bioRxivPlant Biology
Expression atlas of Selaginella moellendorffii provides insights into the evolution of vasculature, secondary metabolism and roots
C. Ferrari, D. Shivhare, B. O. Hansen, N. Winter, A. Pasha, E. Esteban, N. J. Provart, F. Kragler, A. R. Fernie, T. Tohge, M. Mutwil
Abstract
O_LIThe lycophyte Selaginella moellendorffii represents early vascular plants and is studied to understand the evolution of higher plant traits such as the vasculature, leaves, stems, roots, and secondary metabolism. However, little is known about the gene expression and transcriptional coordination of Selaginella genes, which precludes us from understanding the evolution of transcriptional programs behind these traits.\nC_LIO_LIWe here present a gene expression atlas comprising all major organs, tissue types, and the diurnal gene expression profiles for S. moellendorffii. The atlas is part of the CoNekT-Plants database (conekt.plant.tools), which enables comparative transcriptomic analyses across two algae and seven land plants.\nC_LIO_LIWe show that the transcriptional gene module responsible for the biosynthesis of lignocellulose evolved in the ancestor of vascular plants, and pinpoint the duplication and subfunctionalization events that generated multiple gene modules involved in the biosynthesis of various cell wall types. We further demonstrate how secondary metabolism is transcriptionally coordinated and integrated with other cellular pathways. Finally, we identify root-specific genes in vascular plants and show that the evolution of roots did not coincide with an increased appearance of gene families, suggesting that the existing genetic material was sufficient to generate new organs.\nC_LIO_LIOur updated database at conekt.plant.tools provides a unique resource to study the evolution of genes, gene families, transcriptomes, and functional gene modules in the Archaeplastida kingdom.\nC_LI
- organism: plant (other)
- assay: bulk RNA-seq
- research focus: gene regulatory network inference
- research focus: clustering
- research focus: differential expression
- research focus: database / resource
- approach: statistical model
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