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    Genetic correlation, genome-wide association and genomic prediction of portable NIRS predicted carotenoids in cassava roots

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    Journal Article (1.733Mb)
    Date
    2019
    Author
    Ikeogu, U.N.
    Akdemir, D.
    Wolfe, M.D.
    Okeke, U.G.
    Amaefula, C.
    Jannink, J.L.
    Egesi, C.N.
    Type
    Journal Article
    Review Status
    Peer Review
    Target Audience
    Scientists
    Metadata
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    Abstract/Description
    Random 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.
    https://dx.doi.org/10.3389/fpls.2019.01570
    Multi standard citation
    Permanent link to this item
    https://hdl.handle.net/20.500.12478/6902
    IITA Authors ORCID
    Jean-Luc Janninkhttps://orcid.org/0000-0003-4849-628X
    Chiedozie Egesihttps://orcid.org/0000-0002-9063-2727
    Digital Object Identifier (DOI)
    https://dx.doi.org/10.3389/fpls.2019.01570
    Research Themes
    Biotech and Plant Breeding
    IITA Subjects
    Agronomy; Cassava; Food Security; Genetic Improvement; Plant Breeding; Plant Genetic Resources; Plant Health; Plant Production
    Agrovoc Terms
    Cassava; Carotenoids; Genomes; Near Infrared Spetroscopy
    Regions
    Africa; West Africa
    Countries
    Nigeria
    Hubs
    Headquarters and Western Africa Hub
    Journals
    Frontiers in Plant Science
    Collections
    • Journal and Journal Articles4835
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