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Additive genetic variance and covariance between relatives in synthetic wheat crosses with variable parental ploidy levels

Creator: Puhl, L.
Creator: Crossa, J.
Creator: Munilla, S.
Creator: Perez-Rodriguez, P.
Creator: Cantet, R.
Year: 2021
URI: https://hdl.handle.net/10883/21348
Language: English
Publisher: Oxford University Press
Copyright: CIMMYT manages Intellectual Assets as International Public Goods. The user is free to download, print, store and share this work. In case you want to translate or create any other derivative work and share or distribute such translation/derivative work, please contact CIMMYT-Knowledge-Center@cgiar.org indicating the work you want to use and the kind of use you intend; CIMMYT will contact you with the suitable license for that purpose
Type: Article
Place of Publication: United Kingdom
Issue: 2
Volume: 217
DOI: 10.1093/genetics/iyaa048
Keywords: Synthetic Wheat
Keywords: Additive Genetic Variance
Description: Cultivated bread wheat (Triticum aestivum L.) is an allohexaploid species resulting from the natural hybridization and chromosome doubling of allotetraploid durum wheat (T. turgidum) and a diploid goatgrass Aegilops tauschii Coss (Ae. tauschii). Synthetic hexaploid wheat (SHW) was developed through the interspecific hybridization of Ae. tauschii and T. turgidum, and then crossed to T. aestivum to produce synthetic hexaploid wheat derivatives (SHWDs). Owing to this founding variability, one may infer that the genetic variances of native wild populations vs improved wheat may vary due to their differential origin and evolutionary history. In this study, we partitioned the additive variance of SHW and SHWD with respect to their breed origin by fitting a hierarchical Bayesian model with heterogeneous covariance structure for breeding values to estimate variance components for each breed category, and segregation variance. Two data sets were used to test the proposed hierarchical Bayesian model, one from a multi-year multi-location field trial of SHWD and the other comprising the two species of SHW. For the SHWD, the Bayesian estimates of additive variances of grain yield from each breed category were similar for T. turgidum and Ae. tauschii, but smaller for T. aestivum. Segregation variances between Ae. tauschii-T. aestivum and T. turgidum-T. aestivum populations explained a sizable proportion of the phenotypic variance. Bayesian additive variance components and the Best Linear Unbiased Predictors (BLUPs) estimated by two well-known software programs were similar for multi-breed origin and for the sum of the breeding values by origin for both data sets. Our results support the suitability of models with heterogeneous additive genetic variances to predict breeding values in wheat crosses with variable ploidy levels.
Agrovoc: WHEAT
Agrovoc: POLYPLOIDY
Agrovoc: GENETIC VARIANCE
Agrovoc: BREEDING VALUE
Related Datasets: https://hdl.handle.net/11529/10548407
ISSN: 1943-2631
Journal: Genetics
Article number: iyaa048


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    Genetic Resources including germplasm collections, wild relatives, genotyping, genomics, and IP

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