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 Coexpression (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 × 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.

Cytokinin signaling is a key regulatory pathway of many aspects in plant development and environmental stresses. Herein, we initiated the identification and functional characterization of the five CHASE-containing histidine kinases (CHK) in the economically important Malus domestica species. These cytokinin receptors named MdCHK2, MdCHK3a/MdCHK3b, and MdCHK4a/MdCHK4b by homology with Arabidopsis AHK clearly displayed three distinct profiles. The three groups exhibited architectural variations, especially in the N-terminal part including the cytokinin sensing domain. Using a yeast complementation assay, we showed that MdCHK2 perceives a broad spectrum of cytokinins with a substantial sensitivity whereas both MdCHK4 homologs exhibit a narrow spectrum. Both MdCHK3 homologs perceived some cytokinins but surprisingly they exhibited a basal constitutive activity. Interaction studies revealed that MdCHK2, MdCHK4a, and MdCHK4b homodimerized whereas MdCHK3a and MdCHK3b did not. Finally, qPCR analysis and bioinformatics approach pointed out contrasted expression patterns among the three MdCHK groups as well as distinct sets of co-expressed genes. Our study characterized for the first time the five cytokinin receptors in apple tree and provided a framework for their further functional studies.

10Co-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. 11 Introduction 12Constructing global gene co-expression networks is a popular approach to highlight transcriptional relationships (edges) 13 between genes (vertices). The 'Guilt-by-Association' (GBA) principle supposes that genes sharing similar functions are 14 preferentially connected and aims at predicting new functions for proteins by determining how their respective encoding 15 genes are co-expressed with others using a reference dataset containing known gene functions such as the Gene Ontology 16 (GO) 1 . Defining edges connecting genes remains a critical step in global co-expression network construction. Expression 17 data (microarray or RNA-seq) are used to construct expression matrices (genes x samples) and to calculate a distance or 18 a similarity for each possible gene pair. The resulting pairwise distance matrix is then thresholded to obtain an adjacency 19 matrix that discriminates relevant edges. Only edges with a distance below (or a similarity above) the set threshold are 20 considered significant and retained for network construction. The procedure is expected to remove non biologically relevant 21 gene associations while retaining the relevant ones and can be assessed with any reference dataset. Alternatively, guide gene sets 22 may be used to extract more human-readable information from large networks in a process named Pathway-Level Correlation 23 (PLC) 2-6 . This approach aims at capturing the best transcriptional associations of a gene set and at highlighting functional gene 24 groups such as known subpathways in this set. There are two types of approaches to determine transcriptional associations 25 of genes: those that are supervised and those that are unsu...

The use of a VIGS approach to silence the newly characterized apple tree SQS isoforms points out the biological function of phytosterols in plastid pigmentation and leaf development. Triterpenoids are beneficial health compounds highly accumulated in apple; however, their metabolic regulation is poorly understood. Squalene synthase (SQS) is a key branch point enzyme involved in both phytosterol and triterpene biosynthesis. In this study, two SQS isoforms were identified in apple tree genome. Both isoforms are located at the endoplasmic reticulum surface and were demonstrated to be functional SQS enzymes using an in vitro activity assay. MdSQS1 and MdSQS2 display specificities in their expression profiles with respect to plant organs and environmental constraints. This indicates a possible preferential involvement of each isoform in phytosterol and/or triterpene metabolic pathways as further argued using RNAseq meta-transcriptomic analyses. Finally, a virus-induced gene silencing (VIGS) approach was used to silence MdSQS1 and MdSQS2. The concomitant down-regulation of both MdSQS isoforms strongly affected phytosterol synthesis without alteration in triterpene accumulation, since triterpene-specific oxidosqualene synthases were found to be up-regulated to compensate metabolic flux reduction. Phytosterol deficiencies in silenced plants clearly disturbed chloroplast pigmentation and led to abnormal development impacting leaf division rather than elongation or differentiation. In conclusion, beyond the characterization of two SQS isoforms in apple tree, this work brings clues for a specific involvement of each isoform in phytosterol and triterpene pathways and emphasizes the biological function of phytosterols in development and chloroplast integrity. Our report also opens the door to metabolism studies in Malus domestica using the apple latent spherical virus-based VIGS method.

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