Validating genomewide predictions of genetic variance in a contemporary breeding program

Jeffrey L. Neyhart, Kevin P. Smith

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

Predicting the genetic variance among progeny from a cross-prior to making said cross-would be a valuable metric for plant breeders to discriminate among possible parent combinations. The use of genomewide markers and simulated populations is one proposed method for making such predictions. Our objective was to assess the predictive ability of this method for three relevant quantitative traits within a breeding program regularly using genomewide selection. Using a training population of two-row barley (Hordeum vulgare L.) lines, we predicted the mean (µ), genetic variance (VG), and superior progeny mean (µSP, mean of the best 10% of lines) of 330,078 possible parent combinations for Fusarium head blight (FHB) severity, heading date, and plant height. Twenty-seven of these combinations were chosen to develop biparental populations, which were subsequently phenotyped for the same traits. We found that the predictive abilities (rMP) for µ and µSP were moderate to high (rMP = 0.46-0.69), whereas those for VG were lower (rMP = 0.01-0.48). Unsurprisingly, predictive ability was likely a function of trait heritability, as rMP estimates for heading date (the most heritable trait) were highest, and rMP estimates for FHB severity (the least heritable trait) were lowest. We observed strong negative bias when predicting VG (on average -83 to -96%), but the relative consistency of this bias across validation families indicates that it may have little impact when selecting crosses. We concluded that accurate predictions of VG and µSP are feasible, but as with any implementation of genomewide selection, reliable phenotypic data are critical.

Original languageEnglish (US)
Pages (from-to)1062-1072
Number of pages11
JournalCrop Science
Volume59
Issue number3
DOIs
StatePublished - May 1 2019

Bibliographical note

Funding Information:
Paul and to Madeline Smith and Joseph Wodarek for managing the FHB trial in Crookston, MN. We are grateful to Aaron Lorenz and Tyler Tiede for helpful comments and conversation, as well as Austin Case, Jo Heuschele, John Hill Price, Ian McNish, Becky Zhong, and Alexander Susko for assistance and encouragement. Resources from the Minnesota Supercomputing Institute were used to complete this project. This research was supported by the US Wheat and Barley Scab Initiative, the Minnesota Department of Agriculture, Rahr Malting Company, the Brewers Association, the American Malting Barley Association, and USDA National Institute of Food and Agriculture Grant no. 2018-67011-28075.

Funding Information:
We thank Ed Schiefelbein, Guillermo Velasquez, and Karen Beaubien for technical support during population development, phenotypic data collection, and genotyping. Thanks go to Ruth Dill-Macky for suppling Fusarium graminearum inoculum for St. Paul and to Madeline Smith and Joseph Wodarek for managing the FHB trial in Crookston, MN. We are grateful to Aaron Lorenz and Tyler Tiede for helpful comments and conversation, as well as Austin Case, Jo Heuschele, John Hill Price, Ian McNish, Becky Zhong, and Alexander Susko for assistance and encouragement. Resources from the Minnesota Supercomputing Institute were used to complete this project. This research was supported by the US Wheat and Barley Scab Initiative, the Minnesota Department of Agriculture, Rahr Malting Company, the Brewers Association, the American Malting Barley Association, and USDA National Institute of Food and Agriculture Grant no. 2018-67011-28075.

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