- Research article
- Open Access
Expression of genes associated with carbohydrate metabolism in cotton stems and roots
© Taliercio et al; licensee BioMed Central Ltd. 2009
- Received: 08 August 2008
- Accepted: 22 January 2009
- Published: 22 January 2009
Cotton (Gossypium hirsutum L) is an important crop worldwide that provides fiber for the textile industry. Cotton is a perennial plant that stores starch in stems and roots to provide carbohydrates for growth in subsequent seasons. Domesticated cotton makes these reserves available to developing seeds which impacts seed yield. The goals of these analyses were to identify genes and physiological pathways that establish cotton stems and roots as physiological sinks and investigate the role these pathways play in cotton development during seed set.
Analysis of field-grown cotton plants indicated that starch levels peaked about the time of first anthesis and then declined similar to reports in greenhouse-grown cotton plants. Starch accumulated along the length of the stem and the shape and size of the starch grains from stems were easily distinguished from transient starch. Microarray analyses compared gene expression in tissues containing low levels of starch with tissues rapidly accumulating starch. Statistical analysis of differentially expressed genes indicated increased expression among genes associated with starch synthesis, starch degradation, hexose metabolism, raffinose synthesis and trehalose synthesis. The anticipated changes in these sugars were largely confirmed by measuring soluble sugars in selected tissues.
In domesticated cotton starch stored prior to flowering was available to support seed production. Starch accumulation observed in young field-grown plants was not observed in greenhouse grown plants. A suite of genes associated with starch biosynthesis was identified. The pathway for starch utilization after flowering was associated with an increase in expression of a glucan water dikinase gene as has been implicated in utilization of transient starch. Changes in raffinose levels and levels of expression of genes controlling trehalose and raffinose biosynthesis were also observed in vegetative cotton tissues as plants age.
- Cotton Plant
- Starch Accumulation
- Starch Degradation
- Starch Biosynthesis
Cotton (Gossypium hirsutum L) is an important source of fiber for the textile industry. Cotton is a perennial plant that is grown as an annual row crop in much of the world. As a perennial, cotton plants naturally make provisions for growth in the next season by storing starch in stems and roots. Availability of stored starch to support seed and fiber development may impact yield. Additionally, fibers are elongated ovular trichomes that are sites of cellulose deposition which also require photoassimilate from leaves to provide the glucose (GLC) subunits to make cellulose . At peak productivity, leaves subtending developing bolls export up to 33% of photoassimilate to vegetative parts of the plant and up to 28% of carbon needed to complete boll maturation comes from previously assimilated sources . At the whole plant level a large portion of reproductive development occurs after canopy photosynthesis declines . In fact, part of the photosynthetic apparatus appears to be sacrificed to provide nitrogen for developing bolls .
There are no annual species of cotton to help breed truly annual cotton cultivars although current cultivars have been "annualized" to make them better adapted for agriculture. For example flowering of wild cotton is sensitive to day length but flowering of cultivated cotton is largely insensitive to day length. In studies of greenhouse grown cotton plants, levels of starch in stems and roots of cultivated cotton peaked at about 90 days post emergence then dropped . Levels of starch in stems and roots of wild cotton remained high throughout the same period of development. One interpretation of the difference in starch levels between cultivated and wild cotton is that part of the "annualization" of cultivated cotton involved the redistribution of a portion of stored starch to reproductive sinks. Similar levels of starch stored in stems and roots of antique and modern cotton cultivars indicated that redistribution of these reserves may not be subject to selection in breeding programs and therefore not optimized for crop production . Cotton plants produce many more flowers than develop into productive bolls demonstrating that cotton plants have untapped potential to set more bolls [6, 7]. It would be desirable to redirect photoassimilate from unproductive starch reserves to boll development because stored reserves not made available to reproductive tissues are wasted when cotton is grown as an annual crop.
Previous statistical analyses of expressed sequenced tags (ESTs) isolated from cotton stems identified increased expressions of genes associated with lignin and starch biosynthesis consistent with starch and lignin production in the tissues investigated . Our goal was to identify genes and physiological pathways that establish cotton stems and roots as physiological sinks and investigate the role of these pathways in cotton development during seed set. We compare the expression of over 11,000 genes between stems and roots before and after they begin to store starch. Expression data are validated using quantitative-PCR (qPCR) and the physiological impact of altered gene expression is largely confirmed by measuring carbohydrate levels during relevant period of development.
6.69 (0.180) b
5.29 (0.166) c
5.77 (0.174) c
4.53 (0.192) d
8.26 (0.201) a
3.62 (0.158) e
Microarray analysis of RNA from cotton stems and roots
Differentially Expressed Genes
UDPglucose 4-epimerase-like protein
starch branching enzyme I
granule-bound starch synthase Ib precursor
1802404A starch phosphorylase
ADP-glucose pyrophosphorylase large subunit
starch branching enzyme
putative raffinose synthase
starch synthase II precursor
trehalose-6-phosphate phosphatase, putative
putative sucrose transporter [Vitis vinifera]
putative sugar transporter
sucrose phosphate phosphatase
putative trehalose 6-phosphate synthase
putative trehalose-6-phosphate phosphatase
putative trehalose-6-phosphate synthase
putative hexose transporter protein
glucan water dikinase (Starch-related R1 protein)
starch synthase II-2 precursor
ribosomal protein S3
Expression of genes associated with starch metabolism
Many genes associated with starch biosynthesis were up-regulated as starch accumulated, consistent with the starch increase observed in these tissues (Table 2). These include ADPglucose-pyrophosphorylase (ADPGp, EC .22.214.171.124), a variety of starch synthases and starch branching enzymes. Quantitative PCR confirmed a nearly ten-fold increase in the level of transcript encoding the large subunit of ADPGp between -4 W and -2 W and a subsequent significant drop in expression in cotton roots (Fig. 2). We wanted to determine the probable subcellular localization of some of the genes associated with starch metabolism but many of the gene models represented on this microarray lacked completed coding regions. Therefore the best annotated cognate for which a complete coding strand was available was analyzed in-silico for localization to the plastid (Table 2). Most had a high probability of plastid localization. The exceptions were the ADPGp large subunit and one of the starch phosphorylases.
Analysis of sucrose (SUC), GLC and fructose (FRC) metabolism
SUC is used to transport carbon from source tissues to the sink tissues in most plants. Multiple sugar transporters appear to be differentially regulated in starch accumulating tissues (Table 2). Multiple invertases that cleave SUC to form GLC and FRC and an invertase inhibitor are up-regulated in starch accumulating tissues. The only enzyme that synthesizes SUC, sucrose phosphate synthase did not appear to be differentially regulated. An increase in an SPP transcript that appeared to be differentially expressed on the microarrays fell just below the two-fold cut-off for designating a gene as differentially expressed using qPCR (Fig. 2).
Analysis of expression of genes encoding GLC metabolizing enzymes identified several relevant genes that increased in expression in starch accumulating stems and roots. Multiple genes encoding phosphoglucomutase (EC .126.96.36.199) increased in expression in starch-storing stems (Fig. 2). This pattern of expression was confirmed for one of the genes by qPCR. The qPCR analysis also indicated that the mRNA level of two of these genes dropped in later stages of stem development.
Measurement of Soluble Sugars
0 week stem
2 week stem
4 week stem
6 week stem
-2 week root
0 week root
2 week root
4 week root
6 week root
Metabolism of other carbohydrates
Genes associated with raffinose (RAF) and trehalose (TRE) biosynthesis increased in starch accumulating tissues (Table 2). Differential expression of two trehalose phosphate synthases (EC .188.8.131.52) was confirmed by qPCR. Trehalose (α-D-glucopyranosyl-1,1-α-D-glucopyranoside) is a disaccharide of two GLC . RAF (α-1,6-galactosyl-SUC) is a GAL linked to a SUC [12, 13]. The raffinose family of oligosaccharides (RFO) includes stachyose and verbascose in which 2 or 3 galactose molecules are linked to SUC, respectively. There was an increase in genes potentially participating in the metabolism of RFO, including UDP-glucose/galactose 4-epimerase (EC .184.108.40.206), galactinol synthase (EC .220.127.116.11) and α-galactosidase (EC .18.104.22.168) (Table 2). UDP-glucose/galactose 4-epimerase interconverts UDP-glucose and UDP-galactose and is an important pathway for GAL production. Galactinol synthase synthesizes galactinol from UDP-GAL and inositol. Galactinol is the galactosyl donor for RFO biosynthesis. α-Galactosidases play a role in the hydrolytic degradation of RFO [14, 15]. Analysis of soluble carbohydrates in cotton stems and roots supported an increase in raffinose and the increase continued as starch was degraded (Table 3). The levels of trehalose were too low to reliably measure.
We present work that integrates measurements of starch and soluble carbohydrate levels with analyses of gene expression in starch accumulating cotton stems and roots. Consistent with previous reports there is a rapid increase in the levels of starch stored in the stem and root of cotton plants approximately coincident with bloom of the first flower . This high starch content in stems and roots at first anthesis was followed by a subsequent decrease in starch levels in field-grown plants. There was often a novel peak in starch levels prior to first bloom in field-grown plants that was not observed in greenhouse-grown plants.
Roots were generally higher in starch than stems. Analysis of starch in stems at first anthesis failed to demonstrate a clear gradient of starch accumulation along the stem, particularly below the elongation zone. Starch appeared to be synthesized in a concerted fashion along primary stems below the elongating zone of flowering plants. Analysis of starch grains showed that transient starch in leaves could be distinguished from stored starch in stems and roots based on shape and size. Additionally, starch in stems above the elongation zone appeared more similar to stored starch in stems and roots than transient starch in leaves indicating almost the entire stem stores starch.
Microarray analyses were used to investigate changes in gene expression associated with changes in starch levels and were validated using qPCR analyses of expression of selected genes. Statistical analysis of the data indicated an increase in genes associated with carbohydrate metabolism as expected for tissues accumulating starch. Additionally, expression of genes associated with transcription factor activity also increased indicating a potential role for changes in gene expression as stems and roots started to store starch. Some of these transcription factors are likely to play roles in regulating carbohydrate metabolism.
There must be an increased flow of SUC from leaves to stems and roots as starch accumulates. Consistent with this requirement was an increase in expression of genes associated with sugar transport in these tissues. Transcripts encoding invertase and invertase inhibitors increase in tissues accumulating starch. Invertase converts SUC to GLC and FRC providing glucose for starch biosynthesis. We also note that the change of expression of sucrose synthase which converts SUC to GLC-UDP and FRC fell just below the two-fold threshold for consideration. Increases in levels of transcripts encoding hexokinases, phosphoglucomutase and isomerases were consistent with the production of Glucose-1-phosphate for starch biosynthesis (Table 2). SUC and FRC levels peaked in both roots and stems at 4 W post anthesis. Four weeks after first anthesis represents a time of considerable demand for carbohydrates by the developing seeds. Sucrose is synthesized via sucrose phosphate synthase and SPP. Sucrose phosphate synthase synthesizes sucrose-phosphate from GLC-UDP and FRC-P and SPP dephosphorylates sucrose-phosphate. As previously noted the increase in SPP transcripts fell just below the two- fold level in starch accumulating tissues and did not subsequently increase. More detailed analyses of cotton stems after flowering will elucidate important aspects of sucrose metabolism that would allow export of carbon to support seed development.
ADPGp expression is increased in starch storing tissues. ADPGp catalyzes the conversion of glucose-phosphate to glucose-ADP, which is a rate limiting step in starch biosynthesis . As expected, other genes associated with starch biosynthesis such as starch synthase and starch branching enzymes increased in expression during the starch accumulation stage of stem and root development. Starch phosphorylase also appeared to play a role in starch biosynthesis in rice seed . Somewhat unexpected was an increase in expression of genes associated with starch degradation in starch accumulating tissues. QPCR of an α-amylase transcript indicated that these transcript levels increased in starch accumulating tissue and stayed at about the same level as starch decreased. Amylase enzyme activities have been reported to correlate with starch levels in cotton plants . α-Amylase is not required for starch degradation in Arabidopsis leaves indicating it may have functions other than starch degradation . Starch degrading genes, such as those encoding starch debranching enzymes, play a role in starch maturation. Expression of a glucan water dikinase (GWD) transcript increased in expression in starch accumulating tissues and continued to increase in expression as starch was utilized. GWD phosphorylates starch and is necessary for degradation of transient starch in Arabidopsis leaves [19–21].
Most of the proteins directly involved in starch metabolism appeared to be targeted to the plastid as expected. One exception was the ADPGp large subunit. The gene model used on this microarray included the 5' end of the coding sequence but was not predicted to be targeted to the plastid even though other plant ADPGp large subunits were. Failure to localize this ADPGp to the plastid may indicate an error assembling this gene or might indicate this gene is located in the cytosol. A cytosolic localization has been reported for some ADPGp .
Analysis of differentially expressed genes identified an increase in transcripts encoding enzymes for TRE biosynthesis and RAF biosynthesis. Analysis of RAF levels and the expression of genes associated with the biosynthesis of RAF and TRE indicated that they peak in expression in field-grown stems and roots well after starch [11, 23, 24]. The TRE pathway (especially trehalose-6-phosphate) is associated with control of glycolysis, ABA signaling and starch accumulation in Arabidopsis and has been associated with drought stress in cotton . QPCR confirmed an increase in transcripts encoding trehalose phosphate synthase that continued even after starch levels declined. Therefore TRE may play a role in the starch utilization stage of cotton stem development. RAF accumulates prominently in maturing seeds where it is thought to act as a compatible solute in preparation for seed desiccation and as a storage reserve for post-germinative growth . RAF and RFO are thought to play a role in cold and desiccation tolerance in plants and in some plants are prominent transport sugars . The role RFO is playing in cotton is unclear because even at peak levels, they are below those associated with desiccation tolerance. The increase of putative RFO anabolic and catabolic gene expression may point to transient fluctuations in levels, or rapid flux of carbohydrate through this pathway.
Cotton is an unusual crop because it is a perennial that is often grown as an annual row crop. One method of determining how well cotton has been annualized is to measure reserves stored for subsequent regrowth which are unavailable for seed production and therefore wasted in an annual row crop. Starch accounted for about 1.5 % of the dry weight of stems and roots late in boll development. One goal of this research is to identify genes and pathways that could be modified to direct starch into agronomically valuable fiber yield. For example, modification of ADPGp expression reduced starch metabolism in potato . Starch stored in cotton roots and stems prior to flowering appears to be available to developing bolls so it may be more desirable to retain this starch in stems and roots until after flowering and then mobilize all of the starch to support seed and fiber development. It is also important that the mobilization of carbohydrates from the stems and roots is not limited by environmental factors. Improved mobilization of carbohydrates from stem and root may be accomplished by reducing expression of starch biosynthesis genes after flowering and/or by increasing expression of starch degrading enzymes after flowering. Additionally, altering signaling pathways, for example TRE metabolism or expression of relevant transcription factors, may provide valuable targets to coordinately change starch biosynthesis and degradation in a way that favors increased yield. These approaches could be explored by targeting genes presented in this study using standard methods of cotton transformation.
The cotton cultivar STV4793R was grown in Stoneville, MS in 2004 and 2005. The same cultivar was planted in a greenhouse in Stoneville, MS (2004) at two-week intervals and the root and main stems harvested simultaneously. The main stem was divided into approximately four sections of three nodes. The stem sections nearest the root and extending to the apical meristem are termed basal, intermediate, subterminal and terminal stems. Stems and roots were harvested between 8:00 AM and 10:00 AM. Leaves were harvested at 1:00 PM to recover greater levels of starch. Plant material was frozen in liquid nitrogen and ground with liquid nitrogen in a 3 hp Warring Blender (Torrington, CT, USA) at the highest speed for 3 min. Each sample represented at least three plants and 5 g of the ground material were freeze-dried in 50 mL tubes for 5 days. The freeze-dried material was stored at -20°C.
The method described by Hendrix was used to determine the amount of starch in each sample . Briefly, the soluble sugars were extracted from 50–100 mg of the dried material using 3 extractions with 1 mL hot 80% ethanol. The extracted plant material was pelleted in a microfuge tube and the starch gelatinized by heating to 95–98°C in 0.1 M KOH. The samples were neutralized with 0.2 mL 1 M acetic acid and the pH adjusted to 7 by the addition of acetic acid as needed. The starch was digested with 200 μL (300 units) α-amylase solution at 85°C for 30 min. The pH was lowered to 5 with addition of acetic acid, 1 mL of amyloglucosidase was added (125 units), incubated at 55°C for 60 min and 95–98°C for 4 min. The sample was centrifuged and the supernatant solution brought to 6 mL with water. The α-amylase (Sigma), St. Louis, MO, USA and amyloglucosidase (Sigma) were prepared exactly as described by Hendrix, including testing various amounts of samples to be sure starch digestion was complete. The GLC content of each sample was also determined according to Hendrix . Starch was determined by multiplying the total amount of GLC from each sample by 0.9. Each value represents the analysis of starch from three or four replications of 50–100 mg of dried material from each time point. Statistical analysis was done using EXCEL (Microsoft, Seattle, WA).
Starch was isolated using a modification of the method described in Ritte et al . Five grams of ground plant material were added to 25 mL starch extraction buffer (100 mMHEPES pH8, 5 mMDTT, 0.05% triton-X-100) and filtered through a double layer of cheese cloth. The filtrate was filtered through a 30 μm nylon mesh. Analysis of starch isolated without filtration through the mesh indicated that starch grains were much smaller than 30 μm and that this filtration step did not remove larger grains. The filtrate was centrifuged at 1000 × g for 5 min to pellet the starch. The supernatant solution was carefully removed to avoid disturbing the pellet. The pellet was resuspended in 10 mL extraction buffer and carefully layered over 5 mL of a 95% percoll pad (5% extraction buffer, 95% percoll) and centrifuged for 15 min at 2000 × g. The supernatant solution, including the percoll pad was carefully removed and the starch pellet resuspended in 30 mL sterile extraction buffer. Starch was allowed to settle to the bottom of the tube for 18 hrs at 4°C. The supernatant solution was carefully removed and the settled starch was resuspended in 10 mL extraction buffer and centrifuged at 1000 × g for 5 min. The starch pellet was resuspended in 10 mL water and centrifuged for 5 min at 1000 × g three times. The starch pellet was resuspended in 10 mL acetone and centrifuged for 5 min at 1000 × g three times. The pellet was air dried overnight in a chemical hood and stored at -20°C.
About 10 mg of starch were suspended in 50% glycerol and dilutions made to allow best separation of individual grains. The suspensions were stained with I2KI (2%KI, 0.2%I2) and visualized with an Axiovision camera (Zeiss, Thornwood, NY, USA) using the Axiovision 4.4 software (Zeiss). Starch grain diameters were measured with ImageJ 1.36 . Statistical analyses were performed with SAS (Cary, NC, USA).
Soluble sugar analyses
Soluble sugars were extracted from 50 mg of frozen samples (fresh weight) using two extraction with five volumes of MCW (methanol:chloroform:water, 12:5:1) including 10 μM lactose as an internal standard. After extraction, water (0.6 volumes) was added to the combined extracts to separate the chloroform and aqueous phase. Samples were centrifuged for 15 min at 13,000 × g and the aqueous layer transferred to a 15 mL tube and lyophilized. The dried extracts were resuspended in 300 μL HPLC grade water. Neutral sugars were isolated from each sample by passing the solution through a column consisting of AG50W cation exchange resin (H+ form; BioRad, Carlsbad, CA, USA), polyvinyl polypyrrolidone (Sigma), and AG1 anion exchange resin (formate form, Bio-Rad); 250 μL, 100 μL and 250 μL bed volumes, respectively (top to bottom), and eluting with 1.7 mL water. Each eluate was filtered through a 0.22 μm nylon HPLC filters (Corning-Costar, Lowell, MA, USA). Sugars were resolved and quantified against standards by high-performance anion exchange chromatography with pulsed-amperometric detection (HPAEC-PAD) using a CarboPac PA20 column at 40°C, 50 mM NaOH eluent, and quadruple waveform, as recommended by the instrument manufacturer (Dionex, Sunnyvale, CA, USA). GLC and GAL co-elute under these conditions. Values were normalized against lactose. A separate experiment confirmed that these samples did not include molecules that interfered with the use of lactose as an internal standard. Calculations and statistical analyses were done using EXCEL.
RNA extraction and microarray analysis
Total polyribosomal RNA was isolated from the selected tissues by standard methods . The quality of the RNA was confirmed on a bioanalyzer (Agilent, Palo Alto, CA, USA) and probes derived from various RNAs representing tissues with different starch levels were labeled with CY3 or CY5. The labeled nucleic acids were hybridized against 3 microarrays made by Agilent (Palo Alto, CA, USA) that have been described in detail elsewhere . On the first microarray, genes expressed in basal stems 4 weeks and 2 week before anthesis (-4 W and -2 W) grown in the field in 2004 were compared. On the second microarray, genes expressed in -4 W and -2 W greenhouse-grown basal stems were compared, and on the last microarray genes expressed in -4 W and -2 W greenhouse-grown roots were compared. The hybridization and data collection was performed by MoGene (St Louis, MO, USA) using standard methods . These data have been deposited in the NCBI Gene Expression Omnibus (GEO) serial number GSE8973 . Statistical analyses are described in Taliercio and Boykin .
Validation of microarray data
sucrose phosphate phosphatase
phospho gluco mutase
phospho gluco mutase
trehalose phosphate synthase
trehalose phosphate synthase
In-Silicolocalization to plastid
The conceptual open reading frame (ORF) of the ADPGp large subunit was identified using Vector NTI. The protein database at NCBI was queried using BLASTx with candidates lacking the 5'end of the ORF. The plastid localization of these selected sequences were determined using the Chlorop1.1 prediction server .
The authors thank Pameka Johnson for excellent technical assistance. This work was supported by USDA/ARS CRIS number 6402-21000-029-00. Mention of trade names or commercial products in this article is solely for the purpose of providing specific information and does not imply recommendation or endorsement by the U.S. Department of Agriculture.
- Graves AD, Stewart MJ: Chronology of the differentiation of cotton (Gossypium hirsutum L.) fiber cells. Planta. 1988, 175: 254-258. 10.1007/BF00392435.PubMedView ArticleGoogle Scholar
- Constable GA, Rawson HM: Carbon production and utilization in cotton: Inferences from a carbon budget. Aus J Plant Physiol. 1980, 7: 539-553.View ArticleGoogle Scholar
- Pettigrew WT, McCarty JC, Vaughn KC: Leaf senescence-like characteristics contribute to cotton's premature photosynthetic decline. Photosynthesis Res. 2000, 65: 187-195. 10.1023/A:1006455524955.View ArticleGoogle Scholar
- De Souza JG, Viera da Silva J: Partitioning of carbohydrates in annual and perennial cotton (Gossypium hirsutum L.). J Exp Bot. 1987, 38: 1211-1218. 10.1093/jxb/38.7.1211.View ArticleGoogle Scholar
- Wells R: Stem and root carbohydrate dynamics of two cotton cultivars bred fifty years apart. Agronomy J. 2002, 94: 876-882.View ArticleGoogle Scholar
- Guinn G, Mauney JR: Fruiting of cotton. II Effects of plant moisture status and active boll load on boll retention. Agronomy J. 1984, 76: 94-98.View ArticleGoogle Scholar
- Heitholt J: Cotton flowering and boll retention in different planting configurations and leaf shapes. Agronomy J. 1995, 87: 994-998.View ArticleGoogle Scholar
- Taliercio E, Allen RD, Essenberg M, Klueva N, Nguyen H, Patil MA, Payton P, Millena ACM, Phillips AL, Pierce ML, Scheffler B, Turley R, Wang J, Zhang D, Scheffler J: Analysis of ESTs from multiple Gossypium hirsutum tissues and identification of SSRs. Genome. 2006, 49: 306-319. 10.1139/G05-115.PubMedView ArticleGoogle Scholar
- Taliercio E, Boykin D: Analysis of gene expression in cotton fiber initials. BMC Plant Biol. 2007, 7: 22-10.1186/1471-2229-7-22.PubMedPubMed CentralView ArticleGoogle Scholar
- GOstat: Find statistically overrepresented Gene Ontologies within a group of genes. [http://gostat.wehi.edu.au/].
- Grennan AK: The role of trehalose biosynthesis in plants. Plant Physiol. 2007, 144: 3-5. 10.1104/pp.104.900223.PubMedPubMed CentralView ArticleGoogle Scholar
- Bachmann M, Matile P, Keller F: Metabolism of the raffinose family oligosaccharides in leaves of Ajuga reptans L. Plant Physiol. 1994, 105: 1335-1345.PubMedPubMed CentralGoogle Scholar
- Hannah MA, Zuther E, Buchel K, Heyer AG: Transport and metabolism of raffinose family oligosaccharides in transgenic potato. J Exp Bot. 2006, 57: 3801-3811. 10.1093/jxb/erl152.PubMedView ArticleGoogle Scholar
- Carmin N, Zhang G, Petreikov M, Goa Z, Eyal Y, Granot D, Schaffer AA: Cloning and functional expression of alkaline α-galactosidase from melon fruit: similarity to plant SIP proteins uncovers a novel family of plant glycosyl hydrolases. Plant J. 2003, 33: 97-106. 10.1046/j.1365-313X.2003.01609.x.View ArticleGoogle Scholar
- Keller F, Pharr DM: Metabolism of carbohydrates in sinks and sources: galactosyl-sucrose oligosaccarides. Photoassimilate Distribution in Plants and Crops: Source-Sink Relationships. Edited by: Zamski E, Schaffer AA. 1996, 157-183.Google Scholar
- Ball SG, Morell MK: From bacterial glycogen to starch: Understanding the biogenesis of the plant starch granule. Ann Rev Plant Biol. 2003, 54: 207-233. 10.1146/annurev.arplant.54.031902.134927.View ArticleGoogle Scholar
- Satoh H, Shibahara K, Tokunaga T, Nishi A, Tasaki M, Hwang SK, Okita TW, Kaneko N, Fujita N, Yoshida M, Hosaka Y, Sato A, Utsumi Y, Ohdan T, Nakamura Y: Mutation of the plastidial α-Glucan phosphorylase gene in rice affects the synthesis and structure of starch in the endosperm. Plant Cell. 2008, 20: 1833-1849. 10.1105/tpc.107.054007.PubMedPubMed CentralView ArticleGoogle Scholar
- Yu TS, Zeeman SC, Thorneycroft D, Fulton DC, Dunstan H, Lue WL, Hegemann B, Tung SY, Umemoto T, Chapple A, Tsai DL, Wang SM, Smith AM, Chen J, Smith SM: α-Amylase is not required for breakdown of transitory starch in arabidopsis leaves. J Biol Chem. 2005, 280: 9773-9779. 10.1074/jbc.M413638200.PubMedView ArticleGoogle Scholar
- Delatte T, Umhang M, Trevisan M, Eicke S, Thorneycroft D, Smith SM, Zeeman SC: Evidence for distinct mechanisms of starch granule breakdown in plants. J Biol Chem. 2006, 281: 12050-12059. 10.1074/jbc.M513661200.PubMedView ArticleGoogle Scholar
- Edner C, Li J, Albrecht T, Mahlow S, Hejazi M, Hussain H, Kaplan F, Guy C, Smith SM, Steup M, Ritte G: Glucan, water dikinase activity stimulates breakdown of starch granules by plastidial beta-amylases. Plant Physiol. 2007, 145 (1): 17-28. 10.1104/pp.107.104224.PubMedPubMed CentralView ArticleGoogle Scholar
- Zeeman SC, Delatte T, Messerli G, Umhang M, Stettler M, Mettler T, Streb S, Reinhold H, K+|tting O: Starch breakdown: recent discoveries suggest distinct pathways and novel mechanisms. Funct Plant Biol. 2007, 34: 465-473. 10.1071/FP06313.View ArticleGoogle Scholar
- Burton RA, Johnson PE, Beckles DM, Fincher GB, Jenner HL, Naldrett MJ, Denyer K: Characterization of the genes encoding the cytosolic and plastidial forms of ADP-Glucose pyrophosphorylase in wheat endosperm. Plant Physiol. 2002, 130: 1464-1475. 10.1104/pp.010363.PubMedPubMed CentralView ArticleGoogle Scholar
- Eastmond PJ, Li Y, Graham IA: Is trehalose-6-phosphate a regulator of sugar metabolism in plants?. J Exp Bot. 2003, 54: 533-537. 10.1093/jxb/erg039.PubMedView ArticleGoogle Scholar
- Kolbe A, Tiessen A, Schluepmann H, Paul M, Ulrich S, Geigenberger P: Trehalose 6-phosphate regulates starch synthesis via posttranslational redox activation of ADP-glucose pyrophosphorylase. PNAS USA. 2005, 102: 11118-11123. 10.1073/pnas.0503410102.PubMedPubMed CentralView ArticleGoogle Scholar
- Nepomuceno AL, Oosterhuis D, Steward JM, Turley R, Neumaier N, Farias JRB: Expression of heat shock protein and trehalose-6-phosphate synthase homologues induced during water deficit in cotton. Braz J Plant Physiol. 2002, 14: 11-20. 10.1590/S1677-04202002000100002.View ArticleGoogle Scholar
- Teruaki T, Chieko O, Satoshi L, Motoaki S, Mie K, Masatomo K, Kazuko Y-S, Kazuo S: Important roles of drought- and cold-inducible genes for galactinol synthase in stress tolerance in Arabidopsis thaliana. Plant J. 2002, 29: 417-426. 10.1046/j.0960-7412.2001.01227.x.View ArticleGoogle Scholar
- Muller-Rober B, Sonnewald U, Willmitzer L: Inhibition of the ADP-glucose pyrophosphorylase in transgenic potatoes leads to sugar-storing tubers and influences tuber formation and expression of tuber storage protein genes. EMBOJ. 1992, 11 (4): 1299-1238.Google Scholar
- Hendrix DL: Rapid extraction and analysis of nonstructural carbohydrates in plant tissues. Crop Sci. 1993, 33: 1306-1311.View ArticleGoogle Scholar
- Ritte G, Lorberth R, Steup M: Reversible binding of the starch-related R1 protein to the surface of transitory starch granules. Plant J. 2000, 21: 387-391. 10.1046/j.1365-313x.2000.00683.x.PubMedView ArticleGoogle Scholar
- Rasband WS: ImageJ for microscopy. 2000, 1997-2004. [http://rsb.info.nih.gov/ij/].Google Scholar
- Larkins BA, Davis E: Polyribosomes from peas. Plant Physiol. 1973, 52: 655-659. 10.1104/pp.52.6.655.PubMedPubMed CentralView ArticleGoogle Scholar
- Barrett T, Troup DB, Wilhite SE, Ledoux P, Rudnev D, Evangelista C, Kim IF, Soboleva A, Tomashevsky M, Edgar R: NCBI GEO: mining tens of millions of expression profiles – database and tools update. Nucleic Acids Res. 2007, 35: D760-D765. 10.1093/nar/gkl887.PubMedPubMed CentralView ArticleGoogle Scholar
- Pfaffl MW: A new mathmatical model for the relative quantification in real-time RT-PCR. Nucleic Acids Res. 2001, 29: e45-10.1093/nar/29.9.e45.PubMedPubMed CentralView ArticleGoogle Scholar
- Emanuelsson O, Nielsen H, von Heijne G: ChloroP, a neural network-based method for predicting chloroplast transit peptides and their cleavage sites. Protein Sci. 1999, 8: 978-984.PubMedPubMed CentralView ArticleGoogle Scholar
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