Genomic prediction of crown rust resistance in Lolium perenne

BMC Genetics
Sai Krishna ArojjuStephen L Byrne

Abstract

Genomic selection (GS) can accelerate genetic gains in breeding programmes by reducing the time it takes to complete a cycle of selection. Puccinia coronata f. sp lolli (crown rust) is one of the most widespread diseases of perennial ryegrass and can lead to reductions in yield, persistency and nutritional value. Here, we used a large perennial ryegrass population to assess the accuracy of using genome wide markers to predict crown rust resistance and to investigate the factors affecting predictive ability. Using these data, predictive ability for crown rust resistance in the complete population reached a maximum of 0.52. Much of the predictive ability resulted from the ability of markers to capture genetic relationships among families within the training set, and reducing the marker density had little impact on predictive ability. Using permutation based variable importance measure and genome wide association studies (GWAS) to identify and rank markers enabled the identification of a small subset of SNPs that could achieve predictive abilities close to those achieved using the complete marker set. Using a GWAS to identify and rank markers enabled a small panel of markers to be identified that could achieve higher predictive ab...Continue Reading

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Citations

Oct 6, 2020·The Plant Genome·Ian G McNishKevin P Smith
Jan 19, 2019·International Journal of Molecular Sciences·Liqiang HeFrank M You
Aug 21, 2020·G3 : Genes - Genomes - Genetics·Hadi EsfandyariJust Jensen
Dec 4, 2019·G3 : Genes - Genomes - Genetics·Sai Krishna ArojjuMarty J Faville
Jun 10, 2021·TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik·Junrey AmasJacqueline Batley

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Methods Mentioned

BETA
genotyping

Software Mentioned

R
R package BGLR
Bayes
GS
R package lme4
lme4
rrBLUP )
R package randomForest
Bayes B
R package

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