Genomic prediction of tocochromanols in exotic-derived maize
cg.authorship.types | Not CGIAR developing country institute | |
cg.authorship.types | Not CGIAR international institute | |
cg.contributor.affiliation | Iowa State University | |
cg.contributor.affiliation | Hubei Hongshan Laboratory | |
cg.contributor.affiliation | Huazhong Agricultural University | |
cg.contributor.affiliation | United States Department of Agriculture | |
cg.contributor.affiliation | Cornell University | |
cg.contributor.affiliation | Michigan State University | |
cg.contributor.donor | National Science Foundation | |
cg.contributor.donor | United States Department of Agriculture | |
cg.contributor.donor | CGIAR Trust Fund | |
cg.contributor.donor | Iowa State University Plant Sciences Institute | |
cg.contributor.donor | United States Agency for International Development | |
cg.howPublished | Formally Published | |
cg.identifier.doi | https://doi.org/10.1002/tpg2.20286 | |
cg.identifier.project | IFPRI - HarvestPlus | |
cg.identifier.publicationRank | Not ranked | |
cg.isijournal | ISI Journal | |
cg.issn | 1940-3372 | |
cg.issue | 4 | |
cg.journal | Plant Genome | |
cg.reviewStatus | Peer Review | |
cg.subject.impactArea | Nutrition, health and food security | |
cg.volume | 16 | |
dc.contributor.author | Tibbs-Cortes, Laura E. | |
dc.contributor.author | Guo, Tingting | |
dc.contributor.author | Li, Xianran | |
dc.contributor.author | Tanaka, Ryokei | |
dc.contributor.author | Vanous, Adam E. | |
dc.contributor.author | Peters, David | |
dc.contributor.author | Gardner, Candice | |
dc.contributor.author | Magallanes-Lundback, Maria | |
dc.contributor.author | Deason, Nicholas T. | |
dc.contributor.author | DellaPenna, Dean | |
dc.contributor.author | Gore, Michael A. | |
dc.contributor.author | Yu, Jianming | |
dc.date.accessioned | 2025-07-17T17:01:50Z | |
dc.date.available | 2025-07-17T17:01:50Z | |
dc.identifier.uri | https://hdl.handle.net/10568/175678 | |
dc.title | Genomic prediction of tocochromanols in exotic-derived maize | en |
dcterms.abstract | Tocochromanols (vitamin E) are an essential part of the human diet. Plant products, including maize (Zea mays L.) grain, are the major dietary source of tocochromanols; therefore, breeding maize with higher vitamin content (biofortification) could improve human nutrition. Incorporating exotic germplasm in maize breeding for trait improvement including biofortification is a promising approach and an important research topic. However, information about genomic prediction of exotic-derived lines using available training data from adapted germplasm is limited. In this study, genomic prediction was systematically investigated for nine tocochromanol traits within both an adapted (Ames Diversity Panel [AP]) and an exotic-derived (Backcrossed Germplasm Enhancement of Maize [BGEM]) maize population. Although prediction accuracies up to 0.79 were achieved using genomic best linear unbiased prediction (gBLUP) when predicting within each population, genomic prediction of BGEM based on an AP training set resulted in low prediction accuracies. Optimal training population (OTP) design methods fast and unique representative subset selection (FURS), maximization of connectedness and diversity (MaxCD), and partitioning around medoids (PAM) were adapted for inbreds and, along with the methods mean coefficient of determination (CDmean) and mean prediction error variance (PEVmean), often improved prediction accuracies compared with random training sets of the same size. When applied to the combined population, OTP designs enabled successful prediction of the rest of the exotic-derived population. Our findings highlight the importance of leveraging genotype data in training set design to efficiently incorporate new exotic germplasm into a plant breeding program. | en |
dcterms.accessRights | Open Access | |
dcterms.audience | Scientists | |
dcterms.available | 2022-12-27 | |
dcterms.bibliographicCitation | Tibbs-Cortes, Laura E.; Guo, Tingting; Li, Xianran; Tanaka, Ryokei; Vanous, Adam E.; Peters, David; et al. 2023. Genomic prediction of tocochromanols in exotic-derived maize. Plant Genome 16(4): e20286. https://doi.org/10.1002/tpg2.20286 | |
dcterms.issued | 2023-12 | |
dcterms.language | en | |
dcterms.license | CC-BY-NC-ND-4.0 | |
dcterms.publisher | Wiley | |
dcterms.subject | vitamin E | |
dcterms.subject | maize | |
dcterms.subject | nutrition | |
dcterms.subject | germplasm | |
dcterms.subject | biofortification | |
dcterms.subject | fat soluble vitamins | |
dcterms.type | Journal Article |
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