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dc.contributor.authorIkeogu, U.N.
dc.contributor.authorAkdemir, D.
dc.contributor.authorWolfe, M.D.
dc.contributor.authorOkeke, U.G.
dc.contributor.authorAmaefula, C.
dc.contributor.authorJannink, J.L.
dc.contributor.authorEgesi, C.N.
dc.date.accessioned2020-07-07T12:48:44Z
dc.date.available2020-07-07T12:48:44Z
dc.date.issued2019
dc.identifier.citationIkeogu, U.N., Akdemir, D., Wolfe, M.D., Okeke, U.G., Amaefula, C., Jannink, J.L. & Egesi, C.N. (2019). Genetic correlation, genome-wide association and genomic prediction of portable NIRS predicted carotenoids in cassava roots. Frontiers in Plant Science, 10, 1-11.
dc.identifier.issn1664-302X
dc.identifier.urihttps://hdl.handle.net/20.500.12478/6902
dc.description.abstractRandom forests (RF) was used to correlate spectral responses to known wet chemistry carotenoid concentrations including total carotenoid content (TCC), all-trans β-carotene (ATBC), violaxanthin (VIO), lutein (LUT), 15-cis beta-carotene (15CBC), 13-cis beta-carotene (13CBC), alpha-carotene (AC), 9-cis beta-carotene (9CBC), and phytoene (PHY) from laboratory analysis of 173 cassava root samples in Columbia. The cross-validated correlations between the actual and estimated carotenoid values using RF ranged from 0.62 in PHY to 0.97 in ATBC. The developed models were used to evaluate the carotenoids of 594 cassava clones with spectral information collected across three locations in a national breeding program (NRCRI, Umudike), Nigeria. Both populations contained cassava clones characterized as white and yellow. The NRCRI evaluated phenotypes were used to assess the genetic correlations, conduct genome-wide association studies (GWAS), and genomic predictions. Estimates of genetic correlation showed various levels of the relationship among the carotenoids. The associations between TCC and the individual carotenoids were all significant (P < 0.001) with high positive values (r > 0.75, except in LUT and PHY where r < 0.3). The GWAS revealed significant genomic regions on chromosomes 1, 2, 4, 13, 14, and 15 associated with variation in at least one of the carotenoids. One of the identified candidate genes, phytoene synthase (PSY) has been widely reported for variation in TCC in cassava. On average, genomic prediction accuracies from the single-trait genomic best linear unbiased prediction (GBLUP) and RF as well as from a multiple-trait GBLUP model ranged from ∼0.2 in LUT and PHY to 0.52 in TCC. The multiple-trait GBLUP model gave slightly higher accuracies than the single trait GBLUP and RF models. This study is one of the initial attempts in understanding the genetic basis of individual carotenoids and demonstrates the usefulness of NIRS in cassava improvement.
dc.description.sponsorshipBill & Melinda Gates Foundation
dc.format.extent1-11
dc.language.isoen
dc.subjectCassava
dc.subjectCarotenoids
dc.subjectGenomes
dc.subjectNear Infrared Spetroscopy
dc.titleGenetic correlation, genome-wide association and genomic prediction of portable NIRS predicted carotenoids in cassava roots
dc.typeJournal Article
cg.contributor.crpRoots, Tubers and Bananas
cg.contributor.affiliationCornell University
cg.contributor.affiliationNational Root Crops Research Institute, Nigeria
cg.contributor.affiliationUnited States Department of Agriculture
cg.contributor.affiliationInternational Institute of Tropical Agriculture
cg.coverage.regionAfrica
cg.coverage.regionWest Africa
cg.coverage.countryNigeria
cg.coverage.hubHeadquarters and Western Africa Hub
cg.researchthemeBiotech and Plant Breeding
cg.identifier.bibtexciteidIKEOGU:2019
cg.isijournalISI Journal
cg.authorship.typesCGIAR and developing country institute
cg.iitasubjectAgronomy
cg.iitasubjectCassava
cg.iitasubjectFood Security
cg.iitasubjectGenetic Improvement
cg.iitasubjectPlant Breeding
cg.iitasubjectPlant Genetic Resources
cg.iitasubjectPlant Health
cg.iitasubjectPlant Production
cg.journalFrontiers in Plant Science
cg.notesOpen Access Journal; Published online: 04 Dec 2019
cg.accessibilitystatusOpen Access
cg.reviewstatusPeer Review
cg.usagerightslicenseCreative Commons Attribution 4.0 (CC BY 0.0)
cg.targetaudienceScientists
cg.identifier.doihttps://dx.doi.org/10.3389/fpls.2019.01570
cg.iitaauthor.identifierJean-Luc Jannink: 0000-0003-4849-628X
cg.iitaauthor.identifierChiedozie Egesi: 0000-0002-9063-2727


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