Multi-gene metabolic engineering of tomato plants results in increased fruit yield up to 23%

Autores
Vallarino, José G.; Kubiszewski Jakubiak, Szymon; Ruf, Stephanie; Rößner, Margit; Timm, Stefan; Bauwe, Hermann; Carrari, Fernando Oscar; Rentsch, Doris; Bock, Ralph; Sweetlove, Lee J.; Fernie, Alisdair R.
Año de publicación
2020
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
The capacity to assimilate carbon and nitrogen, to transport the resultant sugars and amino acids to sink tissues, and to convert the incoming sugars and amino acids into storage compounds in the sink tissues, are key determinants of crop yield. Given that all of these processes have the potential to co-limit growth, multiple genetic interventions in source and sink tissues, plus transport processes may be necessary to reach the full yield potential of a crop. We used biolistic combinatorial co-transformation (up to 20 transgenes) for increasing C and N flows with the purpose of increasing tomato fruit yield. We observed an increased fruit yield of up to 23%. To better explore the reconfiguration of metabolic networks in these transformants, we generated a dataset encompassing physiological parameters, gene expression and metabolite profiling on plants grown under glasshouse or polytunnel conditions. A Sparse Partial Least Squares regression model was able to explain the combination of genes that contributed to increased fruit yield. This combinatorial study of multiple transgenes targeting primary metabolism thus offers opportunities to probe the genetic basis of metabolic and phenotypic variation, providing insight into the difficulties in choosing the correct combination of targets for engineering increased fruit yield.
Fil: Vallarino, José G.. Institut Max Planck fur Molekulare Physiologie; Alemania
Fil: Kubiszewski Jakubiak, Szymon. Institut Max Planck fur Molekulare Physiologie; Alemania
Fil: Ruf, Stephanie. Institut Max Planck fur Molekulare Physiologie; Alemania
Fil: Rößner, Margit. Institut Max Planck fur Molekulare Physiologie; Alemania
Fil: Timm, Stefan. Universität Rostock; Alemania
Fil: Bauwe, Hermann. Universität Rostock; Alemania
Fil: Carrari, Fernando Oscar. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Fisiología, Biología Molecular y Neurociencias. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Fisiología, Biología Molecular y Neurociencias; Argentina
Fil: Rentsch, Doris. University of Bern; Suiza
Fil: Bock, Ralph. Institut Max Planck fur Molekulare Physiologie; Alemania
Fil: Sweetlove, Lee J.. University of Oxford; Reino Unido
Fil: Fernie, Alisdair R.. Institut Max Planck fur Molekulare Physiologie; Alemania
Materia
Multi‑gene
Metabolic engineering
Tomato plants
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/142320
Acceder
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network_acronym_str CONICETDig
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network_name_str CONICET Digital (CONICET)
spelling Multi-gene metabolic engineering of tomato plants results in increased fruit yield up to 23%Vallarino, José G.Kubiszewski Jakubiak, SzymonRuf, StephanieRößner, MargitTimm, StefanBauwe, HermannCarrari, Fernando OscarRentsch, DorisBock, RalphSweetlove, Lee J.Fernie, Alisdair R.Multi‑geneMetabolic engineeringTomato plantshttps://purl.org/becyt/ford/1.6https://purl.org/becyt/ford/1The capacity to assimilate carbon and nitrogen, to transport the resultant sugars and amino acids to sink tissues, and to convert the incoming sugars and amino acids into storage compounds in the sink tissues, are key determinants of crop yield. Given that all of these processes have the potential to co-limit growth, multiple genetic interventions in source and sink tissues, plus transport processes may be necessary to reach the full yield potential of a crop. We used biolistic combinatorial co-transformation (up to 20 transgenes) for increasing C and N flows with the purpose of increasing tomato fruit yield. We observed an increased fruit yield of up to 23%. To better explore the reconfiguration of metabolic networks in these transformants, we generated a dataset encompassing physiological parameters, gene expression and metabolite profiling on plants grown under glasshouse or polytunnel conditions. A Sparse Partial Least Squares regression model was able to explain the combination of genes that contributed to increased fruit yield. This combinatorial study of multiple transgenes targeting primary metabolism thus offers opportunities to probe the genetic basis of metabolic and phenotypic variation, providing insight into the difficulties in choosing the correct combination of targets for engineering increased fruit yield.Fil: Vallarino, José G.. Institut Max Planck fur Molekulare Physiologie; AlemaniaFil: Kubiszewski Jakubiak, Szymon. Institut Max Planck fur Molekulare Physiologie; AlemaniaFil: Ruf, Stephanie. Institut Max Planck fur Molekulare Physiologie; AlemaniaFil: Rößner, Margit. Institut Max Planck fur Molekulare Physiologie; AlemaniaFil: Timm, Stefan. Universität Rostock; AlemaniaFil: Bauwe, Hermann. Universität Rostock; AlemaniaFil: Carrari, Fernando Oscar. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Fisiología, Biología Molecular y Neurociencias. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Fisiología, Biología Molecular y Neurociencias; ArgentinaFil: Rentsch, Doris. University of Bern; SuizaFil: Bock, Ralph. Institut Max Planck fur Molekulare Physiologie; AlemaniaFil: Sweetlove, Lee J.. University of Oxford; Reino UnidoFil: Fernie, Alisdair R.. Institut Max Planck fur Molekulare Physiologie; AlemaniaNature Research2020-12info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/142320Vallarino, José G.; Kubiszewski Jakubiak, Szymon; Ruf, Stephanie; Rößner, Margit; Timm, Stefan; et al.; Multi-gene metabolic engineering of tomato plants results in increased fruit yield up to 23%; Nature Research; Scientific Reports; 10; 1; 12-2020; 1-182045-2322CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.1038/s41598-020-73709-6info:eu-repo/semantics/altIdentifier/url/https://www.nature.com/articles/s41598-020-73709-6info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T10:16:42Zoai:ri.conicet.gov.ar:11336/142320instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-29 10:16:43.268CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Multi-gene metabolic engineering of tomato plants results in increased fruit yield up to 23%
title Multi-gene metabolic engineering of tomato plants results in increased fruit yield up to 23%
spellingShingle Multi-gene metabolic engineering of tomato plants results in increased fruit yield up to 23%
Vallarino, José G.
Multi‑gene
Metabolic engineering
Tomato plants
title_short Multi-gene metabolic engineering of tomato plants results in increased fruit yield up to 23%
title_full Multi-gene metabolic engineering of tomato plants results in increased fruit yield up to 23%
title_fullStr Multi-gene metabolic engineering of tomato plants results in increased fruit yield up to 23%
title_full_unstemmed Multi-gene metabolic engineering of tomato plants results in increased fruit yield up to 23%
title_sort Multi-gene metabolic engineering of tomato plants results in increased fruit yield up to 23%
dc.creator.none.fl_str_mv Vallarino, José G.
Kubiszewski Jakubiak, Szymon
Ruf, Stephanie
Rößner, Margit
Timm, Stefan
Bauwe, Hermann
Carrari, Fernando Oscar
Rentsch, Doris
Bock, Ralph
Sweetlove, Lee J.
Fernie, Alisdair R.
author Vallarino, José G.
author_facet Vallarino, José G.
Kubiszewski Jakubiak, Szymon
Ruf, Stephanie
Rößner, Margit
Timm, Stefan
Bauwe, Hermann
Carrari, Fernando Oscar
Rentsch, Doris
Bock, Ralph
Sweetlove, Lee J.
Fernie, Alisdair R.
author_role author
author2 Kubiszewski Jakubiak, Szymon
Ruf, Stephanie
Rößner, Margit
Timm, Stefan
Bauwe, Hermann
Carrari, Fernando Oscar
Rentsch, Doris
Bock, Ralph
Sweetlove, Lee J.
Fernie, Alisdair R.
author2_role author
author
author
author
author
author
author
author
author
author
dc.subject.none.fl_str_mv Multi‑gene
Metabolic engineering
Tomato plants
topic Multi‑gene
Metabolic engineering
Tomato plants
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.6
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv The capacity to assimilate carbon and nitrogen, to transport the resultant sugars and amino acids to sink tissues, and to convert the incoming sugars and amino acids into storage compounds in the sink tissues, are key determinants of crop yield. Given that all of these processes have the potential to co-limit growth, multiple genetic interventions in source and sink tissues, plus transport processes may be necessary to reach the full yield potential of a crop. We used biolistic combinatorial co-transformation (up to 20 transgenes) for increasing C and N flows with the purpose of increasing tomato fruit yield. We observed an increased fruit yield of up to 23%. To better explore the reconfiguration of metabolic networks in these transformants, we generated a dataset encompassing physiological parameters, gene expression and metabolite profiling on plants grown under glasshouse or polytunnel conditions. A Sparse Partial Least Squares regression model was able to explain the combination of genes that contributed to increased fruit yield. This combinatorial study of multiple transgenes targeting primary metabolism thus offers opportunities to probe the genetic basis of metabolic and phenotypic variation, providing insight into the difficulties in choosing the correct combination of targets for engineering increased fruit yield.
Fil: Vallarino, José G.. Institut Max Planck fur Molekulare Physiologie; Alemania
Fil: Kubiszewski Jakubiak, Szymon. Institut Max Planck fur Molekulare Physiologie; Alemania
Fil: Ruf, Stephanie. Institut Max Planck fur Molekulare Physiologie; Alemania
Fil: Rößner, Margit. Institut Max Planck fur Molekulare Physiologie; Alemania
Fil: Timm, Stefan. Universität Rostock; Alemania
Fil: Bauwe, Hermann. Universität Rostock; Alemania
Fil: Carrari, Fernando Oscar. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Fisiología, Biología Molecular y Neurociencias. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Fisiología, Biología Molecular y Neurociencias; Argentina
Fil: Rentsch, Doris. University of Bern; Suiza
Fil: Bock, Ralph. Institut Max Planck fur Molekulare Physiologie; Alemania
Fil: Sweetlove, Lee J.. University of Oxford; Reino Unido
Fil: Fernie, Alisdair R.. Institut Max Planck fur Molekulare Physiologie; Alemania
description The capacity to assimilate carbon and nitrogen, to transport the resultant sugars and amino acids to sink tissues, and to convert the incoming sugars and amino acids into storage compounds in the sink tissues, are key determinants of crop yield. Given that all of these processes have the potential to co-limit growth, multiple genetic interventions in source and sink tissues, plus transport processes may be necessary to reach the full yield potential of a crop. We used biolistic combinatorial co-transformation (up to 20 transgenes) for increasing C and N flows with the purpose of increasing tomato fruit yield. We observed an increased fruit yield of up to 23%. To better explore the reconfiguration of metabolic networks in these transformants, we generated a dataset encompassing physiological parameters, gene expression and metabolite profiling on plants grown under glasshouse or polytunnel conditions. A Sparse Partial Least Squares regression model was able to explain the combination of genes that contributed to increased fruit yield. This combinatorial study of multiple transgenes targeting primary metabolism thus offers opportunities to probe the genetic basis of metabolic and phenotypic variation, providing insight into the difficulties in choosing the correct combination of targets for engineering increased fruit yield.
publishDate 2020
dc.date.none.fl_str_mv 2020-12
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/142320
Vallarino, José G.; Kubiszewski Jakubiak, Szymon; Ruf, Stephanie; Rößner, Margit; Timm, Stefan; et al.; Multi-gene metabolic engineering of tomato plants results in increased fruit yield up to 23%; Nature Research; Scientific Reports; 10; 1; 12-2020; 1-18
2045-2322
CONICET Digital
CONICET
url http://hdl.handle.net/11336/142320
identifier_str_mv Vallarino, José G.; Kubiszewski Jakubiak, Szymon; Ruf, Stephanie; Rößner, Margit; Timm, Stefan; et al.; Multi-gene metabolic engineering of tomato plants results in increased fruit yield up to 23%; Nature Research; Scientific Reports; 10; 1; 12-2020; 1-18
2045-2322
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.1038/s41598-020-73709-6
info:eu-repo/semantics/altIdentifier/url/https://www.nature.com/articles/s41598-020-73709-6
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Nature Research
publisher.none.fl_str_mv Nature Research
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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score 13.070432

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