This repository contains most of the RNA-related analyses for our recent paper:
Gilman IS, Moreno-Villena J, Lewis ZR, Goolsby EW, Edwards EJ. submitted. Gene co-expression networks reveal orthology among multiple photosynthetic pathways in Portulaca
A preprint can befound on bioRxiv under MS ID#: BIORXIV/2021/451465.
C4 and Crassulacean acid metabolism (CAM) have been considered as largely independent photosynthetic adaptations in spite of sharing key biochemical modules. Portulaca is a geographically widespread clade of over 100 annual and perennial angiosperm species that primarily use C4 photosynthesis, but facultatively exhibit CAM when drought stressed, a photosynthetic system known as C4+CAM. It has been hypothesized that C4+CAM is rare because of pleiotropic constraints, but these have not been deeply explored. We generated a chromosome-level genome assembly of P. amilis and sampled mRNA from P. amilis and P. oleracea during CAM induction. Gene co-expression network analyses identified C4 and CAM gene modules shared and unique to both Portulaca species. A conserved CAM module linked phosphoenolpyruvate carboxylase (PEPC) to starch turnover during the day-night transition and was enriched in circadian clock regulatory motifs in the P. amilis genome. Preservation of this co-expression module regardless of water status suggests that Portulaca constitutively operate a weak CAM cycle that is transcriptionally and post-transcriptionally upregulated during drought. C4 and CAM mostly used mutually exclusive paralogs for primary carbon fixation and, although it is likely that nocturnal CAM malate stores are shuttled into diurnal C4 decarboxylation pathways, we find some evidence that metabolite cycling may occur at low levels. C4 likely evolved in Portulaca through co-option of redundant paralogs and integration of the diurnal portion of CAM. Thus, the ancestral CAM system did not strongly constrain C4 evolution because photosynthetic gene networks are not co-regulated for both daytime and nighttime functions.
Most analyses can be found in the Wiki and if notebooks aren't loading on GitHub, try copying and pasting the URLs into the Jupyter Notebook Viewer.