Genomic Prediction in Tetraploid Ryegrass Using Allele Frequencies Based on Genotyping by Sequencing

Frontiers in Plant Science
Xiangyu GuoLucas L Janss

Abstract

Perennial ryegrass is an outbreeding forage species and is one of the most widely used forage grasses in temperate regions. The aim of this study was to investigate the possibility of implementing genomic prediction in tetraploid perennial ryegrass, to study the effects of different sequencing depth when using genotyping-by-sequencing (GBS), and to determine optimal number of single-nucleotide polymorphism (SNP) markers and sequencing depth for GBS data when applied in tetraploids. A total of 1,515 F2 tetraploid ryegrass families were included in the study and phenotypes and genotypes were scored on family-pools. The traits considered were dry matter yield (DM), rust resistance (RUST), and heading date (HD). The genomic information was obtained in the form of allele frequencies of pooled family samples using GBS. Different SNP filtering strategies were designed. The strategies included filtering out SNPs having low average depth (FILTLOW), having high average depth (FILTHIGH), and having both low average and high average depth (FILTBOTH). In addition, SNPs were kept randomly with different data sizes (RAN). The accuracy of genomic prediction was evaluated by using a "leave single F2 family out" cross validation scheme, and the ...Continue Reading

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Citations

Sep 3, 2020·TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik·Dorcus C GemenetHugo Campos
Feb 10, 2021·Genes·Matteo MartinaArnaud G Bovy
Mar 24, 2021·Annals of Botany·Claudio CropanoDaniel Thorogood
Jul 1, 2021·Molecular Ecology Resources·Jefferson F ParilAlexandre Fournier-Level
Aug 27, 2021·Frontiers in Plant Science·Stefan WilsonFred van Eeuwijk

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Methods Mentioned

BETA
genotyping
chip
array technology

Software Mentioned

RUST
DMU
GBS
FILTLOW

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