Implementing within‐cross genomic prediction to reduce oat breeding costs

Greg Mellers, Ian Mackay, Sandy Cowan, Irene Griffiths, Maria Martinez-Martin, Jesse A. Poland, Wubishet Abebe Bekele, Nicholas A. Tinker, Alison Bentley, Catherine Howarth

Allbwn ymchwil: Cyfraniad at gyfnodolynErthygladolygiad gan gymheiriaid

9 Dyfyniadau (Scopus)
144 Wedi eu Llwytho i Lawr (Pure)

Crynodeb

A barrier to the adoption of genomic prediction in small breeding programs is the initial cost of genotyping material. Although decreasing, marker costs are usually higher than field trial costs. In this study we demonstrate the utility of stratifying a narrow‐base biparental oat population genotyped with a modest number of markers to employ genomic prediction at early and later generations. We also show that early generation genotyping data can reduce the number of lines for later phenotyping based on selections of siblings to progress. Using sets of small families selected at an early generation could enable the use of genomic prediction for adaptation to multiple target environments at an early stage in the breeding program. In addition, we demonstrate that mixed marker data can be effectively integrated to combine cheap dominant marker data (including legacy data) with more expensive but higher density codominant marker data in order to make within generation and between lineage predictions based on genotypic information. Taken together, our results indicate that small programs can test and initiate genomic predictions using sets of stratified, narrow‐base populations and incorporating low density legacy genotyping data. This can then be scaled to include higher density markers and a broadened population base.
Iaith wreiddiolSaesneg
Rhif yr erthygle20004
Nifer y tudalennau12
CyfnodolynThe Plant Genome
Cyfrol13
Rhif cyhoeddi1
Dyddiad ar-lein cynnar17 Maw 2020
Dynodwyr Gwrthrych Digidol (DOIs)
StatwsCyhoeddwyd - 12 Mai 2020

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