Selecting for Nut Characteristics in Macadamia Using a Genome-wide Association Study

in HortScience

Current macadamia breeding programs involve a lengthy and laborious two-stage selection process: evaluation of a large number of unreplicated seedling progeny, followed by replicated trials of clonally propagated elite seedlings. Yield component traits, such as nut-in-shell weight (NW), kernel weight (KW), and kernel recovery (KR) are commercially important, are more easily measured than yield, and have a higher heritability. A genome-wide association study (GWAS) combined with marker-assisted selection offers an opportunity to reduce the time of candidate evaluation. In this study, a total of 281 progeny from 32 families, and 18 of their 29 parents have been genotyped for 7126 single nucleotide polymorphism (SNP) markers. A GWAS was performed using ASReml with 4352 SNPs. We found five SNPs significantly associated with NW, nine with KW, and one with KR. Further, three of the top 10 markers for NW and KW were shared between the two traits. Future macadamia breeding could involve prescreening of individuals for desired traits using these significantly associated markers, with only predicted elite individuals continuing to the second stage of selection, thus potentially reducing the selection process by 7 years.

Contributor Notes

This paper was presented as a part of the 2017 International Macadamia Research Symposium, 13–14 Sept. 2017, in Big Island, HI.

This research was funded by Hort Innovation Australia, using the macadamia research and development levy and contributions from the Australian Government. Hort Innovation is the grower-owned, not-for-profit research and development corporation for Australian horticulture. KO acknowledges the Australian Postgraduate Award and Charles Morphett Peglar scholarship for financial support. We thank anonymous reviewers for their suggestions and comments.

Corresponding author. E-mail: b.topp@uq.edu.au.

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    Histogram of skewed phenotypes for (A) nut weight (NW) and (B) kernel weight (KW).

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    Quantile-quantile plots of observed and expected –log10(P) values for various nut characteristics: (A) nut weight, (B) kernel weight, and (C) kernel recovery. Each point represents one SNP marker.

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