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


ABSTRACT: BACKGROUND:Breeding 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. RESULTS:Seven SNPs were significantly associated with NW (at a genome-wide false discovery rate of

SUBMITTER: O'Connor K 

PROVIDER: S-EPMC7057592 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature

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

O'Connor Katie K   Hayes Ben B   Hardner Craig C   Nock Catherine C   Baten Abdul A   Alam Mobashwer M   Henry Robert R   Topp Bruce B  

BMC genomics 20200304 1


<h4>Background</h4>Breeding 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  ...[more]

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