Genome-wide association studies for yield component traits in a macadamia breeding population

Katie O’Connor,Catherine Nock,Abdul Baten,Robert Henry,Mobashwer Alam,Craig Hardner,Bruce Topp,Ben Hayes

doi:10.1186/s12864-020-6575-3

Katie O’Connor, Catherine Nock + Show 6 more

Open Access

https://doi.org/10.1186/s12864-020-6575-3

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Abstract

BackgroundBreeding for new macadamia cultivars with high nut yield is expensive in terms of time, labour and cost. Most trees set nuts after four to five years, and candidate varieties for breeding are evaluated for at least eight years for various traits. Genome-wide association studies (GWAS) are promising methods to reduce evaluation and selection cycles by identifying genetic markers linked with key traits, potentially enabling early selection through marker-assisted selection. This study used 295 progeny from 32 full-sib families and 29 parents (18 phenotyped) which were planted across four sites, with each tree genotyped for 4113 SNPs. ASReml-R was used to perform association analyses with linear mixed models including a genomic relationship matrix to account for population structure. Traits investigated were: nut weight (NW), kernel weight (KW), kernel recovery (KR), percentage of whole kernels (WK), tree trunk circumference (TC), percentage of racemes that survived from flowering through to nut set, and number of nuts per raceme.ResultsSeven SNPs were significantly associated with NW (at a genome-wide false discovery rate of < 0.05), and four with WK. Multiple regression, as well as mapping of markers to genome assembly scaffolds suggested that some SNPs were detecting the same QTL. There were 44 significant SNPs identified for TC although multiple regression suggested detection of 16 separate QTLs.ConclusionsThese findings have important implications for macadamia breeding, and highlight the difficulties of heterozygous populations with rapid LD decay. By coupling validated marker-trait associations detected through GWAS with MAS, genetic gain could be increased by reducing the selection time for economically important nut characteristics. Genomic selection may be a more appropriate method to predict complex traits like tree size and yield.

Highlights

Breeding for new macadamia cultivars with high nut yield is expensive in terms of time, labour and cost
Log-transformed (log10(x)) observations for nut weight (NW), kernel weight (KW) and nuts per raceme (NPR), as well as square root transformed observations for Racemes surviving from flowering to nut set (RSN) appeared more normally distributed than raw observations (Fig. 1)
Significant associations were detected for NW, whole kernels (WK) and trunk circumference (TC), but no markers exceeded the significance threshold for KW, kernel recovery (KR), RSN or NPR

Summary

Introduction

Breeding for new macadamia cultivars with high nut yield is expensive in terms of time, labour and cost. Genome-wide association studies (GWAS) are promising methods to reduce evaluation and selection cycles by identifying genetic markers linked with key traits, potentially enabling early selection through marker-assisted selection. This study used 295 progeny from 32 full-sib families and 29 parents (18 phenotyped) which were planted across four sites, with each tree genotyped for 4113 SNPs. ASReml-R was used to perform association analyses with linear mixed models including a genomic relationship matrix to account for population structure. A common approach is using genome-wide association studies (GWAS): each marker (typically single nucleotide polymorphism, SNP) is tested individually to detect evidence of marker-trait associations [4]. This method relies on linkage disequilibrium (LD) between markers and causal polymorphisms [4]. In MAS, candidates are screened for target markers, their phenotypes are predicted based on allelic states, and selections can be made based on these predictions [9, 10]

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