PlantSEED enables automated annotation and reconstruction of plant primary metabolism with improved compartmentalization and comparative consistency.
Identifieur interne : 001E72 ( Ncbi/Checkpoint ); précédent : 001E71; suivant : 001E73PlantSEED enables automated annotation and reconstruction of plant primary metabolism with improved compartmentalization and comparative consistency.
Auteurs : Samuel M D. Seaver [États-Unis] ; Claudia Lerma-Ortiz [États-Unis] ; Neal Conrad [États-Unis] ; Arman Mikaili [États-Unis] ; Avinash Sreedasyam [États-Unis] ; Andrew D. Hanson [États-Unis] ; Christopher S. Henry [États-Unis]Source :
- The Plant journal : for cell and molecular biology [ 1365-313X ] ; 2018.
Descripteurs français
- KwdFr :
- MESH :
- génétique : Génome végétal, Plantes.
- métabolisme : Plantes.
- Algorithmes, Bases de données factuelles, Biologie informatique, Métabolomique, Séquençage nucléotidique à haut débit, Transcriptome, Voies et réseaux métaboliques.
English descriptors
- KwdEn :
- MESH :
- genetics : Genome, Plant, Plants.
- metabolism : Plants.
- methods : Computational Biology, Metabolomics.
- Algorithms, Databases, Factual, High-Throughput Nucleotide Sequencing, Metabolic Networks and Pathways, Transcriptome.
Abstract
Genome-scale metabolic reconstructions help us to understand and engineer metabolism. Next-generation sequencing technologies are delivering genomes and transcriptomes for an ever-widening range of plants. While such omic data can, in principle, be used to compare metabolic reconstructions in different species, organs and environmental conditions, these comparisons require a standardized framework for the reconstruction of metabolic networks from transcript data. We previously introduced PlantSEED as a framework covering primary metabolism for 10 species. We have now expanded PlantSEED to include 39 species and provide tools that enable automated annotation and metabolic reconstruction from transcriptome data. The algorithm for automated annotation in PlantSEED propagates annotations using a set of signature k-mers (short amino acid sequences characteristic of particular proteins) that identify metabolic enzymes with an accuracy of about 97%. PlantSEED reconstructions are built from a curated template that includes consistent compartmentalization for more than 100 primary metabolic subsystems. Together, the annotation and reconstruction algorithms produce reconstructions without gaps and with more accurate compartmentalization than existing resources. These tools are available via the PlantSEED web interface at http://modelseed.org, which enables users to upload, annotate and reconstruct from private transcript data and simulate metabolic activity under various conditions using flux balance analysis. We demonstrate the ability to compare these metabolic reconstructions with a case study involving growth on several nitrogen sources in roots of four species.
DOI: 10.1111/tpj.14003
PubMed: 29924895
Affiliations:
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Seaver</name><affiliation wicri:level="1"><nlm:affiliation>Mathematics and Computer Science Division, Argonne National Laboratory, Argonne, IL, 60439, USA.</nlm:affiliation><country xml:lang="fr">États-Unis</country><wicri:regionArea>Mathematics and Computer Science Division, Argonne National Laboratory, Argonne, IL, 60439</wicri:regionArea><wicri:noRegion>60439</wicri:noRegion></affiliation></author><author><name sortKey="Lerma Ortiz, Claudia" sort="Lerma Ortiz, Claudia" uniqKey="Lerma Ortiz C" first="Claudia" last="Lerma-Ortiz">Claudia Lerma-Ortiz</name><affiliation wicri:level="1"><nlm:affiliation>Horticultural Sciences Department, University of Florida, Gainesville, FL, 32611, USA.</nlm:affiliation><country xml:lang="fr">États-Unis</country><wicri:regionArea>Horticultural Sciences Department, University of Florida, Gainesville, FL, 32611</wicri:regionArea><wicri:noRegion>32611</wicri:noRegion></affiliation></author><author><name sortKey="Conrad, Neal" sort="Conrad, Neal" uniqKey="Conrad N" first="Neal" last="Conrad">Neal Conrad</name><affiliation wicri:level="1"><nlm:affiliation>Mathematics and Computer Science Division, Argonne National Laboratory, Argonne, IL, 60439, USA.</nlm:affiliation><country xml:lang="fr">États-Unis</country><wicri:regionArea>Mathematics and Computer Science Division, Argonne National Laboratory, Argonne, IL, 60439</wicri:regionArea><wicri:noRegion>60439</wicri:noRegion></affiliation></author><author><name sortKey="Mikaili, Arman" sort="Mikaili, Arman" uniqKey="Mikaili A" first="Arman" last="Mikaili">Arman Mikaili</name><affiliation wicri:level="1"><nlm:affiliation>Mathematics and Computer Science Division, Argonne National Laboratory, Argonne, IL, 60439, USA.</nlm:affiliation><country xml:lang="fr">États-Unis</country><wicri:regionArea>Mathematics and Computer Science Division, Argonne National Laboratory, Argonne, IL, 60439</wicri:regionArea><wicri:noRegion>60439</wicri:noRegion></affiliation></author><author><name sortKey="Sreedasyam, Avinash" sort="Sreedasyam, Avinash" uniqKey="Sreedasyam A" first="Avinash" last="Sreedasyam">Avinash Sreedasyam</name><affiliation wicri:level="1"><nlm:affiliation>HudsonAlpha Institute for Biotechnology, Huntsville, AL, 35806, USA.</nlm:affiliation><country xml:lang="fr">États-Unis</country><wicri:regionArea>HudsonAlpha Institute for Biotechnology, Huntsville, AL, 35806</wicri:regionArea><wicri:noRegion>35806</wicri:noRegion></affiliation></author><author><name sortKey="Hanson, Andrew D" sort="Hanson, Andrew D" uniqKey="Hanson A" first="Andrew D" last="Hanson">Andrew D. Hanson</name><affiliation wicri:level="1"><nlm:affiliation>Horticultural Sciences Department, University of Florida, Gainesville, FL, 32611, USA.</nlm:affiliation><country xml:lang="fr">États-Unis</country><wicri:regionArea>Horticultural Sciences Department, University of Florida, Gainesville, FL, 32611</wicri:regionArea><wicri:noRegion>32611</wicri:noRegion></affiliation></author><author><name sortKey="Henry, Christopher S" sort="Henry, Christopher S" uniqKey="Henry C" first="Christopher S" last="Henry">Christopher S. Henry</name><affiliation wicri:level="1"><nlm:affiliation>Mathematics and Computer Science Division, Argonne National Laboratory, Argonne, IL, 60439, USA.</nlm:affiliation><country xml:lang="fr">États-Unis</country><wicri:regionArea>Mathematics and Computer Science Division, Argonne National Laboratory, Argonne, IL, 60439</wicri:regionArea><wicri:noRegion>60439</wicri:noRegion></affiliation></author></analytic><series><title level="j">The Plant journal : for cell and molecular biology</title><idno type="eISSN">1365-313X</idno><imprint><date when="2018" type="published">2018</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Algorithms</term><term>Computational Biology (methods)</term><term>Databases, Factual</term><term>Genome, Plant (genetics)</term><term>High-Throughput Nucleotide Sequencing</term><term>Metabolic Networks and Pathways</term><term>Metabolomics (methods)</term><term>Plants (genetics)</term><term>Plants (metabolism)</term><term>Transcriptome</term></keywords><keywords scheme="KwdFr" xml:lang="fr"><term>Algorithmes</term><term>Bases de données factuelles</term><term>Biologie informatique ()</term><term>Génome végétal (génétique)</term><term>Métabolomique ()</term><term>Plantes (génétique)</term><term>Plantes (métabolisme)</term><term>Séquençage nucléotidique à haut débit</term><term>Transcriptome</term><term>Voies et réseaux métaboliques</term></keywords><keywords scheme="MESH" qualifier="genetics" xml:lang="en"><term>Genome, Plant</term><term>Plants</term></keywords><keywords scheme="MESH" qualifier="génétique" xml:lang="fr"><term>Génome végétal</term><term>Plantes</term></keywords><keywords scheme="MESH" qualifier="metabolism" xml:lang="en"><term>Plants</term></keywords><keywords scheme="MESH" qualifier="methods" xml:lang="en"><term>Computational Biology</term><term>Metabolomics</term></keywords><keywords scheme="MESH" qualifier="métabolisme" xml:lang="fr"><term>Plantes</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Algorithms</term><term>Databases, Factual</term><term>High-Throughput Nucleotide Sequencing</term><term>Metabolic Networks and Pathways</term><term>Transcriptome</term></keywords><keywords scheme="MESH" xml:lang="fr"><term>Algorithmes</term><term>Bases de données factuelles</term><term>Biologie informatique</term><term>Métabolomique</term><term>Séquençage nucléotidique à haut débit</term><term>Transcriptome</term><term>Voies et réseaux métaboliques</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">Genome-scale metabolic reconstructions help us to understand and engineer metabolism. Next-generation sequencing technologies are delivering genomes and transcriptomes for an ever-widening range of plants. While such omic data can, in principle, be used to compare metabolic reconstructions in different species, organs and environmental conditions, these comparisons require a standardized framework for the reconstruction of metabolic networks from transcript data. We previously introduced PlantSEED as a framework covering primary metabolism for 10 species. We have now expanded PlantSEED to include 39 species and provide tools that enable automated annotation and metabolic reconstruction from transcriptome data. The algorithm for automated annotation in PlantSEED propagates annotations using a set of signature k-mers (short amino acid sequences characteristic of particular proteins) that identify metabolic enzymes with an accuracy of about 97%. PlantSEED reconstructions are built from a curated template that includes consistent compartmentalization for more than 100 primary metabolic subsystems. Together, the annotation and reconstruction algorithms produce reconstructions without gaps and with more accurate compartmentalization than existing resources. These tools are available via the PlantSEED web interface at http://modelseed.org, which enables users to upload, annotate and reconstruct from private transcript data and simulate metabolic activity under various conditions using flux balance analysis. We demonstrate the ability to compare these metabolic reconstructions with a case study involving growth on several nitrogen sources in roots of four species.</div></front></TEI><affiliations><list><country><li>États-Unis</li></country></list><tree><country name="États-Unis"><noRegion><name sortKey="Seaver, Samuel M D" sort="Seaver, Samuel M D" uniqKey="Seaver S" first="Samuel M D" last="Seaver">Samuel M D. Seaver</name></noRegion><name sortKey="Conrad, Neal" sort="Conrad, Neal" uniqKey="Conrad N" first="Neal" last="Conrad">Neal Conrad</name><name sortKey="Hanson, Andrew D" sort="Hanson, Andrew D" uniqKey="Hanson A" first="Andrew D" last="Hanson">Andrew D. Hanson</name><name sortKey="Henry, Christopher S" sort="Henry, Christopher S" uniqKey="Henry C" first="Christopher S" last="Henry">Christopher S. Henry</name><name sortKey="Lerma Ortiz, Claudia" sort="Lerma Ortiz, Claudia" uniqKey="Lerma Ortiz C" first="Claudia" last="Lerma-Ortiz">Claudia Lerma-Ortiz</name><name sortKey="Mikaili, Arman" sort="Mikaili, Arman" uniqKey="Mikaili A" first="Arman" last="Mikaili">Arman Mikaili</name><name sortKey="Sreedasyam, Avinash" sort="Sreedasyam, Avinash" uniqKey="Sreedasyam A" first="Avinash" last="Sreedasyam">Avinash Sreedasyam</name></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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