ABSTRACT Atmospheric methane is the second most important greenhouse gas after carbon dioxide, and is responsible for about 20% of the global warming effect since pre-industrial times1,2.

Rice paddies are the largest anthropogenic methane source and produce 7–17% of atmospheric methane2,3. Warm waterlogged soil and exuded nutrients from rice roots provide ideal conditions for

methanogenesis in paddies with annual methane emissions of 25–100-million tonnes3,4. This scenario will be exacerbated by an expansion in rice cultivation needed to meet the escalating

demand for food in the coming decades4. There is an urgent need to establish sustainable technologies for increasing rice production while reducing methane fluxes from rice paddies. However,

_SUSIBA2_ (refs 7, 8), conferred a shift of carbon flux to _SUSIBA2_ rice, favouring the allocation of photosynthates to aboveground biomass over allocation to roots. The altered allocation

resulted in an increased biomass and starch content in the seeds and stems, and suppressed methanogenesis, possibly through a reduction in root exudates. Three-year field trials in China

demonstrated that the cultivation of _SUSIBA2_ rice was associated with a significant reduction in methane emissions and a decrease in rhizospheric methanogen levels. _SUSIBA2_ rice offers a

sustainable means of providing increased starch content for food production while reducing greenhouse gas emissions from rice cultivation. Approaches to increase rice productivity and

reduce methane emissions as seen in _SUSIBA2_ rice may be particularly beneficial in a future climate with rising temperatures resulting in increased methane emissions from paddies9,10.

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support SIMILAR CONTENT BEING VIEWED BY OTHERS SUGAR TRANSPORTER MODULATES NITROGEN-DETERMINED TILLERING AND YIELD FORMATION IN RICE Article Open access 25 October 2024 MYB61 IS REGULATED BY

GRF4 AND PROMOTES NITROGEN UTILIZATION AND BIOMASS PRODUCTION IN RICE Article Open access 15 October 2020 _ZMM28_ TRANSGENIC MAIZE INCREASES BOTH N UPTAKE- AND N UTILIZATION-EFFICIENCIES

Article Open access 07 June 2022 ACCESSION CODES PRIMARY ACCESSIONS GENBANK/EMBL/DDBJ * KR935231 DATA DEPOSITS The sequence of construct containing _HvSBEIIb_ p_:HvSUSIBA2_ has been

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thanks to S. Stymne. We would also like to thank B. Müller, X. Feng, M. Erikson, L. Sun, S. Isaksson, J. Ascue and S. Mayer for their help in determining concentrations of methane and

methanogens, and B. Ingemarsson for discussions concerning the work layout. This work was funded by the following organisations and foundations: The Swedish Research Council for Environment,

Agricultural Sciences and Spatial Planning (Formas) for Project No 219-2014-1172; the joint Formas/Sida-funded programme (Project No 220-2009-2069) on sustainable development in developing

countries; the SLU Lärosätesansökan Programme (TC4F) for Team 4 supported by Vinnova; the Swedish Research Council for Environment, Agricultural Sciences and Spatial Planning (Formas) under

the Strategic Research Area for the TCBB Programme; National Natural Science Foundation of China (projects no 30771298 and no 31370389); the SLU programme BarleyFunFood; the Carl Trygger

Foundation for Project No CTS 11: 450; funding in part by the US Department of Energy Contract DE-AC05-76RL01830 with the Pacific Northwest National Laboratory. AUTHOR INFORMATION Author

notes * J. Su, C. Hu and X. Yan: These authors contributed equally to this work. AUTHORS AND AFFILIATIONS * Institute of Biotechnology, Fujian Academy of Agricultural Sciences, Fuzhou,

350003, China J. Su, C. Hu, Z. Chen, Q. Guan, Y. Wang, D. Zhong & F. Wang * Department of Plant Biology, Uppsala BioCenter, Linnean Center for Plant Biology, Swedish University of

Agricultural Sciences, PO Box 7080, SE-75007, Uppsala, Sweden J. Su, C. Hu, X. Yan, Y. Jin & C. Sun * Hunan Provincial Key Laboratory of Crop Germplasm Innovation and Utilization, Hunan

Agricultural University, Changsha, 410128, China Y. Jin * The Environmental Molecular Sciences Laboratory (EMSL), Pacific Northwest National Laboratory, PO Box 999, K8-93, Richland, 99352,

Washington, USA C. Jansson * Department of Microbiology, Uppsala BioCenter, Swedish University of Agricultural Sciences, Uppsala, SE-75007, Sweden A. Schnürer Authors * J. Su View author

publications You can also search for this author inPubMed Google Scholar * C. Hu View author publications You can also search for this author inPubMed Google Scholar * X. Yan View author

publications You can also search for this author inPubMed Google Scholar * Y. Jin View author publications You can also search for this author inPubMed Google Scholar * Z. Chen View author

publications You can also search for this author inPubMed Google Scholar * Q. Guan View author publications You can also search for this author inPubMed Google Scholar * Y. Wang View author

publications You can also search for this author inPubMed Google Scholar * D. Zhong View author publications You can also search for this author inPubMed Google Scholar * C. Jansson View

author publications You can also search for this author inPubMed Google Scholar * F. Wang View author publications You can also search for this author inPubMed Google Scholar * A. Schnürer

View author publications You can also search for this author inPubMed Google Scholar * C. Sun View author publications You can also search for this author inPubMed Google Scholar

CONTRIBUTIONS J.S., Z.C., Q.G., Y.W. and D.Z. performed measurements of methane emissions from paddies; J.S. also performed western blot and zymogram analyses, methanogen quantification and

starch determination. C.H. was responsible for plasmid constructions, rice transformation, Southern blot analysis and phenotypic trait characterization. X.Y. carried out gene expression

analysis, starch determination, sugar induction experiments and phenotypic trait characterization. Y.J. performed plasmid validation, insertion site identification, methanogen

quantification, measurements of methane emissions in phytotrons and sugar induction experiments, electrophoretic mobility shift assay (EMSA), qPCR and light microscopy. C.J. was involved in

the initiation, layout and discussions concerning the work and manuscript revision. F.W. was involved in the planning of rice transformation and field trial settings. A.S. revised the

manuscript and helped with methane and methanogen determinations. C.S. initiated and coordinated the work, designed the experiments, performed some experiments, and drafted and revised the

manuscript. CORRESPONDING AUTHORS Correspondence to F. Wang or C. Sun. ETHICS DECLARATIONS COMPETING INTERESTS The authors declare no competing financial interests. EXTENDED DATA FIGURES AND

TABLES EXTENDED DATA FIGURE 1 VALIDATION OF AN EXPRESSION CASSETTE CONTAINING BARLEY _SBEIIB_ PROMOTER AND BARLEY _SUSIBA2_ (_HVSBEIIB_ P_:HVSUSIBA2_) IN A BINARY VECTOR AND RICE GENOME. A,

Construction of an expression cassette containing _HvSBEIIb_ p_:HvSUSIBA2_ in a binary vector was performed as described in the Methods. B, Validation of the construct in the rice genome

was performed by PCR-based cloning using primers and HindIII-adaptor ligation, followed by sequencing. Two insertion sites were identified in rice chromosome 2, from nucleotides 57443 to

57444 and 57447 to 57448 (GenBank accession number AP006069), respectively. EXTENDED DATA FIGURE 2 METHANE EMISSIONS OF _SUSIBA2_ RICE COMPARED WITH NIPPONBARE (NIPP) IN PHYTOTRONS. A,

Methane emission of Nipp, _SUSIBA2-77_ and _SUSIBA2-80_ rice (15 daf). Six independent plants (_n_ = 6) from each rice line were used for measurements. B, Methane emission of Nipp and

_SUSIBA2-77_ (28 daf) at 30 min (left panel) or 60 min (right panel) after plants were covered. A linear relationship over time for the measured methane concentrations at 30 and 60 min was

found, as presented by similar methane fluxes determined from the different time points. Three plants (_n_ = 3) from each rice line were used for time point measurements. A statistically

significant reduction of methane emission in _SUSIBA2_ rice is indicated (one-way ANOVA, **_P_ ≤ 0.01 or *_P_ ≤ 0.05, error bars show s.d.). Source data EXTENDED DATA FIGURE 3 DIURNAL AND

SEASONAL METHANE EMISSIONS FROM _SUSIBA2-77_ AND _SUSIBA-80_ RICE COMPARED WITH NIPPONBARE (NIPP) IN AUTUMN 2014 AT THREE SITES IN CHINA. Methane emissions of six independent plants (_n_ =

6) from three time points during the day (morning 8.00 a.m., noon 12.00 p.m. and afternoon 4.00 p.m.) on different dates are presented. Key rice development stages for the corresponding

dates are indicated. Time points for sampling soil and roots for methanogen analysis are indicated by red arrows. A, Methane emission from Fuzhou. B, Methane emission from Guangzhou. C,

Methane emission from Nanning. Reported statistically significant reduction of methane emission in _SUSIBA2_ rice is indicated (one-way ANOVA, **_P_ ≤ 0.01 or *_P_ ≤ 0.05, error bars show

s.d.). Source data EXTENDED DATA FIGURE 4 QPCR QUANTIFICATION OF RHIZOSPHERIC METHANOGENIC COMMUNITIES ASSOCIATED WITH _SUSIBA2-77_ RICE AND NIPP IN PHYTOTRONS. Soil and root samples from

three independent positions, positions 1–3 (_n_ = 3), in the underground vicinity close to the root tip and proximal regions of three independent plants (_n_ = 3) for Nipp and _SUSIBA2-77_

rice were collected and analysed. Technical triplicates per position were applied. Six pairs of primers (Supplementary Table 1) were used to quantify total archaea (ARC) and methanogens

(MET), and the orders Methanobacteriales (MBT), Methanomicrobiales (MMB) and Methanocellales and two families Methanosaetaceae (Mst) and Methanosarcinaceae (Msc) of the order

Methanosarcinales, respectively. Results from soil and root samples are shown in A and B, respectively. Existing numbers of all methanogenic groups and total archaea were significantly

reduced in the _SUSIBA2_ rhizosphere compared to that of Nipp (one-way ANOVA, **_P_ ≤ 0.01 or *_P_ ≤ 0.05, error bars show s.d.). Source data EXTENDED DATA FIGURE 5 QPCR QUANTIFICATION OF

RHIZOSPHERIC METHANOGENS ASSOCIATED WITH _SUSIBA2_ RICE AND NIPPONBARE (NIPP) FROM RICE PADDIES. Soil and root samples (a mixture) from three positions (_n_ = 3) close to the root tip and

proximal regions of three independent plants (_n_ = 3) for Nipp, _SUSIBA2-77_ and _SUSIBA2-80_ rice, respectively, were collected. The sampling time and sites are indicated in Extended Data

Fig. 3. Technical triplicates per position were applied. Six pairs of primers (Supplementary Table 1) were used to quantify total archaea (ARC) and methanogens (MET), and the orders

Methanobacteriales (MBT), Methanomicrobiales (MMB) and Methanocellales and two families Methanosaetaceae (Mst) and Methanosarcinaceae (Msc) of the order Methanosarcinales, respectively.

Primers (Supplementary Table 1) specific to Methanocella were also used for quantification. A, Methanogenic communities in samples from Fuzhou. B, Methanogenic communities in samples from

Nanning. C, _Methanocella_ in samples from Nanning. All methanogenic groups and total archaea were significantly reduced in the _SUSIBA2_ rice rhizosphere compared with Nipp (one-way ANOVA,

**_P_ ≤ 0.01 or *_P_ ≤ 0.05, error bars show s.d.). Source data EXTENDED DATA FIGURE 6 BINDING ACTIVITY OF HVSUSIBA2 TO SURE SEQUENCES IN THE RICE _ISA1_ PROMOTER. A, Three SURE sequences in

the rice _ISA1_ promoter (GenBank accession number AB093426) were used and a negative (‘A stretch’) control was included. B, Barley SUSIBA2 protein (HvSUSIBA2) was overexpressed from _E.

coli_ and used for electrophoretic mobility shift assay (EMSA). EXTENDED DATA FIGURE 7 _HVSBEIIB_ PROMOTER ACTIVITY ANALYSIS IN RICE SEEDLINGS. A, _HvSBEIIb_ p_:GUS_ was introduced in

Nipponbare (Nipp). GUS activity was stained in different tissues of transformant and Nipp lines. The GUS activity was found in transformant stems and induced by sucrose (Suc) in leaves. A,

Nipp leaf. B, Transformant leaf. C, Nipp stem. D, Transformant stem. E, Nipp root. F, Transformant root. G, Nipp leaf induced by 100 mM sucrose. H, Transformant leaf induced by 100 mM

sucrose. Scale bars, 2 mm. EXTENDED DATA FIGURE 8 TRANSCRIPTOMIC ANALYSIS OF GENES RELATED TO SUGAR METABOLISM IN LATE TILLERING PLANTS OF _SUSIBA2_ RICE AND NIPPONBARE (NIPP). Relative

expression levels of 23 genes together with a housekeeping gene, _TIP41-like,_ were analysed by qPCR and compared between Nipp and _SUSIBA2-77_ and _SUSIBA2-80_ rice in leaves, stems and

roots at late tillering stage and in seeds at 7 daf. Three plants were used (_n_ = 3) and technical triplicates were performed for each rice line. _SUT3_ and _SUS5/7_ transcripts were not

detected in all samples (not shown) and _HvSUSIBA2_ expression was similar in _SUSIBA2-77_ and _SUSIBA2-80_ rice, as presented in Fig. 3b. One-way ANOVA was used for statistical analysis

(*_P_ ≤ 0.05 or **_P_ ≤ 0.01, error bars show s.d.). ND, not detected. Source data EXTENDED DATA FIGURE 9 TRANSCRIPTOMIC ANALYSIS OF 23 GENES RELATED TO SUGAR METABOLISM IN DEVELOPING RICE

SEEDS OF _SUSIBA2_ RICE AND NIPPONBARE (NIPP). Relative expression levels of 23 genes together with a housekeeping gene, _TIP41-like,_ were analysed by qPCR and compared between _SUSIBA2-77_

rice and Nipp at 5, 7, 9, 11 and 14 daf. Seeds from three independent plants were used (_n_ = 3) and technical triplicates were performed. _SUT3_ and _SUS5/7_ transcripts were not detected

in all samples (not shown) and _HvSUSIBA2_ expression is presented in Fig. 3b. One-way ANOVA was used for statistical analysis (*_P_ ≤ 0.05 or **_P_ ≤ 0.01, error bars show s.d.). Source

data EXTENDED DATA FIGURE 10 SUGAR-INDUCTION IN NIPPONBARE (NIPP) AND _SUSIBA2_ RICE. Rice leaves of Nipp and _SUSIBA2-77_ were depleted for sucrose in the dark before induction with 100 mM

sucrose. Sugar induction was carried out in the dark for 24 h. An enhanced expression of HvSUSIBA2-regulated genes (9 of the 12 genes except _SUT5, SUS1_ and _GBSSI_ that were not detected

in either rice cultivar under dark conditions) in _SUSIBA2-77_ was observed compared with Nipp. One-way ANOVA was used for statistical analysis (*_P_ ≤ 0.05 or **_P_ ≤ 0.01, error bars show

s.d.). The experiment was repeated at least three times (_n_ = 3). Source data RELATED AUDIO A NEW RICE STRAIN PROMISES HIGH STARCH AND LOW METHANE EMISSIONS. ADAM LEVY TALKS TO PLANT

RESEARCHER PAUL BODELIER. SUPPLEMENTARY INFORMATION SUPPLEMENTARY INFORMATION This file contains Supplementary Table 1. (PDF 137 kb) SUPPLEMENTARY INFORMATION This file contains

Supplementary Table 2. (XLSX 263 kb) SUPPLEMENTARY DATA This file contains the sequences of the construct and insertion sites in Extended Data Fig. 1. (PDF 214 kb) POWERPOINT SLIDES

POWERPOINT SLIDE FOR FIG. 1 POWERPOINT SLIDE FOR FIG. 2 POWERPOINT SLIDE FOR FIG. 3 POWERPOINT SLIDE FOR FIG. 4 SOURCE DATA SOURCE DATA TO FIG. 1 SOURCE DATA TO FIG. 2 SOURCE DATA TO FIG. 3

SOURCE DATA TO EXTENDED DATA FIG. 4 SOURCE DATA TO EXTENDED DATA FIG. 5 SOURCE DATA TO EXTENDED DATA FIG. 6 SOURCE DATA TO EXTENDED DATA FIG. 7 SOURCE DATA TO EXTENDED DATA FIG. 8 SOURCE

DATA TO EXTENDED DATA FIG. 9 SOURCE DATA TO EXTENDED DATA FIG. 10 RIGHTS AND PERMISSIONS Reprints and permissions ABOUT THIS ARTICLE CITE THIS ARTICLE Su, J., Hu, C., Yan, X. _et al._

Expression of barley SUSIBA2 transcription factor yields high-starch low-methane rice. _Nature_ 523, 602–606 (2015). https://doi.org/10.1038/nature14673 Download citation * Received: 20 June

2014 * Accepted: 19 June 2015 * Published: 22 July 2015 * Issue Date: 30 July 2015 * DOI: https://doi.org/10.1038/nature14673 SHARE THIS ARTICLE Anyone you share the following link with

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