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dc.contributor.authorLópez Malvar, Ana 
dc.contributor.authorButrón Gómez, Ana María
dc.contributor.authorMalvar, R. A.
dc.contributor.authorMcQueen Mason, S. J.
dc.contributor.authorFaas, L.
dc.contributor.authorGómez, L. D.
dc.contributor.authorRevilla, P.
dc.contributor.authorFigueroa Garrido, David Jose 
dc.contributor.authorSantiago Carabelos, Rogelio 
dc.date.accessioned2021-11-19T12:28:54Z
dc.date.available2021-11-19T12:28:54Z
dc.date.issued2021-02-09
dc.identifier.citationScientific Reports, 11(1): 3425 (2021)spa
dc.identifier.issn20452322
dc.identifier.urihttp://hdl.handle.net/11093/2722
dc.description.abstractCellulosic ethanol derived from fast growing C4 grasses could become an alternative to finite fossil fuels. With the potential to generate a major source of lignocellulosic biomass, maize has gained importance as an outstanding model plant for studying the complex cell wall network and also to optimize crop breeding strategies in bioenergy grasses. A genome-wide association study (GWAS) was conducted using a subset of 408 Recombinant Inbred Lines (RILs) from a Multi-Parent Advanced Generation Intercross (MAGIC) Population in order to identify single nucleotide polymorphisms (SNPs) associated with yield and saccharification efficiency of maize stover. We identified 13 SNPs significantly associated with increased stover yield that corresponded to 13 QTL, and 2 SNPs significantly associated with improved saccharification efficiency, that could be clustered into 2 QTL. We have pointed out the most interesting SNPs to be implemented in breeding programs based on results from analyses of averaged and yearly data. Association mapping in this MAGIC population highlight genomic regions directly linked to traits that influence the final use of maize. Markers linked to these QTL could be used in genomic or marker-assisted selection programs to improve biomass quality for ethanol production. This study opens a possible optimisation path for improving the viability of second-generation biofuelseng
dc.description.sponsorshipPlan Estatal de Ciencia y Tecnología de España | Ref. RTI2018–096776-B-C21spa
dc.description.sponsorshipPlan Estatal de Ciencia y Tecnología de España | Ref. RTI2018–096776-B-C22spa
dc.language.isoengspa
dc.publisherScientific Reportsspa
dc.rightsAttribution 4.0 International
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.titleAssociation mapping for maize stover yield and saccharification efficiency using a multiparent advanced generation intercross (MAGIC) populationeng
dc.typearticlespa
dc.rights.accessRightsopenAccessspa
dc.relation.projectIDinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/RTI2018-096776-B-C21/ESspa
dc.relation.projectIDinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/RTI2018-096776-B-C22/ESspa
dc.identifier.doi10.1038/s41598-021-83107-1
dc.identifier.editorhttp://www.nature.com/articles/s41598-021-83107-1spa
dc.publisher.departamentoBioloxía vexetal e ciencias do solospa
dc.publisher.grupoinvestigacionAgrobioloxía Ambiental: Calidade, Solos e Plantasspa
dc.subject.unesco2417.13 Ecología Vegetalspa
dc.subject.unesco3103.08 Gestión de la Producción Vegetalspa
dc.subject.unesco3308 Ingeniería y Tecnología del Medio Ambientespa
dc.date.updated2021-11-16T11:52:20Z
dc.computerCitationpub_title=Scientific Reports|volume=11|journal_number=1|start_pag=3425|end_pag=spa


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    Attribution 4.0 International
    Except where otherwise noted, this item's license is described as Attribution 4.0 International