The inhibitory effect of extracellular DNA (exDNA) on the growth of conspecific individuals was demonstrated in different kingdoms. In plants, the inhibition has been observed on root growth and seed germination, demonstrating its role in plant–soil negative feedback. Several hypotheses have been proposed to explain the early response to exDNA and the inhibitory effect of conspecific exDNA. We here contribute with a whole-plant transcriptome profiling in the model species Arabidopsis thaliana exposed to extracellular self- (conspecific) and nonself- (heterologous) DNA. The results highlight that cells distinguish self- from nonself-DNA. Moreover, confocal microscopy analyses reveal that nonself-DNA enters root tissues and cells, while self-DNA remains outside. Specifically, exposure to self-DNA limits cell permeability, affecting chloroplast functioning and reactive oxygen species (ROS) production, eventually causing cell cycle arrest, consistently with macroscopic observations of root apex necrosis, increased root hair density and leaf chlorosis. In contrast, nonself-DNA enters the cells triggering the activation of a hypersensitive response and evolving into systemic acquired resistance. Complex and different cascades of events emerge from exposure to extracellular self- or nonself-DNA and are discussed in the context of Damage- and Pathogen-Associated Molecular Patterns (DAMP and PAMP, respectively) responses.

The sudden exponential increase of biological data concerning genome structure and functionalities, also fostered by the advent of Next Generation Sequencing (NGS) technologies, while expanding the opportunity to highlight still uncovered molecular aspects, challenges bioinformatics in several repects. Data management, processing, updating, dissemination and integration are the major areas of concern. The rapid increase in various omics technologies causes two major issues, which may even appear contrasting: the dissemination of poorly curated datasets, still in the form of raw collections or preliminary draft results, and the fast updating of information that, as a consequence, affects the establishment of stable reliable resources. These issues are mainly caused by the lower rate of bioinformatics in extracting added value information from the large amount of data, when compared to the faster technologies involved in data production. This review describes main bioinformatics resources for plants genomics to underline the heterogeneity of the available collections, coherent with the multifaceted complexity of plant sciences. It aims to provide an in-depth report highlighting bottlenecks that may significantly affect a fluent progress in the field and attempts to suggest possible solutions to the various issues.

The main hallmarks of cancer diseases are the evasion of programmed cell death, uncontrolled cell division, and the ability to invade adjacent tissues. The explosion of omics technologies offers challenging opportunities to identify molecular agents and processes that may play relevant roles in cancer. They can support comparative investigations, in one or multiple experiments, exploiting evidence from one or multiple species. Here, we analyzed gene expression data from induction of programmed cell death and stress response in Homo sapiens and compared the results with Saccharomyces cerevisiae gene expression during the response to cell death. The aim was to identify conserved candidate genes associated with Homo sapiens cell death, favored by crosslinks based on orthology relationships between the two species. We identified differentially-expressed genes, pathways that are significantly dysregulated across treatments, and characterized genes among those involved in induced cell death. We investigated on co-expression patterns and identified novel genes that were not expected to be associated with death pathways, that have a conserved pattern of expression between the two species. Finally, we analyzed the resulting list by HumanNet and identified new genes predicted to be involved in cancer. The data integration and the comparative approach between distantly-related reference species that were here exploited pave the way to novel discoveries in cancer therapy and also contribute to detect conserved genes potentially involved in programmed cell death.