Combined genome-wide association studies and expression quantitative trait locus analysis uncovers a genetic regulatory network of floral organ number in a tree peony (Paeonia suffruticosa Andrews) breeding population

Abstract

Great progress has been made in our understanding of floral organ identity determination and its regulatory network in many species; however, the quantitative genetic basis of floral organ number variation is far less well understood for species-specific traits from the perspective of population variation. Here, using a tree peony (Paeonia suffruticosa Andrews, Paeoniaceae) cultivar population as a model, the phenotypic polymorphism and genetic variation based on genome-wide association studies (GWAS) and expression quantitative trait locus (eQTL) analysis were analyzed. Based on 24 phenotypic traits of 271 representative cultivars, the transcript profiles of 119 cultivars were obtained, which indicated abundant genetic variation in tree peony. In total, 86 GWAS-related cis-eQTLs and 3188 trans-eQTL gene pairs were found to be associated with the numbers of petals, stamens, and carpels. In addition, 19 floral organ number-related hub genes with 121 cis-eQTLs were obtained by weighted gene co-expression network analysis, among which five hub genes belonging to the ABCE genes of the MADS-box family and their spatial–temporal co-expression and regulatory network were constructed. These results not only help our understanding of the genetic basis of floral organ number variation during domestication, but also pave the way to studying the quantitative genetics and evolution of flower organ number and their regulatory network within populations.

Acknowledgements

We would like to thank Miss Fan Kong, Mr Xiao Zhang, and Miss Miaomiao Song from the Institute of Botany, Chinese Academy of Sciences, for helping to collect flower buds and investigate phenotypical traits. We appreciate Miss Xiaohui Wang and Mr Kun Han from Luoyang Academy of Agricultural and Forestry Sciences for collecting phenotypical trait data. We thank Dr Yuannian Jiao for kind suggestions. This work was supported by the National Natural Science Foundation of China (Grant No. 32072065).

Author contributions

S.Q. and L.Z. conceived and supervised the study. P.L., S.Q., L.Y., T.W., L.Z., and W.Z. collected phenotype traits. L.Y., P.L., W.S., and T.N. conducted the experiments. P.L. and S.Q. wrote the manuscript. P.L., L.Y., T.W., and H.Q. performed data analyses. S.Q. and L.Y. revised the manuscript. All the authors read and approved the final manuscript.

Data availability

The data that support the findings of this study are available from the corresponding author upon reasonable request.

Conflict of interest

The authors declare that they have no conflict of interest.

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