Transcriptome sequencing of three Ranunculus species (Ranunculaceae) reveals candidate genes in adaptation from terrestrial to aquatic habitats

Ling Yun Chen, Shu Ying Zhao, Qing Feng Wang, Michael L. Moody

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Adaptation to aquatic habitats is a formidable challenge for terrestrial angiosperms that has long intrigued scientists. As part of a suite of work to explore the molecular mechanism of adaptation to aquatic habitats, we here sequenced the transcriptome of the submerged aquatic plant Ranunculus bungei, and two terrestrial relatives R. cantoniensis and R. brotherusii, followed by comparative evolutionary analyses to determine candidate genes for adaption to aquatic habitats. We obtained 126,037, 140,218 and 114,753 contigs for R. bungei, R. cantoniensis and R. brotherusii respectively. Bidirectional Best Hit method and OrthoMCL method identified 11,362 and 8,174 1:1:1 orthologous genes (one ortholog is represented in each of the three species) respectively. Non-synonymous/synonymous (d N/d S) analyses were performed with a maximum likelihood method and an approximate method for the three species-pairs. In total, 14 genes of R. bungei potentially involved in the adaptive transition from terrestrial to aquatic habitats were identified. Some of the homologs to these genes in model plants are involved in vacuole protein formation, regulating water transport process and microtubule cytoskeleton organization. Our study opens the door to understand the molecular mechanism of plant adaptation from terrestrial to aquatic habitats.

Original languageEnglish (US)
Article number10098
JournalScientific reports
StatePublished - May 20 2015
Externally publishedYes

Bibliographical note

Funding Information:
We thank Ji Yang, Zhi-Ping Song, Wen-Ju Zhang, Yong-Qing Zhu (Fudan University) and Hong-Zhi Kong (Institute of Botany, Chinese Academy of Sciences) for discussion on this study; Peng-Cheng Fu (Luoyang Normal University) for assistance in field work; Yan-Li Wei and Ting-Ting Li (Beijing Genomics Institute) for assistance in data analyses. Financial supports came from the Chinese Academy of Sciences (Grant XDAO5090305 to Q.F.W.) and National Natural Science Foundation of China (Grant 31300182 to L.Y.C.).


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