Multiple-statistical genome-wide association analysis and genomic prediction of fruit aroma and agronomic traits in peaches

Abstract

‘Chinese Cling’ is an important founder in peach breeding history due to the pleasant flavor. Genome-wide association studies (GWAS) combined with genomic selection are promising tools in fruit tree breeding, as there is a considerable time lapse between crossing and release of a cultivar. In this study, 242 peaches from Shanghai germplasm were genotyped with 145 456 single-nucleotide polymorphisms (SNPs). The six agronomic traits of fruit flesh color, fruit shape, fruit hairiness, flower type, pollen sterility, and soluble solids content, along with 14 key volatile odor compounds (VOCs), were recorded for multiple-statistical GWAS. Except the reported candidate genes, six novel genes were identified as associated with these traits. Thirty-nine significant SNPs were associated with eight VOCs. The putative candidate genes were confirmed for VOCs by RNA-seq, including three genes in the biosynthesis pathway found to be associated with linalool, soluble solids content, and cis-3-hexenyl acetate. Multiple-trait genomic prediction enhanced the predictive ability for γ-decalactone to 0.7415 compared with the single-trait model value of 0.1017. One PTS1-SSR marker was designed to predict the linalool content, and the favorable genotype 187/187 was confirmed, mainly existing in the ‘Shanghai Shuimi’ landrace. Overall, our findings will be helpful in determining peach accessions with the ideal phenotype and show the potential of multiple-trait genomic prediction to improve accuracy for highly correlated genetic traits. The diagnostic marker will be valuable for the breeder to bridge the gap between quantitative trait loci and marker-assisted selection for developing strong-aroma cultivars.

Acknowledgements

This work was supported by funds from the National Key Research and Development Program of China (2019YFD1000801), the Science and Technology Commission of Shanghai Municipality (23 N11900400), Hu Nong Ke Chuang Zi (2021) 1-1, Key Scientific and Technological Grant of Zhejiang for Breeding New Agricultural Varieties, China (2021C02066-4), the Outstanding Team Program of Shanghai Academy of Agricultural Science (2022-004), and the ‘Pangao’ Program of Shanghai Academy of Agricultural Science. We are grateful for the help of Shanghai BIOTREE Biological Technology Co., Ltd. (Shanghai, China) in VOC measurement with the Agilent 7890A gas chromatograph and Agilent 5975C mass spectrometer. We thank Professor Lirong Wang, Ke Cao, and Weichao Fang for providing some valuable peach landraces.

Author contributions

X.L. and Z.Y. initiated the project, designed the experiment, and selected the core collection. X.L., M.S., M.Z., Y.H., J.D., H.Z., and X.Z. collected the DNA samples. X.Y.was in charge of the management of irrigation fertilization and pest and disease control of peach orchard. X.L. and H.J. recorded the phenotypes and the VOC quantification. X.L. and J.W. analyzed the phenotypic/genotypic data. X.L. drafted the manuscript. X.L., J.W., Z.Y., and Z.G. reviewed the manuscript. All authors read and approved the final manuscript.

Data availability

The datasets presented in this study are available in the tables, figures and supplementary tables. The original genome resequencing data and the RNA-seq data are publicly available in National Center for Biotechnology Information (NCBI) BioProject database under accession number PRJNA746706 and PRJNA828349.

Conflict of interest

None declared.

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