- Genome-wide association studies for yield component traits in a macadamia breeding population. - Katie O ’ Connor 1,2. - 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. - Results: Seven SNPs were significantly associated with NW (at a genome-wide false discovery rate of <. - industry is largely based on cultivars developed in Hawaii in the late nineteenth century [1]. - 2020 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0. - Full list of author information is available at the end of the article O ’ Connor et al. - The use of genomics in plant breeding is expand- ing [4–6], including employing genome-wide associ- ation studies to identify molecular markers associated with important traits, and genomic selec- tion for complex traits. - 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]. - As the realised kinship estimated from genetic markers is more accurate than recorded pedigree, fitting genomic relationships in the model can reduce false positives of putative large-effect QTLs [7, 8]. - hence, we aim to inves- tigate this option in the Australian macadamia breeding program.. - In that preliminary study, O’Connor et al. - Component traits. - O ’ Connor et al. - Tree type was included in the WK model, with a signifi- cance level of p = 0.063. - Genome-wide associations. - The GRM appeared to have effectively accounted for population structure in all traits except for TC, as no more associations than expected by chance were ob- served at low levels of significance in the QQ plots (Fig. - Fifty-two of the 57 (91%) significant SNPs across the traits were mapped to scaffolds of the v2 macadamia genome assembly (Table 3). - Phenotypic data in the breeding program. - Large phenotypic diversity was observed for many of the traits in this study. - Average phenotypic values observed here for NW, KW and KR were all slightly higher com- pared with the same traits in the preliminary study when the trees were young [32]. - Results of this study differed to that in the preliminary study [32] which analysed the same population when the trees were younger (around 8 years of age). - SD standard deviation, r p , Pearson’s correlation of current data with raw phenotypes for young trees from O’Connor et al. - The number of markers in the current study is comparable with other studies in fruit trees . - however, the fragmented nature of the macadamia genome scaffolds means the distribution of. - Gen- etic linkage maps have been used to anchor scaffolds to chromosomes (Langdon et al. - in preparation), and the location of scaffolds in the genome will be informative for determining locations of genes detected by SNPs in this study.. - For most traits in- vestigated here, the QQ plots showed that only the highly significant markers deviated from the null expect- ation (y = x line), and did not show inflation of the ob- served versus expected p-values at lower significance levels. - However, Kelner et al.. - MAF, minor allele frequency of the marker. - For TC, 16 of the 44 significant markers were non- redundant, suggesting that there may be 16 QTLs con- trolling this trait. - Multiple regression suggested that all of the the markers significantly associated with NW may have detected the same or linked QTLs, with the most significant SNP (s2204) being the only non-redundant marker. - The location of scaffolds in linkage groups (Nock et al. - A direct comparison cannot be made between SNPs found to be significantly associated with nut traits in the preliminary study by O’Connor et al. - [32] and the current study, as two different SNP panels were used in the analyses. - However, some of the significant markers could be mapped to genome assembly scaffolds. - A com- parison of the locations of mapped SNPs between the two studies showed that there were no markers occupy- ing the same scaffold (data not shown). - In the present study, markers were initially excluded with MAF <. - It was interesting, then, that all of the markers associated with NW had very low MAF. - Therefore, the significant markers with low MAF in the current study should be validated in independent studies, preferably with more individuals to observe whether the MAF is similar across populations of different sizes [44], as this will support the findings of this study.. - The results of this GWAS study can be used to demon- strate the implementation of MAS in the macadamia breeding program. - The estimates of BLUEs in the multiple regression analysis indicate the additive effect of the. - The influence of additive gen- etic variance of these alleles was quite different to that which was observed in the raw phenotype, as the pheno- type will have been influenced by non-additive genetic effects and environment. - Again, the SNP should be validated in an independent population, and the effect of the SNP alleles should be estimated in that population.. - Furthermore, the poten- tial issues posed by allelic dropouts, such as lower than expected levels of heterozygosity observed by O’Connor et al. - [34], could be alleviated with the use of a complete reference genome in sequencing of SNPs in the future.. - The v2 scaffolds and chromosomes are being (Nock et al. - Although there was a lack of significant associations in some traits in the current study, these should still be investigated in future work. - This study provides a foundation for genomics- assisted breeding in macadamia and nut crops more broadly, and advances our understanding of the genetic control of yield component traits.. - Methods for association analysis are similar to those in a preliminary study by O’Connor et al. - Trees were planted between 2001 and 2003 across four sites in Queensland, with East Gympie (EG) and Amamoor (AM) in the Gympie region, and Alloway (AL) and Hinkler Park (HP) in the Bundaberg region.. - Clones of five of the parents were measured at all four sites. - Details of genotyping methods for this population were reported in O’Connor et al. - 0 poly- morphic information content, and a test of Mendelian consistency between progeny-parent-parent trios in half of the studied families. - Yield was measured on each tree by manually harvesting nuts from the ground and collecting any nuts still in the tree at the end of the season. - The dry nut-in-shell (DNIS) weight was estimated for each harvest using calculations of moisture content in the 1 kg sample. - Pearson’s correlations were performed between NW, KW and KR raw phenotypes in the current study and those used in O’Connor et al. - g is a vector of averaged breeding values of the individuals across sites, assumed random ~ N (0,G σ 2 g. - Z gs gs describes the genotype by envir- onment (G x E) interaction, where Z gs is a design matrix allocating a specific effect of an individual at a site not accounted for by the mean of the individual across sites,. - and gs is a vector of the breeding values at a specific site, assumed random ~ N (0,G ⨂ I 4 ⨂ σ 2 gs ) where I is a 4 × 4 identity matrix for the four sites, and e is a vector of random errors ~ N (0, σ 2 e ) where σ 2 e is the error vari- ance. - For traits where G x E was a significant factor, the G x E variance component was included in the denominator when calculating heritability.. - Association analysis was performed for each trait using the most parsimonious model, as per O’Connor et al.. - y ¼ Xb þ Wm þ Z g g þ Z gs gs þ e ð2Þ where W is a design matrix allocating records to the marker effect (modelled as 0, 1, or 2 for homozygous, heterozygous and alternate homozygous genotypes, re- spectively), and m is the effect of the marker currently being fitted in the model, as a fixed effect. - QQ (quantile-quantile) plots were constructed for each trait to evaluate whether population structure had been accurately accounted for in the model, by comparing the observed and expected –log 10 significance values of each SNP and ensuring that inflation had not occurred at the lower levels of significance [43]. - 0.05 were deemed significantly associated with the trait. - FDR was again calcu- lated for the markers included in the multiple regression.. - as one of the significant markers, and as such were con- sidered redundant. - An estimation of the additive allele effect of each significant SNP was estimated from fixed effects (best linear unbiased estimators. - were estimated as per O ’ Connor et al. - GWAS: Genome-wide association study. - CN and AB provided genome assembly scaffold data in the chapter. - Data are however available from the authors upon reasonable request and with permission of The University of Queensland for researchers who meet the criteria for access to confidential data. - Hardner CM, Peace C, Lowe AJ, Neal J, Pisanu P, Powell M, et al. - Myles S, Peiffer J, Brown PJ, Ersoz ES, Zhang Z, Costich DE, et al. - Nishio S, Hayashi T, Yamamoto T, Terakami S, Iwata H, Imai A, et al. - Bayesian genome-wide association study of nut traits in Japanese chestnut. - Potential assessment of genome-wide association study and genomic selection in Japanese pear Pyrus pyrifolia. - 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