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ECB-ART-50463
Plant J 2022 May 01;1103:627-645. doi: 10.1111/tpj.15717.
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The adaptive evolution of Euryale ferox to the aquatic environment through paleo-hexaploidization.

Wu P , Zhang L , Zhang K , Yin Y , Liu A , Zhu Y , Fu Y , Sun F , Zhao S , Feng K , Xu X , Chen X , Cheng F , Li L .


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Occupation of living space is one of the main driving forces of adaptive evolution, especially for aquatic plants whose leaves float on the water surface and thus have limited living space. Euryale ferox, from the angiosperm basal family Nymphaeaceae, develops large, rapidly expanding leaves to compete for space on the water surface. Microscopic observation found that the cell proliferation of leaves is almost completed underwater, while the cell expansion occurs rapidly after they grow above water. To explore the mechanism underlying the specific development of leaves, we performed sequences assembly and analyzed the genome and transcriptome dynamics of E. ferox. Through reconstruction of the three sub-genomes generated from the paleo-hexaploidization event in E. ferox, we revealed that one sub-genome was phylogenetically closer to Victoria cruziana, which also exhibits gigantic floating leaves. Further analysis revealed that while all three sub-genomes promoted the evolution of the specific leaf development in E. ferox, the genes from the sub-genome closer to V. cruziana contributed more to this adaptive evolution. Moreover, we found that genes involved in cell proliferation and expansion, photosynthesis, and energy transportation were over-retained and showed strong expression association with the leaf development stages, such as the expression divergence of SWEET orthologs as energy uploaders and unloaders in the sink and source leaf organs of E. ferox. These findings provide novel insights into the genome evolution through polyploidization, as well as the adaptive evolution regarding the leaf development accomplished through biased gene retention and expression sub-functionalization of multi-copy genes in E. ferox.

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References [+] :
Anders, Differential expression analysis for sequence count data. 2010, Pubmed