henhaobio
Sign in

bioRxivSystems BiologyPreprint

Dynamic decomposition of transcriptome responses during plant effector-triggered immunity revealed conserved responses in two distinct cell populations

Xiaotong LiuiD, Daisuke Igarashi, Rachel HillmeriD, Thomas Stoddard, You LuiD, Kenichi TsudaiD, Chad L. MyersiD, Fumiaki KatagiriiD

PDFDOI

Abstract

O_LIRapid plant immune responses in the appropriate cells are needed for effective defense against pathogens. Although transcriptome analysis is often used to describe overall immune responses, collecting transcriptome data with sufficient resolution in both space and time is challenging. C_LIO_LIWe reanalyzed public Arabidopsis time-course transcriptome data obtained after a low-dose inoculation of a Pseudomonas syringae strain expressing the effector AvrRpt2, which induces Effector-Triggered Immunity (ETI) in Arabidopsis. Double-peak time-course patterns were prevalent among thousands of upregulated genes. We implemented a multi-compartment modeling approach to decompose the double-peak pattern into two single-peak patterns for each gene. C_LIO_LIThe decomposed peaks revealed an "echoing" pattern: the peak times of the first and second peaks correlated well across most upregulated genes. We demonstrated that two peaks likely represent responses of two distinct cell populations, which respond either cell-autonomously or indirectly to AvrRpt2. Thus, the peak decomposition extracted spatial information from the time-course data. C_LIO_LIThe echoing pattern also indicated a conserved transcriptome response between two cell populations despite different elicitor types. WRKY transcription factors appeared to underlie the conserved transcriptome response. Activation of a WRKY network via different entry-point WRKYs could explain the conserved transcriptome response elicited by different elicitor types. C_LI

Citations
6

Reproducibility ledger

Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.

Sign in to file a reproducibility report.

Similarity Map
SelectedSame fieldCross-field
THISHillmer '23Chhillar '25Wang '26Zhang '20Rich '18Bjornson '20
77% semantic matchSystems Biology
Rachel Hillmer, Daisuke Igarashi, Thomas Stoddard+4 more·Journal of Bioinformatics and Systems Biology·Jan 1, 2023· 3 citations