dc.creatorOliveira Silva, Franklin Magnum de
dc.creatorLichtenstein, Gabriel
dc.creatorAlseekh, Saleh
dc.creatorRosado‐Souza, Laise
dc.creatorConte, Mariana
dc.creatorFuentes Suguiyama, Vanessa
dc.creatorLira, Bruno Silvestre
dc.creatorFanourakis, Dimitrios
dc.creatorUsadel, Björn
dc.creatorLopes Bhering, Leonardo
dc.creatorDaMatta, Fábio M.
dc.creatorSulpice, Ronan
dc.creatorAraújo, Wagner L.
dc.creatorRossi, Magdalena
dc.creatorde Setta, Nathalia
dc.creatorFernie, Alisdair R.
dc.creatorCarrari, Fernando
dc.creatorNunes Nesi, Adriano
dc.date.accessioned2022-07-18T10:39:07Z
dc.date.accessioned2023-03-15T14:16:05Z
dc.date.available2022-07-18T10:39:07Z
dc.date.available2023-03-15T14:16:05Z
dc.date.created2022-07-18T10:39:07Z
dc.date.issued2018-02
dc.identifier1365-3040
dc.identifierhttps://doi.org/10.1111/pce.13084
dc.identifierhttp://hdl.handle.net/20.500.12123/12338
dc.identifierhttps://onlinelibrary.wiley.com/doi/10.1111/pce.13084
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/6215286
dc.description.abstractTo identify genomic regions involved in the regulation of fundamental physiological processes such as photosynthesis and respiration, a population of Solanum pennellii introgression lines was analyzed. We determined phenotypes for physiological, metabolic, and growth related traits, including gas exchange and chlorophyll fluorescence parameters. Data analysis allowed the identification of 208 physiological and metabolic quantitative trait loci with 33 of these being associated to smaller intervals of the genomic regions, termed BINs. Eight BINs were identified that were associated with higher assimilation rates than the recurrent parent M82. Two and 10 genomic regions were related to shoot and root dry matter accumulation, respectively. Nine genomic regions were associated with starch levels, whereas 12 BINs were associated with the levels of other metabolites. Additionally, a comprehensive and detailed annotation of the genomic regions spanning these quantitative trait loci allowed us to identify 87 candidate genes that putatively control the investigated traits. We confirmed 8 of these at the level of variance in gene expression. Taken together, our results allowed the identification of candidate genes that most likely regulate photosynthesis, primary metabolism, and plant growth and as such provide new avenues for crop improvement.
dc.languageeng
dc.publisherWiley
dc.rightsinfo:eu-repo/semantics/openAccess
dc.sourcePlant, Cell and Environment 41 (2) : 327-341 (Febrero 2018)
dc.subjectIntrogression Lines
dc.subjectMetabolism
dc.subjectQuantitative Trait Loci
dc.subjectPlant Biotechnology
dc.subjectPhotosynthesis
dc.subjectPlant Growth
dc.subjectTomatoes
dc.subjectLíneas de Introgresión
dc.subjectMetabolismo
dc.subjectLoci de Rasgos Cuantitativos
dc.subjectBiotecnología Vegetal
dc.subjectFotosíntesis
dc.subjectCrecimiento de Planta
dc.subjectTomate
dc.subjectSolanum pennellii
dc.titleThe genetic architecture of photosynthesis and plant growthrelated traits in tomato
dc.typeinfo:ar-repo/semantics/artículo
dc.typeinfo:eu-repo/semantics/article
dc.typeinfo:eu-repo/semantics/publishedVersion


Este ítem pertenece a la siguiente institución