Back

Multiomic analisys reveals that viroid infection induces a temporal reprograming of plant-defence mechanisms at multiple regulatory levels

Marquez-Molins, J.; Villalba-Bermell, P.; Corell-Sierra, J.; Pallas, V.; Gomez, G.

2022-04-04 plant biology
10.1101/2022.01.06.475203 bioRxiv
Show abstract

Viroids are circular RNAs of minimal complexity compelled to subvert plant-regulatory networks to accomplish their infectious process. Studies focused on the response to viroid infection have mostly addressed specific regulatory levels and considered a unique infection time. Thus, much remains to be done to understand the temporal evolution and complex nature of viroid-host interactions. Here we present an integrative analysis of the temporal evolution and intensity of the genome-wide alterations in cucumber plants infected with hop stunt viroid (HSVd) by integrating differential host transcriptome, sRNAnome and methylome. Our results support that HSVd promotes the redesign of the cucumber regulatory-pathways predominantly affecting specific regulatory layers at different infection-phases. The initial response was characterized by a reconfiguration of the host-transcriptome by differential exon usage, followed by a progressive transcriptional down-regulation modulated by epigenetic changes. Regarding endogenous small RNAs, the alterations were limited and mainly occur at the late stage. The most significant host-alterations were predominantly related to the down-regulation of transcripts involved in plant-defence mechanisms, the restriction of pathogen-movement and the systemic spreading of defence signals. Altogether our data evidence the existence of a dynamic and yet poorly known arms race between the host and the viroid. We expect that these data constituting the first comprehensive map of the plant responses to a viroid infection contribute to elucidate the molecular basis of this multifaceted defence and counter-defence layout.

Matching journals

The top 12 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.