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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.

Programmed cell death involves complex molecular pathways in both eukaryotes and prokaryotes. In Escherichia coli, the toxin–antitoxin system (TA-system) has been described as a programmed cell death pathway in which mRNA and ribosome organizations are modified, favoring the production of specific death-related proteins, but also of a minor portion of survival proteins, determining the destiny of the cell population. In the eukaryote Saccharomyces cerevisiae, the ribosome was shown to change its stoichiometry in terms of ribosomal protein content during stress response, affecting the relative proportion between ohnologs, i.e., the couple of paralogs derived by a whole genome duplication event. Here, we confirm the differential expression of ribosomal proteins in yeast also during programmed cell death induced by acetic acid, and we highlight that also in this case pairs of ohnologs are involved. We also show that there are different trends in cytosolic and mitochondrial ribosomal proteins gene expression during the process. Moreover, we show that the exposure to acetic acid induces the differential expression of further genes coding for products related to translation processes and to rRNA post-transcriptional maturation, involving mRNA decapping, affecting translation accuracy, and snoRNA synthesis. Our results suggest that the reprogramming of the overall translation apparatus, including the cytosolic ribosome reorganization, are relevant events in yeast programmed cell death induced by acetic acid.

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.

Glutathione-S-transferases (GSTs) are encoded by genes belonging to a wide ubiquitous family in aerobic species and catalyze the conjugation of electrophilic substrates to glutathione (GSH). GSTs are divided in different classes, both in plants and animals. In plants, GSTs function in several pathways, including those related to secondary metabolites biosynthesis, hormone homeostasis, defense from pathogens and allow the prevention and detoxification of damage from heavy metals and herbicides. 1107 GST protein sequences from 20 different plant species with sequenced genomes were analyzed. Our analysis assigns 666 unclassified GSTs proteins to specific classes, remarking the wide heterogeneity of this gene family. Moreover, we highlighted the presence of further subclasses within each class. Regarding the class GST-Tau, one possible subclass appears to be present in all the Tau members of ancestor plant species. Moreover, the results highlight the presence of members of the Tau class in Marchantiophytes and confirm previous observations on the absence of GST-Tau in Bryophytes and green algae. These results support the hypothesis regarding the paraphyletic origin of Bryophytes, but also suggest that Marchantiophytes may be on the same branch leading to superior plants, depicting an alternative model for green plants evolution.