Comparative transcriptomics enables the identification of functional orthologous genes involved in early leaf growth.

Leaf growth is a complex trait for which many similarities exist in different plant species, suggesting functional conservation of the underlying pathways. However, a global view of orthologous genes involved in leaf growth showing conserved expression in dicots and monocots is currently missing. Here, we present a genome-wide comparative transcriptome analysis between Arabidopsis and maize, identifying conserved biological processes and gene functions active during leaf growth. Despite the orthology complexity between these distantly related plants, 926 orthologous gene groups including 2829 Arabidopsis and 2974 maize genes with similar expression during leaf growth were found, indicating conservation of the underlying molecular networks. We found 65% of these genes to be involved in one-to-one orthology, whereas only 28.7% of the groups with divergent expression had one-to-one orthology. Within the pool of genes with conserved expression, 19 transcription factor families were identified, demonstrating expression conservation of regulators active during leaf growth. Additionally, 25 Arabidopsis and 25 maize putative targets of the TCP transcription factors with conserved expression were determined based on the presence of enriched transcription factor binding sites. Based on large-scale phenotypic data, we observed that genes with conserved expression have a higher probability to be involved in leaf growth and that leaf-related phenotypes are more frequently present for genes having orthologues between dicots and monocots than clade-specific genes. This study shows the power of integrating transcriptomic with orthology data to identify or select candidates for functional studies during leaf development in flowering plants.

PRGdb 3.0: a comprehensive platform for prediction and analysis of plant disease resistance genes.

The Plant Resistance Genes database (PRGdb; http://prgdb.org) has been redesigned with a new user interface, new sections, new tools and new data for genetic improvement, allowing easy access not only to the plant science research community but also to breeders who want to improve plant disease resistance. The home page offers an overview of easy-to-read search boxes that streamline data queries and directly show plant species for which data from candidate or cloned genes have been collected. Bulk data files and curated resistance gene annotations are made available for each plant species hosted. The new Gene Model view offers detailed information on each cloned resistance gene structure to highlight shared attributes with other genes. PRGdb 3.0 offers 153 reference resistance genes and 177 072 annotated candidate Pathogen Receptor Genes (PRGs). Compared to the previous release, the number of putative genes has been increased from 106 to 177 K from 76 sequenced Viridiplantae and algae genomes. The DRAGO 2 tool, which automatically annotates and predicts (PRGs) from DNA and amino acid with high accuracy and sensitivity, has been added. BLAST search has been implemented to offer users the opportunity to annotate and compare their own sequences. The improved section on plant diseases displays useful information linked to genes and genomes to connect complementary data and better address specific needs. Through, a revised and enlarged collection of data, the development of new tools and a renewed portal, PRGdb 3.0 engages the plant science community in developing a consensus plan to improve knowledge and strategies to fight diseases that afflict main crops and other plants.