Developing growth-associated molecular markers via high-throughput phenotyping in spinach

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dc.contributor.authorAwika, Henry O.
dc.contributor.authorBedre, Renesh
dc.contributor.authorYeom, Junho
dc.contributor.authorGibbin Marconi, Thiago
dc.contributor.authorEnciso, Juan
dc.contributor.authorMandadi, Kranthi Kiran
dc.contributor.authorJung, Jinha
dc.contributor.authorAvila, Carlos A.
dc.creator.orcidhttp://orcid.org/0000-0001-8874-5100en_US
dc.creator.orcidhttp://orcid.org/0000-0003-0387-1808en_US
dc.creator.orcidhttp://orcid.org/0000-0001-8874-5100en_US
dc.creator.orcidhttp://orcid.org/0000-0001-7571-1155en_US
dc.creator.orcidhttp://orcid.org/0000-0002-2241-8753en_US
dc.creator.orcidhttp://orcid.org/0000-0003-2986-4016en_US
dc.creator.orcidhttps://orcid.org/0000-0001-8874-5100
dc.creator.orcidhttps://orcid.org/0000-0003-0387-1808
dc.creator.orcidhttps://orcid.org/0000-0001-8874-5100
dc.creator.orcidhttps://orcid.org/0000-0001-7571-1155
dc.creator.orcidhttps://orcid.org/0000-0002-2241-8753
dc.creator.orcidhttps://orcid.org/0000-0003-2986-4016
dc.creator.orcidhttps://orcid.org/0000-0001-8874-5100
dc.creator.orcidhttps://orcid.org/0000-0003-0387-1808
dc.creator.orcidhttps://orcid.org/0000-0001-8874-5100
dc.creator.orcidhttps://orcid.org/0000-0001-7571-1155
dc.creator.orcidhttps://orcid.org/0000-0002-2241-8753
dc.creator.orcidhttps://orcid.org/0000-0003-2986-4016http://orcid.org/0000-0001-8874-5100
dc.creator.orcidhttp://orcid.org/0000-0003-0387-1808
dc.creator.orcidhttp://orcid.org/0000-0001-8874-5100
dc.creator.orcidhttp://orcid.org/0000-0001-7571-1155
dc.creator.orcidhttp://orcid.org/0000-0002-2241-8753
dc.creator.orcidhttp://orcid.org/0000-0003-2986-4016
dc.creator.orcidhttps://orcid.org/0000-0001-8874-5100
dc.creator.orcidhttps://orcid.org/0000-0003-0387-1808
dc.creator.orcidhttps://orcid.org/0000-0001-8874-5100
dc.creator.orcidhttps://orcid.org/0000-0001-7571-1155
dc.creator.orcidhttps://orcid.org/0000-0002-2241-8753
dc.creator.orcidhttps://orcid.org/0000-0003-2986-4016
dc.creator.orcidhttp://orcid.org/0000-0001-8874-5100
dc.creator.orcidhttp://orcid.org/0000-0003-0387-1808
dc.creator.orcidhttp://orcid.org/0000-0001-8874-5100
dc.creator.orcidhttp://orcid.org/0000-0001-7571-1155
dc.creator.orcidhttp://orcid.org/0000-0002-2241-8753
dc.creator.orcidhttp://orcid.org/0000-0003-2986-4016
dc.date.accessioned2022-03-10T19:22:18Z
dc.date.available2022-03-10T19:22:18Z
dc.date.issued2019-11-12
dc.description.abstractHigh-throughput imaging and genomic information can be combined to optimize marker development. Genome-wide association studies identified loci associated with plant growth traits. We identified candidate genes associated with plant growth and development. Despite advances in sequencing for genotyping, the lack of rapid, accurate, and reproducible phenotyping platforms has hampered efforts to use genetic analysis to predict traits of interest. Therefore, the use of high-throughput systems to phenotype traits related to crop growth, yield, quality, and resistance to biotic and abiotic stresses has become a major asset for breeding. Here, we assessed the efficacy of unmanned aircraft system (UAS)-based high-throughput phenotyping to obtain data for molecular marker development for spinach (Spinacia oleracea L.) improvement. We used a UAS equipped with a red-green-blue sensor to capture raw images of 284 spinach accessions throughout the crop cycle. Processed images generated orthomosaic and digital surface models for estimating canopy cover, canopy volume, and excess greenness index models. In addition, we manually recorded the number of days to bolting. Genome-wide association studies against a single-nucleotide polymorphism (SNP) panel obtained by ddRADseq identified 99 SNPs significantly associated with growth parameters. Some of these SNPs are in transcription factor and stress-response genes with possible roles in plant growth and development. The results underscore the utility of combining aerial imaging and genomic data analysis to optimize marker development. This study lays the foundation for the use of UAS-based high-throughput phenotyping for the molecular breeding of spinach.en_US
dc.description.abstractHigh-throughput imaging and genomic information can be combined to optimize marker development. Genome-wide association studies identified loci associated with plant growth traits. We identified candidate genes associated with plant growth and development. Despite advances in sequencing for genotyping, the lack of rapid, accurate, and reproducible phenotyping platforms has hampered efforts to use genetic analysis to predict traits of interest. Therefore, the use of high-throughput systems to phenotype traits related to crop growth, yield, quality, and resistance to biotic and abiotic stresses has become a major asset for breeding. Here, we assessed the efficacy of unmanned aircraft system (UAS)-based high-throughput phenotyping to obtain data for molecular marker development for spinach (Spinacia oleracea L.) improvement. We used a UAS equipped with a red-green-blue sensor to capture raw images of 284 spinach accessions throughout the crop cycle. Processed images generated orthomosaic and digital surface models for estimating canopy cover, canopy volume, and excess greenness index models. In addition, we manually recorded the number of days to bolting. Genome-wide association studies against a single-nucleotide polymorphism (SNP) panel obtained by ddRADseq identified 99 SNPs significantly associated with growth parameters. Some of these SNPs are in transcription factor and stress-response genes with possible roles in plant growth and development. The results underscore the utility of combining aerial imaging and genomic data analysis to optimize marker development. This study lays the foundation for the use of UAS-based high-throughput phenotyping for the molecular breeding of spinach.
dc.identifier.citationAwika, H.O., Bedre, R., Yeom, J., Marconi, T.G., Enciso, J., Mandadi, K.K., Jung, J. and Avila, C.A., 2019. Developing Growth‐Associated Molecular Markers via High‐Throughput Phenotyping in Spinach. The Plant Genome, 12(3), p.190027.en_US
dc.identifier.citationAwika, H.O., Bedre, R., Yeom, J., Marconi, T.G., Enciso, J., Mandadi, K.K., Jung, J. and Avila, C.A., 2019. Developing Growth‐Associated Molecular Markers via High‐Throughput Phenotyping in Spinach. The Plant Genome, 12(3), p.190027.
dc.identifier.doihttps://doi.org/10.3835/plantgenome2019.03.0027
dc.identifier.urihttps://hdl.handle.net/1969.6/90257
dc.language.isoen_USen_US
dc.language.isoen_US
dc.publisherWiley Open Accessen_US
dc.publisherWiley Open Access
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International*
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectmolecularen_US
dc.subjectspinachen_US
dc.subjectphenotypingen_US
dc.subjectmolecular
dc.subjectspinach
dc.subjectphenotyping
dc.titleDeveloping growth-associated molecular markers via high-throughput phenotyping in spinachen_US
dc.titleDeveloping growth-associated molecular markers via high-throughput phenotyping in spinach
dc.typeArticleen_US
dc.typeArticle

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