SSR marker development and intraspecific genetic divergence exploration of Chrysanthemum indicum based on transcriptome analysis

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Abstract

BACKGROUND: Chrysanthemum indicum L., an important ancestral species of the flowering plant chrysanthemum, can be used as medicine and for functional food development. Due to the lack of hereditary information for this species and the difficulty of germplasm identification, we herein provide new genetic insight from the perspective of intraspecific transcriptome comparison and present single sequence repeat (SSR) molecular marker recognition technology. RESULTS: Through the study of a diploid germplasm (DIWNT) and a tetraploid germplasm (DIWT), the following outcome were obtained. (1) A significant difference in Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) annotations for specific homologous genes was observed using the OrthoMCL method for the identification of homologous gene families between the two cytotypes. Ka/Ks analysis of common, single-copy homologous family members also revealed a greater difference among genes that experienced positive selection than among those experiencing positive selection. (2) Of more practical value, 2575 SSR markers were predicted and partly verified. We used TaxonGap as a visual tool to inspect genotype uniqueness and screen for high-performance molecular loci; we recommend four primers of 65 randomly selected primers with a combined identification success rate of 88.6% as priorities for further development of DNA fingerprinting of C. indicum germplasm. CONCLUSIONS: The SSR technology based on next-generation sequencing was proved to be successful in the identification of C. indicum germplasms. And the information on the intraspecfic genetic divergence generated by transcriptome comparison deepened the understanding of this complex species' nature.

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Han, Z., Ma, X., Wei, M., Zhao, T., Zhan, R., & Chen, W. (2018). SSR marker development and intraspecific genetic divergence exploration of Chrysanthemum indicum based on transcriptome analysis. BMC Genomics, 19(1), 291. https://doi.org/10.1186/s12864-018-4702-1

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