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Omics in Weed Science: A Perspective from Genomics, Transcriptomics, and Metabolomics Approaches

  • Amith S. Maroli (a1), Todd A. Gaines (a2), Michael E. Foley (a3), Stephen O. Duke (a4), Münevver Doğramacı (a5), James V. Anderson (a6), David P. Horvath (a7), Wun S. Chao (a8) and Nishanth Tharayil (a9)...


Modern high-throughput molecular and analytical tools offer exciting opportunities to gain a mechanistic understanding of unique traits of weeds. During the past decade, tremendous progress has been made within the weed science discipline using genomic techniques to gain deeper insights into weedy traits such as invasiveness, hybridization, and herbicide resistance. Though the adoption of newer “omics” techniques such as proteomics, metabolomics, and physionomics has been slow, applications of these omics platforms to study plants, especially agriculturally important crops and weeds, have been increasing over the years. In weed science, these platforms are now used more frequently to understand mechanisms of herbicide resistance, weed resistance evolution, and crop–weed interactions. Use of these techniques could help weed scientists to further reduce the knowledge gaps in understanding weedy traits. Although these techniques can provide robust insights about the molecular functioning of plants, employing a single omics platform can rarely elucidate the gene-level regulation and the associated real-time expression of weedy traits due to the complex and overlapping nature of biological interactions. Therefore, it is desirable to integrate the different omics technologies to give a better understanding of molecular functioning of biological systems. This multidimensional integrated approach can therefore offer new avenues for better understanding of questions of interest to weed scientists. This review offers a retrospective and prospective examination of omics platforms employed to investigate weed physiology and novel approaches and new technologies that can provide holistic and knowledge-based weed management strategies for future.

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This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (, which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.

Corresponding author

Author for correspondence: Nishanth Tharayil, Department of Plant and Environmental Sciences, 105 Collings Street, Clemson University, Clemson, SC 29634. (Email:


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Abbas, HK, Duke, SO, Sheir, WT, Duke, MV (2002) Inhibition of ceramide synthesis in plants by phytotoxins. Pages 211219 in Upadhyay RK, ed. Advances in Microbial Toxin Research and Its Biochemical Exploitation. London: Kluwer Academic/Plenum
Agrawal, GK, Jwa, N, Lebrun, M, Job, D, Rakwal, R (2010) Plant secretome: unlocking secrets of the secreted proteins. Proteomics 10:799827
Ahsan, N, Lee, D-G, Lee, K-W, Alam, I, Lee, S-H, Bahk, JD, Lee, B-H (2008) Glyphosate-induced oxidative stress in rice leaves revealed by proteomic approach. Plant Physiol Biochem 46:10621070
Ali, M, Nair, KK, Kumar, R, Gopal, M, Srivastava, C, Siddiqi, WA (2017) Development and evaluation of chitosan-sodium alginate based etofenprox as nanopesticide. Adv Sci Eng Med 9:137143
Aliferis, KA, Chrysayi-Tokousbalides, M (2006) Metabonomic strategy for the investigation of the mode of action of the phytotoxin (5 S, 8 R, 13 S, 16 R)-(-)-pyrenophorol using 1H nuclear magnetic resonance fingerprinting. J Agric Food Chem 54:16871692
Aliferis, KA, Chrysayi-Tokousbalides, M (2011) Metabolomics in pesticide research and development: review and future perspectives. Metabolomics 7:3553
Aliferis, KA, Jabaji, S (2011) Metabolomics—a robust bioanalytical approach for the discovery of the modes-of-action of pesticides: a review. Pestic Biochem Physiol 100:105117
Amigo-Benavent, M, Clemente, A, Caira, S, Stiuso, P, Ferranti, P, Castillo, MD (2014) Use of phytochemomics to evaluate the bioavailability and bioactivity of antioxidant peptides of soybean β-conglycinin. Electrophoresis 35:15821589
An, J, Shen, X, Ma, Q, Yang, C, Liu, S, Chen, Y (2014) Transcriptome profiling to discover putative genes associated with paraquat resistance in goosegrass (Eleusine indica L.). PLoS ONE 9:e99940
Anderson, JV (2008) Emerging technologies: an opportunity for weed biology research. Weed Sci 56:281282
Anderson, JV, Delseny, M, Fregene, MA, Jorge, V, Mba, C, Lopez, C, Restrepo, S, Soto, M, Piegu, B, Verdier, V, Cooke, R (2004) An EST resource for cassava and other species of Euphorbiaceae. Plant Mol Biol 56:527539
Anderson, JV, Gesch, RW, Jia, Y, Chao, WS, Horvath, DP (2005) Seasonal shifts in dormancy status, carbohydrate metabolism, and related gene expression in crown buds of leafy spurge. Plant Cell Environ 28:15671578
Anderson, JV, Horvath, DP (2001) Random sequencing of cDNAs and identification of mRNAs. Weed Sci 49:590597
Anderson, JV, Horvath, DP, Chao, WS, Foley, ME, Hernandez, AG, Thimmapuram, J, Liu, L, Gong, GL, Band, M, Kim, R, Mikel, MA (2007) Characterization of an EST database for the perennial weed leafy spurge: an important resource for weed biology research. Weed Sci 55:193203
Arabidopsis Genome Initiative (2000) Analysis of the genome sequence of the flowering plant Arabidopsis thaliana . Nature 408:796815
Araníbar, N, Singh, BK, Stockton, GW, Ott, KH (2001) Automated mode-of-action detection by metabolic profiling. Biochem Biophys Res Commun 286:150155
Baerson, SR, Sánchez-Moreiras, A, Pedrol-Bonjoch, N, Schulz, M, Kagan, IA, Agarwal, AL, Reigosa, MJ, Duke, SO (2005) Detoxification and transcriptome response in Arabidopsis seedlings exposed to the allelochemical benzoxazolin-2(3H)-one (BOA). J Biol Chem 280:2186721881
Bajsa, J, Pan, Z, Dayan, FE, Owens, DK, Duke, SO (2012) Validation of serine/threonine protein phosphatase as the herbicide target site of endothall. Pestic Biochem Physiol 102:3844
Bajsa, J, Pan, Z, Duke, SO (2011a) Serine/threonine protein phosphatases: Multi-purpose enzymes in control of defense mechanisms. Plant Signal Behav 6:19211925
Bajsa, J, Pan, Z, Duke, SO (2011b) Transcriptional responses to cantharidin, a protein phosphatase inhibitor. in, Arabidopsis thaliana reveal the involvement of multiple signal transduction pathways. Physiol Plantarum 143:188205
Bajsa, J, Pan, Z, Duke, SO (2015) Cantharidin, a protein phosphatase inhibitor with broad effects on the transcriptome, strongly upregulates glutathione-S-transferase in the Arabidopsis proteome. J Plant Physiol 173:3340
Basu, C, Halfhill, MD, Mueller, TC, Stewart, CN (2004) Weed genomics: new tools to understand weed biology. Trend Plant Sci 9:391398
Beckwith, EJ, Yanovsky, MJ (2014) Circadian regulation of gene expression: at the crossroads of transcriptional and post-transcriptional regulatory networks. Curr Opin Genet Dev 27:3542
Bell, CJ, Dixon, RA, Farmer, AD, Flores, R, Inman, J, Gonzales, RA, Harrison, MJ, Paiva, NL, Scott, AD, Weller, JW, May, GD (2001) The Medicago Genome Initiative: a model legume database. Nucleic Acids Res 29:114117
Belz, RG, Duke, SO (2014) Herbicides and plant hormesis. Pest Manag Sci 70:698707
Bevan, M, Walsh, S (2005) The Arabidopsis genome: a foundation for plant research. Genome Res 15:16321642
Braun, P, Aubourg, S, Van Leene, J, De Jaeger, G, Lurin, C (2013) Plant protein interactomes. Annu Rev Plant Biol 64:161187
Brunetti, AE, Neto, FC, Vera, MC, Taboada, C, Pavarini, DP, Bauermeister, A, Lopes, NP (2018) An integrative omics perspective for the analysis of chemical signals in ecological interactions. Chem Soc Rev 42:15741591
Cantrell, CL, Duke, SO, Fronczek, FR, Osbrink, WLA, Mamonov, LK, Vassilyev, JI, Wedge, DE, Dayan, FE (2007) Phytotoxic eremophilanes from Ligularia macrophylla . J Agric Food Chem 55:1065610663
Chao, WS, Horvath, DP, Anderson, JV, Foley, ME (2005) Potential model weeds to study genomics, ecology, and physiology in the 21st century. Weed Sci 53:929937
Chen, J, Huang, H, Wei, S, Huang, Z, Wang, X, Zhang, C (2017) Investigating the mechanisms of glyphosate resistance in goosegrass (Eleusine indica (L.) Gaertn.) by RNA sequencing technology. Plant J 89:407415
Chen, S, McElroy, JS, Dane, F, Goertzen, LR (2016) Transcriptome assembly and comparison of an allotetraploid weed species, annual bluegrass, with its two diploid progenitor species, Poa supina Schrad and Poa infirma Kunth. Plant Genome 9, 10.3835/plantgenome2015.06.0050
Chi, WC, Fu, SF, Huang, TL, Chen, YA, Chen, CC, Huang, HJ (2011) Identification of transcriptome profiles and signaling pathways for the allelochemical juglone in rice roots. Plant Mol Biol 77:591607
Corbett, CA, Tardif, FJ (2006) Detection of resistance to acetolactate synthase inhibitors in weeds with emphasis on DNA-based techniques: a review. Pest Manag Sci 62:584597
Cummins, I, Wortley, DJ, Sabbadin, F, He, Z, Coxon, CR, Straker, HE, Sellars, JD, Knight, K, Edwards, L, Hughes, D, Kaundun, SS, Hutchings, SJ, Steel, PG, Edwards, R (2013) Key role for a glutathione transferase in multiple-herbicide resistance in grass weeds. Proc Natl Acad Sci USA 110:58125817
Das, M, Reichman, JR, Haberer, G, Welzl, G, Aceituno, FF, Mader, MT, Watrud, LS, Pfleeger, TG, Guiterrez, RA, Schaffner, AR, Olszyk, DM (2010) A composite transcriptional signature differentiates responses towards closely related herbicides in Arabidopsis thaliana and Brassica napus . Plant Mol Biol 72:545556
Dayan, FE, Duke, SO (2003) Herbicides: protoporphyrinogen oxidase inhibitors. Pages 850863 in Plimmer JR, Gammon DW & Ragsdale NN eds., Encyclopedia of Agrochemicals Volume 2. New York: Wiley
Dayan, FE, Duke, SO (2014) Natural compounds as next-generation herbicides. Plant Physiol 166:10901105
del Castillo, MD, Martinez-Saez, N, Amigo-Benavent, M, Silvan, JM (2013) Phytochemomics and other omics for permitting health claims made on foods. Food Res Int 54:12371249
Délye, C (2013) Unravelling the genetic bases of non-target-site-based resistance (NTSR) to herbicides: a major challenge for weed science in the forthcoming decade. Pest Manag Sci 69:176187
De Vos, RCH, Moco, S, Lommen, A, Keurentjes, JJ, Bino, RJ, Hall, RD (2007) Untargeted large-scale plant metabolomics using liquid chromatography coupled to mass spectrometry. Nat Protoc 2:778
Doğramacı, M, Anderson, JV, Chao, WS, Foley, ME (2014) Foliar application of glyphosate affects molecular mechanisms in underground adventitious buds of leafy spurge (Euphorbia esula) and alters their vegetative growth patterns. Weed Sci 62:217229
Doğramacı, M, Gramig, GG, Anderson, JV, Chao, WS, Foley, ME (2016) Field application of glyphosate induces molecular changes affecting vegetative growth processes in leafy spurge (Euphorbia esula). Weed Sci 64:87100
Doğramacı, M, Horvath, DP, Anderson, JV (2015) Meta-analysis identifies potential molecular markers for endodormancy in crown buds of leafy spurge. Pages 197219 in Anderson JV, ed. Advances in Plant Dormancy. Cham, Switzerland: Springer International
Dorn, KM, Fankhauser, JD, Wyse, DL, Marks, MD (2015) A draft genome of field pennycress (Thlaspi arvense) provides tools for the domestication of a new winter biofuel crop. DNA Res 22:121131
Duhoux, A, Carrère, S, Gouzy, J, Bonin, L, Délye, C (2015) RNA-Seq analysis of rye-grass transcriptomic response to an herbicide inhibiting acetolactate-synthase identifies transcripts linked to non-target-site-based resistance. Plant Mol Biol 87:473487
Duke, SO (2012) Why have no new herbicide modes of action appeared in recent years? Pest Manag Sci 68:505512
Duke, SO, Baerson, SR, Rimando, AM (2003) Glyphosate. In Plimmer JR, Gammon DW & Ragsdale NN eds., Encyclopedia of Agrochemicals Volume 2. New York: Wiley
Duke, SO, Bajsa, J, Pan, Z (2013) Omics methods for probing the mode of action of natural and synthetic phytotoxins. J Chem Ecol 39:333347
Duke, SO, Evidente, A, Fiore, M, Rimando, AM, Dayan, FE, Vurro, M, Christiansen, N, Looser, R, Hutzler, J, Grossmann, K (2011) Effects of the aglycone of ascaulitoxin on amino acid metabolism in Lemna paucicostata . Pestic Biochem Physiol 100:4150
Duke, SO, Heap, I (2017) Evolution of weed resistance to herbicides: what have we learned after seventy years? Pages 6386 in Jugulam M, ed. Biology, Physiology and Molecular Biology of Weeds. Boca Raton, FL: CRC
Duke, SO, Powles, SB (2008) Glyphosate: a once-in-a-century herbicide. Pest Manag Sci 64:319325
Faure, D, Tannières, M, Mondy, S, Dessaux, Y (2011) Recent contributions of metagenomics to studies on quorum-sensing and plant-pathogen interactions. Pages 253263 in Marco D, ed. Metagenomics: Current Innovations and Future Trends. London: Caister Academic
Fernández-Escalada, M, Gil-Monreal, M, Zabalza, A, Royuela, M (2016) Characterization of the Amaranthus palmeri physiological response to glyphosate in susceptible and resistant populations. J Agric Food Chem 64:95106
Fernández-Escalada, M, Zulet-González, A, Gil-Monreal, M, Zabalza, A, Ravet, K, Gaines, T, Royuela, M (2017) Effects of EPSPS copy number variation (CNV) and glyphosate application on the aromatic and branched chain amino acid synthesis pathways in Amaranthus palmeri . Front Plant Sci 8:1970
Fernie, AR, Morgan, JA (2013) Analysis of metabolic flux using dynamic labelling and metabolic modelling. Plant Cell Environ 36:17381750
Fiehn, O (2002) Metabolomics—the link between genotypes and phenotypes. Plant Mol Biol 48:155171
Finkel, E (2009) With “phenomics,” plant scientists hope to shift breeding into overdrive. Science 325:380381
Foley, ME, Chao, WS, Horvath, DP, Doğramacı, M, Anderson, JV (2013) The transcriptomes of dormant leafy spurge seeds under alternating temperature are differentially affected by a germination-enhancing pretreatment. J Plant Physiol 170:539547
Fraceto, LF, Grillo, R, de Medeiros, GA, Scognamiglio, V, Rea, G, Bartolucci, C (2016) Nanotechnology in agriculture: which innovation potential does it have? Front Environ Sci 4:20
Fukushima, A, Kusano, M, Redestig, H, Arita, M, Saito, K (2009) Integrated omics approaches in plant systems biology. Curr Opin Chem Biol 13:532538
Gaines, TA, Lorentz, L, Figge, A, Herrmann, J, Maiwald, F, Ott, MC, Han, H, Busi, R, Yu, Q, Powles, SB, Beffa, R (2014) RNA-Seq transcriptome analysis to identify genes involved in metabolism-based diclofop resistance in Lolium rigidum . Plant J 78:865876
Gaines, TA, Tranel, PJ, Fleming, MB, Patterson, EL, Küpper, A, Ravet, K, Giacomini, DA, Gonzalez, S, Beffa, R (2017) Applications of genomics in weed science. Pages 185217 in Jugulam M, ed. Biology, Physiology and Molecular Biology of Weeds. Boca Raton, FL: CRC Press
Gaines, TA, Zhang, W, Wang, D, Bukun, B, Chisholm, ST, Shaner, DL, Nissen, SJ, Patzoldt, WL, Tranel, PJ, Culpepper, AS, Grey, TL, Webster, TM, Vencill, WK, Sammons, RD, Jiang, J, Preston, C, Leach, JE, Westra, P (2010) Gene amplification confers glyphosate resistance in Amaranthus palmeri . Proc Natl Acad Sci USA 107:10291034
Gardin, JAC, Gouzy, J, Carrere, S, Delye, C (2015) ALOMYbase, a resource to investigate non-target-site-based resistance to herbicides inhibiting acetolactate-synthase (ALS) in the major grass weed Alopecurus myosuroides (black-grass). BMC Genomics 16:590
Gaudin, Z, Cerveau, D, Marnet, N, Bouchereau, A, Delavault, P, Simier, P, Pouvreau, JB (2014) Robust method for investigating nitrogen metabolism of 15N labeled amino acids using AccQ∙ Tag ultra performance liquid chromatography-photodiode array-electrospray ionization-mass spectrometry: application to a parasitic plant–plant interaction. Anal Chem 86:11381145
Giacomini, DA, Gaines, T, Beffa, R, Tranel, PJ (2018) Optimizing RNA-seq studies to investigate herbicide resistance. Pest Manag Sci, 10.1002/ps.4822
Gleixner, G, Scrimgeour, C, Schmidt, HL, Viola, R (1998) Stable isotope distribution in the major metabolites of source and sink organs of Solanum tuberosum L.: a powerful tool in the study of metabolic partitioning in intact plants. Planta 207:241245
Golisz, A, Sugano, M, Fujii, Y (2008) Microarray expression profiling of Arabidopsis thaliana L. in response to allelochemicals identified in buckwheat. J Exp Bot 59:30993109
Golisz, A, Sugano, M, Hiradate, S, Fujii, Y (2011) Microarray analysis of Arabidopsis plants in response to the allelochemical l-DOPA. Planta 233:231240
Großkinsky, DK, Svensgaard, J, Christensen, S, Roitsch, T (2015) Plant phenomics and the need for physiological phenotyping across scales to narrow the genotype-to-phenotype knowledge gap. J Exp Bot 66:54295440
Grossman, K, Chistiansen, N, Looser, R, Tresch, S, Hutzler, Pollmann S, Ehrhardt, T (2012aPhysionomics and metabolomics—two key approaches in herbicide mode of action discovery. Pest Manag Sci 68:294504
Grossmann, K, Hutzler, J, Tresch, S, Christiansen, N, Looser, R, Ehrhardt, (2012bOn the mode of action of the herbicide cinmethylin and 5-benzyloxymethyl-1,2-isoxazolines: putative inhibitors of plant tyrosine aminotransferase. Pest Manag Sci 68:482492
Grossmann, K, Niggeweg, R, Christiansen, N, Looser, R, Ehrhardt, T (2010) The herbicide saflufenacil (Kixor™) is a new inhibitor of protoporphyrinogen IX oxidase activity. Weed Sci 58:19
Guo, L, Qiu, J, Ye, C, Jin, G, Mao, L, Zhang, H, Yang, X, Peng, Q, Wang, Y, Jia, L, Lin, Z (2017) Echinochloa crus-galli genome analysis provides insight into its adaptation and invasiveness as a weed. Nature Commun 8:1031
Haggarty, J, Burgess, KE (2017) Recent advances in liquid and gas chromatography methodology for extending coverage of the metabolome. Curr Opin Biotechnol 43:7785
Han, H, Vila-Aiub, MM, Jalaludin, A, Yu, Q, Powles, SB (2017) A double EPSPS gene mutation endowing glyphosate resistance shows a remarkably high resistance cost. Plant Cell Environ 40:30313042
Hayles, J, Johnson, L, Worthley, C, Losic, D (2017) Nanopesticides: a review of current research and perspectives. Pages 193225 in Grumezescu AM, ed. New Pesticides and Soil Sensors. Amsterdam, Netherlands: Elsevier
He, Q, Kim, KW, Park, YJ (2017) Population genomics identifies the origin and signatures of selection of Korean weedy rice. Plant Biotechnol J 15:357366
Heinzle, E, Matsuda, F, Miyagawa, H, Wakasa, K, Nishioka, T (2007) Estimation of metabolic fluxes, expression levels and metabolite dynamics of a secondary metabolic pathway in potato using label pulse-feeding experiments combined with kinetic network modelling and simulation. Plant J 50:176187
Hirai, MY, Yano, M, Goodenowe, DB, Kanaya, S, Kimura, T, Awazuhara, M, Arita, M, Fujiwara, T, Saito, K (2004) Integration of transcriptomics and metabolomics for understanding of global responses to nutritional stresses in Arabidopsis thaliana . Proc Natl Acad Sci USA 101:1020510210
Hollomon, DW (2012) Do we have the tools to manage resistance in the future? Pest Manag Sci 68:149154
Horvath, DP (2010) Genomics for weed science. Curr Genomics 11:4751
Horvath, DP (2015) Dormancy-associated MADS-BOX genes: A review. Pages 137146 in Anderson J, ed. Advances in Plant Dormancy. Cham, Switzerland: Springer
Horvath, DP, Anderson, JV (2002) A molecular approach to understanding root bud dormancy in leafy spurge. Weed Sci 50:227231
Horvath, DP, Anderson, JV, Soto-Suárez, M, Chao, WS (2006) Transcriptome analysis of leafy spurge (Euphorbia esula) crown buds during shifts in well-defined phases of dormancy. Weed Sci 54:821827
Horvath, DP, Chao, WS, Anderson, JV (2002) Molecular analysis of signals controlling dormancy and growth in underground adventitious buds of leafy spurge. Plant Physiol 128:14391446
Horvath, DP, Chao, WS, Suttle, JC, Thimmapuram, J, Anderson, JV (2008) Transcriptome analysis identifies novel responses and potential regulatory genes involved in seasonal dormancy transitions of leafy spurge (Euphorbia esula L.). BMC Genomics 9:536
Horvath, DP, Patel, S, Doğramacı, M, Chao, WS, Anderson, JV, Foley, ME, Scheffler, B, Lazo, G, Dorn, K, Yan, C, Childers, A (2018) Gene space and transcriptome assemblies of leafy spurge (Euphorbia esula) identify promoter sequences, repetitive elements, high-quality markers, and a full-length chloroplast genome. Weed Sci 66:355367
Horvath, DP, Schaffer, R, West, M, Wisman, E (2003) Arabidopsis microarrays identify conserved and differentially expressed genes involved in shoot growth and development from distantly related plant species. Plant J 34:125134
Jaini, R, Wang, P, Dudareva, N, Chapple, C, Morgan, JA (2017) Targeted metabolomics of the phenylpropanoid pathway in Arabidopsis thaliana using reversed phase liquid chromatography coupled with tandem mass spectrometry. Phytochem Anal 28:267276
Jorrín-Novo, JV, Maldonado, AM, Echevarría-Zomeño, S, Valledor, L, Castillejo, MA, Curto, M, Valero, J, Sghaier, B, Donoso, G, Redondo, I (2009) Plant proteomics update (2007–2008): second-generation proteomic techniques, an appropriate experimental design, and data analysis to fulfill MIAPE standards, increase plant proteome coverage and expand biological knowledge. J Proteomics 72:285314
Kantar, MB, Nashoba, AR, Anderson, JE, Blackman, BK, Rieseberg, LH (2017) The genetics and genomics of plant domestication. BioScience 67:971982
Keith, BK, Burns, EE, Bothner, B, Carey, CC, Mazurie, AJ, Hilmer, JK, Biyiklioglu, S, Budak, H, Dyer, WE (2017) Intensive herbicide use has selected for constitutively elevated levels of stress-responsive mRNAs and proteins in multiple herbicide-resistant Avena fatua L. Pest Manag Sci 73:22672281
Kelly KB, Zhang Q, Lambert KN, Riechers DE (2006) Evaluation of auxin-responsive genes in soybean for detection of off-target growth regulator herbicides. Weed Sci 54:220–229
Kikuchi, J, Shinozaki, K, Hirayama, T (2004) Stable isotope labeling of Arabidopsis thaliana for an NMR-based metabolomics approach. Plant Cell Physiol 45:10991104
Kitano, H (2002) Systems biology: a brief overview. Science 295:16621664
Kohler, C, Springer, N (2017) Plant epigenomics—deciphering the mechanisms of epigenetic inheritance and plasticity in plants. Genome Biol 18:132
Kraehmer, H (2012) Innovation: changing trends in herbicide discovery. Outlooks Pest Manag 23:115118
Kreiner, JM, Stinchcombe, JR, Wright, SI (2018) Population genomics of herbicide resistance: adaptation via evolutionary rescue. Ann Rev Plant Biol 69, 10.1146/annurev-arplant-042817-040038
Kumar, S, Kumar, K, Pandey, P, Rajamani, V, Padmalatha, KV, Dhandapani, G, Kanakachari, M, Leelavathi, S, Kumar, PA, Reddy, VS (2013) Glycoproteome of elongating cotton fiber cells. Mol Cell Proteomics 12:36773689
Kumari, N, Narayan, OM, Rai, LC (2009) Understanding butachlor toxicity in Aulosira fertilissima using physiological, biochemical and proteomic approaches. Chemsophere 77:15011507
Lechelt-Kunze, C, Sans-Piché, F, Riedl, J, Altenburger, R, Haertig, C, Laue, G, Smitt-Jansen, M (2003) Flufenacet herbicide treatment phenocopies the fiddlehead mutant in Arabidopsis thaliana . Pest Manag Sci 59:847856
LeClere, S, Wu, C, Westra, P, Sammons, RD (2018) Cross-resistance to dicamba, 2,4-D, and fluroxypyr in Kochia scoparia is endowed by a mutation in an AUX/IAA gene. Proc Natl Acad Sci USA, 10.1073/pnas.1712372115
Lee, RM, Tranel, PJ (2008) Utilization of DNA microarrays in weed science research. Weed Sci 56:283289
Leslie, T, Baucom, RS (2014) De novo assembly and annotation of the transcriptome of the agricultural weed Ipomoea purpurea uncovers gene expression changes associated with herbicide resistance. G3-Genes Genomes Genetics 4:20352047
Liberman, LM, Sozzani, R, Benfey, PN (2012) Integrative systems biology: an attempt to describe a simple weed. Curr Opin Plant Biol 15:162167
Manabe, Y, Tinker, N, Colville, A, Miki, B (2007) CSR1, the sole target of imidazolinone herbicide in Arabidopsis thaliana . Plant Cell Physiol 48:13401358
Maroli, AS, Nandula, VK, Dayan, FE, Duke, SO, Gerard, P, Tharayil, N (2015) Metabolic profiling and enzyme analyses indicate a potential role of antioxidant systems in complementing glyphosate resistance in an Amaranthus palmeri biotype. J Agric Food Chem 63:91999209
Maroli, AS, Nandula, VK, Duke, SO, Gerard, P, Tharayil, N (2017) Comparative metabolomic analyses of Ipomoea lacunosa biotypes with contrasting glyphosate tolerance captures herbicide-induced differential perturbations in cellular physiology. J Agric Food Chem 66:20272039
Maroli, AS, Nandula, VK, Duke, SO, Tharayil, N (2016) Stable isotope resolved metabolomics reveals the role of anabolic and catabolic processes in glyphosate-induced amino acid accumulation in Amaranthus palmeri biotypes. J Agric Food Chem 64:70407048
Matzrafi, M, Shaar-Moshe, L, Rubin, B, Peleg, Z (2017) Unraveling the transcriptional basis of temperature-dependent pinoxaden resistance in Brachypodium hybridum . Front Plant Sci 8:1064
Maxwell, BD, Foley, ME, Fay, PK (1987) The influence of glyphosate on bud dormancy in leafy spurge (Euphorbia esula). Weed Sci 35:610
McElroy, JS (2018) Weed Genomic Data Repository. Accessed: April 12, 2018
Miyagi, A, Takahara, K, Kasajima, I, Takahashi, H, Kawai-Yamada, M, Uchimiya, H (2011) Fate of 13C in metabolic pathways and effects of high CO2 on the alteration of metabolites in Rumex obtusifolius L. Metabolomics 7:524535
Miyagi, A, Takahara, K, Takahashi, H, Kawai-Yamada, M, Uchimiya, H (2010) Targeted metabolomics in an intrusive weed, Rumex obtusifolius L., grown under different environmental conditions reveals alterations of organ related metabolite pathway. Metabolomics 6:497510
Moghe, GD, Hufnagel, DE, Tang, H, Xiao, Y, Dworkin, I, Town, CD, Conner, JK, Shiu, SH (2014) Consequences of whole-genome triplication as revealed by comparative genomic analyses of the wild radish Raphanus raphanistrum and three other Brassicaceae species. Plant Cell 26:19251937
Molin, WT, Wright, AA, Lawton-Rauh, A, Saski, CA (2017) The unique genomic landscape surrounding the EPSPS gene in glyphosate resistant Amaranthus palmeri: a repetitive path to resistance. BMC Genomics 18:91
Morsy, M, Gouthu, S, Orchard, S, Thorneycroft, D, Harper, JF, Mittler, R, Cushman, JC (2008) Charting plant interactomes: possibilities and challenges. Trends Plant Sci 13:183191
Nandula, VK, Reddy, KN, Koger, CH, Poston, DH, Rimando, AM, Duke, SO, Bond, JA, Ribeiro, DN (2012) Multiple resistance to glyphosate and pyrithiobac in Palmer amaranth (Amaranthus palmeri) from Mississippi and response to flumiclorac. Weed Sci 60:179188
Nandula, VK, Reddy, KN, Rimando, AM, Duke, SO, Poston, DH (2007) Glyphosate-resistant and -susceptible soybean (Glycine max) and canola (Brassica napus) dose response and metabolism relationships with glyphosate. J Agric Food Chem 55:35403545
Narayanan, R, Van de Ven, WJM (2014) Transcriptome and proteome analysis: a perspective on correlation. MOJ Proteomics Bioinform 1:00027
Narayanan, S, Tamura, PJ, Roth, MR, Prasad, PVV, Welti, R (2016) Wheat leaf lipids during heat stress: I. high day and night temperatures result in major lipid alterations. Plant Cell Environ 39:787803
Nelson, R, Wiesner-Hanks, T, Wisser, R, Balint-Kurti, P (2018) Navigating complexity to breed disease-resistant crops. Nat Rev Genet 19:2133
Nestler, H, Groh, KJ, Schönenberger, R, Eggen, RIL, Suter, MJ-F (2012) Linking proteome responses with physiological and biochemical effects of herbicide-exposed Chlamydomonas reinhardii . J Proteome 75:53705385
Niittylae, T, Chaudhuri, B, Sauer, U, Frommer, WB (2009) Comparison of quantitative metabolite imaging tools and carbon-13 techniques for fluxomics. Pages 355372 in Belostotsky D, ed. Plant Systems Biology. Methods in Molecular Biology (Methods and Protocols) Volume 553. New York: Humana
Nuhse, TS, Stensballe, A, Jensen, ON, Peck, SC (2004) Phosphoproteomics of the Arabidopsis plasma membrane and a new phosphorylation site database. Plant Cell 16:23942405
Olsen KM, Caicedo AL, Jia Y (2007) Evolutionary genomics of weedy rice in the USA. J Integr Plant Biol 49:811–816
Palsson, B (2002) In silico biology through “omics”. Nat Biotechnol 20:649650
Parisi, C, Vigani, M, Rodríguez-Cerezo, E (2015) Agricultural nanotechnologies: what are the current possibilities? Nano Today 10:124127
Pasquer, F, Ochsner, U, Zarn, J, Keller, B (2006) Common and distinct gene expression patterns induced by the herbicides 2,4-dichlorophenoxyacetic acid, cinidon-ethyl and tribenuron-methyl in wheat. Pest Manag Sci 62:11551167
Payne, SH (2015) The utility of protein and mRNA correlation. Trends Biochem Sci 40:13
Pedersen, HL, Fangel, JU, McCleary, B, Ruzanski, C, Rydahl, MG, Ralet, M, Farkas, V, von Schantz, L, Marcus, SE, Andersen, MCF, Field R, Ohlin M, Knox JP, Clausen MH, Willats WGT (2012) Versatile high resolution oligosaccharide microarrays for plant glycobiology and cell wall research. J Biol Chem 287:3942939438
Peng, Y, Abercrombie, LLG, Yuan, JS, Riggins, CW, Sammons, RD, Tranel, PJ, Stewart, CN (2010) Characterization of the horseweed (Conyza canadensis) transcriptome using GS-FLX 454 pyrosequencing and its application for expression analysis of candidate non-target herbicide resistance genes. Pest Manag Sci 66:10531062
Peng, Y, Lai, Z, Lane, T, Nageswara-Rao, M, Okada, M, Jasieniuk, M, O’Geen, H, Kim, RW, Sammons, RD, Rieseberg, LH, Stewart, CN (2014) De novo genome assembly of the economically important weed horseweed using integrated data from multiple sequencing platforms. Plant Physiol 166:12411254
Perazzolli, M, Palmieri, MC, Matafora, V, Bachi, A, Pertot, I (2016) Phosphoproteomic analysis of induced resistance reveals activation of signal transduction processes by beneficial and pathogenic interaction in grapevine. J Plant Physiol 195:5972
Pérez-Alonso, MM, Carrasco-Loba, V, Medina, J, Vicente-Carbajosa, J, Pollmann, S (2018) When transcriptomics and metabolomics work hand in hand: a case study characterizing plant CDF transcription factors. High Throughput 7:7
Raghavan, V, Ong, EK, Dalling, MJ, Stevenson, TW (2006) Regulation of genes associated with auxin, ethylene and ABA pathways by 2,4-dichlorophenoxyacetic acids in Arabidopsis . Funct Integr Genom 6:6070
Ravet, K, Patterson, E, Krähmer, H, Hamouzová, K, Fan, L, Jasieniuk, M, Lawton-Rauh, A, Malone, J, McElroy, JS, Merotto, A, Westra, P, Preston, C, Vila-Aiub, M, Busi, R, Tranel, P, Reinhardt, C, Saski, C, Beffa, R, Neve, P, Gaines, T (2018) The power and potential of genomics in weed biology and management. Pest Manag Sci, 10.1002/ps.5048
Riggins, CW, Peng, YH, Stewart, CN, Tranel, PJ (2010) Characterization of de novo transcriptome for waterhemp (Amaranthus tuberculatus) using GS-FLX 454 pyrosequencing and its application for studies of herbicide target-site genes. Pest Manag Sci 66:10421052
Rochfort, S (2005) Metabolomics reviewed: a new “omics” platform technology for systems biology and implications for natural products research. J Nat Prod 68:18131820
Roossinck, MJ (2015) Metagenomics of plant and fungal viruses reveals an abundance of persistent lifestyles. Front Microbiol 5:767
Sauer, U (2006) Metabolic networks in motion: 13C-based flux analysis. Mol Syst Biol 2:62
Schena, M, Shalon, D, Davis, RW, Brown, PO (1995) Quantitative monitoring of gene expression patterns with a complementary DNA microarray. Science 270:467470
Serra, AA, Couée, I, Renault, D, Gouesbet, G, Sulmon, C (2015) Metabolic profiling of Lolium perenne shows functional integration of metabolic responses to diverse subtoxic conditions of chemical stress. J Exp Bot 66:18011816
Shaner, DL, Beckie, HJ (2014) The future for weed control and technology. Pest Manag Sci 70:13291339
Srivastava, A, Kowalski, GM, Callahan, DL, Meikle, PJ, Creek, DJ (2016) Strategies for extending metabolomics studies with stable isotope labelling and fluxomics. Metabolites 6:32
Stewart, CN Jr, ed (2009) Weedy and Invasive Plant Genomics. Hoboken, NJ: Wiley. 253 p
Stewart, CN Jr, Tranel, PJ, Horvath, DP, Anderson, JV, Rieseberg, LH, Westwood, JH, Mallory-Smith, CA, Zapiola, ML, Dlugosch, KM (2009) Evolution of weediness and invasiveness: charting the course for weed genomics. Weed Sci 57:451462
Stewart, CN Jr, Yanhui, P, Abercrombie, LG, Halfhill, MD, Rao, MR, Ranjan, P, Hu, J, Sammons, RD, Heck, GR, Tranel, PJ, Yuan, JS (2010) Genomics of glyphosate resistance. Pages 149165 in Nandula VK, ed. Glyphosate Resistance in Crops and Weeds: History, Development and Management. Hoboken, NJ: Wiley
Sumner, LW, Lei, Z, Nikolau, BJ, Saito, K (2015) Modern plant metabolomics: advanced natural product gene discoveries, improved technologies, and future prospects. Nat Prod Rep 32:212229
Szechyńska-Hebda, M, Budiak, P, Gawroński, P, Górecka, M, Kulasek, M, Karpiński, S (2015) Plant physiomics: photoelectrochemical and molecular retrograde signalling in plant acclimatory and defence responses. Pages 439457 in Barh D, Khan M & Davies E eds., PlantOmics: The Omics of Plant Science. New Delhi: Springer
Tan, W, Gao, Q, Deng, C, Wang, Y, Lee, WY, Hernandez-Viezcas, JA, Peralta-Videa, JR, Gardea-Torresdey, JL (2018) Foliar exposure of Cu(OH)2 nanopesticide to basil (Ocimum basilicum): variety-dependent copper translocation and biochemical responses. J Agric Food Chem 66:33583366
Tanveer, T, Shaheen, K, Parveen, S, Kazi, AG, Ahmad, P (2014) Plant secretomics: identification, isolation, and biological significance under environmental stress. Plant Signal Behav 9:e29426
Thaysen-Andersen, M, Packer, NH (2014) Advances in LC–MS/MS-based glycoproteomics: getting closer to system-wide site-specific mapping of the N- and O-glycoproteome. Biochim Biophys Acta 1844:14371452
Tranel, PJ, Horvath, DP (2009) Molecular biology and genomics: new tools for weed science. BioScience 59:207215
Trenkamp, S, Eckes, P, Busch, M, Fernie, AR (2009) Temporarily resolved GC-MS-based metabolic profiling of herbicide treated plants reveals that changes in polar primary metabolites alone can distinguish herbicides of differing modes of action. Metabolomics 5:277291
van Bentem, SDLF, Hirt, H (2007) Using phosphoproteomics to reveal signalling dynamics in plants. Trends Plant Sci 12:404411
Velini, ED, Alves, E, Godoy, MC, Meschede, DK, Souza, RT, Duke, SO (2008) Glyphosate applied at low doses can stimulate plant growth. Pest Manag Sci 64:489496
Venturelli, S, Belz, RG, Kämper, A, Berger, A, von Horn, K, Wegner, A, Böcker, A, Zabulon, G, Lagenecker, T, Kohlbacher, O, Bameche, F, Weigel, D, Lauer, UM, Bitzer, M, Becker, C (2015) Plants release precursors of histone deacetylase inhibitors to suppress growth of inhibitors. Plant Cell 27:31753189
Vivancos, PD, Driscoll, SP, Bulman, CA, Ying, L, Emami, K, Treumann, A, Mauve, C, Noctor, G, Foyer, CH (2011) Perturbations of amino acid metabolism associated with glyphosate-dependent inhibition of shikimic acid metabolism affect cellular redox homeostasis and alter the abundance of proteins involved in photosynthesis and photorespiration. Plant Physiol 157:256268
Vogel, JP, Garvin, DF, Mockler, TC, Schmutz, J, Rokhsar, D, Bevan, MW, Barry, K, Lucas, S, Harmon-Smith, M, Lail, K, Tice, H (2010) Genome sequencing and analysis of the model grass Brachypodium distachyon . Nature 463:763768
Wang, CS, Lin, WT, Chiang, YJ, Wang, CY (2017) Metabolism of fluazifop-P-butyl in resistant goosegrass (Eleusine indica) in Taiwan. Weed Sci 65:228238
Wang, Z, Li, Q, Zhao, J, Peng, Y (2011) Investigation of the effect of herbicide amprophos methyl on spindle formation and proteome change in maize by immunofluroscence and proteomic technique. Cytologia 76:249259
Welti, R, Shah, J, Li, W, Li, M, Chen, J, Burke, JJ, Fauconnier, M, Chapman, K, Chye, M, Wang, X (2007) Plant lipidomics: discerning biological function by profiling plant complex lipids using mass spectrometry. Front Biosci 12:24942506
Wiersma, AT, Gaines, TA, Preston, C, Hamilton, JP, Giacomini, D, Buell, CR, Leach, JE, Westra, P (2015) Gene amplification of 5-enol-pyruvylshikimate-3-phosphate synthase in glyphosate-resistant Kochia scoparia . Planta 241:463474
Wright, AA, Rodriguez-Carres, M, Sasidharan, R, Koski, L, Peterson, DG, Nandula, VK, Ray, JD, Bond, JA, Shaw, DR (2018a) Multiple herbicide–resistant junglerice (Echinochloa colona): identification of genes potentially involved in resistance through differential gene expression analysis. Weed Sci 66:347354
Wright, AA, Sasidharan, R, Koski, L, Rodriguez-Carres, M, Peterson, DG, Nandula, VK, Ray, JD, Bond, JA, Shaw, DR (2018b) Transcriptomic changes in Echinochloa colona in response to treatment with the herbicide imazamox. Planta 247:369379
Wu, S, Tohge, T, Cuadros-Inostroza, Á, Tong, H, Tenenboim, H, Kooke, R, Méret, M, Keurentjes, JB, Nikoloski, Z, Fernie, AR, Willmitzer, L (2018) Mapping the Arabidopsis metabolic landscape by untargeted metabolomics at different environmental conditions. Mol Plant 11:118134
Yadav, N, Khurana, SMP, Yadav, DK (2015a) Plant secretomics: unique initiatives. Pages 357384 in Barh D, Khan M & Davies E eds., PlantOmics: The Omics of Plant Science. New Delhi: Springer
Yadav, S, Yadav, DK, Yadav, N, Khurana, SMP (2015b) Plant glycomics. Advances and applications. Pages 299329 in Barh D, Khan M & Davies E eds., PlantOmics: The Omics of Plant Science. New Delhi: Springer
Yang, X, Yu, X-Y, Li, Y-F (2013) De novo assembly and characterization of the barnyardgrass (Echinochloa crus-galli) transcriptome using next-generation pyrosequencing. PLoS ONE 8:e69168
Yang, X, Zhang, Z, Gu, T, Dong, M, Peng, Q, Bai, L, Li, Y (2017) Quantitative proteomics reveals ecological fitness cost of multi-herbicide resistant barnyardgrass (Echinochloa crus-galli L.). J Proteomics 150:160169
Zhang, Q, Reichers, DE (2008) Proteomics: an emerging technology for weed science research. Weed Sci 56:306313
Zhang, X (2008) The epigenetic landscape of plants. Science 320:489492
Zhao, B, Huo, J, Liu, N, Zhang, J, Dong, J (2018) Transketolase is identified as a target of herbicidal substance α-terthienyl by proteomics. Toxins 10:41
Zhao, L, Hu, Q, Huang, Y, Fulton, AN, Hannah-Bick, C, Adeleye, AS, Keller, AA (2017a) Activation of antioxidant and detoxification gene expression in cucumber plants exposed to a Cu(OH)2 nanopesticide. Environ Sci: Nano 4:17501760
Zhao, L, Hu, Q, Huang, Y, Keller, AA (2017b) Response at genetic, metabolic, and physiological levels of maize (Zea mays) exposed to a Cu(OH)2 nanopesticide. ACS Sustainable Chem Eng 5:82948301
Zhao, L, Huang, Y, Adeleye, AS, Keller, AA (2017c) Metabolomics reveals Cu(OH)2 nanopesticide-activated anti-oxidative pathways and decreased beneficial antioxidants in spinach leaves. Environ Sci Technol 51:1018410194
Zhu, J, Patzoldt, WL, Radwan, O, Tranel, PJ, Clough, SJ (2009) Effects of photosystem II-interfering herbicides atrazine and bentazon on the soybean transcriptome. Plant Genome 2:191205
Zhu, J, Patzoldt, WL, Shealy, RT, Vodkin, LO, Clough, SJ, Tranel, PJ (2008) Transcriptome response to glyphosate in sensitive and resistant soybean. J Agric Food Chem 56:63556363


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