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

Abstract 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.

[1]  Samuel H. Payne,et al.  The utility of protein and mRNA correlation. , 2015, Trends in biochemical sciences.

[2]  S. Christensen,et al.  Plant phenomics and the need for physiological phenotyping across scales to narrow the genotype-to-phenotype knowledge gap. , 2015, Journal of experimental botany.

[3]  M. Hirai,et al.  Integration of transcriptomics and metabolomics for understanding of global responses to nutritional stresses in Arabidopsis thaliana. , 2004, Proceedings of the National Academy of Sciences of the United States of America.

[4]  L. Rai,et al.  Understanding butachlor toxicity in Aulosira fertilissima using physiological, biochemical and proteomic approaches. , 2009, Chemosphere.

[5]  A. Fernie,et al.  Temporally resolved GC-MS-based metabolic profiling of herbicide treated plants treated reveals that changes in polar primary metabolites alone can distinguish herbicides of differing mode of action , 2008, Metabolomics.

[6]  S. Duke,et al.  Omics Methods for Probing the Mode of Action of Natural and Synthetic Phytotoxins , 2013, Journal of Chemical Ecology.

[7]  Patrick J. Tranel,et al.  Molecular Biology and Genomics: New Tools for Weed Science , 2009 .

[8]  J. Stinchcombe,et al.  Population Genomics of Herbicide Resistance: Adaptation via Evolutionary Rescue. , 2018, Annual review of plant biology.

[9]  Ryan M. Lee,et al.  Utilization of DNA Microarrays in Weed Science Research , 2008 .

[10]  S. Duke,et al.  Inhibition of Ceramide Synthesis in Plants by Phytotoxins , 2002 .

[11]  W. Chao,et al.  Field Application of Glyphosate Induces Molecular Changes Affecting Vegetative Growth Processes in Leafy Spurge (Euphorbia esula) , 2016, Weed Science.

[12]  L. Ying,et al.  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 Photorespiration1[W][OA] , 2011, Plant Physiology.

[13]  Kazuki Saito,et al.  Integrated omics approaches in plant systems biology. , 2009, Current opinion in chemical biology.

[14]  Tyr Wiesner-Hanks,et al.  Navigating complexity to breed disease-resistant crops , 2017, Nature Reviews Genetics.

[15]  Fumio Matsuda,et al.  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. , 2007, The Plant journal : for cell and molecular biology.

[16]  C. N. Stewart,et al.  Characterization of de novo transcriptome for waterhemp (Amaranthus tuberculatus) using GS-FLX 454 pyrosequencing and its application for studies of herbicide target-site genes. , 2010, Pest management science.

[17]  M. Roossinck Metagenomics of plant and fungal viruses reveals an abundance of persistent lifestyles , 2015, Front. Microbiol..

[18]  B. Keller,et al.  Common and distinct gene expression patterns induced by the herbicides 2,4-dichlorophenoxyacetic acid, cinidon-ethyl and tribenuron-methyl in wheat. , 2006, Pest management science.

[19]  P. Jha,et al.  Inter-specific gene flow from herbicide-tolerant crops to their wild relatives , 2017 .

[20]  P. Tranel,et al.  Optimizing RNA-seq studies to investigate herbicide resistance. , 2018, Pest management science.

[21]  Milena Kulasek,et al.  Plant Physiomics: Photoelectrochemical and Molecular Retrograde Signalling in Plant Acclimatory and Defence Responses , 2015 .

[22]  D. Renault,et al.  Metabolic profiling of Lolium perenne shows functional integration of metabolic responses to diverse subtoxic conditions of chemical stress. , 2015, Journal of experimental botany.

[23]  L. Bai,et al.  Quantitative proteomics reveals ecological fitness cost of multi-herbicide resistant barnyardgrass (Echinochloa crus-galli L.). , 2017, Journal of proteomics.

[24]  S. Duke,et al.  Phytotoxic Eremophilanes from Ligularia macrophylla. , 2007, Journal of agricultural and food chemistry.

[25]  C. H. Koger,et al.  Multiple Resistance to Glyphosate and Pyrithiobac in Palmer Amaranth (Amaranthus palmeri) from Mississippi and Response to Flumiclorac , 2012 .

[26]  Kazuo Shinozaki,et al.  Stable isotope labeling of Arabidopsis thaliana for an NMR-based metabolomics approach. , 2004, Plant & cell physiology.

[27]  S. Duke,et al.  Stable Isotope Resolved Metabolomics Reveals the Role of Anabolic and Catabolic Processes in Glyphosate-Induced Amino Acid Accumulation in Amaranthus palmeri Biotypes. , 2016, Journal of agricultural and food chemistry.

[28]  E. Finkel Imaging. With 'phenomics,' plant scientists hope to shift breeding into overdrive. , 2009, Science.

[29]  M. Delseny,et al.  An EST resource for cassava and other species of Euphorbiaceae , 2004, Plant Molecular Biology.

[30]  D. Horvath,et al.  Random sequencing of cDNAs and identification of mRNAs , 2001, Weed Science.

[31]  J. Thimmapuram,et al.  Transcriptome analysis identifies novel responses and potential regulatory genes involved in seasonal dormancy transitions of leafy spurge (Euphorbia esula L.) , 2008, BMC Genomics.

[32]  Y. Fujii,et al.  Microarray expression profiling of Arabidopsis thaliana L. in response to allelochemicals identified in buckwheat , 2008, Journal of experimental botany.

[33]  W. Chao,et al.  Foliar Application of Glyphosate Affects Molecular Mechanisms in Underground Adventitious Buds of Leafy Spurge (Euphorbia esula) and Alters Their Vegetative Growth Patterns , 2014, Weed Science.

[34]  Takayuki Tohge,et al.  Mapping the Arabidopsis Metabolic Landscape by Untargeted Metabolomics at Different Environmental Conditions. , 2018, Molecular plant.

[35]  S. Duke,et al.  Glyphosate applied at low doses can stimulate plant growth. , 2008, Pest management science.

[36]  H. Kitano Systems Biology: A Brief Overview , 2002, Science.

[37]  Johannes Hutzler,et al.  Effects of the aglycone of ascaulitoxin on amino acid metabolism in Lemna paucicostata , 2011 .

[38]  Jennifer W. Weller,et al.  The Medicago Genome Initiative: a model legume database , 2001, Nucleic Acids Res..

[39]  P. Tranel,et al.  Effects of Photosystem‐II‐Interfering Herbicides Atrazine and Bentazon on the Soybean Transcriptome , 2009 .

[40]  J. Gouzy,et al.  RNA-Seq analysis of rye-grass transcriptomic response to an herbicide inhibiting acetolactate-synthase identifies transcripts linked to non-target-site-based resistance , 2015, Plant Molecular Biology.

[41]  Marie-Laure Fauconnier,et al.  Plant lipidomics: discerning biological function by profiling plant complex lipids using mass spectrometry. , 2007, Frontiers in bioscience : a journal and virtual library.

[42]  S. Duke,et al.  Transcriptional responses to cantharidin, a protein phosphatase inhibitor, in Arabidopsis thaliana reveal the involvement of multiple signal transduction pathways. , 2011, Physiologia plantarum.

[43]  C. Chapple,et al.  Targeted Metabolomics of the Phenylpropanoid Pathway in Arabidopsis thaliana using Reversed Phase Liquid Chromatography Coupled with Tandem Mass Spectrometry. , 2017, Phytochemical analysis : PCA.

[44]  T. Stevenson,et al.  Regulation of genes associated with auxin, ethylene and ABA pathways by 2,4-dichlorophenoxyacetic acid in Arabidopsis , 2005, Functional & Integrative Genomics.

[45]  A. Keller,et al.  Response at Genetic, Metabolic, and Physiological Levels of Maize (Zea mays) Exposed to a Cu(OH)2 Nanopesticide , 2017 .

[46]  Y. Fujii,et al.  Microarray analysis of Arabidopsis plants in response to allelochemical l-DOPA , 2011, Planta.

[47]  T. Ehrhardt,et al.  On the mode of action of the herbicides cinmethylin and 5-benzyloxymethyl-1, 2-isoxazolines: putative inhibitors of plant tyrosine aminotransferase. , 2012, Pest management science.

[48]  John Hayles,et al.  Nanopesticides: a review of current research and perspectives , 2017 .

[49]  E. Wisman,et al.  Arabidopsis microarrays identify conserved and differentially expressed genes involved in shoot growth and development from distantly related plant species. , 2003, The Plant journal : for cell and molecular biology.

[50]  M. E. Foley,et al.  The Influence of Glyphosate on Bud Dormancy in Leafy Spurge (Euphorbia esula) , 1987, Weed Science.

[51]  P. Tranel,et al.  Transcriptome response to glyphosate in sensitive and resistant soybean. , 2008, Journal of agricultural and food chemistry.

[52]  Nicolle H Packer,et al.  Advances in LC-MS/MS-based glycoproteomics: getting closer to system-wide site-specific mapping of the N- and O-glycoproteome. , 2014, Biochimica et biophysica acta.

[53]  U. Sauer,et al.  Article number: 62 REVIEW Metabolic networks in motion: 13 C-based flux analysis , 2022 .

[54]  S. Powles,et al.  RNA-Seq transcriptome analysis to identify genes involved in metabolism-based diclofop resistance in Lolium rigidum. , 2014, The Plant journal : for cell and molecular biology.

[55]  A. Stensballe,et al.  Phosphoproteomics of the Arabidopsis Plasma Membrane and a New Phosphorylation Site Databasew⃞ , 2004, The Plant Cell Online.

[56]  Sandra Orchard,et al.  Charting plant interactomes: possibilities and challenges. , 2008, Trends in plant science.

[57]  K. N. Reddy,et al.  Glyphosate-resistant and -susceptible soybean (Glycine max) and canola (Brassica napus) dose response and metabolism relationships with glyphosate. , 2007, Journal of agricultural and food chemistry.

[58]  Qin Zhang,et al.  Proteomics: An Emerging Technology for Weed Science Research , 2008 .

[59]  Hansjoerg Kraehmer Innovation: Changing Trends in Herbicide Discovery , 2012 .

[60]  N. Tinker,et al.  CSR1, the sole target of imidazolinone herbicide in Arabidopsis thaliana. , 2007, Plant & cell physiology.

[61]  K. Aliferis,et al.  Metabolomics in pesticide research and development: review and future perspectives , 2011, Metabolomics.

[62]  A E Brunetti,et al.  An integrative omics perspective for the analysis of chemical signals in ecological interactions. , 2018, Chemical Society reviews.

[63]  Nicole Christiansen,et al.  Physionomics and metabolomics-two key approaches in herbicidal mode of action discovery. , 2012, Pest management science.

[64]  D. Riechers,et al.  Evaluation of auxin-responsive genes in soybean for detection of off-target plant growth regulator herbicides , 2006, Weed Science.

[65]  Mauro Vigani,et al.  Agricultural nanotechnologies: What are the current possibilities? , 2015 .

[66]  Dinesh Kumar Yadav,et al.  Plant Glycomics: Advances and Applications , 2015 .

[67]  Heribert Hirt,et al.  Using phosphoproteomics to reveal signalling dynamics in plants. , 2007, Trends in plant science.

[68]  Maja G. Rydahl,et al.  Versatile High Resolution Oligosaccharide Microarrays for Plant Glycobiology and Cell Wall Research* , 2012, The Journal of Biological Chemistry.

[69]  Jingchao Chen,et al.  Investigating the mechanisms of glyphosate resistance in goosegrass (Eleusine indica (L.) Gaertn.) by RNA sequencing technology , 2017, The Plant journal : for cell and molecular biology.

[70]  S. Duke,et al.  Detoxification and Transcriptome Response in Arabidopsis Seedlings Exposed to the Allelochemical Benzoxazolin-2(3H)-one* , 2005, Journal of Biological Chemistry.

[71]  Yong‐feng Li,et al.  De novo Assembly and Characterization of the Barnyardgrass (Echinochloa crus-galli) Transcriptome Using Next-Generation Pyrosequencing , 2013, PloS one.

[72]  W. Chao,et al.  Potential model weeds to study genomics, ecology, and physiology in the 21st century , 2005, Weed Science.

[73]  P. Prasad,et al.  Wheat leaf lipids during heat stress: I. High day and night temperatures result in major lipid alterations. , 2016, Plant, cell & environment.

[74]  J. Silvan,et al.  Phytochemomics and other omics for permitting health claims made on foods , 2013 .

[75]  Bernhard Palsson,et al.  In silico biology through “omics” , 2002, Nature Biotechnology.

[76]  S. Duke,et al.  Metabolic Profiling and Enzyme Analyses Indicate a Potential Role of Antioxidant Systems in Complementing Glyphosate Resistance in an Amaranthus palmeri Biotype. , 2015, Journal of agricultural and food chemistry.

[77]  C. N. Stewart,et al.  Weed genomics: new tools to understand weed biology. , 2004, Trends in plant science.

[78]  Hideyuki Takahashi,et al.  Fate of 13C in metabolic pathways and effects of high CO2 on the alteration of metabolites in Rumex obtusifolius L. , 2011, Metabolomics.

[79]  Qinjie Chu,et al.  Echinochloa crus-galli genome analysis provides insight into its adaptation and invasiveness as a weed , 2017, Nature Communications.

[80]  K. Burgess,et al.  Recent advances in liquid and gas chromatography methodology for extending coverage of the metabolome. , 2017, Current opinion in biotechnology.

[81]  S. Duke,et al.  Cantharidin, a protein phosphatase inhibitor, strongly upregulates detoxification enzymes in the Arabidopsis proteome. , 2015, Journal of plant physiology.

[82]  R. Gesch,et al.  Seasonal shifts in dormancy status, carbohydrate metabolism, and related gene expression in crown buds of leafy spurge , 2005 .

[83]  M. Gil-Monreal,et al.  Characterization of the Amaranthus palmeri Physiological Response to Glyphosate in Susceptible and Resistant Populations. , 2016, Journal of agricultural and food chemistry.

[84]  David Horvath,et al.  Genomics for Weed Science , 2010, Current genomics.

[85]  O. Fiehn Metabolomics – the link between genotypes and phenotypes , 2004, Plant Molecular Biology.

[86]  Jingao Dong,et al.  Transketolase Is Identified as a Target of Herbicidal Substance α-Terthienyl by Proteomics , 2018, Toxins.

[87]  J. Gouzy,et al.  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) , 2015, BMC Genomics.

[88]  S. Duke,et al.  Comparative Metabolomic Analyses of Ipomoea lacunosa Biotypes with Contrasting Glyphosate Tolerance Captures Herbicide-Induced Differential Perturbations in Cellular Physiology. , 2017, Journal of agricultural and food chemistry.

[89]  Aurélien Mazurie,et al.  Intensive herbicide use has selected for constitutively elevated levels of stress-responsive mRNAs and proteins in multiple herbicide-resistant Avena fatua L. , 2017, Pest management science.

[90]  R. Baucom,et al.  De Novo Assembly and Annotation of the Transcriptome of the Agricultural Weed Ipomoea purpurea Uncovers Gene Expression Changes Associated with Herbicide Resistance , 2014, G3: Genes, Genomes, Genetics.

[91]  Uwe Sauer,et al.  Comparison of quantitative metabolite imaging tools and carbon-13 techniques for fluxomics. , 2009, Methods in molecular biology.

[92]  Paul Henman Targeted! , 2004 .

[93]  V. S. Reddy,et al.  Glycoproteome of Elongating Cotton Fiber Cells* , 2013, Molecular & Cellular Proteomics.

[94]  S. Duke,et al.  Serine/threonine protein phosphatases: Multi-purpose enzymes in control of defense mechanisms , 2011, Plant Signalling & Behavior.

[95]  T. Ehrhardt,et al.  The Herbicide Saflufenacil (Kixor™) is a New Inhibitor of Protoporphyrinogen IX Oxidase Activity , 2010, Weed Science.

[96]  S. Duke,et al.  Natural Compounds as Next-Generation Herbicides , 2014, Plant Physiology.

[97]  R. Edwards,et al.  Key role for a glutathione transferase in multiple-herbicide resistance in grass weeds , 2013, Proceedings of the National Academy of Sciences.

[98]  Felipe F. Aceituno,et al.  A composite transcriptional signature differentiates responses towards closely related herbicides in Arabidopsis thaliana and Brassica napus , 2009, Plant Molecular Biology.

[99]  Marc J-F Suter,et al.  Linking proteome responses with physiological and biochemical effects in herbicide-exposed Chlamydomonas reinhardtii. , 2012, Journal of proteomics.

[100]  L. Valledor,et al.  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. , 2009, Journal of proteomics.

[101]  The Arabidopsis Genome Initiative Analysis of the genome sequence of the flowering plant Arabidopsis thaliana , 2000, Nature.

[102]  W. Chao,et al.  Molecular Analysis of Signals Controlling Dormancy and Growth in Underground Adventitious Buds of Leafy Spurge , 2002, Plant Physiology.

[103]  R. Viola,et al.  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 , 1998, Planta.

[104]  Loren H. Rieseberg,et al.  De Novo Genome Assembly of the Economically Important Weed Horseweed Using Integrated Data from Multiple Sequencing Platforms1[C][W][OPEN] , 2014, Plant Physiology.

[105]  Sébastien Aubourg,et al.  Plant protein interactomes. , 2013, Annual review of plant biology.

[106]  Ainhoa Zulet-González,et al.  Effects of EPSPS Copy Number Variation (CNV) and Glyphosate Application on the Aromatic and Branched Chain Amino Acid Synthesis Pathways in Amaranthus palmeri , 2017, Front. Plant Sci..

[107]  Jianye Zhao,et al.  Investigation of the Effect of Herbicide Amiprophos Methyl on Spindle Formation and Proteome Change in Maize by Immunofluorescence and Proteomic Technique , 2011 .

[108]  Joshua S. Yuan,et al.  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. , 2010, Pest management science.

[109]  S. Duke,et al.  Herbicides and plant hormesis. , 2014, Pest management science.

[110]  J. S. McElroy,et al.  The power and potential of genomics in weed biology and management. , 2018, Pest management science.

[111]  David E. Hufnagel,et al.  Consequences of Whole-Genome Triplication as Revealed by Comparative Genomic Analyses of the Wild Radish Raphanus raphanistrum and Three Other Brassicaceae Species[W][OPEN] , 2014, Plant Cell.

[112]  Ching-Yuh Wang,et al.  Metabolism of Fluazifop-P-butyl in Resistant Goosegrass (Eleusine indica) in Taiwan , 2017, Weed Science.

[113]  Yong-Jin Park,et al.  Population genomics identifies the origin and signatures of selection of Korean weedy rice , 2016, Plant biotechnology journal.

[114]  M. Doğramacı,et al.  Meta-Analysis Identifies Potential Molecular Markers for Endodormancy in Crown Buds of Leafy Spurge; a Herbaceous Perennial , 2015 .

[115]  P. Meikle,et al.  Strategies for Extending Metabolomics Studies with Stable Isotope Labelling and Fluxomics , 2016, Metabolites.

[116]  A. Keller,et al.  Activation of antioxidant and detoxification gene expression in cucumber plants exposed to a Cu(OH)2nanopesticide , 2017, Environmental Science: Nano.

[117]  O. Kohlbacher,et al.  Plants Release Precursors of Histone Deacetylase Inhibitors to Suppress Growth of Competitors[OPEN] , 2015, Plant Cell.

[118]  C. Köhler,et al.  Plant epigenomics—deciphering the mechanisms of epigenetic inheritance and plasticity in plants , 2017, Genome Biology.

[119]  P. Simier,et al.  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. , 2014, Analytical chemistry.

[120]  Justin E. Anderson,et al.  The Genetics and Genomics of Plant Domestication , 2017 .

[121]  D. Horvath Dormancy-Associated MADS-BOX Genes: A Review , 2015 .

[122]  K. Aliferis,et al.  Metabolomics – A robust bioanalytical approach for the discovery of the modes-of-action of pesticides: A review , 2011 .

[123]  W. Chao,et al.  Transcriptome analysis of leafy spurge (Euphorbia esula) crown buds during shifts in well-defined phases of dormancy , 2006 .

[124]  G. Agrawal,et al.  Plant secretome: Unlocking secrets of the secreted proteins , 2010, Proteomics.

[125]  K. Olsen,et al.  Evolutionary Genomics of Weedy Rice in the USA , 2007 .

[126]  R. Kumar,et al.  Development and Evaluation of Chitosan-Sodium Alginate Based Etofenprox as Nanopesticide , 2017 .

[127]  Sai Guna Ranjan Gurazada,et al.  Genome sequencing and analysis of the model grass Brachypodium distachyon , 2010, Nature.

[128]  B. Rubin,et al.  Unraveling the Transcriptional Basis of Temperature-Dependent Pinoxaden Resistance in Brachypodium hybridum , 2017, Front. Plant Sci..

[129]  M. Perazzolli,et al.  Phosphoproteomic analysis of induced resistance reveals activation of signal transduction processes by beneficial and pathogenic interaction in grapevine. , 2016, Journal of plant physiology.

[130]  S. Duke,et al.  Validation of serine/threonine protein phosphatase as the herbicide target site of endothall , 2012 .

[131]  C. Délye Unravelling the genetic bases of non-target-site-based resistance (NTSR) to herbicides: a major challenge for weed science in the forthcoming decade. , 2013, Pest management science.

[132]  P. Benfey,et al.  Integrative systems biology: an attempt to describe a simple weed. , 2012, Current opinion in plant biology.

[133]  J. Leach,et al.  Gene amplification of 5-enol-pyruvylshikimate-3-phosphate synthase in glyphosate-resistant Kochia scoparia , 2014, Planta.

[134]  A. Keller,et al.  Metabolomics Reveals Cu(OH)2 Nanopesticide-Activated Anti-oxidative Pathways and Decreased Beneficial Antioxidants in Spinach Leaves. , 2017, Environmental science & technology.

[135]  Dinesh Kumar Yadav,et al.  Plant Secretomics: Unique Initiatives , 2015 .

[136]  S. Powles,et al.  A double EPSPS gene mutation endowing glyphosate resistance shows a remarkably high resistance cost. , 2017, Plant, cell & environment.

[137]  A. Lawton-Rauh,et al.  The unique genomic landscape surrounding the EPSPS gene in glyphosate resistant Amaranthus palmeri: a repetitive path to resistance , 2017, BMC Genomics.

[138]  L. Koski,et al.  Transcriptomic changes in Echinochloa colona in response to treatment with the herbicide imazamox , 2018, Planta.

[139]  Transcriptome and Proteome Analysis: A Perspective on Correlation , 2014 .

[140]  M. Bevan,et al.  The Arabidopsis genome: a foundation for plant research. , 2005, Genome research.

[141]  H. Beckie,et al.  The future for weed control and technology. , 2014, Pest management science.

[142]  M. Yanovsky,et al.  Circadian regulation of gene expression: at the crossroads of transcriptional and post-transcriptional regulatory networks. , 2014, Current opinion in genetics & development.

[143]  Ryan W. Kim,et al.  Characterization of an EST Database for the Perennial Weed Leafy Spurge: An Important Resource for Weed Biology Research , 2007, Weed science.

[144]  Hideyuki Takahashi,et al.  Targeted metabolomics in an intrusive weed, Rumex obtusifolius L., grown under different environmental conditions reveals alterations of organ related metabolite pathway , 2010, Metabolomics.

[145]  Simone Rochfort,et al.  Metabolomics reviewed: a new "omics" platform technology for systems biology and implications for natural products research. , 2005, Journal of natural products.

[146]  Marta-Marina Pérez-Alonso,et al.  When Transcriptomics and Metabolomics Work Hand in Hand: A Case Study Characterizing Plant CDF Transcription Factors , 2018, High-throughput.

[147]  Transcriptome Assembly and Comparison of an Allotetraploid Weed Species, Annual Bluegrass, with its Two Diploid Progenitor Species, Poa supina Schrad and Poa infirma Kunth , 2016, The plant genome.

[148]  N. Ahsan,et al.  Glyphosate-induced oxidative stress in rice leaves revealed by proteomic approach. , 2008, Plant physiology and biochemistry : PPB.

[149]  L. Fraceto,et al.  Nanotechnology in Agriculture: Which Innovation Potential Does It Have? , 2016, Front. Environ. Sci..

[150]  C. Stewart Weedy and invasive plant genomics , 2009 .

[151]  Kazuki Saito,et al.  Modern plant metabolomics: advanced natural product gene discoveries, improved technologies, and future prospects. , 2015, Natural product reports.

[152]  P. Westra,et al.  Cross-resistance to dicamba, 2,4-D, and fluroxypyr in Kochia scoparia is endowed by a mutation in an AUX/IAA gene , 2018, Proceedings of the National Academy of Sciences.

[153]  J. Keurentjes,et al.  Untargeted large-scale plant metabolomics using liquid chromatography coupled to mass spectrometry , 2007, Nature Protocols.

[154]  W. Chao,et al.  The transcriptomes of dormant leafy spurge seeds under alternating temperature are differentially affected by a germination-enhancing pretreatment. , 2013, Journal of plant physiology.

[155]  Christopher Preston,et al.  Gene amplification confers glyphosate resistance in Amaranthus palmeri , 2009, Proceedings of the National Academy of Sciences.

[156]  StensballeA JensenON PeckSC NhseTS Phosphoproteomics of the Arabidopsis plasma membrane and a new phosphorylation site database. , 2004 .

[157]  James V. Anderson Emerging Technologies: An Opportunity for Weed Biology Research , 2008, Weed Science.

[158]  Loren H. Rieseberg,et al.  Evolution of Weediness and Invasiveness: Charting the Course for Weed Genomics , 2009, Weed Science.

[159]  Hao-jen Huang,et al.  Identification of transcriptome profiles and signaling pathways for the allelochemical juglone in rice roots , 2011, Plant Molecular Biology.

[160]  F. Tardif,et al.  Detection of resistance to acetolactate synthase inhibitors in weeds with emphasis on DNA-based techniques: a review. , 2006, Pest management science.

[161]  Stephen O Duke,et al.  Why have no new herbicide modes of action appeared in recent years? , 2012, Pest management science.

[162]  J. Peralta-Videa,et al.  Foliar Exposure of Cu(OH)2 Nanopesticide to Basil ( Ocimum basilicum): Variety-Dependent Copper Translocation and Biochemical Responses. , 2018, Journal of agricultural and food chemistry.

[163]  D. Hollomon Do we have the tools to manage resistance in the future? , 2012, Pest management science.

[164]  N Aranìbar,et al.  Automated mode-of-action detection by metabolic profiling. , 2001, Biochemical and biophysical research communications.

[165]  Changhui Yan,et al.  Gene Space and Transcriptome Assemblies of Leafy Spurge (Euphorbia esula) Identify Promoter Sequences, Repetitive Elements, High-Quality Markers, and a Full-Length Chloroplast Genome , 2018, Weed Science.

[166]  A. Fernie,et al.  Analysis of metabolic flux using dynamic labelling and metabolic modelling. , 2013, Plant, cell & environment.

[167]  S. Duke,et al.  Glyphosate: a once-in-a-century herbicide. , 2008, Pest management science.

[168]  P. Ferranti,et al.  Use of phytochemomics to evaluate the bioavailability and bioactivity of antioxidant peptides of soybean β‐conglycinin , 2014, Electrophoresis.

[169]  Ronald W. Davis,et al.  Quantitative Monitoring of Gene Expression Patterns with a Complementary DNA Microarray , 1995, Science.

[170]  Eric L. Patterson,et al.  Applications of Genomics in Weed Science , 2017 .

[171]  P. Ahmad,et al.  Plant secretomics , 2014, Plant signaling & behavior.

[172]  K. Dorn,et al.  A draft genome of field pennycress (Thlaspi arvense) provides tools for the domestication of a new winter biofuel crop , 2015, DNA research : an international journal for rapid publication of reports on genes and genomes.

[173]  Xiaoyu Zhang The Epigenetic Landscape of Plants , 2008, Science.

[174]  L. Koski,et al.  Multiple Herbicide-Resistant Junglerice (Echinochloa colona): Identification of Genes Potentially Involved in Resistance through Differential Gene Expression Analysis , 2018, Weed Science.

[175]  Joshua S. Yuan,et al.  Genomics of Glyphosate Resistance , 2010 .

[176]  Simin Liu,et al.  Transcriptome Profiling to Discover Putative Genes Associated with Paraquat Resistance in Goosegrass (Eleusine indica L.) , 2014, PloS one.

[177]  Flufenacet herbicide treatment phenocopies the fiddlehead mutant in Arabidopsis thaliana. , 2003, Pest management science.