Genetic architecture of microhabitat adaptation traits in a pair of sympatric Primulina species

Abstract

Exploring the genetic basis of adaptive divergence at fine spatial scales can broaden our basic understanding of evolution and how organisms may adapt to changing environments in the future. Cave-associated microhabitats provide a unique opportunity to gain insight into microgeographic adaptation. We studied the genetic architecture of microhabitat-related divergence in flower phenology and leaf traits between two sister species of Primulina, P. depressa and P. danxiaensis, which live in sympatry but occupy contrasting microhabitats. We identified 40 significant quantitative trait loci (QTLs) associated with the interspecific differences in these microhabitat adaptation traits. Flowering time was controlled by one major-effect and six minor-effect QTLs, while leaf traits were influenced by 9–12 QTLs of small to moderate effect. The genetic architecture of the flowering time and the specific leaf area was genetically independent of other traits. Our results suggest that microhabitat adaptation in sympatric populations of Primulina differs according to different traits, with leaf traits diverging with the accumulation of many small changes and flowering phenology being driven by major effect variance.

Keywords:

• Primulina
• microhabitat adaptation
• QTL mapping
• species divergence
• leaf traits
• flowering phenology

Acknowledgments

We are sincerely grateful to Prof. Ming Kang and Dr. Lihua Yang (South China Botanical Garden, CAS) for plant collection and advise for project designing.

Authors’ contributions

CF designed this project, conducted the experiments and wrote the manuscript. CF, SZ and JZ analyzed the data. SZ and JZ revised the manuscript.

Data availability statement

All the data and plant material are available from the first author (CF) upon reasonable request. Traits data for analysis are available at the FIGSHARE repository: Feng C, Feng C, Yang L, Kang M, Rausher M. qtlST script and phenotypic data. figshare. Dataset; 2019. https://doi.org/10.6084/m9.figshare.7270715.v3

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported by the National Natural Science Foundation of China (31900278), the Biological Resources Programme, Chinese Academy of Sciences (KFJ-BRP-007-013) and the Special Project for Lushan Plants (2021ZWZX18).