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<PubmedArticle><MedlineCitation Status="PubMed-not-MEDLINE" Owner="NLM"><PMID Version="1">35586220</PMID><DateRevised><Year>2023</Year><Month>11</Month><Day>02</Day></DateRevised><Article PubModel="Electronic-eCollection"><Journal><ISSN IssnType="Print">1664-462X</ISSN><JournalIssue CitedMedium="Print"><Volume>13</Volume><PubDate><Year>2022</Year></PubDate></JournalIssue><Title>Frontiers in plant science</Title><ISOAbbreviation>Front Plant Sci</ISOAbbreviation></Journal><ArticleTitle>The Genetic Architecture of Nitrogen Use Efficiency in Switchgrass (<i>Panicum virgatum</i> L.).</ArticleTitle><Pagination><StartPage>893610</StartPage><MedlinePgn>893610</MedlinePgn></Pagination><ELocationID EIdType="pii" ValidYN="Y">893610</ELocationID><ELocationID EIdType="doi" ValidYN="Y">10.3389/fpls.2022.893610</ELocationID><Abstract><AbstractText>Switchgrass (<i>Panicum virgatum</i> L.) has immense potential as a bioenergy crop with the aim of producing biofuel as an end goal. Nitrogen (N)-related sustainability traits, such as nitrogen use efficiency (NUE) and nitrogen remobilization efficiency (NRE), are important factors affecting switchgrass quality and productivity. Hence, it is imperative to develop nitrogen use-efficient switchgrass accessions by exploring the genetic basis of NUE in switchgrass. For that, we used 331 diverse field-grown switchgrass accessions planted under low and moderate N fertility treatments. We performed a genome wide association study (GWAS) in a holistic manner where we not only considered NUE as a single trait but also used its related phenotypic traits, such as total dry biomass at low N and moderate N, and nitrogen use index, such as NRE. We have evaluated the phenotypic characterization of the NUE and the related traits, highlighted their relationship using correlation analysis, and identified the top ten nitrogen use-efficient switchgrass accessions. Our GWAS analysis identified 19 unique single nucleotide polymorphisms (SNPs) and 32 candidate genes. Two promising GWAS candidate genes, <i>caffeoyl-CoA O-methyltransferase</i> (<i>CCoAOMT</i>) and <i>alfin-like 6</i> (<i>AL6</i>), were further supported by linkage disequilibrium (LD) analysis. Finally, we discussed the potential role of nitrogen in modulating the expression of these two genes. Our findings have opened avenues for the development of improved nitrogen use-efficient switchgrass lines.</AbstractText><CopyrightInformation>Copyright &#xa9; 2022 Shrestha, Chhetri, Kainer, Xu, Hamilton, Piasecki, Wolfe, Wang, Saha, Jacobson, Millwood, Mazarei and Stewart.</CopyrightInformation></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Shrestha</LastName><ForeName>Vivek</ForeName><Initials>V</Initials><AffiliationInfo><Affiliation>Department of Plant Sciences, The University of Tennessee, Knoxville, Knoxville, TN, United States.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>Center for Bioenergy Innovation, Oak Ridge National Laboratory, Oak Ridge, TN, United States.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Chhetri</LastName><ForeName>Hari B</ForeName><Initials>HB</Initials><AffiliationInfo><Affiliation>Center for Bioenergy Innovation, Oak Ridge National Laboratory, Oak Ridge, TN, United States.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Kainer</LastName><ForeName>David</ForeName><Initials>D</Initials><AffiliationInfo><Affiliation>Center for Bioenergy Innovation, Oak Ridge National Laboratory, Oak Ridge, TN, United States.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Xu</LastName><ForeName>Yaping</ForeName><Initials>Y</Initials><AffiliationInfo><Affiliation>Department of Plant Sciences, The University of Tennessee, Knoxville, Knoxville, TN, United States.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>Center for Bioenergy Innovation, Oak Ridge National Laboratory, Oak Ridge, TN, United States.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Hamilton</LastName><ForeName>Lance</ForeName><Initials>L</Initials><AffiliationInfo><Affiliation>Department of Plant Sciences, The University of Tennessee, Knoxville, Knoxville, TN, United States.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>Center for Bioenergy Innovation, Oak Ridge National Laboratory, Oak Ridge, TN, United States.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Piasecki</LastName><ForeName>Cristiano</ForeName><Initials>C</Initials><AffiliationInfo><Affiliation>ATSI Brazil Pesquisa e Consultoria, Passo Fundo, Brazil.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Wolfe</LastName><ForeName>Ben</ForeName><Initials>B</Initials><AffiliationInfo><Affiliation>Department of Plant Sciences, The University of Tennessee, Knoxville, Knoxville, TN, United States.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>Center for Bioenergy Innovation, Oak Ridge National Laboratory, Oak Ridge, TN, United States.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Wang</LastName><ForeName>Xueyan</ForeName><Initials>X</Initials><AffiliationInfo><Affiliation>Center for Bioenergy Innovation, Oak Ridge National Laboratory, Oak Ridge, TN, United States.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>Noble Research Institute, Ardmore, OK, United States.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Saha</LastName><ForeName>Malay</ForeName><Initials>M</Initials><AffiliationInfo><Affiliation>Center for Bioenergy Innovation, Oak Ridge National Laboratory, Oak Ridge, TN, United States.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>Noble Research Institute, Ardmore, OK, United States.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Jacobson</LastName><ForeName>Daniel</ForeName><Initials>D</Initials><AffiliationInfo><Affiliation>Center for Bioenergy Innovation, Oak Ridge National Laboratory, Oak Ridge, TN, United States.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Millwood</LastName><ForeName>Reginald J</ForeName><Initials>RJ</Initials><AffiliationInfo><Affiliation>Department of Plant Sciences, The University of Tennessee, Knoxville, Knoxville, TN, United States.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>Center for Bioenergy Innovation, Oak Ridge National Laboratory, Oak Ridge, TN, United States.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Mazarei</LastName><ForeName>Mitra</ForeName><Initials>M</Initials><AffiliationInfo><Affiliation>Department of Plant Sciences, The University of Tennessee, Knoxville, Knoxville, TN, United States.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>Center for Bioenergy Innovation, Oak Ridge National Laboratory, Oak Ridge, TN, United States.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Stewart</LastName><ForeName>C Neal</ForeName><Initials>CN</Initials><Suffix>Jr</Suffix><AffiliationInfo><Affiliation>Department of Plant Sciences, The University of Tennessee, Knoxville, Knoxville, TN, United States.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>Center for Bioenergy Innovation, Oak Ridge National Laboratory, Oak Ridge, TN, United States.</Affiliation></AffiliationInfo></Author></AuthorList><Language>eng</Language><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType></PublicationTypeList><ArticleDate DateType="Electronic"><Year>2022</Year><Month>05</Month><Day>02</Day></ArticleDate></Article><MedlineJournalInfo><Country>Switzerland</Country><MedlineTA>Front Plant Sci</MedlineTA><NlmUniqueID>101568200</NlmUniqueID><ISSNLinking>1664-462X</ISSNLinking></MedlineJournalInfo><KeywordList Owner="NOTNLM"><Keyword MajorTopicYN="N">accessions</Keyword><Keyword MajorTopicYN="N">genome wide association study</Keyword><Keyword MajorTopicYN="N">nitrogen remobilization efficiency</Keyword><Keyword MajorTopicYN="N">nitrogen use efficiency</Keyword><Keyword MajorTopicYN="N">switchgrass</Keyword></KeywordList><CoiStatement>The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.</CoiStatement></MedlineCitation><PubmedData><History><PubMedPubDate PubStatus="received"><Year>2022</Year><Month>3</Month><Day>10</Day></PubMedPubDate><PubMedPubDate PubStatus="accepted"><Year>2022</Year><Month>4</Month><Day>1</Day></PubMedPubDate><PubMedPubDate PubStatus="entrez"><Year>2022</Year><Month>5</Month><Day>19</Day><Hour>2</Hour><Minute>20</Minute></PubMedPubDate><PubMedPubDate PubStatus="pubmed"><Year>2022</Year><Month>5</Month><Day>20</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="medline"><Year>2022</Year><Month>5</Month><Day>20</Day><Hour>6</Hour><Minute>1</Minute></PubMedPubDate><PubMedPubDate 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Plant Cell 34 557&#x2013;578. 10.1093/plcell/koab251</Citation><ArticleIdList><ArticleId IdType="doi">10.1093/plcell/koab251</ArticleId><ArticleId IdType="pmc">PMC8774053</ArticleId><ArticleId IdType="pubmed">34623442</ArticleId></ArticleIdList></Reference></ReferenceList></PubmedData></PubmedArticle><PubmedArticle><MedlineCitation Status="PubMed-not-MEDLINE" Owner="NLM"><PMID Version="1">34961199</PMID><DateRevised><Year>2021</Year><Month>12</Month><Day>31</Day></DateRevised><Article PubModel="Electronic"><Journal><ISSN IssnType="Print">2223-7747</ISSN><JournalIssue CitedMedium="Print"><Volume>10</Volume><Issue>12</Issue><PubDate><Year>2021</Year><Month>Dec</Month><Day>11</Day></PubDate></JournalIssue><Title>Plants (Basel, Switzerland)</Title><ISOAbbreviation>Plants (Basel)</ISOAbbreviation></Journal><ArticleTitle>Sustainability Trait Modeling of Field-Grown Switchgrass (<i>Panicum virgatum</i>) Using UAV-Based Imagery.</ArticleTitle><ELocationID EIdType="pii" ValidYN="Y">2726</ELocationID><ELocationID EIdType="doi" ValidYN="Y">10.3390/plants10122726</ELocationID><Abstract><AbstractText>Unmanned aerial vehicles (UAVs) provide an intermediate scale of spatial and spectral data collection that yields increased accuracy and consistency in data collection for morphological and physiological traits than satellites and expanded flexibility and high-throughput compared to ground-based data collection. In this study, we used UAV-based remote sensing for automated phenotyping of field-grown switchgrass (<i>Panicum virgatum</i>), a leading bioenergy feedstock. Using vegetation indices calculated from a UAV-based multispectral camera, statistical models were developed for rust disease caused by <i>Puccinia novopanici</i>, leaf chlorophyll, nitrogen, and lignin contents. For the first time, UAV remote sensing technology was used to explore the potentials for multiple traits associated with sustainable production of switchgrass, and one statistical model was developed for each individual trait based on the statistical correlation between vegetation indices and the corresponding trait. Also, for the first time, lignin content was estimated in switchgrass shoots via UAV-based multispectral image analysis and statistical analysis. The UAV-based models were verified by ground-truthing via correlation analysis between the traits measured manually on the ground-based with UAV-based data. The normalized difference red edge (NDRE) vegetation index outperformed the normalized difference vegetation index (NDVI) for rust disease and nitrogen content, while NDVI performed better than NDRE for chlorophyll and lignin content. Overall, linear models were sufficient for rust disease and chlorophyll analysis, but for nitrogen and lignin contents, nonlinear models achieved better results. As the first comprehensive study to model switchgrass sustainability traits from UAV-based remote sensing, these results suggest that this methodology can be utilized for switchgrass high-throughput phenotyping in the field.</AbstractText></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Xu</LastName><ForeName>Yaping</ForeName><Initials>Y</Initials><Identifier Source="ORCID">0000-0003-1178-2776</Identifier><AffiliationInfo><Affiliation>Department of Plant Sciences, University of Tennessee, Knoxville, TN 37996, USA.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>Center for Bioenergy Innovation, Oak Ridge National Laboratory, Oak Ridge, TN 37830, USA.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Shrestha</LastName><ForeName>Vivek</ForeName><Initials>V</Initials><Identifier Source="ORCID">0000-0003-1173-2998</Identifier><AffiliationInfo><Affiliation>Department of Plant Sciences, University of Tennessee, Knoxville, TN 37996, USA.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>Center for Bioenergy Innovation, Oak Ridge National Laboratory, Oak Ridge, TN 37830, USA.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Piasecki</LastName><ForeName>Cristiano</ForeName><Initials>C</Initials><Identifier Source="ORCID">0000-0002-2868-6863</Identifier><AffiliationInfo><Affiliation>Department of Plant Sciences, University of Tennessee, Knoxville, TN 37996, USA.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>Center for Bioenergy Innovation, Oak Ridge National Laboratory, Oak Ridge, TN 37830, USA.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>ATSI Brasil Pesquisa e Consultoria, Passo Fundo 99054-328, RS, Brazil.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Wolfe</LastName><ForeName>Benjamin</ForeName><Initials>B</Initials><AffiliationInfo><Affiliation>Department of Plant Sciences, University of Tennessee, Knoxville, TN 37996, USA.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>Center for Bioenergy Innovation, Oak Ridge National Laboratory, Oak Ridge, TN 37830, USA.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Hamilton</LastName><ForeName>Lance</ForeName><Initials>L</Initials><AffiliationInfo><Affiliation>Department of Plant Sciences, University of Tennessee, Knoxville, TN 37996, USA.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>Center for Bioenergy Innovation, Oak Ridge National Laboratory, Oak Ridge, TN 37830, USA.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Millwood</LastName><ForeName>Reginald J</ForeName><Initials>RJ</Initials><Identifier Source="ORCID">0000-0002-7127-1831</Identifier><AffiliationInfo><Affiliation>Department of Plant Sciences, University of Tennessee, Knoxville, TN 37996, USA.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>Center for Bioenergy Innovation, Oak Ridge National Laboratory, Oak Ridge, TN 37830, USA.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Mazarei</LastName><ForeName>Mitra</ForeName><Initials>M</Initials><Identifier Source="ORCID">0000-0002-6116-7758</Identifier><AffiliationInfo><Affiliation>Department of Plant Sciences, University of Tennessee, Knoxville, TN 37996, USA.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>Center for Bioenergy Innovation, Oak Ridge National Laboratory, Oak Ridge, TN 37830, USA.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Stewart</LastName><ForeName>Charles Neal</ForeName><Initials>CN</Initials><Identifier Source="ORCID">0000-0003-3026-9193</Identifier><AffiliationInfo><Affiliation>Department of Plant Sciences, University of Tennessee, Knoxville, TN 37996, USA.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>Center for Bioenergy Innovation, Oak Ridge National Laboratory, Oak Ridge, TN 37830, USA.</Affiliation></AffiliationInfo></Author></AuthorList><Language>eng</Language><GrantList CompleteYN="Y"><Grant><GrantID>DE-AC05-000R22725</GrantID><Agency>US Department of Energy</Agency><Country/></Grant></GrantList><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType></PublicationTypeList><ArticleDate DateType="Electronic"><Year>2021</Year><Month>12</Month><Day>11</Day></ArticleDate></Article><MedlineJournalInfo><Country>Switzerland</Country><MedlineTA>Plants (Basel)</MedlineTA><NlmUniqueID>101596181</NlmUniqueID><ISSNLinking>2223-7747</ISSNLinking></MedlineJournalInfo><KeywordList Owner="NOTNLM"><Keyword MajorTopicYN="N">UAV</Keyword><Keyword MajorTopicYN="N">chlorophyll</Keyword><Keyword MajorTopicYN="N">high throughput modeling</Keyword><Keyword MajorTopicYN="N">lignin</Keyword><Keyword MajorTopicYN="N">nitrogen</Keyword><Keyword MajorTopicYN="N">rust disease</Keyword><Keyword MajorTopicYN="N">sustainability</Keyword><Keyword MajorTopicYN="N">switchgrass</Keyword></KeywordList><CoiStatement>The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. 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Therefore, we need an improved understanding of how gene regulation confers herbicide resistance in order to slow the evolution of resistance. The present study analyzed differentially expressed genes after glyphosate treatment on a glyphosate-resistant Tennessee ecotype (TNR) of horseweed (<i>Conyza canadensis</i>), compared to a susceptible biotype (TNS). A read size of 100.2 M was sequenced on the Illumina platform and subjected to de novo assembly, resulting in 77,072 gene-level contigs, of which 32,493 were uniquely annotated by a BlastX alignment of protein sequence similarity. The most differentially expressed genes were enriched in the gene ontology (GO) term of the transmembrane transport protein. In addition, fifteen upregulated genes were identified in TNR after glyphosate treatment but were not detected in TNS. Ten of these upregulated genes were transmembrane transporter or kinase receptor proteins. Therefore, a combination of changes in gene expression among transmembrane receptor and kinase receptor proteins may be important for endowing non-target-site glyphosate-resistant <i>C. canadensis</i>.</AbstractText></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Yang</LastName><ForeName>Yongil</ForeName><Initials>Y</Initials><Identifier Source="ORCID">0000-0002-6925-5410</Identifier><AffiliationInfo><Affiliation>Department of Plant Sciences, University of Tennessee, Knoxville, TN 37996, USA.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>Center for Agricultural Synthetic Biology, University of Tennessee, Knoxville, TN 37996, USA.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Gardner</LastName><ForeName>Cory</ForeName><Initials>C</Initials><AffiliationInfo><Affiliation>Program in Bioinformatics and Computational Biology, Saint Louis University, St. Louis, MO 63103, USA.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Gupta</LastName><ForeName>Pallavi</ForeName><Initials>P</Initials><Identifier Source="ORCID">0000-0003-0146-239X</Identifier><AffiliationInfo><Affiliation>Program in Bioinformatics and Computational Biology, Saint Louis University, St. Louis, MO 63103, USA.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>MU Institute for Data Science and Informatics, University of Missouri, Columbia, MO 65211, USA.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Peng</LastName><ForeName>Yanhui</ForeName><Initials>Y</Initials><AffiliationInfo><Affiliation>Department of Plant Sciences, University of Tennessee, Knoxville, TN 37996, USA.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>Centers for Disease Control and Prevention, 1600 Clifton Rd., Atlanta, GA 30333, USA.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Piasecki</LastName><ForeName>Cristiano</ForeName><Initials>C</Initials><Identifier Source="ORCID">0000-0002-2868-6863</Identifier><AffiliationInfo><Affiliation>Department of Plant Sciences, University of Tennessee, Knoxville, TN 37996, USA.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>ATSI Brasil Pesquisa e Consultoria, Passo Fundo 99054-328, RS, Brazil.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Millwood</LastName><ForeName>Reginald J</ForeName><Initials>RJ</Initials><AffiliationInfo><Affiliation>Department of Plant Sciences, University of Tennessee, Knoxville, TN 37996, USA.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Ahn</LastName><ForeName>Tae-Hyuk</ForeName><Initials>TH</Initials><Identifier Source="ORCID">0000-0002-7281-9459</Identifier><AffiliationInfo><Affiliation>Program in Bioinformatics and Computational Biology, Saint Louis University, St. Louis, MO 63103, USA.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>Department of Computer Science, Saint Louis University, St. Louis, MO 63103, USA.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Stewart</LastName><ForeName>C Neal</ForeName><Initials>CN</Initials><Suffix>Jr</Suffix><Identifier Source="ORCID">0000-0003-3026-9193</Identifier><AffiliationInfo><Affiliation>Department of Plant Sciences, University of Tennessee, Knoxville, TN 37996, USA.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>Center for Agricultural Synthetic Biology, University of Tennessee, Knoxville, TN 37996, USA.</Affiliation></AffiliationInfo></Author></AuthorList><Language>eng</Language><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType></PublicationTypeList><ArticleDate DateType="Electronic"><Year>2021</Year><Month>10</Month><Day>14</Day></ArticleDate></Article><MedlineJournalInfo><Country>Switzerland</Country><MedlineTA>Genes (Basel)</MedlineTA><NlmUniqueID>101551097</NlmUniqueID><ISSNLinking>2073-4425</ISSNLinking></MedlineJournalInfo><ChemicalList><Chemical><RegistryNumber>0</RegistryNumber><NameOfSubstance UI="D018744">DNA, Plant</NameOfSubstance></Chemical><Chemical><RegistryNumber>0</RegistryNumber><NameOfSubstance UI="D006540">Herbicides</NameOfSubstance></Chemical><Chemical><RegistryNumber>TE7660XO1C</RegistryNumber><NameOfSubstance UI="D005998">Glycine</NameOfSubstance></Chemical></ChemicalList><CitationSubset>IM</CitationSubset><MeshHeadingList><MeshHeading><DescriptorName UI="D019295" MajorTopicYN="N">Computational Biology</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D035401" MajorTopicYN="N">Conyza</DescriptorName><QualifierName UI="Q000187" MajorTopicYN="N">drug effects</QualifierName><QualifierName UI="Q000235" MajorTopicYN="Y">genetics</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D018744" MajorTopicYN="N">DNA, Plant</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D017343" MajorTopicYN="N">Genes, Plant</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D005998" MajorTopicYN="N">Glycine</DescriptorName><QualifierName UI="Q000031" MajorTopicYN="Y">analogs &amp; derivatives</QualifierName><QualifierName UI="Q000494" MajorTopicYN="N">pharmacology</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D053209" MajorTopicYN="N">Herbicide Resistance</DescriptorName><QualifierName UI="Q000235" MajorTopicYN="Y">genetics</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D006540" MajorTopicYN="N">Herbicides</DescriptorName><QualifierName UI="Q000494" MajorTopicYN="Y">pharmacology</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D017422" MajorTopicYN="N">Sequence Analysis, DNA</DescriptorName><QualifierName UI="Q000379" MajorTopicYN="N">methods</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D059467" MajorTopicYN="N">Transcriptome</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D058728" MajorTopicYN="N">Weed Control</DescriptorName><QualifierName UI="Q000379" MajorTopicYN="N">methods</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D000097797" MajorTopicYN="N">Glyphosate</DescriptorName></MeshHeading></MeshHeadingList><KeywordList Owner="NOTNLM"><Keyword MajorTopicYN="N">ABC transporter</Keyword><Keyword MajorTopicYN="N">CYP450</Keyword><Keyword MajorTopicYN="N">Conyza canadensis</Keyword><Keyword MajorTopicYN="N">differentially expressed gene analysis</Keyword><Keyword MajorTopicYN="N">glyphosate</Keyword><Keyword MajorTopicYN="N">membrane-bound protein kinase</Keyword><Keyword MajorTopicYN="N">non-target-site-based resistance</Keyword></KeywordList><CoiStatement>The authors declare no conflict of interest.</CoiStatement></MedlineCitation><PubmedData><History><PubMedPubDate PubStatus="received"><Year>2021</Year><Month>8</Month><Day>13</Day></PubMedPubDate><PubMedPubDate PubStatus="revised"><Year>2021</Year><Month>9</Month><Day>20</Day></PubMedPubDate><PubMedPubDate PubStatus="accepted"><Year>2021</Year><Month>10</Month><Day>8</Day></PubMedPubDate><PubMedPubDate PubStatus="entrez"><Year>2021</Year><Month>10</Month><Day>23</Day><Hour>1</Hour><Minute>6</Minute></PubMedPubDate><PubMedPubDate PubStatus="pubmed"><Year>2021</Year><Month>10</Month><Day>24</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="medline"><Year>2022</Year><Month>2</Month><Day>8</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="pmc-release"><Year>2021</Year><Month>10</Month><Day>14</Day></PubMedPubDate></History><PublicationStatus>epublish</PublicationStatus><ArticleIdList><ArticleId IdType="pubmed">34681011</ArticleId><ArticleId IdType="pmc">PMC8535903</ArticleId><ArticleId IdType="doi">10.3390/genes12101616</ArticleId><ArticleId 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While effective for integrating relatively small constructs into the plastome, plastid engineering via homologous recombination of transgenes is over 30&#x2009;years old. Here we show the design-build-test of a novel synthetic genome structure that does not disturb the native plastome: the 'mini-synplastome'. The mini-synplastome was inspired by dinoflagellate plastome organization, which is comprised of numerous minicircles residing in the plastid instead of a single organellar genome molecule. The first mini-synplastome in plants was developed in&#xa0;vitro to meet the following criteria: (i) episomal replication in plastids; (ii) facile cloning; (iii) predictable transgene expression in plastids; (iv) non-integration of vector sequences into the endogenous plastome; and (v) autonomous persistence in the plant over generations in the absence of exogenous selection pressure. Mini-synplastomes are anticipated to revolutionize chloroplast biotechnology, enable facile marker-free plastid engineering, and provide an unparalleled platform for one-step metabolic engineering in plants.</AbstractText><CopyrightInformation>&#xa9; 2021 The Authors. Plant Biotechnology Journal published by Society for Experimental Biology and The Association of Applied Biologists and John Wiley &amp; Sons Ltd.</CopyrightInformation></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Occhialini</LastName><ForeName>Alessandro</ForeName><Initials>A</Initials><AffiliationInfo><Affiliation>Department of Food Science, University of Tennessee, Knoxville, TN, USA.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>Center for Agricultural Synthetic Biology, University of Tennessee Institute of Agriculture, Knoxville, TN, USA.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Pfotenhauer</LastName><ForeName>Alexander C</ForeName><Initials>AC</Initials><AffiliationInfo><Affiliation>Department of Food Science, University of Tennessee, Knoxville, TN, USA.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>Center for Agricultural Synthetic Biology, University of Tennessee Institute of Agriculture, Knoxville, TN, USA.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Li</LastName><ForeName>Li</ForeName><Initials>L</Initials><AffiliationInfo><Affiliation>Department of Food Science, University of Tennessee, Knoxville, TN, USA.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>Center for Agricultural Synthetic Biology, University of Tennessee Institute of Agriculture, Knoxville, TN, USA.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Harbison</LastName><ForeName>Stacee A</ForeName><Initials>SA</Initials><AffiliationInfo><Affiliation>Center for Agricultural Synthetic Biology, University of Tennessee Institute of Agriculture, Knoxville, TN, USA.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>Department of Plant Sciences, University of Tennessee, Knoxville, TN, USA.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Lail</LastName><ForeName>Andrew J</ForeName><Initials>AJ</Initials><AffiliationInfo><Affiliation>Center for Agricultural Synthetic Biology, University of Tennessee Institute of Agriculture, Knoxville, TN, USA.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>Department of Plant Sciences, University of Tennessee, Knoxville, TN, USA.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Burris</LastName><ForeName>Jason N</ForeName><Initials>JN</Initials><AffiliationInfo><Affiliation>Department of Food Science, University of Tennessee, Knoxville, TN, USA.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>Center for Agricultural Synthetic Biology, University of Tennessee Institute of Agriculture, Knoxville, TN, USA.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Piasecki</LastName><ForeName>Cristiano</ForeName><Initials>C</Initials><AffiliationInfo><Affiliation>Department of Plant Sciences, University of Tennessee, Knoxville, TN, USA.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Piatek</LastName><ForeName>Agnieszka A</ForeName><Initials>AA</Initials><AffiliationInfo><Affiliation>Department of Plant Sciences, University of Tennessee, Knoxville, TN, USA.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Daniell</LastName><ForeName>Henry</ForeName><Initials>H</Initials><Identifier Source="ORCID">0000-0003-4485-1176</Identifier><AffiliationInfo><Affiliation>Department of Basic and Translational Sciences, School of Dental Medicine, University of Pennsylvania, Philadelphia, PA, USA.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Stewart</LastName><ForeName>C Neal</ForeName><Initials>CN</Initials><Suffix>Jr</Suffix><Identifier Source="ORCID">0000-0003-3026-9193</Identifier><AffiliationInfo><Affiliation>Center for Agricultural Synthetic Biology, University of Tennessee Institute of Agriculture, Knoxville, TN, USA.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>Department of Plant Sciences, University of Tennessee, Knoxville, TN, USA.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Lenaghan</LastName><ForeName>Scott C</ForeName><Initials>SC</Initials><Identifier Source="ORCID">0000-0002-7539-1726</Identifier><AffiliationInfo><Affiliation>Department of Food Science, University of Tennessee, Knoxville, TN, USA.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>Center for Agricultural Synthetic Biology, University of Tennessee Institute of Agriculture, Knoxville, TN, USA.</Affiliation></AffiliationInfo></Author></AuthorList><Language>eng</Language><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType><PublicationType UI="D013485">Research Support, Non-U.S. Gov't</PublicationType><PublicationType UI="D013486">Research Support, U.S. Gov't, Non-P.H.S.</PublicationType></PublicationTypeList><ArticleDate DateType="Electronic"><Year>2021</Year><Month>10</Month><Day>24</Day></ArticleDate></Article><MedlineJournalInfo><Country>England</Country><MedlineTA>Plant Biotechnol J</MedlineTA><NlmUniqueID>101201889</NlmUniqueID><ISSNLinking>1467-7644</ISSNLinking></MedlineJournalInfo><CitationSubset>IM</CitationSubset><MeshHeadingList><MeshHeading><DescriptorName UI="D005818" MajorTopicYN="Y">Genetic Engineering</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D060847" MajorTopicYN="N">Metabolic Engineering</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D010944" MajorTopicYN="N">Plants</DescriptorName><QualifierName UI="Q000235" MajorTopicYN="N">genetics</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D018087" MajorTopicYN="Y">Plastids</DescriptorName><QualifierName UI="Q000235" MajorTopicYN="N">genetics</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D058615" MajorTopicYN="N">Synthetic Biology</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D019076" MajorTopicYN="N">Transgenes</DescriptorName></MeshHeading></MeshHeadingList><KeywordList Owner="NOTNLM"><Keyword MajorTopicYN="N">Solanum tuberosum</Keyword><Keyword MajorTopicYN="N">episomal replication</Keyword><Keyword MajorTopicYN="N">homologous recombination</Keyword><Keyword MajorTopicYN="N">plastid engineering</Keyword><Keyword MajorTopicYN="N">plastome</Keyword><Keyword MajorTopicYN="N">small synthetic plastome &#x2018;mini-synplastome&#x2019;</Keyword></KeywordList><CoiStatement>The authors declare no competing interests.</CoiStatement></MedlineCitation><PubmedData><History><PubMedPubDate PubStatus="revised"><Year>2021</Year><Month>9</Month><Day>8</Day></PubMedPubDate><PubMedPubDate PubStatus="received"><Year>2021</Year><Month>5</Month><Day>24</Day></PubMedPubDate><PubMedPubDate PubStatus="accepted"><Year>2021</Year><Month>9</Month><Day>25</Day></PubMedPubDate><PubMedPubDate 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Science, 347, 991&#x2013;994.</Citation><ArticleIdList><ArticleId IdType="pubmed">25722411</ArticleId></ArticleIdList></Reference></ReferenceList></PubmedData></PubmedArticle><PubmedArticle><MedlineCitation Status="PubMed-not-MEDLINE" Owner="NLM"><PMID Version="1">33193511</PMID><DateRevised><Year>2020</Year><Month>11</Month><Day>17</Day></DateRevised><Article PubModel="Electronic-eCollection"><Journal><ISSN IssnType="Print">1664-462X</ISSN><JournalIssue CitedMedium="Print"><Volume>11</Volume><PubDate><Year>2020</Year></PubDate></JournalIssue><Title>Frontiers in plant science</Title><ISOAbbreviation>Front Plant Sci</ISOAbbreviation></Journal><ArticleTitle>High-Throughput Switchgrass Phenotyping and Biomass Modeling by UAV.</ArticleTitle><Pagination><StartPage>574073</StartPage><MedlinePgn>574073</MedlinePgn></Pagination><ELocationID EIdType="pii" ValidYN="Y">574073</ELocationID><ELocationID EIdType="doi" ValidYN="Y">10.3389/fpls.2020.574073</ELocationID><Abstract><AbstractText>Unmanned aerial vehicle (UAV) technology is an emerging powerful approach for high-throughput plant phenotyping field-grown crops. Switchgrass (<i>Panicum virgatum</i> L.) is a lignocellulosic bioenergy crop for which studies on yield, sustainability, and biofuel traits are performed. In this study, we exploited UAV-based imagery (LiDAR and multispectral approaches) to measure plant height, perimeter, and biomass yield in field-grown switchgrass in order to make predictions on bioenergy traits. Manual ground truth measurements validated the automated UAV results. We found UAV-based plant height and perimeter measurements were highly correlated and consistent with the manual measurements (<i>r</i> = 0.93, <i>p</i> &lt; 0.001). Furthermore, we found that phenotyping parameters can significantly improve the natural saturation of the spectral index of the optical image for detecting high-density plantings. Combining plant canopy height (CH) and canopy perimeter (CP) parameters with spectral index (SI), we developed a robust and standardized biomass yield model [biomass = (<i>m</i> &#xd7; SI) &#xd7; CP &#xd7; CH] where the <i>m</i> is an SI-sensitive coefficient linearly varying with the plant phenological changing stage. The biomass yield estimates obtained from this model were strongly correlated with manual measurements (<i>r</i> = 0.90, <i>p</i> &lt; 0.001). Taking together, our results provide insights into the capacity of UAV-based remote sensing for switchgrass high-throughput phenotyping in the field, which will be useful for breeding and cultivar development.</AbstractText><CopyrightInformation>Copyright &#xa9; 2020 Li, Piasecki, Millwood, Wolfe, Mazarei and Stewart.</CopyrightInformation></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Li</LastName><ForeName>Fei</ForeName><Initials>F</Initials><AffiliationInfo><Affiliation>Department of Plant Sciences, University of Tennessee, Knoxville, Knoxville, TN, United States.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>Center for Bioenergy Innovation, Oak Ridge National Laboratory, Oak Ridge, TN, United States.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Piasecki</LastName><ForeName>Cristiano</ForeName><Initials>C</Initials><AffiliationInfo><Affiliation>Department of Plant Sciences, University of Tennessee, Knoxville, Knoxville, TN, United States.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>Center for Bioenergy Innovation, Oak Ridge National Laboratory, Oak Ridge, TN, United States.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Millwood</LastName><ForeName>Reginald J</ForeName><Initials>RJ</Initials><AffiliationInfo><Affiliation>Department of Plant Sciences, University of Tennessee, Knoxville, Knoxville, TN, United States.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>Center for Bioenergy Innovation, Oak Ridge National Laboratory, Oak Ridge, TN, United States.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Wolfe</LastName><ForeName>Benjamin</ForeName><Initials>B</Initials><AffiliationInfo><Affiliation>Department of Plant Sciences, University of Tennessee, Knoxville, Knoxville, TN, United States.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>Center for Bioenergy Innovation, Oak Ridge National Laboratory, Oak Ridge, TN, United States.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Mazarei</LastName><ForeName>Mitra</ForeName><Initials>M</Initials><AffiliationInfo><Affiliation>Department of Plant Sciences, University of Tennessee, Knoxville, Knoxville, TN, United States.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>Center for Bioenergy Innovation, Oak Ridge National Laboratory, Oak Ridge, TN, United States.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Stewart</LastName><ForeName>C Neal</ForeName><Initials>CN</Initials><Suffix>Jr</Suffix><AffiliationInfo><Affiliation>Department of Plant Sciences, University of Tennessee, Knoxville, Knoxville, TN, United States.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>Center for Bioenergy Innovation, Oak Ridge National Laboratory, Oak Ridge, TN, United States.</Affiliation></AffiliationInfo></Author></AuthorList><Language>eng</Language><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType></PublicationTypeList><ArticleDate DateType="Electronic"><Year>2020</Year><Month>10</Month><Day>20</Day></ArticleDate></Article><MedlineJournalInfo><Country>Switzerland</Country><MedlineTA>Front Plant Sci</MedlineTA><NlmUniqueID>101568200</NlmUniqueID><ISSNLinking>1664-462X</ISSNLinking></MedlineJournalInfo><KeywordList Owner="NOTNLM"><Keyword MajorTopicYN="N">LiDAR</Keyword><Keyword MajorTopicYN="N">Nitrogen</Keyword><Keyword MajorTopicYN="N">biomass</Keyword><Keyword MajorTopicYN="N">phenotype</Keyword><Keyword MajorTopicYN="N">spectral index</Keyword></KeywordList></MedlineCitation><PubmedData><History><PubMedPubDate PubStatus="received"><Year>2020</Year><Month>6</Month><Day>18</Day></PubMedPubDate><PubMedPubDate PubStatus="accepted"><Year>2020</Year><Month>9</Month><Day>16</Day></PubMedPubDate><PubMedPubDate PubStatus="entrez"><Year>2020</Year><Month>11</Month><Day>16</Day><Hour>8</Hour><Minute>48</Minute></PubMedPubDate><PubMedPubDate PubStatus="pubmed"><Year>2020</Year><Month>11</Month><Day>17</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="medline"><Year>2020</Year><Month>11</Month><Day>17</Day><Hour>6</Hour><Minute>1</Minute></PubMedPubDate><PubMedPubDate PubStatus="pmc-release"><Year>2020</Year><Month>1</Month><Day>1</Day></PubMedPubDate></History><PublicationStatus>epublish</PublicationStatus><ArticleIdList><ArticleId IdType="pubmed">33193511</ArticleId><ArticleId IdType="pmc">PMC7606849</ArticleId><ArticleId IdType="doi">10.3389/fpls.2020.574073</ArticleId></ArticleIdList><ReferenceList><Reference><Citation>Adams J. 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This weed species interfere with wheat, corn, rye, and oat, causing significant crop yield losses. This species has evolved glyphosate resistance, making it difficult to control. The mechanisms of glyphosate resistance are still unknown, and an understanding thereof will favor the development of new strategies of management. The present study is the first transcriptome study in LOLMU using glyphosate-resistant and -sensitive biotypes, aiming to identify and to provide a list of the candidate target genes related to glyphosate resistance mechanism. The transcriptome was assembled <i>de novo</i>, producing 87,433 contigs with an N50 of 740 bp and an average length of 575 bp. There were 92 and 54 up- and down-regulated genes, respectively, in the resistant biotype, while a total of 1683 were differentially expressed in the sensitive biotype in response to glyphosate treatment. We selected 14 highly induced genes and seven with repressed expression in the resistant biotype in response to glyphosate. Of these genes, a significant proportion were related to the plasma membrane, indicating that there is a barrier making it difficult for glyphosate to enter the cell.</AbstractText></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Cechin</LastName><ForeName>Joanei</ForeName><Initials>J</Initials><AffiliationInfo><Affiliation>Department of Crop Protection, Federal University of Pelotas, Pelotas, RS 96160-000, Brazil.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Piasecki</LastName><ForeName>Cristiano</ForeName><Initials>C</Initials><AffiliationInfo><Affiliation>Department of Crop Protection, Federal University of Pelotas, Pelotas, RS 96160-000, Brazil.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>Department of Plant Sciences, University of Tennessee, Knoxville, TN 37996, USA.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Benemann</LastName><ForeName>Daiane P</ForeName><Initials>DP</Initials><AffiliationInfo><Affiliation>Department of Crop Protection, Federal University of Pelotas, Pelotas, RS 96160-000, Brazil.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Kremer</LastName><ForeName>Frederico S</ForeName><Initials>FS</Initials><AffiliationInfo><Affiliation>Center for Technological Development, Federal University of Pelotas (UFPel), Pelotas, RS 96010-610, Brazil.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Galli</LastName><ForeName>Vanessa</ForeName><Initials>V</Initials><AffiliationInfo><Affiliation>Center for Technological Development, Federal University of Pelotas (UFPel), Pelotas, RS 96010-610, Brazil.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Maia</LastName><ForeName>Luciano C</ForeName><Initials>LC</Initials><AffiliationInfo><Affiliation>Department of Plant Breeding, Federal University of Pelotas (UFPel), Pelotas, RS 96010-610, Brazil.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Agostinetto</LastName><ForeName>Dirceu</ForeName><Initials>D</Initials><AffiliationInfo><Affiliation>Department of Crop Protection, Federal University of Pelotas, Pelotas, RS 96160-000, Brazil.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Vargas</LastName><ForeName>And Leandro</ForeName><Initials>AL</Initials><AffiliationInfo><Affiliation>Department of Weed Science, Brazilian Agricultural Research Corporation (EMBRAPA), Passo Fundo, RS 99050-970, Brazil.</Affiliation></AffiliationInfo></Author></AuthorList><Language>eng</Language><GrantList CompleteYN="Y"><Grant><GrantID>00000</GrantID><Agency>Coordena&#xe7;&#xe3;o de Aperfei&#xe7;oamento de Pessoal de N&#xed;vel Superior</Agency><Country/></Grant><Grant><GrantID>000000</GrantID><Agency>Conselho Nacional de Desenvolvimento Cient&#xed;fico e Tecnol&#xf3;gico</Agency><Country/></Grant></GrantList><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType></PublicationTypeList><ArticleDate DateType="Electronic"><Year>2020</Year><Month>05</Month><Day>28</Day></ArticleDate></Article><MedlineJournalInfo><Country>Switzerland</Country><MedlineTA>Plants (Basel)</MedlineTA><NlmUniqueID>101596181</NlmUniqueID><ISSNLinking>2223-7747</ISSNLinking></MedlineJournalInfo><KeywordList Owner="NOTNLM"><Keyword MajorTopicYN="N">Italian ryegrass</Keyword><Keyword MajorTopicYN="N">RNA-Seq</Keyword><Keyword MajorTopicYN="N">differential gene expression</Keyword><Keyword MajorTopicYN="N">next-generation sequencing</Keyword><Keyword MajorTopicYN="N">resistance mechanism</Keyword></KeywordList><CoiStatement>The authors declare no conflict of interest.</CoiStatement></MedlineCitation><PubmedData><History><PubMedPubDate PubStatus="received"><Year>2020</Year><Month>5</Month><Day>2</Day></PubMedPubDate><PubMedPubDate PubStatus="revised"><Year>2020</Year><Month>5</Month><Day>23</Day></PubMedPubDate><PubMedPubDate PubStatus="accepted"><Year>2020</Year><Month>5</Month><Day>24</Day></PubMedPubDate><PubMedPubDate PubStatus="entrez"><Year>2020</Year><Month>6</Month><Day>3</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="pubmed"><Year>2020</Year><Month>6</Month><Day>3</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="medline"><Year>2020</Year><Month>6</Month><Day>3</Day><Hour>6</Hour><Minute>1</Minute></PubMedPubDate><PubMedPubDate PubStatus="pmc-release"><Year>2020</Year><Month>5</Month><Day>28</Day></PubMedPubDate></History><PublicationStatus>epublish</PublicationStatus><ArticleIdList><ArticleId IdType="pubmed">32481698</ArticleId><ArticleId IdType="pmc">PMC7357135</ArticleId><ArticleId IdType="doi">10.3390/plants9060685</ArticleId><ArticleId IdType="pii">plants9060685</ArticleId></ArticleIdList><ReferenceList><Reference><Citation>Vargas L., Roman E.S., Rizzardi M.A., Silva V.C. 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This highly competitive weed species significantly interferes with crop growth and substantially decreases crop yield. Despite its agricultural importance, the molecular mechanisms of glyphosate resistance are still unknown. The present RNA-Seq study was performed with the goal of identifying differentially expressed candidate transcripts (genes) related to metabolism-based non-target site glyphosate resistance in <i>C. bonariensis</i>. The whole-transcriptome was <i>de novo</i> assembled from glyphosate-resistant and -sensitive biotypes of <i>C. bonariensis</i> from Southern Brazil. The RNA was extracted from untreated and glyphosate-treated plants at several timepoints up to 288 h after treatment in both biotypes. The transcriptome assembly produced 90,124 contigs with an average length of 777 bp and N50 of 1118 bp. In response to glyphosate treatment, differential gene expression analysis was performed on glyphosate-resistant and -sensitive biotypes. A total of 9622 genes were differentially expressed as a response to glyphosate treatment in both biotypes, 4297 (44.6%) being up- and 5325 (55.4%) down-regulated. The resistant biotype presented 1770 up- and 2333 down-regulated genes while the sensitive biotype had 2335 and 2800 up- and down-regulated genes, respectively. Among them, 974 up- and 1290 down-regulated genes were co-expressed in both biotypes. In the present work, we identified 41 new candidate target genes from five families related to herbicide transport and metabolism: 19 ABC transporters, 10 CYP450s, one glutathione S-transferase (GST), five glycosyltransferases (GT), and six genes related to antioxidant enzyme catalase (CAT), peroxidase (POD), and superoxide dismutase (SOD). The candidate genes may participate in metabolic-based glyphosate resistance via oxidation, conjugation, transport, and degradation, plus antioxidation. One or more of these genes might 'rescue' resistant plants from irreversible damage after glyphosate treatment. The 41 target genes we report in the present study may inform further functional genomics studies, including gene editing approaches to elucidate glyphosate-resistance mechanisms in <i>C. bonariensis</i>.</AbstractText></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Piasecki</LastName><ForeName>Cristiano</ForeName><Initials>C</Initials><Identifier Source="ORCID">0000-0002-2868-6863</Identifier><AffiliationInfo><Affiliation>Department of Crop Protection, Federal University of Pelotas (UFPel), Pelotas 96010-610, Brazil. cpiasecki@utk.edu.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>Department of Plant Sciences, University of Tennessee (UTK), Knoxville, TN 37996, USA. cpiasecki@utk.edu.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Yang</LastName><ForeName>Yongil</ForeName><Initials>Y</Initials><Identifier Source="ORCID">0000-0002-6925-5410</Identifier><AffiliationInfo><Affiliation>Department of Plant Sciences, University of Tennessee (UTK), Knoxville, TN 37996, USA. yyang98@utk.edu.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Benemann</LastName><ForeName>Daiane P</ForeName><Initials>DP</Initials><AffiliationInfo><Affiliation>Department of Crop Protection, Federal University of Pelotas (UFPel), Pelotas 96010-610, Brazil. daiane.benemann@ufpel.edu.br.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Kremer</LastName><ForeName>Frederico S</ForeName><Initials>FS</Initials><AffiliationInfo><Affiliation>Center for Technological Development, Federal University of Pelotas (UFPel), Pelotas 96010-610, Brazil. frederico.kremer@thrivedatascience.com.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Galli</LastName><ForeName>Vanessa</ForeName><Initials>V</Initials><AffiliationInfo><Affiliation>Center for Technological Development, Federal University of Pelotas (UFPel), Pelotas 96010-610, Brazil. vanessa.galli@ufpel.edu.br.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Millwood</LastName><ForeName>Reginald J</ForeName><Initials>RJ</Initials><AffiliationInfo><Affiliation>Department of Plant Sciences, University of Tennessee (UTK), Knoxville, TN 37996, USA. rmillwood@utk.edu.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Cechin</LastName><ForeName>Joanei</ForeName><Initials>J</Initials><AffiliationInfo><Affiliation>Department of Crop Protection, Federal University of Pelotas (UFPel), Pelotas 96010-610, Brazil. jcechin@ufpel.edu.br.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Agostinetto</LastName><ForeName>Dirceu</ForeName><Initials>D</Initials><AffiliationInfo><Affiliation>Department of Crop Protection, Federal University of Pelotas (UFPel), Pelotas 96010-610, Brazil. dirceu_agostinetto@ufpel.edu.br.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Maia</LastName><ForeName>Luciano C</ForeName><Initials>LC</Initials><AffiliationInfo><Affiliation>Department of Plant Breeding, Federal University of Pelotas (UFPel), Pelotas 96010-610, Brazil. luciano.maia@ufpel.edu.br.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Vargas</LastName><ForeName>Leandro</ForeName><Initials>L</Initials><AffiliationInfo><Affiliation>Department of Weed Science, Brazilian Agricultural Research Corporation (Embrapa), Passo Fundo 99050-970, Brazil. leandro.vargas@embrapa.br.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Stewart</LastName><ForeName>C Neal</ForeName><Initials>CN</Initials><Suffix>Jr</Suffix><Identifier Source="ORCID">0000-0003-3026-9193</Identifier><AffiliationInfo><Affiliation>Department of Plant Sciences, University of Tennessee (UTK), Knoxville, TN 37996, USA. nealstewart@utk.edu.</Affiliation></AffiliationInfo></Author></AuthorList><Language>eng</Language><GrantList CompleteYN="Y"><Grant><GrantID>0000</GrantID><Agency>Conselho Nacional de Desenvolvimento Cient&#xed;fico e Tecnol&#xf3;gico</Agency><Country/></Grant><Grant><GrantID>00000</GrantID><Agency>Coordena&#xe7;&#xe3;o de Aperfei&#xe7;oamento de Pessoal de N&#xed;vel Superior</Agency><Country/></Grant></GrantList><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType></PublicationTypeList><ArticleDate DateType="Electronic"><Year>2019</Year><Month>06</Month><Day>07</Day></ArticleDate></Article><MedlineJournalInfo><Country>Switzerland</Country><MedlineTA>Plants (Basel)</MedlineTA><NlmUniqueID>101596181</NlmUniqueID><ISSNLinking>2223-7747</ISSNLinking></MedlineJournalInfo><KeywordList Owner="NOTNLM"><Keyword MajorTopicYN="N">RNA-Seq</Keyword><Keyword MajorTopicYN="N">differential gene expression</Keyword><Keyword MajorTopicYN="N">hairy fleabane</Keyword><Keyword MajorTopicYN="N">herbicide metabolization</Keyword><Keyword MajorTopicYN="N">herbicide resistance</Keyword><Keyword MajorTopicYN="N">next-generation sequencing</Keyword><Keyword MajorTopicYN="N">non-target-site resistance (NTSR)</Keyword></KeywordList><CoiStatement>The authors declare no conflict of interest.</CoiStatement></MedlineCitation><PubmedData><History><PubMedPubDate PubStatus="received"><Year>2019</Year><Month>5</Month><Day>4</Day></PubMedPubDate><PubMedPubDate PubStatus="revised"><Year>2019</Year><Month>5</Month><Day>31</Day></PubMedPubDate><PubMedPubDate PubStatus="accepted"><Year>2019</Year><Month>6</Month><Day>4</Day></PubMedPubDate><PubMedPubDate PubStatus="entrez"><Year>2019</Year><Month>6</Month><Day>12</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="pubmed"><Year>2019</Year><Month>6</Month><Day>12</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="medline"><Year>2019</Year><Month>6</Month><Day>12</Day><Hour>6</Hour><Minute>1</Minute></PubMedPubDate><PubMedPubDate 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Overproduction and accumulation of ROS results in metabolic disorders and can lead to the oxidative destruction of the cell. Several stress factors cause ROS overproduction and trigger oxidative stress in crops and weeds. Recently, the involvement of the antioxidant system in weed interference and herbicide treatment in crops and weeds has been the subject of investigation. In this review, we address ROS production and plant mechanisms of defense, alterations in the antioxidant system at transcriptional and enzymatic levels in crops induced by weed interference, and herbicide exposure in crops and weeds. We also describe the mechanisms of action in herbicides that lead to ROS generation in target plants. Lastly, we discuss the relations between antioxidant systems and weed biology and evolution, as well as the interactive effects of herbicide treatment on these factors.</AbstractText></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Caverzan</LastName><ForeName>Andr&#xe9;ia</ForeName><Initials>A</Initials><Identifier Source="ORCID">0000-0003-0925-144X</Identifier><AffiliationInfo><Affiliation>Faculty of Agronomy and Veterinary Medicine, Agronomy Post-Graduate Program, University of Passo Fundo (UPF), Passo Fundo 99052-900, Brazil. acaverzan@hotmail.com.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Piasecki</LastName><ForeName>Cristiano</ForeName><Initials>C</Initials><Identifier Source="ORCID">0000-0002-2868-6863</Identifier><AffiliationInfo><Affiliation>Department of Crop Protection, Federal University of Pelotas, Pelotas 96160-000, Brazil. c_piasecki@hotmail.com.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Chavarria</LastName><ForeName>Geraldo</ForeName><Initials>G</Initials><AffiliationInfo><Affiliation>Faculty of Agronomy and Veterinary Medicine, Agronomy Post-Graduate Program, University of Passo Fundo (UPF), Passo Fundo 99052-900, Brazil. geraldochavarria@upf.br.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Stewart</LastName><ForeName>C Neal</ForeName><Initials>CN</Initials><Suffix>Jr</Suffix><AffiliationInfo><Affiliation>Department of Plant Sciences, University of Tennessee, Knoxville, TN 37996-4561, USA. nealstewart@utk.edu.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Vargas</LastName><ForeName>Leandro</ForeName><Initials>L</Initials><AffiliationInfo><Affiliation>Department of Weed Science, Brazilian Agricultural Research Corporation (EMBRAPA), Passo Fundo 99050-970, Brazil. leandro.vargas@embrapa.br.</Affiliation></AffiliationInfo></Author></AuthorList><Language>eng</Language><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType><PublicationType UI="D016454">Review</PublicationType></PublicationTypeList><ArticleDate DateType="Electronic"><Year>2019</Year><Month>03</Month><Day>02</Day></ArticleDate></Article><MedlineJournalInfo><Country>Switzerland</Country><MedlineTA>Int J Mol Sci</MedlineTA><NlmUniqueID>101092791</NlmUniqueID><ISSNLinking>1422-0067</ISSNLinking></MedlineJournalInfo><ChemicalList><Chemical><RegistryNumber>0</RegistryNumber><NameOfSubstance UI="D006540">Herbicides</NameOfSubstance></Chemical><Chemical><RegistryNumber>0</RegistryNumber><NameOfSubstance UI="D017382">Reactive Oxygen Species</NameOfSubstance></Chemical></ChemicalList><CitationSubset>IM</CitationSubset><MeshHeadingList><MeshHeading><DescriptorName UI="D018556" MajorTopicYN="N">Crops, Agricultural</DescriptorName><QualifierName UI="Q000187" 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MajorTopicYN="N">metabolism</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D017382" MajorTopicYN="N">Reactive Oxygen Species</DescriptorName><QualifierName UI="Q000378" MajorTopicYN="Y">metabolism</QualifierName></MeshHeading></MeshHeadingList><KeywordList Owner="NOTNLM"><Keyword MajorTopicYN="N">herbicide resistance</Keyword><Keyword MajorTopicYN="N">herbicide treatment</Keyword><Keyword MajorTopicYN="N">oxidative stress</Keyword><Keyword MajorTopicYN="N">reactive oxygen species (ROS)</Keyword><Keyword MajorTopicYN="N">weed evolution</Keyword></KeywordList><CoiStatement>The authors declare no conflict of interest. </CoiStatement></MedlineCitation><PubmedData><History><PubMedPubDate PubStatus="received"><Year>2019</Year><Month>2</Month><Day>3</Day></PubMedPubDate><PubMedPubDate PubStatus="accepted"><Year>2019</Year><Month>2</Month><Day>25</Day></PubMedPubDate><PubMedPubDate 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                                     <div class="mbp_pagination text-right"><ul class="page_navigation" style="text-align:right"><li class="page-item" style="border:none;">Page <strong>1</strong> of <strong>1</strong></li></ul></div> 
                          
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					 <h5 class="title mb-3"><a href="https://www.litmetric.com/detail/35586220/The-Genetic-Architecture-of-Nitrogen-Use-Efficiency-in-Switchgrass-L">The Genetic Architecture of Nitrogen Use Efficiency in Switchgrass ( L.).</a></h5><div class="publication-auther"><a href="https://www.litmetric.com/author/Vivek+Shrestha" class="tag" style="margin-bottom: 5px;">Vivek Shrestha</a> <a href="https://www.litmetric.com/author/Hari+B+Chhetri" class="tag" style="margin-bottom: 5px;">Hari B Chhetri</a> <a href="https://www.litmetric.com/author/David+Kainer" class="tag" style="margin-bottom: 5px;">David Kainer</a> <a href="https://www.litmetric.com/author/Yaping+Xu" class="tag" style="margin-bottom: 5px;">Yaping Xu</a> <a href="https://www.litmetric.com/author/Lance+Hamilton" class="tag" style="margin-bottom: 5px;">Lance Hamilton</a> <a href="https://www.litmetric.com/author/Cristiano+Piasecki" class="tag" style="margin-bottom: 5px;">Cristiano Piasecki</a></div><p class="mb-0 fz14 list-inline-item mb5-sm pe-1"><i class="flaticon-contract fz16 vam text-thm2 me-1"></i> Front Plant Sci</p><p class="mb-0 fz14 list-inline-item mb5-sm pe-1"><i class="flaticon-calendar fz16 vam text-thm2 me-1 bdrl1 pl15 pl0-xs bdrn-xs"></i> May 2022</p></div>
								 </div><p class="text mt10">Switchgrass ( L.) has immense potential as a bioenergy crop with the aim of producing biofuel as an end goal. Nitrogen (N)-related sustainability traits, such as nitrogen use efficiency (NUE) and nitrogen remobilization efficiency (NRE), are important factors affecting switchgrass quality and productivity.</p><a href="https://www.litmetric.com/detail/35586220/The-Genetic-Architecture-of-Nitrogen-Use-Efficiency-in-Switchgrass-L" class="ud-btn btn-thm mb25 me-4 "><i class="flaticon-contract fz16 vam text-thm2 me-1" style="color:white"></i> View Article and Find Full Text PDF <i class="fal fa-arrow-right-long"></i></a><div class="skill-tags d-flex align-items-center justify-content-start mb20-md"></div></div>
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					 <h5 class="title mb-3"><a href="https://www.litmetric.com/detail/34961199/Sustainability-Trait-Modeling-of-Field-Grown-Switchgrass-Using-UAV-Based-Imagery">Sustainability Trait Modeling of Field-Grown Switchgrass () Using UAV-Based Imagery.</a></h5><div class="publication-auther"><a href="https://www.litmetric.com/author/Yaping+Xu" class="tag" style="margin-bottom: 5px;">Yaping Xu</a> <a href="https://www.litmetric.com/author/Vivek+Shrestha" class="tag" style="margin-bottom: 5px;">Vivek Shrestha</a> <a href="https://www.litmetric.com/author/Cristiano+Piasecki" class="tag" style="margin-bottom: 5px;">Cristiano Piasecki</a> <a href="https://www.litmetric.com/author/Benjamin+Wolfe" class="tag" style="margin-bottom: 5px;">Benjamin Wolfe</a> <a href="https://www.litmetric.com/author/Lance+Hamilton" class="tag" style="margin-bottom: 5px;">Lance Hamilton</a></div><p class="mb-0 fz14 list-inline-item mb5-sm pe-1"><i class="flaticon-contract fz16 vam text-thm2 me-1"></i> Plants (Basel)</p><p class="mb-0 fz14 list-inline-item mb5-sm pe-1"><i class="flaticon-calendar fz16 vam text-thm2 me-1 bdrl1 pl15 pl0-xs bdrn-xs"></i> December 2021</p></div>
								 </div><p class="text mt10">Unmanned aerial vehicles (UAVs) provide an intermediate scale of spatial and spectral data collection that yields increased accuracy and consistency in data collection for morphological and physiological traits than satellites and expanded flexibility and high-throughput compared to ground-based data collection. In this study, we used UAV-based remote sensing for automated phenotyping of field-grown switchgrass (), a leading bioenergy feedstock. Using vegetation indices calculated from a UAV-based multispectral camera, statistical models were developed for rust disease caused by , leaf chlorophyll, nitrogen, and lignin contents.</p><a href="https://www.litmetric.com/detail/34961199/Sustainability-Trait-Modeling-of-Field-Grown-Switchgrass-Using-UAV-Based-Imagery" class="ud-btn btn-thm mb25 me-4 "><i class="flaticon-contract fz16 vam text-thm2 me-1" style="color:white"></i> View Article and Find Full Text PDF <i class="fal fa-arrow-right-long"></i></a><div class="skill-tags d-flex align-items-center justify-content-start mb20-md"></div></div>
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					 <h5 class="title mb-3"><a href="https://www.litmetric.com/detail/34681011/Novel-Candidate-Genes-Differentially-Expressed-in-Glyphosate-Treated-Horseweed">Novel Candidate Genes Differentially Expressed in Glyphosate-Treated Horseweed ().</a></h5><div class="publication-auther"><a href="https://www.litmetric.com/author/Yongil+Yang" class="tag" style="margin-bottom: 5px;">Yongil Yang</a> <a href="https://www.litmetric.com/author/Cory+Gardner" class="tag" style="margin-bottom: 5px;">Cory Gardner</a> <a href="https://www.litmetric.com/author/Pallavi+Gupta" class="tag" style="margin-bottom: 5px;">Pallavi Gupta</a> <a href="https://www.litmetric.com/author/Yanhui+Peng" class="tag" style="margin-bottom: 5px;">Yanhui Peng</a> <a href="https://www.litmetric.com/author/Cristiano+Piasecki" class="tag" style="margin-bottom: 5px;">Cristiano Piasecki</a></div><p class="mb-0 fz14 list-inline-item mb5-sm pe-1"><i class="flaticon-contract fz16 vam text-thm2 me-1"></i> Genes (Basel)</p><p class="mb-0 fz14 list-inline-item mb5-sm pe-1"><i class="flaticon-calendar fz16 vam text-thm2 me-1 bdrl1 pl15 pl0-xs bdrn-xs"></i> October 2021</p></div>
								 </div><p class="text mt10">The evolution of herbicide-resistant weed species is a serious threat for weed control. Therefore, we need an improved understanding of how gene regulation confers herbicide resistance in order to slow the evolution of resistance. The present study analyzed differentially expressed genes after glyphosate treatment on a glyphosate-resistant Tennessee ecotype (TNR) of horseweed (), compared to a susceptible biotype (TNS).</p><a href="https://www.litmetric.com/detail/34681011/Novel-Candidate-Genes-Differentially-Expressed-in-Glyphosate-Treated-Horseweed" class="ud-btn btn-thm mb25 me-4 "><i class="flaticon-contract fz16 vam text-thm2 me-1" style="color:white"></i> View Article and Find Full Text PDF <i class="fal fa-arrow-right-long"></i></a><div class="skill-tags d-flex align-items-center justify-content-start mb20-md"></div></div>
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					 <h5 class="title mb-3"><a href="https://www.litmetric.com/detail/34585834/Mini-synplastomes-for-plastid-genetic-engineering">Mini-synplastomes for plastid genetic engineering.</a></h5><div class="publication-auther"><a href="https://www.litmetric.com/author/Alessandro+Occhialini" class="tag" style="margin-bottom: 5px;">Alessandro Occhialini</a> <a href="https://www.litmetric.com/author/Alexander+C+Pfotenhauer" class="tag" style="margin-bottom: 5px;">Alexander C Pfotenhauer</a> <a href="https://www.litmetric.com/author/Li+Li" class="tag" style="margin-bottom: 5px;">Li Li</a> <a href="https://www.litmetric.com/author/Stacee+A+Harbison" class="tag" style="margin-bottom: 5px;">Stacee A Harbison</a> <a href="https://www.litmetric.com/author/Andrew+J+Lail" class="tag" style="margin-bottom: 5px;">Andrew J Lail</a> <a href="https://www.litmetric.com/author/Cristiano+Piasecki" class="tag" style="margin-bottom: 5px;">Cristiano Piasecki</a></div><p class="mb-0 fz14 list-inline-item mb5-sm pe-1"><i class="flaticon-contract fz16 vam text-thm2 me-1"></i> Plant Biotechnol J</p><p class="mb-0 fz14 list-inline-item mb5-sm pe-1"><i class="flaticon-calendar fz16 vam text-thm2 me-1 bdrl1 pl15 pl0-xs bdrn-xs"></i> February 2022</p></div>
								 </div>		<div class="blockquote-style1 mb-4 mb-lg-5" ><h5 style="font-weight:bold">Article Synopsis</h5><div class="col-auto">
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                    <ul><li><i class='far fa-check text-thm3 bgc-thm3-light'></i>- The development of the 'mini-synplastome' provides a new method for introducing synthetic circuits in plant plastids without disturbing the native plastome.</li><li><i class='far fa-check text-thm3 bgc-thm3-light'></i>- This innovative genome structure is based on the unique organization of dinoflagellate plastomes, featuring multiple minicircles instead of a single genome.</li><li><i class='far fa-check text-thm3 bgc-thm3-light'></i>- Mini-synplastomes aim to enhance chloroplast biotechnology by allowing easy cloning and predictable transgene expression, while remaining independent from the plant's existing genetic material.</li> </ul>
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              </div></div><a href="https://www.litmetric.com/detail/34585834/Mini-synplastomes-for-plastid-genetic-engineering" class="ud-btn btn-thm mb25 me-4 "><i class="flaticon-contract fz16 vam text-thm2 me-1" style="color:white"></i> View Article and Find Full Text PDF <i class="fal fa-arrow-right-long"></i></a><div class="skill-tags d-flex align-items-center justify-content-start mb20-md"></div></div>
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					 <h5 class="title mb-3"><a href="https://www.litmetric.com/detail/33193511/High-Throughput-Switchgrass-Phenotyping-and-Biomass-Modeling-by-UAV">High-Throughput Switchgrass Phenotyping and Biomass Modeling by UAV.</a></h5><div class="publication-auther"><a href="https://www.litmetric.com/author/Fei+Li" class="tag" style="margin-bottom: 5px;">Fei Li</a> <a href="https://www.litmetric.com/author/Cristiano+Piasecki" class="tag" style="margin-bottom: 5px;">Cristiano Piasecki</a> <a href="https://www.litmetric.com/author/Reginald+J+Millwood" class="tag" style="margin-bottom: 5px;">Reginald J Millwood</a> <a href="https://www.litmetric.com/author/Benjamin+Wolfe" class="tag" style="margin-bottom: 5px;">Benjamin Wolfe</a> <a href="https://www.litmetric.com/author/Mitra+Mazarei" class="tag" style="margin-bottom: 5px;">Mitra Mazarei</a></div><p class="mb-0 fz14 list-inline-item mb5-sm pe-1"><i class="flaticon-contract fz16 vam text-thm2 me-1"></i> Front Plant Sci</p><p class="mb-0 fz14 list-inline-item mb5-sm pe-1"><i class="flaticon-calendar fz16 vam text-thm2 me-1 bdrl1 pl15 pl0-xs bdrn-xs"></i> October 2020</p></div>
								 </div><p class="text mt10">Unmanned aerial vehicle (UAV) technology is an emerging powerful approach for high-throughput plant phenotyping field-grown crops. Switchgrass ( L.) is a lignocellulosic bioenergy crop for which studies on yield, sustainability, and biofuel traits are performed.</p><a href="https://www.litmetric.com/detail/33193511/High-Throughput-Switchgrass-Phenotyping-and-Biomass-Modeling-by-UAV" class="ud-btn btn-thm mb25 me-4 "><i class="flaticon-contract fz16 vam text-thm2 me-1" style="color:white"></i> View Article and Find Full Text PDF <i class="fal fa-arrow-right-long"></i></a><div class="skill-tags d-flex align-items-center justify-content-start mb20-md"></div></div>
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					 <h5 class="title mb-3"><a href="https://www.litmetric.com/detail/32481698/Transcriptome-Analysis-Identifies-Candidate-Target-Genes-Involved-in-Glyphosate-Resistance-Mechanism">Transcriptome Analysis Identifies Candidate Target Genes Involved in Glyphosate-Resistance Mechanism in .</a></h5><div class="publication-auther"><a href="https://www.litmetric.com/author/Joanei+Cechin" class="tag" style="margin-bottom: 5px;">Joanei Cechin</a> <a href="https://www.litmetric.com/author/Cristiano+Piasecki" class="tag" style="margin-bottom: 5px;">Cristiano Piasecki</a> <a href="https://www.litmetric.com/author/Daiane+P+Benemann" class="tag" style="margin-bottom: 5px;">Daiane P Benemann</a> <a href="https://www.litmetric.com/author/Frederico+S+Kremer" class="tag" style="margin-bottom: 5px;">Frederico S Kremer</a> <a href="https://www.litmetric.com/author/Vanessa+Galli" class="tag" style="margin-bottom: 5px;">Vanessa Galli</a></div><p class="mb-0 fz14 list-inline-item mb5-sm pe-1"><i class="flaticon-contract fz16 vam text-thm2 me-1"></i> Plants (Basel)</p><p class="mb-0 fz14 list-inline-item mb5-sm pe-1"><i class="flaticon-calendar fz16 vam text-thm2 me-1 bdrl1 pl15 pl0-xs bdrn-xs"></i> May 2020</p></div>
								 </div><p class="text mt10">Italian ryegrass (; LOLMU) is one of the most troublesome weeds in temperate regions in the world. This weed species interfere with wheat, corn, rye, and oat, causing significant crop yield losses. This species has evolved glyphosate resistance, making it difficult to control.</p><a href="https://www.litmetric.com/detail/32481698/Transcriptome-Analysis-Identifies-Candidate-Target-Genes-Involved-in-Glyphosate-Resistance-Mechanism" class="ud-btn btn-thm mb25 me-4 "><i class="flaticon-contract fz16 vam text-thm2 me-1" style="color:white"></i> View Article and Find Full Text PDF <i class="fal fa-arrow-right-long"></i></a><div class="skill-tags d-flex align-items-center justify-content-start mb20-md"></div></div>
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					 <h5 class="title mb-3"><a href="https://www.litmetric.com/detail/31181629/Transcriptomic-Analysis-Identifies-New-Non-Target-Site-Glyphosate-Resistance-Genes-in">Transcriptomic Analysis Identifies New Non-Target Site Glyphosate-Resistance Genes in .</a></h5><div class="publication-auther"><a href="https://www.litmetric.com/author/Cristiano+Piasecki" class="tag" style="margin-bottom: 5px;">Cristiano Piasecki</a> <a href="https://www.litmetric.com/author/Yongil+Yang" class="tag" style="margin-bottom: 5px;">Yongil Yang</a> <a href="https://www.litmetric.com/author/Daiane+P+Benemann" class="tag" style="margin-bottom: 5px;">Daiane P Benemann</a> <a href="https://www.litmetric.com/author/Frederico+S+Kremer" class="tag" style="margin-bottom: 5px;">Frederico S Kremer</a> <a href="https://www.litmetric.com/author/Vanessa+Galli" class="tag" style="margin-bottom: 5px;">Vanessa Galli</a></div><p class="mb-0 fz14 list-inline-item mb5-sm pe-1"><i class="flaticon-contract fz16 vam text-thm2 me-1"></i> Plants (Basel)</p><p class="mb-0 fz14 list-inline-item mb5-sm pe-1"><i class="flaticon-calendar fz16 vam text-thm2 me-1 bdrl1 pl15 pl0-xs bdrn-xs"></i> June 2019</p></div>
								 </div><p class="text mt10"> (hairy fleabane) is one of the most problematic and widespread glyphosate-resistant weeds in the world. This highly competitive weed species significantly interferes with crop growth and substantially decreases crop yield. Despite its agricultural importance, the molecular mechanisms of glyphosate resistance are still unknown.</p><a href="https://www.litmetric.com/detail/31181629/Transcriptomic-Analysis-Identifies-New-Non-Target-Site-Glyphosate-Resistance-Genes-in" class="ud-btn btn-thm mb25 me-4 "><i class="flaticon-contract fz16 vam text-thm2 me-1" style="color:white"></i> View Article and Find Full Text PDF <i class="fal fa-arrow-right-long"></i></a><div class="skill-tags d-flex align-items-center justify-content-start mb20-md"></div></div>
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					 <h5 class="title mb-3"><a href="https://www.litmetric.com/detail/30832379/Defenses-Against-ROS-in-Crops-and-Weeds-The-Effects-of-Interference-and-Herbicides">Defenses Against ROS in Crops and Weeds: The Effects of Interference and Herbicides.</a></h5><div class="publication-auther"><a href="https://www.litmetric.com/author/Andreia+Caverzan" class="tag" style="margin-bottom: 5px;">Andréia Caverzan</a> <a href="https://www.litmetric.com/author/Cristiano+Piasecki" class="tag" style="margin-bottom: 5px;">Cristiano Piasecki</a> <a href="https://www.litmetric.com/author/Geraldo+Chavarria" class="tag" style="margin-bottom: 5px;">Geraldo Chavarria</a> <a href="https://www.litmetric.com/author/C+Neal+Stewart" class="tag" style="margin-bottom: 5px;">C Neal Stewart</a> <a href="https://www.litmetric.com/author/Leandro+Vargas" class="tag" style="margin-bottom: 5px;">Leandro Vargas</a></div><p class="mb-0 fz14 list-inline-item mb5-sm pe-1"><i class="flaticon-contract fz16 vam text-thm2 me-1"></i> Int J Mol Sci</p><p class="mb-0 fz14 list-inline-item mb5-sm pe-1"><i class="flaticon-calendar fz16 vam text-thm2 me-1 bdrl1 pl15 pl0-xs bdrn-xs"></i> March 2019</p></div>
								 </div><p class="text mt10">The antioxidant defense system acts to maintain the equilibrium between the production of reactive oxygen species (ROS) and the elimination of toxic levels of ROS in plants. Overproduction and accumulation of ROS results in metabolic disorders and can lead to the oxidative destruction of the cell. Several stress factors cause ROS overproduction and trigger oxidative stress in crops and weeds.</p><a href="https://www.litmetric.com/detail/30832379/Defenses-Against-ROS-in-Crops-and-Weeds-The-Effects-of-Interference-and-Herbicides" class="ud-btn btn-thm mb25 me-4 "><i class="flaticon-contract fz16 vam text-thm2 me-1" style="color:white"></i> View Article and Find Full Text PDF <i class="fal fa-arrow-right-long"></i></a><div class="skill-tags d-flex align-items-center justify-content-start mb20-md"></div></div>
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