River System Hydrology in Texas

River/reservoir system hydrology in the 15 major river basins and 8 coastal basins of Texas is explored using information derived from the Water Availability Modeling (WAM) System maintained by the Texas Commission on Environmental Quality and databases maintained by the Texas Water Development Board and the U.S. Geological Survey. River basin volume budgets and trend and frequency metrics for simulated naturalized and regulated stream flows and reservoir storage are developed using the WAM System. Trend and frequency statistics for observed precipitation, reservoir evaporation rates, and stream flow are also developed. Comparative analyses are performed to assess long-term changes. The research supports updating hydrology, incorporating environmental flow standards, and otherwise expanding the WAM System. However, the characterization of river system hydrology has broad general relevance for water resources planning and management. Analyses of long-term changes in hydrology are a central focus of the report, but the information provided describes river system hydrology in general

Applications of Expanded WRAP Modeling Capabilities to the Brazos WAM

The Water Rights Analysis Package (WRAP) is routinely applied in the Texas Commission on Environmental Quality (TCEQ) Water Availability Modeling (WAM) System. However, the Brazos River Basin studies documented by this report represent inaugural applications of the following new WRAP modeling capabilities: (1) conditional reliability modeling to determine short-term storage and flow frequencies and supply reliabilities conditioned on preceding reservoir storage contents; (2) capabilities added to allow simulations to be performed with daily time steps; and (3) simulation of reservoir operations for flood control. The Brazos WAM studies presented in this report provide a data and experience base for evaluating, demonstrating, and developing guidance for applying the new WRAP modeling capabilities. The studies also provide a better understanding of water management in the Brazos River Basin

Water Rights Analysis Package (WRAP) River System Hydrology

The Water Rights Analysis Package (WRAP) is documented by a Reference Manual and Users Manual and several auxiliary manuals including this Hydrology Manual that cover specific aspects of the modeling system. This Hydrology Manual focuses specifically on the WRAP program HYD. The purpose of HYD is to facilitate developing hydrology-related input data for the WRAP simulation model SIM. The purpose of this manual is to document the HYD software

Environmental Flows in Water Availability Modeling

The Texas Commission on Environmental Quality (TCEQ) Water Availability Modeling (WAM) System created pursuant to the 1997 Senate Bill 1 consists of the Water Rights Analysis Package (WRAP) and WRAP datasets for all of the river basins of Texas. The Texas Instream Flow Program was created by the Texas Legislature with its 2001 Senate Bill 2. The 2007 Senate Bill 3 established a new regulatory approach to provide for environmental flow needs of the river systems of Texas with flow standards developed through a stakeholder process culminating in TCEQ rulemaking. TR-440 explores recently expanded WRAP/WAM modeling capabilities for modeling environmental flow requirements established through the Senate Bill 3 process and evaluating their impacts on other water rights. The Brazos WAM is used as a case study to illustrate both daily and monthly modeling capabilities. The datasets developed for the case study are not designed for direct application in the water rights permitting process but rather to develop, test, and demonstrate recently expanded capabilities for modeling environmental flows

A Model for Solving the Optimal Water Allocation Problem in River Basins with Network Flow Programming When Introducing Non-Linearities

[EN] The allocation of water resources between different users is a traditional problem in many river basins. The objective is to obtain the optimal resource distribution and the associated circulating flows through the system. Network flow programming is a common technique for solving this problem. This optimisation procedure has been used many times for developing applications for concrete water systems, as well as for developing complete decision support systems. As long as many aspects of a river basin are not purely linear, the study of non-linearities will also be of great importance in water resources systems optimisation. This paper presents a generalised model for solving the optimal allocation of water resources in schemes where the objectives are minimising the demand deficits, complying with the required flows in the river and storing water in reservoirs. Evaporation from reservoirs and returns from demands are considered, and an iterative methodology is followed to solve these two non-network constraints. The model was applied to the Duero River basin (Spain). Three different network flow algorithms (Out-of-Kilter, RELAX-IVand NETFLO) were used to solve the allocation problem. Certain convergence issues were detected during the iterative process. There is a need to relate the data from the studied systems with the convergence criterion to be able to find the convergence criterion which yields the best results possible without requiring a long calculation time.We thank the Spanish Ministry of Economy and Competitivity (Comision Interministerial de Ciencia y Tecnologia, CICYT) for funding the projects INTEGRAME (contract CGL2009-11798) and SCARCE (program Consolider-Ingenio 2010, project CSD2009-00065). We also thank the European Commission (Directorate-General for Research & Innovation) for funding the project DROUGHT-R&SPI (program FP7-ENV-2011, project 282769). And last, but not least, to the Fundacion Instituto Euromediterraneo del Agua with the project "Estudio de Adaptaciones varias del modelo de optimizacion de gestiones de recursos hidricos Optiges".Haro Monteagudo, D.; Paredes Arquiola, J.; Solera Solera, A.; Andreu Álvarez, J. (2012). A Model for Solving the Optimal Water Allocation Problem in River Basins with Network Flow Programming When Introducing Non-Linearities. Water Resources Management. 26(14):4059-4071. https://doi.org/10.1007/s11269-012-0129-7S405940712614Ahuja R, Magnanti T, Orlin J (1993) Network flows: theory, algorithms and applications. Prentice Hall, New YorkAndreu J, Capilla J, Sanchís E (1996) AQUATOOL, a generalized decision-support system for water resources planning and operational management. J Hydrol 177:269–291Bersetkas D (1985) A unified framework for primal-dual methods in minimum cost network flows problems. Math Program 32:125–145Bersetkas D, Tseng P (1988) The relax codes for linear minimum cost network flow problems. Ann Oper Res 13:125–190Bersetkas D, Tseng P (1994) RELAX-IV: A faster version of the RELAX code for solving minimum cost flow problems. Completion Report under NSFGrant CCR-9103804. Dept. of Electrical Engineering and Computer Science, MIT, BostonChou F, Wu C, Lin C (2006) Simulating multi-reservoir operation rules by network flow model. ASCE Conf Proc 212:33Chung F, Archer M, DeVries J (1989) Network flow algorithm applied to California aqueduct simulation. J Water Resour Plan Manag 115:131–147Ford L, Fulkerson D (1962) Flows in networks. Princeton University Press, PrincetonFredericks J, Labadie J, Altenhofen J (1998) Decision support system for conjunctive stream-aquifer management. J Water Resour Plan Manag 124:69–78Harou JJ, Medellín-Azuara J, Zhu T et al (2010) Economic consequences of optimized water management for a prolonged, severe drought in California. Water Resour Res 46:W05522Hsu N, Cheng K (2002) Network Flow Optimization Model for Basin-Scale Water Supply Planning. J Water Resour Plan Manag 128:102–112Ilich N (1993) Improvement of the return flow allocation in the Water Resources Management Model of Alberta Environment. Can J Civ Eng 20:613–621Ilich N (2009) Limitations of network flow algorithms in river basin modeling. J Water Resour Plan Manag 135:48–55Kennington JL, Helgason RV (1980) Algorithms for network programming. John Wiley and Sons, New YorkKhaliquzzaman, Chander S (1997) Network flow programming model for multireservoir sizing. J Water Resour Plan Manag 123:15–21Kuczera G (1989) Fast Multireservoir Mulltiperiod Linear Programming Models. Water Resour Res 25:169–176Kuczera G (1993) Network linear programming codes for water-supply headworks modeling. J Water Resour Plan Manag 119:412–417Labadie J (2004) Optimal operation of multireservoir systems: state-of-the-art review. J Water Resour Plan Manag 130:93–111Labadie J (2006) MODSIM: river basin management decision support system. In: Singh W, Frevert D (eds) Watershed models. CRC, Boca Raton, pp 569–592Labadie J, Baldo M, Larson R (2000) MODSIM: decision support system for river basin management. Documentation and user manual. Dept. Of Civil Engineering, CSU, Fort CollinsManca A, Sechi G, Zuddas P (2010) Water supply network optimisation using equal flow algorithms. Water Resour Manag 24:3665–3678MMA (2000) Libro blanco del agua en España. Ministerio de Medio Ambiente, Secretaría general Técnica, Centro de PublicacionesMMA (2008) Confederación Hidrográfica del Duero. Memoria 2008. http://www.chduero.es/Inicio/Publicaciones/tabid/159/Default.aspx . Last accessed 25 June 2012Perera B, James B, Kularathna M (2005) computer software tool REALM for sustainable water allocation and management. J Environ Manag 77:291–300Rani D, Moreira M (2010) Simulation-optimization modeling: a survey and potential application in reservoir systems operation. Water Resour Manag 24:1107–1138Reca J, Roldán J, Alcaide M, López R, Camacho E (2001a) Optimisation model for water allocation in deficit irrigation systems I. Description of the model. Agric Water Manag 48:103–116Reca J, Roldán J, Alcaide M, López R, Camacho E (2001b) Optimisation model for water allocation in deficit irrigation systems II. Application to the Bembézar irrigation system. Agric Water Manag 48:117–132Sechi G, Zuddas P (2008) Multiperiod hypergraph models for water systems optimization. Water Resour Manag 22:307–320Sun H, Yeh W, Hsu N, Louie P (1995) Generalized network algorithm for water-supply-system optimization. J Water Resour Plan Manag 121:392–398Wurbs R (1993) Reservoir-system simulation and optimization models. J Water Resour Plan Manag 119:455–472Wurbs R (2005) Modeling river/reservoir system management, water allocation, and supply reliability. J Hydrol 300:100–113Yamout G, El-Fadel M (2005) An optimization approach for multi-sectoral water supply management in the greater Beirut area. Water Resour Manag 19:791–812Yates D, Sieber J, Purkey D, Hubert-Lee A (2005) WEAP21 – a demand-, priority-, and preference-driven water planning model. Part 1: model characteristics. Water Int 30:487–500Zoltay V, Vogel R, Kirshen P, Westphal K (2010) Integrated watershed management modeling: generic optimization model applied to the Ipswich river basin. J Water Resour Plan Manag 136:566–57

Design of simple synthetic RNA thermometers for temperature-controlled gene expression in Escherichia coli

RNA thermometers are thermosensors that regulate gene expression by temperature-induced changes in RNA conformation. Naturally occurring RNA thermometers exhibit complex secondary structures which are believed to undergo a series of gradual structural changes in response to temperature shifts. Here, we report the de novo design of considerably simpler RNA thermometers that provide useful RNA-only tools to regulate bacterial gene expression by a shift in the growth temperature. We show that a single small stem-loop structure containing the ribosome binding site is sufficient to construct synthetic RNA thermometers that work efficiently at physiological temperatures. Our data suggest that the thermometers function by a simple melting mechanism and thus provide minimum size on/off switches to experimentally induce or repress gene expression by temperature

Agricultural land use changes – a scenario-based sustainability impact assessment for Brandenburg, Germany

AbstractDecisions for agricultural management are taken at farm scale. However, such decisions may well impact upon regional sustainability. Two of the likely agricultural management responses to future challenges are extended use of irrigation and increased production of energy crops. The drivers for these are high commodity prices and subsidy policies for renewable energy. However, the impacts of these responses upon regional sustainability are unknown. Thus, we conducted integrated impact assessments for agricultural intensification scenarios in the federal state of Brandenburg, Germany, for 2025. One Irrigation scenario and one Energy scenario were contrasted with the Business As Usual (BAU) scenario. We applied nine indicators to analyze the economic, social and environmental effects at the regional, in this case district scale, which is the smallest administrative unit in Brandenburg. Assessment results were discussed in a stakeholder workshop involving 16 experts from the state government.The simulated area shares of silage maize for fodder and energy were 29%, 37% and 49% for the BAU, Irrigation, and Energy scenarios, respectively. The Energy scenario increased bio-electricity production to 41% of the demand of Brandenburg, and it resulted in CO2 savings of up to 3.5milliontons. However, it resulted in loss of biodiversity, loss of landscape scenery, increased soil erosion risk, and increased area demand for water protection requirements. The Irrigation scenario led to yield increases of 7% (rapeseed), 18% (wheat, sugar beet), and 40% (maize) compared to the BAU scenario. It also reduced the year-to-year yield variability. Water demand for irrigation was found to be in conflict with other water uses for two of the 14 districts. Spatial differentiation of scenario impacts showed that districts with medium to low yield potentials were more affected by negative impacts than districts with high yield potentials.In this first comprehensive sustainability impact assessment of agricultural intensification scenarios at regional level, we showed that a considerable potential for agricultural intensification exists. The intensification is accompanied by adverse environmental and socio-economic impacts. The novelty lies in the multiscale integration of comprehensive, agricultural management simulations with regional level impact assessment, which was achieved with the adequate use of indicators. It provided relevant evidence for policy decision making. Stakeholders appreciated the integrative approach of the assessment, which substantiated ongoing discussions among the government bodies. The assessment approach and the Brandenburg case study may stay exemplary for other regions in the world where similar economic and policy driving forces are likely to lead to agricultural intensification

Insensitivity of chloroplast gene expression to DNA methylation

Presence and possible functions of DNA methylation in plastid genomes of higher plants have been highly controversial. While a number of studies presented evidence for the occurrence of both cytosine and adenine methylation in plastid genomes and proposed a role of cytosine methylation in the transcriptional regulation of plastid genes, several recent studies suggested that at least cytosine methylation may be absent from higher plant plastid genomes. To test if either adenine or cytosine methylation can play a regulatory role in plastid gene expression, we have introduced cyanobacterial genes for adenine and cytosine DNA methyltransferases (methylases) into the tobacco plastid genome by chloroplast transformation. Using DNA cleavage with methylation-sensitive and methylation-dependent restriction endonucleases, we show that the plastid genomes in the transplastomic plants are efficiently methylated. All transplastomic lines are phenotypically indistinguishable from wild-type plants and, moreover, show no alterations in plastid gene expression. Our data indicate that the expression of plastid genes is not sensitive to DNA methylation and, hence, suggest that DNA methylation is unlikely to be involved in the transcriptional regulation of plastid gene expression

Rewiring carotenoid biosynthesis in plants using a viral vector

[EN] Plants can be engineered to sustainably produce compounds of nutritional, industrial or pharmaceutical relevance. This is, however, a challenging task as extensive regulation of biosynthetic pathways often hampers major metabolic changes. Here we describe the use of a viral vector derived from Tobacco etch virus to express a whole heterologous metabolic pathway that produces the health-promoting carotenoid lycopene in tobacco tissues. The pathway consisted in three enzymes from the soil bacteria Pantoea ananatis. Lycopene is present at undetectable levels in chloroplasts of non-infected leaves. In tissues infected with the viral vector, however, lycopene comprised approximately 10% of the total carotenoid content. Our research further showed that plant viruses that express P. ananatis phytoene synthase (crtB), one of the three enzymes of the heterologous pathway, trigger an accumulation of endogenous carotenoids, which together with a reduction in chlorophylls eventually result in a bright yellow pigmentation of infected tissues in various host-virus combinations. So, besides illustrating the potential of viral vectors for engineering complex metabolic pathways, we also show a yellow carotenoid-based reporter that can be used to visually track infection dynamics of plant viruses either alone or in combination with other visual markers.We thank Veronica Aragones and M. Rosa Rodriguez-Goberna for excellent technical assistance. This research was supported by Spanish Ministerio de Economia y Competitividad (MINECO) grants BIO2014-54269-R to J.-A.D., and BIO2014-59092-P and BIO2015-71703-REDT to M. R.-C. Financial support from the Generalitat Valenciana (PROMETEOII/2014/021), the Programa Iberoamericano de Ciencia y Tecnologia para el Desarrollo (Ibercarot 112RT0445), and the Generalitat de Catalunya (2014SGR-1434) is also acknowledged. E.M. is the recipient of a pre-doctoral fellowship (AP2012-3751) from the Spanish Ministerio de Educacion, Cultura y Deporte. B.L. is supported by a postdoctoral fellowship (FPDI-2013-018882) from MINECO.Majer, E.; Llorente, B.; Rodríguez-Concepción, M.; Daros Arnau, JA. (2017). Rewiring carotenoid biosynthesis in plants using a viral vector. Scientific Reports. 7. https://doi.org/10.1038/srep41645S7O’Connor, S. E. Engineering of secondary metabolism. Annu. Rev. Genet. 49, 71–94 (2015).Sainsbury, F. & Lomonossoff, G. P. Transient expressions of synthetic biology in plants. Curr. Opin. Plant Biol. 19, 1–7 (2014).Gleba, Y. Y., Tusé, D. & Giritch, A. Plant viral vectors for delivery by Agrobacterium. Curr. Top. Microbiol. Immunol. 375, 155–192 (2014).Chen, Q., He, J., Phoolcharoen, W. & Mason, H. S. Geminiviral vectors based on bean yellow dwarf virus for production of vaccine antigens and monoclonal antibodies in plants. Hum. Vaccin. 7, 331–338 (2011).Pogue, G. P., Lindbo, J. A., Garger, S. J. & Fitzmaurice, W. P. Making an ally from an enemy: plant virology and the new agriculture. Annu. Rev. Phytopathol. 40, 45–74 (2002).Peyret, H. & Lomonossoff, G. P. When plant virology met Agrobacterium: the rise of the deconstructed clones. Plant Biotechnol. J. 13, 1121–1135 (2015).Bedoya, L. C., Martínez, F., Orzáez, D. & Daròs, J. A. Visual tracking of plant virus infection and movement using a reporter MYB transcription factor that activates anthocyanin biosynthesis. Plant Physiol. 158, 1130–1138 (2012).Majer, E., Daròs, J. A. & Zwart, M. P. Stability and fitness impact of the visually discernible Rosea1 marker in the Tobacco etch virus genome. Viruses 5, 2153–2168 (2013).Bedoya, L., Martínez, F., Rubio, L. & Daròs, J. A. Simultaneous equimolar expression of multiple proteins in plants from a disarmed potyvirus vector. J. Biotechnol. 150, 268–275 (2010).Kelloniemi, J., Mäkinen, K. & Valkonen, J. P. Three heterologous proteins simultaneously expressed from a chimeric potyvirus: infectivity, stability and the correlation of genome and virion lengths. Virus Res. 135, 282–291 (2008).Carrington, J. C., Haldeman, R., Dolja, V. V. & Restrepo-Hartwig, M. A. Internal cleavage and trans-proteolytic activities of the VPg-proteinase (NIa) of tobacco etch potyvirus in vivo . J. Virol. 67, 6995–7000 (1993).Li, X. H. & Carrington, J. C. Complementation of tobacco etch potyvirus mutants by active RNA polymerase expressed in transgenic cells. Proc. Natl. Acad. Sci. USA 92, 457–461 (1995).Fraser, P. D. & Bramley, P. M. The biosynthesis and nutritional uses of carotenoids. Prog. Lipid Res. 43, 228–265 (2004).Meléndez-Martínez, A. J., Mapelli-Brahm, P., Benítez-González, A. & Stinco, C. M. A comprehensive review on the colorless carotenoids phytoene and phytofluene. Arch. Biochem. Biophys. 572, 188–200 (2015).Rodríguez-Concepción, M. & Boronat, A. Elucidation of the methylerythritol phosphate pathway for isoprenoid biosynthesis in bacteria and plastids. A metabolic milestone achieved through genomics. Plant Physiol. 130, 1079–1089 (2002).Giuliano, G. Plant carotenoids: genomics meets multi-gene engineering. Curr. Opin. Plant Biol. 19, 111–117 (2014).Cazzonelli, C. I. & Pogson, B. J. Source to sink: regulation of carotenoid biosynthesis in plants. Trends Plant Sci. 15, 266–274 (2010).Ruiz-Sola, M. A. & Rodríguez-Concepción, M. Carotenoid biosynthesis in Arabidopsis: a colorful pathway. Arabidopsis Book 10, e0158 (2012).Nisar, N., Li, L., Lu, S., Khin, N. C. & Pogson, B. J. Carotenoid metabolism in plants. Mol. Plant 8, 68–82 (2015).Misawa, N. et al. Elucidation of the Erwinia uredovora carotenoid biosynthetic pathway by functional analysis of gene products expressed in Escherichia coli . J. Bacteriol. 172, 6704–6712 (1990).Hasunuma, T. et al. Biosynthesis of astaxanthin in tobacco leaves by transplastomic engineering. Plant J. 55, 857–868 (2008).Lu, Y., Rijzaani, H., Karcher, D., Ruf, S. & Bock, R. Efficient metabolic pathway engineering in transgenic tobacco and tomato plastids with synthetic multigene operons. Proc. Natl. Acad. Sci. USA 110, E623–632 (2013).Mann, V., Harker, M., Pecker, I. & Hirschberg, J. Metabolic engineering of astaxanthin production in tobacco flowers. Nat. Biotechnol. 18, 888–892 (2000).Wurbs, D., Ruf, S. & Bock, R. Contained metabolic engineering in tomatoes by expression of carotenoid biosynthesis genes from the plastid genome. Plant J. 49, 276–288 (2007).Cordero, M. T. et al. Dicer-like 4 is involved in restricting the systemic movement of Zucchini yellow mosaic virus in Nicotiana benthamiana . Mol. Plant-Microbe Interact. doi: 10.1094/MPMI-11-16-0239-R (2016).Ye, X. et al. Engineering the provitamin A (b-carotene) biosynthetic pathway into (carotenoid-free) rice endosperm. Science 287, 303–305 (2000).Ravanello, M. P., Ke, D., Alvarez, J., Huang, B. & Shewmaker, C. K. Coordinate expression of multiple bacterial carotenoid genes in canola leading to altered carotenoid production. Metab. Eng. 5, 255–263 (2003).Fujisawa, M. et al. Pathway engineering of Brassica napus seeds using multiple key enzyme genes involved in ketocarotenoid formation. J. Exp. Bot. 60, 1319–1332 (2009).Ohara, K., Ujihara, T., Endo, T., Sato, F. & Yazaki, K. Limonene production in tobacco with Perilla limonene synthase cDNA. J. Exp. Bot. 54, 2635–2642 (2003).Gutensohn, M. et al. Cytosolic monoterpene biosynthesis is supported by plastid-generated geranyl diphosphate substrate in transgenic tomato fruits. Plant J. 75, 351–363 (2013).Yamano, S., Ishii, T., Nakagawa, M., Ikenaga, H. & Misawa, N. Metabolic engineering for production of beta-carotene and lycopene in Saccharomyces cerevisiae. Biosci. Biotechnol. Biochem. 58, 1112–1114 (1994).Bahieldin, A. et al. Efficient production of lycopene in Saccharomyces cerevisiae by expression of synthetic crt genes from a plasmid harboring the ADH2 promoter. Plasmid 72, 18–28 (2014).Xie, W., Lv, X., Ye, L., Zhou, P. & Yu, H. Construction of lycopene-overproducing Saccharomyces cerevisiae by combining directed evolution and metabolic engineering. Metab. Eng. 30, 69–78 (2015).Li, Y., Cui, H., Cui, X. & Wang, A. The altered photosynthetic machinery during compatible virus infection. Curr. Opin. Virol. 17, 19–24 (2016).Tilsner, J. & Oparka, K. J. Tracking the green invaders: advances in imaging virus infection in plants. Biochem. J. 430, 21–37 (2010).Kumagai, M. H. et al. Cytoplasmic inhibition of carotenoid biosynthesis with virus-derived RNA. Proc. Natl. Acad. Sci. USA 92, 1679–1683 (1995).Kumagai, M. H., Keller, Y., Bouvier, F., Clary, D. & Camara, B. Functional integration of non-native carotenoids into chloroplasts by viral-derived expression of capsanthin-capsorubin synthase in Nicotiana benthamiana . Plant J. 14, 305–315 (1998).Zhai, S., Xia, X. & He, Z. Carotenoids in staple cereals: metabolism, regulation, and genetic manipulation. Front. Plant Sci. 7, 1197 (2016).Zhang, H. et al. A Narcissus mosaic viral vector system for protein expression and flavonoid production. Plant Methods 9, 28 (2013).Nielsen, A. Z. et al. Redirecting photosynthetic reducing power toward bioactive natural product synthesis. ACS Synth. Biol. 2, 308–315 (2013).Sainsbury, F., Saxena, P., Geisler, K., Osbourn, A. & Lomonossoff, G. P. Using a virus-derived system to manipulate plant natural product biosynthetic pathways. Methods Enzymol. 517, 185–202 (2012).Geisler, K. et al. Biochemical analysis of a multifunctional cytochrome P450 (CYP51) enzyme required for synthesis of antimicrobial triterpenes in plants. Proc. Natl. Acad. Sci. USA 110, E3360–3367 (2013).Kanagarajan, S., Muthusamy, S., Gliszczynska, A., Lundgren, A. & Brodelius, P. E. Functional expression and characterization of sesquiterpene synthases from Artemisia annua L. using transient expression system in Nicotiana benthamiana . Plant Cell Rep. 31, 1309–1319 (2012).Mozes-Koch, R. et al. Expression of an entire bacterial operon in plants. Plant Physiol. 158, 1883–1892 (2012).Thole, V., Worland, B., Snape, J. W. & Vain, P. The pCLEAN dual binary vector system for Agrobacterium-mediated plant transformation. Plant Physiol. 145, 1211–1219 (2007).Engler, C., Gruetzner, R., Kandzia, R. & Marillonnet, S. Golden gate shuffling: a one-pot DNA shuffling method based on type IIs restriction enzymes. PLoS One 4, e5553 (2009).Gibson, D. G. et al. Enzymatic assembly of DNA molecules up to several hundred kilobases. Nat. Methods 6, 343–345 (2009).Cunningham, F. X. Jr., Chamovitz, D., Misawa, N., Gantt, E. & Hirschberg, J. Cloning and functional expression in Escherichia coli of a cyanobacterial gene for lycopene cyclase, the enzyme that catalyzes the biosynthesis of b-carotene. FEBS Lett. 328, 130–138 (1993).Shivprasad, S. et al. Heterologous sequences greatly affect foreign gene expression in tobacco mosaic virus-based vectors. Virology 255, 312–323 (1999).Schürer, H., Lang, K., Schuster, J. & Mörl, M. A universal method to produce in vitro transcripts with homogeneous 3′ ends. Nucleic Acids Res. 30, e56 (2002).Lu, R. et al. High throughput virus-induced gene silencing implicates heat shock protein 90 in plant disease resistance. EMBO J. 22, 5690–5699 (2003).Dickmeis, C., Fischer, R. & Commandeur, U. Potato virus X-based expression vectors are stabilized for long-term production of proteins and larger inserts. Biotechnol. J. 9, 1369–1379 (2014).Nakagawa, T. et al. Improved Gateway binary vectors: high-performance vectors for creation of fusion constructs in transgenic analysis of plants. Biosci. Biotechnol. Biochem. 71, 2095–2100 (2007).Bedoya, L. C. & Daròs, J. A. Stability of Tobacco etch virus infectious clones in plasmid vectors. Virus Res. 149, 234–240 (2010).Sparkes, I. A., Runions, J., Kearns, A. & Hawes, C. Rapid, transient expression of fluorescent fusion proteins in tobacco plants and generation of stably transformed plants. Nat. Protoc. 1, 2019–2025 (2006).Llorente, B. et al. Tomato fruit carotenoid biosynthesis is adjusted to actual ripening progression by a light-dependent mechanism. Plant J. 85, 107–119 (2016)