Expanding the BLUP alphabet for genomic prediction adaptable to the genetic architectures of complex traits.

Heredity
Jiabo WangZhiwu Zhang

Abstract

Improvement of statistical methods is crucial for realizing the potential of increasingly dense genetic markers. Bayesian methods treat all markers as random effects, exhibit an advantage on dense markers, and offer the flexibility of using different priors. In contrast, genomic best linear unbiased prediction (gBLUP) is superior in computing speed, but only superior in prediction accuracy for extremely complex traits. Currently, the existing variety in the BLUP method is insufficient for adapting to new sequencing technologies and traits with different genetic architectures. In this study, we found two ways to change the kinship derivation in the BLUP method that improve prediction accuracy while maintaining the computational advantage. First, using the settlement under progressively exclusive relationship (SUPER) algorithm, we substituted all available markers with estimated quantitative trait nucleotides (QTNs) to derive kinship. Second, we compressed individuals into groups based on kinship, and then used the groups as random effects instead of individuals. The two methods were named as SUPER BLUP (sBLUP) and compressed BLUP (cBLUP). Analyses on both simulated and real data demonstrated that these two methods offer flexibil...Continue Reading

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Citations

Mar 3, 2019·Journal of Experimental Botany·Diane R WangBrent E Ewers
Jan 29, 2020·Evolutionary Applications·Tanja PyhäjärviOuti Savolainen
Oct 14, 2018·Genetics, Selection, Evolution : GSE·Biaty RaymondRoel F Veerkamp
Oct 1, 2020·Genetics, Selection, Evolution : GSE·Sara de Las Heras-SaldanaJulius H J van der Werf
Oct 6, 2020·The Plant Genome·Inés BerroLucía Gutiérrez
Aug 21, 2020·G3 : Genes - Genomes - Genetics·Christopher O HernandezMichael R Mazourek
Jan 15, 2021·The Plant Genome·Laura Tibbs CortesJianming Yu
Jan 21, 2021·Frontiers in Plant Science·Karansher S SandhuArron H Carter
Mar 16, 2021·Frontiers in Genetics·Marlee R LabrooJessica E Rutkoski
Jun 12, 2021·TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik·Elaheh VojganiHenner Simianer

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Software Mentioned

R
Bayes B
SUPER
cBLUP
pBLUP
gBLUP
MAS
Bayesian LASSO
sBLUP
MTDFREML

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