E-12
Senescence-associated protein
8.00E-37
Hypothetical protein OsI_16996
5.00E-04
Hypothetical protein OsI_24919
1.00E-09
Hypothetical protein OsJ_27784
2.00E-100
CUE domain containing protein
4.00E-06
WRKY transcription factor 34
2.00E-72
Conserved hypothetical protein
1.00E-04
Hypothetical protein OsI_28542
5.00E-54
Prolamin
4.00E-31
rRNA intron-encoded homing endonuclease
4.00E-27
Glutelin
7.00E-49
A55
B53
F77
1
2
1
AAM92796.1
NP_001055525.1
EEE63701.1
D23
1
BAD38184.1
NO SIMILARITY FOUND (BLAST) (26)
Oryza sativa
Oryza sativa
Oryza sativa
Oryza sativa
Gypothetical protein
Ubiquitin-associated domain containing protein
Hypothetical protein OsJ_18519 (Ubiquitin
Associated domain)
C2 domain-containing protein-like
8.00E-37
9.00E-54
4.00E-65
3.00E-86
Validation of the SHH results by semi-quantitative PCR
To verify the conclusions from the SHH experiment, we selected two housekeeping genes,
the gene for the eukaryotic elongation factor-1 α subunit (eEF-1 α) and UBQ5, to follow the
SSH experiment by semi-quantitative PCR. When we used the same batch of RNA as in the
SHH experiment, or RNA isolated from other stages of seed development, or from other
tissues, we found expression levels of the two housekeeping genes to be more or less the
same in GM077 and BP034. Furthermore, expression levels were constant throughout seed
development and in different tissues of mutant and wild-type rice (Figure 3A, B).
Importantly, we observed that the cDNA for eEF-1 α could be detected in the tester (GM077)
and driver (BP034) samples prior to SSH, but not in the sample after subtraction
hybridization (Figure 3C), lending support to the validity of the SSH approach. We also
chose some additional genes, related to starch biosynthesis and carbon portioning (Materials
and Methods) to further verify the reliability of the SHH experiment and to obtain detailed
quantitative data on gene expression in the two rice lines. Results from those analyses are
presented below.
Figure 3 Validation of the suppression subtractive hybridization (SSH) results by semiquantitative RT-PCR. (A) Semi-quantitative RT-PCR analysis of eEF-1α on the same RNA
samples from BP034 and GM077 as used in the SHH experiment, i.e., RNA from seeds of 12
day after flowering (Se12), and samples from the same time point for leaves (L12), roots
(R12), and stems (St12). (B) Semi-quantitative RT-PCR analysis of UBQ5 on RNA samples
as in the SHH experiment (Se12), and for seeds from 3, 6, 18 and 24 day after flowering, and
for leaves (L12), roots (R12), and Stems (St12), respectively. (C) Semi-quantitative RT-PCR
analysis of cDNA levels of eEF-1α before and after subtractive hybridization
Gene expression profiling in the waxy mutant
To further validate the results from the SHH experiment and to quantify expression of genes
involved in starch biosynthesis and/or carbon portioning, we chose 19 genes as
representatives for gene expression analysis by qPCR, including two reference genes, eEF-1
α and UBQ5 (Additional file 5). According to the results obtained by qPCR, we divided the
genes into five groups (Figure 4; Table 3). The classification was based on qPCR
quantification of the differential gene expression in GM077; “significantly decreased” (P <
0.01), “not changed” (P > 0.05), “increased” (P < 0.05), “significantly increased” (P < 0.01)
and “not detected”. Intriguingly, among the four significantly increased genes, AGPS, SBEI,
ISA1 and SUSIBA2-like, all except SBEI were found in the SHH library. We noted that the
expression level for the upregulated genes in GM077 correlated well with the expression
level for the SUSIBA2-like transcription factor gene (Figure 4).
Figure 4 qPCR analytic results of gene expression levels for 13 detectable genes
potentially involved in carbon portioning between starch and other carbohydrates.
Biological triplets (seeds of 12 days after flowering from three different plants) and technical
triplets were performed. The difference between BP034 and GM077 was analyzed
statistically by the ANOVA test and presented as “increased” (*P < 0.05) and “significantly
increased” (**P < 0.01) between the two rice cultivars. Error bars are as indicated. AGP
(gene for ADP-glucose pyrophosphorylase), UGP (gene for UDP-glucose
pyrophosphorylase), SS (gene for starch synthase), SUS (gene for sucrose synthase), BE (gene
for branching enzyme), ISA (gene for isoamylase), SUSIBA2-like (gene for sugar signaling in
barley 2 - like)
Table 3 Category of 19 genes with different expression levels detected by qPCR in waxy
rice (GM077) and wild type (BP034)
Gene expression level (waxy/wt, or
Gene name GenBank Accession No.
GM077/BP034)
Significantly decreased (P < 0.01)
GBSSI
X62134
No change (P > 0.05)
BEIIa
AB023498
SUS1
OsJNBa0090P23.3
SUS2
NM_001063582.1
SUS3
L03366.1
SUS6
OJ1149_C12-2
UBQ5
AK061988
eEF-1α
AK061464
Increased (P < 0.05)
GBSSII
AY069940
SSI
D16202
BEIIb
D16201
SUS4
NM_001056599.1
UGP1
DQ395328.1
Significantly increased (P < 0.01)
AGPS
AK103906
BEI
D11082
ISA1
AB015615
SUSIBA2- AK121838
like
Not detected
UGP2
AF249880.1
SUS5/7
OsJNBa0033H08.16/
OsJNBb0026I12.4
Gene expression correlation of SUSIBA2-like and ISA1 in the mutant and wild
type
Sun et al. [33,34] have demonstrated that ISA1 and SBEIIb in barley were upregulated by the
activity of the SUSIBA2 transcription factor and a good correlation in gene expression levels
has been demonstrated between SUSIBA2 and its target genes, such as ISA1 and SBEIIb
[33,34,44]. To learn if this correlation holds true in rice also, and in an effort to find
SUSIBA2-like-controlled genes in rice, we selected rice ISA1 as a representative to study the
correlation in expression between SUSIBA2-like and its target genes in rice. For this study,
we chose different tissues and different time points in both the mutant GM077 and the wild
type BP034. As displayed in Figure 5A and B, there was an excellent correlation between
expression levels for the two genes in the analyzed samples. The statistical analysis (Figure
5C) indicated that the relative levels of the spatial and temporal expression for the two genes
in both rice lines shared a Pearson correlation coefficient (r) of 0.90 (P < 0.01).
Figure 5 qPCR analysis of correlation between ISA1 and SUSIBA2-like in gene
expression in BP034 and GM077. (A) Spatial and temporal expression levels of ISA1 and
SUSIBA2-like in the BP034 rice. (B) Spatial and temporal expression levels of ISA1 and
SUSIBA2-like in the GM077 rice. (C) Plots of corresponding expression levels of ISA1 and
SUSIBA2-like in both BP034 and GM077. Statistical analysis indicated the correlation to be
extremely significant (P < 0.01) between both ISA1 and SUSIBA2-like with 0.90 of Pearson
correlation coefficient (r). daf (days after flowering)
Discussion
Although waxy mutants of higher plants and the responsible gene (GBSSI) have been studied
to a large extent, and the high content of amylopectin in the mutant is known [39,45-53], little
information about carbon partitioning to other carbohydrates and oil fractions in waxy
mutants has been reported. Moreover, gene regulation of carbon reallocation to amylopectin
in the mutant is poorly understood. We are interested in the partitioning of photosynthates
between starch and other storage compounds in cereal seeds. In this study, we selected one of
the rice waxy mutants to follow carbon partitioning between starch and other carbohydrates
when amylose biosynthesis is impeded. Our carbohydrate analysis indicated that when the
amylose content is reduced, the vast majority of the assimilated carbon is reallocated to
amylopectin, rather than to other carbohydrates or lipids. Interestingly, such a reallocation did
not change seed weight but, rather, shifted carbon from one compound (amylose) to another
(amylopectin) within the starch biosynthesis machinery.
To understand the molecular mechanisms controlling the increase in amylopectin
biosynthesis, we set out to identify genes that were upregulated in the waxy mutant. From the
SHH experiments we found three candidates that have previously been shown to be directly
involved in starch synthesis and/or its regulation, AGP [54], ISA1 [55], and SUSIBA2-like
[34]. The functions and regulation of AGPase and isoamylase have been reviewed and well
documented previously [27,45,56-59]. In cereal endosperm cells, there are two forms of
AGPase, one cytosolic and one plastidic. The major fraction of ADP-glucose in cereal
endosperm is believed to be produced in the cytosol and then transported to the amyloplast
for subsequent starch biosynthesis. Isoamylase is suggested to play an important role in
amylopectin biosynthesis and starch granule formation [45,56-58]. Both AGPase (cytosolic
form) and ISA1 have been demonstrated as important players in amylopectin synthesis and
starch granule formation in rice [55]. Our qPCR results indicate that AGPase S (cytosolic
form) [60] and ISA1 are instrumental for the accumulation of additional amylopectin in the
amylose–reduced mutant GM077. In the SHH experiment, we could not confirm that the
identified AGPS corresponded to the cytosolic enzyme as the unigene sequence did not cover
the transit peptide sequence region. However, our qPCR analysis of both cytosolic (Figure 4)
and plastidic (not shown) forms according to Ohdan et al. [60] indicated that clone ID No. 74
should be the cytosolic form.
The mechanism behind the elevated expression of AGP and ISA1 in the rice mutant remains
unclear. One possibility for the enhanced AGP activity could be that the total amount of
AGPase needs to be increased to provide ample supply of ADP-glucose when more plastidic
AGPase is being recruited to multienzyme complexes for the regulation of carbon
partitioning [61]. Another possibility is that the extra AGPase is required in GM077 to
convert Glc1-P to ADP-glucose in the cytosol (see also below). Since ISA1 is generally
accepted as an important player in amylopectin synthesis and granule formation [45,56-58], it
is not surprising that the ISA1 expression in GM077 significantly increased when extra
amylopectin was produced in the endosperm.
We also observed that the genes for sucrose synthase 4 and UDPase 1 were upregulated in
GM077. Since accumulation of other carbohydrates synthesized from the UDP-glucose
precursor, such as cellulose and β-glucan, were unaffected in the mutant, we suggest that the
increased expression of the genes for sucrose synthase 4 and UDPase 1 may be also
associated with amylopectin synthesis. Sucrose synthase 4 is suggested to be cytosolic [23]
and may produce UDP-glucose, which is converted by UDPase 1 to the hexose-phosphate
used for amylopectin synthesis [16]. Indeed, sucrose synthases 2 and 3 in Arabidopsis, which
belong to the same group as rice sucrose synthase 4 [23], have been recently reported to
direct carbon to starch synthesis [62]. In our experiment, the elevated expression of cytosolic
AGP supports that notion. Enhanced levels of AGPase may be needed to convert the Glc 1-P
produced by sucrose synthase 4 and UDPase 1 to ADP-glucose for additional amylopectin
synthesis. For other forms of sucrose synthases and for UDPase 2, we did not find any
significant shifts in gene expression between GM077 and BP034.
This study is centered on carbon partitioning and gene regulation in seeds of a waxy rice
mutant. Our results provide no information about how carbon partitioning is regulated at the
level of enzyme activity. Lü et al. [46] used transgenic rice with antisense inhibition of
GBSSI to examine the activities of major starch synthesis enzymes. Some of the phenotypic
traits observed by Lü et al. in the GMO rice were similar to what we found for the GM077
mutant, such as no changes in seed weight and only small changes in total starch content. In
accordance with our gene expression analysis, they also noticed an increase in isoamylase
activities. However, they did not observe any changes in activities for AGPase or SBEs,
which seems to disagree with our results at the gene activity level. We do not yet know the
reason for this disparity between gene expression and enzyme activity but it should be noted
that the levels of transcripts and proteins in a cell are determined by several factors, like the
rate of transcription initiation, mRNA stability, efficiency of translation, and protein stability
and modifications.
Our knowledge about gene regulation and the involvement of putative transcription factors in
carbon partitioning is poor. Sun et al. [34,35] reported that the barley SUSIBA2 transcription
factor participates in sugar signaling in barley and that it upregulates target genes by binding
to the SURE-element (with an A/T rich region and a putative AAAA core) within the
promoter region [34,63]. They suggested that the SURE-element(s) in promoter regions of
sugar-inducible genes may play an important role in SUSIBA2-controlled gene expression.
Interestingly, when we searched the promoter region of the nine upregulated genes in
GM077, including the rice SUSIBA2-like, we found a number of putative SURE elements in
all of the genes (Additional file 6). A very good correlation at the gene expression level was
found for SUSIBA2-like and ISA1. We suggest that upregulation of ISA1 and other genes in
the GM077 mutant is mediated by the SUSIBA2-like transcription factor. This notion is
further corroborated by recent transgenic studies in rice (Hu et al. unpublished). Interestingly,
when we performed a bioinformatic analysis on the gene expression patterns of the three
selected genes (SUSIBA2-like, ISA1 and AGPS) from the SSH experiment in this study using
the publicly available rice and Arabidopsis microarray data, we found some correlations
between SUSIBA2-like and the other genes (Additional file 7). However, ISA1 is expressed in
Arabidopsis leaves but not in rice leaves and the expression level of SUSIBA2-like is
generally low in both species for reasons we do not know. Since SUSIBA2-like is a
transcription factor, its gene expression level should be low. What caused the differential
expression of ISA1 in the two species is unclear. In vitro and in vivo protein-DNA interaction
studies are under way to further determine the involvement of SUSIBA2-like and SURE
elements in the regulation of starch biosynthesis in the rice endosperm.
In addition to their high value as starch crops, there is an increasing interest in using cereals
for the production of non-starch compounds, such as β-glucan and fructan for functional
foods, and oil for biofuel applications [9,10,17]. Our experimental data implicate three genes
of importance for amylopectin synthesis in the rice endosperm, AGP, ISA1, and SUSIBA2like. Since AGPS and SUSIBA2-like likely control the entire metabolic pathway for starch
synthesis in cereals, we believe they are good targets for redirecting carbon flux from starch
biosynthesis to alternative products. In fact, approaches to downregulate AGPS in
Arabidopsis to enhance oil production at the expense of starch biosynthesis met with success
[18]. It will be interesting to explore the potential for modulating SUSIBA2 activity as a
strategy for rerouting photosynthate from starch biosynthesis to other anabolic pathways in
cereal seeds.
Conclusion
Understanding of carbon allocation in cereal seeds is of great importance in plant biology. In
this study we used a rice waxy mutant to gain molecular insights into how amylose
deficiency affects carbon allocation in cereal seeds. Analysis of carbohydrate and oil
fractions in the waxy mutant showed that when amylose is deficient, carbon is mainly
allocated to amylopectin rather than to other carbon end products, such as β-glucan or oil.
Gene expression profiling identified several candidate genes implicated in the carbon
reallocation response. These genes included AGP and SUSIBA2-like. We suggest that these
two genes are promising targets in efforts to redirect carbon flux in cereal seeds from starch
biosynthesis to alternative carbon end products. To our knowledge, this study is the first
comparative analysis of carbon fractions and gene expression profiling on a global scale in a
waxy mutant.
Methods
Plant materials and growth
Rice seeds of the BP034 and GM077 cultivars were obtained from the waxy rice-breeding
program at the Institute of Nuclear Agricultural Sciences, Zhejiang University, China. The
GM077 mutant was originally generated by γ-irradiation in the waxy rice-breeding program
[36-38, Bao et al. unpublished]. It has been developed to a nearly isogenic background
through many years of breeding. The rice plants were field-grown on the campus farm at
Zhejiang University. Individual tillers were labeled at flowering. Seed samples were
harvested on day 3, 6, 12, 18 and 24 after flowering, respectively. At least 6 panicles from
different individuals of BP034 or GM077 were sampled at each time point. At the same time
points (day 3, 6, 12, 18 and 24 after flowering), the leaves, stems and roots of the
corresponding rice plants were harvested. The harvested tissues were immediately frozen in
liquid nitrogen and kept at -80 °C until use.
Carbohydrate analyses
Mature and dry seeds were prepared as described previously [44,64,65]. Iodine staining and
spectrophotometer scanning were performed as described by Sun et al. [35]. Total starch and
amylose contents were pre-analyzed as described by Sun et al. [35]. Dietary fiber components
were analyzed with the Uppsala method [66] and fructan (including fructooligosaccharides)
as described by Rakha et al. [67]. Total dietary fiber was calculated as the sum of fiber
components analyzed with the Uppsala method and fructan. The mixed-linkage β-glucan
content was analyzed as described by McCleary and Codd [64], the starch content as
described by Santacruz et al. [68] and the amylose content as described by Chrastil [69]. The
arabinoxylan content was calculated as the sum of arabinose and xylose residues determined
by the Uppsala method, the cellulose content as the difference between glucose residues
determined by the Uppsala method and the mixed-linkage β-glucan content, and the
amylopectin content as the difference between the starch and amylose contents. Free Glc and
Suc were analyzed according to Bergmeyer et al. [70] and Bernt and Bergmeyer [71],
respectively. The crude oil content was determined according to the European standard
method [72].
Oligonucleotides
Oligonucleotides used in the experiments for qPCR, semi-quantitative PCR, and SHH are
listed in Additional file 5. Nineteen representative genes were selected including the two
reference genes eEF-1α and UBQ5. The oligonucleotides were purchased from Invitrogen
(Carlsbad, CA, USA).
RNA isolation
Total RNA was isolated according to the protocol described previously [34,35].
Quantitative PCR (qPCR) and semi-quantitative PCR
qPCR and semi-quantitative PCR were performed as described previously [34,73]. The
SYBR Green Master Mix and cDNA synthesis kit were purchased from Toyobo (Osaka,
Japan) and Promega (Madison, WI, USA), respectively. A real-time PCR machine, iQ5 from
Bio-Rad (Hercules, CA, USA), was used for qPCR and a PCR thermo cycler, MJ Research
PTC-200 (GMI, Ramsey, MN, USA), was used for semi-quantitative PCR. The rice genes of
eEF-1α and UBQ5 were used as endogenous references for data normalization [74] in qPCR.
The relative transcript level was calculated by the method of 2-∆Ct [74].
Construction of a cDNA subtractive library of GM077 vs BP034
The cDNA subtractive library of GM077 vs BP034 was constructed using the SSH technique
[75]. Total RNA of GM077 from seeds at 12 daf was used as the tester and the corresponding
sample of BP034 as the driver. The protocol in Dai et al. [76] was followed with the
following modifications: i) Transcripts were enriched by in vitro transcription; and ii)
Duplex-specific nuclease (DSN)-mediated normalization and subtraction were used. The
procedure is outlined in Additional file 8, and all linkers, adapters and PCR primers are listed
in Additional file 5. PCR products generated by SHH were digested by SalI and cloned in the
pUC19 vector. Recombinant plasmids were used to transform Escherichia coli DH5α.
Transformed bacteria were applied to LB plates containing 50 µg ml-1 ampicillin for selection
and 40 µg ml-1 X-gal for detection of α-complementation [77]. White and positive colonies
were picked for colony PCR screening to check inserts. Positive colonies with inserts were
propagated. Plasmids were isolated and sequenced at Beijing Genomics Institute (BGI,
Beijing, China) using the M13 forward and reverse primers. The eEF-1α gene was used to
monitor efficiency of the suppression subtractive hybridization by semi-quantitative PCR.
Bioinformatics and statistical analysis
The obtained sequences were edited by the DNAstar® software (Madison, WI, USA).
Unigene sequences were used for BLASTX and TBLASTX searches against the protein
database (http://blast.ncbi.nlm.nih.gov/). The retrieved proteins with high sequence
similarities (E-value < 10-5) were categorized using the NCBI KOGnitor COG classification
(http://www.ncbi.nlm.nih.gov/COG) based on the method of Tatusov et al. [43]. The ciselement analysis of gene promoters was performed using the BioEdit software (Carlsbad, CA,
US). The significance of differences in obtained data was tested by ANOVA (analysis of
variance) with a threshold P-value of 0.05 (http://www.ats.ucla.edu/stat/). Publicly available
microarray data for rice (http://ricexpro.dna.affrc.go.jp) and for Arabidopsis
(http://www.weigelworld.org/resources/microarray/AtGenExpress)
were
used
for
bioinformatics analyses of gene expression patterns of SUSIBA2-like, ISA1 and AGPS.
Competing interests
The authors declare that they have no competing interests.
Authors’ contributions
M-ZZ and J-HF did the experiments of SSH, semi-quantitative and qPCR, starch pre-analysis
and bioinformatics analysis. XY carried out statistical and promoter analysis, and partial
bioinformatics analysis. JL did partially the experiment of qPCR. J-SB did the breeding work
in many years to generate the nearly isogenic waxy mutant, GM077. GF performed the
carbohydrate and oil analysis. RA, CJ and PÅ were involved in the carbohydrate and oil
analysis and in revising the manuscript. CS contributed to the experimental design,
coordination of the study, drafting the manuscript and interpreting the results. All authors
read and approved the final manuscript.
Acknowledgements
This work was funded by the following organizations and foundations:
• The SLU Lärosätesansökan Program (TC4F) for Team 4 supported by Vinnova.
• The SLU program BarleyFunFood.
• The Natural Science Foundation Program (Y3090617, Y304463) supported by Zhejiang
Province, China.
• The Swedish Research Council for Environment, Agricultural Sciences and Spatial
Planning (Formas) under the Strategic Research Area for the TCBB Program.
• The Joint Formas/Sida-funded program on sustainable development in developing
countries.
• The Swedish International Development Cooperation Agency (Sida/SAREC).
• The Carl Trygger Foundation.
• The Swedish Farmers’ Foundation (SLF).
• In part by the U.S. Department of Energy Contract DEAC02-05CH11231 with Lawrence
Berkeley National Laboratory.
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Additional files
Additional_file_1 as DOCX
Additional file 1 Phenotypic traits of BP034 and GM077
Additional_file_2 as JPEG
Additional file 2 Absorbance spectra of the iodine-stained starch samples from BP034 and
GM077. Starch standard samples with known amylose contents are included in the spectra.
ST (standard), AC (amylose content). The iodine-staining was performed as described
previously [35]
Additional_file_3 as DOCX
Additional file 3 Content of carbohydrates, Klason lignin and oil in BP034 and GM077
Additional_file_4 as DOCX
Additional file 4 Functional categories in Clusters of Orthologous Groups (COGs) for
proteins deduced from the obtained cDNAs after subtraction of GM077 (tester) with BP034
(driver)
Additional_file_5 as DOCX
Additional file 5 Oligonucleotides
Additional_file_6 as DOCX
Additional file 6 Putative SURE-elements in promoter regions of the upregulated genes
indentified in GM077. GenBank accession number for each gene is listed in Table 3. The
putative SURE-element sequence (in green) was based on Sun et al. [34] & Grierson et al.
[63]. The nucleotide position is relative to translation initiate site (the ATG codon). GBSS
(gene for granule-bound starch synthase), AGP (gene for ADP-glucose pyrophosphorylase),
SS (gene for starch synthase), BE (gene for branching enzyme), ISA (gene for isoamylase),
SUSIBA2-like (gene for sugar signaling in barley 2-like), UGP (gene for UDP-glucose
pyrophosphorylase), SUS (gene for sucrose synthase)
Additional_file_7 as JPEG
Additional file 7 Gene expression profiling of three selected genes (SUSIBA2-like, ISA1 and
AGPS) from the SSH experiment during plant development of rice and Arabidopsis. The
microarray data from two publicly available websites was used for rice
(http://ricexpro.dna.affrc.go.jp) and Arabidopsis
(http://www.weigelworld.org/resources/microarray/AtGenExpress), respectively. (A) Rice
SUSIBA2-like (GenBank Ac No. AK121838). (B) Arabidopsis WRKY20 (a homologue of
SUSIBA2, GenBank Ac No. NM_11898). (C) Rice ISA1 (GenBank Ac No. AB015615). (D)
Arabidopsis ISA1 (GenBank Ac No. NM_128551). (E) Rice AGPS (GenBank Ac No.
AK103906). (F) Arabidopsis AGPS (GenBank Ac No. NM_124205)
Additional_file_8 as JPEG
Additional file 8 A flow chart of DSN-mediated (duplex-specific nuclease) suppression
subtractive hybridization (SSH). A small amount of RNA samples from tester (GM077) and
driver (BP034) was used for template-switching cDNA synthesis and step-out PCR
amplification [78]. SP6 and T7 RNA polymerases were then employed to generate sufficient
tester and driver transcripts, respectively. After a secondary reverse transcription and RNA
digestion, the tester cDNAs were subjected to an excess amount of driver RNA for
hybridization. Hybridization was performed by denaturation and ressociation. cDNAs in
hybrids with RNA were digested by duplex-specific nuclease. The left-over single-stranded
cDNAs from hybridization were only the temples for exponential PCR amplification to
generate cDNA fragments for construction of a cDNA library. Tsp (template-switching
primer), 3´ap (adaptor primer), PI (primer I)
Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
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