Self-organizing maps (SOM) based methodology reveals gene regulatory networks in plant evolution

PROCHETTO S.; STEGMAYER G.; REINHEIMER R.

Congreso; XIICAB2C; 2022

BACKGROUNDKranz syndrome is a set of leaf anatomical and functional characteristics of species using C4photosynthesis. The current model for the evolution of C4 photosynthesis from a C3 ancestor proposes a series of gradual anatomical changes followed by biochemical adaptation of the C4 cycle enzymatic machinery. This transition occurred several times in various angiosperm lineages and is particularly interesting in grasses, where more than 1/3 of the C4 origins occurred. Despite decades of studies, the molecular mechanisms responsible for the evolution of photosynthesis remain unknown. In this work, leaf development traits from closely related C3, C4 and intermediate species (Proto-Kranz, PK) were used together with gene expression data to study gene regulatory networks and identify potential drivers for the establishment of Kranz anatomy.RESULTSSelf-organizing maps (SOM) were developed to group features (genes and phenotypic traits) into clusters according to their expression along leaf development. Building several species-specific SOM and analyzing features displacement (changes in expression patterns) between species with different photosynthetic subtypes, allowed us to infer changes in gene regulatory networks and identify novel potential drivers for leaf development. The analysis between SOM showed generaltrends of specific gene displacements in the developmental network associated with photosynthesis, vascular development and transcription related processes. At the same time, a small subset of genes was observed to be displaced together with phenotypic traits, suggesting potential roles in the establishment of Kranz anatomy in grasses. This SOM based methodology applied to species-scaled transcriptomic and phenotypic data turned out to be a powerful tool to investigate the evolution of gene regulatory networks in leaf development.CONCLUSIONSThe development of species-specific SOM for combining phenotypic traits and transcriptomicslead to the detection of displacements in gene regulatory networks between species with differentphotosynthesis subtypes, increasing the knowledge about the evolutionary path that leads to Kranzanatomy in grasses. Altogether, this method proved to be a useful tool for studying the evolution ofgene regulatory networks and the detection of potential drivers of phenotypic differentiation.