Duge de Bernonville, T. | Search bioRxiv

bioRxiv2019

An Erwinia amylovora inducible promoter for intragenic improvement of apple fire blight resistance

Intragenesis is an important alternative to transgenesis to produce modified plants containing native DNA only. A key point to develop such a strategy is the availability of regulatory sequences controlling the expression of the gene of interest. With the aim of finding apple gene promoters either inducible by the fire blight pathogen Erwinia amylovora (Ea) or moderately constitutive, we focused on polyphenoloxidase genes (PPO). These genes encode oxidative enzymes involved in many physiological processes and have been previously shown to be up-regulated during the Ea infection process. We found ten PPO and two PPO-like sequences in the apple genome and characterized the promoters of MdPPO16 (pPPO16) and MdKFDV02 PPO-like (pKFDV02) for their potential as Ea-inducible and low-constitutive regulatory sequences respectively. Expression levels of reporter genes fused to these promoters and transiently or stably expressed in apple were quantified after various treatments. Unlike pKFDV02 which displayed a variable activity, pPPO16 allowed a fast and strong expression of transgenes in apple following Ea infection in a Type 3 Secretion System dependent manner. Altogether our results indicate that pKFDV02 did not keep its promises as a constitutive and weak promoter whereas pPPO16, the first Ea-inducible promoter cloned from apple, can be a useful component of intragenic strategies to create fire blight resistant apple genotypes. Key messagepPPO16, the first Ea-inducible promoter cloned from apple, can be a useful component of intragenic strategies to create fire blight resistant apple genotypes.

bioengineering↗

bioRxiv2018

Ranking genome-wide correlation measurements improves microarray and RNA-seq based global and targeted co-expression networks

Co-expression networks are essential tools to infer biological associations between gene products and predict gene annotation. Global networks can be analyzed at the transcriptome wide scale or after querying them with a set of guide genes to capture the transcriptional landscape of a given pathway in a process named Pathway Level Correlation (PLC). A critical step in network construction remains the definition of gene co-expression. In the present work, we compared how Pearson Correlation Coefficient (PCC), Spearman Correlation Coefficient (SCC), their respective ranked values (Highest Reciprocal Rank (HRR)), Mutual Information (MI) and Partial Correlations (PC) performed on global networks and PLCs. This evaluation was conducted on the model plant Arabidopsis thaliana using microarray and differently pre-processed RNA-seq datasets. We particularly evaluated how dataset x distance measurement combinations performed in 5 PLCs corresponding to 4 well described plant metabolic pathways (phenylpropanoid, carbohydrate, fatty acid and terpene metabolisms) and the cytokinin signaling pathway. Our present work highlights how PCC ranked with HRR is better suited for global network construction and PLC with microarray and RNA-seq data than other distance methods, especially to cluster genes in partitions similar to biological subpathways.

bioinformatics↗