Genomic prediction and genome-wide association study using combined genotypic data from different genotyping systems: application to apple fruit quality traits

Abstract

With advances in next-generation sequencing technologies, various marker genotyping systems have been developed for genomics-based approaches such as genomic selection (GS) and genome-wide association study (GWAS). As new genotyping platforms are developed, data from different genotyping platforms must be combined. However, the potential use of combined data for GS and GWAS has not yet been clarified. In this study, the accuracy of genomic prediction (GP) and the detection power of GWAS increased for most fruit quality traits of apples when using combined data from different genotyping systems, Illumina Infinium single-nucleotide polymorphism array and genotyping by random amplicon sequencing-direct (GRAS-Di) systems. In addition, the GP model, which considered the inbreeding effect, further improved the accuracy of the seven fruit traits. Runs of homozygosity (ROH) islands overlapped with the significantly associated regions detected by the GWAS for several fruit traits. Breeders may have exploited these regions to select promising apples by breeders, increasing homozygosity. These results suggest that combining genotypic data from different genotyping platforms benefits the GS and GWAS of fruit quality traits in apples. Information on inbreeding could be beneficial for improving the accuracy of GS for fruit traits of apples; however, further analysis is required to elucidate the relationship between the fruit traits and inbreeding depression (e.g. decreased vigor).

Acknowledgements

We are grateful to all the members of the NARO Institute of Fruit Tree and Tea Science for maintaining the apple trees. This research was supported by a grant from the Ministry of Agriculture, Forestry and Fisheries of Japan (Genomics-based Technology for Agricultural Improvement, NGB-2007 and 2010), Cabinet Office, Government of Japan, Cross-ministerial Strategic Innovation Promotion Program (SIP), ‘Technologies for Smart Bio-industry and Agriculture’ (funding agency: Bio-oriented Technology Research Advancement Institution, NARO), MAFF commissioned project study on ‘Smart breeding technologies to Accelerate the development of new varieties toward achieving “Strategy for Sustainable Food Systems, MIDORI”’ Grant Number JPJ012037 and a Grant-in-Aid for JSPS Research Fellow (JP22K20577 and JP23K13928).

Author contributions

M.F.M. and M.K. conceived and designed the study. M.K. and S.M. extracted DNA and performed SNP genotyping. T.S. helped with SNP genotyping. S.M. performed the phenotyping. M.I. improved the estimation algorithm for the parental phase. M.F.M. combined the genotypes obtained using different genotyping systems and performed GP and GWAS. H.I. provided technical help for the statistical analysis. M.F.M., M.K., and S.M. drafted the manuscript. All the authors have read and approved the manuscript.

Data availability

Information on DNA markers is available from Supplementary Data Tables.

Conflict of interest statement

None declared.

Competing financial interests

The authors declare no competing financial interests.

Supplementary Data

Supplementary data is available at Horticulture Research online.

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