GTBLUP and GTIBLUP

Bruno C Perez; Marco C A M Bink; Karen L Svenson; Gary A Churchill; Mario P L Calus

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GTBLUP and GTIBLUP

BP Bruno C Perez

MB Marco C A M Bink

KS Karen L Svenson

GC Gary A Churchill

MC Mario P L Calus

This method is extracted from research article: G3 (Bethesda), Sep 2022

Adding gene transcripts into genomic prediction improves accuracy and reveals sampling time dependence

DOI: 10.1093/g3journal/jkac258

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The GTBLUP model fitted the $g$ and $t$ as independent random effects, each with their own variance component (Guo et al. 2016; Li et al. 2019). The model is $y * = 1 μ + g + t + e,$ where all the parameters are as defined above.

The GTIBLUP model fitted $g$ , $t$ , and the interaction between $g$ and $t$ with an additional variance component (Morgante et al. 2020). This model is $y * = 1 μ + g + t + gt + e$ , where $y *$ , $1 μ$ , $g$ , $t,$ and $e$ are as defined above, and $gt$ is the vector of interaction (between genomic and transcriptomic) effects, where $gt \sim N (0, {G # T σ}_{g t}^{2})$ and # is the Hadamard product.

This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

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